Rubella virus tropism and single cell responses in human primary tissue and microglia-containing organoids

Abstract

Rubella virus is an important human pathogen that can cause neurologic 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 developing 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.

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Galina Popova et al., 2023. eLife https://doi.org/10.7554/eLife.87696.2 1 of 42
Neuroscience, Stem Cells and Regenerative Medicine
Rubella virus tropism and single cell responses in
human primary tissue and microglia-containing
organoids
Galina Popova, Hanna Retallack, Chang N. Kim, Albert Wang, David Shin, Joseph DeRisi ,
Tomasz J. Nowakowski
Department of Neurological Surgery, University of California, San Francisco, CA, USA • Eli and Edythe Broad
Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, USA •
Department of Anatomy, University of California, San Francisco, CA, USA • Department of Psychiatry and
Behavioral Sciences, University of California, San Francisco, CA, USA • Weill Institute for Neurosciences, University
of California, San Francisco, CA, USA • Department of Biochemistry and Biophysics, University of California San
Francisco, San Francisco, CA, USA • Chan Zuckerberg Biohub, San Francisco, CA, USA
(https://en.wikipedia.org/wiki/Open_access)
(https://creativecommons.org/licenses/by/4.0/)
Abstract
Rubella virus is an important human pathogen that can cause neurologic 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 developing 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.
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Galina Popova et al., 2023. eLife https://doi.org/10.7554/eLife.87696.2 2 of 42
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 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 recognized 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 et
al., 2016). As of 2019, RV-containing 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
two-fold increase in reported rubella cases worldwide (26,033 total cases in 2018 vs 49,179
cases in 2019) (Plotkin, 2021) and included CRS the following year (423 total cases worldwide
in 2019 vs 1,252 cases in 2020) (World Health Organization, 2022).
The most common features of CRS are congenital cataracts, sensorineural deafness, and
cardiac defects (Banatvala & Brown, 2004). In addition, microcephaly (Munro, Sheppard,
Smithells, Holzel, & Jones, 1987), developmental delay and autism (Chess, 1977), and
schizophrenia spectrum disorders (Brown et al., 2001) are associated 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
respiratory 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, Pham, & Abe, 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 et al., 1965; Esterly & Oppenheimer, 1967; Korones, 1965; Monif, Avery, Korones, &
Sever, 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 degeneration
(Rorke & 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 et al., 2016; Nguyen et al., 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,
Jiang, & Tien, 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
molecular 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

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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 (Figure 1A). At 72 hours 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 (Figure 1B-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, GenBank Accession OM816675,
Figure 1E) and validated by GFP expression in Vero cells (Figure 1 – 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
(Figure 1F) consistent with the wildtype M33 RV.
Figure 1.
Rubella virus 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
72 hours. B,C. Immunostaining for
RV capsid and Iba1 on cultured corti-
cal slices at 72 hpi, at 10x with scale
bar 100 μm (B) and at 40x objective
with scale bar 50 μm (C). D.
Quantification of RV capsid-positive
cells co-labeled with microglial mark-
er Iba1: 764/819 (93.3%) of RV+ cells
were microglia based on Iba1 stain-
ing 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 72 hours. F. Examples of GFP fluorescence and Iba1 immunostaining at 72 hpi of cultured
cortical slices with GFP-RV, at 62x with scale bar 20 μm. GFP expression of modified rubella virus is localized to Iba1-posi-
tive microglia cells (arrows).

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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 et al., 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 et al., 2017) (https://cells.ucsc.edu/?ds=cortex-dev&gene=MOG) or human
radial glial cells (Eze, Bhaduri, Haeussler, Nowakowski, & Kriegstein, 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 et al., 2018), cannot explain viral tropism for microglia.
Thus, to identify factors contributing to the relatively 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 (Figure 2A). Surprisingly, RV infection of the
microglia monoculture was negligible (Figure 2B). 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 (Figure 2C-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 (Figure 2F).
Similar to the cortical brain slices, microglia represented the main cell type infected with RV
in the mixed co-cultures (Figure 2G). 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 (Figure 2 – figure
supplement 2A-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 (Figure 2 – figure supplement
2D). No statistically significant difference was detected in RV infectivity in cells cultured with
or without microglia (Figure 2 – figure supplement 3).
Figure 2.
Rubella virus 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 purified using MACS. Microglia
cells were cultured alone or in com-
bination with neurons, glial cells, or
all cell types. 2D cultures were infect-
ed with RV for 72 hours and pro-
cessed for immunostaining. B-E.

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Representative images of microglia cultured with different cell types. Cell cultures were stained for microglia marker Iba1
(red), RV capsid (green) and DAPI (grey; on the overlay Merge channel). B. Purified microglia only. C. Microglia and neu-
rons (purified with PSA-NCAM magnetic beads) co-cultured at 1:5 ratio. D. Microglia and glial cell types (flow through
fraction after PSA-NCAM magnetic beads) cultured together at 1:5 ratio. E. Microglia cultured with non-microglial cells
(flow-through after CD11b magnetic beads; mixed cell populations) at 1:5 ratio. F. Quantification of RV capsid im-
munopositivity among microglia (Iba1+) for conditions in B-E. FT: flow through after microglia MACS purification. Error
bars denote SEM. Each data point represents a field of view from the same experimental batch. G. Quantification of mi-
croglia (Iba1+) among RV capsid-positive cells.
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 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 (Figure 3A). 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 (Figure 3B-C). Consistent with our previous experiments, microglia
represented the main cell type infected with RV (Figure 3D). 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.
Figure 3.
Direct cell-cell contact is
not required for microglia
infection by rubella virus.
A. Schematic for experimental set
up. Primary human brain tissue was
dissociated, and microglia were cul-
tured with or without microglia-de-
pleted flow through portion. Cells
were co-cultured in direct contact or
in solution-permeable chambered
transwells (TW). B. Representative
images of microglia-enriched cul-
tures (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 perme-
able transwell chamber (bottom row)
infected with RV for 72 hours. C.
Quantification of RV capsid im-
munopositivity among microglia
(Iba1+). Three fields of view across the same experiment were quantified for each condition. Error bars represent SEM. p-
value between microglia and co-culture condition is 0.0479. p-value between microglia and trans well condition is 0.0159.
D. Quantification of microglia (Iba1+) among RV capsid-positive cells.

Galina Popova et al., 2023. eLife https://doi.org/10.7554/eLife.87696.2 6 of 42
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 development (Nowakowski &
Salama, 2022). Brain organoids were generated following previously established protocols
(Pasca et al., 2015), and at five 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 et al., 2021). After allowing microglia to engraft into the
organoids, we exposed neuroimmune organoids to RV or heat-inactivated control and
cultured them for 72 hours or two weeks to identify short- and long-term consequences of
the viral exposure (Figure 4A). 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 population that harbors
viral infection (Figure 4 B-C).
Figure 4.
Microglia in neuroimmune organoids are
infected with rubella virus.
A. Primary human microglia were transplanted into brain
organoids and resulting neuroimmune organoids were ex-
posed to RV. After 72 hours or 2 weeks organoids were pro-
cessed for immunofluorescence validation (this figure) or
scRNAseq analysis (Figure 5). B. Representative immunoflu-
orescence images of brain organoids without microglia
subjected to RV exposure for 72 hrs. Radial glial cells are la-
beled with Sox2 (cyan), microglia are labeled with Iba1
(red) and RV is labeled with anti-RV capsid antibody
(green). Scale bar is 50 μm. C. Representative immunofluo-
rescence images of brain organoids with microglia at 72 hrs
(top panel) or 2 weeks (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 ex-
amples of microglia cells. Scale bar is 50 μm.
To determine brain-wide consequences of the RV infection across different cell types, at 72
hours after RV exposure we processed neuroimmune organoids for single-cell RNA

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sequencing with 10X Genomics and downstream analysis. After processing for single-cell
RNA sequencing, cells with fewer than 500 detected genes and/or more than 20%
mitochondrial genes were removed from the analysis. Ribosomal transcripts and
pseudogenes were excluded. Approximately 11,000 cells passed filtering criteria (Figure 5A,
Figure 5 – figure supplement 4A-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) (Figure 5B,
Figure 5 – figure supplement 4 D-E for individual cluster marker genes, Figure 5 – source
data file 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 et al., 2022) and the canonical microglia marker P2RY12 was not detected in those cells
(Figure 5 – figure supplement 4F). 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 significant transcriptomic differences including genes involved in the interferon signaling
pathway and its response (IFI27, IFI6, IFITM3)(HLA-A (Campbell, Bizilj, Colman, Tuch, &
Harrison, 1986; Keskinen, Ronni, Matikainen, Lehtonen, & Julkunen, 1997) and BST2
(Holmgren, Miller, Cavanaugh, & Rall, 2015)) (cluster 1, Figure 5E, Figure 5 – figure
supplement 4 – source data file 1). The majority of cells in cluster 1 came from RV-exposed
organoids (Figure 5D). 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 (Figure 5E-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 at 72 hours
post-exposure (Figure 5 G-H), while the overall cell numbers were not changed in either
condition (Figure 5I).
Figure 5.
Rubella virus exposure of brain
organoids leads to interferon
response.
A. Single cell RNA sequencing analysis identi-
fied 13 clusters, including neurons and glial
cells (Div.: dividing cells, RG: radial glia, Astros:
astrocytes, IPC: intermediate progenitor cells).
B. Dot plot depicting cluster marker genes for
each cluster. C. UMAP plots of organoids col-
ored 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

