Journal of Neuroinflammation

Shook et al. Journal of Neuroinflammation(2024) 21:163
https://doi.org/10.1186/s12974-024-03157-w

Open Access

RESEARCH

Maternal SARS-CoV-2 impacts fetal placental
macrophage programs and placenta-derived
microglial models of neurodevelopment
Lydia L. Shook1,2†, Rebecca E. Batorsky3†, Rose M. De Guzman1,2,4, Liam T. McCrea4,5, Sara M. Brigida1, Joy E. Horng4,5,
Steven D. Sheridan4,5, Olha Kholod6, Aidan M. Cook7, Jonathan Z. Li8, Donna K. Slonim9, Brittany A. Goods6,7†,
Roy H. Perlis4,5† and Andrea G. Edlow1,2*†
Abstract
Background The SARS-CoV-2 virus activates maternal and placental immune responses. Such activation in thesetting of other infections during pregnancy is known to impact fetal brain development. The effects of maternal
immune activation on neurodevelopment are mediated at least in part by fetal brain microglia. However, microglia
are inaccessible for direct analysis, and there are no validated non-invasive surrogate models to evaluate in utero
microglial priming and function. We have previously demonstrated shared transcriptional programs between
microglia and Hofbauer cells (HBCs, or fetal placental macrophages) in mouse models.
Methods and results We assessed the impact of maternal SARS-CoV-2 on HBCs isolated from 24 term placentas(N = 10 SARS-CoV-2 positive cases, 14 negative controls). Using single-cell RNA-sequencing, we demonstrated that
HBC subpopulations exhibit distinct cellular programs, with specific subpopulations differentially impacted by SARSCoV-2. Assessment of differentially expressed genes implied impaired phagocytosis, a key function of both HBCs andmicroglia, in some subclusters. Leveraging previously validated models of microglial synaptic pruning, we showedthat HBCs isolated from placentas of SARS-CoV-2 positive pregnancies can be transdifferentiated into microglia-likecells (HBC-iMGs), with impaired synaptic pruning behavior compared to HBC models from negative controls.
Conclusion These findings suggest that HBCs isolated at birth can be used to create personalized cellular models ofoffspring microglial programming.
Keywords Hofbauer cells, Microglia, Single-cell RNA sequencing, Fetal brain, Placenta, Neurodevelopment,
Neuroimmune, SARS-CoV-2, COVID-19†

Lydia L. Shook, Rebecca E. Batorsky contributed equally to this work
as first authors. Brittany A. Goods, Roy H. Perlis, Andrea G. Edlow
contributed equally to this work as last authors.
*Correspondence:
Andrea G. Edlow
aedlow@mgh.harvard.edu
1Vincent Center for Reproductive Biology, Massachusetts General
Hospital, 55 Fruit Street, Thier Research Building, 903B, Boston, MA
02114, USA
2
Department of Obstetrics, Gynecology and Reproductive Biology,
Harvard Medical School, Boston, MA, USA

3

Data Intensive Studies Center, Tufts University, Boston, MA, USA
Center for Genomic Medicine, Massachusetts General Hospital, Boston,
MA, USA
5
Department of Psychiatry, Massachusetts General Hospital, Harvard
Medical School, Boston, MA, USA
6
Thayer School of Engineering and Program, Dartmouth College,
Hanover, NH, USA
7
Department of Molecular and Systems Biology, Geisel School of
Medicine, Dartmouth College, Lebanon, NH, USA
8
Department of Medicine, Brigham and Women’s Hospital, Harvard
Medical School, Boston, MA, USA
9
Department of Computer Science, Tufts University, Medford, MA, USA
4© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use,sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) andthe source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in thisarticle are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not includedin the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you willneed to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The
Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available
in this article, unless otherwise stated in a credit line to the data.

Shook et al. Journal of Neuroinflammation(2024) 21:163

Background
Multiple population-based studies have suggested thatmaternal infection during pregnancy may have a transgenerational impact on offspring neurodevelopment.
Initial work found that the incidence of schizophrenia
was increased after influenza pandemics in Finland [1],Denmark [2], and the UK [3]. Subsequent registry studies
directly examining the association of maternal infection
requiring hospitalization during pregnancy with diagnoses of autism and other neurodevelopmental disorders
in offspring also found risk to be increased [4, 5]. Using
electronic health records, we identified an increased
risk of delayed acquisition of speech and motor milestones, beyond that attributable to prematurity, in a US
cohort of offspring whose mothers had SARS-CoV-2 during pregnancy [6, 7]. Similarly, authors of a prospective
cohort study of 127 children in Brazil found an increased
risk of neurodevelopmental delay with in utero exposure to maternal SARS-CoV-2 infection [8], and a recent
meta-analysis of smaller studies identified additional
evidence of neurodevelopmental sequelae – including
reductions in fine motor and problem-solving skills – in
infants with in utero SARS-CoV-2 exposure compared to
unexposed and pre-pandemic cohorts [9]. If these earlysignals foreshadow an increased risk of neurodevelopmental disorders in childhood and adulthood, the publichealth implications could be profound, given the significant number of pregnancies exposed to SARS-CoV-2
infection.
Despite the convergence of studies suggesting thatmaternal viral infection may increase offspring risk forneurodevelopmental disorders, the precise biologicalmechanisms leading to offspring neurodevelopmental vulnerability in SARS-CoV-2 are not known. Direct
placental and fetal infection with SARS-CoV-2 virus is
uncommon based on current evidence [10–14], and thus
vertical transmission is unlikely to be a major cause of
neurodevelopmental sequelae. Animal models of maternal immune activation (MIA), in which offspring of pregnant dams treated with an immune stimulus recapitulate
the behavioral hallmarks of human neurodevelopmental
disorders, have been used for decades to investigate candidate in utero mechanisms of neurodevelopmental programming [15–18]. Embryonic microglia have emerged
as central mediators of offspring neuropathology in thesetting of MIA [15]. However, microglia from surviving
offspring are inaccessible for direct analysis in humans,necessitating alternative models for evaluating the impactof SARS-CoV-2 on the fetal brain.
Prior work from our group has identified remarkablesimilarities in the transcriptional programs and reactivityof fetal placental macrophages, or Hofbauer cells (HBCs),
and fetal brain microglia isolated from mouse embryos[19, 20]. These two cell types share an embryonic origin

Page 2 of 19

in the fetal yolk sac [21, 22], and both carry the imprintof the in utero environment, with fetal yolk sac-derived
macrophages serving as the progenitors for the lifelong pool of microglia [23, 24]. Here, we investigate theimpact of SARS-CoV-2 exposure on the transcriptional
profiles of HBC subpopulations to gain insight into fetal
resident tissue macrophage programming. Our results
demonstrate that HBCs are a heterogeneous cell type,with eight subpopulations exhibiting distinct cellular
programs, and that maternal SARS-CoV-2 infection isassociated with varying impact on function in these subpopulations. Assessment of differentially expressed genes
implies impaired phagocytosis in specific subclusters,a key function of both HBCs and microglia; we confirm
these effects using a previously validated assay of microglial synaptic pruning via synaptosome phagocytosis[25–27]. In aggregate, we demonstrate the application of
HBC-based cellular models to gain non-invasive insight
into the impact of in utero exposures on fetal brain
development.

Results
Hofbauer cells are a heterogeneous population with
subclusters demonstrating both M1- and M2-like
transcriptional signatures

Placental chorionic villous tissues were collected fromN = 24 birthing individuals: N = 10 individuals who had apositive SARS-CoV-2 nasopharyngeal PCR test during
pregnancy, and N = 14 individuals with a negative PCR
at delivery and no history of a positive SARS-CoV-2 test
during pregnancy. In the majority of SARS-CoV-2 positive maternal cases, infections occurred remote fromdelivery (median [IQR]: 12.2 [0.8–19.6] weeks prior
to delivery) in unvaccinated individuals. No placental samples were infected with SARS-CoV-2 at delivery(defined as having detectable SARS-CoV-2 viral load in avalidated assay sensitive to 40 copies/mL) and individuals tested negative for SARS-CoV-2 by PCR at admission for delivery [14, 28]. For simplicity, we will use thenomenclature “SARS-CoV-2 positive” to refer to cases ofmaternal infection with SARS-CoV-2 during pregnancy
and “SARS-CoV-2 negative” to refer to controls, i.e. nohistory of maternal infection with SARS-CoV-2 during
pregnancy. Additional participant characteristics are provided in Table 1, results of placental pathology examination are provided in Supplementary File S8, and known
offspring neurodevelopmental outcomes are detailedin Table S2. Offspring neurodevelopmental outcomesshould be interpreted with the caveats that participant
numbers are too small to draw conclusions about association or causality, and that fewer than half of children
with neurodevelopmental disorders will have received adiagnosis by 5 years of age [29].

