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Popova, Retallack etal. eLife 2023;12:RP87696. DOI: https://doi.org/10.7554/eLife.87696 1 of 20
Rubella virus tropism and single- cell
responses in human primary tissue and
microglia- containing organoids
Galina Popova1,2,3,4,5,6†, Hanna Retallack6†, Chang N Kim1,2,3,4,5,6, Albert Wang1,2,3,4,5,6,
David Shin1,2,3,4,5,6, Joseph L DeRisi6,7*, Tomasz Nowakowski1,2,3,4,5,6*
1Department of Neurological Surgery, University of California, San Francisco, San
Francisco, United States; 2Eli and Edythe Broad Center for Regeneration Medicine
and Stem Cell Research, University of California, San Francisco, San Francisco,
United States; 3Department of Anatomy, University of California, San Francisco,
San Francisco, United States; 4Department of Psychiatry and Behavioral Sciences,
University of California, San Francisco, San Francisco, United States; 5Weill Institute
for Neurosciences, University of California, San Francisco, San Francisco, United
States; 6Department of Biochemistry and Biophysics, University of California, San
Francisco, San Francisco, United States; 7Chan Zuckerberg Biohub, San Francisco,
United States
Abstract Rubella virus is an important human pathogen that can cause neurological deficits in a
developing fetus when contracted during pregnancy. Despite successful vaccination programs in the
Americas and many developed countries, rubella remains endemic in many regions worldwide and
outbreaks occur wherever population immunity is insufficient. Intense interest since rubella virus was
first isolated in 1962 has advanced our understanding of clinical outcomes after infection disrupts
key processes of fetal neurodevelopment. Yet it is still largely unknown which cell types in the devel-
oping brain are targeted. We show that in human brain slices, rubella virus predominantly infects
microglia. This infection occurs in a heterogeneous population but not in a highly microglia- enriched
monoculture in the absence of other cell types. By using an organoid- microglia model, we further
demonstrate that rubella virus infection leads to a profound interferon response in non- microglial
cells, including neurons and neural progenitor cells, and this response is attenuated by the presence
of microglia.
eLife assessment
The manuscript represents an important study on the pathogenesis of rubella virus tropism and
neuropathology in human microglia- containing human stem cell derived organoids and human
fetal brain slices. The strength of evidence is compelling, employing two different human- relevant
models. The findings will be of broad interest to virologists and infectious disease experts, as well
as neurodevelopmental biologists. The findings could also be of interest to pediatrics and obstetrics
clinical colleagues.
Introduction
Neurotropic viruses contracted during pregnancy can have grave consequences for the fetus. These
comprise both viruses of longstanding concern like human cytomegalovirus and herpes simplex virus
as well as emerging viruses like Zika virus. Yet our understanding of how direct viral infection and
SHORT REPORT
*For correspondence:
joseph.derisi@ucsf.edu (JLDeR);
tomasz.j.nowakowski@gmail.
com (TN)
†These authors contributed
equally to this work
Competing interest: The authors
declare that no competing
interests exist.
Funding: See page 16
Preprint posted
24 October 2022
Sent for Review
31 March 2023
Reviewed preprint posted
23 May 2023
Reviewed preprint revised
22 June 2023
Version of Record published
20 July 2023
Reviewing Editor: Joseph G
Gleeson, University of California,
San Diego, United States
Copyright Popova, Retallack
etal. This article is distributed
under the terms of the Creative
Commons Attribution License,
which permits unrestricted use
and redistribution provided that
the original author and source
are credited.
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indirect inflammatory consequences affect fetal brain development is limited. This is true even for
well- studied pathogens like rubella virus (RV), which is an enveloped, single- stranded RNA virus of
the family Matonaviridae restricted to human transmission. Infection with RV typically causes a mild,
self- limiting illness with a characteristic rash during childhood, often referred to as ‘German measles’.
However, infection during pregnancy can cause miscarriage, stillbirth, or a range of birth defects
including congenital rubella syndrome (CRS). The sequelae of congenital RV infection were first recog-
nized in 1941 and although the first RV vaccines were licensed in 1969, an estimated 105,000 infants
with CRS were born each year worldwide as of 2010 (Vynnycky etal., 2016). As of 2019, RV- con-
taining vaccine coverage remains incomplete and inconsistent, with ongoing endemic transmission
and reporting gaps primarily in the African, Eastern Mediterranean, and South- East Asian World
Health Organization Regions (World Health Organization, 2020). Countries with RV- containing
vaccine programs also remain susceptible to outbreaks, such as Japan and China, where outbreaks
in 2013–14 and 2018–19 caused a twofold increase in reported rubella cases worldwide (26,033 total
cases in 2018 vs 49,179cases in 2019) (Plotkin, 2021) and included CRS the following year (423 total
cases worldwide in 2019 vs 1252cases in 2020) (World Health Organization, 2022).
The most common features of CRS are congenital cataracts, sensorineural deafness, and cardiac
defects (Banatvala and Brown, 2004). In addition, microcephaly (Munro etal., 1987), developmental
delay and autism (Chess, 1977), and schizophrenia spectrum disorders (Brown etal., 2001) are asso-
ciated with the syndrome, but the pathophysiology of these neurological complications is not well
described. To gain mechanistic insight into the pathophysiology of CRS, it is essential to understand
the tropism of the virus. Initial infection in the lymphoid tissues of the nasopharynx and upper respi-
ratory tract leads to systemic viremia, with virus spread across the placenta and into nearly all fetal
organs on post- mortem examination, primarily via infected mononuclear cells (Nguyen etal., 2015).
As for the fetal nervous system, RV was isolated from cerebrospinal fluid and brain tissue of fetuses
and infants with CRS in studies from the 1960s (Bellanti etal., 1965; Esterly and Oppenheimer,
1967; Korones, 1965; Monif etal., 1965). However, further details of where RV might replicate in the
brain are lacking. Autopsies in that early era revealed nonspecific gliosis and cerebral vessel degener-
ation (Rorke and Spiro, 1967). In limited pathology specimens from more recent outbreaks, RV RNA
and antigens were identified in rare cells in the cortex and cerebellum presumed to be ‘nerve cells’
and neural progenitor cells (Lazar etal., 2016; Nguyen etal., 2015). Experimental infections of cells
that might not accurately represent the primary cells in the developing brain have yielded little further
insight. To complicate the matter, myelin oligodendrocyte glycoprotein (MOG) has been proposed as
a cellular receptor for RV (Cong etal., 2011), but it is exclusively expressed in oligodendrocytes in
the human brain and therefore cannot explain infection in other cell populations. Thus, there is clear
evidence for the presence of RV in the central nervous system in infants with CRS, but the identity of
infected cell type(s) remains elusive.
Here, we address RV tropism in the human developing brain and other poorly understood molec-
ular aspects of CRS. By combining primary human brain tissue with a variety of cell culture techniques,
we show that microglia are the predominant cell type infected by RV. Furthermore, we show that
diffusible factors from non- microglia cells are necessary to render microglia susceptible to RV. By using
brain organoids supplemented with primary microglia, we demonstrate that RV infection leads to a
robust interferon response and leads to dysregulation of multiple genes implicated in human brain
development. Finally, we compared transcriptomic changes between microglia- transplanted and non-
transplanted organoids and found that in the presence of microglia, interferon pathway upregulation
following RV exposure is reduced.