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immunofluorescence in brain organoids with microglia with wild type RV (bottom panel) or heat-inactivated control (top
panel) 72 hours post-infection. IFITM3 is labeled in magenta, microglia are labeled with Iba1 (green), cell nuclei are la-
beled with DAPI (grey). H. Quantification of fluorescence intensity of IFITM3 normalized to DAPI intensity per organoid.
Columns represent mean of four organoids. Dots represent averages across several section for each individual organoid.
Error bars represent SEM. Unpaired parametric student t-test was used to compare the two groups in H-I. p-value=0.04 I.
Quantification of fluorescence intensity of DAPI staining per organoid. p-value=0.22.
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 (Figure 6A). 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 (Figure 6A, 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 (Figure 6A, Figure 5 –
source data file 2) – two genes that form heterodimers in vivo and are associated with
induction of gliogenesis (Tchieu et al., 2019) in embryonic brain development. Early
disruption in the function of either gene is associated with neurodevelopmental deficits and
perinatal mortality in mice (das Neves et al., 1999; Steele-Perkins et al., 2005) and with
intellectual disability in humans (Schanze et al., 2018).
Figure 6.
NOVA1 expression is
reduced in response to
rubella virus exposure.
A. Differentially expressed genes in
different cell types in response to RV
treatment without (top panel) and
with microglia (bottom panel). IPC –
intermediate progenitor cells. In the
presence of microglia, fewer differ-
entially expressed genes in response
to RV treatment were identified
across all major cell types. In
organoids with microglia, NOVA1
trended towards a decrease in IPC
and neurons (labeled in blue in the
panel). Kolmogorov-Smirnov test
was used on DEGs with p-value<0.05.
*** <0.001, NS – not significant, *
<0.05. B. Violin plot for NOVA1 that is
differentially expressed in response
to RV and presence of microglia. IPC
– intermediate progenitor cells, RG – radial glia, Div. – dividing cells, EN – excitatory neurons. C. Representative images of

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RV-exposed organoids with microglia at 2 weeks 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 quantification
for NeuN+ neurons that were also positive for NOVA1 in control (heat-inactivated RV) or RV condition. Unpaired paramet-
ric student t-test was used to compare the two groups in D-G. p-value=0.088. E. Cell number quantification for EOMES+ in-
termediate progenitors that were also positive for NOVA1 in control (heat-inactivated RV) or RV condition. p-value=0.0042.
F. Cell number quantification for NeuN+ neurons per organoid area displayed in 1,000cells x mm2 or organoid surface
area in control (heat-inactivated RV) or RV condition. p-value=0.0004. G. Cell number quantification for EOMES+ interme-
diate progenitor cells per organoid area displayed in 1,000cells x mm2 or organoid surface area in control (heat-inactivat-
ed RV) or RV condition. p-value=0.86.
Genes with expression levels affected both by the presence of microglia and by RV exposure
included NOVA alternative splicing regulator 1 (NOVA1) (Figure 6B). NOVA1 is a master
regulator of alternative splicing (Zhang et al., 2010) in the central nervous system with
potential links to neurologic diseases (Parikshak et al., 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 organoids 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 two weeks, we used immunostaining to
quantify numbers of neurons or intermediate progenitor cells (IPC) – two major cell types
with the most robust predicted NOVA1 level changes based on the scRNAseq experiment
(Figure 6C). We detected a statistically significant decrease of NOVA1+ IPCs in response to RV
exposure (Figure 6E). Numbers of NOVA1+ neurons also had a trend towards reduction
(Figure 6D); 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 et al., 2021; van der Logt, van Loon, & van der Veen, 1980), and adds
new information to the limited understanding 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 et
al., 2016; Sugishita et al., 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 et al., 2017; Retallack et al., 2016; Rock et al.,
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

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neurodevelopmental disorders, including neurite length and gene expression changes
associated with schizophrenia and autism (Warre-Cornish et al., 2020). The interferon
response is additionally associated with pathobiology in a range of congenital infections and
interferonopathies (Crow & Manel, 2015). Furthermore, in our preliminary experiments 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 transcriptional 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
populations may also shed light on neuroimmune consequences of other congenital
infections that coincide temporally with phases of microglia population expansion and
reduction (Menassa et al., 2022).
Interestingly, RV infection rates were largely influenced by the local cell environment, where
proximity 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,
Cioe, Rieti, & Orsi, 1990; Otsuki et al., 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 et al., 2022; Cakir et al., 2019;
Popova et al., 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 predominant cellular target of RV infection. Another
possibility is microglia actively altering the microenvironment 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 perturbations 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.

Galina Popova et al., 2023. eLife https://doi.org/10.7554/eLife.87696.2 11 of 42
Material and 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/blob/main
/rmd/rub.Rmd.
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 T.J.N.), Chan Zuckerberg Biohub
Intercampus Investigator Award, NARSAD Young Investigator Grant (to T.J.N), NINDS award
R01NS123263 (to T.J.N), and NRSA F32 1F32MH118785 (to G.P.), NINDS F31NS108615 (to H.R.),
UCSF Discovery Fellows Program (to H.R.), and the Chan Zuckerberg Biohub (to J.D.). T.J.N. is
a New York Stem Cell Foundation Robertson Neuroscience Investigator.
Author contributions
These authors contributed equally: G.P., H.R..
G.P. and H.R. performed the experiments and analyzed the data. C.N.K. analyzed single cell
RNA sequencing data. D.S. provided brain organoids and A.W. performed
immunofluorescence and image analysis. G.P. and H.R. prepared figures and wrote the
manuscript with input from all authors. T.J.N. and J.D. provided oversight of the project. All
authors reviewed the manuscript and agreed on its content.
Materials and Methods
Cell lines
Vero cells were obtained from ATCC (CRL-1587) and maintained in DMEM (ThermoFisher,
11965-118) with 10% (vol/vol) fetal bovine serum (ThermoFisher, 10438026), 10mM HEPES
(ThermoFisher, 15630-080), and 1X penicillin/streptomycin (ThermoFisher, 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,

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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 hours post-transfection, culture media was collected and passaged onto fresh
Vero cells. To generate viral stocks, Vero cells were inoculated with low passage number RV
(P2-P3) and cultured at 37°C. Culture media was collected at 72 hours 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
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.
Primary prenatal brain slices
Deidentified primary tissue samples were collected with previous patient consent in strict
observance 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 125 mM NaCl, 2.5 mM KCl, 1mM MgCl2, 1 mM CaCl2, and 1.25 mM
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 185 mM sucrose, 2.5 mM KCl, 1 mM MgCl2, 2 mM CaCl2, 1.25 mM 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
observance of the legal and institutional ethical regulations. Brain tissue was immediately
placed in a sterile conical tube filled with oxygenated artificial spinal fluid (aSCF) containing

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125 mM NaCl, 2.5 mM KCl, 1mM MgCl2, 1 mM CaCl2, and 1.25 mM 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 magnetic-activated cell
sorting (MACS) kit with CD11b magnetic beads (Miltenyi Biotec, 130-049-601) following
manufacturer’s instructions. Briefly, primary brain tissue was minced to 1mm3 pieces and
enzymatically digested in 10 ml of 0.25% trypsin reconstituted from 2.5% trypsin (Gibco,
15090046) in DPBS (Gibco, 14190250) for 30 mins at 37 °C. 0.5 ml of 10 mg/ml of Dnase (Sigma
Aldrich, DN25) was added in the last 5 minutes of dissociation. After the enzymatic digestion,
tissue was mechanically triturated using a 10 ml pipette, filtered through a 40 μm cell
strainer (Corning 352340), pelleted at 300xg for 5 minutes and washed twice with DBPS.
Dissociated cells were resuspended in MACS buffer (DPBS with 1 mM EGTA and 0.5% BSA)
with addition of 0.5 mg/ml DNAse and incubated with CD11b antibody for 15 minutes on ice.
After the incubation, cells were washed with 10 ml of MACS buffer and loaded on LS
columns (Miltenyi Biotec, 130-042-401) on the magnetic stand. Cells were washed 3 times
with 3 ml of MACS buffer, then the column was removed from the magnetic field and
microglia cells were eluted in 5 ml of MACS buffer. Cells were pelleted at 300xg, re-
suspended in 1 ml of culture media, counted, and used for downstream analysis. We
routinely obtained 1×10^6 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
0.1 mg/ml of poly-d-lysine (Sigma Aldrich, P7280) for 1 hr and 1:200 laminin (Thermo Fisher,
23017015) and 1:1,000 fibronectin (Corning, 354008) for 2 hrs. Microglia were plated at
1×10^5 cells/well and maintained 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 100 ng/ml IL34 (Peprotech, 200-34), 2 ng/ml TGFβ2
(Peprotech,100-35B), and 1x CD lipid concentrate (Thermo Fisher, 11905031) for 5-8 days. For
co-culture experiments, other cell types were cultured with microglia at 5:1 ratio (1×10^5
microglia cells for each 5×10^5 non-microglial cells).
iPSC lines
All work related to human iPS cells has been approved by the UCSF Committee on Human
Research and the UCSF GESCR (Gamete, Embryo, and Stem Cell Research) Committee.
Human iPS cell line “WTC-10” derived from healthy 30-year-old Japanese male fibroblasts
was from the Conklin Lab, UCSF (Bershteyn et al., 2017; Kreitzer et al., 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.

