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Understanding human nephrogenesis and scaling synthesis of organoids facilitate modeling of kidney development and disease

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Understanding human nephrogenesis and scaling synthesis of organoids facilitate modeling of kidney development and disease

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Content Copyright 2021 Trinh Khiet (Tracy) Tran UNDERSTANDING HUMAN NEPHROGENESIS AND SCALING SYNTHESIS OF ORGANOIDS FACILITATE MODELING OF KIDNEY DEVELOPMENT AND DISEASE by Trinh Khiet (Tracy) Tran A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY DEVELOPMENT, STEM CELLS, AND REGENERATIVE MEDICINE August 2021 ii Acknowledgements Doing a PhD in the McMahon lab has changed my life forever. I want to thank Andy McMahon for his patience, generosity, and his exceptional commitment to scientific guidance. If I had to redo my PhD, I would definitely choose to do it under Andy again. I joined the lab as a blank sheet of paper: I had never been to any formal lecture on Developmental Biology, had very little idea of what constitutes good science, and of course did not fully comprehend why Andy is a monumental scientist. I admire Andy for having accepted the risks and taken me as his student. Though I am still learning to become a good developmental biologist and still trying to appreciate good science every day, I am thankful that the corner stone was laid with the help of Andy, and that my future science will forever be influenced by him. I am grateful for having Jill McMahon. She essentially orchestrated all the scientific activities in the lab and took great care of all of us. Her compassion towards all the people around her has exemplified that one can choose to be talented and compassionate at the same time. Her positive spirit is one that I will always aspire. With Nils Lindström, I am grateful that he is a mentor, a colleague, a friend, and family. I thank all the good and bad time that has strengthened the trust so that our friendship is still thriving after constant exchanges of rude insults on both life and science. I look forward to our future collaborations in which our students will perhaps witness the most childish arguments of their PIs, and ponder how we still manage to do nice science. Also during graduate school, I learned to come out of my shell thanks to Lisa Rutledge. Long lab hours became much more tolerable, even joyful, as I had a great company like Lisa. The laughter that we shared has held and will hold the record of being “the most notoriously loud” for many years to come. iii I thank Jack Song for being a very trustworthy colleague and brother. We shared a labor- intensive project and hence, also shared countless number of hours doing work together and discussing life and science. His commitment and enthusiasm for science have made the collaboration a very enjoyable time. I am certain we will have much more to collaborate on beyond PKD! Helena Bugacov has also transformed my life in many ways. We started with a rough working relationship and hurt each other deeply. I have learned from her the importance of appreciating the people around me. Our connection has grown beyond science since then as we became partners in the Health Science Mentor project at the Central Juvenile Hall, attended yoga classes together, and sailed a boat (more like being silly on a boat) together. I am grateful for the undergraduate, masters and rotation students that I worked with, especially Stacy Moroz, Jeff Liu, Gio Suh, Trang Nguyen, Helena Bugacov and DK Kim. It has been a humbling experience to work with these kind, talented and hard-working individuals, and they each taught me various lessons on becoming a better person. I am excited about the challenging career paths, all science related, that some of them have taken after parting the lab. To Helena and DK, I have no doubt you will leave your cocoons to become beautiful and successful butterflies soon. For each day I spent in the McMahon lab, I collected a piece to solve a jigsaw puzzle, and the picture started to emerge. I am realizing that the core of good science, besides a pure motivation to learn the unknown, is the support of a great team. I have been very fortunate to be in this environment and become motivated to build my own. I thank you all for being such great elements of this team! I am also thankful for my thesis committee, chaired by Dr. Gage Crump and joined by Dr. Qilong Ying, Dr. Justin Ichida, and Dr. Janos Peti-Peterdi, for being very supportive of my research and career development. I am also humbled to be a part of the talented, kind and generous BCC community. iv To my parents in Vietnam, my sisters Nhi and My, and my partner Lance, I am blessed with your unconditional love, and I would never be able to go this far without you. My ultimate life goal is to achieve happiness with you. With deep appreciation, Tracy Tran v Table of Contents Chapters Chapter Titles Page Acknowledgements ii List of Tables vi List of Figures vii Abstract x Chapter 1 Introduction: An Overview of Mammalian Kidney Development and Rationales behind Current Approaches to Generate Human Kidney Cell Types from Pluripotent Stem Cells 1 Chapter 2 Conserved and Divergent Features of Human and Mouse Kidney Development 16 Chapter 3 Conserved and Divergent Features of Mesenchymal Progenitor Cell Types within the Cortical Nephrogenic Niche of the Human and Mouse Kidney 73 Chapter 4 Conserved and Divergent Molecular and Anatomic Features of Human and Mouse Nephron Patterning 115 Chapter 5 Progressive Recruitment of Mesenchymal Progenitors Reveals a Time- Dependent Process of Cell Fate Acquisition in Mouse and Human Nephrogenesis 147 Chapter 6 In vivo Development Trajectories of Human Podocyte Inform in vitro Differentiation of Pluripotent Stem Cell-Derived Podocytes 179 Chapter 7 A Scalable Mini-Organoid Model of Autosomal Dominant Polycystic Kidney Disease for Disease Mechanism and Drug Discovery 228 Chapter 8 Conclusions and Discussions 273 References 279 vi List of Tables Table Description Page 2.1 Summary of samples used in the study 58 2.2 Anatomical ontology map (see www.gudmap.org for detailed ontology) of nephrogenic structures and their first appearance in CS13 to CS23 kidney samples 60 2.3 26 Mouse anchor genes analyzed for expression in the human fetal kidney. Samples analyzed ranging in ages from week 14 to week 16. 61 4.1 Summary of protein localization patterns. Proteins detected in figures are summarized and related to data on whether proteins are causative of human or mouse kidney disease/phenotype. 138 6.1 Review recent approaches to assess in vitro derived podocytes 214 vii List of Figures Figure Figure Title Page 1.1 Formation of the Mammalian Nephron 9 2.1 Histological analyses of human kidney development 43 2.2 Histological analyses of human kidney development 45 2.3 Immunofluorescent characterization of early human kidney development and lobulation 47 2.4 Histological analyses of human kidney development 49 2.5 3D wholemount analyses of early human kidney development 50 2.6 Three-dimensional characterization of the human nephrogenic compartment 52 2.7 Three-dimensional characterization of the human nephrogenic compartment 54 2.8 Identification of genes differentially expressed during maturation of human embryonic kidney 56 2.9 Kidneys from week 8, 10, and 11 embryos and fetuses immuno stained for nephron markers indicative of mature cell-type development 58 S2.1 Histological reference data for mouse kidney development 63 S2.2 Immunofluorescent characterization of early human kidney development and lobulation 65 S2.3 Three-dimensional characterization of the human nephrogenic compartment 67 S2.4 Analysis of gene expression within whole kidney RNAseq data from week 9 day 5, week 11 day 3, week 13, week 17, and week 21 human fetal kidneys 68 S2.5 Mouse kidneys immuno stained for nephron markers indicative of mature cell-type development 70 3.1 In situ hybridization labelling for nephron compartment marker genes 94 3.2 Nephron and interstitial progenitor markers mix and persist into epithelializing nephrons 96 3.3 Transcriptional profiling of mouse and putative human nephron progenitor cells assisted by intracellular staining of Six2/SIX2 followed by FACS (MARIS) 98 3.4 In situ hybridization labelling for human and mouse enriched nephron progenitor genes 100 3.5 In situ hybridization labelling for human and mouse enriched nephron progenitor genes 102 3.6 Transcriptional profiling of human and mouse interstitial progenitor cells 104 3.7 Single-cell transcriptional profiling of human nephrogenic niche cells 106 3.8 Validation of NPC cell-populations and exploration of novel NPC marker genes 108 S3.1 MEIS1 is present in human NPCs at a protein level 110 S3.2 Enriched nephron progenitor signature from SIX2 MARIS compared to ITGA8 cell-surface labeling 112 S3.3 Comparisons of human and mouse interstitial progenitor cells 113 4.1 Nephron progenitor induction in human and mouse nephrogenic niches 128 4.2 Nephron patterning through to the S-shaped body stage in human and mouse kidneys 130 viii 4.3 Transcription factor maps in the human renal vesicle and S-shaped body nephron 132 4.4 Transcription factor maps in the mouse renal vesicle and S-shaped body nephron 134 4.5 Diversity in the human and mouse renal vesicle and S-shaped body nephron 136 4.6 Fate-mapping of S-shaped body nephron Wnt4 expression to adult nephron segment 138 4.7 Activation of mature cell-lineage markers in the early development nephron 139 S4.1 Nephron induction and morphogenesis in human and mouse nephrons 142 S4.2 Nephron induction and morphogenesis during the cessation of nephrogenesis 144 S4.3 Nephron induction and morphogenesis in human and mouse nephrons (single-channels) 145 5.1 Three dimensional images and single-cell RNA-seq analyses show nephron progenitor cells form a continuum from niche to nascent nephron 163 5.2 Single-cell RNA-seq analyses of nephrogenic trajectories show differences in the order of segment-fates acquisition 165 5.3 Gene correlation networks demark nephron segment fates along temporal trajectories 167 5.4 Positional identities in the nephron are specified by gradual recruitment of progenitor cells 169 S5.1 Cellular connection from NPCs to nephron is prevalent during human kidney organogenesis – as relating to Figure 5.1 171 S5.2 Single-cell RNA-seq analysis of week 17 human nephrogenic niche and SISH validation for single-cell RNA-seq data – as relating to Figure 5.2 173 S5.3 Single-cell analyses exploring cluster and single-cell level relationships – as relating to Figure 5.2 175 S5.4 Single-cell analyses exploring cluster relationships to modules – as relating to Figure 5.3 177 6.1 Single-Cell RNA-Seq Analyses Showing Transcriptional Changes during Differentiation of human NPCs to Podocytes 203 6.2 In vivo Validation of Early and Late Podocyte Signatures 205 6.3 Single-cell RNA-Seq Analyses Showing Transcriptional Changes during in vitro derivation of podocytes 207 6.4 Comparison of in vitro derived podocytes to human podocytes 209 6.5 Examination of vasculature’s contribution to glomerular construction 211 S6.1 Single-Cell RNA-Seq Analyses of Week 15 and Week 17 Human Fetal Kidneys Showing Transcriptional Changes during Differentiation of human NPCs to Podocytes (Related to Figure 6.1A-E) 216 S6.2 Pseudotime Analyses Showing Transcriptional Changes during Human Podocyte Development (Related to Figure 6.1F-H) 218 S6.3 Examination of in vitro Derived Kidney Organoids Containing Podocyte- like Cells (Related to Figure 6.3) 220 S6.4 Identification of Mesangial Cells, Glomerular Endothelial Cells and Early/Late Podocytes in Human Week 17, Merged Kidney Organoid and Czerniecki Organoid scRNA-Seq Datasets (Related to Figure 6.4 and 6.5) 222 ix S6.5 Heatmaps Presenting Expression of Human Early and Late Podocyte Genes along the in vivo Differentiation Trajectory from NPCs to Podocytes (Related to Figure 6.1H) 224 S6.6 Heatmaps Presenting Expression of Human Early and Late Podocyte Genes along the in vitro Differentiation Trajectory from NPCs to Podocytes (Related to Figure 6.3H) 226 7.1 Generation of Miniature Kidney Organoids 252 7.2 Single-cell Transcriptomic Profiling of Miniature Kidney Organoids 254 7.3 Vascularization of Miniature Kidney Organoids 256 7.4 Cyst Formation in PKD1-/- and PKD2-/- Miniature Kidney Organoids 258 7.5 High-throughput Screening to Identify Compounds Inhibiting Cyst Initiation 260 S7.1 Immunofluorescent analyses of human fetal kidney and miniature kidney organoids (Related to Figure 7.1) 262 S7.2 scRNA-seq analysis of miniature kidney organoids (Related to Figure 7.2) 264 S7.3 scRNA-seq analysis of miniature kidney organoids (Related to Figure 7.2) 266 S7.4 scRNA-seq analysis of miniature kidney organoids (Related to Figure 2); and PKD1-/- PKD2-/- mutant analyses (Related to Figure 7.4) 268 S7.5 qPCR analyses of miniature kidney organoid differentiation (Related to Figures 7.1 and 7.4) 270 S7.6 Phenotypic screens using methylcellulose-embedded miniature organoids (Related to Figure 7.5) 271 8.1 Lentivirus approach to examine and utilize NPHS1 enhancer activity in organoids 276 x Abstract The human kidney is an architecturally intricate organ that packs a network of about 1 million nephrons filtering blood to maintain fluid homeostasis. Additionally, it participates in cross- body communications by secreting hormones regulating hematopoiesis, blood pressure and bone composition, playing vital roles in maintaining the homeostasis of body’s systems. How the human kidney forms has been inferred from animal model studies. This body of knowledge has informed recent approaches to differentiate human nephron cell types from pluripotent stem cells, yet the lack of molecular understanding of human kidney development hindered a thorough assessment of synthetic human kidney cell types. My thesis studies first aimed to achieve a molecular view of human kidney formation. By employing the immunofluorescence imaging technology, I contributed to describe gross anatomical progression, nephrogenic niche development, nephron progenitor characteristic, and signatures of nephron polarity establishment in human developing kidneys. These studies laid the foundation to assess in vitro nephrogenesis in human pluripotent stem cell-derived organoids, and acknowledge possible applications of kidney organoids in disease modeling and developmental biology. Lastly, I optimized a scalable workflow to generate kidney organoids in large quantity for polycystic kidney disease modeling. Using this system, I performed a small-molecule kinase inhibitor screen, and identified compounds capable of inhibiting cyst initiation in PKD1-/- and PKD2-/- organoids. Altogether, these studies present an in vivo informed approach to enable developmental biology and clinical applications for synthetic human nephron cell types. 1 Chapter 1 An Overview of Mammalian Kidney Development and Rationale for Current Approaches to Generate Human Kidney Cell Types from Pluripotent Stem Cells Kidney Structure and Function The human kidney is an architecturally intricate organ that performs numerous vital functions. It packs a network of about 1 million nephrons which filter blood to maintain fluid homeostasis (Nyengaard and Bendtsen, 1992; Sasaki et al., 2019). Distinct nephrons form at different times are precisely positioned within the organ (Figure 1.1 A). Juxta-glomerular nephrons form early with filtering renal corpuscles close to the cortical medulla boundary while the renal corpuscles of later arising cortical nephrons are positioned towards the cortex. The proximal-most end of a juxtamedullary nephron, the renal corpuscle (RC), and segments 1 and 2 of the proximal tubule (PT) are located in the cortex, while segment 3 elongates into the outer stripe of the outer medulla. From the S3 segment, the thin descending limb of the loop of Henle (LoH) extends deep into the medulla before ascending towards the cortex. At the outer/inner medullary boundary, the renal tubule undergoes a morphological transition to the thick ascending limb/distal straight tubule. The distal tubule (DT) extends into the cortex generating the macula densa, where the distal tubule meets the RC. The next transition forms the distal convoluted tubule, then a connecting tubule segment that connects the nephron with the ureteric epithelium of the collecting duct, a distinct cell lineage. Cortical nephrons differ in having shorter loops of Henle which only reach into the inner stripe of the outer medulla. As the plasma filtrate flows through the nephron, these segments, made up of at least 23 nephron progenitor-derived cell types (Chen et al., 2021; Ransick et al., 2019), execute various filtration steps to retain proteins and reabsorb amino acids, glucose, ions, and water. Filtrate from the nephrons meets in the collecting duct, which leads the urine to the renal papilla to the ureter 2 before entering the bladder. A pair of human kidneys can filter 150 L of blood every day to generate 1-2 L of urine. Supporting the vascular and non-vascular epithelial nephrons are the interstitial cells, including pericytes and smooth muscle, and neurons innervating from the sympathetic nervous system (Skorecki et al., 2015). Additionally, the kidney participates in cross-body communications by secreting hormones regulating hematopoiesis, blood pressure and bone composition, playing vital roles in maintaining the homeostasis of body’s systems (Thomas et al., 2008). Mammalian Kidney Development The embryological development of this complex organ has not ceased to intrigue. By examining animal models, we have gathered some insights into how kidneys are built (Little and McMahon, 2012; McMahon, 2016; Saxen, 1987). It is within the intermediate mesoderm (IM), which is formed in response to integrated Wnt, FGF, BMP and Nodal signaling after gastrulation, that the kidney arises. In mouse, at around embryonic day 8.75 (E8.75), nephric ducts elongate bilaterally along the craniocaudal axis starting around the 12 th somite level in mammals until they reach the cloaca. As the nephric ducts grow posteriorly, they induce a mesenchymal to epithelial transition in adjacent IM mesenchyme generating small nephron-like pronephric (somites 5-8) and mesonephric tubules (somites 10-17). In amniotes, the adult kidney arises from metanephric mesenchyme at the hind limb level (in the mouse, somites 27-28) through an extended series of interactions between an offshoot of the mesonephric duct, the ureteric bud. In the mouse metanephric kidney development commences at around E10.5, and the last wave of nephron induction is completed around postal natal day 3 (P3) generating in total ~15,000 nephrons/kidney (Little and McMahon, 2012; McMahon, 2016). Key Progenitor Populations in Metanephric Kidney Development Formation of the metanephric kidney begins as the ureteric bud (UB) outgrows and invades the metanephric mesenchyme (MM). The communications between the UB and MM, mainly via 3 GDNF/Ret, FGF and retinoic acid signaling, instruct the branching of the UB and form the arborized collecting duct (CD) system of the kidney (Costantini, 2012; Costantini and Kopan, 2010). The UB tips house the precursor of all CD cell types, whose proportions vary along the cortico-medullary axis (Costantini, 2012; Little and McMahon, 2012; McMahon, 2016). As the UB branches, it carries with it the nephron progenitor cell (NPC) population of the MM. NPCs condense and cap each branch tip (also called the capping mesenchyme) and are readily distinguished in all vertebrates by the expression of Six2. Signals from the UB tip and the surrounding interstitium regulate the equilibrium between self-renewal and nephron commitment within the cap mesenchyme. It is via this well- orchestrated balance that the mammalian kidney generates enough nephrons during development for a lifelong usage though studies in the human kidney have highlighted a surprising variability in nephron number and evidence of increased risk of kidney disease in those with a low nephron endowment (Bertram et al., 2011; Puelles et al., 2011; Walker et al., 2012). The MM also contains the interstitial progenitor cells (IPCs) which give rise to the stromal tissue surrounding the filtration units and vascular and ureteric epithelial associated cell types throughout the kidney (McMahon, 2016). Foxd1+ mesenchymal cells within the MM are the stromal cell progenitors (Kobayashi et al., 2014). The machineries driving the interstitial cell maintenance and differentiation are not well understood. Recently, the diversity of the kidney stromal lineage has been explored using scRNA-seq technology, which identified distinct transcriptional signatures of stromal cells along the corticomedullary axis (England et al., 2020). Lastly, the origins of the kidney vasculature and neurons still require much interrogation though recent effort has revealed the spatio-temporal emergence and elaboration of these networks (Carmeliet and Tessier-Lavigne, 2005; Daniel et al., 2018; Munro et al., 2017). High-resolution confocal imaging of vascular growth in the embryonic mouse kidney has revealed blood vessels invading the metanephric mesenchyme from the Wolffian duct side before the establishment of vascular plexuses around the caps (Daniel et al., 2018; Munro et al., 2017). Additionally, RNA-seq 4 analyses combined with immunofluorescent validation has linked transcriptional and spatial views of the capillary network in the developing kidney (Daniel et al., 2018). When building a synthetic kidney, the prioritized task is to generate the nephron, the functional unit. Hereon, this review will focus on current understandings of mammalian nephrogenesis that have founded the approaches to derive nephron cell types in vitro and to assess their synthesis. Regulation of the Cap Mesenchyme The mouse Six2+ NPC pool starts with ~2,000 cells within the metanephric condensate at E10.5. It then expands to ~12,000 cells in E11.5, and reaches ~200,000 cells before the final round of nephrogenesis at P1 (Kobayashi et al., 2008; Wainwright et al., 2015). Throughout kidney development, it has been estimated that at least 1 million NPCs are generated, giving rise to ~15,000 mouse nephrons. Maintenance of NPC demands tight transcriptional regulation. A number of transcriptional regulatory components have been shown to be important including Wt1, Osr1, Hox11 paralogs, Sall1, Six1, Six2 and Eya1. Wt1 and Osr1 are first expressed in the IM and both are essential for MM survival and kidney organogenesis. Osr1 activity is specific to the MM and Wt1 functions earlier in IM specification (Kreidberg et al., 1993; Mugford et al., 2008a). The other transcription factors’ functions are specific to the metanephric kidney. The Hox11 paralogs demarcate the metanephros, and they act redundantly and synergistically to govern the formation of metanephros (Wellik et al., 2002). Interestingly, ectopic expression of Hoxd11 in the mesonephros is sufficient to activate distal tubule signatures specific to the metanephric kidney (Mugford et al., 2008b). Six1 is expressed in the mouse MM briefly from E10.5-11.25, but its activity is essential for the early MM maintenance and successful UB invasion; consequently mutants fail to form a kidney (O’Brien et al., 2016; Xu et al., 2003). The closely related Six-factor Six2, is specifically expressed in NPCs from E10.5 until NPCs are lost at P3. Six2 is required for the maintenance of the NPC population with NPCs undergoing a 5 premature and complete commitment to nephrogenesis in Six2 mutants at the onset of nephrogenesis (Kobayashi et al., 2008; Self et al., 2006). Loss of Sall1 or Eya1 function results in a severe reduction in kidney size or kidney agenesis as a result of failed MM maintenance and failed ureteric bud invasion (Basta et al., 2014; Nishinakamura et al., 2001; Xu et al., 2014, 1999). Of note, though the redundant functions of Pax2 and Pax8 in nephric duct elongation were well documented (Bouchard et al., 2002; Grote et al., 2006), recent Pax2 removal in the cap mesenchyme has revealed its role in repressing interstitial fate in NPCs, contributing to the maintenance of this population (Naiman et al., 2017). Importantly, these transcription factors act in concert with each other. Co-IP experiments have demonstrated the importance of interactions between Eya1, Six2, cMyc and nMyc in maintaining their own functions and in NPC self-renewal (Xu et al., 2014). Collaborative actions of Six2, Hoxd11, Osr1 and Wt1 have also been highlighted using ChIP-seq, identifying key regulatory elements as well as core NP maintenance and differentiation genes regulated by these key transcriptional regulators (O’Brien et al., 2018a). Integration of FGF, BMP, FAT and Wnt signaling pathways is important in balancing self- renewal and commitment of NPC. Fgf9 and Fgf20 can have partially overlapping functions in early MM survival and self-renewal. While homozygous knock-out of Fgf9 did not show much effect on the kidney size, homozygous mutation of Fgf20 resulted in smaller kidneys, suggesting a more important role. Ablating one functional copy of Fgf9 and two copies of Fgf20 caused a range from mild to severe reduction in kidney size, and compound homozygous loss of Fgf9 and Fgf20 led to kidney agenesis due to apoptosis of the early MM and failed UB branching (Barak et al., 2012a). FGF signaling activity could be through Fgfr1 and Fgfr2 and mediated by RAS signaling (Brown et al., 2011; Poladia et al., 2006). The earliest indicators of NPC differentiation are the expression of Fgf8, Wnt4 and Pax8 in the pretubular aggregates (Grieshammer et al., 2005; Perantoni et al., 2005; Plachov et al., 1990; Stark et al., 1994). Fgf8 functions to maintain survival of NPCs and tubular nephrons and is upstream of Lhx1 and Wnt4 (discussed later). 6 Bmp7 is also required for NPC maintenance and proliferation likely through JNK mediator, but it can also prime NPCs for Wnt/β-catenin-induced differentiation via Smad (Blank et al., 2009; Brown et al., 2011, 2013, 2015; Dudley and Robertson, 1997; Dudley et al., 1995, 1999). Of note, Fgf2, Fgf9 and Bmp7 were among the first factors identified to support the MM in vitro, leading to later creation of cocktails to expand NPCs (Barak et al., 2012b; Blank et al., 2009; Brown et al., 2013, 2015; Dudley et al., 1999; Li et al., 2016). Members of the Wnt signaling pathways play key roles in both self-renewal and differentiation programs. Though loss of Wnt9b, Wnt4 or Ctnnb1 inhibits nephron induction, Wnt9b and Ctnnb1 mutants also show precocious depletion of NPCs upon removal in later nephrogenesis (Carroll et al., 2005; Karner et al., 2011; Kispert et al., 1998; Park et al., 2007a). Moreover, the need of a low dosage of CHIR99021, a GSK3β inhibitor stabilizing β-catenin, in in vitro NPC expansion cocktails substantiated the requirement of canonical Wnt signaling in maintenance (Brown et al., 2015; Li et al., 2016). By using an in vitro simulation of NPC maintenance and differentiation, Park and colleagues highlighted the orchestrating acts between Six2 and β-catenin through ChIP-seq studies, identifying key regulatory elements and co-binding of these two factors to regulate NPC commitment genes (Park et al., 2012). Wnt4 controls the mesenchymal-to-epithelial transition of the NPCs initially via the canonical Wnt pathway (Kispert et al., 1998; Park et al., 2007b; Stark et al., 1994). Evidence suggests a switch in Wnt4 pathway activity in the MET establishing the renal vesicle, the epithelial precursor of the nephron (Lindström et al., 2015; Tanigawa et al., 2011). The non-canonical Wnt pathway utilized by Wnt11 is also a component in maintaining NPC pool size and a tightly organized cap morphology (O’Brien et al., 2018b). Wnt signaling also plays additional roles later in kidney development outside of nephrogenesis in morphogenesis of the medullary zone (Yu et al., 2008). Interstitial cells contribute to the self-renewal/differentiation balance of the NPC pool. Global deletion of Foxd1, whose expression demarcates the mouse interstitial progenitor cells, led to 7 expansion of the NPC population by inhibiting stromal Dcn, which blocks the Smad-mediated commitment to making nephrons of NPC (Das et al., 2013; Fetting et al., 2014). Additionally, stromal Fat4 input, potentially acting through YAP/TAZ , also contributes to regulating cap size by allowing activation of Wnt/β-catenin induction program (Das et al., 2013). Establishment of Nephron Polarity On commitment, NPCs coalesce under the UB tip to form densely packed, but non-epithelial, pretubular aggregates (PTAs). A full epithelial transition results in the formation of a renal vesicle (RV), the precursor for each nephron. At this stage, an emerging polarity is evident prefiguring the proximal-distal polarity of the mature nephron. The distal end lies closest to the ureteric epithelium and expresses Cdh1 and Jag1, while the proximal domain further away retains Wt1 (Georgas et al., 2009; Lindström et al., 2015; Mugford et al., 2009). The developing nephron undergoes a stereotypical morphogenesis through comma-shaped body (CSB) and S-shaped body (SSB) stages where a patent luminal connection is formed with the adjacent ureteric epithelium of the collecting system (Figure 1.1) (see Chapter 4). At the S-shape body stage, the nephron anlagen can be roughly divided into 3 major domains: proximal (Wt1 high , Jag1 low and Cdh1 low ), medial (Jag1 high , Wt1 low , and Cdh1 low ) and distal (Cdh1 high , Jag1 low and Wt1 - ) (Georgas et al., 2009; Lindström et al., 2015; Mugford et al., 2009). The Notch signaling pathway is a major driver of the proximal/medial fate specification. While Notch2 regulates the podocyte and proximal tubule fates, ectopic expression of Notch1 favors only proximal tubule formation (Cheng et al., 2007; Chung et al., 2017; Surendran et al., 2010). Notch signaling is likely regulated by several ligands (including Jag1 and Dll1) as well as well as downstream transcriptional regulators (including Hes1, Hes5 and HeyL), which demarcate the distal domain of the RV stage and later in the medial and/or proximal segment of the S-shaped body stage (Chen and Al-Awqati, 2005; Georgas et al., 2009; Lindström et al., 2015). 8 The involvement of transcriptional regulators has also been investigated in patterning the renal vesicle and early nephron precursors. Normal podocyte development is contingent on the functions of Wt1, Mafb, Tcf21 and Foxc2 (Berry et al., 2015; Maezawa et al., 2014; Moriguchi et al., 2006; Takemoto et al., 2006). Irx3 and Hnf1b, whose activities are highest in the SSB’s medial segment, are essential for formation of the loop of Henle fate, while Hnf1b also dictates the emergence of the proximal tubule (Heliot et al., 2013; Reggiani et al., 2007). Hnf4a, another member of the Hepatocyte Nuclear Factor family, whose expression is restricted to a small domain in the medial SSB, is required for the maturation of the proximal tubule (Marable et al., 2020). The canonical Wnt pathway also dictates nephron segmentation. A gradient from low to high levels of TCF/Lef activity has been detected along the proximo-distal axis of the S-shaped body, and increased β-catenin activity biased the distal fate and vice versa. Additionally, combined perturbation of the Wnt/β-catenin, BMP, PTEN and Notch signaling using small molecule inhibitors highlights the collaborative action of these pathways in establishing nephron segment precursors (Lindström et al., 2013, 2015). Among the transcriptional regulators, Lhx1 and Pou3f3, detected in the distal segment of RV and SSB, are indispensable to the distal fate formation (including the loop of Henle, macula densa, and distal tubule) (Kobayashi et al., 2005a; Nakai et al., 2003). Importantly, lineage mapping studies of nephron precursor domains to link regional patterning with the adult nephron segments have not been employed to date so there remains a big gap in our understanding of lineage relationships in nephron precursors, though recent single cell RNA-seq analyses have led to predictive models (See Chapters 4, 5 and 6). As the loss of renal activity in chronic disease results in severe secondary complications, improving approaches to better understand and model human kidney disease is an important priority. The advent of techniques to derive mouse, and later human, pluripotent stem cells has offered the opportunity to synthesize mammalian tissues in vitro to serve further clinical endeavors. 9 Hence, developmental biology findings from studying the mouse, though incomplete, have become valuable in informing the differentiation of mammalian kidney cells in vitro. Synthetic Kidney Structures in Development and Disease Modeling Figure 1.1. Formation of the Mammalian Nephron. (A) Schematic diagram of mammalian nephron development from nephron progenitors to mature functional nephron (Adapted from Nils Lindström - (Ransick et al., 2019). (B) Early mammalian nephrogenesis steps shown by immunofluorescence analysis of WT1, JAG1 and CDH1 expression (human week 17 kidney). 10 Early attempts to generate mouse kidney cell types from PSCs The first effort to examine the ability of growth factors to direct the formation of renal lineage cells from PSCs was credited to Schuldiner and colleagues (2000). This attempt identified NGF, HGF and activin A capable of activating Renin and Wt1 expression from embryoid bodies (EBs) (Schuldiner et al., 2000). A later study described that overexpressing Wnt4 in EBs that were cultured with HGF and activin A activated Wt1, Pax2 and Aqp2 expression, and Wnt4 enhanced tubule formation (Kobayashi et al., 2005b). Also starting from EBs, the work of Kim and Dressler marked the first successful induction of intermediate mesoderm-like cells by providing the EBs with retinoic acid (RA), activin A and BMP7. This group then observed the upregulation of Pax2, Wt1, Wnt4, Lhx1, Six2, Eya1, Gdnf and Cdh6 compared to ESCs. These treated EB could integrate into forming nephron tubules in ex vivo cultured rudimentary kidney (Kim and Dressler, 2005). Vigneau et al. generated a reporter line to aid the visualization and selection of primitive streak cells: the LacZ-T-GFP mESC line. The group treated EBs with activin A for 4 days to generate renal progenitor-like cells expressing WT1, Pax2, Cdh11, and T. The differentiated culture was subjected to selection for LacZ-T-GFP+ using fluorescence-activated cell sorter (FACS). These cells could integrate into the cap mesenchyme of kidney explant culture, and presumably became more differentiated and incorporated into proximal tubules upon injection into neonatal mouse kidneys. (Vigneau et al., 2007) Several groups have attempted to differentiate EBs into renal lineages. Low level of BMP4 after 4-day EB differentiation (which is now primitive streak) promotes expression of bh1-Globin, Pax2, Pod1, KSP, and Podocalyxin (Bruce et al., 2007). Overexpressing Pax2 in EBs can induce expression of Aqp1 and Itga8 (Nakane et al., 2008). Treating mouse iPSC- or mESC-derived EBs with activin-A promoted renal tubular differentiation as showed by expression of KSP, WT1, and PAX2 (Morizane et al., 2009). Ren and colleagues used ureteric bud-conditioned medium following the 11 RA/ActivinA treatment of EBs and found higher expression of renal lineage signatures (including Wt1, Cdh1, Pod1 and Pax2) (Ren et al., 2010). Notably, Mae et al. skipped EB formation and used small molecules to differentiate mESCs to IM by first inducing BMP7-expressing cells by combining Jak, PI3K and RhoA inhibition. The cells were then treated with RA to enhance the expression of renal lineage markers (including Pax2, Osr1, Wt1, Six2 and Lhx1) (Mae et al., 2010). Nishikawa et al. (2012) aimed to mimic the in vivo developmental steps by first forming mesoderm-like cells expressing T by treating mESC with a cocktail of Activin-A, Bmp4 and Lithium (a Wnt signaling agonist). IM-like cells expressing Pax2 and Lhx1 were then induced by treating mesoderm-like cells with RA. IM-like cells, when cultured with UB- or MM-conditioned media, enhanced the expression of MM and UB marker expression respectively. Though not fully defined, this study showed that in vitro derived mouse IM cells can give rise to cells resembling cells of the renal lineage (Nishikawa et al., 2012). Directed differentiation attempts to generate amalgamation of human kidney cell types from hPSCs Among the first group to direct hPSCs towards the renal lineage, Mae and colleagues constructed an OSR1-GFP reporter hiPSC line as Osr1 expression demarcated and was required for mouse MM formation (James et al., 2006; Mugford et al., 2008a; Tena et al., 2007). Using this cell line, this group found that the combination of Activin A and CHIR99021 could promote mesendoderm fate, and the addition of BMP7 and CHIR99021 later induced OSR1-GFP+ cells. OSR1+ cells could further differentiate into kidney-like cells, and formed tubular structures upon transplantation into immunodeficient mice (Mae et al., 2013). Other groups independently achieved the induction of MIXL1+T+ posterior primitive streak by using high dosages of Wnt signaling (5-8 µM CHIR99021) or a combination of BMP4 high and Activin A low . While Takasato and colleagues derived IM-like cells by providing a high level of FGF9, Lam et al. treated primitive streak (PS) cells with FGF2 and RA to attain PAX2+ LHX1+ WT1+ IM-like cells. Upon 12 further differentiation, the IM-like cells from both protocols formed tubules expressing nephron segment signatures (Lam et al., 2014; Takasato et al., 2014). Further refinements of these protocols yielded more efficient approaches to generate complex human renal structures, referred to broadly as “kidney organoids” (Morizane et al., 2015; Takasato et al., 2015). Though small molecules and growth factor combinations differ among human kidney organoid methodologies, the common first step induces the posterior PS by treating hPSCs with high concentrations of CHIR99021. Morizane and colleagues then treated PS cells with Activin A to promote posterior IM induction, followed by a low dosage of FGF9 to achieve NPC-like cells. In contrast, the Takasato protocol required a high concentration of FGF9 to generate kidney progenitor like cells. Both protocols used CHIR99021 (at different concentrations and durations) as the inductive signal to enhance nephrogenesis, and accomplished the formation of nephron-like structures at the end of the protocols. Initial bulk mRNA profiling and immunofluorescence assessment identified structures composed of segments with signatures of podocyte, proximal tubule, loops of Henle, and distal nephron in organoids generated by both approaches. Concurrently, a simpler method was developed by Freedman and colleagues in which hPSCs were seeded between two layers of Matrigel to form spheroids, and a high dosage of CHIR99021 was provided to generate IM-like cells. Further differentiation of these cells gave nephron-like structures with proximal, medial and distal segments (Freedman et al., 2015). Directed differentiation attempts to generate nephron and ureteric progenitors from PSCs Instead of generating a mixture of nephron-like cells, Taguchi and colleagues approached the differentiation of renal cells differently and aimed for the progenitor populations first (Taguchi et al., 2014). Starting with the mouse, this group mimicked the in vivo developmental process of metanephric mesenchyme by first generating PS cells expressing T and treating the cells with BMP4 and CHIR99021 to promote formation of posterior mesoderm, then inducing posterior IM by balancing Activin A, BMP4, Wnt and RA signaling, and eventually metanephric mesenchyme using 13 FGF9 and a low dosage of CHIR99021. The same strategy was applied to the human counterpart to attain human metanephric mesenchymal cells capable of generating nephron-like structures upon co-culture with mouse spinal cord as the nephron inductive signal provider. With the reasoning that the ureteric bud cells came from the anterior IM, Taguchi and Nishinakamura first generated this population of IM from nascent mesoderm cells by first providing FGF and retinoic acid signaling and inhibiting BMP signaling (Taguchi and Nishinakamura, 2017). The in vitro anterior IM cells were then directed to Wolffian duct cells using Wnt, RA and FGF signaling agonists. Upon further differentiation, FACS-sorted Hoxb7+/Cxcr4+/Kit+ cells acquired UB- signatures and formed branched structures when being combined with in vivo or in vitro derived metanephric mesenchyme. The in vitro model of the mouse kidney also developed nephron structures (connecting to the ureteric epithelium) without the requirement of an inductive signal (CHIR99021). Following a similar procedure, branching human UB was also synthesized from hPSCs even though robust nephrogenesis has not been achieved. This work marked a major step forward: it provided evidence that in vitro derived nephron and ureteric progenitors, when co-cultured with embryonic stromal progenitors, could mimic mammalian kidney development in which the differentiated UB acted as a signaling center to induce nephrogenesis and to direct the establishment of the nephron-CD connection. However, the ability of in vitro derived UB to maintain NPC self-renewal has not been explored in this model. Also, even though more robust branching and nephrogenesis have been achieved in this system using the in vitro derived human UBs compared to a previous attempt (Xia et al., 2013), there exists a gap between the mouse and human synthetic systems, emphasizing the need to further interrogate human kidney formation. Importantly, future scRNA-seq profiling can offer an unbiased view of the cellular diversity generated in this model. Assessment of Robustness and Reproducibility of Directed Differentiation Protocols Alongside the constant improvement of directed differentiation approaches, various groups have independently repeated and evaluated the published procedures. Enrichment of desired renal 14 lineage cells in in vitro culture has been assessed by quantitative PCR, bulk transcriptional profiling, western blot, and immunofluorescence. However, their limitation lies at the unbiased evaluation of misdirected cell types. The recent advent of single-cell technology can overcome such caveats to achieve an in-depth catalog of in vivo and in vitro kidney cell types. As an early example of such studies, Wu and colleagues identified the presence of cells with signatures of kidney interstitium, endothelium, and nephron segments (podocyte, proximal tubule, loop of Henle, medial and distal precursor), but also detected the presence of neuron-like, melanocyte-like, and muscle-like cells in the organoids derived from the Takasato or Morizane protocols. Using adult human kidney biopsy as the reference, the study also concluded that organoid nephron cells were immature compared to the adult nephrons based on a small set of selected markers. Expression of disease relevant genes were also detected in various nephron segments in the organoids, substantiating the potential of these systems as valuable disease models (Wu et al., 2018). Human versus Mouse Even though the mouse serves as a valuable model to understand mammalian development, mouse is not man. Notably, human kidney organogenesis spans almost 30 weeks and generates ~1 million nephrons; this process in the mouse lasts ~10 days and forms ~15,000 functional units. Furthermore, the human adult kidney is made up of 8-15 renal lobes connected with the same number of calyces, while the mouse only has one calyx. Such differences require species-specific developmental programs that have not been well interrogated. Essentially, a molecular understanding of human kidney formation is needed to elaborate the observations made decades ago (Osathanondh and Potter, 1963; Saxen, 1987). Goals of My Thesis Project 15 I joined the McMahon lab and entered the kidney field when two major technological advancements excited the entire scientific community: single-cell OMICS and human organoid differentiation. These technologies promised a myriad of applications to eventually regenerate and repair the human body, yet our views of early human body construction were limited. As an attempt to fill that gap, my teammates and I have been committed to first paint a molecular view of the human fetal kidney, and second, to realistically appreciate the kidney cell types that we synthesize from hPSCs. These studies have now generated testable hypotheses on human kidney development, and led to the well-informed usage of organoids for kidney disease modeling and developmental biology. Most importantly, they have shaped my personal growth as an aspiring scientist. I invite you to revisit this journey in the next chapters. 16 Chapter 2 Conserved and Divergent Features of Human and Mouse Kidney Organogenesis This work has been published on the Journal of American Society of Nephrology (PMID: 29449453). It was led by Nils Lindström, and Andrew McMahon supervised the conceptualization, experimental design, data collection, data analysis, manuscript editing and reviewing. I contributed to the optimization of immunofluorescence analysis and confocal imaging to visualize nephron structures and validate transcriptional findings. INTRODUCTION Studies, predominantly in the mouse and rat, have provided a mechanistic framework for mammalian kidney development; for reviews, see work by Costantini, Kopan, Little, and McMahon 3– 5 Genetic, molecular and cellular analyses have provided detailed insights into the cell types, and molecular and cellular processes, engaged in kidney developmental programs. Interactions amongst epithelial and mesenchymal progenitor pools are responsible for generating distinct kidney components and driving kidney assembly. Progenitors within branch tips of the ureteric epithelium generate the collecting duct network for kidney drainage and the epithelial cell types within this epithelial network that regulate water, salt and pH balance. Branching is dependent on signals from a population of metanephric mesenchyme capping each branch tip while ureteric branch-tip derived signals regulate the maintenance and differentiation of mesenchymal progenitor cell types. When ureteric branching commences, these mesenchymal cells comprise two lineage compartments, Six2+/Cited1+ nephron progenitors that generate all cell types of the nephron, from proximal podocytes to distal connecting segments 6,7 , and interstitial progenitors that give rise to all interstitial cell types, mesangial cells within the glomerulus, vascular associated pericytes and interstitial fibroblasts 8,9 . Vascular components arise through intrinsic programs of angiogenesis initiated by vascular progenitors within the early metanephric anlagen 10 . 17 Kidney disease is linked to defective developmental pathways 11 and mouse studies modelling human gene mutations with defective kidney development, point to likely conservation in mechanistic aspects of mouse and human kidney development. Further evidence suggests the acquisition of chronic kidney disease is linked to nephron deficiencies that mostly likely reflect underlying developmental events 12 . The development-disease linkage and recent progress enabling human pluripotent stem cells (PSC) to be differentiated into a variety of kidney-like structures, has rekindled interest in how the human kidney forms, the diversity of normal cell-types and the limits to non-human models of kidney developmental programs 13–16 . Seminal histological studies by Osathanondh and Potter 17–20 , Oliver 21 , Kampmeier 22 , Huber 23 , and Peter 24 underlie our current understanding of human kidney development. These studies described the emergence of key anatomical features and provided a comparative histological view from cross species studies of human, mouse, cat, chick, cetacean and multiple other mammalian kidney types 21,24 . These anatomical comparisons highlighted evolutionary conserved features of mammalian kidney developmental programs, as well as distinct species differences. For example, variation in lobulation and the cortico-medullary architecture was suggested to reflect the evolutionary pressure for particular physiological characteristics in mammalian species where size and the animal’s environment place species=specific demands on kidney function 21,23,25–29 . Recognizing the importance of these early studies, there is nevertheless a need to place human kidney development in a modern molecular and cellular framework providing robust sets of data for the biomedical community. An improved understanding of human kidney development can provide new insight into developmental and disease mechanisms, inform on conserved and non- conserved features of development from mice to man, and provide important insight and standards for the analysis of in vitro-directed efforts for kidney organogenesis. For example, recent studies have documented differences in the gene regulatory programs acting within human and mouse 18 nephron progenitors, highlighting the need for a more comprehensive view of human kidney development 30 . In the first of a series of papers, we assembled a developmental series of 135 kidney specimens spanning the earliest stages to mid-gestation, creating a publicly available histological reference resource (www.gudmap.org). Macro-anatomical and micro niche-architecture were dissected through a variety of molecular and cellular approaches. This resource will serve as a bridge to legacy data making human kidney development accessible to a modern research and clinical audience. Subsequent papers will provide an in-depth analysis of the mesenchymal progenitor populations, induction and patterning of the early nephron and morphogenesis of the collecting duct system. MATERIALS AND METHODS Animal care and embryo collection All animal work was reviewed and institutionally approved by Institutional Animal Care and Use Committees (IACUC) at the University of Southern California and performed according to institutional guidelines. Swiss Webster mice were purchased from Taconic Biosciences and maintained as a breeding colony. Timed matings were set up to recover embryos and neonates at the appropriate age. Human kidney material Consented, anonymized, human fetal tissue was obtained from elective terminations following review of the study by Keck School of Medicine of the University of Southern California’s Institutional Review Board. Kidney samples ranging in age from 4 to 23 weeks of gestation were supplied by collaborators at the Children’s Hospital of Los Angeles, the University of California, San Francisco or the Wellcome-funded Human Developmental Biology Resource center at the Institute of Genetic Medicine, Newcastle Upon Tyne, UK and the Institute of Child Health, London, UK. 19 Gestational age was determined per guidelines specified by the American College of Obstetricians and Gynecologists using ultrasound, heel to toe, and crown to rump measurements following published Carnegie Stages 37–39 . Stages indicate the age of the embryo or fetus from the point of conception/fertilization. Samples from the Children’s Hospital of Los Angeles were received immediately after elective terminations and transported on ice at 4°C in 10% fetal bovine serum, 25mM Hepes, high glucose DMEM (SIGMA). Samples from the University of California, San Francisco were transported similarly by overnight courier. Samples from the Human Developmental Biology Resource center were supplied as whole tissues fixed in 4% formaldehyde and shipped in phosphate-buffered saline (PBS), or as paraffin sections or whole tissue embedded in paraffin. Given the anonymized nature of the specimens, no further information was available regarding the specimens or the normalcy of the pregnancy. Dissemination of data The histological and video image data are visible online at www.gudmap.org. High-resolution tile-scan images for SISH, IF, and H&E can be viewed through standard web-browsers. Specific DOIs for the histological and 3D data can be viewed at: https://doi.org/10.25548/BURB-6P44 and https://doi.org/10.25548/S5RE-NVCE : McMahon, A. GUDMAP Consortium. Sample preparation for sectioning and immunofluorescent staining For immunoanalysis, human kidney samples were fixed in 4% formaldehyde overnight at 4°C with mixed-motion provide by a Nutator (Thomas Scientific). Samples were subsequently washed twice with PBS then placed in 30% sucrose, 24 hours for week 8 and 48 hours for week 16 samples, prior to embedding and freezing in Optimal Cutting Temperature compound (Tissue-Tek, 4583). Mouse kidney samples were fixed in in 4% formaldehyde at 4°C for 20 min and washed twice with PBS and then placed in 30% sucrose for 24 hours prior to embedding and sectioning. All samples were sectioned at 10 µm intervals, placed on slides, and stored at -80°C before use. Immunofluorescent detection of target antigens was largely performed as previously described 1 with 20 some modifications. Slides were washed in PBS for 5 min to remove OCT and subsequently blocked for 30 min in PBS with 1.5% SEA block (ThermoFisher Scientific, 37527) and 0.25% TritonX100. Primary antibodies were diluted in the blocking solution and applied to the samples overnight at 4 °C: SIX1 (Cell Signaling, 12891, 1:1000), JAG1 (R&D, AF599, 1:300) CUBN (Santa Cruz, sc-20607, 1:500), AQP2 (Santa Cruz, sc-9882, 1:300), CALB1 (Sigma, C9848, 1:300), VEGFR2 (Cell Signaling, 2479, 1:150), MAFB (Santa Cruz, sc-10022, 1:300), NPHS2 (Abcam, ab50339, 1:10,000), LRP2 (My Bio Source, MBS690201, 1:1000), SLC12A1 (Sigma, HPA018107, 1:1000), UMOD (R&D, AF5144 and AF5175, 1:500), SLC12A3 (Sigma, HPA028748, 1:300, SIX2 (Sigma Aldrich, SAB1401533; 1:500), SIX2 (MyBioSource, MBS610128; 1:1000), CITED1 (Abcam, ab55467; 1:300), FOXD1 (Santa Cruz, sc-47585; 1:750), KRT8 (DSHB, troma-1; 1:50), β-laminin (Santa Cruz, sc-33709; 1:300), PHH3 (Cell Signaling; 9706, 1:500), CDH1 (BD Transduction Laboratories, 610182; 1:300). After incubation in primary antibodies the samples were washed 3 times in PBS with 0.25% TritonX100 (PBT). Secondary antibodies were diluted in the blocking solution and applied to the sample for 1 hour at room temperature. All secondary antibodies were purchased from Molecular Probes ThermoFisher Scientific and used at a 1:1000 dilution. For 5 channel imaging, secondary antibodies were employed as follows: AlexaFluor 488, 555, 594, 647. After incubating with secondary antibodies, samples were washed 3 times in PBT and once in PBS. Nuclei were stained with 1 µg/ml Hoechst 33342 (Invitrogen) in PBS for 5 min before a final PBS wash. Sections were mounted in ProLong Gold Antifade Reagent (Life technologies) and imaged on either a Leica SP8 (confocal microscope) or a Zeiss Axio Scan.Z1 Slide Scanner. Paraffin sectioning and H&E staining To preserve optimum histology, samples used for H&E staining were fixed in Bouin’s solution (Sigma) at 4°C overnight. Samples were subsequently rinsed 4 times in 70% ethanol with 0.85% NaCl. Samples were dehydrated through an ethanol series, washed in xylene then placed in paraffin (Shandon/Thermo Scientific) at 56°C for embedding. Sections were collected from wax blocks at 21 5µm intervals, dried, and stored at room temperature for long-term use. Prior to hematoxylin and eosin (H&E) staining, sections were dewaxed and rehydrated through a reverse xylene and ethanol series to PBS. Samples were stained for 30-45 sec each in hematoxylin then for 15-30 sec in eosin and finally counterstained with fast red for 1 minute. Samples were dehydrated and scanned at high resolution (10X) on a Zeiss Axio Scan.Z1 Slide Scanner to generate high-resolution tiled image files of the entire tissue section. The number and age-distribution of samples can be found in Table 1. In situ hybridization In situ hybridization stains were performed on frozen sectioned samples as previously described (https://www.gudmap.org/Research/Protocols/McMahon.html). The number and age- distribution of samples can be found in Table 1. 