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Signaling mechanisms governing intestinal regeneration and gut-glia cross-talk in Drosophila

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Signaling mechanisms governing intestinal regeneration and gut-glia cross-talk in Drosophila

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SIGNALING MECHANISMS GOVERNING INTESTINAL REGENERATION
AND GUT-GLIA CROSS-TALK IN DROSOPHILA

by

Xiaoyu Cai

A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the Requirements for the Degree
DOCTOR OF PHILOSOPHY
(BIOLOGY OF AGING)

August 2021

ii

ACKNOWLEDGMENTS
My accomplishments during my Ph.D training at the program of Biology of Aging would
not be possible without my mentor, Dr. Heinrich Jasper. I really want to thank Henri for offering
me the tremendous opportunity to study under his mentorship. He has provided me a great
working environment allowing me to explore the questions I was interested in with freedom,
while giving me a lot of supports and guidance. He is always available for discussion when I
couldn’t figure out things on my own. I have been greatly influenced by Henri’s innovative ways
of scientific thinking and passion for the science, and have learned valuable lessons of writing
and presentation from him. All these influences have enabled me to become a component
scientist, and would persist through my scientific career.
I would like to acknowledge my families with great gratitude, especially my parents and
my partner, Daniel. Despite the long distance, my parents have given me unconditional love and
support, which helped me overcome all the challenges to pursue this degree. They have always
been very open minded, believe in me and support my decisions, no matter how big or small.
Also, I would like to sincerely thank Daniel, who has been working at the same lab with me
during my graduate study. He is a passionate and smart scientist, and has taught me a lot about
cell biology, especially about Dynein (one of his favorite cytoskeletal motor proteins), live
imaging, writing and how to present my work on screen. He is always there whenever I need
anything, and believes in me. I will miss the fun “Dynein Lesson Time” at lab, but look forward to
our years ahead.
I also want to sincerely thank the members of my thesis committee, my co-mentor Dr.
Pejmun Haghighi, Dr. Gordon Lithgow, Dr. Rachel Brem and Dr. Pinchas Cohen for their
mentorship, advice and support, which are invaluable to me in my career life. I especially want
to thank Pejmun for the collaboration and the discussion for my second project. Also, during my
iii

transition period from Buck to Genentech, he and his lab members offered me a friendly working
environment, helping me adapt to changes in my lab. In addition, I would like to thank Dr. Kelvin
Davies, the Director of Biology of Aging program, for his understanding, help, and support when
I moved to Genentech with my lab, and Jim DeVera as well as Molly Susag for all the kind help
during my graduate career.
In addition, I really want to thank my excellent collaborators, Drs. Hongjie Li, George
Pyrowolakis, Martin Jensen, and Elie Maksoud for all the technical support and scientific
discussion. Without them, I would not have been able to complete and publish my two projects.
Lastly, I want to thank my fellow colleagues and friends, both past and present. Jialin
Xiao was a senior Ph.D student in this program when we first met, and was the first friend I
made in U.S. She helped me adapt to life in Los Angeles, and taught me so many things in both
science and life, which I have always been very grateful for and would never forget. I also really
appreciate the friendship and company from Lifen Wang, Hongjie Li, Yanyan Qi, Jie Zhu, and
Chisaka Kuehnemann, who are my closest friends in the Bay Area. They always listen to my
feelings and share their experiences. My acknowledgement will not be complete without
mentioning my awesome fellow colleagues, Suzy Jackson, Linlin Guo, Lindy McClelland
Tollervey, Josh Kramer, Imilce A. Rodriguez-Fernandez, Helen Tauc, Otto Morris, Kristen
Browder, Dena Leman, Nadja Katheder, Samantha Haller, Rebecca Marton, Jill De Jong,
Aliaksandr Khaminets, Robert Heler, Rebeccah Riley, Jina Yun, Joana Neves, Pedro Sousa-
Victor, and David Madden. Thanks for teaching me lab skills and providing great comments on
my projects.

iv

In the following chapters, Chapter 2 are modified from the journal article entitled “AWD
regulates timed activation of BMP signaling in intestinal stem cells to maintain tissue
homeostasis,” published in Nature Communications, 2019 July 5
th
, by Xiaoyu Tracy Cai, Hongjie
Li, Abu Safyan, Jennifer Gawlik, George Pyrowolakis and Heinrich Jasper.
Chapter 3 are modified from a manuscript entitled “Gut cytokines modulate olfaction
through metabolic reprogramming of glia,” under revision in Nature, by Xiaoyu Cai, Hongjie Li,
Martin Borch Jensen, Elie Maksoud, Jovencio Borneo, Yuxin Liang, Liqun Luo, Stephen Quake,
Pejmun Haghighi and Heinrich Jasper.

v

TABLE OF CONTENTS
Acknowledgements ii
List of Figures vii
Abbreviations x
Abstract xv
Chapter 1: Introduction 1
1.1 Drosophila gastrointestinal tract 1
1.1.1 Structure 1
1.1.2 Plasticity of Intestinal Regeneration 4
1.1.3 Effect of aging on Drosophila intestine 7
1.1.4 BMP signaling in intestinal regeneration 12
1.2 The roles of gastrointestinal signals in neurodegeneration 14
1.2.1 Overview 14
1.2.2. Benefits of using Drosophila as a model 17
1.3 Drosophila CNS 19
1.3.1 Overview 19
1.3.2 Glia functions 20
1.3.3 Olfactory system 23
1.3.4. The role of JAK/STAT signaling in the CNS 26

Chapter 2: AWD regulates timed activation of BMP Signaling in ISCs to maintain tissue
homeostasis. 29
2.1 Tkv is induced and internalized in ISCs upon infection. 30
2.2 Highwire and proteasome activity control Tkv turn-over. 36
2.3 Infection induces AWD expression to promote Tkv endocytosis. 42
2.4 JNK regulates Tkv internalization through AWD. 49
2.5 Internalization of Tkv optimizes BMP signal transduction. 51
2.6 AWD/Tkv/MAD restore ISC quiescence during regeneration. 57
vi

Chapter 3: Gut cytokines modulate olfaction through metabolic reprogramming of glia. 62
3.1 Enteric infection modulates olfaction. 62
3.2 Gut-derived Upd cytokines regulate olfaction. 72
3.3 Age-related JAK activation leads to EG loss. 75
3.4 Glial JAK activation reprograms lipid metabolism. 85
3.5 Chronic JAK activation leads to lipid toxicity. 88

Chapter 4: Summary and discussion 96
4.1 Endocytic regulation of BMP signaling 99
4.2 The role of BMP signaling in controlling ISC activity during regeneration 100
4.3 Novel roles of AWD in intestinal regeneration 101
4.4 Neuron/glia metabolic coupling 102
4.5 Complicated roles of JAK/STAT signaling in the CNS 103
4.6 Antagonistic pleiotropy of olfactory modulation 104

Materials and Methods 106
References 122

vii

LIST OF FIGURES
Figure 1: Structure of the Drosophila midgut epithelium. 3
Figure 2: Dynamic control of ISC activity by BMP signaling in Drosophila during regeneration. 6
Figure 3: Drosophila BMP signaling. 13
Figure 4: Drosophila Gal4-UAS system. 18
Figure 5: A modified cartoon showing Drosophila olfactory system. 23
Figure 6: Drosophila JAK/STAT signaling. 27
Figure 7: Tkv is induced and internalized in ISCs in response to Ecc15 infection. 33
Figure 8: Validation of Tkv-3xHA fly lines in larval imaginal disc and adult ISCs. 35
Figure 9: Highwire and proteasome-dependent downregulation of Tkv during homeostasis. 39
Figure 10: A targeted RNAi screen to identify possible regulators of Tkv stability in ISCs. 41
Figure 11: Infection-induced AWD is sufficient and required for Tkv internalization. 44
Figure 12: AWD promotes the co-localization of Tkv with lysosomes. 46
Figure 13: AWD doesn’t affect Sax expression in ISCs. 48
Figure 14: JNK signaling promotes Tkv internalization through AWD in ISCs. 50
Figure 15: AWD regulates MAD signaling in ISCs. 54
Figure 16: Regulation of MAD signaling by AWD is Rab5 and Dynamin (Shibire) dependent. 56
Figure 17: AWD/Tkv/MAD promote ISC quiescence and host resistance to acute infection. 59
Figure 18: AWD overexpression doesn’t affect ISC proliferation. 61

viii

Figure 19: Temporal activation of JAK/STAT signaling in ensheathing glia upon infection
transiently inhibits olfactory discrimination, contributing to Ecc15 aversion and increasing
host survival. 65

Figure 20: Orco and Gr63 odor receptors are required for infection-induced avoidance
behaviors towards enteropathogens. 67

Figure 21: Infection does not influence numbers and the morphology of ensheathing glia at
the antennal lobe. 69

Figure 22: JAK/STAT signaling in ensheathing glia promotes avoidance behavior against
Ecc15, yet increasing host survival upon acute infection. 71

Figure 23: Gut-derived Upd ligands activate STAT in glia and regulate olfaction sensitivity. 73

Figure 24: Gut-derived Upd2 and Upd3 are sufficient and required for infection-induced
STAT activation in the glia. 74

Figure 25: Chronic activation of JAK/STAT signaling in old EGs causes decline of olfaction
sensitivity during aging. 77

Figure 26: Chronic activation of JAK/STAT signaling in ensheathing glia drives the decline
of ensheathing glia numbers at the antennal lobe during aging. 79

Figure 27: Age-related decline of olfaction sensitivity and morphological decays of
ensheathing glia are independent from microbiota. 81

Figure 28: JAK/STAT signaling regulates glial lipid metabolism. 83
Figure 29: JAK/STAT signaling regulates LD accumulation via Glaz and Outsiders upon
infection, with no influence on lipid peroxidation. 87

Figure 30: Reducing LDs in ensheathing glia aggravates infection-caused mortality,
yet partially alleviates age-related olfactory degeneration. 90

ix

Figure 31: Deactivation of JAK/STAT signaling alleviates lipid toxicity during aging, thus
rescuing the age-related decline of ensheathing glia numbers. 92

Figure 32: Inhibiting lipid export or lactate intake in projection neurons partially rescues the
decline of olfaction sensitivity upon infection and during aging. 94

Figure 33: Dynamic control of ISC activity by AWD-facilitated endocytic regulation of
Tkv/MAD signaling during the regenerative response. 97

Figure 34: Model for the impact of gut-derived cytokines on neuron/glia metabolic coupling
at the antennal lobe. 98

x

ABBREVIATIONS
Anterior midgut (AM)
Autophagy-specific gene 1 (Atg1)
Antennal lobe (AL)
Abnormal wing disc (AWD)
After heat shock (AHS)
Blood brain barrier (BBB)
Bone Morphogenetic Protein (BMP)
BMP receptor (BMPR)
Basket (Bsk)
Basigin (Bsg)
Copper cell region (CCR)
Central nervous system (CNS)
Cortex glia (CG)
Delta (DI)
Decapentaplegic (Dpp)
Dual Oxidase (Duox)
Draper (Drpr)
Drosophila insulin-like peptide 2 (DILP2)
xi

Dally-like (dlp)
Domeless (Dome)
Escargot (Esg)
Enteroblast (EB)
Enterocyte (EC)
Enteroendocrine cell (EE)
Erwinia carotovora carotovora 15 (Ecc15)
Ensheathing glia (EG)
Excitatory amino acid transporter 1 (EAAT1)
Excitatory amino acid transporter 2 (EAAT2)
Fibroblast growth factor (FGF)
Fluorescence-activated cell sorting (FACS)
Gastrointestinal (GI)
Gastric stem cell (GSSC)
Glass bottom boat (Gbb)
Gamma aminobutyric acid (GABA)
Glial lazarillo (Glaz)
Hemipterous (Hep)
Hindsight (Hnt)
Highwire (Hiw)
xii

5-hydroxytryptamine (5-HT)
Intestinal stem cell (ISC)
Immune deficiency (Imd)
Jun amino-terminal kinases (JNK)
Janus kinase (JAK)
Klumpfuss (Klu)
Local interneurons (LNs)
Lateral horn (LH)
Lactate dehydrogenase (Ldh)
Lipase 4 (Lip-4)
Mushroom body (MB)
Middle midgut (MM)
Mitogen-activated protein kinase (MAPK)
Mesencephalic astrocyte-derived neurotrophic factor (MANF)
Monocarboxylate transporters (MCTs)
Neural lazarillo (Nlaz)
Nicotinamide adenine dinucleotide phosphate (NADPH)
Outsiders (Out)
Olfactory receptor neurons (ORNs)
Posterior midgut (PM)
xiii

Platelet-derived growth factor (PDGF)
Peptidoglycan recognition proteins (PGRPs)
Perineural glia (PNG)
Projection neurons (PNs)
Platelet-derived growth factor/VEGF receptor (PVR)
Puckered (Puc)
Pseudomonas Entomophila (PE)
Preference index (P.I.)
Reactive oxygen species (ROS)
RNA interference (RNAi)
RNA sequencing (RNA-seq)
Stem cell (SC)
Smad on X (SMOX)
Saxophone (Sax)
Single cell RNA sequencing (scRNA-seq)
Screw (Scw)
Subperineural glia (SPG)
Signal transducers and activators of transcription (STAT)
Suppressors of cytokine signaling (SOCS)
Tramtrack (Ttk)
xiv

Thickveins (Tkv)
Transforming growth factor-β (TGF-β)
Tumor necrosis factor-alpha (TNFα)
Transforming growth factor-β receptor (TGFβR)
Unpaired (Upd)
Upstream Activation Sequence (UAS)
Vascular endothelial growth factor (VEGF)

xv

ABSTRACT
The gastrointestinal (GI) tract is one of the largest immune organs in most metazoans,
acting not only as a barrier to segregate inhabited microbiota from the host, but also as a source
of immunological cytokines and chemokines to activate immune responses in other tissues,
including the brain. Therefore, maintaining GI homeostasis is essential for both digestive health
and brain function.
Intestinal stem cells (ISC) reside along the GI tract, regenerating the epithelia. In the
Drosophila intestine, injury-induced regeneration involves initial activation of ISC proliferation
and subsequent return to quiescence. These two phases of the regenerative response are
controlled by differential availability of the bone morphogenetic protein (BMP) type I receptor,
Thickveins (Tkv) (Ayyaz, Li, & Jasper, 2015), yet how its expression is dynamically regulated
remains unclear. As such, I explored the ISC-specific regulatory mechanisms responsible for
Tkv expression, and found that post-translational regulation of Tkv is critical for the dynamic
control of BMP responses during a regenerative episode. My results suggest that Tkv turnover
is regulated by the E3 ubiquitin ligase Highwire (Hiw) and by high proteasome activity in
quiescent ISCs. In response to tissue damage, Tkv is temporarily stabilized due to general
downregulation of proteasome activity, and internalized into Rab5-positive endocytic vesicles.
This internalization is facilitated by the Drosophila homologue of Nm23 (abnormal wing discs,
AWD), which is upregulated in active ISCs by JNK signaling. The AWD-facilitated endocytosis
of Tkv is critical for the return of ISCs to quiescence, to prevent epithelial dysplasia, and for host
survival during acute intestinal infection. These findings not only contribute to understanding the
role of BMP signaling in the regulation of ISC activity during regeneration, but also provide
molecular insights underlying tissue homeostasis.
xvi

In addition, I used the Drosophila olfactory circuit as an experimental model to
investigate cellular mechanisms orchestrating the inter-tissue communication between the gut
and the antennal lobe (AL), an important component of the olfactory circuit, and explored how
this cross-talk influences infection-induced avoidance behavior, infection tolerance, as well as
olfactory decline during aging. My findings suggest that intestinal inflammation reduces olfaction
sensitivity and reprograms lipid metabolism in ensheathing glia (EG). Upon acute infection, the
gut epithelium secretes Unpaired (Upd) cytokines, leading to the activation of JAK/STAT
signaling in ensheathing glia at the AL. This causes glial lipid overload due to elevated
expression of the Lipocalin Glia Lazarillo (Glaz) and the Monocarboxylate Transporter (MCT)
Outsiders (Out), resulting in transient inhibition of olfaction sensitivity. This gut-glia cross-talk
promotes avoidance of enteropathogens and thus increases host resistance to infection. During
aging, however, chronic activation of this inflammatory crosstalk between gut and glia not only
causes constitutive lipid droplet accumulation, but also enhances lipid peroxidation. This, in turn,
promotes the loss of EG at the AL, and impairs olfactory discrimination with age. My findings are
an example of how an adaptive mechanism that protects the host by promoting pathogen
avoidance can also contribute to the age-related decline of neuronal function when activated
constitutively in the aging organism. Futhermore, the study highlights the role of gut-derived
inflammatory cytokines in the degeneration of neuronal function, and identifies glial metabolic
reprogramming by inflammatory pathways as a mechanism causing lasting changes in neuronal
activity.

1

Chapter 1 : Introduction
1. 1 Drosophila gastrointestinal tract
1.1.1 Structure
Anatomically, the Drosophila intestine is composed of three regions with distinct
developmental origins: the ectoderm-derived foregut, which includes the pharynx, esophagus,
and crop, and is responsible for food intake, storage, and early digestion; the ectoderm-derived
hindgut, which is largely responsible for water reabsorption and ion exchange; and the
endoderm-derived midgut, which is the main digestive and absorptive region (Buchon et al.,
2013; Miguel-Aliaga, Jasper, & Lemaitre, 2018; Stoffolano & Haselton, 2013).
The midgut, including the anterior midgut (AM), middle midgut (MM), and posterior
midgut (PM), is finely subdivided into 10-14 regions, based on differences in cellular behaviors
and gene expression (Buchon, Broderick, Poidevin, Pradervand, & Lemaitre, 2009; Marianes &
Spradling, 2013; Murakami, Shigenaga, Matsumoto, Yamaoka, & Tanimura, 1994). Despite the
morphological and functional differences between these subdivisions, all three regions are
maintained and regenerated by the multipotent adult stem cell (SC) population, the intestinal
stem cell (ISC). ISCs reside basally next to the visceral muscle, and can self-renew and
differentiate into the epithelial cell types of each region (Buchon & Osman, 2015; Lucchetta &
Ohlstein, 2012). Cell type-specific transcriptomic analysis from different regions of the midgut
(Dutta et al., 2015) has revealed that the complex regulation of such regionalization not only
necessitates the regional heterogeneity of ISC behaviors controlled by complex gene regulatory
networks, but also relies on the gradient activities of some developmental morphogens, like
wingless or bone morphogenetic proteins (BMP), at several compartmental boundaries (Buchon
et al., 2013; H. Li, Qi, & Jasper, 2013; A. Tian, Benchabane, Wang, & Ahmed, 2016).
2

The ISC-derived lineage is relatively conserved throughout the adult midgut epithelium.
Upon injury, activated ISCs, marked by the expression of Escargot (Esg) and Delta (DI), divide
symmetrically to generate two daughter ISCs, or asymmetrically to produce either enteroblasts
(EBs, Esg+, DI-), which would terminally differentiate into polyploid absorptive enterocytes (ECs,
Pdm1+), pre-EC progenitors (Prospero+), which would terminally differentiate into diploid
secretory enteroendocrine cells (EEs, Prospero+) (Fig. 1) (Biteau & Jasper, 2014; Z. Guo &
Ohlstein, 2015; Hu & Jasper, 2019; Micchelli & Perrimon, 2006; Ohlstein & Spradling, 2006). A
recent study has used single cell RNA sequencing (scRNA-seq) analysis to further identify
various subclusters of ISCs throughout the intestinal epithelium, and computed several
differentiation trajectories of ISCs (Hung, Li, Liu, & Perrimon, 2021), indicating the heterogeneity
of the ISC population and the complexity of its lineage commitment.
A sophisticated understanding of mechanisms regulating cell fate decisions of ISCs has
emerged during the past decade. EC specification requires activity of Notch signaling, the
transcription factors Sox21a, Hindsight (Hnt), and Klumpfuss (Klu), and the downregulation of
the transcription factor Esg, while EE specification relies less on Notch activity, but requires the
transcription factor Prospero (Baechler, McKnight, Pruchnicki, Biro, & Reed, 2015; Biteau &
Jasper, 2014; Z. Guo & Ohlstein, 2015; Ignesti et al., 2014; Korzelius et al., 2019; Zhai, Boquete,
& Lemaitre, 2017). Activation of the acheate-scute complex proneural genes, repression of
Notch signaling and Esg expression, and loss of the Tramtrack (Ttk) transcriptional repressor
may cooperatively promote EE specification (C. Wang, Guo, Dou, Chen, & Xi, 2015; Yin & Xi,
2018; Zeng & Hou, 2015). A recent study performed scRNA-seq analysis on EEs, and identified
11 subtypes of EEs located at different subdivisions of the midgut epithelium (X. Guo et al.,
2019). They have found that the identity specification for each EE subcluster is determined by
binary expression states of 14 transcription factors. However, how the upstream regulators
coordinate the expression of these transcription factors in EEs remains unclear.
3

Figure 1: Structure of the Drosophila midgut epithelium.
(a) The Drosophila midgut consists of the anterior midgut (AM), middle midgut (MM), and
posterior midgut (PM). Right: a modified cartoon depicting that the gut epithelium is
composed of ISC, EB, EC and EE (Biteau, Hochmuth, & Jasper, 2011).
(b) The ISC lineage. During homeostasis, ISCs are quiescent, which can be activated upon
stress. ISCs can give rise to two daughter ISCs, or one ISC and one EB, which differentiates
to an EC, or one ISC and one pre-EE which differentiates to an EE.

In contrast to the similarity in ISC-derived lineage between AM and PM epithelium, ISCs
in the copper cell region (CCR) of the midgut, known as gastric stem cells (GSSCs), are distinct.
This region of the midgut (the MM), is similar to the stomach of vertebrates and GSSCs give rise
to acid-secreting copper cells to maintain compartmentalization and microbiota homeostasis (H.
Li & Jasper, 2016; H. Li, Qi, & Jasper, 2016).

4

1.1.2 Plasticity of Intestinal Regeneration
Dynamic control of ISC activity
The intestinal epithelium serves as a barrier between the luminal substances and other
organs. Large luminal ECs are the most vulnerable to epithelial injury caused by normal
digestion, toxic luminal contents, enteropathogens, and oxidative stress. Damaged ECs
undergo apoptosis and are shed from the epithelium, which can be quickly replaced by new
cells to maintain the barrier integrity (J. Liang, Balachandra, Ngo, & O'Brien, 2017; Tetteh et al.,
2016). Such effective epithelium repair relies on the dynamic control of ISC activity (Biteau et al.,
2011; Karin & Clevers, 2016; Lemaitre & Miguel-Aliaga, 2013). During homeostasis, ISCs are
quiescent, but can be transiently activated and rapidly become mitotic in response to tissue
damage (Biteau et al., 2011; H. Li & Jasper, 2016; Rock & Hogan, 2011). Rapid mitotic entry
involves complex integration of various autocrine, paracrine, and systemic mitogentic signals,
including JAK/STAT signaling, EGFR signaling, JNK signaling, Hedgehog signaling, Hippo
signaling, Wnt signaling, and BMP signaling (Biteau et al., 2011; Jiang et al., 2009; Karpowicz,
Perez, & Perrimon, 2010; Lemaitre & Miguel-Aliaga, 2013; H. Li & Jasper, 2016; G. Lin, Xu, & Xi,
2008; F. Ren et al., 2010; Shaw et al., 2010; Staley & Irvine, 2010; A. Tian et al., 2016). Ca
2+

signaling not just integrates these signals to stimulate and sustain ISC proliferation (Deng,
Gerencser, & Jasper, 2015), but also plays a central role in alternating the metabolism to match
the energetic demands during proliferation (O. Morris, Deng, Tam, & Jasper, 2020). A recent
study has identified two central mechanisms, aerobic glycolysis and increased activity of the
electron transport chain, that are responsible for ATP production during ISC activation, the latter
of which is finely tuned by mitochondria Ca
2+
(O. Morris et al., 2020). Of note, heterogeneous
responses of ISCs to the same signaling pathway have been observed as a result of
regionalization, as GSSCs respond differently to JAK/STAT and BMP signaling in the CCR,
compared to ISCs in the PM region (LI et al. 2013a, Li et al 2016. JIANG et al. 2009).
5

As regeneration concludes, ISCs return to quiescence to avoid hyperplasia, and
reinstate epithelial homeostasis. However, mechanisms driving ISC back to quiescence are only
starting to be investigated. Recently, a couple of studies have suggested that the post-
transcriptional regulation plays an important role in promoting ISC quiescence after regeneration
(McClelland, Jasper, & Biteau, 2017; Takemura et al., 2021). For example, the mRNA
degradation factor Tis11, induced in activated ISCs, is involved in the targeted degradation of
pro-proliferative transcripts, including several key components of critical proliferative signaling
pathways, thus promoting the re-entry into quiescence in ISCs (McClelland et al., 2017).
Consistent with this notion, another study identified the Drosophila Mov10 gene as an additional
important modulator of ISC activity during the termination stage of midgut regeneration, which
reestablishes ISC quiescence by regulating the activity of the microRNA gene silencing complex
(Takemura et al., 2021). Moreover, a secondary response to BMP-like ligands,
Decapentaplegic (Dpp), can finely control the transition between activation and quiescence of
ISCs (Ayyaz, Li, & Jasper, 2015). In this study, it has been demonstrated that the transition
from a pro-proliferative to an anti-proliferative response of ISCs to Dpp is achieved by
differential activation of the Type I receptors Saxophone (Sax) and Thickveins (Tkv), and of their
downstream effectors Smad on X (Smox) and Mad (Ayyaz et al., 2015). Sax is constitutively
expressed in ISCs, and responds to the early Dpp signal derived from hemocytes, which are
Drosophila macrophage-like immune cells, to promote ISC proliferation through SMOX, while
Tkv is only detectable in ISCs in the later phase of the response. The presence of Tkv diverts
the Dpp response from Sax/SMOX signaling to MAD signaling, promoting a return of ISCs to
quiescence (Fig. 2).
6

The roles of other tissues in gut regeneration
Recent breakthrough discoveries have suggested that other tissues, including immune
cells (hemocytes), visceral muscle, fat body (an immune organ), and brain can signal to the gut,
and are either required for the maintenance of intestinal homeostasis, or contribute to tissue
regeneration. During homeostasis, trachea-derived Dpp ligands, or brain-derived Drosophila
insulin-like peptide 2 (Dilp2) and autophagy-specific gene 1 (Atg1), are required for the
maintenance of intestinal homeostasis (Amcheslavsky, Jiang, & Ip, 2009; Z. Li, Zhang, Han, Shi,
& Lin, 2013; Ulgherait, Rana, Rera, Graniel, & Walker, 2014). Upon infection, hemocytes, the
Drosophila macrophage-like immune cells, are recruited to the gut epithelium to stimulate ISC
proliferation by secreting mitogenic Dpp ligands and Unpaired (Upd) cytokines, while Dpp
ligands later derived from neighboring visceral muscles promote ISC return to quiescence after
regeneration (Ayyaz et al., 2015; Chakrabarti et al., 2016). In addition, loss of lamin B in fat
Figure 2: Dynamic control of ISC activity by BMP signaling in Drosophila during
regeneration.
Upon bacterial challenge, Dpp ligands bind to Sax and Punt in ISCs, activating Smox
signaling and contributing to ISC activation. After regeneration, Tkv is induced in ISCs, and
Dpp bind to Tkv and Punt instead, leading to the activation of Tkv/Mad signaling and
promoting ISC quiescence.
7

body leads to the deregulation of Immune deficiency (Imd) signaling pathway in the midgut
epithelium, accelerates intestinal aging (H. Chen, Zheng, & Zheng, 2014).

1.1.3 Effect of aging on Drosophila intestine
Although adaptive ISC division and differentiation are required for tissue regeneration
and homeostasis, uncontrolled proliferation and deregulated differentiation have been
considered hallmarks of aging in the intestine. With an improved understanding of regenerative
plasticity of Drosophila midgut, this tissue has been widely employed as a powerful model to
study the basic biology and genetics of age-related dysfunction of barrier epithelia in metazoans,
and has shed light into the relationship between intestinal homeostasis and host longevity. In
the aging midgut, there is a consistent display of intestinal dysplasia in the posterior midgut,
which is characterized by ISC over-proliferation and accumulation of polyploid misdifferentiated
cells. This dysplasia results in commensal dysbiosis, loss of barrier function, alternation of
compartmentalization, and ultimately systematic infection and host mortality (Ayyaz et al., 2015;
Biteau, Hochmuth, & Jasper, 2008; Biteau et al., 2010; Buchon, Broderick, Chakrabarti, &
Lemaitre, 2009; Choi, Kim, Yang, Kim, & Yoo, 2008).

Intestinal dysplasia
Intestinal dysplasia, reminiscent of ISC dysfunction during aging, is characterized by an
accumulation of ISCs that are over-proliferative and misdifferenated (Biteau et al., 2008; Biteau
et al., 2010; L. Guo, Karpac, Tran, & Jasper, 2014; Hochmuth, Biteau, Bohmann, & Jasper,
2011; H. Li et al., 2016; L. Wang, Ryoo, Qi, & Jasper, 2015). Age-related increase of ISC
proliferation has been attributed to the aberrant activation of ISCs in response to various
intrinsic and extrinsic stress signaling pathways, like JNK signaling, insulin signaling, JAK/STAT
8

signaling, platelet-derived growth factor (PDGF) / vascular endothelial growth factor (VEGF)
signaling, p38b mitogen-activated protein kinase (MAPK) signaling (Biteau et al., 2008; Biteau
et al., 2010; Buchon, Broderick, Chakrabarti, et al., 2009; Choi et al., 2008; Cronin et al., 2009;
Jiang et al., 2009; Park, Kim, & Yoo, 2009). Accordingly, lifespan extension by limiting the rate
of ISC proliferation in the aging intestine also supports this notion (Biteau et al., 2010; L. Guo et
al., 2014; Hu & Jasper, 2019; Rera et al., 2011). However, as these stress signaling pathways
play wide-ranging functions in gut regeneration, an intricate balance between maintaining
regenerative potential and preventing hyper-proliferative disorders is critical for lifespan.
Moderate inhibition of JNK and insulin signaling activities during aging is beneficial and delays
tissue degeneration, while strong inhibition alleviates age-related hyperplasia, but shortens
lifespan (Biteau et al., 2010; M. C. Wang, Bohmann, & Jasper, 2003, 2005). In contrast, the
roles of different Unpaired ligands, known to activate JAK/STAT signaling in Drosophila, varies,
as Upd1 is required for basal ISC maintenance throughout life, while Upd2 and Upd3 contribute
to ISC over-proliferation during aging (Osman et al., 2012).
In spite of the overall increase of ISC proliferation during aging, a recent study has also
documented that an age-related change in ISC fate shifting from asymmetric divisions to
symmetric divisions, due to the regulation of spindle orientation by the chronic activation of Jun
amino-terminal kinase (JNK), contributing to intestinal hyperplasia (Hu & Jasper, 2019).
Remarkably, altering spindle orientation in aged ISCs to favor asymmetric divisions improves
intestinal homeostasis and increases lifespan (Hu & Jasper, 2019). Moreover, the amitosis of
ECs, which increases during aging, is also underlying the accumulation of ISCs in the aged
intestine (Lucchetta & Ohlstein, 2017).
Because mitochondria Ca
2+
is found as a key modulator of metabolic adaption in young
activated ISCs upon injury, it is important to determine the extent of its role during ISC over-
proliferation and age-related dysplasia. Researchers have recently discovered the Warburg-like
9

metabolic reprograming in aged ISCs, which reduces mitochondria Ca
2+
intake and ETC activity
while increasing the glycolysis (O. Morris et al., 2020), phenocopying cancer metabolism
(DeBerardinis & Chandel, 2016; Vander Heiden & DeBerardinis, 2017).
Another feature of intestinal dysplasia is increased ISC mis-differentiation, leading to an
accumulation of cells co-expressing stem and progenitor cell markers, such as DI and Esg, and
differentiation markers, such as Pdm1 (Biteau et al., 2008; Buchon, Broderick, Chakrabarti, et
al., 2009; Hochmuth et al., 2011). The molecular mechanisms underlying this process, however,
are not fully understood. A recent study has shown that Piwi overexpression, a regulator of
heterochromatin maintenance and the suppressor of retrotransposon activation, prevents the
age-related mis-differentiation, without affecting ISC over-proliferation, suggesting that Piwi-
mediated retrotransposon control is specifically essential for ISC mis-differentiation (Sousa-
Victor et al., 2017).

Age-related changes in host-commensal Interaction
The microbiota regulates host immunity in both Drosophila and mammals (Ichinohe et al.,
2011; Sansone et al., 2015). During aging, commensal microbiota become dysbiotic,
characterized as increased microbial loads and a shift in the microbial community composition
(Clark et al., 2015), which is likely due to a loss of gut compartmentalization and pH imbalance
driven by the chronic activation of JAK/STAT signaling (H. Li et al., 2016). However, age-related
increases in tissue dysplasia and loss of epithelial integrity are delayed in flies reared under
axenic conditions. These flies have improved lifespan, indicating an essential role of commensal
microbiota in the regulation of intestinal functionality and ultimately lifespan (Broderick, Buchon,
& Lemaitre, 2014; Buchon, Broderick, Chakrabarti, et al., 2009; L. Guo et al., 2014; C. Ren,
Webster, Finkel, & Tower, 2007).
10

The Drosophila midgut, thus, has been widely used an amendable model to dissect the
interplay between microbial dynamics, innate immune responses, and intestinal aging. Recent
studies have unveiled that loss of innate immune homeostasis in the gut epithelium has
important implications for the age-related progression of intestinal dysfunctions. In young flies,
the Drosophila macrophage-like immune cells, hemocytes, are recruited to the epithelial surface
upon infection, secreting Dpp ligands to promote ISC proliferation and regeneration, while such
interactions were misregulated in old flies, further promoting intestinal dysplasia (Ayyaz et al.,
2015).
In addition, the deregulation of innate immune signaling has been correlated with the
intestinal aging caused by microbiota dysbiosis. Hyperactivated Rel/NF-kappaB signaling
sensitizes flies to dysbiotic microbiota with age (Bonnay et al., 2013; L. Guo et al., 2014; Ha, Oh,
Bae, & Lee, 2005; Maillet, Bischoff, Vignal, Hoffmann, & Royet, 2008). Accordingly, inhibiting
NF-kappaB signaling in old flies, either pharmacologically (Moskalev & Shaposhnikov, 2011), or
genetically by overexpressing PGRPs of the SC class in ECs (L. Guo et al., 2014), preserves
commensal dysbiosis, restricts ISC over-proliferation, and extends lifespan. The other immune
mechanism complimentary to Rel/NF-kappaB signaling in the gut is mediated by reactive
oxygen species (ROS), which is mainly produced by nicotinamide adenine dinucleotide
phosphate (NADPH) oxidase enzyme dual oxidase (Duox) (L. Guo et al., 2014; Ha et al., 2005;
Ryu et al., 2008). During aging, genes normally responding to increased levels of ROS have
been found to increase dramatically in the gut epithelium (L. Guo et al., 2014). This suggests
commensal dysbiosis may aid in the breakdown of intestinal barrier functionality via oxidative
stress (L. Guo et al., 2014; Hochmuth et al., 2011). Although low dose oxidants during larval
development extends lifespan, resulting from the early-on remodeling of microbiota (Obata,
Fons, & Gould, 2018), ectopic induction of ROS by dysbiotic microbiota during the late life is
detrimental and promotes intestinal dysplasia (L. Guo et al., 2014). Interestingly, a recent study
11

used an immune-deficient model to further characterize the link between innate immunity and
intestinal aging. Researchers have found increased loads of microbiota in flies carrying a null
mutated SD class of peptidoglycan recognition proteins (PGRP-SD), accompanied by a higher
release of lactic acid and elevated ROS production from another NADPH oxidase, Nox. These
defects resulted in intestinal hyperplasia and shortened lifespan (Iatsenko, Boquete, & Lemaitre,
2018). In turn, over-expression of PGRP-SD in ECs limits dysbiosis and extends lifespan
(Iatsenko et al., 2018).

Loss of intestinal barrier function
The gut barrier plays important roles in the absorption of water and various nutrients,
while protecting the host from toxins, antigens, and microorganisms. The development of the
noninvasive Smurf assay, lead to the observation that, during aging, permeability of the
intestinal barrier increases in flies, resulting in systemic upregulation of anti-microbial peptides
(Clark et al., 2015; Rera et al., 2011; Rera, Clark, & Walker, 2012). As such, barrier dysfunction
has been found to be more sensitive and accurate than chronological age in predicting the
forthcoming mortality of flies (Rera et al., 2012), yet the underlying pathophysiology of such
leakage has not been fully understood. In healthy animals, epithelial cells are tightly bound
together by intercellular junctional complexes, which maintain the paracellular permeability and
epithelial integrity (Buckley & Turner, 2018; Qin et al., 2016). In the Drosophila midgut,
researchers have identified an alternation in the expression and localization of septate junctions
between adjacent ECs during aging, particularly noticeable at tricellular junctions (Clark et al.,
2015; Resnik-Docampo et al., 2017; Salazar et al., 2018). Such deregulation of junction proteins,
occurring before the deterioration of gut permeability, accelerates intestinal hyperplasia and
contributes to microbial dysbiosis, consequentially impairing the intestinal barrier integrity (Clark
et al., 2015; Resnik-Docampo et al., 2017; Salazar et al., 2018). In contrast, another study from
12

the same group recently revealed that tricellular junction proteins are also required for
maintaining ISC homeostasis and epithelium permeability, but seemingly with no relation with
commensal dysbiosis (Resnik-Docampo et al., 2018).

