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Identification of therapeutic targets in human cerebral brain organoid models of neurodegeneration

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Identification of therapeutic targets in human cerebral brain organoid models of neurodegeneration

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Identification of Therapeutic Targets in Human Cerebral Brain Organoid Models of
Neurodegeneration

by

Joshua Eugene Berlind

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(DEVELOPMENT, STEM CELLS AND REGENERATIVE MEDICINE)

May 2023

Copyright 2023 Joshua Eugene Berlind
ii

Acknowledgments
I have been extremely fortunate to pursue my PhD among so many wonderful and
passionate individuals. First, I would like to thank my mentor, Dr. Justin Ichida, for his excellent
mentorship, guidance, and support during these past five years. He has always provided an
excellent environment to succeed, giving both freedom and direction when needed. From the first
time we discussed potential projects in the lab, Dr. Ichida has been an inspirational scientist and
leader, and his ability to inspire excitement in others was a big part of my decision to join the lab
initially and is essential for advancing our field. Thank you for helping me to become a more
critical, passionate, and independent scientist. I also thank all current and past Ichida lab members
for their help, advice, and for the shared laughs. I would like to thank my committee members, Dr.
Giorgia Quadrato, Dr. Berislav Zlokovic, Dr. Zhen Zhao, and Dr. Qilong Ying for their support
and guidance over the last several years. Your feedback has been invaluable to improve our
research aims. I’d also like to thank Dr. Jesse Lai, a former postdoc in our lab and co-author on
these studies, for his mentorship and discussions. Working with you on these projects was a true
pleasure and helped inspire me to be a better scientist. I’d also like to thank our collaborators, the
optical imaging core, and the flow cytometry core for their help.
I am incredibly lucky to share my triumphs and hardships with a wonderful group of friends
and family and I thank them for their support during my PhD and in life. I especially appreciated
this during the past year, in which your love and friendship helped guide me through an unexpected
medical emergency. Importantly, I would like to thank my in-laws, Rada, Mehdi, and Raayan for
their immense support and encouragement during this journey. I would like to thank my parents,
René and Mark, and my sister, Amanda for all of their love and support. They gave me every
opportunity to follow and be successful in whatever path I chose and have always encouraged me
iii

and shown excitement in my work. Lastly, I would like to thank my wife, Neaka. Since we met
over ten years ago, you have been my partner in all that I do and my best friend. You have always
listened, read (and re-read) everything I pushed in front of you, and been there to guide me through
difficult times. Your unwavering love and support have carried me through this journey, and I
cannot imagine reaching this stage without you. Thank you for everything that you are and all that
you do.

iv

Table of Contents
Acknowledgements.……………………………………………………………………………….ii
List of Figures……………………………………………………………………………………..v
Abstract…………………………………………………………………………………………..vii
Chapter 1: Introduction……………………………………………………………………………1
1.1 Traumatic brain injury and dementia………………………………………………….1
1.2 Pathophysiology of frontotemporal dementia…………………………………………3
1.3 Organoids as a model for neurologic disease.………………………………………...6
1.4 Thesis Goals………………………………………………………………………….11

Chapter 2: KCNJ2 inhibition mitigates mechanical injury in human brain organoids….……….13
2.1 Abstract………………………………………………………………………………13
2.2 Introduction…………………………………………………………………………..14
2.3 Results………………………………………………………………………………..16
2.4 Discussion……………………………………………………………………………26
2.5 Figures………………………………………………………………………………..33

Chapter 3: KCTD20 inhibition mitigates excitotoxicity in human frontotemporal dementia
brain organoids…………………………………………………………………………………...51
3.1 Abstract………………………………………………………………………………51
3.2 Introduction…………………………………………………………………………..51
3.3 Results………………………………………………………………………………..54
3.4 Discussion……………………………………………………………………………62
3.5 Figures………………………………………………………………………………..68

Chapter 4: ELAVL4, splicing, and glutamatergic dysfunction precede neuron loss
in MAPT mutation cerebral organoids …...……………………..………………………………89
4.1 Abstract………………………………………………………………………………89
4.2 Introduction…………………………………………………………………………..90
4.3 Results………………………………………………………………………………..92
4.4 Discussion…………………………………………………………………………..103
4.5 Figures………………………………………………………………………………109

Chapter 5: Conclusions…………………………………………………………………………134
References………………………………………………………………………………………139
Appendices……………………………………………………………………………………...169
Appendix A: Methods and Materials…………………………………………………...169
A.1 Methods…………………………………………………………………………..169
A.2 Experimental Models…………………………………………………………….176
A.3 Statistical Analysis……………………………………………………………….177
v

List of Figures
Figure 1.1 Pathophysiology of TBI……………………………………………………………….2
Figure 1.2 Genetic makeup of FTD……………………………………………………………….4
Figure 1.3 Disease-causing mutations in MAPT…………………………………………………..5
Figure 1.4 Generation of human cortical organoids………………………………………………7
Figure 2.1 A novel iPSC-organoid mechanical injury model exhibits TBI-related pathology….33
Figure 2.2 TDP-43 loss-of-function drives neurodegeneration in deep-layer excitatory
neurons…………………………………………………………………………………………...34
Figure 2.3 A CRISPRi screen identifies KCNJ2 as a modifier of mechanical injury in vitro…...36
Figure 2.4 Knockdown of Kcnj2 reduces TDP-43 pathology, cell death, and motor deficits
following controlled cortical impact in mice…………………………………………………….38
Figure 2.5 KCNJ2 inhibition suppresses TDP-43 pathology in injured ALS/FTD organoids…..40
Figure S2.1 Generation of iPSC cortical organoids and HIFU characterization………………...42
Figure S2.2 Single cell RNA sequencing analysis of cell-specific responses to HIFU………….44
Figure S2.3 Validation of top protective genes from CRISPRi screen…………………………..46
Figure S2.4 KCNJ2 sgRNAs are enriched in HIFU CRISPRi screen…………………………...47
Figure S2.5 Intracellular calcium promotes TDP-43 phosphorylation…………………………..48
Figure S2.6 Astrogliosis and TDP-43 pathology following in vivo CCI………………………...49
Figure S2.7 C9ORF72 organoids showed reduced neurite outgrowth following mechanical
injury……………………………………………………………………………………………..50
Figure 3.1 Glutamate induces oligomeric tau formation and neurodegeneration………………..68
Figure 3.2 A CRISPRi screen identifies KCTD20 as a modifier of glutamate excitotoxicity…..69
Figure 3.3 Tau-V337M organoids display enhanced tau pathology and neurodegeneration
following glutamate……………………………………………………………………………...71
Figure 3.4 Improved neuron survival following KCTD20 knockdown depends on exocytosis...73
Figure 3.5 Protective effects of KCTD20 knockdown are mediated by lysosomal exocytosis….75
Figure 3.6 TFEB activity is modulated by KCTD20 inhibition...…………………………….....77
Figure 3.7 Kctd20 knockdown reduces tau pathology and improves neuron survival
in vivo using MAPT transgenic mice…………………………………………………………….79
Figure S3.1 Additional gene targets from CRISPRi screen……………………………………...81
Figure S3.2 KCTD20 inhibition inhibits AKT/mTOR activity………………………………….82
Figure S3.3 Survival of C9ORF72 ALS/FTD neurons is improved with KCTD20 ASO……….83
Figure S3.4 Proteostasis stressors induce tau oligomerization and neurodegeneration………….84
Figure S3.5 Organoid cell identity following single cell RNAseq………………………………85
Figure S3.6 Effect of exocytosis pathway inhibition on neuron survival………………………..86
Figure S3.7 Mouse pups injected ICV with glutamate recapitulate changes in tau and TFEB,
which is mitigated by Kctd20 ASO……………………………………………………………...87
Figure S3.8 Tau pathology and neuron loss in adult transgenic MAPT P301S mice……………88
Figure 4.1 Cerebral organoids exhibit similar differentiation patterns as developing human
brains……………………………………………………………………………………………109
Figure 4.2 Tau-V337M organoids exhibit neuronal loss, early autophagy disruption,
and progressive tau accumulation………………………………………………………………111
Figure 4.3 Tau-V337M organoids reveal loss of deep- and upper-layer glutamatergic
neurons………………………………………………………………………………………….113
Figure 4.4 Tau-V337M organoids exhibit early neuronal maturation and upregulation of
synaptic signaling pathways……………………………………………………………………115
vi

Figure 4.5 Accelerated glutamatergic gene and ELAVL4 expression aberrant splicing in
V337M neurons………………………………………………………………………………...117
Figure 4.6 ELAVL4 binds MAPT RNA and co-localizes with cytosolic stress granules in
tau-V337M neurons…………………………………………………………………………….119
Figure 4.7 Tau-V337M susceptibility to glutamate excitotoxicity is reversed by antagonists
of excitatory receptors and PIKFYVE inhibition………………………………………………120
Figure S4.1 Cerebral organoid differentiation recapitulates key features of human brain
patterning……………………………………………………………………………………….122
Figure S4.2 Tau-V337M organoids exhibit neuron-specific loss over time……………………124
Figure S4.3 Characterization of autophagy markers and MAPT expression in organoids……..125
Figure S4.4 Changes in enriched gene expression pathways in tau-V337M organoids………..127
Figure S4.5 Summary of differential gene expression in tau-V337M organoids………………129
Figure S4.6 Ordering of organoid cell types and enrichment of tau-V337M and V337V
gene expression modules in pseudotime………………………………………………………..130
Figure S4.7 Susceptibility to glutamate excitotoxicity in tau-V337M organoids is
reversed by apilimod……………………………………………………………………………132

vii

Abstract
Dementia-related diseases have a devastating personal and societal impact and present a
significant challenge to the biomedical field. This is due in part to a diverse genetic etiology giving
rise to diseases like amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD),
where up to 70% (FTD) and 90% (ALS) of cases are sporadic. Additionally, environmental
impacts which contribute significantly to the risk of developing dementia such as traumatic brain
injury (TBI) have highly variable biophysical forces and complex pathophysiology which
complicate efforts to advance new therapies to humans. The ability to study these processes,
especially the interplay between environmental and genetic contributions to neurodegeneration,
has largely eluded researchers. Recently, the use of patterned brain organoids has shown promise
to bridge the translational gap between traditional in vitro and in vivo models while preserving
human biology and the capacity for genetic manipulation and large-scale screening approaches. In
this thesis, I present our efforts to develop organoid models of TBI and glutamate excitotoxicity
with overlap between genetic models of ALS and FTD, respectively. In these models, we
demonstrate key neurodegenerative phenotypes and disease-specific susceptibilities that underlie
known pathogenic mechanisms and identify therapeutic targets to mitigate these effects. Together,
the work presented here has contributed to the advancement of disease modeling and improved
understanding of pathophysiology while identifying promising genetic targets in multiple
neurodegenerative diseases.
1

Chapter 1: Introduction
1.1 Traumatic brain injury and dementia
Traumatic brain injury (TBI), defined as a forceful blow or jolt to the head, is a major global
cause of disability and death, with nearly 70 million estimated annual cases worldwide
1
. Elderly
citizens, athletes, and military personnel are at elevated risk, with the reported incidence of TBI in
individuals aged 65 and older increasing by 50% in recent years
2,3
. Out of all TBI patients, 10-
15% are estimated to sustain a severe TBI, and of these nearly 60% have unfavorable outcomes
including death and life-long disability
2,4
. Numerous biomarkers for TBI from the blood or
cerebrospinal fluid (CSF) have been identified for diagnostic and predictive purposes, including
the astrocytic proteins S100B and glial fibrillary acidic protein (GFAP), inflammatory cytokines,
and neuronal proteins including ubiquitin C-terminal hydrolase-L1 (UCH-L1), neurofilament
light- and heavy-chains (NfL and NfH), and tau
5,6
. Of these, phosphorylated tau secreted into the
CSF at acute timepoints strongly correlates with injury severity and long-term outcomes
3,7
.
The injury response to TBI is divided into distinct primary and secondary phases. Primary
injury refers to the external physical forces sustained during injury, including skull fracture,
hematoma, and brain contusions; whereas secondary injury describes the cellular and molecular
changes occurring in the hours-weeks following injury
2,8
. These secondary responses include
excitotoxic effects from excess glutamate release, imbalance of ions including Ca
2+
, oxidative
stress, mitochondrial damage, inflammation from microglia and astrocyte activation, blood-brain
barrier (BBB) leakage, and edema
9
(Fig. 1.1). Despite advances in the understanding of TBI
pathophysiology, current pharmacologic and surgical interventions fail to significantly improve
outcomes
4
.
2

Figure 1.1 Pathophysiology of TBI
Simplified diagram of molecular changes following TBI. Excess glutamate due to reduced astrocytic uptake
promotes excitotoxic effects, in part through NMDA channels, including increased cytosolic and
mitochondrial calcium influx. This causes reduced ATP production and increased reactive oxygen species,
contributing to cellular energy crisis. Coupled with calcium-activated caspases, axon damage, and defective
axonal transport, these changes promote neuron death. Astrocytes and microglia become reactive following
TBI, secreting inflammatory cytokines and chemokines which recruit macrophages and other peripheral
immune cells. Coupled with damage to the blood-brain barrier, this promotes bleeding, edema, and
increased cranial pressure. (Modified from Rosenfeld et al., 2012)

TBI is the strongest environmental risk factor for dementia, and is highly correlated with
neurodegenerative diseases including chronic traumatic encephalopathy (CTE) and amyotrophic
lateral sclerosis (ALS)
1,10–14
. A single moderate-severe TBI is sufficient to increase the risk of
dementia by up to 4-fold
11,15,16
. CTE in particular has been linked to TBI in athletes, with post-
mortem sampling revealing a CTE diagnosis in 99% of professional football players
17
. Although
CTE is neuropathologically distinct from ALS and other dementias and is clinically defined by
deposition of hyperphosphorylated tau, several studies have identified widespread cytosolic
inclusions of TAR DNA-binding protein of 43 kd (TDP-43) in up to 85% of CTE cases across all
layers of the cortex
10,12,18,19
. TDP-43 pathology has also been identified following single acute TBI
3

in human patients
20,21
. TDP-43, which functions as a regulator of RNA splicing and transport in
the nucleus, is the major pathologic protein in up to 97% of ALS patients
22
. This suggests a
potentially causative link to explain the reported four- to six-fold higher neurodegenerative
mortality from ALS in athletes with a history of brain injury
11,13
.

1.2 Pathophysiology of frontotemporal dementia
Frontal temporal dementia (FTD), a clinical manifestation of frontotemporal lobar
degeneration (FTLD), is one of the leading causes of early-onset dementia and is characterized by
progressive atrophy of the frontal and temporal lobes and deficits or changes in behavior, memory,
and executive function
23,24
. FTD represents a group of neurodegenerative disorders which present
as two primary associated syndromes: behavioral variant FTD (bvFTD) which is most common
and presents with behavioral changes and executive dysfunction, and primary progressive aphasia
(PPA) with language decline and speech difficulty
25
. Although there is heterogeneity between
patients, bvFTD shows preferential atrophy of the medial frontal and anterior temporal lobes,
whereas cortical atrophy in PPA is typically asymmetric across the anterior temporal lobes
26
. The
average age of onset for FTD is 45-64, with a median survival time of 6-11 years
23
. Approximately
30% of patients have a family history of FTD, with inherited mutations in microtubule-associated
protein tau (MAPT), progranulin (GRN), and chromosome 9 open reading frame 72 (C9orf72) each
responsible for 5-10% of total FTD cases (Fig. 1.2)
27
. This differentiates FTD from other
neurodegenerative diseases such as Alzheimer’s disease and ALS, in which 1% and 10% of cases,
respectively, are attributed to inherited mutations
22,25
. FTD lies on a continuous disease spectrum
with ALS, with approximately 20% of ALS patients meeting the diagnostic criteria for FTD and
vice versa
28
. To date, there is no cure for FTD, and approved treatments are primarily limited to
4

the management of neuropsychiatric symptoms
25
.

Figure 1.2 Genetic makeup of FTD
Genetic landscape of frontotemporal dementia. (i) Approximately 70% of cases are sporadic, 30% familial.
(ii) Within sporadic and familial cases, tau and TDP-43 are the major pathologic protein in the majority of
cases, each representing near 45% of total cases. (iii) Representative proportions of clinical presentations
(orange) or causative genetic mutations (green) associated with each pathologic characterization. CBD=
corticobasal degeneration; PSP= progressive supranuclear palsy; GGT= globular glial tauopathy; aFTLD-
U= atypical frontotemporal lobar degeneration with ubiquitin inclusions. (Modified from Greaves and
Rohrer, 2019).

Neuropathologic characterization of FTD is based on the major aggregated protein species, of
which tau (FTD-tau) and TDP-43 (FTD-TDP) comprise approximately 90% of all cases
23,25
. Tau
mutations were first causally linked to FTD in 1998, and FTD-tau is estimated to comprise 45%
of FTD sporadic and familial cases
23,29,30
. Among the clinical presentations of FTD, tau pathology
is most commonly linked with bvFTD
24
. Tau protein is encoded by the MAPT gene and plays
important roles in axonal and microtubule stability and synaptic plasticity
31
. Mature tau is found
in six isoforms in approximately equimolar ratios in the adult brain, based on the inclusion or
exclusion of repeated N-terminal regions (exons 2 and 3, 0-2N) and microtubule binding domains
(exon 10, 3R or 4R) through alternative splicing
31
. Over 50 disease-causing mutations have been
reported in MAPT, primarily affecting the microtubule binding domains with many (e.g. P301L)
in exon 10 and therefore only present in 4R tau and others (e.g. V337M) in exon 12 which affect
both 3R and 4R tau isoforms (Fig. 1.3)
25,31
.
5

Figure 1.3 Disease-causing mutations in MAPT
Schematic of MAPT gene with exonic FTD-causing mutations shown. The most common clinical and cited
variants are in bold. Inclusion of zero, one, or both exon 2 and 3 via alternative splicing result in 0N, 1N,
and 2N tau isoforms. Exclusion or inclusion of exon 10 results in 3R or 4R isoforms, respectively. Blue
domains form the N-terminal repeat region. Yellow represents the proline-rich region. Purple forms the
microtubule-binding repeat domain. Splicing patterns and intronic mutations not shown. (Modified from
Ghetti et al., 2014)

Specifically in FTD patients with the V337M mutation in MAPT, magnetic resonance imaging
studies have shown preferential atrophy of the lateral temporal lobes, corresponding with
pronounced bvFTD symptoms
32,33
. As with many mutations in the microtubule binding domains
of MAPT, V337M decreases the binding affinity of tau to microtubules, making tau a more
favorable substrate for phosphorylation and resulting in abundant neuronal deposits of
hyperphosphorylated 3R and 4R tau filaments (paired helical filaments, PHFs)
34–36
. The V337M
mutation also enhances formation of tau oligomers, soluble multimeric intermediate structures
preceding tau filaments with demonstrated neurotoxicity in vitro and in vivo
37–43
. Additionally,
tau-V337M has been shown to disrupt neuronal activity and promote hyperexcitability, a
physiologic hallmark of FTD and other neurodegenerative diseases including ALS, Alzheimer’s
disease, and TBI
44–47
.
Defects in protein clearance and degradation pathways, including the autophagy-lysosomal
and secretory pathways, are among the major mechanisms that contribute to neurodegeneration in
6

FTD-tau and other dementias
22,48–52
. Mutations in a number of genes which regulate these
processes have been linked to FTD, including TBK1, SQSTM1, CHMP2B, and UBQLN2
49,53
.
Further, abnormal staining for LC3, an autophagosome marker, and the lysosomal marker LAMP1,
has been reported in FTD-tau brain sections
54,55
. Direct evidence demonstrates that autophagic and
lysosomal processes are impaired in models of tauopathy, including in MAPT V337M neurons,
and that stimulation of these pathways is therapeutic in part by reducing intracellular tau
pathology
47,56,57
. Interestingly, overexpression of mutant tau does not stimulate activation of the
unfolded protein response to degrade proteins, suggesting that extracellular secretion of aggregated
tau may be the more effective therapeutic method for protein clearance
58,59
. Tau secretion mediated
by multiple classes of exosomes has been demonstrated, where it can subsequently be cleared from
the CSF into the glymphatic system via aquaporin-4 channels
60–62
.

1.3 Organoids as a model for neurologic disease
Embryonic stem cells (ESCs) were first used in 3-dimensional self-organizing models in
2008, generating spontaneous differentiations into neural tissues
63
. This paved the way for
protocols using ESCs, and later induced pluripotent stem cells (iPSCs), to generate dorsally
specified cerebral brain organoids
64,65
. Addition of refined medium compositions and
combinations of small molecules and growth factors enabled more defined and reproducible
organoid cultures enriched for specific brain regions, including the cortex
66–69
. In a process
mimicking human developmental cues, cortical organoid induction into the ectodermal lineage is
achieved through dual-SMAD inhibition using the molecules SB-431542 and Dorsomorphin. The
emerging population of radial glia is expanded via epidermal growth factor (EGF) and fibroblast
growth factor 2 (FGF2) supplementation, and differentiation and maturation of glutamatergic
7

neurons is promoted by treatment with neurotrophin-3 (NT-3) and brain-derived neurotrophic
factor (BDNF). This patterning protocol yields a heterogeneous population of radial glia, deep-
and superficial-layer neurons, and astrocytes with extended culture (Fig. 1.4)
66
. Cortical organoids
grown from this protocol yield functional, primarily glutamatergic neurons and reproducible cell
populations which resemble up to early postnatal human cortical stages based on transcriptional
and epigenetic signatures
66–68
.

Figure 1.4 Generation of human cortical organoids
Schematic of cortical organoid differentiation protocol. iPSCs are seeded in 96-well U-bottom low-
attachment plates prior to induction. Radial glia develop and give rise to glutamatergic neurons, and later
astrocytes. (Modified from Paşca et al., 2015).

Human iPSC-derived organoids have several advantages over mouse models, including the
presence of human-specific cell types and developmental regions
70
. Organoids are also more
amenable to genetic manipulation and larger sample sizes to expedite research studies.
Additionally, their multicellular composition and 3-dimensional cytoarchitecture may provide
advantages over monolayer culture models while preserving the ability to leverage large scale
screening approaches
71
. To date, organoids representing various brain regions have been used to
model numerous inherited and environmental disorders. Among the earliest reported phenotypes
to be modelled in brain organoids was microcephaly, which showed that inherited mutations led
to smaller brain organoid sizes in vitro
64
. When maternal Zika virus infection was reported to be
8

linked with fetal microcephaly, researchers were able to recapitulate this phenotype in infected
brain organoids, demonstrating a causal link
72,73
. Brain organoids have also been utilized to study
a number of mono- and polygenic neurodevelopmental disorders, including autism spectrum
disorders (ASD), fragile X syndrome, and schizophrenia
74–78
. Connected organoid assembloids, or
fusion systems, such as cortico-thalamic and cortico-spinal-muscle have also been implemented
to improve organoid physiology and model long range connections between brain regions as well
as connectopathies
79–81
. To enhance drug target discovery, genetic screening using CRISPR-based
approaches has been performed in organoids at a small scale (less than 200 genes), although
genome-wide screening and high-throughput compound screens have yet to be reported
82–84
.
Importantly, although organoid cultures do not fully recapitulate the maturation or physiology of
adult human tissue, organoids representing different brain regions have been successfully utilized
to model age-related neurodegenerative diseases including Alzheimer’s disease, ALS/FTD,
Parkinson’s disease, and Huntington’s disease
47,85–89
.
For studies on TBI, animal models have dominated the field. Rodents are the most
common, although larger mammals (cat, sheep, pig) and primates are studied, and several types of
injury have been developed that relate to different clinical manifestations. Once such model is
controlled cortical impact (CCI), in which a physical impact of defined pressure is delivered to the
brain
90
. CCI is used to induce mild to severe focal brain injury with direct brain deformation and
hemorrhaging, which mimics ballistic, concussive, and sports-related injuries
91
. Rodent CCI has
been reported to induce motor deficits and pathology similar to what’s observed in human TBI,
including aggregation and phosphorylation of tau and TDP-43, astrogliosis, and
neurodegeneration
92–97
. However, there are key differences between rodent and human injury in
this context, including noted differences in the structure and function of tau and the downstream
9

splicing targets of TDP-43
98–100
. Other physical injury models, such as fluid percussive injury (FPI)
or weight drop injury (WDI) model similar biophysical properties but have more variable
experimental parameters
91
. Additional methods, such as diffuse shock wave injury, model
explosive-related injuries as seen in soldiers, although these require large, highly-specialized
equipment not readily available to many academic institutions
101,102
. Several in vitro systems have
been developed, including mechanical deformation of neurons and axonal stretching or
shearing
103–105
. Although useful for modeling some aspects of TBI such as ion influx and axonal
injury, these methods do not recapitulate the physical forces experienced in TBI and lack multi-
cellular composition and cytoarchitectural niches found in three dimensional tissue
106
. To address
these shortcomings and bridge the gap between traditional in vitro and in vivo models, there has
been a noted need for organoid models of TBI
106
. Since 2022, two publications have reported the
use of blast injury on brain organoids, where ultrasound or blast forces are shown to reduce
neuronal firing, upregulate several injury markers (including UCHL1, S100β, Nf-H), and promote
cell death
107,108
. Although these findings help to validate the use of brain organoids to model TBI,
to date they lack mechanistic details and have not been utilized to uncover novel therapeutic targets
or incorporate genetic risk factors.
The study of FTD-tau in non-transgenic animals is made difficult due to differences
between human and murine tau. One key difference is that adult mice almost exclusively express
4R tau, whereas adult human neurons contain a mix of 3R and 4R
31,109,110
. Another difference is
an expanded N-terminal domain in human tau protein which is thought to contribute to a
pathological ‘paperclip’ conformation and participate in unique protein-protein interactions, which
is not found in mice
98,111
. Because of these differences, human tau dynamics are best studied using
human transgenic animal models or human iPSC-derived cell culture systems. Numerous
10

transgenic mouse strains have been characterized, most notably the MAPT P301S and P301L
strains
112
. Both models display characteristic tau aggregation, motor and cognitive deficits, and
neurodegeneration, with enhanced pathology in P301S strains
113–116
. However, to preserve human
physiology and maintain the capacity for compound and genetic screening, iPSC models have been
heavily utilized in recent years. To this end, an extensive cell bank of iPSCs from tauopathy
patients, including multiple MAPT V337M patients, has been established
117
. iPSC-derived V337M
neurons recapitulate major FTD disease phenotypes, including increased tau phosphorylation and
excitability
44,118
. One caveat to this approach is that iPSC-derived neurons are developmentally
immature and mainly express 3R tau unless cultured for extended time periods (over a year for
glutamatergic neurons), limiting the ability to study the large number of MAPT mutations found
in exon 10 (Fig. 1.3)
112,119
. However, new findings using patient-derived organoids, which display
improved maturation and physiology over monolayer cultures, show that neurons express both 3R
and 4R tau, expanding the ability to study different familial mutations
47,120
. Organoids also provide
the ability to study mixed cultures to determine the effects of mutant tau on other cell populations,
demonstrated in a 2022 report showing that cholesterol homeostasis is impaired in astrocytes from
patient-derived organoids
121
.
Despite the demonstrated utility of brain organoids as models of human development and
disease, there are several noted limitations in their use. Organoid cultures are subject to increased
cellular stress relative to in vivo cells, marked by ectopic activation of metabolic and ER stress
pathways, which impairs the specificity of developing cell types
122
. Cortical organoids also lack
important cell types and structures which play important roles in physiology and disease, including
microglia and vasculature. Additionally, compared to adult tissue brain organoids are still
immature in their neuronal activity, network regulation, and cell maturation, although the noted
11

presence of dendritic spines and transcriptional developmental milestones with extended culture
represents an upgrade over monolayer models
68,69,123
. These deficiencies are mitigated in part by
organoid engraftment in vivo into mouse brains, which has been shown to reduce cell stress and
improve cell-type specification and maturation
122,124
.