Results
RV infects microglia in the human developing brain
To investigate RV tropism in the human brain, cultured cortical slices from mid- gestation samples
were infected with M33 RV, representing a laboratory strain originally derived from a clinical isolate
(Figure1A). At 72 hr post- infection, immunostaining for the RV capsid protein revealed numerous
cells positive for the RV antigen, of which >90% were co- labeled with the microglia marker Iba1
(Figure1B–D). To confirm functional transcription and translation of the viral genome, a new reporter
construct of RV designed to express GFP within the non- structural P150 gene was generated (RV- GFP,
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GenBank Accession OM816675, Figure1E) and validated by GFP expression in Vero cells (Figure1—
figure supplement 1). In human primary brain slices infected with RV- GFP, GFP expression was
detected predominantly in microglia, confirming the production of RV proteins inside this cell type
(Figure1F) consistent with the wild type M33 RV.
Cell microenvironment influences RV infectivity
Such specificity of RV for microglia in this model is striking given that microglia represent only 1–5% of
the cells of the human developing brain (Menassa etal., 2022). Moreover, the previously published
viral entry factor MOG is not specific to microglia according to analysis of publicly available RNA and
protein expression profiles of the human developing brain (Nowakowski etal., 2017) (https://cells.
ucsc.edu/?ds=cortex-dev&gene=MOG) or human radial glial cells (Eze et al., 2021) (https://cells.
ucsc.edu/?ds=early-brain&gene=MOG). Further, common components of the host cell membrane,
such as sphingomyelin and cholesterol that appear to be essential for RV entry (Otsuki etal., 2018),
cannot explain viral tropism for microglia. Thus, to identify factors contributing to the relatively
Figure 1. Rubella virus (RV) infects primary human microglia in cultured brain slices. (A) Schematic for brain slice infection. Mid- gestation (GW18- 23)
human brain slices were infected with RV for 72hr. (B, C) Immunostaining for RV capsid and Iba1 in cultured cortical slices at 72 hpi, at 10× (scale
bar 100μm) (B)and at 40× magnication (scale bar 50μm) (C).(D) Quantication of RV capsid- positive cells co- labeled with microglial marker Iba1:
764/819 (93.3%) of RV+ cells were microglia based on Iba1 staining across four biological replicates. Error bars denote standard deviation. (E) Diagram
of viral genome of GFP- expressing RV (RV- GFP). Cortical brain slices were infected with RV- GFP for 72hr. (F) Examples of GFP uorescence and Iba1
immunostaining at 72 hpi of cultured cortical slices with GFP- RV, at 62× (scale bar 20μm). GFP expression of modied RV is localized to Iba1- positive
microglia cells (arrows).
The online version of this article includes the following gure supplement(s) for gure 1:
Figure supplement 1. GFP expression in rubella virus (RV)- infected Vero cells.
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specific infection of microglia, RV infectivity was tested in monocultures of primary human microglia.
Microglia from mid- gestation cortical brain samples were purified using magnetic- activated cell
sorting (MACS) and then subsequently infected with RV (Figure2A). Surprisingly, RV infection of the
microglia monoculture was negligible (Figure2B). To resolve this apparent paradox, we investigated
whether microglia infectivity could be restored by the presence of other cell types, such as neurons
or progenitor cells. Microglia were co- cultured with either neuronally enriched cultures (sorted with
PSA- NCAM magnetic beads) or the glial component (flow- through that was depleted of both the
CD11b- positive microglia cells and the PSA- NCAM- positive population). Both conditions together
with mixed brain cells (flow- through from CD11b- depleted fraction; FT) successfully restored infection
(Figure2C–E). In the pure microglial cultures, less than 2% of microglia were positive for RV capsid
by immunostaining, but when different cell fractions were added to the culture (neuronal, glial, or
mixed cultures), up to 60% of microglia had RV capsid immunopositivity (Figure2F). Similar to the
cortical brain slices, microglia represented the main cell type infected with RV in the mixed co- cultures
Figure 2. Rubella virus (RV) infection of microglia is dependent on the presence of other cells. (A) Schematic of rubella infection. Primary prenatal
brain tissue was dissociated and different cell types were puried using magnetic- activated cell sorting (MACS). Microglia cells were cultured alone
or in combination with neurons, glial cells, or all cell types. 2D cultures were infected with RV for 72hr and processed for immunostaining. (B–E)
Representative images of microglia cultured with different cell types. Cell cultures were stained for microglia marker Iba1 (red), RV capsid (green), and
DAPI (gray; on the overlay Merge channel). (B) Puried microglia only. (C) Microglia and neurons (puried with PSA- NCAM magnetic beads) co- cultured
at 1:5 ratio. (D) Microglia and glial cell types (ow- through fraction after PSA- NCAM magnetic beads) cultured together at 1:5 ratio. (E) Microglia
cultured with non- microglial cells (ow- through after CD11b magnetic beads; mixed cell populations) at 1:5 ratio. (F) Quantication of RV capsid
immunopositivity among microglia (Iba1+) for conditions in B–E. FT: ow- through after microglia MACS purication. Error bars denote SEM. Each data
point (N=4) represents a eld of view from the same experimental batch and represents a technical replicate. (G) Quantication of microglia (Iba1+)
among RV capsid- positive cells.
The online version of this article includes the following gure supplement(s) for gure 2:
Figure supplement 1. Rubella virus (RV) inoculum dilution in mixed co- cultures of microglia and non- microglia cells.
Figure supplement 2. Rubella infection in non- microglia cells.
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(Figure2G). Furthermore, mixed cultures inoculated with lower viral titers had fewer cells with RV
capsid immunopositivity overall, but retained a high proportion of infected microglia demonstrating
specificity for microglia (Figure2—figure supplement 1A–C). Despite RV capsid co- localizing with
microglia cells and GFP protein being produced from RV- GFP in microglia, RV titering experiments
failed to detect significant production of newly released virions in microglia co- cultures (Figure2—
figure supplement 1D). No statistically significant difference was detected in RV infectivity in cells
cultured with or without microglia (Figure2—figure supplement 2).
We then tested whether RV capsid immunopositivity in microglia could be due to phagocytic activity
by this macrophage population. To exclude microglia engulfing other infected cells, a transwell system
Figure 3. Direct cell- cell contact is not required for microglia infection by rubella virus (RV). (A) Schematic for experimental setup. Primary human brain
tissue was dissociated, and microglia were cultured with or without microglia- depleted ow- through portion. Cells were co- cultured in direct contact or
in solution- permeable chambered transwells (TW). (B) Representative images of microglia- enriched cultures (top row), microglia cultured with other cell
types in the same well (middle row), and microglia cultured in the bottom compartment with other cell types cultured in a permeable transwell chamber
(bottom row) infected with RV for 72hr. (C) Quantication of RV capsid immunopositivity among microglia (Iba1+). Three elds of view across the same
experiment were quantied for each condition and represent technical replicates. Error bars represent SEM. p- value between microglia and co- culture
condition is 0.0479. p- value between microglia and transwell condition is 0.0159. (D) Quantication of microglia (Iba1+) among RV capsid- positive cells.