1.1.4 BMP signaling in intestinal regeneration
Morphogen gradients direct the specification of different cell fates, which not only ensure
tissue patterning in the embryo, but also play an essential role for the functioning of adult
tissues (Tabata & Takei, 2004; Wolpert, 1969). Bone morphogenetic proteins (BMPs), a class of
highly conserved morphogens, belong to members of transforming growth factor-β (TGF-β)
superfamily of ligands, and are involved in multiple developmental processes and in
regenerating various adult tissues, including airway, intestine and bones (Bier & De Robertis,
2015; G. Chen et al., 2020; Tadokoro, Gao, Hong, Hotten, & Hogan, 2016; Thorne et al., 2018).
Elements of this pathway include secreted BMP ligands, BMP type I and type II receptors,
receptor-regulated Smad transcription factors, BMP antagonists, as well as extracellular
metalloproteinases that cleave and inactivate BMP antagonists (Canalis, Economides, &
Gazzerro, 2003; Miyazono, Kamiya, & Morikawa, 2010). BMP ligands bind to their
serine/threonine kinase receptors (type II receptors, BMPRII), leading to the receptor
phosphorylation and the activation of the type I receptors (BMPRI). Activated BMPRI
phosphorylates and activates R-Smads (Smad1, 5 and 8) which then form complexes with Co-
Smad (Smad4), and translocate into the nucleus to regulate downstream gene expression
(Canalis et al., 2003; Miyazono et al., 2010; Miyazono, Maeda, & Imamura, 2005; Sieber, Kopf,
Hiepen, & Knaus, 2009). BMP receptors can also regulate cellular functions by signaling
through non-Smad pathways, such as p38/MAPK and JNK signaling, to regulate multiple
cellular functions (Y. E. Zhang, 2017). So far, more than 20 BMP ligands have been identified in
mammals, while Drosophila only has three known BMP ligands, Dpp, Glass bottom boat (Gbb),
13

and Screw (Scw), which are expressed at different
levels depending on tissue type (Bangi & Wharton,
2006; Bier & De Robertis, 2015). These ligands
signal through their receptors, Thickveins (Tkv),
Saxophone (Sax) and Punt, leading to the activation
of Drosophila Smad proteins, Smad on X (Smox), or
Mad (Fig. 3).
BMP signaling play complex roles in the control of ISC function, with several studies
reporting somewhat contradictory consequences of BMP signaling perturbation in Drosophila
ISCs. Long-term inactivation of BMP signaling in both ISCs and EBs causes significant ISC loss
by promoting symmetric non-self-renewing divisions (A. Tian & Jiang, 2014), while short-term
inhibition of BMP signaling prevents DNA-damage induced proliferation of ISCs (A. Tian, Wang,
& Jiang, 2017). In contrast, constitutive activation of BMP signaling receptor, Tkv, promotes ISC
self-renewal (A. Tian & Jiang, 2014). Upon Erwinia carotovora carotovora 15 (Ecc15) infection,
hemocyte-derived BMP ligands, Dpp, activates ISC proliferation to promote repair, while
visceral muscle-derived Dpp inhibits ISC proliferation in the later phase of the response to
promote ISC quiescence (Ayyaz et al., 2015; Z. Guo, Driver, & Ohlstein, 2013). This is
consistent with the current understanding on the role of BMP receptor (BMPR) in the
mammalian intestinal epithelium regeneration, as loss of BMPRIA causes overgrowth of the
crypt (He et al., 2004). Ayyaz et al. has also demonstrated that overexpression of constitutively
active Tkv in ISCs can rescue age-related intestinal dysplasia in Drosophila (Ayyaz et al., 2015),
though this observation conflicts with another study (A. Tian & Jiang, 2014). In addition, BMP
signaling is required for EC maintenance during homeostasis and acts on EBs to promote EC
differentiation and growth after injury (Z. Li et al., 2013; Zhou et al., 2015). BMP signaling also
influences differentiation of midgut copper cells (Driver & Ohlstein, 2014; H. Li et al., 2013).
Figure 3: Drosophila BMP signaling.
14

In the mammalian intestine, BMP ligands and antagonists secreted from mesenchymal
cells cooperatively shape the gradient of BMP activity along the crypt-villus axis, as BMP
ligands are most abundant near the lumen, while antagonist mainly localize near the base of the
crypt (Bitgood & McMahon, 1995; Hardwick et al., 2004; He et al., 2004; Kosinski et al., 2007).
As such, BMP signaling inhibits ISC self-renewal to restrict intestinal epithelium hyper-
proliferation by suppressing Wnt signaling or directly inhibiting ISC signature genes (He et al.,
2004; Qi et al., 2017; Q. Tian, He, Hood, & Li, 2005). Disruption of BMP gradients causes
adverse effects on intestinal homeostasis and impairs tissue regeneration, eventually resulting
in diseases. Mutations on BMPRI or Smad4 have been found in patients with juvenile polyposis
syndrome (Howe et al., 2001; Howe et al., 1998). Consistent with this, BMP antagonist, Noggin,
stimulates the growth of intestinal organoids and causes de novo crypt formation and polyposis
(Haramis et al., 2004; Urbischek et al., 2019).

1.2 The roles of gastrointestinal signals in neurodegeneration
1.2.1 Overview
Since the middle of 19
th
century when enteric nervous system was first discovered in
mammals (Furness, 2012), more attention has been brought to the field of gut-brain interaction
given the unparalleled relationship between these two organs. Firstly, there are large and
complex networks of enteric nerves closely interfacing with intestine, as the intestinal surface
area is the largest body surface in most metazoans (Furness, Kunze, Bertrand, Clerc, &
Bornstein, 1998; Mayer, 2011). Secondly, the intestinal epithelium contains thousands of
neuroendocrine cells producing various hormones, which can act as neurotransmitters and can
be sensed by the enteric nerves (Gunawardene, Corfe, & Staton, 2011; Sundler, Böttcher,
Ekblad, & Håkanson, 1989). Thirdly, the intestine is one of the largest organ of immunity that
15

contains almost two thirds of immune cells in the body, while closely interacting with trillions of
inhabited microbiota (Chassaing, Kumar, Baker, Singh, & Vijay-Kumar, 2014; Mayer, 2011).
Thus, microbiota-derived antigens can activate tissue resident immune cells, further leading to
local, neural or peripheral immune responses.
As such, a bidirectional communication network, the “gut-brain axis”, has been
developed during the past decade (Carabotti, Scirocco, Maselli, & Severi, 2015; Mayer, 2011).
Consistent with this notion, increasing studies have identified CNS as an important regulator for
intestinal homeostasis and regeneration, while gastrointestinal signals, in turn, can influence
various neurological processes and neurodegenerative disorders (Clemmensen et al., 2017;
Erny et al., 2015; Minter et al., 2016; Montiel-Castro, Gonzalez-Cervantes, Bravo-Ruiseco, &
Pacheco-Lopez, 2013; Rothhammer et al., 2016; Sampson et al., 2016; S. C. Wu, Cao, Chang,
& Juang, 2017).
As the intestine contains various microorganisms, a growing body of evidence points to
a role of the microbiome in regulating CNS functions, thus influencing human health and
diseases (Dodiya et al., 2019; Erny et al., 2015; Keshavarzian, Engen, Bonvegna, & Cilia, 2020;
Minter et al., 2016; Montiel-Castro et al., 2013; Rothhammer et al., 2016; Sampson et al., 2016;
S. C. Wu et al., 2017; L. Zhang et al., 2017). Firstly, intestinal microbes can directly regulate the
functionalities of immune cells, blood brain barrier, and the vagus nerve in the CNS by secreting
afferent neuromodulatory metabolites, such as short chain fatty acids (Matheoud et al., 2019;
Montiel-Castro et al., 2013; Rothhammer et al., 2016; Silva, Bernardi, & Frozza, 2020).
Furthermore, as commensal dysbiosis has been associated with the breakdown of the intestinal
barrier and intestinal inflammaging (Arrieta & Finlay, 2012; Clark et al., 2015; L. Guo et al., 2014;
Salazar et al., 2018), “dysbiotic” microbiota can promote neuroinflammation, cause changes in
neurogenesis, and lead to brain injury by activating peripheral and neural immune responses in
16

both flies and vertebrates (Antonini, Lo Conte, Sorini, & Falcone, 2019; Bercik et al., 2011;
Carabotti et al., 2015; Fang, 2016; S. C. Wu et al., 2017).
Shifts in the composition and diversity of gut microbial species have been observed in
many neurodegenerative diseases (Keshavarzian et al., 2020; Sampson et al., 2016; L. Zhang
et al., 2017), and aggravate neurodegenerative symptoms in models for Alzheimer’s disease
and Parkinson’s disease (Dodiya et al., 2019; Minter et al., 2016; S. C. Wu et al., 2017).
Conversely, germ-free mice, which are reared under sterile conditions, or mice fed with oral
broad-spectrum antibiotics exhibit substantial improvements in these disease-related
neurodegenerative symptoms (Minter et al., 2016; Sampson & Mazmanian, 2015).
Electrically excitable neuroendocrine cells from the intestinal epithelium can produce
various neurotransmitters that are traditionally thought to be only made in the central nervous
system, such as 5-hydroxytryptamine (5-HT), gamma aminobutyric acid (GABA), and gut
peptides, which can then be directly sensed by the vagus nerve to modulate CNS functions
(Mawe & Hoffman, 2013; Nozawa et al., 2009). Recently, studies have linked these
neuroendocrine cells with the pathological progression of Parkinson’s disease (Angot & Brundin,
2009; Angot et al., 2012; Liddle, 2018). One of the classical hallmarks of this disease is the
accumulation of Lewy bodies in the brain, which are mainly composed of misfolded α-synuclein
proteins (Del Tredici & Braak, 2008). Surprisingly, neuroendocrine cells in the gut express α-
synuclein, and Lewy bodies have also been found in the gut epithelium and the enteric nerves
during the early phase of this disease (Angot & Brundin, 2009; Angot et al., 2012). Therefore,
it’s reasonable to conceive that the Parkinson’s disease is initiated from gut-derived α-synuclein,
which can be directly transferred to the brain via the vagus nerve, like prions. However, more
investigations are required in order to further understand the physiological and molecular
underpinnings underlying this process.
17

In summary, understanding gut-brain interactions and dissecting the roles of gut-derived
signals in the etiology of neurodegenerative diseases may thus lead to the identification of
alternative therapeutic strategies for neurodegenerative diseases.

1.2.2 Benefits of using Drosophila as a model
Drosophila melanogaster, also known as the fruit fly, has been one of the most
commonly used and powerful model systems for biomedical research with various advantages.
Firstly, Drosophila has complex organ systems, some of which share great similarities with
human organs, like intestine and brain, in addition to its fully sequenced genome which contains
homologs for 77% of human disease-related genes (Reiter, Potocki, Chien, Gribskov, & Bier,
2001; Rubin & Lewis, 2000). These features enable the fruit fly to become a genetically
controlled model system to study human diseases, providing opportunities for targeted drug
screen in a whole organism at a very low cost. Secondly, a previously developed Drosophila
Gal4-UAS system allows for cell- or tissue- specific transgenic overexpression or RNA
interference (RNAi) of any gene in an inducible way, in which the transcription factor, Gal4,
originally found in yeast is inserted into fly genome and its expression is cell or tissue specific,
and can further bind with upstream activation sequences (UAS) to drive the expression of
downstream transgenes (Brand & Perrimon, 1993) (Fig. 4). Thus, the presence of Gal4 and
UAS in the same cell type or tissue allows over-expression or knockdown of any gene of
interest, which can be induced during any phase of fruit flies’ life cycle, promoting genetic
studies during the developmental processes and in adult tissues. Previous studies have
identified corresponding Gal4 drivers for different cell types in the gut epithelium and in the
neural system, such as mex1::Gal4, a driver for gut ECs (Phillips & Thomas, 2006), esg::Gal4, a
driver for both gut ISCs and EBs (Amcheslavsky et al., 2009; Deng et al., 2015; L. Guo et al.,
2014; McClelland et al., 2017; Resnik-Docampo et al., 2017; A. Tian et al., 2016), repo::Gal4, a
18

Figure 4: Drosophila Gal4-UAS system.
Yeast transcription factor, Gal4, is inserted into fly genome, the expression of which is
controlled by genes of interest (e.g. Esg, which is expressed in ISCs and EBs in the gut). In
the presence of upstream activation sequence (UAS), Gal4 can bind to UAS, driving the
expression of downstream RNAi or over-expression constructs. This allows cell- or tissue-
specific manipulation of genes of interest.
driver for all glia in the brain (Sepp, Schulte, & Auld, 2001), as well as elav::Gal4, a driver
specific for neurons (Luo, Liao, Jan, & Jan, 1994). Also, years of fly researches have made
whole-genome RNAi libraries available for public use. Thirdly, Drosophila has greater
reproduction capacity with shorter lifespan than vertebrate models, ensuring enough progeny
numbers for different study purposes.

In addition, considerable conservation between Drosophila and mammalian intestinal
regeneration and pathogenesis, signaling pathways that control ISC activity, and molecular
mechanisms governing neural development and promoting neurodegeneration have been
increasingly documented within past decade, leading to increasing human disease modeling
using Drosophila, such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and
intestinal infectious diseases (Apidianakis & Rahme, 2011; Capo, Wilson, & Di Cara, 2019; Lu &
Vogel, 2009; Lucchetta & Ohlstein, 2012). Also, it’s relatively cheaper and easier to generate
19

and maintain germ-free fruit flies (Kietz, Pollari, & Meinander, 2018), contributing to understand
the role of microbiota in the modulation of neuronal activities (Poinsot et al., 2020; Schretter et
al., 2018). Altogether, these traits make Drosophila as a great model system, facilitating
breakthrough studies of the gut-brain communication.
Despite these similarities, inherent differences between Drosophila and mammals with
respect to simpler cell composition and tissue structure of both intestine and brain, reduced
microbiota composition, fewer gene paralogs, etc, have also been considered as the limitations
of Drosophila model systems for resolving human pathology, yet allowing for powerful
reductionist studies.

1.3 Drosophila CNS
1.3.1 Overview
Adult Drosophila CNS is a complex neural network, consisting of a central brain, two
optical lobes and ventral nerve cords, and developed from around 100 pairs of neural stem cells
that undergo serials of mitosis in two neurogenic periods before adulthood (Y. J. Lee et al., 2020;
Truman & Bate, 1988). 90% of total cell population represents neurons, the cell bodies of which
locate at the cortical regions, while synaptic connections are sequestered to form neuropils
(Kremer, Jung, Batelli, Rubin, & Gaul, 2017; Shih et al., 2015). To visualize and analyze each
individual neuron, a public resource, the FlyCircuit database, has been created with confocal
microscopy data obtained from 23,579 projection neurons (Shih et al., 2015). Based on the
functional and spatial connection specificity of these projection neurons, the central brain has
been further subdivided into five main functional modules, including olfaction,
auditory/mechanosensation, pre-motor, and left and right vision (Shih et al., 2015).
Heterogeneous strengths of connectivity have been observed within each individual module, or
20

between neighboring or spatially distant modules in Drosophila to ensure segregated
processing of information, similar to macaque and humans (Kaiser, 2015; Kaiser & Hilgetag,
2006; Watts & Strogatz, 1998).
The remaining 10% cells in the central brain are glia, which associate with all these
functional modules, but display great morphological and functional diversity. Five main subtypes
of glia, including astrocytes, ensheathing glia (EG), cortex glia (CG), perineural glia (PNG) and
subperineural glia (SPG) have been reported (Freeman, 2015; Kremer et al., 2017). Among
them, EG and astrocytes are usually found wrapping axons in the neuropil regions, or between
neuropils and cortex, while CG, PNG and SPG are only found in the cortical regions (Kremer et
al., 2017). CG encapsulate neuronal cell bodies, while PNG and SPG are sheet-like surface glia,
which form septate junctions with one another and altogether function as a “blood brain barrier
(BBB)” (DeSalvo et al., 2014; Kremer et al., 2017).

1.3.2 Glia functions
Glia are key players in the central nervous system from development to degeneration
(Jessen, 2004). During development, glial cells contribute to circuit homeostasis during the
neurogenesis, and maintain functionalities of neural stem cells, while glia in the adult brain also
perform many other important functions, such as electrical and metabolic support of neurons, or
control of neuronal activity by regulating neurotransmitter homeostasis, and modulating brain
innate immunity (Damisah et al., 2020; Zuchero & Barres, 2015). As such, glial dysfunction has
been linked with the progression of various CNS disorders in humans (Zuchero & Barres, 2015).
As Drosophila glia share many similarities with mammalian counterparts in terms of morphology
and functionality (Allen & Lyons, 2018; Freeman, 2015; Kremer et al., 2017; Zuchero & Barres,
2015), investigating glial functions in Drosophila not only can deepen our understanding of glial
21

biology, but also provides great insights into discovering novel therapeutic targets for
neurological disorders.
Surface glia (PNG and SPG) maintains BBB integrity and regulates passage of nutrients
or signaling molecules into the brain in adult Drosophila. Transcriptomic analysis has revealed a
significant enrichment of genes involved in cell adhesion, transmembrane transporters, as well
as fatty acid and carbohydrate metabolisms in Drosophila surface glia, consistent with
transcriptomes of mammalian BBB glia (DeSalvo et al., 2014). Overexpression of Poly-Q
aggregates in surface glia impairs BBB integrity and restricts lifespan (Yeh, Liu, Chu, Liu, & Sun,
2018). Consistent with the transcriptomic traits, previous studies have also discovered that
surface glia are essential for glucose and organic anion transport in Drosophila, contributing to
brain energy homeostasis while providing chemoprotection (Seabrooke & O'Donnell, 2013;
Volkenhoff, Hirrlinger, Kappel, Klämbt, & Schirmeier, 2018). In addition, surface glia have been
linked with sleep regulation. For example, mesencephalic astrocyte-derived neurotrophic factor
(MANF) in surface glia is required for laminar integrity, and loss of MANF leads to laminar
degeneration, disrupted daily activity/sleep pattern, and shortened lifespan (Walkowicz et al.,
2017). Also, dynamin-dependent endocytosis in surface glia is required for the maintenance of
BBB integrity, and affects sleep (Artiushin, Zhang, Tricoire, & Sehgal, 2018). Moreover, surface
glia seems also involved in alcohol-related behaviors in flies (Bainton et al., 2005; Parkhurst et
al., 2018), similar to mammalian brain vascular endothelial cells (Hindle et al., 2017).
CG is present in the cortical regions, wrapping each individual neuronal soma to
separate from other neurons (Freeman, 2015). A single CG seems being able to wrap up to 100
neurons during the late phase of development (Kremer et al., 2017). In the developing brain, CG
clears dead neurons by activating phagocytosis receptor, Draper (Drpr), in the optic lobes
(Nakano et al., 2019). Also, CG plays a critical role in maintaining neuroblasts via PDGF
signaling, and in promoting gas exchange as well as providing trophic support for neurons
22

(Pereanu, Spindler, Cruz, & Hartenstein, 2007; Read, 2018). In adult flies, CG associates with
alcohol-induced sedation (K. M. Lee, Mathies, & Grotewiel, 2019), sleep/wake regulation (Farca
Luna, Perier, & Seugnet, 2017), and light-induced epilepsy (Kunduri et al., 2018).
Astrocytes and EG extend their cellular processes to cover synaptic neuropils, and
establish spatial domains (Kremer et al., 2017). In contrast to EG which only lie in between
cortex and neuropils, astrocytes dynamically and aggressively invade into neuropils to establish
a dense meshwork and to associate closely with synapses (Stork, Sheehan, Tasdemir-Yilmaz,
& Freeman, 2014). It has been shown that the autocrine fibroblast growth factor (FGF) signaling
directs the growth of astrocyte membrane and instructs the branch formation in the neuropil
(Stork et al., 2014). Except for the structural link with synapses, astrocytes also modulate the
excitatory/inhibitory balance of synaptic transmission. Astrocytes express neurotransmitter
transporters, like GABA transporter or the excitatory amino acid transporter 1 (EAAT1), which
can take in excessive glutamate or GABA (W. F. Chen et al., 2015; Schousboe, Bak, &
Waagepetersen, 2013), similar to neurotransmitter recycling in human astrocytes (Weber &
Barros, 2015). Also, astrocytes express enzymes essential for breaking down these
neurotransmitters, and modulate the transcription of genes responsible for neurotransmitter
cycling, to ensure the balance of excitation and inhibition (W. F. Chen et al., 2015; Mazaud et al.,
2019; Schousboe et al., 2013). In addition, astrocytes secret factors to regulate fly sleep, such
as immunoglobulin domain protein Noktochor and the cytokine tumor necrosis factor-alpha
(TNFα) (Sengupta, Crowe, You, Roberts, & Jackson, 2019; Vanderheyden et al., 2018).
Astrocytes also exhibits dynamic Ca
2+
influx, which not only encodes sleep need (Blum et al.,
2021), but also promotes olfaction-driven chemotaxis and touch-induced startle responses (Ma,
Stork, Bergles, & Freeman, 2016).
In contrast to astrocytes, EG don’t closely associate with synapses, but only cover the
neuropil surface (Pereanu et al., 2007). During the development, olfactory neuron-derived FGF
23

instructs EG cellular processes to wrap each glomeruli structure, ensuring discrete glomerular
formation (B. Wu, Li, Chou, Luginbuhl, & Luo, 2017). In adults, EG can be recruited by
degenerating axons in response to axon injury, and function like phagocytes to clear debris via
Drpr signaling (Doherty, Logan, Taşdemir, & Freeman, 2009; Kazama, Yaksi, & Wilson, 2011;
Purice et al., 2017). Moreover, insulin-like signaling pathway and the downstream effector, Akt1,
are required for axon clearance upon Drpr activation (Musashe, Purice, Speese, Doherty, &
Logan, 2016). At the behavior level, EG mitochondrial sulfite oxidase, Shopper, modulates
glutamate homeostasis, thus affecting locomotion (Otto et al., 2018), while the excitatory amino
acid transporter 2 (EATT2) in EG regulates sleep duration (Stahl et al., 2018).

1.3.3 Olfactory system
In Drosophila, olfaction is initiated at olfactory receptor neurons (ORNs) in the head, the
antenna and the maxillary palp. There are 50 classes of ORNs, defined by the expression of 1-2
unique olfactory receptors. Each ORN connects with one specific projection neuron (PN), and
same class of ORNs converge in the same glomerulus at the antennal lobe (AL) so that each
glomerulus receiving input from just a single class of ORN, similar to mammalian olfactory bulb
(L. Liang & Luo, 2010). After receiving information, PN axons further synapse with higher
olfactory centers, the mushroom body (MB) and the lateral horn (LH), to instruct insect behavior
(Fig. 5).
24

ORNs express up to 60 odorant receptors encoded by 60 Or genes (Gao & Chess,
1999), and some of gustatory receptors can also function as odorant receptors (Suh et al.,
2004). Each odorant receptor is expressed by 40 ORNs on average (Vosshall, Amrein, Morozov,
Rzhetsky, & Axel, 1999). The same class of ORNs bilaterally project onto a pair of glomeruli
(one on each AL), while similar classes of ORNs tend to project to neighboring glomeruli (Couto,
Alenius, & Dickson, 2005). Previous single sensillum recordings have shown that many odors
can activate more than one class of ORNs, while one ORN class can respond to various odors,
suggesting odors may be encoded in a combinatorial manner, requiring multiple glomeruli.
Within each glomerulus at the AL, it has been estimated that about 60 ORNs and 3 PNs form
hundreds of synapses (Mosca & Luo, 2014). PNs postsynaptic to the same class of ORN exhibit
synchronized spontaneous spikes to convey the same type of olfactory information, and odors
increase such correlations (Kazama & Wilson, 2009). At the AL, ORNs can also connect with
local interneurons (LNs), which form dendrodendritic synapses with PNs, leading to lateral
excitation (Yaksi & Wilson, 2010). PNs have been further classified to two types: cholinergic
PNs which are excitatory and relay the information to Kenyon cells at the MB and to LH, and
GABAergic PNs which are inhibitory and only signal to the LH (Jefferis et al., 2007; E. C. Marin,
Jefferis, Komiyama, Zhu, & Luo, 2002; Seki et al., 2017; Wong, Wang, & Axel, 2002). MB is
where olfactory information is translated into learned behavioral responses (Heisenberg, 2003),
while LH plays important roles in numerous innate behavioral responses (Schultzhaus, Saleem,
Figure 5: A modified cartoon showing Drosophila olfactory system (Sayin, Boehm,
Kobler, De Backer, & Grunwald Kadow, 2018).
Odor molecules bind to olfactory receptor neurons (ORNs) in the antennae (or in the
maxillary palp, not shown). ORNs send axons and synapse with projection neurons (PNs), or
local interneurons (LNs). PNs project to the lateral horn (LH), and/or form synapse with the
Kenyon cells (KC) in the muschroom body (MB) followed by signaling to MB output neurons
(MBONs).
25

Iftikhar, & Carney, 2017; Seki et al., 2017). Previous studies have shown that attractive and
aversive odors activate separate clusters in both MB and LH (Seki et al., 2017).
In this system, glia and neurons operate as a tightly coupled unit to ensure the proper
processing of olfactory information (H. Liu et al., 2014; B. Wu et al., 2017). EG, for example,
establish the glomerular structures of the AL during development by insulating neighboring
glomeruli (B. Wu et al., 2017), while contributing to the olfactory circuit plasticity upon severe
injuries on ORN axons (Kazama et al., 2011). Astrocytic Ca
2+
signaling has also been found as
an evolutionarily conserved regulator for olfactory behaviors through modulation of olfactory
circuit in both flies and mammals (H. Liu et al., 2014; Ma et al., 2016; Ung, Tepe, Pekarek,
Arenkiel, & Deneen, 2020).
Olfactory perception significantly influences our nutrition, food intake, safety, and
physiological, and mental well-being (Doty & Kamath, 2014; Proserpio et al., 2019; Soria-
Gomez, Bellocchio, & Marsicano, 2014; Soria-Gómez et al., 2014). Modulating olfactory
perception to induce avoidance behaviors can serve as a critical defense mechanism against
infections (Adamo, 2005; A. Wang et al., 2016) (Ayres & Schneider, 2009). A dedicated
olfactory circuit in flies senses Geosmin, a volatile compound released by mold and some
bacteria, and elicits avoidance behaviors (Stensmyr et al., 2012). Olfactory receptors also
mediate an initial attraction of flies to enteropathogen containing food (Charroux, Daian, & Royet,
2020; Kobler, Rodriguez Jimenez, Petcu, & Grunwald Kadow, 2020). This attraction is lost after
infection, when an avoidance behavior is triggered by immune receptors in the brain (Kobler et
al., 2020), gustatory bitter neurons, and the neuropeptide Leukokinin (Charroux et al., 2020).
While the etiology of infection-induced avoidance behaviors remains poorly understood, there
are indications that infection influences sensory perception. Alteration of olfactory and gustatory
perception has, for example, been identified as a common symptom of COVID-19 (Brann et al.,
2020; Salmon Ceron et al., 2020).
26

Using olfactory T-maze assays, previous studies have found a profound decline of
sensitivity to both aversive and attractive odors in aging flies (Hussain et al., 2018). Similarly,
olfactory perception also declines with age in humans, and its loss has been suggested as an
early biomarker for neurodegenerative diseases, such as Alzheimer’s disease and Parkinson’s
disease (Kotecha, Correa, Fisher, & Rushworth, 2018; C. Marin et al., 2018; Rey, Wesson, &
Brundin, 2018; Yoo et al., 2020; X. Zhang et al., 2020; Zou, Lu, Liu, Zhang, & Zhou, 2016).
Recently, such neurological processes and neurodegenerative disorders are increasingly
recognized as being influenced by gastrointestinal signals (Clemmensen et al., 2017; Erny et al.,
2015; Minter et al., 2016; Montiel-Castro et al., 2013; Rothhammer et al., 2016; Sampson et al.,
2016; S. C. Wu et al., 2017). Therefore, understanding how gut-brain cross-talks, and clarifying
the physiological and molecular underpinnings of olfactory modulation under infection conditions,
as well as of olfactory degeneration with age may lead to the identification of alternative
therapeutic strategies for neurodegenerative diseases.

1.3.4 The role of JAK/STAT signaling in the CNS
JAK/STAT signaling is an evolutionarily conserved inflammatory pathway (Murray, 2007;
Rawlings, Rosler, & Harrison, 2004). Upon inflammation, secreted cytokines can bind to
receptors on the cell surface, leading to phosphorylation and activation of receptor-associated
Janus kinase (JAK) (R. Morris, Kershaw, & Babon, 2018). JAK further phosphorylates the
intracellular tails of the receptors, which, in turn, act as docking sites for the downstream
transcription factor, the signal transducers and activators of transcription (STAT) (R. Morris et al.,
2018). STAT is phosphorylated by JAK, and dissociates from receptors followed by subsequent
translocation to the nuclear, driving the expression of cytokine-responsive genes (R. Morris et
al., 2018). To ensure the proper switch-off of this pathway, the suppressors of cytokine signaling
27

(SOCS) family are upregulated by STAT, inhibiting the signaling cascade (R. Morris et al., 2018).
JAK/STAT signaling is very complicated in mammals, including more than 50 cytokines, 40
receptors, 4 JAK and 7 STAT family members (Murray, 2007), but is relatively simple in
Drosophila, including three IL-6-like cytokines (Upd1, Upd2 and Upd3), one receptor (Domeless
(Dome)), one JAK (Hop), one STAT (STAT92E), and three SOCS (Fig. 6) (Amoyel & Bach,
2012).

JAK/STAT signaling has been implicated in various physiological and pathological
processes in Drosophila CNS (Ben Haim et al., 2015; Boza-Serrano, Yang, Paulus, & Deierborg,
2018; Herrmann et al., 2008; Nicolas et al., 2013; Qin et al., 2016). During the development,
JAK/STAT signaling promotes neuroblast proliferation, and regulates neuronal differentiation
through modulation of cell adhesion molecules at the MB (Du & Wang, 2020; Kucherenko &
Shcherbata, 2013). Also, an activity gradient of JAK/STAT signaling has been observed in the
developing optic lobe, which negatively regulates the progression of the proneural wave, but
contributing to the maintenance and proliferation of the neuroepithelial stem cells (W. Wang, Li,
Figure 6 : Drosophila JAK/STAT signaling.
Upd ligands bind to Dome receptor, causing the phosphorylation and activation of receptor-
associated kinase Hop. Hop then phosphorylates transcription factor STAT92E, which
relocates to the nuclear to promote the transcription of downstream genes.
28

Zhou, Yue, & Luo, 2011; Yasugi, Umetsu, Murakami, Sato, & Tabata, 2008). Furthermore,
JAK/STAT signaling is involved in early sex determination in flies (Sefton, Timmer, Zhang,
Béranger, & Cline, 2000).
In adults, JAK/STAT signaling plays important roles in both neurons and glia, and has
been associated with the progression of some neurodegenerative diseases. Previous studies
have suggested JAK/STAT signaling is not just required in neurons at the MB for olfactory
aversive long-term memory (Copf, Goguel, Lampin-Saint-Amaux, Scaplehorn, & Preat, 2011),
but also regulates glial responsiveness to axon injury (Doherty et al., 2014; Purice et al., 2017).
However, upregulation of JAK/STAT signaling in glia, due to ectopic activation of Drpr, has been
reported in a fly model for Alzheimer’s Disease (Ray, Speese, & Logan, 2017), consistent with
the observation that microglia STAT activation happens before Aβ deposition in Alzheimer’s
mouse models (Boza-Serrano et al., 2018). Also, glial activation of JAK/STAT signaling
promotes both glial and neuronal deaths when human wild-type Tau is overexpressed in fly glia,
indicating its causal relationship with glia Tau toxicity (Colodner & Feany, 2010). Consistently,
inhibition of this signaling pathway is protective against neurodegeneration in a rat model for
Parkinson’s disease (Qin et al., 2016). These studies indicate a complex role of JAK/STAT
signaling in the control of glial and neuronal functionality in different contexts.

29

Chapter 2: AWD regulates timed activation of BMP Signaling in ISCs
to maintain tissue homeostasis
The complexity of the response of ISCs to the perturbation of BMP signaling indicates
that a detailed, temporally resolved characterization of BMP signaling in ISCs and their daughter
cells is critical. As mentioned above, it has been previously shown that the differentiation
between a pro-proliferative and an anti-proliferative response of ISCs to Decapentaplegic (Dpp)
ligands is achieved by differential activation of the Type I receptors Saxophone (Sax) and Tkv,
and of their downstream effectors Smad on X (SMOX), and Mad(Ayyaz et al., 2015). Sax is
constitutively expressed in ISCs and responds to the early Dpp signal derived from hemocytes
to promote ISC proliferation through SMOX, while Tkv is only detectable in ISCs in the later
phase of the response. The presence of Tkv diverts the Dpp response from Sax/SMOX
signaling to Mad signaling, promoting a return of ISCs to quiescence. The dynamic regulation of
Tkv expression thus functions as a key switch controlling the transition between activation and
quiescence of ISCs, yet the mechanisms regulating the expression of Tkv in ISCs have not
been resolved.
To explore these mechanisms, I used Drosophila midgut epithelium as the model system,
and found that post-translational regulation of Tkv is critical for the dynamic control of Dpp
responses during a regenerative episode. My work suggests that Tkv turnover is regulated by
the E3 ubiquitin ligase Highwire and by high proteasome activity in quiescent ISCs. In response
to tissue damage, Tkv is temporarily stabilized due to general downregulation of proteasome
activity, and internalized into Rab5-positive endocytic vesicles. This internalization is facilitated
by the Drosophila homologue of Nm23, AWD, which is upregulated in active ISCs by JNK
signaling. The AWD-facilitated endocytosis of Tkv is critical for the return of ISCs to quiescence,
to prevent epithelial dysplasia, and for host survival during acute intestinal infection. My thesis
30

work identifies a central mechanism responsible for a return to SC quiescence during
regenerative processes, and has important implications for our understanding of SC regulation
and tissue homeostasis in barrier epithelia.