1.4 Thesis Goals
In this thesis, I aim to identify neuroprotective targets in environmental (TBI) and genetic
(FTD) models of neurodegeneration. When I joined Justin’s lab in 2018, I began working with
Jesse Lai to develop and characterize a new model of organoid TBI, using focused ultrasound
waves adapted with the help of Russell Jacobs and Naomi Sta. Maria to inflict blast-like injury.
We found that organoid TBI recapitulated several key injury markers found in in vivo TBI models
and human TBI and identified selectively vulnerable neuron populations which may underlie the
elevated risk of neurodegenerative disease. We then performed a genome-wide CRISPR
interference screen to identify genetic targets whose inhibition was neuroprotective with injury.
We successfully identified that knockdown of KCNJ2 is neuroprotective and were able to validate
these findings using established in vivo TBI models and in ALS patient-derived organoids, which
display enhanced pathology.
Early on in this work, I became interested in glutamate-driven excitotoxicity as a shared
mechanism of neurodegeneration between TBI and multiple neurodegenerative diseases, including
FTD. In parallel with the TBI study, we developed an organoid model of excitotoxicity to study
this further, with the goal of identifying therapeutic targets that may be broadly efficacious across
multiple diseases. We found that excess glutamate induced neurodegeneration and tau pathology,
and extended the work to include FTD patient-derived organoids, where we found that these
12

phenotypes are exacerbated. This model was also utilized by the Tau Consortium, a collaborative
group of investigators including Sally Temple and Alison Goate, to characterize MAPT V337M
patient organoids and identify glutamate signaling as a key pathogenic mechanism in FTD. We
again performed a genetic screen to identify protective targets in this model and found that
inhibition of KCTD20 improved neuron survival and tau pathology in wild type and FTD
organoids, as well as in vivo using MAPT transgenic mice. We show that this mechanism is
dependent on lysosomal exocytosis, which may help to clear toxic tau species from neurons.
In summary, with great help and support by my mentor, Justin, and my primary
collaborator and co-author, Jesse, we have identified genetic targets to mitigate convergent
environmental and genetic organoid models of neurodegeneration. These findings highlight
important aspects of disease pathophysiology and provide potential therapeutics to improve neuron
survival and function in diverse models.

13

Chapter 2: KCNJ2 inhibition mitigates mechanical injury in
human brain organoids
2.1 Abstract
Traumatic brain injury (TBI) strongly correlates with neurodegenerative disease. However,
it remains unclear which neurodegenerative mechanisms are intrinsic to the brain itself and which
strategies most potently mitigate these processes, particularly in individuals genetically
predisposed to neurodegeneration. Here, we developed a high-intensity ultrasound platform to
precisely inflict mechanical injury to iPSC-derived cortical organoids. Mechanical injury in
organoids elicits several classic hallmarks of TBI including neurodegeneration, tau
phosphorylation, and TDP-43 phosphorylation and nuclear egress. We found that deep layer
excitatory neurons were particularly vulnerable to mechanical injury, TDP-43 proteinopathy and
loss-of-function drove neurodegeneration, and organoids derived from C9ORF72 amyotrophic
lateral sclerosis/frontotemporal dementia (ALS/FTD) patients displayed exacerbated TDP-43
dysfunction upon injury. Using genome-wide CRISPR interference screening, we identified a
mechanosensory channel, KCNJ2, whose inhibition potently mitigated neurodegenerative
processes in vitro and in vivo, including in C9ORF72 ALS/FTD organoids. Thus, we find that
targeting KCNJ2 may limit acute neurodegeneration after brain injury and we present a scalable
and genetically-flexible cerebral organoid model that may enable identification of additional
modifiers downstream of mechanical stress.

14

Graphical Abstract

2.2 Introduction
Traumatic brain injury (TBI) is the leading environmental risk factor for neurodegenerative
disease, and is estimated to occur in over 60 million cases per year worldwide.
1
Recent studies
have linked TBI to pathological accumulation of the neurotoxic proteins tau, TDP-43 and amyloid-
beta, leading to progressive neurodegenerative diseases including chronic traumatic
encephalopathy (CTE)
10,18
, amyotrophic lateral sclerosis (ALS)
11–14
, Alzheimer’s disease
11,15,125

and other dementias.
126,127
A single moderate-severe TBI has been reported to increase the risk of
15

developing dementia by 4-fold.
15,16
Notably, current surgical and pharmacological interventions
largely fail to mitigate the consequences of TBI.
9

TBI is a complex insult that involves damage not only to the brain itself, but also to the
blood-brain-barrier, which allows blood-derived cells and immune factors to enter the central
nervous system (CNS).
9
Although current TBI models, predominantly rodent-focused, have been
instrumental in gaining early insights into neurodegenerative mechanisms, efforts to develop
effective human-relevant therapeutic strategies have been limited by several unresolved issues that
are difficult to address.
4
These key issues include the following: 1) it remains unclear which
degenerative mechanisms are brain-intrinsic and which are secondary insults from surrounding
tissues, 2) it is unclear which mechanisms drive the degeneration of human neurons when they are
mechanically injured in a three-dimensional context, 3) the basis of differences in injury
susceptibility between different neuronal subtypes remains unknown, and 4) there are no means to
perform large-scale screens to identify the most potent approaches for mitigating TBI, especially
in individuals harboring genetic risk factors for neurodegeneration.
To address these key limitations in the field, we developed a high-intensity focused
ultrasound (HIFU) platform with which we can precisely deliver severe (e.g. blast overpressure
>0.6 MPa) primary brain injuries to human induced pluripotent stem cell (iPSC)-cortical brain
organoids.
66,128,129
Recent studies have taken a similar approach, using ultrasound to mimic blast
injury in 3D neural tissues.
108,130
While these studies characterize biomarkers and
electrophysiological changes after in vitro blast injury and demonstrate the potential of this
approach, to date they do not address underlying mechanistic details or suggest potential
therapeutic approaches. Here, this defined cellular model allowed us to dissect discrete
mechanisms of human-specific TBI pathophysiology that have thus far eluded the field, namely
16

neuron-intrinsic mechanisms of injury within three-dimensional brain tissue. While this model is
not an all-encompassing model of TBI, we find that organoids mechanically injured with HIFU
recapitulate key pathological changes observed in TBI, including neurodegeneration, tau
phosphorylation, and TDP-43 proteinopathy. Although TBI is often associated with tau
dysfunction, we unexpectedly observe that TDP-43 proteinopathy and loss-of-function drive
neurodegeneration in early stages post-injury. Interestingly, deep layer excitatory neurons are more
vulnerable to injury-induced TDP-43 dysfunction than upper layer cortical neurons, and organoids
generated from C9ORF72 ALS/FTD patients displayed exacerbated TDP-43 dysfunction post-
injury compared to healthy control organoids. Using genome-wide CRISPR interference
screening, we identify a mechanosensory channel, KCNJ2, whose inhibition potently mitigates
injury-induced neurodegenerative processes in healthy and C9ORF72 ALS/FTD patient
organoids, as well as in a murine model of controlled cortical impact (CCI). These results highlight
the importance of TDP-43 dysfunction acutely after mechanical injury, uncover key differences in
injury-susceptibility between neuronal subtypes, establish an approach for monitoring injury
responses in different human genetic backgrounds, and suggest that inhibiting KCNJ2 may
mitigate early neurodegeneration after brain injury.

2.3 Results
iPSC organoid injury induces TBI-related clinical and post-mortem biomarkers
We generated human cortical organoids from iPSCs derived from healthy individuals as
previously described (Figure S2.1A).
66
By day 45 of culture, these organoids exhibited neuronal
MAP2 expression and possessed both deep and upper layer cortical neurons as determined by
immunocytochemistry using CTIP2 and SATB2 antibodies (Figures S2.1B and S2.1C). Astrocytes
were present in extended cultures of 100 days (Figure S2.1D). Consistent with previous studies,
17

these organoids did not display spatial separation of deep and upper layer cortical neurons.
70,122

Cortical organoids generated in this manner have been shown to be electrically active.
68
We next
adapted a previously-described custom-built stereotaxic high-intensity focused ultrasound (HIFU)
to inflict mechanical injury and characterized the exerted pressure (Figures S2.1E and S2.1F).
128

All organoids used in this study were cultured for 2 months prior to injury and injured at 0.6 MPa,
unless otherwise stated.
To monitor neurodegeneration over time, we infected organoids with a SYN1::eGFP
lentiviral reporter to label excitatory neurons on the organoid surface, immobilized them using
Matrigel, performed HIFU, and imaged the site of injury over the course of 7 days (Figure 2.1A).
This approach enabled longitudinal tracking of individual neurons on the organoid surface and
reduced confounding factors such as neurons generated after injury and any variability in neuron
numbers between organoids as we have previously described.
47
We observed pressure-dependent
neurodegeneration over this time course as shown by single neuron survival tracking, in addition
to a complementary loss of neurofilament light chain (Nf-L) and β3 tubulin (Figures 2.1B-2.1F) at
cross-sectional timepoints by immunofluorescence staining and western blot analysis. Using this
model, we observed highly reproducible neurodegeneration after injury across 2 differentiations
of both male and female iPSC lines (Figure S2.1G).
To determine if our mechanical injury model mimics processes known to occur in humans
after TBI, we assessed well-characterized TBI biomarkers. Patients display elevated
phosphorylated tau (p-tau, Thr231) levels in serum within 24 hours post-TBI.
3
ELISA
measurements showed that supernatant collected from injured organoids contained pressure- and
time-dependent increases in the ratio of p-tau to total tau (Figures 2.1G and 2.1H). Similar to post-
mortem TBI patient samples, we observed a nonsignificant trend towards astrogliosis in day 100
18

organoids 7 days following injury (Figures S2.1H and S2.1I).
131
Bulk RNA-sequencing analyses
24 hours post-injury showed an enrichment of transcriptional programs that recapitulated changes
found in several animal models of TBI, including the unfolded protein response (Figure 2.1I). This
was despite marked differences between established in vivo models, which highlights the overall
heterogeneity between variable types of traumatic injury.
132–134
The increased influx of Ca
2+
in
neurons is thought to be a major contributor of mitochondrial dysfunction and subsequent
pathology following TBI.
135,136
Live imaging before and after injury using Fluo-4-AM dye to label
intracellular Ca
2+
showed that ultrasound injury to organoids induced an influx of neuronal
Ca
2+
(Figure S2.1J).
Lastly, human and pre-clinical animal TBI models have shown that both single and repeat
blast injury or severe TBI is sufficient to induce TDP-43 pathology.
10,12,20,21,96,97,137,138
Moreover,
TBI is a known risk factor for ALS.
11,13
We found a striking accumulation of phosphorylated TDP-
43 in the cytoplasm of neurons at 7 days post-injury (7 dpi) (Figures 2.1J and 2.1K). Since TDP-
43 mis-localization has been previously linked to dysregulated nucleocytoplasmic transport, we
investigated the integrity of nuclear pore complexes.
139,140
We observed a decrease in nuclear pore
expression by RNAseq and a corresponding loss of the NUP98-complex volume at the nuclear
membrane (Figures S2.1K-S2.1M). Moreover, using a previously described genetic construct to
monitor nuclear GFP-export and RFP-import, we observed a deficit in nuclear import following
mechanical injury (Figures S2.1N-S2.1P).
141
Collectively, these data suggest that HIFU injury of
cortical organoids elicits several biomarkers and disease mechanisms associated with TBI.

Enhanced TDP-43 dysfunction occurs in deep layer neurons and induces neurodegeneration
To determine how mechanical injury affected different neuronal subtypes and glial cells,
we conducted single-cell RNA sequencing on 2530 cells from 10 5-month organoids subjected to
19

sham or HIFU (Figures S2.2A-S2.2C). Unsupervised pseudotime analysis (Monocle2) identified
1408 differentially-expressed genes driving the transition from a sham-enriched state 1 to an
injury-enriched state 6 in deep layer excitatory neurons (Figures 2.2A-2.2C). In contrast,
pseudotime analysis only identified 11 and 48 significant differentially-expressed pseudotime-
driving genes (significance defined as q < 0.05) in astrocytes and excitatory upper layer neurons,
respectively (Figures S2.2D-S2.2G). The collection of genes differentially expressed between
sham and injured deep layer neurons (1408 genes) was enriched for pathways involved in diverse
neurodegenerative diseases, including ALS (Figure 2.2D). Unbiased assessment of only the top
100 most significantly expressed genes between state 1 and state 6 identified ALS as the most
significantly enriched pathway in injured neurons, with a marked enrichment in the following
ALS-related gene families: cytoskeletal regulators (NEFL, NEFM, PFN1, RAC1)
142–144
,
proteasomal subunits (PSMD7)
145
, and electron transport chain proteins (NDUFA4, NDUFA8,
NDUFB10, UQCRFS1, UQCRC2)
146–150
(Figure S2.2H, Table S1).
In ALS, FTD, and many cases of CTE, affected neurons exhibit TDP-43 pathology in the
form of nuclear loss and cytosolic inclusions.
12,22
One of TDP-43’s physiological functions is to
mediate the appropriate splicing of pre-mRNA for multiple neuronal genes.
151,152
Loss of nuclear
TDP-43 therefore results in the incorporation of cryptic exons which often lead to frameshift and
nonsense-mediated decay of many TDP-43 target genes, at least some of which are critical for
normal neuronal function.
152
However, it is not clear which cortical neuron subtypes are most
vulnerable to such disease processes after mechanical injury. In deep layer excitatory neurons, we
found a striking downregulation of many putative TDP-43 target genes in the injury-enriched state
6 (Figure 2.2E), suggestive of a layer-specific TDP-43 loss-of-function signature following
mechanical injury.
152,153
Immunostaining confirmed that although upper and deep layer neurons
20

both had significant reductions in TDP-43 nuclear:cytoplasmic ratios after injury, deep layer
CTIP2
+
neurons showed an enhanced reduction in the nuclear:cytoplasmic ratio of TDP-43
compared to upper layer SATB2+ neurons (Figures 2.2F-2.2H). Notably, the CTIP2+ and
SATB2+ neurons in organoids did not segregate into separate layers as they do in vivo (Figure
S2.1C). This suggests that the neuronal subtype specificity observed here is not affected by the
spatial proximity to the injury. However, as neurogenesis of deep and upper layer neurons is not
synchronized, we cannot rule out that neuronal age contributes to the differential response to HIFU
injury.
Loss of TDP-43 function leads to a well-characterized reduction in the total mRNA and
protein levels of stathmin-2.
152,153
Injured organoids indeed had significantly reduced stathmin-2
mRNA and protein at 7 dpi (Figures 2.2E, 2.2I-2.2K). We also observed other TDP-43- and ALS-
associated pathologies following injury, including decreased expression of UNC13A mRNA and
reduced nuclear localization of ELAVL3 at 7 dpi (Figures 2.2L-2.2N).
100,154,155
Thus, mechanical
injury induced TDP-43 pathology and dysfunction, particularly in deep layer excitatory neurons
as compared to upper layer neurons or astrocytes.
To determine if TDP-43 dysfunction drives neurodegeneration after mechanical injury, we
treated organoids with a previously-described TDP-43 bait oligonucleotide that modulates the
phase transition properties of TDP-43 and prevents its aggregation, thereby mitigating its toxic
gain-of-function.
156
Consistent with previous results, bait oligonucleotide treatment induced an
increase in the neuronal nuclear:cytoplasmic ratio of TDP-43 following injury (Figures 2.2O and
2.2P).
156
This treatment significantly mitigated neurodegeneration after HIFU injury (Figure
2.2Q). In contrast, treatment with 10 µM of the bait oligonucleotide in the absence of injury
accelerated neurodegeneration, potentially due to interference with normal TDP-43 function in the
21

absence of injury-induced TDP-43 pathology
152,157,158
. These data suggest that TDP-43
dysfunction is a major driver of injury-induced neurodegeneration in organoids and preferentially
affects deep layer neurons.

Suppression of KCNJ2 mitigates HIFU-induced neurodegeneration
Existing studies have generally explored broadly-acting and non-specific approaches for
mitigating the effects of mechanical injury
159,160
. As a result, there is a need to identify the most
specific and disease-modifying targets using unbiased genome-wide screens.
161
To identify
potential genetic modifiers of neuron survival following mechanical injury, we conducted a
genome-wide CRISPR interference screen. In order to maximize and enrich the number of
neurons, we generated NGN2-organoids (n=300) from iPSCs stably expressing dCas9-BFP-KRAB
and a dox-inducible NGN2 cassette. A similar differentiation method has yielded diverse neuron
types, but because this method bypasses the neuron progenitor stage, glial cells are absent.
162
We
next transduced the organoids with a genome-wide lentiviral sgRNA library as previously
described and divided them into HIFU and sham-injured control groups of 150 spheroids each
(Figure 2.3A).
163
We isolated total DNA at 7 dpi and PCR-amplified and sequenced the sgRNA
sequences as previously described
163
. Reads were analyzed using the standard MAGeCK-RRA
pipeline and enriched genes (representative of >2 sgRNAs/gene) were assessed by GO molecular
function (Figures 2.3B and 2.3C; Tables S2, S3). Ion channel ontologies were strongly enriched
from the protective sgRNAs, and among these, mechanosensitive channel activity is particularly
relevant to TBI (Figure 2.3C). Although mechanosensitive channels have been implicated in
neuronal injury, it has remained unclear which channels might be most effective at mitigating
neurodegeneration if targeted during or after TBI.
103,160,164

We tested several of the most significant protective genes for secondary validation by
22

longitudinal survival tracking of injured organoids infected with target sgRNAs identified from
the screen (Figures S2.3A-S2.3D). Each target showed at least 1 sgRNA imparting a protective
effect on neuronal survival. Of the genes tested, the inward-rectifying potassium channel, KCNJ2,
a reported mechanosensitive ion channel
165,166
, was a top protective hit (6/8 KCNJ2 sgRNAs
protective; Figure S2.4A). We also identified sgRNAs targeting multiple KCNJ2 interactors
among the significantly enriched and de-enriched guide RNAs, further suggesting that KCNJ2
function could regulate neurodegeneration after mechanical injury (Figure S2.4B).
167
KCNJ2 was
particularly attractive as a genetic target compared to other mechanosensitive ion channels
observed in the screen, including multiple transient potential receptor channel (TRPC) family
members, due to its statistical significance and its monogenic channel properties, which is in
contrast to TRPC channels such as TRPC1/4/5 which operate in heterotetramers.
165,168
To validate
the role of KCNJ2 in injured organoids, we employed genetic knockdown and small molecule
inhibition of KCNJ2 using two sgRNAs and ML133
169
, respectively. Genetic suppression of
KCNJ2 maintained neuron survival in injured organoids to the level of the uninjured controls
(Figures 2.3D and 2.3E; Figures S2.4C-S2.4E). In addition, small molecule inhibition of KCNJ2
with ML133 significantly reduced neurodegeneration following mechanical injury (Figure 2.3F).
Using a third modality, we further validated the specificity of KCNJ2 through antisense
oligonucleotide (ASO) treatment and found that KCNJ2 ASO also improved the survival of
mechanically injured neurons (Figure 2.3G). ASO-mediated knockdown or chemical inhibition of
KCNJ2 alone in the absence of injury did not affect neuron survival (Figure S2.4F). Interestingly,
we found that inhibiting KCNJ2 activity post-injury was also neuroprotective, with administration
of ML133 one hour post-injury significantly improving neuron survival (Figure S2.4G).
Importantly, inhibition of KCNJ2 using ML133 also significantly reduced the ratio of p-
23

tau to total tau (Figure 2.3H). Consistent with KCNJ2 possessing mechanosensitive ion channel
activity, treatment with ML133 during ultrasound stimulation reduced injury-induced Ca
2+
influx
into neurons (Figures 2.3I and 2.3J). Based on previous studies suggesting that cytosolic Ca
2+
regulates the nucleocytoplasmic transport of TDP-43 and directly contributes to ALS pathology,
we hypothesized that KCNJ2 may be mediating this mechanism.
170
We found that direct induction
of intracellular Ca
2+
with ionomycin was sufficient to induce TDP-43 phosphorylation in the
absence of injury and that this was mitigated by chelating extracellular Ca
2+
with BAPTA-AM,
suggesting that Ca
2+
influx mediated by KCNJ2 observed during mechanical injury can directly
induce TDP-43 pathology (Figures S2.5A-S2.5D).
Interestingly, direct induction of Ca
2+
with ionomycin did not result in a similar increase,
and in fact the opposite, of the p-tau/tau ratio we observed following HIFU (Figure S2.5E).
Considering the reduction in p-tau to total tau ratio following KCNJ2 inhibition, these data suggest:
1) separate mechanisms of TDP-43 and tau phosphorylation, 2) more complex signal transduction
regulates tau phosphorylation following mechanical injury, 3) downstream KCNJ2 signaling
contributes in part to the post-injury phosphorylation of tau. Collectively, inhibiting KCNJ2
activity in vitro mitigates neurodegeneration and injury biomarker levels after HIFU injury.

Kcnj2 antisense oligonucleotide treatment reduces TDP-43 pathology following controlled cortical
impact in vivo
TDP-43 proteinopathy has previously been described in animal models of TBI.
96,97
In a
controlled cortical impact (CCI) mouse model, at 3 dpi we observed a significant reduction in
neuronal TDP-43 nuclear:cytoplasmic ratio and accumulation of cytoplasmic TDP-43 at the site
of injury (Figures 2.4A-2.4D). These changes were associated with increased cell death at 3 dpi in
the cortex proximal to the injury site (Figures S2.6A and S2.6B). We also noted elevated
24

astrogliosis 3 dpi in the cortex via increased GFAP coverage (Figures S2.6C and S2.6D). In
addition to TDP-43 mis-localization, we also found an increase in cytoplasmic phospho-TDP43 in
the cortex of injured mice (Figures S2.6E and S2.6F). To assess if Kcnj2 modulates TBI
pathophysiology in vivo, we performed an intracerebroventricular injection of a Kcnj2-targeted
ASO (500 µg) 5 days prior to injury (Figure 2.4E). ASO treatment induced a ~50% reduction in
Kcnj2 mRNA and protein levels (Figures S2.6G-S2.6I). At 3 dpi, we found that injured mice
treated with Kcnj2 ASO displayed an increased neuronal nuclear:cytoplasmic TDP-43 ratio and a
significant reduction in cytoplasmic TDP-43 relative to non-targeting control (NT) ASO-treated
mice (Figures 2.4F-2.4H). In contrast to NT ASO injured mice, Kcnj2 ASO reduced the levels of
cytoplasmic phosphorylated TDP-43 at 3 dpi (Figures 2.4I and 2.4J). Kcnj2 ASO also reduced
cell death at 3 dpi, evidenced by reduced TUNEL-positive cells proximal to the injury site relative
to injured NT ASO mice (Figures 2.4K and 2.4L). Additionally, injured Kcnj2 ASO-treated mice
showed significantly reduced astrogliosis at 3 dpi (Figures S2.6J and S2.6K). We also aimed to
assess whether Kcnj2 knockdown improves motor function following injury. Injured NT ASO
mice had a significant reduction in rotarod performance at 1 dpi and 3 dpi compared to NT sham,
while mice treated with Kcnj2 ASO did not exhibit a significant loss in motor function following
injury at 3 dpi (Figure 2.4M). Collectively, these data suggest that inhibition of KCNJ2 can
effectively reduce the acute TDP-43 injury and degenerative responses following TBI in vitro and
in vivo.

KCNJ2 inhibition mitigates pathological injury processes potentiated by the C9ORF72 repeat
expansion
TBI is a strong environmental risk factor for ALS, and over 85% of late-stage CTE patients
exhibit TDP-43 proteinopathy post-mortem.
10–14
We have previously shown that motor neurons
25

derived from C9ORF72 ALS/FTD patients exhibit lower nuclear:cytoplasmic TDP-43 ratios.
171

Interestingly, while C9ORF72 ALS/FTD patient organoids did not show enhanced
neurodegeneration within 7 days following injury (Figure S2.7A), we observed significantly
enhanced cytoplasmic TDP-43 and phospho-TDP-43 in patient-derived organoids after HIFU
injury relative to injured wild-type organoids (Figures 2.5A-2.5C). We also observed a more
significant loss of the ALS/FTD associated TDP-43 splicing target STMN2 in C9ORF72 organoids
compared to healthy controls (Figure 2.5D). To determine if reduced STMN2 expression impaired
neurite outgrowth as previously described
152,153
, we injured healthy and C9ORF72 NGN2-
organoids and embedded them in a collagen hydrogel to observe neurite outgrowth. This assay
was conducted in homogenous NGN2-organoids to avoid the contribution of glial cells. We
observed that HIFU injury reduced neurite outgrowth in both patients and controls, and notably,
the C9ORF72 repeat expansion exacerbated this reduction (Figure 2.5E; Figures S2.7B and
S2.7C).
Human gene expression data from C9ORF72 and sporadic ALS patients showed increased
neuronal expression of KCNJ2 relative to pathologically normal individuals (Figure S2.7D)
172
.
Similarly, C9ORF72 organoids exhibited a higher expression of KCNJ2 compared to age- and sex-
matched control organoids (Figure S2.7E). To assess if inhibition of KCNJ2 mitigates acute
neurodegeneration following injury in an ALS/FTD genetic background, we treated C9ORF72
organoids with ML133 immediately prior to injury and observed a significant reduction in
neuronal loss over the course of 7 days (Figure 2.5F). Moreover, ML133 co-treatment with injury
mitigated the post-injury reduction in the nuclear:cytoplasmic ratio of TDP-43, the increase of
cytoplasmic phosphorylated TDP-43, as well as a loss of full-length STMN2 expression (Figures
2.5G-2.5J). Together, these data show that C9ORF72 ALS/FTD patient organoids have enhanced
26

susceptibility to TDP-43 loss-of-function following mechanical injury, which may lower the
threshold for disease. Modulating KCNJ2 function may reduce disease pathogenesis following
TBI in individuals harboring genetic mutations predisposing them to neurodegeneration.