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was employed where microglia and other cell types are grown in compartments separated by a semi-
permeable membrane that allows media exchange without direct cell- cell contacts (Figure3A). Both
the presence of other cell types in the same well (co- culture) and the media exchange between the
two chambers (transwell) restored infection in microglia (Figure3B–C). Consistent with our previous
experiments, microglia represented the main cell type infected with RV (Figure3D). Together, these
results suggest that RV capsid immunostaining cannot be explained by phagocytosis of other infected
cells, but it is possible that infection of microglia is influenced by diffusible factors from other cell
populations found in the tissue microenvironment.
Rubella infection elicits an interferon response in brain organoids
Given the striking difference in infection rates in different cell environments, we next investigated
how the presence of microglia modulates response to the viral infection in other cell populations. We
used brain organoids as a model of early brain development that, unlike primary brain slices, can be
cultured for prolonged period of time to investigate long- term consequences of RV exposure. Under
standard protocols, brain organoids do not robustly develop any cells of myeloid origin, making them
a useful reductionist model for investigating the role of immune cells in brain homeostasis and devel-
opment (Nowakowski and Salama, 2022). Brain organoids were generated following previously
established protocols (Paşca etal., 2015), and at 5 weeks of differentiation, when the majority of
cell types are present in the organoids, mid- gestation primary human microglia were introduced as
previously described (Popova etal., 2021). After allowing microglia to engraft into the organoids, we
exposed neuroimmune organoids to RV or heat- inactivated control and cultured them for 72hr or 2
weeks to identify short- and long- term consequences of the viral exposure (Figure4A). In organoids
with engrafted primary microglia subsequently exposed to RV, immunostaining revealed RV capsid in
microglia, similar to primary tissue and co- culture experiments. We detected RV capsid in microglia,
but not in other cell types, in both timepoints, suggesting that microglia remain the main cell popula-
tion that harbors viral infection (Figure4B–C).
To determine brain- wide consequences of the RV infection across different cell types, at 72hr
after RV exposure we processed neuroimmune organoids for single- cell RNA sequencing (scRNAseq)
with 10x Genomics and downstream analysis. After processing for scRNAseq, cells with fewer than
500 detected genes and/or more than 20% mitochondrial genes were removed from the anal-
ysis. Ribosomal transcripts and pseudogenes were excluded. Approximately 11,000 cells passed
filtering criteria (Figure 5A, Figure 5—figure supplement 1A–C), revealing the expected major
cell populations of the human developing brain (Nowakowski et al., 2017), including radial glia
cells, immature and mature neurons, and astrocytes (Figure 5A–B). Cell cluster annotations were
assigned based on combinations of co- expressed cluster marker genes, such as FGFBP2 and SOX2
for radial glial cells (clusters 5 and 10), TAGLN3, HES6, NEUROD4 for neural progenitor cells (cluster
7), TUBB2A, TUBB2B, STMN2 for neurons (cluster 2), CLU, PTN, and SPARCL1 for astrocytes (cluster
6), and MKI67, UBE2C, and CENPF for dividing cells (clusters 3 and 4) (Figure5B, Figure5—figure
supplement 1D–E for individual cluster marker genes, Figure 5—source data 1 for the full list
of markers). Cells derived from organoids with and without microglia were present in all clusters
(Figure 5C). A separate microglia cluster was not identified. Rare cells expressing the microglia
marker AIF1 (encoding the Iba1 protein) were present, but such cells have been previously reported
to develop spontaneously in organoids (He etal., 2022) and the canonical microglia marker P2RY12
was not detected in those cells (Figure5—figure supplement 1F). We attribute the apparent lack
of microglia to both the small starting population and loss due to cell dissociation during processing
for scRNAseq. Consistent with the lack of microglia cells in our scRNAseq data, we did not recover
appreciable numbers of the viral transcripts. However, exposure of organoids to RV resulted in signif-
icant transcriptomic differences including genes involved in the interferon signaling pathway and
its response (IFI27, IFI6, IFITM3) (HLA- A [Campbell etal., 1986; Keskinen et al., 1997] and BST2
[Holmgren et al., 2015]) (cluster 1, Figure 5E, Figure 5—figure supplement 1 and Figure 5—
source data 1). The majority of cells in cluster 1 came from RV- exposed organoids (Figure5D). While
genes involved in the interferon response showed increased expression in organoids both with and
without microglia, the magnitude of their upregulation was lower among cells in microglia- containing
organoids (Figure5E–F). We confirmed higher expression levels of IFITM3 protein in organoids with
microglia exposed to RV in comparison to organoids with microglia exposed to heat- inactivated RV
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Figure 4. Microglia in neuroimmune organoids are infected with rubella virus (RV). (A) Primary human microglia were transplanted into brain organoids
and resulting neuroimmune organoids were exposed to RV. After 72hr or 2weeks organoids were processed for immunouorescence validation (this
gure) or single- cell RNA sequencing (scRNAseq) analysis (Figure5). (B) Representative immunouorescence images of brain organoids without
microglia subjected to RV exposure for 72hr. Radial glial cells are labeled with Sox2 (cyan), microglia are labeled with Iba1 (red), and RV is labeled with
anti- RV capsid antibody (green). Scale bar is 50μm. (C) Representative immunouorescence images of brain organoids with microglia at 72hr (top
panel) or 2weeks (bottom panel) after RV exposure. Radial glial cells are labeled with Sox2 (cyan), microglia are labeled with Iba1 (red), and RV is labeled
with anti- RV capsid antibody (green). Dashed boxes represent zoomed- in examples of microglia cells. Scale bar is 50μm.
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Figure 5. Rubella virus (RV) exposure of brain organoids leads to interferon response. (A) Single- cell RNA sequencing analysis identied 13 clusters,
including neurons and glial cells (Div.: dividing cells, RG: radial glia, Astros: astrocytes, IPCs: intermediate progenitor cells). (B) Dot plot depicting cluster
marker genes for each cluster. (C) Uniform manifold approximation and projection (UMAP) plots of organoids colored by the presence or absence of
microglia. (D) UMAP plots of organoids colored by the presence or absence of RV treatment. (E) Feature plot for expression levels of IFITM3. (F) IFITM3
expression in all cells across different conditions. (G) Representative images of IFITM3 immunouorescence in brain organoids with microglia with wild
type RV (bottom panel) or heat- inactivated control (top panel) 72hr post- infection. IFITM3 is labeled in magenta, microglia are labeled with Iba1 (green),
cell nuclei are labeled with DAPI (gray). (H) Quantication of uorescence intensity of IFITM3 normalized to DAPI intensity per organoid. Columns
represent mean of four organoids. Dots represent averages across several sections for each individual organoid. Error bars represent SEM. Unpaired
parametric Student’s t- test was used to compare the two groups in H–I. p- value = 0.04. (I) Quantication of uorescence intensity of DAPI staining per
organoid. p- value = 0.22.
The online version of this article includes the following source data and gure supplement(s) for gure 5:
Source data 1. Cluster marker genes for brain organoid single- cell RNA sequencing (scRNAseq) dataset, related to Figure5.
Source data 2. Differentially expressed genes detected in brain organoid single- cell RNA sequencing (scRNAseq) dataset, related to Figure5.