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Organoid generation
Cerebral organoids were generated based on a previously published method (Pasca et al.,
2015) with several modifications. Briefly, hiPSCs cultured on Matrigel were dissociated into
clumps using 0.5 mM EDTA in Ca2+/Mg2+-free DPBS and transferred into ultra-low
attachment 6-well plates in neural induction media (GMEM containing 20% (v/v) KSR, 1%
(v/v) penicillin-streptomycin, 1% (v/v) non-essential amino acids, 1% (v/v) sodium pyruvate,
and 0.1mM 2-mercaptoethanol). For the first nine days, neural induction media was
supplemented with the SMAD inhibitors SB431542 (5 μM) and dorsomorphin (2 μM), and the
Wnt inhibitor IWR1-endo (3 μM). Additionally, the Rho Kinase Inhibitor Y-27632 (20 μM) was
added during the first four days of neural induction to promote survival. Neural induction
media was replaced every two days for eight 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 80 rpm. Between days 9-25, organoids were
transferred to an expansion media (1:1 mixture of Neurobasal and DMEM/F12 containing 2%
(v/v) B27 without vitamin A, 1% N2, 1% (v/v) non-essential amino acids, 1% (v/v) Glutamax,
1% (v/v) antibiotic/antimycotic, 0.1mM 2-mercaptoethanol) supplemented with FGFβ (10
ng/mL) and EGF (10 ng/mL). Between days 25-35, 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 2-3 days.
Microglia-organoid engraftment and co-culture
Microglia from mid-gestation cortical tissue were MACS-purified and immediately added to
organoids between week 5 and 6 in 6-well plates at 1×10^5 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.
Rubella virus infection
Cells cultured in 2D were inoculated by adding RV stock virus to culture media in 1:1
dilution (250 ul of media to the equal volume of viral stock, 1.75×105 total ffu/well) to achieve
a multiplicity of infection (MOI) of 2. After four hours, media was exchanged with fresh cell
culture media. Cortical brain slices were treated with 500 ul of RV viral stock (3.5×105 total
ffu/slice) applied over the slice culture filter for four hours, and then the viral culture media
was removed and replaced with fresh slice culture media. Organoids were treated in 6-well
plates with 2ml of 1:1 dilution of viral stock:organoid maintenance media (7×105 total ffu)
for four hours, and then viral media was exchanged for fresh media. For all experimental
conditions, cells were fixed and processed for downstream analysis at 72 hours post
infection. Supernatant from non-infected Vero cells (mock) or heat-inactivated RV (650C, 30
mins) was used as control.
For titering experiments, microglia co-cultures or Vero cells (as controls) were infected at the
indicated MOI. Cells were inoculated for 4 hours, then fresh media was replaced, and
sampled at the indicated 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
10 minutes and washed with PBS three times for five minutes each wash. Blocking and

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permeabilization were performed in a blocking solution consisting of 10% normal donkey
serum, 1% Triton X-100, and 0.2% gelatin for 1 hour. Primary and secondary antibodies were
diluted and incubated in the blocking solution. Cell cultures were incubated with primary
antibodies at the room temperature for 1 hour, washed 3x with washing buffer (0.1% Triton
X-100 in PBS), and incubated with secondary antibodies for 1 hour at the room temperature.
Organoid samples were fixed in 4% PFA at the room temperature for 1 hour. Whole
organoids were incubated in 30% sucrose (w/v) at 40C overnight, cryopreserved in OCT/30%
sucrose (1:1) and then cryosectioned at 20 μm 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 1 hour. Primary and secondary antibodies were diluted and
incubated in the blocking solution. Cryosections were incubated with primary antibodies at
40C overnight, washed 3x for 10 minutes each with washing buffer (0.1% Triton X-100 in
PBS). Slides were incubated with species-specific AlexaFluor secondary antibodies (1:2,000)
overnight at 40C and then washed with washing buffer for at least 3x for 10 minutes 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 1 hour. 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 20x air lens (0.75 NA) and 63x
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 rubella virus capsid (1:500, Abcam,
ab34749), rat Sox2 (1:500, Invitrogen, 14-9811-82), chicken GFP (1:1,000, Aves labs, GFP-1020),
mouse NOVA1 (1:500, Santa Cruz, sc100334), rabbit EOMES (1:200, Sigma Aldrich,
HPA028896), chicken NeuN (1:1,000, Millipore, ABN91), rabbit IFITM3 (1:500, Proteintech,
11714-1-AP).
Organoid single-cell capture for single-cell RNA
sequencing
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 addition of DNase for 1 hr at 37°C. Following enzymatic digestion,
organoids were mechanically triturated using a P1000 pipette, filtered through a 40 μm cell
strainer test tube (Corning 352235), pelleted at 300xg for 5 minutes, washed twice with DBPS
and re-suspended in 180 µl of DPBS on ice for barcoding with MULTI-seq indices (McGinnis
et al., 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 10x Anchor:Barcode mixture was added to 180 µl of cell
suspension. Cells were incubated on ice for 5 minutes, and then 20 µl of co-anchor was
added to each tube. Cells were incubated on ice for additional 5 minutes 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 seven lanes of 10x Genomics using
Chromium single cell 3’ reagent kit (v2 Chemistry) following the manufacturer’s protocol.

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Single cell RNA-seq libraries were generated using the 10x Genomics Chromium 3’ Gene
Expression Kit. Briefly, barcoded single cell mixtures from different conditions ranging from
2-3 individual conditions per lane were loaded onto chromium chips with a capture target of
10,000 cells per sample. The 10x protocol was modified for collection of MULTI-seq barcodes.
During SPRI clean up 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 clean up step was transferred to fresh 1.5
mL Eppendorf tubes, and 260 µL SPRI (for a final ratio of 3.2X) and 180 µL 100% isopropanol
(for a final ratio of 1.8X) were added. After pipette mixing 10 times, the solution was
incubated at room temperature for 5 minutes, placed on magnetic rack for solution to clear.
The supernatant was removed, and the beads were washed with 500 µL of 80% ethanol
twice. Air-dry beads were removed from magnet, resuspended in 50 µL 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 10x lane. PCR was performed with the following protocol: 95 °C for
5 min, (98 °C for 15 sec, 60 °C for 30 sec, 72 °C for 30 sec) repeated for 10 times, 72 °C for 1
min, 4 °C hold.
PCR product was cleaned with 1.6X SPRI beads and resuspended in in 25 µL 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.
Single cell RNA-seq analysis
CellRanger 3.0 was used to create a cell by gene matrix which was then processed using Solo
(Fleming, Marioni, & Babadi, 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 et al., 2019) (https://github.com/chris-mcginnis-
ucsf/MULTI-seq). Uniform manifold approximation and projection (UMAP) (Leland McInnes,
John Healy, Nathaniel Saul, & Großberger, 2018) embeddings and neighbors for Leiden
clustering (Traag, Waltman, & van Eck, 2019) were used for clustering and visualization.
Nebulosa was used to generate density plots and (Bunis, Andrews, Fragiadakis, Burt, & Sirota,
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 (Hafemeister & Satija, 2019) integration workflow.

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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 interest 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 0.76 μm
according to image resolution. Relevant measurements including intensity mean, standard
deviation, min & 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 region of
interest 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 positive 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 2-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 representing 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 significance for cell counts. Unpaired nonparametric Kolmogorov-
Smirnov test was used to compare differentially expressed genes that reached significance
value of p=0.05 between conditions in organoids.
Parts of figure schematics were done using Biorender.com.
References
Banatvala J. E. , Brown D. W (2004) Rubella Lancet 363:1127–1137
https://doi.org/10.1016/S0140-6736(04)15897-2