3D sample preparation and whole mount staining As the renal capsule interferes with whole-mount immunofluorescence procedures, isolated kidneys were carefully decapsulated in PBS to not disturb the underlying tissue organization. To obtain kidney samples for whole-mount study, kidneys were placed on surgical gauze soaked in PBS with a petri dish and an approximately 3mm slice removed from each kidney lobe, parallel to the kidney surface. Each slice was fixed in 4% formaldehyde in PBS for 45 minutes at 4˚C without shaking, then washed in PBS. Whole mouse kidneys were isolated and similarly decapsulated but processed whole during the whole-mount staining procedure. Slices or whole kidneys were incubated for 1hr in PBS with 2% SEA Block and 0.1% TritonX100 at 4°C while shaking on a Nutator platform. Primary antibodies were resuspended in blocking solution, this mix was added to each tissue sample, then incubated for 48 hours with Nutator-directed sample agitation. Then, samples were washed for up to 8 hours in 5 washes of PBT. Secondary antibodies were diluted in blocking solution, and samples were incubated in secondary antibodies similarly to primary antibody incubation. The samples were washed 3 times in PBT before being incubated in 1 µg/ml Hoechst 33342 for 2 hours. The slices or kidneys were then washed in PBS, and dehydrated through a methanol series (50%, 22 75%, 100%), through a 50% Benzyl alcohol, Benzyl benzoate (BABB) / 50% methanol solution (1 hr) and finally into 100% BABB. Specimens were stored in BABB at 4 o C until imaging. The number and age-distribution of samples can be found in Table 1. Confocal imaging Imaging of cortical slices (3D) were performed on a Leica SP8 using a 10x objective and a 40x objective (40x/1.30 Oil HC PL APO CS2). 1024x1024 images were captured at 5 µm and 0.35 µm optical resolution, respectively. Images for quantitative comparison of protein levels in the nephron progenitor compartment were performed on images captured using a 63x objective. Image preparation for publishing declaration Three dimensional (3D) images were opened and processed in LAS X (Leica), Imaris (Bitplane) and Photoshop (Adobe) while 2D sectional images were opened and processed in LAS X, Imaris, Photoshop, and Fiji. For both sets of images brightness, contrast, and transparency were altered for optimal rendering of fluorescent signals and tissue structures. Image and sample quantification 2D immunofluorescent analyses Frozen and sectioned samples were stained as described above to detect SIX2, SIX2, LEF1, FOXD1, and CITED1. KRT8 and β-laminin were used as structural markers to determine the location of the ureteric epithelium and nephrons. Images were captured with a 63x objective on a Leica SP8. Data were captured as 8-bit images. IMARIS 8.2 (Bitplane) was used for quantification of nuclear antibody signals. The Spot function was used to manually add circular spots to mark all nuclei on the image frame using DAPI-highlighted nuclei as a reference. Due to the convoluted shape of nuclei in 2D sections and the circular shape of the spot function, we used multiple smaller spots to represent single nuclei to ensure accurate quantitation and coverage across the nuclei. Spots were grouped into three cell populations: (1) cap mesenchyme (SIX2 + cells), (2) cortical interstitium (FOXD1 + cells), 23 (3) all other cells. To compare the mean intensity of spots we first normalized the mean intensity values taking into consideration the background signal and the maximum signal for each channel. To do this we measured the intensity for each channel throughout all spots and identified the lower 5 th percentile intensity mean (background), as well as the maximum value. Each spot’s intensity mean was thereafter normalized as follows: ( 𝐼𝐼 𝐼𝐼𝐼𝐼 𝐼𝐼 𝐼𝐼𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝑚𝑚 𝐼𝐼 𝑚𝑚 𝐼𝐼 𝑜𝑜𝑜𝑜 𝐼𝐼 𝑠𝑠 𝑜𝑜𝐼𝐼 − 5𝐼𝐼 ℎ 𝑠𝑠 𝐼𝐼 𝑝𝑝 𝑝𝑝 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝑝𝑝 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝑀𝑀 𝑚𝑚 𝑀𝑀 𝐼𝐼 𝑚𝑚 𝑀𝑀 𝑚𝑚 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 − 5𝐼𝐼 ℎ 𝑠𝑠 𝐼𝐼 𝑝𝑝 𝑝𝑝 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝑝𝑝 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 ) 𝑀𝑀 100 This transforms the intensity mean of each spot onto a 0-100 scale with the 5 th percentile equaling 0 and the maximum being 100, respectively. To plot the normalized intensity of spots against their position within the cap mesenchyme population we marked the most cortical point of the cap mesenchyme and utilized this as point 0. A line was extended in a medullary direction parallel to the ureteric epithelium around which the cap mesenchyme was located. 3D immunofluorescent analyses Three-dimensional image analyses were performed using Imaris 8.2 (Bitplane) and Amira (FEI Thermo Fisher Scientific). To count nephron progenitor cells around nephron progenitor tips, progenitor populations (SIX1+ human SIX2+ mouse) were segmented and the spot function was used to detect individual nuclei. These analyses were performed on data collected from the whole- mounts cortical slices (human) or whole kidneys (mouse). The human cortical slices were imaged at three different positions across the cortical slice surface. The mouse kidneys were image twice per kidney in triplicate kidneys. For the analyses the following number of (individual niches) were examined per stage: wk11 (9); wk13 (13); wk15 (18); wk16 (16); wk17 (17); wk18 (18); wk23 (20); ms E15.5 (13); ms P2 (20). To analyze ureteric branch tip spacing, tips were identified tips and manually marked using the spot function. The XYZ coordinate of all tips within an imaged area was compared to each other to identify the nearest neighboring tip. Distance intervals were determined using Matlab (MathWorks). The following (number of tips) were analyzed for each stage from 1 24 kidney per age: wk11 (217); wk13 (233); wk15 (273); wk16 (297); wk17 (266); wk18 (161); wk23 (310); ms E15.5 (264); ms P2 (281). To quantify the number of ureteric epithelial tips per niche, niches were individually selected and tips counted. The following (number of niches) were analyzed: wk11 (60); wk13 (29); wk15 (25); wk16 (46); wk17 (27); wk18 (20); wk23 (69); ms E15.5 (18); ms P2 (31). The number and age-distribution of separate samples can be found in Table 1. RNA expression analyses RNA isolation for whole kidneys Week 9 kidneys were treated whole and larger kidneys were cut to generate a wedge from the cortex to the medulla. The ureter was removed prior to processing. The tissue was manually cut into small pieces using a scalpel and placed in an Eppendorf tube with 500 µl Trizol LS (Thermo Fisher Scientific) and subsequently homogenized. 100 µl Chloroform (Thermo Fisher Scientific) was added per sample and the samples vigorously mixed. The samples were incubated for 5-10min at room temperature followed by centrifugation at 14,000 RPM for 15 min at 4°C. After centrifugation, the aqueous phase was moved to a new tube, 500 µl Isopropanol (Thermo Fisher Scientific) was added and the samples separately mixed. After 5-10 min at room temperature the samples were again centrifuged at 14,000 RPM for 15 min at 4°C. The resultant RNA pellet was washed with 80% Ethanol and centrifuged at 14,000 RPM for 5 min at 4°C. Finally, the RNA pellet was air dried and then resuspend in RNAse free water. DNA was at this point removed by treating the samples with Dnase I, and collection using spin columns RNeasy Micro Kit (QIAGEN). The number and age- distribution of samples can be found in Table 1. RNA-seq data generation and analysis All RNA samples were polyA selected, synthesized into Illumina NGS libraries with Kapa stranded mRNA-Seq kit, and were sequenced on Illumina NextSeq500 platform by the pair-end 75 bp option. Mouse and human mRNA-Seq reads were aligned to human reference genome (hg38) 25 using TopHat2 2 . To quantify gene expression, we calculated Reads Per Kilobase Million (RPKM) values with aligned mRNA-Seq reads using Partek Genomics Suite (version 6.6, St. Louis, MO, USA. To remove bias created by the polyA selection procedure, Transcripts Per Million (TPM) was calculated by normalizing the RPKM to the proportion of exon reads within individual libraries. Gene ontology enrichment analyses were performed using DAVID (Huang et al., 2009). For results shown in Figure 8 due to insufficient number of samples for t-tests, we identified differentially expressed genes between week 9 and week 21 human kidney samples by the following threshold: 1) mean TPM > 5 in at least one of the groups; 2) mean fold difference > 2 between groups. For all the rest of the comparison between stages, due to overall similarity between samples, we used following threshold: 1) mean TPM > 5 in at least one of the groups; 2) mean fold difference > 1.5 between groups. RESULTS Our study was based on 135 consented, anonymous donated kidney specimens spanning 4- 23 weeks of human kidney development. Table 1 provides a detailed chart of the number and developmental distribution of the kidney samples and the various analyses performed at different developmental time windows. Human renal development has previously been categorized into 4 phases 19 : phase 1 (week 5 to 15), phase 2 (week 14/15 to week 20-22), phase 3 (week 20-22 to 32-36), and phase 4 (week 32-36 to adulthood). Over this period, the human kidney generates approximately 1,000, 000 nephrons 12,31 , though this number varies considerably with low nephron counts likely contributing to kidney disease 31–35 . In contrast, the mouse forms around 16,000 nephrons over a 12-13 day period of active nephrogenesis 36 . We focus here on the first two periods. Phase 1, begins during the embryonic developmental period, captured by the Carnegie Stages (CS; approximately day 1-58, week 1-8) 37–39 . Within phase 1, we have focused on weeks 7-8 (CS 21-23, day 49-58), the end of the embryonic range and in phase 2, weeks 15-17, close to the midpoint of active human 26 nephrogenesis 40 . Human samples were compared to embryonic day 15.5 (E15.5) and postnatal day 2 (P2) mouse kidneys, highlighting mid and late stages of the nephrogenic program 36,41 . Emergence of ureteric branch tips and capping mesenchyme Outgrowth of the ureteric bud from the nephric duct into the adjacent metanephric mesenchyme initiates active metanephric kidney development. The interactions between epithelial tip and kidney progenitor types within the metanephric mesenchyme drives assembly of the mammalian kidney 3–5,42 . Our focus herein lies in providing an overview of human kidney organogenesis: organizational changes within the branching collecting duct network, capping mesenchymal populations and nephrogenic program. Detailed molecular and cellular analyses of each of these events will be discussed separately. In the mouse, outgrowth of the ureteric bud into an adjacent pre-specified population of metanephric mesenchymal progenitors, the initiating event in kidney morphogenesis, commences at E11 (Fig. S2.1A). Potter (1972) reported human metanephric kidney development beginning at CS13; approximately 4 weeks post-fertilization (embryo crown to rump length of 5mm). Consistent with this view, a single non-divided bulbous-shaped ureteric bud outgrowth surrounded by metanephric mesenchyme was observed in the CS13 embryo (Fig. 2.1A). By CS16, the bud generated one to two branches with cap-mesenchyme cells tightly clustered around each branch tip (Fig. 2.1B and Fig. 2.4A) resembling the E12.5 mouse kidney (Fig. S2.2.1B). In contrast to the mouse, the branching human ureteric epithelium was bi-layered from CS13-CS16 (Fig. 2.1A-B, Fig. 2.4A). By CS19, ureteric branch tips where unilaminar and physically distinct mesenchymal cell populations that likely harbor the nephron progenitors, cap each branch tip (Fig. 2.2.1C, Fig. 2.4B), a persistent arrangement maintained to 23 weeks, the latest stage studied (Fig. 2.1D-E, Fig. 2.2, Fig. 2.4, Fig. 2.6). During the CS16-CS22 period branch tips adopt a ‘T’ or ‘Y’ -shape (Fig. 2.1B-D). The ureteric branch tip morphology changed at around CS23 when tips showed a pronounced expanded morphology with a prominent lumen (Fig. 2.1E, Fig., 3A, F, and Fig. 2.4D). This tip reorganization 27 persisted to week 9 (not shown) but was not observed beyond week 10, (Fig. 2.2A, B). Following CS23, tips maintained a ‘V’-shaped morphology to week 16 (Fig. 2.2A-D). The human nephrogenic niche is distributed across lobular and inter lobular regions of the kidney cortex Unlike the mouse, the human kidney is comprised of multiple lobes 21,25 . The region between lobes has previously been suggested to form the column of Bertin but Potter argues that a better term might be sheets of Bertin as they are the surfaces of two nephrogenic zones 25 . As these regions are simply the meeting point of two peripheral curvatures of kidney cortex, we refer to these as interlobular folds or interlobular regions. Lobulation is first detected at CS19 with the appearance of striations between anterior and posterior kidney domains (Fig. 2.1C). The stromal striations described here contrast with the view of Potter 25 . The cortical surfaces of the kidney indent from CS20-23 (Fig. 2.1D-E), and visible lobes become morphologically pronounced as additional lobe folds appear from 10-16 weeks (Fig. 2.2). To further examine the nephrogenic niches at peripheral and interlobular regions, we performed an immunofluorescent analysis to detect cells-types characteristic of the mouse nephrogenic niche. The earliest samples compatible with immunodetection were CS23 kidneys. At this time, a dense population of SIX2+ nephron progenitor cells surrounded the ureteric epithelial tips (Fig. 2.3A), similar to the organization documented in the week-16 human kidney 30 . This progenitor population was 2-7 cell-layers thick (arrowheads in Fig. 2.3A), the thicker portions located to the sides of the ureteric epithelial branch tips. The cells closest to the tip were polarized with their long axis approximately perpendicular to the tip while other SIX2+ putative progenitors where rounded without an elongated nucleus. At 15 weeks, 2-3 layers of SIX2 + nephron progenitors were tightly packed around each ureteric epithelial tip (Fig. 2.3B-C, S2.2A). SIX2 + cells show a specific organization with long axis of cells closest to the ureteric epithelial tip orientated at right angles to 28 branch tips (Fig. 2.3B-C). Peripheral and interlobular regions displayed a similar morphology (Fig. 2.3B-C). The architecture of the E15.5 mouse nephrogenic niche resembled that of CS23 and week 15 human kidneys although smaller in size with fewer SIX2+ cells (Fig. 2.3D). The P2 mouse nephrogenic niche was distinctly different from human stages examined here, the few SIX2+ cells around the tips morphologically resembled pretubular aggregates and renal vesicles, early committed stages in the nephrogenic program (Fig 3E; see later discussion of human nephrogenesis). In the mouse, MEIS1+/FOXD1+ cells demarcate the interstitial progenitor pool that lies above the SIX2+ nephron progenitors beneath the kidney capsule (Fig. S2.2C; 9,43 ). A similar positioned SIX2-; MEIS1+ population of putative interstitial progenitors was observed in the human kidney with SIX2-; MEIS1+ cells separating adjacent SIX2+ nephron progenitor niches in interlobular regions (Fig. S2.2D, E). To broadly examine active nephrogenesis we visualized JAG1, a marker for nascent nephrons 44 , and WT1, a marker of interstitial and nephron progenitor cell-types that in the mouse shows polarized activity in early renal vesicles prefiguring a role in podocyte development (Fig. 2.3I-J). We observed a continuous active program of nephrogenesis across interlobular (15-week) and peripheral regions (CS23 and 15-week) human kidneys (Fig. 2.3F-H, S2.2B). In conclusion, the similarities in cell morphology, cell types and cell organization suggest peripheral and interlobular mesenchymal niches follow similar programs in the human kidney. Further, clear parallels are evident in the organization of nephrogenic niches between mouse and man. The formation of the first generation of nephrons and organization of the ureteric epithelial network To characterize the process of nephrogenesis in broad detail, we first examined histological preparations for structural features indicative of the nephrogenic program. In the mouse, the first physical evidence of nephron commitment is the appearance of a tightly clustered group of cells, the 29 pretubular aggregate (PTA), beneath the ureteric branch tip 45 . Thereafter, the PTA forms an epithelial nephron precursor, the renal vesicle (RV) which transitions through a complex morphogenesis to an S-shaped body nephron anlagen (SSB) with a patent luminal connection to the adjacent collecting duct network 5 . The emergence of different structures and anatomical features during the first nephrogenic events are summarized in Table 2. Evidence of human nephrogenesis was first observed at CS16 (Fig. 2.4A), with PTAs beneath the ureteric branch tips resembling those of the E12.0 mouse kidney (data not shown). By CS19, PTAs, comma-shaped bodies (CSB) and SSBs were observed beneath the ureteric branch tips (Fig. 2.4B). The connection of the nephron to the ureteric epithelium was evident by SSB stage. At CS19 it was possible to find a maximum of 2 generations of developing nephrons per tip; e.g., a PTA and a SSB. Capillary loop stage nephrons were first detected at CS22, by which time 3 generations of nephrons were observed; e.g., a PTA, SSB, and a capillary loop nephron (Fig. 2.4C). Capillary loop stage nephrons at CS23 were extensively vascularized indicative of a mature glomerular organization but showed a rudimentary associated tubular network (Fig. 2.4D). Subsequent developmental time-points, exhibited further nephron generations and maturation of the renal corpuscles (Fig. 2.4E-H). Based on the first appearance of a structure, progression from the first PTA to a connected SSB takes between 3 to 14 days: the shortest and longest time intervals between CS16 and CS18 stages, and a further 1 to 10 days to a capillary loop stage nephron. With a mid-point time-frame estimate, progression from a PTA to an S-shaped body stage would take around 8 days with a further 5 days of development to the capillary loop stage. In contrast, in the mouse there are no nephrons at E11.5 (Fig. S2.1A) and clear SSB stages by E12.5 (Fig. S2.1B) consistent with time-lapse imaging of developing kidney 46,47 indicating a time-span of around 24 hours from induction to SSB formation. To better characterize the development of the first generation of nephrons we performed whole-mount analysis of complete kidneys for JAG1 and KRT8 to visualize early nephrons (RV to SSB 30 stages) and the ureteric epithelium, respectively, in whole kidney tile scan reconstructions from CS20 to week 11. At CS20, three branching events of the ureteric bud have generated anterior and posterior subdivisions (first branching event), and subsequent bifurcation divisions (Fig. 2.5A). Scoring individual JAG1+ structures indicated that the kidney contained 111 developing nephrons spanning RV to SSB stages. A second CS20 sample (Fig. 2.5B) exhibited morphologically thinner and more elongated epithelial branch tips, though the endowment (114) and maturation of nephrons closely matched. By CS22 (Fig. 2.5C), the ureteric bud elongated further and the kidney contained 170 nephrons ranging from RV to SSB stages. By CS23, ureteric branch tips swelled, consistent with the histological data discussed earlier (Fig. 2.5D). Initiation of renal pelvis development was evident with the early branches visible but partially engulfed within the pelvis, pointing to ongoing remodeling of the collecting duct epithelium. By week 11, an additional expansion of the pelvic region was observed (Fig. 2.5E) and >1000 nascent nephrons could be visualized (Fig. 2.5F), more mature nephrons evident in histological evidence were not detected with this procedure. Video images of the whole-mount data can be viewed in the supplementary data (Supplementary movies 1-5). These five samples all displayed a ureteric bud division along the anterior-posterior axis of the kidney. All specimens also displayed a single major interdomain branch projecting in a dorsal direction. Although the interdomain branch is consistently closer to the posterior domain branch point it did not appear to project from this branch raising the possibility that the initial division of the ureteric bud is a trifurcation in the human; trifurcations are also commonly observed in the first branching of the T-stage ureteric outgrowth in the mouse kidney 48,49 and has been speculated to occur in human 21 though this branch could also have emerged from the posterior domain branch, immediately after an initial bifurcation. The three-dimensional architecture of the nephrogenic niche 31 Studies in the mouse kidney have quantified cell types and cell organization in the nephrogenic niche over the period of nephrogenesis 36 . Over the initial period of branching, there is a reduction of nephron progenitors per ureteric epithelial branch tip, followed by a lengthy period where progenitor numbers remain approximately constant per branch tip until birth with the cessation of branching and an accelerated commitment of progenitors to nephrogenesis. To resolve events in the human nephrogenic niche, we performed 3D confocal imaging on mm thick cortical slices from kidney specimens ranging from week 11 to week 23. Slices were immunostained to visualize SIX1, a marker of nephron progenitors in the human kidney 30 , PHH3, a marker of cells entering mitosis 50 , and KRT8, highlighting the ureteric epithelial tree and distal nephron forming structures. Human samples were compared with E15.5 and P2 mouse kidney samples to examine cross-species differences and similarities. Videos displaying the 3D architecture are included (Supplementary movies 6-11). From week 11, the earliest stage we were able to analyze with this approach, approximately 1464 (SEM ± 157) SIX1 + nephron progenitors capped each branch tip (Fig. 2.6A, G). The progenitor to tip ratio progressively decreased to 486 (SEM ± 38) at week 15 (Fig. 2.6B, C and G), then remained fairly constant (only a 15% drop) to week 17 (Fig. 2.6C-E, G). Thereafter, the progenitor tip ratio declined to 292 (SEM±27) at week 18 and 240 (SEM± 14) by week 23 (Fig. 2.6F-G). Examining mitotic frequencies, showed a decrease in the number of PHH3+ cells within the SIX1+ population over time from ~1.3% at week 11 to ~0.5% at week 23 (Fig. 2.6H) suggesting that decreased nephron progenitor proliferation and enhanced nephrogenesis contributes to a decrease in progenitor numbers in the nephrogenic niche. In contrast, the percentage of PHH3+ cells in the mouse nephrogenic niche was similar at E15.5 and P2, consistent with published studies 36 . Of note, the morphology and PHH3+ cell levels for the week 17 specimen more closely resembled a younger week 15 kidney. This observation may reflect normal sample variability in the population or some uncharacterized developmental anomaly retarding development of this kidney specimen. 32 The changes in nephron progenitor number/branch tip occurred alongside changes in the morphologies of both the branch tips and progenitor pool. At week 11, nephron progenitors cap large, bulbous tips (Fig.6A and S3A). As the nephron progenitor population decreased during development, progenitors tightly packed around ureteric epithelial tips, shifting to the side of the tip (Fig. 2.6A-F) while tips narrowed in diameter as the kidney developed. At week 23 ureteric tips pointed upwards with no sign of bifurcations. The cap-tip architecture in the week 11 human kidney most closely resembled the E15.5 mouse kidney, with relatively large NPC population loosely positioned above the tips (Fig. S2.3B), whereas the week 23 kidneys were more similar to the later P2 mouse kidney, with a small, tightly packed NPC population mainly displaced to the side of tips. The distribution of ureteric epithelial tips across the kidney surface also changed during kidney development. Tip-to-tip distance decreased by 27% from week 11 (106µm ± SEM1.6µm) to week 23 (77µm ± SEM0.7µm) (Fig. 2.7A-C). Macroscopically, the distribution of tips and their nephron progenitor populations across the kidney surface displayed a rosette-like pattern of circular radially symmetrically distributed tips; this was particularly evident at later stages for example at week 23. The center of the radial symmetry reflects a shared branching lineage for each cluster. Each cluster contained 2 to 3 tips at week 11 (Fig. 2.7D-E), and, 5-8 tips at week 23. Interestingly, nephron progenitor cells were primarily positioned on the outward facing surfaces of each branch tip within a cluster (Fig. 2.7G-H). Human kidney transcriptional profiling To generate an overview of the gene-expression landscape during human kidney development we collected RNA from whole kidneys at 5 developmental stages: weeks 9, 11, 13, 17, and 21, and performed RNA-seq profiling on each sample (GEO accession numbers: GSE100859). To validate these data and determine whether genes associated with mature kidney functions could be identified we first compared the first and the last stage kidneys: week 9 and 21. Overall gene expression was closely correlated between these samples (R value of 0.96; Fig. 2.8A) though 170 33 genes were relatively enriched at week 9 while 247 genes were enriched at week 21 (Fig. 2.8B; Supplementary table 1; enrichment defined as 2-fold higher expression at either stage). GO-term analyses highlighted cell proliferation terms in the 9 week kidneys and excretion and ion transport in the week 21 kidney consistent with functional maturation over the 12-week developmental period (Supplementary table 1). Multiple genes associated with nephron progenitors, interstitial progenitors, or cell proliferation were among the 170 genes enriched at week 9. Conversely, genes associated with the medullary region and nephron functionality, for example solute carriers and transmembrane transport proteins, were identified within the 247 genes enriched at week 21. We also performed a step-wise comparative analysis for each developmental stage against the preceding and subsequent time-point (Supplementary tables 2 and 3). The first time-point indicating a physiological change was week 17: a comparison of week 17 with week 13 RNA-seq generated enriched GO terms for Excretion with the detection of multiple genes associated with a more mature nephron or collecting duct type, genes included: CLCNKA, CLCNKB, UMOD, AQP6, SCNN1G, SCNN1B, ATP6V1B1, ATP6V0A4, AQP3, KCNJ1, AQP2 (Supplementary table 2). In summary, the broad transcriptional profiles are a rich dataset providing information that will be especially useful in assessing in vitro efforts to generate kidney-like structures. Emergence of physiologically mature cell-types in the developing human nephron Our data indicate that no mature nephrons are present at 8 to 9 weeks of development (Fig. 2.1E), however, this is the point when human kidneys have been described to become functional, as inferred from their contribution to the amniotic fluid volume 51 . To examine when cell-types associated with mature nephron identities emerge during human kidney development and to assess the degree of conservation between species, we undertook multiple approaches. First, we performed high resolution in situ hybridizations (SISH) for 26 genes known to be expressed within the nephron lineage; so-called anchor genes from an earlier appraisal to identify a minimum set of non-redundant molecular markers for key cell types in the developing and adult mouse kidney 52 . Second, we 34 analyzed the RNA from our whole kidney RNA profiles by comparing these data to existing RNA expression profiles from specific segments of the adult rat nephron. Third, we assembled a collection of 14 antibodies that recognize epitopes of proteins that are known to be present in specific nephron segments in the mouse and performed immunofluorescent analyses on cryo-sectioned kidneys from specimen ranging from week 8 to week 16. GUDMAP studies identified a list of 32 anchor genes on the basis of their specificity demarcating distinct cell types in the mouse nephron and not elsewhere in the kidney 52,53 . To determine when mature cell-types emerge and whether mouse anchor-genes are equivalently expressed in the human kidney, we performed section in situ hybridization (SISH) to visualize expression of the human counterpart of 26 of these genes; no human genes equivalent could be identified or sequence amplified for the other 6 (AI317395, BC089597, Cml1, Ugt2b37, Fam129a, and C230096N06). SISH was performed on > 9 sections per probe on samples originating from specimen aged 9-17 weeks of development. The SISH experiments were carried out on both cryo- sectioned and wax sectioned specimen. Twenty of the 26 gene were detected in the human kidney (Fig. 2.8C-K, Table 3). Only three (11%) genes displayed a directly comparable expression between mouse and human kidneys: SLC22A6, ENTPD5, and UMOD (Fig. 2.8C, D; Table 3; and data not shown). Six genes (23%) recapitulated the mouse expression domain but displayed additional expression not documented in the mouse, while 11 (42%) where expressed in what is likely a different cell population and 6 (23%) where not detected in the human SISH kidney studies. Data highlighting distinct expression domains for ACE, CRYL1, PRODH2, SLC3A1, SLC27A2, C2 and FBP1 are presented in (Fig. 2.8E-K) and data for all anchor genes are summarized in Table 3. As examples, FBP1 and C2 demarcate proximal tubule (PT) domains in the mouse kidney: FBP1 was expressed in human proximal tubule, but also more broadly within the renal pelvis and renal calyces and the loop of Henle (Fig. 2.8K) while C2 was absent from the PT but expressed strongly in both nephron and interstitial progenitor compartments 35 (Fig. 2.8J). Genes that were not detected by SISH (FMO2, MOGAT2, SLC18A1, SLC6A20, SPP2, and NPY) showed low or undetectable transcript levels in the wk9–wk21 whole kidney RNA-seq data consistent with the negative in situ hybridization result. Analysis of individual NCBI adult gene tissue summaries suggests none of these genes are strongly expressed in adult kidney (RPKM values of 5 or less). To extend rodent and human comparisons, we compared nephron segment RNA profiles from the rat and our human kidney RNA-seq data, analyzing expression of 56 genes highlighted in the rat nephron for distinct expression within specific rat nephron segments 54 . Whole expression profiles are included in Supplementary table 3. Over the week 9 to week 21 period, the proportions of different cell-types changes in the kidney 21,24,25 and it is therefore challenging to directly deduce the emergence of mature cell-types from whole tissue RNA samples. However, the expectation would be that mature cell-types of the various segments of the adult nephron remain rare at week 9 increasing with developmental age with a concomitant increase in the expression of genes associated with each cell type. We arrange the 56 genes into their respective expression domains (Fig. S2.4) as previously described for the rat 54 . Genes specific to the renal corpuscle such as NPHS2, PODXL, MAFB, SYNPO, and NPHS1 increased moderately and gradually over time. Genes expressed in S2-S3 segments of the proximal tubule (PTH1R and HNF4A) increased strongly from week 9 to week 11 and gradually thereafter. SPP1 and S100A6, marker-genes for the proximal portions of the loop of Henle, increased robustly and consistently over time. CLU, UMOD, and SLC12A1, expressed in the distal portion of the loop of Henle; DEFB1, expressed in distal convoluted tubule and connecting segment; and AQP2, expressed in the collecting duct, were all strongly upregulated after week 13 increasing to week 21. The data are consistent with the presence of renal corpuscles by week 11 that increase with other mature segments developing by week 11. Interestingly, many genes did not follow a coordinated behavior (e.g., PTERG3 and MAP3K7) or increase over development as expected. The 36 low level of conserved gene expression (11%) as established for the mouse anchor genes, raises the possibility that expression of several of the rat segmental markers genes may not be conserved in the developing human kidney. To improve the resolution, we performed antibody staining on kidneys from week 8 through to week 11 and compared expression patterns against E18.5 mouse kidneys, where immature and functional nephrons are abundant. Podocytes were labelled with for MAFB and NPHS2. To detect proximal tubule cells immunolabelling was performed against LRP2, CUBN 55 , and FITC-conjugated Lotus tetragonolobus lectin (LTL) was also used to label proximal tubule brush borders 56 . Distal tubules were detected using antibodies for SLC12A1 and SLC12A3 whilst the ascending limb of the loop of Henle was detected using antibodies for SLC12A1 and UMOD 57–59 . The collecting duct was labelled using KRT8, AQP2, and CALB1; KRT8 also demarcate the distal tubule. Vascular components within the renal corpuscle were labelled by VEGFR2. The distribution of these patterning markers is highlighted in (Fig. 2.9A). AQP2+, CALB1+, and KRT8+ collecting duct tubules (Fig. 2.9B, C) and rare CUBN+, LTL+, and LRP2+ proximal tubules (Fig. 2.9 B, D, E) were observed in the week 8, human kidney. Similarly, some morphologically immature MAFB+, VEGFR2+, and NPHS2+ renal corpuscles were also present (Fig. 2.9C, E-F). KRT8/18, specific to the mouse collecting duct, was also widely expressed in both the distal and proximal portions of nephrons (Fig. 2.9B-D, F). Ascending loop of Henle markers SLC12A1 and UMOD were absent until week 10 (Fig. 2.9G-H), and the distal tubule marker SLC12A3 until 11 (Fig. 2.9I). While the location of CUBN, AQP2, and LRP2 were as expected from mouse studies, UMOD and SLC12A1 showed a reduction in their overlapping domain in the human kidney versus mouse nephron (Fig. 2.9H; Fig. S5C). Unlike the mouse, where Calb1 is strongly detected in both the collecting duct and in the connecting tubule (Fig. S5A), we did not detect human CALB1 in nephrons at these time-points. DISCUSSION 37 In this study, we examined human kidney organogenesis in a large number of embryonic and fetal kidneys ranging from week 5 through to week 23, using immunohistochemistry, histology, three- dimensional modelling, and RNA profiling. Macro-anatomical features are conserved in the human and mouse albeit with distinct organization and temporal dynamics, and differences in associated gene expression. We discuss these findings, contrasting human and mouse development with a particular focus towards informing in vitro efforts to model human kidney development. Nephrogenic period in vivo and in induced NPCs Progression to S-shaped body nephrons takes under 24 hours in the mouse kidney and in primary mouse nephron progenitor cells the process takes less than 48 hours when induced in vitro 60 . Following the progression of the first set of nephrons in the human kidney indicates nephrogenesis commences at CS16 with S-shaped body formation at CS18-CS19, somewhat earlier than Potter (1972) described. This provides an estimate of around 8 days for the transition to S- shaped bodies. The slower time course of the nephrogenic program is consistent with mouse and human comparisons in other organ systems though the regulatory mechanisms determining the “pace of development” across mammalian species are not understood. Comparing the initiation of in vivo and PSC derived in vitro nephrogenesis Directed differentiation of nephrons has been described independently by three groups 13–15 . While each protocol differs in the detail, there is a common logic in WNT/FGF pathway-mediated induction of anterior or posterior intermediate mesoderm for varying times and the subsequent interaction amongst induced cell-types to generate complex nephron-like structures over varying periods of time: 18 days 14 , 22 days 13 , and 16 days 15 . In the kidney specimens analyzed, the first pretubular aggregate is detected at CS16 (37-41 days post ovulation) approximately 5-13 days after the initiation of ureteric bud ingrowth into the metanephric mesenchyme. The first S-shaped body is observed at CS18-19 or 44-51 days post 38 ovulation. The exact in vivo equivalent stage for human embryo-derived stem cells (ESCs) is debated, but reasonably falls between embryonic day (E) 6 post fertilization, when cells are most efficiently derived and embryonic disc stages pre-gastrulation E14 where single-cell transcriptomic analyses have placed ESCs 61 Taking a broad and inclusive range E6-14 as a developmental starting point for ESCs and induced pluripotent cell (iPSC) equivalents 62 , if in vitro development reflected an in vivo clock, the first S-shaped bodies would appear around 30-45 days after the initiation of hIPSC/hESC differentiation. Thus, initiation of in vitro nephrogenesis is either relatively accelerated or in vitro nephron structures may be more representative of earlier formed pronephric or mesonephric kidney structures 40 . In the mouse, activity of Hox11 paralogs specifically demarcate the metanephric kidney anlagen and their combined action is essential for metanephric kidney development 63,64 . Though there is strong evidence that Hox-boundaries correlate with morphological conservation across species, the anterior extent of Hox11 expression has not been determined in the human embryo. Analysis of our RNA-seq data herein confirms the expression of HOX10/11 paralogs and absence of HOX12/13 paralogs in human kidney samples as expected from mouse studies (Supplementary Table 4). Hox11 activity in in vitro kidney organoids appears to vary depending on the protocol. Re- analysis of RNA-seq data from human kidney organoids profiled by Takasato et al., shows no evidence of significant HOX11 paralog activity 14 though transcripts for HOX10 paralogs, and other HOX-members are present within the dataset (see Supplementary Table 3). In contrast, immunostaining supports HOXD11 paralog activity within organoids developed by Takasato et al., and Morizane et al., 14,65 In vitro studies will benefit from a more detailed molecular and cellular analysis of how kidney-like structures form. A pseudo-stratified ureteric bud We observed the appearance of a pseudo-stratified ureteric epithelium branch tip during stages CS16-CS19. Potter (1972), likewise described a multilayered organization but concluded this 39 to be an artefact of the high cell-density and crowding of cells 25 . However, the appearance of this structure in multiple early specimens and disappearance at later stages suggest this is a real structural feature of the outgrowing epithelium of the human, but not the mouse, ureteric bud. Multilayered branching epithelia have been reported in the mammary gland and other branching systems 66 . After budding, the mouse ureteric bud bifurcates (or more rarely trifurcates), there then follows an extensive period of bifurcation 36,48 . In the wholemount analysis of human kidney specimens (CS20 - week11 – Fig. 2.5), interdomain branches do not obviously originate from either the anterior or posterior domain branches. The increased cellularity of the outgrowing human ureteric bud might facilitate the formation of interdomain branching shortly after anterior and posterior domain branches form from the first bifurcation of the ureteric bud tip. Mechanisms driving lobulation of the human kidney The mechanisms driving kidney lobulation and the physiological purpose of this process are unknown. It has been suggested that lobulation correlates with increased organism body size but exceptions to this are common 21 . We detected the first sign of lobulation at CS19, when a subset of mesenchymal cells within the kidney align along the radial axis of the kidney forming striated cells clusters between the anterior and posterior domains of the kidney (arrowed in Fig 1C). The striated cells, presumably of an interstitial cell origin, presage the physical separation of lobes and may therefore play a role in the formation of lobes though addressing their function, or the triggers for their formation (local signaling and/or mechanical stresses) will be difficult to determine. Following the appearance of striations, surface indentations were observed, then actual lobes became evident anteriorly, in close proximity to the adrenal gland. Interestingly, at the level of our analysis, nephrogenic niches within interlobular or peripheral regions of the cortex were indistinguishable. The onset of renal function corresponds with a transitional period of collecting duct morphogenesis at CS23/week8 40 In the human kidney, we observe maturing glomeruli at an early stage of collecting duct development resembling the E12.5 – E13.5 mouse kidney, 2-3 days before active functional glomeruli are present in the mouse. Previous studies have suggested human kidneys start to contribute to amniotic fluid volume at this time 51 . Further, our immunofluorescence analyses also show vascularized renal corpuscles (Fig. 2.9) connected to proximal tubules displaying several physiologically important proteins, e.g., CUBN and LRP2. In contrast, Loop of Henle marker activity, including UMOD, and SLC12A1, emerged at week 10, and only at around week 11 could distal tubule marker SLC12A3 be observed (Fig.9 and Fig. 2.2). This suggests glomerular filtration may be occurring at CS23 but it is likely considerably later in human kidney development that the organ adopts a more mature functional activity. Interestingly, multiple kidney specimens around CS23 and week 9 displayed characteristically expanded collecting duct morphologies distinct from other stages. This has not been described in the mouse, and is unlikely to be a prominent feature given the number of careful analyses examining mouse branching morphogenesis 36 . If active glomerular filtration is indeed occurring, this could lead to transient swelling of ureteric branch tips if the ureter connection to the bladder had not formed or was obstructed 67,68 . This could also explain the observed luminal expansion which extends into stalk regions. Alternatively, altered signaling within the nephrogenic niche or interactions between tip cells and surrounding matrix could modify branch tip morphology, and this could spread through the epithelial network 69,70 . The architecture of the developing human nephrogenic niche We observed that the 3D architecture and composition of human and mouse nephrogenic niches followed a similar developmental progression in their reduction of progenitor endowment but proceeded at different time-scales. The developmental range we described in 3D for the human occurred over circa 80 days (11 weeks), and what we consider a comparative developmental progression occurred in the mouse within 9 days (E12.5-P2). Although we observed macroscopic 41 similarities in the anatomy of nephrogenic niche, absolute numbers of cellular components as well as absolute distance among anatomical structures varied across species. The number of nephron progenitors per human tip, the number of human ureteric epithelial tips, as well as distance between tips, is of a different order in the human kidney. Further, the formation of rosette-like clusters of ureteric tips (Fig. 2.7G-H), where nephrogenic niches face outwards, away from the center is a distinct human feature. Given the placement of progenitors, nephron formation occurs radially around branch clusters. What accounts for this asymmetry is unclear. Non-conserved expression of anchor genes A priority of the GUDMAP initiative has been to identify robust sets of genes to unambiguously identify discrete structures in the mouse kidney, so called anchor genes 52 . Evaluation of human PSC and NPC derived kidney-like structures in kidney organoids has leant heavily on these genes to interpret in vitro nephrogenesis. Surprisingly, only 3 of 26 anchor genes conserved what appeared to be a “mouse-like” expression pattern in the human kidney. Some prominent mouse expressed genes like Spp2 52 , which encodes a secreted phosphoprotein that binds members of the Tgf-ß superfamily 71 and is a specific product of a sub-region of the mouse proximal tubule segment, are likely completely absent from the human kidney. This raises the question of how Spp2 modifies kidney form, function or physiology across species. Clearly, these differences stress the need for developing strong criteria for scoring cell diversity and identifying minimal sets of cell type identifiers most appropriate to assess human renal kidney cell types and renal activity. This is especially important given the clinical relevance of several of these genes. For example, SLC3A1 mutations are linked to cysteinuria 72 and FBP1 mutations to clear cell renal cell carcinoma 73 . These findings also impact interpretation of human kidney organoid development and the investment into gene-reporter driven efforts to identify and isolate critical cell types from these in vitro model systems. As examples, GATA3 and KRT8/18 have both been used to identify ureteric epithelial derivatives in several reports of human kidney organoids 14 . However, in contrast to the 42 mouse, both proteins extend form the ureteric epithelium into the distal nephron tubule indicating neither protein is a specific marker for the ureteric epithelial lineage (Fig. 2.9; and data not shown). MAIN FIGURES AND TABLES 43 Figure 2.1. Histological analyses of human kidney development. (A-E) Hematoxylin and eosin staining of human kidneys from CS13 to CS23. PTA: Pretubular aggregate, RV: Renal vesicle,, SSB: S-shaped body nephron, UBT: Ureteric bud tip, CM: Cap mesenchyme, RC: Renal corpuscle, DT: Distal tubule,PT: Proximal tubule, CD: collecting duct. Scale bars as indicated on fields. Black arrowheads point to cell-striations, red arrowheads point to surface indentations. Boxed areas shown in Figure 2-4. 44 45 Figure 2.2. Histological analyses of human kidney development. (A-D) Hematoxylin and eosin staining of human kidneys from week 10 to week 16. Scale bars as indicated on fields. Red arrowheads point to surface indentations, green arrowheads point to lobe folds. 46 47 Figure 2.3. Immunofluorescent characterization of early human kidney development and lobulation. (A-C) Sagittal sections of a week 8 (CS23) and week 15 kidney with immunofluorescent labelling for SIX2, KRT8/18, and PHH3 (insert shows high magnification of week 8 tip and nephron progenitors; scalebar 20 µm). (B-C) show a peripheral and interlobular region of week 15 cortex, respectively. Inserts show high-magnification of tips with surrounding nephron progenitors. Scale-bars in inserts are 20 µm and inserts show SIX2, KRT8, DAPI stain. Arrowheads in inserts point to polarized progenitor cells. Equivalent stains for mouse E15.5 and P2 are shown in (D-E). (F-H) Sagittal section of a week 8 (CS23) and week 15 kidney with staining for WT1, JAG1, and CDH1. (G-H) shows a peripheral and interlobular region of week 15 kidney cortex, respectively. (I-J) show equivalent stains for mouse E15.5 and P2 stages. PTA: Pretubular Aggregate; SSB: S-shaped body nephron; RV: Renal Vesicle. White arrowheads point to lobe folds, open arrows point to multi-layered cap mesenchyme, yellow arrowheads point to polarized progenitors around tips. White dashed lines demark where lobes meet. 48 49 Figure 2.4. Histological analyses of human kidney development. (A-I) Hematoxylin and eosin staining of human kidneys from CS16 to week 16 kidney as specified on fields. Magnified fields from Fig 1 have been rotated so top and bottom reflect the cortico-medullary axis. PTA: Pretubular aggregate, RV: Renal vesicle; SSB: S-shaped body nephron, UBT: Ureteric bud tip, CM: Cap mesenchyme, RC: Renal corpuscle; DT: Distal tubule; PT: Proximal tubule. Scale bars as indicated on fields. 50 Figure 2.5. 3D wholemount analyses of early human kidney development. (A-F) Immunofluorescently labelled whole human kidneys at CS20, CS22, CS23, and week11 stained for JAG1 to mark nascent nephrons and KRT8 to highlight the ureteric bud. The week 11 sample also stained for WT1 to mark glomeruli. Nephron counts performed using the JAG1 stains and highlighted using spheres. p.b: posterior domain branch; i.b: interdomain branch; a.b.: anterior domain branch, indicated with dashed lines and arrowheads. Nephron counts and scale bars as indicated on fields. 51 52 Figure 2.6. Three-dimensional characterization of the human nephrogenic compartment. (A-F) Whole-mount immunofluorescent stains for SIX1 and KRT8 in week11 to week 23 kidneys. Images display a view from the top of the nephrogenic compartment looking downwards towards the center of the kidney, a single confocal section, and the side-view of the niche. Single slices also display PHH3 stain. (G) Quantitative analysis of the number of nephron progenitor cells per ureteric bud tip. (H) Quantitative analysis of PHH3+ cells in the SIX1 + cell population. 53 54 Figure 2.7. Three-dimensional characterization of the human nephrogenic compartment. Whole- mount immunofluorescent stains for SIX1 and KRT8 in week11 to week 23 kidneys and quantitative analyses. (A-B, D-E) Images displaying lower magnification overview of changes to the tip niche morphologies. Green spheres indicate individual terminal points of tips which were measured to analyze tip-to-nearest-tip distances. (C, F) Quantitative analysis of distances between tips and number of ‘tips-per-niche’ during development. Colored areas in D-E highlight individual clusters of niches and the numbers indicate tips per cluster. (G-H) Schematic showing the top-view architecture of the rosettes and the side-view distribution of tips, niches, nascent nephrons, and mature nephrons (arcading not shown). 55 56 Figure 2.8. Identification of genes differentially expressed during maturation of human embryonic kidney. (A) Gene-level correlation of normalized mRNA-Seq reads between week 9 human kidney samples and week 21 human kidney samples. (B) (Left) Number of differentially expressed genes between week 9 human kidney samples and week 21 human kidney samples. (Middle) Results of gene ontology (GO) terms enrichment analysis of the indicated gene sets, with representative ones (right) from each set of genes. (C-K) Expression of genes defined as anchor-genes in the mouse. Human samples range in age from week 14 day4 to week 16 day 3. Expression and age as defined on the fields. Square inserts show magnified representative regions of nephron segments and kidney compartments that were labelled. 57 58 Figure 2.9. Kidneys from week 8, 10, and 11 embryos and fetuses immuno stained for nephron markers indicative of mature cell-type development. (A) Table indicating the expected detection pattern for proteins used in Fig.9. (B-F) week 8. (G-H) Week 10 day 3. (I) Week 11 day 4. The antibody stains and structures are as indicated on fields. Scale bar is 50 µm. PT: proximal tubule; DT: distal tubule; LOH: loop of Henle; RC: renal corpuscle; CD: collecting duct. 59 60 Table 2.1. Summary of samples used in the study. Graphed data for specimens used for H&E, SISH, IHC, whole-mount (WM), and RNA-seq. Table 2.2. Anatomical ontology map (see www.gudmap.org for detailed ontology) of nephrogenic structures and their first appearance in CS13 to CS23 kidney samples. 61 Table 2.3. 26 Mouse anchor genes analyzed for expression in the human fetal kidney. Samples analyzed ranging in ages from week 14 to week 16. EPT: early proximal tubule. Term as previously described 52 . Ontology accession numbers for human samples as described on Gudmap.org. Green fields indicate conserved expression between mouse and human. 