Figure supplement 1. Single- cell RNA sequencing (scRNAseq) analysis of brain organoids.
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at 72hr post- exposure (Figure5G–H), while the overall cell numbers were not changed in either
condition (Figure5I).
To investigate how the presence of microglia and RV exposure modulate gene expression profiles
across different cell populations, we stratified gene expression differences based on the major cell
types for each of the four conditions (absence and presence of microglia; absence or presence of
RV exposure). Radial glia and dividing cells had a greater transcriptomic response to RV exposure as
compared to neurons, both with and without microglia (Figure6A). Cells captured from microglia-
containing organoids showed fewer differentially expressed genes in response to RV in each of the
major cell classes compared to organoids that did not contain microglia (Figure6A, top vs bottom
panel), with radial glia and neurons reaching statistically significant levels (p- values shown on the right
side of the panel) and neural progenitor cells showing the overall trend without reaching statistical
significance. One gene family that was specifically downregulated in the presence of RV in organoids
without microglia included nuclear factor I – NFIB and NFIA (Figure6A, Figure 5—source data 2)
– two genes that form heterodimers in vivo and are associated with induction of gliogenesis (Tchieu
etal., 2019) in embryonic brain development. Early disruption in the function of either gene is asso-
ciated with neurodevelopmental deficits and perinatal mortality in mice (das Neves et al., 1999;
Steele- Perkins etal., 2005) and with intellectual disability in humans (Schanze etal., 2018).
Genes with expression levels affected both by the presence of microglia and by RV exposure
included NOVA alternative splicing regulator 1 (NOVA1) (Figure6B). NOVA1 is a master regulator of
alternative splicing (Zhang etal., 2010) in the central nervous system with potential links to neurolog-
ical diseases (Parikshak etal., 2016). Unlike primary brain slices, brain organoids can be cultured for
extended periods of time, providing a human- specific model for studying long- term consequences
of RV infection. To better mimic normal human brain development, we used neuroimmune organ-
oids with microglia exposed to RV or heat- inactivated controls to determine how the presence of
the viral infection influences NOVA1 expression and neuronal cell differentiation. After 2 weeks, we
used immunostaining to quantify numbers of neurons or intermediate progenitor cells (IPCs) – two
major cell types with the most robust predicted NOVA1 level changes based on the scRNAseq exper-
iment (Figure6C). We detected a statistically significant decrease of NOVA1+ IPCs in response to RV
exposure (Figure6E). Numbers of NOVA1+ neuronsalso had a trend toward reduction (Figure6D);
however, it did not reach statistical significance. Concurrently with reduction of NOVA1+ cells, we
detected lower numbers of neurons (Figure 6F), but not IPCs (Figure 6G), in organoids after RV
exposure.
Discussion
Here, we demonstrate that in the developing brain RV predominantly infects microglia, the resident
macrophage population. This finding is consistent with RV tropism for monocytes in the periphery
(Perelygina etal., 2021; van der Logt etal., 1980), and adds new information to the limited under-
standing of RV infection in the central nervous system. Supporting data from real- world infections
including post- mortem specimens would be helpful to evaluate clinical strains. Tropism for microglia
raises interesting questions about how and where RV persists in CRS, perhaps in brain tissue during
the extended period of viral shedding, similar to other relatively immuno- privileged sites such as the
eye (Doan etal., 2016; Sugishita etal., 2016). Notably, we did not detect significant production
of newly released virions, suggesting potential limitations of the culture system. Our findings also
help contextualize CRS in comparison to congenital infections by other neurotropic viruses: human
immunodeficiency virus type 1 and Zika virus, which target microglia directly; herpes simplex virus,
which replicates poorly in microglia with cytopathic effect; and human cytomegalovirus, which causes
microglia to produce antiviral cytokines without productive infection or cytopathic effect (Lum etal.,
2017; Retallack etal., 2016; Rock etal., 2004).
Like some of these other viruses, we found that by establishing viral transcription and translation in
microglia, RV elicits a strong interferon response in other cell types. It has been previously shown that
the interferon response in neurons derived from induced pluripotent stem cells can induce molecular
and morphological changes associated with neurodevelopmental disorders, including neurite length
and gene expression changes associated with schizophrenia and autism (Warre- Cornish etal., 2020).
The interferon response is additionally associated with pathobiology in a range of congenital infec-
tions and interferonopathies (Crow and Manel, 2015). Furthermore, in our preliminary experiments
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Figure 6. NOVA1 expression is reduced in response to rubella virus (RV) exposure. (A)Differentially expressed genes in different cell types in response
to RV treatment without (top panel) and with microglia (bottom panel). IPCs – intermediate progenitor cells. In the presence of microglia, fewer
differentially expressed genes in response to RV treatment were identied across all major cell types. In organoids with microglia, NOVA1 trended
toward a decrease in IPCs and neurons (labeled in blue in the panel). Kolmogorov- Smirnov test was used on DEGs with p- value <0.05. ***<0.001,
NS – not signicant, *<0.05. (B)Violin plot for NOVA1 that is differentially expressed in response to RV and presence of microglia. IPCs – intermediate
progenitor cells, RG – radial glia, Div. – dividing cells, EN – excitatory neurons. (C)Representative images of RV- exposed organoids with microglia at
2weeks post- exposure, stained with DAPI for cell nuclei (blue), NOVA1 (magenta), NeuN for neurons (green), and EOMES for intermediate progenitor
cells (cyan). (D)Cell number quantication for NeuN+ neuronsthat were also positive for NOVA1 in control (heat- inactivated RV) or RV condition.
Averages of 3- 5 sections (technical replicates) across 3 organoids (biological replicates, individual data points) where used for quantication in D-
G. Unpaired parametric Student’s t- test was used to compare the two groups in D–G. p- value = 0.088. (E)Cell number quantication for EOMES+
intermediate progenitors that were also positive for NOVA1 in control (heat- inactivated RV) or RV condition. p- value = 0.0042. (F)Cell number
quantication for NeuN+ neurons per organoid area displayed in 1000 cells × mm2 or organoid surface area in control (heat- inactivated RV) or RV
condition. p- value = 0.0004. (G) Cell number quantication for EOMES+ intermediate progenitor cells per organoid area displayed in 1000 cells × mm2
or organoid surface area in control (heat- inactivated RV) or RV condition. p- value = 0.86.
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in organoids, where microglia do not develop under standard protocols, the RV- induced interferon
response was attenuated in the presence of microglia, suggesting a possible protective role of
microglia on other cell types. One limitation of the current work is the lack of information on tran-
scriptional differences in microglia in the context of RV- exposed organoids due to the low number
of recovered microglia in scRNAseq experiments. However, our data on molecular changes in neural
progenitor cells and neurons, which likely produce the bulk of neurological symptoms seen in CRS,
provide a valuable resource for future investigation of congenital viral infections. Our finding that the
presence of microglia may reduce RV- associated transcriptional differences across different cell popu-
lations may also shed light on neuroimmune consequences of other congenital infections that coin-
cide temporally with phases of microglia population expansion and reduction (Menassa etal., 2022).