2.4 Discussion
Traumatic brain injury is a complex disease process with contributions from cells within
and outside the central nervous system, blood, biophysical forces resulting from intracranial
pressure and edema, and genetic modifiers of the injury response. Our mechanical injury model
represents a starting point for bridging the translational gap from rodent to human models of TBI.
As a preliminary step, it provides increased granularity of intrinsic cellular mechanisms following
mechanical injury via a reductionist cellular approach. Recent studies have taken a similar
approach using ultrasound to mimic blast injury in 3D neural tissue, demonstrating the
translational relevance of this model to mimic aspects of TBI.
108,130
This model recapitulates TBI-
related biomarkers (ptau/tau)
3
, histological markers (TDP-43 mis-localization)
10,12
, transcriptomic
signatures (cellular respiration and proteostasis dysregulation)
132–134
, and neurodegeneration.
Using this novel human iPSC model, we have uncovered several key findings.
First, we show that TDP-43 dysfunction is a key driver of neurodegeneration after
mechanical injury. Surprisingly, although tau phosphorylation and pathology are used as
diagnostic tools for TBI and CTE, respectively, we found that TDP-43 mis-localization appeared
rapidly after injury and that specifically mitigating the phase transition properties using a
previously-described TDP-43 bait oligonucleotide rescued neurodegeneration.
156
Interestingly, we
observed that the TDP-43 bait oligonucleotide induced neurodegeneration in the absence of injury.
This bait is based on a well-characterized high-affinity nucleic acid motif for TDP-43.
173
High
27

concentrations of these oligonucleotides can potentially competitively displace TDP-43 from its
required targets leading to on-target toxicity via dysregulated and pathological splicing of nascent
transcripts. However, in the presence of injury, when the localization of TDP-43 shifts into the
cytoplasm, there is likely less competition in the nucleus for endogenous transcripts, and the
mitigation of phase separation in the cytoplasm imparts a neuroprotective phenotype as previously
described.
156
This provides evidence that the toxic gain-of-function associated with cytoplasmic
TDP-43 localization is responsible in part for neurodegeneration following mechanical injury in
our model. Based on our data demonstrating a reduction in STMN2 RNA and protein, as well as
UNC13A, following injury, it is likely that TDP-43 loss-of-function also contributes. A recent
study inflicting TBI in zebrafish suggested that phase-separated TDP-43 contributes to
neurodegeneration, and that reduction of these condensates promotes a protective and regenerative
microglia state.
174
While activated microglia can exacerbate neuronal TDP-43 pathology, our
organoid system does not contain microglia, suggesting that mechanical injury directly triggered
TDP-43 dysfunction in neurons, in part via increased levels of cellular Ca
2+
.
175
Indeed, our data
indicate that Ca
2+
induction directly promotes TDP-43 phosphorylation and mis-localization,
consistent with previous findings showing that cytosolic calcium regulates nucleocytoplasmic
transport of TDP-43 and contributes to pathology in ALS.
170
Thus, our results suggest that
targeting TDP-43 may be important for mitigating neurodegeneration after TBI.
Furthermore, using single cell RNAseq and histological validation, we found that deep
layer glutamatergic neurons displayed enhanced TDP-43 dysfunction following injury compared
to upper layer neurons. These findings are consistent with a previous study using mouse CCI in
which deep layer neurons exhibited enhanced glutamate signaling following injury, a phenotype
that has been attributed to TDP-43 pathology.
176,177
While TDP-43 proteinopathy has been shown
28

in all layers of the cortex in TBI patients post-mortem, this layer-specific enrichment for TDP-43
dysfunction at acute timepoints may allude to the susceptibility of deep layer neurons observed in
ALS.
12,178
However, as previous studies were performed in vivo, it was not possible to determine
if the differential susceptibility of deep and upper layer cortical neurons resulted from differences
in proximity to the site of injury, or cell intrinsic properties. Because organoids do not possess the
defined cortical layering observed in rodent or human brains, our study suggests that intrinsic
differences between deep and upper layer neurons, not differential locations or injury forces,
explain the enhanced severity of TDP-43 pathology in deep layer neurons post-injury. These
findings may point to differences between deep and upper layer neurons that one could exploit to
protect TBI patients against diseases in which deep layer neurons are lost, including ALS.
Our organoid model is scalable and genetically malleable, thus enabling CRISPR screening
to identify genes that modulate the outcome of acute mechanical injury. Such capability is
desperately needed given the challenges in identifying therapeutic targets through genetic
analyses. Previous gene association studies in patients with TBI have shown contradicting results,
particularly pertaining to polymorphisms in APOE4.
179
In addition, a recent prospective GWAS
study of over 5000 patients followed for one year post-TBI were unable to identify any genetic
variants above genome-wide significance linked to TBI outcome.
180
Although studies have
implicated mechanosensation in TBI, effective approaches for mitigating mechanotransduction in
human cortical neurons have remained unclear due to the lack of a suitable model system.
161
Using
genome-wide phenotypic screening on human organoids, we show for the first time in human cells,
and subsequently validated in a mouse CCI model, that inhibition of the mechanosensitive ion
channel KCNJ2 in neurons potently curbs neurodegeneration and reduces TDP-43 mis-localization
following mechanical injury in vitro and in vivo, in part through the neuroprotective decrease of
29

Ca
2+
entry into neurons following injury.
170,181
We chose KCNJ2 for follow-up studies over other
mechanosensitive ion channels observed in the screen due to its statistical significance and its
monogenic properties (in contrast to TRPC members which form heterotetramers), suggesting it
would be more amenable to genetic intervention.
165,168
Inhibition and loss-of-function mutations
in KCNJ2 have been shown to depolarize resting membrane potentials.
182
While neuronal
hyperexcitability has been shown to cause seizures and increased morbidity among TBI patients,
it is possible that fine-tuning resting membrane potentials via KCNJ2 modulation counteracts the
acute suppression of neuronal activity and global metabolic depression observed in animals
following injury.
183,184
Indeed, a recent study has shown that systemic vascular KCNJ2 activity is
reduced following TBI, suggesting a potential compensatory function of KCNJ2 to injury
185
. Other
studies have shown that KCNJ2 inhibition mitigates neuropathic pain, demonstrating its relevance
to nervous system disorders.
186
Although KCNJ2 loss-of-function mutations, some of which
disrupt channel trafficking to the plasma membrane, have been linked to cardiac and
developmental deficits in Anderson-Tawil syndrome, it is possible that transient or low-level
inhibition of KCNJ2 activity in the brain may be tolerated.
187–189
Critically for its potential as a
therapeutic, we found that small molecule inhibition of KCNJ2 one hour post-injury, but not three
hours post-injury, was sufficient to improve neuron survival. This is in line with the therapeutic
window of current pharmacological interventions, such as barbiturates, which are administered
within 1-2 hours of TBI in humans.
4
KCNJ2 inhibition could also be considered as a prophylactic
treatment for individuals at elevated acute risk of TBI, such as athletes.
We tested whether Kcnj2 inhibition in vivo could rescue motor deficits following CCI and
found that NT ASO-treated mice displayed a significant decline at 1 and 3 dpi, while Kcnj2 ASO
prevented a significant decrease in rotarod performance in injured mice at 3 dpi. This suggests that
30

Kcnj2 knockdown may promote improved recovery post-injury, however, rotarod performance
was not significantly improved in injured Kcnj2 mice relative to NT mice. These data are similar
to previous studies on decompressive craniectomy, the current gold standard surgical procedure
for severe TBI, which show only a modest improvement in rotarod performance in the surgical
group.
4,190
It is likely that such a severe injury, which causes significant bleeding and gross lesions
in addition to neuropathology, presents a significant cumulative challenge in regards to rescuing
motor function. Knockdown of a single gene, such as Kcnj2, may be insufficient to address these
numerous insults, resulting in only a mild improvement in motor function in this context despite
observed improvements in neuron pathology, astrogliosis, and cell death. Nonetheless, targeting
Kcnj2 in mice prior to injury also alleviated the TDP-43 pathological burden and astrogliosis,
suggesting that its therapeutic effects may persist beyond the acute phase of injury. Additionally,
in vivo validation using a conventional and well-characterized model of murine TBI of one of our
top screen targets demonstrates the translational relevance of the HIFU model.
Finally, the ability to study TBI and its synergism with genetic predisposition for
neurodegenerative disease in human cells has largely eluded researchers. The G4C2 repeat
expansion in C9ORF72 is the most common form of familial ALS/FTD, in which TDP-43
represents the major pathological protein in 97% of patients.
22
Here, we show that brain organoids
derived from ALS/FTD patients harboring the C9ORF72 hexanucleotide repeat expansion display
significantly elevated TDP-43 pathology acutely post-injury relative to injured healthy control
organoids. This was not found to correlate with enhanced neurodegeneration, perhaps due the acute
injury time frame we examined, but may sensitize neurons to greater degeneration over an
extended period of time. Upon injury, C9ORF72 ALS/FTD patient organoids also displayed an
enhanced loss of TDP-43 dependent transcript STMN2, which has been previously shown to affect
31

patient survival and neurite maintenance, respectively.
152–154
Consistent with previous
observations of STMN2-mediated neurite dysfunction, we observed an exacerbated deficit in
neurite outgrowth in C9ORF72 ALS/FTD organoids following injury, suggesting a more severe
TDP-43 loss-of-function.
152,153
These findings highlight TDP-43 dysfunction as a potential
mechanistic link to explain how TBI and genetic mutations can synergize to increase risk of long-
term neurodegenerative diseases.
87,178
Importantly, inhibition of KCNJ2 was sufficient to reduce
neurodegeneration and TDP-43 dysfunction in genetically-predisposed C9ORF72 ALS/FTD
patient organoids.
Collectively, we describe here a human organoid platform for the discovery and validation
of modifiers of mechanical injury outcome in healthy and disease-associated genetic backgrounds.
This injury model aims to bridge the gap between traditional in vitro systems and complex higher
organisms, thereby providing a scalable and genetically-flexible system to identify potential
disease mechanisms and therapies for the acute and chronic effects of TBI. We show that TDP-43
dysfunction is a key driver of neurodegeneration after mechanical injury and identify an intrinsic
vulnerability of deep layer excitatory neurons to TDP-43 dysfunction. Finally, we show that
KCNJ2 inhibition potently mitigates injury-induced disease processes in an ALS/FTD-associated
genetic background and in vivo, in part via a neuroprotective decrease in cytosolic Ca
2+
following
injury. Future work will address long-term consequences of mechanical injury in various genetic
backgrounds, as well as incorporate additional cell types such as microglia or oligodendrocytes,
thus enabling an unprecedented analysis of neuron-autonomous and non-autonomous responses to
injury.

Limitations of the study
32

This study demonstrates the utility of the HIFU model to recapitulate features of traumatic
brain injury in human organoids and study intrinsic cellular injury mechanisms in variable genetic
backgrounds, but we acknowledge that this model does not fully capture the complex cascade of
events found in human TBI. Our system models the intrinsic effects of primary blast injury forces,
but does not incorporate the full range of biophysical forces present in human TBI or secondary
insults including ischemia, blood-brain-barrier leakage, microglial activation, and more. Future,
more-complex iterations of this model will seek to address these additional stressors. Lastly,
organoid cultures represent a relatively neonatal state that differs from adult neural tissue.
Although functional neuronal activity is observed, and the findings are validated in an adult mouse
model, there are inevitably factors that cannot immediately translate from stem cell models to
humans.

33

2.5 Figures

Figure 2.1 A novel iPSC-organoid mechanical injury model exhibits TBI-related pathology.

(A) Two month old SYN1::eGFP labelled organoids were immobilized using matrigel, injured using high-
intensity focused ultrasound, and imaged at the injury site over 7 days. (B) Kaplan-Meier survival analysis
of HIFU-injured organoids (n= 50 neurons/condition; Log-Rank test). (C) representative surface images of
SYN1::eGFP-labelled organoids injured at 0.6 MPa (scale bar, 100 µm). (D-F) Western blot quantification
(D and E) and representative immunoblots (F) of neurofilament-L and Tubulin 𝛽 3 7 days post injury (dpi)
normalized to total protein (n=8; Mann-Whitney U test). (G) Pressure- and (H) time-dependent changes in
pTau (Thr231) to total tau ratio in the supernatant of injured organoids compared to sham measured by
MSD electrochemical ELISA (n=8; 3 iPSC lines; One-way ANOVA with Tukey's correction). (I) Ingenuity
pathway analysis of differentially-expressed genes 24 hours post-injury (n=3 organoids). (J) Representative
images and (K) quantification of phosphorylated TDP-43 in MAP2+ neurons 7 dpi (n= 25
neurons/condition; averaged across 2 sections; unpaired t test two-tailed; 10 µm scale bar).

34

Figure 2.2 TDP-43 loss-of-function drives neurodegeneration in deep-layer excitatory neurons.

(A) Unsupervised pseudotime analysis of deep-layer cortical neurons from 5-month-old organoids 7 days
35

following 0.6 MPa injury (n=5 organoids/condition; 1 iPSC line). (B and C) Proportion of cells in states 1
and 6, respectively (Fisher's Exact test). (D) KEGG enrichment of pseudotime-driving genes. (E) Gene
expression heatmap of differentially expressed TDP-43-response genes (q<0.01) (F-H) Quantification (F)
and representative images (G and H) of deep layer (CTIP2
+
) and upper layer (SATB2
+
) neuron changes in
TDP-43 nucleocytoplasmic ratio 7 dpi (n= 100 neurons/condition; different iPSC line from A; One-way
ANOVA with Tukey's correction; 5 µm scale bar). (I and J) Validation of STMN2 expression by western
blot in organoids 7 dpi and (K) qPCR in organoids 8 hours post-injury (n=7 organoids; unpaired t test two-
tailed). (L) qPCR of UNC13A in organoids 8 hours post-injury, normalized to 18S (n=6 organoids; unpaired
t test two-tailed). (M) Representative images of ELAVL3 in organoids 7dpi and (N) quantification of
ELAVL3 nucleocytoplasmic ratio (unpaired t test, two-tailed; Scale bars 5 µm). (O) Representative images
and (P) quantification of nuclear/cytoplasmic ratio of TDP-43 following injury in TDP-43 bait oligo- or
scramble- pretreated organoids (n=40 neurons/condition; unpaired t test two-tailed; Scale bars 5 µm). (Q)
Neuronal survival of sham and injured organoids following 24 hour pretreatment with 10µM TDP-43 bait
or scramble oligo (n= 120 neurons/condition, Log-Rank test).

36

Figure 2.3 A CRISPRi screen identifies KCNJ2 as a modifier of mechanical injury in vitro.

(A) 2-month NGN2-organoids stably (n=300) expressing dCas9-BFP-KRAB were transduced with a
lentiviral genome-wide sgRNA library (209,070 gRNAs (10 gRNAs/gene), 3790 non-targeting gRNAs).
37

Organoids were injured using HIFU (0.6 MPa; n=150) and sgRNAs were enriched by PCR and sequenced
to determine enrichment of sgRNAs compared to sham-injured organoids (n=150) 7 days post-injury. (B)
Volcano plot of protective and detrimental sgRNAs (P < 0.05) determined by MAGeCK-RRA. (C) Gene
Ontology Molecular Function enrichment of top protective and detrimental sgRNAs. (D and E) Organoids
expressing dCas9-BFP-KRAB were lentivirally transduced with SYN1::eGFP, KCNJ2-targeting sgRNAs
or non-targeting sgRNAs, injured at 0.6 MPa. GFP+/BFP+ neurons were tracked longitudinally for 9 days
for survival. (n=120 neurons/condition; Log-Rank test). (F) 2 month organoids were treated with 30 µM
ML133 or DMSO immediately before injury (0.6 MPa), and SYN1::eGFP neurons were tracked
longitudinally over 7 days post injury (n= 120 neurons/condition; Log-Rank test). (G) organoids were
treated with 10 µM NT or KCNJ2 ASO three days before injury (0.6 MPa), and SYN1::eGFP neurons were
tracked longitudinally over 7 days post injury (n= 120 neurons/condition; Log-Rank test). (H) Changes in
pTau (Thr231) to total tau ratio in the supernatant of sham or injured organoids pre-treated with 30 µM
ML133 or DMSO measured by MSD electrochemical ELISA (n=7 organoids/group; One-way ANOVA
with Tukey's correction). (I) Calcium traces and (J) peak amplitude of organoids loaded with 1 µM Fluo-
4-AM and imaged for 2 min before and after injury in the presence of DMSO or 30 µM ML133 (unpaired
t test, two-tailed; n= 40-60 neurons/condition analyzed).

38

Figure 2.4 Knockdown of Kcnj2 reduces TDP-43 pathology, cell death, and motor deficits following
controlled cortical impact in mice.

(A) A cranial window (centred at Bregma -2.5mm/lateral 2.5mm) was drilled in 8 week old C57Bl6
wildtype mice and injured using a 2 mm metal flat-tip impactor (3 m/s, 1 mm depth, 180 ms dwell time).
Three days post-injury, mice were perfused with PBS and PFA. Coronal sections of CCI or sham operated
mice were (B) immunostained and (C) quantified for TDP-43 nuclear:cytoplasmic ratio and (D)
cytoplasmic intensity (N=6 mice/group; unpaired t test two-tailed; Scale bars 25 µm). (E) 500μM NT or
Kcnj2 ASO was injected ICV 5 days before sham or CCI injury (F-H) Representative TDP-43
39

immunostaining (F) at the site of injury 3 dpi of mice injected with 500 µg Kcnj2 or a non-targeting ASO,
(G) quantification of TDP-43 nuclear:cytoplasmic ratio and (H) cytoplasmic intensity (N=5-8 littermate
controls/group; unpaired t test two-tailed; Scale bars 25 µm). Representative immunostaining (I) and
quantification (J) of cytoplasmic phosphorylated TDP-43 (S403/404) at the site of injury 3 dpi of mice
injected with 500 µg Kcnj2 or a non-targeting ASO (N=5 littermate controls/group; unpaired t test two-
tailed; Scale bars 25 µm). (K) Representative TUNEL immunostaining at the site of injury 3 dpi and
quantification (L) of the number of TUNEL-positive cells per area (N=3-8 littermate controls/group; One-
way ANOVA with Tukey’s correction; Scale bars 50 µm). (M) Rotarod test was performed before injury,
1 dpi, and 3 dpi on NT and Kcnj2 ASO injected mice subjected to sham surgery or CCI. Fold change
calculated for each mouse relative to its pre-surgery performance (Two-way ANOVA with Sidak’s
correction).

40

Figure 2.5 KCNJ2 inhibition suppresses TDP-43 pathology in injured ALS/FTD organoids.

(A-C) 2-month organoids derived from gender-matched wildtype or C9ORF72 ALS/FTD patients were
injured (0.6 MPa) and fixed 7 dpi for immunostaining (n=100 neurons/condition). Representative images
(A), quantification of (B) cytoplasmic TDP-43, (C) phospho-TDP-43 (Ser409/410) (One-way ANOVA
with Tukey's correction; scale bar: 5 µm). (D) qPCR of STMN2 expression in WT and C9ORF72 organoids
8 hours post injury, normalized to 18S (n=7-8 organoids; 2 iPSC lines per genotype; One-way ANOVA
with Tukey's correction). (E) Injured NGN2-organoids were embedded in collagen and neurite outgrowth
was measured at 6 dpi (n=40 neurites/condition; 1 iPSC line per genotype; One-way ANOVA with Tukey's
correction). (F) Survival analysis of injured 2-month C9ORF72 organoids treated with the KCNJ2 inhibitor,
ML133 (n=120 neurons/condition; Log-Rank test). (G) Representative images, quantification of (H) TDP-
43 N/C ratio, (I) cytoplasmic phospho-TDP-43, and (J) STMN2 expression in C9ORF72 organoids 7 days
41

(TDP-43) and 8 hours (STMN2) post-injury in the presence or absence of ML133 (n= 40-80
neurons/condition; One-way ANOVA with Tukey's correction; scale bar: 5 µm).

42

Figure S2.1 Generation of iPSC cortical organoids and HIFU characterization.

(A) Outline of cortical organoid generation. (B-D) Characterization of (B) neural progenitor regions, (C)
cortical layering in d45 organoids, and (D) astrocytes after 100 days of culture. (E) Simplified schematic
of HIFU apparatus which emits an ellipsoid area of acoustic pressure (dotted line). (F) The intensity of the
pressure can be fine-tuned by adjusting the input voltage and the distance from the organoid. (G)
Reproducibility of mechanical injury in 2 month organoids (2 iPSC lines; 7 organoids/line, 30
neurons/organoid) (H-I) Seven days post-injury, we observe a trend towards astrogliosis. (J) Calcium ion
influx was assayed using Fluo-4-AM and showed an increase in Ca
2+
entry into neurons following injury.
(K) Expression of nuclear pores are down-regulated 24h post-injury, and (L-M) volume of NUP98 around
43

neuronal nuclei is decreased (scale bar, 5 µm). (N) Schematic (O) representative images, and (P)
quantification of nucleocytoplasmic transport deficits and loss of nuclear import of RFP (scale bar, 5 µm).
Statistical tests used were DESeq2 k, Mann-Whitney U test m, and two-tailed t test p, n=10-30
neurons/condition. Data representative of at least 3 healthy control iPSC lines.

44

45

Figure S2.2 Single cell RNA sequencing analysis of cell-specific responses to HIFU.

(A) UMAP of scRNA-seq data in 5-month-old injured and sham organoids 7 dpi by cell type. (ExM-U,
maturing excitatory upper enriched; ExDp, excitatory deep layer; Ast, astrocytes; IP, intermediate
progenitors; RG, radial glia; G2/M, cycling progenitors; S phase, cycling progenitors; UnDf, undefined.
(B) Representative markers used to define cell identity as described by CoDEx
(http://solo.bmap.ucla.edu/shiny/webapp/). (C) Number of each cell type identified per condition. (D-E)
Monocle2 unsupervised pseudotime analysis of ExM-U neurons and (E) enrichment of pseudotime-driving
genes (adj. P value < 0.05) by KEGG. (F and G) Monocle2 unsupervised pseudotime analysis of astrocytes
and (G) enrichment of pseudotime-driving genes (adj. P value < 0.05) by KEGG. (H) KEGG enrichment
of top 100 significant pseudotime-driving genes in deep-layer excitatory neurons (adj. P value < 0.05).

46

Figure S2.3 Validation of top protective genes from CRISPRi screen.

(A-D) dCas9-BFP-KRAB-expressing organoids were transduced with SYN1::eGFP and NT sgRNA or (A)
FAM179A-targeting sgRNA, (b) CAPN7-targeting sgRNA, (C) FOXRED2-targeting sgRNA, or (D)
FLVCR1-targeting sgRNA and injured at 0.6 MPa. GFP+/BFP+ neurons were longitudinally for 9 days for
survival. (n=120 neurons/condition; Log-Rank test).

47

Figure S2.4 KCNJ2 sgRNAs are enriched in HIFU CRISPRi screen.

(A) Enrichment of 6/8 sgRNAs in injured condition 7 dpi. (B) Identification of KCNJ2-interacting proteins
among enriched and de-enriched sgRNAs. (C) Validation of KCNJ2 antibody by overexpression in
HEK293T cells and optimization of Western Blotting. (D and E) dCas9-BFP-KRAB-expressing neurons
were transduced with KCNJ2-targeting sgRNA or non-targeting sgRNA, and lysates were analyzed by
Western blot for KCNJ2 expression (unpaired t test, two-tailed). (F) Survival analysis of sham organoids
treated with 30µM ML133 or 10µM KCNJ2 ASO (n=120 neurons/condition; Log-Rank test). (G) Survival
analysis of injured organoids treated with 30µM ML133 1 hour or 3 hours post-injury (n=120
neurons/condition; Log-Rank test).

48

Figure S2.5 Intracellular calcium promotes TDP-43 phosphorylation.

(A) Representative images and (B-D) quantification in 2-month organoids of TDP-43 and pTDP43
(S409/410) following 24 hour treatment with Ionomycin and BAPTA-AM (n= 120 neurons/condition, One-
way ANOVA with Tukey's correction; Scale bars 25 µM). (E) Levels of ptau/tau in the supernatant after
24 hour treatment with Ionomycin and BAPTA-AM (One-way ANOVA with Tukey’s correction; 6
organoids/condition).

49

Figure S2.6 Astrogliosis and TDP-43 pathology following in vivo CCI.

(A) Representative images and (B) quantification of TUNEL-positive cells at the site of injury 3 dpi in
sham and CCI mice (N=5 mice/group; unpaired t test two-tailed). (C) Representative images and (D)
quantification of GFAP+ astrocytes at the site of injury 3 dpi (5 random fields 100 µm
2
analyzed per
ipsilateral cortex; unpaired t test, two-tailed; N=6 mice/group). (E) Representative images and (F)
quantifications of phospho-TDP-43 (Ser403/404) at the site of injury 3 dpi (unpaired t test, two-tailed; N=6
mice/group; Scale bars 100 µm). (G-I) 500 µg of a Kcnj2-targeting ASO was injected into the right lateral
ventricle of littermate controls. Brains were harvested 5 days post injection for (G and H) Western blot and
(I) qPCR (N=4 mice/group, unpaired t test, two-tailed). (J) Representative images and (K) quantification of
GFAP at the site of injury 3 dpi of mice injected with 500 µg Kcnj2 or a non-targeting ASO (N=5
mice/group, unpaired t test, two-tailed; Scale bars 100 µm).

50

Figure S2.7 C9ORF72 organoids showed reduced neurite outgrowth following mechanical injury.

(A) Organoids derived from sex-matched healthy or C9ORF72 ALS/FTD donor iPSCs (1 male, 1 female)
were injured and neurons (n=120 neurons/condition) were longitudinally tracked for 7 days. Representative
data shown (Log-Rank Test). (B) Injured NGN2-organoids were embedded in collagen and neurite
outgrowth was measured at 4 dpi (n= 40 neurites/condition measured; 1 iPSC line per genotype; One-way
ANOVA with Tukey's correction). (C) Representative images of neurite outgrowth (scale bar, 200 µm).
(D) KCNJ2 gene expression data from pathologically normal, C9ORF72 ALS (c9ALS), and sporadic ALS
(sALS) patients. Groups divided by cell type (Excitatory Upper Layer or Excitatory Lower Layer); DESeq2.
(E) qPCR of KCNJ2 expression in gender-matched wildtype or C9ORF72 ALS/FTD organoids (n=6
organoids/group; One-way ANOVA with Tukey’s correction).

51

Chapter 3: KCTD20 inhibition mitigates excitotoxicity in human
frontotemporal dementia brain organoids
3.1 Abstract
Excitotoxicity is a major pathologic mechanism in frontotemporal dementia (FTD) and
other neurodegenerative diseases. However, the most effective strategies to mitigate this process
are unclear. Here, we show that wild-type iPSC-derived organoids treated with glutamate mimic
key FTD phenotypes, including tau oligomerization and neurodegeneration, and that these
phenotypes are enhanced in FTD patient-derived organoids. Using a genome-wide CRISPR
interference screen, we identified that inhibition of KCTD20 mitigates tau pathology and
neurodegeneration in healthy and patient organoids in vitro and in transgenic mice overexpressing
mutant human tau in vivo. We find that the reduction in oligomeric tau and corresponding
improvement in neuron survival depends on lysosomal exocytosis, which is upregulated following
KCTD20 inhibition. Our results highlight the relevance of using glutamate to model aspects of
human disease and identifies KCTD20 inhibition as a strategy for reducing neurotoxic protein
aggregates.

3.2 Introduction
Excitotoxicity refers to the toxic effects of excitatory neurotransmitters, primarily
glutamate, and is a major pathologic mechanism in multiple neurodegenerative diseases including
Parkinson’s disease, Alzheimer’s disease, Huntington’s disease, and amyotrophic lateral
sclerosis/frontotemporal dementia (ALS/FTD)
45,47,191–193
One of the primary consequences of
glutamate excitotoxicity is a neuronal influx of calcium ions, both from outside the cell mainly via
the highly Ca
2+
-permeable ionotropic N-methyl-D-aspartate (NMDA) receptors or from internal
52

stores via metabotropic receptor signaling
191,194–196
. This leads to: activation of calcium-dependent
proteases, lipases, and DNases; increased reactive oxygen species; and uptake of excess calcium
by mitochondria resulting in membrane depolarization and reduced ATP production, which over
time collectively contribute to cell death
191,196,197
. Additionally, calcium influx following
glutamate receptor activation can disrupt microtubule binding and promote tau pathology, directly
and through activation of calcium-dependent kinases
198–201
. Current therapeutics for diseases
implicated with excitotoxicity like ALS/FTD, such as riluzole, aim to modify disease pathogenesis
in part by decreasing synaptic glutamate release
202
. Other pharmacologic agents, such as
memantine, are direct NMDA receptor antagonists and have shown moderate success in
Alzheimer’s disease
203
. Memantine was not successful in clinical trials for treatment of FTD,
perhaps because modulating glutamate neurotransmission at the required levels would have
deleterious consequences or because concurrent tuning of GABAergic signaling is required to
balance neurotransmitter defects
204–206
.
Frontotemporal dementia accounts for 5-15% of all dementias, and is a leading cause of
early-onset dementia
207
. FTD with tau pathology (FTD-tau) is present in approximately 45% of all
FTD cases
23
. Over 50 disease-causing variants have been identified in MAPT, which primarily
affect the microtubule binding domains and collectively account for 10-20% of familial FTD
patients
25,208
. One commonly studied mutation, MAPT V337M, is located in exon 12 and expressed
in 3R and 4R tau isoforms
117
. Similar to other mutations in the microtubule binding domains, tau-
V337M decreases the affinity of tau to microtubules and enhances tau phosphorylation, promoting
neuronal deposits of hyperphosphorylated paired helical filaments in patients
34–36
. The V337M
mutation is also shown to enhance formation of oligomeric tau, soluble multimeric intermediate
structures preceding tau filaments with demonstrated neurotoxicity
37,39,42,209
. Oligomeric tau is
53

suggested to be the most toxic species in disease, occurring before, and contributing to
neurodegeneration in the absence of, filamentous tau species
210–212
. Additionally, tau-V337M has
been shown to promote hyperexcitability of iPSC-derived neurons, and patient-derived tau-
V337M cortical organoids are sensitized to glutamate excitotoxicity
44,47
. Current FTD therapies
primarily aim to manage neuropsychiatric symptoms, highlighting an urgent need to identify new
treatments
25
.
A large bank of FTD patient iPSC lines with causative MAPT mutations has been
established, leading to improved mechanistic studies on induced neuron cultures
117,213,214
.
Recently, cortical organoids grown from these lines have recapitulated disease phenotypes and
demonstrated notable improvements in disease modeling due to improved neuron physiology and
maturity, especially related to tau maturation with the noted inclusion of 4R tau species in
organoids
47
. Here, we use cortical organoids from control and MAPT V337M iPSCs to model
excitotoxicity in vitro. We find that glutamate recapitulates FTD phenotypes in wild-type
organoids, which display increased oligomeric tau and neurodegeneration following glutamate
treatment, and that these phenotypes are enhanced in tau-V337M organoids. Using genome-wide
CRISPR screening, we identified KCTD20, whose knockdown mitigates tau pathology and neuron
death in healthy and diseased organoids. Our analysis indicated that the protective effects of
KCTD20 knockdown depend on exocytosis, and we find that lysosomal exocytosis specifically is
required, via a TFEB-regulated mechanism. We validated these findings in vivo using transgenic
MAPT P301S mice, an FTD model with pronounced tau pathology
113
. These data suggest that
targeting KCTD20 may mitigate tau pathology and neurodegeneration in diseases which display
excitotoxicity, such as FTD, and highlight the importance of secretion mechanisms to clear toxic
protein species.
54

3.3 Results
Glutamate excitotoxicity promotes tau oligomerization and neurodegeneration

We generated iPSC-derived human cortical organoids as previously described
66
. Cortical
organoids contain a mix of deep- and superficial-layer neurons, radial glia, and astrocytes with
extended culture, and have been shown to be electrically active
66,68
. To model the excitotoxic
effects seen in FTD patient neurons, we treated wild-type organoids with glutamate and tracked
the survival of Synapsin1::eGFP (SYN1::eGFP) lentivirus-infected neurons over 7 days as
previously described (Figure 3.1A)
47
. We observed a dose-dependent effect on neuron survival,
with approximately 50% of tracked neurons degenerating following 5mM glutamate treatment
(Figures 3.1B and 3.1C). This effect was consistent between organoid replicates and independent
iPSC lines (Figure 3.1D). Co-treatment with ionotropic glutamate receptor inhibitors Nimodipine,
CNQX, and MK-801 reduced glutamate-induced neurodegeneration, demonstrating the selectivity
of this phenotype (Figure 3.1E)
45
. We also observed that glutamate induces a dose-dependent
increase in high molecular weight (HMW) oligomeric tau (T22) in as early as 48 hours with
pronounced increases in HMW T22 species within 7 days (Figures 3.1F-3.1J)
210
. This is similar to
phenotypes observed in FTD, in which the V337M mutation in MAPT has been demonstrated to
promote neuron death and tau oligomerization
37,47
.