62 SUPPLEMENTAY FIGURES 63 Figure S2.1. Histological reference data for mouse kidney development. (A-D) Hematoxylin and eosin staining of mouse kidneys from E11.5 to P2. Scale bars as indicated on fields. Boxed regions in low magnification field show the magnified regions on the right-hand side. 64 65 Figure S2.2. Immunofluorescent characterization of early human kidney development and lobulation. (A-B) Sagittal sections of a week 15 kidney with immunofluorescent labelling for SIX2, KRT8/18, and PHH3, and WT1, JAG1, CDH1, respectively. These are whole kidney views of the same samples displayed in Figure 3. Arrowheads mark lobe folds. (C-E) Mouse and human samples stained for SIX2 MEIS1 KRT8 show distribution of interstitial cells surrounding the cap mesenchyme. D and E are peripheral and interlobular regions from a week 15 kidney. Dotted white line separates two lobes in E 66 67 Figure S2.3. Three-dimensional characterization of the human nephrogenic compartment. (A) Whole-mount immunofluorescent stains for KRT8 from week 11 to week 23 kidneys. (B) 3D view of the embryonic (E15.5) and postnatal day 2 mouse kidney. 68 Figure S2.4. Analysis of gene expression within whole kidney RNAseq data from week 9 day 5, week 11 day 3, week 13, week 17, and week 21 human fetal kidneys. Genes analyzed are in rat enriched within the compartments indicated in the diagrams (Lee et al., 2015). Genes, expression values, and samples are as indicated on graphs. RC: renal corpuscle; S1-S3: segments in proximal tubule; SDL: short descending limb; LDLOM: long descending limb outer medulla; LDLIM: long descending limb inner medulla; tAL: thin ascending limb; mTAL: medullary thick ascending limb; cTAL: cortical thick ascending limb; DCT: distal convoluted tubule; CNT: connecting tubule. 69 70 MOVIE LEGENDS Supplementary movie 2.1. Whole human CS20 kidney resolved in 3D. Whole-mount stained for KRT8 (white) and JAG1 (orange). As shown in Fig. 2.5A. Supplementary movie 2.2. Whole human CS20 kidney resolved in 3D. Whole-mount stained for KRT8 (white) and JAG1 (orange). As shown in Fig. 2.5B. Figure S2.5. Mouse kidneys immuno stained for nephron markers indicative of mature cell-type development. (A-E) E18.5 mouse kidneys immuno-stained for nephron markers indicative of physiological maturation. Antibody stains and structures as indicated on fields. Scale bar is 50 µm. PT: proximal tubule; DT: distal tubule; LOH: loop of Henle; RC: renal corpuscle; CD: collecting duct; PT: proximal convoluted tubule. 71 Supplementary movie 2.3. Whole human CS22 kidney resolved in 3D. Whole-mount stained for KRT8 (white) and JAG1 (orange). As shown in Fig. 2.5C. Supplementary movie 2.4. Whole human CS23 kidney resolved in 3D. Whole-mount stained for KRT8 (white) and JAG1 (orange). As shown in Fig. 2.5D. Supplementary movie 2.5. Whole human wk11 kidney resolved in 3D. Whole-mount stained for KRT8 (white) and JAG1 (orange). As shown in Fig. 2.5E. Supplementary movie 2.6. Three-dimensional architecture of week 11 human nephrogenic niches. Supplementary movie 2.7. Three-dimensional architecture of week 13 human nephrogenic niches. Supplementary movie 2.8. Three-dimensional architecture of week 15 human nephrogenic niches. Supplementary movie 2.9. Three-dimensional architecture of week 16 human nephrogenic niches. Supplementary movie 2.10. Three-dimensional architecture of week 18 human nephrogenic niches. Supplementary movie 2.11. Three-dimensional architecture of week 23 human nephrogenic niches. SUPPLEMENTARY TABLE LEGENDS Supplementary table 2.1. Whole kidney RNA-seq profiling. Differentially expressed genes at week 9 and week 21. 72 Supplementary table 2.2. Whole kidney RNA-seq profiling. GO-term analyses for differentially expressed genes between week 9, week 11, week 13, week 17, and week 21. Supplementary table 2.3. Whole kidney RNA-seq profiling. Differentially expressed genes between week 9, week 11, week 13, week 17, and week 21. Supplementary table 2.4. Expression of HOX genes in human fetal kidney and re-analysis of RNA-seq data from Takasato et al., 2015, focusing on HOX gene expression. 73 Chapter 3 Conserved and Divergent Features of Mesenchymal Progenitor Cell Types within the Cortical Nephrogenic Niche of the Human and Mouse Kidney This work has been published on the Journal of American Society of Nephrology (PMID: 29449449). It was led by Nils Lindström and Andrew McMahon, who supervised the conceptualization, experimental design, data collection, data analysis, manuscript editing and reviewing. I contributed to the experimental design and optimization of immunofluorescence analysis and confocal imaging to visualize the nephrogenic niches and validate transcriptional findings. INTRODUCTION Unlike many organ systems where long-lived stem cell populations generate and regenerate functional mature cell types, the mammalian metanephric (definitive, adult) kidney forms from a small subset of lineage-restricted progenitor cell types that undergo expansion and commitment over a limited period of fetal and neonatal development 1 . Molecular, cellular and genetic studies in the mouse have demonstrated that the transcription factors Foxd1 and Six2 demarcate self-renewing, lineage-restricted interstitial and nephron progenitor cells (IPCs and NPCs), respectively 2,3 . Each population occupies a unique position within the nephrogenic niche, NPCs closely associate with underlying collecting duct progenitor cells (CDPCs), while IPCs localize between the NPCs and the renal capsule 1 . Interactions amongst these progenitor pools drives the process of kidney organogenesis 1 . In these, the self-renewal and commitment of NPCs is finely balanced by complex reciprocal signaling networks through Fgf, Bmp, Gdnf, Wnt, Notch, Fat4, and Hippo signaling pathways 4–15 . Their control of NPC fate, self-renewal, proliferation and survival is directed by a number of transcription factors operating within NPCs including Six2, Sall1, Osr1, Pax2 and Hox11 paralogs 16– 20 . On induction, a subset of NPCs around each ureteric epithelial branch tip undergoes a 74 mesenchymal to epithelial transformation forming an epithelial nephron precursor, the renal vesicle. The mouse kidney forms approximately 16,000 nephrons 21 , all initiated over a 12-13 day period of development 21 . In contrast, the final nephron count varies widely in the human kidney, with 1,000,000 a reasonable estimate, and all nephrogenesis initiated and completed in a period of 30- 32 weeks 22 . Interestingly, low nephron counts are linked to kidney disease 22 . Cessation of mouse nephrogenesis is marked by the exhaustion of the nephron progenitor pool 21,23 and this is likely the case in the developing human kidney. In conjunction with the commitment of NPCs, there is a progressive commitment of adjacent IPCs to different interstitial compartments in the mouse kidney 2 . This process is less well understood though temporal fate mapping studies indicate a progressive recruitment of IPCs along the expanding radial axis of the kidney into distinct vascular-associated (pericytes and mesangial cells) and tubule-associated interstitial fibroblast populations in cortical and medullary regions 2,24,25 . At the molecular level, IPCs or their derivatives activate a number of transcriptional regulators that distinguish IPCs from adjacent NPCs: these include Foxd1, Meis1, Pbx1 10,26,27 . The role of these is largely unclear though genetic analysis shows Foxd1 and other IPC proteins play a key role in regulating interactions with NPCs and CDPCs 9,10,14,28,29 . Our understanding of mammalian nephron and interstitial progenitor types is almost entirely based on rat and mouse models. In the human kidney, initial studies have pointed to molecular differences between mouse and human NPCs in the expression of SIX family members, key factors in the specification and maintenance of NPCs 16,30,31 . Recent advances in generating kidney-like structures from human pluripotent stem cells highlight the need to understand human kidney progenitor types and their differentiated cellular derivatives to characterize and optimize in vitro strategies 32–36 . Here, we employed a variety of approaches to examine NPC and IPC compartments in the developing human fetal kidney. These data yield new insights into human kidney development and provide a valuable resource to guide in vitro efforts to engineer normal kidney structures. 75 MATERIALS AND METHODS Human kidney specimens Consented, anonymized, human fetal tissue was obtained from elective terminations following review of the study by Keck School of Medicine of the University of Southern California’s Institutional Review Board. Kidney samples ranging in age from 13 to 18 weeks of gestation were supplied from the Children’s Hospital of Los Angeles and the University of California, San Francisco. Gestational age was determined per guidelines specified by the American College of Obstetricians and Gynecologists using ultrasound, heel to toe, and crown to rump measurements following published Carnegie Stages 67–69 . Stages as stated in the manuscript indicate age of embryo or fetus from point of conception/fertilization. Samples from the Children’s Hospital of Los Angeles were received immediately after elective terminations and transported on ice at 4°C in 10% fetal bovine serum, 25mM Hepes, high glucose DMEM (SIGMA). Samples from the University of California, San Francisco were transported similarly but by overnight courier. Given the anonymized nature of the specimens, no further information was available regarding the specimens or the normalcy of the pregnancy. Animals All animal work was reviewed and institutionally approved by Institutional Animal Care and Use Committees (IACUC) at the University of Southern California and performed according to institutional guidelines. Timed matings were set up to recover embryos and neonates at the appropriate age. The Foxd1-GCE strain (B6;129S4-Foxd1tm2(GFP/cre/ERT2)Amc/J) was generated as previously described (Humphreys et al., 2010). The Rosa26tdTomato reporter line (B6.Cg- Gt(ROSA)26Sortm14(CAG-tdTomato)Hze/J) was obtained from JAX (Madisen et al., 2010). Heterozygous Foxd1-GCE animals were crossed with female Rosa26tdTomato homozygous females. Pregnant females were injected with 3mg Tamoxifen per 40g at E13.3 and kidneys collected at 76 E14.5. The Six2TGC line was generated as previously described 3 . Male heterozygous Six2TGCs animals were crossed with female Swiss Webster mice and embryos collected at E16.5. Image and sample quantification 2D immunofluorescent analyses Frozen and sectioned samples were stained as described previously (Lindström et al., 2017a) to detect SIX2, SIX2, LEF1, FOXD1, and CITED1. KRT8 and β-laminin were used as structural markers to determine the location of the ureteric epithelium and nephrons. Images were captured with a 63x objective on a Leica SP8. Data were captured as 8-bit images. IMARIS 8.2 (Bitplane) was used for quantification of nuclear antibody signals. The Spot function was used to manually add circular spots to mark all nuclei on the image frame using DAPI-highlighted nuclei as a reference. Due to the convoluted shape of nuclei in 2D sections and the circular shape of the spot function, we used multiple smaller spots to represent single nuclei to ensure accurate quantitation and coverage across the nuclei. Spots were grouped into three cell populations: (1) cap mesenchyme (SIX2 + cells), (2) cortical interstitium (FOXD1 + cells), (3) all other cells. To compare the mean intensity of spots we first normalized the mean intensity values taking into consideration the background signal and the maximum signal for each channel. To do this we measured the intensity for each channel throughout all spots and identified the lower 5 th percentile intensity mean (background), as well as the maximum value. Each spot’s intensity mean was thereafter normalized as follows: ( 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝑚𝑚 𝐼𝐼 𝑚𝑚 𝐼𝐼 𝑜𝑜𝑜𝑜 𝐼𝐼 𝑠𝑠 𝑜𝑜𝐼𝐼 − 5𝐼𝐼 ℎ 𝑠𝑠 𝐼𝐼 𝑝𝑝 𝑝𝑝 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝑝𝑝 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝑀𝑀 𝑚𝑚 𝑀𝑀 𝐼𝐼 𝑚𝑚 𝑀𝑀 𝑚𝑚 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 − 5𝐼𝐼 ℎ 𝑠𝑠 𝐼𝐼 𝑝𝑝 𝑝𝑝 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝑝𝑝 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 𝐼𝐼 ) 𝑀𝑀 100 This transforms the intensity mean of each spot onto a 0-100 scale with the 5 th percentile equaling 0 and the maximum being 100, respectively. To plot the normalized intensity of spots against their position within the cap mesenchyme population we marked the most cortical point of the cap mesenchyme and utilized this as point 0. A line was extended in a medullary direction parallel to the ureteric epithelium around which the cap mesenchyme was located. 77 RNA-sequencing data All RNA sequencing data is provided at the Gene Expression Omnibus; GEO accession numbers: GSE102378 (mouse RNAseq data), GSE102230 (human RNAseq data), (human single-cell RNA seq data: GSE102596). Full details for the number of samples can be found for each submission. In brief: MARIS or conventional RNA sequencing was performed on 5 kidneys for SIX2 MARIS, 2 kidneys for MEIS1/SIX2 MARIS, 3 kidneys for mouse Six2 MARIS, 3 kidneys for mouse Six2-GFP sequencing, 2 kidneys for mouse Foxd1 sequencing. One kidney was dissociated for single- cell RNA sequencing. The GEO submission comprises 39 RNA-seq libraries for RNA-seq and 1 multi- cell library for single-cell RNA sequencing. MARIS Staining and FACS The MARIS staining and FACS procedure was performed as described in Hrvatin et al., 2014 45 with the following modifications. Human and mouse cortical nephrogenic zone cells were digested from E16.5 embryonic mouse kidneys or 13-18 week fetal human kidneys using 10 mg/ml pancreatin (Sigma, P1625) and 2.5 mg/ml collagenase A (Roche, 11 088 793 001) enzyme mixture and filtered through 40 µm filter (BD Falcon 352340) as described in 70 . Cell fixation, washing, permeabilization, and centrifugation were performed as described in Hrvatin et al., 2014 45 using the following solutions with all subsequent steps performed at 4° C. Fix buffer: 4% PFA (Electron Microscopy Sciences), 0.1% saponin (Sigma-Aldrich 47036) in molecular grade PBS (Ambion) supplemented with 1 ∶100 RNasin Plus RNase Inhibitor (Promega, N2615) Wash Buffer: PBS containing 0.2% BSA (Gemini Bio-Products), 0.1% saponin (Sigma-Aldrich), 1 ∶100 RNasin Plus RNase Inihibitor. SIX2 Primary antibody (Mybiosource, MBS610128) and MEIS1/2/3 Primary antibody (Active Motif, 39795) staining of cells at 1:5000 dilution was carried out while rocking for overnight at 4° C in staining buffer containing PBS with 1% BSA, 0.1% saponin and 1 ∶25 RNasin Plus RNase Inhibitor. Cells were washed and stained with donkey anti-rabbit Alexa 488 (Thermofischer, A-21206) and goat anti-mouse IgG1 555 (Thermofischer, A21127) secondary antibody for 45 minutes. 78 Subsequent washing and FACS sorting were performed at a concentration of 5-10 M cells/ml with sort buffer containing PBS, 0.5% BSA, and 1 ∶25 RNasin Plus RNase Inhibitor. Cells were sorted on the FACSAria I and II (BD Biosciences) using FACSDiva software. Sorting gates were set with reference to negative controls with no primary antibody stain. The sorting efficiency was maintained at above 90%. Cells were collected in tubes that were coated with a small amount of sorting buffer. For FACS sorting of Six2TGC and TdTomato positive cells, the mouse kidneys were dissected and dissociated in the same enzymatic solution as described above. The cells were not fixed but instead immediately FAC sorted for GFP or tdTomato. RNA isolation of MARIS The RNA isolation was performed as described in Hrvatin et al., 2014 with the following modifications. FACS collected SIX2+, SIX2-, MEIS1+SIX2+, MEIS1+SIX2-, and MEIS1-SIX2- cells were pelleted by centrifugation at 3000 g for 10′ at 4° C. Total RNA was isolated using the RecoverAll Total Nucleic Acid Isolation kit (Ambion, AM1975), starting at protease digestion step with protease incubation time of 1 hour at 50°C and inactivated at 80° C for 15 minutes. Cell lysates were frozen at −80° C overnight and extracted for RNA according to the manufacturers recommended protocol. For the non-fixed mouse cells, the RNA was isolated as previously described (Lindstrom et al., 2017). RNA-seq analysis mRNA-Seq libraries were synthesized with Kapa stranded mRNA-Seq kit, and were sequenced on Illumina NextSeq500 platform at USC Epigenome Center. All mRNA-Seq reads were aligned to the mouse or human reference genome (mm10 or hg38) using the TopHat2 (Trapnell et al., 2009). Quantification of RNA-Seq reads to generate RPKM was performed by Partek Genomics Suite software, version 6.6 (St. Louis, MO, USA). TPM was calculated by dividing RPKM value by ratio of sequencing reads from the corresponding library that were mapped to exon regions of the 79 genome. We identified differentially expressed genes as those satisfying the following 3 criteria: 1) p value smaller than 0.05 from statistical tests performed by DESeq2 71 ; 2) more than 3-fold difference of average normalized read counts between the groups compared; 3) average TPM more than 5 in at least one of the groups. Gene ontology (GO) analysis was performed using PANTHER classification system 72 ; http://pantherdb.org/). We ranked the relevance of GO terms by fold enrichment of number of observed genes over number of expected genes. The GO terms with binomial p value more than 0.01 were omitted due to statistical insignificance. We analyzed the variability between all the MARIS RNA-Seq data for NPCs from both the huSIX2+MARIS and the huSIX2+/MEIS1+ MARIS data and found that correlation between samples was high in 6/7 samples (R 2 range 0.929 to 0.977). Replicate 1 from the huSIX2+MARIS displayed lower correlation to the other samples (R 2 =0.715 to 0.778). This variability may have arisen at various points: 1) each replicate RNA sample was extracted from a different human fetal kidney with no known, but presumed genetic variability, in addition to samples originating from a range of close developmental stages; 2) RNA from replicates 2-5 for the huSIX2+MARIS exhibited lower quality, as measured by RNA integrity, due to difficulties in library construction/sequencing consequent to low RNA content thereby indicating that replicate 1 may be higher quality; 3) The total amount of mapped reads from replicates 2-5 are approximately 25% less than replicate 1, which might have contributed to decreased sample complexity. Single-cell sequencing Cell preparation Cells were dissociated as described for the MARIS protocol from a week 16 kidney and live cells sorted by FACS using DAPI (Thermo Fisher Scientific) and DRAQ5 (Thermo Fisher Scientific) to select against dead cells and for live cells, respectively. 78 % of cells were live and intact, indicating robust isolation methods. Seven thousand live cells were input into a 10X Genomics Chromium device expecting the capture of 4000 cells. Illumina ready sequence-able libraries were then 80 generated using the 10X Chromium single cell 3’ RNASeq protocol. Subsequently, sequencing was carried out on the Illumina NextSeq 500/550 platform with the goal of obtaining at least 50,000 reads per cell. 3731 valid barcodes (‘cells) were recovered after filtering and UMI counting. Sequence Mapping Mapping was performed using the CellRanger software version 1.3.1 through the CellRanger count command. We used STAR version 2.5.1b to map the second end of the FASTQ reads to the human genome version GRCh37.p13 and uniquely mapped reads were counted using the Ensembl GTF annotation as reference. A total of 70.1% of the reads had unique mapping, which corresponded to a total of 3,731 valid barcodes. Quality Control To filter out potential doublets and low quality cells we calculated 3 quality measures for each individual cell: 1. the Good-Turing estimate of observed expression 73 given by S = 1-n1/N, where n1 is the number of genes with one mapped read and N is the total number of reads in the cell. Saturation ranged from 40% to 100%. We chose to keep only cells with S > 0.6. 2. The percentage of mitochondrial gene expression. We filtered out any cell with more than 5% of the total expression mapped to genes annotated to come from mitochondrial DNA. 3. The deviation from a read-UMI fitted curve: We expect the number of observed genes to increase linearly with the number of reads for cells that have not attained full saturation. We fitted a line between the number of non-zero genes and number of reads and filtered out cells whose residuals were more than 5 standard deviations from the line. A total of 2,750 cells were kept after filtering through these 3 criteria, indicating 73% of sequenced cells were of high quality. 81 Analysis of week 16 scRNAseq dataset We used the Seurat R package 55 version 1.4 for further analysis of the remaining cells. The MeanVarPlot function with default parameters was used to find a subset of genes whose variability is above the expected technical noise. We found 582 such genes, which were further used for Principal Component Analysis (PCA function). To find significant PCs, we used the JackStraw test 74 and kept the first 24 PCs, which had p < 10 -4 . These PCs were used for clustering using the FindClusters function with k = 30 nearest neighbors. We found 12 clusters, whose identities were further validated by the AssessNodes function, which builds a random forest classifier for each split node in the cluster hierarchy. The highest out of bag error (OOBE) we found was 9%, which indicates that all clusters have a clear identity. Differential expression was performed with the likelihood ratio proposed by McDavid 75 and implemented in the FindAllMarkers function, in which genes inside a cluster are compared with the expression in all cells outside of the cluster. We set the minimum average difference between inside and outside clusters to 0.15 and no minimum average expression threshold. Analysis of Cluster 4 We repeated the aforementioned procedures with only the subset of 318 cells that were assigned to cluster 4. We found 685 variable genes and the 4 first principal components to be statistically significant (p < 10 -4 ). Clustering with 4 principal components yielded 4 sub-clusters whose maximum OOBE was 6.5%. RESULTS Differences and similarities in anchor gene expression patterns in the nephrogenic zone Mouse studies have identified Cited1 and Six2 as transcription factor-encoding genes expressed specifically by NPCs 3,37 and each is an anchor gene for the NPC compartment 38 . NPCs are surrounded by IPCs that in the mouse control NPC self-renewal and differentiation 9,14,29 and 82 branching growth of the CDPC population 28 . Two well-characterized transcriptional regulators identifying the mouse IPC compartment are Foxd1 and Meis1. Each is present in IPCs but not NPCs; however, Foxd1 is IPC specific within this lineage, whereas Meis1 extends into IPC derivatives outside of the nephrogenic zone 2,26,39,40 . We examined expression of human orthologs of these well characterized mouse NPC and IPC markers in the developing human kidney at week 14-15. As in the mouse, CITED1 and SIX2 were strongly expressed within mesenchymal cells capping the ureteric epithelial branch tips, the likely human NPC population (Fig. 3.1A and B). However, whereas Cited1 transcripts were restricted to NPCs in the mouse, CITED1 expression extended into differentiating pretubular aggregates in the human kidney. Further, Six2 RNA extend into early NPC-derivatives, pretubular aggregates, and renal vesicles in the mouse 41 , but in the human SIX2 expression was detected much later, within proximal regions of the S-shaped body (Fig. S3.1 D-E). Examining FOXD1 and MEIS1, we observed a FOXD1+/MEIS1+ population of peripheral mesenchymal cells similarly positioned to mouse IPCs, that are likely human IPC counterparts (Fig. 3.1C, D). Surprisingly, expression of both genes also extended into adjacent NPCs and early NPC derivatives, although expression of both genes was weaker in the NPC population (Fig. 3.1C, D). FOXD1 was also detected in podocytes consistent with a separate role for Foxd1 in podocyte programs from mouse kidney studies 10 . Sall1 and Wt1, encode zinc-finger containing transcription factors critical for kidney development expressed in both NPCs and IPCs in the mouse kidney with highest levels in the NPC population 17,42,43 . Human counterparts of both genes showed a mouse-like expression in the likely human NPC and IPC populations (Fig. 3.1E-F). In all material examined, no differences in gene expression were observed between peripheral and interlobular regions of the human kidney. To determine whether overlapping gene expression profiles resulted in co-translation of SIX2, CITED1, MEIS1 and FOXD1 mRNAs in NPCs, we performed immunolabelling studies on week 8 and 83 16 human kidneys comparing these data with E15.5 and P2 mouse kidneys. These developmental stages were chosen for reasons discussed previously 44 as they represent two stages of active nephrogenesis during and after ureteric branching 21,23 . In the mouse nephrogenic niche, Six + /Cited1 + cells cluster around Krt8 + ureteric epithelial branch tips (Fig. 3.2A). High Six2 levels were observed in NPCs and Six2 was present at lower levels in anatomically distinct pretubular aggregates (Fig. 3.2B) while Cited1 was restricted to NPCs, as predicted from in situ hybridization data (Fig. 3.2C) and previous studies 41 . In the human nephrogenic niche, SIX2 + /CITED1 + cells were more broadly distributed around epithelial branch tips (Fig. 3.2D) with a less marked difference in SIX2 levels in pretubular aggregates (Fig. 3.2E) with detectable SIX2 and CITED1 extending into renal vesicles (Fig. 3.2F and data not shown). Analysis of Foxd1 showed Foxd1 + IPCs surrounding Six2 + NPCs in the developing mouse kidney; no Foxd1 was detected in the NPC population (Fig. 3.2G-I). At P2 Foxd1 was detected at very low levels around the nephrogenic niche (Fig. S3.1 (F-G). In the human kidney, a strong FOXD1+ putative IPC population surrounded SIX2+ NPCs; however, FOXD1 was present in SIX2+ NPCs (Fig. 3.2J-L), albeit at lower levels (13% lower than in IPCs). MEIS1 was also detected within human NPCs and mouse NPCs showed low levels of Meis1 at both E15.5 and P2 (Fig. S3.1A-C). In summary, human and mouse kidneys differ in the broader extent of co-activation of IPC-associated regulatory factors within the NPC population and the persistence of NPC-associated regulatory factors into differentiating nephron components. RNA-sequence analysis of purified human and mouse nephron and interstitial progenitors suggest divergences and similarities in regulatory pathways Previous studies have attempted to obtain transcriptional profiles of human NPCs utilizing an ITGA8-directed antibody enrichment protocol to compare transcriptional profiles between mouse and human NPC compartments (O’Brien et al., 2016). These approaches identified the transcription factor SIX1 as a specific component of the human NPC population during periods of active 84 nephrogenesis. These NPC enriched populations showed significant contamination from other mesenchymal cell types 30 . To obtain a more specific human SIX2+ NPC profile, we applied the MARIS (Method for Analyzing RNA following Intracellular Sorting) approach 45 . In this, a cortical mesenchymal kidney isolate was fixed and permeabilized, then immunostained with anti Six2/SIX2 antibodies. Mouse (Six2+) and human (SIX2+) NPC-enriched populations were purified from by FACS, mRNA isolated and RNA-sequencing performed to obtain NPC expression profiles. Initially, we performed control experiments using a transgenic Six2GFP transgenic reporter mouse strain which labels Six2+ nephron progenitors with nuclear GFP 3 . E16.5 Six2GFP expressing kidneys were gently dissociated to release cells from the cortical nephrogenic niche and Six2GFP+ and Six2GFP- cells were either directly isolated by FACS or subjected to MARIS, then transcriptionally profiled (Fig. 3.3A). Mouse cells processed for MARIS with a Six2 antibody are hereafter referred to as mMARIS-Six2+ or mMARIS-Six2-. The two isolation techniques were similar in cell content: approximately half of the cortical cell preparation (56%) were Six2-GFP+ and a similar fraction (66%) were mMARIS-Six2+. Six2GFP+ and mMARIS-Six2+ RNA-seq datasets showed a strong correlation (R 2 =0.97) indicating that MARIS generates a comparable transcriptional profile to FACS isolation of viable, GFP-labelled Six2+ cells (Fig. 3.3B). As expected, both the Six2GFP+ and mMARIS-Six2+ cells expressed nephron progenitor markers such as Phf19, Cited1, Osr1, and Six2 (Fig. 3.3C – Supplementary table 1). The key difference between these two approaches was in the detection of early nephron induction markers such as Wnt4 and Pax8: these were weakly expressed in Six2-GFP+ cells but not mMARIS-Six2+ NPCs. Thus, mMARIS-Six2+ sorted cells likely displayed a more progenitor-like profile, presumably a reflection of the bias in setting a window for Six2 detection in the MARIS that selects for the higher Six2 levels relative to live FACs of Six2-GFP+ NPCs. In addition, perdurance of GFP in Six2-GFP+ NPCs may capture a small population of the earliest induced NPCs. As expected, GO-Term analyses showed mMARIS-Six2 and Six2-GFP samples were enriched for genes associated with kidney 85 development. Collectively, these data demonstrate the MARIS strategy can generate a robust NPC transcriptional signature. To profile SIX2+ human NPCs, we performed a brief cortical dissociation of human fetal kidneys (week 16) to release mesenchymal cell types, then performed MARIS to isolate SIX2+ cells (Fig. 3.3D). Approximately 70% of the human cortical cell population was positive for SIX2; a comparable number to mouse cortical isolations. An initial comparison of the hMARIS-SIX2+ RNA-seq data to the previously generated ITGA8+ NPC-enriched cell profile 30 showed a good correlation (R 2 =0.81 - Supplementary figure S3.2A). Further analysis showed the hMARIS-SIX2+ sample displayed a higher expression of nephron progenitor markers (Supplementary figure S3.2C) and lower expression of genes expressed by differentiating cells, except for PAX8, or in epithelializing nephron structures (Supplementary figure S2D). The hMARIS-SIX2+ RNA profile also showed minimal contamination by blood and vascular endothelial cell types (Supplementary figure S3.2E), and reduced expression of genes indicative of cells within the ureteric epithelium that underlies the NPC niche (Supplementary figure S3.2F). In conclusion, the hMARIS-SIX2+ RNA-seq profile matched expectations for a highly-enriched NPC population. Overall, hMARIS-SIX2+ and mMARIS-Six2+ expression profiles showed a significant correlation in their gene expression profiles (R 2 =0.61) (Fig. 3.3E). Genes common to both mouse and human nephron progenitors included known progenitor markers such as SIX2, CITED1, PHF19, OSR1, SALL1, EYA1. Several genes expressed in nephron progenitors in both species still displayed variations in absolute expression levels; for example, CITED1 was expressed at lower levels compared to Cited1 (TPM values of 54 human vs. 259 mouse) and as expected, SIX1 showed an extreme difference 30 ; Six1 was undetectable in mouse NPCs (TPM values of 27 human vs. 0 mouse). To specifically identify genes with differential expression profiles between human and mouse NPCs, we looked for genes expressed at levels greater than 5 Transcripts Per Million (TPM) with an 86 expression level differential of 3-fold or greater. By these criteria, 1230 genes were enriched in human NPCs and 1087 genes in mouse NPCs (see Supplementary table 2). GO-Term analyses on the mouse-enriched genes indicated a strong upregulation of genes involved in oxidative phosphorylation and mitochondrial function, and the regulation of cell proliferation (Fig. 3.3F). Other genes strongly enriched in human progenitors included components of retinoic acid signaling CRABP2 (TPM values of 349 human vs. 54 mouse), cell-adhesion complexes CDH24 (TPM values 284 human vs. 9 mouse), and genes linked to human disease and congenital disorders: DAPL1, linked to renal neoplasia (Klomp et al., 2010; DAPL1 TPM values 155 human vs. 0 mouse ) and COL9A2 linked to Stickler syndrome, which is associated with renal agenesis (Baker et al., 2011; COL9A2: TPM values 139 human vs. 2 mouse). Conversely, several genes were more strongly represented in mouse NPCs including: Crym, a previously identified anchor gene for mouse NPCs that is not detected in human NPCs (Rumballe et al., 2011; TPM values of 205 mouse vs 0 TPM in human) and Capn6 (TPM values of 248 mouse vs. 2 human). In situ data and data from a transgenic mouse model confirm mouse NPC activity of Crym (GUDMAP ID 22105 and 14077) and Capn6 expression in cap mesenchyme and nascent nephrons has been documented in mouse kidney studies 48 . Variation was also observed in related genes with potential overlapping activities. As an example, Rspo1 a modulator and agonist of WNT-signaling 49 was expressed at 6-fold higher levels compared to RSPO1 (TPM values of 84 mouse vs. 13 human), in contrast, RSPO3 and Rspo3 displayed comparable levels (TPM values of 20 human vs. 19 mouse). A redundancy between Rspo1 and Rspo3 actions could underlie the absence of a phenotype in Rspo1 mutants 50,51 . To validate expression predictions from the MARIS data, we selected 17 genes enriched in either human or mouse NPCs for further characterization by SISH (Fig. 3.4 and Fig. 3.5 – supplementary table 3). Of these, we could detect expression for 16 in either or both the mouse or human kidney. The exception was Fgf20/FGF20, which is predicted to be mouse NPC specific, but 87 was below the limits of SISH detection (TPM values of 10 mouse vs 0 human). Matching the differential expression predictions, HIP1R, UNC5B, LYPD1, DAPL1, ECEL1, COL9A2, WASF3, TNFRSF19, were expressed at high levels in human NPCs (Fig. 3.4 and Fig. 3.5) and Crym, Serpinf1, Slc12a2, Foxd2, Rspo1, Capn6 in mouse NPCs (Fig. 3.4 and Fig. 3.5). Interestingly, RSPO1, CRYM, CAPN6, and SLC12A2, four human homologs of mouse-specific nephron-progenitor enriched genes were actually expressed in developing human nephrons at the S-shaped body stage, a profile not observed in the developing mouse kidney (Fig. 3.4I-J, L-M). Conversely, mouse homologs of human- specific nephron-progenitor enriched genes Unc5b, Col9a2, and Pcdh15 were also expressed in other cellular compartments of the mouse kidney (Fig. 3.6D, G, K). In summary, SISH analysis verified predicted species-specific differences in expression profiles, indicating that other predicted differences are likely to be valid, and identified additional species-specific differences in the expression of this cohort of genes in other kidney structures. Data in Fig. 3.1 and Fig. 3.2 indicate that human orthologs of mouse genes distinguishing mouse IPCs from mouse NPCs were also expressed within the human NPC population. To evaluate if this is a wider trend and to compare human and mouse IPC gene expression profiles we adopted a two-pronged approach. First, we extracted a mouse IPC-enriched gene expression profile by isolating mouse IPCs using the Foxd1-GCE strain, where Cre-ERT2 is expressed from the Foxd1 locus 2,24 in combination with the Rosa26tdTomato reporter line (Madisen et al., 2010). Pregnant mice were injected with tamoxifen at E13.5 and Tomato+ cells were isolated at E14.5 for RNA sequencing. To be able to compare this expression profile to mouse NPCs we isolated mouse NPCs using the Six2- GFP reporter strain as described above. Second, to identify a human IPC RNA profile we performed MARIS co-labelling with MEIS1 (FOXD1 antibodies were not compatible with this procedure) and SIX2 antibodies on preparations of cortical, mesenchyme cell-enriched human kidney isolates at week 13- 15 (Supplementay Fig. 3.3A) generating RNA-seq profiles for MEIS1+/SIX2- (IPC-enriched), MEIS1+/SIX2+ (NPCs), and cortex cells (Supplementay Fig. 3.3B). 88 We first contrasted genes enriched in either human or mouse IPC (hIPC and mIPC) to their respective cortex RNA profiles (Supplementary Fig.3C). hIPCs and mIPCs enriched genes showed a low correlation (R=.0.36) as expected because of the broader specificity of MEIS1 to Foxd1. We focused the analysis to identify genes differentially expressed between human IPC and NPCs (Fig. 3.6A). As anticipated, the human IPC and NPC fractions both expressed FOXD1 and MEIS1 (TPM 38 vs. 41 and 120 vs. 110, respectively) whereas SIX2 and CITED1 where confined to NPCs (TPM 2 vs. 191 and 1 vs. 49). Applying similar thresholding criteria as in earlier MARIS data, 503 genes showed enriched expression in hIPCs vs. hNPC cell fractions (Fig. 3.6A; Supplementary table 4) including genes associated with extracellular matrix or matrix interactions (ITGA9, ITGA1, COL3A1), transcription (GATA3) and cell signaling (PDGFRB). Conversely, 534 genes were specifically enriched in NPC versus IPC fractions. These included well-characterized NPC marker genes such as SIX2, CITED1, EYA1, genes identified earlier in SIX2 MARIS comparisons such as PCDH15, LYPD1, and ECEL1 and novel gene predictions including ELAVL4, FAT3, and CRABP2. Enrichment of PDGFRA, PDGFRB, and PBX1 within hIPCs was confirmed through immunolabelling studies (Fig. 3.6C). In agreement with expression profiles, PDGFRA and PDGRFB were only detected in IPCs (expression extends also into likely IPC interstitial/stromal derivatives) while PBX1 was present in both hIPCs and hNPCs but at markedly elevated within hIPCs (Fig. 3.6C). To determine whether human orthologs of mouse IPC markers were expressed more broadly in NPCs we first identified a full set of genes whose expression was enriched in mouse mIPCs compared to mNPCs (Fig. 3.6B; Supplementary table 5); this gave a set of 647 genes including Foxd1 and Meis1, and other recognizable interstitial markers. We next determined whether the human orthologs of these 706 genes were expressed in hIPC and hNPC enriched fractions, and the relative expression between each cell population (Fig. 3.6D; Supplementary table 6). Twenty-seven percent of human orthologs were enriched in hIPCs displaying a similar expression to the mouse. 89 Twenty-two percent of genes were co-expressed in both hNPCs and hIPCs including in addition to MEIS1 and FODX1, SMOC2, and ROR2. Smoc2 is expressed broadly in the cortical nephrogenic interstitium of the mouse but is largely absent from NPCs 52 . SMOC2 was expressed at similar levels in hNPC and hIPC cell fractions (TPM 10 vs. 14, respectively). In contrast, Ror2 expression is linked to mouse NPCs 53 and while ROR2 was found at higher levels in hNPCs, ROR2 transcripts were also present in IPCs (TPM 29 vs. 12, respectively). Three percent of the mIPC markers were not expressed in hIPCs but were expressed in hNPCs having potentially shifted expression from the interstitial to nephrogenic lineage (e.g., CRABP2) while 49% of genes were not expressed above the cutoff threshold (TPM 5) in the human IPC fraction. Collectively, the data indicate a significant disparity between the transcription profiles of human and mouse IPCs. Cellular diversity of human nephron progenitors Single-cell RNA sequencing (scRNAseq) can potentially reveal cellular heterogeneity that is difficult to define with other procedures. We applied scRNAseq using the 10xGenomics platform 54 to profile 2750 predominantly mesenchymal cell types from the cortical nephrogenic niche of the week 16 fetal human kidney. Twelve cell-populations emerged from unsupervised clustering analyses using Seurat 55 (Fig. 3.7A) Clusters were identified by known marker genes for each population (Supplementary table 7). Four cell-population clusters belonged to the interstitial lineage, whilst the nephrogenic lineage was represented by 3 cell-populations, the remaining populations included vascular endothelial cells, distinct proliferating cell compartments and cells of the immune system (Fig. 3.7A, B; Supplementary table 7). Here, we focused on the NPC compartment of these data. NPCs were identified as cell- population 4 on the basis of CITED1, SIX1, LYPD1, and DAPL1 expression (Fig. 3.7A). To scrutinize cellular diversity within cell-population 4, we re-examined this cluster (Fig. 3.7C – Supplementary table 8). Four NPC sub-clusters emerged, which segregated into 4 distinguishable cell-populations; we termed these 4A, 4B, 4C, and 4D (Fig. 3.7C). NPCs (4A) expressed TMEM100, CITED1, and 90 MEOX1. A second cell-population (4B) differentially expressed ID1, MEG3, and DAPL1, and induced NPCs (4C) expressed CCND1, PAX8, and LHX1, and contained a small subpopulation of differentiating MAFB and PODXL expressing cells likely initiating podocyte differentiation (Fig. 3.7J). Proliferating cells (4D) expressed CENPF, MKI67 and TOP2A (Fig. 3.7C-E, I) and likely represented a mixture of several cell-types aggregated by their shared strong cell-cycle profile as TOP2A/MKI67/CENPF expressing cells included subsets of cells expressing PAX8, SIX1, and CITED1 (Fig. 3.7E-I). In the progression of mouse nephrogenesis Cited1+/Six2+ self-renewing nephron progenitors transition into Cited1-/Six2+ cells, a cell-state primed for differentiation, then to an induced, committed Cited1-/Six2-/Pax8+ nephron-forming cell state 5,41 . The expression domains for CITED1, SIX2, and SIX1 recapitulated that expected for self-renewing, primed, and committed NPCs (Fig. 3.8A) and their expression profiles (Fig. 3.7F) suggest they closely correspond to the cell- populations identified as 4A to 4C, which define overlapping expression domains. In situ hybridization showed that COL9A2, PCDH15, UNC5B, and ECEL1, as identified earlier (Fig. 3.3-4) were mainly expressed in 4A cells, while WASF3, DAPL1, PHF19 and TNFRSF19 were expressed also in 4B, and LYPD1 most strongly in 4C (Fig. 3.8A, Fig. 3.7F-H). Each domain showed significant overlap. TMEM100, and ROBO2 were predicted to be co-expressed in population 4A and follow a CITED1-like pattern (Supplementary table 8). TMEM100 and ROBO2 displayed a restricted localization within NPCs, but unlike CITED1 their expression did not persist into early nephron- forming stages (Fig. 3.8C) though much later in nephron development ROBO2 was upregulated in podocytes. ROBO2 was also present in the interstitial lineage. DISCUSSION Here, we examined the conserved and divergent features of the human and mouse nephrogenic niche using single-cell sequencing, MARIS sequencing, RNA sequencing, in situ hybridization and immunohistochemistry. In summary, we find that cells in the human nephrogenic 91 niche show significant divergence from their mouse counterparts and that the boundaries between NPC and IPC lineages follow different rules to those defined in the mouse. We focus our discussion to the differences and similarities of human and mouse NPCs and IPCs and the impact these may have on the nephrogenic niche. Comparative analysis of human and mouse nephron progenitor cells A number of genes have been identified genetically as having important roles within the NPC compartment of the developing mouse kidney. These include Six2, Eya1, Osr1, Gas1, Itga8, and Fgf20 and Pax2 which are expressed within NPCs and not IPCs; and Wt1 and Sall1 which are expressed in both NPCs and IPCs, but at elevated levels in the former 4,16–18,43,56–59 . Human equivalents of these genes showed broad conservation consistent with conserved roles from mouse to man. Interestingly, we observe conservation in gene expression profiles for other highly NPC restricted genes, such as Cited1 and Phf19, that have no observable function in the mouse kidney (Boyle et al., 2007; unpublished data) indicating conservation in regulatory programs that do not appear to underlie a functional role in all mammalian species. Whether there is a distinct role for either gene in human NPCs remains to be determined. Although several functionally important genes showed conserved expression, our comparative analyses of human and mouse NPCs highlighted a large number of genes (1230 and 1087, respectively) enriched in NPCs of each species. We confirmed the predictions hold for all 16 genes detectable by SISH indicating there are likely to be many more genes with bone-fide expression differences in these datasets. These findings beg the question – what might be distinct biological processes at play within mouse and human NPCs? Two critical processes are the regulation of progenitor self-renewal and differentiation, the balance of which ultimately determine the final number of nephrons formed. In the mouse, both require Wnt9b signaling in NPCs, the Wnt9b ligand is secreted by the subjacent ureteric epithelium 6,61 . Several mouse Wnt9b target genes have been suggested including Cited1, Btbd11, Etv5, Gdnf, 92 and Itga8 6 ; many of which are functionally important in the mouse NPC 13,58,62 . Strikingly, human NPCs displayed multiple examples of putative WNT9B targets that could not be detected, such as CDH4, SLC45A3, SORBS2, CLDN9, PLA2G7, and SLC12A2 suggesting differences in regulatory mechanisms between mouse and man. Gene Ontology analyses of species-enriched genes in mouse and human NPCs suggested increased oxidative metabolism in mouse. Consistent with these data, basic cellular processes such as metabolism, formulate a large portion of inter-species gene expression disparity 63 . Although a functional role for metabolism in NPCs has not been directly addressed, deletion of p53 in mouse NPCs result in aberrant cell-metabolism and reduced NPC numbers 64 . A temporally condensed nephrogenic program, as seen in the mouse compared to human (Lindström et al., 2017a), may increase metabolic demands on NPCs. Of note, during the validation of gene expression differences, we found Rspo1, Crym, Capn6, and Slc12a2 to be enriched in mouse but not in human NPCs. RSPO1, CRYM, CAPN6, and SLC12A2 were instead specifically expressed in narrow segments within the human S-shaped body. The transposition of gene expression from one compartment to another suggests either the loss of a requirement or the necessity a different cell-type. Alternatively, these genes are simply a readout of broader underlying changes to pathways and may represent non-essential genes that fluctuate in expression without functional consequences. The exact nature of all these differences requires further investigation to determine if they relate to biological function. Gene expression in human nephron and interstitial progenitors adhere to different rules from those in the mouse Our data suggested that human orthologs of mouse IPC marker genes (Foxd1/FOXD1 and Meis1/MEIS1) were not restricted to the IPC lineage, as they are in the mouse, but were also expressed in human NPCs. To examine this in greater detail we performed RNA profiling on mouse and human IPCs and NPCs and demonstrated that only 27% of genes that we categorized as mouse 93 IPC marker genes were enriched in human IPCs. The remaining mouse IPC marker genes (73% - 472 genes) would therefore be categorized as displaying non-conserved expression patterns. It has recently been shown that mouse NPCs maintain their identity and prevent lineage switching to interstitial cell types via a Pax2-dependent mechanism 20 . When Pax2 is genetically removed from mouse NPCs, they upregulate IPC-enriched genes such as Col1a1, Col3a1, Col1a2, Anax2, Dcn 20 . Given that Pax2 is implicated in interstitial cell fate repression, we scrutinized the expression of PAX2 to determine if it is downregulated in human NPCs. However, human PAX2 was robustly expressed in NPCs (NPC TPM values of 364 human vs. 159 mouse). COL1A1 and ANXA2 were not expressed in either NPCs or IPCs in the human but we did find expression of COL3A1, COL2A2, and DCN in IPCs and not NPCs, as expected from the mouse. It is therefore unlikely that the increased expression of IPC genes in human NPCs is a result of a PAX2 dependent mechanism. The change in FOXD1 expression is noteworthy due to the known function of Foxd1 in regulating, directly or indirectly, the patterning of the kidney capsule, collecting duct and nephron 10,26 . FOXD1 mRNA and protein levels were very similar comparing human NPCs and IPCs, suggesting FOXD1 within NPCs could fundamentally alter signaling dynamics within the nephrogenic niche. In mouse IPC’s Foxd1 is required to regulate both Dcn and Fat4,which encode a leucine-rich proteoglycan and a membrane bound signaling factor, respectively 9,65 . Foxd1 and Fat4 mutants both display an expansion of NPCs due to a failure of NPC commitment, a phenotype that closely resembles a gross ablation of the IPC compartment 9,14,29 . While DCN expression remains enriched in IPCs compared to NPCs as in the mouse (TPM IPCs: 11 versus 45; TPM NPCs: 4 versus 2), interestingly, human FAT4 is expressed at much lower levels than its mouse counterpart in IPCs (TPM values of 4 versus 21) suggesting a potential alteration in the FAT4 signaling axis. As reduced FAT4 signaling is predicted to enhance progenitor expansion, such a mechanism could contribute to a larger, longer-lived human NPC population. Single-cell analyses reveal population complexities in the human cap mesenchyme 94 Single-cell RNA sequencing is likely to play an important role in defining cell diversity and providing evidence for diversity generating processes in human kidney development where genetic approaches, a mainstay of mouse studies, are not possible. A current mouse-centered model of NPC differentiation, suggests NPCs differentiate from a self-renewing Cited1+ state and progress through an intermediate state primed for differentiation in response to a combination of Wnt, Bmp, and Hippo signaling 5,9,61 . The human NPC population displays comparable diversity as judged by single cell transcriptional profiling. We validated predicted cell-clusters by examining the expression of 14 genes by in situ hybridization (Fig. 3.8) and showed that gene expression patterns can be categorized within the expression domains as defined by CITED1, SIX2, and SIX1. Our data agree with scRNAseq data from the mouse which indicates that the NPC population displays low diversity 66 . The focus is now on determining the pathways and genes that control the differentiation cascade during induction and the differentiation trajectories that generate specific cell states within developing nephron precursors. MAIN FIGURES AND TABLES Figure 3.1. In situ hybridization labelling for nephron compartment marker genes. Left hand and right column fields display in situ hybridization labelling of cryo-sectioned human week 14-15 kidneys. Sections show peripheral nephrogenic niches and interlobular nephrogenic niches (Left and Right, respectively). IM: Interstitial Mesenchyme, CM: Cap Mesenchyme, UB: Ureteric Bud, PTA: Pretubular Aggregate, RV: Renal Vesicle. Red, blue, and black dashed lines indicate nascent nephrons, cap mesenchyme, and ureteric bud epithelium, respectively. 95 96 Figure 3.2. Nephron and interstitial progenitor markers mix and persist into epithelializing nephrons. A, D display immunofluorescent stains for CITED1 and SIX2 in mouse and human kidneys. Insert in D shows CITED1 protein in the human RV (scale bar 10 µm). (B, C, E, F) Quantitative analyses of signal intensity distribution for CITED1 and SIX2. (G-L) Immunofluorescent analysis for FOXD1 and SIX2 and intensity correlation plots for these. IM: Interstitial Mesenchyme, CM: Cap Mesenchyme, UB: Ureteric Bud, PTA: Pretubular aggregate, RV: Renal vesicle. White, blue, and red dashed lines, indicate ureteric bud epithelium, cap mesenchyme, and nascent nephrons, respectively. Scale as indicated on fields. 97 98 Figure 3.3. Transcriptional profiling of mouse and putative human nephron progenitor cells assisted by intracellular staining of Six2/SIX2 followed by FACS (MARIS). (A) Separation of Six2+ cell population from dissociated mouse (m) embryonic kidney cortex cells by either FACS of Six2GFP reporter line (middle) or Six2 MARIS (right). (B) Gene-level correlation of normalized mRNA-Seq reads between NPC profiles generated by Six2 reporter line (Six2GFP+) and Six2 MARIS (mSIX2+). (C) Overlap (left) between NPC-specific genes identified by differential gene expression analysis between Six2GFP+ vs. Six2GFP- (TPM_Six2GFP+ > 5, TPM_Six2GFP+/TPM_Six2GFP- > 3, p < 0.05), or between mSix2+ vs. mSix2- (TPM_mSix2+ > 5, TPM_mSix2+/TPM_Six2- > 3, p < 0.05). Results (middle) of gene ontology (GO) terms enrichment analysis of the indicated gene sets, with representative ones (right) from each set of genes. (D) Separation of SIX2+ cell population from dissociated human (hu) fetal kidney cortex. (E) Gene-level correlation of normalized mRNA-Seq reads between human and mouse NPC profiles obtained by MARIS; human- (orange) or mouse- (cyan) enriched genes were indicated. (F) Top 3 GO terms enriched from the human- (top) and mouse- (bottom) enriched genes. 99 100 Figure 3.4. In situ hybridization labelling for human and mouse enriched nephron progenitor genes. (A-O) In situ hybridization labelling of cryo-sectioned human week 16 kidneys. In situ labelling as indicated on fields. Inserts show enlarged regions from main fields. Scale bars as indicated on fields. 