Interestingly, RV infection rates were largely influenced by the local cell environment, where prox-
imity to non- microglia cells was necessary for RV infection of microglia. This requirement did not
depend on cell- to- cell contact or cell type, thus eliminating phagocytosis of infected non- microglia
cells or cell type- specific factors as the explanation for enhanced microglia infectivity. It is possible
that the non- microglia supporting cells generate a reservoir of virus, though infection of non- microglia
cells was limited and it is unclear how these virions would be different from virions in the viral stocks.
More likely, diffusible factors contribute to RV infection of microglia, perhaps in conjunction with
other ubiquitous cell surface elements. For instance, such factors could alter the activation state of
microglia and thereby alter infectivity. Based on previous reports in 2D cell cultures and pathology
examination of infected tissues, RV can establish infection in a variety of cell types, suggesting that
the viral entry receptor is ubiquitously expressed, or that viral entry is facilitated by cell membrane
components and their modifications. Indeed, membrane phospholipids and glycolipids have been
shown to participate in viral entry (Mastromarino etal., 1990; Otsuki etal., 2018). While our study
did not directly address the molecular mechanisms of entry, our findings motivate new directions
to advance our limited understanding of host factors needed for RV entry and infection. Moreover,
our study highlights the importance of considering tissue complexity when studying viral infection in
brain organoids. Complex, multi- lineage organoids can now be designed by incorporating vascular
or immune cells into differentiation protocols (Cakir etal., 2022; Cakir etal., 2019; Popova etal.,
2021). We show that transcriptomic consequences of RV exposure are dependent on the presence
of microglia in the organoid tissue environment, while future studies will be needed to determine the
precise mechanisms that mediate this effect. One possibility is that microglia become the predomi-
nant cellular target of RV infection. Another possibility is microglia actively altering the microenviron-
ment to modulate the antiviral response.
Clearly, efforts to eliminate RV worldwide through vaccination are a priority. However, our work
on neuroimmune interactions in CRS may inform how early brain development goes awry in many
contexts including prenatal infection with other neurotropic viruses, genetic conditions associated
with dysregulated interferon responses such as Aicardi Goutières syndrome, and a variety of perturba-
tions that activate common inflammatory pathways. Understanding the specific role of microglia may
be key to unlocking the pathophysiology and developing therapies to prevent or mitigate damage.
Materials and methods
Cell lines
Vero cells were obtained from ATCC (CRL- 1587) and maintained in DMEM (Thermo Fisher, 11965-
118) with 10% (vol/vol) fetal bovine serum (Thermo Fisher, 10438026), 10mM HEPES (Thermo Fisher,
15630- 080), and 1× penicillin/streptomycin (Thermo Fisher, 10378016). Cell cultures were routinely
checked to be free from mycoplasma.
Rubella virus
To generate viral stocks, a plasmid containing a full infectious clone of RV- M33 was linearized then
added to an in vitro transcription reaction with Sp6 (New England Biolabs, M0207L). The resulting
RNA was purified then polyadenylated (New England Biolabs, M0276S) and capped using Vaccinia
Capping System (New England Biolabs, M2080S). This RNA was then introduced to Vero cells using
TransIT- mRNA transfection (Mirus Bio, MIR 2250). At 72 hr post- transfection, culture media was
collected and passaged onto fresh Vero cells. To generate viral stocks, Vero cells were inoculated
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with low passage number RV (P2- P3) and cultured at 37°C. Culture media was collected at 72hr
post- inoculation, clarified, and stored at −80°C. Immunofluorescent titering assays were performed
on Vero cells using anti- RV capsid antibody (ab34749), yielding titers of 105–106 focus- forming units/
ml (ffu/ml) for RV stocks. RV- GFP stocks were prepared in the same manner, from a plasmid that had
been modified through an in vitro reaction with nCas9 and custom guides to cut the RV- M33 plasmid
midway through the p150 gene at residues 717–718 (dgRNA system with DNA oligos for RNA in vitro
transcription as follows: tracrRNA sequence: AAA AAG CAC CGA CTC GGT GCC ACT TTT TCA AGT
TGA TAA CGG ACT AGC CTT ATT TTA ACT TGC TAT GCT GTC CTA TAG TGA GTC GTA TTA, crRNA
oRV012 sequence: CAA AAC AGC ATA GCT CTA AAA CGC TCG CGG CCA CGT CAC CGC CTA TAG
TGA GTC GTA TTA). After cutting the plasmid, an sfGFP sequence flanked by Gly- Gly- Ser- Gly- Gly
linkers (PCR- amplified using primers oRV010: CTG GCC CCG GCC AGC TCG GAG GAT CGG GCG
GAA TGA GCA AGG GCG AGG AG and oRV011: GTG ACG TGG CCG CGA GTC CTC CTG ATC CGC
CAG TGA TCC CGG CGG CG) was inserted using InFusion (TakaraBio, 638916). GFP expression of
the resulting virus was validated through co- labeling of RV- GFP- infected Vero cells with anti- RV capsid
antibody. All viral stocks were tested to be free from mycoplasma.
Consent statement UCSF
Deidentified tissue samples were collected with previous patient consent in strict observance of
the legal and institutional ethical regulations. Protocols related to human iPSCs were approved by
the Human Gamete, Embryo, and Stem Cell Research Committee (institutional review board) at the
University of California, San Francisco.
Primary prenatal brain slices
Deidentified primary tissue samples were collected with previous patient consent in strict obser-
vance of the legal and institutional ethical regulations. Cortical brain tissue was immediately placed
in a sterile conical tube filled with oxygenated artificial cerebrospinal fluid (aCSF) containing 125mM
NaCl, 2.5mM KCl, 1mM MgCl2, 1mM CaCl2, and 1.25mM NaH2PO4 bubbled with carbogen (95%
O2/5% CO2). Blood vessels and meninges were removed from the cortical tissue, and then the tissue
block was embedded in 3.5% low- melting- point agarose (Thermo Fisher, BP165- 25) and sectioned
perpendicular to the ventricle to 300 μm using a Leica VT1200S vibrating blade microtome in a
sucrose protective aCSF containing 185mM sucrose, 2.5mM KCl, 1mM MgCl2, 2mM CaCl2, 1.25mM
NaH2PO4, 25 mM NaHCO3, 25 mM d-(+)- glucose. Slices were transferred to slice culture inserts
(Millicell, PICM03050) on six- well culture plates (Corning) and cultured in prenatal brain slice culture
medium containing 66% (vol/vol) Eagle’s basal medium, 25% (vol/vol) HBSS, 2% (vol/vol) B27, 1%N2
supplement, 1% penicillin/streptomycin and GlutaMax (Thermo Fisher). Slices were cultured in a 37°C
incubator at 5% CO2, 8% O2 at the air- liquid interface created by the cell culture insert.
Primary human microglia purification
Deidentified primary tissue samples were collected with previous patient consent in strict obser-
vance of the legal and institutional ethical regulations. Brain tissue was immediately placed in a
sterile conical tube filled with oxygenated artificial spinal fluid containing 125 mM NaCl, 2.5 mM
KCl, 1mM MgCl2, 1 mM CaCl2, and 1.25mM NaH2PO4 bubbled with carbogen (95% O2/5% CO2).