KCTD20 inhibition mitigates glutamate-induced neurodegeneration
Although excitotoxicity has been linked to neurodegenerative diseases, with select FDA-
approved medications for ALS/FTD aimed in part at decreasing synaptic glutamate release, the
most effective genetic modifiers of this response remain unclear
171,202,215,216
. To identify potential
genetic modifiers of glutamate-induced neurodegeneration in neurons, we conducted a genome-
55

wide CRISPR interference (CRISPRi) screen on an enriched neuronal population of neurogenin 2
(NGN2)-overexpressing organoids (Figure S3.1A). This differentiation method yields mature,
diverse neuron types in the absence of glia
162
. NGN2 organoids contain broad expression of
neuronal markers including MAP2 and NeuN, with an enrichment of BRN2-positive upper layer
neurons (Figure S3.1B). We used a previously reported iPSC line stably expressing dCas9-BFP-
KRAB and dox-inducible NGN2 constructs to generate NGN2-organoids (n=300) for the screen
163
.
Organoids were transduced with a genome-wide lentiviral sgRNA library, then divided into
glutamate treated and PBS control groups (Figure 3.2A). As previously described, we isolated total
DNA after 10 days of treatment with 5mM glutamate or an equal volume of PBS, PCR amplified
the guides, and performed next-generation sequencing
163
. sgRNA reads were analyzed using the
standard MAGeCK-RRA pipeline to determine enriched and de-enriched gene targets from the
glutamate-treated organoids relative to PBS controls (Figure 3.2B). In this analysis, enriched gene
targets suggest that knockdown of a given gene improved survival of glutamate-treated neurons.
Significantly enriched genes (-log10(P-value)>1.3) were assessed using GO molecular function,
which identified multiple ion channel etiologies (Figure 3.2C).
We designed antisense oligonucleotides (ASOs) against the top enriched gene targets for
secondary validation to test an alternate modality of knockdown (Figures S3.1C-S3.1F). Of the
genes tested, we found that knockdown of KCTD20 significantly improved the survival of
glutamate treated neurons using multiple ASOs and using individually cloned sgRNAs relative to
negative control (NC5) ASO and non-targeting sgRNA, respectively (Figures 3.2D and 3.E, Figure
S3.1G). Although little is known about KCTD20 function, it is reported to positively regulate the
activity of Akt
217
. We confirmed that knockdown of KCTD20 reduces activated (phosphorylated
Thr308) Akt levels in neurons with and without glutamate treatment (Figures S3.2A and S3.2B).
56

Because Akt promotes activation of mTOR via phosphorylation, and mTOR inhibition has been
shown to be neuroprotective, we next assessed mTOR activity following KCTD20 knockdown
218–
221
. With glutamate treatment, we found that activated mTOR (phosphorylated Ser2448) was
decreased following KCTD20 knockdown (Figures S3.2C and S3.2D). Co-treatment of glutamate
and the mTOR inhibitor rapamycin had a similar effect on neuron survival to KCTD20 ASO
(Figure S3.2E). We hypothesized that, through inhibition of Akt/mTOR, KCTD20 knockdown
may promote autophagic activation or other protein clearance pathways as seen with previous
mTOR inhibitors
220
. Western blot for the autophagosome adaptor LC3 showed that glutamate
treated organoids had reduced autophagic flux (marked by a decreased ratio of LC3-II to LC3-I),
while KCTD20 ASO prevented a decrease in flux after glutamate (Figures S3.2F and S3.2G).

KCTD20 inhibition reduces tau oligomerization and neurodegeneration in tau-V337M organoids
Our previous data show that glutamate induces tau oligomerization and neurodegeneration
in wild-type organoids. To test these phenotypes in a genetic model of excitotoxicity, we generated
patient iPSC-derived organoids with the FTD-causing MAPT V337M mutation. In the absence of
stressors, V337M organoids have elevated phosphorylated and oligomeric tau compared to
CRISPR-corrected MAPT V337V controls (Figures 3.3A-3.3C)
47
. Compared to isogenic V337V
organoids, we found that V337M organoids display enhanced neurodegeneration following 5mM
glutamate treatment (Figure 3.3D and 3.3E). This corresponds to previous reports, where we found
enhanced neurodegeneration in three independent pairs of V337M and V337V lines
47
. This effect
was not due to expression levels of the NMDA subunit NR1, which was unchanged between
mutant and isogenic organoids (Figure S3.3A and S3.3B).
Importantly, KCTD20 ASO significantly improved neuron survival in tau-V337M
organoids treated with glutamate (Figure 3.3F). The effect on neuron survival was significantly
57

better than a previously described MAPT ASO, which was found to be protective in tau transgenic
mice and in non-human primate FTD models (Figure 3.3F)
222
. We found a corresponding reduction
in oligomeric tau in glutamate-treated organoids following KCTD20 knockdown in both MAPT
V337M and wild-type organoids (Figures 3.3G and 3.3H, Figures S3.3C and S3.3D). Because
glutamate excitotoxicity has been described in neurodegenerative diseases beyond FTD, we tested
whether KCTD20 inhibition was neuroprotective in other genetic models. We found that, similar
to tau-V337M, organoids grown from C9ORF72 ALS/FTD patients displayed a significant
survival deficit compared to wild-type organoids after glutamate treatment (Figure S3.3E). Co-
treatment with KCTD20 ASO significantly improved survival of C9ORF72 neurons (Figure
S3.3F). In addition to glutamate, we tested alternative proteostasis stressors, including the inhibitor
of autophagosome fusion bafilomycin and the proteosome inhibitor MG132. Treatment with
bafilomycin and MG132 increased HMW oligomeric tau and induced a corresponding decrease in
neuron survival, while co-treatment with KCTD20 ASO reduced neurodegeneration (Figures
S3.4A-S3.4C). Taken together, KCTD20 knockdown mitigates neurodegeneration following
excitotoxic stress in multiple genetic backgrounds while reducing oligomeric tau levels.

Improved neuron survival following KCTD20 knockdown depends on exocytosis
To examine transcriptional signatures following glutamate treatment in the absence or
addition of KCTD20 knockdown, we performed single-cell RNA sequencing (scRNA-seq) on 3-
month MAPT V337M organoids (Figure 3.4A). Samples were multiplexed using oligonucleotide-
tagged streptavidin antibodies to barcode distinct experimental conditions, and ~39,000 high-
quality cells were recovered
223
. Following sample demultiplexing, scRNA-seq normalization,
reduction, and clustering, cells were manually annotated using reference expression data from
gestational week 17 human neocortex (Figure 3.4B, Figure S3.5A)
224
. We tested whether
58

glutamate affects excitatory neuron survival at the transcriptional level and found that 5mM
glutamate results in a significant decrease in the proportion of ExNs over time, which was
mitigated by KCTD20 ASO (Figure 3.4C). We next calculated unsupervised cell pseudotime
trajectories using Monocle 2 in ExNs
225,226
. Cell proportions per treatment and state were
calculated and significant marker genes (adjusted p<0.05) were used to determine defining
enriched biological processes in Enrichr (Figures 3.4D and 3.4E, Figure S3.5B). As expected,
glutamate treatment increased the proportion of cells in State 2, defined by Glutamate Receptor
and Ion Channel activity (Figures 3.4D and 3.4E). We chose to focus analysis on states with
significant changes in opposing directions between glutamate and glutamate with KCTD20 ASO
co-treatment. Cells in State 1, defined by Neurodegenerative Disease and mTOR Signaling
pathways, were reduced by glutamate treatment and that relative to glutamate alone KCTD20 ASO
significantly increased ExNs in State 1 (Figures 3.3D and 3.3E, Figure S3.5B).
To identify pathways affected by the knockdown of KCTD20, we divided all ExN neurons
based on their relative expression of KCTD20 into KCTD20-low and KCTD20-high groups
(relative expression <0.9 and >1.3). Genes that were upregulated in KCTD20-low neurons
(average log2(Fold Change)>0.25, adjusted p-value<0.05), which corresponded with the
neuroprotective state in our previous experiments, were used to determine enriched biological
processes. GO Biological Processes and Elsevier pathway analysis identified pathways involving
exocytosis and secretion in KCTD20-low neurons among the most significantly enriched pathways
(Figures 3.4F and 3.4G). Feature expression of genes involved in these pathways, including SYT1,
VAMP2, SNAP25, and AP2B1 have been reported to play specific roles in secretion and are linked
to dementia and developmental disorders (Figure S3.5C)
148,227,228
. We hypothesized that
knockdown of KCTD20 may therefore decrease oligomeric tau species and improve neuron
59

survival by promoting exocytosis. This is similar to previous findings in ALS/FTD demonstrating
that upregulating unconventional protein clearance mechanisms involving exocytosis is
neuroprotective, in part by clearing aggregation-prone proteins
51
. We tested this by treating
organoids with glutamate, KCTD20 ASO, and the neutral sphingomyelinase 2 (nSMase2) inhibitor
GW4869, which broadly blocks exocytosis
229
. Longitudinal tracking of neuron survival showed
that inhibiting exocytosis with GW4869 abolishes the protective effect of KCTD20 knockdown
on neuron survival following glutamate treatment (Figure 3.4H). GW4869 also exacerbated
oligomeric tau levels in glutamate-treated organoids (Figures S3.5D and S3.5E). This suggests that
the neuroprotective effect of KCTD20 knockdown is dependent on exocytosis.

Protective effects of KCTD20 knockdown are mediated by lysosomal exocytosis
Inhibition of nSMase2 broadly blocks cellular exocytosis pathways by inhibiting ceramide
production
54
. To identify which specific exocytosis mechanisms mediate the effects of KCTD20
knockdown, we designed ASOs against key targets involved in membrane fusion of multivesicular
bodies (SMPD3, VAMP7)
230–232
, macroautophagy and amphisome exocytosis (ATG7,
RAB8A)
233–235
, chaperone-mediated autophagy (HSPA8)
236
, LC3-dependent extracellular vesicle
loading and secretion (NSMAF)
237
, lysosomal exocytosis (MCOLN1)
238
, and secretory autophagy
(GORASP1)
239
. ASOs were treated in combination with KCTD20 ASO and glutamate and
compared to NC5 PBS and NC5 glutamate conditions. Of the genes tested, knockdown of SMPD3
and MCOLN1 promoted a significant increase in hazard ratio and reduction in neuron survival
(Figures 3.5A and 3.5B, Figure S3.6A). The SMPD3 gene encodes nSMase2 protein, and therefore
its knockdown mimics the effect of GW4869 treatment. However, MCOLN1 specifically regulates
lysosomal exocytosis and was chosen for further validation
238
. We confirmed that the combination
of glutamate, KCTD20 ASO, and MCOLN1 ASO abolished the protective effect on neuron
60

survival of KCTD20 ASO with glutamate alone in MAPT V337M and isogenic V337V organoids
(Figure 3.5C, Figure S3.6B). Isolation of exosomes from tau-V337M organoids treated with
glutamate and NC5 or KCTD20 ASO showed that oligomeric tau, and the lysosomal marker
LAMP1, are secreted, and that KCTD20 knockdown results in significantly elevated levels of
secreted oligomeric tau and LAMP1 (Figures 3.5D and 3.5E).
The transcription factor EB (TFEB) is a master regulator of autophagy and lysosomal
biogenesis-related genes, including MCOLN1 and LAMP1
240,241
. We therefore aimed to assess
whether KCTD20 knockdown affects TFEB expression or activity. Knockdown of KCTD20 did
not affect TFEB mRNA levels (Figure S3.6C). However, we found that glutamate alone induced
a reduction in nuclear TFEB localization, which was reversed by KCTD20 knockdown (Figures
3.6A and 3.6B). Similarly, glutamate treatment promoted an increase in TFEB phosphorylation
(p-TFEB Ser142), which inhibits its transcriptional activity, and we found that co-treatment with
KCTD20 ASO decreased p-TFEB levels (Figures 3.6C and 3.6D). This data suggests that KCTD20
knockdown helps to maintain TFEB activity during excitotoxic stress, which may support neuron
survival by increasing lysosomal exocytosis to clear oligomeric tau (Figure 3.6E).

Kctd20 knockdown reduces tau pathology and improves neuron survival in vivo using MAPT
transgenic mice
We next sought to validate key phenotypes in vivo using wild-type C57BL/6J and in MAPT
P301S transgenic mice, an FTD model overexpressing humanized mutant tau
113
. To achieve
widespread ASO delivery to the central nervous system (CNS), we performed
intracerebroventricular (ICV) injection of Kctd20 ASO in wild-type mice at postnatal day 1 (P1)
as previously described, resulting in significant knockdown of Kctd20 protein (Figures S3.7A-
61

S3.7C)
242,243
. We found that negative control (NC) ASO-injected mice given a subsequent ICV
injection of 40 nmol glutamate showed increased tau phosphorylation (p-tau, Ser202/Thr205) in
the cortex at P5, while this was prevented in Kctd20 ASO-injected mice (Figures S3.7D and
S3.7E). We found a corresponding decrease in nuclear TFEB in NC ASO mice following
glutamate, while nuclear TFEB in Kctd20 ASO mice was not changed (Figures S3.7F and S3.7G).
Transgenic MAPT P301S mice accumulate significant tau pathology by 5 months with a
corresponding reduction in upper layer neuron numbers
113,244,245
. Similar to our in vitro data, we
found increased oligomeric tau staining in the cortex of untreated 6-month-old transgenic mice
relative to wild-type animals (Figures S3.8A and S3.8B). We confirmed that MAPT transgenic
mice display a neurodegeneration phenotype, evidenced by decreased numbers of NeuN-positive
cells in the cortex relative to wild-type (Figures S3.8C and S3.8D). To test whether Kctd20
knockdown could alleviate these changes, we performed ICV injection of 500ug Kctd20 or NC
ASO in 5-month-old mice as previously described (Figure 3.7A)
246
. A single ASO injection
induced significant knockdown of Kctd20 within five days, which was sustained over four weeks
until tissue was collected for assessment (Figures 3.7B and 3.7C). We found that Kctd20 ASO-
injected mice had significantly reduced levels of oligomeric tau in the cortex and hippocampus
compared to NC ASO mice (Figures 3.7D and 3.7E, Figures S3.8E and S3.8F). We also found a
reduction in p-tau following Kctd20 knockdown (Figure S3.8G). We next performed
immunostaining for TFEB and found that nuclear TFEB was significantly reduced in MAPT P301S
mice compared to wild-type (Figures S3.8H and S3.8I). When treated with Kctd20 ASO,
transgenic mice displayed increased nuclear TFEB localization, suggestive of greater TFEB
activity (Figures 3.7F and 3.7G). Importantly, we found that Kctd20 knockdown improved
survival of neurons in MAPT transgenic mice, evidenced by increased numbers of NeuN-positive
62

cells in the cortex (Figures 3.7H and 3.7I). Collectively, these data suggest that Kctd20 inhibition
can reduce tau pathology and improve neuron survival in vivo.

3.4 Discussion
Glutamate-induced excitotoxicity contributes to the pathogenesis of multiple
neurodegenerative diseases including FTD, in which the V337M mutation in MAPT is shown to
increase neuron excitability
44,45,47
. Our organoid model of glutamate treatment mimics key FTD
phenotypes such as tau oligomerization and neurodegeneration, which are enhanced in FTD
patient-derived organoids. This demonstrates the relevance of using glutamate to model aspects of
human disease and provides a platform for drug and gene target discovery with potentially broad
efficacy. Using this system, we conducted a genome-wide phenotypic screen to identify genetic
targets which could modulate excitotoxic neuron death. We found that KCTD20 inhibition
mitigates the effects of glutamate treatment in wild-type and tau-V337M organoids, in part by
clearing oligomeric tau species via lysosomal exocytosis. Additionally, we show that Kctd20
inhibition improves tau pathology and neuron survival in a transgenic mouse model of FTD.
We recently reported that tau-V337M organoids are sensitized to glutamate signaling
47
.
This study builds on our previous work to demonstrate that glutamate treatment recapitulates FTD
phenotypes in non-diseased genetic backgrounds. Glutamate has long been known to induce
excitotoxicity in neuronal cultures, and that chronic excitotoxicity contributes to
neurodegenerative diseases
45,191,193,247
. Here, we show direct evidence that glutamate contributes
to FTD disease pathogenesis, promoting oligomeric tau formation and neurodegeneration in wild-
type organoids in a dose-dependent manner. This phenocopies tau-V337M organoids, which
display enhanced neurodegeneration with glutamate and have elevated oligomeric tau levels
63

relative to isogenic controls in the absence of any treatment. Although neurofibrillary tangles
(NFTs) are pathologic hallmarks of neurodegenerative diseases including FTD, evidence suggests
that memory loss and neurodegeneration can be dissociated from NFTs
248
. Instead, tau oligomers
are hypothesized to be the more toxic species, and have been shown to accumulate in tauopathy
models (including tau-V337M) and cause synaptic dysfunction, memory loss, and neurotoxicity
in vitro and in vivo
37–39,41,210
. In our system, oligomeric tau correlates with neurodegeneration
following glutamate, providing support for its utility as a model for aspects of neurodegenerative
diseases.
Organoid models represent a physiologic upgrade over monolayer neuron cultures, and,
although they remain developmentally immature compared to adult tissue, have successfully been
implemented to study age-related degenerative diseases
47,71,121
. This is especially critical for
modeling tauopathies, with reports demonstrating that 3 dimensional cultures allow for expression
of both 3R and 4R tau
47,120
. Our organoid excitotoxicity model is scalable, allowing for large scale
screening to help address an urgent need for novel therapeutic targets. Although previous drug
targets have aimed to mitigate glutamate signaling, they either have limited efficacy or have failed
in clinical trials, possibly because directly limiting the activity of a key neurotransmitter to the
required levels would have negative consequences
202,204,205
. One such strategy to inhibit NMDA
receptors caused severe side effects including cataplexy, motor and memory deficits, and reduced
consciousness
249
. To this end, using a CRISPR interference platform we performed a phenotypic
screen to identify gene targets which could mitigate excitotoxic neuron death
163
. We show that
inhibition of KCTD20 significantly improves survival of wild-type, tau-V337M FTD, and
C9ORF72 ALS/FTD neurons following glutamate treatment, in part by reducing oligomeric tau
levels. Although FTD and ALS comprise a disease spectrum with overlapping phenotypes, the
64

primary pathology and affected regions differ with TDP-43 as the predominant pathologic protein
in up to 97% of ALS cases whereas tau and TDP-43 cases are roughly equal in FTD
22
. It is notable
that KCTD20 knockdown was also neuroprotective in a genetic background associated with
significant TDP-43 pathology, suggesting that its therapeutic effects may be applicable to a range
of excitotoxicity-associated diseases
27
. Similarly, in transgenic MAPT P301S mice, which display
elevated oligomeric tau staining and neurodegeneration compared to wild-type animals, we found
that Kctd20 knockdown improved neuron survival with a corresponding reduction in oligomeric
tau.
The KCTD family of proteins generally are soluble non-channel proteins with a common
BTB domain responsible for E3 ligase and transcriptional activity
250
. However, KCTD20 is
relatively isolated from other KCTD paralogs based on amino acid sequence identity, with its only
reported function as an allosteric regulator of Akt activity along with predicted involvement in
Akt/mTOR signaling
217,251
. We confirmed that knockdown of KCTD20 reduced Akt and mTOR
activation in glutamate-treated organoids and hypothesized that because mTOR is strongly linked
with protein clearance pathways in neurodegenerative diseases, that this may provide a link to
explain the reduction in oligomeric tau species observed with KCTD20 knockdown
252
. KCTD20
knockdown had a similar effect on neuron survival as the mTOR inhibitor rapamycin but may be
preferable as a therapeutic because KCTD20 inhibition did not decrease mTOR activity under non-
excitotoxic conditions, potentially avoiding the side effects of long-term mTOR inhibition
253
.
Interestingly, we found that alternate proteostasis stressors including MG132 and bafilomycin
increased oligomeric tau and neurodegeneration, which could be reversed by KCTD20 ASO. This
suggests that the effects of KCTD20 inhibition may not be strictly limited to excitotoxicity but
may generally serve as a strategy to reduce toxic protein aggregates. In relation to glutamate,
65

among its many physiologic functions, glutamate signaling has been implicated in drug
addiction
254
. Interestingly, a GWAS study linked KCTD20 to cocaine addiction, providing
additional evidence of its relationship to this pathway
255
. Kctd20 was also found to be upregulated
in synaptoneurosomes of alcohol-treated mice, and further study of its role in addiction would be
of interest
256
.
Using single cell RNAseq, we found that neurons with low KCTD20 expression had
differential gene expression enriched for exocytosis and secretion pathways. To test whether
exocytosis was necessary for KCTD20 knockdown to be protective, we co-treated organoids with
glutamate, KCTD20 ASO, and the nSMase2 inhibitor GW4869 to globally block exocytosis
229
.
GW4869 abolished the protective effect of KCTD20 ASO on survival of glutamate-treated
organoids and exacerbated oligomeric tau levels, suggesting that exocytosis was indeed required.
Because GW4869 blocks multiple mechanisms of exocytosis, we sequentially probed specific
pathways to determine if their inhibition alongside KCTD20 inhibition reduced neuron survival.
Of the targets tested, we found that co-inhibition of KCTD20 with SMPD3 and MCOLN1 ASOs
reduced neuron survival. SMPD3 encodes nSMase2 protein, and therefore did not provide further
clarification. However, MCOLN1 plays a critical role in lysosomal exocytosis by regulating local
Ca
2+
levels to promote membrane fusion between lysosomes and the plasma membrane
238
. The
transcription factor TFEB is a primary regulator of lysosomal exocytosis, upregulating key genes
including MCOLN1 and the lysosomal protein LAMP1 to promote clearance of proteins, including
tau
61,241
. Indeed, activation of lysosomal exocytosis via TFEB has been shown to reduce tau
pathology in vivo without causing seeding of tau aggregates, potentially via glymphatic
clearance
61,62
. We found that glutamate induced a reduction in TFEB activity based on its nuclear
localization and phosphorylation state, and that KCTD20 inhibition reversed this in vitro and in
66

glutamate-injected C57BL/6J mice. Additionally, P301S mice had reduced nuclear TFEB
localization relative to wild-type animals, which was increased with Kctd20 ASO. It is possible
that KCTD20 affects TFEB activity via its effect on Akt/mTOR, although further testing is
required to determine this
257
. Critically, we found that secreted LAMP1 and oligomeric tau in
purified exosome fractions were increased following KCTD20 inhibition, providing evidence that
lysosomal secretion is upregulated and that tau oligomers are removed from the cell in part by this
mechanism. Further experiments are necessary to demonstrate that KCTD20-mediated TFEB
activity directly enhances lysosomal exocytosis and testing is ongoing. Recent studies have found
similar results demonstrating that unconventional protein clearance mechanisms can be stimulated
to reduce the pathologic burden of aggregation-prone proteins in neurodegenerative diseases,
although the specific mechanisms of secretion demonstrate specificity to the genetic target
51
.
Collectively, we describe a human organoid model of excitotoxicity to test genetic and
chemical modifiers of injury in healthy and diseased genetic backgrounds. This model
recapitulates several key FTD phenotypes in wild-type organoids, while enhancing them in patient-
derived organoids. We show that KCTD20 inhibition is neuroprotective in non-diseased and tau-
V337M organoids, as well as in vivo using an established mouse model of FTD, in part by clearing
tau oligomers via lysosomal exocytosis. Future work will address the efficacy of KCTD20
inhibition in related neurodegenerative diseases and lysosomal storage disorders, and whether
protein clearance is specific to tau or if other disease-relevant proteins (TDP-43, α-Synuclein, Aβ)
are affected.

Limitations of the Study
This study demonstrates the relevance of using glutamate excitotoxicity to model aspects
67

of FTD pathogenesis in human cortical organoids in different genetic backgrounds but does not
fully model FTD. FTD, and other dementias, take many years to develop, and the maturation of
key cell types (neurons, microglia, etc.) and pathologies (protein aggregation, inflammation) over
this time span is not comparable to organoid cultures, which represent a neonatal state. Additional
deficiencies, including lower expression of 4R tau in organoids compared to adult humans and the
lack of key cell types such as microglia and endothelial cells, affect the comprehensiveness of the
model. Our data characterizing the increase of TFEB activity following KCTD20 inhibition
requires further studies to determine whether this is directly mediated by Akt/mTOR or by another
mechanism.

68

3.5 Figures

Figure 3.1 Glutamate induces oligomeric tau formation and neurodegeneration.

(A) Two month old SYN1::eGFP labelled organoids were immobilized using matrigel, treated with L-
glutamic acid (glutamate) or vehicle control, and imaged for 7 days to longitudinally track neuron survival.
(B) Kaplan-Meier survival analysis of SYN1::eGFP organoids treated with vehicle control, 100 μM and
5mM glutamate organoids. GFP+ neurons were tracked for 7 days to determine neuron survival (n= 100
neurons/condition; Log-Rank test). (C) representative surface images of a SYN1::eGFP-labelled neuron
treated with 5mM glutamate (scale bar, 50 µm). (D) Inter-organoid reproducibility of glutamate treatment
on neurodegeneration (2 iPSC lines; 4 organoids/line, 30 neurons/organoid). (E-G) Oligomeric tau (T22)
expression by western blot (E) in organoids treated with glutamate for 48 hours and quantification of high-
molecular weight species above (F) 75 kDa and above (G) 150 kDa (n=6-7 organoids/group; One-way
ANOVA with Dunnett’s correction). (H) Representative western blot and (I) quantification of high-
molecular weight (>150 kDa) oligomeric tau in organoids treated with 5 mM glutamate for 7 days (n=6
organoids/group; unpaired t test, two-tailed). (J) Survival of GFP+ neurons in organoids treated with
glutamate and DMSO or ionotropic glutamate receptor inhibitors (3i; Nimodipine, CNQX, MK-801)
(n=200 neurons/group; Log-Rank test).

69

Figure 3.2 A CRISPRi screen identifies KCTD20 as a modifier of glutamate excitotoxicity.

(A) 2-month NGN2-organoids stably (n=300) expressing dCas9-BFP-KRAB were transduced with a
lentiviral genome-wide sgRNA library (209,070 gRNAs (10 gRNAs/gene), 3790 non-targeting gRNAs).
Organoids were treated with 5 mM glutamate (n=150) and sgRNAs were enriched by PCR and sequenced
to determine enrichment of sgRNAs compared to vehicle-treated organoids (n=150) after 10 days. (B)
Volcano plot of protective and detrimental sgRNAs (P < 0.05) determined by MAGeCK-RRA, with most
significant protective sgRNAs highlighted. (C) Gene Ontology Molecular Function pathway enrichment of
top protective and detrimental sgRNAs. (D) dCas9-BFP-KRAB expressing NGN2-organoids were
transduced with SYN1::eGFP, KCTD20-targeting sgRNAs or non-targeting sgRNAs, and treated with
glutamate. GFP+/BFP+ neurons were longitudinally tracked for 7 days for survival. (n=120
70

neurons/condition; Log-Rank test). (F) 2 month organoids were treated with 10 µM NT or KCTD20 ASO
three days before glutamate treatment, and GFP+ neurons were tracked longitudinally over 7 days (n= 300
neurons/condition; Log-Rank test).

71

Figure 3.3 Tau-V337M organoids display enhanced tau pathology and neurodegeneration following
glutamate.

(A) Histology sections of isogenic tau-V337V and tau-V337M organoids stained for phosphorylated tau
(Ser396/Ser404; PHF-1). (B) Representative immunostaining and (C) quantification of untreated isogenic
tau-V337V and tau-V337M organoids for oligomeric tau (n=80 neurons/group; unpaired t test, two-tailed).
(D and E) Isogenic tau-V337M and tau-V337V organoids were transduced with SYN1::eGFP and treated
with 5 mM glutamate or vehicle. GFP+ neurons were tracked longitudinally for 7 days for survival. (n=120
neurons/condition; Log-Rank test). (E) 300 day organoids were treated with 10 µM NT, KCTD20 ASO, or
MAPT ASO for three days before glutamate treatment, and GFP+ neurons were tracked longitudinally over
7 days (n= 120 neurons/condition; Log-Rank test). (F) Western blot and (G) quantification of high-
72

molecular weight (>150 kDa) oligomeric tau in organoids treated with 10 µM NT or KCTD20 ASO for 3
days and then 5 mM glutamate for 7 days (n=6 organoids/group; One-way ANOVA with Tukey’s
correction).