101 102 Figure 3.5. In situ hybridization labelling for human and mouse enriched nephron progenitor genes. (A-O) Complementary in situ hybridization labelling of cryo-sectioned mouse E15.5 and P2 mouse kidneys to Figure 4. In situ labelling as indicated on fields. Scale bars as indicated on fields. Scale bars in magnified inserts are 20 µm. 103 104 Figure 3.6. Transcriptional profiling of human and mouse interstitial progenitor cells. (A) Gene- level correlation of normalized mRNA-Seq reads between human (hu) IPC and NPC. (B) Gene- level correlation of normalized mRNA-Seq reads between mouse (ms) IPC and NPC. (C) Immunostaining of interstitial markers in mouse and human kidneys as specified on fields. (D) Breakdown of mouse (top) or human (bottom) genes expressed in IPC or NPC by their relative expression in the 2 cell types. Genes enriched in one of the cell types satisfy TPM > 5 and fold change >3. Other expressed genes are categorized as ‘non-DE’. (Middle) Pie chart shows breakdown of mouse IPC-enriched genes by their relative expression between human IPC and NPC. 105 106 Figure 3.7. Single-cell transcriptional profiling of human nephrogenic niche cells. (A) tSNE plot displaying principal component analysis of ~2800 human kidney cortex cells from week 16 kidney. Cell-identities as indicated on figure by gene expression. Dashed line demarks the nephron progenitors. (B) Cluster hierarchies inferred from differential gene expression and GO- term analyses of top 50 differentially expressed genes per cluster. (C) tSNE plot displaying principal component analysis of cells from cluster 4 in (A). (D) Cluster hierarchies inferred from differential gene expression and GO-term analysis of top 50 differentially expressed genes per cluster as seen in (C). (E) tSNE plots displaying gene expression levels in cells. (F-J) Gene expression plots for novel and established NPC markers. Genes as indicated on plots. 107 108 Figure 3.8. Validation of NPC cell-populations and exploration of novel NPC marker genes. (A) Genes identified in NPC sub-clusters stratify into distinct gene expression patterns, SISH for genes as specified on fields, clusters as specified. (B) Gene expression plot for TMEM100, ROBO2, and CITED1. (C) Immunofluorescent staining for TMEM100, CITED1, ROBO2, and KRT8/19 in human fetal kidney. Scale bar as indicated. 109 110 Figure S3.1. MEIS1 is present in human NPCs at a protein level. (A) Immunofluorescent stain for MEIS1, SIX2, and KRT8 in human week 16 kidney and (B-C) in mouse E15.5 and P2 kidneys. Red dashed lines indicate NPCs. (D-E) SISH for Six2 and SIX2 in mouse E15.5 and human week 15 kidneys. (F-G) Immunofluorescent stain for Foxd1 in E15.5 and P2 mouse kidneys. IM: Interstitial Mesenchyme, CM: Cap Mesenchyme, UB: Ureteric Bud, PTA: Pretubular Aggregate, RV: Renal Vesicle. Scale bars as indicated on fields. 111 112 Figure S3.2. Enriched nephron progenitor signature from SIX2 MARIS compared to ITGA8 cell- surface labeling. (A) Gene-level correlation of normalized mRNA-Seq reads between NPC profiles generated by SIX2 MARIS and ITGA8 labeling. (B) A schematic depicting cell types present in the nephrogenic zone, same colors used as for the graphs in C-F. (C) Markers of uninduced nephron progenitors, (D) induction and lineage commitment, (E) blood/endothelial, and (F) ureteric epithelium from SIX2+ MARIS and ITGA8+ cells. 113 SUPPLEMENTARY TABLE LEGENDS Supplementary table 3.1. Genes expressed in mouse Six2GFP+ NPCs isolated by sorting for GFP or by MARIS for Six2 protein. Gene lists correspond to that described in Fig. 3.3C. Supplementary table 3.2. Genes enriched in mouse Six2+ NPCs isolated by MARIS and in human SIX2+ cells isolated by MARIS. Gene lists correspond to that described in Fig. 3.3F. Supplementary table 3.3. Gene list for human or mouse NPC enriched genes validated by SISH. Supplementary table 3.4. Gene lists for comparisons between human IPCs and NPCs from Figure 3.6C. Figure S3.3. Comparisons of human and mouse interstitial progenitor cells. (A) Immunostaining of 16-week human fetal kidney as specified on fields. (B) FACS of SIX2 and MEIS1 MARIS with human fetal kidney cortical cells. (C) Gene-level correlation of normalized mRNA-Seq reads from mouse (ms) and human (hu) IPC over conserved genes between mouse and human, top 3 Gene Ontology terms, and representative genes. 114 Supplementary table 3.5. Gene lists for comparisons between mouse IPCs and NPCs from Figure 3.6D. Supplementary table 3.6. Gene lists for comparisons of mouse IPC enriched genes and their expression in human IPCs or NPCs from Figure 3.6F. Supplementary table 3.7. Differential gene expression analysis for clusters 1-12 from Figure 3.7A. Supplementary table 3.8. Differential gene expression analysis for clusters 1-4 from Figure 3.7E. 115 Chapter 4 Conserved and Divergent Molecular and Anatomic Features of Human and Mouse Nephron Patterning This chapter has been published on the Journal of American Society of Nephrology (PMID: 29449451). Nils Lindström and I led the study, designed experiments, tested reagents, collected data, and prepared the manuscript, with the contribution from Jinjin Guo, Elisaneth Rutledge, Riana Parvez, Matthew Thornton, Brendan Grubbs, and Jill A. McMahon. Andrew McMahon supervised and advised the conceptualization, methodology, data analysis, funding acquisition, manuscript review and editing. INTRODUCTION Studies predominantly in the mouse and rat have provided a blueprint for mammalian nephrogenesis 1,2 . Nephron formation involves a complex series of interactions among nephron progenitor cells (NPCs), overlying interstitial progenitor cells (IPCs) and underlying epithelial cells at the branch tips of the developing ureteric epithelial collecting duct network 1–3 . Nephrogenesis within the Six2+/Cited1+ NPC pool 4,5 is promoted by Wnt9b/Ctnnd1, Lif, Bmp7, and FAT4 signaling 6–15 . Signaling initiates a subset of NPCs to form pretubular aggregate (PTAs) beneath the ureteric epithelial branch tips and PTAs activate synthesis of transcriptional regulators (Pax8) and signaling factors (Wnt4 and Fgf8) that are essential for further progression of the nephrogenic program 16–18 . In this, Wnt4 is critical for a mesenchymal to epithelial transition that establishes the renal vesicle (RV), the precursor for each nephron 16,19–21 . In addition to a classic apical-basal epithelial polarity, the RV displays proximal-distal polarity relative to the adjacent ureteric epithelium. Although careful lineage mapping has not been performed, evidence suggests cells positioned in close contact with the ureteric epithelium generate fates of the distal tubule and connecting segment, while the proximal region forms podocytes and 116 parietal epithelium of the renal corpuscle 22,23 . The RV undergoes a complex morphogenesis through comma (CSB) and S-shaped body (SSB) stages with a concurrent increase in regional cell complexity along the proximal-distal axis and the formation of a patent-luminal connection between the distal SSB and ureteric epithelial-derived collecting duct network 24 . Genetic analysis and in vitro studies have demonstrated that Notch, Bmp, PI3-kinase, Fgf, and Wnt signaling pathways play critical roles in the elaboration of proximal-distal pattern in the RV to SSB transition. Distal cells express Wnt4, and exhibit high levels of Lef1, a transcriptional target and mediator of canonical Wnt signaling 22 . Elevating Wnt-signaling in vitro leads to an inhibition of proximal and expansion of distal cell identities, consistent with an instructive role for Wnt-signaling in promoting distal cell fates 25 . Lgr5, a Wnt target, is expressed in a subdomain of the distal SSB delineating a distal tubule precursor population, and also suggests Wnt-dependency in distal identity formation 25,26 . Further evidence indicates Fgf8 18 and appropriate levels of Bmp signaling are also critical 25 . At the transcriptional level, distal development is contingent on the activity of Pou3f3 and Lhx1 27,28 . The medial segment of the SSB is demarcated by high expression of genes encoding multiple Notch-pathway components: the Notch ligands Jag1 and Dll1, Notch receptors Notch1 and Notch2, the Notch pathway modulator Lfng, and Notch transcriptional targets Hes1, Hes5, and HeyL 29–31 . Genetic analysis has demonstrated Notch signaling through Notch2 is required for normal development of proximal tubule segments and components of the renal corpuscle 30,31 . The transcription factors Irx3 and Hnf1b are both required for medial development 32,33 . In the proximal- most region of the nephron, normal podocyte identity development is dependent on the action of several transcriptional regulators, notably Mafb, Tcf21, and Foxc2 34–36 . The ongoing function of these factors beyond the SSB stage are unclear though conditional removal of Tcf21 later in mature podocytes indicates a continuing role in podocyte programs 34 . Of note, the precise mapping of distal, medial, and proximal markers to determine potential overlap, has not been performed. 117 Macro-anatomical analyses of the developing human kidney suggest a broadly similar architecture to its murine counterpart 37–40 . However, molecular analyses of progenitor compartments comparing the mouse and human kidney have identified distinct regulatory features that may underlie differences in nephron-forming programs 41,42 . Here, we performed detailed comparative molecular and cellular analyses to extend an understanding of early nephron patterning in the developing mouse and human kidney. Overall, these studies argue for similar processes at play, although we observed unanticipated cellular diversity in the early epithelializing human nephron. In addition, fate-mapping of cells within a Wnt4+ domain provides a register for the positioning of proximal cell fates within the developing SSB that is likely shared between mouse and man. The complexity of emerging patterns in the human nephron will guide and inform in vitro efforts to recapitulate human nephrogenesis. MATERIALS AND METHODS The protocols as relating to human kidney material, animal husbandry, in situ hybridization, immunolabelling, and microscopy are as described previously in this series of papers 40,42 . Specific details pertinent to this study are described here. Animal care and embryo collection All animal work was reviewed and institutionally approved by Institutional Animal Care and Use Committees (IACUC) at the University of Southern California and performed according to institutional guidelines. Wnt4GCE mice were generated as described previously 4 and were mated with Rosa26tdToamto mice (B6.Cg-Gt(ROSA)26Sortm14(CAG-tdTomato)Hze/J) 55 obtained from the Jackson Laboratories. Timed matings were set up to recover neonates at the appropriate age. Tamoxifen was injected at postnatal day 3 and kidneys collected at week 8. Three experimental animals were sectioned and stained for this analysis. Antibody-directed analyses 118 Immunofluorescent stains were performed as outlined previously 40 with the following primary antibodies: PAX2 (R&D, AF3364, 1:500; Biolegend 901001 1:500), PAX8 (Abcam, 189249, 1:1000), HES1 (Cell Signaling, 11988, 1:300), SALL1 (R&D PP-K9814-00 1:500), WT1 (Abcam, ab89901, 1:1000), FOXC2 (R&D, AF6989, 1:500), LHX1 (Santa Cruz, sc-19341, 1:300), LEF1 (Cell Signaling, 2230, 1:300; Santa Cruz, sc-8591, 1:100), SOX9 (Abcam, ab185230, 1:1000), GATA3 (R&D, AF2605, 1:300), HNF1B (Santa Cruz, sc-22840, 1:300), HOXD11 (Abcam, ab60715, 1:300), POU3F3 (Thermo Scientific, PA5-64311, 1:1000), SIX1 (Cell Signaling, 12891, 1:1000), JAG1 (R&D, AF599, 1:300), CUBN (Santa Cruz, sc-20607, 1:500), AQP1 (Abcam, ab168387, 1:1000), AQP2 (Santa Cruz, sc-9882, 1:300), SLC3A1 (Sigma, HPA038360, 1:500), CALB1 (Sigma, C9848, 1:300), MAFB (Santa Cruz, sc-10022, 1:300), NPHS2 (Abcam, ab50339, 1:10,000), LRP2 (My Bio Source, MBS690201, 1:1000), SLC12A1 (Sigma, HPA018107, 1:1000), UMOD (R&D, AF5144 and AF5175, 1:500), SLC12A3 (Sigma, HPA028748, 1:300, SIX2 (Sigma Aldrich, SAB1401533; 1:500), SIX2 (MyBioSource, MBS610128; 1:1000), CITED1 (Abcam, ab55467; 1:300), KRT8 (DSHB, troma-1; 1:50), β-laminin (Santa Cruz, sc-33709; 1:300), CDH1 (BD Transduction Laboratories, 610182; 1:300). Secondary antibodies were purchased from Molecular Probes (ThermoFisher Scientific) and used at a 1:1000 dilution. Sample numbers analyzed The number (n) of independent human fetal kidneys analyzed for each antibody were as follows: CITED1 (n=6), LEF1 (n=6), KRT8 (n=6), SIX2 (n=6), PAX8 (n=3), WT1 (n=6), JAG1 (n=6), CDH1 (n=6), FOXC2 (n=6), HNF1B (n=6), HES1 (n=3), SOX9 (n=4), MAFB (n=5), LHX1 (n=3), GATA3 (n=4), HOXD11 (n=3), PAX2 (n=4), SIX1 (n=5), SIX2 (n=5), POU3F3 (n=3), SLC3A1 (n=3), SLC12A1 (n=4), SLC12A3 (n=4), PODXL (n=3), LRP2 (n=4), CUBN (n=4), UMOD (n=3), AQP1 (n=4), NPHS2 (n=4), CALB1 (n=4), SALL1 (n=3). In situ hybridization and confocal imaging 119 In situ hybridization on frozen sections of mouse and human kidney samples followed previously published procedures 40,42 and (https://www.gudmap.org/Research/Protocols/McMahon.html). Imaging of Immunofluorescent and in situ hybridization signals was performed as described previously 40,42 . Nephron Models To generate nephron models of transcription factor patterns, kidneys were immuno-stained for each transcription factor. Schematized anatomical models were generated for nephrons representing 2D sections through the mid-line of renal vesicles or S-shaped body nephrons. Immunofluorescent stains were considered, and localization patterns binned into visually distinguishable levels of protein intensity. Each antibody stain was detectable within a range, and were binned into 3 categories: absent, detected, detected at a high-level (gray, medium intensity color, intense color), thereby likely reducing actual complexity. Each factor map is underpinned by examining greater than 5 renal vesicle and s-shaped body stages, together with intermediate stages, to produce maps representing the location of specific sets of markers. Sample numbers are indicated elsewhere in the Methods section. To generate intersection-maps of protein localization patterns, semi-transparent maps were superimposed in Illustrator (Adobe) (Fig. 4.4A-B). On merging, larger and smaller domains became apparent, highlighted by the distribution of the various markers. Domains which were intersected multiple times in analysis of adjacent sections were simplified into a single broader domain (eg domain 4). RESULTS Differentiation of nephron progenitor cells into early nephron structures and establishment of transitory cell-lineages In the mouse, Six2+/Cited1+ NPCs give rise to the entire nephron 4,5 . A similarly positioned population of Six2+/Cited1+ cells is present within the developing human kidney and this population 120 displays a similar transcriptional profile in mouse-human comparisons 40,42 . In vitro induction experiments show that a SIX2+ enriched cell-population from the human fetal kidney generates nephron-like cell types 43 . Here, we focus on the process of nephron formation by the nephron progenitor population comparing week 16-17 human fetal kidneys with the mouse kidney at early (embryo day 15.5 [E15.5]) and late (postnatal day 2 [P2]) stages of development. Table 1 summarizes the proteins studied, their functional properties, localization and disease association, and overlap comparing human and mouse datasets. During differentiation, mouse NPCs downregulate expression of transcription factors associated with the NPC-state including Cited1 and Six2; Six2 is itself required for the self-renewal of NPCs 44 . Conversely, early commitment of NPCs is highlighted by the activation of genes encoding other transcriptional regulators such as Pax8, Lef1, and Lhx1, and novel signal components such as the Notch ligand Jag1, Wnt4 and Fgf8 17,22,28,29 . Consistent with canonical Wnt signaling triggering nephrogenesis 6,10 , activation of the canonical Wnt target Lef1 precedes subsequent expression of Pax8, Fgf8 Wnt4, and Lhx1 in the PTA to RV transition 16–18,28 . Thus, Lef1 provides one of the first indicators of initiation of nephrogenesis 22 . SIX2 and CITED1 down-regulation in human NPCs at week 16-17 resembles the E15.5 mouse kidney; however, each protein shows a distinct, human-specific pattern of retention in specific regions of developing nephron intermediates 42 (Supplementary figure 1). CITED1 remains detectable in the proximal PTA, and SIX2 is found in the proximal PTA, RV, and SSB. In the mouse, low Cited1 and Six2 levels were detected in PTAs and the proximal RV, respectively. Lef1, which is only observed in the mouse kidney in conjunction with PTA formation showed a sporadic distribution within human NPCs, close to the PTA transition zone (Fig. 4.1A, B), consistent with in situ hybridization analysis of LEF1 expression (Fig. 4.1C). To examine whether the “earlier” onset of LEF1 production in human NPCs reflected a relative staging disparity, we immunolabelled Lef1 in the P2 mouse kidney (Supplementary figure 2). As described by Rumballe et al., (2011), at P2 the kidney 121 cortex is more densely packed with epithelial structures, fewer NPCs are visible, and structurally recognizable cap mesenchyme populations are infrequent 45 . Commitment to nephron formation is accelerated at P2 relative to E15.5 46 . However, as at early stages, most Lef1 was restricted to forming nephrons. Occasional Six2+/Lef1+ cells were observed in the cap mesenchyme clearly distinct from the more extensive SIX2+/LEF1+ population in human NPCs (Supplementary figure 2). PAX8 was also detected within a similar NPC domain in the human but not the mouse kidney, extending throughout the RV by epithelialization (Fig. 4.1D; Supplementary figure 3A, A’, 3E). Anti- PAX2 and anti-PAX8 antibodies showed distinct patterns of immunoreactivity (Supplementary figure 3E). Together these data suggest a temporal and spatial divergence or change in cellular dynamics associated with NPC induction in the human kidney (see Discussion). Unlike LEF1 and PAX8, WNT4 mRNA and JAG1 were first detected at PTA stages where expression localized to distally located cells (Fig. 4.1E, E’, F, F’), a more restricted region at both PTA and RV stages to the mouse 16 . JAG1 was absent from early PTAs but present within intracellular vesicles in cells of the late PTAs/early RVs that lay closest to the ureteric bud tip, as in the mouse (Fig. 4.1E; Supplementary figure 1; S4.3C’). By the RV stage, JAG1 localized to the cell surface on the lateral cell of distally located cells (Fig. 4.1E; S4.3C’). At this stage of nephrogenesis, CDH1, a homophilic cell adhesion factor with a broad role in epithelial formation 47 , was first evident in the distal RV (Fig. 4.1E; S4.3C’’) as in the mouse 48 . However, JAG1 extended beyond distal CDH1 producing cells to medial regions of the RV. At this stage, low levels of the transcriptional regulatory factor SOX9 were evident in a few distal cells of the human RV, a more limited distribution to the mouse at morphologically equivalent stages (Supplementary figure 1) 49 . The order of appearance for these proteins/genes during induction was: LEF1, followed by PAX8 and WNT4, then JAG1 and LHX1 (data not shown). In summary, LEF1 and PAX8 activation within morphologically distinct human NPCs likely indicate early inductive signaling not visible in the mouse NPC population. However, the activation of 122 WNT4, LHX1, SOX9, CDH1, and JAG1 and the localization of PAX8 and LEF1 in forming nephrons was quite similar between the two species, as were the parallel morphological changes accompanying early stages of nephron induction. Developmental progression from renal vesicles to S-shaped body nephrons Mouse RVs progress through a series of morphogenetic events that remain poorly understood 2 . The ontology for the mouse and human SSB comprises 6 terms/anatomical domains: renal connecting tubule of SSB, distal segment of SSB, medial segment of SSB, proximal segment of SSB, visceral epithelium of SSB, and parietal epithelium of SSB (www.gudmap.org), though where the boundaries of each domain lies is not clear. Further, there is fluidity in gene expression domains with genes expressed in the RV adopting new patterns within the SSB. Several genes have been shown to identify discrete domains at this stage and loss of their activity results in altered patterning of the nephron. Notable genes, with the normal domains and regions altered on loss-of-function in parentheses include: mutations Hnf1b (distal/medial; loss of proximal/medial nephron regions), Sox9 (distal; none reported), Cdh1 (distal/medial; none reported), Lef1 (distal/medial; none reported), Jag1 (medial; loss of proximal/medial nephron regions), Hes1 (medial; none reported), Wt1 (proximal; none reported), Foxc2 (proximal; loss of podocyte identity), and Mafb (proximal; loss of podocyte identity) 25,30,31,33,49–51 . As in the mouse SSB, the connecting and distal segments were demarcated by strong labelling of HNF1B, CDH1, SOX9, and PAX8 (Fig. 4.2A, B, D – PAX8 in Supplementary figure 1), the medial and proximal segments by JAG1 high , DLL1, HES1, LEF1, but also HNF1B (Fig. 4.2A, B, C, E; DLL1 data not shown) and the proximal, parietal, and visceral segments by WT1, MAFB, and FOXC2, and JAG1 low (Fig. 4.2A, B, D). Rather than sharp boundaries of gene expression, the gradual reduction of gene expression at proximal and distal boundaries generated partially overlapping domains of gene expression, and consequently, a greater potential for cell heterogeneity than is recognized by the current ontology. 123 For example, the region between the distal and the medial domains displayed strong LEF1 labelling and lower but overlapping labelling for SOX9 and JAG1. Similarly, Wnt4/WNT4 transiently demarcates a subset of the proximal segment of the SSB that directly contacts the ureteric epithelium, a region sandwiched between the presumptive renal corpuscle lineages and medial segment; Wnt4/WNT4 expression was rapidly lost after the SSB stage (Fig. 4.2F). Though boundary positions may shift along the proximal distal axis; overall, human and mouse nephrons displayed conserved boundaries of gene activity though transitions varied. As examples, human WT1 extends further into the medial segment than mouse Wt1, while human JAG1 shows sharper boundaries than its mouse counterpart (Fig. 4.2B, D). Mapping transcription factors to the developing human nephron reveals additional cellular complexity To better define the domains in the human SSB and relate the molecular organization between the RV and SSB. we performed immunostaining for 14 transcription factors present in the mouse and human RV and SSB (WT1, FOXC2, MAFB, LHX1, LEF1, SOX9, GATA3, HNF1B, HOXD11, PAX2, PAX8, SIX1, SIX2, and POU3F3) and mapped their localization to nephron models extending the current mouse-focused understanding of individual factors to a high-resolution synthesis of the data (Fig. 4.3, 4) and 17,22,27,28,33,35,41,44,49,50,52–54 . Simplified comparative domain maps based on the markers above were compiled for the mouse and human RV (Fig. 4.3A, 4A) and SSB (Fig. 4.3B, 4B). These maps predict additional molecular diversity beyond those defined by current working ontologies (Fig. 4.5C). The human RV model indicated the presence of at least 6 domains (Fig. 4.5A); two distal domains (1-2), a large medial (3) and three proximal (4-6) domains. The SSB model suggested 9 domains (Fig. 4.5A); domains 4 and 6 were intersected by multiple protein domains so additional molecular heterogeneity is expected within these cell populations. The mouse models displayed analogous domains (Fig. 4.5B). To test whether the predicted cellular diversity from these models was reflected 124 by actual molecular diversity, we co-stained human RVs and SSBs for WT1, FOXC2, and MAFB which are predicted to divide the RV into regions 1, 2, 3-5, and 6, and distinguish between domains 1-3, 4, 5, 6, 7, and 8-9 in the SSB (Fig. 4.5D). Consistent with the model, this analysis detected predicted domains on the basis of the presence, absence and levels of these 3 factors (Fig. 4.5E). Further, the transcription factors HOXD11, GATA3, and SOX9, separated the RVs into domains 1, 2-5, and 6 and 1, 2, 2-3, 4, and 5-9 in the SSB (Fig. 4.5G), as predicted (Fig. 4.5F). In summary, there is clearly greater molecular and cellular heterogeneity in the early stages of nephrogenesis than previously documented. Further, the conservation in the observed heterogeneity between the mouse and human suggests a functional relevance to the emerging pattern of the mammalian nephron. Delineating the emergence of mature nephron segment-markers in the early nephron Domain 6 in the SSB closely aligns with the domain of Wnt4/WNT4 expression (Fig. 4.2F). To delineate this precursor/mature-segment relationship we performed Wnt4-CRE-mediated fate- mapping in the mouse kidney. At P2, NPC populations are depleted and remaining Six2-expressing cells are found within epithelializing structures (Fig. 4.6A). Wnt4 is at this point expressed in some PTA stages but predominantly in RVs and SSBs (Fig. 4.6A). Therefore, injection of tamoxifen at P3 into neonatal Wnt4 CreERT2 ;Rosa26 tdTomato mice 4,55 , results in stable activation of td-Tomato in descendants of domain 6. Analysis of kidneys in adult mice at week 8 showed td-Tomato+ cells generated exclusively LTL and Lrp2+ proximal tubule cells in the kidney cortex (Fig. 4.6B, C) 56,57 ; labelled cells were negative for renal corpuscle markers, and for Umod, Slc12a1, and Slc12a3 which demarcate the ascending loop of Henle and the distal convoluted tubule 58–60 . The observation that distinct transcriptional domains exist within the SSB begs the question of when functional proteins mediating physiological actions of mature nephron segments are first detected? Temporally, mature nephron segments first emerge between week 10 and 11 of human development 40 . However, how their emergence reflects patterning within the SSB or later capillary loop stage nephron (CLS) that forms from elongation of the SSB is unclear. To address this question, 125 we examined the distribution of well-characterized proteins that have been used as markers of mature nephron identities in pluripotent stem cell-derived organoid models of kidney development; from proximal to distal: the renal corpuscle and podocyte markers PODXL, NPHS2, WT1 and MAFB; proximal tubule markers SLC3A1, LRP2, CUBN and AQP1; ascending loop of Henle markers SLC12A1 and UMOD; and distal convoluted tubule marker SLC12A3. LRP2, CUBN, PODXL, MAFB, WT1, and NPHS2 were first detected at the SSB stage (Fig. 4.7). SLC3A1 was first detected at low levels in the late SSB, while AQP1, UMOD, and SLC12A1 emerged in CLS nephrons. UMOD and SLC12a3 where first detected after the CLS in more elongated loops of Henle and distal tubules, respectively (Fig. 4.7; Table 1). These data are consistent with the general view of a proximal to distal progression in the local production of key proteins underlying regional nephron functions. However, each of these proteins are present at markedly elevated levels in functional nephrons (compare high and low power fields in Fig. 4.7). DISCUSSION We report a detailed characterization of the anatomical and molecular patterning of the human nephron from induction to S-shaped body formation. The findings complement recent descriptions of human kidney development and comparative studies of the mouse and human nephrogenic niche 40,42 . The data lead to four important findings. First, inductive programs are demonstrably active in NPCs in the human nephrogenic niche. Second, there is significantly greater cellular diversity in developing nephrons with strong conservation between the human and mouse kidney. Third, fate tracing to link emerging patterns with mature structures, demonstrates that a Wnt4+ population localized to the proximal SSB comprises proximal-tubule precursors in the mouse, and likely the human, kidney. Finally, the analysis of segment specific markers of mature nephron cell-types connects patterning with the emerging regional anatomy of the functional mammalian nephron. Early inductive responses initiate in the human cap mesenchyme 126 In the mouse, Lef1 is first detected in the pretubular aggregate and is thought to be a direct response to canonical Wnt/β-catenin signaling from the ureteric bud 6,22 . This is considered a key event in nephron induction, followed by the activation of Wnt target genes Pax8, Wnt4, Lhx1, each essential for nephron formation and epithelialization 16,17,19–21,28 . In the human niche, LEF1 is detected in NPCs nearest to the ureteric tip and in NPCs connecting to developing PTAs and RVs, while in the mouse LEF1 has a later onset in already formed RVs. Thus, human NPCs display overt Wnt-driven commitment to nephrogenesis at an earlier stage the mouse. Further, the human niche appears to form a continuum of LEF1+/PAX8+ NPCs extending to coalescing PTAs and RVs, a population not readily detected in either the E15.5 or P2 mouse kidney. A clear physical separation between NPCs and already committed progeny may not occur until the RV stage and it is only after incorporation into the PTA and RV that WNT4 and LHX1 turn on, as in the E15.5 and P2 mouse kidney. One explanation for the differences here may be the distinct kinetics of mouse and human nephrogenesis. Previous estimates suggest that the transition from PTA to SSB can takes up to 3-8 days in human but less than 24hrs in the mouse 40 . Consequently, a more protracted process in the human kidney could lend increased temporal resolution enabling distinct stages in the nephrogenic program to be more readily distinguished. Interestingly, the temporal order to the NPC induction with LEF1, likely reporting elevated Wnt signaling, followed by PAX8, WNT4, and LHX1 is consistent with genetic studies in the mouse that have placed Pax8 upstream of Wnt4 16 and Wnt4 upstream of Lhx1 10 . Cellular diversity and patterning of the early nephron Current mouse and human kidney anatomical ontologies (www.gudmap.org) propose three terms for the RV and six terms for the SSB. The mapping of 14 transcription factors, chosen for their readily identifiable nuclear organization and direct relevance to patterning events themselves, identified at least six domains in the RV, dividing the RV into three distal and medial domains, and 127 three proximal domains. Domain six corresponded to the region where active NPC recruitment was occurring displaying the highest levels of SIX2 presumably reflecting the recent recruitment from SIX2+ NPCs and the perdurance of SIX2 mRNA and protein in recruited cells. MAFB+ cells first emerged in this RV domain. In the SSB we detected nine domains with additional diversity detected in the distal and medial segments, each comprising three domains. Of note, domain six in SSBs faithfully recapitulated an expression domain of WNT4 in the SSB (Fig. 4.2F). This region of the SSB is in close proximity to the ureteric epithelium (Fig. 4.2D, F) where it would be predicted to receive high levels of collecting duct derived ligands such as WNT9B and LIF 6,15 . Importantly, co-staining with selected proximal (WT1, FOXC2, MAFB) and distal (HOXD11, GATA3, SOX9) protein marker sets validated predictions from the composite models based on the distribution of single factors. The organization predicted here can be further tested through single cell RNA analysis and should serve as a useful template for relational mapping of these datasets and for exploring the in vivo relevance of nephron patterning processes in in vitro kidney organoid models of mouse and human nephrogenesis. Establishing direct evidence to link domains of emerging cell diversity to the distinct anatomy of the mature nephron is challenging especially where co-expression of more than one factor, or levels of factor activity, complicate genetic approaches. However, we were able to show that the SSB-specific Wnt4 domain corresponds with cells fated to give rise to proximal tubule cells. Similar studies will only be possible in the human kidney in organoid models, and these will only be relevant to normal development if normal nephrogenic programs are shown to occur in vitro. Nephron patterning and mature kidney markers Analysis of the onset of detectable levels of several key markers of mature cell-types in the adult nephron suggest a proximal to distal hierarchy in nephron maturation, which is consistent with distal identities forming last during kidney development 40 . Delayed development of distal identities compared to proximal ones may reflect a primary need to generate a proximal filtration device before any other functions are necessary, and a secondary requirement for recovery of low molecular weight 128 compounds, e.g., glucose, sodium; as would be critical to organismal fitness. Mature distal cell-types have not been reported in pluripotent stem-cell derived renal organoids 61–63 also suggestive of a late developmental time for the maturation of these fates or the absence of environmental cues directing their development. MAIN FIGURES AND TABLES Figure 4.1. Nephron progenitor induction in human and mouse nephrogenic niches. (A-F) and (A’- F’) immunofluorescent stains and in situ hybridization on human and mouse kidneys, respectively. Ages and stains as specified on fields. Yellow, red, and cyan dashed lines indicate cap mesenchyme, ureteric bud, and nephrons, respectively. NPC: nephron progenitor cells, UB: ureteric bud, PTA: pretubular aggregate, IPC: interstitial progenitor cells, CSB: comma-shaped body, RV: renal vesicle. Stars in (F, F’) indicate the nephron axes: Green: distal, orange: proximal, magenta start indicates ureteric bud. Scale bars on immunofluorescent data indicate 10 µm. For single-channel views see Supplementary figure S4.1 and S4.3. 129 130 Figure 4.2. Nephron patterning through to the S-shaped body stage in human and mouse kidneys. (A-F) and (A’-F’) immunofluorescent stains and in situ hybridization on human and mouse kidneys respectively. Ages and stains as specified on fields. Stars in (F, F’) indicate the nephron axes: Green: distal, orange: proximal, magenta indicates the ureteric bud. NPC: nephron progenitor cells, UB: ureteric bud, PTA: pretubular aggregate, IPC: interstitial progenitor cells, CSB: comma-shaped body, RV: renal vesicle, SSB: s-shaped body, CLN: capillary loop stage nephron. Scale bars indicate 10 µm. 131 132 Figure 4.3. Transcription factor maps in the human renal vesicle and S-shaped body nephron. (A- B) Single channel immunofluorescent stains with DAPI showing transcription factor localization patterns in renal vesicles and S-shaped body nephrons. Nephron model schematics indicate where transcription factor is present; two-level colour scheme used to indicate strong and weak detection where applicable. Scale bars indicate 10 µm. Proximal (p), medial (m) and distal (d) segments indicated on fields. 133 134 Figure 4.4. Transcription factor maps in the mouse renal vesicle and S-shaped body nephron. (A- B) Single channel immunofluorescent stains with DAPI showing transcription factor localization patterns in renal vesicles and S-shaped body nephrons. Nephron model schematics indicate where transcription factor is present; two-level colour scheme used to indicate strong and weak detection where applicable. Scale bars indicate 10 µm. Proximal (p), medial (m) and distal (d) segments indicated on fields. 135 136 Figure 4.5. Diversity in the human and mouse renal vesicle and S-shaped body nephron. (A-C) Predicted cellular diversity in the human and mouse renal vesicle (RV) and s-shaped body nephron (SSB) and current ontological terms. (D-E) Predicted and tested subdomains identified by detection of WT1, FOXC2, and MAFB in human nephrons. (F-G) Predicted and tested subdomains identified by detection of SOX9, GATA3, and HOXD11 in human nephrons. Dashed magenta line outlines nephrons. Dashed orange line indicates region where transcription factor is detected. 137 138 Figure 4.6. Fate-mapping of S-shaped body nephron Wnt4 expression to adult nephron segment. (A) In situ hybridization on P2 mouse kidneys for Six2 and Wnt4. (B-C) TdTomato+ cells in week 8 mouse kidney post fate-mapping from post-natal day 3. Immunofluorescent stains as stated on fields. TAL: thin ascending limb of the loop of Henle, RC: renal corpuscle, PT: proximal tubule, DT: distal tubule, LOH: Loop of Henle. 139 Figure 4.7. Activation of mature cell-lineage markers in the early development nephron. Immunofluorescent stains for markers of the distal, proximal, Loop of Henle, and renal corpuscle domains of the nephron. Stains as specified on fields. Tissue from wk5-16 human kidney. Scale bar is 10 µm and 50 µm in higher and lower magnification fields, respectively. SSB: S-shaped body nephron, Po: podocytes, UB: ureteric bud, PT: proximal tubule, DT: distal tubule, aLOH: ascending loop of Henle. 140 Expression and localization patterns for antibodies and in situ hybridization performed in study Kidney phenotype/disease Cap mesenchyme Renal vesicle S-shaped body nephron Gene symbol Gene name Protein type Mouse Human Mous e Huma n Mous e Huma n Mouse Human Reference CDH1 Cadherin 1 Cell- adhesion protein - - - - + + + + Vestweber et al., 1985 CITED1 Cbp/p300- interacting transactivator with Glu/Asp-rich carboxy-terminal domain 1 Transcriptio n factor - - + + - - - - Boyle et al., 2007 FOXC2 Forkhead box C2 Transcriptio n factor + + + + + + + + Takemoto et al., 2006 GATA3 Gata binding protein 3 Transcriptio n factor + + - - - - - + Grote et al., 2008 HES1 Hairy/enhancer of spli homolog 1 Transcriptio n factor - - + + + + + + Chen et al., 2005 HNF1B Hnf1 homebox B Transcriptio n factor + + - - + + + + Heliot et al., 2013 HOXD1 1 Homeobox d11 Transcriptio n factor + - + + ? + ? + Wellik et al., 2002 JAG1 Jagged 1 Notch ligand + + - - + + + + Liu et al., 2013 KRT8 Keratin 8 Cell- adhesion protein - - - - - + - + Chen et al., 2005 LEF1 Lymphoid enhancer binding factor 1 Transcriptio n factor - - - + + + + + Mugford et al., 2009 Table 4.1. Summary of protein localization patterns. Proteins detected in figures are summarized and related to data on whether proteins are causative of human or mouse kidney disease/phenotype. 141 LHX1 Lim homeobox gene 1 Transcriptio n factor + - - - + + + + Kobayashi et al., 2005 MAFB v-maf musculoaponeuroti c fibrosarcoma oncogene family, protein B Transcriptio n factor + - - - + + + + Moriguchi et al., 2006 PAX2 Paried box 2 Transcriptio n factor + + + + + + + + Bouchard et al., 2002 PAX8 Paired box 8 Transcriptio n factor + + - - + + + + Bouchard et al., 2002 POU3F3 POU domain, class 3, transcription factor 3 Transcriptio n factor + - - - + + + + Nakai et al., 2003 SIX1 Sine oculis-related homebox 1 Transcriptio n factor + + - + - + - + Xu et al., 2003 SIX2 Sine oculis-related homebox 2 Transcriptio n factor + + + + + + - + Self et al., 2006 SOX9 SRY-box 9 Transcriptio n factor + + - - + + + + Reginensi et a., 2011 WNT4 Wingless-type MMTV integration site family, member 4 Wnt ligand + + - - + + + + Stark et al., 1994 WT1 Wilms' Tumour Protein 1 Transcriptio n factor + + + + + + + + Armstrong et al., 1994 First point of detection for commonly used protein markers of mature tubule segments in the human kidney Gene symbol Gene name Stage first observed Gudmap ontology number LRP2 LDL Receptor Related Protein 2 Proximal segment of s-shaped body 27764 SLC3A1 Solute Carrier Family 3 Member 1 Proximal segment of s-shaped body; early proximal tubule 27764; 27784 SLC12A1 Solute Carrier Family 12 Member 1 Immature loop of Henle ascending limb 35426 SLC12A3 Solute Carrier Family 12 Member 3 Early distal tubule (after Capillary Loop Stage) 28390 CUBN Cubilin Early proximal tubule 27784 142 PODXL Podocalyxin Like Proximal renal vesicle; visceral epithelium of s-shaped body 31549; 27766 WT1 Proximal renal vesicle; visceral epithelium of s-shaped body; proximal segment of s-shaped body 31549; 27766; 27764 NPHS2 Podocin Visceral epithelium of s-shaped body 27766 MAFB Proximal renal vesicle; visceral epithelium of s-shaped body 31549; 27766 UMOD Uromodulin Early distal tubule (after Capillary Loop Stage) 28390 AQP1 Aquaporin 1 Early proximal tubule (after Capillary Loop Stage) 27784 SUPPLEMENTAY FIGURES Figure S4.1. Nephron induction and morphogenesis in human and mouse nephrons. (A-C) Immunofluorescent stains on human and mouse kidneys. Antibodies, features, and stages as indicated on fields. NPC: nephron progenitor cells, UB: ureteric bud, PTA: pretubular aggregate, IPC: interstitial progenitor cells, CSB: comma-shaped body, RV: renal vesicle, SSB: s-shaped body. Scale bars indicate 10 µm. 143 144 Figure S4.2. Nephron induction and morphogenesis during the cessation of nephrogenesis. Immunofluorescent stains on P2 mouse kidneys. Staining as specified on fields. Rare double Lef1+/Six2+ cell in a position indicative of NPC identity marked by cyan arrowhead. NPC: nephron progenitor cells, UB: ureteric bud, CSB: comma-shaped body, RV: renal vesicle. Scale bars indicate 25 µm. 145 Figure S4.3. Nephron induction and morphogenesis in human and mouse nephrons (single- channels). (A-D) Single-channel immunofluorescent stains as shown in Figure 1. Immunofluorescent stains on human and mouse kidneys as shown. (E) Comparison for PAX2 and PAX8 labelling in the nephrogenic niche. Antibodies, features, and stages as indicated on fields. NPC: nephron progenitor cells, UB: ureteric bud, PTA: pretubular aggregate, IPC: interstitial progenitor cells, CSB: comma-shaped body, RV: renal vesicle, SSB: s-shaped body. Scale bars indicate 10 µm. White arrowheads point to structures as indicated. Red arrowhead points to PAX8+/CITED1+ cells not yet incorporated into the nascent nephron. Green arrowheads point to faint JAG1+ stain emerging in PTA prior to CDH1 being present. 146 147 Chapter 5 Progressive Recruitment of Mesenchymal Progenitors Reveals a Time-Dependent Process of Cell Fate Acquisition in Mouse and Human Nephrogenesis One prominent feature that we observed while studying the human kidney was a cellular connection between the cap mesenchyme and the developing nephron. Previously, nephron development was often described as a process happening independent of the contribution from the NPCs. The cellular connection between the NPCs and developing nephron, first observed in the human and later noticed in the mouse kidney, suggested a more dynamic contribution of the NPCs to the developing and polarizing nephrons. This chapter examines the hypothesis that early nephron cell fates are determined dependent on when the induced NPCs cells arrive at the developing nephron. This work has been published on the journal Developmental Cell (PMID: 29870722). It was spearheaded by Nils Lindström, and was co-driven by Guilherme De Sena Brandine and me to integrate computational, live imaging, and cryosection fluorescence imaging methods in the study. Andrew Ransick, Gio Suh, Jinjin Guo, Albert D. Kim, Riana K. Parvez, Seth W. Ruffins, Elisabeth A. Rutledge, Matthew E. Thornton, Brendan Grubbs, and Jill A. McMahon also contributed to material and data collection. Andrew McMahon supervised the conceptualization, experimental design, data collection, data analysis, manuscript editing and reviewing, while Andrew D. Smith advised on experimental design and computational analyses. INTRODUCTION The mammalian nephron comprises at least 14 physiologically distinct functional cell-types (Lee et al., 2015). These are organized within segmental domains with a proximal-distal axis of polarity: proximal cell identities generate key components of a filtering structure, the renal corpuscle, while the most distal cells connect the distal tubule segment to the urine transporting collecting duct system 148 (O’Brien and McMahon, 2014). Genetic, cellular and molecular studies predominantly in the mouse have demonstrated that mesenchymal Six2 + /Cited1 + nephron progenitor cells (NPCs) undergo a reiterative inductive process that generates a pretubular aggregate (PTA) which epithelializes into a renal vesicle (RV) in conjunction with the parallel branching growth of the adjacent collecting duct network. Morphogenetic processes transform the RV through comma- and s-shaped body stages (CSBs and SSBs) to mature nephron structures (reviewed by Desgrange and Cereghini, 2015; McMahon, 2016). Aggregation and epithelialization have largely been viewed as tightly coupled processes with nephron patterning initiating after PTA formation and evident in the RV as distinct proximal and distal cellular domains of gene activity (Georgas et al., 2009; Mugford et al., 2009; O’Brien and McMahon, 2014; Yang et al., 2013). Patterning requires regional Wnt, Bmp, Notch, and Fgf-signaling to specify proximal-distal fates (Cheng et al., 2007; Grieshammer et al., 2005; Lindström et al., 2015) through the actions of several transcription factors including Pou3f3, Lhx1, Irx2, Hnf1b, Foxc2, and Mafb (Heliot et al., 2013; Kobayashi et al., 2005; Moriguchi et al., 2006; Nakai et al., 2003; Reggiani et al., 2007; Takemoto et al., 2006). However, the mechanisms initiating axial polarity in early nephron- forming stages are not understood (O’Brien and McMahon, 2014). We present multiple lines of evidence that RV formation is not a singular event in time. Rather, NPCs are progressively recruited with the time of recruitment predicting proximal-distal cell fate. The findings prompt a reevaluation of nephron patterning pathways in the context of a Time-dependent Cell-fate Acquisition (TCA) model of nephron patterning. METHODS Experimental Model and Subject Details Animal studies 149 Institutional Animal Care and Use Committees (IACUC) at the University of Southern California reviewed and approved all animal work as performed in this study. All work adhered to institutional guidelines. Timed matings were set up to recover embryos at the appropriate age (embryonic day 11.5 to 12.5), sex not known. The Six2GCE strain B6;129-Six2tm3(EGFP/cre/ERT2)Amc/J) was generated as previously described (Kobayashi et al., 2008) by placing a EGFP CreERT2 construct into the Six2 locus. The Rosa26mTmG reporter line (B6.129(Cg)-Gt(ROSA)26Sortm4(ACTB-tdTomato,-EGFP)Luo/J) (Muzumdar et al., 2007), the Cdh1CFP line (B6.129P2(Cg)-Cdh1tm1Cle/J) (Snippert et al., 2010), and the Tg(Hoxb7-Venus*)17Cos/J (Chi et al., 2009) were obtained from JAX and are reporter mouse strains that in cre-dependent and independent manners label cells and structures in the kidney. Heterozygous Six2-GCE animals were crossed with female Rosa26mTmG homozygous females; double heterozygous males were crossed with homozygous Cdh1CFP or tgHoxb7Venus females; mice all adults. Progeny was bred to reporter-strain homozygosity. E11.5-E12.5 kidneys were cultured in media (see Confocal live imaging section below) as previously described with 1µM 4-hydroxy tamoxifen (SIGMA H7904) (Lindström et al., 2015); cultures were performed on Transwell filter inserts. Analysis was performed on three Six2 CE/+ ; Rosa26 mTmG/mTmG ; Cdh1 CFP/CFP and eleven Six2 CE/+ ; Rosa26 mTmG/+ ; tgHoxb7Venus imaged kidneys. Human kidney studies Consented, anonymized, human fetal kidney tissue was obtained from elective terminations following review of the study by Keck School of Medicine of the University of Southern California’s Institutional Review Board. Kidney samples ranging in age from 8 to 18 weeks of gestation were supplied by collaborators at the Children’s Hospital of Los Angeles. Gestational age was determined per guidelines specified by the American College of Obstetricians and Gynecologists using ultrasound, heel to toe, and crown to rump measurements following published Carnegie Stages (O’Rahilly and Müller, 2010; O’Rahilly et al., 1987; Strachan et al., 1997). The sex of the specimen was not reported. Consented samples were received immediately after elective terminations and transported from the 150 Children’s Hospital of Los Angeles on ice at 4°C in 10% fetal bovine serum, 25mM Hepes, high glucose DMEM (SigmaAldrich). Methods details 3D reconstructions of cell-streaming Three dimensional imaging was performed as previously described (Lindström et al., 2018b) by carrying out whole-mount immunofluorescent stains on slices of human kidney cortex. Slices were fixed in 4% formaldehyde in 1x phosphate buffer saline (PBS) on ice for 45 min, washed in 1XPBS, blocked in 1xPBS with 0.1% TritonX100 and 2% SEA Block (ThermoFisher Scientific) for 1 hr, and sequentially incubated in primary and secondary antibodies overnight. Primary and secondary antibodies were diluted in the block solution. To clear tissue slices, the slices were dehydrated in methanol via increasing concentrations 50%, 75%, 100%, diluted in PBS - each for 1hr - and subsequently submerged in a 50:50 benzyl benzoate/benzyl alcohol (BABB):methanol solution, followed by 100% BABB; full details in (Lindström et al., 2018b). Imaging of nascent nephrons was performed on a Leica SP8 using a 40X objective (1.3Oil, HC PL APO CS2). To generate 3D models, nephrons and tips were digitally segmented by hand and visualized in AMIRA 6.4 (FEI Thermo Fisher Scientific). Sixteen nascent nephrons were analyzed at week 13 and 24 nephrons at week 16-17. Confocal live imaging Kidneys were dissected at E11.5-E12.5 and cultured o/n at 37°C on a Transwell filter (Corning) in FluoroBrite DMEM (Life technologies, A18967-01) supplemented with 10% fetal calf serum, 1% Pen/Strep, and 1X Glutamax (Thermofisher). Filter inserts were transferred to 35mm MatTek glass bottom dishes in customized holders and imaged for 24-48 hour periods using a Leica SP8 system using a 25x HC FLUOTAR L 25x/0.95 water immersion objective. The water immersion was maintained through a Leica water cap with a modified water and drainage system allowing for continues flow of water. 151 Immunofluorescent staining and in situ hybridization Immunofluorescent detection of proteins and in situ hybridization detection of mRNAs was performed as previously described (Lindström et al., 2018b). In brief, kidneys were fixed in 4% PFA overnight, immersed in 30% sucrose for 24 hrs, embedded in Optimal Cutting Temperature solution, and cryo-sectioned into 10 µm sections. For antibody stains, slides were washed in 1xPBS, blocked in 1XPBS with 0.25% TritonX100 and 1.5% SEA Block for 30min, and then sequentially incubated in primary and secondary antibodies at 4°C overnight; full details of protocol as described (Lindström et al., 2018b). Primary antibodies and dilutions as follows: ALDH1A1 (Abcam, ab52492, 1:300), HES1 (Cell Signaling, 11988, 1:300), CDH6 (R&D, AF2715, 1:1000), HNF1B (Santa Cruz, sc-22840, 1:300), MAFB (R&D, MAB3810, 1:500), CLDN5 (Novus Biologicals, NB120-15107, 1:100) ERBB4 (R&D, MAB1131, 1:300), MECOM (R&D, MAB75061, 1:300), SIX2 (Sigma Aldrich, SAB1401533, 1:500), SIX2 (MyBioSource, MBS610128; 1:1000), CITED1 (Abcam, ab55467; 1:300, KRT8 (DSHB, troma-1; 1:50), CDH1 (BD Transduction Laboratories, 610182; 1:300), PAPPA2 (R&D, AF1668; 1:300). Secondary antibodies were purchased from Molecular Probes AlexaFluor 488, 555, 594, and 647. Nuclei were labelled with 1 µg/ml Hoechst 33342 (Molecular Probes) in PBS for 5 min. Sections were mounted in ProLong Gold Antifade Reagent (Life technologies) and imaged at 63X. Single-cell RNA-seq data – isolation of cells and sequencing Single-cell transcriptomes were obtained as previously described (Lindström et al., 2018c) from two replicate week 17 kidneys by digestion of the nephrogenic zone. In brief, whole kidneys were placed in collagenase A/ pancreatin enzyme mix (Brown et al., 2015) and placed on a nutator to release cells from the nephrogenic niche. Live and intact cells were collected by FACS, positively selecting for DRAQ5+ cells (ThermoFisher Scientific) and excluding DAPI+ (ThermoFisher Scientific) cells. 