Prenatal human microglia were purified from primary brain tissue from mid- gestation (gestational
week 18–23) samples using MACS kit with CD11b magnetic beads (Miltenyi Biotec, 130- 049- 601)
following the manufacturer’s instructions. Briefly, primary brain tissue was minced to 1 mm3 pieces and
enzymatically digested in 10ml of 0.25% trypsin reconstituted from 2.5% trypsin (Gibco, 15090046)
in DPBS (Gibco, 14190250) for 30min at 37°C; 0.5ml of 10mg/ml of DNAse (Sigma- Aldrich, DN25)
was added in the last 5min of dissociation. After the enzymatic digestion, tissue was mechanically
triturated using a 10ml pipette, filtered through a 40μm cell strainer (Corning 352340), pelleted at
300×g for 5min, and washed twice with DBPS. Dissociated cells were resuspended in MACS buffer
(DPBS with 1mM EGTA and 0.5% BSA) with addition of 0.5mg/ml DNAse and incubated with CD11b
antibody for 15min on ice. After the incubation, cells were washed with 10ml of MACS buffer and
loaded on LS columns (Miltenyi Biotec, 130- 042- 401) on the magnetic stand. Cells were washed three
times with 3ml of MACS buffer, then the column was removed from the magnetic field and microglia
cells were eluted in 5ml of MACS buffer. Cells were pelleted at 300×g, resuspended in 1ml of culture
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media, counted, and used for downstream analysis. We routinely obtained 1×106 of microglia cells
from a single MACS purification.
For experiments requiring microglia co- culture with different cell types, the flow- through eluent
from microglia selection served either as a cell type fraction depleted of microglia (denoted as ‘flow-
through’) or was used for an additional separation between neuronal and glial fractions by using PSA-
NCAM antibody (Miltenyi Biotec, 130- 092- 966) following the same procedure described for microglia
purification.
2D microglia cultures
Microglia were cultured on glass- bottom 24- well plates (Cellvis, P24- 1.5H- N) pre- coated with 0.1mg/
ml of poly- d- lysine (Sigma- Aldrich, P7280) for 1hr and 1:200 laminin (Thermo Fisher, 23017015) and
1:1000 fibronectin (Corning, 354008) for 2hr. Microglia were plated at 1×105cells/well and main-
tained in culture media containing 66% (vol/vol) Eagle’s basal medium, 25% (vol/vol) HBSS, 2% (vol/
vol) B27 (Thermo Fisher, 17504001), 1% N2 supplement (Thermo Fisher, 17502001), 1% penicillin/
streptomycin, and GlutaMax (Thermo Fisher) additionally supplemented with 100ng/ml IL34 (Pepro-
tech, 200- 34), 2 ng/ml TGFβ2 (Peprotech,100- 35B), and 1× CD lipid concentrate (Thermo Fisher,
11905031) for 5–8days. For co- culture experiments, other cell types were cultured with microglia at
5:1 ratio (1×105 microglia cells for each 5×105 non- microglial cells).
iPSC lines
All work related to human iPSCs has been approved by the UCSF Committee on Human Research and
the UCSF GESCR (Gamete, Embryo, and Stem Cell Research) Committee.
Human iPSC line ‘WTC- 10’ derived from healthy 30- year- old Japanese male fibroblasts was from
the Conklin Lab, UCSF (Bershteyn etal., 2017; Kreitzer etal., 2013). Human iPSC line ‘13325’ was
derived from 9- year- old female fibroblasts originally obtained from Coriell cell repository.
Human iPSC line ‘1323- 4’ derived from healthy 48- year- old Caucasian female fibroblasts (gift from
the Conklin Lab, UCSF) was used for immunofluorescence validation analysis as we found that this line
generates more reproducible brain organoids.
Organoid generation
Cerebral organoids were generated based on a previously published method (Paşca etal., 2015) with
several modifications. Briefly, hiPSCs cultured on Matrigel were dissociated into clumps using 0.5mM
EDTA in Ca2+/Mg2+- free DPBS and transferred into ultra- low attachment six- well plates in neural induc-
tion media (GMEM containing 20% [vol/vol] KSR, 1% [vol/vol] penicillin- streptomycin, 1% [vol/vol]
non- essential amino acids, 1% [vol/vol] sodium pyruvate, and 0.1 mM 2- mercaptoethanol). For the
first 9 days, neural induction media was supplemented with the SMAD inhibitors SB431542 (5μM) and
dorsomorphin (2μM), and the Wnt inhibitor IWR1- endo (3μM). Additionally, the Rho kinase inhibitor
Y- 27632 (20μM) was added during the first 4 days of neural induction to promote survival. Neural
induction media was replaced every 2 days for 8 days, and Y- 27632 was removed from the media on
the fourth day. After neural induction, plates containing cortical organoids were transferred to a plate
shaker rotating at 80rpm. Between days 9 and 25, organoids were transferred to an expansion media
(1:1 mixture of Neurobasal and DMEM/F12 containing 2% [vol/vol] B27 without vitamin A, 1%N2, 1%
[vol/vol] non- essential amino acids, 1% [vol/vol] GlutaMax, 1% [vol/vol] antibiotic/antimycotic, 0.1mM
2- mercaptoethanol) supplemented with FGFβ (10ng/ml) and EGF (10ng/ml). Between days 25 and
35, organoids were maintained in neural differentiation media without FGF or EGF. From day 35
onward, organoids were maintained in neural differentiation media containing B27 with vitamin A with
full media exchanges every 2–3days.
Microglia-organoid engraftment and co-culture
Microglia from mid- gestation cortical tissue were MACS- purified and immediately added to organoids
between weeks 5 and 6 in six- well plates at 1×105 microglia cells/organoid and kept off the shaker
overnight. The following day, the plates were returned to the shaker and maintained following a usual
organoid maintenance protocol.
RV infection
Cells cultured in 2D were inoculated by adding RV stock virus to culture media in 1:1 dilution (250µl of
media to the equal volume of viral stock, 1.75×105 total ffu/well) to achieve a multiplicity of infection
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(MOI) of 2. After 4 hr, media was exchanged with fresh cell culture media. Cortical brain slices were
treated with 500µl of RV viral stock (3.5×105 total ffu/slice) applied over the slice culture filter for 4 hr,
and then the viral culture media was removed and replaced with fresh slice culture media. Organoids
were treated in six- well plates with 2ml of 1:1 dilution of viral stock:organoid maintenance media
(7×105 total ffu) for 4 hr, and then viral media was exchanged for fresh media. For all experimental
conditions, cells were fixed and processed for downstream analysis at 72hr post- infection. Superna-
tant from non- infected Vero cells (mock) or heat- inactivated RV (65°C, 30min) was used as control.
For titering experiments, microglia co- cultures or Vero cells (as controls) were infected at the indi-
cated MOI. Cells were inoculated for 4hr, then fresh media was replaced, and sampled at the indi-
cated timepoints. Media samples were clarified and flash frozen. Viral titer was then quantified in the
media samples using immunofluorescence titering assay.