2.1 Tkv is induced and internalized in ISCs upon infection.
To explore the mechanisms regulating Tkv expression in ISCs, my collaborator
generated a transcriptional reporter using the Tkv promoter (TkvA-lacZ; Supplementary Fig. 8a).
Reporter activity was observed in ISCs both under homeostatic conditions and in activated ISCs
(4h post Ecc15 infection; Fig. 7a), suggesting that the previously described induction of Tkv
protein in the late phase of the regenerative response (determined using an antibody (Ayyaz et
al., 2015)), may be a consequence of post-transcriptional regulation of Tkv expression in ISCs. I
performed qPCR analysis on Fluorescence-activated cell sorting (FACS)-sorted ISCs from flies
exposed to Ecc15 infection to further confirm this notion, and again found no significant changes
in tkv mRNA levels in activated ISCs (12h or 18h post Ecc15 infection) compared to
homeostatic conditions (Fig.7b). To test directly whether Tkv expression is regulated
posttranscriptionally, my collaborator used homologous recombination to generate a
translational reporter line for Tkv which expresses a C-terminally tagged (3xHA) Tkv from its
endogenous locus (Fig. 8a) (Baena-Lopez, Alexandre, Mitchell, Pasakarnis, & Vincent, 2013;
Norman, Vuilleumier, Springhorn, Gawlik, & Pyrowolakis, 2016). Tkv-3xHA localizes to the
plasma membrane and distributes in a typical tissue pattern in 3
rd
instar larval imaginal discs
(Fig. 8b), and adult wings of Tkv-3xHA flies show no growth defects or other abnormalities (Fig.
8c), suggesting that Tkv-3xHA flies are functionally wildtype. To confirm that the insertion of the
3xHA tag has no effect on gene expression and function of tkv, my collaborator knocked down
tkv in wing imaginal discs, and found that TkvHA expression (Fig. 8b,d) and pMAD (Fig. 8d)
levels were greatly reduced in imaginal discs. This was also repeated in ISCs after Ecc15
31

infection (Fig. 8e). I crossed this line into animals containing a GFP lineage-tracing system
initiated from ISCs ('escargot flip out', esg
ts
F/O (Jiang et al., 2009)), and fed progeny Ecc15 to
induce a regenerative response. TkvHA expression was not observed in ISCs under
homeostatic conditions, confirming the notion that its expression is regulated post-
transcriptionally (Fig. 7c). Upon infection, however, ISCs upregulated TkvHA expression (Fig.
7d), recapitulating previous data from immunohistochemistry (Ayyaz et al., 2015). To assess the
kinetics of this response, I examined expression of TkvHA in a time-course post Ecc15 infection
by immunohistochemistry. In contrast to Sax, which is continuously expressed under both
homeostatic and infected conditions (Fig. 8f), TkvHA was not observed in ISCs until 12h post-
Ecc15 challenge, and increased strongly around 18h after challenge (Fig. 7d and Fig. 8f). To
confirm the immunohistochemistry quantification independently, I quantified TkvHA and Sax
protein levels in sorted GFP-labelled ISCs by intracellular Flow Cytometry assay (Leeman et al.,
2018) every 6 hours post-Ecc15 challenge during a 24 hour regenerative episode. These
experiments confirmed the strong time-dependent induction of TkvHA in ISCs (up to 3 fold)
upon Ecc15 infection, with a peak around 24h, further supporting a role for Tkv in the recovery
phase after a regenerative response (Fig. 7e). Sax was continuously expressed and slightly
upregulated in ISCs around 24h (less than 2 fold), coinciding with the upregulation of TkvHA
(Fig. 8g). In the later phase of the proliferative response, Sax and Tkv expression thus overlap,
indicating that Tkv may have to compete with Sax for Type II receptor binding. It has been
shown previously that Sax/Smox signaling is repressed when Tkv/Mad signaling is activated, as
indicated by the cytoplasmic localization of Smox and the phosphorylation of Mad (pMAD),
respectively (Ayyaz et al., 2015). The dynamic regulation of Tkv in ISCs is independent from
Sax, as loss of Sax or forced Sax overexpression did not prevent Tkv induction (Ayyaz et al.,
2015) (Fig. 8e).
32

Our immunohistochemistry experiments also revealed that, in contrast to plasma
membrane-bound Sax, Tkv has a distinct subcellular distribution in ISCs. Both overexpressed
GFP-tagged Tkv (Tkv-GFP) and endogenous HA-tagged Tkv (TkvHA) localized to intracellular
puncta in addition to its expected localization on the membrane (Fig. 7f,g, Fig. 8f). These puncta
corresponded to Rab5+ early endosomes and lysosomes (Fig. 7g), suggesting that Tkv is both
stabilized and actively internalized during the late phase of a regenerative response. These
observations are reminiscent of previously documented endocytosis of Tkv at larval
neuromuscular junctions (O'Connor-Giles, Ho, & Ganetzky, 2008; Rodal et al., 2011) and during
wing posterior crossvein formation (Gui, Huang, & Shimmi, 2016), and I decided to explore the
ISC-specific mechanisms regulating the induction and endocytosis of Tkv during regeneration,
as well as their functional consequences.
33

34

Figure 7: Tkv is induced and internalized in ISCs in response to Ecc15 infection.
(a, a’) Cartoon depicting the gene structure of TkvA-lacZ flies. Transcription from tkv
promoter in ISCs (green, arrowheads) under homeostatic conditions (mock) and 4h after
Ecc15 infection.
(b) qPCR analysis of tkv mRNA level in ISCs under mock conditions and after Ecc15
infection (normalized to actin5c).
(c) Cartoon depicting the gene structure of Tkv-3xHA flies. Tkv-3xHA protein was detected
within ISCs (esg::Gal4, UAS::GFP, green; Delta+, red) and ISC-derived daughter cells
(GFP+, DELTA-), in posterior midgut (PM) of flies at 18h after Ecc15 infection, determined by
immunohistochemistry with rabbit anti-HA antibody. Average HA fluorescence intensity in
Delta+ cells was normalized to the mean value of mock.
(d, d’) Time-dependent induction of Tkv in ISCs, measured as the average intensity of Tkv-
3xHA in ISCs per PM during the course of a 18h Ecc15 infection (normalized to the mean
value of 0h).
(e) Median fluorescence of Tkv-3xHA in GFP+ ISCs during the course of a 24h Ecc15
infection, as measured by intracellular Flow Cytometry analysis(normalized to the median
value of control samples at 0h collected on the same day of measurement).
(f, g) Overexpressed Tkv-GFP fusion protein (f) or endogenous Tkv-3xHA protein (g)
present as puncta in ISCs (GFP+). Tkv-3xHA puncta, detected by rat anti-HA antibody (used
in the rest of the study), corresponded to Rab5+ early endosomes (green, yellow
arrowheads) and lysosomes (red, red arrowheads), quantification of which were from single
slice images (n=101 cells from 7 guts) in g’. Gain was increased for mock (f) for better
visualization.
Error bars indicated SEM (b: n=3 flies, c: n=7 flies, d: n=7 flies, e: n≥327 cells for each
biological replicate). P values from Student’s t-test (in a, b, c and d) or from one-tailed
Wilcoxon rank-sum test (in e): ****p<0.0001; ***p<0.001; **p<0.01; *p<0.05; NS=not
significant. Experiments were repeated 3 times (in c, d, f, g) and at least 4 times (in e).

35

36

2.2 Highwire and proteasome activity control Tkv turn-over.
Ubiquitin-mediated proteosomal degradation has been shown to influence turn-over of
BMP receptors in multiple model systems (W. Li et al., 2016; Raja et al., 2016; Xia et al., 2010;
Zhao et al., 2015), and I performed a limited genetic screen to identify possible regulators of Tkv
stability in ISCs. I used RNAi to target potential E3 ubiquitin ligases and protein kinases and
other factors, including Highwire, Fused, Lkb1, Ube3a, Smurf, Dally, Dally-like (dlp), and
Pentagone, to test whether these factors influence the kinetics of TkvHA expression in ISCs
during regeneration (Fig. 10a). This screen revealed that Highwire, a conserved RING-H2 E3
ubiquitin ligase(Honjo & Tracey, 2018; McCabe et al., 2004; C. Wu, Daniels, & DiAntonio, 2007;
C. Wu, Wairkar, Collins, & DiAntonio, 2005), negatively regulates Tkv protein levels in ISCs.
Figure 8: Validation of Tkv-3xHA fly lines in larval imaginal disc and adult ISCs.
(a) In scale illustration of the genome engineered tkv with exons shown as bars (open
reading frames in orange, 5’ and 3’ UTR in grey). The genomic locus of tkv generates 4
different isoforms through alternative transcriptional start sites (arrows) resulting in proteins
with different N-terminal sequences. The position and extent of TkvA are shown in green.
The HA epitope tag was inserted just before the stop codon in the last exon of the gene,
common to all isoforms.
(b) Immunohistochemistry of Tkv-3xHA in a 3rd instar larval imaginal disc using an anti-HA
antibody. Tkv-3xHA localizes at the plasma membrane and distributes in the typical tissue
pattern with low levels of protein in medial and elevated levels in lateral regions of the disc.
(c) Tkv-3xHA fly wings display no patterning and growth defects.
(d) pMad staining in Tkv-3xHA fly wing imaginal discs expressing either GFP (control) or
tkv
RNAi
in dorsal cells under the control of apterous-Gal4 (apGal4). pMAD was dramatically
reduced in dorsal cells when tkv was knocked down.
(e) Tkv-3xHA expression level in ISCs expressing tkv
RNAi
and ISCs overexpressing Sax after
18h Ecc15 infection.
(f) Different expression patterns of Sax and Tkv in ISCs during tissue regeneration.
(g) Median fluorescence of Sax in GFP+ ISCs during the course of a 24h Ecc15 infection,
as measured by intracellular Flow Cytometry analysis. Fluorescence was normalized to the
median value of control samples at 0h collected on the same day of measurement.
Error bars indicate SEM (e: n=5-6 flies, g: n≥189 cells for each biological replicate). P
values from Student’s t-test (in e) or from one-tailed Wilcoxon rank-sum test (in g):
****p<0.0001; **p<0.01; *p<0.05; NS=not significant. One representative image from 4-8
flies tested in a single experiment was shown in b-f. Experiments were reproduced twice (in
b-f) and at least 4 times (in g).
37

Highwire has been shown to interact with the Smad protein Medea to negatively regulate BMP
signaling during the growth of neuromuscular synapses (McCabe et al., 2004), but a role in Tkv
protein turnover has not yet been reported. Flies with an ISC-specific knockdown of highwire, or
carrying a mutation resulting in a large deletion of its N-terminal domain (including the RING
finger domain required for E3 ubiquitin ligase activity; hiw
ΔN/ΔN
) (C. Wu et al., 2005), exhibited
increased Tkv on the surface of ISCs in homeostatic conditions (Fig. 9a,b, Fig. 10b). However,
these conditions did not influence downstream DPP signal transduction in ISCs, as assessed by
measuring the levels of nuclear-localized pMAD (Fig. 9a,b, Fig. 10b). To further test whether
Highwire enzymatic activity is required for the regulation of Tkv stability in ISCs, I over-
expressed Highwire
ΔRING
, a full-length Highwire with two point mutations in its RING finger
domain, which have been reported to specifically disrupt its E3 ubiquitin ligase activity (C. Wu et
al., 2005). TkvHA was significantly stabilized in these ISCs (Fig. 9c), further supporting the
notion that the enzymatic activity of Highwire is required for maintaining low Tkv expression in
ISCs during homeostasis. I confirmed and quantified the stabilization of Tkv in ISCs using Flow
Cytometry (Fig. 9e).
Inhibiting proteasome function by feeding flies the proteasome inhibitor PS-341 for 2
days resulted in similar ectopic expression of Tkv in ISCs without activation of pMAD (Fig. 9d,e),
consistent with a role of the ubiquitin proteasome pathway in the degradation of Tkv in
homeostatic conditions. I asked whether this observation was indicative of a general change in
proteasome activity in activated ISCs, and used a CL1–GFP fusion protein (Pandey et al., 2007),
as a readout for proteasome activity in ISCs. CL-1 is a constitutive degradation signal that
promotes rapid degradation of associated proteins by an active ubiquitin-proteasome system,
and a GFP signal is thus only detectable in these cells when proteasome function is impaired.
GFP levels increased significantly in ISCs as early as 4h post Ecc15 infection, and perdured
until the late phase of the regenerative response, coinciding with Tkv accumulation (Fig. 9f).
38

Using Flow Cytometry, I also quantified Highwire protein levels after infection and found a slight
upregulation at 12h post-Ecc15 challenge, but no significant changes at other time points (Fig.
9g), consistent with qPCR analysis of highwire mRNA in ISCs (Fig. 10c).
Altogether, these results suggest that constitutive Highwire activity may license Tkv for
degradation even in activated ISCs, but that inhibition of downstream proteasome activity
prevents degradation and allows accumulation of Tkv in the late phase of the regenerative
response.
39

40

Figure 9: Highwire and proteasome-dependent downregulation of Tkv during
homeostasis.
(a-d) Expression of Tkv-3xHA and phosphorylated MAD (pMAD) in wildtype ISCs (a, c, d:
arrowheads, GFP+; mCherry
RNAi
was expressed as RNAi control), highwire
RNAi
expressing
ISCs (a: arrowheads, GFP+), highwire
N/ N
homozygous mutant ISCs (b: arrowheads,
Delta+), ISCs overexpressing hiw
ΔRing
(c: arrowheads, GFP+), and ISCs in which
proteasome activity was inhibited by 2 day feeding of 25 µM PS341 (d: arrowheads, GFP+)
respectively. Tkv-3xHA was detected by rat anti-HA antibody in a, c, d, while rabbit anti-
TKV antibody was used in b. Quantifications of the average intensity of Tkv-3xHA and
pMAD expression in ISCs per posterior midgut (PM) under the above conditions were
normalized to the mean value of control samples respectively. The same quantifications for
wildtype ISCs expressing mCherry
RNAi
were used in a and d, as both experiments were
done at the same time.
(e) Median fluorescence of Tkv-3xHA in GFP+ ISCs under conditions as noted, measured
by intracellular Flow Cytometry analysis. Fluorescence was normalized to the median value
of control samples expressing mCherry
RNAi
collected on the same day of measurement.
(f) Kinetics of ISC proteasome activity, measured as relative expression of CL1-GFP fusion
protein in ISCs (Delta+) of PM during the course of an Ecc15 infection episode of 18h
(normalized to the mean value of 0h). Antibodies of Armadillo (Arm), labelling plasma
membrane, and Prospero (Prosp), labelling enteroendoncrine cells, were used to help
quantify GFP fluorescence intensity in ISCs.
(g) Median fluorescence of Highwire in GFP+ ISCs during the course of a 24h Ecc15
infection, as measured by intracellular Flow Cytometry analysis. Fluorescence was
normalized to the median value of control samples at 0h collected on the same day of
measurement.
Error bars indicate SEM (a-d, f: n=7 flies; e: n≥918 cells, g: n≥109 cells for each biological
replicate). P values from Student’s t-test (in a-d, f) or from one-tailed Wilcoxon rank-sum
test (in e and g): ****p<0.0001; ***p<0.001; **p<0.01; *p<0.05; NS=not significant.
Experiments were repeated three times (in a-d and f) or 4 times (in g).

41

Figure 10: A targeted RNAi screen to identify possible regulators of Tkv stability in
ISCs.
(a) Knocking down candidates: Ube3a, Smurf, Fused, Lkb1, Dally, Dally-like, Pentagone,
didn’t significantly induce Tkv-3xHA expression in ISCs.
(b) Expression of Tkv and pMAD in wildtype ISCs (Delta+) of W
1118
flies.
(c) Relative mRNA levels of highwire, normalized to actin5c, in ISCs under homeostatic
conditions and at 16h post-Ecc15 infection.
Error bars indicate SEM (n=3). P values from Student’s t-test: NS=not significant. One
representative image from 4-7 flies tested in a single experiment was shown in a and b.
Experiments were reproduced twice.

42

2.3 Infection induces AWD expression to promote Tkv endocytosis.
To investigate the mechanisms regulating the endocytosis of Tkv, I analyzed previously
reported RNAseq data from ISCs isolated from Ecc15 infected animals (Sousa-Victor et al.,
2017). I observed significant induction of the Drosophila homologue of the Nm23 gene,
abnormal wing discs (AWD), within four hours after Ecc15 infection, and this induction prevailed
at 16 hours after infection. A similar induction in ISCs isolated from infected intestines was also
reported in a study published previously (Dutta et al., 2015), suggesting that AWD is
reproducibly induced during the activation of ISCs. I confirmed this induction using
immunohistochemistry and flow cytometry, and found that AWD strongly accumulates in ISCs
between 12 and 24 hours post Ecc15 infection (Fig. 11a,b).
AWD, a nucleoside diphosphate kinase, generates GTP to support the function of
dynamin (shibire) during synaptic vesicle internalization (Krishnan et al., 2001). Dynamin is
required for clathrin-mediated endocytosis (Mettlen, Pucadyil, Ramachandran, & Schmid, 2009),
and, accordingly, for endocytosis of BMP receptors (Gui et al., 2016; Heining, Bhushan,
Paarmann, Henis, & Knaus, 2011; O'Connor-Giles et al., 2008; Winther et al., 2013). Previous
genetic studies have suggested a role for AWD and its mammalian homologue Nm23 in the
endocytic regulation of several cell surface proteins, such as platelet-derived growth
factor/VEGF receptor (PVR) (Nallamothu, Woolworth, Dammai, & Hsu, 2008), FGF
receptor(Dammai, Adryan, Lavenburg, & Hsu, 2003), Notch(Ignesti et al., 2014), and Domeless
(Nallamothu et al., 2008). To test whether AWD also facilitates Tkv internalization in activated
ISCs, I overexpressed AWD in ISCs of infected flies. This resulted in larger Tkv puncta that
corresponded to acidic compartments based on lysotracker staining (Fig. 11c,d, Fig. 12b,c).
Similarly, AWD overexpression was sufficient to promote the internalization of TKV in quiescent
ISCs with repressed proteasome function or deficient in highwire (Fig. 12d). AWD
overexpression in homeostatic ISCs (where Tkv protein is not stabilized and TkvHA is not
43

detectable), did not result in Tkv+ vesicles (Fig. 12a), indicating that internalization of Tkv
through AWD activity and stabilization of Tkv by downregulation of proteasome activity are two
separate processes that cooperate to regulate BMP signaling in ISCs. Highwire is not required
for the internalization of TkvHA in AWD over-expressing ISCs (Fig. 12d), further supporting this
notion.
In turn, knockdown of AWD inhibited the internalization of Tkv after infection (Fig. 11e,
Fig. 12e; validation of the overexpression and knockdown efficiency are shown in Fig. 13a). I
confirmed this requirement for AWD in Tkv internalization using mosaic analysis with a
repressible cell marker (MARCM) (T. Lee & Luo, 2001) to generate ISCs homozygous for the
awd loss of function allele awd
j2A4
(Dammai et al., 2003; Krishnan et al., 2001)(Fig. 11f, Fig. 12b).
Two days after heat shock (AHS), and 18 hours after Ecc15 infection, Tkv accumulated on the
membrane of AWD mutant (GFP+) cells, but was found in endocytic vesicles only in
neighboring wild-type (GFP-) cells (Fig. 11f). The expression and localization of Sax, in contrast,
was not affected by overexpression or knockdown of AWD in ISCs (Fig. 12c).
We further monitored the dynamics of GFP-tagged Tkv in ISCs using time-lapse imaging.
Over-expressing AWD increased the maximal number of Tkv puncta in ISCs and resulted in
more Tkv puncta that co-localized with lysosomes under homeostatic conditions (Fig. 11g,h, Fig.
13d). Infection did not further increase these numbers, suggesting that induction of AWD in
ISCs is the rate limiting step promoting endocytosis of Tkv after infection (Fig. 13d). Accordingly,
knockdown of AWD significantly reduced average numbers of Tkv puncta in ISCs post septic
challenge (Fig. 11g, Fig. 13d).
Combined, these data show that induction of AWD is sufficient and required for
endocytosis of Tkv in ISCs.
44

45

Figure 11: Infection-induced AWD is sufficient and required for Tkv internalization.
(a) AWD protein level in ISCs (GFP+) with or without Ecc15 infection determined by
immunohistochemistry.
(b) Median fluorescence of AWD in GFP+ ISCs during the course of a 24h Ecc15 infection,
as measured by intracellular Flow Cytometry analysis. Fluorescence was normalized to the
median value of control samples at 0h collected on the same day of measurement.
(c) Tkv-3xHA puncta (arrowheads) in wildtype or awd overexpressing ISCs (GFP+) after 18h
of Ecc15 infection were revealed by immunohistochemistry. Sizes of Tkv-3xHA puncta were
quantified.
(d) Co-localization between Tkv-3xHA puncta and lysosomes in wildtype or awd
overexpressing ISCs after 18h of Ecc15 infection was quantified.
(e) Tkv-3xHA expression in wildtype or awd
RNAi
expressing ISCs upon 18h of Ecc15 infection.
Average number of Tkv-3xHA puncta in ISCs per posterior midgut (PM) was quantified.
(f) Differential Tkv-3xHA expression patterns inside (GFP+, indicated by yellow arrowhead)
and outside (GFP-, indicated by red arrowhead) of awd mutant clones after Ecc15 challenge.
Numbers of Tkv-3xHA puncta was quantified.
(g) Maximal numbers of Tkv-GFP puncta within 30min of time-lapse imaging were quantified
in ISCs in which awd was overexpressed in the absence of infection, or after 20h of Ecc15
infection in ISCs in which awd was knocked down.
(h) Quantification of the percentage of Tkv-GFP puncta co-localized with lysosomes in
wildtype and awd overexpressing ISCs in the absence of infection, from 30min time-lapse
movies.
Error bars indicate SEM (a: n=7 flies, b: n≥109 cells for each biological replicate, c: n=7-9
flies; d: n=6-10 flies; e: n=9 flies; f: n=7-9 flies; g, h: n=5 flies). P values from Student’s t-test
(in a, c-h) or from one-tailed Wilcoxon rank-sum test (in b): ****p<0.0001; ***p<0.001;
**p<0.01; *p<0.05; NS=not significant. Experiments were repeated three times (in a, c-f) and
at least 4 times (in b).

46

47

Figure 12: AWD promotes the co-localization of Tkv with lysosomes.
(a) Expression of Tkv-3xHA in wildtype and awd
OE
ISCs (a: arrowheads, GFP+) under
homeostatic conditions.
(b) Expression of Tkv-3xHA in wildtype and awd
OE
ISCs (b: arrowheads, GFP+) at 18h post-
Ecc15 infection.
(c) Co-staining of lysosomes by LysoTracker and Tkv-3xHA in ISCs after 18h of Ecc15
challenges, with and without awd
OE
.
(d) Tkv-3xHA expression in wildtype or awd
OE
ISCs, when proteasome activity was inhibited
by 25uM PS341 oral feeding for 2 days or when highwire was specifically knocked down in
ISCs.
(e) Tkv-3xHA expression in ISCs after 18h of Ecc15 infection with a different awd
RNAi
line
overexpressed.
Error bars indicate SEM. P values from Student’s t-test: ***p<0.001; NS=not significant.
Experiments were repeated three times.

48

49

2.4 JNK regulates Tkv internalization through AWD.
To explore the upstream mechanisms responsible for inducing AWD and Tkv expression
in ISCs, I tested whether candidate signaling pathways that are activated in ISCs upon septic
injury and regulate ISC proliferation and differentiation may influence AWD and/or Tkv
expression levels (Biteau et al., 2011). JNK signaling was both sufficient and required for AWD
and Tkv induction in ISCs: knockdown of the JNK phosphatase Puckered (Puc), or
overexpression of the JNK kinase hemipterous (Hep), induced the expression of Tkv and AWD
in the absence of infection (Fig. 14a,b,e), while loss of the JNK basket (bsk) prevented induction
in ISCs upon infection (Fig. 14c,d,e). I used MARCM clone analysis to confirm the requirement
for bsk: bsk mutant ISCs failed to upregulate AWD and Tkv following Ecc15 infection (Fig. 14f).
To test whether AWD acts downstream of JNK to regulate Tkv subcellular localization, I
knocked down AWD in ISCs expressing puc RNAi. Loss of AWD inhibited the internalization of
Tkv that was induced by JNK activation (Fig. 14g).
We also asked whether AWD overexpression was sufficient to promote the endocytosis
of Tkv in bsk deficient ISCs, but since loss of JNK prevented Tkv accumulation in ISCs, its
internalization could not specifically be assessed (Fig. 14h).
Figure 13: AWD doesn’t affect Sax expression in ISCs.
(a) Overexpression or knockdown efficiency of awd in ISCs was confirmed by
immunohistochemistry using AWD antibody.
(b) All the cells inside of awd mutant clones were DELTA+, quantified as average percentage
of DELTA+ cells in MARCM clone per posterior midgut.
(c) Immunostaining of SAX in ISCs (arrowheads, GFP+) upon Ecc15 infection when awd was
overexpressed or knocked down.
(d) Analysis of 30min time-lapse movies with Tkv-GFP overexpressed in ISCs. Total numbers
of Tkv-GFP puncta in ISCs at each time point within 30mins were quantified in wildtype,
awd
OE
and awd
RNAi
ISCs with or without 20h of Ecc15 infection.
Error bars indicate SEM (a: n≥4 flies, b: n=7 flies, c: n=5-6 flies, d: n=5 flies). P values from
Student’s t-test: **p<0.01; NS=not significant. Experiments were repeated twice in a-c.

50

JNK thus promotes both stabilization of Tkv and AWD induction, while AWD functions to
facilitate subsequent internalization of Tkv downstream of JNK.

51

2.5 Internalization of Tkv optimizes BMP signal transduction.
While receptor endocytosis has been proposed to promote receptor turnover and
downregulate signal transduction in many cases, it has also been found to be required to
maintain or even promote signaling activity of specific receptors (Di Guglielmo, Le Roy,
Goodfellow, & Wrana, 2003; Gui et al., 2016; Katzmann, Babst, & Emr, 2001; Mukherjee,
Tessema, & Wandinger-Ness, 2006; Scita & Di Fiore, 2010; Thompson et al., 2005). In Mv1Lu,
R1B and HepG2 cells, for example, transforming growth factor-β receptor (TGFβR) is
internalized into sorting endosomes, where it phosphorylates its downstream transcription factor
SMAD2 (Di Guglielmo et al., 2003). The role of dynamin-dependent endocytosis in BMP signal
transduction, however, remains controversial: while inhibiting endocytosis increases BMP-Smad
Figure 14: JNK signaling promotes Tkv internalization through AWD in ISCs.
(a, b) Expression of Tkv-3xHA (a) or AWD (b) in ISCs (arrowheads, GFP+) determined by
immunohistochemistry, when JNK was activated by overexpressing JNK Kinase (hep) or
knocking down puckered (puc) for 4 days.
(c, d) Expression of Tkv-3xHA (c) and AWD (d) in ISCs (arrowheads, GFP+) upon 18h
Ecc15 infection, when JNK signaling was deactivated by overexpressing a dominant
negative form of JNK (bsk
DN
) in ISCs.
(e) Normalized average intensity levels of Tkv-3xHA and AWD in ISCs per posterior midgut
(PM) under conditions of a-d (normalized to the mean values of control samples expressing
mCherry
RNAi
).
(f) Differential expression of AWD or TKV protein between bsk mutant ISCs (DELTA+,
GFP+, indicated by yellow arrowheads) and wildtype ISCs (DELTA+, GFP-, indicated by red
arrowheads) after Ecc15 challenge. Lines connect data for wildtype and mutant ISCs from
same guts in quantification.
(g) Tkv-3xHA expression in puc
RNAi
ISCs (arrowheads, GFP+) with and without awd loss of
function. Tkv-3xHA punctum numbers were quantified.
(h) Expression level of Tkv-3xHA in awd overexpressing ISCs with and without deactivating
JNK signaling by co-expressing bsk
DN
, measured as the average HA intensity in ISCs after
18h Ecc15 infection. Quantifications were normalized to the mean values of samples
overexpressing awd alone.
Error bars indicate SEM (e: n=7 flies, f: n=5-7 flies, g: n=9-11 flies, h=12 flies). P values
were calculated from Student’s t-test, except that ratio paired t-test was performed to
examine the significant differences of AWD or TKV expression between wildtype ISCs and
bsk
170b
ISCs within the same gut (in f): ****p<0.0001; **p<0.01; *p<0.05; NS=not significant.
Experiments were repeated 3 times (in a-e, g-h) or twice (in f).

52

signaling at the Drosophila neuromuscular junction (O'Connor-Giles et al., 2008), endocytosis
has been found to promote signal transduction in neurons and the fly developing wing (Gilboa et
al., 2000; Gui et al., 2016; Hegarty, Sullivan, & O'Keeffe, 2017).
We asked whether AWD-facilitated endocytosis of Tkv is required for BMP signal
transduction in ISCs, and found that over-expressing AWD in ISCs was sufficient to increase
pMAD levels following Ecc15 challenge (Fig. 15a). In addition, overexpression of AWD in
wildtype flies fed PS-341 for 2 days (SFig. 16a), or in ISCs deficient in highwire also further
increased pMAD level in ISCs (Fig. 15c), suggesting that AWD increases BMP signaling activity
in conditions in which Tkv protein is internalized. Accordingly, ISCs expressing two different
RNAi constructs targeting AWD showed reduced pMAD levels after Ecc15 infection (Fig. 15e),
and AWD mutant ISCs did not up-regulate pMAD levels in response to Ecc15 infection (Fig.
15g), confirming that AWD is required for BMP signal activation upon infection. These results
were further confirmed using Flow Cytometry to quantify pMAD levels in GFP-labelled ISCs (Fig.
15b,d,f).
The GTPases Rab5, Rab7, and Rab11 play important roles in sorting/early endosomes,
late endosomes, and recycling endosomes, respectively, during endocytosis. Since Tkv puncta
preferentially localized to Rab5+ early endosomes upon infection, and further overexpression of
AWD after septic challenge promoted Tkv co-localization with lysosomes, I wondered whether
the AWD-facilitated endocytic regulation of BMP signal transduction is dependent on Rab5. I
knocked down Rab5, while over-expressing AWD in ISCs following Ecc15 challenge for 18
hours, and found that, while Tkv aggregated on the ISC membrane in these conditions, pMAD
levels were not increased (Fig. 16b).
Since AWD has been shown to be required for the endocytosis of Notch (Ignesti et al.,
2014), and since I found that, similar to notch deficient ISCs, awd mutant ISCs fail to properly
differentiate (Fig. 15g), I asked whether loss of notch affects the localization of TkvHA and
53

activation of MAD. Loss of Notch did not prevent the endocytosis of TkvHA or MAD
phosphorylation (Fig. 16c), indicating that the endocytic regulation of BMP signaling by AWD is
independent of Notch signaling.
Since AWD provides GTP for dynamin, I also asked whether the regulation of BMP
signal transduction by AWD in ISCs depends on dynamin. Indeed, loss of dynamin (shibire)
inhibited the induction of pMAD in AWD overexpressing ISCs (Fig. 16b).
Altogether, these results confirm that AWD acts to facilitate Tkv internalization through
dynamin-mediated endocytosis in ISCs, and that this internalization is required for the activation
of BMP signaling in the recovery phase during intestinal regeneration.

54

55

Figure 15: AWD regulates MAD signaling in ISCs.
(a, e) pMAD level in wildtype(a and e, arrowheads), awd

over-expressing (a, arrowheads)
and

awd
RNAi
(e, arrowheads) ISCs (GFP+) at 18h after Ecc15 challenge determined by
immunohistochemistry. Average intensity levels of pMAD in ISCs per posterior midgut (PM)
were quantified and normalized to the mean value of control samples expressing
mCherry
RNAi
.
(c) Expression of pMAD in highwire
RNAi
ISCs (arrowheads, GFP+) with and without awd
OE

was revealed by immunohistochemistry.
(b, d, f) Histogram overlay of pMAD fluorescence in GFP+ ISCs under conditions as noted,
measured by intracellular Flow Cytometry assay. Median fluorescence intensity of pMAD in
GFP+ ISCs under these conditions, was computed by FlowJo software and normalized to
the median value of control samples expressing mCherry
RNAi
collected on the same day of
measurement.
(g) Differential expression of pMAD between awd mutant ISCs (DELTA+, GFP+, indicated
by yellow arrowheads) and wildtype ISCs (DELTA+, GFP-, indicated by red arrowheads)
after 18h of Ecc15 challenge. Lines connect data for wildtype and mutant ISCs from same
guts in quantification.
Error bars indicate SEM (a: n=7 flies, b: n≥ 1923 cells for each replicate, c: n=6-7 flies, d:
n≥ 233 cells for each replicate, e: n=7 flies, f: n≥ 6072 cells for each replicate, g: n=6-7
flies). P values were calculated from Student’s t-test in a, c, g and e, except that the ratio
paired t-test was performed to examine the significant differences of pMAD expression
between wildtype ISCs and awd mutant ISCs within the same gut in g. One-tailed Wilcoxon
rank-sum test was performed in b, d and f. ****p<0.0001; **p<0.01; *p<0.05; NS=not
significant. Experiments were repeated 3 times (in a, c and e), or twice (in g).

56

57

2.6 AWD/Tkv/MAD restore ISC quiescence during regeneration.
To test whether, similar to Tkv (Ayyaz et al., 2015), AWD is required to restore ISC
quiescence and re-establish tissue homeostasis after regeneration has concluded, I measured
the number of mitotic figures (phospho-histone H3+ ISCs) in a time-course following infection
with Ecc15. Loss of Tkv or MAD prevented ISC recovery to quiescence post infection, as
reported (Fig. 18a). Overexpression of AWD did not further inhibit ISC proliferation after
recovery from Ecc15 challenge (Fig. 18b), but knockdown of AWD prevented re-establishment
of ISC quiescence, resulting in ISC over-proliferation at 24 hours post Ecc15 infection (Fig. 17a),
similar to Tkv or MAD loss of function conditions (Fig. 18a). Loss of AWD also led to intestinal
dysplasia, while wildtype flies fully recovered from Ecc15 challenge after 2 days (Fig. 17b).
Over-expressing GFP-tagged wildtype Tkv inhibits ISC proliferation in wild-type animals (Ayyaz
et al., 2015), but I did not observe this when ISCs were deficient in AWD (Fig. 17c), in line with
the observation from live imaging that loss of AWD reduces the number of TKV-GFP puncta in
ISCs (Fig. 17g). Even 2 days after regeneration concludes in wild-type flies, AWD deficient ISCs
continued to be active (Fig. 17b). Overexpressing constitutively active Tkv, in turn, was sufficient
to rescue ISC over-proliferation caused by AWD knockdown at 24 hours post septic challenges
(Fig. 17d).
Figure 16: Regulation of MAD signaling by AWD is Rab5 and Dynamin (Shibire)
dependent.
(a) Expression of pMAD in ISCs (arrowheads, GFP+) in which proteasome activity was
inhibited by 2day feeding of 25 µM PS341, with or without awd overexpression.
(b) Expression of Tkv-3xHA and pMAD in wildtype and notch
RNAi
ISCs (arrowheads, GFP+) at
18h post-Ecc15 infection.
(c) Expression of Tkv-3xHA and pMAD in awd
OE
ISCs (arrowheads, GFP+) at 18h of Ecc15
infection when tkv
RNAi
, rab5
RNAi
or shibire
RNAi
was co-expressed respectively. Error bars
indicate SEM (a-c: n=7 flies). P values from Student’s t-test: ****p<0.0001; **p<0.01; *p<0.05;
NS=not significant. Experiments were repeated three times.

58

The induction of Tkv endocytosis by AWD is thus required for the re-establishment of
ISC quiescence. I asked whether this role for AWD would also influence the maintenance of
barrier function of the intestinal epithelium during regeneration. I used the ‘Smurf’ assay, in
which intestinal penetration of a blue food dye is assessed, to measure barrier function (Rera et
al., 2012), and assessed resilience to infection in animals orally infected with Pseudomonas
Entomophila (PE), an enteropathogen that induces tissue damage and causes death. Flies
lacking Tkv/MAD or AWD showed increased barrier dysfunction and rapidly succumbed to PE
infection (Fig. 17e,g), suggesting that recovery of ISC quiescence by inducing AWD and
activating Tkv/MAD signaling plays a critical role in host survival to infection. Overexpression of
constitutively active Tkv, however, also caused increased mortality (Fig. 17h), and, accordingly,
does not rescue barrier dysfunction or mortality after acute PE infection in AWD knockdown
conditions (Fig. 17f,h). It is likely that this is due to continuous inhibition of ISCs proliferation by
constitutively active Tkv (Fig. 18c), preventing proper regeneration of the epithelium.

59

60

Figure 17: AWD/Tkv/MAD promote ISC quiescence and host resistance to acute
infection.
(a) Dynamic mitotic activity of ISCs when awd was specifically knocked down with two
different RNAi lines was measured as numbers of phospho-Histone H3+ (pH3+) cells per gut
during the course of an Ecc15 infection episode of 24h.
(b) Gut dysplasia was observed at posterior midgut 2 days after Ecc15 oral infection when
tkv, mad or awd were knocked down in ISCs respectively. Numbers of pH3+ cells per gut of
these conditions were quantified.
(c, d) Quantification of ISC mitotic activity in response to Ecc15 infection, when awd was
knocked in ISCs with and without co-overexpressing Tkv-GFP fusion protein (c) or
constitutively active Tkv (Tkv
QD
, d), measured as numbers of pH3+ cells per gut.
(e) Portion of Smurf flies when tkv, mad or awd were knocked down in ISCs respectively,
monitored after a prior feeding on PE for 48h.
(f) Portion of Smurf flies when awd was knocked down in ISCs and EBs (with esgG4,
tubG80
ts
driver) with and without Tkv
QD
co-overexpression, monitored after a prior feeding on
PE for 24h.
(g) Survival rates of flies (same as e) in response to acute intestinal damage were monitored
after continuous PE infection.
(h) Survival rates of flies (same as f) in response to acute intestinal damage were monitored
after continuous PE infection.
Error bars indicate SEM (a: n≥10 flies; b: n≥8 flies; c, d: n≥10 flies; e, f: n=3 experiments). P
values in g and h were calculated from log rank test (cohort sizes: g: n = 40, 53, 42, 81 for
mCherry
RNAi
, tkv
RNAi
, awd
RNAi
, mad
RNAi
, respectively; h: n=90, 62, 90, 60 for mCherry
RNAi
,
awd
RNAi
, UAS:Tkv
QD
, awd
RNAi
;UAS:Tkv
QD
, respectively). Other P values from Student’s t-test:
****p<0.0001; ***p<0.001; **p<0.01; * p<0.05, NS=not significant. One representative image
from 4-7 flies tested in a single experiment was shown in b. Experiments were reproduced
twice (in a-c, g), or three times (in d, e, f, h).