8000 cells were input into the 10X Chromium system and processed for single-cell library construction as per 10x Genomics instructions and as we describe previously (Lindström et al., 2018c). The data is available at GEO accession number GSE112570. Quality control, mapping (to 152 GRCh37.p13) and count table assembly of the library was performed using the CellRanger pipeline version 2.1 (as consistent with 10x Genomics guidelines) and as described in our previous work (Lindström et al., 2018c). Quantification and Statistical Analysis Quantification of protein intensity during gradual recruitment Fiji was used to quantify SIX1, CITED1, JAG1, PAX8, and DAPI intensity profiles in 2D cryo- sections (as shown in Fig. 5.1 and S5.1) along the proximal-to-distal axis of the nephron. Images were captured at equivalent settings per range, in 8-bit, and a 9 µm segmented line (comparable to nuclei size) was fitted along the thickest part of the lateral sides of the nephron (as indicated on Fig. 5.1 and S5.1). The plot profile function was used to measure the average intensity across the line along its length. The SIX1 and CITED1 signals were presented as percentages of the signal detected in adjacent NPC populations where the signal was the highest, while JAG1 and PAX8 were presented as raw 8-bit signals. Computational isolation of nephrogenic lineage The initial step of our analysis required isolating nephrogenic lineage cells from other cells in the sample (e.g., interstitial lineage and blood cells). For consistency with previous analysis we applied the same procedure as outlined in (Lindström et al., 2018c); cells were selected based on expression of nephrogenic lineage markers and absence of markers indicate interstitial, ureteric, vascular, or immune cell lineages. We initially calculated 3 quality control metrics for each cell: (1) the number of genes with one or more mapped reads, (2) the percentage of reads mapped to genes annotated as mitochondrial, (3) the Good-Turing estimate of cell saturation (Good, 1953). Based on visual inspection of the histograms of these 3 metrics, we filtered out cells expressing fewer than 1,000 genes, as well as cells mapping more than 5% of their reads to mitochondrial genes and cells whose Good-Turing estimate was smaller than 0.7. The remaining 7,343 cells were clustered using the Seurat 153 R package. We ran Principal Component Analysis on the dataset and used 39 PCs based on the JackStraw test (p < 0.05) and clustered the cells using the Seurat FindClusters function with 39 PCs and default remaining parameters. We found 16 resulting clusters, displayed in a t-SNE plot in Supplementary Figure S5.4A. Based on the differential expression test (FindAllMarkers function, bimod test) and the cluster hierarchy (BuildClusterTree function), We inferred that 5 of the clusters (11, 13, 14, 15 and 16), totalizing 3,367 cells, belonged to the nephrogenic lineage, and were selected for secondary analysis. Identifying variable genes and dimensionality reduction Raw read counts from the nephrogenic lineage cells were analyzed using the Seurat R package (Satija et al., 2015). Standard Seurat log-normalization, variable gene selection and Principal Component Analysis (PCA) were performed using the LogNormalize, FindVariableGenes, ScaleData and RunPCA functions, respectively, with the same parameters used in the previous step. This yielded 1,168 genes that are variable across cells and 19 statistically significant principal components (cutoff of p=0.05, JackStraw test). Identifying distinct cell types within the nephrogenic lineage The 3,367 nephrogenic lineage cells were clustered using the Gaussian Mixture Model (GMM) based on the 19-dimensional PC space (see above), as implemented in the mclust package (Scrucca et al., 2016). GMM is particularly well-suited for the context where cells transition into states through continuous differentiation, as it allows for probabilistic assignment of cells to clusters and the estimated probability distribution associated with each cluster. We determined the number of clusters using Bayesian Information Criterion (BIC) (Schwarz, 1978), evaluating BIC for 1 to 50 clusters, and retaining 22 clusters, for which BIC was maximized. These 22 clusters defined 22 distinct cell types within the nephrogenic lineage. Measuring similarity between identified cell types 154 The estimated means and covariances of each cluster were used as the basis for assessing relationships between cell types. We chose to apply the Bhattacharyya distance metric (BD) (Bhattacharyya, 1943) to quantify the dissimilarity between cluster distributions as given by their estimated mean and covariance matrices. This metric approximates the amount of overlap between the density functions for two distributions. Because BD accounts for the distribution variances, it distinguishes the similarities between two pairs of distributions that have equal centroid distances but overlap in different ways in high dimension, and is an accurate estimate of the classification error between points generated from pairs of distributions (Choi and Lee, 2003). The BD between clusters was used as input to build the cluster hierarchy with complete linkage (Fig. 5.2C). To identify pairs of phenotypes that were most likely related through developmental transitions, we calculated the minimum spanning tree using BD as edge values between clusters (Supplementary figure S5.3A). Pseudotemporal reconstruction of lineages We used the Monocle2 algorithm (Qiu et al., 2017) to reconstruct the differentiation pathways across the 3,367 cells. We used the 1,168 aforementioned variable genes with the Seurat-normalized expression values as input and used the reduceDimension function to run the DDRTree algorithm and estimate the ordering of cells along a trajectory. Both the cluster identities and the known marker genes for different phenotypes were used to infer the start of the trajectory (Fig. 5.2D – top). We selected cells that were projected onto specific lineages based on the branches (cell “states”, as assigned by the orderCells function in Monocle) they were projected onto. Initially, we selected only cells from the branch that did not contain the cycling lineage (Fig. 5.2D – bottom). Subsequently, we reran the Monocle algorithm by manually selecting cells assigned to the branch that contained most cells from nephron progenitor clusters and each other individual branch until only a single trajectory was identified. The branches selected in each iterative step are shown in Supplementary figure S5.3C. Each trajectory was recalculated using the reduceDimension and orderCells functions with default 155 parameters. The unbranched paths were analyzed to identify genes that vary along pseudotime using Monocle’s generalized additive model (Trapnell et al., 2014) implemented in the differentialGeneTest function. Clustering genes into correlated modules We used Weighted Gene Correlation Network Analysis (WGCNA) (Zhang and Horvath, 2005) to group differentially expressed genes into correlated modules. We constructed a signed network, wherein every pair of genes is connected by a power of their correlation. We used the pickSoftThreshold method in WGCNA to choose the correlation power estimate ( 3 β = ). We used the blockwiseModules function in WGCNA to obtain the modules shown in (Fig. 5.3A), which resulted in disjoint sets of correlated genes. Single cells were scored for each module by their eigengene expression (Fig. 5.3B – displayed as feature plot heatmap in main figure and boxplots in Supplementary figure S5.4). For a fixed module Mj, the first PC using only the genes in Mj was calculated, and each single cell i was projected into this component, yielding a set of eigengene values mij as cell i’s coordinate in module j’s first PC. The larger the value of mij, the higher the expression of the module genes for cell i. For each module, a smooth spline was fitted for the pseudotime value inferred from the main trajectory and the module eigengene (function smooth.spline in R with smoothing parameter equal to 1) – (Fig. 5.3D-E). Gene-list GO-term ontology queries Differentially expressed genes or gene module lists were queried by PANTHER (Mi et al., 2013) identifying Biological Processes. Data and Software availability The single cell RNA sequencing data is available at GEO accession number GSE112570. RESULTS 156 Nephron progenitors stream from the niche into forming nephrons over time. We recently reported that human SIX2 + NPCs make a continuous connection with the epithelializing renal vesicle (Lindström et al., 2018a; Fig. 5.1A, B; S5.1A-C; week 8, 15, 16 , and 18). Close scrutiny of the more rapidly developing mouse kidney identified similar structures, albeit infrequently (Lindström et al., 2018a). Thus, the greater temporal resolution of the human nephrogenic program highlights a conserved mode of progenitor recruitment that could significantly impact nephron forming processes (Lindström et al., 2018a, 2018b). In the human kidney, streaming NPCs connecting to PTAs and RVs upregulate LEF1 and PAX8, molecular readouts of NPC induction (Lindström et al., 2018a). Committed NPCs within the stream are primed to incorporate into nascent nephron structures over what is likely an extensive period of time. To examine this process, we performed two (Fig. 5.1B, C, S5.1A-D; week 8, 15, 16, 18) and three-dimensional (3D) (Fig. 5.1D, Movie 5.1; week 13 and 16) imaging of the developing human kidney. Cell-streaming was persistent from PTA to late RV stages. Expression of NPC markers SIX1 and CITED1 decreased in a proximal-to-distal direction suggesting gradual decay over time from the SIX1/CITED1 producing NPCs (Fig. 5.1C; S5.1D). SIX2 + NPCs connected directly to JAG1 + PTAs (Fig. 5.1C: field1, 1D, Movie 5.1). Interestingly, the cellular connection was structured into two layers suggesting a pre-epithelial segregation of NPC populations within the nephrogenic niche (Fig. 5.1C; S5.1A, Movie 5.1). By the RV stage, the interconnection progressively reduced and eventually exclusively linked to the proximal end of the forming RV (farthest from the ureteric epithelium (Fig. 5.1C: fields2-4; S5.1D: fields2-4)) adjacent to early forming MAFB + podocyte precursors (Fig. 5.1D; S1B; Movie 5.1). This organization was readily observed in human fetal kidney samples from weeks 8 to 18 reflecting a general feature of the nephrogenic program (N > 30; Fig. S5.1C). Nephron formation can be visualized in real-time using mouse kidney organ culture models. To monitor NPCs and their derivatives, we sporadically labelled NPCs with myristoylated-GFP (mGFP; Six2 CreERT2 and Rosa26 mTmG strains; Kobayashi et al., 2008 and Muzumdar et al., 2007, respectively), 157 visualizing cells in the subjacent branching ureteric epithelium with either CFP or venus fluorescent proteins (Cdh1 CFP and tgHoxb7-Venus; Snippert et al., 2010 and Chi et al., 2009, respectively; Fig 5.1F- G). Cdh1 CFP and tgHoxb7-Venus also weakly labelled the distal epithelializing nephron (Fig. 5.1G; S1E- G; E11.5 and E15.5). Labelled cells were tracked for 24 to 48-hours to monitor their recruitment into the nephron anlagen. Strikingly, NPCs initiating PTA formation were positioned directly adjacent to the ureteric epithelium under the branch tip where they underwent a mesenchymal-to-epithelial transition generating polarized Cdh1 CFP+ or tgHoxb7-Venus + cells (Fig. 5.1F-G; S5.1F-G; Movies 2-3; E11.5-E12.5 kidneys). NPCs that arrived later, once a PTA or RV was established, incorporated into the proximal end of the forming nephron precursor (Movie 5.2-3, Fig. 5.1G). To determine how the positioning of cells related to distinct cellular identities at the RV stage, we performed immunofluorescent whole-mount analysis following time-lapse imaging to examine Wt1 (a proximally-restricted transcriptional determinant) and Jag1 (a distal PTA and medial RV-restricted Notch-ligand) activity in mGFP + cells. NPCs incorporated early into forming PTAs exhibited a tgHoxb7- Venus + /Jag1 low /Wt1 - distal identity (Fig. 5.1G-right). The last recruited NPCs displayed a tgHoxb7- Venus - /Jag1 - /Wt1 high proximal-identity and an epithelial morphology characteristic of proximal-most podocyte/parietal cell fates. Thus, NPCs adopted distinct predictable proximal-distal cell fates depending on the time of their recruitment. Interestingly, distal cells also accumulate a weak endogenous fluorescent signal that may reflect RNA or protein transfer from the adjacent ureteric epithelium. Single-cell analyses of the human nephron lineage predicts developmental progression of segment-specific fates. To explore regional patterning during human nephrogenesis, we segregated nephron forming lineages in single-cell transcriptomic data generated from nephron forming regions of two ~17 week human kidneys (Fig. S5.2A, replicates merged) as previously described (Lindström et al., 2018c). This yielded 3367 cells clustering into cell groups consisting of NPCs (TMEM100 + , WASF3 + , MEOX1 + ), NPCs 158 primed for differentiation (HEY1 + , LYPD1 + ), induced/differentiating cells (HES1 + , LHX1 + , PAX8 + ), podocyte precursors and podocytes (MAFB + / PTPRO + ), proximal precursors (CDH6 + , JAG1 + ), distal precursors (MAL + , SOX9 + ), and maturing cell types of the loop of Henle (LOH: SLC12A1 + ), and proximal (SLC3A1 + ) and distal (ALDH1A1 + , GATA3 + ) tubules (Fig. 5.2A-C; Table S1A). In situ hybridization (SISH) for known marker genes confirmed the clusters contained a mixture of early and late precursors for each fate (Fig. S5.2D; week 15-16). The inclusion of MEOX1 + , MAFB + , SLC12A1 + and SLC3A1 + , and GATA3 + cells suggested the selected cells comprise primarily of NPC, PTA, RV, and SSB cells, with only rare cells from Capillary Loop Stage nephrons consistent with the cortical isolation procedure (Fig. 5.2A-C; S5.2D). Hierarchical clustering suggested a close similarity between podocyte precursors (clusters 20 and 21) and NPCs (clusters 2-5), and a more distant relationship between NPCs and tubular precursors (clusters 14-16, 18) (Fig. 5.3C). To explore the developmental relationships between these cellular states we computed the pairwise Bhattacharyya distances between the estimated distributions for corresponding clusters (Bhattacharyya, 1943). These distances reveal a close similarity between podocyte precursors (clusters 20 and 21) and NPCs (clusters 2-5), and a more distant relationship between NPCs and tubular precursors (clusters 14-16, 18) (Fig. 5.3C). The minimum spanning tree based on these pairwise distances suggests podocytes form via a distinct developmental trajectory compared to the proximal and distal tubular nephron fates (Fig. S5.3A; Table S1B). Pseudotime temporal analyses of the nephrogenic lineage were performed with Monocle 2 to predict the single-cell level differentiation trajectories resulting in proximal-distal positional identities (Qiu et al., 2017; Trapnell et al., 2014). Through reiterative pseudo-temporal analyses, NPCs were again found to generate distinct trajectories to podocytes and to proximal/distal tubule precursor fates (Fig. 5.2D). In pseudotime, NPC clusters were ordered closer to podocyte precursor than distal and proximal precursor (Fig. S5.3B). Further pseudo-temporal analyses divided precursor fates into 3 paths corresponding to: path2: NPCs to podocyte fate, path5: NPC to proximal precursors, path6: NPC to medial, distal, and loop of Henle precursors (Fig. S5.3C). Gene expression profiles were identified that 159 predicted specific cell-types identifiable with by known markers (Fig. 5.2E). Representative genes from each group were selected and their regionally-restricted expression along the proximal-distal axis confirmed, validating the modeling of differentiation trajectories (Fig. 5.2F; S5.3C; week 15-17). The pseudotime differentiation trajectories, along with direct analysis of inter-cluster relationships via distributional distances, are consistent with podocyte fates segregating from the NPC population through a different trajectory than that adopted by cells forming tubular epithelial nephron components. Gene networks define developing cell identities along a differentiation time line. To determine if gene-networks linked to cellular identities could be identified directly from their correlation within the single-cells in this dataset, we performed Weighted Gene Correlation Network Analyses (WGCNAs; Langfelder and Horvath, 2008) on the single-cell RNA-seq data. Distinct gene- modules/gene-sets emerged from this approach (M1-M26; Fig. 5.3A; Table S1C). Thirteen were recognizable by marker genes validated in human kidney analyzes (Lindström et al., 2018a, 2018b, 2018c) and seven of these were enriched for biological process GO-terms linked to the kidney (Fig. 5.3A; Table S1D). The gene-sets correlated closely to cells (Fig. 5.3B), and specific clusters (Fig. S5.4), suggesting they were linked to known cellular identities. The gene sets identified differentiating cells encompassing a range of maturing signatures (M1-M5, M7-M8, M11), as well as mature differentiated signatures of LOH and proximal cell-fates (M9-M10) (Fig. 5.3A,B; S5.4). To validate the correlation between gene-sets and specific cell-identities we compared genes with known expression patterns in the mouse kidney (TCF21, NPHS2, ERBB4, MECOM, EMX2, and POU3F3), and uncharacterized genes (CLDN5, OLFM3, ASS1, KDM2B, PAPPA2). Each gene’s expression followed the predicted cell fate assigned to the module; as examples, CLDN5, OLMF3, TCF21 and NPHS2 were expressed within podocytes (M6) though CLDN5 and OLMF3 specifically demarcated developing podocytes from late RV stage to late SSB stage, while TCF21 and NPHS2 were upregulated in maturing podocytes (Fig. 5.3C; S5.2E). Similarly, ADAMTS1, ASS1, PAPPA2, ERBB4, 160 MECOM, KDM2B, EMX2, and POU3F3 were expressed in the segments predicted by network and tSNE analyses (Fig. 5.3A-C; S5.2E; week 15-17). To determine if gene-sets could be linked to pseudo-temporal differentiation-trajectories, we examined the relationship between WGCNA gene-sets and the pseudotime path of the nephrogenic lineage. The NPC gene set (M1) displayed a strong correlation to cells early in the projected differentiation trajectory while proximal, medial/LOH, and distal identity modules peaked later in pseudotime (Fig. 5.3D-E). Expression of the NPC gene-set of the NPC cluster decreased as induction and differentiation modules were activated along pseudotime (Fig. 5.3D) and as in earlier analyses, genes associated with the formation of podocytes were predicted to be activated in cells closer to a NPC state than genes associated with proximal and distal tubular nephron fates (Fig. 5.1-2; Fig. 5.3E). These data combined are consistent with NPCs differentiating directly into podocytes at a late-stage of a protracted program of NPC commitment to the nephron-forming RV. Novel marker genes for nephron segment fates emerge in positions consistent with gradual recruitment of nephron progenitors over time. Our data suggest a temporal and spatial order to the emergence of regional domains in the forming nephron. By the SSB stage, distinct proximal-distal regions are highlighted by markers predicted from transcriptomic analyses (Fig. 5.2-3): distal (SOX9, KRT8, and EMX2); distal/medial (MECOM and ERBB4), medial (JAG1); proximal (CDH6), and podocytes (MAFB and CLDN5) (Fig. 5.4A; week 15-16). To determine where and when distal, medial, and proximal domains form, we identified the first appearance of SOX9, JAG1, and MAFB in the PTA-to-RV transition (Fig. 5.4B). As anchor points in this analysis, position 1 demarcates the first recruited cells positioned under the ureteric bud contacting the ureteric epithelium while position 2 demarcates the most recently recruited from the stream of NPCs that connects to the NPC niche. In the PTA, low levels of JAG1 were detected at position 1. JAG1 levels were elevated in cells in the same position by early RV stages and by mid-RV stages low level SOX9 activity was also evident 161 in this cell population. At this time, weak MAFB + cells first appeared at position 2. Continued RV development was accompanied by consolidation and distal-medial segregation of positional markers: SOX9 was further upregulated in cells at position 1 while JAG1 expanded proximally. By the late RV stage, distinct distal SOX9 high /JAG1 low and medial SOX9 - /JAG1 high domains were evident while MABF + podocyte precursors were located just above the connecting streaming NPCs consistent with the 3D reconstruction in Fig. 5.1D. Though there are no unique markers to distinguish parietal epithelium precursors of the renal corpuscle, the last recruited cells beneath the MAFB+ population is likely to correspond to the parietal lineage. Collectively, these data support a model of progressive establishment of cellular identities along the proximal-distal axis of the nephron anlagen. DISCUSSION Our data identifies a dynamic cellular process that provides a mechanistic framework for how positional identities are initiated in formation of the mammalian nephron. The timing of NPC recruitment dictates the spatial positioning of each cell and the subsequent fate of cells along the proximal-distal axis of the nephron (Fig. 5.4C). This raises the question of how time of recruitment and position can regulate cell fate outcomes? Localized Wn9b secreted by the ureteric epithelium has been proposed to initiate proximal- distal axial asymmetry in the nephron (Carroll et al., 2005; Lindström et al., 2015; Schneider et al., 2015). In a Time-dependent Cell-fate Acquisition (TCA) process, NPCs would likely be subject to different concentrations of Wnt9b/WNT9B for varying periods of time with early recruits receiving a higher and longer dose. Other nephron-intrinsic signaling networks, composed of Bmp and Fgf, also play a role in conjunction with Wnt signaling to regulate distal nephron development (Grieshammer et al., 2005; Lindström et al., 2015) while proximal cell fate specification requires Notch signaling (Cheng et al., 2007) through the Notch ligand Jag1 (Liu et al., 2013). Our analyzes of how distal-to-proximal identities emerge during nephrogenesis raises the possibility that distal fates initially form with a medial JAG1 + identity but over time distal cells downregulate JAG1 and upregulate SOX9, with medial 162 identity shifting proximally. Integration of duration and concentration of signaling has been demonstrated in a diversity of patterning processes (Sagner and Briscoe, 2017). Delineating cell-cell interactions through deeper single-cell RNA-seq analysis with greater gene resolution and live imaging of mutant mouse models will shed light on how these cellular signaling events incorporate into the TCA model. Recently, several groups have reported the generation of nephron-like structures with proximal-distal polarity from directed differentiation of pluripotent stem cells (Morizane et al., 2015; Taguchi et al., 2014; Takasato et al., 2015). However, no evidence of a normal nephrogenic niche organization has been presented for these models and the identities of emerging cell-types remain to be clarified. In the light of the data here, in vitro nephrogenic programs may not fully recapitulate the diversity of cell states observed in the normal kidney. Distal cell fates that normally develop in close association with the ureteric epithelium are predicted to be particularly susceptible to a disruption of normal nephrogenic processes. MAIN FIGURES AND TABLES 163 Figure 5.1 Three dimensional images and single-cell RNA-seq analyses show nephron progenitor cells form a continuum from niche to nascent nephron. (A) Schematic of nephrogenesis from NPC to PTA, RV, and SSB. Colors denote indicated cell fates. Cells connecting NPCs and nascent nephron indicated with ‘*’. (B) Immunofluorescent stain of structures as depicted in (A); cellular connection indicated by arrowheads. (C) Immunofluorescent staining to show a developmental progression from PTA to SSB coupled to changes in the levels of SIX1 and JAG1. Dashed yellow lines indicates where intensity measurements were made and corresponds to x-axis for graph. (D-E) 3D reconstruction of cell-connections (arrowheads) from NPCs to PTA/RV – see also Movie 1. JAG1 and MAFB shown as heatmap signals (green, high; blue, low). (F) Time-lapse of NPCs forming nephrons in the mouse kidney. Culture time as indicated. Four cells marked by numbers 1-4 per nephron. These show the order of inclusion; see also Movies 2-3). (G) Time-lapse and immunofluorescent stains of nephrons and migrating mGFP + cells; arrowheads indicate mGFP + cells incorporating into nephron. Genetic strains, fluorescent proteins and immunostains as indicated. UB: ureteric bud, PTA: pretubular aggregate, RV: renal vesicle, SSB: s-shaped body nephron, D: distal, M: Medial, P: Proximal, CNT: connecting tubule, LOHa: loop of Henle anlagen, Pt: proximal tubule, Pe: parietal epithelium, Po: podocytes. See also Supplementary figure S5.1 and Movies 5.1-5.3. 164 165 Figure 5.2 Single-cell RNA-seq analyses of nephrogenic trajectories show differences in the order of segment-fates acquisition. (A) Unbiased clustering of nephron lineage cells analyzed by single-cell RNA-seq displayed in tSNE plot (B) Gene expression plots for marker genes; cluster numbers as indicated. (C) Cluster hierarchy indicating cluster similarities and representative differentially expressed genes, dendrogram axis CDD: Cluster Distribution Distance. (D) Pseudotime analysis of nephrogenic lineage (the full step-wise analysis used to break trajectories into single paths is shown in S3C). Proliferating cells branch due to collective cell- cycling signature and the first subsequent split is between tubular proximal/distal precursors and the podocytes. (E) Heatmaps of selected genes’ whose expression changes along predicted pseudotime trajectories and gene expression plots. Differentiation trajectories to podocytes (Path 2), proximal fates (Path 5), and medial, LOH, and distal precursors (Path 6) are shown; path numbers are as indicated in Fig.S3C. (F) Immunofluorescent and in situ hybridization detection of indicated protein or mRNA transcripts for genes with changing expression profiles along pseudotime trajectories. Antibody in red, DAPI in gray, mRNA-probe in blue. NPC: nephron progenitor cell, LOH: Loop of Henle, UB: ureteric bud, CNT: connecting tubule, PTA: pretubular aggregate, RV: renal vesicle, Prolif: proliferating, Prim: primed for differentiation, Diff: differentiating, D: distal segment, M: Medial segment, L: loop of Henle analagen, Pt: Proximal tubule, Pe: Parietal epithelium, Po: Podocyte. Segmented lines in (F) show SSB axis, green segmented line indicates domain with strong protein localization or gene expression. See also Supplementary figures S5.2 and S5.3. 166 167 Figure 5.3 Gene correlation networks demark nephron segment fates along temporal trajectories. (A) Gene modules with representative genes highlighted, validated genes in bold, and GO-term analyses. (B) Eigengene expression across single cells. (C) Genes and proteins validated by in situ hybridization and immunofluorescent stains. Dashed line indicates axis of RV or SSB. (D-E) Module-specific smooth spline fitting of the relationship between pseudotime values inferred from Monocle2 as shown in Figure 5.2D: Path1 and eigengene expression in each single-cell. Pseudotime on the x-axis and eigengene expression on the y-axis. NPC: nephron progenitor cell, RV: renal vesicle, SSB: S-shaped body nephron, LOH: loop of Henle anlagen, CLN: Capillary loop stage nephron, Diff: differentiated. See also Supplementary figure S5.4. 168 169 Figure 5.4 Positional identities in the nephron are specified by gradual recruitment of progenitor cells. (A) Immunofluorescent analysis of nephron-segment identity markers in (A) SSBs where fates are demarked as follows: D: distal tubule, L: loop of Henle anlagen, M: medial segment, Pt: proximal tubule, Pe: parietal epithelium, Po: podocytes. (B) emerging proximal-distal polarities at 2 positions (1 and 2) during PTA-RV-CSB stages. Scale bars 10 μm. Immunofluorescent stains as indicated. Nephron development stage indicated above fields in B. (C) Top: Schematic model for progressive recruitment of NPCs over time and sequential cell fate acquisition. Bottom: Specification of cell-fates along cumulative time as indicated by pseudotime. PTA: pretubular aggregate, RV: renal vesicle, SSB: S-shaped body nephron, UB: ureteric bud, NPC: nephron progenitor, LOH: loop of Henle anlage, RC: renal corpuscle precursor. 170 SUPPLEMENTAY FIGURES 171 Figure S5.1. Cellular connection from NPCs to nephron is prevalent during human kidney organogenesis – as relating to Figure 5.1. (A-B) Immunofluorescent detection of whole nephrogenic niches showing single optical sections. Arrowheads mark the cellular connection. Dashed and white magenta lines indicate UB and nascent nephron, respectively. (C) Cellular connection in week 8 human kidneys. (D) Immunofluorescent stain (top) showing developmental progression from PTA to SSB and quantification (bottom) of CITED1 and PAX8 signals. Dashed yellow lines indicates where intensity measurements were made and corresponds to x-axis for graph. (E) Live Cdh1-CFP protein localized in distal RVs and SSBs on a membrane-Tomato background. (F-G) Immunofluorescent detection of distal (SOX9, EMX2) and proximal (MAFB, WT1) markers on sectioned in vivo tgHoxb7-Venus E15.5 kidney sections. NPC: nephron progenitor cell, RV: renal vesicle, PTA: pretubular aggregate, SSB: s-shaped nephron. UB: ureteric bud, D: distal, P: proximal. 172 173 Figure S5.2. Single-cell RNA-seq analysis of week 17 human nephrogenic niche and SISH validation for single-cell RNA-seq data – as relating to Figure 2. (A) Unbiased clustering analysis of cells isolated from two human week 17 nephrogenic niches merged. (B) Cluster identities and identification and selection of the nephrogenic lineage (dashed line) using nephron-lineage markers e.g., as shown in (C). (D) In situ hybridization for genes from selected clusters and analyses in Fig.3. (E) In situ hybridization for whole kidneys as used for validation in Figure 5.2 and 5.3. NPC: nephron progenitor cell, PTA: Pretubular aggregate, RV: renal vesicle, SSB: S-shaped body nephron, UB: ureteric bud, CLN: Capillary loop nephron; CNT: Connecting tubule, PT: Proximal tubule. 174 175 Figure S5.3. Single-cell analyses exploring cluster and single-cell level relationships – as relating to Figure 5.2. (A) Minimum spanning tree derived from pairwise Bhattacharyya distances between cluster distribution estimates. (B) Distribution of pseudotime values for clusters 1-21, defined as the distance of each single cell to the trajectory start along the learned manifold. (C) Reiterative pseudotime analyses following paths between distinct cell states. Path numbers as used in Figure 5.2D. NPC: nephron progenitor cell. 176 177 MOVIE LEGENDS Movie 5.1. Cell-connection between NPC population and forming nephron as relating to Fig. 1D-E. 3D rendering of human nephrons forming with prominent cellular connections bridging the NPC populations and the nephrons. Stains, stages, and structures are indicated in the movie. PTA: pretubular aggregate, RV: renal vesicle. Figure S5.4. Single-cell analyses exploring cluster relationships to modules – as relating to Figure 5.3. Eigengene expression across clusters; with y-axis indicating eigengene and x-axis cluster number. NPC: Nephron progenitor cells. 178 Movie 5.2. Gradual recruitment and specification of cell-fates visualized by confocal time-lapse imaging of Six2 CreERT2 ; Rosa26 mTmG ; Cdh1 CFP kidney cultures as relating to Fig.1F. Movie 5.3. Gradual recruitment and specification of cell-fates visualized by confocal time-lapse imaging of Six2 CreERT2 ; Rosa26 mTmG ; tgHoxb7-Venus kidney cultures as relating to Fig. 1G. Two nephrons shown with late/proximal recruitment, or early/distal recruitment. SUPPLEMENTAY TABLES Table 5.1A-D Gene expression and network analyses from single-cell RNA-seq of week 17 human kidney as relating to Fig.2-3. Tab 1 (A). Differentially expressed genes relating to Figure 2A-C. Tab 2 (B) Bhattacharyya distance matrix relating to Figure 2C; S2A. Tab 3 (C) Modules, relating to Figure 3; S4. Tab 4 (D) GO-Term analyses from single-cell RNA-seq analyses relating to Figure 3A. 179 Chapter 6 In vivo Development Trajectories of Human Podocyte Inform in vitro Differentiation of Pluripotent Stem Cell-Derived Podocytes This chapter has been published on the Developmental Cell journal (PMID: 31265809). I led the study, and data collection and manuscript preparation were achieved with the contribution from Nils Lindström, Andrew Ransick, Guilherme De Sena Brandine, Qiuyu Guo, Albert Kim, Balint Der, Janos Peti-Peterdi, Andrew D. Smith, Matthew Thornton, Brendan Grubbs, and Jill A. McMahon. Andrew McMahon supervised and advised me in the conceptualization, methodology, data analysis, funding acquisition, manuscript review and editing. INTRODUCTION The functional unit of the kidney, the nephron, is made up of more than 14 distinct cell types (Lee et al., 2015). The most proximal component, the renal corpuscle, contains the glomerular filtration apparatus with the vascular endothelium ensheathed by podocytes in a three-dimensional network supported by mesangial myofibroblasts, encased by an outer capsule of parietal epithelium (McMahon, 2016). Within the renal corpuscle, podocytes extend foot processes wrapping the glomerular vasculature thus forming an interface for blood filtration. Podocytes are highly susceptible to damage during kidney injury, and genetic defects to podocytes frequently result in severe kidney disease (Greka and Mundel, 2012). Recent progress has seen the publication of several directed differentiation protocols that generate complex associations of kidney-like cell types – kidney organoids – from pluripotent human stem cells (Freedman et al., 2015; Morizane et al., 2015; Taguchi et al., 2014; Takasato et al., 2014, 2015; Yamaguchi et al., 2016). Podocyte-like cells (PLCs) have been independently described several times in these systems (Kim et al., 2017; Sharmin et al., 2016). Data suggests PLCs develop along a process akin to that occurring in vivo. When transplanted either under the mouse kidney 180 capsule or subcutaneously, PLCs attract and interact with mouse endothelial cells (Bantounas et al., 2018; van den Berg et al., 2018; Sharmin et al., 2016). Transcriptionally, PLCs, human glomeruli, and mouse podocytes partially overlap (Sharmin et al., 2016), and structurally, PLCs establish an apico-basal polarity resembling human capillary-loop stage podocytes (Bantounas et al., 2018; Kim et al., 2017; Sharmin et al., 2016). These findings suggest that pluripotent stem cell-derived PLCs have potential for regenerative therapeutic approaches, disease modeling and drug discovery. However, realizing this potential requires a strong understanding of normal podocyte development to optimize in vitro programs and to accurately assess PLC-derived cell types. To this end, we employed scRNA-seq to obtain a detailed picture of the in vivo program of human podocyte development. Comparison with in vitro PLC production demonstrates an extensive but not complete, autonomous maturation in the absence of normal glomerular formation with PLCs displaying, vascular and mesangial organizing properties on transplantation beneath the mouse renal capsule. These data inform and support translational strategies with PLCs while highlighting areas where improvement is required to normalize PLC actions and properties. MATERIALS AND METHODS hESC Maintenance and Differentiation to Generate Kidney Organoids MAFB-P2A-eGFP H9 hESC cells were cultured in StemFit media (Ajinomoto, ASB01-R) supplemented with 10ng/ml of FGF2 (R&D, 273-F9) on Geltrex-coated plates (Geltrex from ThermoFisher, A1413302). When cells reach 60% confluent, differentiation was started following the Bonventre protocol with minor modification: 4 days of 8μM CHIR99021 (Sigma Aldrich, SML1046) treatment, followed by 3 days of 10ng/ml ActivinA (R&D, 338-AC-050) incubation, and 1 day of 10ng/ml FGF9 incubation. On day8, the cells were dissociated using TrypLE dissociation enzyme (Gibco, 12563011), and cell number was acquired. 75,000 cells/well were seeded on a 96-well ultralow-attachment plate (Corning, CLS7007) to form aggregates. The aggregates were formed in 181 3uM CHIR and 10ng/ml FGF9. On Day10, the media was changed to basal media with 10ng/ml FGF9. From Day13 to Day28, the aggregates were cultured in growth factor-free basal media. All differentiation steps were done using basal differentiation media (Advanced RPMI 1640 (Gibco, 12633020) + 1X Glutamax (Gibco, 35050079) + 1% Penicillin-Streptomycin (Invitrogen, 15070063). Immunofluorescent analyses Before the immuno-detection was performed, frozen sections tissue was thawed at room temp for 10 minutes. Antigen retrieval was done in 1X Citrate Buffer pH 6.0 (Sigma) in a pressure cooker. The slides were washed with water and air dried for 5 min. The slides were incubated with 1.5% Seablock (ThermoFisher) in PBS + 0.25%TritonX block buffer for 1 hour at room temperature, and in primary antibody mixture (diluted in block buffer) at 4°C overnight. Primary antibodies used in the study are listed as follow: LHX1 (R&D, MAB2725,1:300), MAFB (R&D, MAB3810, 1:500), MAFB (Santa Cruz, sc-10022, 1:100), PAX8 (abcam, ab189249, 1:1000), KRT8/18 (DSHB, troma-1; 1:50), NPHS2 (abcam, ab50339, 1:10000), SYNPO (R&D, MAB8977, 1:300), TGFBR3 (R&D, AF-242-PB, 1:300), ANXA1 (Cell Signaling, 32934, 1:200), ARMH4/C14orf37 (Sigma Aldrich, HPA001789, 1:300), WT1 (abcam, ab89901, 1:1000), CUBN (Santa Cruz, sc-20607, 1:300), CDH1(Biosciences, 610182, 1:300 ), PDGFRB (abcam, ab32570, 1:500), VEGFR2 (Cell Signaling, 2479,1:150), GFRA3 (R&D, AF670, 1:300), PAX2 (R&D, AF3364, 1:500), F3 (R&D, AF2339, 1:500), PLVAP ( BioRad, MCA2539GA,1:300), GATA3 (R&D, AF2605, 1:300), PECAM1 (BD Pharmingen, BDB550274, 1:300), EHD3 (Novus Biologicals, NBP2-31896, 1:300), FOXC2 (R&D, AF6989, 1:300). Secondary antibodies conjugated with AlexaFluor 488, 555, 594, and 647 were purchased from Molecular Probes. Slides were incubated with 1 µg/ml Hoechst 33342 (Molecular Probes) in PBS for 5 min to stain the nuclei. Sections were mounted in ProLong Gold Antifade Reagent (Life technologies) and imaged at 10X or 63X using the Leica SP8 confocal microscope. In situ hybridization 182 We utilized RNAscope® Multiplex Fluorescent Reagent Kit v2 (Advanced Cell Diagnostics, Inc.) to perform fluorescent in situ hybridization. The slides were prepared as described above. Briefly, the tissues were treated with hydrogen peroxide and protease, then hybridized with RNAscope probes for 2 hours at 40°C using the HybEZ oven (Advanced Cell Diagnostics, Inc.). The probes were then amplified and detected with tyramide signal amplification fluorescence. To detect nuclei, the slides were incubated with 1 µg/ml Hoechst 33342 (Molecular Probes). The tissue was imaged at 63X using the Leica SP8 confocal microscope. The catalog numbers of probes from Advanced Cell Diagnostics, Inc. used in this work are listed as follow: MAFB (400801-C2), RP4.31 (511381-C3), OLFM3 (549051-C3), PLA2R1 (524581), COL4A3 (461861) and TNNT2 (518991-C3). Single-Cell RNA-Sequencing and Analyses of Human Fetal Kidneys Human kidney samples were embedded in 4% agarose block, and were sectioned to 300-μm thick sections using the vibratome (Leica VT1000S). The vibratome sections were further dissected manually to separate the outer cortex from the inner cortex. The specimens were enzymatically digested using collagenase A/pancreatin. Live single cells (DAPI- DRAQ5+) were selected using fluorescence-activated cell sorting (FACS) and were captured by microfluidic droplets using the Chromium 10x genomics platform as described previously (Lindström et al., 2018c). Quality control, mapping to reference genome and count table assembly of the libraries were performed using CellRanger 2.1 (10x Genomics) (Lindström et al., 2018c). The data is available at GEO accession number GSE124472. The datasets from Zone 1 and Zone 2 cells were merged into one for initial analysis using the MergeSeurat function in Seurat package. The merged dataset was log-normalized using NormalizeData function. The ScaleData function was used to scale and center genes in the dataset, regressing the following variables against each gene: nUMI, nGene, saturation, and orig.ident. Quality control filtering was performed on the cells using the following criteria: saturation ≥70%, ≤5% mitochondrial genes. Principle components (PCs) were calculated using the RunPCA function, and 183 statistically significant PCs (p < 0.01, Jackstraw criteria - Chung and Storey, 2015) were selected to use for clustering. We performed clustering using mclust package (Scrucca et al., 2016) with 41 PCs. Cluster assignments were initialized by hierarchical clustering (“hcVVV” initialization in mclust). The number of clusters were decided based on Bayesien Information Criterion (BIC). Cell types were identified using known markers as well as GO term analyses of top differentially expressed genes. Single-Cell RNA-Sequencing and Analyses of Human Kidney Organoids Two dd16 and two dd28 kidney organoids of the same differentiation batch were dissociated by incubating with the Accumax TM Cell Dissociation Solution (Innovative Cell Technologies, Inc.) for 20min with gentle pipetting using P1000 tips. The dissociation enzyme was neutralized by autoMACS TM Running Buffer (Milteny Biotec), and the cells were centrifuged at 300 g for 5min. The pellet was resuspended in autoMACS TM Running Buffer (Milteny Biotec). The cell solution was run through a 40-µm cell strainer (Falcon) before live single cells (DAPI- DRAQ5+) were selected using FACS. The single cells were captured and subjected to single-cell sequencing using the Chromium 10x genomics platform (Lindström et al., 2018c). The two dd16 datasets and two dd28 datasets were merged with the Seurat package using MergeSeurat function. Quality control and cluster finding were performed as described above for the human kidney datasets. Pseudotime Reconstruction of Lineages NPCs, early induced NPCs, early podocytes and podocytes were subset from the merged Zone1/Zone2 dataset using the Seurat package. We used the Monocle2 package to reconstruct differentiation trajectory. Cells assigned by Monocle to the “proliferative” branch were selected against as described in (Lindström et al., 2018d). Non-proliferative cells were re-analyzed to build a developmental trajectory. Differentially Expressed Gene Test between Two Podocyte Clusters 184 Differentially expressed genes from podocyte clusters in each dataset were obtained using the FindMarkers function (Bimod test). The following comparisons were performed: Week 15 (clusters 5 and 7) Zone 1 versus Zone2, Week 17 (clusters 3, 15 and 21) Zone 1 versus Zone 2, or Week 17 Late Podocyte (clusters 3 and 21) versus Organoid Podocyte (clusters 14, 19, 26 and 29) (representing “Podocyte Differences”). To account for “batch” variation due to tissue handling and origins of tissues, we selected non-epithelial clusters from the datasets (non-podocytes and PAX2- negative clusters – listed in table below), and performed differentially expressed gene test to obtain gene lists representing “Background Differences” (Supplementay Table 2). Differentially expressed genes specific to podocyte were identified as “Podocyte Differences” genes absent from the “Background Differences” list, and were presented in volcano plots. Samples Clusters selected for “Podocyte Differences” Clusters selected for “Background Differences” Week 15 5, 7 6, 11, 14, 15, 16, 17, 18, 19, 20, 21 Week 17 3, 15, 21 6, 8, 12, 13, 14, 16, 17, 18, 19, 20 Organoid 14, 19, 26, 29 1, 3, 4, 5, 6, 11, 13, 16, 20, 23, 24, 25, 27 EP and LP gene list generation To obtain the list of representative EP and LP genes (Figure 6.3C), we first inferred a set of genes that changed significantly across the differentiation trajectory using the differentialGeneTest function in Monocle2 (q-value < 0.05). We then filtered this list by selecting only genes correlated 185 with known EP and LP markers: For a set of previously profiled markers (Figure 6.3D) we obtained the 50 genes with highest Pearson correlation with each one and selected, among the union of all correlated genes, the ones that were significant in the trajectory. Each resulting gene was visualized in a trajectory heatmap and manually curated to generate the lists of 158 EP genes and 104 LP genes. Hierarchical clustering of human week 17 clusters and organoid cell clusters Using the Seurat package, the Week 17 merged dataset was combined with the Kidney Organoid merged dataset (using MergeSeurat function) after identification of all clusters, and 70 PCs were calculated. To account for transcriptional differences due to origins of tissue, we examined all PCs using boxplots for distributions of cell loadings of each cluster and removed PC2, which was homogeneous within one origin, but heterogeneous between human and organoid origins. Hierarchical clustering was then performed using the BuildClusterTree function with PCs 1 to 70 excluding PC2. SWNE analysis of the merged human week 17 and organoid cell clusters The Seurat object of merged human week 17 and organoid cells generated above was used as the input for SWNE (Wu et al., 2018a, 2018b). To select genes as input for SWNE (var.genes), we extracted the genes with highest loadings in each significant principal component of our joint analysis (PCs 1 to 70, excluding PC2). We sorted the squared loadings of each gene in decreasing order and kept the genes whose cumulative squared sum is smaller than 0.5. Our candidate gene list is the union of all significant genes across all principal components. Using var.genes, SWNE embedding was generated with 20-k factors. The plot was generated with alpha.exp = 1.6, snn.exp = 1, n_pull = 8, and 6 embedded factor genes (SIX2, PDGFRB, POU3F3, PAX2, OLFM3, and MAFB). mRNA-Seq of MAFB-eGFP+ cells from kidney organoids 186 Dd16 and dd28 kidney organoids from at least 3 differentiation batches were dissociated using the Accumax TM Cell Dissociation Solution (Innovative Cell Technologies, Inc.) and resuspended in autoMACS TM Running Buffer (Milteny Biotec) for FACS as described above. Live eGFP+ single cells were selected using stringent gate to separate the brightest eGFP+ DAPI- DRAQ5+ cells from eGFP- DAPI- DRAQ5+ cells. 50,0000 – 100,0000 cells collected from FACS were pelleted at 4°C, 2000 g for 10min, and resuspended in RLT buffer (RNeasy MicroKit, Qiagen). The RNeasy kit was used to purify RNA from the cells following the manufacturer’s protocol. mRNA-Seq libraries were prepared with KAPA Stranded mRNA-Seq Kit (Kapa Biosystems, #KK8420). The libraries were subsequently sequenced with Illumina NextSeq500 model with pair-end 75 bp setting. mRNA-Seq of human fetal renal corpuscles Human fetal kidneys of week 16-17 were minced and ground using the seal end of a 3-ml syringe plunger (BD Medical) on a 100-µm cell strainer (Falcon). Dissociated tissue passing through the strainer was collected in DMEM, and the flow-through was filtered using a 70-µm cell strainer (Falcon). Renal corpuscles trapped on the 70-µm strainer were collected in DMEM, concentrated by centrifuging at 1000 g for 5 min, and lysed in RLT buffer for RNA extraction (RNeasy MicroKit, Qiagen). The 70-µm strainer flow-through portion was also collected in RLT buffer for mRNA profiling. mRNA-Seq libraries were prepared as described above. mRNA-Seq of immortalized podocytes Human immortalized podocytes were obtained from Dr. Moin Saleem’s group (University of Bristol) and cultured following the existing protocols (Saleem et al., 2002; Lan et al., 2012). Cells were collected before thermoswitch (cultured at 33°C) and after thermoswitch (cultured at 37°C) in RLT buffer (RNeasy MicroKit, Qiagen) for RNA extraction. mRNA-Seq libraries were prepared as described above. mRNA-Seq data analysis 187 mRNA-Seq reads were aligned with TopHat2 (Kim et al., 2013; Trapnell et al., 2009) to hg38 assembly. The aligned reads were quantified with Partek Genomics Suite software, version 6.6 (St. Louis, MO, USA) to obtain both RPKM and counts at gene level. TPM was calculated by dividing the RPKM by the mapping ratio of the library to exon regions of the genome. To identify differentially expressed genes, count tables of the two groups of data being compared were first processed through DESeq2 (Love et al., 2014) to obtain the p values from negative binomial tests which evaluates the significance of difference by read counts. Next, the TPM tables of the same samples were used to calculate the two-sample independent t-test p values. Both p values were used in screening for differentially expressed genes (p < 0.05 in both cases). Only genes with TPM > 5 in the more highly expressed samples were selected. Top 2000 most variably expressed genes of all samples were selected and their TPM values were plotted with 'heatmap2' in the 'gplot' package of R. Gene-list GO-term Queries Differentially expressed genes or gene module lists were queried by ToppGene (Chen et al., 2009) identifying Biological Processes and Coexpression Atlas. OMIM gene expression analysis Genes associated with human “glomerulosclerosis” and “glomerulopathy” were obtained from the Online Mendelian Inheritance in Man database and Lepori et al., 2018. The average expression levels of OMIM genes were calculated using the AverageExpression function in Seurat for the following cell populations: Week 17 early and late podocyte, Week 17 mesangial cells, Week 17 glomerular endothelial cells, Organoid early and late podocytes. Genes with average expression higher than 0 were presented using the DotPlot function in Seurat. Analysis of published scRNASeq dataset 188 Datasets from the Czerniecki et al. (2018) and Wu et al. (2018) studies were acquired through GEO (GSE109718 and GSE118184, respectively). The Seurat package was used to obtain feature plots displaying expression of genes of interest. Analysis of microarray datasets Microarray data was acquired through GEO (GSE17142, GSE17143, GSE17145). The Oligo package (Carvalho et al., 2018) was used to process the CEL files. The Limma package (Ritchie et al., 2015) was used to normalize the data sets and perform statistical inference. To find differentially expressed genes between two given groups, we used the following threshold: DEseq value > 6, fold change > 3 and p-value < 0.01. Renal capsule transplant The procedure was adapted from (Yoshimura et al., 2017). Week 8-12 NOD.CB17- Prkdc<SCID>/J mice were anesthetized with Ketamine/Xylazine. Surgery site at the dorsal flank was shaved and swabbed with Proviodine/alcohol. An 8-10 mm incision was made, and the fascia was incised before the kidney was externalized. The kidney capsule was kept moistened with sterile saline during the procedure. A small incision was made in the outer membrane of the renal capsule at the caudal end, using a sharp 24g needle and the sub capsular space is flushed with 1ml of basal differentiation media using a blunted 24g needle 30g needle (B30-50, Strategic Applications, Inc.) attached to a 1 ml syringe. Two agarose rods (2mm long, 0.5mm diameter) were pushed into the sub capsular space in the shape of an open V using forceps. A 20g indwelling needle (SURFLO® PTFE I.V. Catheter needle, TESR-OX2025CA, VWR) attached to a 1 ml syringe and draw up 3-4 dd13-14 organoids basal differentiation media into the needle. The indwelling needle was inserted under the renal capsule to place organoids between the agarose rods. The capsule incision was cauterized, and the kidney was replaced into the retroperitoneum. The muscle layer was sutured, and the skin was closed with wound clips. 189 Intravital multiphoton microscopy NOD SCID mice were anesthetized with isoflurane (3% in induction chamber and 1.5-1.8% for maintenance through nasal cone). Alexa594-conjugated bovine serum albumin (ThermoFisher) was administered iv. by retro-orbital injections to label the circulating plasma (30µL iv. bolus from 10 µg/ml stock solution). Subcapsular organoid implants in left kidney were exteriorized through a 8-10 mm incision under sterile conditions. In all procedures, body temperature was maintained by using a homeothermic blanket (Harvard Apparatus, Holliston, MA). The mouse was placed on the stage of an inverted microscope with the exposed kidney placed in a coverslip-bottomed chamber bathed in normal saline. Image acquisition of intact organoids was performed in vivo using a Leica SP8 DIVE multiphoton confocal fluorescence imaging system (Leica Microsystems) powered by a Coherent Discovery laser system at 860 nm excitation (Coherent) and a DMI8 inverted microscope’s external Leica 4Tune spectral hybrid detectors (emission at 530±10nm for eGFP and 600nm for Alexa594- Albumin). Images were acquired in 12-bit, 512×512 pixel using a 40X Leica water immersion objective (NA 1.1). (Hackl et al., 2013; Kang et al., 2006). All animal protocols were approved by the Institutional Animal Care and Use of Committee at the University of Southern California. Data and Software Availability The bulk and single-cell RNA sequencing datasets are available under GEO accession numbers: GSE127344, GSE124392, and GSE124472. RESULTS Single-cell transcriptomic analysis of human nephrogenesis Analysis of kidney organoids generated by the directed differentiation of pluripotent stem cells suggests organoid nephron-like structures resemble fetal and not mature nephrons (Freedman et al., 2015; Morizane et al., 2015; Taguchi et al., 2014; Takasato et al., 2016). Given the lack of a 190 comprehensive molecular frame-work for the formation of kidney cell-types in the human fetal kidney, conclusions were limited and primarily founded on analysis of a few specific podocyte markers and selected morphological criteria. We have begun to assemble a frame-work for the earliest stages of human nephrogenesis, within the cortical nephrogenic zone (Lindström et al., 2018a, 2018b, 2018c, 2018d; O’Brien et al., 2016). To extend these analyses to include more mature cell types, we performed scRNA-Seq analyses on both the nephrogenic zone and the inner cortex. To preserve spatial information, we cut 300-µm thick vibratome sections of week 15-17 fetal kidney samples, manually dissected the outer nephrogenic cortex (Zone 1) and the inner cortex (Zone 2), and dissociated each region to enable scRNAseq (using the 10x Chromium platform, as described previously in Lindström et al., 2018c) (Figure 6.1A). Zone 1 and Zone 2 cells enrich for early and late nephron cell-types, respectively, and display contiguous transcriptomic signatures of nephron development. To visualize renal corpuscle developmental programs with a focus on podocyte development, we performed immunofluorescent analysis against specific proteins in Zone 1 and 2 to distinguish podocytes (MAFB), ECs (VEGFR2), interstitial cells (PDGFRB), and epithelial nephron cell types (KRT8/18) in human fetal kidneys (Figure 6.1B). MAFB+ podocyte precursors emerged first in the proximal segment of the renal vesicle (RV). As the RV matured to comma-shaped body (CSB) nephrons and the glomerular cleft formed and expanded, cuboidal podocyte precursors lie on the proximal side of the glomerular cleft. Endothelial and interstitial cells invaded the glomerular cleft at the CSB stage and were likely progressively recruited during the transition to the S-shaped body (SSB) stage, as podocyte precursor cells extended along the length of the glomerular cleft (Figure 6.1B). The RV to SSB progression was limited to Zone 1. In zone 2, nephrons matured to the capillary loop stage (CLSN) and functional filtering nephrons. The progressive development of the renal corpuscle is highlighted by the interplay amongst podocytes 191 (MAFB+), ECs (VEGFR2+), and mesangial cell population (PDGFRB+) as these cell types expand, rearrange and mature to form the renal filtration unit (Figure 6.1B). Zone 1 and 2 scRNA-seq profiles from a week 17 human kidney were subjected to quality control filtering, and 7,518 single-cell transcriptional profiles were merged into one dataset. Cell groupings were identified by unsupervised clustering using a Gaussian mixture model (Lindström et al., 2018d; Scrucca et al., 2016) . Twenty-one clusters emerged from this analysis (Figure 6.1C). Each cluster was identified by the expression of known human kidney cell type markers (Lindström et al., 2018c, 2018a, 2018b, 2018d) (Figure 6.1C and 6.1E) (Supplementay Table 1). Following expectations, Zone 1 was enriched for early progenitor and differentiated cell types from the nephrogenic, interstitial, and ureteric lineages, whereas Zone 2 consisted of more mature cell-types (Figures 6.1C, 6.1D and S6.1E). ECs were identified in both Zone 1 and Zone 2, while mesangial cells (MCs) predominated in Zone 2 (Figures 6.1C, 6.1D and S6.1E). Cell cluster identification suggested a continuum of nephrogenic lineage cell progression from nephron progenitor cells (NPCs) to maturing nephron cell types. As we also aimed to examine the presence of glomerular vascular and mesangial cells in the in vitro culture, signatures of these two cell types were identified from the scRNA-Seq datasets. We confirmed that co-expression of PDGFRB and GATA3 marked the pericytes recruited to renal corpuscles, and committed mesangial cells in late RC co-expressed GATA3 and TMEFF2 (Figures S6.4A, 6.5G and 6.5H). Human glomerular vascular cells activated PECAM1, EHD3 and GATA5 (Figure 6.5I and S4A), and GATA5 expression was also detected in the mouse glomerular vasculature (Messaoudi et al., 2015) (Figure 6.5K). To validate key predictions from the week 17 kidney analysis, we performed scRNA-seq on a week 15 kidney sample. The 6,129 Zone 1 and 2 scRNA-Seq profiles formed 21 clusters (Figures S6.1A-D). Though the proportion of cells varied within clusters at week 15 and week 17, as expected, the cell type diversity was similar. Overall, the scRNA-seq quality was stronger in the week 17 sample, 192 and to avoid a loss of resolution in more detailed studies of the podocyte, we focused on this sample for further analysis. Establishing the developmental trajectory from nephron progenitor to human podocyte To identify normal transcriptional changes in the podocyte forming program, we selected 3,318 cells including: NPCs (cluster 1 and 9), proliferative developing nephron cells (cluster 10), early podocytes (cluster 15), and maturing podocytes (cluster 3 and 21). Monocle2.0 was used to assemble data into a predicted developmental trajectory (Figures S6.2A, S6.2B, 6.1F and 6.1G). One end-point of the trajectory comprised nephron progenitors (B1), and the other podocytes (B2) with a side branch of proliferating cells, collectively grouped by a strong cell cycle signature (branch B3), (Figure S6.2C). A second iteration of pseudotime analysis was performed from NPCs to podocytes (2,705 cells of branches B1 and B2). As expected, Zone 1 and Zone 2 cells concentrated at either ends of the trajectory (Figure 6.1F). NPC genes such as SIX1, SIX2, EYA1 and MEOX1 were present at the start of the trajectory and downregulated along the predicted developmental progression. The loss of an NPC signature corresponded to the onset of a podocyte signature. A cohort of genes predicted to display a distinct transient early podocyte (EP)-restricted activity (including LHX1, PAX8, FBLN2, OLFM3, PCDH9, SLC16A1, GFRA3, and LEFTY1) gave way to a late podocyte (LP) gene expression signature (including PLA2R1, ARMH4, F3, SYNPO, NPHS2, MAFB, TGFBR3, COL4A3, COL4A4, TNNT2, PLCE1 and ANXA1) (Figure 6.1H). Analysis of week 15 and 17 scRNA-seq confirmed EP and LP signatures within Zones 1 and 2, respectively (Figures S6.1F and S6.1G). We generated comprehensive human EP (huEP) and LP (huLP) signatures by identifying genes whose expression correlated with representative EP and LP signatures (Figure S6.2D), and examined their expression along the human podocyte developmental trajectory (Figures S6.5) to generate curated lists of 158 EP and 104 LP signature genes. Among the EP genes, about half were activated in NPCs. Many of these were enriched in uncommitted and committed NPCs (red text, underlined – Figure S6.5), and were upregulated in the early period of podocyte development (Figure S6.2E). 