Shook et al. Journal of Neuroinflammation(2024) 21:163

Page 3 of 19

Table 1 Clinical information of study participants. GA: Gestational age. M: male. F: female. N/A: not applicable. COVID-19 infections
occurred in unvaccinated individuals, with the exception of D18 who had completed the primary mRNA vaccine series 7 weeks
prior to conception. 1COVID-19 severity was defined by NIH criteria (Available at https://www.covid19treatmentguidelines.nih.gov/
overview/clinical-spectrum/). 2Maternal age is provided as a range to preserve participant anonymity. Control subjects D1 and D6
were diagnosed with a hypertensive disorder of pregnancy at delivery not requiring medical therapy; no other participants had a
hypertensive disorder of pregnancy. Newborn 5-minute APGARs were > 7 for all participants. Additional clinical information is provided
in Supplementary Data File S8
Study ID

Maternal SARS-CoV-2 COVID-19 severity1
infection in pregnancy

GA at SARS-CoV-2
infection (weeks)

Infant Sex

Maternal Age2
(years)

D1
D2
D3
D4
D5
D6
D7
D8
D9
D10
D11
D12
D13
D14
D15
D16
D17
D18
D19
D20
D21
D22
D23
D24

No
No
No
No
No
No
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
No
No
No
No

N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
11.3
28.3
24.7
16.3
32.4
22.6
38.9
38
37.6
28
N/A
N/A
N/A
N/A
N/A
N/A

M
M
M
M
F
M
M
F
M
M
M
M
M
F
F
F
F
M
M
M
F
M
F
F

36–40
26–30
26–30
26–30
36–40
31–35
41–45
< 26
31–35
26–30
31–35
26–30
31–35
36–40
26–30
31–35
< 26
31–35
31–35
26–30
36–40
31–35
31–35
31–35

N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Mild
Mild
SevereMild
Mild
Asymptomatic
Mild
Asymptomatic
Severe
Mild
N/A
N/A
N/A
N/A
N/A
N/A

To assess the HBC transcriptome, we first used a previously-described protocol to obtain primarily HBCs fromplacental villi; in this protocol, a Percoll-based gradientand negative bead-based selection steps are used to isolate putative HBCs from other cell types present in thechorionic villi (including trophoblasts, fibroblasts) [30].
Single-cell RNA sequencing was performed on cell suspensions from N = 4 SARS-CoV-2 positive cases withsymptomatic COVID-19 disease and N = 8 SARS-CoV-2
negative controls (10x Genomics). Demographic andclinical information for these participants are presented
in Table 1 (D1-12).
After quality control filtering to remove putative doublets and cells with less than 300 identified genes, we
obtained a dataset comprised of a total of 70,817 cells.
We then performed sample integration and graph-based
clustering to identify broad cell types (Figure S1A).
Based on analyses of marker gene expression (Figure
S1B), we found that the majority of cells in our dataset
had marker gene expression consistent with monocytes/

GA at Delivery Infant(weeks)birthweight(grams)
39.3
3200
38.9
3450
38.9
3350
40.3
3670
39
2785
37.1
3360
39
2850
40.4
3270
39.9
3370
40.1
3125
39
3395
40.3
3985
38.6
3660
40.7
4260
38.9
3365
38.1
3340
38.6
3135
40.6
3495
39.7
3385
39.9
3350
40.1
3330
40.1
3530
39.6
2850
40.4
3350

macrophages, and that other cell types were represented
to a lesser extent, including some fibroblasts, vascular endothelial cells (VECs), extravillous trophoblasts(EVTs), leukocytes (NK cells, CD8 + T cells, B cells), neutrophils and red blood cells (Figure S1C). From this dataset, we excluded all cell types that were not identifiable
as macrophages/monocytes. After additional quality control filtering for nUMIs, gene counts, and percent mitochondrial reads (see Methods), this resulted in a dataset
containing 31,719 high-quality placental macrophages/
monocytes. All subsequent analyses were performed
with this final dataset.
After re-processing selected cells for quality control
as described, we identified 10 total subclusters of macrophages/monocytes (Fig. 1A), with representation ofeach subcluster across donors from both SARS-CoV-2
positive cases and controls (Figure S2A). To distinguish
HBCs, which are placental macrophages of fetal origin,from macrophages or monocytes of maternal origin, weused cells isolated from male placentas (N = 10). Male

Shook et al. Journal of Neuroinflammation(2024) 21:163

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Fig. 1 Transcriptomic profiles of fetal and maternal macrophages and monocytes isolated from term placentas with and without SARS-CoV-2 infection
during pregnancy. (A) Uniform Manifold Approximation and Projection (UMAP) visualization of 31,719 high-quality placental macrophage and monocyte
cells enriched from placentas of pregnancies with (N = 4) and without (N = 8) SARS-CoV-2 infection shows 10 clusters. HBC: Hofbauer cell; PAMM: placentaassociated maternal monocyte/macrophage. (B) Cluster-specific expression of DDX3Y, expressed only in fetal cells, and XIST, expressed only in maternal
cells, in placentas from individuals carrying a male fetus (N = 10). (C) Correlation of cluster-average gene expression with annotated cell types identified by
Suryawanshi et al., Sci Adv, 2018. Each heatmap shows Spearman correlation coefficients. Highest correlation coefficient per cluster is indicated by black
dots. HBC clusters were most highly correlated with Suryawanshi HBC clusters, PAMM cluster most correlated with decidual macrophages. (D) Heatmap
displaying expression (log2 fold change) of the top 5 marker genes per cluster. (E) Gene Ontology (GO) Biological Process enrichment analysis for cluster
marker genes. GO terms displayed were curated from the top significant GO terms in each cluster, selecting the processes most relevant to macrophagefunction, and reducing redundancy. Gene Count gives the number of genes in the query set that are annotated by the relevant GO category. GO termswith an adjusted p-value < 0.05 were considered significantly enrichedShook et al. Journal of Neuroinflammation(2024) 21:163

fetal origin was confirmed by high expression of DDX3Y
and low expression of XIST in 8 subclusters; these werelabeled HBC 0–7 (Fig. 1B). The macrophage cluster withhigh expression of XIST (consistent with maternal origin)
was annotated as placenta-associated maternal macrophages and monocytes (PAMMs, Fig. 1B) [31]. A small
cluster of monocytes – identified as such by high expression of monocyte marker genes S100A8, S100A9, and
TIMP1 – demonstrated equal expression levels of both
DDX3Y and XIST, suggesting that both fetal and maternal cells were present in this monocyte cluster. To further
support HBC cluster annotation, we next compared theoverall gene expression profiles of each cluster to a previously published single-cell dataset derived from humanfirst-trimester placenta and decidua [32]. In this analysis,
all putative HBC subclusters showed highest correlation
with HBC expression profiles from this dataset, whereas
the monocyte and PAMM clusters had higher correlation
with decidual macrophages than HBCs (Fig. 1C).
To delineate differences in the identity and functionsof HBC subclusters, we next assessed top marker genes
defining each subcluster, shown as an average heatmap(Fig. 1D); the complete list of marker genes by subcluster
is available in Supporting Data Values File (S1). Marker
genes for HBC clusters 3, 4, 5, and 7 suggested involvement in classic M1 macrophage/pro-inflammatory activities. HBC cluster 3 demonstrated high expression ofchemokine (C-X-C motif ) ligand genes (CXCLs) as wellas pro-inflammatory marker genes IL1B, IL1A, TNF, and
NFKB1. HBC cluster 4 demonstrated high expression ofmultiple CC chemokine ligand genes (CCLs) in a profile
similar to that observed in HBCs responding to lipopolysaccharide stimulation in vitro [33]. HBC cluster 5 wascharacterized by high expression of genes encoding major
histocompatibility complex (MHC) class II molecules(human leukocyte antigen (HLA)-DRA/B1 and -DP) andFc-gamma binding protein (FCGBP), suggesting a rolein antigen presentation to CD4 + T cells. MHC class II
molecules are critical to antigen-specific responses, andupregulation of HLA complexes and antigen presentation pathways has been observed in proteomic analyses
of HBCs stimulated with the viral dsRNA mimic poly(I:C) [33]. HBC cluster 7 demonstrated marker genes fromthe interferon-induced protein with tetratricopeptide
repeats (IFIT) family (IFIT2, IFIT3), CXCL10, ISG15, andMX1, associated with a pro-inflammatory type 1 interferon antiviral response. To gain further insight into the
biological processes reflected in each HBC subcluster,
we performed Gene Ontology (GO) enrichment analyses of cluster marker genes (Fig. 1E). GO biological process enrichment results are available in Supporting Data
Values File (S2). As would be expected given marker
gene expression noted previously, pathways involved in
M1-like immune/inflammatory responses were enriched