61

Figure 18: AWD overexpression doesn’t affect ISC proliferation.
(a, b) Dynamic mitotic activity of ISCs, when tkv, mad or smox was respectively knocked
down (a), or when awd was overexpressed, measured as numbers of pH3+ cells per gut
during the course of an Ecc15 infection episode up to 24h.
(c) Mitotic activity of ISCs with or without Tkv
QD
overexpression in response to 12h Ecc15
infection, measured as numbers of pH3+ cells per gut.
Error bars indicate SEM (a: n≥10 flies, b: n≥10 flies, c: n≥9 flies). P values from Student’s t-
test: ****p<0.0001; ***p<0.001; NS=not significant. Experiments were repeated twice.
62

Chapter 3: Gut cytokines modulate olfaction through metabolic
reprogramming of glia
Infection-induced aversion against enteropathogens is a conserved sickness behavior
that can promote host survival (Ayres & Schneider, 2009; A. Wang et al., 2016). The etiology of
this behavior remains poorly understood, but studies in Drosophila have linked olfactory and
gustatory perception to avoidance behaviors against toxic microbes (Charroux et al., 2020;
Kobler et al., 2020; Stensmyr et al., 2012). Whether and how enteric infections directly influence
sensory perception to induce or modulate such behaviors remains unknown. Here, I found that
enteropathogen infection in Drosophila can modulate olfactory perception through metabolic
reprogramming of EG of the AL. Infection-induced Unpaired cytokine expression in the intestine
activates JAK/STAT signaling in EG, inducing the expression of glial MCTs and the
apolipoprotein Glaz, impacting glia/neuron metabolic coupling in the AL. This modulates
olfaction sensitivity, promoting avoidance of bacteria-laced food and increasing animal survival.
While transient in young animals, gut-induced metabolic reprogramming of EG becomes
constitutive in old animals due to age-related intestinal inflammation, contributing to an age-
related decline in olfaction sensitivity. My work identifies adaptive glial metabolic reprogramming
by gut-derived cytokines as a mechanism causing lasting changes in neuronal function in the
aging animal.

3.1 Enteric infection modulates olfaction.
We used a modified the CAFE assay (Ja et al., 2007) to measure choice between food
containing or not Erwinia Carotovora Carotovora 15 (Ecc15), a non-lethal enteropathogen that
causes intestinal inflammation(Jiang et al., 2009) (Fig. 19a). Consistent with recent reports
(Kobler et al., 2020), naïve flies consumed more Ecc15-containing food than normal food (Fig.
63

19b). But when orally infected with Ecc15 for 24 hours prior to the feeding assays, flies
developed a distinct aversion to food containing Ecc15 (Fig. 19b, Fig. 20a). To assess whether
this involved changes in olfactory perception, I determined the “preference index” (P.I.) for
attractive (such as Putrescine (Hussain et al., 2018)) or aversive odors (such as 3-Octanol
(Hussain et al., 2018)) in T-maze assays (Hussain et al., 2018) (Fig. 19c). Preference or
aversion for attractive or aversive odors, respectively, declined upon infection, indicating that
infection causes a non-selective decline in olfactory discrimination (Fig. 19d). This was transient,
as 5 days after infection, olfaction sensitivity recovered (Fig. 19d), coincident with clearance of
bacteria and epithelial regeneration (Tracy Cai et al., 2019). Olfactory discrimination was not
influenced by starvation or by exposure to heat-killed Ecc15 (Fig. 20b,d). Odorant receptor
mutants (Gr63a
1
and Orco
1
) ingested less Ecc15 food under naïve conditions, and when
infected, failed to further reduce ingestion of Ecc15 containing food (Fig. 20c). Together, these
observations suggest that after an initial odorant-mediated attraction, flies develop aversion to
enteropathogens, through a concerted activation of gustatory and immune receptors (Charroux
et al., 2020; Kobler et al., 2020) and suppression of olfaction.
Upon oral infection with Ecc15, damaged intestinal ECs produce the inflammatory IL6-
like cytokines, Unpaired 2 and 3 (Upd2 and Upd3), to stimulate ISC proliferation and epithelial
regeneration (Jiang et al., 2009). Upds activate the JAK/STAT signaling pathway through the
receptor Dome and the JAK homologue Hop. Using a 2xSTAT::GFP reporter (GFP expression
under the control of STAT binding sites) as a readout of JAK-STAT signaling activity (Bach et al.,
2007), I found upregulated GFP expression in the brain 4 hours post oral Ecc15 infection (Fig.
19e, Fig. 21a), as well as after oral infection with PE, a more lethal enteropathogen that
damages the gut epithelium (Tracy Cai et al., 2019) (Fig. 19e, Fig. 21a). JAK/STAT activity was
observed in a sparse population of cells of the brain that stained positive for the glial marker
Repo (Hakim-Mishnaevski, Flint-Brodsly, Shklyar, Levy-Adam, & Kurant, 2019) (Fig. 19f).
64

Subtype-specific Gal4 drivers revealed that EG were the main population among the five
subtypes of Drosophila glia (astrocytes, ensheathing, perineural, subperineural, and cortex glia
(Freeman, 2015)) that upregulated STAT activity in response to Ecc15 infection (Fig. 19g, Fig.
21b). This was confirmed using four different Gal4 drivers to label EG (Fig. 21c-e) and by flow
cytometry (Fig. 21f). Infection did not influence numbers (Fig. 21d) and membranous processes
(labeled using UAS::mCD4GFP) of EG at the AL (Fig. 21g), and glomerular
compartmentalization in the AL and lobe size remained unaffected (Fig. 21g). JAK/STAT
activation in EG was sufficient and required for infection-induced changes in olfactory
discrimination, as over-expressing constitutively active Hop (Hop
tuml
) (Classen, Bunker, Harvey,
Vaccari, & Bilder, 2009) in EG reduced olfactory discrimination (Fig. 19h), while loss of Dome or
STAT in all glia (repo::Gal4), or specifically in EG (GMR56F03::Gal4), rescued the decline of
olfactory discrimination caused by Ecc15 infection (Fig. 19h, Fig. 22a). Locomotion of flies was
not affected by these genetic perturbations (not shown). Knockdown efficiency of RNAi lines
targeting Dome or STAT was confirmed by immunostaining using the 10xSTAT::GFP reporter
(Bach et al., 2007) (a reporter containing 10 STAT92E binding sites; Fig. 22b). Over-expression
of Hop
tuml
in EG also reduced ingestion of Ecc15-containing food and promoted survival of flies
fed PE containing food, while Dome or STAT knockdown in EG increased ingestion of Ecc15-
containing food in infected flies and increased mortality when flies were fed with PE containing
food (Fig. 19i, Fig. 22c,d,f,g; control perturbations in Fig. 22e). I propose that the corresponding
changes in ingestion of PE-laced food contribute to the reduced mortality, but it is possible that
additional genetic background conditions influence mortality, as seen for example in Orco
mutant flies, which ingest less bacteria (Fig. 20c) but show increased susceptibility to PE (Fig.
22h).

65

66

Figure 19: Temporal activation of JAK/STAT signaling in ensheathing glia upon
infection transiently inhibits olfactory discrimination, contributing to Ecc15 aversion,
and increasing host survival.
(a) Modified CAFE assay used.
(b) Percentages of normal food intake and of Ecc15
+
food intake for wild-type flies with or
without Ecc15 infection.
(c) Olfactory T-maze assay and calculation of preference index (P.I.).
(d) P.I. of young flies 24 hours (1d) and 5 days (5d) post Ecc15 infection, respectively.
(e, f) STAT activity in the brain of infected flies. Numbers of STAT::GFP
+
cells from 48um z-
sections quantified in e. Anti-repo immunohistochemistry to label all glia in f.
(g) STAT activity in each subtype of glia with or without Ecc15 infection. Numbers of GFP
+

mCherry
+
cells in the central brain were quantified from 48um z-sections.
(h) P.I. of young flies with indicated JAK/STAT perturbation in EG. RNAi constructs were
expressed in EG for 7 days by shifting animals to 29ºC (restrictive temperature for Gal80
ts
).
Animals were exposed to Ecc15 for 24 hours.
(i) Intake of Ecc15
+
food by young flies with indicated JAK/STAT perturbation in EG.
Averages and s.e.m. are shown. n=21 flies from 7 replicates per condition for b, n=5-8
independently performed experiments with a cohort of 30-90 flies for each experiment for d,
n=6-7 brains per condition for e, n=5-7 brains per condition for g, n=5-7 independently
performed experiments with a cohort of 30-90 flies for each experiment for h, n=24-27 flies
from 8-9 replicates per condition for i.
Data shown in g are representative of 2 independently performed experiments, and those
shown in b, e, i are representative from 3 separate experiments. P values in g and i (left)
from Mann-Whitney test; other P values from Kruskal-Wallis test. ****p<0.0001;***p<0.001;
**p<0.01; *p<0.05; NS=not significant.

67

68

Figure 20: Orco and Gr63 odor receptors are required for infection-induced avoidance
behaviors towards enteropathogens.
(a) Intake of total food, Ecc15 containing food and normal food for wild-type flies
(w
1118
xOreR) during homeostasis and 24 hours post Ecc15 infection respectively.
(b) Intake of total food, Ecc15 containing food and normal food for wild-type flies
(w
1118
xOreR) during homeostasis, infected with heat-killed Ecc15 or starved on water for 24
hours correspondingly.
(c) Intake of total food, Ecc15 containing food and normal food for wild-type flies
(w
1118
xOreR), Gr63a
1
flies, Orco
1
flies with or without Ecc15 infection respectively.
(d) Preference index (P.I.) of flies in b, measured by T maze assay.
Averages and s.e.m. are shown. The sample size is as follows: n=21 flies from 7 replicates
per condition for a, n=30 flies from 10 replicates per condition for b, n=21-30 flies from 7-10
replicates per condition for c, n=6-8 independently performed experiments with a cohort of
30-60 flies for each experiment for d.
Data shown in b, c are representative of 2 independently performed experiments, and those
shown in a are representative from 3 separate experiments. P values in a from Mann-
Whitney test; other P values from Kruskal-Wallis test. ****p<0.0001;***p<0.001; **p<0.01;
*p<0.05; NS=not significant.

69

70

Figure 21: Infection does not influence numbers and the morphology of ensheathing
glia at the antennal lobe.
(a) Representative images of 2xSTAT::GFP expression in the central brain upon 4 hour
Ecc15 infection or PE infection determined by immunostaining. Anti-GFP antibody amplifies
2xSTAT::GFP signal.
(b, e) Representative images of 2xSTAT::GFP expression in EG (nls.mCherry
+
driven by
GMR56F03::Gal4) in the central brain during homeostasis and upon 4 hour Ecc15 infection.
Antennal lobe (AL) region was zoomed in b and additional images were shown in e. Anti-
GFP antibody amplifies 2xSTAT::GFP signal. Anti-NC82 antibody stained neuropils in e.
(c) Quantifications of 2xSTAT::GFP reporter activity in EG (nls.mCherry
+
in the presence of
corresponding Gal4 drivers) during homeostasis and upon Ecc15 infection. Numbers of
GFP
+
mCherry
+
cells from both ALs were quantified from 30um z-sections (2um each). Four
different EG-specific Gal4 drivers were tested correspondingly.
(d) Quantifications of EG numbers (nls.mCherry
+
driven by SPARC::Gal4, GMR10E12::Gal4
or GMR56F03::Gal4 respectively) at both ALs under mock and infected conditions.
(f) Histogram overlay of GFP fluorescence in mCherry
+
EG in the presence of
GMR56F03::Gal4 under conditions as noted, measured by intracellular flow cytometry
assay. X-axis: the GFP fluorescence intensity level (logarithmic scale); y-axis: the number of
events (normalized to its peak height, noted as normalized to modal). Median fluorescence
intensity of GFP in mCherry
+
EG under these conditions, was computed by FlowJo software
and normalized to the median value of mock samples collected on the same day of
measurement. mCherry
+
EG were sorted by the following gates: 1): forward versus side
scatter (FSC vs SSC); 2): side scatter height versus width (SSC-H vs SSC-W); 3): forward
scatter height versus width (FSC-H vs FSC-W); 4): fixable viability dye (eFluor™ 660 to label
dead cells before fixation) versus DAPI (labelling nuclei to exclude debris); 5): GFP versus
mCherry fluorescence channel (GFP vs mCherry).
(g) Representative images showing EG morphology at the antennal lobe from control and
infected animals. EG Nuclei were labelled by RedStinger, while cellular processes were
labelled by CD4::GFP. Anti-NC82 antibody labelled neuropils. Representative images were
generated from 7 um z-sections (1um each) after performing maximal intensity projection.
Average intensity levels of CD4::GFP were quantified from 20um z-stack confocal images
after maximal intensity projection. Antennal lobe sizes were quantified and normalized to the
mean value of mock animals.
Averages and s.e.m. are shown. The sample size is as follows: n=5-8 brains per condition
for c, n=6-8 brains per condition for d, n=97, 135, 822 mCherry
+
cells from mock flies and
n=123, 91, 145, 163 mCherry
+
cells from infected flies for f, n=8-9 brains per condition for g.
Data shown in c, d, and g are representative of 2 independently performed experiments. P
values from Mann-Whitney test. ***p<0.001; **p<0.01; *p<0.05; NS=not significant.

71

72

3.2 Gut-derived Upd cytokines regulate olfaction.
JAK/STAT activation in glia at the AL could be triggered in naïve flies or prevented in
infected flies by over-expression or knockdown, respectively, of Upd2 and Upd3 in intestinal
ECs using Mex1::Gal4 (Phillips & Thomas, 2006), an EC driver with no expression in the brain
(Fig. 23a-c, Fig. 24a-c). Consistently, EC-derived Upd2 and Upd3 were sufficient and required
for the modulation of olfactory discrimination caused by infection (Fig. 23d, Fig. 24d).
Knockdown of Upd2 or Upd3 did not affect olfaction in naïve flies (Fig. 24d; knockdown
efficiency of RNAi lines targeting Upd2 or Upd3 confirmed by qPCR, Fig. 24e), and perturbing
these ligands in fatbody (cg::Gal4) or hemocytes (hml::Gal4), tissues that are sources for Upds
Figure 22: JAK/STAT signaling in ensheathing glia promotes avoidance behavior
against Ecc15, yet increasing host survival upon acute infection.
(a) Preference index (P.I.) of young infected flies expressing mCherry
RNAi
, Dome
RNAi
or
Stat
RNAi
in all glia (repo::Gal4;tubG80
ts
), measured by T-maze assay.
(b) Quantification of STAT::GFP activity in the glia of flies knocking down Dome
RNAi
or
Stat
RNAi
in all glia (repo::Gal4; 10xSTAT::GFP), to confirm knockdown efficiency for various
RNAi lines targeting Dome or STAT correspondingly.
(c, d) Total food intake and normal food intake of flies overexpressing Hop
tuml
and of infected
flies knocking down Dome and Stat in EG (driven by GMR56F03::Gal4;tubG80
ts
), measured
by CAFE assay.
(e) Intake of total food, Ecc15 containing food and normal food for flies expressing
mCherry
RNAi
, LacZ
RNAi
and UAS::LacZ in EG during homeostasis.
(f, g) Survival curve of flies overexpressing Hop
tuml
(f) or knocking down Dome and Stat (g)
in EG upon continuous PE infection.
(h) Survival curves of wild-type flies (w
1118
xOreR), Gr63a
1
flies, Orco
1
flies upon continuous
PE infection.
Averages and s.e.m. are shown. The sample size is as follows: n=4 independently
performed experiments for a, n=6-8 brains per condition for b, n=24-27 flies from 8-9
replicates per condition for c, n=18-27 flies from 6-9 replicates per condition for d, n=24 flies
from 8 replicates per condition for e, n=74, 96 flies for mCherry
RNAi
and Hop
tuml
respectively
for f, n=97, 118 flies for mCherry
RNAi
and Dome
RNAi
respectively for g, n=101, 63, 90 flies for
wild-type flies (w
1118
xOreR), Orco
1
, Gr63a
1
flies for h.
Data shown in c, d, f, g are representative of 3 independently performed experiments; data
shown in b, e and h are representative of 2 independently performed experiments. P values
from Mann-Whitney test in c; P values from Kruskal-Wallis test in a, b, d and e; P values
from Log-rank test in f-h. ****p<0.0001; **p<0.01; *p<0.05; NS=not significant.

73

in other contexts (Chakrabarti et al., 2016; Rajan & Perrimon, 2012), did not significantly impact
STAT activity in glia at the AL (Fig. 24f-i).
Figure 23: Gut-derived Upd ligands activate STAT in glia and regulate olfaction
sensitivity.
(a) Gut-derived Upds and their possible impact on the AL.
(b, c) Numbers of STAT::GFP
+
glia per antennal lobe from flies overexpressing upd2, upd3
in enterocytes (ECs) during homeostasis (b) and from infected flies after loss of upd2, upd3
in ECs (c).
(d) P.I. of young flies with indicate perturbations of upd2 or upd3 in ECs.
Averages and s.e.m. are shown. n=6-7 flies per condition for b and c, n=5-9 independently
performed experiments with a cohort of 30-90 flies for each experiment for d.
Data shown in b, c are representative of 3 independently performed experiments. P values
from Kruskal-Wallis test. ****p<0.0001; **p<0.01; *p<0.05.

74

75

3.3 Age-related JAK activation leads to EG loss.
Loss of olfaction sensitivity is an early sign of normal aging and neurodegeneration (Doty
& Kamath, 2014; Hussain et al., 2018; Zou et al., 2016). In aging Drosophila, olfactory
perception was reported to deteriorate before vision (Hussain et al., 2018), a decline that I were
able to recapitulate in the T-maze assays (Fig. 25a). Glomerular compartments in the AL
became less organized and less distinct in geriatric (60-70 day old) animals (Fig. 26a) and AL
size increased with age (Fig. 26b). This correlates with a reduction in the number of EG and of
glial membranous processes (Fig. 26b), changes that are expected to impact AL structure (B.
Wu et al., 2017), and thus likely contribute to the age-related decline in olfaction.
Figure 24: Gut-derived Upd2 and Upd3 are sufficient and required for infection-
induced STAT activation in the glia.
(a) Expression of nuclear mCherry driven by Mex1::Gal4 in the gut and brain of adult flies.
(b-c) Activity of 2xSTAT::GFP reporter in the central brain of flies overexpressing upd2, upd3
in ECs, driven by Mex1::Gal4;tubG80
ts
, during homeostasis (b) and of infected flies loss of
upd2, upd3 in ECs (c). Representative images were generated from 30um z-sections, and
the AL region was zoomed in.
(d) Preference index (P.I.) of flies expressing mCherry
RNAi
, UAS::LacZ, LacZ
RNAi
and
additional RNAi lines targeting upd2 or upd3 in ECs with or without Ecc15 infection.
(e) qPCR analysis confirming the knockdown efficiency of multiple RNAi lines targeting upd2
or upd3 correspondingly.
(f, h) Activity of 2xSTAT::GFP reporter in the central brain of flies overexpressing upd2, upd3
in hemocytes (driven by hm1::Gal4) during homeostasis and of infected flies loss of upd3 in
hemocytes. Numbers of GFP
+
repo
+
cells per AL were quantified from 30um z-sections in h,
and the AL region was zoomed in.
(g, i) Activity of 2xSTAT::GFP reporter in the central brain of flies overexpressing upd2 in
fatbody (driven by cg::Gal4) during homeostasis and of infected flies loss of upd3 in fatbody.
Numbers of GFP
+
repo
+
cells per AL were quantified from 30um z-sections in i, and the AL
region was zoomed in.
Averages and s.e.m. are shown. The sample size is as follows: n=4-5 independently
performed experiments for d, n=2-4 replicates per condition for e, n=9-14 brains per
condition for h, n=6-13 brains per condition for i.
Data shown in e, h and i are representative of 2 independently performed experiments. P
values from Kruskal-Wallis test. ****p<0.0001; ***p<0.001; **p<0.01; *p<0.05; NS=not
significant.

76

Aging in Drosophila is accompanied by the development of intestinal inflammation, and
is associated with the constitutive expression and release of Upd cytokines (H. Li et al., 2016).
Consistently, JAK/STAT activity in AL EG was elevated in old flies (Fig. 25b, Fig. 26c), and
knockdown of Dome or STAT in EG specifically (Fig. 25c) or in all glia (Fig. 26d) rescued the
decline of olfactory discrimination in old animals. Knockdown of Dome in EG also rescued the
age-related decline of EGs and restored the size of the AL (Fig. 26e). JAK/STAT activation in
EG of old animals is a consequence of intestinal Upd release, as knocking down Upd2 and
Upd3 in ECs alleviated STAT activation in the AL (Fig. 25d, Fig. 26f), and prevented the age-
related decline of olfactory discrimination (Fig. 25e).
This age-related decline of olfactory discrimination was independent of the microbiota,
as germ-free old flies still exhibited reduced olfaction sensitivity, elevated JAK/STAT signaling in
the AL, decreased numbers of EG, loss of glial cellular processes, and an enlarged AL (Fig. 27).
These results are consistent with the observation that the age-related increase in Upd released
from the gut is independent of the microbiota (H. Li et al., 2016).
To understand why ensheathing but not other glia selectively respond to Upd ligands
and activate JAK/STAT signaling during aging or infection, I performed scRNA-seq on purified
glia from young and old flies. Either all glia (labelled using repo::Gal4) or EGs selectively
(labelled using GMR56F03::Gal4) were profiled using Smart-seq2 (Picelli et al., 2014) (Fig.
28a,b). The expression of dome was significantly higher in EG than in other glia (Fig. 28c),
consistent with the specific upregulation of socs36E, a known target of JAK/STAT signaling, in
ensheathing but not other glia during aging (Fig. 28d). These results are supported by a similar
upregulation of socs36E in EG of old animals observed in a previous scRNA-seq dataset (Davie
et al., 2018) (Fig. 28e,f).

77

78

Figure 25: Chronic activation of JAK/STAT signaling in old EGs causes decline of
olfaction sensitivity during aging.
(a) P.I. of young and old wild-type (w
1118
x OreR) flies.
(b) 2xSTAT::GFP expression

in EG at the AL during aging. GFP
+
mCherry
+
cells from both
ALs were quantified from 20um z-sections per sample.
(c) P.I. of young control flies and of old flies with indicated perturbations in EG.
(d) Numbers of 2xSTAT::GFP
+
glia per AL of old flies with indicated perturbation in ECs.
(e) P.I. of young control flies and of old flies with indicated perturbations in ECs.
Averages and s.e.m. are shown. n=3-7 independently performed experiments with a cohort
of 30-60 flies for each experiment for a, n=5-9 brains per condition for b, n=5-7
independently performed experiments with a cohort of 30-90 flies for each experiment for c,
n= n=8-9 brains per condition for d, n=5-6 independently performed experiments with a
cohort of 30-90 flies for each experiment for e.
Data shown in b and d are representative of 2 independently performed experiments. P
values from Kruskal-Wallis test. **p<0.01; *p<0.05.

79

80

Figure 26: Chronic activation of JAK/STAT signaling in ensheathing glia drives the
decline of ensheathing glia numbers at the antennal lobe during aging.
(a) Representative images of glomerular compartments at the AL from young and old
animals. Confocal images were generated from 20um z-sections (1um each) after
performing maximal intensity projection. Anti-NC82 antibody labelled neuropils.
(b) Representative single z-section images showing EG morphology at the AL from young
and old animals. EG nuclei were labelled by RedStinger driven by GMR56F03::Gal4, while
cellular processes were labelled by CD4::GFP. Average intensity levels of CD4::GFP and AL
sizes were quantified from 20um z-stack confocal images after maximal intensity projection.
AL sizes were quantified and normalized to the mean values of young animals.
(c) Representative images of 2xSTAT::GFP reporter activity in EG (nls.mCherry
+
driven by
GMR56F03::Gal4) at the AL from young and old animals. Images were generated from 20
um z-sections (1um each) after performing maximal intensity projection.
(d) Preference index (P.I.) of old flies expressing mCherry
RNAi
, Dome
RNAi
or Stat
RNAi
in all glia
(repo::Gal4;tubG80
ts
), measured by T-maze assay.
(e) Representative images showing EG morphology at the AL from old flies with or without
Dome knockdown. EG nuclei were labelled by RedStinger in the presence of
GMR56F03::Gal4;tubG80
ts
, while cellular processes were labelled by CD4::GFP. Average
intensity levels of CD4::GFP and numbers of RedStinger
+
cells per AL were quantified. AL
sizes were quantified and normalized to the mean value of old control animals. Flies were
aged at 25C for 14 days followed by 29C for 14 days to induce Dome
RNAi
expression.
(f) Representative images showing the activity of 2xSTAT::GFP reporter in the central brain
of old flies knocking down upd2 or upd3 in ECs, driven by Mex1::Gal4;tubG80
ts
.
Representative images were generated from 30um z-sections, and the AL region was
zoomed in.
Averages and s.e.m. are shown. The sample size is as follows: n=6-8 brains per condition
for b, n=3-4 independently performed experiments for d, n=7-10 brains per condition for e.
Data shown in b and e are representative of 2 independently performed experiments. P
values from Mann-Whitney test in b and e; P values from Kruskal-Wallis test in d. **p<0.01;
*p<0.05; ns=not significant.

81

82

Figure 27: Age-related decline of olfaction sensitivity and morphological decays of
ensheathing glia are independent from microbiota.
(a) Preference index (P.I.) of germ-free wild-type flies (w
1118
xOreR) during aging, measured
by T-maze assay.
(b) Representative images of 2xSTAT::GFP reporter activity in EG at the AL from
conventionally-reared or germ-free old flies. EG nuclei were labelled by nls.mCherry in the
presence of GMR56F03::Gal4 driver. Anti-GFP antibody amplified 2xSTAT::GFP signal.
Anti-NC82 antibody labelled neuropils. Confocal images were generated from 20um z-
sections after performing maximal intensity projection. Flies were aged at room temperature
(RT).
(c, d) Representative images showing EG morphology at the AL from young and old animals
that were conventionally reared and from old germ-free animals respectively (c). EG nuclei
were labelled by RedStinger in the presence of GMR56F03::Gal4, while cellular processes
were labelled by CD4::GFP. Anti-NC82 antibody labelled neuropils. Images were generated
from 20um z-sections after performing maximal intensity projection. Average intensity levels
of CD4::GFP and numbers of RedStinger
+
cells per AL were quantified in d. AL sizes were
quantified and normalized to the mean value of young conventionally reared animals in d.
Flies were aged at room temperature (RT).
Averages and s.e.m. are shown. The sample size is as follows: n=2-7 independently
performed experiments with a cohort of 30-60 flies for each experiment for a, n=6-7 brains
per condition for b, n=5-8 brains per condition for d.
Data shown in b and d are representative of 2 independently performed experiments. P
values from Mann-Whitney test in b; other P values from Kruskal-Wallis test. **p<0.01;
*p<0.05; NS=not significant.

83

84

Figure 28: JAK/STAT signaling regulates glial lipid metabolism.
(a) Workflow of single-cell RNA sequencing (scRNA-seq) using plate-based Smart-seq2.
FACS: fluorescence-activated cell sorting. Four groups of glia were sequenced: 5d and 50d
all glia (GFP
+
, driven by rep::Gal4); 5d and 50d EG (GFP
+
, driven by GMR56F03::Gal4).
(b) Visualization of glial cells using tSNE plots. Cells were colored according to cell types,
ages and Louvain clusters with default resolution. Non-ensheathing glia (non-EG) were
curated from all repo
+
glia with EG (GMR56F03::Gal4
+
) removed. See Methods. EG and
non-EG were readily separated into different clusters (left and middle). In total, 10 clusters
were formed from these glia (right), suggesting the heterogeneity of glial population.
(c) Violin plot showing expression levels of dome in non-EG and EG. For both EG and non-
EG, cells were combined from young and old flies. In non-EG, dome expression was barely
detected except in one cell. In EG, a subset of cells showed high expression of dome.
(d) Violin plots showing expression levels of Socs36E in young and old non-EG (left) and EG
(right) respectively.
(e) Visualization of all annotated glial cells from a previously published whole fly brain
scRNA-seq dataset (Davie et al. 2018) using tSNE plot. scRNA-seq was performed using
droplet-based 10x Genomics platform. Glia were colored in red (repo
+
), while neurons were
colored in grey. Two subsets of EG (in orange box) and six subsets of non-EG (in blue box)
were annotated.
(f) Violin plots showing expression levels of socs36E in non-EG and EG at eight different
ages. Cells from 3 day-, 6 day- and 9 day-old flies were combined as young samples, and
were compared with cells from 50 day-old flies (old).
(g) Gating strategy for sorting STAT::GFP
+
glia and STAT::GFP
-
glia from the brain of young
mock or young infected (4 hour Ecc15 infection) flies overexpressing tdTomato in all glia
(repo::Gal4) while expressing 10xSTAT::GFP reporter.
(h) Visualization of gene expression variation between STAT::GFP
+
glia and STAT::GFP
-
glia
by PCA plot. Each dot represents a sample replicate independently collected from a cohort
of 100 flies. Samples with the same genotype were grouped together, while samples with
different treatments were colored separately.
(i) Volcano plot displaying differentially expressed genes between STAT::GFP
+
glia and
STAT::GFP
-
glia (highlighted in red) under homeostatic conditions, using a cut-off of two-fold
change, p value<0.001, FDR<0.01.
(j) Gene Ontology analysis of significantly upregulated genes in STAT::GFP
+
glia during
homeostasis.
(k) Lipid storage-associated genes were significantly upregulated in STAT::GFP
+
glia during
homeostasis. nRPKM values of each gene in STAT::GFP
+
glia and STAT::GFP
-
glia were
shown correspondingly.
(l) Genes involved in monocarboxylate transport were significantly upregulated in
STAT::GFP
+
glia during homeostasis. nRPKM values of each gene in STAT::GFP
+
glia and
STAT::GFP
-
glia were shown correspondingly.
(m) Schematic demonstrating mitochondrial fatty acid β-oxidation.
(n) Genes involved in fatty acid β-oxidation that were significantly upregulated in
STAT::GFP
+
glia during homeostasis. nRPKM values of each gene in STAT::GFP
+
glia and
STAT::GFP
-
glia were shown correspondingly.
Averages and s.e.m. are shown. P values in k, l and n were calculated by Partek Flow; P
values in c, d and f from Student’s t-test. *****p<0.00001; ****p<0.0001; ***p<0.001;
**p<0.01; NS=not significant.

85

3. 4 Glial JAK activation reprograms lipid metabolism.
Bulk RNA sequencing analysis on glia (repo::Gal4, UAS::tdTomato) purified from brains
of flies expressing a 10xSTAT::GFP reporter(Bach et al., 2007) (Supplementary Fig. 3.7g)
revealed that the transcriptomes of STAT::GFP
+
glia from Ecc15 infected and uninfected
animals were more similar to each other than to STAT::GFP
-
glia of either condition, indicating
that JAK/STAT induction has a stronger influence on glial transcriptomes than other infection-
related changes (Fig. 28h). Differentially expressed genes (866 genes using a cut-off of two-fold
change, p value<0.001, FDR<0.01 and reads>0.5; Fig. 28i), were significantly enriched in genes
encoding proteins involved in lipid metabolism and carbohydrate transmembrane transport (Fig.
28j). These included the lipid binding protein glial lazarillo (Glaz, a homologue of apolipoprotein
D in mammals (L. Liu, MacKenzie, Putluri, Maletic-Savatic, & Bellen, 2017; L. Liu et al., 2015)),
which facilitates lipid transport from neurons to glia in flies (L. Liu et al., 2017; L. Liu et al., 2015),
the lipid droplet surface binding proteins Lsd-1 and Lsd-2 (Fauny, Silber, & Zider, 2005; Men,
Binh, Yamaguchi, Huy, & Kamei, 2016), the diacylglycerol O-acyltransferase Midway (a central
regulator of triacylglycerol biosynthesis (Kühnlein, 2012)), and Coatomer, which is responsible
for protein delivery to lipid droplets (Soni et al., 2009) (Fig. 28k). This induction of lipid storage
genes was coupled with induction of the monocarboxylate transporter (MCT) Outsiders (Out),
and the MCT accessory protein Basigin (Bsg), sugar transporters (Tret1-1 and Tret1-2), and 17
enzymes involved in β-oxidation (Fig. 28l-n).
Glial MCTs promote lipid production in neurons and lipid droplet accumulation in glia by
establishing a neuron/glia “lactate shuttle” (L. Liu et al., 2017). To test a potential role for STAT
signaling in influencing this shuttle at the AL, I assessed lipid droplet accumulation at the AL in
infected young flies using a combination of a neutral lipid probe (LipidTox, deep red) and a lipid
peroxidation probe (C11-Bodipy, 581/591). I observed a transient accumulation of lipid droplets
(LDs) 24 hours post infection, which decreased 4 days post infection (Fig. 29a), possibly due to
86

elevated β-oxidation (Fig. 18m,n) (Ioannou et al., 2019; Schonfeld & Reiser, 2017). Over-
expression of Hop
tuml
in EG of young flies also promoted LD accumulation (Fig. 29b), while
knocking down Dome or STAT rescued infection-induced LD accumulation (Fig. 29c). Glaz and
Outsiders were required for LD accumulation upon infection (Fig. 29d), and over-expressing
Upd2 and Upd3 in the gut induced LD accumulation at the AL, while knockdown of Upd2 or
Upd3 alleviated LD accumulation in infected flies (Fig. 29e). I confirmed the efficiency of target
gene knockdown with the various RNAi lines used by qPCR (Fig. 29f,g). Infection or JAK/STAT
perturbation did not influence lipid peroxidation in LDs in young flies (Fig. 29h,i).

87

88

3.5 Chronic JAK activation leads to lipid toxicity.
During neuronal stress, neurons can preferentially transfer fatty acids to glia, causing
lipid accumulation and increasing fatty acid β-oxidation in glia (Ioannou et al., 2019; L. Liu et al.,
2015). I observed a significant induction of LDs specifically in EG at the AL in old animals (Fig.
31a), phenocopying Hop
tuml
over-expression (Fig. 29b). As fatty acid β-oxidation is a source of
reactive oxygen species (ROS) (Ioannou et al., 2019; Rosca et al., 2012) that can result in lipid
peroxidation, and lipid peroxidation in pigment cells (glia of the retina) promotes the demise of
Figure 29: JAK/STAT signaling regulates LD accumulation via Glaz and Outsiders
upon infection, with no influence on lipid peroxidation.
(a) Immunostaining detecting lipid droplets (LDs) at the AL from young flies during
homeostasis, 24 hours post Ecc15 infection, or 4 days post infection, using LipidTox deep
red probes. LD numbers per antennal lobe were quantified.
(b, c) Immunostaining detecting LDs at the AL from young flies overexpressing mCherry
RNAi

or Hop
tuml
in EG (driven by GMR56F03::Gal4;tubG80
ts
) during homeostasis (b), and from
infected flies knocking down Dome or Stat in EG (c). LD numbers per AL were quantified.
(d) Immunostaining detecting LDs at the AL from infected flies knocking down Glaz or
Outsiders (out) in EG driven by GMR56F03::Gal4;tubG80
ts
. LD numbers per antennal lobe
were quantified.
(e) Immunostaining detecting LDs at the AL from young flies overexpressing Upd cytokines
in ECs, driven by Mex1::Gal4;tubG80
ts
, during homeostasis, and from infected flies knocking
down Upd cytokines in ECs. LD numbers per antennal lobe were quantified.
(f, g) qPCR analysis confirming the knockdown efficiency of multiple RNAi lines targeting
Out, Glaz, Nlaz, and Ldh correspondingly.
(h, i) Representative images showing lipid peroxidation in LDs at the AL from young flies
expressing mCherry
RNAi
or Hop
tuml
in EG (driven by GMR56F03::Gal4;tubG80
ts
) during
homeostasis (h), from young flies 24 hours or 4 days post Ecc15 infection (i, left), and from
infected flies knocking down Dome or Stat in EG (i, right). Lipid peroxidation levels of LDs for
each sample were measured as the mean intensity ratios of 488nm:561nm in LDs. The
ratios were normalized to the mean value of corresponding control samples.
Averages and s.e.m. are shown. The sample size is as follows: n=7-10 brains per condition
for a, n=5-7 brains per condition for b, n=7-13 brains per condition for c, n=7-13 brains per
condition for d, n=5-8 brains per condition for e, n=3-4 biological replicates per condition for f
and g, n=5-6 brains per condition for h, n=7-10 brains per condition for i,.
Images shown in a-e, h-i were generated from 20um z-sections (1um each) after performing
maximal intensity projection. Data shown in a-e, h-i are representative of 3 independently
performed experiments. P values in b, f, g and h from Mann-Whitney test; other P values
from Kruskal-Wallis test. ***p<0.001; **p<0.01; *p<0.05; NS=not significant.