73

Figure 3.4 Improved neuron survival following KCTD20 knockdown depends on exocytosis.

(A) Experimental schematic. 3 month tau-V337M organoids were treated with 10 µM NT or
KCTD20 ASO for 3 days followed by 5 mM glutamate for 3 and 6 days. Samples were multiplexed with
streptavadin antibody barcodes prior to single cell reaction (10X) and sequencing. (B) UMAP of single cell
74

RNAseq data by cell type (ExN= excitatory neuron; IP= intermediate progenitor; RG= radial glia; Ast=
astrocyte; Pg= progenitor; Un= undefined). (C) Cell type proportions in each experimental condition
(Fisher’s Exact test). (D) Unsupervised pseudotime analysis of ExNs from all conditions. Significant
marker genes (P<0.05) were input to Enrichr to determine defined biological processes enriched in each
state.for each state. (E) Elsevier and (F) GO Biological Processes enrichment of significantly upregulated
genes (average log 2(Fold Change)>0.25, adjusted p-value<0.05) in KCTD20-low ExNs. (G) Survival
analysis of Syn1::eGFP neurons pre-treated with NT or KCTD20 ASO followed by DMSO, glutamate, or
glutamate and 10 µM GW4869 (n=120 neurons/group; Log-Rank test).

75

Figure 3.5 Protective effects of KCTD20 knockdown are mediated by lysosomal exocytosis.

(A) Hazard ratio (Mantel-Haenszel) graphs of neuron survival following 7 days of longitudinal imaging
(n= 4 organoids/30 neurons/group; One-way ANOVA with Dunnett’s correction). (B) Organoids were
treated with 10 µM NT, KCTD20, or MCOLN1 ASO for 3 days. Kaplan-Meier survival analysis of
SYN1::eGFP neurons in ASO-organoids treated with glutamate for 7 days (n=120 neurons/group; Log-Rank
test). (C) Neuron survival in tau-V337M organoids pre-treated with 10 µM NT, KCTD20, or MCOLN1
ASO for 3 days followed by 5 mM glutamate for 7 days (n=120 neurons/group; Log-Rank test). (D-F)
Western blot (D) and quantification of LAMP1 (E) and oligomeric tau (F) from isolated exosome fraction
of NT or KCTD20 ASO tau-V337M and tau-V337V organoids treated with glutamate for 48 hours (n=3
76

wells group, 6 organoids/well; One-way ANOVA with Tukey’s correction).

77

Figure 3.6 TFEB activity is modulated by KCTD20 inhibition.

(A) Representative immunostaining and (B) quantification of nuclear TFEB levels in ASO-treated
organoids after 7 days of vehicle or 5 mM glutamate (n=40 neurons/group; One-way ANOVA with Tukey’s
E
78

correction). (C) Representative immunostaining and (D) quantification of cytoplasmic phosphorylated
TFEB (Ser142) in ASO-treated organoids following 7 days of vehicle or 5 mM glutamate (n=6
organoids/group; One-way ANOVA with Tukey’s correction). (E) Schematic of proposed mechanism for
KCTD20 inhibition.

79

Figure 3.7 Kctd20 knockdown reduces tau pathology and improves neuron survival in vivo using
MAPT transgenic mice.

(A) Schematic of experimental timeline for intracerebroventricular ASO injections. (B and C) qPCR of
Kctd20 in NT or Kctd20 ASO injected MAPT P301S mice after (B) 5 days and (C) 4 weeks (N=4-6
DAPI TFEB DAPI T22
80

mice/group; unpaired t test two-tailed). (D) Representative immunostaining and (E) quantification of
oligomeric tau in the cortex of 6 month MAPT mice 4 weeks after injection with NT or Kctd20 ASO (N=7-
8 mice/group; unpaired t test two-tailed). (F) Representative immunostaining and (G) quantification of
nuclear TFEB in the cortex of 6 month MAPT mice 4 weeks after injection with NT or Kctd20 ASO (N=7-
8 mice/group; unpaired t test two-tailed). (H) Representative immunostaining and (I) quantification of the
average number of NeuN per area in the cortex of 6 month MAPT mice 4 weeks after injection with NT or
Kctd20 ASO (N=7-8 mice/group; quantification representative of average counts across 5 300μM
2
regions;
unpaired t test two-tailed).

81

Figure S3.1 Additional gene targets from CRISPRi screen.

(A) Schematic of NGN2-organoid generation. (B) Representative immunostaining in day 10 NGN2-
organoids for MAP2, NeuN, and Brn2. (C-F) Kaplan-Meier survival analysis of SYN1::eGFP neurons in
ASO-organoids treated with glutamate for 7 days for ASOs against (C) GNG13, (D) TMEM63C, (E)
SSRP1, and (F) SLC39A8 relative to NC5 ASO (n=120 neurons/group; Log-Rank test). (G) qPCR of
KCTD20 in organoids after 72 hour treatment with NC5 or KCTD20 ASO, normalized to 18S (n=6
organoids; unpaired t test two-tailed).

82

Figure S3.2 KCTD20 inhibition inhibits AKT/mTOR activity.

(A) Representative immunostaining and (B) quantification of neuronal phosphorylated AKT (Thr308) and
total AKT in organoids treated with NT or KCTD20 ASO and vehicle or 5 mM glutamate for 7 days (n=80
neurons/group; One-way ANOVA with Tukey’s correction). (C) Representative immunostaining and (D)
quantification of phosphorylated mTOR (Ser2448) and total mTOR in neurons treated with NT or KCTD20
ASO and vehicle or 5 mM glutamate for 7 days (n=80 neurons/group; One-way ANOVA with Tukey’s
correction). Survival of SYN1::eGFP neurons treated with 5 mM glutamate with vehicle, KCTD20 ASO,
10 μM LY-294002, or 10 μM rapamycin (n=120 neurons/group; Log-Rank test). (F) Representative western
blot and (G) quantification of LC3 II-I ratio in organoids after 3 day ASO treatment followed by 6 hour
5mM glutamate, normalized to total protein (n= 5 organoids/group; One-way ANOVA with Tukey’s
correction).

83

Figure S3.3 Survival of C9ORF72 ALS/FTD neurons is improved with KCTD20 ASO.

(A) Representative western blot and (B) quantification of surface isolated NR1 in tau-V337V and tau-
V337M organoids, normalized to transferrin receptor (n= 5 organoids/group; unpaired t test two-tailed).
(C) Representative immunostaining and (D) quantification of neuronal oligomeric tau in wild-type
organoids treated with NC5 or KCTD20 ASO followed by glutamate for 7 days (n= 80 neurons/group;
One-way ANOVA with Tukey’s correction). (E) Kaplan-Meier survival analysis of SYN1::eGFP neurons
of NT ASO wild-type or C9ORF72 ALS/FTD organoids treated with vehicle or 5 mM glutamate (n=100
neurons/group; Log-Rank test). (F) Kaplan-Meier survival analysis of SYN1::eGFP neurons of glutamate-
treated wild-type or C9ORF72 ALS/FTD organoids pre-treated with NT or KCTD20 ASO (n=100
neurons/group; Log-Rank test).

84

Figure S3.4 Proteostasis stressors induce tau oligomerization and neurodegeneration.

(A) Western blot and (B) quantification of oligomeric tau, normalized to tau5, in organoids treated with
vehicle, 5 mM glutamate, 250 nM bafilomycin, 10 μM TFEB agonist TFEB-1, or 10 μM MG132 for 48
hours (n= 6-7 organoids/group; One-way ANOVA with Dunnett’s correction). (C) Neuron survival of
organoids pre-treated with NC or KCTD20 ASO followed with vehicle, 250 nM bafilomycin, or 10 μM
MG132 (n=120 neurons/group; Log-Rank test).

85

Figure S3.5 Organoid cell identity following single cell RNAseq.

(A) Representative markers used to define cell identity as described by CoDEx
(http://solo.bmap.ucla.edu/shiny/webapp/). (B) Contingency table of cell proportions per state in
pseudotime for each treatment group (Fisher’s Exact test). (C) Dot plot of representative marker genes from
GO Biological Processes exocytosis pathways. (D) Representative immunostaining and (E) quantification
of neurons following treatment with glutamate and 10 μM GW4869 (n=30 neurons/group; One-way
ANOVA with Tukey’s correction).

86

Figure S3.6 Effect of exocytosis pathway inhibition on neuron survival.
(A) Hazard ratio (Mantel-Haenszel) graphs of neuron survival following 7 days of longitudinal
imaging with glutamate, KCTD20 ASO, and ASOs against VAMP7, SMPD3, HSPA8, ATG7,
RAB8A, ATG5, NSMAF, MCOLN1 and GORASP (n= 3 organoids/30 neurons/group; One-way
ANOVA with Dunnett’s correction). Kaplain-Meier survival of tau-V337V organoids with
combinations of NC5, KCTD20, and MCOLN1 ASO with vehicle or glutamate (kgm= KCTD20 ASO +
MCOLN1 ASO + glutamate) (n=120 neurons/group; Log-Rank test). qPCR of TFEB in organoids after 72
hour treatment with NC5 or KCTD20 ASO, normalized to 18S (n=6 organoids; unpaired t test two-tailed).

87

Figure S3.7 Mouse pups injected ICV with glutamate recapitulate changes in tau and TFEB, which
is mitigated by Kctd20 ASO.

(A) Experimental schematic. (B) Representative western blot and (C) quantification of Kctd20 from
homogenized whole brain lysate, dissected into ipsilateral and contralateral hemispheres relative to ASO
injection site, normalized to Gapdh (N=5 mice/group; One-way ANOVA with Tukey’s correction). (D)
Representative immunostaining and (E) quantification of phosphorylated tau (Ser202/Thr205) in BL/6J
mice injected ICV with NC or Kctd20 ASO and vehicle or glutamate (N=5-8 mice/group; One-way
ANOVA with Tukey’s correction). (F) Representative immunostaining and (G) quantification of nuclear
TFEB in BL/6J mice injected ICV with NC or Kctd20 ASO and vehicle or glutamate (N=120
neurons/group, 20 neurons/mouse; One-way ANOVA with Tukey’s correction).

88

Figure S3.8 Tau pathology and neuron loss in adult transgenic MAPT P301S mice.

(A) Representative immunostaining and (B) quantification of oligomeric tau in the cortex of 6 month P301S
mice (N=13-14 mice/group; unpaired t test two-tailed). (C) Representative immunostaining and (D)
quantification of NeuN positive neurons in the cortex of 6 month P301S mice. Each data point
representative of average NeuN numbers across 5 300μm
2
regions (N=13-14 mice/group; unpaired t test
two-tailed). (E) Representative immunostaining and (F) quantification of oligomeric tau in the hippocampus
of 6 month P301S mice injected with NC or Kctd20 ASO (N=5-8 mice/group; unpaired t test two-tailed).
(G) quantification of phosphorylated tau (Ser202/Thr205) in the cortex of 6 month P301S mice injected
with NC or Kctd20 ASO (N=7-8 mice/group; unpaired t test two-tailed). (H) Representative
immunostaining and (I) quantification of nuclear TFEB in the cortex of 6 month transgenic mice injected
with NC or Kctd20 ASO (N=8 mice/group; unpaired t test two-tailed).

89

Chapter 4: ELAVL4, splicing, and glutamatergic dysfunction precede neuron
loss in MAPT mutation cerebral organoids
This work has been published in Cell (PMID 34314701). This work was led by Kathryn R. Bowles
with support from Maria Catarina Silva, Jacob C. Garza, Celeste M. Karch, Justin K. Ichida,
Stephen J. Haggarty, John F. Crary, Alison M. Goate and Sally Temple. Formal analysis was
conducted by Kathryn R. Bowles, Kristen Whitney, Taylor Bertucci, Jacob C. Garza, myself, Jesse
D. Lai, Justin K. Ichida, Sidhartha Mahali, Celeste M. Karch, Yiyuan Liu, Nathan C. Bowles,
Ronald E. Gordon and Susan K. Goderie. Investigation was carried out by Kathryn R. Bowles,
Maria Catarina Silva, Taylor Bertucci, Jacob C. Garza, Kevin H. Strang, Kristen Whitney,
Sidhartha Mahali, Jacob A. Marsh, Cynthia Chen, myself, Jesse D. Lai and Rebecca Chowdhurry.
Original draft written by Kathryn R. Bowles, Maria Catarina Silva and Taylor Bertucci. Data and
corresponding text for Figure 7 and Figure S7 were provided by myself and Jesse D. Lai.

4.1 Abstract
Frontotemporal dementia (FTD) because of MAPT mutation causes pathological
accumulation of tau and glutamatergic cortical neuronal death by unknown mechanisms. We used
human induced pluripotent stem cell (iPSC)-derived cerebral organoids expressing tau-V337M
and isogenic corrected controls to discover early alterations because of the mutation that precede
neurodegeneration. At 2 months, mutant organoids show upregulated expression of MAPT,
glutamatergic signaling pathways, and regulators, including the RNA-binding protein ELAVL4,
and increased stress granules. Over the following 4 months, mutant organoids accumulate splicing
changes, disruption of autophagy function, and build-up of tau and P-tau-S396. By 6 months, tau-
V337M organoids show specific loss of glutamatergic neurons as seen in individuals with FTD.
90

Mutant neurons are susceptible to glutamate toxicity, which can be rescued pharmacologically by
the PIKFYVE kinase inhibitor apilimod. Our results demonstrate a sequence of events that precede
neurodegeneration, revealing molecular pathways associated with glutamate signaling as potential
targets for therapeutic intervention in FTD.

Graphical abstract

4.2 Introduction
Frontotemporal dementia (FTD) encompasses a spectrum of disorders accounting for 5%–
6% of all dementias and 20% of cases under the age of 65
208,258
. FTD is heritable, with around
50% of cases having a family history, 10%–20% of which show autosomal dominant inheritance
because of mutations in the microtubule-associated protein tau (MAPT) gene (FTD-tau)
207,259
.
91

Pathologic studies reveal accumulation of filamentous, hyperphosphorylated tau protein (P-tau) in
cerebral cortical and hippocampal neurons and glia, and tau redistribution from axons to the
somatodendritic compartment. These changes correlate with degeneration of synapses and
neuronal loss in frontal and temporal cortices
112,260
. There is great need to identify molecular
changes and disease biomarkers that precede cell death when therapeutic intervention will likely
have the most effect.
MAPT is alternatively spliced, resulting in two major isoforms, 3R and 4R tau, defined by
exclusion or inclusion of exon 10, respectively. To date, 111 unique MAPT variants have been
identified (https://www.alzforum.org/mutations/mapt), of which 35 pathogenic mutations are
outside exon 10. This is important because little 4R tau is expressed in induced pluripotent stem
cell (iPSC)-derived models without a splice-site mutation
119,261–263
. Despite this limitation, iPSC-
based models derived from individuals with a MAPT mutation indicate molecular mechanisms
underlying tauopathies
213,214,261,264–267
. The tau-V337M mutation selected for this study is located
in MAPT exon 12, expressed in iPSC-derived neurons, and associated with FTD with abundant
neurofibrillary tangles in frontal and temporal cortices and the cingulate gyrus and atrophy
throughout the hippocampus and amygdala
33,268,269
. In iPSC-derived induced neurons, tau-V337M
disrupts neuronal activity regulation and excitability, spurring further studies in more complex
models
44
.
Brain organoids derived from iPSCs develop in culture along a trajectory mimicking key
features of fetal brain development and can be patterned toward specific brain regions affected in
tauopathy
66,67,270–272
. Increasing evidence showing that early alterations in brain development
contribute to later manifestation of neurodegenerative diseases further encourages use of iPSC-
based organoid systems to study FTD-tau
273
. Here we report characterization of over 6,000
92

cerebral organoids derived from three tau-V337M mutation carriers and respective isogenic
CRISPR-corrected lines (Table S1; Figure 1A)
117
. We show that tau-V337M organoids exhibit
earlier expression of glutamatergic signaling pathways and synaptic genes, progressive
accumulation of total and phosphorylated tau (P-tau S396), alteration of autophagy and lysosomal
proteins, formation of stress granules, and widespread changes in splicing with later selective death
of glutamatergic neurons. Finally, we demonstrate that glutamate-induced cell death in these
organoids can be pharmacologically blocked by apilimod treatment, predicted to target autophagy-
lysosomal function and glutamate receptor recycling through PIKFYVE kinase inhibition
274,275
.

4.3 Results
Selective loss of glutamatergic neurons in tau-V337M organoids
FTD-tau is associated with glutamatergic neuronal loss in frontal and temporal cortices
46
.
To determine whether this is recapitulated in cerebral tau-V337M organoids, we assessed changes
in the proportions of different neural cell types over 6 months of differentiation. Tau-V337M iPSC
lines derived from three donors and corresponding isogenic corrected (V337V) controls, totaling
seven lines were differentiated into cerebral organoids and assessed at 2, 4, and 6 months using
multiple phenotypic assays (Figure 4.1A; Table S1)
67,117
. We performed bulk RNA sequencing
(RNA-seq) on 239 individual organoids and single-cell RNA-seq (scRNA-seq) on 339 individual
organoids (>370,000 cells, ~800–1,000 cells per organoid). Oligonucleotide-tagged antibodies
against cell surface markers (cell hashing) barcoded organoid samples prior to multiplex
sequencing to reveal replicable effects
223
.
Following scRNA-seq data normalization, reduction, and clustering, automated annotation
with SingleR, using scRNA-seq expression data from the human neocortex at gestational week 17
(GW17)–GW18 as a reference, identified 16 different cell types (Figures 4.1B and 4.1C)
224,276
.
93

Transcriptional signatures in the human frontal cortex at this age correlate highly with gene
expression profiles of organoids
277
. Organoid development followed the expected temporal
changes (Figures 4.1B-4.1D; Figure S4.1A)
64,67,270,278
. At 2 months, all organoids had a similar
cell composition with a large proportion of deep-layer excitatory (ExDp2) neurons (Figures 4.1B
and 4.1C). Overtime, the proportion of upper cortical layer-enriched (ExM-U) neurons increased,
as did inhibitory neurons, astrocytes, and oligodendrocytes (all p < 2.2 × 10
−16
; Figures 4.1B-
4.1D). Although all lines showed the same overall maturation pattern, variability between lines
and individual organoids increased over time (Figures 4.1C and 4.1D; Figure S4.1A), indicating
donor and clonal effects on long-term maturation. There was no batch-specific effect on
differentiation over three replicates assessed by uniform manifold approximation and projection
(UMAP) (Figure S4.1B) and no clustering because of mutation at 2 or 4 months (Figure S4.1C).
Immunostaining of organoid sections confirmed the progressive maturation of organoids observed
by scRNA-seq (Figure 4.1E; Figures S4.1D and S4.1E).
We examined whether tau-V337M affects excitatory neuron survival, as observed in the
FTD brain
46
. Although there were no differences in neuronal proportions at 2 or 4 months, there
was a significant reduction in excitatory neurons in deep-layer (ExDp2, p = 0.004), maturing
(ExM, p = 0.003), and newborn (ExN, p = 0.0001) categories in 6-month tau-V337M organoids
relative to V337V (Figure 4.2A). These differences were validated by immunohistochemistry
(IHC) analysis, which showed a reduction in neuronal nuclear protein+ (NeuN+) neurons at 4 and
6 months (Figures 4.2B and 4.2C) and in MAP2+ neurons at 6 months (Figures S4.2A and S4.2B).
In contrast, there was no effect on interneuron or astrocyte numbers (Figure S4.2C). Differential
gene expression and Ingenuity Pathway Analysis (IPA) of tau-V337M-enriched astrocyte clusters
in scRNA-seq data revealed upregulation of interleukin-6 (IL-6) signaling (Z score = 0.54–1.46, p
94

= 2.26 × 10
−1
–1.8–10
−2
), interleukin-8 (IL-8) signaling (Z score = 0.67–1.28, p = 5.73 × 10
−4
_9.64
× 10
−5
) and neuroinflammation signaling (Z score = 0.13–3.0, p = 2 × 10
−1
-2.6 × 10
−3
) pathways
across all three isogenic pairs at 4–6 months, suggesting increased neuroinflammation in mutant
organoids (Figures S4.2D-S4.2F). These results demonstrate that tau-V337M cerebral organoids
recapitulate aspects of the selective excitatory neuron vulnerability and glial inflammatory
response observed in the human tauopathy brain
46,279
.

Early autophagy-lysosomal pathway dysfunction in tau-V337M organoids
Disruption of the autophagy-lysosomal pathway (ALP) is another pathological hallmark in
human tauopathy brain
54,55,280
. To examine whether the tau-V337M mutation was associated with
early disruption of this pathway (Figure 4.2D), we used electron microscopy (EM) to visualize
morphological features of ALP vesicles in 2-month organoids (Figures 4.2E and 4.2F). Lysosome-
related multi-membrane lamellar bodies were rare in healthy neurons (Figure 4.2E) but more
frequent in tau-V337M neurons, including those showing early signs of apoptosis (Figure 4.2F),
suggesting ALP dysfunction. The key ALP markers LAMP1 and CTSD were increased
significantly in tau-V337M organoids compared with isogenic controls at 2 months (Figures 4.2G
and 4.2I), indicating alterations in lysosomal degradation and proteolytic cleavage of pro-CTSD.
High-molecular-weight (HMW) ubiquitinated species were increased significantly in tau-V337M
organoids at 2 months, suggesting disrupted degradation and accumulation of poly-ubiquitinated
proteins and, thus, increased proteostasis stress in mutant organoids. In contrast, pro-CTSD was
increased significantly at 6 months in the absence of increased active CTSD, whereas
sequestosome 1 (p62) and microtubule-associated protein 1A/1B-light chain 3 (LC3-II) were
reduced significantly at the same time point (Figures 4.2H and 4.2I), suggesting defects in
proteolytic cleavage and activity.
95

IHC of 2-month cerebral organoids revealed LAMP1 and p62 primarily in neurons, similar
to the staining pattern in the brain from an adult individual, indicating that the predominant ALP
dysfunction is neuronal (Figures S4.3A and S4.3B), consistent with increased lamellar bodies
observed in neurons by EM (Figures 4.2E and 4.2F). Notably, we did not observe significant
dysregulation of ALP in our transcriptomics data, indicating dysfunction at the protein level. These
findings demonstrate that iPSC-tau-V337M organoids phenocopy aspects of ALP dysfunction
seen in the FTD brain, which may be triggered by expression of mutant tau protein in neurons
early in disease development.

V337M organoids exhibit increased tau and P-tau and degeneration of vulnerable cortical layers
Because tau accumulation is a key hallmark of FTD-tau, we examined this in mutant
organoids over time. Tau-V337M organoids showed no genotype-dependent differences at 2
months (Figure 4.2J), but a significant increase in total tau and the P-tau S396/total tau ratio
emerged between 4 and 6 months compared with isogenic controls (Figures 4.2J-4.2L). The
increased tau burden with age mirrors prior observations in 2D iPSC-derived neuronal models and
in the human V337M brain
33,118,214,261,266,268,281,282
. Although expression of 4R tau was low, it
increased in tau-V337M and V337V organoids with age (Figures S4.3C and S4.3D), with no
consistent differences between genotypes over time.
RNA-seq data analysis revealed that MAPT mRNA expression was higher in tau-V337M
organoids compared with V337V at 2 months; however, this was no longer observed at 4 months
and was reversed at 6 months (Figure S4.3E), potentially reflecting neuron loss (Figures 4.2A-
4.2C). Hence, increased tau protein at 6 months (Figure 4.2L) is likely due to tau accumulation
and not increased expression. The scRNA-seq data revealed that MAPT expression was highest in
excitatory glutamatergic neurons (Figures 4.3A-4.3C, Figure S4.3F), particularly of cortical layers
96

VI-V (ExDp2; Figure 4.3C). Moreover, MAPT expression was significantly higher in tau-V337M
ExDp2 neurons compared with V337V controls at every time point (2 months, p = 6.49 × 10
−23
; 4
months, p = 1.88 × 10
−18
; 6 months, p = 3.27 × 10
−08
) and in ExDp1 and ExM-U at 4 months
(ExDp1, p = 1.16 × 10
−07
; ExM-U, p = 2.82 × 10
−04
; Figure 4.3C). In contrast, there was no
difference in MAPT expression in inhibitory interneurons (Figure S4.3G). Notably, this links high
expression of MAPT and mutant tau to later selective vulnerability of the same neuronal subtypes.
In the tau-V337M human brain, neurofibrillary tangles follow a “tram track” pattern with
stronger staining in cortical layers II and V, which appear to be particularly vulnerable to selective
neuronal loss; hence, we investigated this in the organoid model
33,268,283
. Immunostaining revealed
higher P-Tau S202/T205 (AT8) and P-Tau S396/S404 (PHF1) in V337M organoid neurons
expressing MEF2C (predominantly upper layers II-IV) or BCL11B/CTIP2 (layer V; Figure 4.3D),
corroborating the tau pathology in V337M human brain tissue
33,268,284
. scRNA-seq data analysis
revealed significantly fewer glutamatergic neurons expressing MEF2C and BCL11B/CTIP2 in
V337M versus V337V organoids at 6 months (Figures 4.3E and 4.3F), supported by
immunostaining analysis (Figure 4.3G). Hence, tau-V337M organoids replicate the cortical layer
vulnerability observed in the human FTD brain.

Early neuronal maturation and upregulation of synaptic signaling pathways in mutant glutamatergic
neurons
To identify early changes underlying neuronal dysfunction prior to tau aggregation and
neurodegeneration, we conducted a gene set enrichment analysis (GSEA) on differentially
expressed genes at 2, 4, and 6 months in the RNA-seq data (Figures S4.4A-S4.4G and S4.5A-
S4.5H). In mutant organoids, we observed upregulation of numerous synapse-related pathways
compared with isogenic controls at 2 months (Figure S4.4A, bold text) but downregulation
97

between 2 and 6 months (Figure S4.4B). Further inspection of these pathways emphasized
glutamatergic receptor genes with non-monotonic patterns of early upregulation and late
downregulation in mutant compared with control organoids, including GRM5 (p = 1.25 × 10
−04
,
log2 fold change [FC] = 1.08), GRIN1 (p = 3.89 × 10
−03
, FC = 0.47), and GRM4 (p = 6.9 × 10
−03
,
FC = 0.64) (Figure 4.4A, Figure S4.4G).
Following our findings of altered synaptic signaling pathways and loss of glutamatergic
neurons over time, we examined excitatory neuronal populations in scRNA-seq data (ExDp2,
ExDp1, ExM, and ExM-U). For each isogenic set, excitatory neurons were re-clustered, and
V337M-enriched clusters were identified (FC > 1.5; Figures 4.4B and 4.4C) and assessed for
differential gene expression. Tau-V337M enriched clusters of 2-month neurons showed
downregulation of pathways prominent in immature cells, such as differentiation of neuroglia
(Z score = −0.274 to −2.175, p = 3.78 × 10
−08
–4.67 × 10
−11
) and differentiation of neurons (Z score
= −1.131 to −2.606, p = 1.74 × 10
−09
_1.39 × 10
−20
) in all three donor lines (Figure 4.4D). In
contrast, and consistent with the bulk data, pathways associated with neuronal maturation and
synaptic signaling, such as growth of axons (Z score = 0.239–1.482, p = 9 × 10
−06
−2.3 × 10
−13
),
dendritic growth/branching (Z score = 0.465–1.608, p = 2.37 × 10
−09
−5.05 × 10
−07
), and long-term
potentiation (Z score = 0.102–2.775, p = 4.1 × 10
−11
−6.91 × 10
−05
) were upregulated at 2 months
(Figure 4.4D) and downregulated at 6 months in V337M-enriched clusters (Figure 4.4E).
To further characterize temporal gene interactions, we used the scRNA-seq data to carry
out pseudobulk network analysis on differentially expressed genes between tau-V337M and
V337V glutamatergic neurons over time and identified several gene communities (Figure 4.4F).
Gene Ontology (GO) enrichment revealed that the largest community, C_7, was enriched
significantly for pathways such as neurogenesis, nervous system process, regulation of cell
98

differentiation, and synaptic signaling (all false discovery rate [FDR] < 0.01) and contained 9
glutamatergic receptor genes, validating that dysregulation of these genes and pathways is a
dominant transcriptional effect of tau-V337M expression over time. C_7 interacted with
communities related to cellular structure and organization, including cellular component
morphogenesis (C_9) and cytoskeleton organization (C_11). Several communities were enriched
for metabolic processes, suggesting that mutant tau may impair neuronal metabolic homeostasis
over time (Figure 4.4F).
We next carried out pseudotime analysis to order cells by differentiation state (Figures
S6A-S6E)
225,226
. V337M-enriched modules occurred early in pseudotime, encompassing ExDp2
neurons, indicating aberrant gene expression networks early in development (Figure S4.6F). Of
the top 3,000 variable genes across excitatory neurons, 391 had significantly different trajectories
in mutant neurons compared with isogenic controls; GO analysis revealed significant enrichment
of glutamatergic signaling pathways, including glutamate binding, glutamatergic synapse,
clathrin-sculpted glutamate transport vesicle, and glutamate neurotransmitter release cycle (all p <
0.05). We then clustered significantly different gene trajectories to identify those with similar
expression patterns (Figure 5A). Of the 27 genes associated with enriched glutamatergic GO
pathways, 11 were in cluster 2, including GRIA2 and MAPT (Figure 4.5A-4.5C). This cluster was
characterized by earlier upregulated gene expression in tau-V337M neurons relative to V337V,
which converged at later pseudotime points (Figures 4.5B and 4.5C). GO enrichment of cluster 2
genes showed enrichment for neuron projection (p = 3.63 × 10
−15
), synapse (p = 1.34 × 10
−13
), and
axon (p = 2.14 × 10
−13
) cellular compartments (Figure 4.5D) as well as nervous system
development (p = 5.35 × 10
−13
) and synapse organization (p = 7.1 × 10
−12
) molecular functions.
We also found significant enrichment of neural differentiation pathways in cluster 1, including
99

forebrain neuron differentiation (p = 8.762 × 10
−4
), forebrain generation of neurons (p = 1.937 ×
10
−3
), and nervous system development (p = 4.052 × 10
−3
), with early increased expression similar
to cluster 2 (Figure 4.5A, Figure S4.6G).
We noted that a major regulator of glutamatergic cell fate and signaling, ELAVL4, was also
present in cluster 2 (Figures 4.5B and 4.5C). ELAVL4 encodes a neuronal specific RNA binding
protein (RBP) associated with neural development, synaptic plasticity, splicing, glutamate receptor
activation and glutamate levels, and multiple neurological diseases
285–293
. Given these functions,
we identified ELAVL4 as a potential regulator of accelerated glutamatergic neuron maturation.