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in HBC 3, 4, 5, and 7, including “response to interleukin-1,” “response to interferon-gamma,” “response totumor necrosis factor,” and “positive regulation of cytokine production.”
Gene signatures of HBC clusters 0, 1, and 2 reflectedengagement in specific stress response processes, particularly response to inflammation and/or tissue damage, toultimately support placental function. HBC 0 and HBC
1 were characterized by genes encoding heat shock proteins and other proteins involved in endoplasmic reticulum stress and the unfolded protein response, such as
HSPA6, HSPA1B, DNAJB1, HSP90B1, HSPA5 and BAG3.
The unfolded protein response represents a homeostatic
response to restore balance when endoplasmic reticulum
stress is sensed and to modulate and/or resolve inflammation [34]. Additionally, HBC 0’s high expression of
PDK4 and KLF2 may suggest involvement in attenuating oxidative stress responses and reducing pro-inflammatory cytokine production [35, 36], and HBC 1’s highexpression of FABP5 and HMOX1 suggests engagement
in anti-inflammatory responses against heme-induced
toxicity and induction towards M2 polarization [37, 38].
GO enrichment analysis of these clusters similarly demonstrated enrichment of pathways such as “response to
unfolded protein”, “response to heat”, “response to endoplasmic reticulum stress”, and pathways related to cellularstress response and apoptosis (e.g. “extrinsic apoptotic
signaling pathway”, “response to oxidative stress” and“ERK1 and ERK2 cascade”).
GO enrichment analysis also suggested both HBC
0 and HBC 1 were engaged in homeostatic functions
including “receptor-mediated endocytosis”, “regulation ofangiogenesis” and “vascular development”, and nutrientsensing functions such as “response to nutrient levels”
and “response to starvation.” HBC 2 was characterized byhigh expression of the genes encoding secreted phosphoprotein 1 (SPP1) and Nicotinamide N -methyltransferase(NNMT), both associated with M2 (anti-inflammatory)
macrophage polarization in the context of tumor-associated macrophages [39, 40]; SPP1, also known as osteopontin, is secreted by HBCs and plays an important rolein endothelial biology and angiogenesis [41]. GO analysis of HBC cluster 2 also demonstrated enrichment in“receptor-mediated endocytosis” (involved in intracellular transport of macromolecules), as well as “cellular lipid
catabolic process,” and processes associated with stromal
tissue development.
HBC 6 was characterized by expression of genes
involved in regulation of actin polymerization andcytoskeleton organization (TMSB4X and AIF1, which
encodes the canonical microglial marker Iba1 [42]) andseveral ribosomal proteins including RPS18, RPS23,
and RPS4Y1. GO enrichment analysis of this cluster
demonstrates highly specific enrichment of proteinShook et al. Journal of Neuroinflammation(2024) 21:163

processing pathways (e.g. “protein targeting” pathways,“cytoplasmic translation,” “translational initiation”) andpathways related to RNA catabolism, oxidative phosphorylation, and ATP metabolism. Marker genes of thematernal PAMM subcluster included APOE, APOC1,
VIM, LGALS1, and GPNMB among others, an expression pattern consistent with previously reported maternal placental macrophage transcriptional profiles [43,44]. High expression of LGALS1/3 and GPNMB by the
PAMM cluster suggests a role in inflammation regulation[45–47], which was echoed by GO analyses identifying
enrichment in immune response and immunomodulatory pathways (e.g. “antigen processing and presentation,“positive regulation of cytokine production”, and “regulation of innate immune response”). In addition, GO
enrichment analysis demonstrated PAMM were engaged
in lipid metabolic processes and receptor-mediatedendocytosis, consistent with their known involvement
in lipid engulfment, and tissue repair/scar formation [41,43].
Maternal SARS-CoV-2 infection drives cluster-specificdifferences in immune signaling and metabolic pathways

Once the baseline functions of HBC and PAMM subclusters had been established, we then sought to characterize the impact of maternal SARS-CoV-2 infection
on the transcriptomic profile of HBC subclusters. To doso, we identified differentially expressed genes (DEG) bymaternal SARS-CoV-2 status within each cluster. DEG
were defined using log fold-change threshold of 0.2 andadjusted p-value of 0.05 (see Methods for full details). We
first verified that each subcluster included representationfrom both SARS-CoV-2 + cases and controls (Fig. 2A, top
panel). The proportion of cells from cases versus controls
was consistent across all subclusters, except for HBC 0,
which demonstrated a significantly greater contribution of control donor cells (Figure S2A). Of the 8 HBC
clusters, a majority (5) were significantly impacted bymaternal SARS-CoV-2 infection: HBC 0, 1, 2, 3, and 5(Fig. 2A, bottom panel). In contrast, HBC clusters 4, 6,
and 7 had very few DEG in the setting of maternal SARSCoV-2 infection, with three, zero, and two DEG respectively (Supporting Data Values File S3). Of the 5 highly
impacted clusters, HBC 1 and HBC 5 had the highest
number of DEG by maternal SARS-CoV-2, with 723 and566 DEG, respectively. PAMMs were impacted by SARSCoV-2 to a lesser extent, with 67 DEG identified. Bothup- and down-regulated DEG were identified across all
impacted clusters. The complete list of DEG by SARSCoV-2 infection status per subcluster are available in
Supporting Data Values File (S3).
GO pathway enrichment analysis of DEG indicatedthat in the context of maternal SARS-CoV-2 infection,
specific pathways involved in immune responses were

Page 6 of 19

enriched in all impacted HBC clusters (HBC 0, 1, 2, 3 and5), including response to lipopolysaccharide, response tointerferon-gamma, cellular response to tumor necrosis
factor, and regulation of T cell activation (Fig. 2B, Supporting Data Values File S4). Additionally, all subclusters
were enriched for pathways related to cellular movement,such as cell chemotaxis, leukocyte cell-cell adhesion,and myeloid leukocyte migration; heat shock-related
pathways (unfolded protein response); and phagocytosis
pathways.
GO enrichment analysis of DEG also indicated somebiological processes that were only impacted in specificclusters in the setting of maternal SARS-CoV-2 infection(Fig. 2B-C). For example, regulation of vascular development was only implicated in HBC 0 and the PAMM
cluster, and regulation of lipid metabolism and transport
in all clusters except HBC 5. Cellular energy utilization
pathways (e.g. ATP metabolism, electron transport chain/oxidative phosphorylation and cellular respiration), cellular stress/apoptosis pathways, and protein processing andactin cytoskeleton organization pathways were impacted
in HBC clusters but not PAMMs. Taken together, thesefunctional analyses suggest that in the context of maternal SARS-CoV-2 infection, HBC subclusters and PAMMs
are differentially impacted, with key implicated biological processes including innate immune and pro-inflammatory signaling, cell chemotaxis and migration, cellular
ATP and lipid metabolism, cellular phagocytosis, and theunfolded protein response.
To better understand the impact of SARS-CoV-2 on
HBC functions, we next used Ingenuity Pathway Analysis (IPA), which predicts strength and directionality (i.e.
activation or suppression) of enriched canonical pathways by subcluster. In this analysis, pathways with absolute Z-score value greater than 1 (consistent with IPA
being able to predict a direction of dysregulation of thepathway) and Benjamini Hochberg-adjusted p < 0.05
were included and displayed by subcluster (Fig. 2C and
Figure S2B-F, Supporting Data Values File S5). Z-scores≥ 1 indicate upregulated signaling in the pathway and ≤1 indicate downregulated pathway signaling [48]. BothHBC 1 and HBC 2 subclusters exhibited a primarily
anti-inflammatory response to SARS-CoV-2, with activation of PPAR signaling and oxidative phosphorylation, ametabolic profile associated with an anti-inflammatory/
pro-resolution phase macrophage signature [49, 50]. In
HBC 1 and 2, suppression of IL-6, IL-1, and IL-17 pathways, and activation of LXR/RXR signaling pathways
in SARS-CoV-2+ cases suggests involvement in resolution of inflammation, as LXR/RXR pathway activationin macrophages is associated with inhibition of inflammatory gene expression and promotion of lipid metabolism [51]. Also consistent with an anti-inflammatory role,
HBC 2 showed strong suppression of the Coronavirus