89

photoreceptors in the retina (L. Liu et al., 2015), I reasoned that overall ROS levels might
increase in glia with age. This would be consistent with the observation that oxidative stress
contributes to age-related dysfunction of cholinergic projection neurons within the olfactory
circuit (Hussain et al., 2018). I expressed various genetically encoded ROS sensors in all glia
(repo::Gal4) or in ensheathing glia only (GMR56F03::Gal4) to measure levels of hydrogen
peroxide (H2O2; measured by RoGFP2_Orp1 (Albrecht, Barata, Grosshans, Teleman, & Dick,
2011)) or the glutathione redox potential (E GSH; measured by RoGFP2_Grx1(Albrecht et al.,
2011)) within the mitochondria or cytosol, respectively. Cytosolic H 2O 2 levels were elevated in all
glia and in EG of old flies, while cytosolic E GSH and mitochondrial H2O 2 levels remained
unchanged (Fig. 31b-e). In contrast to acute intestinal infection in young animals, lipids were
peroxidated in LDs of old animals (Fig. 31f). Knocking down STAT specifically in ensheathing
glia, or knocking down Upd2 and Upd3 in gut ECs, inhibited LD accumulation and alleviated
lipid peroxidation in old animals (Fig. 31f,g).
Olfactory discrimination was partially rescued in old and in young infected animals after
Glaz and Out knockdown in EG (Fig. 30a, Fig. 32a). Glaz and Out knockdown also led to more
Ecc15 food consumption, increased mortality after PE exposure, and reduced LD accumulation
in glia of old flies (Fig. 30b,c, Fig. 32b-e). Knocking down lactate dehydrogenase (Ldh) or Out in
PNs (GH146::Gal4), on the other hand, rescued olfactory discrimination of infected or aged flies
(Fig. 30d, Fig. 32f), while food preference or mortality were not influenced (Fig. 32g,h). In
contrast, over-expression of lipase 4 (Lip-4) in PNs, or knockdown of the neuronal lipid binding
protein, neural lazarillo (Nlaz), significantly improved olfactory discrimination in infected or old
flies (Fig. 30d, Fig. 32f), and Lip-4 over-expression increased Ecc15 food consumption and
increased mortality after PE exposure (Fig. 30e,f, Fig. 32i).

90

91

Figure 30: Reducing LDs in ensheathing glia aggravates infection-caused mortality,
yet partially alleviates age-related olfactory degeneration.
(a) P.I. of young infected flies (7 day old) and of old flies (aged at 25C for 14 days followed
by 29C 14 days) after knockdown of the indicated genes in EG.
(b) Ecc15
+
food intake of young infected flies after knockdown of the indicated genes in EG.
(c) Survival curve of young flies upon continuous PE infection after knockdown of the
indicated genes in EG.
(d) P.I. of young infected flies after over-expressing Lip-4, or knocking down indicated genes
in projection neurons (PNs) using GH146::Gal4.
(e) Ecc15
+
food intake of young infected flies with indicated perturbation in PNs.
(f) Survival curve of flies with indicated perturbation upon continuous PE infection.
(a-f) Averages and s.e.m. are shown. n=3-14 independently performed experiments with a
cohort of 30-60 flies for each experiment for a, n=18-24 flies from 6-8 replicates per condition
for b, n=102, 120, 104, 132 and 84 flies for mCherry
RNAi
, Dome
RNAi
, Stat
RNAi
, Glaz
RNAi
and
Out
RNAi
respectively for c, n=4-13 independently performed experiments with a cohort of 30-
60 flies for each experiment for d, n=24 flies from 8 replicates per condition for e, n=61 and
80 flies for mCherry
RNAi
and Lip-4 correspondingly in f.
Data shown in b, c are representative of 2 independently performed experiments, and those
shown in e, f are representative from 3 separate experiments. P values in c and f from Log-
rank test; P values from Mann-Whitney test in e; other P values from Kruskal-Wallis test.
**p<0.01; *p<0.05; NS=not significant.

92

93

Figure 31: Deactivation of JAK/STAT signaling alleviates lipid toxicity during aging,
thus rescuing the age-related decline of ensheathing glia numbers.
(a) Immunostaining detecting LDs in EG (RedStinger
+
, CD4::GFP
+
) at the AL of young (5-7
day old) and old (51-54 day old) animals, using LipidTox deep red probes. LD numbers per
glia were quantified.
(b) Cytosolic H2O2 levels in EG at the AL from young (7 day old) and old (50 day old)
animals, measured as the mean intensity ratio of 405nm:488nm. The ratios for old animals
were normalized to the mean value for young animals.
(c-e) Levels of cytosolic H2O2 (c), cytosolic glutathione redox potential (d) and mitochondrial
H2O2 (e) in all glia (driven by repo::Gal4) from young and old animals, measured as the
mean intensity ratios of 405nm:488nm for corresponding ROS sensors.
(f) Representative images showing lipid peroxidation in LDs at the AL from young flies
expressing mCherry
RNAi
in EG (driven by GMR56F03::Gal4;tubG80
ts
) and from old flies
expressing mCherry
RNAi
or Stat
RNAi
in EG. LD numbers per AL were quantified. Lipid
peroxidation levels of LDs for each sample were measured as the mean intensity ratio of
488nm:561nm. The ratios were normalized to the mean value of young control samples.
Flies were aged at room temperature (RT) before transferred to 29C for 7 days.
(g) Representative images showing lipid peroxidation in LDs at the AL from old flies loss of
upd2 or upd3 in ECs driven by Mex1::Gal4;tubG80
ts
. LD numbers per AL were quantified.
Lipid peroxidation levels of LDs for each sample were measured as the mean intensity ratio
of 488nm:561nm. The ratios were normalized to the mean value of old control samples.
Averages and s.e.m. are shown. The sample size is as follows: n=6-8 brains per condition
for a, b, n=6-7 brains per condition for c-e, n=8-11 brains per condition for f, n=4-6 brains per
condition for g.
Images shown in a-g were generated from 20um z-sections (1um each) after performing
maximal intensity projection. Data shown in a-e are representative of 2 independently
performed experiments, and those shown in f and g are representative of 3 separate
experiments. P values in a-d from Mann-Whitney test; other P values from Kruskal-Wallis
test. ***p<0.001; **p<0.01; *p<0.05; NS=not significant.

94

95

Figure 32: Inhibiting lipid export or lactate intake in projection neurons partially
rescues the decline of olfaction sensitivity upon infection and during aging.
(a) Preference index (P.I.) of young infected flies knocking down Dome, Stat, Glaz or
Outsiders (out) in EG with additional RNAi lines.
(b, c) Intake of total food, Ecc15
+
food and normal food for mock flies during homeostasis
and for infected flies loss of Dome, Stat, Glaz or Out, measured by CAFE assay. Glaz
RNAi

and Out
RNAi
lines in b and c are different.
(d) Survival curve of young flies loss of Glaz or Out upon continuous PE infection. Glaz
RNAi

and Out
RNAi
lines are the same as flies in b.
(e) Representative images showing LD accumulation and lipid peroxidation at the AL from
old flies with knockdown of Glaz or Out in EG driven by GMR56F03::Gal4;tubG80
ts
. LD
numbers per AL were quantified. Lipid peroxidation levels of LDs for each sample were
measured as the mean intensity ratio of 488nm:561nm. The ratios were normalized to the
mean value of old control samples. Flies were aged at 25C for 14 days followed by 29C 14
days to induce expression of RNAi lines.
(f) P.I. values of old flies overexpressing Lip-4, or knocking down Nlaz, Ldh, or Out in
projection neurons (PNs) using GH146::Gal4 driver.
(g) Intake of total food, Ecc15
+
food and normal food for young infected flies knocking down
Nlaz, or Out in PNs.
(h) Survival curve of flies knocking down Nlaz or Out in PNs upon continuous PE infection.
(i) Intake of total food and normal food for young infected flies over-expressing Lip-4 in PNs.
Averages and s.e.m. are shown. The sample size is as follows: n=4-5 independently
performed experiments with a cohort of 30-90 flies for each experiment for a, n=15-21 flies
from 5-7 replicates per condition for b, n=18-24 flies from 6-8 replicates per condition for c,
n=100, 59, 85 flies for mCherry
RNAi
, Glaz
RNAi
, Out
RNAi
respectively for d, n=7-15 brains per
condition for e, n=4-13 independently performed experiments with a cohort of 30-90 flies for
each experiment for f, n=18-24 flies from 6-8 replicates per condition for g, n=49, 86, 87, 53
flies for mCherry
RNAi
, Nlaz
RNAi
, Out
RNAi
(v51157), Out
RNAi
(BL67858), respectively for h, n=24
flies from 8 replicates per condition for i.
Data shown in b-d, g, h are representative of 2 independently performed experiments, and
those shown in e and i are representative from 3 separate experiments. P values in d and h
from Log-rank test; P values in i from Mann-Whitney test; other P values from Kruskal-Wallis
test. ***p<0.001; **p<0.01; *p<0.05; NS=not significant.

96

Chapter 4: Summary and Discussion
My thesis work has identified a central mechanism responsible for a return to ISC
quiescence during regeneration, and has important implications for our understanding of SC
regulation and tissue homeostasis in barrier epithelia. My work has also uncovered that gut-
derived cytokines, which are known to promote ISC proliferation and tissue regeneration upon
infection, can reprogram glial lipid metabolism to modulate olfactory perception, thus promoting
avoidance behavior towards enteropathogens and increasing host infection tolerance. This
adaptive reprogramming of glial metabolism by gut-derived cytokines, however, leads to lasting
changes in glia and promotes olfactory degeneration during aging.
My results have suggested that the AWD-dependent endocytic regulation of BMP
receptor, Tkv, is an essential step to switch ISC from proliferation to quiescence during
regeneration (Fig. 33). Highwire-mediated Tkv degradation ensures low levels of Tkv protein in
quiescent ISCs, while changes in proteasome activity and subsequent AWD-facilitated
internalization of Tkv in activated ISCs are essential steps for the switch-on of MAD signaling.
These findings are further connected to JNK-mediated activation of AWD expression, thus
providing a temporally resolved model for the transition from activated ISCs to resting ISCs after
regeneration has concluded. My results have also shown that this control of Tkv internalization
in the late phase of the regenerative response is essential for the re-establishment of epithelial
homeostasis after injury, thus providing insight into the mechanisms ensuring tissue
homeostasis by dynamic control of somatic stem cell activity.

97

Figure 33: Dynamic control of ISC activity by AWD-facilitated endocytic regulation of
Tkv/MAD signaling during the regenerative response.
(a) Model. Under homeostatic conditions, Highwire and proteasomes maintain high turn-over
of Tkv protein, leading to its absence in ISCs. During the early induction phase after
infection, Dpp ligands first bind to constantly expressed Sax, promoting ISC proliferation
through Smox signaling. Meanwhile, activated JNK stabilizes Tkv on ISC membrane,
potentially by inhibiting proteasomal activity, while upregulating AWD expression. During the
late recovery phase, stabilization of Tkv protein followed by AWD-facilitated internalization to
early endosomes switches on MAD signaling, allowing a return to ISC quiescence.
(b) Timeline of ISC proliferation and relative expression of Tkv/Sax/Highwire/Awd during one
regeneration episode.

In addition, my results have suggested that gut-derived inflammatory cytokines play an
important role in modulating glia/neuron metabolic coupling in the brain of Drosophila. This
interaction causes an adaptive temporary halt of olfactory discrimination upon intestinal infection,
98

but contributes to age-related olfactory decline (Fig. 34). My findings have indicated that the gut-
derived cytokines Upd2 and Upd3 reprogram lipid metabolism in EG, increasing lactate and lipid
transport between glia and olfactory neurons and resulting in LD accumulation and upregulation
of mitochondrial β-oxidation. This upregulation, in particular, may act as a source of elevated
ROS production during aging. Chronic activation of this JAK/STAT-induced metabolic shift in old
animals results in the accumulation of peroxidated lipids in EG and their associated
morphological decay. My results have identified this chronic metabolic shift and decline of EG
numbers as a contributing factor in the previously described functional decline of olfactory
neurons (Hussain et al., 2018; Ioannou et al., 2019; L. Liu et al., 2017; L. Liu et al., 2015).
Figure 34: Model for the impact of gut-derived cytokines on neuron/glia metabolic
coupling at the antennal lobe.
Acute infection causes a temporary halt of olfaction sensitivity by activating JAK/STAT
signaling in glia, which promotes transient accumulation of lipid droplets by Glaz and Out. This
leads to avoidance towards enteropathogen and increases host survival. During aging, chronic
activation of JAK/STAT signaling leads to lipid accumulation and lipid peroxidation, contributing
to age-related loss of ensheathing glia and olfactory degeneration.

99

4.1 Endocytic regulation of BMP signaling
Although previous studies have indicated that clathrin/dynamin-dependent endocytosis
of BMP type I receptors is conserved in various models, including C. elegans, Drosophila,
mouse, and human fibroblasts, the role of endocytosis in BMP signal transduction remains
inconclusive, and may depend on the specific endocytic trafficking routes of the receptors in
each context (Amsalem et al., 2016; Gleason, Akintobi, Grant, & Padgett, 2014; Gui et al., 2016;
Katzmann et al., 2001; O'Connor-Giles et al., 2008; Rodal et al., 2011; Thompson et al., 2005).
My results have suggested that the stabilization of Tkv, and its accumulation on the plasma
membrane is not sufficient to activate MAD signaling in ISCs, but that AWD-facilitated
internalization into Rab5+ endosomes is required. I didn’t observe a significant decline in TkvHA
levels in awd gain of function conditions, but the live imaging results revealed that increased
awd activity can promote localization of Tkv to lysosomes, suggesting that AWD-facilitated
receptor internalization promotes both signaling activity and the subsequent turnover of ligand
receptor complexes in lysosomes.
The endocytic role of AWD has been implicated in the regulation of multiple signaling
pathways during development, including PVR signaling (Nallamothu et al., 2008), FGF signaling
(Dammai et al., 2003), Notch signaling (Ignesti et al., 2014), and Domeless signaling (Ignesti et
al., 2014). My thesis work has suggested that in ISCs, AWD specifically regulates Tkv/MAD
signaling, not Sax/Smox signaling, and that this regulation is independent of its role in Notch
signaling, as the internalization of Tkv and the activation of pMAD is not affected by loss of
notch in ISCs.
AWD participates in endocytosis by enhancing dynamin (shibire) activity and by
regulating Rab5 function in early endosome maturation (Dammai et al., 2003; Fancsalszky et al.,
2014; Ignesti et al., 2014; Nallamothu et al., 2008; Woolworth, Nallamothu, & Hsu, 2009).
Accordingly, MAD phosphorylation downstream of AWD-facilitated endocytosis of Tkv is Rab5
100

and dynamin-dependent in ISCs. This supports the role of AWD as a supplier of GTP for Rab5
and dynamin GTPases, and contributes to our understanding of the complex role of endocytosis
in BMP signal transduction. Dynamin-dependent endocytosis has been shown to negatively
regulate BMP-Smad signaling at Drosophila neuromuscular junction (O'Connor-Giles et al.,
2008), but this contrasts with its function in neurons and wing crossvein formation (Gui et al.,
2016; Hegarty et al., 2017). My results suggest positive regulation of BMP signaling by
endocytosis in ISCs.

4.2 The role of BMP signaling in controlling ISC activity during regeneration
Previous studies have suggested that ISC proliferation is regulated by a complex
interplay of cell autonomous and non-autonomous signals, which engage JNK and BMP
signaling, as well as other signaling pathways, including JAK/STAT, EGFR, Insulin, Hippo, and
Wingless signaling (Biteau et al., 2011; Jiang et al., 2009; Karpowicz et al., 2010; Lemaitre &
Miguel-Aliaga, 2013; H. Li & Jasper, 2016; G. Lin et al., 2008; F. Ren et al., 2010; Rera et al.,
2012; Shaw et al., 2010; Staley & Irvine, 2010; A. Tian et al., 2016). A sophisticated
understanding of signaling dynamics controlling the transition from quiescent to activated ISCs
after tissue damage is emerging (Deng et al., 2015; H. Li & Jasper, 2016). My results have
clarified the molecular events that mediate the return from the activated state to quiescence in
the recovery phase of the regenerative response. JNK activation, which occurs early in
regenerative responses (Biteau et al., 2008), initiates this transition by promoting Tkv
stabilization and internalization. Detailed in vivo analysis of signaling pathway activities for other
pro-proliferative pathways in ISCs during the regenerative response will be needed to address
the question of whether specific inactivation of those pathways in ISCs also contributes to the
return to quiescence.
101

BMP signaling has a complex role in the regulation of intestinal homeostasis (Ayyaz et
al., 2015; Z. Guo et al., 2013; Z. Li et al., 2013; A. Tian & Jiang, 2014; A. Tian et al., 2017), and
my results support previous findings reporting that Tkv/MAD signaling is required for the re-
establishment of epithelial homeostasis in the recovery phase of the regenerative response.
Accordingly, lack of AWD/Tkv/MAD signaling leads to ISC over-proliferation, epithelial dysplasia,
and barrier dysfunction. These findings are consistent with the role of BMPR in the mammalian
intestinal epithelium regeneration, as loss of BMPRIA causes overgrowth of the crypt (He et al.,
2004).
Which downstream mechanisms mediate these effects of Tkv/MAD signaling, however,
remain largely unknown. A previous study has identified Tis11 as a critical mediator of the return
to quiescence in ISCs (McClelland et al., 2017). Tis11 promotes degradation of mRNAs
encoding pro-mitotic factors, and its expression peaks around 16 hours post Ecc15 infection,
coinciding with Tkv accumulation and MAD activation. It is therefore interesting to speculate that
Tis11 acts downstream of MAD signaling to promote the re-entry into quiescence. Future
studies will investigate this hypothesis.

4.3 Novel roles of AWD in intestinal regeneration.
To date, studies of AWD using model organisms have provided important insight into its
role in vesicle transport during development (Dammai et al., 2003; Fancsalszky et al., 2014;
Ignesti et al., 2014; Nallamothu et al., 2008; Woolworth et al., 2009). AWD, or its mammalian
homologue NME1, has also been identified as a conserved metastasis suppressor by regulating
tumor cell motility and invasion(Banerjee, Jha, & Robertson, 2015; Fan et al., 2013;
Fancsalszky et al., 2014; Jarrett et al., 2013). My results contribute to this body of work by
providing evidence supporting an essential role of AWD in the control of ISC proliferative
102

plasticity and epithelial regeneration. It is expected that additional downstream effectors of AWD
beyond Tkv/MAD signaling (such as changes in Notch signaling activity) contribute to the
precise control of ISC function and intestinal regeneration. Given the evolutionary conservation
of the investigated signaling pathways, as well as of the control of somatic stem cell regulation
(Haller et al., 2017), it will be of interest to investigate this role of AWD/NME1 in tissue
regeneration further. New insight into the control of tissue regeneration and homeostasis can be
expected from such work.

4.4 Neuron/glia metabolic coupling
Previous studies have suggested that glia can provide metabolic support for neurons
during development or in the adult brain (Damisah et al., 2020; Zuchero & Barres, 2015).
However, such metabolic coupling seems to be essential for the alleviation of neuronal stress
(Ioannou et al., 2019; L. Liu et al., 2017). My thesis work advances our understanding of how
neuron/glia metabolic coupling can be influenced by peripheral signals. This is of particular
importance for understanding the etiology of neurodegenerative diseases. In Alzheimer’s
Disease, for example, changes in lipid processing between neurons and glia associated with
APOE4 are thought to be a major risk factor for the severity of the disease (Y. T. Lin et al., 2018;
C. C. Liu, Liu, Kanekiyo, Xu, & Bu, 2013). Through a mechanism similar to the one described
here, chronic intestinal infection or inflammation could shift the balance of lipid metabolism and
transport in the human brain, an assault that might become more pernicious in patients who
carry the APOE4 allele. Understanding the interaction between inflammation and metabolic
shifts in neurons and glia is thus likely to provide further insight into the etiology of
neurodegenerative diseases.
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How do changes in glial metabolism influence neuronal activity in the antennal lobe?
Recent studies have suggested that lipid droplet accumulation and the susceptibility of these
lipids to peroxidation are detrimental for neuronal health (Ioannou et al., 2019; L. Liu et al., 2017;
L. Liu et al., 2015; Nguyen et al., 2017; Unger, Clark, Scherer, & Orci, 2010). Lipid transfer from
neurons to glia can be protective for hyperactive neurons, as transferred lipids are further
consumed by glial mitochondria, which in turn promotes the expression of detoxification genes
in glia (Ioannou et al., 2019). At the same time, it was reported that retinal degeneration is likely
a consequence of synergistic effects of lipid droplet accumulation combined with lipid
peroxidation and oxidative stress in Drosophila and mice (L. Liu et al., 2017; L. Liu et al., 2015).
My results suggest that reducing lipid load in glia without influencing lipid peroxidation partially
rescues olfaction sensitivity during infection, reducing enteropathogen avoidance and
sensitizing the animal to infection. This suggests that LD accumulation in ensheathing glia
modulates the function of PNs through mechanisms other than (or in addition to) lipid
peroxidation. In aging flies, on the other hand, I find that the long-term consequences of chronic
JAK/STAT – mediated metabolic reprogramming include increased lipid peroxidation, possibly
through the upregulation of mitochondrial β-oxidation. This may contribute to the age-related
decline of EG, compromising neuronal function. Detailed characterization of this metabolic
reprogramming, and further exploration of the role of lipid synthesis in PNs for glial lipid
accumulation and for olfactory perception are important avenues for further study.

4.5 Complicated roles of JAK/STAT signaling in the CNS
As introduced above, JAK/STAT signaling has been implicated in various physiological
and pathological processes in the CNS (Ben Haim et al., 2015; Boza-Serrano et al., 2018; Copf
et al., 2011; Doherty et al., 2014; Herrmann et al., 2008; Nicolas et al., 2013; Purice et al., 2017;
Qin et al., 2016; Ray et al., 2017). These studies reveal a complex role for JAK/STAT signaling
104

in the control of glial and neuronal function in different contexts, and specific outcomes of
JAK/STAT activation in a given situation are likely determined by the spatial and temporal
availability of specific ligands. My data demonstrate that in flies Upd2 and Upd3 exert a non-
redundant role in modulating olfactory perception. Upd3 has been shown to act locally in the gut,
while Upd2 acts as a long-distance signal (Hombría, Brown, Häder, & Zeidler, 2005; Wright,
Vogt, Smythe, & Zeidler, 2011), raising the possibility that local Upd3 signaling in the gut
controls Upd2 production, which then triggers JAK/STAT activation in EGs. It will be interesting
to explore this relationship in more detail (Chakrabarti et al., 2016; H. Li et al., 2016; S. C. Wu et
al., 2017).

4.6 Antagonistic pleiotropy of olfactory modulation
My results also add to the emerging insight into the regulation of avoidance behavior
against enteropathogens in insects. Previous studies have identified a requirement for gustatory
bitter neurons (Charroux et al., 2020) and for immune receptors in octopaminergic neurons
(Kobler et al., 2020) in this complex but essential behavior. Upds constitute an additional direct
signal from the damaged intestinal epithelium, and I proposed that Upd-mediated suppression
of olfactory perception is required to prevent sensory interference and attraction to a food
source after pathogenicity has been established. This notion is consistent with the fact that flies
are attracted to Ecc15 containing food for about an hour through olfactory cues, before the
aversion behavior is established by activation of gustatory neurons (Charroux et al., 2020).
Suppressing olfaction at that later stage would thus stabilize the avoidance behavior. It will be
interesting to explore the relationship between the various signals in the establishment and
execution of this adaptive behavior.
105

My thesis work also highlights an instance of ‘antagonistic pleiotropy’ in which a short-
term adaptive mechanism that has presumably evolved to increase tolerance to infections, has
long-term deleterious consequences in the aging animal. Here, the mechanism contributes to
the decline of olfaction sensitivity, and it highlights the need to explore similar
neuroinflammatory processes that play important adaptive roles early in life, but can contribute
to age-related neurodegeneration in humans. Understanding metabolic changes elicited by such
neuroinflammatory processes in glia and neurons may further reveal intervention strategies to
mitigate the damage caused by chronic exposure to inflammatory cytokines.

106

Materials and Methods
Drosophila stocks, husbandry and treatments
Flies were kept on standard fly food at 25 °C and 65% humidity with a 12 h light/dark
cycle and only female animals were used in all experiments. The Gal4-UAS target expression
system was used to conditionally express UAS-linked transgenes in the presence of indicated
Gal4. Crosses with tub::G80
ts
were maintained at 18°C on standard fly food and 3 day-old
female adults were transferred to 29°C to temporarily induce transgene expression, unless
otherwise indicated. Crosses without tub::G80
ts
were maintained at 25°C on standard fly food.
The following fly lines were obtained from Bloomington Drosophila Stock Center: w
1118
,
mcherry RNAi(35785), UAS::Tkv-EGFP (51653), smox RNAi (26756), mad RNAi (31315), hiw
RNAi(28031), awd RNAi
#1
(33712), awd RNAi
#2
(42532), shibire RNAi(28513), rab5 RNAi(30518),
UAS::Rab5-GFP(43336), bsk
DN
(6409), fused RNAi(31043), ube3a RNAi(31972), smurf
RNAi(40905). pentagone RNAi(51169), dally RNAi(28747), dally-like(dlp) RNAi(34089),
UAS::Tkv
QD
(36536), Oregon-R (OreR), Gr63a
1
(9941), Orco
1
(23129), UAS::Hop
tuml
/FM7c(8492),
upd2 RNAi(33988), upd2 RNAi(33949), dome RNAi(34618), stat RNAi(35600), ldh RNAi(33640),
GMR54H02Gal4(45784), GMR54C07Gal4(50472), GMR86E01Gal4(45914),
GMR56F03Gal4(39157), UAS::LacZ(1776), UAS::nls.mCherry(38425), GMR10E12Gal4(46517),
SPARCGal4(77473), GMR83E12Gal4(40363), TubG80
ts
(7013), 10xSTAT::GFP(26198),
repoGal4(7415), UAS::lipase-4 (67142), GH146Gal4(30026), out RNAi(67858),
UAS::MitoRoGFP2_Orp1(67667), nSybGal4(51635), UAS::mCD8-GFP(5137), actinGal4(4414),
hmlGal4, UAS::2xGFP(30140), UAS::2xGFP(60292).
The following fly lines were provided by Vienna Drosophila RNAi Center: tkv RNAi
(3059), puc RNAi (3018), lkb1RNAi(108356KK), dome RNAi(106071), stat RNAi(106980), Glaz
RNAi(15387), Glaz RNAi(107433), upd3 RNAi(27134), Nlaz RNAi(35558), out RNAi(51157).
107

The following fly lines were gift from other labs: UAS::CL1-GFP(Dr. Udai B Pandey), Hiw
ΔN/ΔN
(Dr. Arson DiAntonio), UAS::Awd S1 and UAS::Awd T7 (Dr. Tien Hsu(Dammai et al.,
2003)), FRT82, Awd
j2a4
(Dr. Tien Hsu), UAS::Hep (Dr. Marek Mlodzik), MARCM40A
(hsFlp;FRT40A tub-Gal80;tub-Gal4,UAS-GFP) (Dr. Benjamin Ohlstein), FRT40A, bsk
170b
(Dr.
Nicholas E. Baker), notch RNAi and MARCM82(hsFlp; tub-Gal4, UAS-GFP; FRT82,
tubGal80)(Dr. Nobert Perrimon), UAS::hiw
ΔRing
(Dr. Pejmun Haghighi), esg
ts
F/O (esgGal4,
tubG80
ts
, UAS-GFP; UAS-flp, act > STOP > Gal4, Dr. Huaqi Jiang), 2xSTAT::GFP (Erika Bach),
LacZ RNAi(Masayuki Miura), UAS::Hop
tuml
/cyo (David Bilder), upd3 RNAi (Steven Hou),
UAS::upd2 (Martin Zeidler), UAS::upd3 (Nicolas Buchon),
UAS::CD4GFP,UAS::RedStinger/Tm6 (Liqun Luo) , NP1Gal4 (Dominique Ferrandon),
Mex1Gal4;tubG80
ts
(Lucy O’Brien), UAS::tdTomato (Michael A. Welte), cgGal4(Carl S.
Thummel), UAS::CytoRoGFP2_Orp1 and UAS::CytoRoGFP2_Grx1 (Tobias Dick).
UAS::Sax(F001576) was obtained from FlyORF (Zurich ORFeome Project).
Standard fly food was prepared with the following recipe: 1L distilled water, 22g
molasses, 6.2 ml propionic acid, 13g agar, 80g corn flour, 65g malt extract, 18g brewer’s yeast,
10g soy flour, 2g methyl-p-benzoate in 7.3 ml of EtOH. For proteasome inhibitor feeding
experiments, 20uM Bortezomib (PS-341) from ApexBio(Cat No.A2614) was additionally added.
For Smurf experiments, 500mg/ml of Blue dye no. 1 (Alfa Chem) was additionally added, and
45-60 female flies (20-30 flies per vial) were flipped three times a week. Smurf flies were
counted visually every other day.
This study follows all ethical regulations for research required for the use of Drosophila
melanogaster as an animal model. Complying with NIH regulations, no ethical approval was
required for work with Drosophila melanogaster.

108

Generation of TkvA-lacZ and Tkv-3xHA reporter lines
TkvA is an intronic fragment from the tkv genomic locus (around 4kb, Supplementary Fig.
2.1a) and was amplified by genomic PCR using primers: BglII_tkvA (forward):
GGTTTagatctAGGATCAGAGGGATATGAGGATGCC; Acc65I_tkvA (reverse):
GGTTTggtaccGACGAATGTGCAACAGTTGGAAACGC. The fragment was cloned into the
BglII/Acc65I sites of the reporter vector placZattB and the construct was inserted in the landing
site attP2 on chromosome 3L by phiC31/attB integration. TkvA was the only fragment from a
collection of reporter constructs tilling the genomic locus of tkv to activate reporter expression in
ISCs.
Genome engineered tkv carries three tandem repeats of the hemaglutinin (HA) tag at the
C-terminus and was generated by homologous recombination followed by site-directed insertion
(Baena-Lopez et al., 2013; Norman et al., 2016). First, the two last exons of the gene were
replaced by an attP-containing cassette using the vector pTV(Cherry) and homology arms
flanking the deleted segment, generating tkv[ko,attP]. In the second step, the gene was
reconstituted by re-inserting the missing exons to generate tkv[attP/B,3xHA] (tkv-3xHA in short).
To this end, the last two exons of tkv (including the intervening intron) were cloned into the
vector RIV (white), modified to include sequences coding for the HA tags just prior to the stop
codon and inserted in the tkv[ko,attP] chromosome by standard phiC31/attP transgenesis. The
mini-white cassette used for selection was removed by Cre-mediated recombination resulting in
the final tkv-3xHA chromosome, which, besides the HA tag, contains a attP/B hybrid sequence
in the last large intron of tkv and a single loxP site in the 3’UTR of the gene as remnants of the
genome engineering. The integrity of the generated chromosomes was confirmed molecularly
and genetically. Flies with tkv-3xHA as the only source of TKV develop normally, display no
obvious phenotypic abnormalities and are fully fertile.

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Immunostaining
Adult female Drosophila guts were dissected in 1×, PH 7.4 phosphate-buffered saline
(PBS), and fixed for 30 minutes at room temperature in fixation buffer containing: 25 mM KCl,
100 mM glutamic acid, 1 mM MgCl 2, 20 mM MgSO 4, 4 mM sodium phosphate, and 4%
formaldehyde. Guts were washed for 30 minutes - 1 hour at 4 °C in washing buffer containing:
1x PBS, 0.5% bovine serum albumin and 0.1% Triton X-100, followed by incubation in primary
antibodies overnight at 4 °C, 1h washing at 4 °C, and secondary antibodies for 2 hours at room
temperature. For pSMad3 staining, phosphatase inhibitor (Roche, 4906837001) was added in
fixation buffer, 1 hour wash, and primary antibody incubation following the same protocol above.
For Delta staining, methanol–heptane fixation method was used(H. Li et al., 2013). For
LysoTracker staining, guts were dissected following the above protocol and incubated in 1x PBS
containing 50uM LysoTracker® Red DND-99 (Thermo Fisher Scientific, L7528) for 5-10 minutes
at room temperature. Guts were washed in 1x PBS for three times (10 minutes each time),
followed by regular fixation protocol as described above.
Adult female Drosophila heads were dissected in 1×, PH 7.4 phosphate-buffered saline
(PBS), and fixed for 20 minutes at room temperature in fixation buffer containing: 1xPBS and 4%
formaldehyde. Heads were washed in washing buffer (1xPBS, 0.1% Triton X-100) for 1 hour
(20min each, 3 times), followed by incubation in blocking buffer (1x PBS, 0.1% Triton X-100, 5%
donkey serum) at room temperature for 1 hour. Samples were incubated in primary antibodies
for two nights at 4 °C, followed by 1.5 hour washing at room temperature (30min each, 3 times),
and secondary antibody incubation for 2 hours at room temperature. For neutral lipid droplet
staining, brains were dissected and fixed as above, followed by 30min wash in washing buffer.
Brains were stained with HCS LipidTOX™ Deep Red neutral lipid stain (ThermoFisher, H34477,
1:200 diluted in 1xPBS) on an orbital shake at room temperature overnight. Following one wash
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with 1xPBS, brains were mounted with SlowFade™ Gold Antifade Mountant (ThermoFisher,
S36936) and imaged on the same day.
Primary antibodies and dilution used in this study: rabbit anti-pSMad3 (Epitomics Cat.
No. EP823Y, 1:500), rabbit anti-β-galactosidase (Cappel MP Biomedicals, 1:5000), rabbit anti-
phospho-Histone H3 Ser 10 (EMD Millipore Cat. No. 06-570, 1:1000), rabbit anti-AWD (gift from
Dr. Tien Hsu, 1:100), mouse anti-Armadillo (DSHB, 1:100), mouse anti-Prospero (DSHB, 1:50),
rabbit anti-Sax (Abcam Cat. No. ab42105, 1:200), rat anti-Delta (gift from Dr. Matthew D. Rand,
1:1000), rabbit anti-Tkv (gift from Dr. Marcos Gonzalez-Gaitan, 1:100), rat anti-HA (Roche Cat.
No. 11867423001, dissolved in distilled water and stored at 100ug/ml, 1:300), rabbit anti-HA
(Cell Signaling Cat. No. 3724S, 1:100), mouse anti-repo (DSHB 8D12, 1:100), mouse anti-NC82
(DSHB, 1:50-1:100), rabbit anti-GFP (ClonTech, Cat# 632592, 1:500). Fluorescent secondary
antibodies were bought from Jackson Immunoresearch. DAPI was used to stain DNA. All the
images were taken on a Zeiss LSM 700 confocal microscope, a Yokogawa CSU-W1/Zeiss 3i
Marianas spinning disk confocal microscope, or a Leica SP5 confocal microscope using 20x,
40x or 100x objective. All the images were processed by Illustrator and ImageJ.

Starvation and bacterial infection
Bacterial strains, Ecc15 or PE, were cultured in LB medium at 29°C for 18-24 hours.
Bacteria were centrifuged at 5000rpm, room temperature for 10 minutes and resuspended in
500ul 5% sucrose (OD100). Bacteria sucrose solution was then added to empty fly vials
containing Whatman filter paper at the bottom. Flies were starved in empty vials for 2-3 hours
before transferred to vials containing bacteria solution, except for overnight wet starvation
during which flies were starved in vials containing 500ul ddH2O on Whatman filter paper. Flies
were infected with Ecc15 for 4 hours or 24 hours as noted correspondingly, before the
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dissection or use in assays. To infect flies with heat-killed Ecc15, Ecc15 sucrose solution was
boiled at 95 °C for 30min, and cooled down before use. Mock flies were treated identically, but
fed with 500ul 5% sucrose without bacteria only. For PE survival experiments, flies were
infected in vials containing 500ul PE sucrose solution on Whatman filter paper continuously, and
100ul 5% sucrose was added every day to vials until the end point. For Smurf assay, flies were
infected with PE for 1 or 2 days, as indicated, and shifted to normal Smurf food, followed by
visually counting numbers of blue flies.

Axenic fly culture
Sterile flies were generated and aged under sterile conditions as described before (H. Li
et al., 2016). In brief, embryos collected on sterile apple juice agar plates (recipe: 700ml H2O,
22.5g Agar, 250ml apple juice, 25g sucrose, 7ml 20% Methyl 4-hydroxybenzoate in Ethanol)
were bleached for 3 min in 2.7% sodium hypochlorite (2-fold diluted bleach), and washed twice
with sterile ddH2O for 1 min. To make conventional control flies, collected eggs were washed
with same amount of ddH2O instead as above. These embryos were transferred into sterile
food in a tissue culture hood, followed by adding 100ul of sterile 70% glycerol on top. Flies
were maintained in a laminar flow hood and flipped into new sterile food every 2-3 days. To
validate axenic conditions, adult fly guts were dissected and plated onto nutrient agar plates to
check commensal loads.