Galina Popova et al., 2023. eLife https://doi.org/10.7554/eLife.87696.2 18 of 42
Bellanti J. A. , Artenstein M. S. , Olson L. C. , Buescher E. L. , Luhrs C. E. , Milstead K. L (1965)
Congenital rubella. Clinicopathologic, virologic, and immunologic studies Am J Dis Child
110:464–472
https://doi.org/10.1001/archpedi.1965.02090030484020
Bershteyn M. , Nowakowski T. J. , Pollen A. A. , Di Lullo E. , Nene A. , Wynshaw-Boris A. ,
Kriegstein A. R. (2017) Human iPSC-Derived Cerebral Organoids Model Cellular Features of
Lissencephaly and Reveal Prolonged Mitosis of Outer Radial Glia Cell Stem Cell 20:435–449
https://doi.org/10.1016/j.stem.2016.12.007
Brown A. S. , Cohen P. , Harkavy-Friedman J. , Babulas V. , Malaspina D. , Gorman J. M. , Susser
E. S (2001) A E. Bennett Research Award. Prenatal rubella, premorbid abnormalities, and adult
schizophrenia. Biol Psychiatry 49:473–486
https://doi.org/10.1016/s0006-3223(01)01068-x
Bunis D. G. , Andrews J. , Fragiadakis G. K. , Burt T. D. , Sirota M (2020) dittoSeq: Universal
User-Friendly Single-Cell and Bulk RNA Sequencing Visualization Toolkit Bioinformatics
https://doi.org/10.1093/bioinformatics/btaa1011
Cakir B. , Tanaka Y. , Kiral F. R. , Xiang Y. , Dagliyan O. , Wang J. , Park I. H (2022) Cakir, B.,
Tanaka, Y., Kiral, F. R., Xiang, Y., Dagliyan, O., Wang, J.,…Park, I. H. (2022). Expression of
the transcription factor PU.1 induces the generation of microglia-like cells in human
cortical organoids. Nat Commun, 13(), 430. doi:10.1038/s41467-022-28043-y Expression of
the transcription factor PU.1 induces the generation of microglia-like cells in human cortical
organoids. Nat Commun 13
https://doi.org/10.1038/s41467-022-28043-y
Cakir B. , Xiang Y. , Tanaka Y. , Kural M. H. , Parent M. , Kang Y. J. , Park I. H (2019) Engineering
of human brain organoids with a functional vascular-like system Nat Methods 16:1169–
1175
https://doi.org/10.1038/s41592-019-0586-5
Campbell I. L. , Bizilj K. , Colman P. G. , Tuch B. E. , Harrison L. C (1986) Interferon-gamma
induces the expression of HLA-A,B,C but not HLA-DR on human pancreatic beta-cells J
Clin Endocrinol Metab 62:1101–1109
https://doi.org/10.1210/jcem-62-6-1101
Chess S (1977) Follow-up report on autism in congenital rubella J Autism Child Schizophr
7:69–81
https://doi.org/10.1007/BF01531116
Cong H. , Jiang Y. , Tien P (2011) Identification of the myelin oligodendrocyte glycoprotein
as a cellular receptor for rubella virus J Virol 85:11038–11047
https://doi.org/10.1128/JVI.05398-11
Crow Y. J. , Manel N (2015) Aicardi-Goutieres syndrome and the type I interferonopathies
Nat Rev Immunol 15:429–440
https://doi.org/10.1038/nri3850

Galina Popova et al., 2023. eLife https://doi.org/10.7554/eLife.87696.2 19 of 42
das Neves L. , Duchala C. S. , Tolentino-Silva F. , Haxhiu M. A. , Colmenares C. , Macklin W. B. ,
Gronostajski R. M (1999) Disruption of the murine nuclear factor I-A gene (Nfia) results in
perinatal lethality, hydrocephalus, and agenesis of the corpus callosum Proc Natl Acad Sci
U S A 96:11946–11951
https://doi.org/10.1073/pnas.96.21.11946
Doan T. , Wilson M. R. , Crawford E. D. , Chow E. D. , Khan L. M. , Knopp K. A. , DeRisi J. L (2016)
Illuminating uveitis: metagenomic deep sequencing identifies common and rare
pathogens Genome Med 8
https://doi.org/10.1186/s13073-016-0344-6
Esterly J. R. , Oppenheimer E. H (1967) Vascular lesions in infants with congenital rubella
Circulation 36:544–554
https://doi.org/10.1161/01.cir.36.4.544
Eze U. C. , Bhaduri A. , Haeussler M. , Nowakowski T. J. , Kriegstein A. R (2021) Single-cell atlas
of early human brain development highlights heterogeneity of human neuroepithelial
cells and early radial glia Nat Neurosci 24:584–594
https://doi.org/10.1038/s41593-020-00794-1
Finak G. , McDavid A. , Yajima M. , Deng J. , Gersuk V. , Shalek A. K. , Gottardo (2015) MAST: a
flexible statistical framework for assessing transcriptional changes and characterizing
heterogeneity in single-cell RNA sequencing data Genome Biol 16
https://doi.org/10.1186/s13059-015-0844-5
Fleming S. J. , Marioni J. C. , Babadi M. (2019) Fleming, S. J., Marioni, J. C., & Babadi, M.
(2019). CellBender remove-background: a deep generative model for unsupervised
removal of background noise from scRNA-seq datasets. bioRxiv, 791699.
doi:10.1101/791699 CellBender remove-background: a deep generative model for unsupervised
removal of background noise from scRNA-seq datasets. bioRxiv
https://doi.org/10.1101/791699
Hafemeister C. , Satija R (2019) Normalization and variance stabilization of single-cell
RNA-seq data using regularized negative binomial regression Genome Biol 20
https://doi.org/10.1186/s13059-019-1874-1
He Z. , Maynard A. , Jain A. , Gerber T. , Petri R. , Lin H. C. , Treutlein (2022) Lineage recording
in human cerebral organoids Nat Methods 19:90–99
https://doi.org/10.1038/s41592-021-01344-8
Holmgren A. M. , Miller K. D. , Cavanaugh S. E. , Rall G. F (2015) Bst2/Tetherin Is Induced in
Neurons by Type I Interferon and Viral Infection but Is Dispensable for Protection
against Neurotropic Viral Challenge J Virol 89:11011–11018
https://doi.org/10.1128/JVI.01745-15
Keskinen P. , Ronni T. , Matikainen S. , Lehtonen A. , Julkunen I (1997) Regulation of HLA class
I and II expression by interferons and influenza A virus in human peripheral blood
mononuclear cells Immunology 91:421–429
https://doi.org/10.1046/j.1365-2567.1997.00258.x

Galina Popova et al., 2023. eLife https://doi.org/10.7554/eLife.87696.2 20 of 42
Korones S. B (1965) Bacterial Infection of the Neonate GP 32:89–100
Kreitzer F. R. , Salomonis N. , Sheehan A. , Huang M. , Park J. S. , Spindler M. J. , Conklin B. R
(2013) A robust method to derive functional neural crest cells from human pluripotent
stem cells Am J Stem Cells 2:119–131
Lazar M. , Perelygina L. , Martines R. , Greer P. , Paddock C. D. , Peltecu G. , Zaki S. R (2016)
Immunolocalization and Distribution of Rubella Antigen in Fatal Congenital Rubella
Syndrome EBioMedicine 3:86–92
https://doi.org/10.1016/j.ebiom.2015.11.050
McInnes Leland , Healy John , Saul Nathaniel , Großberger L (2018) UMAP: Uniform Manifold
Approximation and Projection Journal of Open Source Software 3
https://doi.org/10.21105/joss.00861
Lum F. M. , Low D. K. , Fan Y. , Tan J. J. , Lee B. , Chan J. K. , Ng L. F (2017) Zika Virus Infects
Human Fetal Brain Microglia and Induces Inflammation Clin Infect Dis 64:914–920
https://doi.org/10.1093/cid/ciw878
Mastromarino P. , Cioe L. , Rieti S. , Orsi N (1990) Role of membrane phospholipids and
glycolipids in the Vero cell surface receptor for rubella virus Med Microbiol Immunol
179:105–114
https://doi.org/10.1007/BF00198531
McGinnis C. S. , Patterson D. M. , Winkler J. , Conrad D. N. , Hein M. Y. , Srivastava V. , Gartner Z.
J (2019) MULTI-seq: sample multiplexing for single-cell RNA sequencing using lipid-
tagged indices Nat Methods 16:619–626
https://doi.org/10.1038/s41592-019-0433-8
McQuin C. , Goodman A. , Chernyshev V. , Kamentsky L. , Cimini B. A. , Karhohs K. W. ,
Carpenter A. E (2018) CellProfiler 3.0: Next-generation image processing for biology PLoS
Biol 16
https://doi.org/10.1371/journal.pbio.2005970
Menassa D. A. , Muntslag T. A. O. , Martin-Estebane M. , Barry-Carroll L. , Chapman M. A. ,
Adorjan I. , Gomez-Nicola (2022) The spatiotemporal dynamics of microglia across the
human lifespan Dev Cell
https://doi.org/10.1016/j.devcel.2022.07.015
Monif G. R. , Avery G. B. , Korones S. B. , Sever J. L (1965) Postmortem Isolation of Rubella
Virus from Three Children with Rubella-Syndrome Defects Lancet 1:723–724
https://doi.org/10.1016/s0140-6736(65)92084-2
Munro N. D. , Sheppard S. , Smithells R. W. , Holzel H. , Jones G (1987) Temporal relations
between maternal rubella and congenital defects Lancet 2
https://doi.org/10.1016/s0140-6736(87)90775-6