Increased ELAVL4 expression in mutant organoids and aberrant splicing of synaptic genes
Differential splicing analysis (Figures 4.5D-4.5F, Figure S4.6H) showed a dramatic
increase in the number of differentially spliced junctions in tau-V337M compared with tau-V337V
organoids, from 190 at 2 months to over 5,000 at 6 months (Figure S4.6H)
294
. GO analysis of
differentially spliced genes (DSGs) at 6 months revealed a significant enrichment in several
synaptic pathways (Figure 4.5D). Exon 5 (chromosome 9 [chr9]: 137145902–13749009) of the N-
methyl-D-aspartate (NMDA) receptor gene GRIN1 (log likelihood ratio [loglr] = 12.6, p = 2.76 ×
10
−3
) was more frequently excluded in V337M organoids compared with V337V (differential
percent spliced in [dPSI] = −0.06; Figure 4.5E), and exon 14 (chr4: 157360143–157361538) of
the β-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor gene GRIA2 (loglr
= 27.18, p = 1.96 × 10
−6
) was more frequently included in V337M organoids (dPSI = 0.038; Figure
4.5F). Therefore, although the V337M mutation did not affect MAPT splicing, it did affect the
regulation of splicing in pathways associated with neuronal and synaptic maturation that may
contribute to glutamatergic neuronal vulnerability.
100

When examining potential splicing regulators, we noted that neuronal ELAVL genes
regulate RNA splicing in mouse brain and human neuroblastoma cells and control glutamate levels
and neuronal excitability
288,290
. Expression of ELAVL4 family members is enriched in deep
cortical layers in the human brain, and consistent with this, ELAVL4 is enriched in deep-layer
organoid neurons with higher expression in tau V337M compared with V337V (ExDp2 and
ExDp1; Figure 4.5G)
295
. ELAVL4 may therefore be relevant to the susceptibility of this neuronal
population, and its abnormal expression could contribute to aberrant splicing.
To assess the potential contribution of ELAVL4 expression to altered splicing regulation of
synaptic genes in tau-V337M organoids, we determined whether there was an intersection between
our DSGs and transcripts bound to neuronal ELAVL proteins (nELAVL) in the human brain
detected by RNA immunoprecipitation sequencing (RIP-seq)
290,296
. The proportion of DSGs
overlapping with nELAVL-bound RNA increased by more than 3-fold with age, revealing over
50% of DSGs as potential ELAVL4 cargo (Figures 4.5H and 4.5I). GO enrichment of these
potential cargo genes revealed processes associated with RNA splicing (p = 2.4 × 10
−08
, FDR =
0.2.2 × 10
−06
) and neuron differentiation (p = 2.1 × 10
−24
, FDR = 1.4 × 10
−20
). Semantic analysis
of the significant GO categories (FDR < 0.1) showed enrichment of neuronal differentiation, cell
projection organization, and other categories, further supporting the concept that
aberrant ELAVL4 expression affects several neuronal functions in tau-V337M organoids (Figure
4.5J).

ELAVL4 binds the MAPT 3’ UTR and co-localizes with tau and stress granules in mutant organoids
Pathological accumulation of tau and RBPs in stress granules in tau-P301S mice
contributes to mislocalization of RNAs and splicing components to the cytosol
297,298
. Mutant tau
may therefore cause cellular changes that impair ELAVL4 function, such as recruitment to stress
101

granules, affecting its regulation of glutamatergic gene expression and splicing
289,290
. Furthermore,
studies of murine and HEK293 cells report that ELAVL4 binds and localizes the MAPT transcript
and regulates its local translation; therefore, disruption of ELAVL4 function by mutant tau may
further promote aberrant MAPT expression and tau mislocalization, observed with disease
299–301
.
Hence, we investigated the interactions between ELAVL4 and the MAPT transcript and tau protein
and the incidence of stress granule formation in tau-V337M and tau-V337V organoids over time.
RIP showed that ELAVL4 binds MAPT RNA in tau-V337V and V337M organoids (Figure
4.6A). scRNA-seq data analysis revealed a significant increase in the stress granule
genes TIA1 and G3BP1 in all glutamatergic neuronal subtypes in tau-V337M compared with
V337V (Figure 4.6B). Immunostaining and western blot analyses also showed elevated G3BP1
protein in 2-month tau-V337M organoids (Figures 4.6C-4.6F), corroborating the transcriptional
analysis and confirming that mutant tau organoids are more susceptible to stress than controls. We
found co-localization of G3BP1 with ELAVL4 in tau-V337M neurons (Figure 4.6G), indicating
sequestration of ELAVL4 in granular structures, as reported previously in amyotrophic lateral
sclerosis (ALS) models
302
. Furthermore, we observed co-localization of tau with ELAVL4 and
TIA1 or G3BP1 (Figures 4.6H and 4.6I). These findings support a mechanism whereby the mutant
tau transcript and protein interact with ELAVL4 to promote stress and expression of stress granule
proteins that contribute to ELAVL4 mislocalization and impaired function in glutamatergic
neurons.

Excitotoxic stress vulnerability and neuronal death in V337M organoids is reversed by apilimod
Because our transcriptomics analyses showed that tau-V337M organoids display early
increased expression of glutamatergic signaling components, we examined susceptibility to
glutamate stimulation. We used 4- and 12-month organoids to model advancing disease and
102

established a method for longitudinal tracking of individual neurons by transduction with
a Synapsin1::GFP lentivirus and daily imaging (Figure 4.7A)
275
. Viability of labeled cells at the
end of the experiment was assessed by co-staining with DRAQ5 (Figure S4.7A). In the absence of
excess glutamate, neurons in control and tau-V337M organoids survived equally well (Figure
4.7B, Figure S4.7G). In contrast, repeated treatment with 5 mM glutamate triggered a more rapid
and significant loss of tau-V337M neurons relative to isogenic controls (p < 0.0001; Figures 4.7C
and 4.7D, Figures S4.7B, S4.7C, S4.7H, and S4.7I). These findings were recapitulated in three
isogenic pairs, demonstrating reproducibility of the phenotype (Figure 4.7E). Importantly, co-
treatment of 4-month organoids with selective inhibitors of ionotropic glutamate receptors (3i)
significantly rescued survival of isogenic tau-V337V (p = 0.005) and tau-V337M (p < 0.0001)
neurons, demonstrating that cell death was driven specifically by excitotoxicity (Figures 4.7F-
4.7H, Figure S4.7D). Thus, neurons in tau-V337M organoids were more sensitive to glutamate-
induced toxicity than neurons in control organoids.
PIKFYVE is a lipid kinase that regulates endolysosomal trafficking by converting
phosphatidylinositol 3-phosphate (PI3P) into phosphatidylinositol-3,5-bisphosphate
(PI3,5P2; Figure 4.7F)
303
. Small-molecule inhibition of PIKFYVE (e.g., apilimod) can prevent
recycling of receptors back to post-synaptic densities and protect against NMDA-induced
excitotoxicity in vitro and in vivo (Figure 4.7F)
275
. We hypothesized that PIKFYVE inhibition
may rescue glutamate-induced neuronal loss in tau-V337M organoids (Figure 4.7F). To test this,
we performed longitudinal tracking of Synapsin1::GFP-labeled neurons with or without 10 μM
apilimod treatment. Apilimod fully rescued the increased cell death in neurons of tau-V337M
cortical organoids in response to excess glutamate (p < 0.0001) (Figures 4.7G and 4.7H, Figures
S4.7J-S4.7L). We did not observe any change in total tau or P-tau protein levels following
103

treatment, indicating that the rescue conferred by apilimod was not a result of tau lowering (Figures
S4.7E and S4.7F). To confirm that the effect was via PIKFYVE, we used an antisense
oligonucleotide (ASO) targeting PIKFYVE to directly suppress gene expression (Figures 4.7I-
4.7K). Compared with the negative control (NC), PIKFYVE ASO treatment significantly
improved survival in mutant tau-V337M (p < 0.0001) but not tau-V337V neurons (Figures 4.7J
and 4.7K). Our results reveal that early deficits in the glutamatergic neuronal network can be
detected in cortical organoids derived from iPSCs from individuals with FTD and that vulnerability
to excitotoxicity can be blocked pharmacologically.

4.4 Discussion
We have characterized a 3D cerebral organoid model of FTD using iPSC lines from three
donors with the tau-V337M mutation and isogenic corrected controls to identify temporal changes
leading to neurodegeneration. This model exhibits progressive accumulation of total tau and P-tau,
glial inflammation, impaired autophagy function, and, later, specific loss of glutamatergic neurons.
Upregulation of glutamatergic signaling pathways, increased ALP markers, and splicing changes
are seen in 2-month mutant neurons preceding cell death. We showed that ELAVL4 protein
directly binds MAPT RNA and co-localizes with tau. Upregulated expression of ELAVL4 at 2
months and mislocalization of ELAVL4 with G3BP1-positive stress granules suggests a
mechanism by which mutant tau may lead to aberrant expression and function of this RBP.
Additionally, we show that these abnormalities lead to neuronal dysfunction and vulnerability to
excitotoxicity. Hence, we uncovered a time course of molecular changes in critical pathways
associated with MAPT mutation that result in preferential deep cortical layer glutamatergic
neuronal death.
104

Given that organoid models do not accurately reflect adult aging, it is interesting that we
observed neurodegeneration. This may be due to model-associated stress on a vulnerable neuronal
population contributing to accelerated neuronal death
122
. Indeed, we observed increased stress
granules in tau-V337M organoids compared with isogenic controls, also observed in mouse tau-
P301L brain
297
. Expression of tau-V337M resulted in progressive accumulation of total tau and P-
tau S396 as organoids aged, as seen in human FTD brain
268,269,304
. Furthermore, ALP markers
increased at 2 months in tau-V337M organoids, consistent with early impaired function and
corroborating increased LAMP1 and accumulation of autophagic vesicles in the human brain and
models of tauopathy
55,280,305–307
. Interestingly, by 6 months, LC3II and p62 levels were reduced
significantly in tau-V337M organoids, suggesting impairments in autophagosome/phagolysosome
formation and reduced proteolysis. Differences in ALP markers between 2 and 6 months may
reflect proteolytic stress and neuronal dysfunction as well as neuronal loss with time. Because ALP
impairment contributes to pathological accumulation of tau, it is likely that ALP dysfunction
associated with mutant tau further contributes to tau accumulation
54,280,308
.
Tau neurofibrillary tangles occur primarily in cortical layers II and V in the tau-V337M
brain, and layer V neuronal subsets preferentially die
33,268,309
. We found that MAPT expression was
highest in deep-layer glutamatergic excitatory neurons encompassing layer V and more substantial
loss of deep cortical neurons at 6 months in tau-V337M organoids, suggesting that
high MAPT expression may underlie selective neuronal vulnerability, but with longer culture
periods we may see increased loss of later-born upper-layer cells.
Our studies point to major alterations in glutamatergic signaling pathways associated
with MAPT mutation. Glutamate excitotoxicity is the predominant cause of cerebral
neurodegeneration
46,310
. Human clinical studies of FTD and tau-V337M animal models suggest
105

impairments in glutamatergic circuits and signaling
311–314
. We show early upregulation of these
pathways, consistent with electrophysiological evidence of advanced synaptic maturation and
excitability in tau-P301L, N279K, and V337M MAPT mutation iPSC neurons in 2D culture and
with increased seizure susceptibility in individuals with FTD early in disease
44,261,315
. Premature
synaptic maturation and glutamatergic signaling likely predispose neurons to dysfunction and
excitotoxicity, resulting in later synaptic loss and neurodegeneration, and may be common across
different MAPT mutations.
Alternative splicing is crucial for synaptic maturation
316
. We observed splicing
dysregulation in tau-V337M organoids in genes converging on synaptic signaling pathways and
increased stress granule markers, consistent with aberrant splicing processes
297,298,317
. In the tau-
P301S mouse, aggregation of RBPs with tau in stress granules and the resulting alterations in
splicing converge on synaptic transmission pathways, similar to tau-V337M organoids
318
. These
mice exhibit increased inclusion of exon 14 of the AMPA receptor subunit GRIA2, also observed
in tau-V337M organoids, which can cause an excitatory phenotype by slower desensitization of
AMPA receptors
318–320
. We also identified increased exclusion of GRIN1 exon 5 in tau-V337M
organoids, associated previously with overproduction of excitatory synapses in layer V pyramidal
neurons in adult mice, resulting in seizure susceptibility, which may contribute to the cortical layer
vulnerability observed in our model and in FTD brains
321
.
ELAVL4 is selectively expressed in neuronal populations vulnerable to cell death in tau-
V337M organoids, consistent with its reported expression in the brain
287,322
. ELAVL4 expression
decreases self-renewal of neural progenitor cells and promotes deep-layer glutamatergic neuronal
differentiation
289,322,323
. Our pathway analysis of mutant-enriched glutamatergic neuron clusters
showed downregulation of neuronal differentiation pathways at 2 months and that neuronal
106

differentiation pathways were accelerated in tau-V337M neurons over pseudotime, supporting the
assertion that early ELAVL4 expression promotes neuronal maturation. ELAVL4 regulates RNA
splicing, glutamate levels, and neuronal excitability and binds to the glutamatergic
receptor GRM5 and other genes within the long-term potentiation (LTP) pathway, which were
upregulated in tau-V337M organoids
286,288,290,301
.
Here we demonstrate that ELAVL4 likely binds MAPT RNA at the 3′ UTR and exonic
sites. Interestingly, ELAVL4 binds the 3′ UTR of MAPT RNA in rat primary neurons and in mouse
P19 cells, where it has been proposed to regulate MAPT stability and translation, contributing to
normal tau localization and neuronal polarity
299–301
. We observed ELAVL4 co-localized with tau
protein and the stress granule markers TIA1 and G3BP1. Tau influences stress granule formation
in neurons, and tau-TIA1 interaction can lead to formation and stabilization of toxic tau
oligomers
324
.
Given its pleiotropic functions, our observation of perturbed ELAVL4 expression and
localization could contribute to several phenotypes observed in tau-V337M organoids, including
aberrant MAPT/tau expression, early neuronal maturation, aberrant glutamate signaling, and
dysregulated splicing. Additionally, dysfunctional proteostasis may result in increased levels of
tau and ELAVL4 because of impaired protein clearance, promoting their cytosolic accumulation.
Dysregulation of ELAVL4 may not be restricted to FTD-tau; ELAVL4 is a target of FUS activity,
co-localizes with FUS in cytoplasmic speckles and stress granules, and is present in TAR DNA-
binding protein 43 (TDP-43) inclusions
302,325
. ELAVL4-mediated splicing dysregulation resulting
from its mislocalization and sequestration to stress granules may therefore be a shared mechanism
unifying FTD-tau with other familial forms of FTD.
We demonstrate that susceptibility to glutamate-induced neuronal death in tau-V337M
107

neurons can be blocked by treatment with the PIKFYVE inhibitor apilimod and through
knockdown of PIKFYVE mRNA using an ASO. It has been proposed that apilimod reduces
glutamatergic receptor expression and electrophysiological activity by preventing RAS-associated
binding protein (RAB)-dependent recycling of the receptors back to the cell surface
326
. In addition,
PIKFYVE inhibition increases the number of EEA1-positive endosomes and LAMP1-positive
lysosomes and improves proteostasis in neurons
275,327
. Therefore, PIKFYVE inhibition may rescue
glutamate-induced neurodegeneration by correcting ALP dysfunction, increasing turnover of
misfolded tau, and favoring elimination of internalized NMDA and AMPA receptors over
recycling back to the synapse. Importantly, humans and mice haplodeficient for PIKFYVE are
normal, and apilimod has shown good tolerability in phase I and II clinical trials, indicating
potential therapeutic value
328,329
.
Temporal analysis of human organoid models has revealed early pathological events in
neurodegeneration. In our working model, the MAPT mutation results in accumulation of mutant
tau, which alters glutamatergic synaptic signaling via two mechanisms: first by altered splicing
and homeostasis of glutamatergic signaling genes driven in part by
dysregulated ELAVL4 expression and function because of sequestration in stress granules, and
second by impaired proteostasis, preventing recycling of receptors away from the synapse and
promoting further tau accumulation. Both mechanisms result in increased susceptibility to
excitotoxicity. Although these changes are initially accommodated by plasticity, over time they
result in glutamatergic neuron death. Our discovery that PIKFYVE inhibition prevents selective
glutamatergic cell death encourages further study of the mechanism as a therapeutic strategy in
FTD.

108

Limitations of the study
This study demonstrates the value of iPSC-derived forebrain organoid models to
investigate mechanisms of FTD neurodegeneration, but several outstanding questions remain.
Given the low 4R tau expression in these organoid models, additional effects of the mutant 4R
protein may be missed. The generalizability of these findings to other MAPT mutations and to
sporadic tauopathies remains to be elucidated. It would be of interest to include microglia in the
model, given their contribution to tau pathology, spread, and synaptic degeneration
330
. Our data
characterizing glutamatergic signaling in tau-V337M organoids require additional validation by
comprehensive electrophysiological assessment to confirm our hypothesized mechanism. Future
studies are needed to determine the relative contribution of the MAPT mutation-associated changes
we identified.

109

4.5 Figures

Figure 4.1 Cerebral organoids exhibit similar differentiation patterns as developing fetal brains.

(A) Experiment summary schematic.
(B) UMAP of scRNA-seq data at 2, 4, and 6 months by cell type. Ast, astrocytes; ExDp1, excitatory deep
layer 1; ExDp2, excitatory deep layer 2; ExM, maturing excitatory; ExM-U, maturing excitatory upper
enriched; ExN, newborn excitatory; Glia, unspecified glia/non-neuronal cells; InCGE, interneurons caudal
ganglionic eminence; InMGE, interneurons medial ganglionic eminence; IP, intermediate progenitors;
OPC, oligodendrocyte precursor cells; oRG, outer radial glia; PgG2M, cycling progenitors (G2/M phase);
110

PgS, cycling progenitors (S phase); UN, unspecified neurons; vRG, ventricular radial glia.
(C) Cell type proportions (%) per line at 2, 4, and 6 months.
(D) Cell type proportions (%) for individual organoids over time. Linear model, ***p < 0.001.
(E) Schematic of organoid maturation and neural cell layering (left) and marker visualization (right).
Confirmation of dorsal forebrain progenitors at 20 days: PAX6, SOX2, FOXG1, and Nestin; proliferation
marker Ki67; absence of SOX10. 2 months: increased MAP2ab, β-III-tubulin neurons; deep-layer
glutamatergic neurons TBR1, BCL11B/CTIP2; early glia S100β; few upper layer neurons SATB2+. 4–6
months: few progenitors (SOX2 and PAX6); deep- and upper-layer neurons (BRN2, MEF2C, and SATB2);
GFAP+ Ast and Calbindin+ interneurons; robust tau and NeuN; expression of vGLUT1+ and pre- and post-
synaptic markers SYN1 and HOMER1, respectively; white arrows indicate adjacent boutons. Scale bars,
100 μm unless otherwise indicated.

111

Figure 4.2 Tau-V337M organoids exhibit neuronal loss, early autophagy disruption, and progressive
tau accumulation.

(A) Proportion of glutamatergic neurons (ExDp2, ExM, and ExN) per organoid at 2, 4, and 6 months. Linear
model,
∗∗
p < 0.01,
∗∗∗
p < 0.001.
(B and C) Imaging and quantification of neuronal density by NeuN+ over time in tau-V337M and isogenic
V337V organoids. Mann-Whitney test,
∗
p < 0.05. Scale bars, 250 μm (insets) and 50 μm.
(D) Schematic of the ALP and key markers.
(E and F) Electron photomicrographs of neurons in 2-month-old tau-V337V (E) and V337M (F) organoids.
Lamellar bodies are indicated by red arrows. Scale bars, 50 μm (E) and 5 μm (F).
112

(G–I) Western blot and densitometry quantification of ALP markers in tau-V337M and isogenic organoids
at 2 (G) and 6 months (H). Relative densitometry ± SEM. Unpaired t test,
∗
p ≤ 0.01,
∗∗∗
p ≤ 0.0001; n = 3
organoids per group.
(J–L) Western blot and densitometry quantification of total tau and P-tau S396 levels in tau-V337M and
isogenic V337V organoids at 2 (J), 4 (K), and 6 (L) months. Bars represent mean total tau densitometry or
P-tau/total tau in mutant organoids (%) relative to isogenic controls (100%) ± SEM. Two-tailed unpaired t
test,
∗
p ≤ 0.01,
∗∗
p ≤ 0.001,
∗
p ≤ 0.0001; ns, non-significant; n = 9 per group from 3 independent
experiments.

113

Figure 4.3 Tau-V337M organoids reveal loss of deep- and upper-layer glutamatergic neurons.

(A and B) Expression of MAPT (A) and glutamatergic neuronal subtypes (ExDp1, ExDp2, ExM, and ExM-
U) (B) projected onto scRNA-seq UMAPs at 2, 4, and 6 months.
(C) Proportion of MAPT-expressing glutamatergic neuronal subtypes over time by mutation. Expression is
scaled within each time point. Dot size, proportion of MAPT-expressing cells; color
depth, MAPT expression level. Values: differential gene expression p value adjusted by model-based
analysis of single-cell transcriptomics (MAST) general linear model comparisons of differential expression.
(D) BCL11B/CTIP2 and MEF2C in tau-V337M (right) and isogenic V337V (left) 6-month organoids
colocalized with P-tau S202/T205 (AT8) and P-tau S396/S404 (PHF1) staining. Scale bar, 10 μm.
(E and F) Proportion of V337M and V337V ExDp2 neurons expressing the layer V
marker BCL11B/CTIP2 (E) or ExM-U neurons expressing the layer II–IV marker MEF2C (F) at each time
point; values: proportion of cells expressing each gene. MAST general linear model,
∗
p < 0.05
∗∗
p <
114

0.01
∗∗∗
p < 0.001 between V337M and V337V neurons. Shown are UMAPs of gene expression in ExDp2
neurons (E) or ExM-U neurons (F) at each time point.
(G) Time-course image quantitative analysis of BCL11B/CTIP2+ neurons at 2, 4, and 6 months normalized
to DAPI. n ≥ 3 organoids from 3 separately generated organoid batches (representative image shown in D).
n = number of organoids. One-way ANOVA, Tukey post hoc test,
∗
p < 0.05,
∗∗∗∗
p < 0.0001.

115

Figure 4.4 Tau-V337M organoids exhibit early neuronal maturation and upregulation of synaptic
signaling pathways.

A) Expression and connectivity of glutamatergic receptor genes and MAPT at 2 months and 2–6 months.
Red, upregulation in tau-V337M organoids compared with isogenic V337V; green, downregulation; depth
of color, extent of expression fold change.
(B) UMAPs of glutamatergic neurons for each isogenic pair colored by mutation (top) and age (bottom). 2-
month V337M-enriched clusters are indicated by black arrowheads, and 6-month V337M-enriched clusters
are indicated by gray arrowheads.
(C) UMAPs in (B) colored by Seurat cluster.
116

(D and E) Z scores for enriched pathways derived from IPA for V337M-enriched 2-month (D) and 6-month
(E) glutamatergic neuronal clusters (C) for each isogenic pair.
(F) Network analysis constructed from significantly differentially expressed genes over time between tau-
V337V and tau-V337M glutamatergic neurons following pseudobulk analysis of scRNA-seq data.
Communities (C_) are labeled with ID number in bold, with the number of genes in parentheses and the
most frequent parent GO term following GO enrichment and semantic similarity analysis.

117

Figure 4.5 Accelerated glutamatergic gene and ELAVL4 expression precedes aberrant splicing in
V337M neurons.

(A) Expression of genes with significantly differential trajectories over pseudotime in tau-V337M versus
tau-V337V glutamatergic neurons by spline regression model. Trajectories grouped by unsupervised
hierarchical clustering are centered across genes. Genes in significantly enriched glutamatergic signaling
pathways are highlighted in cluster 2.
(B) Comparison of cluster 2 pseudotime trajectories in tau-V337M and tau-V337V glutamatergic neurons.
Dashed lines highlight the central region of pseudotime, where gene expression differs between mutant and
control cells.
118

(C) Trajectories of average MAPT, glutamatergic pathway gene NSG1, and ELAVL4 expression in tau-
V337M and tau-V337V glutamatergic neurons over pseudotime. Adjusted p value for statistical comparison
(spline regression) of trajectories is shown in the bottom right corner.
(D) GO pathways enriched for DSGs between 6-month-old tau-V337M and tau-V337V organoids.
(E and F) Leafcutter analysis of differentially spliced intron clusters in the glutamatergic receptor
genes GRIN1 (E) and GRIA2 (F). Exons, black boxes. Red band thickness and inserted values represent
proportion of spliced exon-exon pairs.
(G) Expression of ELAVL4 in tau-V337M and tau-V337V glutamatergic neurons. Dot size, proportion of
cells expressing ELAVL4; depth of color, ELAVL4 expression level. Values: differential gene expression p
value adjusted by MAST general linear model comparisons of differential expression.
(H) Number of known nELAVL gene targets by RIP (Scheckel et al., 2016) that are differentially spliced
in tau-V337M organoids over time.
(I) Overlap between number of DSGs in tau-V337M organoids and genes in the brain known to be bound
by nELAVL by RIP analysis (Scheckel et al., 2016).
(J) Semantic analysis of significant GO pathways enriched for DSGs known to be nELAVL targets
(Scheckel et al., 2016).

119

Figure 4.6 ELAVL4 binds MAPT RNA and co-localizes with cytosolic stress granules in tau-V337M
neurons.

(A) ELAVL4 RNA immunoprecipitation (RIP) detects MAPT 3′ untranslated region (UTR) and exon 13 in
tau-V337V (left panel) and tau-V337M organoids (right panel). CALM3, positive control.
(B) Expression of TIA1 and G3BP1 in tau-V337M and tau-V337V glutamatergic neurons. Dot size,
proportion of cells expressing a gene; depth of color, expression level. Values: differential gene expression
p value adjusted by MAST general linear model.
(C and D) G3BP1 immunostaining (C) and quantification of G3BP1 intensity relative to DAPI (D) in tau-
V337V and V337M organoids at 2 months. Bars represent mean intensity ± SD. Unpaired t test,
∗
p ≤ 0.01.
n = 4 images per organoid; n = 3 organoids per line for 2 independent experiments.
(E and F) Western blot and densitometry quantification of G3BP1 in tau-V337M and isogenic V337V
organoids at 2 months. Bars represent G3BP1 densitometry in mutant organoids (%) relative to isogenic
controls ± SEM. Unpaired t test,
∗∗
p ≤ 0.01; n = 6 per group for 2 independent experiments.
(G) ELAVL4 and G3BP1 colocalization (white arrows) in tau-V337V and V337M organoids at 2 months.
Scale bar, 20 μm.
(H) ELAVL4 and TIA1 co-localization with tau at 2 months (scale bar, 5 μm) and ELAVL4 with tau at
4 months (white arrows; scale bar, 10 μm).
(I) Co-localization of tau, ELAVL4, and G3BP1 in tau-V337M organoids at 4 months. Scale bar, 5 μm.