Time-lapse live imaging of Drosophila intestines
Adult female flies were dissected in Shields and Sang M3 insect medium (Sigma Cat. No.
S8398). Intestines were transferred to a 35mm glass bottom dish (MatTek, P35G-1.5-14-C),
with 50-100ul 3.5% low melting agarose (dissolved in M3 insect medium) added on top. After 20
112

minutes, 3ml M3 insect medium was added in the dish, and intestines were imaged at intervals
of 30 seconds for 20-30 minutes on a Zeiss LSM 780 confocal microscope using 40x objective.
For LysoTracker labelling, intestines were transferred to 1x PBS containing 1uM LysoTracker®
Red DND-99 (Thermo Fisher Scientific Cat. No. L7528) after dissection and incubated at room
temperature for 5-10 minutes followed by washing with 1x PBS for 20 minutes. Movies were
analyzed using Image J.

Ex vivo live imaging of Drosophila brains
Adult female flies were dissected in Adult Hemolymph-like Saline (AHLS) culture media
containing 2mM CaCl2, 5mM KCl, 5mM HEPES, 8.2mM MgCl2, 108mM NaCl, 4mM NaHCO3,
1mM NaH2PO4, 5mM Trehalose and 10 mM Sucrose. Brains were transferred to a 35mm glass
bottom dish (MatTek, P35G-1.5-14-C), with 50-100ul 3% low melting agarose (dissolved in
AHLS media) added on top. After 5 minutes, 3ml AHLS media was added in the dish, and
brains were imaged on the Yokogawa CSU-W1/Zeiss 3i Marianas spinning disk confocal
microscope with Photometrics Evolve EMCCD camera under 40x objective. For ratiometric
CytoRoGFP2_Orp1, MitoRoGFP2_Orp1 and CytoRoGFP2_Grx1 biosensors, probe
fluorescence was excited sequentially using the 405 nm and 488 nm laser lines and emission
was detected at 500-550 nm. Imaging settings were carefully optimized prior to each experiment
to ensure optimal dynamic range without saturating cameras. Identical z-stacks were acquired
for each sample.
For lipid peroxidation staining and imaging, fly brains were dissected in Shields and
Sang M3 insect medium (Sigma S8398) and incubated for 30 min in this medium containing
LipidToxTM Deep Red (1:200) and 2 μM C11- BODIPY 581/591 (Invitrogen, D3861) at 37°C.
Following two rinse with 1× PBS, brains were mounted with SlowFade™ Gold Antifade
113

Mountant and imaged immediately with Yokogawa CSU-W1/Zeiss 3i Marianas spinning disk
confocal microscope possessing Photometrics Evolve EMCCD camera, under 40x objective.
Identical z-stacks were acquired for each sample. Lipid peroxidation were determined by the
intensity of oxidized lipids (excitation: 488 nm, emission: 500-540 nm) over the intensity of non-
oxidized lipids (excitation: 561 nm, emission: 570-610 nm).

Cell sorting and RT-qPCR
Flies expressing cytosolic GFP specifically in ISCs were crossed to mCherry
RNAi
. 70-100
intestines were dissected per condition in cold dissection buffer (1xPBS, 1% BSA, 5% FBS) and
treated with 0.1% trypsin for 1 hour at 29 °C, followed by pipetting up-and-down to dissociate
tissue. Cells were collected after centrifugation at 4 °C, 500g for 5 minutes, and resuspended in
dissection buffer. GFP+ cells were sorted followed by RNA extraction with Trizol (Invitrogen).
For whole brain or whole gut RNA extraction, 20 guts from Np1::Gal4 flies or 10 heads from
Actin::Gal4 or nSyb::Gal4 flies were collected correspondingly in Trizol (Invitrogen) per
biological replicate.
cDNA synthesized by using an oligo-dT primer was then applied in real-time PCR on a
Bio-Rad CFX96 detection system with the following primers, or on a QuantStudio 8 Flex system
(ThermoFischer) with the following Taqman Probes (ThermoFischer). For data analysis, C(t)
values of hiw or tkv levels in linear scale were normalized to actin5c.
Primer sequences are listed as following:
hiw (F): 5’-CACGCGCAGAAAAATGCAAC-3’;
hiw (R): 5’-CCGCATTCCCTTCCAGAACA-3’;
actin5C (F): 5’-CTCGCCACTTGCGTTTACAGT-3’;
actin5C (R): 5’-TCCATATCGTCCCAGTTGGTC-3’.

114

Taqman probes are listed as following:
tkv(Dm01844694_g1); actin5c(Dm02361909_s1); Dm01845230_g1(outsiders),
Dm01821385_m1(Glaz), Dm01844576_g1(Nlaz), Dm01841229_g1(Ldh),
Dm01844134_g1(upd2), Dm01844142_g1(upd3).

Glia sorting, Bulk RNA sequencing and data analysis
About 100 brains were dissected for each replicate in cold Shields and Sang M3 insect
medium (Sigma S8398) containing 10% fetal bovine serum (FBS; ThermoFisher,16000036).
Brains were dissociated in the solution containing 300ul papain (Sigma, P4762; dissolved in
1xPBS to a final concentration of 100units/ml) and 4.1ul liberase TM solution (Roche,
5401119001; reconstituted with 1xPBS to a final centration of 2.5mg/ml) at 25°C, 1000rpm for
20min, as described before (H. Li et al., 2017). Cells were collected and stained with Calcein
blue (ThermoFisher, C1429, 1:1000) for 20-30min on ice. After wash with PBS, cells were
resuspended in dissection buffer with SYTOX™ deep red cell stain (ThermoFisher, S11381,
1:1000). GFP+ tdTomato+ cells and GFP- tdTomato+ cells were sorted into Trizol
(ThermoFisher, 15596026) respectively using Fluorescence Activated Cell Sorting (FACS) with
BD FACSAria™ Fusion, followed by RNA extraction. cDNA was generated from 2 nanograms of
RNA using Smart-Seq V4 Ultra Low Input RNA Kit (Takara cat#: 634894). 150 picograms of
cDNA was used to make sequencing libraries by Nextera XT DNA Sample Preparation Kit
(Illumina cat#: FC-131-1024). Libraries were sequenced for 50 single read cycles and 30 million
reads per sample on Illumina NovaSeq 6000. Reads were aligned to Drosophila genome
(version BDGP6), using the GSNAP aligner as part of the HTSeqGenie R package (version 4.2).
Reads that uniquely aligned within exonic boundaries of genes were used to derive expression
estimates. nRPKM (reads per kilobase per normalized million mapped reads) where the total
library sizes were normalized using the median ratio method described before (Anders & Huber,
2010), were generated for each gene. Differential gene expression analysis was performed in
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Partek Flow (Partek Inc., St Louis, MO) and Gene Ontology analysis was done using tools at
Flymine.org and Geneontology.org.

Single-cell RNA sequencing using Smart-seq2 and data analysis
80-100 adult female flies at 5-or 50- day old which over-expressed mCD8::GFP
specifically in glia (using repo::Gal4) or in EG (using GMR56F03::Gal4) were dissected
respectively in cold Shields and Sang M3 insect medium (Sigma S8398) containing 10% fetal
bovine serum (FBS; ThermoFisher,16000036). To improve glial dissociation efficiency and
viability for Smart-seq2, I compared different enzyme combinations, including papain, liberase,
collagenase, and trypsin, and found that the combination of collagenase and trypsin performed
the best. To make 1ml dissociation buffer, I mixed 250ul collagenase (2.5mg/ml, Sigma
#C9891), 100ul trypsin EDTA (0.05%), and 650ul 1x PBS. Brains were dissociated at 25°C,
1000rpm for 30min (samples were pipetted 50-100 times every 10 min). After single-cell
suspension was prepared, GFP positive cells were FACs sorted into individual wells of 384-well
plates using SH800 (Sony Biotechnology). Full-length poly(A)-tailed RNA was reverse-
transcribed and amplified by PCR following the Smart-seq2 protocol (Picelli et al., 2014). cDNA
was digested using lambda exonuclease (New England Biolabs) and then amplified for 25
cycles. Sequencing libraries were prepared from amplified cDNA, pooled, and quantified using
BioAnalyser (Agilent). Sequencing was performed using the Novaseq 6000 Sequencing system
(Illumina) with 100 paired-end reads and 2 x 8 bp index reads.
Reads were aligned to the Drosophila genome (r6.10) using STAR (2.5.4) (Dobin et al.,
2013). Gene counts were produced using HTseq (0.11.2) with default settings except “-m
intersection-strict” (Anders, Pyl, & Huber, 2015). Low-quality cells having fewer than 10,000
uniquely mapped reads were removed. To normalize for differences in sequencing depth across
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individual cells, gene counts to counts per million reads (CPM) were rescaled. All analyses were
performed after converting gene counts to logarithmic space via the transformation
Log2(CPM+1). For data visualization, principal component analysis (PCA) on the cell x gene
matrix was performed, and tSNE plot was used to further project the top 50 PCs into a two-
dimensional space. Figures were generated using scanpy in Python.
For sc-RNAseq analysis in Chapter 3, the non-ensheathing glial population was
manually curated. Repo::Gal4 labels all glia, and some repo::Gal4+ glial cells were clustered
with ensheathing glial clusters (GMR56F03::Gal4+) as expected. These cells belong to repo+
ensheathing glia. Ensheathing glial markers were used to validate these cells. The rest
repo::Gal4+, GMR56F03::Gal4- cells were categorized as non-ensheathing glia. Of note, a
small number of GMR56F03::Gal4+ cells appeared to be non-ensheathing glia, presumably due
to the non-specificity of this Gal4 driver, which were excluded from the analysis. For analysis in
Fig. 28e,f, cells were extracted from a previously published dataset (Davie et al., 2018)in which
57k filtered brain cells that were sequenced using 10x Genomics platform.

Olfactory T-maze assay
For young flies with targeted gene over-expression or knockdown, experimental crosses
were maintained at 18°C, and 3-4 day old progenies were transferred to 29°C for another 5-7
days before T-maze assay. To age flies, wild-type flies (w1118xOreR) were maintained at 25°C.
Experimental flies expressing dome
RNAi
, stat
RNAi
, Glaz
RNAi
, or out
RNAi
in the presence of
GMR56F03Gal4;tubG80
ts
were aged at 25°C for 14-16 days followed by aging at 29°C for 10-14
days, unless otherwise specified. Experimental flies with upd2RNAi and upd3RNAi were aged at
29°C during the adult life for 28-30 days, while flies expressing Nlaz
RNAi
, ldh
RNAi
, out
RNAi
and
UAS::Lip-4 in PNs were aged at 25°C for 36-40 days. Axenic flies were aged at room
117

temperature in a tissue culture hood as described above. During experimentation, a cohort of
30-90 flies were tested under each condition, the result of which was considered as one
replicate and was indicated as one dot in the panel.
T-maze assay was performed in the dark at 22-24°C and 35%-40% humidity. Only
female flies were tested, and flies were given 1 min to make a choice before counting. Attractive
odor, Putrescine (Sigma 51799), and aversive odor, 3-Octanlo (Sigma 218405) were diluted by
ddH2O and paraffin oil (Sigma 18512) respectively. 100mM Putrescine and 100mM 3-Octanol
were used for wild-type flies (w
1118
crossed with OreR), while 1M Putrescine and 10mM 3-
Octanol were supplied to the rest genotypes. 50ul of odorant solution and control solution were
sequentially added onto Whatman filter paper of the odorant tube and the control tube, before
installed into the T-maze device. After experimentation, flies in the odorant tube and the control
tube were counted. The preference index (P.I.) was calculated using the equation:
P.I.=(N(odor)-N(control))/(N(odor)+N(control))*100%. Statistical analysis was performed using
nonparametric Mann-Whitney test or Kruskal-Wallis test in Prism GraphPad.

CAFE assay
Three flies were put in a transparent vial containing 1cm high 1% agar at the bottom to
keep the moisture. Two 5ul capillaries were inserted into a cotton plug on top. One capillary
contained liquid food, including 10% yeast, 10% sucrose, and blue dye, while the other one
contained liquid food mixed with Ecc15. To make Ecc15-mixed liquid food, 40ml Ecc15 was
freshly cultured as described above, and was resuspended in 3ml liquid food. The food intakes
were recorded at corresponding time points and the capillaries were changed every 24 hours.

Intracellular Flow Cytometry and FACs analysis statistics
118

To prepare ISC samples, 15-20 female fly guts were dissected for each biological
replicate. Single cell suspension of each sample was prepared freshly, following the above
dissociation step by trypsin. Cells were immediately transferred to 1.2ml FACs tubes
(ThermoFisher Cat. No. 3487), washed with 1x cold PBS, and resuspended with fixable viability
dye eFluor™ 780 solution (1:1000, diluted in 1x cold PBS).
To prepare brain cell samples, 20 brains were dissected for each biological replicate.
Single cell suspension of each sample was prepared freshly, following the above dissociation
step using the combination of papain and liberase. Cells were immediately transferred to 1.2ml
FACs tubes (ThermoFisher Cat. No. 3487), washed with 1x cold PBS, and resuspended with
fixable viability dye eFluor™ 660 solution (1:1000, diluted in 1x cold PBS).
After 20min incubation with fixable viability dye on ice, cells were washed twice with 1x
cold PBS and spun down at 4C, 300g for 5min. Samples were pulse vortexed for 10sec in
residual volume of remains (around 50-100ul), to completely dissociate the pellet before fixation.
eBioscience™ Foxp3 / Transcription Factor Staining Buffer Set (ThermoFisher Cat. No. 00-
5523-00) was used for the following fixation and permeabilization steps. Cell pellet was
resuspended in 500ul fixation buffer (1 part of fix/permeabilization concentrate: 3 parts of
diluents), and fixed at room temperature for at least 30min. Fixed cells were spun down at
700xg for 5min and blocked at room temperature for 10min in blocking buffer (1x
permeabilization buffer containing 2% goat serum). For antibody staining, cells were incubated
at room temperature for 30min-1hr with primary antibodies diluted in blocking buffer. Cells were
then washed with 1x permeabilization buffer twice and incubated with fluorescent secondary
antibodies diluted in blocking buffer at room temperature for 30min-1hr. Cells were washed with
1xpermeabilization buffer twice and resuspended with 1x FACs buffer (1xPBS, 0.5% BSA, 0.05%
Na Azide). DAPI was added to each sample at a final concentration 1ug/ml, to stain nuclei, and
analyzed by BD Symphony flow cytometer.
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Primary antibodies and dilution used in this study: rabbit anti-pSMad3 (Epitomics Cat.
No. EP823Y, 1:800), rat anti-HA (Roche Cat. No. 11867423001, dissolved in distilled water and
stored at 100ug/ml, 1:500), rabbit anti-Sax (Abcam Cat. No. ab42105, 1:500), rabbit anti-AWD
(gift from Dr. Tien Hsu, 1:300), mouse anti-Highwire (DSHB, 6H4, 1:300), anti-GFP antibody
(ClonTech, Cat# 632592, 1:500). Fluorescent secondary antibodies were bought from Jackson
Immunoresearch (1:500).
FlowJo v10 Software computed the median fluorescence intensity (MFI) of channels of
interest in GFP-labelled ISCs, and generated histogram (x-axis: fluorescence intensity levels of
channels of interest in logarithmic scale; y-axis: the number of events, noted as modal). To
overlay multiple cell populations with different sizes, the absolute cell counts were normalized to
the peak height at mode of the distribution, noted as normalized to mode in y-axis. To combine
values from experiments conducted on different days, all values collected on the same day were
normalized to the median value of control samples on the same day of measurement. Median
value of fluorescence minus one control (FMO) containing all the fluorochromes except for the
one being measured was subtracted from the median values of all the samples, to reduce the
background. Wilcoxon rank-sum test was used to compare the significant differences of MFIs
between samples by Prism.

MARCM clone induction
2–3-day-old flies were heat-shocked for 45 min at 37 °C and kept at room temperature
for 2-5 days as indicated, followed by bacterial infection before dissection.

Image quantification and statistical analyses.
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Confocal images were obtained using a Zeiss LSM 780 confocal microscope, Zeiss 3i
Marianas spinning disk confocal microscope and Leica SP5 confocal microscope. Images to be
compared were collected using identical laser and detector settings unless noted otherwise, and
analyzed using NIH ImageJ. Quantifications in Chapter 2 were only performed in the posterior
midgut. Mean values of background signal in the vicinity of the analyzed ISCs were subtracted
from absolute fluorescence intensity values of individual ISCs of interest, followed by
normalization to the mean of control samples.
Images taken on live brains with CytoRoGFP2_Orp1, MitoRoGFP2_Orp1 or
MitoRoGFP2_Grx1 fluorescent biosensors were analyzed with Image J. Z-stack images were
converted to maximal intensity projections. For ratiometric measurements of these biosensors,
the 488 nm excitation channel was used for image segmentation and ROIs detection. For
CytoRoGFP2_Orp1 and CytoRoGFP2_Grx1, ROIs were carefully selected to represent each
single glia at the antennal lobe manually, while automated ROI detection was optimized and
utilized for MitoRoGFP2_Orp1. Mean intensity values within each ROI were calculated under
405 nm and 488 nm excitation channels sequentially. The intensity ratio of 405nm:488nm for
each ROI was calculated in excel, and was compiled to generate the mean ratio for each brain
sample.
To create false color ratio images, maximal intensity projections were first converted
from 16 to 32-bit format. ROIs were detected manually or automatically in the same way as
described above. Image background (regions outside of ROIs) was cleared. A ratio image was
generated by pixel by pixel division of 405 nm image over 488 nm image. Ratio images in false
color were generated in Image J using the “fire” LookUp Table (LUT).
For ratiometric measurement of lipid peroxidation in lipid droplets at the antennal lobe,
maximal intensity projections were acquired from z-stack images in Image J. ROIs were
manually selected to represent each neutral lipid droplet at the antennal lobe under the LipidTox
121

Alexa 647 (deep red) channel. After applying ROIs to the 488nm (oxidized) and 561nm (non-
oxidized) excitation channels, the intensity ratio of 488nm:561nm for each ROI was calculated in
excel, and was compiled to generate the mean value for each brain sample. The mean value for
each genotype group was normalized to the mean of control samples.
Sample size and number of replicates are described in the corresponding legends.
Statistical analyses were performed with Prism (GraphPad Software, La Jolla, CA, USA) In
Chapter 2, student’s t-test was used to compare means from two independent groups of data
with normal distribution, except that ratio paired t-test was used to compare mean values of
AWD, Tkv and pMAD expression between mutant ISCs and wildtype ISCs within the same gut
in MARCM clone analysis. In Chapter 3, Mann-Whitney test was used to compare means from
two independent groups without normal distribution, while Kruskal-Wallis test was used for
multiple comparisons. Log-rank test was used to test for statistical significance in PE survival
assay in both Chapter 2 and 3. No statistical method was used to predetermine sample sizes.

Data and code availability
The authors declare that the data supporting the findings of this study are available
within the paper and its supplementary information files. Raw sequencing reads and
preprocessed sequence data for glia Bulk RNAseq files have been deposited in GEO under
accession code GSE168530 and scRNAseq reads and preprocessed sequence data have been
deposited in GEO under accession code GSE168572. Analysis code is available at
https://github.com/Hongjie-Li/flyglia.

122

References
Adamo, S. A. (2005). Parasitic suppression of feeding in the tobacco hornworm, Manduca sexta:
parallels with feeding depression after an immune challenge. Arch Insect Biochem
Physiol, 60(4), 185-197. doi:10.1002/arch.20068
Albrecht, S. C., Barata, A. G., Grosshans, J., Teleman, A. A., & Dick, T. P. (2011). In vivo
mapping of hydrogen peroxide and oxidized glutathione reveals chemical and regional
specificity of redox homeostasis. Cell Metab, 14(6), 819-829.
doi:10.1016/j.cmet.2011.10.010
Allen, N. J., & Lyons, D. A. (2018). Glia as architects of central nervous system formation and
function. Science, 362(6411), 181-185. doi:10.1126/science.aat0473
Amcheslavsky, A., Jiang, J., & Ip, Y. T. (2009). Tissue damage-induced intestinal stem cell
division in Drosophila. Cell Stem Cell, 4(1), 49-61. doi:10.1016/j.stem.2008.10.016
Amoyel, M., & Bach, E. A. (2012). Functions of the Drosophila JAK-STAT pathway: Lessons
from stem cells. Jakstat, 1(3), 176-183. doi:10.4161/jkst.21621
Amsalem, A. R., Marom, B., Shapira, K. E., Hirschhorn, T., Preisler, L., Paarmann, P., . . .
Ehrlich, M. (2016). Differential regulation of translation and endocytosis of alternatively
spliced forms of the type II bone morphogenetic protein (BMP) receptor. Mol Biol Cell,
27(4), 716-730. doi:10.1091/mbc.E15-08-0547
Anders, S., & Huber, W. (2010). Differential expression analysis for sequence count data.
Genome Biol, 11(10), R106. doi:10.1186/gb-2010-11-10-r106
Anders, S., Pyl, P. T., & Huber, W. (2015). HTSeq--a Python framework to work with high-
throughput sequencing data. Bioinformatics, 31(2), 166-169.
doi:10.1093/bioinformatics/btu638
Angot, E., & Brundin, P. (2009). Dissecting the potential molecular mechanisms underlying
alpha-synuclein cell-to-cell transfer in Parkinson's disease. Parkinsonism Relat Disord,
15 Suppl 3, S143-147. doi:10.1016/s1353-8020(09)70802-8
Angot, E., Steiner, J. A., Lema Tomé, C. M., Ekström, P., Mattsson, B., Björklund, A., & Brundin,
P. (2012). Alpha-synuclein cell-to-cell transfer and seeding in grafted dopaminergic
neurons in vivo. PLoS One, 7(6), e39465. doi:10.1371/journal.pone.0039465
123

Antonini, M., Lo Conte, M., Sorini, C., & Falcone, M. (2019). How the Interplay Between the
Commensal Microbiota, Gut Barrier Integrity, and Mucosal Immunity Regulates Brain
Autoimmunity. Front Immunol, 10, 1937. doi:10.3389/fimmu.2019.01937
Apidianakis, Y., & Rahme, L. G. (2011). Drosophila melanogaster as a model for human
intestinal infection and pathology. Dis Model Mech, 4(1), 21-30.
doi:10.1242/dmm.003970
Arrieta, M. C., & Finlay, B. B. (2012). The commensal microbiota drives immune homeostasis.
Front Immunol, 3, 33. doi:10.3389/fimmu.2012.00033
Artiushin, G., Zhang, S. L., Tricoire, H., & Sehgal, A. (2018). Endocytosis at the Drosophila
blood-brain barrier as a function for sleep. Elife, 7. doi:10.7554/eLife.43326
Ayres, J. S., & Schneider, D. S. (2009). The role of anorexia in resistance and tolerance to
infections in Drosophila. PLoS Biol, 7(7), e1000150. doi:10.1371/journal.pbio.1000150
Ayyaz, A., Li, H., & Jasper, H. (2015). Haemocytes control stem cell activity in the Drosophila
intestine. Nat Cell Biol, 17(6), 736-748. doi:10.1038/ncb3174
Bach, E. A., Ekas, L. A., Ayala-Camargo, A., Flaherty, M. S., Lee, H., Perrimon, N., & Baeg, G.
H. (2007). GFP reporters detect the activation of the Drosophila JAK/STAT pathway in
vivo. Gene Expr Patterns, 7(3), 323-331. doi:10.1016/j.modgep.2006.08.003
Baechler, B. L., McKnight, C., Pruchnicki, P. C., Biro, N. A., & Reed, B. H. (2015).
Hindsight/RREB-1 functions in both the specification and differentiation of stem cells in
the adult midgut of Drosophila. Biol Open, 5(1), 1-10. doi:10.1242/bio.015636
Baena-Lopez, L. A., Alexandre, C., Mitchell, A., Pasakarnis, L., & Vincent, J. P. (2013).
Accelerated homologous recombination and subsequent genome modification in
Drosophila. Development, 140(23), 4818-4825. doi:10.1242/dev.100933
Bainton, R. J., Tsai, L. T., Schwabe, T., DeSalvo, M., Gaul, U., & Heberlein, U. (2005). moody
encodes two GPCRs that regulate cocaine behaviors and blood-brain barrier
permeability in Drosophila. Cell, 123(1), 145-156. doi:10.1016/j.cell.2005.07.029
Banerjee, S., Jha, H. C., & Robertson, E. S. (2015). Regulation of the metastasis suppressor
Nm23-H1 by tumor viruses. Naunyn Schmiedebergs Arch Pharmacol, 388(2), 207-224.
doi:10.1007/s00210-014-1043-8
124

Bangi, E., & Wharton, K. (2006). Dpp and Gbb exhibit different effective ranges in the
establishment of the BMP activity gradient critical for Drosophila wing patterning. Dev
Biol, 295(1), 178-193. doi:10.1016/j.ydbio.2006.03.021
Ben Haim, L., Ceyzeriat, K., Carrillo-de Sauvage, M. A., Aubry, F., Auregan, G., Guillermier,
M., . . . Escartin, C. (2015). The JAK/STAT3 pathway is a common inducer of astrocyte
reactivity in Alzheimer's and Huntington's diseases. J Neurosci, 35(6), 2817-2829.
doi:10.1523/jneurosci.3516-14.2015
Bercik, P., Denou, E., Collins, J., Jackson, W., Lu, J., Jury, J., . . . Collins, S. M. (2011). The
intestinal microbiota affect central levels of brain-derived neurotropic factor and behavior
in mice. Gastroenterology, 141(2), 599-609, 609.e591-593.
doi:10.1053/j.gastro.2011.04.052
Bier, E., & De Robertis, E. M. (2015). EMBRYO DEVELOPMENT. BMP gradients: A paradigm
for morphogen-mediated developmental patterning. Science, 348(6242), aaa5838.
doi:10.1126/science.aaa5838
Biteau, B., Hochmuth, C. E., & Jasper, H. (2008). JNK activity in somatic stem cells causes loss
of tissue homeostasis in the aging Drosophila gut. Cell Stem Cell, 3(4), 442-455.
doi:10.1016/j.stem.2008.07.024
Biteau, B., Hochmuth, C. E., & Jasper, H. (2011). Maintaining tissue homeostasis: dynamic
control of somatic stem cell activity. Cell Stem Cell, 9(5), 402-411.
doi:10.1016/j.stem.2011.10.004
Biteau, B., & Jasper, H. (2014). Slit/Robo signaling regulates cell fate decisions in the intestinal
stem cell lineage of Drosophila. Cell Rep, 7(6), 1867-1875.
doi:10.1016/j.celrep.2014.05.024
Biteau, B., Karpac, J., Supoyo, S., Degennaro, M., Lehmann, R., & Jasper, H. (2010). Lifespan
extension by preserving proliferative homeostasis in Drosophila. PLoS Genet, 6(10),
e1001159. doi:10.1371/journal.pgen.1001159
Bitgood, M. J., & McMahon, A. P. (1995). Hedgehog and Bmp genes are coexpressed at many
diverse sites of cell-cell interaction in the mouse embryo. Dev Biol, 172(1), 126-138.
doi:10.1006/dbio.1995.0010
Blum, I. D., Keleş, M. F., Baz, E. S., Han, E., Park, K., Luu, S., . . . Wu, M. N. (2021). Astroglial
Calcium Signaling Encodes Sleep Need in Drosophila. Curr Biol, 31(1), 150-162.e157.
doi:10.1016/j.cub.2020.10.012
125

Bonnay, F., Cohen-Berros, E., Hoffmann, M., Kim, S. Y., Boulianne, G. L., Hoffmann, J. A., . . .
Reichhart, J. M. (2013). big bang gene modulates gut immune tolerance in Drosophila.
Proc Natl Acad Sci U S A, 110(8), 2957-2962. doi:10.1073/pnas.1221910110
Boza-Serrano, A., Yang, Y., Paulus, A., & Deierborg, T. (2018). Innate immune alterations are
elicited in microglial cells before plaque deposition in the Alzheimer's disease mouse
model 5xFAD. Sci Rep, 8(1), 1550. doi:10.1038/s41598-018-19699-y
Brand, A. H., & Perrimon, N. (1993). Targeted gene expression as a means of altering cell fates
and generating dominant phenotypes. Development, 118(2), 401-415.
Brann, D. H., Tsukahara, T., Weinreb, C., Lipovsek, M., Van den Berge, K., Gong, B., . . . Datta,
S. R. (2020). Non-neuronal expression of SARS-CoV-2 entry genes in the olfactory
system suggests mechanisms underlying COVID-19-associated anosmia. Science
Advances, 6(31), eabc5801. doi:10.1126/sciadv.abc5801
Broderick, N. A., Buchon, N., & Lemaitre, B. (2014). Microbiota-induced changes in drosophila
melanogaster host gene expression and gut morphology. mBio, 5(3), e01117-01114.
doi:10.1128/mBio.01117-14
Buchon, N., Broderick, N. A., Chakrabarti, S., & Lemaitre, B. (2009). Invasive and indigenous
microbiota impact intestinal stem cell activity through multiple pathways in Drosophila.
Genes Dev, 23(19), 2333-2344. doi:10.1101/gad.1827009
Buchon, N., Broderick, N. A., Poidevin, M., Pradervand, S., & Lemaitre, B. (2009). Drosophila
intestinal response to bacterial infection: activation of host defense and stem cell
proliferation. Cell Host Microbe, 5(2), 200-211. doi:10.1016/j.chom.2009.01.003
Buchon, N., & Osman, D. (2015). All for one and one for all: Regionalization of the Drosophila
intestine. Insect Biochem Mol Biol, 67, 2-8. doi:10.1016/j.ibmb.2015.05.015
Buchon, N., Osman, D., David, F. P., Fang, H. Y., Boquete, J. P., Deplancke, B., & Lemaitre, B.
(2013). Morphological and molecular characterization of adult midgut
compartmentalization in Drosophila. Cell Rep, 3(5), 1725-1738.
doi:10.1016/j.celrep.2013.04.001
Buckley, A., & Turner, J. R. (2018). Cell Biology of Tight Junction Barrier Regulation and
Mucosal Disease. Cold Spring Harb Perspect Biol, 10(1).
doi:10.1101/cshperspect.a029314
Canalis, E., Economides, A. N., & Gazzerro, E. (2003). Bone morphogenetic proteins, their
antagonists, and the skeleton. Endocr Rev, 24(2), 218-235. doi:10.1210/er.2002-0023
126

Capo, F., Wilson, A., & Di Cara, F. (2019). The Intestine of Drosophila melanogaster: An
Emerging Versatile Model System to Study Intestinal Epithelial Homeostasis and Host-
Microbial Interactions in Humans. Microorganisms, 7(9).
doi:10.3390/microorganisms7090336
Carabotti, M., Scirocco, A., Maselli, M. A., & Severi, C. (2015). The gut-brain axis: interactions
between enteric microbiota, central and enteric nervous systems. Ann Gastroenterol,
28(2), 203-209.
Chakrabarti, S., Dudzic, J. P., Li, X., Collas, E. J., Boquete, J. P., & Lemaitre, B. (2016). Remote
Control of Intestinal Stem Cell Activity by Haemocytes in Drosophila. PLoS Genet, 12(5),
e1006089. doi:10.1371/journal.pgen.1006089
Charroux, B., Daian, F., & Royet, J. (2020). Drosophila Aversive Behavior toward Erwinia
carotovora carotovora Is Mediated by Bitter Neurons and Leukokinin. iScience, 23(6),
101152. doi:10.1016/j.isci.2020.101152
Chassaing, B., Kumar, M., Baker, M. T., Singh, V., & Vijay-Kumar, M. (2014). Mammalian gut
immunity. Biomed J, 37(5), 246-258. doi:10.4103/2319-4170.130922
Chen, G., Xu, H., Yao, Y., Xu, T., Yuan, M., Zhang, X., . . . Wu, M. (2020). BMP Signaling in the
Development and Regeneration of Cranium Bones and Maintenance of Calvarial Stem
Cells. Front Cell Dev Biol, 8, 135. doi:10.3389/fcell.2020.00135
Chen, H., Zheng, X., & Zheng, Y. (2014). Age-associated loss of lamin-B leads to systemic
inflammation and gut hyperplasia. Cell, 159(4), 829-843. doi:10.1016/j.cell.2014.10.028
Chen, W. F., Maguire, S., Sowcik, M., Luo, W., Koh, K., & Sehgal, A. (2015). A neuron-glia
interaction involving GABA transaminase contributes to sleep loss in sleepless mutants.
Mol Psychiatry, 20(2), 240-251. doi:10.1038/mp.2014.11
Choi, N. H., Kim, J. G., Yang, D. J., Kim, Y. S., & Yoo, M. A. (2008). Age-related changes in
Drosophila midgut are associated with PVF2, a PDGF/VEGF-like growth factor. Aging
Cell, 7(3), 318-334. doi:10.1111/j.1474-9726.2008.00380.x
Clark, R. I., Salazar, A., Yamada, R., Fitz-Gibbon, S., Morselli, M., Alcaraz, J., . . . Walker, D. W.
(2015). Distinct Shifts in Microbiota Composition during Drosophila Aging Impair
Intestinal Function and Drive Mortality. Cell Rep, 12(10), 1656-1667.
doi:10.1016/j.celrep.2015.08.004
127

Classen, A. K., Bunker, B. D., Harvey, K. F., Vaccari, T., & Bilder, D. (2009). A tumor
suppressor activity of Drosophila Polycomb genes mediated by JAK-STAT signaling. Nat
Genet, 41(10), 1150-1155. doi:10.1038/ng.445
Clemmensen, C., Muller, T. D., Woods, S. C., Berthoud, H. R., Seeley, R. J., & Tschop, M. H.
(2017). Gut-Brain Cross-Talk in Metabolic Control. Cell, 168(5), 758-774.
doi:10.1016/j.cell.2017.01.025
Colodner, K. J., & Feany, M. B. (2010). Glial fibrillary tangles and JAK/STAT-mediated glial and
neuronal cell death in a Drosophila model of glial tauopathy. J Neurosci, 30(48), 16102-
16113. doi:10.1523/jneurosci.2491-10.2010
Copf, T., Goguel, V., Lampin-Saint-Amaux, A., Scaplehorn, N., & Preat, T. (2011). Cytokine
signaling through the JAK/STAT pathway is required for long-term memory in Drosophila.
Proc Natl Acad Sci U S A, 108(19), 8059-8064. doi:10.1073/pnas.1012919108
Couto, A., Alenius, M., & Dickson, B. J. (2005). Molecular, anatomical, and functional
organization of the Drosophila olfactory system. Curr Biol, 15(17), 1535-1547.
doi:10.1016/j.cub.2005.07.034
Cronin, S. J., Nehme, N. T., Limmer, S., Liegeois, S., Pospisilik, J. A., Schramek, D., . . .
Penninger, J. M. (2009). Genome-wide RNAi screen identifies genes involved in
intestinal pathogenic bacterial infection. Science, 325(5938), 340-343.
doi:10.1126/science.1173164
Damisah, E. C., Hill, R. A., Rai, A., Chen, F., Rothlin, C. V., Ghosh, S., & Grutzendler, J. (2020).
Astrocytes and microglia play orchestrated roles and respect phagocytic territories
during neuronal corpse removal in vivo. Sci Adv, 6(26), eaba3239.
doi:10.1126/sciadv.aba3239
Dammai, V., Adryan, B., Lavenburg, K. R., & Hsu, T. (2003). Drosophila awd, the homolog of
human nm23, regulates FGF receptor levels and functions synergistically with
shi/dynamin during tracheal development. Genes Dev, 17(22), 2812-2824.
doi:10.1101/gad.1096903
Davie, K., Janssens, J., Koldere, D., De Waegeneer, M., Pech, U., Kreft, Ł., . . . Aerts, S. (2018).
A Single-Cell Transcriptome Atlas of the Aging Drosophila Brain. Cell, 174(4), 982-
998.e920. doi:10.1016/j.cell.2018.05.057
DeBerardinis, R. J., & Chandel, N. S. (2016). Fundamentals of cancer metabolism. Sci Adv, 2(5),
e1600200. doi:10.1126/sciadv.1600200
128