Shook et al. Journal of Neuroinflammation(2024) 21:163

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Fig. 2 Impact of maternal SARS-CoV-2 infection on Hofbauer cell subclusters. DEG: differentially expressed genes. (A) Barplot demonstrating proportionof cells per cluster from SARS-CoV-2 positive cases (red) and negative controls (gray), top panel. Number of DEG upregulated (dark blue) and downregulated (light blue) by SARS-CoV-2 exposure per cluster, bottom panel. (B) Gene Ontology (GO) Biological Process enrichment analysis for DEG. Gene Countgives the number of genes in the query set that are annotated by the relevant GO category. GO terms with an adjusted p-value < 0.05 were consideredsignificantly enriched. (C) Heatmap and table of the top 3 upregulated and downregulated DEG by SARS-CoV-2 by cluster. Color represents gene expression level (log2 fold change), *adjusted P-value < 0.05. (D) Ingenuity Pathway Analysis (IPA) of DEG for HBC clusters 0 (left) and 1 (right). Canonical pathways
with absolute Z-score ≥ 1 and adjusted p-value < 0.05 are shown. IPA analysis for remaining HBC clusters depicted in Supplement

Shook et al. Journal of Neuroinflammation(2024) 21:163

Pathogenesis Pathway and activation of Oxytocin Signaling Pathway, the latter of which is involved in attenuatingoxidative and cellular inflammatory responses in macrophages [52].
Conversely, HBC 0 and 3 demonstrated primarily activated pro-inflammatory immune responses in
SARS-CoV-2 positive cases, with increases in LPS/IL-1
mediated inhibition of RXR (HBC 3), Interferon induction (HBC 3), Neuroinflammation signaling (HBC 0
and 3), T-cell signaling (HBC 0 and 3), and Productionof nitric oxide and reactive oxygen species (ROS) (HBC0). Upregulation of apoptosis and ROS pathways in HBCcluster 0 may explain the significantly decreased representation of SARS-CoV-2 positive cases compared tocontrols in this cluster. Metabolic processes were suppressed in both clusters, including Oxytocin signaling
pathway (HBC 0), Sirtuin signaling (HBC 3), and MSPRON signaling (HBC 0 and 3) [52–54]. In the context
of maternal SARS-CoV-2 infection, subcluster HBC 5presented a mixed picture of both pro- and anti-inflammatory signaling, with upregulation of interferon, EIF 2,
neuroinflammation and T cell related signaling pathways,
balanced by upregulation of anti-inflammatory pathways such as PPAR signaling and downregulation of proinflammatory signaling pathways such as Coronavirus
Pathogenesis pathway, FAK and TNF-mediated signaling
pathways.
Compared to HBC subclusters, PAMMs were less
impacted overall by maternal SARS-CoV-2 at a transcriptomic level, with 67 DEG identified. In the setting ofmaternal SARS-CoV-2 infection, PAMMs showed activation of pathways involved in immune responses including
Production of Nitric Oxide and Reactive Oxygen Species,
B-cell signaling pathways, Interferon induction, and activation of the pattern recognition receptor TREM-1 signaling. Similar pro-inflammatory patterns were observed
for monocytes, including activation of antiviral response
pathways and Th1 signaling pathways, and suppression of
MSP-RON signaling (Figure S2C). Taken together, theseanalyses point to transcriptional shifts in some but not
all subclusters in response to SARS-CoV-2, with a greater
response by HBCs compared to PAMMs, driven by a
combination of immune activation/pro-inflammatory
signature in subclusters HBC 0 and HBC 3 and an antiinflammatory tissue repair signature in clusters HBC 1
and HBC 2.
Maternal SARS-CoV-2 infection impacts HBCtranscriptional programs associated with phagocytosis,
neuroinflammation, and neurological disorders

Tissue-resident macrophages promote resolution of
inflammation through phagocytosis of apoptotic cells,
invading pathogens, or cellular debris [55, 56]. Phagocytosis is also a key function of microglia in early brain

Page 8 of 19

development [57–59]. IPA functional analysis of SARSCoV-2-specific HBC signatures demonstrated thatmacrophage phagocytosis (Fig. 3A) and neurologicaldisease-related pathways (Fig. 3B) were key functions andpathways implicated by the cluster-specific gene expression signatures (Supporting Data Values File S6). Figure 3
summarizes the impact of maternal SARS-CoV-2 infection on placental macrophage phagocytosis (Fig. 3A andC), illustrating the potential for altered HBC gene programs to provide insight into both fetal brain microglial function and the impact of maternal SARS-CoV-2
infection on neurodevelopment (Fig. 3B and D). These
analyses predicted SARS-CoV-2-associated suppressionof phagocyte chemotaxis and cell movement pathways(e.g. reduced “activation of phagocytes”, “recruitment ofphagocytes”, “cell movement of phagocytes”, “adhesionof phagocytes”) in HBC 1, 2 and 5, consistent with the
suppression of synaptosome phagocytosis (a proxy forsynaptic pruning) observed in subsequent experiments
using in vitro Hofbauer cell induced microglial assays,
detailed below. In contrast to the consistent suppressionof phagocytosis in HBC clusters 1, 2 and 5, HBC clusters
0 and 3 and the PAMM cluster demonstrated activationof phagocytosis-related pathways including “Phagocytosis” (HBC 0), “Immune response of phagocytes” (HBC0), “Phagocytosis by macrophages” (HBC 3) and “Cellular infiltration by phagocytes” (HBC 3). A representative phagocytosis pathway from IPA and expressionof its constituent genes by cluster is depicted as a heatmap in Fig. 3C. Cluster-specific alterations in phagocyte
movement in the setting of maternal SARS-CoV-2 infection were primarily driven by expression differences in
CXCL2, NFKB1A, NFKB1Z, IL1B, CXCL8, CD36, andICAM1 by cluster (Fig. 3C). Concordant with patterns
observed in canonical pathways analyses, HBC 1 and 2(and to a lesser extent HBC 5), which showed primarily
immunomodulatory signatures, also show suppressedphagocytosis and phagocytic movement pathways, versus
proinflammatory clusters HBC 0 and 3, which demonstrate activation of phagocytosis.
In addition to phagocytosis, pathways relevant to neurologic disease and microglial functions emerged as key
dysregulated pathways in the setting of maternal SARSCoV-2 infection. We therefore assessed whether DEG of
HBC subclusters map to neuroinflammatory/neurodevelopmental pathways and functions in IPA, and plotted
pathway activation Z-scores by subcluster (Fig. 3B). The
transcriptional signature of HBC 1 – in which Fc-gamma
receptor-mediated phagocytosis (Fig. 2C) and other previously-described phagocytosis pathways (Fig. 3A) aresuppressed in SARS-CoV-2 + cases – is also associatedwith increased neuroinflammation, including positive
activation Z-scores for “Inflammation of central nervous
system”, “Myelitis”, and “Encephalitis.” Cluster-specificShook et al. Journal of Neuroinflammation(2024) 21:163

Page 9 of 19

Fig. 3 Impact of maternal SARS-CoV-2 on HBC gene programs associated with phagocytosis and neurologic disease. (A-B) Ingenuity Pathway Analysis(IPA) phagocytosis diseases and functions pathways (A), and neurologic diseases or functions (B), enriched for ≥ 3 DEGs, with absolute Z-score ≥ 1 andadjusted P-value < 0.05. Activation Z-score represented by color and number of DEGs by circle size, with red color indicating pathway activation and blue
color indicating suppression. (C-D). Heatmap of gene expression in “Cellular Infiltration by Phagocytes” IPA Pathway (C) and “Inflammation of Central
Nervous System” (D) by cluster. Color represents gene expression level (log2 fold change), *adjusted P-value < 0.05. (E). Module score by subcluster incomparison to cluster-specific gene expression of single-cell datasets from human brain: Microglia and Border Associated Macrophages (Askenase et al.,Sci Immunol, 2021) and Yolk Sac Macrophages and Monocytes (Bian et al., Nature, 2020). Color indicates module score