193 Seventy-five genes were transiently expressed in a narrow window of early podocyte development including a number of genes known to control or demarcate nephron induction (green text, underlined – Figure S6.5) (Figure S6.2E). Interestingly, 40 EP genes encoded ribosomal proteins (“RPL” or “RPS” genes) downregulated at the initiation of podocyte development. The LP signature list included genes encoding transcription factors known to regulate podocyte development, cytoskeletal components and extracellular matrix proteins linked to glomerular function (Figure S6.2F). Many EP (CCND1) and LP genes (CD151, GSN, COL4A4, THSD7A, NPHS2, CLIC5, VEGFA, PLA2R1, COL4A3, CTGF, and MAFB) have been associated with genetic disorders of the glomerulus or kidney (Figure S6.2K) (Online Mendelian Inheritance in Man, 2018). We confirmed the expression of 72/104 LP genes in adult podocytes using Human Protein Atlas, highlight their relevance as mature podocyte signature (Uhlén et al., 2010; Uhlén et al., 2015) (Supplementay Table 2). To determine whether human podocyte differentiation is conserved in the mouse, we compared the human EP and LP signatures with the mouse microarray analyses of Mafb-GFP+ podocytes from E13.5 embryos and adult kidneys (Brunskill et al., 2011). Our analyses suggested a modest overlap between the two species, with 13 EP and 40 LP genes shared between mouse and human (Figure S6.2G and S6.2H), many of which have been described to be important for mouse podocyte morphogenesis (discussed later). We pinpointed when in podocyte development EP and LP gene profiles were established by combining immunofluorescent detection of target protein, or RNAscope fluorescent in situ hybridization to a target mRNA, on sections of 15-17 week human fetal kidneys. RV and SSB podocyte precursors expressed EP markers (OLFM3, PAX8, and LHX1) but expression ceased prior to or at CLSN stages (Figure 6.2A-C). GFRA3 expression was restricted to CLSN podocytes (Figure 6.2D). We also examined the expression of RPS21, encoding Ribosomal Protein S6.21, using in situ hybridization and observed lower activity in mature renal corpuscle podocytes (Figures S6.2I and S6.2J). LP markers (NPHS2, SYNPO, ARMH4, ANXA1, F3, TGFBR3, PLA2R1, COL4A3, and TNNT2) were first detected in 194 SSB or CLSNs, and the highest levels were observed in mature renal corpuscles (Figures 6.2E-J, S6.4E and S6.4F). Interestingly, ANXA1, which is only expressed in the late RC stage, displayed a unique distribution with markedly varying levels in individual podocytes within a single renal corpuscle (Figure 6.2J). Based on these observations, we estimated the expression windows of EP and LP genes, and categorized them into smaller groups. EP signature genes can be separated into those activated in NPCs and early committed NPCs (group EP1), those activated in RV and highly expressed in SSB-stage podocyte precursors (group EP2), and those transiently expressed in the CLSN podocytes (group EP3) (Figure S6.5). LP genes maintained high expression levels in late RC-stage podocytes, but can be divided into the early- and late-activated groups (groups LP1 and LP2, respectively) (Figure S6.6). In summary, the single-cell transcriptome profiles define the molecular development of the human podocyte lineage providing a molecular frame-work for analyzing development of PLCs in vitro. Transcriptomic profiling of podocyte-like cells generated from MAFB-reporting hESCs To facilitate analysis of in vitro derived PLCs, we generated a MAFB-P2A-eGFP H9 hESC line that places eGFP under the control of the MAFB gene (Figure S6.3A). MAFB encodes a key transcriptional regulator of podocyte gene expression that has been shown to play a critical role in mouse podocyte development (Sadl et al., 2002). Expression of the mouse and human gene can be detected in podocyte precursors as early as the RV stage (Figure 6.1B, 6.2A-J) and MAFB activity continues into mature podocytes in both the adult mouse and human fetal kidney (Lindström et al., 2018a). MAFB-P2A-eGFP H9 hESCs were differentiated into kidney organoids using existing protocols (Morizane et al., 2015) with minor modifications (Figure 6.3A). Whole organoid transcriptional profiling at differentiation day (dd) 0, 8, 10, 16, 22 and 28, guided by parallel immunofluorescent analysis with informative markers, showed induction and differentiation of characteristic nephron cell types in the kidney organoids (Figure S6.3B and S6.3C). eGFP+ cells first appeared at dd13-14 with a subsequent increase in both the numbers of eGFP+ cells and the level of eGFP fluorescence to dd28 (Figure 6.3B). 195 As expected, the eGFP signal was tightly correlated with endogenous MAFB activity and colocalized with WT1, a known determinant of podocyte programs (Berry et al., 2015; Chau et al., 2011; Gebeshuber et al., 2013; Hammes et al., 2001; Kann et al., 2015; Moore et al., 1999) (Figure S6.3D). RNAseq profiling of FACS-isolated MAFB-eGFP+ cells from day 28 organoids confirmed significant enrichment of MAFB and other podocyte marker genes (Figure 6.3C). Further, hierarchical clustering of eGFP+ cells with human fetal renal corpuscles, immortalized podocytes (imPod) before and after thermoswitch emphasized improved resemblance of hESC-derived podocytes to the in vivo cells, supporting their use as a markedly enhanced tool for in vitro studies (Figure S6.3F). Additionally, gene ontology (GO) analysis highlighted podocyte-related terms (Figure S6.3E). Collectively, these data demonstrate the eGFP+ labelling strategy specifically identifies PLCs in kidney organoid culture. To investigate whether PLCs develop along a similar trajectory to human fetal podocytes, we performed scRNAseq on organoids at dd16 and dd28 (2,153 cells from dd16, and 5,818 cells from dd28). These two time points were selected as organoids strongly expressed EP signatures (including PAX8, OLFM3, LYPD1, SLC16A1) at dd16, and mature nephron signatures (including F3, PTPRO, C14orf37 or ARMH4, SYNPO, ANXA1) at dd28. (Figure S6.3C). After quality control filtering, unsupervised clustering of scRNA profiles for 7,200 organoid cells assigned this population to 29 groups (Figure 6.3D, Figure S6.3G). Each of these was identified through expression of marker genes, and hierarchical clustering was performed to match these groupings with the most closely related clusters of the week 17 human kidney scRNA-seq (Figure 6.3D). Similarity Weighted Nonnegative Embedding (SWNE) analysis (Wu et al., 2018) of the in vivo and in vitro cells merged object concurred with the hierarchical clustering and confirmed our identifications of in vitro cell types (Figure 6.3E). Organoids comprised cells with transcriptional signatures indicative of interstitial cells (COL1A1+, ALDH1A2+), nephron progenitors (SIX1+, MEOX1+), early developing nephron cells (PAX8+, LHX1+), precursors of the medial/distal segment (SOX9+, MECOM+, EMX2+), proximal tubule (LRP2+, SLC3A1+), parietal epithelial cells (LIX1+, CDH6+), and early and late podocytes (OLFM3+, 196 MAFB+, NPHS2+). Two clusters unexpectedly expressed muscle markers (MYOG+, MYL1+) and another cluster displayed a prominent neuronal signature (MAP6+, NEUROD1+) supporting recent observations of lineage heterogeneity in kidney organoid protocols (Czerniecki et al., 2018; Wu et al., 2018). Two clusters (10 and 15) with mixed but incomplete NPC and IC signatures were left “unidentified”. Of note, organoids are devoid of vascular cells precluding vascular podocyte interactions in podocyte development in vitro. To examine the PLC lineage more specifically, we identified 2,188 cells with NPC-like or PLC signatures and predicted developmental trajectories between the cell types (Figure S6.3H, S6.3I). As branch 3 (B3) contained mostly mitotic cells, we focused on the differentiation trajectory from organoid NPC to PLCs of 1,941 B1 and B2 cells (Figures S6.3H, S6.3J, 6.3G and S6.3I). We observed similar transcriptional changes to those identified in human podocyte development. EP signature genes (including OLFM3, PAX8, LHX1, SLC16A1) were transiently upregulated as NPC signature genes were deactivated, and downregulated when LP signature genes (including ANXA1, NPHS2, PTPRO, PLCE1, SYNPO, PLA2R1, ARMH4, F3, TGFBR3) were upregulated (Figure 6.3H). EP and LP genes were also enriched in dd16 and dd28 MAFB-eGFP+ cells, respectively, in bulk RNA-seq analyses (Figure 6.3F). Immunofluorescent analysis of EP and LP-associated proteins within PLCs at dd16 and dd28 confirmed the EP to LP gene expression transition (Figure 6.4A-F). In summary, PLCs follow a developmental trajectory similar to that observed in human podocyte development: dd16 PLCs resemble podocytes in SSBs while dd28 PLCs are similar to podocytes of the CLSN or later stages. Comparison of podocyte-like cells and human podocytes To determine the overlap between PLCs and human podocytes, we performed differential expression gene test between their transcriptomes (Figure 6.4G) (Supplementay Table 1). Of the previously identified EP and LP signature genes in the fetal kidney, most of these (137 EP genes and 84 LP genes) followed a similar early-late developmental time course in vitro (Figures S6.6). LP genes were absent, or expressed at low level, including genes encoding key extracellular matrix components 197 linked to kidney disease (including COL4A3, COL4A4) and angiogenic factors (including CXCL12, EFNB1) (Figures 6.4G, 6.4H and S6.6) (Supplementay Table 2). Among the EP genes, we validated the expression of OLFM3 and GFRA3 in dd28 podocytes by in situ hybridization and immunofluorescence, respectively (Figure 6.5D and 6.5F). We also observed co-expression of EP (GFRA3) and LP genes (ANXA1) in dd28 MAFB+ cells (Figures 6.4J and 6.5F). While GFRA3 and ANXA1 were detected at distinct stages of in vivo podocyte development - CLSN and late RC respectively (Figures 6.2D, 6.2H and 6.4I), co-expression in dd28 organoids showed the down-regulation of EP signature genes was incomplete. Dd28 organoid were a mosaic of EP-like (e.g., GFRA3+ANXA1-) and LP-like (e.g., GFRA3- ANXA1+) cell types (Figures 6.4J and 6.5F). Further, some LP genes including TNNT2, TNNI1, CAPN2, DCN, IGFBP7, CTGF, CXCL12 and CYR61 were weakly active in dd16 podocytes, but subsequently downregulated in dd28 PLCs (see TNNT2 in Figure 6.5E). An examination of published scRNA-Seq profiling of kidney organoids (Czerniecki et al., 2018; Wu et al., 2018) also suggests similar mis- expression of EP and LP genes in other organoid datasets in the literature indicating the observations here are likely of broad relevance to in vitro organoid models (Figure S6.4C and S6.4D). Collectively, these findings show a surprising level of maturation of in vitro derived podocytes that is independent of the vascular and mesangial components, and pinpoint aspects of in vitro podocyte programming for further improvement. Examination of glomerular disease-relevant genes To examine the applicability of in vitro derived podocytes to glomerular disease studies, we examined expression of genes associated with human glomerulosclerosis and glomerulopathy in the human glomerular cell types (Lepori et al., 2018, Online Mendelian Inheritance in Man, 2018). Forty- three genes were expressed in all three glomerular components: LMNA, COL4A1, MPV17, KANK2 and MYO1E were more highly expressed in the mesangial cells, while DGKE, KHDRBS3, SOX18, SLC7A7, KANK4 and TAL1 were enriched in the endothelial component. Of the twelve genes activated in podocytes, PAX2 and FAH were upregulated only in EPs, while PTPRO, COL4A3, COL4A4, PLCE1, 198 CRB2, NPHS1, TCF21, and ARHGAP24 were first detected in EPs and showed increased activity in LPs (Figure S6.2K). We surveyed the expression of these disease-associated genes in in vitro EP and LP populations, and highlighted podocyte genes that were detected in the in vitro derived cells to inform future glomerular disease modeling studies (highlighted in red, Figure S6.2K). Vasculature interactions in renal corpuscle development Podocytes produce VEGFA, which promotes concurrent development of the vascular network and mesangial support system (Eremina et al., 2003, 2006). Organoids generated via the Morizane protocol adopted here are largely avascular (Figure S6.4B). To determine whether co-development with vascular cell types may normalize podocyte maturation programs, dd13-14 organoids were implanted beneath the kidney capsule of NOD/SCID mice (Figure 6.5A). Live imaging of blood flow facilitated by plasma labeling showed organoids were well vascularized by the host mouse circulatory system (Plvap+) 10 days after implantation (Figure 6.5B and Supplementay video 1). OLFM3 and GFRA3, EP signature genes which display persistent activity in vitro, continued to be expressed in late vascularized podocytes post transplantation (Figure 6.5D and 6.5F), Similarly, we failed to observed normalization of the LP signature gene TNNT2 which remained undetectable in PLCs post transplantation (Figure 6.5E). However, COL4A3, mutations in which result in glomerular degeneration in Alport’s syndrome was now expressed in vascularized podocytes (Figure 6.5D). Thus, vascular interactions partially normalized the expression of a critical component of the glomerular basement membrane. Our scRNA-Seq analyses indicated that pericytes and mesangial cells were absent in the avascular organoids (Figure S6.4B). In vascularized organoids, MAFB+ HuNu+ in vitro derived podocytes formed renal corpuscle-like structure with PDGFRB+ HuNu+ organoid interstitial cells and PECAM1+ HuNu- mouse ECs (HuNu: Human Nucleus) (Figure 6.5C). Though TMEFF2 was not detected in PDGFRB+ cells recruited to podocyte clusters (data not showed), expression of GATA3 lends support to human organoid derived interstitial cells adopting an early pericyte identity (Figure 6.5J). 199 Additionally, the expression of GATA5 in mouse endothelial cells attracted to podocyte clusters supports the activation of an early glomerular-specific vascular signature (Figure 6.5K). In summary, in vitro derived podocytes nucleate vascular (host-derived) and mesangial (graft- derived) developmental programs, suggesting full maturation will require an interplay amongst all these cell types. DISCUSSION In this study, we extended recent reports from our group and others of human fetal kidney development, with a focus on the programs underlying human podocyte development (Lindström et al., 2018d, Menon et al., 2018). These data provide a benchmark for an unbiased assessment of human podocyte development as well as a resource for mining of regulatory mechanism to improve kidney organoid-directed programming of the kidney’s filtration system. Development of the human podocyte Deep profiling identified transcriptomic changes highlighting temporally distinct gene expression profiles in the staged progression of podocyte maturation. The transition from NPC to EP is associated with the down-regulation of a large set of ribosomal protein-encoding genes that remain active in other cell types of the human fetal kidney (Figures S6.4I and S6.4J), and the activation of EP signature genes profiled in our previous studies (Lindström et al., 2018c), several of which are critical for the formation of the mouse kidney (Müller et al., 1997; Ohuchi et al., 2000; Xu et al., 1999, 2003). NPCs are highly proliferative. However, proliferation drops as NPC commit to EP precursors, which undergo terminal cell divisions prior to forming mitotically quiescent mature podocytes (Hiromura et al., 2001). Genes of group EP2 are expressed transiently in the RV, SSB, and CLSN podocyte precursors, among which the expression of HEY1, CDH6, PAX8, JAG1, OLFM3, PCDH9 and LHX1 in human podocyte precursors has been documented (Lindström et al., 2018a, 2018d). Though their specific roles in podocyte development have not been examined, Cdh6, Pax8 200 and Lhx1 have been reported to play important roles in the mouse kidney formation or nephron induction (Bouchard et al., 2002; Kobayashi et al., 2005; Mah et al., 2000). Group EP3 comprises genes upregulated only in the CLSN, possibly as a transient response to endothelial/mesangial invasion and early establishment of signaling center at slit diaphragm. Among these, the transient expression of GFRA3, encoding GDNF receptor α3, hints at the possible importance of GDNF signaling in this specific time window of podocyte and glomerular formation. Among LP signature genes, group LP1 are detected as early as RV-stage podocyte precursors and maintained expression in late podocyte development, while LP2 genes are highly expressed in late RC podocytes. A large portion of them are disease-relevant ECM protein-encoding genes, some with known functions in mouse podocyte development (including ACTN4, NPHS1, NPHS2, PODXL, SYNPO, TJP1, PLCE1, COL4A3, COL4A4) (Ahvenainen et al., 1956; Asanuma et al., 2006; Boute et al., 2000; Invest., 1970; Itoh et al., 2014; Kaplan et al., 2000; Lepori et al., 2018; Online Mendelian Inheritance in Man, 2018). Our comparative analyses with the mouse podocyte transcriptional profiles highlight novel cross-species shared LP genes. For instance, PHACTR4 (Phosphatase and Actin Regulator 4) has been shown to regulate directional migration of enteric neural crest cells (Zhang et al., 2012), but its importance in podocyte cytoskeletal architecture and migration has not been studied. Additionally, the anti-inflammatory function of ANXA1 (Annexin A1) has been highlighted in diseases of various organ systems (Jong et al., 2016; Ries et al., 2016) and may function in podocyte antigen presenting activities (Goldwich et al., 2013). Notably, we also identified novel human LP-specific genes (including 6.200A6, MYL9, TPPP6, SNCA, TNNI1, TNNT2, MYL12, PDLIM2, PALLD, GSN) that are associated with cytoskeletal proteins, suggesting species-specific functions in maintaining podocyte architecture. Temporal expression of EP and LP genes is likely to be orchestrated by temporal programs of transcription factor activity. SIX1, SIX2, EYA1 and MEOX1, which are linked to the maintenance of mouse and human NPCs (Kobayashi et al., 2008; O’Brien et al., 2016; Self et al., 2006; Xu et al., 201 1999, 2003), could play a role in EP1 gene activation, while PAX8, LHX1, HEY1 activity would be more likely to play a role in EP2 and EP3 programs. Clearly, transient EP-restricted activity of these transcription factors rules out a progressive role in specification of mature podocytes. Transcription factors known to play essential role specifically in podocyte development (e.g., TCF21 and MAFB) were first detected in RV-stage podocyte precursors overlapping with NPC genes (SIX1 and TMEM100). Evidence points to conserved functions for several podocyte specifying transcriptional regulators between mouse and human, with activity continuing into LP programs regulating podocyte morphogenesis (Maezawa et al., 2014; Moriguchi et al., 2006). Signaling inputs from the slit diaphragm established at the capillary loop stage likely regulate LP gene activity (Greka and Mundel, 2012; Schell et al., 2014). The renal corpuscle is composed of three tightly interacting cellular components: podocytes, vascular and mesangial cells. Disrupting their interactions results in defective renal corpuscle development in the mouse kidney (Eremina et al., 2003, 2006; Kikkawa et al., 2003; Levéen et al., 1994; Lindahl et al., 1998; Soriano, 1994). Our analysis is consistent with a conserved role of VEGF signaling in recruitment and organization of the vasculature. A transient activation of SEMA3A was observed in EPs; Sema3a regulates morphogenesis of podocytes and recruitment of endothelial cells in the mouse kidney (Reidy et al., 2009). We also observed FBLN2 expression in podocytes; Fbln2 is required for vessel wall integrity (Chapman et al., 2010; Xu and Shi, 2014), and recent studies link Fbln2 to promoting vascular invasion (Kim et al., in preparation). Development of in vitro derived podocytes in comparison with the in vivo counterpart and roles of the vasculature in renal corpuscle development Our scRNA-seq analyses of human podocyte differentiation will facilitate evaluating in vitro efforts to produce normal podocytes, identifying regulatory mechanisms at play within the podocyte, and determining podocyte interactions with other cell types and the extracellular matrix. Comparing in vitro derived MAFB-eGFP+ cells with the in vivo podocyte developmental program, there is a 202 striking overlap: 137 of 158 EP genes and 84 of 104 LP genes were expressed as expected despite the absence of vascular or mesangial cell types. Podocytes in organoid transplants attract and interact with host vasculature and interstitial cells in the vicinity upregulate a pericyte signature. Further, there is a normalization of donor human podocyte programs in transplants. Together these results suggest further improvements can be made in vitro through the optimization of mesangial and vascular compartments in the organoid models. Recently, flow has been showed important for enhanced endothelial growth in bioengineered kidney organoid chips (Homan et al., 2019) though maturation of all three RC components are still up for investigation. Additionally, our predicted RC ligand-receptor interactions (Supplementay Table 2) could inform RC culture conditions that bode well for approaches to model podocyte-related kidney disease. 203 MAIN FIGURES AND TABLES Figure 6.1: Single-Cell RNA-Seq Analyses Showing Transcriptional Changes during Differentiation of human NPCs to Podocytes (A) Left: Vibratome section of week 15-17 human fetal kidney containing Zone 1 and Zone 2 cells. Right: IF stain of a week 15-17 kidney cryosection highlighting mesenchymal progenitor cells, ureteric epithelial cells, early and late nephrons. Dotted lines indicated sites of micro- dissection to separate Zone 1 and Zone 2. (B) IF stain showing morphogenesis of the renal corpuscle through RV, SSB, CLSN and late RC stages. (C) Unsupervised clustering of Week 17 kidney cells from both Zone 1 and Zone 2 displayed in a tSNE plot with annotation of cluster identities. In parentheses are differentially expressed genes used for cluster identification). (D) tSNE plot of Week 17 kidney cells colored by their original zonal identities. (E) Violin plots of differentially expressed genes used to classify 21 clusters. Dotted-lined boxes mark uncommitted/committed NPC and podocyte clusters subjected to secondary analyses. (F) Pseudotime trajectory from NPC to podocytes after removal of cells with strong cell-cycling signature. Cells are colored by their cluster identities. (G) Pseudotime trajectory from NPCs to podocytes with cells colored by their original zonal identities. (H) Heatmaps of selected genes whose expression changes along the differentiation trajectory from NPCs to podocytes. RV: renal vesicle, SSB: S-shaped body nephron, CLSN: capillary loop stage nephron, Late RC: late renal corpuscle, huNPC: human nephron progenitor cell, huEP: human early podocyte, huLP: human late podocyte. 204 205 Figure 6.2: In vivo Validation of Early and Late Podocyte Signatures (A) Fluorescent in situ hybridization showing expression of EP gene OLFM3 in RV, SSB, CLSN and late RC stages. Scale bars denote 50µm. (B) to (J) IF stains of EP markers (LHX1, PAX8 and GFRA3), and LP markers (NPHS2, SYNPO, ARMH4, ANXA1, F3, TGFBR3, and MAFB) showing their expression in RV, SSB, CLSN and late RC stages. Scale bars denote 50µm. RV: renal vesicle, SSB: S-shaped body nephron, CLSN: capillary loop stage nephron, Late RC: late renal corpuscle, EP: early podocyte, LP: late podocyte. 206 207 Figure 6.3: Single-cell RNA-Seq Analyses Showing Transcriptional Changes during in vitro derivation of podocytes (A) Schematic diagram summarizing the 28-day protocol to generate kidney organoids from human ESC. Red stars denote the time points selected for further analyses using scRNA-Seq. (B) Bright-field and (gray scale) endogenous eGFP (green) imaging of the kidney organoids after transition to 3D cultures. Scale bars denote 200µm. (C) RNA expression levels of known podocyte markers in MAFB-eGFP+ cells versus MAFB-eGFP- cells. Statistical significance is determined using student t-test. (D) Top: Unsupervised clustering of cells from dd16 and dd28 presented in a tSNE plot. Bottom: Annotation of organoid cluster identities and differentially expressed genes used for cluster identification. Hierarchical clustering suggested relationship among organoid cell clusters and human week 17 cell types. Asterisks (*) mark organoid NPC and podocyte clusters selected for secondary analyses using Monocle. (E) SWNE overlay of Week 17 human kidney and organoid clusters. Black numbers: Week 17 human kidney clusters; Blue numbers (with asterisks): organoid clusters. “Factor genes” in red are known kidney cell type markers. (F) Volcano plot with annotations of selected genes that were differentially expressed between dd16 and dd28 MAFB-eGFP+ cells. (G) Pseudotime trajectory from organoid NPCs to podocytes with cells colored by their cluster identities. (H) Heatmaps of selected genes whose expression changes along the differentiation trajectory from organoid NPCs to podocytes. Org: organoid, NPC: nephron progenitor cell, IC: interstitial cell, dd: differentiation day, EP: early podocyte, LP: late podocyte 208 209 Figure 6.4: Comparison of in vitro derived podocytes to human podocytes (A) to (F) IF stains to validate expression of EP markers (PAX8 and LHX1) and LP markers (SYNPO, ARMH4, ANXA1, and F3) in dd16 and dd28 organoid podocytes. Scale bars denote 50µm. (G) Volcano plot displaying genes either enriched in human LPs or organoid LPs. Blue text highlighting genes plotted in Figure 4H. (H) Heatmaps showing expression of selected OrgLP-enriched genes (C11orf71, GFRA3, ITIH5, OLFM3, and LEFTY1) and HuLP-enriched genes (PLA2R1, COL4A4, TNNT2, COL4A3 and LOX) along the in vivo or in vitro podocyte differentiation trajectory. (I) and (J) Feature plots showing expression of ANXA1 and GFRA3 analyzed using scRNA-Seq of Week 17 human fetal kidney (I), or kidney organoids (J). 210 211 Figure 6.5: Examination of vasculature’s contribution to glomerular construction (A) Schematic diagram summarizing the experimental design to vascularize in vitro derived podocytes (B) Multiphoton imaging snapshots of vascularized in vitro derived podocytes before and after Alexa 594-conjugated Albumin dye injection. Scale bars denote 50µm. (C) IF analysis of vascularized organoids showing human or mouse origins of podocytes, interstitial and vascular components. Scale bars denote 50µm. (D) and (E) Fluorescent in situ hybridization showing expression of EP gene (OLFM3) and LP genes (COL4A3 and TNNT2) in dd16, dd28 and vascularized in vitro derived MAFB+ podocytes. Scale bars denote 50µm. (F) IF stains of in dd16, dd28 and vascularized in vitro derived podocytes. Scale bars denote 50µm. (G) and (H) IF stain (G) and fluorescent in situ hybridization (H) highlighting PDGFRB+ GATA3+ pericytes and GATA3+ TMEFF2+ mesangial cells in human developing nephrons. Scale bars denote 50µm. (I) IF analysis showing EHD3+ PECAM1+ glomerular endothelial cells in human developing nephrons. Scale bars denote 50µm. (J) IF stain showing expression of GATA3 in interstitial cells recruited to podocyte clusters. Scale bars denote 50µm. (K) IF stain combined with in situ hybridization (italicized gene names) showing mouse Gata5+ glomerular vascular cells in adult mouse renal corpuscle (LEFT panel) and vascularized organoid (RIGHT panel). Scale bars denote 50µm. 212 213 214 Table 6.1: Review recent approaches to assess in vitro derived podocytes. Study Reporter Cell Line for Podocyte Identification Comparison with in vivo Podocytes In vivo Sample Type Method Findings Sharmin et al., 2016 NPHS1-GFP iPSC mouse adult podocytes, human glomeruli Microarray Shared genes among in vitro podocytes, human glomeruli and mouse adult podocytes are enriched for podocyte signature genes Wu et al., 2018 N/A adult kidney cells single-cell RNA Seq of organoids, and single-nucleus RNA- Seq of human adult kidney biopsy Identified podocyte-like cells in organoids by comparing average gene expression of organoid and human fetal kidney cell clusters Hale et al., 2018 MAFB-BFP iPSC human matrisome database mass spectrometry in vitro 3D-cultured podocytes and human matrisome have shared extracellular matrix proteins Czerniecki et al., 2018 N/A Human Fetal Kidney (Menon et al., 2018) single-cell RNA Seq of organoids and human fetal kidney Identified podocyte-like cells in organoids by comparing average gene expression of 215 organoid and human fetal kidney cell clusters Combes et al., 2019 N/A Human Fetal Kidney (Lindström et al., 2018) single-cell RNA Seq of organoids and human fetal kidney Identified podocyte-like cells in organoids by comparing average gene expression of organoid and human fetal kidney cell clusters Yoshimura et al., 2019 NPHS1-GFP iPSC Human Adult Podocytes RNA Seq Identified shared and different gene expression profiles between in vitro and in vivo podocytes Tran et al. (our study) MAFB-eGFP H9 hESC Human Fetal Kidney single-cell RNA Seq of organoids and human fetal kidney Identifed shared transcriptional signatures between in vitro and in vivo podocyte development, pinpointed abnormal gene expression in vitro, and highlighted the potential of in vitro derived podocytes as a model for human podocyte development and disease studies 216 SUPPLEMENTAY FIGURES Figure S6.1: Single-Cell RNA-Seq Analyses of Week 15 and Week 17 Human Fetal Kidneys Showing Transcriptional Changes during Differentiation of human NPCs to Podocytes (Related to Figure 6.1A-E) (A) Unsupervised clustering of Week 15 kidney cells from both Zone 1 and Zone 2 displayed in a tSNE plot with annotation of cluster identities. In parentheses are differentially expressed genes used for cluster identification). (B) tSNE plot of Week 15 kidney cells colored by their original zonal identities. (C) Violin plots of differentially expressed genes used to classify 21 clusters of Week 15 cells. (D) and (E) Bar graphs presenting zonal contribution in Week 15 kidney (D) or Week 17 (E) clusters (F) and (G) Volcano plots with annotations of genes that are differentially expressed between Zone 1 and Zone 2 of Week 15 (F) or Week 17 kidney (G). 217 218 Figure S6.2: Pseudotime Analyses Showing Transcriptional Changes during Human Podocyte Development (Related to Figure 6.1F-H) (A) and (B) Pseudotime trajectories from NPCs to Podocytes with cells colored by their cluster identities (A) or zonal identities (B). (C) Expression of EYA1, MAFB, and TOP2A along the pseudotime trajectory indicating B3 is mostly comprised of proliferative cells. (D) Representative EP and LP genes that were used in gene expression correlation analysis to obtain a more complete list of EP and LP genes. (E) and (F) GO term analyses of human EP gene list (E) or human LP gene list (F) using ToppFun. (G) and (H) Venn diagrams displaying shared and species-specific EP genes (G) or LP genes (H). (I) and (J) Fluorescent in situ hybridization (I) and quantification (J) showing expression of RPS21 in human developing nephrons. Scale bars denote 50µm. (K) Dotplot showing expression of OMIM genes associated with glomerulosclerosis and glomerulopathy in the human glomerular cell types and organoid EP and LP. Genes detected in in vitro derived podocytes are highlighted red. B: Branch, hu: human, EP: early podocyte, LP: late podocyte 219 220 Figure S6.3: Examination of in vitro Derived Kidney Organoids Containing Podocyte-like Cells (Related to Figure 6.3) (A) Schematic diagram of CRISPR-Cas9 targeting of MAFB locus in H9 hESC. (B) IF stains of dd16 and dd28 kidney organoids suggesting formation of nephron-like structures. Scale bars denote 50µm. (C) Expression levels of NPC markers (SIX1, SIX2, and EYA1), developing nephron markers (PAX8, JAG1, and HNF1B), nephron segment markers (SLC3A1 and SLC12A1), early and late podocyte markers (OLFM3, MAFB, and SYNPO, PLA2R1) along the kidney organoid differentiation protocol. (D) IF stains showing co-expression of eGFP with MAFB and WT1 in dd28 organoids. Scale bars denote 50µm. (E) GO term analyses of genes enriched in dd28 MAFB-eGFP+ cells in comparison to MAFB-eGFP- cells using ToppFun. (F) Hierarchical clustering using the top 2000 most variably expressed genes of transcriptional profiles of eGFP+ hESC-derived podocytes, eGFP- organoid cells, imPods, human fetal RCs and kidneys. (G) tSNE plot of merged kidney organoid cells colored by their original “differentiation day” identities (H) Pseudotime trajectories from organoid NPCs to podocytes with cells colored by their cluster identities (left) or “differentiation day” identities (right). (I) Pseudotime trajectory from organoid NPCs to podocytes with cells colored by their original “differentiation day” identities after removal of proliferative cells. (J) Expression of EYA1, MAFB, and TOP2A along the pseudotime trajectory indicating B3 is mostly comprised of proliferative cells. 221 222 Figure S6.4: Identification of Mesangial Cells, Glomerular Endothelial Cells and Early/Late Podocytes in Human Week 17, Merged Kidney Organoid and Czerniecki Organoid scRNA-Seq Datasets (Related to Figure 6.4 and 6.5) (A) and (B) Feature plots showing the presence of pericytes (PDGFRB+ GATA3+), mesangial cells (GATA3+ TMEFF2+) and glomerular endothelial cells (PECAM1+ EHD3+) in Week 17 (A), and absence of these cell types in (B) Merged Kidney Organoids. (C) and (D) Feature plots showing the presence of early podocytes (MAFB+ OLFM3+), late podocytes (MAFB+ TGFBR3+), and late podocytes expressing EP gene (ANXA1+ GFRA3+) in (C) Czerniecki Organoids (Czerniecki et al., 2018), and (D) Wu Organoids (Wu et al., 2018) using the Morizane protocol (M). (E) and (F) Fluorescent in situ hybridization of OLFM3, PLA2R1, COL4A3, TNNT2 and MAFB in human developing nephron. Scale bars denote 50µm. 223 224 Figure S6.5: Heatmaps Presenting Expression of Human Early and Late Podocyte Genes along the in vivo Differentiation Trajectory from NPCs to Podocytes (Related to Figure 6.1H) NPC: nephron progenitor cell, EP: early podocyte, LP: late podocyte, hu: human. 225 226 Figure S6.6: Heatmaps Presenting Expression of Human Early and Late Podocyte Genes along the in vitro Differentiation Trajectory from NPCs to Podocytes (Related to Figure 6.3H) NPC: nephron progenitor cell, EP: early podocyte, LP: late podocyte, hu: human, RC: renal corpuscle. 227 228 CHAPTER 7 A Scalable Mini-Organoid Model of Autosomal Dominant Polycystic Kidney Disease for Disease Mechanism and Drug Discovery At the time that this dissertation was being written, this chapter was under review for publication. The study was co-led by me and Cheng (Jack) Song, who contributed to experimental design, data collection and analysis. Complete data collection was made possible with the help of Trang Nguyen, Jill A. McMahon, Nils Lindström and Rui Yang. Andrew McMahon supervised the conceptualization, experimental design, data collection and analysis, manuscript editing and reviewing, while Daniel C.-H. Lin advised on designing the high-throughput screen and manuscript preparation. INTRODUCTION The human kidney performs the vital task of filtering blood through a network of around a million nephrons to maintain homeostasis of tissue fluid (Nyengaard and Bendtsen, 1992; Sasaki et al., 2019). Hormonal interactions also regulate hematopoiesis, blood pressure and bone composition. As a consequence, the loss of renal activity in chronic disease results in secondary complications including anemia, increased cardiovascular risk, bone disorders, and nutritional problems (Thomas et al., 2008). Chronic kidney disease affects up to 15% of the adult population in the United States (Centers for Disease Control and Prevention, 2019). Treatment options remain largely limited to dialysis and kidney transplantation, casting a burden on the healthcare system. Improving approaches to better understand and model human kidney disease is an important priority. Multiple research groups have pioneered the generation of kidney organoid systems sharing several features (Czerniecki et al., 2018; Freedman et al., 2015; Kumar et al., 2019; Lam et al., 2014; Low et al., 2019; Morizane et al., 2015; Taguchi and Nishinakamura, 2017; Taguchi et al., 229 2014; Takasato et al., 2014, 2016). In these model systems, human pluripotent stem cells (PSCs) differentiate into organized 3-D structures comprising multiple kidney cell types of the nephron lineage and potentially the ureteric epithelial collecting system lineage (Howden et al., 2019; Taguchi and Nishinakamura, 2017; Uchimura et al., 2020). Kidney organoids have been used to explore developmental processes (Czerniecki et al., 2018; Low et al., 2019; Przepiorski et al., 2018; Taguchi et al., 2014), examine physiological activities (Berg et al., 2018; Kumar et al., 2019; Low et al., 2019), model disease (Forbes et al., 2018; Freedman et al., 2015; Hale et al., 2018; Kim et al., 2017; Low et al., 2019) and identify disease modulators (Czerniecki et al., 2018). Grafted organoids have been reported to generate a renal filtrate (Berg et al., 2018; Low et al., 2019; Xinaris et al., 2012). Despite the burden of kidney disease, only modest progress has been made in identifying effective drugs. Autosomal dominant polycystic kidney disease (ADPKD), with ~93% of the cases attributed to mutations in the PKD1 or PKD2 gene, is the most common monogenic cause of end- stage kidney disease and amongst the most common autosomal dominant gene mutations in the human population (Harris and Torres, 2018). Until recently, there has been no pharmacological intervention to help ADPKD disease patients. In 2018, the US Food and Drug Administration approved Tolvaptan, an AVPR2 inhibitory drug that slowed disease progression in a subset of ADPKD patients (Beaudoin et al., 2019; Higashihara et al., 2011; Hopp et al., 2015; Reif et al., 2011; Torres et al., 2016, 2017). AVPR2 is restricted to a subset of principal cell and principal cell-like epithelial cell types in the connecting region of the nephron and collecting system (Ransick et al., 2019a, 2019b). Broader acting drugs are needed to target both cyst initiation and cystic growth throughout the nephron and collecting system. Several groups have reported cystic growth in PKD1 and PKD2 mutant kidney organoid cultures where rare cystic outgrowths are augmented by forskolin, consistent with cAMP levels driving cystogenesis (Cruz et al., 2017; Czerniecki et al., 2018; Freedman et al., 2015; Kuraoka et 230 al., 2020). Others have failed to observe cyst formation in vitro in a different larger-scale outgrowth model (Kumar et al., 2019). To date screens have been low-throughput, relying on manually displacing organoids from a retaining extracellular gel, and focused on identifying small molecules enhancing cyst formation (Czerniecki et al., 2018). Currently, there are no reports of cyst suppressing screens that could potentially identify therapeutic small molecule candidates. Cost, scalability and reproducibility are further challenges to the wider adoption of kidney organoid models. Here, we developed, characterized and validated a simple and readily scalable, cost-effective mini-kidney organoid platform for modeling ADPKD, identifying novel compounds blocking cyst formation in both PKD1 and PKD2 mutant models. MATERIALS AND METHODS 1. Miniature kidney organoid cultures a. hPSC Maintenance Geltrex-coated plate preparation DMEM/F12 (Life Technologies, 11320-033) was aliquoted into a 50-ml conical vial and 120µl of Geltrex added to make a 1% Geltrex mix. After thorough mixing, 2ml of 1% Geltrex was pipetted into each well of a 6-well plate (or 1ml/well for a 12-well plate). The Geltrex plates were incubated at 37 o C/5% CO2 overnight before use. hPSC expansion and maintenance Two hPSC line were used in this study: H9 human embryonic stem cells (hESC) (female) from WiCell (WA09) and a genetically modified MAFB-P2A-eGFP H9 hESC line as previously described (Tran et al., 2019). hPSCs were thawed in StemFit media (Ajinomoto, ASB01-R) supplemented with 100ng/ml of FGF2 (R&D, 273-F9) and 10µM Y27632 (Tocris, 1254) on 1% Geltrex-coated plates (ThermoFisher, A1413302). On reaching 70-80% confluency (1-2 days), cells were passaged in StemFit media + 100ng/ml of FGF2 + 10µM Y27632 into a 12-well plate at a seeding density of 231 6,000 cells/well. The medium was changed 48 hours later to StemFit media + 100ng/ml of FGF2 for cell expansion and replenished every 2 days. For freezing, when wells reached 70-80% confluency each well of hPSCs was mixed with 1ml of 10% DMSO/90% fetal bovine serum (FBS) and stored in insulated styrofoam boxes at -80oC overnight before transferring to liquid nitrogen storage. b. Directed Differentiation to Generate Miniature Kidney Organoids The differentiation protocol was developed based on published protocols (Morizane and Bonventre, 2016; Morizane et al., 2015) adapted in our laboratory. Each biological replicate was generated from a distinct frozen vial of hPSCs. After thawing and growth to 70% confluency, hPSCs were dissociated using Accutase (Gibco, A1110501) and seeded on 12-well plates and cultured as above. The differentiation procedure was initiated at 60% confluency. Briefly, culture medium was supplement for 4 days with 8μM CHIR99021 (Sigma Aldrich, SML1046), followed by 3 days with 10ng/ml ActivinA (R&D, 338-AC-050), and 1 day of 10ng/ml FGF9 incubation (R&D, 273-F9). At day 8, the cells were dissociated using TrypLE dissociation enzyme (Gibco, 12563011), and 600,000 cells seeded into each well of a 12-well EZSPHERE plate (Nacalai USA, TCI-4815-903SP-50P) in 3μM CHIR and 10ng/ml FGF9. Each well generated ~400 mini-organoids and each mini-organoid comprised ~1,500 cells. On differentiation day (dd) 10, the medium was switched to Advanced RPMI 1640 (Gibco, 12633020) + 1X Glutamax (Gibco, 35050079) + 1% Penicillin-Streptomycin (Invitrogen, 15070063), denoted basal differentiation medium, with 10ng/ml FGF9. From dd13 to dd28, cultures were maintained in basal differentiation medium. c. Validation of PKD1 and PKD2 mutant alleles Single cell-derived clones of the PKD1 and PKD2 targeted hESC lines were expanded and genomic DNA was extracted using the DNeasy Blood & Tissue Kit (Qiagen, 69504). CRISPR-Cas9 targeted regions were amplified using the Q5 High-Fidelity 2X Master Mix (PKD1: primers: 5’- TCCAGATGGGGCAGAGCCTG-3’ and 5’-CCTCCTTCCTCCTGAGACTC-3’ and PKD2: 5’- CTGTGTTCCAGTGACCTACG-3’, and 5’-AAGGCACAGGCAAAGTTCTCA-3’), and cloned into the pCR™- 232 Blunt II-TOPO™ vector using the Zero BluntTM TOPOTM PCR Cloning Kit (Invitrogen K280002). The inserted TOPO plasmids were expanded and Sanger sequencing performed to validate CRISPR mutations on each allele. d. Embedding of Miniature Kidney Organoids for Observation and Phenotypic Drug Screening Preparation of methycellulose plates To prepare cultures for fixed organoid tracking over time, 15g of methylcellulose powder (Sigma-Aldrich, M0512) was autoclaved in a 500-ml Erlenmeyer flask. The autoclaved methylcellulose was dissolved in 60°C 450 ml of Advanced RPMI 1640 Medium (Gibco, 12633020). Fifty milliliters of Advanced RPMI 1640 Medium + 1X Glutamax (Gibco, 35050079) and 1% Penicillin-Streptomycin (Invitrogen, 15070063) was then added at room temperature to a final volume of 500ml and a stock concentration of 30 µg/ml methylcellulose. The final stock solution was cleared by centrifugation at 4000 x g for 2 hours. For mini-organoid culture and imaging, 34 µl of the 30 µg/ml methylcellulose stock solution was added to 136 µl of basal differentiation media to each well of a 96-well plate (brand) to achieve the final concentration of 6 µg/ml methylcellulose optimal for mini-organoid embedding. Mini-organoid embedding for spheroid assay At dd13, miniature kidney organoids were transferred from the EZSPHERE plates to a sterile 35-mm dish by gentle pipetting with wide-bore P1000 tips. Under a dissecting microscope, 10-12 mini-organoids were picked up in 10µl of media were picked up and released into a well of the methylcellulose plate. e. Protein kinase inhibitor PKD screening of mini-kidney organoid cultures Protein kinase inhibitor library and additional small molecule compounds: 233 Two hundred and fourty-seven annotated small molecule protein kinase inhibitory compounds were screened at 1 µM in the primary screen. Purchased compounds represented the following commercial libraries: EMD-Protein Kinase Inhibitor 2 (EMD Calbiochem®, Catalog no. 539745), EMD-Protein Kinase Inhibitor 3 (EMD Calbiochem®, Catalog no. 539746), EMD-Protein Kinase Inhibitor 4 (EMD Calbiochem®, Catalog no. 539747). Primary screen: Protein kinase inhibitors were diluted in DMSO to generate 10 µM stocks. At dd14, 20 µl of each diluted compound or DMSO was added to a methycellulose well with embedded organoids (180µl of media) to achieve a final concentration of 1 µM. The plates were loaded onto an ImageXpress Micro System for live imaging throughout the screening period. The imaging was performed using the “Standard” algorithm, at 4X magnification, 2 camera binning, with laser-based and image-based focusing enabled, and well-to-well autofocus was set to “focus on plate bottom and well bottom”. To avoid observer bias, we performed blinded experiments in which the compound maps were not revealed to the researcher processing the ImageXpress output until all analyses were completed. Scoring phenotypes: Initially, we screened the PKD2-/- line with the full compound libraries. We categorized the outcomes of compound treatments into 3 groups: 1) “no-hit” wells were cyst formation and growth appeared normal at dd20 (cyst area ≥30% organoid size), 2) “hit” wells in which no cyst formation was observed but epithelial structures remained healthy, and 3) “non-specific hit” (NS hit) wells were no cyst formation occurred but there was clear evidence of cell death and general growth retardation in the culture. Secondary screen: 234 Compounds scored as “hits” in the primary PKD2-/- focused screen were selected for validation in a secondary PKD1-/- and PKD2-/- mutant organoid screen testing a concentration range of each small molecule along with “no hit” and “NS-hit” controls. At dd14, 20 µl of each diluted compound stock or DMSO was added to a methycellulose well with embedded organoids (180 µl) to achieve a final concentration of 0.1, 1 or 10 µM (with the exception of UCN-01, which was examined at 0.2, 2 or 20 µM). The plates were imaged for 7 days using the ImageXpress Micro System as described above. Compounds that inhibit cyst formation in both PKD1-/- and PKD2-/- mini-organoids were classified as final “hits”. 2. Characterization of the mini-organoid system a. Single-cell RNA-seq analysis About 300 miniature organoids were collected at dd8, dd10, dd14, dd16 and dd28 for scRNA-seq. The organoids were dissociated using 7.5 mg/ml Bacillus licheniformis cold active protease (Creative Enzymes, NATE-0633) mixed with 10 mg/ml collagenase type 2 (Worthington, #LS00417) and 125 U/ml DNase I (Worthington, #LS002058) in DPBS (150 µl) at 12oC for 20 min. The digestion mix was mixed twenty times with P-1000 wide-bore pipette tips. The dissociation reaction was terminated by mixing with 150 µl of 20% fetal bovine serum in DPBS. The cells were filtered through a pre-wetted 40-µm strainer (Falcon), and 1 ml of DPBS was used to wash cells off the strainer. The 1.3 ml of dissociated cell mix was combined with 3 ml of AutoMACS Running Buffer (Miltenyl Biotec, 130-091-221) and cells were briefly pelleted at 1250 rpm at 4oC. The cell pellet was then resuspended in 350 µl of AutoMACS Running Buffer, with 14 µM DAPI and 5 µM DRAQ5 added freshly. Single live cells (DAPI- and DRAQ5+) were selected by fluorescence-activated cell sorting (FACS) and single cell profiling with a 10x Genomics Chromium Single Cell 3’ GEM, Library & Gel Bead Kit (10X Genomics, PN-1000075). After recovery from the emulsion, cDNA was cleaned-up and amplified by PCR, examined on a 4200 Tape station (Agilent) for yield assessment, and then processed into barcoded library for Illumina sequencing. Paired-end sequencing on the Illumina 235 HiSeq 4000 platform was performed using the HiSeq 3000/4000 SBS PE clustering kit (PE-410- 001) and 150 cycle flow cell (FC-410-1002). From fastq files, quality control, alignment to reference genome (hg38) and generation of count tables of the five libraries were done using CellRanger 3.1 (10X Genomics). The Seurat 3.0 package was used for scRNA-seq analyses (Stuart et al., 2019). The five datasets were merged using the merge function. To filter out low-quality cells, we kept cells that had more than 500 and fewer than 5,500 features, fewer than 20,000 RNA counts, and less than 35% mitochondrial gene content. The merged data was log-normalized using the NormalizeData function. To scale and center genes in the dataset, the ScaleData function was applied. 2000 variable genes were determined using the FindVariableFeatures function. The RunPCA was applied to calculate principle components (PCs), and 40 PCs were used to determine neighbor cells and cluster assignment (using the FindNeighbors and FindClusters functions). The UMAP reduction was calculated using RunUMAP to determine UMAP embedding. Differentially expressed genes of each cluster were found using the FindAllMarkers function. The in vivo datasets of human week 17 fetal kidney from our 2019 study (Tran et al., 2019) (GSE124472) were used for comparison with the scRNA-seq profiles of the in vitro derived nephrogenic cell subset. After the nephrogenic cells were subset from the week 17 datasets, the in vitro and in vivo nephrogenic cells were merged and integrated using scTransform. The merged dataset was first split based on in vitro or in vivo origin of the cells. scTransform was performed on each origin using 10,000 variable features. To prepare for integration, integration features and anchors were determined using SelectIntegrationFeatures, PrepSCTIntegration and FindIntegrationAnchors and 20 PCs. The two origins were then integrated using IntegrateData. RunPCA was then used to calculate PCs, and 40 PCs were used for neighbor and cluster finding as described above. Cell embedding was presented as a UMAP reduction output (Becht et al., 2019). 