120

Figure 4.7 Tau-V337M susceptibility to glutamate excitotoxicity is reversed by antagonists of
excitatory receptors and PIKFYVE inhibition.

(A) Longitudinal imaging method for tracking neuronal survival in cerebral organoids.
(B) Survival of SYN1::GFP+ neurons in 4-month tau-V337M and isogenic V337V organoids without
glutamate treatment. n = 80 neurons from 5 organoids per group. Log rank test. ns, not significant
(C) Images of 4-month tau-V337M and isogenic V337V organoids treated with 5 mM glutamate. Neurons
labeled with a lentivirus encoding SYN1::GFP. Scale bars, 50 μm.
(D) Survival of SYN1::GFP+ neurons in tau-V337M and isogenic V337V 4-month organoids with
glutamate treatment. n = 100 neurons from 5 individual organoids per group. Log rank test.
∗∗∗∗
p < 0.0001.
121

(E) Percentage of surviving neurons following 7 days of glutamate treatment from 3- to 4-month organoids.
Each point represents an independent experiment among three isogenic pairs. Two-tailed unpaired t
test,
∗
p = 0.0436.
(F) Schematic of the proposed mode of action for apilimod and effect on neuronal vulnerability to
excitotoxic stress.
(G) Survival of SYN1::GFP+ neurons in tau-V337M organoids with glutamate treatment and DMSO. 3i,
10 μM CNQX + 10 μM MK-801 + 2 μM nimodipine or 10 μM apilimod. n = 120 neurons from 5 individual
organoids per group. Log rank test,
∗∗
p < 0.01
∗∗∗∗
p < 0.0001.
(H) Images of 4-month tau-V337M organoids treated with 5 mM glutamate and DMSO. 3i, 10 μM CNQX +
10 μM MK-801 + 2 μM nimodipine or 10 μM apilimod. Neurons were labeled with SYN1::GFP. Scale bars,
50 μm.
(I) Relative PIKFYVE expression in ND03231 organoids by qRT-PCR following treatment with
a PIKFYVE ASO, normalized to 18S expression. Bars represent mean expression ± SEM with n = 6
organoids per group. Two-tailed unpaired t test,
∗∗
p < 0.01.
(J and K) Survival of SYN1::GFP+ neurons in 4-month tau-V337M (J) and tau-V337V (K) organoids with
glutamate and 10 μM negative control (NC) or PIKFYVE ASO treatment. n = 120 neurons from 5
individual organoids per group. Log rank test,
∗∗∗
p = 0.001,
∗∗∗∗
p < 0.0001.

122

Figure S4.1 Cerebral organoid differentiation recapitulates key features of human brain patterning.

(A) Cell type proportions and variability for individual organoids over time for all cell types identified.
Points are colored by donor line. Differences in cell type proportion are calculated compared to proportion
of cells at 2 months using a linear model,
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
p < 0.001.
(B-C) UMAP reduction of cell hashing single cell sequencing data from cerebral organoids at 2, 4 and
6 months of age, colored by batch (B) and mutation (C).
(D) Immunohistochemical staining of glial markers ALDH1L1 (4 months), IBA1 (6 months) (negative as
expected), and GFAP (2, 4 and 6 months) in tau-V337M (GIH6-A02) and isogenic corrected (GIH6-E11)
organoids. Scale bars 250 μm (inserts) and 50 μm.
123

(E) Quantification of GFAP+ cells at 2, 4 and 6 months of organoid differentiation in tau-V337M (GIH6-
A02) and isogenic corrected (GIH6-E11) organoids.

124

Figure S4.2 Tau-V337M organoids exhibit neuron-specific loss over time.

(A-B) Imaging of MAP2+ neurons (A) and quantitative analysis (B) at 2, 4 and 6 months, in mutant (GIH6-
A02) and isogenic corrected (GIH6-E11) organoids. Mann-Whitney: at 6 months
∗
p = 0.006.
(C) Proportion of Astrocytes, InCGE (inhibitory neurons from the caudal ganglionic eminence), and
InMGE (inhibitory neurons from the medial ganglionic eminence) per organoid at 2, 4 and 6 months of
differentiation. Points are colored by mutation (V337M = red, V337V = blue). A linear model was
conducted between glutamatergic cell type proportions in mutant versus isogenic-corrected organoids at
each time point, p > 0.05, not significant.
(D-E) UMAP reduction plots of astrocytes from each isogenic cell line pair colored by mutation (D) and
Seurat cluster (E). Black arrows indicate mutant cell-enriched clusters.
(F) Heatmap of enrichment z-scores of pathways significantly up- or downregulated in mutant-enriched
astrocyte clusters in each isogenic pair using Ingenuity Pathway Analysis.

125

Figure S4.3 Characterization of autophagy markers and MAPT expression in organoids.

(A) Quantitative analysis of IHC staining of p62 positive cells in tau-V337V and tau-V337M organoids
over time.
(B) IHC imaging of autophagy-lysosomal pathway markers p62 and LAMP1 in tau-V337M organoids
(2 months) and in human brain tissue; morphology characteristic of neurons. Organoid scale bar = 250 μm,
insets = 10 μm. Human brain scale bar = 50 μm.
(C) qRT-PCR analysis of 4R:3R MAPT ratio in tau-V337V and V337M organoids at 2, 4 and 6 months.
Each isogenic pair is denoted by a different shape, tau-V337M lines = green, V337V = orange. N = 6-8.
(D) Western blot analysis of 4R tau in tau-V337V and V337M organoids at 2, 4 and 6 months (n = 3 per
group). 2-month-old samples and the recombinant tau ladder were run in the same gel and the image was
cropped for the sole purpose of excluding samples not included in this analysis.
(E) Violin plots show residuals of MAPT expression in organoids derived from bulk RNA-seq data
following correction for covariates (V337M = green, V337V = orange). Each isogenic cell line is denoted
by different color data points (GIH6 = green, GIH7 = orange, NDB = purple). Statistical comparisons
(linear mixed model for repeated-measures) were carried out between V337M and V337V organoids at
each time point,
∗
p < 0.05.
126

(F) Proportion of MAPT-expressing cell-types in 2, 4 and 6-month organoids, with expression scaled within
each time point. Dot size represents the proportion of cells expressing detectable MAPT, and depth of color
denotes level of MAPT expression.
(G) Proportion of MAPT expressing interneurons in tau-V337V and V337M organoids at 2, 4 and 6 months.
Dot size represents the proportion of cells expressing MAPT, and the depth of color denotes the level
of MAPT expression. n.s./not significant.

127

Figure S4.4 Changes in enriched gene expression pathways in tau-V337M organoids.

(A-B) Gene set enrichment analysis of differentially expressed genes in the bulk RNA-seq data at 2 months
of differentiation (A) and the interaction between mutation and age from 2-6 months (B). NES = normalized
enrichment score. Adjusted -log10 p-value is indicated by depth of color on bars. Synaptic-related pathways
are highlighted in bold.
128

(C-F) Gene set enrichment analysis of differentially expressed genes in the bulk RNA-seq data at 4 months
(C), 6 months (D) and the interaction between mutation and age between 2-4 months (E) and 4-6 months
(F). NES = normalized enrichment score. Adjusted -log10 p-value is indicated by depth of color on bars.
(G) Expression and connectivity of glutamatergic receptor genes and MAPT at 4 months (left) and 6 months
(right) of organoid differentiation. Red indicates gene upregulation in V337M organoids compared to
isogenic controls, and green indicates gene downregulation. Depth of color reflects the extent of fold-
change expression.

129

Figure S4.5 Summary of differential gene expression in tau-V337M organoids.

(A) Standardized z-scores (Zstd) for all differentially expressed genes in the bulk RNaseq data between
tau-V337M and V337V organoids at 2, 4 and 6 months, as determined by linear mixed model for repeated-
measures.
(B-D) Volcano plots denoting number, fold change and significance of differentially expressed genes
between tau-V337M and V337V organoids in the bulk RNA-seq data at 2 (B), 4 (C) and 6 (D) months.
(E-H) Principal components (PC) plots of bulk RNaseq samples, colored by batch (E), age (F), donor cell
line (G) and mutation (H).

130

Figure S4.6 Ordering of organoid cell types and enrichment of tau-V337M and V337V gene
expression modules in pseudotime.

(A) Separation of cell types present in organoids by pseudotime in tau-V337V (left) and tau-V337M (right)
organoids.
(B-C) UMAP reduction of all tau-V337V (left) and tau-V337M (right) cells colored by pseudotime (B) and
cell type (C). Cells appearing earliest in pseudotime are denoted by dark purple, and those latest in
pseudotime are in yellow.
(D-E) UMAP reduction of all excitatory neurons colored by pseudotime (D) and cell type (E). Cells earliest
in pseudotime are denoted by dark purple, and those latest in pseudotime are in yellow.
(F) UMAPs of excitatory neurons indicating the location and expression score of the top 9 enriched gene
clusters in tau-V337M organoids.
131

(G) Heatmaps of cluster 1 genes over pseudotime in tau-V337M (top) and V337V (bottom) glutamatergic
neurons. Purple = low expression, orange = high expression.
(H) Number of significantly differentially spliced intron junctions between tau-V337M and tau-V337V
organoids at each differentiation time-point (exact number shown above each bar) as determined by
LeafCutter analysis.

132

Figure S4.7 Susceptibility to glutamate excitotoxicity in tau-V337M organoids is reversed by
apilimod.

(A) Co-labeling of SYN1::eGFP transduced and non-transduced cells with the live cell marker DRAQ5 in
4 month old organoids.
(B-C) Quantification (B) and representative images (C) of the proportion of SATB2+/NeuN+ glutamatergic
neurons in 4-month-old isogenic tau-V337V (GIH6-E11, n = 3) and tau-V337M (GIH6-A02, n = 6)
organoids following 48h of 5 mM glutamate treatment. Line and error bars represent mean and SEM,
respectively. Statistical analysis by unpaired Student’s t test. Scale bar, 50 μm.
133

(D) Survival of SYN1::GFP+ neurons in tau-V337V (GIH6-E11) 4-month-old organoids with 5 mM
glutamate treatment and DMSO, 3i (10 μM CNQX + 10 μM MK-801 + 2 μM Nimodipine), n = 120
neurons tracked from 5 individual organoids per group. Log-rank test:
∗∗
p < 0.01,
∗∗∗∗
p < 0.0001. These
organoids are not of the same isogenic pair as Figure 7G.
(E) Western blot of 4-month-old isogenic tau-V337V (GIH6-E11 and GIH7-B12) and tau-V337M (GIH6-
A02 and GIH7-A01) organoids treated with 5 mM glutamate and DMSO ± 10 μM apilimod.
Phosphorylated tau PHF1 (S396/S404) (red) and total tau (green).
(F) Quantification of (E), normalized to total protein levels. n = 5 organoids per group. Significance
determined by One-way ANOVA with Tukey’s multiple comparisons test.
(G) Survival curves for SYN1::GFP+ neurons in 12-month-old isogenic tau-V337V (NDB06) and tau-
V337M (NDB09) organoids.
(H, I) IF imaging and survival curves for SYN1::GFP+ neurons in 12-month-old tau-V337M (NDB09) and
isogenic V337V (NDB06) organoids with 5 mM glutamate treatment. n = 80 neurons tracked in total from
5 individual organoids per group. Significance determined by log-rank test,
∗∗∗∗
p < 0.0001.
(J) Images of 12-month-old isogenic control (NDB06) and tau-V337M (NDB09) organoids treated with
5 mM glutamate and DMSO or 10 μM apilimod. Neurons were labeled with a lentivirus
encoding SYN1::GFP. Scale bars are 10 μm.
(K-L) Survival of 12-month-old SYN1::GFP
+
neurons in Tau-V337M (NDB09, J) and tau-V337V
(NDB06, K) organoids with glutamate treatment and DMSO or apilimod. n = 80 neurons tracked in total
from 5 individual organoids per group, log-rank test
∗∗ ∗∗
p < 0.0001 or ns/not significant.

134

Chapter 5: Conclusions
Neurodegenerative diseases loom large as an increasing burden on our society. By 2050,
the incidence of dementia is estimated to triple to greater than 150 million cases, and more effective
disease-modifying therapies are desperately needed
331
. To address these challenges, genetic and
environmental organoid models of neurodegeneration are valuable tools to help bridge the
translational gap between traditional in vitro systems and animal models. Although current
organoid models have limitations, including a lack of key cells such as microglia and perinatal
developmental maturity, recent work has demonstrated the ability of organoids to effectively
model aspects of neurodegenerative and age-related diseases
47,87,332
. Here, we developed novel
organoid models of traumatic brain injury and glutamate excitotoxicity as environmental risk
factors for dementia-related diseases with an emphasis on cross-talk between ALS and FTD,
respectively.
We developed a method implementing focused ultrasonic waves to inflict mechanical
injury on organoids to mimic blast-like forces in TBI. We demonstrate that this model recapitulates
TBI-related phenotypes including secreted phosphorylated tau, TDP-43 mis-localization, and
neurodegeneration
3,10,12
. We found that, although tau pathology is the standard diagnostic criteria
for human TBI, in this system TDP-43 dysfunction is a key driver of neurodegeneration following
injury. Our data suggests that deep-layer excitatory neurons display enhanced TDP-43
dysfunction. Although TDP-43 pathology has been shown across all layers of the cortex in human
post-mortem samples, the enhanced pathology observed in deep-layer neurons at acute timepoints
in our organoid model provides a possible mechanistic link to the elevated risk of ALS following
TBI, in which deep-layer neurons are particularly vulnerable among the cortical population
11–13,178
.
Indeed, in injured C9ORF72 ALS/FTD patient-derived organoids we found increased TDP-43
135

pathology and loss-of-function, evidenced by reduced STMN2 expression and neurite outgrowth
relative to injured wild type organoids, which itself is a known phenotype of ALS
152
. Although
this alone does not constitute a diseased state, it does suggest that acute changes in TDP-43 after
injury are similar to those seen in neurodegenerative diseases and that, especially in individuals
with genetic risk factors or mutations that are pre-disposed to ALS, brain injury may accelerate
the progression to a diagnostic disease threshold. Therefore, strategies aimed at mitigating TDP-
43 dysfunction following TBI may reduce the risk of ALS over time.
Critically, using this model we show an unprecedented ability to identify genetic modifiers
of TBI. This has been a challenge due in part to highly variable biophysical forces experienced in
TBI and is a significant need due to the limited efficacy of current surgical and pharmacologic
interventions
4
. Indeed, a recent prospective GWAS study reported that no genetic variants linked
to TBI outcome reached the genome-wide significance threshold
180
. By using organoids grown
from iPSCs engineered to express deactivated Cas9 machinery to promote transcriptional
repression, we conducted a genome-wide screen on HIFU injured organoids
163
. We found that
chemical and genetic inhibition of KCNJ2 mitigates neurodegeneration after injury, in part by
reducing Ca
2+
influx. KCNJ2 inhibition also improved TDP-43 pathology and neurodegeneration
in C9ORF72 ALS/FTD organoids and in vivo in a well-established mouse model of TBI. This
demonstrates the therapeutic potential of KCNJ2 inhibition and the overall translational relevance
of the model to identify and test modifiers of TBI. Additionally, although we focus here on
neurons, the contribution of non-neuronal cell types, especially microglia and astrocytes for their
roles in neuroinflammation in the secondary phase of injury, are important to the pathophysiology
of TBI
333–336
. Our organoid TBI model is well suited to examine post-injury changes in astrocytes
and, as organoid models advance and microglia or vascular endothelial cells are introduced, we
136

anticipate an enhanced mechanistic understanding of intrinsic and extrinsic cellular contributions
of these populations to injury and a continued ability to identify injury modifiers in these cell types.
We next created a model of glutamate excitotoxicity, a common pathway of
neurodegeneration in multiple diseases including ALS/FTD and in TBI
9,45
. Glutamate is the
primary excitatory neurotransmitter in the central nervous system, with physiologic roles in
learning and memory and, when dysregulated, pathologic roles in ischemia, epilepsy, and
neurodegeneration
46,310,337
. Several FTD-causing mutations and associated genes, including in
MAPT and GRN, have been linked to dysfunctional glutamatergic signaling
47,338–340
. Additionally,
phosphorylation and oligomerization of tau in MAPT V337M FTD neurons has been linked to
hyperexcitability
37,44,47
. However, conflicting reports have associated FTD with glutamate
hypofunction, with glutamate receptor impairment in part via autoimmune-mediated antibody
inhibition
314,341
. We found that a high dose of glutamate induces tau oligomerization and
neurodegeneration in wild type organoids and expanded our study to include FTD patient-derived
organoids with the MAPT V337M mutation, in which glutamate-induced neurodegeneration was
enhanced. This provides evidence for the direct role of glutamate excitotoxicity in acute neuronal
pathology and degeneration in FTD and non-diseased neurons, and suggests that observed
glutamatergic deficits in FTD may arise at later stages as a compensatory effect or result from the
reported degeneration of the glutamatergic neuron population
206
. Despite this, previous
pharmacologic agents aimed at inhibiting glutamate signaling at the level of glutamate-receptor
binding have been unsuccessful in FTD, perhaps because directly inhibiting a key neurotransmitter
at the required levels would be deleterious
204,205
. Current approved therapies for FTD are limited
to management of behavioral symptoms, highlighting a need for disease-modifying targets
28
.
Based on these findings, therapeutic strategies to mitigate the toxic effects of excess glutamate
137

signaling downstream of receptor activation may be a more effective approach.
We performed a genetic screen in this model to identify genetic modifiers of excitotoxic
neuron death and found that knockdown of KCTD20 potently mitigates glutamate-induced
neurodegeneration in wild-type, tau-V337M and C9ORF72 ALS/FTD organoids and in a
transgenic FTD mouse model. Improved neuron survival was associated with a reduction in
oligomeric tau species, consistent with reports that impaired clearance of neurotoxic protein
aggregates contributes to neurodegenerative disease pathogenesis
50
. We found that this effect was
dependent on exocytosis, and specifically that inhibition of lysosomal exocytosis abolished the
protective effect of KCTD20 knockdown. Pathogenic tau clearance in FTD via TFEB-mediated
lysosomal exocytosis has been previously demonstrated without spreading tau aggregates,
potentially by tau clearance from the CNS via the glymphatic system
60–62
. We found increased
levels of oligomeric tau in purified exosomes and increased TFEB activity in organoids following
KCTD20 inhibition, providing a potential mechanism of tau clearance and neuronal rescue.
Interestingly, mutant tau does not activate the unfolded protein response in a murine tauopathy
model, suggesting that secretion mechanisms rather than internal degradation may be the more
effective strategy for alleviating the burden of aggregated proteins
58
. Indeed, our lab has previously
reported that exocytosis can be stimulated to clear disease-related proteins, although the
mechanisms of secretion and substrate appear to be specific to the genetic target
51
. These data help
to establish the relevance of using glutamate-induced excitotoxicity to model and identify
therapeutic targets in FTD. These findings may be broadly applicable to other excitotoxic
neurodegenerative diseases, as we found in C9ORF72 patient organoids. It is notable that KCTD20
knockdown was also neuroprotective in this genetic background associated with significant TDP-
43 pathology, suggesting that its therapeutic effects may be not be limited to tauopathies and may
138

be applicable to a range of excitotoxicity-associated diseases
27
. Future work implementing this
model will test the efficacy of KCTD20 inhibition and look to identify new targets in Alzheimer’s
disease and Huntington’s disease patient-derived organoids.
Neurodegenerative diseases, including those highlighted in this thesis, are incredibly
complex in their genetic etiologies, pathophysiology, and intrinsic and extrinsic mechanisms of
multiple cell types. Here, we focused on modeling and targeting specific phenotypes in neurons to
identify new therapeutics. Moving forward, it will be important to use these models to test the
targets we identified and to identify new targets in non-neuronal cells to more accurately depict
human disease states. Several groups have begun to do so by integrating different cell types
(microglia, endothelial cells) into organoids or by in vivo organoid transplantation, which enhances
neuronal maturity and leads to vascular invasion
124,332,342
. Additionally, due to the genetic
flexibility of organoids to incorporate patient-derived iPSCs from different familial and sporadic
neurodegenerative diseases, we anticipate that the models presented here will serve as useful pre-
clinical platforms for mechanistic research and target discovery. Finally, for successful clinical
testing of these and other targets, early detection and screening approaches will be critical. For
traumatic brain injury, mitigating acute pathologic changes is the most likely to be efficacious for
reducing the long-term risk of dementia. In FTD, in which a relatively large (30%) fraction of
patients have a family history, coupled with improved biomarker discovery, earlier diagnosis and
treatment is likely to broadly improve the outcome of upcoming clinical trials
27,28,343
. Together,
these approaches will enhance our understanding of a spectrum of environmental and genetic
neurodegenerative diseases and contribute to our ability to develop new therapies.

139

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Appendices
Appendix A: Methods and Materials

A.1 Methods

iPSC reprogramming
Gene editing of iPSC lines and insertion of hNGN2 was performed by transfection of iPSCs using
Lipofectamine Stem Transfection Reagent together with the following plasmids: pC13N-dCas9-
BFP-KRAB (Addgene #127968), CLYBL-TO-hNGN2-BSD-mApple (Addgene #124229), and
pMXs-p53DD (Addgene #22729). Transfected cells were allowed to recover and subsequently
selected with Geneticin (Thermo) and blasticidin (Thermo).

Vectors and viral transduction
Lentivirus was produced through transfection of 80-90% confluent HEK293T cells on 0.1%
gelatin-coated 10 cm plates grown in DMEM/F12 with 10% FBS. Prior to transfection,
polyethylenimine (PEI, Sigma) was mixed with OptiMEM and incubated for five minutes at room
temperature. The packaging plasmids pPAX2 and VSVG, and viral vector plasmid were
subsequently added followed by a 15-minute incubation at room temperature. The transfection mix
was then added to cells dropwise. Fresh DMEM/F12 with 10% FBS was replenished after 24
hours, and supernatant was collected after 48 and 72 hours. Supernatant was filtered using 0.45
µM filters and concentrated with 1/3 volume of Lenti-X (Clontech) overnight at 4⁰C. Concentrated
virus was centrifuged at 1500g, 4⁰C, for 45 minutes, then resuspended in DMEM/F12 and stored
at -80⁰C. Viral vectors used in this study: pHR-hSyn-EGFP (Addgene #114215), pUltra-hSyn-
mCherry, pHAGE-RSV-tdTomato-2A-GCaMP6f (Addgene #80317), pLVX-EF1alpha-
2xGFP:NES-IRES-2xRFP:NLS (Addgene #71396). Organoids were transduced with virus by
combining concentrated virus with 1:1000 polybrene in neural medium. Medium was refreshed
after 24 hours to remove virus.

Cryopreservation
Organoids were fixed in 4% paraformaldehyde (VWR) for 1 hr at 4°C, washed with PBS, and
dehydrated in 30% sucrose overnight. The following day, organoids were embedded in Tissue-
Tek O.C.T. Compound (Sakura) and frozen in a dry ice-ethanol bath. Frozen tissue blocks were
then processed into 14-µm sections using the Leica CM3050 S cryostat (Leica Biosystems) and
adhered onto Superfrost Plus Microscope slides (Fisher) and stored at -80°C until use.

Immunofluorescent staining
Tissue sections were rehydrated in 1X Tris Buffered Saline (TBS; Sigma) containing 0.1% tween-
20 (TBST), permeabilized for 15 min at room temperature in TBS + 0.1% triton X-100, blocked
with TBST + 5% fetal bovine serum for 30 min at room temperature, and stained overnight with
primary antibodies diluted in blocking buffer. The following day, slides were washed with TBST
and incubated with Alexa Fluor secondary antibodies and DAPI (Life Technologies) for 1 hr.
Slides were washed 3 times with TBST and coverslips were mounted using Vectashield (Vector
Laboratories). MitoTracker Red CMXRos was used according to the manufacturer’s protocol, 1h
prior to fixation. Complete list of antibodies used, see Western blot section.

170

Immunohistochemistry
Whole organoids were fixed in 10% neutral buffered formalin for 30 minutes and embedded in
paraffin and sectioned at 7 µm. Antigen retrieval was performed using Tris/EDTA buffer, ph=8-
8.5 for 1 hour. Immunohistochemical staining was performed using a Ventana Benchmark XT.

Microscopy
A Zeiss AxioZoom.v16 wide-field fluorescent microscope was used for longitudinal imaging of
SYN1::eGFP-labelled neurons. For all other imaging, a Zeiss LSM 800: AxioObserver.M2 upright
confocal microscope was used with a 20X, 40X, or 63X objective.

Image analysis
Confocal images were captured using a Zeiss LSM 800: AxioObserver.M2 upright confocal
microscope with a 20X, 40X, or 63X objective. Images were analyzed using NIH ImageJ software.
For single neuron and nuclear quantifications, fluorescent integrated density was measured in
ImageJ and normalized to ROI area. Single-neuron measurements were calculated by thresholding
neuronal cell bodies based on SYN1::eGFP intensity to create individual cell regions of interest
(ROIs) then measuring target signal. Nuclear:cytoplasmic measurements were calculated by
thresholding DAPI and SYN1::eGFP then measuring target signal. Target intensity was normalized
to DAPI intensity. Nuclear pores were imaged through Z-stacks spanning whole nuclei using a
Zeiss LSM 800 confocal microscope. Huygens Essential (Scientific Volume Imaging (SVI)) was
used for deconvolution. Imaris (BitPlane) was used to quantify nuclear pore volume and
counts. Neuronal nuclei were selected by creating a 3D mask out of the surface of each neuron
and excluding any signal outside of that mask. Imaris “spots” function was then used to find and
measure Nup98 complexes based on the radius of the fluorescent signal. The volumes were then
recorded as well as the overall count per neuron.

Live imaging of SYN1::eGFP neurons
Longitudinal tracking of neuron survival in 3D was performed as previously described
47
. Cerebral
organoids were transduced with lentivirus encoding SYN1::eGFP for 5 days and immobilized in
Matrigel (VWR) prior to experimental use. Continuous Z-stacks spanning 150 µM from the
organoid surface were captured daily using a Zeiss AxioZoom.v16 wide-field upright fluorescent
microscope. For the survival time course, glutamate (L-Glutamic acid monosodium salt hydrate in
PBS) was added to culture medium at day zero, and was replenished after one, two, four, and six
days; or for organoid TBI, organoids were injured at day zero and fresh medium was added after
one, two, four, and six days. All planes were collapsed into a single image by extended depth of
focus using the Zen Pro software. Post-processing and image alignments were performed using
ImageJ software (NIH). Staining with 1:500 DRAQ5 (Biolegend 424101) for 15 minutes at room
temperature was used to assess live cells remaining at experimental endpoint. Detection of live
neurons was determined by co-localization of SYN::eGFP and DRAQ5.