Shook et al. Journal of Neuroinflammation(2024) 21:163

expression of the genes in the “Inflammation of central nervous system pathway” is depicted in Fig. 3D,with upregulation of signaling in this pathway driven byincreased expression of ANXA1, FN1, CCL3, SLC1A3,NLRP3, and MERTK, among others. Interestingly, HBC
3 – in which “Inflammation of Central Nervous System”
is also predicted to be activated after maternal SARSCoV-2 infection and whose transcriptional signature
is consistent with activation in phagocytosis pathways,
also implicates increased “Apoptosis of neurons” and“Neuronal cell death” (Fig. 3B). In a developmental context, this pattern may represent a functional rather thanpathologic gene signature in response to SARS-CoV-2, as
microglia (resident brain macrophages) play a key role inneuronal cell turnover, regulation of neural progenitors,
and synaptic rewiring in early neurodevelopment, all via
phagocytosis [60]. Thus, increased phagocytosis by tissue-resident macrophages might be an adaptive response
to SARS-CoV-2-associated inflammation, while reduced
phagocytosis could be a pathologic or maladaptive
response to maternal immune activation (e.g., reduced
microglial phagocytosis and reduced synaptic pruning
associated with maternal immune activation is thought
to be a key aspect of the pathogenesis of autism spectrum
disorder and other neurodevelopmental pathologies [61–63]). Taken together, these data support the concept that
HBC transcriptional signatures provide insight into protective versus pathologic microglial programming in thesetting of an immune challenge such as SARS-CoV-2.
Prior work from our group in a mouse model has
shown that HBCs and fetal brain microglia share transcriptional profiles and responses to maternal obesity, an
immune-activating exposure [20]. To further probe thepotential connection between transcriptional signaturesof HBC subclusters and brain microglia in humans, wenext compared marker genes from HBC subclusters withgene modules from published human single cell atlasesof macrophages derived from adult and embryonic brain(Fig. 3E, Supporting Data Values File S7) [64, 65]. Nearly
all HBC subclusters scored highly for gene signatures
found in microglia, yolk sac macrophages, or CNS border associated macrophages, compared with monocytes
and PAMMs. HBC 2 and 1 exhibited greatest similarity
to yolk sac macrophages whereas HBC 3 and 4 were most
like microglia isolated from adult brain samples. In contrast, monocytes and PAMMs were most similar to circulating monocytes, which is concordant with their shared
myeloid lineage [41]. This analysis supports the conceptthat HBCs isolated from full term human placenta sharetranscriptional signatures with yolk sac macrophages andfetal brain microglia, and thus may offer insights into
global reprogramming of fetal macrophage populations,
including those of the fetal brain, in the setting of maternal immune-activating exposures.

Page 10 of 19

HBCs isolated from placentas of SARS-CoV-2 positive
pregnancies can be transdifferentiated to microglia-likecells (HBC-iMGs)

To gain insight into the functional consequences ofmaternal SARS-CoV-2 infection on HBC populations,
we used a model in which HBCs isolated from SARSCoV-2 positive cases (N = 10) and SARS-CoV-2 negative
controls (N = 9) were cultured in media containing IL-34
and GM-CSF to obtain transdifferentiated microglia-likecells (HBC-iMGs) (see Methods). Following culture, we
assessed the expression of multiple markers associatedwith microglial identity, including IBA1, TMEM119,
PU.1, P2RY12 and CX3CR1 [66, 67], and identified
expression of all markers in the majority of HBC-iMGsfrom both SARS-CoV-2 positive cases and negative controls (Fig. 4A, Figure S3A-C).
SARS-CoV-2-exposed HBC-iMGs demonstrate preserved
morphology but impaired phagocytic behavior compared
to HBC-iMGs from uninfected control placentas

To assess differences in cell phenotype by maternal
SARS-CoV-2 infection, we first evaluated cellular morphology of IBA1-positive HBC-iMGs by quantitative
assessment of two morphological characteristics: eccentricity (amoeboid vs. bipolar shape) and solidity (amoeboid/bipolar vs. ramified shape) (Fig. 4B-C), features
extracted via segmentation using CellProfiler (Methods).
More ramified microglial morphology in vivo is generally typical of resting-state, tissue-surveilling microglia
in vivo [68, 69], while more amoeboid morphology isclassically attributed to an immune-activated state [70],and typical of microglial patterns observed in fetal states[68, 71]. In this analysis, HBC-iMGs from SARS-CoV-2
negative controls demonstrated similar morphology tothat observed in positive cases, reflected in solidity andeccentricity (Fig. 4B-C). In aggregate, our results suggest
a lack of pronounced difference in microglial maturity orfunctional state, recognizing that no single measure captures activation state [72].
Transcriptional analyses of HBC clusters pointed toa cluster-specific impact of maternal SARS-CoV-2 onphagocytosis pathways. HBC clusters with the greatest
similarity to embryonic/yolk sac microglia (e.g. HBC 1,
2) also exhibited cellular programs suggestive of impaired
phagocytosis. Using a previously-validated model ofsynaptic pruning [25–27], a key physiologic function of
microglia in early brain development, we next tested thefunctional capability of HBC-iMGs to engage in phagocytosis. In this assay, HBC-iMGs were co-cultured for
3 h with pHrodo Red-labeled neuronal synaptosomes
derived from human induced pluripotent stem cells prior
to fixation and imaging. This pH-sensitive label fluoresces following intracellular engulfment (see Methods).
Synaptosome engulfment by IBA1-positive cells wasShook et al. Journal of Neuroinflammation(2024) 21:163

Page 11 of 19

Fig. 4 Phenotypic characterization of HBC-iMGs by direct cytokine reprogramming. HBC-iMGs: Hofbauer cells transdifferentiated toward microglia-likecells. (A) Representative images of HBC-iMGs, immunostained for microglial markers: IBA1, PU.1, P2RY12, TMEM119. Scale bar = 100 μm. (B) Morphologysmoothed density plots (solidity vs. eccentricity) for SARS-CoV-2 negative and positive samples as indicated. Representative confocal microscopy imagesof amoeboid, bipolar, and ramified HBC-iMGs. Scale bar = 50 μm. (C) Violin plots represent distribution of cell solidity (left) and eccentricity (right) measurements from SARS-CoV-2 negative controls (blue, n = 8965 cells from 9 participants) and positive cases (orange, n = 4754 cells from 10 participants).
Solid lines represent median values and dashed lines interquartile range. Group differences assessed by linear mixed effects model. ns = not significant

Shook et al. Journal of Neuroinflammation(2024) 21:163

then measured by quantifying fluorescence using confocal microscopy images with CellProfiler software applied
for segmentation and thresholding (Fig. 5A). Comparedto SARS-CoV-2 negative cases, HBC-iMGs from positive cases demonstrated significant impairment in synaptosome phagocytosis, reflected by a reduced mean
phagocytic index and thus a decrease on average acrossall subpopulations of assayed cells (Fig. 5B). Phagocytic
index was reduced across all SARS-CoV-2 positive samples, and was driven by reduced phagocytic uptake percell, independent of the proportion of cells engaged inphagocytosis in any given sample. (Figure S3D). These
functional analyses demonstrating reduced phagocytic
capability following maternal SARS-CoV-2 infection
are thus consistent with the transcriptomic signatures
observed in a subset of HBC suggesting downregulationof phagocytosis.

Discussion
Data from observational cohorts suggests an increased
neurodevelopmental risk of offspring exposed in utero tomaternal SARS-CoV-2 infection [6–8] but the underlying mechanism for offspring brain vulnerability remains
unknown. Studies have consistently demonstrated
that maternal SARS-CoV-2 infection drives alterations in immune cell populations and pro-inflammatory
responses at the maternal-fetal interface [73–80] thathave the capacity to impact the fetal brain [81]. Even in
the absence of direct viral transmission to the fetus, profiling of umbilical cord blood immune cell populations
and the serum proteome demonstrates that maternal

Page 12 of 19

SARS-CoV-2 infection can shape fetal and neonatal
immunity [44, 82–84]. Prior bulk and single-cell transcriptomic analyses have also revealed significant reprogramming at the maternal-fetal interface following
SARS-CoV-2 infection during pregnancy [44, 73, 74, 79],
yet granular information on fetal placental cell populations has been relatively limited by their lower representation in these studies.
Here we report single-cell RNA-seq data that provide
new insights into the heterogeneous functions that fetal
placental macrophages, or Hofbauer cells, and maternal resident placental macrophages and monocytes or
PAMMs, perform at baseline, and how these programs
are altered in the setting of maternal SARS-CoV-2
infection. We found that maternal SARS-CoV-2 infection in pregnancy, even distant from delivery and in
the absence of placental infection, was associated withsignificant alterations in the transcriptional programsof Hofbauer cells. These programs were more significantly impacted than those of maternal placental macrophages, as indicated by number of DEG. Effects ofmaternal SARS-CoV-2 infection were subcluster-specific,
with phagocytosis being a key dysregulated function,
and affected Hofbauer cell clusters exhibited signaturesconsistent with neuroinflammation and neurologic disease. We directly tested this predicted dysregulation
using in vitro models of HBC-based induced microglia (HBC-iMGs) [25–27], confirming that SARS-CoV-2
infection altered HBC-iMG function but not other phenotypic characteristics as indicated by preserved morphology. SARS-CoV-2 exposed HBC-iMGs exhibited