236 “RNA” was used as the default assay (DefaultAssay function), and the integrated dataset was re- normalized using NormalizeData before assaying gene expression levels. Similarly, the interstitial cell populations were extracted from the week 17 human fetal kidney dataset and merged with the mini-organoid dataset. The in vitro and in vivo interstitial cells were merged and integrated using scTransform as described above (using all 26857 variable features). To compare the transcriptomic profiles of in vitro and in vivo nephron segment cells, the following clusters were extracted from the integrated in vivo/in vitro nephrogenic cell dataset: clusters 1, 6 and 20 for podocyte, cluster 13 for proximal tubule, and clusters 14 and 19 for putative medial/distal nephron precursor. Each subset was integrated using scTransform as described above (using all 26857 variable features). “RNA” was used as the default assay (DefaultAssay function), and the integrated datasets were re-normalized using NormalizeData before examination of gene expression levels. Differential gene test was performed using FindAllMarkers to look for genes highly expressed in the in vitro or the in vivo cells. To account for batch differences, these gene lists were compared with differentially expressed gene list from comparing the in vitro and in vivo interstitial cells, and genes that were present in all four lists (interstitium, podocyte, proximal tubule, and medial/distal nephron precursor) were considered “background differences”. Cell-type specific differences were presented in Supplementay Table 1, and relative expression levels of representative differentially expressed genes were highlighted in dotplots in Figure S7.6.3G (using DotPlot). b. Histology Mini-organoids were fix in 4% paraformaldehyde for 10 minutes at 4oC temperature and were washed three times in 1XPBS. Samples were then transferred to an embedding mold with 15% sucrose/7.5% gelatin in PBS and incubated in the gelatin solution at 37°C until the organoids sink. 237 The mini-organoids in gelatin solution was then frozen in a dry ice/ethanol slurry. Samples were stored at -80°C until cryosectioning and processing. c. Immunohistochemistry and in situ hybridization Frozen sections were warmed to room temperature for 10 minutes before the staining procedure. Citrate Buffer pH 6.0 (Sigma) was used for antigen retrieval in a pressure cooker. The slides were then washed with water and air dried for 5 min. 1.5% Seablock (ThermoFisher) in PBS + 0.25%TritonX block buffer was applied on the tissue for 1 hour at room temperature for blocking. The slides were then incubated with primary antibody mixture (diluted in block buffer) at 4oC overnight. Primary antibodies used in the study are listed as follow: WT1 (abcam, ab89901, 1:5000), JAG1 (R&D, AF599, 1:300), LAMB1 (Santa Cruz, sc-33709, 1:50), SOX9 (abcam, ab185230, 1:1000), HNF4A (R&D, MAB4605, 1:500), CUBN (R&D, AF3700, 1:500), SLC12A1 (Sigma, HPA018107, 1:500), LTL (Vector Laboratories, FL-1321, 1:300), SLC3A1 (Sigma, HPA038360, 1:500), NPHS1 (abcam, ab136927, 1:5000), POU3F3 (ThermoFisher, PA5-64311, 1:500), MAFB (R&D, MAB3810, 1:500), PAX8 (abcam, ab189249, 1:1000), CDH1(Biosciences, 610182, 1:300), PAX2 (R&D, AF3364, 1:500), GATA3 (R&D, AF2605, 1:300), ACE2 (R&D, AF933, 1:500). We used secondary antibodies conjugated with AlexaFluor 488, 555, 594, and 647 (diluted to 1:1000 in block buffer) purchased from Molecular Probes. To stain the nuclei, slides were treated with 1 mg/ml Hoechst 33342 (Molecular Probes) in PBS for 5 min. ProLong Gold Antifade Reagent (Life technologies) was applied on the tissue for mounting, and images were acquired at 40X using the Leica SP8 confocal microscope. d. RNA extraction, cDNA synthesis and quantitative polymerase chain reaction About 200 mini-organoids were collected for transcriptional analyses for each time point. The RNeasy Micro Kit (Qiagen, 74004) was used for RNA extraction following the manufacturer’s protocol. cDNA was synthesized from 200 µg of RNA for each sample using the SuperScript IV VILO Master Mix with ezDNase enzyme (Invitrogen, 11766050). 238 Quantitative polymerase chain reaction (qPCR) was performed using the Taqman Fast Advanced Master Mix (ThermoFisher, 444557) following the manufacturer’s instruction on the ViiA 7 Real-Time PCR System (ThermoFisher). The following probes from ThermoFisher were used for transcriptional analyses: WT1 (Hs01103751_m1), MAFB (Hs00534343_4.2), PAX2 (Hs01057416_m1), HNF4A (Hs00230853_m1), GATA3 (Hs00231122_m1), SLC3A1 (Hs00942976_m1), SLC12A1 (Hs00165731_m1) and SLC12A3 (Hs01027568_m1). e. Western Blot To prepare protein lysate samples, miniature organoids and control samples were suspended and homogenized in lysis buffer (RIPA buffer (Pierce, 89901) supplemented with 1 mM benzamidine hydrochloride (TCI America, TCB0013), 1X protease inhibitor cocktail (Cell signaling, 5871), 100 μM PMSF (Sigma-Aldrich, 11359061001), and protease inhibitor cocktail tablets (one tablet/10ml of buffer) (Sigma, 11836170001)), and left on ice for 30mins. Next, samples were centrifuged for 15 min at 16,000×g at 4°C, and supernatants were transferred to low protein binding tubes (Eppendorf). Total protein concentrations were measured using the BCA protein assay kit (Pierce, 87003-294), according to manufacturer’s instructions. Protein lysates were flash frozen and stored at -80°C. Protein lysates were separated by SDS-polyacrylamide gel electrophoresis (SDS-PAGE). 4– 15% Mini-PROTEAN™ TGX Stain-Free™ Protein Gels (Bio-Rad, 4568086) were used. After electrophoresis, protein lysates were electroblotted to methanol activated Low-Fluorescence PVDF Transfer Membranes (Bio-Rad, IPFL20200). Membranes were then dried at 37°C for 5 minutes and then re-activated with methanol. Blots were stained with Li-Cor’s Revert-700 Total Protein Stain (Li- Cor, 926-11010) for normalization and imaged using a Li-Cor Odyssey Clx. In the subsequent incubation and washing steps, blots were placed on an orbital shaker. Blots were then de-stained following the manufacturer’ instruction and were incubated in block buffer (Li-Cor Intercept block, 13 927-60001) for 1 hour at room temperature. Blots were then transferred to a primary antibody mix 239 (in block buffer supplemented with 0.1% Tween20) and were incubated overnight at 4°C. The following primary antibodies were used: PKD1 (Kerafast, Clone E8-8C3C10, catalog number EMD303)(Yu et al., 2007), PKD2 (Santa Cruz, sc-28331). On the following day, blots were washed four times in TBS-T (5 min each) at room temperature, and then incubated in secondary antibody (1:10,000) in block buffer with 0.1% Tween20 and 0.1% SDS for 1 hour at room temperature. The following secondary antibodies were used: IRDye® 800CW Goat anti-Rat IgG (H + L) (Li-Cor, 926- 32219) for PKD1; IRDye® 680RD Donkey anti-Mouse IgG (H + L) (Li-Cor, 926-68072) for PKD2. Blots were then washed twice with TBS-T for 5 minutes each at room temperature, followed by two 5- minute TBS washes at room temperature. Blots were imaged using the Li-Cor Odyssey Clx system. 3. Vascularization of miniature kidney organoids All surgical procedures were carried out with appropriate oversight and compliance following guidelines after institutional review by USC’s Institutional Animal Care and Use Committee (IACUC). The procedure was adapted from (Yoshimura et al., 2017). Week 8–12 NOD.CB17-Prkdc<SCID>/J mice were anesthetized with Ketamine/Xylazine. The surgery site on the dorsal flank was shaved and swabbed with Proviodine/alcohol. An 8-10 mm incision was made in the flank and the fascia was incised before the kidney was externalized. The kidney capsule was kept moist with sterile saline during the procedure. A small incision was made in the outer membrane of the renal capsule at the caudal end, using a sharp 24g needle and the sub capsular space is flushed with 1ml of basal differentiation media using a blunted 24g needle 30g needle (B30-50, Strategic Applications, Inc.) attached to a 1 ml syringe. Two agarose rods (2mm long, 0.5mm diameter) were pushed into the sub capsular space in the shape of an open V using forceps. A 20g indwelling needle (SURFLO® PTFE I.V. Catheter needle, VWR, TESR-OX2025CA) attached to a 1 ml syringe and draw up 3-4 dd13-14 organoids basal differentiation media into the needle. The indwelling needle was inserted under the renal capsule to place organoids between the agarose rods. The capsule incision was cauterized, 240 and the kidney was replaced into the retroperitoneum. The muscle layer was sutured, and the skin was closed with wound clips. 4. Quantification and statistical analysis Details of sample size were provided in the Method Details section for each experiment. Wilcoxon Rank Sum test was performed, and p-values were presented in Figure 7.4D. Kruskal-Wallis test was performed, and p-values were presented in Figures S7.6D-I. RESULTS Generation of miniature kidney organoids with nephron-like structures To achieve a reproducible, large-scale production of 3-D kidney organoids, we utilized commercially available EZSPHERE 12-well plates, which are constructed using laser-based microfabrication to contain uniform microwells of 800-µm diameter and 400-µm depth (Sato et al., 2016). Each well contains 420 microwells; hence, each plate can generate over 4,000 mini- organoids. At differentiation day (dd8), cells were dissociated into single cells, and 600,000 cells were reseeded in each well of the EZSPHERE plate to produce about 400 miniature 3-D aggregates with 1,500 cells per aggregate (Figure 7.1A). We used a well-validated MAFB-P2A-eGFP H9 hESC line (Tran et al., 2019) to visualize the formation of podocyte-like cells in the mini-organoids, and observed the emergence of eGFP+ cells at day 14 of differentiation (Figure 7.1B), agreeing with our previous observation of 100,000-cell kidney organoids generated in 96-well plates (referred to as “maxi-organoids” herein) (Tran et al., 2019). At dd25, each miniature organoid comprised 1-2 eGFP+ clusters, suggesting 1-2 nephron-like structures formed in each organoid (Figure 7.1B). A number of recent studies have provided a good understanding of human nephrogenesis and a foundation for characterizing mini-organoid development (Figures 7.2A-F) (Cao et al., 2020; Hochane et al., 2019; Kim et al., 2019; Lindström et al., 2018a, 2018b, 2018c, 2018d; Menon et al., 2018; Tran et al., 2019). Transcriptional profiling using qPCR highlighted robust upregulation of 241 nephrogenic signatures (including WT1, PAX2, MAFB, HNF4A, GATA3, SLC3A1, SLC12A1 and SLC12A3) over the differentiation time course (Figure S7.3A). A detailed immunofluorescence analysis of nephron segmentation signatures validated these findings. On dd13, we documented the presence of CDH1+ epithelial structures with WT1-high and WT1-low domains, reminiscent of polarization in the early renal vesicle in vivo (Figure 7.1C). Dd13 also marked the emergence of cells with signatures of proximal nephron segment precursors (MAFB+ or WT1+), medial precursors (MAFB-/SOX9-/JAG1+, or HNF4A+), and distal nephron precursors (SOX9+ or GATA3+) (Figures 7.1C and 1D). At dd14 and dd16, the segmentation of developing nephron-like structures was more apparent with serially ordered proximal, medial and distal precursor domains (Figures 7.1C, 7.1D and 7.1E). Additionally, we also detected the presence of WT1+HNF4A+, HNF4A+POU3F3+ and GATA3+POU3F3+ nephron subdomains in the dd25 mini-organoids (Figure 7.2G). Though these segments have not been fate mapped in the mammalian kidney, HNF4A+ cells are predicted to give rise to proximal tubule segments, and GATA3+ cells to distal nephron structures (Lindström et al., 2020). Expression of genes associated with segmental functions were also detected at dd25: MAFB+ podocyte-like cell clusters were adjacent to a CUBN+ proximal tubule-like segment, which connected with an SLC12A1+ ascending distal tubule-like segment (Figure 7.1F). Though RNA-seq data showed weak expression of the distal convoluted tubule gene SLC12A3 (Figure S7.5A), SLC12A3 could not be detected by immunofluorescence. To assess the uniformity of development in an individual mini-organoid, quantitative PCR was performed on 20 individual mini-organoids collected at dd28 from 2 independent batches of differentiation (10 individual organoids/batch). Each mini-organoid showed a strong transcriptional signature for nephron segmentation, including MAFB, SLC3A1, SLC12A1 and GATA3 (Figure 7.1G). Although mini-organoids collectively lacked the stereotyped morphogenesis described in human nephrogenesis (Lindström et al., 2020), polarization and patterning generated segmented early nephron-like structures arise with uniformity in the miniature kidney organoids. 242 Developmental trajectories of nephron-like cell types To further examine the emergence of nephron-like cells in mini-organoids, we applied single- cell RNA-sequencing (scRNA-seq) technology to capture single-cell transcriptomic profiles of organoids at dd8, dd10, dd14, dd16 and d28 (Figures 7.2A, 7.3A and 7.3B). After filtering low quality cells and clustering in Seurat version 3, cluster identities were assigned through the expression of well-established cell markers (Supplementay Table 1, Figures 7.3C and 7.3E). Strong nephrogenic signatures were identified in a number of clusters (clusters 1, 3, 4, 5, 8, 9, 10, 19, 27, 28 and 29). In addition, and in agreement with single cell analysis from others and our group of larger kidney organoids (Combes et al., 2019; Kumar et al., 2019; Tran et al., 2019; Wu et al., 2018), we observed a variety of other cell types including: interstitial cells expressing PDGFRA but not nephrogenic genes (clusters 2, 11, 12, 22, 23 and 24), SOX17+ CDH5+ endothelial cells (cluster 31), NEUROD1 and NEUROG1 expressing neuron-like cells (clusters 13, 14, 17 and 25), SOX10+ and FOXD3+ neural crest-like cells (cluster 6, 7, 18, 20 and 21), TNNI1+ ACTC1+ muscle-like cells (cluster 16), as well as several unidentified cell types (cluster 0, 15 and 26) (Supplementay Table 1, Figure 7.3C). To focus of the nephrogenic component, we subset 14,566 cells from the nephrogenic clusters for further analyses (Figures 7.3C and 7.3E). Re-clustering of this sub-population identified cells with strong transcriptional characteristics of induced nephron progenitors, early and late podocytes, medial and distal precursors, and proximal tubule cells (Figures 7.2B, 7.2C). When examining the origins contributing to the various nephrogenic identities, we noticed induced nephron progenitor-like clusters were dominantly composed of day 8 cells, while day 10, 14 and 16 cells contributed to nephron segment precursors (Figures 7.3F and 7.3G). Late podocyte-like cells and proximal tubule-like cells were detected in day 28 mini-organoids and medial/distal precursor cells were also observed in organoids of this late timepoint. 243 Consistent with a nephron segmental patterning, mini-organoid nephrogenic lineage cells expressed transcription factor genes shown to be essential for mouse nephron segmentation (Basta et al., 2014; Berry et al., 2015; Grote et al., 2006; Guo et al., 2004; Hartwig et al., 2010; Kann et al., 2015; Kobayashi et al., 2008; Moriguchi et al., 2006; Naiman et al., 2017; Park et al., 2012; Sadl et al., 2002; Self et al., 2006; Xu et al., 1999, 2003), which are also known to be present in early nephron structures in the human kidney (Lindström et al., 2018c, 2018d). Thus, it is likely core nephrogenic programs were activated in the in vitro system and underlie the specification and patterning of nephron-like cell types (Figure S7.4A). To compare the in vitro derived cells with the human kidney, we subset 4377 nephrogenic cells from week 17 human fetal kidney datasets (Tran et al., 2019) and merged the in vivo with the in vitro derived nephrogenic cells (Figure 7.4D). Cluster identification validated the presence of nephrogenic cell types (Figure 7.2F and Supplementay Table 1). Nephron progenitor, nephron segment precursor, late podocyte and proximal tubule identities were composed of both human fetal kidney and cells of in vitro origin, highlighting similarities between the in vivo and in vitro derived cells. Genes displaying a high correlation with MAFB, HNF4A, SLC12A1 and GATA3 in the mini- organoids emphasized signatures of podocyte (i.e. PODXL, PTPRO, NPHS2, TCF21, CLIC5, etc.), proximal tubule (i.e. CUBN, LRP2, HNF4G, SLC3A1, SLC34A1, etc.), loop of Henle (i.e. TFCP2L1, IRX1, DEFB1, ERBB4, MAL, etc.), and distal precursor (i.e. CALB1, MECOM, MAL, ALDH1A1, EMX2, etc.) cell identities (Supplementay Table 1). Importantly, differences were observed in transcriptional profiles of in vitro and in vivo derived cells. Clusters 10 and 16 (proliferative in vitro mesenchyme) and cluster 20 (in vitro podocytes) were predominantly composed of organoid cells. Furthermore, while core transcription factors driving nephrogenesis marked the segmentation of in vitro nephron-like structures (Figure S7.3G), incomplete maturation was documented in an unbiased comparison with the human fetal kidney (Figure S7.4B and Supplementay Table 1). For example, in vitro derived podocytes exhibited 244 lower expression of late-activated genes encoding structural proteins or extra cellular matrix components as reported in conventional kidney organoids (COL4A3, COL4A4, TNNI1 and TNNT2; Tran et al., 2019; Yoshimura et al., 2019, and generally, solute carriers and transporters mediating key kidney functions were expressed at lower levels in organoid-derived cell types (SLC5A12, SLC22A6, SLC22A8, SLC12A1 and SLC12A3) (Figure S7.4B and Supplementay Table 1). We also compared cellular diversity of the interstitial cell component. Nephron and interstitial progenitors likely share a common origin (Mugford et al., 2008) and may play a role in organizing nephron structures (Das et al., 2013; England et al., 2020). Interstitial cells extracted from the week 17 human fetal kidney data (expressing MEIS1, PDGFRA and/or PDGFRB) (Tran et al., 2019) were subjected to cluster identification (Figures S7.3A and S7.3B). Together with MEIS1, PDGFRA and PDGFRB, differential expression of FAM162B, LUM, KISS1, REN, TYMS, MEF2C, MYH1, TOP2A, COL8A1, FOXD1, CADM1, C7, POSTN, TAGLN, SHISA3, DKK1, USP53, GATA3, CCL2, IRF1, TMX4, and GRID2 highlighted the cellular diversity and replicative state of interstitial cells in the developing human kidney. Merging these data with the mini-organoid scRNA-seq-derived interstitial subset (MEIS1, PDGFRA and/or PDGFRB expressing clusters 2, 11, 12, 15, 22, 23 and 24), highlighted an absence in vitro of specific interstitial subtypes: COL8A1+/FOXD1+ (cluster 12), CCL2+/IRF1+ (cluster 14), and TMX4+/GRID2+ (cluster 16) and a reduced representation of USP53/GATA3+ (cluster 10) and MEF2C+/MYH11+ (cluster 13) cell types (Figures S7.3C-F). These analyses suggested a less complex interstitial component in the in vitro system compared to the human fetal kidney. Vascularization of miniature kidney organoids Maxi organoid models have been shown to recruit vasculature and undergo extended development on grafting to the adult kidney. To examine the ability of miniature kidney organoids to recruit the vasculature, we transplanted the organoids derived from MAFB-P2A-eGFP hESCs under the kidney capsule of NOD/SCID mice (Figure 7.6A). Twenty-days post-transplant, MAFB+ in vitro 245 derived podocytes (also stained positive for human nuclei (HuNu+)) were surrounded by HuNu- VEGFR2+ mouse endothelial cells. Vascularized podocytes expressed PODXL and ANXA1, indicating mature podocyte-like signatures (Figure 7.6C) (Tran et al., 2019). Proximal tubule-like structures were also detected in transplanted mini-organoids (HNF4A+ CUBN+ LRP2+ ACE2+) connected to SLC12A1+ distal tubule-like segment (Figures 7.3E, 7.3F and 7.3G). Rare distal convoluted tubule- like cells were also observed in the transplanted mini-organoids as indicated by SLC12A3 immunofluorescence. Thus, mini-organoids resemble maxi-organoid transplants showing vascular recruitment, segmented nephron signatures and the additional maturation of nephron cell types. Modeling polycystic kidney diseases using miniature kidney organoids The presence of nephron-like structures in mini kidney organoids laid the foundation for the use of the in vitro system to model kidney diseases. To explore the utility of the mini-organoids in modeling polycystic kidney disease (PKD), we generated mutations in the two key genes associated with almost all ADPKD, PKD1 and PKD2 (Bergmann et al., 2018; Harris and Torres, 2018). Both mutations where generated through CRISPR-Cas9 directed double strand-DNA cleavage and non- homologous end joining repair on the H9 hESC line used in mini-organoid characterization (Figure 7.4A). Though PKD2 mutations were introduced into the wildtype H9 hESC line, PKD1 was targeted in a derivative that underwent several additional reporter gene insertions beyond the MAFB reporter described above 5-T PKD1-/-H9 hESC line) (Figure 7.4A). Acknowledging the genetic complexity of the PKD1 gene, which has six known highly homologous pseudogenes (Bogdanova et al., 2001), we designed a guide RNA specific to the PKD1 gene sequence but not the pseudogenes (Figure S7.4B). Deletion mutations were characterized by Sanger sequencing identifying deletions predicted to generate a loss of function for both alleles of PKD1 (distinguishing the functional allele from pseudogenes) and PKD2 (Figures S7.4B and S7.4C). As expected, a wild-type PKD2 protein (PC2) was present in wildtype, and absent from PKD2-/- mutant, mini-organoids (Figure S7.4D). PKD1 encodes a 462 kDa-primary polypeptide (PC2) which was present in positive control HEK cells but 246 not in either wild-type or mutant kidney organoids (arrowhead in Figure S7.4D). Consistent with earlier findings (Yu et al. 2007), the PKD1 antibody also detects 140 kDa PKD1 cleavage product in HEK cells overexpressing PKD1 (arrow in Figure S7.4D), and this PKD1 product was only present in wild-type mini-organoids. Thus, both PKD1-/- and PKD2-/- mutant hPSC clones lost respective PKD protein functions. To determine whether PKD mutant hESC lines can replicate cystic outgrowth and enable PKD disease modelling, PKD1-/- and PKD2-/- hESCs were differentiated alongside the wild-type hESC lines. Transcriptional profiling and qPCR confirmed PKD mutant mini-organoids underwent a similar differentiation trajectory to wild-type hESCs (Figures S7.5B-D). However, we also observed robust cyst formation by both PKD1 and PKD2 mutant mini-organoids (Figure 7.4B-C). Cysts formed in 25- 30% of PKD2 mutant and 50-60% PKD1 mutant mini-organoids from dd15-20. When the seeding density of PKD2 mutant organoids was increased from 1,500 cells to 5,000 or 7,000 cells, cystogenesis was delayed and fewer organoids developed cysts (Figures S7.6A and S7.6B). These cystic structures expanded continuously and reached ~1 cm diameter after 3 months of culture (Figure S7.4G). Utilizing an optimal seeding density of ~1,500 cells/micro-well, we explored cyst formation in more depth in wild type, PKD1 and PKD2 mutant organoids cultured in methylcellulose supplemented media. The methylcellulose provided a gel-like support, retaining organoids and facilitating automated imaging of cyst progression (Figure 7.5A). Ninety-nine PKD1-/- organoids and 32 PKD2-/- organoids were tracked together with their wildtype counterparts from dd14 to dd20. At dd14, PKD1-/- and PKD2-/- organoids formed protrusions that enlarged into epithelial cysts recognizable as early as dd15; some cysts expanded to 4-fold the area of wildtype organoids by dd 20 (Figure 7.4D). Importantly, epithelial out-pocketing of nephron epithelia was observed at a lower frequency in H9 ESC controls; however, these did not enlarge into cystic structures (Figures 7.4B and 7.4C). Antibody profiling showed cystic epithelia displayed a complex profile with contributions from 247 proximal (JAG1+, HNF4A+ or SLC3A1+) and distal nephron segments (SOX9+ or POU3F3+) (Figures 7.4E and S7.4F). Phenotypic screening to identify protein kinase inhibitors inhibiting cyst initiation With the advantage of mass production of miniature organoids, we screened small molecule protein kinase inhibitor (PKI) libraries to identify inhibitors of cyst initiation (Figure 7.5A). PKIs can provide broad insight into signaling pathway activities which may uncover novel mechanisms or avenues for therapeutic approaches beyond the primary PKI hit. Cyst formation was initially calibrated using vehicle (DMSO-) treated PKD1-/- (n=933) and PKD2-/- (n=1241) mutant organoids. We performed automated bright-field imaging of each organoid daily from dd14-20. At dd20, 52.3% of PKD1-/- and 25.3% of PKD2-/- organoids formed cysts (Figure 7.5B). Positive Z-scores at dd20 for both the PKD1-/- and PKD2-/- lines (0.40 and 0.37 respectively) demonstrated that positive and negative outcomes could be determined with confidence (Zhang et al., 1999) (Figure S7.6C). We therefore launched a series of screens to identify PKIs impeding cyst initiation (summarized in Figure 7.5C). The primary screen was performed with a library of 247 PKIs which was assembled by combining the EMD Protein Kinase Inhibitor 2, 3 and 4 collections using a single dose of 1µM focusing on PKD2-/- organoids (Supplementay Table 2). Approximately 12-15 organoids were screened per well scoring cyst formation within 9 wells on three separate plates for each compound, over a 6-day period (dd14-20). Plate set up and assessment of outcomes were blinded to remove operator bias in scoring the data. Screen outcomes were categorized into three groups: 1) “negative hits” were defined as wells with continued cyst formation, 2) “positive hits” wells were those without cyst formation but with the organoids continuing growth and development, 3) “non-specific hits” (NS hits) were wells with no visible cyst formation but evidence of general growth retardation or cell death (Figure S7.6J and Supplementay Movies 1, 2 and 3). To increase the stringency of the screen, only compounds identified as “positive hits” in all 9 wells for each compound were considered true 248 “hits” and selected for a secondary screen. Among the 247 initial screen compounds, 11 compounds were identified as NS hits, 9 as positive hits (Supplementay Table 2). Hits and various controls (Supplementay Table 2) underwent a similarly structured secondary screen on both PKD1-/- and PKD2-/- organoids examining three different compound concentrations: 0.1, 1 and 10 µM. For controls, we included Tolvaptan, an inhibitor of AVPR2 and the first FDA approved pharmacological treatment for ADPKD, and two compounds shown to inhibit cyst formation in ADPKD mouse models: Carfilzomib, a proteasome inhibitor and Celastrol, a pentacyclic triterpene (Booij et al., 2019; Chang et al., 2018; Fedeles et al., 2011). Importantly, AVPR2 is activated in differentiated cells of the connecting segment and collecting duct that are absent from kidney organoids, consistent with our scRNA-seq analysis (Beaudoin et al., 2019; Higashihara et al., 2011; Hopp et al., 2015; Reif et al., 2011; Torres et al., 2016, 2017) Thus, Tolvaptan was predicted to have no inhibitory activity in our assay. Carfilzomib and celastrol, but not Tolvaptan, scored as positive hits in the secondary screening assay (Figure 7.5D), further underscoring the validity of the mini-organoid model for drug screening. Carlfilzomib inhibited cyst formation at all concentrations evaluated in PKD2-/- mini- organoids, but only at the highest concentration in PKD1-/- mini-organoids. For compounds identified in the primary PKD2-/- screen, the protein kinase C pathway inhibitors UCN-01 and UCN- 02 showed variable results in PKD1/- and PKD2-/- cyst inhibition, whereas compounds QNZ and IKK inhibitor VII, potential NF-ĸB pathway modulators (see Discussion); (Tobe et al., 2003; Waelchli et al., 2006), inhibited both PKD1-/- and PKD2-/- cyst formation (Figure 7.5D). Of note, QNZ prevented cyst formation in both PKD1 and PKD2 mutants at all doses evaluated including the lowest concentration (0.1 µM), highlighting QNZ’s inhibitory activity in the screening platform. DISCUSSION Recognizing the need for a scalable system to generate kidney organoids for developmental studies and translational application, we developed a culture model that provides a good solution to 249 generating tens of thousands of relatively homogenous miniature human kidney organoids, of a size and cellular complexity well suited for screening purposes. While a detailed developmental analysis of mini-organoid programs shows morphologically distinct structures from those observed the in vivo nephrogenic program, our analyses point to similarities in the patterning processes and cellular outcomes. As with all reports of kidney organoid systems, eliminating unwanted cell types and normalizing programs for developmentally and functionally interconnected cell types (vascular, interstitial and collecting system) will further improve the kidney modelling capability. Utilizing the mini-organoid model, we developed a robust platform to study cyst initiation and expansion in ADPKD. Mini-organoids carrying homozygous LOF in either PKD1 or PKD2 formed reproducible and robust cystic structures, with a higher percentage of organoids forming cysts quantitatively greater with PKD1-/- compared to PKD2-/- (Figure 7.5B). As cysts continue to grow to centimeter-sized structures and detach from the parental organoid body, the platform also provides a model for studying aspects of late-stage cystic expansion. We are currently developing additional approaches to screen cysts during this phase. Previous studies have documented cyst formation promoted by small molecule simulators of cAMP production in alternative PKD1 and PKD2 PSC-generated organoid models (Czerniecki et al., 2018). In the absence of stimulation, cysts have been reported in the aforementioned organoid model, albeit at low frequency (~5%). Here, the requirement for manual extraction of cystic forming organoids from an adherent matrix encased culture further complicates high throughput screening (Czerniecki et al., 2018). Cyst formation is clearly assay dependent as others have not observed cyst formation in a large kidney organoid culture model (Kumar et al., 2019). In our model, the number of cells in the starting epithelial aggregate influences both the timing and frequency of cyst formation. Importantly, the fraction of cyst-forming mini-organoids is improved from 25-50% to ~80% by a preselection at dd14 (Figure S7.6A). Coupling machine learning with an organoid-sized sorting 250 system (Pulak, 2006) could generate a highly efficient, automated platform for future large-scale screening. Previous kidney organoid screens identified compounds enhancing cystogenesis: forskolin, which elevates intracellular levels cAMP levels, and blebbistatin, which inhibits myosin ATPase activity (Czerniecki et al., 2018; Low et al., 2019). In the mini-organoid model, neither small molecule significantly increased cyst formation or cyst growth in the limited period of cystogenesis examined in this study (Figures S7.6D-I). However, screening protein kinase inhibitor libraries for compound suppressing cystogenesis in PKD1-/- and PKD2-/- mini-organoids identified UCN-01, UCN-02, IKK inhibitor VII and QNZ as novel compounds inhibiting cyst formation in the mini-organoid assay. UCN-01 and UCN-02 are derivatives of PKC inhibitor Staurosporine (Karaman et al., 2008; Rüegg and Gillian, 1989; Takahashi et al., 1989). (Karaman et al., 2008; Rüegg and Gillian, 1989; Takahashi et al., 1989). Staurosporine appeared to generally inhibit cell growth even at lowest concentration evaluated (0.1 µM), agreeing with previous reports on its apoptosis induction role. In contrast, UCN-01 and UCN-02 dose response experiments revealed that these compounds were not as potent as staurosporine in inhibiting cell growth, and at some concentrations could specifically inhibit cyst formation without affecting overall organoid growth (Figure 7.5D). However, the dose responses of UCN-01 and UCN-02 varied with the PKD1 and PKD2 mutant models. Differential responses may be due to the fact that UCN-01 and UCN-02 are stereoisomers, thus likely having some differential properties. Alternatively, PKC’s role in cyst formation may vary dependent on genotype. An altered sensitivity to PKC-mediated growth suppression may enable specific targeting of cystic growth. Finally, UCN-01, UCN-02 and staurosporine have promiscuous kinase inhibition (Tamaoki and Nakano, 1990), so non-PKC mechanisms cannot be ruled out. IKK inhibitor VII is a selective competitive inhibitor of NF-κB signaling blocking activity of IκB kinases (IKKs) and transcriptional activation of the NF-κB pathway. IKK inhibitor VII targets both IKK- 1 and IKK-2. However, annotated IKK-2-specific kinase inhibitors in the library did not prevent cyst 251 formation in our primary screen suggesting a link to IKK-1 inhibition and potentially non-canonical NF-κB pathway activity in cystogenesis (Supplementay Table 2). APKD rat studies have highlighted the expression of noncanonical NF-κB pathway transcriptional components in cystic epithelial cells (Ta et al., 2016). Interestingly, QNZ (quinazoline, chemical formula 6-amino-4-(4-phenoxyphenethyl-amino)) has also been reported to potently inhibit NF-κB pathway activation (Scheurer et al., 2019; Tobe et al., 2003). However, additional studies suggested QNZ indirectly modulates NF-κB signaling through the control of Ca2+ entry into the cell (Choi et al., 2006). Further, phenotypic screens in Drosophila and induced pluripotent stem cell-derived Huntington’s disease model showed QNZ inhibition of neuronal store-operated Ca2+ entry pathway activity (Nekrasov et al., 2016; Wu et al., 2011). PKD2 encodes a selective ion channel in complex with PKD1, linked to primary cilium transport of Ca2+, and potentially monovalent cations (DeCaen et al., 2013; Kleene and Kleene, 2017; Koulen et al., 2002; Liu et al., 2018; Su et al., 2018). Elevated Ca2+ levels have been reported in proximal tubule cell cultures from PKD1 mutant mice (Yanda et al., 2019). The strong inhibitory activity of QNZ on cystogenesis in both ADPKD mini-organoid models at the lowest dose supports a further evaluation of the mechanistic action of this compound for potential therapeutic insight. In conclusion, the uniformity, scalability and size of organoids in the miniature kidney organoid platform are well suited to high-throughput image-based screening assays. The mini- organoids may also be better suited for renal implantation, evaluating functional integration will be an interesting avenue for future studies. In a proof-of-principle, we confirmed cyst inhibition in ADPKD mini-organoid kidney models with small molecule inhibitors active in ADPKD animal models, and identified novel inhibitory compounds. The mini-organoid system should enhance efforts to model, mechanistically dissect, and discover, novel therapeutic approaches to treat kidney disease. MAIN FIGURES 252 Figure 7.1: Generation of Miniature Kidney Organoids (A) Schematic diagram of directed differentiation to generate miniature kidney organoids. (B) Brightfield (grey) and fluorescent (green) images of miniature kidney organoids derived from MAFB-P2A-eGFP H9 hESC. Scale bars indicate 50 µm unless labeled differently. (C to F) Immunofluorescent analyses of MAFB-P2A-eGFP mini-organoids at various differentiation time points. Scale bars indicate 50 µm. (G) qPCR analyses of MAFB, SLC3A1, SLC12A1 and GATA3 expression in individual mini-organoids from 2 batches of differentiation (batch 1: no. 1 to 10; batch 2: no. 11 to 20). 253 254 Figure 7.2: Single-cell Transcriptomic Profiling of Miniature Kidney Organoids (A) Schematic diagram describing scRNA-seq time points. (B) UMAP reduction of nephrogenic cell clusters in miniature kidney organoids colored by clusters. (C) Dotplot of gene markers used for identification of nephrogenic cell clusters in mini-organoids. (D) UMAP reduction of scTransform-integrated in vitro derived and human fetal kidney nephrogenic cells. (E) Dotplot of gene markers used for identification of scTransform-integrated in vitro and in vivo derived nephrogenic cell clusters. (F) Hierarchical clustering of in vitro and in vivo derived nephrogenic cell clusters. (G) UMAP reduction of scTransform-integrated in vitro derived and human fetal kidney nephrogenic cells colored by original identities. (H) Bar graph of cell count presenting contribution of different original identities to the integrated in vitro and human fetal kidney nephrogenic cell clusters. 255 256 Figure 7.3: Vascularization of Miniature Kidney Organoids (A) Schematic diagram describing the transplantation procedure to vascularize MAFB-P2A-eGFP miniature organoids (B to G) Immunofluorescent analyses of cryosectioned vascularized MAFB-P2A-eGFP mini- organoids. Scale bars indicate 50 µm. 257 258 Figure 7.4: Cyst Formation in PKD1-/- and PKD2-/- Miniature Kidney Organoids (A) Schematic diagram describing the CRISPR-Cas9-induced mutations on PKD1 or PKD2 alleles, and the resulted premature stop codons that stop translation. (B and C) Brightfield images showing cyst formation progress from differentiation day 14 to 20 of PKD1-/- or PKD2-/- mutants alongside their isogenic wildtype controls. (D) Boxplots comparing area increases of PKD1-/- or PKD2-/- mutants with their isogenic wildtype controls from differentiation day 14 to 20 (Wilcoxon Rank Sum test). (E) Immunofluorescent analyses showing contribution of different nephron segment-like cells to cystic epithelial cells. Scale bars indicate 50 µm. 259 260 Figure 7.5: High-throughput Screening to Identify Compounds Inhibiting Cyst Initiation (A) Schematic diagram describing the timeline of the phenotypic assay to identify compounds inhibiting cyst formation. (B) Quantification of cyst formation rate of DMSO-treated PKD1-/- or PKD2-/- mini-organoids from 96-wells of methylcellulose-embedded mini-organoids for each line. (C) Schematic diagram describing the screening process to identify protein kinase inhibitors impeding cyst formation. (D) Compounds validated in both PKD1-/- and PKD2-/- mini-organoids to inhibit cyst formation. Carfilzomib and Celastrol were included as literature-based positive controls and Tolvaptan as a negative control based on the absence AVPR2 expression. 261 262 SUPPLEMENTAY FIGURES Figure S7.1: Immunofluorescent analyses of human fetal kidney and miniature kidney organoids (Related to Figure 7.1) (A-G) Immunofluorescent analyses of the human week 15-17 fetal kidney cryosections as positive controls for these analyses on the miniature kidney organoids. Scale bars indicate 50 µm. (H) Immunofluorescent analyses of the day 25 mini-organoids indicating the presence of cells resembling human nephron segment subdomains. 263 264 Figure S7.2: scRNA-seq analysis of miniature kidney organoids (Related to Figure 7.2) (A) UMAP reduction of cell clusters in miniature kidney organoids colored by clusters. (B) UMAP reduction of cell clusters in miniature kidney organoids colored by original identities (C) Dotplot of gene markers used for identification of cell clusters in miniature kidney organoids. Clusters highlighted in yellow were selected for subsequent analyses of the nephrogenic lineage. (D) Bar graph of cell count presenting contribution of different original identities to the cell clusters in miniature kidney organoids. (E) Hierarchical clustering of cell clusters in miniature kidney organoids. (F) UMAP reduction of nephrogenic cell clusters in miniature kidney organoids colored by original identities. (G) Bar graph of cell count presenting contribution of different original identities to the nephrogenic cell clusters in miniature kidney organoids. 265 266 Figure S7.3: scRNA-seq analysis of miniature kidney organoids (Related to Figure 7.2) (B) UMAP reduction of interstitial cell clusters in human fetal kidney. (B) Dotplot of differentially expressed genes markers displaying interstitial cell diversity in human fetal kidney. (C) UMAP reduction of scTransform-integrated in vitro derived and human fetal kidney interstitial cells colored by clusters. (D) UMAP reduction of scTransform-integrated in vitro derived and human fetal kidney interstitial cells colored by original identities. (E) Dotplot of differentially expressed genes markers displaying interstitial cell diversity in integrated in vitro derived and human fetal kidney interstitial cells. (F) Bar graph of cell count presenting contribution of different original identities to the interstitial cell clusters in the integrated in vitro and human fetal kidney population. (G) Dotplots highlighting differentially expressed genes in in vitro and in vivo derived cells. 267 268 Figure S7.4: scRNA-seq analysis of miniature kidney organoids (Related to Figure 2); and PKD1- /- PKD2-/- mutant analyses (Related to Figure 7.4) (A) Feature plots of transcription factor genes on UMAP reduction of the nephrogenic lineage miniature. (B) Sanger sequencing reads of PCR clones amplified from the PKD1-/- mutant to validate the location of indel mutations on the real gene loci. (C) Sanger sequencing reads of PCR clones amplified from the PKD2-/- mutant to validate the location of indel mutations at the PKD2 gene locus. (D and E) Western Blots showing expression of PKD2 (D) and PKD1 (E) proteins in wildtype and mutant mini-organoids. Panel (E) compares induced (positive control) PKD1 expression to control HEK293 cells with wild type and PKD1-/- mutant organoids. A full-length wildtype PKD1 protein (arrowhead) is up-regulated in induced HEK 293 cells but is not detected in kidney organoids. The 140 kDa PKD1 cleavage product (arrow) detected in induced HEK cells and in wild-type mini-organoids was absent in extracts of PKD1 mutant organoids, consistent with functional inactivation of PKD1. An asterisk marks a background band in all samples. (F) Immunofluorescent analyses showing contribution of different nephron segment-like cells to cystic epithelial cells. Scale bars indicate 50 µm. (G) Brightfield image of PKD2-/- cysts cultured for 3 months. 269 270 Figure S7.5: qPCR analyses of miniature kidney organoid differentiation (Related to Figures 7.1 and 7.4) (A to D) qPCR analyses showing upregulation of nephron markers along the differentiation timeline in miniature kidney organoids derived from (A) MAFB-P2A-eGFP H9 hESC, (B) PKD2-/- H9 hESC, (C) 5-T hESC, and (D) 5-T PKD1-/- hESC. 271 Figure S7.6: Phenotypic screens using methylcellulose-embedded miniature organoids (Related to Figure 7.5) (A and B) Brightfield images and quantification of identifiable cyst formation rates of PKD2-/- organoids started at different cell number. (C) Z-scores calculations based on cyst formation rates of DMSO-treated PKD1-/- or PKD2-/- mutants. (D to I) Boxplots showing cyst formation rates of PKD1-/- or PKD2-/- mutants treated with either DMSO or different concentrations of Blebbistatin, 8-Br-cAMP or Forskolin. (J) Brightfield images showing examples of “no-hit”, “hit” or “non-specific” growth inhibitor compounds. Red asterisks indicate organoids showed at higher magnification. Red arrowheads indicate identifiable cysts. 272 273 Chapter 8 Conclusions and Discussions By integrating various imaging and transcriptional profiling techniques, with the mouse as an anchor, we have surveyed human kidney formation, spanning weeks 5 to 23 of gestation. The two species share some major principles in building the kidney. Organogenesis of the human kidney also commences with the invasion of the metanephric mesenchyme by the nephric duct outgrowth. Subsequently, the UB branches to create the collecting duct network, concurring the induction of nephrons at nephrogenic niches situated at the UB tips. Nevertheless, kidney formation in the two species differ in time and scale. The human takes ~7 times longer to develop the first SSB (roughly twice the size of a mouse SSB). Additionally, the human kidney might form functional nephrons at an earlier developmental stage. At the equivalent stage CS23, E12.5 – E13.5 mouse renal corpuscles have not been established or just reach the capillary loop stage, while the human counterparts appear functional. The physiological implications as well as how the human nephrons could achieve faster development of the proximal domain relative to other kidney components are not well understood. Lobulation is another notable difference where the human kidney has multiple lobes relative to the single lobe in the mouse, evident by multiple renal pyramids in the medullary region. Importantly, at the molecular level, we acknowledged various anchor genes utilized to identify specific anatomical structures in the mouse are not conserved in the human. The divergent gene expressions were emphasized again in the transcriptional profiling of the human and mouse mesenchymal progenitors. Collectively, this initial effort, though presented only snapshots of human kidney formation, sparked the discussion on species-specific signatures and highlighted the need to further interrogate human organogenesis (Lindström et al., 2018a, 2018b). 274 As we reviewed human and mouse nephrogenesis in detail, we obtained, for the first time, a high-resolution categorization of the forming nephrons by overlaying expression domains of transcription factors driving mammalian nephron patterning. We could enhance the proximal, medial and distal segment definitions by dividing the human and mouse RV into five sub-domains and identifying nine in the SSB nephrons (Lindström et al., 2018c). These studies raise a number of important questions that remain unanswered. What signals and regulatory factors drive the emerging segmental organization? What is the lineage relationship amongst these early domains and adult nephron cell types? When are adult cell types specified? What are the transitions beyond the SSB in which there are 9 transcriptionally distinct domains that will generate ~20 distinct adult nephron cell types? Through confocal views of the human fetal kidney and cell tracking in the developing mouse kidney in vitro, we have proposed a new model of how mammalian nephrons form: NPCs actively contribute to nephron development, and depending on their arrival time into the aggregating and epithelializing nephron structure, NPCs acquire different nephron segment fates (Lindström et al., 2018d). Importantly, human-centered observations were central to building the model and the mouse was used to validate key predictions of the model. The model enhanced former views of mammalian nephrogenesis, which often treated the cap mesenchyme and the developing nephron as two separate entities, and proposed a link between these two developmental steps. This study also marked the first use of scRNA-seq to investigate the transcriptional relationships between kidney cell fates. We inferred that the generation of the most proximal cell fates - the podocyte and parietal epithelium - NPCs might take a separate “path” and require fewer transcriptional changes than the formation of the main tubular component of nephrons. These distinct developmental paths can potentially be explained by differential Wnt/β-catenin signaling forming a gradient along the proximo-distal axis of the developing nephron (Lindström et al., 2015). The distalmost region of the nephron precursor lying closest to the ureteric epithelium is predicted to 275 be constantly exposed to high Wnt9b signaling from the ureteric epithelium, while the proximal domain precursors are recruited late into the forming nephron furthest from this signaling source. The nephron also undergoes a reproducible and complex morphogenesis in which folding enables potential interactions between proximal and distal regions not possible in the linear nephron. Together, the potential requirement for timed graded signaling and novel cell interactions enabled by nephron morphogenesis, might pose difficulties for organoid directed strategies to emulate to accomplish full differentiation and patterning of the nephron. With a better understanding of human early nephrogenesis, we inquired how mature nephron cell types are made, and whether the organoid-derived nephrons recapitulate the in vivo cells (Tran et al., 2019). We first focused on the formation of human podocytes, which occurs within the most mature structure found in the week 15-17 human fetal kidney, and identified the transcriptional changes during podocyte differentiation from NPCs. Using a genetically engineered reporter cell line to specifically profile podocytes generated in kidney organoids, we described a remarkably similar developmental process in organoids in vitro to that observed in vivo (Tran et al., 2019). Clearly, amongst all nephron segments, the podocyte is the most normally developed cell type from the perspective of gene expression, potentially reflecting the more direct link from NPC to a mature podocyte lineage as suggested by our computational analysis (Lindström et al., 2018d). Organoid podocytes lack normal vascular and mesangial contributions, which clearly account for some of the differences in in vitro derived podocytes, and we showed that key gene expression differences (e.g., expression of the Alport Syndrome related Col4a3, Col4a4 and Col4a5) are normalized when organoids were implanted into the mouse kidney and vascularized. Identifying vasculature-independent and -dependent programs of podocyte development will further enhance in vitro podocyte formation and increase the value of organoid systems for glomerular disease modeling. As it stands now, 3D-organoid-derived podocytes are far superior to the “gold-standard”– a virally immortalized human podocyte cell line. 276 The strong resemblance between human and organoid podocyte formation justifies the use of kidney organoids to study podocyte fate commitment. Indeed, I have a proof-of-principle which is not included in this thesis as the remaining experiments are not fully flushed out. We developed a lentivirus-based method to deliver a construct carrying the NPHS1 enhancer, a minimal promoter, and the mKate2 reporter and developed an effective infection protocol (at the transitional stage from 2D to 3D culture), assaying for enhancer activity at differentiation day 20 (Figure 8.1 A). We observed mKate2 fluorescence indicative of the NPHS1 enhancer activity only in podocytes as expected from transgenic studies with the same element in mice (Figure 8.1 B) (Eremina et al., 2006; Guo et al., 2004; Wong et al., 2000). Recently, we have predicted transcription factor (TF) binding sites on the NPHS1 enhancer, and we are now generating enhancer mutants with modifications at putative TF binding sites to examine the requirements for binding in the kidney organoid system. Additionally, enhancers can also serve as a powerful genetic tool to ablate or overexpress genes specifically in the podocyte or any other nephron compartments. Figure 8.1. Lentivirus approach to examine and utilize NPHS1 enhancer activity in organoids. (A) Schematic diagram summarizing the workflow to infect kidney organoids with lentivirus. (B) Schematic diagram of the lentivirus construct to examine the activity of the NPHS1 enhancer, and expression of the mKate2 reporter in day 20 kidney organoids. Scale bar: 100 µm. 277 The developmental single-cell transcriptomics of the human podocyte, in combination with the chromatin accessibility profiles, provided insight predicting key transcriptional regulators of the podocyte program combining motif enrichment (ATAC-seq) with expression studies (RNA-seq). This too is being examined by a colleague in the laboratory through RNA-mediated transduction with a cocktail of 11 TFs (WT1, MAFB, TCF21, FOXD1, FOXC2, HOXC9, LMX1B, DACH1, TEAD1, SIX1 and SIX2) into human embryonic fibroblasts carrying a podocyte specific MAFB-GFP reporter. If successful, the RNA approach is well suited to rapid generation of other human nephron cell types. To improve the cost-effectiveness and scalability of human kidney organoid model, I developed and characterized a miniature kidney organoid platform. Using this workflow, we modeled autosomal dominant polycystic kidney disease (ADPDK) caused by mutations of PKD1 or PKD2, and observed cyst formation in mutant organoids. Utilizing the size and scalability advantage, we performed a phenotypic screen and identified small molecule inhibitors that can block cystic 278 initiation. One of these compounds also had the ability to reduce early and late cyst size, while not inhibiting nephrogenesis in wildtype organoids. The findings stemming from the miniature kidney organoid platform have encouraged further testing in the mouse model and submission of a patent application covering the screening technology and initial results from the PKD study (Patent application number: US 2020/0390825 A1 – submitted on 12/17/2020). This PKD model raises reasonable questions about the applicability of the organoid system to modeling APKD. For instance, we noticed a reversed polarity of the cystic cells compared to human patient samples or mouse models. In the former, the ciliated apical surface is reversed facing away from the lumen of the cyst which likely reflects the absence of basement membrane interactions in the culture model. More generally, the current organoid models raise questions about the normality of cell types. Aside from the podocyte, most nephron segments are not well developed examining our (and others’) scRNA-seq data, potentially reflecting an absence of normal patterning cues. Hence, searching for additional signaling modulators that facilitate such enhancement is an important next step. The size advantage of the mini-organoid platform also allows for flow cytometry- based assays that can support such high-throughput searches. Improving the tubular nephrons will lay a stronger foundation for genetic kidney disease modeling. Kidney organoids have additional value for modeling nephron injury and repair. 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Abstract (if available)