Del Tredici, K., & Braak, H. (2008). A not entirely benign procedure: progression of Parkinson's
disease. Acta Neuropathol, 115(4), 379-384. doi:10.1007/s00401-008-0355-5
Deng, H., Gerencser, A. A., & Jasper, H. (2015). Signal integration by Ca(2+) regulates
intestinal stem-cell activity. Nature, 528(7581), 212-217. doi:10.1038/nature16170
DeSalvo, M. K., Hindle, S. J., Rusan, Z. M., Orng, S., Eddison, M., Halliwill, K., & Bainton, R. J.
(2014). The Drosophila surface glia transcriptome: evolutionary conserved blood-brain
barrier processes. Front Neurosci, 8, 346. doi:10.3389/fnins.2014.00346
Di Guglielmo, G. M., Le Roy, C., Goodfellow, A. F., & Wrana, J. L. (2003). Distinct endocytic
pathways regulate TGF-beta receptor signalling and turnover. Nat Cell Biol, 5(5), 410-
421. doi:10.1038/ncb975
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., . . . Gingeras, T. R.
(2013). STAR: ultrafast universal RNA-seq aligner. Bioinformatics, 29(1), 15-21.
doi:10.1093/bioinformatics/bts635
Dodiya, H. B., Kuntz, T., Shaik, S. M., Baufeld, C., Leibowitz, J., Zhang, X., . . . Sisodia, S. S.
(2019). Sex-specific effects of microbiome perturbations on cerebral Abeta amyloidosis
and microglia phenotypes. J Exp Med, 216(7), 1542-1560. doi:10.1084/jem.20182386
Doherty, J., Logan, M. A., Taşdemir, O. E., & Freeman, M. R. (2009). Ensheathing glia function
as phagocytes in the adult Drosophila brain. J Neurosci, 29(15), 4768-4781.
doi:10.1523/jneurosci.5951-08.2009
Doherty, J., Sheehan, A. E., Bradshaw, R., Fox, A. N., Lu, T. Y., & Freeman, M. R. (2014). PI3K
signaling and Stat92E converge to modulate glial responsiveness to axonal injury. PLoS
Biol, 12(11), e1001985. doi:10.1371/journal.pbio.1001985
Doty, R. L., & Kamath, V. (2014). The influences of age on olfaction: a review. Front Psychol, 5,
20. doi:10.3389/fpsyg.2014.00020
Driver, I., & Ohlstein, B. (2014). Specification of regional intestinal stem cell identity during
Drosophila metamorphosis. Development, 141(9), 1848-1856. doi:10.1242/dev.104018
Du, L., & Wang, J. (2020). JAK/STAT pathway promotes Drosophila neuroblast
proliferation via the direct CycE regulation. bioRxiv, 2020.2007.2010.195875.
doi:10.1101/2020.07.10.195875
129

Dutta, D., Dobson, A. J., Houtz, P. L., Glasser, C., Revah, J., Korzelius, J., . . . Buchon, N.
(2015). Regional Cell-Specific Transcriptome Mapping Reveals Regulatory Complexity
in the Adult Drosophila Midgut. Cell Rep, 12(2), 346-358.
doi:10.1016/j.celrep.2015.06.009
Erny, D., Hrabe de Angelis, A. L., Jaitin, D., Wieghofer, P., Staszewski, O., David, E., . . . Prinz,
M. (2015). Host microbiota constantly control maturation and function of microglia in the
CNS. Nat Neurosci, 18(7), 965-977. doi:10.1038/nn.4030
Fan, Y., Yao, Y., Li, L., Wu, Z., Xu, F., Hou, M., . . . Zhou, Q. (2013). nm23-H1 gene driven by
hTERT promoter induces inhibition of invasive phenotype and metastasis of lung cancer
xenograft in mice. Thorac Cancer, 4(1), 41-52. doi:10.1111/j.1759-7714.2012.00140.x
Fancsalszky, L., Monostori, E., Farkas, Z., Pourkarimi, E., Masoudi, N., Hargitai, B., . . . Takacs-
Vellai, K. (2014). NDK-1, the homolog of NM23-H1/H2 regulates cell migration and
apoptotic engulfment in C. elegans. PLoS One, 9(3), e92687.
doi:10.1371/journal.pone.0092687
Fang, X. (2016). Potential role of gut microbiota and tissue barriers in Parkinson's disease and
amyotrophic lateral sclerosis. Int J Neurosci, 126(9), 771-776.
doi:10.3109/00207454.2015.1096271
Farca Luna, A. J., Perier, M., & Seugnet, L. (2017). Amyloid Precursor Protein in Drosophila
Glia Regulates Sleep and Genes Involved in Glutamate Recycling. J Neurosci, 37(16),
4289-4300. doi:10.1523/jneurosci.2826-16.2017
Fauny, J. D., Silber, J., & Zider, A. (2005). Drosophila Lipid Storage Droplet 2 gene (Lsd-2) is
expressed and controls lipid storage in wing imaginal discs. Dev Dyn, 232(3), 725-732.
doi:10.1002/dvdy.20277
Freeman, M. R. (2015). Drosophila Central Nervous System Glia. Cold Spring Harb Perspect
Biol, 7(11). doi:10.1101/cshperspect.a020552
Furness, J. B. (2012). The enteric nervous system and neurogastroenterology. Nat Rev
Gastroenterol Hepatol, 9(5), 286-294. doi:10.1038/nrgastro.2012.32
Furness, J. B., Kunze, W. A., Bertrand, P. P., Clerc, N., & Bornstein, J. C. (1998). Intrinsic
primary afferent neurons of the intestine. Prog Neurobiol, 54(1), 1-18.
doi:10.1016/s0301-0082(97)00051-8
Gao, Q., & Chess, A. (1999). Identification of candidate Drosophila olfactory receptors from
genomic DNA sequence. Genomics, 60(1), 31-39. doi:10.1006/geno.1999.5894
130

Gilboa, L., Nohe, A., Geissendorfer, T., Sebald, W., Henis, Y. I., & Knaus, P. (2000). Bone
morphogenetic protein receptor complexes on the surface of live cells: a new
oligomerization mode for serine/threonine kinase receptors. Mol Biol Cell, 11(3), 1023-
1035. doi:10.1091/mbc.11.3.1023
Gleason, R. J., Akintobi, A. M., Grant, B. D., & Padgett, R. W. (2014). BMP signaling requires
retromer-dependent recycling of the type I receptor. Proc Natl Acad Sci U S A, 111(7),
2578-2583. doi:10.1073/pnas.1319947111
Gui, J., Huang, Y., & Shimmi, O. (2016). Scribbled Optimizes BMP Signaling through Its
Receptor Internalization to the Rab5 Endosome and Promote Robust Epithelial
Morphogenesis. PLoS Genet, 12(11), e1006424. doi:10.1371/journal.pgen.1006424
Gunawardene, A. R., Corfe, B. M., & Staton, C. A. (2011). Classification and functions of
enteroendocrine cells of the lower gastrointestinal tract. Int J Exp Pathol, 92(4), 219-231.
doi:10.1111/j.1365-2613.2011.00767.x
Guo, L., Karpac, J., Tran, S. L., & Jasper, H. (2014). PGRP-SC2 promotes gut immune
homeostasis to limit commensal dysbiosis and extend lifespan. Cell, 156(1-2), 109-122.
doi:10.1016/j.cell.2013.12.018
Guo, X., Yin, C., Yang, F., Zhang, Y., Huang, H., Wang, J., . . . Xi, R. (2019). The Cellular
Diversity and Transcription Factor Code of Drosophila Enteroendocrine Cells. Cell Rep,
29(12), 4172-4185.e4175. doi:10.1016/j.celrep.2019.11.048
Guo, Z., Driver, I., & Ohlstein, B. (2013). Injury-induced BMP signaling negatively regulates
Drosophila midgut homeostasis. J Cell Biol, 201(6), 945-961. doi:10.1083/jcb.201302049
Guo, Z., & Ohlstein, B. (2015). Stem cell regulation. Bidirectional Notch signaling regulates
Drosophila intestinal stem cell multipotency. Science, 350(6263).
doi:10.1126/science.aab0988
Ha, E. M., Oh, C. T., Bae, Y. S., & Lee, W. J. (2005). A direct role for dual oxidase in Drosophila
gut immunity. Science, 310(5749), 847-850. doi:10.1126/science.1117311
Hakim-Mishnaevski, K., Flint-Brodsly, N., Shklyar, B., Levy-Adam, F., & Kurant, E. (2019). Glial
Phagocytic Receptors Promote Neuronal Loss in Adult Drosophila Brain. Cell Rep, 29(6),
1438-1448.e1433. doi:10.1016/j.celrep.2019.09.086
Haller, S., Kapuria, S., Riley, R. R., O'Leary, M. N., Schreiber, K. H., Andersen, J. K., . . . Jasper,
H. (2017). mTORC1 Activation during Repeated Regeneration Impairs Somatic Stem
Cell Maintenance. Cell Stem Cell, 21(6), 806-818.e805. doi:10.1016/j.stem.2017.11.008
131

Haramis, A. P., Begthel, H., van den Born, M., van Es, J., Jonkheer, S., Offerhaus, G. J., &
Clevers, H. (2004). De novo crypt formation and juvenile polyposis on BMP inhibition in
mouse intestine. Science, 303(5664), 1684-1686. doi:10.1126/science.1093587
Hardwick, J. C., Van Den Brink, G. R., Bleuming, S. A., Ballester, I., Van Den Brande, J. M.,
Keller, J. J., . . . Peppelenbosch, M. P. (2004). Bone morphogenetic protein 2 is
expressed by, and acts upon, mature epithelial cells in the colon. Gastroenterology,
126(1), 111-121. doi:10.1053/j.gastro.2003.10.067
He, X. C., Zhang, J., Tong, W. G., Tawfik, O., Ross, J., Scoville, D. H., . . . Li, L. (2004). BMP
signaling inhibits intestinal stem cell self-renewal through suppression of Wnt-beta-
catenin signaling. Nat Genet, 36(10), 1117-1121. doi:10.1038/ng1430
Hegarty, S. V., Sullivan, A. M., & O'Keeffe, G. W. (2017). Endocytosis contributes to BMP2-
induced Smad signalling and neuronal growth. Neurosci Lett, 643, 32-37.
doi:10.1016/j.neulet.2017.02.013
Heining, E., Bhushan, R., Paarmann, P., Henis, Y. I., & Knaus, P. (2011). Spatial segregation of
BMP/Smad signaling affects osteoblast differentiation in C2C12 cells. PLoS One, 6(10),
e25163. doi:10.1371/journal.pone.0025163
Heisenberg, M. (2003). Mushroom body memoir: from maps to models. Nat Rev Neurosci, 4(4),
266-275. doi:10.1038/nrn1074
Herrmann, J. E., Imura, T., Song, B., Qi, J., Ao, Y., Nguyen, T. K., . . . Sofroniew, M. V. (2008).
STAT3 is a critical regulator of astrogliosis and scar formation after spinal cord injury. J
Neurosci, 28(28), 7231-7243. doi:10.1523/jneurosci.1709-08.2008
Hindle, S. J., Munji, R. N., Dolghih, E., Gaskins, G., Orng, S., Ishimoto, H., . . . Bainton, R. J.
(2017). Evolutionarily Conserved Roles for Blood-Brain Barrier Xenobiotic Transporters
in Endogenous Steroid Partitioning and Behavior. Cell Rep, 21(5), 1304-1316.
doi:10.1016/j.celrep.2017.10.026
Hochmuth, C. E., Biteau, B., Bohmann, D., & Jasper, H. (2011). Redox regulation by Keap1 and
Nrf2 controls intestinal stem cell proliferation in Drosophila. Cell Stem Cell, 8(2), 188-199.
doi:10.1016/j.stem.2010.12.006
Hombría, J. C., Brown, S., Häder, S., & Zeidler, M. P. (2005). Characterisation of Upd2, a
Drosophila JAK/STAT pathway ligand. Dev Biol, 288(2), 420-433.
doi:10.1016/j.ydbio.2005.09.040
132

Honjo, K., & Tracey, W. D., Jr. (2018). BMP signaling downstream of the Highwire E3 ligase
sensitizes nociceptors. PLoS Genet, 14(7), e1007464.
doi:10.1371/journal.pgen.1007464
Howe, J. R., Bair, J. L., Sayed, M. G., Anderson, M. E., Mitros, F. A., Petersen, G. M., . . .
Vogelstein, B. (2001). Germline mutations of the gene encoding bone morphogenetic
protein receptor 1A in juvenile polyposis. Nat Genet, 28(2), 184-187. doi:10.1038/88919
Howe, J. R., Roth, S., Ringold, J. C., Summers, R. W., Järvinen, H. J., Sistonen, P., . . .
Aaltonen, L. A. (1998). Mutations in the SMAD4/DPC4 gene in juvenile polyposis.
Science, 280(5366), 1086-1088. doi:10.1126/science.280.5366.1086
Hu, D. J., & Jasper, H. (2019). Control of Intestinal Cell Fate by Dynamic Mitotic Spindle
Repositioning Influences Epithelial Homeostasis and Longevity. Cell Rep, 28(11), 2807-
2823.e2805. doi:10.1016/j.celrep.2019.08.014
Hung, R. J., Li, J. S. S., Liu, Y., & Perrimon, N. (2021). Defining cell types and lineage in the
Drosophila midgut using single cell transcriptomics. Curr Opin Insect Sci, 47, 12-17.
doi:10.1016/j.cois.2021.02.008
Hussain, A., Pooryasin, A., Zhang, M., Loschek, L. F., La Fortezza, M., Friedrich, A. B., . . .
Grunwald Kadow, I. C. (2018). Inhibition of oxidative stress in cholinergic projection
neurons fully rescues aging-associated olfactory circuit degeneration in Drosophila. Elife,
7. doi:10.7554/eLife.32018
Iatsenko, I., Boquete, J. P., & Lemaitre, B. (2018). Microbiota-Derived Lactate Activates
Production of Reactive Oxygen Species by the Intestinal NADPH Oxidase Nox and
Shortens Drosophila Lifespan. Immunity, 49(5), 929-942.e925.
doi:10.1016/j.immuni.2018.09.017
Ichinohe, T., Pang, I. K., Kumamoto, Y., Peaper, D. R., Ho, J. H., Murray, T. S., & Iwasaki, A.
(2011). Microbiota regulates immune defense against respiratory tract influenza A virus
infection. Proc Natl Acad Sci U S A, 108(13), 5354-5359. doi:10.1073/pnas.1019378108
Ignesti, M., Barraco, M., Nallamothu, G., Woolworth, J. A., Duchi, S., Gargiulo, G., . . . Hsu, T.
(2014). Notch signaling during development requires the function of awd, the Drosophila
homolog of human metastasis suppressor gene Nm23. BMC Biol, 12, 12.
doi:10.1186/1741-7007-12-12
Ioannou, M. S., Jackson, J., Sheu, S. H., Chang, C. L., Weigel, A. V., Liu, H., . . . Liu, Z. (2019).
Neuron-Astrocyte Metabolic Coupling Protects against Activity-Induced Fatty Acid
Toxicity. Cell, 177(6), 1522-1535.e1514. doi:10.1016/j.cell.2019.04.001
133

Ja, W. W., Carvalho, G. B., Mak, E. M., de la Rosa, N. N., Fang, A. Y., Liong, J. C., . . . Benzer,
S. (2007). Prandiology of Drosophila and the CAFE assay. Proceedings of
the National Academy of Sciences, 104(20), 8253-8256. doi:10.1073/pnas.0702726104
Jarrett, S. G., Novak, M., Harris, N., Merlino, G., Slominski, A., & Kaetzel, D. M. (2013). NM23
deficiency promotes metastasis in a UV radiation-induced mouse model of human
melanoma. Clin Exp Metastasis, 30(1), 25-36. doi:10.1007/s10585-012-9495-z
Jefferis, G. S., Potter, C. J., Chan, A. M., Marin, E. C., Rohlfing, T., Maurer, C. R., Jr., & Luo, L.
(2007). Comprehensive maps of Drosophila higher olfactory centers: spatially
segregated fruit and pheromone representation. Cell, 128(6), 1187-1203.
doi:10.1016/j.cell.2007.01.040
Jessen, K. R. (2004). Glial cells. Int J Biochem Cell Biol, 36(10), 1861-1867.
doi:10.1016/j.biocel.2004.02.023
Jiang, H., Patel, P. H., Kohlmaier, A., Grenley, M. O., McEwen, D. G., & Edgar, B. A. (2009).
Cytokine/Jak/Stat signaling mediates regeneration and homeostasis in the Drosophila
midgut. Cell, 137(7), 1343-1355. doi:10.1016/j.cell.2009.05.014
Kaiser, M. (2015). Neuroanatomy: connectome connects fly and mammalian brain networks.
Curr Biol, 25(10), R416-418. doi:10.1016/j.cub.2015.03.039
Kaiser, M., & Hilgetag, C. C. (2006). Nonoptimal component placement, but short processing
paths, due to long-distance projections in neural systems. PLoS Comput Biol, 2(7), e95.
doi:10.1371/journal.pcbi.0020095
Karin, M., & Clevers, H. (2016). Reparative inflammation takes charge of tissue regeneration.
Nature, 5 2 9, 307-315. doi:10.1038/nature17039
Karpowicz, P., Perez, J., & Perrimon, N. (2010). The Hippo tumor suppressor pathway regulates
intestinal stem cell regeneration. Development, 137(24), 4135-4145.
doi:10.1242/dev.060483
Katzmann, D. J., Babst, M., & Emr, S. D. (2001). Ubiquitin-dependent sorting into the
multivesicular body pathway requires the function of a conserved endosomal protein
sorting complex, ESCRT-I. Cell, 106(2), 145-155.
Kazama, H., & Wilson, R. I. (2009). Origins of correlated activity in an olfactory circuit. Nat
Neurosci, 12(9), 1136-1144. doi:10.1038/nn.2376
134

Kazama, H., Yaksi, E., & Wilson, R. I. (2011). Cell death triggers olfactory circuit plasticity via
glial signaling in Drosophila. J Neurosci, 31(21), 7619-7630. doi:10.1523/jneurosci.5984-
10.2011
Keshavarzian, A., Engen, P., Bonvegna, S., & Cilia, R. (2020). The gut microbiome in
Parkinson's disease: A culprit or a bystander? Prog Brain Res, 252, 357-450.
doi:10.1016/bs.pbr.2020.01.004
Kietz, C., Pollari, V., & Meinander, A. (2018). Generating Germ-Free Drosophila to Study Gut-
Microbe Interactions: Protocol to Rear Drosophila Under Axenic Conditions. Curr Protoc
Toxicol, 77(1), e52. doi:10.1002/cptx.52
Kobler, J. M., Rodriguez Jimenez, F. J., Petcu, I., & Grunwald Kadow, I. C. (2020). Immune
Receptor Signaling and the Mushroom Body Mediate Post-ingestion Pathogen
Avoidance. Curr Biol. doi:10.1016/j.cub.2020.09.022
Korzelius, J., Azami, S., Ronnen-Oron, T., Koch, P., Baldauf, M., Meier, E., . . . Jasper, H.
(2019). The WT1-like transcription factor Klumpfuss maintains lineage commitment of
enterocyte progenitors in the Drosophila intestine. Nat Commun, 10(1), 4123.
doi:10.1038/s41467-019-12003-0
Kosinski, C., Li, V. S., Chan, A. S., Zhang, J., Ho, C., Tsui, W. Y., . . . Chen, X. (2007). Gene
expression patterns of human colon tops and basal crypts and BMP antagonists as
intestinal stem cell niche factors. Proc Natl Acad Sci U S A, 104(39), 15418-15423.
doi:10.1073/pnas.0707210104
Kotecha, A. M., Correa, A. D. C., Fisher, K. M., & Rushworth, J. V. (2018). Olfactory Dysfunction
as a Global Biomarker for Sniffing out Alzheimer's Disease: A Meta-Analysis. Biosensors
(Basel), 8(2). doi:10.3390/bios8020041
Kremer, M. C., Jung, C., Batelli, S., Rubin, G. M., & Gaul, U. (2017). The glia of the adult
Drosophila nervous system. Glia, 65(4), 606-638. doi:10.1002/glia.23115
Krishnan, K. S., Rikhy, R., Rao, S., Shivalkar, M., Mosko, M., Narayanan, R., . . . Ramaswami,
M. (2001). Nucleoside diphosphate kinase, a source of GTP, is required for dynamin-
dependent synaptic vesicle recycling. Neuron, 30(1), 197-210.
Kucherenko, M. M., & Shcherbata, H. R. (2013). Steroids as external temporal codes act via
microRNAs and cooperate with cytokines in differential neurogenesis. Fly (Austin), 7(3),
173-183. doi:10.4161/fly.25241
135

Kühnlein, R. P. (2012). Thematic review series: Lipid droplet synthesis and metabolism: from
yeast to man. Lipid droplet-based storage fat metabolism in Drosophila. J Lipid Res,
53(8), 1430-1436. doi:10.1194/jlr.R024299
Kunduri, G., Turner-Evans, D., Konya, Y., Izumi, Y., Nagashima, K., Lockett, S., . . . Acharya, J.
K. (2018). Defective cortex glia plasma membrane structure underlies light-induced
epilepsy in cpes mutants. Proc Natl Acad Sci U S A, 115(38), E8919-e8928.
doi:10.1073/pnas.1808463115
Lee, K. M., Mathies, L. D., & Grotewiel, M. (2019). Alcohol sedation in adult Drosophila is
regulated by Cysteine proteinase-1 in cortex glia. Commun Biol, 2, 252.
doi:10.1038/s42003-019-0492-5
Lee, T., & Luo, L. (2001). Mosaic analysis with a repressible cell marker (MARCM) for
Drosophila neural development. Trends Neurosci, 24(5), 251-254.
Lee, Y. J., Yang, C. P., Miyares, R. L., Huang, Y. F., He, Y., Ren, Q., . . . Lee, T. (2020).
Conservation and divergence of related neuronal lineages in the Drosophila central brain.
Elife, 9. doi:10.7554/eLife.53518
Leeman, D. S., Hebestreit, K., Ruetz, T., Webb, A. E., McKay, A., Pollina, E. A., . . . Brunet, A.
(2018). Lysosome activation clears aggregates and enhances quiescent neural stem cell
activation during aging. Science, 359(6381), 1277-1283. doi:10.1126/science.aag3048
Lemaitre, B., & Miguel-Aliaga, I. (2013). The digestive tract of Drosophila melanogaster. Annu
Rev Genet, 47, 377-404. doi:10.1146/annurev-genet-111212-133343
Li, H., Horns, F., Wu, B., Xie, Q., Li, J., Li, T., . . . Luo, L. (2017). Classifying Drosophila
Olfactory Projection Neuron Subtypes by Single-Cell RNA Sequencing. Cell, 171(5),
1206-1220.e1222. doi:10.1016/j.cell.2017.10.019
Li, H., & Jasper, H. (2016). Gastrointestinal stem cells in health and disease: from flies to
humans. Dis Model Mech, 9(5), 487-499. doi:10.1242/dmm.024232
Li, H., Qi, Y., & Jasper, H. (2013). Dpp signaling determines regional stem cell identity in the
regenerating adult Drosophila gastrointestinal tract. Cell Rep, 4(1), 10-18.
doi:10.1016/j.celrep.2013.05.040
Li, H., Qi, Y., & Jasper, H. (2016). Preventing Age-Related Decline of Gut Compartmentalization
Limits Microbiota Dysbiosis and Extends Lifespan. Cell Host Microbe, 19(2), 240-253.
doi:10.1016/j.chom.2016.01.008
136

Li, W., Yao, A., Zhi, H., Kaur, K., Zhu, Y. C., Jia, M., . . . Zhang, Y. Q. (2016). Angelman
Syndrome Protein Ube3a Regulates Synaptic Growth and Endocytosis by Inhibiting
BMP Signaling in Drosophila. PLoS Genet, 12(5), e1006062.
doi:10.1371/journal.pgen.1006062
Li, Z., Zhang, Y., Han, L., Shi, L., & Lin, X. (2013). Trachea-derived dpp controls adult midgut
homeostasis in Drosophila. Dev Cell, 24(2), 133-143. doi:10.1016/j.devcel.2012.12.010
Liang, J., Balachandra, S., Ngo, S., & O'Brien, L. E. (2017). Feedback regulation of steady-state
epithelial turnover and organ size. Nature, 548(7669), 588-591.
doi:10.1038/nature23678
Liang, L., & Luo, L. (2010). The olfactory circuit of the fruit fly Drosophila melanogaster. Sci
China Life Sci, 53(4), 472-484. doi:10.1007/s11427-010-0099-z
Liddle, R. A. (2018). Interactions of Gut Endocrine Cells with Epithelium and Neurons. Compr
Physiol, 8(3), 1019-1030. doi:10.1002/cphy.c170044
Lin, G., Xu, N., & Xi, R. (2008). Paracrine Wingless signalling controls self-renewal of
Drosophila intestinal stem cells. Nature, 455(7216), 1119-1123.
doi:10.1038/nature07329
Lin, Y. T., Seo, J., Gao, F., Feldman, H. M., Wen, H. L., Penney, J., . . . Tsai, L. H. (2018).
APOE4 Causes Widespread Molecular and Cellular Alterations Associated with
Alzheimer's Disease Phenotypes in Human iPSC-Derived Brain Cell Types. Neuron,
98(6), 1141-1154.e1147. doi:10.1016/j.neuron.2018.05.008
Liu, C. C., Liu, C. C., Kanekiyo, T., Xu, H., & Bu, G. (2013). Apolipoprotein E and Alzheimer
disease: risk, mechanisms and therapy. Nat Rev Neurol, 9(2), 106-118.
doi:10.1038/nrneurol.2012.263
Liu, H., Zhou, B., Yan, W., Lei, Z., Zhao, X., Zhang, K., & Guo, A. (2014). Astrocyte-like glial
cells physiologically regulate olfactory processing through the modification of ORN-PN
synaptic strength in Drosophila. Eur J Neurosci, 40(5), 2744-2754.
doi:10.1111/ejn.12646
Liu, L., MacKenzie, K. R., Putluri, N., Maletic-Savatic, M., & Bellen, H. J. (2017). The Glia-
Neuron Lactate Shuttle and Elevated ROS Promote Lipid Synthesis in Neurons and
Lipid Droplet Accumulation in Glia via APOE/D. Cell Metab, 26(5), 719-737.e716.
doi:10.1016/j.cmet.2017.08.024
137

Liu, L., Zhang, K., Sandoval, H., Yamamoto, S., Jaiswal, M., Sanz, E., . . . Bellen, H. J. (2015).
Glial lipid droplets and ROS induced by mitochondrial defects promote
neurodegeneration. Cell, 160(1-2), 177-190. doi:10.1016/j.cell.2014.12.019
Lu, B., & Vogel, H. (2009). Drosophila models of neurodegenerative diseases. Annu Rev Pathol,
4, 315-342. doi:10.1146/annurev.pathol.3.121806.151529
Lucchetta, E. M., & Ohlstein, B. (2012). The Drosophila midgut: a model for stem cell driven
tissue regeneration. Wiley Interdiscip Rev Dev Biol, 1(5), 781-788. doi:10.1002/wdev.51
Lucchetta, E. M., & Ohlstein, B. (2017). Amitosis of Polyploid Cells Regenerates Functional
Stem Cells in the Drosophila Intestine. Cell Stem Cell, 20(5), 609-620.e606.
doi:10.1016/j.stem.2017.02.012
Luo, L., Liao, Y. J., Jan, L. Y., & Jan, Y. N. (1994). Distinct morphogenetic functions of similar
small GTPases: Drosophila Drac1 is involved in axonal outgrowth and myoblast fusion.
Genes Dev, 8(15), 1787-1802. doi:10.1101/gad.8.15.1787
Ma, Z., Stork, T., Bergles, D. E., & Freeman, M. R. (2016). Neuromodulators signal through
astrocytes to alter neural circuit activity and behaviour. Nature, 539(7629), 428-432.
doi:10.1038/nature20145
Maillet, F., Bischoff, V., Vignal, C., Hoffmann, J., & Royet, J. (2008). The Drosophila
peptidoglycan recognition protein PGRP-LF blocks PGRP-LC and IMD/JNK pathway
activation. Cell Host Microbe, 3(5), 293-303. doi:10.1016/j.chom.2008.04.002
Marianes, A., & Spradling, A. C. (2013). Physiological and stem cell compartmentalization within
the Drosophila midgut. Elife, 2, e00886. doi:10.7554/eLife.00886
Marin, C., Vilas, D., Langdon, C., Alobid, I., Lopez-Chacon, M., Haehner, A., . . . Mullol, J.
(2018). Olfactory Dysfunction in Neurodegenerative Diseases. Curr Allergy Asthma Rep,
18(8), 42. doi:10.1007/s11882-018-0796-4
Marin, E. C., Jefferis, G. S., Komiyama, T., Zhu, H., & Luo, L. (2002). Representation of the
glomerular olfactory map in the Drosophila brain. Cell, 109(2), 243-255.
doi:10.1016/s0092-8674(02)00700-6
Matheoud, D., Cannon, T., Voisin, A., Penttinen, A. M., Ramet, L., Fahmy, A. M., . . . Desjardins,
M. (2019). Intestinal infection triggers Parkinson's disease-like symptoms in Pink1(-/-)
mice. Nature, 571(7766), 565-569. doi:10.1038/s41586-019-1405-y
138

Mawe, G. M., & Hoffman, J. M. (2013). Serotonin signalling in the gut--functions, dysfunctions
and therapeutic targets. Nat Rev Gastroenterol Hepatol, 10(8), 473-486.
doi:10.1038/nrgastro.2013.105
Mayer, E. A. (2011). Gut feelings: the emerging biology of gut-brain communication. Nat Rev
Neurosci, 12(8), 453-466. doi:10.1038/nrn3071
Mazaud, D., Kottler, B., Gonçalves-Pimentel, C., Proelss, S., Tüchler, N., Deneubourg, C., . . .
Fanto, M. (2019). Transcriptional Regulation of the Glutamate/GABA/Glutamine Cycle in
Adult Glia Controls Motor Activity and Seizures in Drosophila. J Neurosci, 39(27), 5269-
5283. doi:10.1523/jneurosci.1833-18.2019
McCabe, B. D., Hom, S., Aberle, H., Fetter, R. D., Marques, G., Haerry, T. E., . . . Haghighi, A.
P. (2004). Highwire regulates presynaptic BMP signaling essential for synaptic growth.
Neuron, 41(6), 891-905.
McClelland, L., Jasper, H., & Biteau, B. (2017). Tis11 mediated mRNA decay promotes the
reacquisition of Drosophila intestinal stem cell quiescence. Dev Biol, 426(1), 8-16.
doi:10.1016/j.ydbio.2017.04.013
Men, T. T., Binh, T. D., Yamaguchi, M., Huy, N. T., & Kamei, K. (2016). Function of Lipid
Storage Droplet 1 (Lsd1) in Wing Development of Drosophila melanogaster. Int J Mol Sci,
17(5). doi:10.3390/ijms17050648
Mettlen, M., Pucadyil, T., Ramachandran, R., & Schmid, S. L. (2009). Dissecting dynamin's role
in clathrin-mediated endocytosis. Biochem Soc Trans, 37(Pt 5), 1022-1026.
doi:10.1042/bst0371022
Micchelli, C. A., & Perrimon, N. (2006). Evidence that stem cells reside in the adult Drosophila
midgut epithelium. Nature, 439(7075), 475-479. doi:10.1038/nature04371
Miguel-Aliaga, I., Jasper, H., & Lemaitre, B. (2018). Anatomy and Physiology of the Digestive
Tract of Drosophila melanogaster. Genetics, 210(2), 357-396.
doi:10.1534/genetics.118.300224
Minter, M. R., Zhang, C., Leone, V., Ringus, D. L., Zhang, X., Oyler-Castrillo, P., . . . Sisodia, S.
S. (2016). Antibiotic-induced perturbations in gut microbial diversity influences neuro-
inflammation and amyloidosis in a murine model of Alzheimer's disease. Sci Rep, 6,
30028. doi:10.1038/srep30028
Miyazono, K., Kamiya, Y., & Morikawa, M. (2010). Bone morphogenetic protein receptors and
signal transduction. J Biochem, 147(1), 35-51. doi:10.1093/jb/mvp148
139

Miyazono, K., Maeda, S., & Imamura, T. (2005). BMP receptor signaling: transcriptional targets,
regulation of signals, and signaling cross-talk. Cytokine Growth Factor Rev, 16(3), 251-
263. doi:10.1016/j.cytogfr.2005.01.009
Montiel-Castro, A. J., Gonzalez-Cervantes, R. M., Bravo-Ruiseco, G., & Pacheco-Lopez, G.
(2013). The microbiota-gut-brain axis: neurobehavioral correlates, health and sociality.
Front Integr Neurosci, 7, 70. doi:10.3389/fnint.2013.00070
Morris, O., Deng, H., Tam, C., & Jasper, H. (2020). Warburg-like Metabolic Reprogramming in
Aging Intestinal Stem Cells Contributes to Tissue Hyperplasia. Cell Rep, 33(8), 108423.
doi:10.1016/j.celrep.2020.108423
Morris, R., Kershaw, N. J., & Babon, J. J. (2018). The molecular details of cytokine signaling via
the JAK/STAT pathway. Protein Sci, 27(12), 1984-2009. doi:10.1002/pro.3519
Mosca, T. J., & Luo, L. (2014). Synaptic organization of the Drosophila antennal lobe and its
regulation by the Teneurins. Elife, 3, e03726. doi:10.7554/eLife.03726
Moskalev, A., & Shaposhnikov, M. (2011). Pharmacological inhibition of NF-κB prolongs
lifespan of Drosophila melanogaster. Aging (Albany NY), 3(4), 391-394.
doi:10.18632/aging.100314
Mukherjee, S., Tessema, M., & Wandinger-Ness, A. (2006). Vesicular trafficking of tyrosine
kinase receptors and associated proteins in the regulation of signaling and vascular
function. Circ Res, 98(6), 743-756. doi:10.1161/01.RES.0000214545.99387.e3
Murakami, R., Shigenaga, A., Matsumoto, A., Yamaoka, I., & Tanimura, T. (1994). Novel tissue
units of regional differentiation in the gut epithelium of Drosopbila, as revealed by P-
element-mediated detection of enhancer. Rouxs Arch Dev Biol, 203(5), 243-249.
doi:10.1007/bf00360519
Murray, P. J. (2007). The JAK-STAT signaling pathway: input and output integration. J Immunol,
178(5), 2623-2629. doi:10.4049/jimmunol.178.5.2623
Musashe, D. T., Purice, M. D., Speese, S. D., Doherty, J., & Logan, M. A. (2016). Insulin-like
Signaling Promotes Glial Phagocytic Clearance of Degenerating Axons through
Regulation of Draper. Cell Rep, 16(7), 1838-1850. doi:10.1016/j.celrep.2016.07.022
Nakano, R., Iwamura, M., Obikawa, A., Togane, Y., Hara, Y., Fukuhara, T., . . . Tsujimura, H.
(2019). Cortex glia clear dead young neurons via Drpr/dCed-6/Shark and Crk/Mbc/dCed-
12 signaling pathways in the developing Drosophila optic lobe. Dev Biol, 453(1), 68-85.
doi:10.1016/j.ydbio.2019.05.003
140

Nallamothu, G., Woolworth, J. A., Dammai, V., & Hsu, T. (2008). Awd, the homolog of
metastasis suppressor gene Nm23, regulates Drosophila epithelial cell invasion. Mol
Cell Biol, 28(6), 1964-1973. doi:10.1128/mcb.01743-07
Nguyen, T. B., Louie, S. M., Daniele, J. R., Tran, Q., Dillin, A., Zoncu, R., . . . Olzmann, J. A.
(2017). DGAT1-Dependent Lipid Droplet Biogenesis Protects Mitochondrial Function
during Starvation-Induced Autophagy. Dev Cell, 42(1), 9-21.e25.
doi:10.1016/j.devcel.2017.06.003
Nicolas, C. S., Amici, M., Bortolotto, Z. A., Doherty, A., Csaba, Z., Fafouri, A., . . . Peineau, S.
(2013). The role of JAK-STAT signaling within the CNS. Jakstat, 2(1), e22925.
doi:10.4161/jkst.22925
Norman, M., Vuilleumier, R., Springhorn, A., Gawlik, J., & Pyrowolakis, G. (2016). Pentagone
internalises glypicans to fine-tune multiple signalling pathways. Elife, 5.
doi:10.7554/eLife.13301
Nozawa, K., Kawabata-Shoda, E., Doihara, H., Kojima, R., Okada, H., Mochizuki, S., . . . Ito, H.
(2009). TRPA1 regulates gastrointestinal motility through serotonin release from
enterochromaffin cells. Proc Natl Acad Sci U S A, 106(9), 3408-3413.
doi:10.1073/pnas.0805323106
O'Connor-Giles, K. M., Ho, L. L., & Ganetzky, B. (2008). Nervous wreck interacts with thickveins
and the endocytic machinery to attenuate retrograde BMP signaling during synaptic
growth. Neuron, 58(4), 507-518. doi:10.1016/j.neuron.2008.03.007
Obata, F., Fons, C. O., & Gould, A. P. (2018). Early-life exposure to low-dose oxidants can
increase longevity via microbiome remodelling in Drosophila. Nat Commun, 9(1), 975.
doi:10.1038/s41467-018-03070-w
Ohlstein, B., & Spradling, A. (2006). The adult Drosophila posterior midgut is maintained by
pluripotent stem cells. Nature, 439(7075), 470-474. doi:10.1038/nature04333
Osman, D., Buchon, N., Chakrabarti, S., Huang, Y. T., Su, W. C., Poidevin, M., . . . Lemaitre, B.
(2012). Autocrine and paracrine unpaired signaling regulate intestinal stem cell
maintenance and division. J Cell Sci, 125(Pt 24), 5944-5949. doi:10.1242/jcs.113100
Otto, N., Marelja, Z., Schoofs, A., Kranenburg, H., Bittern, J., Yildirim, K., . . . Klämbt, C. (2018).
The sulfite oxidase Shopper controls neuronal activity by regulating glutamate
homeostasis in Drosophila ensheathing glia. Nat Commun, 9(1), 3514.
doi:10.1038/s41467-018-05645-z
141