Immunofluorescence
Cells cultured on glass- bottom well plates were fixed in 4% PFA at the room temperature for 10min
and washed with PBS three times for 5 min each wash. Blocking and permeabilization were performed
in a blocking solution consisting of 10% normal donkey serum, 1% Triton X- 100, and 0.2% gelatin
for 1hr. Primary and secondary antibodies were diluted and incubated in the blocking solution. Cell
cultures were incubated with primary antibodies at the room temperature for 1hr, washed 3× with
washing buffer (0.1% Triton X- 100 in PBS), and incubated with secondary antibodies for 1hr at the
room temperature.
Organoid samples were fixed in 4% PFA at the room temperature for 1hr. Whole organoids were
incubated in 30% sucrose (wt/vol) at 4°C overnight, cryopreserved in OCT/30% sucrose (1:1), and
then cryosectioned at 20μm thickness. Blocking and permeabilization were performed in a blocking
solution consisting of 10% normal donkey serum, 1% Triton X- 100, and 0.2% gelatin for 1hr. Primary
and secondary antibodies were diluted and incubated in the blocking solution. Cryosections were
incubated with primary antibodies at 4°C overnight, washed 3× for 10min each with washing buffer
(0.1% Triton X- 100 in PBS). Slides were incubated with species- specific Alexa Fluor secondary anti-
bodies (1:2000) overnight at 4°C and then washed with washing buffer for at least 3× for 10min each.
Finally, slices were mounted with glass coverslips using DAPI Fluoromount- G (Southern Biotech, 0100-
20) mounting media.
Cortical slices were fixed in 4% PFA at room temperature for 1hr. Antibody staining was performed
as for organoid samples above, with the exceptions that no cryosectioning was performed.
Images were collected using Leica SP8 confocal system with 20× air lens (0.75 NA) and 63× oil lens
(1.40 NA). Images were processed using ImageJ/Fiji and Affinity Designer software.
Antibodies
Primary antibodies used in this study included: rabbit Iba1 (1:500, Wako, 019- 19741), guinea pig
Iba1 (1:500, Synaptic Systems, 234 004), mouse RV capsid (1:500, Abcam, ab34749), rat Sox2 (1:500,
Invitrogen, 14- 9811- 82), chicken GFP (1:1000, Aves labs, GFP- 1020), mouse NOVA1 (1:500, Santa
Cruz, sc100334), rabbit EOMES (1:200, Sigma- Aldrich, HPA028896), chicken NeuN (1:1,000, Milli-
pore, ABN91), rabbit IFITM3 (1:500, Proteintech, 11714- 1- AP).
Organoid single-cell capture for scRNAseq
Two organoids per experimental condition were washed with Ca2+/Mg2+- free DPBS and cut into 1 mm2
pieces and enzymatically digested with papain digestion kit (Worthington, LK003163) with the addi-
tion of DNAse for 1hr at 37°C. Following enzymatic digestion, organoids were mechanically triturated
using a P1000 pipette, filtered through a 40μm cell strainer test tube (Corning 352235), pelleted at
300×g for 5min, washed twice with DBPS, and resuspended in 180µl of DPBS on ice for barcoding
with MULTI- seq indices (McGinnis etal., 2019) for multiplexing. Anchor and barcoded strands unique
for each sample were mixed in 1:1 molar ratio in DPBS (without BSA or FBS to avoid sequestering
labeling oligonucleotides) and 20 µl of 10× Anchor:Barcode mixture was added to 180 µl of cell
suspension. Cells were incubated on ice for 5min, and then 20µl of co- anchor was added to each
tube. Cells were incubated on ice for additional 5min and washed with ice- cold 1% BSA in DPBS. Cells
were counted and kept on ice to prevent barcode loss. Two organoid lines with and without microglia
that were treated with RV or uninfected Vero cell supernatant were combined and captured across
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seven lanes of 10x Genomics using Chromium Single Cell 3' Reagent Kit (v2 Chemistry) following the
manufacturer’s protocol.
scRNAseq libraries were generated using the 10x Genomics Chromium 3’ Gene Expression Kit.
Briefly, barcoded single- cell mixtures from different conditions ranging from two to three individual
conditions per lane were loaded onto chromium chips with a capture target of 10,000cells per
sample. The 10× protocol was modified for collection of MULTI- seq barcodes. During SPRI cleanup
immediately following cDNA amplification, supernatant was saved to recover the barcode fraction.
Endogenous transcript cDNA remained bound to the SPRI beads and the protocol was continued
for endogenous transcripts without change. Libraries were prepared following the manufacturer’s
protocol and sequenced on an Illumina NovaSeq with a targeted sequencing depth of 50,000 reads
per cell. BCL files from sequencing were then used as inputs to the 10x Genomics Cell Ranger pipeline.
MULTI-seq barcode amplification
Supernatant collected after cDNA amplification cleanup step was transferred to fresh 1.5ml Eppen-
dorf tubes, and 260µl SPRI (for a final ratio of 3.2×) and 180µl 100% isopropanol (for a final ratio of
1.8×) were added. After pipette mixing 10 times, the solution was incubated at room temperature for
5min, placed on magnetic rack for solution to clear. The supernatant was removed, and the beads
were washed with 500µl of 80% ethanol twice. Air- dry beads were removed from magnet, resus-
pended in 50µl buffer EB. After clearing the solution on the magnet, supernatant was transferred to
a new PCR strip. Libraries were prepared with KAPA HiFi master mix with universal I5 primers and RPI
primers unique for each 10× lane. PCR was performed with the following protocol: 95°C for 5min
(98°C for 15s, 60°C for 30s, 72°C for 30s) repeated for 10 times, 72°C for 1min, 4°C hold.
PCR product was cleaned with 1.6× SPRI beads and resuspended in 25µl buffer EB. Barcode libraries
were quantified at 1:5 concentration using Bioanalyzer High Sensitivity DNA analysis. Barcodes were
sequenced as fraction of endogenous cDNA library with a target of 3000–5000 barcode reads per cell.
scRNAseq analysis
CellRanger 3.0 was used to create a cell by gene matrix which was then processed using Solo (Fleming
etal., 2019) for doublet detection and removal. A minimum of 1000 genes, 500 UMI counts, and 20%
mitochondrial cutoff were used to remove low- quality cells from all datasets. MAST (Finak et al.,
2015) was used on log normalized raw counts for all differential expression tests. The gene marker
lists were filtered after testing by specifically removing unannotated genes from HGNC. Organoid
demultiplexing and doublet filtering was done through deMULTIplex (McGinnis etal., 2019) (https://
github.com/chris-mcginnis-ucsf/MULTI-seq ; McGinnis, 2019). Uniform manifold approximation and
projection (UMAP) (McInnes etal., 2018) embeddings and neighbors for Leiden clustering (Traag
etal., 2019) were used for clustering and visualization. Nebulosa was used to generate density plots
and (Bunis etal., 2020) for color- blind friendly plotting of clusters. Pearson correlation was calculated
on the intersection of the shared genes between datasets which averaged Pearson residuals for each
cluster. Organoid cells were batch corrected using default parameters of the SCTransform (Hafe-
meister and Satija, 2019) integration workflow.
Image analysis and statistical tests
2D microglia co-cultures
Cell co- localization with the RV capsid was quantified using the CellProfiler 3.0 software (McQuin
et al., 2018). First, individual cells were identified by using IdentifyPrimaryObjects module with
threshold strategy ‘Global’, threshold method ‘Otsu’, and a two- class thresholding for each individual
channel for DAPI, Iba1 and RV capsid fluorescence images. Then, resulting cell objects were paired by
using RelateObjects module to identify Iba1- postive, RV- positive and double- positive DAPI objects.