Western blot
Organoids and mouse tissue collected for western blot analysis were lysed in RIPA buffer (Santa
Cruz) supplemented with 1X cOmplete EDTA-free protease inhibitor cocktail (Roche), 1% (v/v)
phosphatase inhibitor cocktail 3 (Sigma) and 5 nM Trichostatin A deacetylase inhibitor (Cayman).
Lysed samples were incubated on ice for 20 minutes followed by centrifugation at 12000g for 15
minutes at 4⁰C. Supernatant was transferred to fresh microcentrifuge tubes and stored at -80⁰C.
171

Protein quantification was measured by bicinchoninic acid assay (BCA, Thermo) following
manufacturer protocols.
Samples were run on 10% or 15% SDS-PAGE gels. Odyssey One-Color protein molecular weight
marker (LI-COR) was used as a size marker. Gels were transferred onto Immobilon-FL PVDF
membranes (Millipore). Total protein was measured using the Revert 700 total protein stain kit
(LI-COR) using standard protocols. After washing, membranes were blocked in Intercept TBS
blocking buffer (LI-COR) overnight at 4⁰C. Primary antibodies were added in Intercept buffer +
0.2% tween-20 and incubated overnight at 4⁰C. Membranes were washed 3 times with 1X TBS +
0.1% tween-20 (TBS-T), and IRDye secondary antibodies (LI-COR) were added in Intercept
buffer containing 0.2% tween-20 and 0.1% SDS for 1 hour at room temperature followed by 3
washes in 1X TBS-T and 2 washes in 1X TBS. Membranes were visualized on the Odyssey CLx
imaging system (LI-COR). Target bands were normalized to total protein for quantification per
manufacturer protocols. Complete list of antibodies used: Chicken anti-MAP2 (Abcam); ab5392.
Mouse anti-NeuN (Millipore); MAB377. Mouse anti-PAX6 (Thermo); MA1-109. Rat anti-CTIP2
(Sigma); MABE1045. Guinea pig anti-SATB2 (SY); 327 004. Rabbit anti-GFAP (Abcam);
ab7260. Rabbit anti-phosphorylated TDP-43 S409/410 (Proteintech); 22309-1-AP. Rabbit anti-
TDP-43 N-terminal (Proteintech); 10782-2-AP. Rabbit anti-TDP-43 C-terminal (Proteintech);
12892-1-AP. Mouse anti-phosphorylated tau S202/S205 AT8 (Invitrogen); MN1020. Mouse anti-
Tau-5 (Invitrogen); AHB0042. Rabbit anti-tau T22 (Millipore); ABN454. Rabbit anti-
phosphorylated tau S396 (Thermo); 44-752G. Mouse anti-phosphorylated tau Thr231 AT180
(Thermo); MN1040. Chicken anti-GFP (Aves); GFP-1010.Rabbit anti-NUP98 (Cell Signaling);
C39A3. Rabbit anti-STMN2 (Novus); NBP1-49461. Mouse anti-HuC (ELAVL3) (Proteintech);
55047-1-AP. Mouse anti-phosphorylated CaMKII alpha Thr286 (Thermo); MA1-047. Rabbit anti-
Kir2.1/KCNJ2 (Alomone); APC-026. Chicken anti-TUBB3 (Aves); TUJ. Chicken anti-NfL
(Aves); NFL. Mouse anti-TDP-43 3H8 (Abcam); ab104223. Mouse anti-phosphorylated TDP-43
S403/S404 (Proteintech); 66079-1-Ig. Rabbit anti-NeuN (Abcam); ab177487. Rabbit anti-
KCTD20 (Abcam); ab122094. Mouse anti-mTOR (Proteintch); 66888-1-Ig. Rabbit anti-
phosphorylated mTOR Ser2448 (Cell Signaling); 5536T. Mouse anti-AKT (Cell Signaling);
2920S. Rabbit anti-phosphorylated AKT Thr308 (Cell Signaling); 13038S. Rabbit anti-TFEB
(Bethyl); A303-673A. Rabbit anti-phosphorylated TFEB Ser142 (Millipore); ABE1971-I. Mouse
anti-LAMP1 (Abcam); ab25630. Rabbit anti-MCOLN1 (Alomone); ACC-081.

qRT-PCR
Total RNA was extracted from organoid or mouse tissue with RNeasy Mini Kit (Qiagen 74104)
and reverse transcribed with random primer using Protoscript II First Strand Synthesis Kit (NEB)
using manufacturer protocols. RNA concentration was measured by Nanodrop (Thermo). Real-
time PCR was conducted using iTaq SYBR Green Supermix (Bio-Rad). Relative expression was
calculated using the ΔΔCt method and normalized to housekeeping controls. The following
primers were used: Hs STMN2 fwd, AGCTGTCCATGCTGTCACTG. Hs STMN2 rev,
GGTGGCTTCAAGATCAGCTC. Hs UNC13A fwd, GGACGTGTGGTACAACCTGG. Hs UNC13A rev,
GTGTACTGGACATGGTACGGG. Hs KCNJ2 fwd, TGCGCCAGCAACAGGACAT. Hs KCNJ2 rev,
GTGTCTCTGGGAGCCTTGTG. Hs 18S fwd, CTCAACACGGGAAACCTCAC. Hs 18S rev,
CGCTCCACCAACTAAGAACG. Hs KCTD20 fwd, CGGGGAGCGACGAGATTT. Hs KCTD20 rev,
TCACTGCCACGGTGAACATT. Hs TDP43 fwd, TCATCCCCAAGCCATTCAGG. Hs TDP43 rev,
TGCTTAGGTTCGGCATTGGA. Hs TFEB fwd, GCAAGCTCAGGCTGGGAG. Hs TFEB rev,
TATTGATGGCCGGGGTGGG. Ms Kcnj2 fwd, TGTACCAGCAACAGGACAAGT. Ms Kcnj2 rev,
GGAGAGATGGATGCTTCCGAG. Ms Gapdh fwd, TGTCAAGCTCATTTCCTGGTATG. Ms Gadph
172

rev, TTATGGGGGTCTGGGATGGA. Ms Hprt fwd, GCAGCGTTTCTGAGCCATTG. Ms Hprt rev,
CATCATCGCTAATCACGACGC. Ms Kctd20 fwd, GGAGTATGTGATCGCGGAGG. Ms Kctd20 rev,
TCGTGCAGTAGAGCACTCAG.

Bulk RNA sequencing
Organoids were injured by HIFU and collected for RNAseq at the indicated timepoints post-injury.
Supernatant was removed and organoids were lysed in RLT buffer (Qiagen). Messenger RNA was
extracted using NEBNext Poly(A) mRNA Magenetic Isolation Module according to the
manufacturer’s protocol, and 3’ RNA-Seq library were prepared using the 3’-Digital Gene
Expression RNAseq Library Kit (Amaryllis Nucleics). Libraries were sequenced on an Illumina
NextSeq 500 machine (10-25M reads, single-end, 80 bp).
RNA sequencing output was aligned to the GRCh38/hg38 reference genome using STAR
alignment (STAR 2.5.3a) in PartekFlow (Partek)
344
. Genes were annotated using the
GENCODE29_v2 comprehensive gene annotation. Post-alignment quality control was performed
in PartekFlow. To identify differentially expressed genes, the DESeq2 (v3.5) package in
PartekFlow was used to estimate dispersion and size factors, fit the data to a local model, and
generate differential statistics using the Wald hypothesis test. Ingenuity Pathway Analysis (IPA,
Qiagen) were used to perform downstream analysis using differential genes.

Single cell RNA sequencing
Organoid Dissociation and Cell Hashing
Organoids were dissociated for single-cell RNA sequencing as described with minor
modifications
270
. In brief, organoids were incubated in Papain (Worthington LK003176) with
DNase1 (Worthington LK003170) reconstituted per manufacturer instructions for 60 minutes at
37⁰C with gentle shaking at 27 rpm with regular pipetting. Single-cell suspension was added to
Earle’s Balanced Salt Solution (EBSS) with Ovomucoid Inhibitor (Worthington LK003182) and
DNase1, pelleted, resuspended in ice-cold Neurobasal-A (Invitrogen) with 0.2% bovine serum
albumin (BSA), and filtered through 40 µM Flowmi tips (Sigma BAH136800040-50EA). Cell
count and viability was determined by Trypan Blue staining using a hemocytometer. Cells were
labeled with hashtag-oligonucleotide (HTO) antibodies (Biolegend TotalSeq-B, 405287, 405289,
405291) and libraries were prepared following manufacturer protocols (10X Genomics,
CG000206 Rev D).
Single-Cell RNA Seq Alignment and QC
Data alignment and QC was conducted through the University of Southern California Center for
Advanced Research Computing (CARC) using the Cell Ranger count Feature Barcode Analysis
pipeline (10X Genomics) for concurrent UMI identification, reference genome (human hg38
genome) alignment, and HTO assignment. Samples were demultiplexed using the HTODemux
pipeline in R version 4.0.1
345
. Data was further processed using Seurat v4.0 to remove cells with
< 200 detectable genes and > 20% mitochondrial rate
346
.
Data Analysis
Data from different lanes and cell lines were integrated using SCTransform to regress out
percentage of mitochondrial genes and anchored using the top 5,000 variable features
347
. Principle
Component Analysis (PCA) was run using the top 5,000 variable genes, and Uniform Manifold
Approximation and Projection (UMAP) was implemented for data reduction. Data was then log-
normalized and re-scaled, and clusters were identified using default parameters. Differentially
expressed genes (DEGs) were calculated based on raw gene count data using MAST with default
173

covariates. Significant DEGs between conditions were submitted to Enrichr and Ingenuity
Pathway Analysis (IPA, Qiagen) for pathway analysis.
Calculation of Pseudotime Trajectories
Excitatory deep-layer neuron clusters in sham and HIFU-injured organoids were ordered in
pseudotime using Monocle2
226
. Genes were ordered based on significance as defined by p < 0.05
and clusters were generated by unsupervised clustering. FindAllMarkers function was
implemented to identify marker genes of pseudotime clusters, and genes with adjusted p < 0.05
were submitted for ontology enrichment through Enrichr. Proportions of cells in each state across
conditions were calculated using Fisher’s Exact test.

CRISPRi screen
Library and Experimental Design
The CRISPRi-v2 sgRNA library (Addgene # 1000000090) was electroporated into MegaX
DH10B T1R Electrocomp Cells (Invitrogen #C640003) and inoculated in LB+carbenicillin for
16h shaking at 37C. Libraries were purified by Maxiprep (Qiagen #12963). Lentivirus was made
as described above. Induced cortical spheroids (iCSs) were transduced with the lentiviral
CRISPRi-v2 sgRNA library 7 days prior to injury. Organoids (n=150/group) were given HIFU or
sham injury; or glutamate or vehicle (n=150/group). Degeneration was monitored throughout the
experiment to validate neuronal death.
Amplicon Library Preparation
Total genomic DNA (gDNA) was isolated using the Monarch Genomic DNA Purification Kit
(NEB #T3010S). To amplify the sgRNA cassette, the total gDNA was split and amplified using
custom mirrored Illumina indexing primers using Q5 High-Fidelity DNA polymerase (NEB
#M0491). The desired amplicon (~150 bp) was further enriched using SPRIselect (Beckman
Coulter) double size selection beads and quantified by Bioanalyzer and Qubit.
Next-generation Sequencing & Bioinformatics
Amplicon libraries were sequenced with the NextSeq 500/550 High Output Kit v2.5 (75 cycles)
with a 20% Phi-X spike-in. Trimming and alignments were performed in Python 3.8.3 and analysis
was conducted using the MAGeCKFlute pipeline in R version 4.0.1. Only genes with >2
representative sgRNAs detected in the sequencing were retained for downstream analyses.

Calcium imaging
Organoids were incubated with 1 µM of Fluo-4,AM (Thermo) for 15 minutes and washed twice
in complete neural medium. Organoids were then immobilized in Matrigel and imaged on a Zeiss
Axiozoom.v16 before and immediately after injury for 2 minutes at 24 frames per second. Change
in fluorescence was calculated by measuring peak fluorescent intensity per frame normalized to
background fluorescence.

TUNEL staining
In situ detection of apoptosis was performed using the Click-iT Plus TUNEL Assay (Invitrogen,
C10617) according to manufacturer protocols. Following Click-iT reaction, slides were
counterstained with DAPI prior to mounting.

Tau pThr231/total tau ELISA
Total and phosphorylated (Thr231) tau concentrations were quantitatively measured using a 96-
well electrochemiluminescence-linked immunoassay (Meso Scale Discovery, K15121D) using
manufacturer protocols. Supernatant was collected from organoid culture medium and tau/p-tau
174

concentrations were calculated after normalization to a standard curve.

Generation of collagen hydrogels
A collagen solution was prepared on ice, consisting of 200µl of 5mg/mL cultrex rat collagen I
(R&D Systems) and 10µL of 7.5% sodium bicarbonate. Spheroids were placed into a 24 well ultra-
low attachment plate with minimal media. Taking care not to introduce air bubbles, 15µL of the
collagen solution was pipetted on top of spheroids. The embedded spheroids were then incubated
at 37°C for 30 minutes to induce polymerization prior to addition of neuronal media.

Neurite length quantification
The average neurite length of the longest 10 neurites was determined by tracing the distance from
spheroid edge to observable neurite end using Fiji in brightfield images after 6 days post-
embedding (n = 4 for each condition).

Exosome isolation
Magnetic isolation and purification of exosomes from organoid supernatant using the Exosome
Isolation Kit Pan, human (Miltenyi) according to manufacturer protocols. Exosomes were eluted
in exosome lysis buffer and immediately processed for western blot.

In vitro antisense oligonucleotide treatment
Organoids were treated with 10 µM antisense oligonucleotide (ASO) for 72 hours prior to start of
the experiment. ASO sequences were custom designed and synthesized (IDT). The following
sequences were used: Negative control (NC5)- 5’-
mG*mC*mG*mA*mC*T*A*T*A*C*G*C*G*C*A*mA*mU*mA*mU*mG-3’. KCTD20 aso1-
5’- mU*mC*mU*mC*mC*T*A*C*T*C*A*A*G*G*T*mG*mA*mG*mA*mC-3’. KCTD20
aso2- 5’-mG*mC*mA*mG*mA*A*A*G*G*A*A*A*A*G*G*mU*mU*mA*mG*mG-3’.
KCTD20 aso4- 5’-mU*mG*mG*mA*mC*A*T*T*C*T*G*A*A*T*G*mA*mG*mA*mC*mC-
3’. KCNJ2 aso1- 5’-
mG*mA*mG*mC*mU*T*A*C*A*G*T*C*T*T*T*mC*mU*mU*mU*mG-3’. VAMP7 aso1-
5’-mC*mU*mA*mG*mG*C*T*A*A*A*C*A*G*G*T*mG*mG*mC*mU*mA-3’. MCOLN1
aso1- 5’-mG*mG*mU*mU*mA*G*A*T*G*T*A*C*C*T*T*mC*mA*mC*mA*mU-3’.
HSPA8 aso1- 5’-mC*mA*mA*mG*mG*A*A*G*G*T*A*G*T*T*G*mC*mC*mA*mA*mC-
3’. NSMAF aso1- 5’-
mA*mU*mC*mU*mG*C*C*C*T*A*A*G*A*G*A*mA*mU*mA*mG*mC-3’. SMPD3 aso1-
5’-mG*mG*mA*mU*mU*G*T*C*A*A*A*A*A*C*A*mG*mU*mC*mC*mC-3’. ATG5
aso1- 5’-mG*mU*mG*mG*mU*A*A*T*A*G*C*A*T*A*G*mU*mC*mC*mA*mA-3’.
ATG7 aso1- 5’-mG*mU*mU*mG*mA*G*T*G*C*C*A*T*A*C*C*mA*mG*mU*mA*mG-3’.
GORASP aso1- 5’-
mG*mG*mA*mU*mA*G*A*C*C*T*A*G*T*C*A*mG*mG*mU*mA*mG-3’. RAB8A aso1-
5’-mU*mG*mG*mU*mU*G*A*C*C*T*G*G*T*C*C*mC*mA*mG*mU*mC-3’.

Controlled cortical impact
Severe TBI was performed as previously described
90
. In brief, mice were administered 0.5 mg/kg
of Buprenorphine SR subcutaneously prior to surgical procedures and anesthetized with 3-5%
isofluorane throughout the procedures. The head was then secured to a digital stereotactic frame
(RWD Life Sciences), hair around the head was shaved, scalp was cleaned 3 times with alternating
iodine and 70% ethanol wipes, and an incision was made from the base of the neck up to in between
175

the eyes. A 3mm diameter circular cranial window was drilled centred at Bregma -2.5 mm and
lateral 2.5 mm. Controlled impact was performed using a 2 mm metal flat-tip impactor (RWD) at
a velocity of 3 m/s, a depth of 1 mm and an impact duration of 180 ms. The scalp was closed with
sutures, and mice were allowed to recover from anesthesia on a heat pad. Mice undergoing sham
procedures were treated as above except for impact. Mice were monitored daily for 3 days post-
op. Mice were transcardially perfused at experimental endpoints with PBS followed by 4%
formaldehyde and cryoprotection in 30% sucrose. Brain tissue was snap frozen and stored at -
80⁰C.

Adult intracerebroventricular injection
Intracerebroventricular injections were performed as previously described
246
. Mice were secured
to a stereotactic frame and the skull was exposed as described above. Using a microdrill (RWD
Life Sciences), a small hole was made 1.00 mm to the right and 0.3 mm anterior of bregma. A
syringe (Hamilton #80014) with a 32 gauge needle (Hamilton #7752-05) was secured to a KDS
Legato 130 Syringe pump, zeroed at the hole and lowered -3.0 mm at a rate of 1 mm/sec. Up to 10
uL of ASO or the vehicle was delivered at 1 µL/s. Following 5-7 minutes after injection, the needle
was raised at 1 mm/s, and the skin was sutured. Mice were placed on a heated recovery pad until
fully ambulating. ASO sequences were custom-designed and synthesized at IDT with previously
described modifications. The following sequences were used: Negative control- 5’-
/52MOErC/*/i2MOErC//i2MOErT//i2MOErA//i2MOErT/A*G*G*A*C*T*A*T*C*C*/i2MOEr
A//i2MOErG//i2MOErG/*/i2MOErA/*/32MOErA/-3’. msKcnj2 aso1- 5’-
/52MOErT/*/i2MOErT//i2MOErC//i2MOErC//i2MOErT/T*G*A*A*A*C*C*T*T*T*/i2MOEr
G//i2MOErT//i2MOErG/*/i2MOErC/*/32MOErT/-3’. msKctd aso1- 5’-
52MOErG/*/i2MOErC//i2MOErA//i2MOErC//i2MOErA/G*A*C*T*G*T*T*T*C*T*/i2MOEr
C//i2MOErT//i2MOErG/*/i2MOErA/*/32MOErC/-3’. msKctd aso2- 5’-
52MOErT/*/i2MOErT//i2MOErA//i2MOErC//i2MOErC/A*G*A*G*A*G*C*T*T*C*/i2MOEr
T//i2MOErT//i2MOErC/*/i2MOErA/*/32MOErC/-3’. msKctd aso3- 5’-
/52MOErA/*/i2MOErA//i2MOErC//i2MOErA//i2MOErG/T*T*C*A*C*T*T*C*C*T*/i2MOEr
C//i2MOErT//i2MOErC/*/i2MOErC/*/32MOErT/-3’. msKcnj2 aso1- 5’-
/52MOErT/*/i2MOErT//i2MOErC//i2MOErC//i2MOErT/T*G*A*A*A*C*C*T*T*T*/i2MOEr
G//i2MOErT//i2MOErG/*/i2MOErC/*/32MOErT/-3’.

Rotarod assay
Mouse motor function, coordination, and equilibrium was tested using the Rotor Rod (SD
Instruments) rotarod assay as previously described
348
. In brief, animals were placed into the device
and run under the following conditions: 0 seconds 5 rpm; 300 seconds 5 to 50 rpm ramp.
Experiment was halted after completion of the time course, and latency to fall was recorded.
Animals were tested in triplicate for each timepoint.

Mouse pup antisense oligonucleotide and glutamate intracerebroventricular injection
Neonatal mice were cryo-anesthetized on ice prior to injection at postnatal day 1 and 3 (P1, P3).
Anesthetic depth was assessed by toe-pinch. Antisense oligonucleotides (ASOs) were
administered at P1 via intracerebroventricular (ICV) injection per previously established protocols
using a model 1701RN, 33-gauge 10 µL Neuros Syringe (Hamilton)
242
. 22.5 µg ASO in 1.5 µL
phosphate-buffered saline (PBS, pH=7.4) was given per animal. 40 nmol glutamate in 3 µL PBS
(or 3 µL PBS control) was injected ICV at P3 contralateral to ASO injection site. Mice were placed
in a clean, pre-warmed container to recover for 10 minutes or until responsiveness returned.
176

Animals were euthanized 48 hours later. Brain tissue was snap frozen, stored at -80⁰C, and
processed into 25 µM sections using a Leica CM3050S cryostat (Leica).

Genotyping of transgenic mice
Crude DNA was isolated from tail snips using Tail Lysis Buffer with 1:20 ProteinaseK at 55⁰C
overnight, followed by 85⁰C for 45 minutes. DNA was purified using the Monarch Genomic DNA
Purification Kit (NEB #T3010S) and quantification was determined by nanodrop. Purified DNA
was diluted to 7.5 ng/µL in UltraPure Distilled Water. Zygosity of Tg(Thy1-
MAPT*P301S)2541Godt mice was determined by qPCR. Primers were designed against human
MAPT and mouse Actb (β-actin) with the following sequences: MAPT-FWD- 5'-
GATTGGGTCCCTGGACAATA-3'; MAPT-REV- 5'-GTGGTCTGTCTTGGCTTTGG-3';
bActin-FWD-5'- CGAGGCCCAGAGCAAGAGAG -3'; bActin-REV- 5'-
CGGTTGGCCTTAGGGTTCAG-3'. DNA was mixed with 10 µL SYBRGreen Master mix (),
0.40 µM FWD primer, 0.40 µM REV primer, and UltraPure water for a final reaction volume of
20 µL/well. Samples were tested in triplicate for MAPT and Actb and run on a Roche LightCycler
qPCR machine under the following cycle conditions: 95⁰C for 3:30 minutes; (95⁰C for 0:10
minutes, 65⁰C for 0:30 minutes) x 45 cycles. Expression was calculated using ΔΔCt. Mice
homozygous for the transgene were identified as having a Ct value of 1 lower than the
heterozygous mice.

A.2 Experimental Models

Cell Lines
Lymphocytes from healthy donors and ALS/FTD patients harbouring the C9ORF72 GGGGCC
repeat expansion, and their isogenic controls were obtained from the NINDS Biorepository at the
Coriell Institute and reprogrammed into iPSCs as previously described
275
. Cell lines derived from
FTLD-Tau patients harbouring the V337M point mutation, and their corresponding CRISPR-
corrected isogenic control, were acquired and generated by the Tau Consortium Stem Cell Group
as previously described: GIH6-E11 (WT/WT), GIH6-A02 (V337M/WT), GIH7-B12 (WT/WT),
GIH7-A01 (V337M/WT), ND-B06 (WT/WT), ND-B09 (V337M/WT)
117
.The cell line containing
a stable integration of dCas9-BFP-KRAB and TetO-Ngn2 into the CLYBL locus was a generous
gift from Dr. Martin Kampmann at UCSF
163
. Cells were maintained under feeder-free conditions
on Matrigel (BD) in mTeSR1 medium (Stem Cell Technologies) at 37⁰C and 5% C02. Cells were
fed daily with 2 mL mTeSR1 per well. Cultures were not grown in excess of 80% confluency, and
passaging of iPSC colonies was performed using 10 µM EDTA.

Generation of cortical organoids
The generation of human cortical organoids was adapted from a previously published protocol
66
. In brief,
iPSCs at ~70% confluence were dissociated into single cells with Accutase (Stem Cell Technologies) and
10,000 cells/well were seeded into a 96-well U-Bottom Low-Attachment plate (Corning) in mTeSR1 + 10
µM ROCK inhibitor (Y-27632; Tocris) to generate iPSC spheroids. Media was replaced 24h after seeding
with mTeSR1 without ROCK inhibitor. For the following 5 days, neural induction was initiated with 10
µM dorsomorphin (Cayman Chemicals) and 10 µM SB-431542 (Cayman Chemicals) in DMEM/F12
containing 20% KnockOut Serum (Gibco), 1 mM non-essential amino acids (Gibco), 1X GlutaMAX and
0.1 mM b-mercaptoethanol. From days 6-15, media was refreshed daily with neural medium (Neurobasal-
A (Invitrogen), B-27 Supplement without vitamin A (Gibco), 1X GlutaMAX, 2% penn/strep) supplemented
with 20 ng/mL bFGF (Peprotech) and 20 ng/mL EGF (Peprotech), and every other day from days 16-25.
On day 20, organoids were transferred to 6-well low attachment plates (Corning) and placed on an orbital
177

shaker rotating at 60 rpm. From days 26-43, media was refreshed every other day with neural medium
containing 20 ng/mL NT-3 (Peprotech) and 20 ng/mL BDNF (R&D). Organoids were maintained from day
43 onwards in neural medium and refreshed every 3-4 days.
Ngn2-induced cortical spheroids (NGN2-organoids) were produced using iPSC lines with an integrated Tet-
ON hNGN2 in the CLYBL locus. iPSC’s were grown to 80% confluency, treated with 2 µg/mL doxycycline
for 60 minutes in mTeSR1, then dissociated into single cells with Accutase and seeded into 96-well U-
Bottom Low-Attachment plates at 30,000 cells/well in neural medium supplemented with 2 µg/mL
doxycycline, 10 ng/mL NT-3, 10 ng/mL BDNF, 0.33% Matrigel, and 10 µM ROCK inhibitor. Fresh
medium with 2 µg/mL doxycycline, 10 ng/mL NT-3, 10 ng/mL BDNF, and 0.33% Matrigel was added
daily on day 1-5, and every other day from day 6-10. Spheroids were maintained from day 10 onwards in
neural medium with 10 ng/mL NT-3 and 10 ng/mL BDNF refreshed every 3 days.

High-intensity focused ultrasound (HIFU)
We used a custom-built focused ultrasound machine mounted on a stereotactic frame as previously
described
128
. In brief, a 6.4 cm 510 kHz transducer (H107 & Y107 Sonic Concepts) was attached
within a 3D-printed coupling cone filled with degassed water. An Agilent 33220A waveform
generator drove a Henry Electronics 50 watt amp and was monitored using a PVDF hydrophone
(RP Acoustic, RP24l) and an oscilloscope in FFT mode (Tektronics TDS3014B). Assuming 0%
attenuation, the acoustic pressure generated by this apparatus was calculated using the formula P
= V/M(f), where P is the acoustic pressure, V is the input voltage (V, volts), and M(f) is the
sensitivity of the hydrophone as a function of frequency (150 mV/MPa for the hydrophone used
here).

Mouse models
All animal care and use were in accordance with local institution guidelines of the University of
Southern California and approved by the Institutional Animal Care and Use Committee (IACUC)
board of the University of Southern California under protocol numbers 11938 and 21174. Wildtype
C57Bl/6J mice from Jackson Laboratories (Stock No: 000664). Transgenic humanized-tau mice
(strain: Tg(Thy1-MAPT*P301S)2541Godt) were kindly gifted by Dr. Daniel Geschwind and Dr.
Liting Deng with permission from Dr. Michel Goedert
113
. Mice were housed under standard
conditions with food and water ad libitum in the University of Southern California’s vivarium.
Eight-twelve week old littermates were used for all experiments unless otherwise noted.

A.3 Statistical Analysis

Analysis was performed using the statistical package Prism (GraphPad Prism Version 9.3.1).
Statistical analysis of neuron survival experiments was conducted using a two-sided log-rank test.
For each condition, survival data from 100 SYN1::eGFP neurons were randomly selected and used
to generate a survival curve unless otherwise stated. For all other experiments, differences between
two groups were calculated using a two-tailed Student’s t-test (when data was normally
distributed) or two-sided Mann-Whitney test to compare ranks if data was not normally distributed.
Differences between three or more groups were analyzed by One-way ANOVA with Tukey
correction for multiple testing. Significance was assessed by P < 0.05. Error bars represent s.e.m.
unless otherwise stated.

Abstract (if available)

Abstract Dementia-related diseases have a devastating personal and societal impact and present a significant challenge to the biomedical field. This is due in part to a diverse genetic etiology giving rise to diseases like amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), where up to 70% (FTD) and 90% (ALS) of cases are sporadic. Additionally, environmental impacts which contribute significantly to the risk of developing dementia such as traumatic brain injury (TBI) have highly variable biophysical forces and complex pathophysiology which complicate efforts to advance new therapies to humans. The ability to study these processes, especially the interplay between environmental and genetic contributions to neurodegeneration, has largely eluded researchers. Recently, the use of patterned brain organoids has shown promise to bridge the translational gap between traditional in vitro and in vivo models while preserving human biology and the capacity for genetic manipulation and large-scale screening approaches. In this thesis, I present our efforts to develop organoid models of TBI and glutamate excitotoxicity with overlap between genetic models of ALS and FTD, respectively. In these models, we demonstrate key neurodegenerative phenotypes and disease-specific susceptibilities that underlie known pathogenic mechanisms and identify therapeutic targets to mitigate these effects. Together, the work presented here has contributed to the advancement of disease modeling and improved understanding of pathophysiology while identifying promising genetic targets in multiple neurodegenerative diseases.

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Asset Metadata

Creator Berlind, Joshua Eugene (author)

Core Title Identification of therapeutic targets in human cerebral brain organoid models of neurodegeneration

School Keck School of Medicine

Degree Doctor of Philosophy

Degree Program Development, Stem Cells and Regenerative Medicine

Degree Conferral Date 2023-05

Publication Date 05/03/2024

Defense Date 04/24/2023

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

Tag amyotrophic lateral sclerosis,frontotemporal dementia,neurodegeneration,OAI-PMH Harvest,organoid,traumatic brain injury

Format theses (aat)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Quadrato, Giorgia (committee chair), Ichida, Justin (committee member), Ying, Qilong (committee member), Zhao, Zhen (committee member), Zlokovic, Berislav (committee member)

Creator Email berlind@usc.edu,joshberlind@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC113099381

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