Galina Popova et al., 2023. eLife https://doi.org/10.7554/eLife.87696.2 21 of 42
Nguyen T. V. , Pham V. H. , Abe K (2015) Pathogenesis of Congenital Rubella Virus Infection
in Human Fetuses: Viral Infection in the Ciliary Body Could Play an Important Role in
Cataractogenesis EBioMedicine 2:59–63
https://doi.org/10.1016/j.ebiom.2014.10.021
Nowakowski T. J. , Bhaduri A. , Pollen A. A. , Alvarado B. , Mostajo-Radji M. A. , Di Lullo E. ,
Kriegstein A. R (2017) Spatiotemporal gene expression trajectories reveal developmental
hierarchies of the human cortex Science 358:1318–1323
https://doi.org/10.1126/science.aap8809
Nowakowski T. J. , Salama S. R (2022) Cerebral Organoids as an Experimental Platform for
Human Neurogenomics Cells 11
https://doi.org/10.3390/cells11182803
Otsuki N. , Sakata M. , Saito K. , Okamoto K. , Mori Y. , Hanada K. , Takeda M (2018) Both
Sphingomyelin and Cholesterol in the Host Cell Membrane Are Essential for Rubella
Virus Entry J Virol 92
https://doi.org/10.1128/JVI.01130-17
Parikshak N. N. , Swarup V. , Belgard T. G. , Irimia M. , Ramaswami G. , Gandal M. J. ,
Geschwind D. H (2016) Genome-wide changes in lncRNA, splicing, and regional gene
expression patterns in autism Nature 540:423–427
https://doi.org/10.1038/nature20612
Pasca A. M. , Sloan S. A. , Clarke L. E. , Tian Y. , Makinson C. D. , Huber N. , Pasca S. P (2015)
Functional cortical neurons and astrocytes from human pluripotent stem cells in 3D
culture Nat Methods 12:671–678
https://doi.org/10.1038/nmeth.3415
Perelygina L. , Faisthalab R. , Abernathy E. , Chen M. H. , Hao L. , Bercovitch L. , Sullivan K. E
(2021) Rubella Virus Infected Macrophages and Neutrophils Define Patterns of
Granulomatous Inflammation in Inborn and Acquired Errors of Immunity Front Immunol
12
https://doi.org/10.3389/fimmu.2021.796065
Plotkin S. A (2021) Rubella Eradication: Not Yet Accomplished, but Entirely Feasible J Infect
Dis 224
https://doi.org/10.1093/infdis/jiaa530
Popova G. , Soliman S. S. , Kim C. N. , Keefe M. G. , Hennick K. M. , Jain S. , Nowakowski T. J
(2021) Human microglia states are conserved across experimental models and regulate
neural stem cell responses in chimeric organoids Cell Stem Cell 28:2153–2166
https://doi.org/10.1016/j.stem.2021.08.015
Retallack H. , Di Lullo E. , Arias C. , Knopp K. A. , Laurie M. T. , Sandoval-Espinosa C. , DeRisi J. L
(2016) Zika virus cell tropism in the developing human brain and inhibition by
azithromycin Proc Natl Acad Sci U S A 113:14408–14413
https://doi.org/10.1073/pnas.1618029113

Galina Popova et al., 2023. eLife https://doi.org/10.7554/eLife.87696.2 22 of 42
Rock R. B. , Gekker G. , Hu S. , Sheng W. S. , Cheeran M. , Lokensgard J. R. , Peterson P. K (2004)
Role of microglia in central nervous system infections Clin Microbiol Rev 17:942–964
Rorke L. B. , Spiro A. J (1967) Cerebral lesions in congenital rubella syndrome J Pediatr
70:243–255
https://doi.org/10.1016/s0022-3476(67)80419-0
Schanze I. , Bunt J. , Lim J. W. C. , Schanze D. , Dean R. J. , Alders M. , Richards L. J (2018) NFIB
Haploinsufficiency Is Associated with Intellectual Disability and Macrocephaly Am J Hum
Genet 103:752–768
https://doi.org/10.1016/j.ajhg.2018.10.006
Steele-Perkins G. , Plachez C. , Butz K. G. , Yang G. , Bachurski C. J. , Kinsman S. L. , Gronostajski
R. M (2005) The transcription factor gene Nfib is essential for both lung maturation and
brain development Mol Cell Biol 25:685–698
https://doi.org/10.1128/MCB.25.2.685-698.2005
Sugishita Y. , Akiba T. , Sumitomo M. , Hayata N. , Hasegawa M. , Tsunoda T. , Tahara (2016)
Shedding of Rubella Virus among Infants with Congenital Rubella Syndrome Born in
Tokyo Japan, 2013-2014. Jpn J Infect Dis 69
https://doi.org/10.7883/yoken.JJID.2015.316
Tchieu J. , Calder E. L. , Guttikonda S. R. , Gutzwiller E. M. , Aromolaran K. A. , Steinbeck J. A. ,
Studer (2019) NFIA is a gliogenic switch enabling rapid derivation of functional human
astrocytes from pluripotent stem cells Nat Biotechnol 37:267–275
https://doi.org/10.1038/s41587-019-0035-0
Traag V. A. , Waltman L. , van Eck N. J. (2019) From Louvain to Leiden: guaranteeing well-
connected communities Sci Rep 9
https://doi.org/10.1038/s41598-019-41695-z
van der Logt J. T. , van Loon A. M. , van der Veen J. (1980) Replication of rubella virus in
human mononuclear blood cells Infect Immun 27:309–314
https://doi.org/10.1128/iai.27.2.309-314.1980
Vynnycky E. , Adams E. J. , Cutts F. T. , Reef S. E. , Navar A. M. , Simons E. , Dabbagh A. J (2016)
Vynnycky, E., Adams, E. J., Cutts, F. T., Reef, S. E., Navar, A. M., Simons, E.,…Dabbagh, A. J.
(2016). Using Seroprevalence and Immunisation Coverage Data to Estimate the Global
Burden of Congenital Rubella Syndrome, 1996-2010: A Systematic Review. PLoS One, 11(),
e0149160. doi:10.1371/journal.pone.0149160 Using Seroprevalence and Immunisation Coverage
Data to Estimate the Global Burden of Congenital Rubella Syndrome, 1996-2010: A Systematic
Review. PLoS One 11
https://doi.org/10.1371/journal.pone.0149160
Warre-Cornish K. , Perfect L. , Nagy R. , Duarte R. R. R. , Reid M. J. , Raval P. , Price (2020)
Interferon-gamma signaling in human iPSC-derived neurons recapitulates
neurodevelopmental disorder phenotypes Sci Adv 6
https://doi.org/10.1126/sciadv.aay9506

Galina Popova et al., 2023. eLife https://doi.org/10.7554/eLife.87696.2 23 of 42
World Health Organization, W (2020) Rubella vaccines: WHO position paper Weekly
Epidemiological Record 95:306–324
World Health Organization, W (2022) World Health Organization, W. (2022). Immunization
dashboard. doi:https://immunizationdata.who.int/pages/incidence/crs.html?
CODE=Global&YEAR= Immunization dashboard
Zhang C. , Frias M. A. , Mele A. , Ruggiu M. , Eom T. , Marney C. B. , Darnell R. B (2010)
Integrative modeling defines the Nova splicing-regulatory network and its
combinatorial controls Science 329:439–443
https://doi.org/10.1126/science.1191150
Author information
Galina Popova
Department of Neurological Surgery, University of California, San Francisco, CA, USA, Eli and
Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of
California, San Francisco, CA, USA, Department of Anatomy, University of California, San
Francisco, CA, USA, Department of Psychiatry and Behavioral Sciences, University of California,
San Francisco, CA, USA, Weill Institute for Neurosciences, University of California, San
Francisco, CA, USA, Department of Biochemistry and Biophysics, University of California San
Francisco, San Francisco, CA, USA
ORCID iD: 0000-0001-8249-219X
Hanna Retallack
Department of Biochemistry and Biophysics, University of California San Francisco, San
Francisco, CA, USA
ORCID iD: 0000-0003-0533-9102
Chang N. Kim
Department of Neurological Surgery, University of California, San Francisco, CA, USA, Eli and
Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of
California, San Francisco, CA, USA, Department of Anatomy, University of California, San
Francisco, CA, USA, Department of Psychiatry and Behavioral Sciences, University of California,
San Francisco, CA, USA, Weill Institute for Neurosciences, University of California, San
Francisco, CA, USA, Department of Biochemistry and Biophysics, University of California San
Francisco, San Francisco, CA, USA
Albert Wang
Department of Neurological Surgery, University of California, San Francisco, CA, USA, Eli and
Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of
California, San Francisco, CA, USA, Department of Anatomy, University of California, San
Francisco, CA, USA, Department of Psychiatry and Behavioral Sciences, University of California,
San Francisco, CA, USA, Weill Institute for Neurosciences, University of California, San
Francisco, CA, USA, Department of Biochemistry and Biophysics, University of California San
Francisco, San Francisco, CA, USA

Galina Popova et al., 2023. eLife https://doi.org/10.7554/eLife.87696.2 24 of 42
David Shin
Department of Neurological Surgery, University of California, San Francisco, CA, USA, Eli and
Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of
California, San Francisco, CA, USA, Department of Anatomy, University of California, San
Francisco, CA, USA, Department of Psychiatry and Behavioral Sciences, University of California,
San Francisco, CA, USA, Weill Institute for Neurosciences, University of California, San
Francisco, CA, USA, Department of Biochemistry and Biophysics, University of California San
Francisco, San Francisco, CA, USA
Joseph DeRisi
Department of Biochemistry and Biophysics, University of California San Francisco, San
Francisco, CA, USA, Chan Zuckerberg Biohub, San Francisco, CA, USA
For correspondence: joe@derisilab.ucsf.edu
ORCID iD: 0000-0002-4611-9205
Tomasz J. Nowakowski
Department of Neurological Surgery, University of California, San Francisco, CA, USA, Eli and
Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of
California, San Francisco, CA, USA, Department of Anatomy, University of California, San
Francisco, CA, USA, Weill Institute for Neurosciences, University of California, San Francisco,
CA, USA, Department of Biochemistry and Biophysics, University of California San Francisco,
San Francisco, CA, USA
For correspondence: tomasz.nowakowski@ucsf.edu
Editors
Reviewing Editor
Joseph Gleeson
University of California, San Diego, United States of America
Senior Editor
Sara Sawyer
University of Colorado Boulder, United States of America
Reviewer #1 (Public Review):
The authors sought to address the longstanding question of which cell types are infected
during congenital or perinatal rubella virus infection. They used brain slice and organoid-
microglia experimental models to demonstrate that the main cell types targeted by rubella
virus are microglia. The authors further show that infection results in augmented interferon
responses in neighboring neuronal cells but not in the microglia themselves. The data
convincingly support the conclusions, with major strengths being the sophisticated primary
cell models and single-cell RNA-Seq used to pinpoint microglia as the main cellular targets of
rubella virus, and neurons as the bystander targets of immune signaling. This study reveals
a new cellular target that will have important implications for basic studies on rubella virus-
host interactions and for the potential development of therapies or improved vaccines
targeting this virus. As rubella virus is a pathogen of high concern during human pregnancy,
this study is also relevant in the field of neonatal infectious diseases.