Pandey, U. B., Nie, Z., Batlevi, Y., McCray, B. A., Ritson, G. P., Nedelsky, N. B., . . . Taylor, J. P.
(2007). HDAC6 rescues neurodegeneration and provides an essential link between
autophagy and the UPS. Nature, 447(7146), 859-863. doi:10.1038/nature05853
Park, J. S., Kim, Y. S., & Yoo, M. A. (2009). The role of p38b MAPK in age-related modulation
of intestinal stem cell proliferation and differentiation in Drosophila. Aging (Albany NY),
1(7), 637-651. doi:10.18632/aging.100054
Parkhurst, S. J., Adhikari, P., Navarrete, J. S., Legendre, A., Manansala, M., & Wolf, F. W.
(2018). Perineurial Barrier Glia Physically Respond to Alcohol in an Akap200-Dependent
Manner to Promote Tolerance. Cell Rep, 22(7), 1647-1656.
doi:10.1016/j.celrep.2018.01.049
Pereanu, W., Spindler, S., Cruz, L., & Hartenstein, V. (2007). Tracheal development in the
Drosophila brain is constrained by glial cells. Dev Biol, 302(1), 169-180.
doi:10.1016/j.ydbio.2006.09.022
Phillips, M. D., & Thomas, G. H. (2006). Brush border spectrin is required for early endosome
recycling in Drosophila. J Cell Sci, 119(Pt 7), 1361-1370. doi:10.1242/jcs.02839
Picelli, S., Faridani, O. R., Björklund, A. K., Winberg, G., Sagasser, S., & Sandberg, R. (2014).
Full-length RNA-seq from single cells using Smart-seq2. Nat Protoc, 9(1), 171-181.
doi:10.1038/nprot.2014.006
Poinsot, P., Penhoat, A., Mitchell, M., Sauvinet, V., Meiller, L., Louche-Pélissier, C., . . . Peretti,
N. (2020). Probiotic from human breast milk, Lactobacillus fermentum, promotes growth
in animal model of chronic malnutrition. Pediatr Res, 88(3), 374-381.
doi:10.1038/s41390-020-0774-0
Proserpio, C., Invitti, C., Boesveldt, S., Pasqualinotto, L., Laureati, M., Cattaneo, C., & Pagliarini,
E. (2019). Ambient Odor Exposure Affects Food Intake and Sensory Specific Appetite in
Obese Women. Frontiers in Psychology, 10(7). doi:10.3389/fpsyg.2019.00007
Purice, M. D., Ray, A., Munzel, E. J., Pope, B. J., Park, D. J., Speese, S. D., & Logan, M. A.
(2017). A novel Drosophila injury model reveals severed axons are cleared through a
Draper/MMP-1 signaling cascade. Elife, 6. doi:10.7554/eLife.23611
Qi, Z., Li, Y., Zhao, B., Xu, C., Liu, Y., Li, H., . . . Chen, Y. G. (2017). BMP restricts stemness of
intestinal Lgr5(+) stem cells by directly suppressing their signature genes. Nat Commun,
8, 13824. doi:10.1038/ncomms13824
142

Qin, H., Buckley, J. A., Li, X., Liu, Y., Fox, T. H., 3rd, Meares, G. P., . . . Benveniste, E. N.
(2016). Inhibition of the JAK/STAT Pathway Protects Against alpha-Synuclein-Induced
Neuroinflammation and Dopaminergic Neurodegeneration. J Neurosci, 36(18), 5144-
5159. doi:10.1523/jneurosci.4658-15.2016
Raja, E., Tzavlaki, K., Vuilleumier, R., Edlund, K., Kahata, K., Zieba, A., . . . Moustakas, A.
(2016). The protein kinase LKB1 negatively regulates bone morphogenetic protein
receptor signaling. Oncotarget, 7(2), 1120-1143. doi:10.18632/oncotarget.6683
Rajan, A., & Perrimon, N. (2012). Drosophila cytokine unpaired 2 regulates physiological
homeostasis by remotely controlling insulin secretion. Cell, 151(1), 123-137.
doi:10.1016/j.cell.2012.08.019
Rawlings, J. S., Rosler, K. M., & Harrison, D. A. (2004). The JAK/STAT signaling pathway. J
Cell Sci, 117(Pt 8), 1281-1283. doi:10.1242/jcs.00963
Ray, A., Speese, S. D., & Logan, M. A. (2017). Glial Draper Rescues Abeta Toxicity in a
Drosophila Model of Alzheimer's Disease. J Neurosci, 37(49), 11881-11893.
doi:10.1523/jneurosci.0862-17.2017
Read, R. D. (2018). Pvr receptor tyrosine kinase signaling promotes post-embryonic
morphogenesis, and survival of glia and neural progenitor cells in Drosophila.
Development, 145(23). doi:10.1242/dev.164285
Reiter, L. T., Potocki, L., Chien, S., Gribskov, M., & Bier, E. (2001). A systematic analysis of
human disease-associated gene sequences in Drosophila melanogaster. Genome Res,
11(6), 1114-1125. doi:10.1101/gr.169101
Ren, C., Webster, P., Finkel, S. E., & Tower, J. (2007). Increased internal and external bacterial
load during Drosophila aging without life-span trade-off. Cell Metab, 6(2), 144-152.
doi:10.1016/j.cmet.2007.06.006
Ren, F., Wang, B., Yue, T., Yun, E. Y., Ip, Y. T., & Jiang, J. (2010). Hippo signaling regulates
Drosophila intestine stem cell proliferation through multiple pathways. Proc Natl Acad
Sci U S A, 107(49), 21064-21069. doi:10.1073/pnas.1012759107
Rera, M., Bahadorani, S., Cho, J., Koehler, C. L., Ulgherait, M., Hur, J. H., . . . Walker, D. W.
(2011). Modulation of longevity and tissue homeostasis by the Drosophila PGC-1
homolog. Cell Metab, 14(5), 623-634. doi:10.1016/j.cmet.2011.09.013
143

Rera, M., Clark, R. I., & Walker, D. W. (2012). Intestinal barrier dysfunction links metabolic and
inflammatory markers of aging to death in Drosophila. Proc Natl Acad Sci U S A, 109(52),
21528-21533. doi:10.1073/pnas.1215849110
Resnik-Docampo, M., Koehler, C. L., Clark, R. I., Schinaman, J. M., Sauer, V., Wong, D. M., . . .
Jones, D. L. (2017). Tricellular junctions regulate intestinal stem cell behaviour to
maintain homeostasis. Nat Cell Biol, 19(1), 52-59. doi:10.1038/ncb3454
Resnik-Docampo, M., Sauer, V., Schinaman, J. M., Clark, R. I., Walker, D. W., & Jones, D. L.
(2018). Keeping it tight: The relationship between bacterial dysbiosis, septate junctions,
and the intestinal barrier in Drosophila. Fly (Austin), 12(1), 34-40.
doi:10.1080/19336934.2018.1441651
Rey, N. L., Wesson, D. W., & Brundin, P. (2018). The olfactory bulb as the entry site for prion-
like propagation in neurodegenerative diseases. Neurobiol Dis, 109(Pt B), 226-248.
doi:10.1016/j.nbd.2016.12.013
Rock, J. R., & Hogan, B. L. (2011). Epithelial Progenitor Cells in Lung Development,
Maintenance, Repair, and Disease. Annu Rev Cell Dev Biol. doi:10.1146/annurev-
cellbio-100109-104040
Rodal, A. A., Blunk, A. D., Akbergenova, Y., Jorquera, R. A., Buhl, L. K., & Littleton, J. T. (2011).
A presynaptic endosomal trafficking pathway controls synaptic growth signaling. J Cell
Biol, 193(1), 201-217. doi:10.1083/jcb.201009052
Rosca, M. G., Vazquez, E. J., Chen, Q., Kerner, J., Kern, T. S., & Hoppel, C. L. (2012).
Oxidation of fatty acids is the source of increased mitochondrial reactive oxygen species
production in kidney cortical tubules in early diabetes. Diabetes, 61(8), 2074-2083.
doi:10.2337/db11-1437
Rothhammer, V., Mascanfroni, I. D., Bunse, L., Takenaka, M. C., Kenison, J. E., Mayo, L., . . .
Quintana, F. J. (2016). Type I interferons and microbial metabolites of tryptophan
modulate astrocyte activity and central nervous system inflammation via the aryl
hydrocarbon receptor. Nat Med, 22(6), 586-597. doi:10.1038/nm.4106
Rubin, G. M., & Lewis, E. B. (2000). A brief history of Drosophila's contributions to genome
research. Science, 287(5461), 2216-2218. doi:10.1126/science.287.5461.2216
Ryu, J. H., Kim, S. H., Lee, H. Y., Bai, J. Y., Nam, Y. D., Bae, J. W., . . . Lee, W. J. (2008).
Innate immune homeostasis by the homeobox gene caudal and commensal-gut
mutualism in Drosophila. Science, 319(5864), 777-782. doi:10.1126/science.1149357
144

Salazar, A. M., Resnik-Docampo, M., Ulgherait, M., Clark, R. I., Shirasu-Hiza, M., Jones, D. L.,
& Walker, D. W. (2018). Intestinal Snakeskin Limits Microbial Dysbiosis during Aging
and Promotes Longevity. iScience, 9, 229-243. doi:10.1016/j.isci.2018.10.022
Salmon Ceron, D., Bartier, S., Hautefort, C., Nguyen, Y., Nevoux, J., Hamel, A. L., . . .
Bequignon, E. (2020). Self-reported loss of smell without nasal obstruction to identify
COVID-19. The multicenter Coranosmia cohort study. J Infect.
doi:10.1016/j.jinf.2020.07.005
Sampson, T. R., Debelius, J. W., Thron, T., Janssen, S., Shastri, G. G., Ilhan, Z. E., . . .
Mazmanian, S. K. (2016). Gut Microbiota Regulate Motor Deficits and
Neuroinflammation in a Model of Parkinson's Disease. Cell, 167(6), 1469-1480.e1412.
doi:10.1016/j.cell.2016.11.018
Sampson, T. R., & Mazmanian, S. K. (2015). Control of brain development, function, and
behavior by the microbiome. Cell Host Microbe, 17(5), 565-576.
doi:10.1016/j.chom.2015.04.011
Sansone, C. L., Cohen, J., Yasunaga, A., Xu, J., Osborn, G., Subramanian, H., . . . Cherry, S.
(2015). Microbiota-Dependent Priming of Antiviral Intestinal Immunity in Drosophila. Cell
Host Microbe, 18(5), 571-581. doi:10.1016/j.chom.2015.10.010
Sayin, S., Boehm, A. C., Kobler, J. M., De Backer, J. F., & Grunwald Kadow, I. C. (2018).
Internal State Dependent Odor Processing and Perception-The Role of Neuromodulation
in the Fly Olfactory System. Front Cell Neurosci, 12, 11. doi:10.3389/fncel.2018.00011
Schonfeld, P., & Reiser, G. (2017). Brain energy metabolism spurns fatty acids as fuel due to
their inherent mitotoxicity and potential capacity to unleash neurodegeneration.
Neurochem Int, 109, 68-77. doi:10.1016/j.neuint.2017.03.018
Schousboe, A., Bak, L. K., & Waagepetersen, H. S. (2013). Astrocytic Control of Biosynthesis
and Turnover of the Neurotransmitters Glutamate and GABA. Front Endocrinol
(Lausanne), 4, 102. doi:10.3389/fendo.2013.00102
Schretter, C. E., Vielmetter, J., Bartos, I., Marka, Z., Marka, S., Argade, S., & Mazmanian, S. K.
(2018). A gut microbial factor modulates locomotor behaviour in Drosophila. Nature,
563(7731), 402-406. doi:10.1038/s41586-018-0634-9
Schultzhaus, J. N., Saleem, S., Iftikhar, H., & Carney, G. E. (2017). The role of the Drosophila
lateral horn in olfactory information processing and behavioral response. J Insect Physiol,
98, 29-37. doi:10.1016/j.jinsphys.2016.11.007
145

Scita, G., & Di Fiore, P. P. (2010). The endocytic matrix. Nature, 463(7280), 464-473.
doi:10.1038/nature08910
Seabrooke, S., & O'Donnell, M. J. (2013). Oatp58Dc contributes to blood-brain barrier function
by excluding organic anions from the Drosophila brain. Am J Physiol Cell Physiol, 305(5),
C558-567. doi:10.1152/ajpcell.00408.2012
Sefton, L., Timmer, J. R., Zhang, Y., Béranger, F., & Cline, T. W. (2000). An extracellular
activator of the Drosophila JAK/STAT pathway is a sex-determination signal element.
Nature, 405(6789), 970-973. doi:10.1038/35016119
Seki, Y., Dweck, H. K. M., Rybak, J., Wicher, D., Sachse, S., & Hansson, B. S. (2017). Olfactory
coding from the periphery to higher brain centers in the Drosophila brain. BMC Biol,
15(1), 56. doi:10.1186/s12915-017-0389-z
Sengupta, S., Crowe, L. B., You, S., Roberts, M. A., & Jackson, F. R. (2019). A Secreted Ig-
Domain Protein Required in Both Astrocytes and Neurons for Regulation of Drosophila
Night Sleep. Curr Biol, 29(15), 2547-2554.e2542. doi:10.1016/j.cub.2019.06.055
Sepp, K. J., Schulte, J., & Auld, V. J. (2001). Peripheral glia direct axon guidance across the
CNS/PNS transition zone. Dev Biol, 238(1), 47-63. doi:10.1006/dbio.2001.0411
Shaw, R. L., Kohlmaier, A., Polesello, C., Veelken, C., Edgar, B. A., & Tapon, N. (2010). The
Hippo pathway regulates intestinal stem cell proliferation during Drosophila adult midgut
regeneration. Development, 137(24), 4147-4158. doi:10.1242/dev.052506
Shih, C. T., Sporns, O., Yuan, S. L., Su, T. S., Lin, Y. J., Chuang, C. C., . . . Chiang, A. S.
(2015). Connectomics-based analysis of information flow in the Drosophila brain. Curr
Biol, 25(10), 1249-1258. doi:10.1016/j.cub.2015.03.021
Sieber, C., Kopf, J., Hiepen, C., & Knaus, P. (2009). Recent advances in BMP receptor
signaling. Cytokine Growth Factor Rev, 20(5-6), 343-355.
doi:10.1016/j.cytogfr.2009.10.007
Silva, Y. P., Bernardi, A., & Frozza, R. L. (2020). The Role of Short-Chain Fatty Acids From Gut
Microbiota in Gut-Brain Communication. Front Endocrinol (Lausanne), 11, 25.
doi:10.3389/fendo.2020.00025
Soni, K. G., Mardones, G. A., Sougrat, R., Smirnova, E., Jackson, C. L., & Bonifacino, J. S.
(2009). Coatomer-dependent protein delivery to lipid droplets. J Cell Sci, 122(Pt 11),
1834-1841. doi:10.1242/jcs.045849
146

Soria-Gomez, E., Bellocchio, L., & Marsicano, G. (2014). New insights on food intake control by
olfactory processes: the emerging role of the endocannabinoid system. Mol Cell
Endocrinol, 397(1-2), 59-66. doi:10.1016/j.mce.2014.09.023
Soria-Gómez, E., Bellocchio, L., Reguero, L., Lepousez, G., Martin, C., Bendahmane, M., . . .
Marsicano, G. (2014). The endocannabinoid system controls food intake via olfactory
processes. Nature Neuroscience, 17(3), 407-415. doi:10.1038/nn.3647
Sousa-Victor, P., Ayyaz, A., Hayashi, R., Qi, Y., Madden, D. T., Lunyak, V. V., & Jasper, H.
(2017). Piwi Is Required to Limit Exhaustion of Aging Somatic Stem Cells. Cell Rep,
20(11), 2527-2537. doi:10.1016/j.celrep.2017.08.059
Stahl, B. A., Peco, E., Davla, S., Murakami, K., Caicedo Moreno, N. A., van Meyel, D. J., &
Keene, A. C. (2018). The Taurine Transporter Eaat2 Functions in Ensheathing Glia to
Modulate Sleep and Metabolic Rate. Curr Biol, 28(22), 3700-3708.e3704.
doi:10.1016/j.cub.2018.10.039
Staley, B. K., & Irvine, K. D. (2010). Warts and Yorkie mediate intestinal regeneration by
influencing stem cell proliferation. Curr Biol, 20(17), 1580-1587.
doi:10.1016/j.cub.2010.07.041
Stensmyr, M. C., Dweck, H. K., Farhan, A., Ibba, I., Strutz, A., Mukunda, L., . . . Hansson, B. S.
(2012). A conserved dedicated olfactory circuit for detecting harmful microbes in
Drosophila. Cell, 151(6), 1345-1357. doi:10.1016/j.cell.2012.09.046
Stoffolano, J. G., Jr., & Haselton, A. T. (2013). The adult Dipteran crop: a unique and
overlooked organ. Annu Rev Entomol, 58, 205-225. doi:10.1146/annurev-ento-120811-
153653
Stork, T., Sheehan, A., Tasdemir-Yilmaz, O. E., & Freeman, M. R. (2014). Neuron-glia
interactions through the Heartless FGF receptor signaling pathway mediate
morphogenesis of Drosophila astrocytes. Neuron, 83(2), 388-403.
doi:10.1016/j.neuron.2014.06.026
Suh, G. S., Wong, A. M., Hergarden, A. C., Wang, J. W., Simon, A. F., Benzer, S., . . . Anderson,
D. J. (2004). A single population of olfactory sensory neurons mediates an innate
avoidance behaviour in Drosophila. Nature, 431(7010), 854-859.
doi:10.1038/nature02980
Sundler, F., Böttcher, G., Ekblad, E., & Håkanson, R. (1989). The neuroendocrine system of the
gut. Acta Oncol, 28(3), 303-314. doi:10.3109/02841868909111198
147

Tabata, T., & Takei, Y. (2004). Morphogens, their identification and regulation. Development,
131(4), 703-712. doi:10.1242/dev.01043
Tadokoro, T., Gao, X., Hong, C. C., Hotten, D., & Hogan, B. L. (2016). BMP signaling and
cellular dynamics during regeneration of airway epithelium from basal progenitors.
Development, 143(5), 764-773. doi:10.1242/dev.126656
Takemura, M., Bowden, N., Lu, Y. S., Nakato, E., O'Connor, M. B., & Nakato, H. (2021).
Drosophila MOV10 regulates the termination of midgut regeneration. Genetics.
doi:10.1093/genetics/iyab031
Tetteh, P. W., Basak, O., Farin, H. F., Wiebrands, K., Kretzschmar, K., Begthel, H., . . . Clevers,
H. (2016). Replacement of Lost Lgr5-Positive Stem Cells through Plasticity of Their
Enterocyte-Lineage Daughters. Cell Stem Cell, 18(2), 203-213.
doi:10.1016/j.stem.2016.01.001
Thompson, B. J., Mathieu, J., Sung, H. H., Loeser, E., Rorth, P., & Cohen, S. M. (2005). Tumor
suppressor properties of the ESCRT-II complex component Vps25 in Drosophila. Dev
Cell, 9(5), 711-720. doi:10.1016/j.devcel.2005.09.020
Thorne, C. A., Chen, I. W., Sanman, L. E., Cobb, M. H., Wu, L. F., & Altschuler, S. J. (2018).
Enteroid Monolayers Reveal an Autonomous WNT and BMP Circuit Controlling Intestinal
Epithelial Growth and Organization. Dev Cell, 44(5), 624-633.e624.
doi:10.1016/j.devcel.2018.01.024
Tian, A., Benchabane, H., Wang, Z., & Ahmed, Y. (2016). Regulation of Stem Cell Proliferation
and Cell Fate Specification by Wingless/Wnt Signaling Gradients Enriched at Adult
Intestinal Compartment Boundaries. PLoS Genet, 12(2), e1005822.
doi:10.1371/journal.pgen.1005822
Tian, A., & Jiang, J. (2014). Intestinal epithelium-derived BMP controls stem cell self-renewal in
Drosophila adult midgut. Elife, 3, e01857. doi:10.7554/eLife.01857
Tian, A., Wang, B., & Jiang, J. (2017). Injury-stimulated and self-restrained BMP signaling
dynamically regulates stem cell pool size during Drosophila midgut regeneration. Proc
Natl Acad Sci U S A, 114(13), E2699-e2708. doi:10.1073/pnas.1617790114
Tian, Q., He, X. C., Hood, L., & Li, L. (2005). Bridging the BMP and Wnt pathways by PI3
kinase/Akt and 14-3-3zeta. Cell Cycle, 4(2), 215-216.
148

Tracy Cai, X., Li, H., Safyan, A., Gawlik, J., Pyrowolakis, G., & Jasper, H. (2019). AWD
regulates timed activation of BMP signaling in intestinal stem cells to maintain tissue
homeostasis. Nat Commun, 10(1), 2988. doi:10.1038/s41467-019-10926-2
Truman, J. W., & Bate, M. (1988). Spatial and temporal patterns of neurogenesis in the central
nervous system of Drosophila melanogaster. Dev Biol, 125(1), 145-157.
doi:10.1016/0012-1606(88)90067-x
Ulgherait, M., Rana, A., Rera, M., Graniel, J., & Walker, D. W. (2014). AMPK modulates tissue
and organismal aging in a non-cell-autonomous manner. Cell Rep, 8(6), 1767-1780.
doi:10.1016/j.celrep.2014.08.006
Ung, K., Tepe, B., Pekarek, B., Arenkiel, B. R., & Deneen, B. (2020). Parallel astrocyte calcium
signaling modulates olfactory bulb responses. J Neurosci Res, 98(8), 1605-1618.
doi:10.1002/jnr.24634
Unger, R. H., Clark, G. O., Scherer, P. E., & Orci, L. (2010). Lipid homeostasis, lipotoxicity and
the metabolic syndrome. Biochim Biophys Acta, 1801(3), 209-214.
doi:10.1016/j.bbalip.2009.10.006
Urbischek, M., Rannikmae, H., Foets, T., Ravn, K., Hyvönen, M., & de la Roche, M. (2019).
Organoid culture media formulated with growth factors of defined cellular activity. Sci
Rep, 9(1), 6193. doi:10.1038/s41598-019-42604-0
Vander Heiden, M. G., & DeBerardinis, R. J. (2017). Understanding the Intersections between
Metabolism and Cancer Biology. Cell, 168(4), 657-669. doi:10.1016/j.cell.2016.12.039
Vanderheyden, W. M., Goodman, A. G., Taylor, R. H., Frank, M. G., Van Dongen, H. P. A., &
Gerstner, J. R. (2018). Astrocyte expression of the Drosophila TNF-alpha homologue,
Eiger, regulates sleep in flies. PLoS Genet, 14(10), e1007724.
doi:10.1371/journal.pgen.1007724
Volkenhoff, A., Hirrlinger, J., Kappel, J. M., Klämbt, C., & Schirmeier, S. (2018). Live imaging
using a FRET glucose sensor reveals glucose delivery to all cell types in the Drosophila
brain. J Insect Physiol, 106(Pt 1), 55-64. doi:10.1016/j.jinsphys.2017.07.010
Vosshall, L. B., Amrein, H., Morozov, P. S., Rzhetsky, A., & Axel, R. (1999). A spatial map of
olfactory receptor expression in the Drosophila antenna. Cell, 96(5), 725-736.
doi:10.1016/s0092-8674(00)80582-6
Walkowicz, L., Kijak, E., Krzeptowski, W., Górska-Andrzejak, J., Stratoulias, V., Woznicka,
O., . . . Pyza, E. M. (2017). Downregulation of DmMANF in Glial Cells Results in
149

Neurodegeneration and Affects Sleep and Lifespan in Drosophila melanogaster. Front
Neurosci, 11, 610. doi:10.3389/fnins.2017.00610
Wang, A., Huen, S. C., Luan, H. H., Yu, S., Zhang, C., Gallezot, J. D., . . . Medzhitov, R. (2016).
Opposing Effects of Fasting Metabolism on Tissue Tolerance in Bacterial and Viral
Inflammation. Cell, 166(6), 1512-1525.e1512. doi:10.1016/j.cell.2016.07.026
Wang, C., Guo, X., Dou, K., Chen, H., & Xi, R. (2015). Ttk69 acts as a master repressor of
enteroendocrine cell specification in Drosophila intestinal stem cell lineages.
Development, 142(19), 3321-3331. doi:10.1242/dev.123208
Wang, L., Ryoo, H. D., Qi, Y., & Jasper, H. (2015). PERK Limits Drosophila Lifespan by
Promoting Intestinal Stem Cell Proliferation in Response to ER Stress. PLoS Genet,
11(5), e1005220. doi:10.1371/journal.pgen.1005220
Wang, M. C., Bohmann, D., & Jasper, H. (2003). JNK signaling confers tolerance to oxidative
stress and extends lifespan in Drosophila. Dev Cell, 5(5), 811-816. doi:10.1016/s1534-
5807(03)00323-x
Wang, M. C., Bohmann, D., & Jasper, H. (2005). JNK extends life span and limits growth by
antagonizing cellular and organism-wide responses to insulin signaling. Cell, 121(1),
115-125. doi:10.1016/j.cell.2005.02.030
Wang, W., Li, Y., Zhou, L., Yue, H., & Luo, H. (2011). Role of JAK/STAT signaling in
neuroepithelial stem cell maintenance and proliferation in the Drosophila optic lobe.
Biochem Biophys Res Commun, 410(4), 714-720. doi:10.1016/j.bbrc.2011.05.119
Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of 'small-world' networks. Nature,
393(6684), 440-442. doi:10.1038/30918
Weber, B., & Barros, L. F. (2015). The Astrocyte: Powerhouse and Recycling Center. Cold
Spring Harb Perspect Biol, 7(12). doi:10.1101/cshperspect.a020396
Winther, A. M., Jiao, W., Vorontsova, O., Rees, K. A., Koh, T. W., Sopova, E., . . . Shupliakov, O.
(2013). The dynamin-binding domains of Dap160/intersectin affect bulk membrane
retrieval in synapses. J Cell Sci, 126(Pt 4), 1021-1031. doi:10.1242/jcs.118968
Wolpert, L. (1969). Positional information and the spatial pattern of cellular differentiation. J
Theor Biol, 25(1), 1-47. doi:10.1016/s0022-5193(69)80016-0
150

Wong, A. M., Wang, J. W., & Axel, R. (2002). Spatial representation of the glomerular map in
the Drosophila protocerebrum. Cell, 109(2), 229-241. doi:10.1016/s0092-
8674(02)00707-9
Woolworth, J. A., Nallamothu, G., & Hsu, T. (2009). The Drosophila metastasis suppressor gene
Nm23 homolog, awd, regulates epithelial integrity during oogenesis. Mol Cell Biol,
29(17), 4679-4690. doi:10.1128/mcb.00297-09
Wright, V. M., Vogt, K. L., Smythe, E., & Zeidler, M. P. (2011). Differential activities of the
Drosophila JAK/STAT pathway ligands Upd, Upd2 and Upd3. Cell Signal, 23(5), 920-
927. doi:10.1016/j.cellsig.2011.01.020
Wu, B., Li, J., Chou, Y. H., Luginbuhl, D., & Luo, L. (2017). Fibroblast growth factor signaling
instructs ensheathing glia wrapping of Drosophila olfactory glomeruli. Proc Natl Acad Sci
U S A, 114(29), 7505-7512. doi:10.1073/pnas.1706533114
Wu, C., Daniels, R. W., & DiAntonio, A. (2007). DFsn collaborates with Highwire to down-
regulate the Wallenda/DLK kinase and restrain synaptic terminal growth. Neural Dev, 2,
16. doi:10.1186/1749-8104-2-16
Wu, C., Wairkar, Y. P., Collins, C. A., & DiAntonio, A. (2005). Highwire function at the
Drosophila neuromuscular junction: spatial, structural, and temporal requirements. J
Neurosci, 25(42), 9557-9566. doi:10.1523/jneurosci.2532-05.2005
Wu, S. C., Cao, Z. S., Chang, K. M., & Juang, J. L. (2017). Intestinal microbial dysbiosis
aggravates the progression of Alzheimer's disease in Drosophila. Nat Commun, 8(1), 24.
doi:10.1038/s41467-017-00040-6
Xia, L., Jia, S., Huang, S., Wang, H., Zhu, Y., Mu, Y., . . . Chen, D. (2010). The Fused/Smurf
complex controls the fate of Drosophila germline stem cells by generating a gradient
BMP response. Cell, 143(6), 978-990. doi:10.1016/j.cell.2010.11.022
Yaksi, E., & Wilson, R. I. (2010). Electrical coupling between olfactory glomeruli. Neuron, 67(6),
1034-1047. doi:10.1016/j.neuron.2010.08.041
Yasugi, T., Umetsu, D., Murakami, S., Sato, M., & Tabata, T. (2008). Drosophila optic lobe
neuroblasts triggered by a wave of proneural gene expression that is negatively
regulated by JAK/STAT. Development, 135(8), 1471-1480. doi:10.1242/dev.019117
Yeh, P. A., Liu, Y. H., Chu, W. C., Liu, J. Y., & Sun, Y. H. (2018). Glial expression of disease-
associated poly-glutamine proteins impairs the blood-brain barrier in Drosophila. Hum
Mol Genet, 27(14), 2546-2562. doi:10.1093/hmg/ddy160
151

Yin, C., & Xi, R. (2018). A Phyllopod-Mediated Feedback Loop Promotes Intestinal Stem Cell
Enteroendocrine Commitment in Drosophila. Stem Cell Reports, 10(1), 43-57.
doi:10.1016/j.stemcr.2017.11.014
Yoo, H. S., Chung, S. J., Lee, Y. H., Ye, B. S., Sohn, Y. H., & Lee, P. H. (2020). Association
between Olfactory Deficit and Motor and Cognitive Function in Parkinson's Disease. J
Mov Disord. doi:10.14802/jmd.19082
Zeng, X., & Hou, S. X. (2015). Enteroendocrine cells are generated from stem cells through a
distinct progenitor in the adult Drosophila posterior midgut. Development, 142(4), 644-
653. doi:10.1242/dev.113357
Zhai, Z., Boquete, J. P., & Lemaitre, B. (2017). A genetic framework controlling the
differentiation of intestinal stem cells during regeneration in Drosophila. PLoS Genet,
13(6), e1006854. doi:10.1371/journal.pgen.1006854
Zhang, L., Wang, Y., Xiayu, X., Shi, C., Chen, W., Song, N., . . . Qin, C. (2017). Altered Gut
Microbiota in a Mouse Model of Alzheimer's Disease. J Alzheimers Dis, 60(4), 1241-
1257. doi:10.3233/jad-170020
Zhang, X., Huang, W., Shao, Q., Yang, Y., Xu, Z., Chen, J., . . . Ge, X. (2020). Drp1, a potential
therapeutic target for Parkinson's disease, is involved in olfactory bulb pathological
alteration in the Rotenone-induced rat model. Toxicol Lett, 325, 1-13.
doi:10.1016/j.toxlet.2020.02.009
Zhang, Y. E. (2017). Non-Smad Signaling Pathways of the TGF-β Family. Cold Spring Harb
Perspect Biol, 9(2). doi:10.1101/cshperspect.a022129
Zhao, G., Wu, Y., Du, L., Li, W., Xiong, Y., Yao, A., . . . Zhang, Y. Q. (2015). Drosophila S6
Kinase like inhibits neuromuscular junction growth by downregulating the BMP receptor
thickveins. PLoS Genet, 11(3), e1004984. doi:10.1371/journal.pgen.1004984
Zhou, J., Florescu, S., Boettcher, A. L., Luo, L., Dutta, D., Kerr, G., . . . Boutros, M. (2015).
Dpp/Gbb signaling is required for normal intestinal regeneration during infection. Dev
Biol, 399(2), 189-203. doi:10.1016/j.ydbio.2014.12.017
Zou, Y. M., Lu, D., Liu, L. P., Zhang, H. H., & Zhou, Y. Y. (2016). Olfactory dysfunction in
Alzheimer's disease. Neuropsychiatr Dis Treat, 12, 869-875. doi:10.2147/ndt.S104886
Zuchero, J. B., & Barres, B. A. (2015). Glia in mammalian development and disease.
Development, 142(22), 3805-3809. doi:10.1242/dev.129304

Abstract (if available)

Abstract The gastrointestinal (GI) tract is one of the largest immune organs in most metazoans, acting not only as a barrier to segregate inhabited microbiota from the host, but also as a source of immunological cytokines and chemokines to activate immune responses in other tissues, including the brain. Therefore, maintaining GI homeostasis is essential for both digestive health and brain function. ❧ Intestinal stem cells (ISC) reside along the GI tract, regenerating the epithelia. In the Drosophila intestine, injury-induced regeneration involves initial activation of ISC proliferation and subsequent return to quiescence. These two phases of the regenerative response are controlled by differential availability of the bone morphogenetic protein (BMP) type I receptor, Thickveins (Tkv) (Ayyaz, Li, & Jasper, 2015), yet how its expression is dynamically regulated remains unclear. As such, I explored the ISC-specific regulatory mechanisms responsible for Tkv expression, and found that post-translational regulation of Tkv is critical for the dynamic control of BMP responses during a regenerative episode. My results suggest that Tkv turnover is regulated by the E3 ubiquitin ligase Highwire (Hiw) and by high proteasome activity in quiescent ISCs. In response to tissue damage, Tkv is temporarily stabilized due to general downregulation of proteasome activity, and internalized into Rab5-positive endocytic vesicles. This internalization is facilitated by the Drosophila homologue of Nm23 (abnormal wing discs, AWD), which is upregulated in active ISCs by JNK signaling. The AWD-facilitated endocytosis of Tkv is critical for the return of ISCs to quiescence, to prevent epithelial dysplasia, and for host survival during acute intestinal infection. These findings not only contribute to understanding the role of BMP signaling in the regulation of ISC activity during regeneration, but also providemolecular insights underlying tissue homeostasis. ❧ In addition, I used the Drosophila olfactory circuit as an experimental model to investigate cellular mechanisms orchestrating the inter-tissue communication between the gut and the antennal lobe (AL), an important component of the olfactory circuit, and explored how this cross-talk influences infection-induced avoidance behavior, infection tolerance, as well as olfactory decline during aging. My findings suggest that intestinal inflammation reduces olfaction sensitivity and reprograms lipid metabolism in ensheathing glia (EG). Upon acute infection, the gut epithelium secretes Unpaired (Upd) cytokines, leading to the activation of JAK/STAT signaling in ensheathing glia at the AL. This causes glial lipid overload due to elevated expression of the Lipocalin Glia Lazarillo (Glaz) and the Monocarboxylate Transporter (MCT) Outsiders (Out), resulting in transient inhibition of olfaction sensitivity. This gut-glia cross-talk promotes avoidance of enteropathogens and thus increases host resistance to infection. During aging, however, chronic activation of this inflammatory crosstalk between gut and glia not only causes constitutive lipid droplet accumulation, but also enhances lipid peroxidation. This, in turn, promotes the loss of EG at the AL, and impairs olfactory discrimination with age. My findings are an example of how an adaptive mechanism that protects the host by promoting pathogen avoidance can also contribute to the age-related decline of neuronal function when activated constitutively in the aging organism. Futhermore, the study highlights the role of gut-derived inflammatory cytokines in the degeneration of neuronal function, and identifies glial metabolic reprogramming by inflammatory pathways as a mechanism causing lasting changes in neuronal activity.

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Asset Metadata

Creator Cai, Xiaoyu (author)

Core Title Signaling mechanisms governing intestinal regeneration and gut-glia cross-talk in Drosophila

School Leonard Davis School of Gerontology

Degree Doctor of Philosophy

Degree Program Biology of Aging

Degree Conferral Date 2021-08

Publication Date 07/18/2021

Defense Date 06/04/2021

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

Tag aging,intestinal regeneration,intestinal stem cells,JAK/STAT signaling,OAI-PMH Harvest,olfaction sensitivity,olfactory degeneration

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Jasper, Heinrich (committee chair), Brem, Rachel (committee member), Cohen, Pinchas (committee member), Haghighi, Pejmun (committee member), Lithgow, Gordon (committee member)

Creator Email xiaoyu.t.cai@gmail.com,xiaoyuca@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC15602413

Unique identifier UC15602413

Legacy Identifier etd-CaiXiaoyu-9773

Document Type Dissertation

Format application/pdf (imt)

Rights Cai, Xiaoyu

Type texts

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

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