Abstract The human kidney is an architecturally intricate organ that packs a network of about 1 million nephrons filtering blood to maintain fluid homeostasis. Additionally, it participates in cross-body communications by secreting hormones regulating hematopoiesis, blood pressure and bone composition, playing vital roles in maintaining the homeostasis of body’s systems. How the human kidney forms has been inferred from animal model studies. This body of knowledge has informed recent approaches to differentiate human nephron cell types from pluripotent stem cells, yet the lack of molecular understanding of human kidney development hindered a thorough assessment of synthetic human kidney cell types. My thesis studies first aimed to achieve a molecular view of human kidney formation. By employing the immunofluorescence imaging technology, I contributed to describe gross anatomical progression, nephrogenic niche development, nephron progenitor characteristic, and signatures of nephron polarity establishment in human developing kidneys. These studies laid the foundation to assess in vitro nephrogenesis in human pluripotent stem cell-derived organoids, and acknowledge possible applications of kidney organoids in disease modeling and developmental biology. Lastly, I optimized a scalable workflow to generate kidney organoids in large quantity for polycystic kidney disease modeling. Using this system, I performed a small-molecule kinase inhibitor screen, and identified compounds capable of inhibiting cyst initiation in PKD1-/- and PKD2-/- organoids. Altogether, these studies present an in vivo informed approach to enable developmental biology and clinical applications for synthetic human nephron cell types.

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Asset Metadata

Creator Tran, Trinh (Tracy) Khiet (author)

Core Title Understanding human nephrogenesis and scaling synthesis of organoids facilitate modeling of kidney development and disease

School Keck School of Medicine

Degree Doctor of Philosophy

Degree Program Development, Stem Cells and Regenerative Medicine

Degree Conferral Date 2021-08

Publication Date 08/08/2021

Defense Date 06/16/2021

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag Development,developmental trajectory,disease modeling,drug screen,high-throughput,Kidney,nephron,nephron patterning,OAI-PMH Harvest,organoids,PKD,PKD1,PKD2,podocyte,polarity,polycystic kidney disease,RNA-seq,single-cell,single-cell transcriptomics,transcriptomics

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Crump, Gage (committee chair), McMahon, Andrew P. (committee chair), Ichida, Justin (committee member), Peti-Peterdi, Janos (committee member), Ying, QiLong (committee member)

Creator Email trinh.kh.tran@gmail.com,trinhktr@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC15722211

Unique identifier UC15722211

Legacy Identifier etd-TranTrinhT-10026

Document Type Dissertation

Format application/pdf (imt)

Rights Tran, Trinh (Tracy) Khiet

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given.

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA

Repository Email cisadmin@lib.usc.edu