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Reviewer #2 (Public Review):
Maternal infection by Rubella virus (RV) early during pregnancy is a serious threat to the
health of the fetus. It can cause brain malformation and later expose the newborn to a
constellation of symptoms collectively named Congenital Rubella Syndrome (CRS). In this
manuscript, the authors provide novel exciting findings on the pathophysiological
mechanisms of RV infection during human brain development. By combining analyses of
human fetal brain material and cerebral organoids, Popova and colleagues uncovered a
selective tropism of RV for microglial cells. Their results suggest that the infection of
microglia by RV relies on the presence of diffusible factors secreted by neighboring brain
cells. Moreover, the authors showed that RV infection of human cerebral organoids leads to
a strong interferon response and dysregulation of neurodevelopmental genes, which both
may contribute to brain malformation. Altogether, these data shed some new light on the
cellular tropism and the pathophysiological mechanisms triggered by RV infection in the
developing brain. This study also raises the importance of using human cell-based models to
further understand the pathophysiological mechanisms of CRS. Identifying the cellular and
molecular targets of Rubella virus will also pave the way to develop therapies against CRS.
Author Response
The following is the authors’ response to the original reviews.
We thank the reviewers for their time in evaluating the strengths and weaknesses of our
manuscript.
We are pleased to see that all reviewers recognized the high significance of our work, noting
that the manuscript addresses “longstanding question of which cell types are infected during
congenital or perinatal rubella virus infection”. As noted by reviewer 1, “This study reveals a
new cellular target that will have important implications for basic studies on rubella virus-host
interactions and for the potential development of therapies or improved vaccines targeting
this virus. As the rubella virus is a pathogen of high concern during human pregnancy, this
study also has important implications in the field of neonatal infectious diseases”.
Below, we provide responses (in blue) to specific critiques:
Reviewer #1 (Public Review):
A weakness is that the current data do not provide information on the full replicative potential of
the rubella virus in microglia, or whether the virus persists in this system.
See our response below. Briefly, we include new experimental evidence from primary tissue,
microglia-transplanted organoids, and Vero cells to further characterize the dynamics of viral
infection.

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Reviewer #1 (Recommendations for the authors):
Most of the viral assays in the brain slices and organoids examine viral protein synthesis, which is
a surrogate for genome replication. However, basic virological characterization is lacking and
would improve the robustness of the model and its potential utility to understand better rubella
virus-microglia interactions. Questions the authors should consider with new experiments
include:
Are new virions produced? Can viruses be detected in the media?
Or, are the infections abortive, with viral protein synthesis occurring, but no virus production?
We performed RV titering experiments in dissociated microglia co-cultured with other cell
types, as well as Vero cells as a control. While we can detect a robust increase in viral titer
from Vero cells, it fell below detection levels in microglia co-cultures. See Author response
image 1. We now include these data in Supplementary Figure 2D.
Author response image 1.
Rubella virus titering experiment performed in Vero cells (positive control) or dissociated
microglia co-cultures. In primary microglia co- cultures, viral titer falls below detection levels
after several days of infection.
While we could not detect an increase in the viral particles from microglia mixed cultures, we
confirmed the presence of GFP from the RV-GFP reporter construct, and we believe it serves
as a proof that the virus can infect microglia cells and lead to production of functional viral
protein (Author response image 2, Figure 1E-F of the current manuscript):
Author response image 2.
We also observed an increase in RV RNA over time in tissue slice infections, using qPCR
(Author response image 3, not included in the manuscript).

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Author response image 3.
Modest increase in RV RNA over time in brain slice infections. Rubella virus RNA measured by
qPCR relative to GAPDH gene, in n=3 samples (2 technical replicates each condition). Brain
slices were exposed to RV, then collected at end of inoculation (4 hours post infection), or at 3
or 5 days post infection, and processed for RNA extraction and RT-qPCR.
How long do the infections persist in the model? What is the fate of infected microglia over time?
Time courses to monitor infection and cell health would be useful.
We performed a longer infection with RV in organoids transplanted with microglia, and after
two weeks of infection, we can detect multiple microglia cells positive for the RV capsid. These
data are now included in Figure 4 of the current manuscript.
Author response image 4.
After 2 weeks post infection, microglia remain positive for RV capsid.
Reviewer #2 (Public Review):
Weaknesses
The set of data is rather descriptive. It suggests that microglia are the predominant brain target
of RV in vivo, without identifying the targeting mechanism that provides cell type specificity.
Moreover, what are the diffusible cues released from the brain environment that increase
microglia infection and RV replication?
We agree with the reviewer that identifying molecular mechanisms that underlie this
phenotype will be very interesting to explore in future research, and we acknowledge the
limitation of the study in the Discussion.

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It is unclear why brain organoids not supplemented by microglia are susceptible to RV
inoculation.
We could not detect RV capsid in organoids without microglia after 72 hours of inoculation.
We attribute any changes seen at the level of single cell transcriptomics in the absence of
microglia transplantation to exposure to virus-associated particles, including but not limited
to viral RNA species, viral proteins, or even other components of the viral stocks made in Vero
cells. These factors may induce transcriptomic differences even in the absence of RV infection.
In the text, we take care to refer to these condition as “Rubella virus-exposed” rather than
“Rubella virus- infected”. We now include the following panel from Author response image 5
in Figure 4B of the current manuscript.
Author response image 5.
Organoids without microglia do not show positive RV immunofluorescence.
Reviewer #2 (Recommendations for the authors):
Several points could be further addressed to improve the data set and shed more light on some
aspects of this manuscript:
• Figure 1. Additional microglia markers should be used to reinforce the evidence that microglia
cells are the principal RV targets. Since Iba1 is a marker of activated microglia, does RV have a
selective tropism to all microglia or only to activated ones in human fetal brain slices?
The reviewer brings up an interesting point that, in our mind, can be separated into two
independent questions:
1. Are Iba1-positive cells bona fide microglia, or are there other cell populations of
macrophage/monocyte origin that are labeled with Iba1? Therefore, additional
markers should be used for immunolabeling;
2. Is RV infection selective for microglia “activation” status, when only 5mmune-primed
cells can be infected?
For the first point, we have previously shown that in the developing human brain, virtually all
Iba1-positive cells are also P2RY12-positive (unpublished; Author response image 6).
Therefore, in primary human brain slices, there is a negligible amount of non-microglia
macrophages. However, in culture microglia quickly lose their “homeostatic” identity,
including P2RY12 expression, as quickly as six hours after ex vivo extraction (Gosselin et al.,
2017; DOI: 10.1126/science.aal3222).
Author response image 6.
P2RY12 co-localizes with Iba1 in primary brain tissue from gestational week 17.5, including
cells with more ameboid morphology (arrows)

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However, in organoids at 2 weeks post-RV exposure, we found microglia with both ameboid
and more ramified morphology (Author response image 7). It would be challenging and
beyond the scope of this manuscript to use morphology or Iba1 intensity levels to determine
cause and effect as microglia activation state relates to RV infectivity (i.e. do activated
microglia preferentially get infected with the virus, or do infected microglia become activated
and upregulate Iba1 levels and change morphology).
Author response image 7.
Examples of microglia with round (top) and ramified (bottom) morphology that co-localize
with RV capsid staining.
Regarding RV tropism in the 2D culture of microglia, some Iba- cells are infected by RV as they
show capsid staining. What are these cells? Are neurons and/or glia also susceptible to RV in vitro
infection? Are non-microglial cells getting RV infected in the absence of microglia?
In the absence of microglia cells, a small proportion of non-microglia cells get infected with
RV. There is no statistically significant difference in the number of cells that get infected with
RV in the presence or absence of microglia across different cell types. We add these data as
Supplement Figure 3.
Author response image 8.