Fig. 5 Impact of maternal SARS-CoV-2 on HBC-iMG synaptosome engulfment. HBC-iMGs: Hofbauer cells transdifferentiated toward microglia-like cells(A) Representative image showing colocalization of pHrodo-red labeled synaptosomes (SYN) and IBA1 positive HBC-iMGs. Hoechst = nuclear stain. Scalebar = 100 μm. (B) Violin plots of phagocytic index of image fields from phagocytosis assays of HBC-iMGs from 9 SARS-CoV-2 negative controls (blue,n = 484 fields) and 10 SARS-CoV-2 positive cases (orange, n = 394 fields). Phagocytic index is calculated as synaptosome area in pixels divided by cellcount per image field. Solid lines represent median values and dashed lines interquartile range. Group differences assessed by linear mixed effects model.
*P < 0.05

Shook et al. Journal of Neuroinflammation(2024) 21:163

reduced synaptosome phagocytosis, an assay that serves
as a proxy for synaptic pruning. Notably, reduced synaptic pruning by microglia has been identified as a key
mechanism in the pathogenesis of a range of neurodevelopmental disorders including autism [61, 85], a neurodevelopmental disease associated with maternal immune
activation and viral infection in pregnancy [63, 86, 87].
Thus, the altered resident tissue macrophage programs
described here may not be specific to SARS-CoV-2 infection but may reflect more general alterations observed inviral infection in pregnancy.
Although an unavoidable limitation of our study is
the inability to directly assay fetal brain microglia of thelive offspring from cases and controls, data from mousemodels show that HBCs mirror the transcriptional andfunctional responses of fetal brain microglia to maternal
obesity, a chronic inflammatory state [19, 20]. Considering the shared fetal yolk sac origin of HBCs and brain
microglia [21, 22], HBCs may serve as a more accessible
cell type at birth that could provide information about
fetal brain immune programming. The creation of personalized fetal cellular models of neurodevelopment afterin utero exposure to maternal SARS-CoV-2 infection orother immune-activating exposures has the potential
to identify at-risk offspring earlier in life, which in turn
could facilitate efforts to normalize neurodevelopmental
trajectories [88, 89].
Our study is unique in its in-depth, focused interrogation of fetal immune cell populations of the placenta inthe context of a remote maternal viral infection. Throughsex-chromosome-specific gene expression mapping, wewere able to reliably assign fetal cell identity to 8 subtypesof HBCs, engaged in a myriad of functions at baseline.
Similar to prior work in first trimester placenta, we identified subclusters with transcriptional programs associated with angiogenesis and tissue remodeling, as well
as clusters enriched for immune defense functions [43].
Concordant with prior single-cell RNA sequencing studies of the placenta in the context of SARS-CoV-2 infection [44, 90], we identified that even in the absence of
direct placental infection or active COVID-19 disease at
the time of delivery, infection with SARS-CoV-2 in pregnancy, even remote from delivery, had a profound impact
on the transcriptional programs of the fetal macrophage
population, and to a lesser extent maternal PAMMs.
We defined a broad range of responses to SARS-CoV-2
across HBC subclusters, including some clusters withrelatively few DEG and others with significant transcriptional shifts. Impacted HBC subclusters demonstrated
transcriptional programs evoking the changes observedin neuroinflammation, and the same subclusters exhibited alterations in phagocytosis and in chemotaxis andcellular movement. To investigate these results further
we created induced microglial cellular models from thePage 13 of 19

same samples (HBC-iMG). Phenotypic and functional
analyses of HBC-iMGs from SARS-CoV-2 positive
samples demonstrated significant impairments in synaptosome phagocytosis. Reduced phagocytic efficiency
appeared to result from reduced capacity for synaptosome uptake within the cell, rather differences in the proportion of cells engaged in phagocytosis.
We demonstrated for the first time that HBCs can beused to create microglia-like cell models, applying thisapproach to gain insight into fetal brain immune programming in the context of maternal SARS-CoV-2 infection. As yolk-sac derived macrophages that colonize thefetal brain early in development [21], microglia play afundamental role in neurogenesis by promoting neuralprecursor cell proliferation, axonal outgrowth, and synaptic wiring throughout development [57–59]. A key
function of microglia in normal neurodevelopment also
includes selective phagocytosis of excess neuronal precursors and synapses to edit and refine the architectureof neuronal communication [59, 91]. Evidence from animal models of maternal immune activation (MIA) suggests that microglia are keenly responsive to maternal
innate immune signaling, and MIA-induced disruptionof normal microglial function can recapitulate social deficits and other behaviors correlative of those observed inneurodevelopmental disorders such as autism spectrum
disorder and schizophrenia [61, 62, 92, 93]. In contrast
to induced pluripotent stem cell (iPSC)-based models of
fetal microglia [94, 95], which have been shown to disrupt cellular phenotypes and imprinting such that the differentiated cells may not recapitulate the input cell typeand consequences of exposure [96, 97], our HBC-basedmodel is derived from the primary tissue itself and does
not require long-term passaging, making it more likely toretain epigenetic programming signatures [98]. Patientspecific HBC-iMGs may therefore have advantages over
iPSC-derived models for investigating the consequencesof maternal exposure on fetal microglia programming.
We note, however, that these models are intended to
examine microglial behavior in an experimental context,
not to precisely recapitulate in vivo processes. In thesame way, while phagocytosis assays correlate with pruning in 2D culture [25–27], as a model system they cannot
capture the full range of developmental or regional specificity of pruning.
A primary strength of our study is inclusion of rigorously phenotyped individuals without a history of prior
SARS-CoV-2 infection or vaccination and of contemporaneously enrolled control subjects. We thus were able
to examine the impact of maternal SARS-CoV-2 on an
immunologically naïve cohort in the absence of prior
immunity to SARS-CoV-2, with a consequence beingthat we could not assess the impact of prior vaccination.
Neither the impact of COVID-19 severity nor fetal sex

Shook et al. Journal of Neuroinflammation(2024) 21:163

could be assessed in this study due to the study design(primarily focused on symptomatic infection and malesamples as a proof of principle study) and small sample
size. Sex differences will be particularly important toassess in future work, given the importance of fetal sex
on offspring neurodevelopmental vulnerability and fetoplacental programming [99, 100]. Evaluation of HBCiMG motility will also be an important future direction
to explore given studies linking maternal immune activation to delayed microglial migration [101, 102]. Taken
together, our results suggest the ability of HBC-iMGs toserve as personalized cellular models of microglial programming in the setting of maternal exposures, including SARS-CoV-2 and potentially other environmental
exposures that might impact neurodevelopment. They
demonstrate potential mechanisms by which these exposures may contribute to adverse neurodevelopmental
outcomes.

Methods
Study design and participant enrollment

In this study, 24 pregnant individuals with full-term, singleton pregnancies delivering at Massachusetts General
Hospital (March 2021 - June 2023) were included. Participants were classified as SARS-CoV-2 positive (N = 10)
if they had symptomatic COVID-19 infection during
pregnancy confirmed by positive SARS-CoV-2 nasopharyngeal PCR test, or were asymptomatic but tested
positive on routine SARS-CoV-2 screening at delivery.
Participants were classified as SARS-CoV-2 negative(N = 14) if they did not have a positive SARS-CoV-2 nasopharyngeal PCR or COVID-19 symptoms during pregnancy and had a negative SARS-CoV-2 nasopharyngeal
PCR at delivery upon universal COVID-19 screening on
Labor and Delivery. Pregnant individuals were eligible forinclusion if they were 18 years or older and were delivering during the COVID-19 pandemic. Exclusion criteria included a history of autoimmune disease or chronicuse of immunomodulatory medications. A study questionnaire and review of the electronic health record wasused to determine key demographic and clinical variables
such as maternal age, gestational age at delivery, gestational age at positive COVID-19 test, COVID-19 disease
severity at diagnosis, any prior diagnoses of COVID-19
or history of COVID-19 vaccination, and infant sex andbirthweight. Placental pathology was performed for specific clinical indications per institutional protocol [103].
COVID-19 disease severity was assigned as asymptomatic, mild, moderate, or severe using NIH criteria [104],
also endorsed for use in pregnancy by the Society for
Maternal Fetal Medicine. Manual review of the electronic health records of the offspring in this study was
performed to assess for the presence of diagnostic codes

Page 14 of 19

associated with abnormal neurodevelopment, as previously described [6, 7].
Placenta collection and processing