Finally, CalculateMath was used to quantify proportions for each cell population, including RV- positive
and RV- negative Iba1 microglia cells and non- microglia cells, depending on the analysis.
Organoid immunofluorescence quantifications
For cytoplasmic IFITM3 staining, whole organoid sections were treated as regions of interest and
average fluorescence intensity for IFITM3 was normalized to DAPI fluorescence using QuPath 0.3.2.
To conduct IFITM3 intensity quantifications, the entire organoid section was defined as region of
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interest (ROI) by using the wand tool. Intensity calculation features with the analyze function for the
DAPI and IFITM3 channels were then used to determine ROI fluorescence intensities. To set up the
calculation, preferred pixel size was set to 0.76μm according to image resolution. Relevant measure-
ments including intensity mean, standard deviation, min and max, and organoid area were calculated
and retrieved from QuPath detection measurements.
For analyzing nuclear signal for NOVA1/EOMES/NeuN experiments, QuPath 0.3.2 was used to
identify and quantify individual cell nuclei. First, each organoid was selected as ROI by using the wand
tool. To establish total EOMES count in each organoid, the cell detection function was applied to the
appropriate channel where adjustments were made, including thresholding and deselecting. The posi-
tive cell detection function with the EOMES channel thresholding value were then applied on NOVA1
channel to identify cells that are NOVA1+/EOMES+ double positive. Thresholding adjustments were
made to account for imaging variations in EOMES channel. To quantify NOVA1+/NeuN+ nuclei, the
same two- step detection procedure described above was utilized with NOVA1 and NeuN channels.
All relevant quantification values were then collected from QuPath detection measurements. Three
to five organoid sections per each organoid were imaged and analyzed, with each data point repre-
senting an average of several sections per individual organoid.
Prism 9.3.1 was used for statistical analysis and data plotting. Unpaired t- test with assumed Gaussian
distribution of the variants and the same standard deviations were used to calculate statistical signifi-
cance for cell counts. Unpaired nonparametric Kolmogorov- Smirnov test was used to compare differ-
entially expressed genes that reached significance value of p=0.05 between conditions in organoids.
Parts of figure schematics were done using https://www.biorender.com/.
Acknowledgements
We thank Tom Hobman for generously sharing reagents for the Rubella M33 strain, and all members
of the Nowakowski and DeRisi laboratories for helpful discussions and comments throughout this
project. We would like to thank UCSC Cell Browser and especially Maximilian Haeussler and Brittney
Wick for making the single- cell data publicly available. This study was supported in part by gifts from
Schmidt Futures and the William K Bowes Jr. Foundation, Simons Foundation grant (SFARI 491371
to TJN), Chan Zuckerberg Biohub Intercampus Investigator Award, NARSAD Young Investigator
Grant (to TJN), NINDS award R01NS123263 (to TJN), and NRSA F32 1F32MH118785 (to GP), NINDS
F31NS108615 (to HR), UCSF Discovery Fellows Program (to HR), and the Chan Zuckerberg Biohub (to
JD). TJN is a New York Stem Cell Foundation Robertson Neuroscience Investigator.
Additional information
Funding
Funder Grant reference number Author
National Institutes of
Health
R01NS123263 Tomasz Nowakowski
National Institutes of
Health
1F32MH118785 Galina Popova
National Institutes of
Health
5F31NS108615 Hanna Retallack
Simons Foundation SFARI 491371 Tomasz Nowakowski
Chan Zuckerberg Biohub Intercampus Investigator
Award
Tomasz Nowakowski
Joseph L DeRisi
NARSAD Young Investigator Grant Tomasz Nowakowski
Schmidt Futures Tomasz Nowakowski
William K. Bowes, Jr.
Foundation
Tomasz Nowakowski
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Popova, Retallack etal. eLife 2023;12:RP87696. DOI: https://doi.org/10.7554/eLife.87696 17 of 20
Funder Grant reference number Author
University of California, San
Francisco
Discovery Fellows Program Hanna Retallack
The funders had no role in study design, data collection and interpretation, or the
decision to submit the work for publication.
Author contributions
Galina Popova, Conceptualization, Formal analysis, Investigation, Methodology, Writing - original
draft, Writing – review and editing; Hanna Retallack, Conceptualization, Resources, Formal analysis,
Investigation, Visualization, Methodology, Writing - original draft, Writing – review and editing; Chang
N Kim, Data curation, Formal analysis; Albert Wang, Investigation; David Shin, Resources, Investiga-
tion; Joseph L DeRisi, Conceptualization, Resources, Supervision, Methodology, Writing – review and
editing; Tomasz Nowakowski, Conceptualization, Supervision, Funding acquisition, Writing – review
and editing
Author ORCIDs
Galina Popova
http://orcid.org/0000-0001-8249-219X
Hanna Retallack
http://orcid.org/0000-0003-0533-9102
Albert Wang
http://orcid.org/0000-0001-5989-4617
Tomasz Nowakowski
http://orcid.org/0000-0003-2345-4964
Ethics
De- identified tissue samples were collected with previous patient consent in strict observance of the
legal and institutional ethical regulations. Protocols related to human iPSC cells were approved by
the Human Gamete, Embryo, and Stem Cell Research Committee (institutional review board) at the
University of California, San Francisco.
Peer review material
Reviewer #1 (Public Review): https://doi.org/10.7554/eLife.87696.3.sa1
Reviewer #2 (Public Review): https://doi.org/10.7554/eLife.87696.3.sa2
Author Response https://doi.org/10.7554/eLife.87696.3.sa3
Additional files
Supplementary files
• MDAR checklist
Data availability
Sequences of RV and RV- GFP have been deposited at Genbank under accessions OM816674 and
OM816675 respectively. Single- cell RNA- seq data for iPSC- derived organoids are available from
Gene Expression Omnibus (GEO) under the accession code GSE232462. Processed single- cell data,
including dimensionality reduction object, is freely available at https://cells.ucsc.edu/?ds=rubella-
organoids. Code associated with analysis of the single cell analysis can be accessed at Github: https://
github.com/cnk113/analysis-scripts (copy archived at Kim, 2023).
The following datasets were generated:
Author(s) Year Dataset title Dataset URL Database and Identifier
Retallack H, DeRisi J 2022 Synthetic construct clone
M33, complete sequence
https://www. ncbi.
nlm. nih. gov/ nuccore/
OM816674
NCBI GenBank, OM816674
Popova G, Kim CN,
Nowakowski TJ
2023 Rubella virus tropism and
single cell responses in
human primary tissue
and microglia- containing
organoids
https://www. ncbi.
nlm. nih. gov/ geo/
query/ acc. cgi? acc=
GSE232462
NCBI Gene Expression
Omnibus, GSE232462
Continued on next page
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Author(s) Year Dataset title Dataset URL Database and Identifier
Retallack H, DeRisi J 2023 Synthetic construct clone
M33- p150GFP, complete
sequence
https://www. ncbi.
nlm. nih. gov/ nuccore/
OM816675
NCBI GenBank, OM816675
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