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Rubella infection in non-microglia cells. A. Representative images of different cell types
depleted of microglia. Cell cultures were stained RV capsid (green) and DAPI. B. Quantification
of total cells that are positive for RV capsid across conditions. C. Quantification of RV+ cells
that are not microglia across different cell populations. No statistically significant difference
was detected in RV infectivity in cells c-cultured with or without microglia.
• Figure 3. The low rate of Rubella virus infection in homogenous CD11b+ cell culture raises the
question of whether the Rubella virus can infect microglia at a specific activation stage. It is also
surprising that there is no infection of such cell population (also CD11b+) alone while cultured in
2D, as reported in figure 2. Why such a difference?
It is well established that culture of microglial cells isolated from brain tissue alters their
molecular properties, which likely alters the cell surface protein composition. In the revised
discussion, we include activation as a possible mechanism that will require further
investigation.
• Fig 4A-B, it is unclear whether organoids that are not engrafted with microglia get infected
upon RV (with active viral replication) inoculation. If non-microglia-supplemented organoids are
indeed infected and allow RV replication, this suggests that organoids might not be the ideal
system to model human fetal brain RV infection at GW18-23.
We could not detect RV capsid in organoids without microglia after 72 hours of inoculation.
We include the following panel from Author respone image 9 in Figure 4 now.
Author response image 9.
Organoids without microglia do not show positive RV immunofluorescence.

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• Figure 4E, why are cells derived from microglia-free organoids so much enriched in the UMAP
plots as compared to the other organoid condition? Is RV impacting cell fitness, proliferation, or
neurodifferentiation?
This perceived difference is due to data presentation. Based on cell proportions, cells from
organoids that were treated with microglia are more represented in the scRNAseq data, and
this difference most likely comes from user-introduced imbalance in cell loading and possible
cell losses during demultiplexing (Author response image 10, panel A). Cell number
composition across different conditions and cell types, including RV and MG treatment, are
shown in Supplement Figure 4 of the current manuscript (Author response image 10, panel B).
Contribution of each condition can be visualized via UCSC single cell data browser: https://
cells.ucsc.edu/?ds=rubella-organoids
Author response image 10.
Data composition depending on condition. A. Cell number contribution from organoids with
and without microglia. B. Contribution of each condition to each cluster composition.
• Figure 4F-H. If microglia is the predominant target for RV in the brain, why are microglia-free
organoids susceptible to RV and who are the other cellular targets, whose infection leads to
activation of interleukin pathway genes and dysregulation of brain developmental markers in
selected subpopulations (RGCs, ENs..).
Thank you for bringing this point. We did not detect any appreciable RV genomic RNA in our
published single cell data, nor did we identify RV capsid in the RV-exposed organoids without
microglia. Our experiments on dissociated cell cultures show that a small population (~1-4%)
of other cell types was positive for the RV capsid, including neuron-enriched and glial-
enriched fractions (Author response image 11; Supplementary Figure 3C in current

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manuscript). We expect a similar proportion of non-microglia cells to be infected in the brain
organoids. One possible explanation for the robust interferon response even in the absence
of productive infection in other cell types is exposure to virions and virus-associated particles,
including but not limited to viral RNA species, viral proteins, or even other components of the
viral stocks made in Vero cells (which is a cell line that should not produce interferons, but
may produce other unmeasured cytokines as a virally infected cell culture).
Author response image 11.
Quantification of RV+ cells that are not microglia across different cell populations. No
statistically significant difference was detected in RV infectivity in cells cultured with or without
microglia.
• QRT-PCR validations of some of these key brain targets should be performed.
We agree with the reviewer that further validation of the predicted molecular changes
downstream of Rubella exposure would be valuable. We have opted to validate IFITM3 and
NOVA1 expression differences using immunostaining, and the results are consistent with our
predictions from scRNAseq, and the data is presented in revised Figure 5 and 6 of the current
manuscript.
Reviewer #3 (Public Review):
Weaknesses of the paper: Overall, additional control experiments are needed to support the
stated conclusions. Affinity chromatography is used to purify microglia and other cell types, but
the overall cell enrichment is not quantified.
We appreciate the reviewer concern. However, affinity based enrichments rarely guarantee
purity of the enrichment, and we do not believe accurate estimation of the purification purity
would alter the biological interpretation of the data.

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In cell mixing experiments, the authors do not rule out the possibility that the added non-
microglia cells also become infected, releasing additional infectious viruses. The finding that a
diffusible factor is required for RV infection would be unusual if not unprecedented; therefore,
additional data are required to support this claim and rule out other interpretations.
We provide quantification of non-microglia cells that are positive for RV capsid in the presence
and absence of microglia. Small (~1-4%) of non-microglia cells get infected with the virus and
can potentially release more of the virus (see Author response image 12), but we do not know
how this newly produced virus would be different from the one that was applied to the cells
directly. To follow up our co-culture experiments, we wanted to exclude a possibility of
microglia engulfing RV- infected cells in co-cultures, therefore we separated the two cell
fractions by a liquid-permeable membrane (Figure 3 of the current manuscript). It is possible
that factors secreted by other cell populations in the transwell assay experiments act on
microglia cells to upregulate a yet unidentified receptor on microglia surface or other
infection-dependent molecule rendering them infectable by the virus.
We re-phrase the text by de-emphasizing “soluble factors” and focusing on excluding
phagocytosis of infected cells as a possible mechanism of RV capsid immunoreactivity in
microglia cells.
Author response image 12.
Rubella infection in non-microglia cells. A. Representative images of different cell types
depleted of microglia. Cell cultures were stained RV capsid (green) and DAPI. B. Quantification
of total cells that are positive for RV capsid across conditions. C. Quantification of RV+ cells
that are not microglia across different cell populations. No statistically significant difference
was detected in RV infectivity in cells c-cultured with or without microglia.

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The methods section would be improved by including details about the iPSC line that was used.
We include the following section in Materials and Methods:
iPSC lines.
All work related to human iPS cells has been approved by the UCSF Committee on Human
Research and the UCSF GESCR (Gamete, Embryo, and Stem Cell Research) Committee. Human
iPS cell line “WTC-10” derived from healthy 30-year-old Japanese male fibroblasts was from
the Conklin Lab, UCSF (Bershteyn et al., 2017; Kreitzer et al., 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 organoid differentiations.
and by a more thorough description of virus-specific details, including the numbers of infectious
particles added per volume of incubation media.
We now include the following data in the Materials and Methods section:
Rubella virus infection
Cells cultured in 2D were inoculated by adding RV stock virus to culture media in 1:1 dilution
(250 ul of media to the equal volume of viral stock, 1.75x105 total ffu/well) to achieve a
multiplicity of infection (MOI) of 2. After four hours, media was exchanged with fresh cell
culture media. Cortical brain slices were treated with 500 ul of RV viral stock (3.5x105 total
ffu/slice) applied over the slice culture filter for four hours, and then the viral culture media
was removed and replaced with fresh slice culture media. Organoids were treated in 6-well
plates with 2ml of 1:1 dilution of viral stock:organoid maintenance media (7x105 total ffu) for
four hours, and then viral media was exchanged for fresh media. For all experimental
conditions, cells were fixed and processed for downstream analysis at 72 hours post infection.
Supernatant from non-infected Vero cells (mock) or heat-inactivated RV (650C, 30 mins) was
used as control.
In addition to immunofluorescence, adding additional data to demonstrate and quantify virus
infection (PCR and plaque assays. or immunofluorescence using an anti-double-stranded RNA
antibody such as J2) from the infected brain slices and organoids would provide greater
assurance that the virus is indeed replicating under the experimental conditions.
We performed RV titering experiment in dissociated microglia co-cultured with other cell
types, as well as Vero cells control. While we can detect a robust increase in viral titer from
Vero cells, it fell below detection levels in microglia co-cultures. We now include these data in
Supplementary Figure 2D.
Author response image 13.
Rubella virus titering experiment performed in Vero cells (positive control) or dissociated
microglia co-cultures. In primary microglia co- cultures, viral titer falls below detection levels
after several days of infection.

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Unfortunately, we did not find J2 staining informative because we could detect signal in both
wild type RV infection conditions and in heat-inactivated RV, presumably due to native dsRNA
species present in cells. We did not detect any increase or difference in the pattern of staining
between RV and heat-inactivated virus-exposed conditions (Author response image 14; not
included in the manuscript).
Author response image 14.
J2 antibody labels dsRNA in both RV-exposed and control heat- inactivated virus conditions,
presumably due to native dsRNA that is not unique to the viral replication.
Organoid imaging with immunofluorescence would be very informative in demonstrating the
presence of microglia and also in showing which cells are virus-infected in the context of
organoid structures.
We provide images from 72hrs and 2 week RV infection, providing a zoomed-out view of
organoids with microglia and RV capsid staining. We also provide images of 72hrs post-
infection in organoids without microglia Author response image 15, Figure 4C in current
manuscript).
Author response image 15.
Microglia in organoids co-localize with RV capsid staining.

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GenBank accession numbers are listed for the recombinant RV and GFP-RV reporter, but a search
using those numbers did not locate the deposits--perhaps the deposits were very recent?
Both viral construct information is now available on GenBank:
M33 RV strain can be found here: https://www.ncbi.nlm.nih.gov/nuccore/OM816674
RV-GFP can be found here: https://www.ncbi.nlm.nih.gov/nuccore/OM816675
The authors incorrectly refer to the GFP virus as a new strain; it is not a viral strain and should be
referred to as a reporter virus.
Thank you, we changed the description to
“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, GenBank Accession OM816675)”
Given that the authors show that Vero cell cultures are infected by the Rubella virus in the
absence of other cells, additional evidence is needed to demonstrate that a diffusible factor from
other cells enables microglia to be infected by the Rubella virus.
We have revised the manuscript to indicate that our data is consistent with the possibility that
a diffusible factor is involved. Our experiment utilizing transwell assay argues against
phagocytosis and physical interactions as primary drivers, but future studies will be needed to
determine if soluble factors are involved.
The authors did not detect Rubella virus transcripts in the single-cell RNA sequencing experiment,
nor was a microglia cluster found.
Indeed, microglia recovery using scRNAseq is very inefficient. We note this limitation in the
discussion.
Innate immune responses can be activated in the presence of viral particles but without virus
replication, as in inactivated viral vaccines; therefore changes in interferon responses do not
necessarily prove virus replication.
We agree with the reviewer on this point, it is difficult, if at all possible, to entirely eliminate
the possibility that some of the transcriptomic changes, particularly the interferon responses,
are not induced by the exposure to viral particles. We have revised the manuscript to more
rigorously described the conditions as “RV-exposed”.