Placentas were obtained within 20 min after delivery
and submerged in Cytowash media (Dulbecco’s Modified Eagle Medium (DMEM) containing 2.5% FBS, 1%
Penicillin-Streptomycin, 0.1% Gentamicin) and stored at
4 °C until cell isolation. Isolation of Hofbauer cells was
performed using previously described protocols [30];reagents are listed in Supplemental Table S1 and isolation
workflow and study procedures are depicted in Supplemental Figure S4. Briefly, placental chorionic villi wereseparated from fetal membranes and decidua, washed in
DPBS wash, and mechanically homogenized. Placental
tissue was then serially digested in Collagenase Digestion Buffer, Trypsin Digestion Buffer, and Collagenase
Digestion Buffer 2. Undigested tissue was removed bypassage through sterile gauze and 100 μm filter. The cellsuspension was centrifuged at 257 g for 8 min at 4 °C,
washed, spun again, and resuspended in media. The
cells were then suspended in 4mL of 20% Percoll and
5mL of 35% Percoll was underlayed through a #1 glass
Pasteur pipette [105]. After centrifugation for 30 min at
4 °C without brake at 1000 g, cells were isolated from theinterphase layer, washed in media, and spun at 257 g for
8 min at 4 °C. Cell pellets were immunopurified by negative selection by incubation with anti-EGFR (to remove
syncytiotrophoblasts) and anti-CD10 (to remove fibroblasts) conjugated to magnetic Dynabeads, prepared aspreviously described (76), for 20 min at 4 °C. Tubes wereplaced on a DynaMagTM magnet for 5 min to magnetically bind cytotrophoblasts (anti-EGFR) and fibroblasts(anti-CD10) – allowing media containing unbound placental macrophages to pass through into collection tubes.
Cells were cryopreserved in 90% FBS and 10% dimethyl
sulfoxide (DMSO) at 1–10 million cells/vial and stored at-80 °C for downstream analyses. SARS-CoV-2 viral loads
were assessed in all placental tissues using qPCR as previously described, with 40 copies/mL as limit of detection[14, 28].
Single-cell RNA-sequencing (scRNA-Seq) data analysis

Sequencing. Cryopreserved HBCs were thawed at 37 °C
and diluted with RPMI 1640 including 10% FBS and
1% Pen/Strep. The cell suspension was centrifuged at
300 g for 5 min at room temperature, with the brake off.
The supernatant was aspirated and the cell pellet was
resuspended in media. Dead cells were removed using
OptiPrepTM Density Gradient Medium (Sigma) andcell count and viability of cells were calculated using
LunaFX7 automated counter. Cells were immediately
loaded onto 10x Genomics platform with a loading target of approximately 10,000 viable cells/sample. Libraries

Shook et al. Journal of Neuroinflammation(2024) 21:163

were sequenced on an Illumina NextSeq 2000 P3 flowcell
machine with a sequencing target of 25,000 reads per cell.
Initial cluster identification. Raw reads were aligned
to reference genome GRCh38 and quantified using Cell
Ranger (version 6.0.1, 10x Genomics) and after initial
cellranger filtering an average of 6,295 cell/sample and20,459 reads/cell were present. Putative doublet cells
were removed using predictions generated from DoubletFinder (v2.0.3) as were cells containing less than 300
identified genes, which resulted in an object containing 70,817 cells. All samples were integrated to remove
batch effects from individuals using the Seurat Single
Cell Transform workflow (Seurat version 4.3.0) with the
top 2,000 variable features. Cells were clustered using
the Louvain algorithm on the shared nearest neighbor
graph and visualized by UMAP using the first 30 principal components. Several clustering resolutions were used
to scan through the data to identify a resolution (0.3)
that allowed us to identify top-level cell types based onmarker genes. Marker genes were identified using the
Wilcoxon rank sum test with the following parameters:
only.pos = TRUE, min.pct = 0.2, logfc.threshold = 0.5.
Additionally, expression of well-known cell-type markers was assessed to refine top-level identities: hofbauer,
fibroblasts, NK cells/CD8 T cells, VECs (vascular endothelial cells), EVTs (extravillous trophoblasts), RBCs
(red blood cells), B cells, and neutrophils (Supplemental
Figure S1). For subsequent analyses, we created a subsetof the data including only cells identified as “Hofbauer,”which included macrophage and monocyte populations.
Subcluster analysis. The data were re-integrated andprocessed similarly as described above to identify macrophage/monocyte subclusters. Only high-quality cells
were retained (mitoRatio < 0.25 and nUMI > 1000 and< 9681, or 3 standard deviations above the mean UMI
count). The number of subclusters was optimized by
iteratively clustering across several cluster resolutions,and identifying the resolution that provided non-redundant clusters (resolution = 0.3) as determined by marker
gene identification with Seurat’s Wilconcon rank-sum
test (only.pos = TRUE, min.pct = 0.3, and logfc.threshold = 0.5). Subclusters were then assigned as HBCs (0–7),
PAMMs or Monocytes based on marker genes. To delineate fetal from maternal origin of subclusters, we evaluated sex-specific markers using only cells from placentas
with a male fetus (N = 10). This allowed for maternal vs.
fetal cell differentiation, as fetal cells would be expected
to have increased expression of the male-specificY-linked gene DEAD-Box Helicase 3 Y-Linked (DDX3Y)
and maternal cells would exhibit high expression of thefemale-specific gene X-inactive specific transcript (XIST).
The macrophage cluster with high expression of XIST
consistent with maternal origin was annotated as maternal placenta-associated macrophages and monocytes

Page 15 of 19(PAMMs). To further support cell cluster annotation,
we also compared the overall gene expression profiles ofeach cluster to a previously published single-cell dataset
derived from human first-trimester placenta and decidua[32].
Differential gene expression by SARS-CoV-2 status.
For differential gene expression analysis between cells
from SARS-CoV-2 positive cases and negative controls,
we used the Seurat FindMarkers() within each clusterwith the following parameters: test.use = “MAST”, min.
pct = 0.3, logfc.threshold = 0.2, latent.vars = “donor”.
Genes with Benjamini-Hochberg adjusted p-value < 0.05
were considered significant. Gene lists used to computemodule scores in Fig. 3E for comparison to Bian et al.
[64] and Askenase et al. [65] datasets are given in Supporting Data Values File (S7).
Functional enrichment analyses. Gene Ontology (GO)
Biological Process enrichment analysis was performed
on both cluster marker genes and SARS-CoV-2 differentially expressed genes in each cluster using R package
clusterProfler (v. 3.18.1) [106] and underlying database
AnnotationDb org.Hs.eg.db (v3.12.0). GO terms wereconsidered significant with adjusted p-value < 0.05. IPA
Canonical Pathway and Diseases and Functions analysis
were performed with IPA (Content Version: 90,348,151)
with pathways considered significant with adjusted
p-value < 0.05.
Derivation of Hofbauer cells transdifferentiated toward
microglia-like cells (HBC-iMGs) by direct cytokine
reprogramming

HBC-iMGs were derived from HBCs using previously
described methods [25–27], with modifications as noted.
Briefly, thawed HBCs were plated on Geltrex-coated24-well plates (1 × 106 cells in 0.5 mL per well) or 96-wellplates (2 × 105 cells in 0.1mL per well) depending on cellavailability. After cells were incubated at 37 °C for 24 h,
the media was completely replaced with RPMI 1640
including GlutaMAX, 1% penicillin–streptomycin, 100
ng/mL of human recombinant IL-34 (Peprotech), and10 ng/mL of GM-CSF (Peprotech). At day 6 of transdifferentiation, the cultures were assayed and subsequently
fixed with 4% PFA to perform endpoint analysis using
immunocytochemistry.
HBC-iMG immunocytochemistry

HBC-iMGs were washed twice with PBS and blocked for
1 h with 5% FBS and 0.3% Triton-X (Sigma Aldrich) in
PBS at room temperature. Next, they were washed threetimes with 1% FBS in PBS and incubated with primary
antibodies in 5% FBS and 0.1% Triton-X overnight at 4 °C
(Anti-IBA1, 1:500; Abcam #ab5076; Anti-TMEM119,
1:500; Abcam #ab18537; Anti-CX3CR1, 1:100, Abcam#ab8021; Anti-PU.1, 1:1000, Abcam #ab183327, andShook et al. Journal of Neuroinflammation(2024) 21:163

Anti-P2RY12, 1:100, Alomone Labs). Cells were thenwashed three times with 1% FBS in PBS and incubated insecondary antibodies (Invitrogen Alexa Fluor, 1:500) andHoechst 33,342 (1:5000) in 5% FBS and 0.1% Triton-X in
PBS for 45 min at 4 °C. Cells were washed two final times
and imaged using the IN Cell Analyzer 6000 (Cytiva).
Proportion of labeled cells was analyzed using CellProfiler [107] as described below. Cells were segmented
using one of the four microglia markers used and percent
marker positive cells calculated by dividing the number of marker positive cells by the number of identified
nuclei, per image. A total of 12 20x images per sample
were analyzed.
Synaptosome derivation and phagocytosis assay