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Figure 4: it would be helpful to define the abbreviations used in the figure legend (e.g. IPC, RG,
EN). In the volcano plots, the gene names are blocked by the dots, and the figure becomes very
pixelated when enlarged to read the text.
We have added abbreviations and replaced the figure files with higher resolution images
(Figure 6 in current manuscript).
The value of including Supplemental Figure 2 (MOG) is not clear because it receives little mention
in the text and also seems to be previously published data that could be cited.
We have removed the figure and replaced it with a citation and a link to the Cell Browser.
Supplemental Figure 4: In panel G, the legend shows "YH10" and "13325". These terms are not
described in the Figure legend, nor did a search of the manuscript identify these terms. In its
current form Supp. Fig. 4G is not interpretable. In addition, would be more clear to use the term
"RV-infected" instead of "treated" to describe the addition of the virus.
We have expanded the Methods section to include the description of different organoid lines
and added a revised legend for Supplementary Figure 4. We do not provide evidence of RV
infecting organoids without microglia, therefore we have revised the claims that organoid
cells become infected with the virus and replaced it with “RV-exposed” to better reflect the
conditions studied.
Reviewer #3 (Recommendations for the authors):
1. Demonstrate and quantify virus replication to provide data to complement the imaging.
In order of data quality, plaque assays would be most convincing in demonstrating
infection and release of infectious virus, while a time course of PCR on RV transcripts
would support a conclusion of replicating virus. Further, staining with an anti-double-
stranded RNA antibody (J2) would represent evidence of virus replication.
In response to the reviewer’s comment, we performed an RV titering experiment in
dissociated microglia co-cultured with other cell types, as well as Vero cells control. While we
can detect a robust increase in viral titer from Vero cells, it fell below detection levels in
microglia co-cultures. We now include these data in Supplementary Figure 2D.
Author response image 16.
Rubella virus titering experiment performed in Vero cells (positive control) or dissociated
microglia co-cultures. In primary microglia co- cultures, viral titer falls below detection levels
after several days of infection.

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We detected a very modest increase in RV RNA in infected brain slices over time using RT-
qPCR (see Author response image 17, not included in current manuscript)
Author response image 17.
Modest increase in RV RNA over time in brain slice infections. Rubella virus RNA measured by
qPCR relative to GAPDH gene, in n=3 samples (2 technical replicates each condition). Brain
slices were exposed to RV, then collected at end of inoculation (4 hours post infection), or at 3
or 5 days post infection, and processed for RNA extraction and RT-qPCR.
Unfortunately, we did not find J2 staining informative because we could detect signal in both
wild type RV infection conditions and in heat-inactivated RV, presumably due to native dsRNA
species present in cells. We did not detect any increase of difference in the pattern of staining
between RV and heat-inactivated virus-exposed conditions (Author response image 18; not
included in the manuscript).
Author response image 18.
J2 antibody labels dsRNA in both RV-exposed and control heat- inactivated virus conditions,
presumably due to native dsRNA that is not unique to the viral replication.
We utilized FISH to detect negative-stranded (non-genomic) RV RNA as an alternative to J2 to
indicate RNA replication. However, it proved to be not very sensitive, as a small quantity of

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negative-strand RV RNA could be detected in highly infected Vero cells, but negative-strand RV
RNA was not detected in more modestly infected microglia (based on positive-strand RV RNA
quantification), as in Author response image 19, not included in current manuscript.
Author response image 19.
FISH probes to positive strand (genomic) and negative strand (replication template) RV RNA in
Vero cells and microglia co-cultures. A: representative images of Vero cells infected with RV
(top row) or Zika virus as control (bottom row). At 72hpi, cells were fixed and processed for
immunofluorescence with anti-RV capsid antibody (RVcap) or Zika virus antibody (Zika4G2),
and then FISH was performed using probes to positive strand (+) or negative strand (-) RV
RNA. Negative strand RV RNA difficult to visualize at low-power magnification, and required
quantification within cell borders defined by wheat germ agglutinin staining with results in
panel B. B: In Vero cells, negative strand RV RNA is detected in strongly infected cells.
Infection strength determined by intensity of RV capsid immunofluorescence staining and
positive strand RV RNA (RVcap/(+) 2/3 indicates robust infection, RVcap/(+) 1 indicates weak
infection). ZIKVinf = Zika virus infected control. C: In microglia co-cultures, positive strand RV
RNA detected in cells with RV capsid immunopositivity (RVcap_pos). RVinf = RV infected. RVHI =
heat-inactivated RV. D: In microglia co-cultures, negative strand RV RNA quantification not
significantly different between mock, heat-inactivated RV (RVHI), or RV- infected conditions
(RVinf), including cells with weak positive-strand RV RNA (RVinf, (+)<8) or cells with stronger
positive-strand RV RNA ((RVinf, (+)>=8). Two biological replicates (bHR60 and bHR61), n
indicates number of cells counted.
While we could not detect an increase in the viral particles from microglia mixed cultures, we
confirmed the presence of GFP from the RV-GFP reporter construct, and we believe it serves
as a proof that the virus can infect microglia cells and lead to production of functional viral
protein (see Author response image 20, Figure 1E-F of the current manuscript)

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Author response image 20.
Thus, overall we detect replication of viral RNA and protein (qPCR, RV-GFP), but not an
appreciable increase in released newly-made virions. The discussion now reflects this more
clearly in the current manuscript.
1. The claim of requiring a diffusible factor to enable RV infection requires additional data.
A suggestion would be to include further characterization of affinity-purified cells to
define the levels of cell enrichment and to determine which other cell types are present, It
is also important to test the RV infection of the fractionated cell types alone before adding
to the microglia, in order to demonstrate whether RV is replicating in cell types other than
microglia.
We performed quantifications of RV capsid-positive cells in each of the affinity-purified cell
populations: neuron-enriched (purified with PSA-NCAM beads), glia-enriched (PSA-NCAM
depleted cell fraction), or non-microglia fraction (“Flow through”, depleted of CD11b+ cells).
We show that across each condition, we have low infectivity (ranging from ~1 to 4% of total
cell population) after 72 hours post-infection. We include these data in Supplementary Figure
3.
Author response image 21.
Rubella infection in non-microglia cells. A. Representative images of different cell types
depleted of microglia. Cell cultures were stained RV capsid (green) and DAPI. B. Quantification
of total cells that are positive for RV capsid across conditions. C. Quantification of RV+ cells
that are not microglia across different cell populations. No statistically significant difference
was detected in RV infectivity in cells c-cultured with or without microglia.

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Another approach to limit cell heterogeneity would be to use iPSC-derived cells, which are highly
enriched as a single cell type as a specific cell type, to test the requirement for additional cell
types to achieve RV infection of microglia.
In our prior publication (Popova et al. 2021) we have identified a number of molecular
differences between primary and iPSC derived microglia. iPSC derived microglia like cells
could show differences in infection tropism from primary microglia, and those results may be
difficult to interpret biologically. We agree with the reviewer that iPSC derived cells would be
an interesting model, there are now several distinct protocols for deriving microglia like cells
from pluripotent stem cells and we feel that embarking on a protocol comparison project
would fall outside the scope of the current manuscript.
1. Consider a longer organoid infection. The authors did not identify viral RNA transcripts in
their organoid scRNAseq data after a 72-hour infection. Although the 72-hour time point
seems right for cells in 2D culture, it’s possible that the infection in the organoids is slower
because the virus has to spread inwardly. It would be worth trying a time course out to 2
weeks, collecting organoids every few days and then imaging and doing pcr or plaque
assays. Zoomed-out views that show immunofluorescence of the entire organoid would
also be beneficial in assessing organoid quality and immunofluorescent staining to
identify cell types,
We performed longer RV infection for two weeks and now present data on RV capsid in
microglia in 72 hrs and 2 weeks post-infection (Author response image 22, Figure 4C of the
current manuscript). We have also validated one of the scRNAseq-generated gene candidates
in combination with different cell type markers and present data on whole organoids
immunostained with NeuN for neurons and EOMES for intermediate progenitor cells that
demonstrate the overall structure of the organoids (Author response image 23; Figure 6 of the
current manuscript).
Author response image 22.

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Microglia in organoids co-localize with RV capsid staining. Organoid with microglia were
exposed to RV for 72 hrs or two weeks.
Author response image 23.
Organoids labeled with splice regulator NOVA1 (magenta), neuronal marker NeuN (green)
and intermediate progenitor cell marker EOMES (cyan).