Synaptosome generation from neural progenitor cell
cultures. Induced pluripotent stem cells were reprogrammed from fibroblasts and used to derive expandable neural progenitor cells, and large-scale differentiatedneural cultures, as previously described [25–27]. After
media removal, neural cultures were collected by scraping in 10 ml per T1000 flask 1× gradient buffer (ice-cold
0.32 M sucrose, 600 mg/L Tris, 1 mM NaH3CO3, 1 mM
EDTA, pH 7.4 with added HALT protease inhibitor—
Thermo-Fisher Scientific # 78,442) and homogenizedusing a Dounce Tissue Grinder (Wheaton #357,544
15 ml) with the ‘tight’ plunger. Homogenate was collected
and centrifuged at 700 g g for 10 min at 4 °C to remove
large debris. The gradient buffer was removed by aspiration and saved on ice then the pellet was resuspended
in 10 mL of 1× gradient buffer and homogenization was
repeated as above. The final homogenates were combined
and centrifuged at 15,000 g for 15 min at 4 °C. This second pellet was resuspended in 12 ml 1× gradient bufferand slowly added on top of a pre-formed sucrose gradient in Ultracentrifuge Tubes (Beckman Coulter UltraClear #344,058) containing 12 ml each 1.2 M (bottom)
and 0.85 M (middle) sucrose layers. The gradients were
centrifuged using Ultracentrifuge swinging bucket rotor#SW32TI at 26,500 RPM (~ 80,000 g) for 2 h at 4 °C withthe brake off. The synaptosome band (in between 0.85
and 1.2 M sucrose layers) was removed using a 5-mL
syringe and 19Gx1 ½″ needle, diluted with 5-fold 1x gradient buffer then centrifuged at 20,000 g for 20 min at
4 °C. The final pellet was resuspended in an appropriate
volume of 1× gradient buffer containing 1 mg/mL bovine
serum albumin (BSA) with HALT protease and phosphatase inhibitors added, aliquoted and slowly frozen
at − 80 °C. Protein concentration was measured by BCA
and enrichment of pre-synaptic (synapsin, SNAP-25) andpost-synaptic (PSD-95) markers was determined by western blot analysis.
Phagocytosis Assay. Synaptosomes were thawed andlabeled with pHrodo Red SE (Thermo-Fisher ScientificPage 16 of 19#P36600) at 1:2 (mg dye: mg synaptosome) and incubatedat room temperature for 1 h. Labeled synaptosomes were
centrifuged at 15,000 g for 15 min to wash away unboundpHrodo Red SE. They were resuspended in RPMI 1640
and then sonicated for 1 h before adding to HBC-iMGs at
15 mg total protein per well in 24-well plates, or 3 mg per
well in 96-well format. HBC-iMGs with synaptosomes
were incubated at 37 °C for three hours and then fixedwith 4% PFA for 15 min at room temperature. Immunocytochemistry was performed to quantify phagocytosis,
with images analyzed in CellProfiler (v4.2.4). HBC-iMGs
were segmented as described below using IBA1 staining and phagocytic index was calculated by dividing thesignal area of pHrodo Red by the number of segmented
cells, per image.
Image analysis

CellProfiler (v4.2.4) was used to identify cellular andsubcellular structures in the confocal images [107]. The
module CorrectIlluminationCalculate and CorrectIlluminationApply were used in all channels to correct
uneven illumination and uneven background. Nuclei
and cell bodies were each identified using IdentifyPrimaryObjects. Specifically, pixel diameter ranges and theautomatic thresholding method Otsu were applied. The
module RelateObjects was used to drop structures incorrectly identified as nuclei by ensuring they were only
accepted when they have a surrounding microglia-likecell. IdentifySecondaryObjects was used to more accurately outline cells around these nuclei and avoid debris.
The module IdentifyTertiaryObjects identified cytoplasm
by subtracting the area of the nucleus from the cell. IdentifySecondaryObjects was used with Otsu thresholding
to identify and measure synaptosomes. Background red
signal was eliminated by increasing the lower bounds on
the automatic threshold, using reference images from
Cytochalasin treatment as a positive control of diminished phagocytosis. MaskObjects was used with the celland synaptosome objects to omit red signal from outside
the cell. Overlays of the outlines of all generated image
structures were created for quality check purposes using
the OverlayOutlines module. Cell area, count, and signal
intensity were created with MeasureObjectSizeShape,
MeasureObjectIntensity, ExportToSpreadSheet, andExportToDatabase. RStudio 2 (1.4) was used to organize the metadata exported from CellProfiler. Phagocytic
index was calculated as area of Synaptosomes divided bycell count per image. As a confirmation, the integrated
intensity of Synaptosome signal divided by cell area wasalso checked to make sure both measures corresponded.
Images containing > 80 cells were omitted due to procedure inaccuracy with dense fields. Outliers were excluded
by calculating a phagocytic index threshold of 3 SD above
the mean. Morphology data was produced using cell level

Shook et al. Journal of Neuroinflammation(2024) 21:163

metadata from CellProfiler followed by a cleaning process matching the field level dataset cleaning. Cells withan area or synaptosome area of greater than the meanplus 3 SD were omitted. In total, at least 12 20x images
per sample were analyzed.

Page 17 of 19

Competing interests
R.H.P. has received fees for service as a scientific advisor to Belle Artificial
Intelligence, Burrage Capital, Circular Genomics, Genomind, Swan Artificial
Intelligence Studios, and Vault Health. A.G.E. serves as a consultant for Mirvie,Inc. and receives research funding from Merck Pharmaceuticals outside of thiswork. The other authors have no disclosures to report.
Received: 11 March 2024 / Accepted: 18 June 2024

Statistics

Group differences were assessed using Mann-Whitney U
tests, with the exception of cellular morphology, which
was analyzed at the level of single cells, and phagocytosis, analyzed at the level of individual fields, using linear
mixed effects models (via the lme4 package in R). Nominal two-tailed P values less than 0.05 were considered
statistically significant. Dark lines represent median anddotted lines interquartile range, unless otherwise specified. Statistical analyses were performed in GraphPad
Prism (version 9.3) and R (version 4.2.3).

Supplementary Information

The online version contains supplementary material available at https://doi.
org/10.1186/s12974-024-03157-w.
Supplementary Material 1
Supplementary Material 2
Acknowledgements
Not applicable.
Author contributions
L.L.S. and R.E.B. contributed equally, and as co-first authors. A.G.E. conceived
the study and, together with R.H.P., designed the experiments. Acquisition of
data: L.L.S., R.E.B., R.M.D., L.T.M., S.M.B., S.D.S., J.Z.L., S.B., J.E.H., B.A.G., R.H.P., A.G.E.
Analysis and interpretation of data: L.L.S., R.E.B., R.M.D., L.T.M., O.K., S.D.S., A.M.C.,
D.K.S., B.A.G., R.H.P., A.G.E. Drafting of the manuscript: L.L.S., R.E.B., R.M.D., L.T.M.,
A.G.E. Revising the manuscript critically for important intellectual content:
L.L.S., R.E.B., R.M.D., L.T.M., S.M.B., O.K.,J.E.H., S.D.S., A.M.C., D.K.S., J.Z.L., B.A.G.,
R.H.P., A.G.E. All authors have given final approval for submission.
Funding
NIH/NICHD: 1R01HD100022-01, 3R01HD100022-02S2, and 1U19AI16789901 to A.G.E; 1K12HD103096 to L.L.S.; NIH/NIMH: 1RF1MH132336-01 to A.G.E.
and R.H.P.; NIH: 5T32HG010464 to R.M.D.; B.A.G. was supported in part by theGeisel School of Medicine at Dartmouth’s Center for Quantitative Biology
by NIH/NIGMS: P20GM130454. J.Z.L. was supported by a grant from the
Massachusetts Consortium for Pathogen Readiness (MassCPR).
Data availability
Sequencing data will be made available for download on GEO upon
acceptance. Supporting Data Values are available as a supplemental .XLSX file.
R code supporting the conclusions of this manuscript is made available here:
https://github.com/rbatorsky/covid-placenta-edlow.

Declarations
Ethics approval and consent to participate
This study was approved by the Mass General Brigham Institutional Review
Board (Protocol #2020P003538). All participants provided written informed
consent prior to participation.
Consent for publication
Not applicable.

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