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| Status |
Public on Jul 05, 2023 |
| Title |
SARS-CoV-2 Niches in Human Placenta Revealed by Spatial Transcriptomics |
| Organisms |
Homo sapiens; Severe acute respiratory syndrome coronavirus 2 |
| Experiment type |
Expression profiling by high throughput sequencing
Other
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| Summary |
Diverse placental functions are compartmentalized to separate maternal-fetal antigens and restrict vertical transmission of pathogens. We hypothesized a high-resolution map, with single-cell and spatial resolution, would identify previously undetectable microbe immune microenvironments. To test this hypothesis, we utilized Visium Spatial Transcriptomics paired with H&E staining to generate 17,927 spatial transcriptomes and integrated these data with 273,944 published placenta single-cell and single-nuclei transcriptomes to generate a term placenta atlas of the maternal decidua, fetal chorionic villi, and chorioamniotic membranes. Comparisons of healthy control placentae (n=4), SARS-CoV-2 asymptomatic (n=4; no COVID-19 symptoms), and symptomatic (n=5; pneumonia, respiratory failure) placentae identified distinct thresholds of SARS-CoV-2 detection including (i) no detectable virus, (ii) sparse virus (limit of detection determined to be 1/7,000 cells), and (iii) highly positive SARS-CoV-2 in syncytiotrophoblasts, rigorously cross-validated by RT-qPCR, RNAscope, and immunohistochemistry. High levels of SARS-CoV-2 in placentae were associated with histiocytic intervillositis and perivillous fibrin deposition. Spatial transcriptomics revealed that this led to a significant shift from anti-inflammatory M2 macrophage populations toward intermediate pro-inflammatory M1 macrophages. In conclusion, we identified immune microenvironments representing host-pathogen battlegrounds where SARS-CoV-2 detection in the placenta was not dependent on maternal symptoms. Additional studies utilizing this approach are warranted, especially in the placenta.
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| Overall design |
Spatial transcriptomics. Human placentae from distinct regions including the chorionic villi, decidua, and chorioamniotic membranes, or cross-sections from the parenchyma, were fresh-frozen in optimal cutting temperature solution (FF-OCT). Blocks were cryosectioned and H&E stained directly on 10X Genomics Visium Gene Expression slides (v2) and imaged using a Nikon Eclipse SE Ni microscope using a Nikon DS-Ri1 camera, Nikon Plan Apo objective at 10x magnification (0.45 aperture, 0.91 μm/pixel resolution). Tissues were permeabilized and RNA was subject to spatial transcriptomics library preparation including poly(dT) reverse transcription. Libraries were sequenced on the Illumina NovaSeq S4 platform with 2% PhiX. Single-cell and spatial transcriptomics analyses. Reads were demultiplexed and aligned to a custom human (GRCh38) and SARS-CoV-2 reference genome (NC_045512.2) using SpaceRanger (v1.3.0) and custom bash scripts. Downstream analyses were done using the package Seurat (v4.0.3) in rStudio (v4.1.1). Counts matrices were filtered iteratively to exclude low-quality transcriptomes and clusters defined by quality control metrics (e.g. mitochondrial or hemoglobin gene expression). Spatial transcriptomes were normalized and scaled using a negative binomial model (SCTransform) and the top 3,000 most variable transcripts were used for to principal component analysis dimension reduction. The first 30 PCA dimensions were used for K-nearest neighbors’ analysis, clustered using a Louvain algorithm with the default resolution parameter (0.6), and visualized by unique manifold approximation and projection (UMAP) in two dimensions. Significantly upregulated transcripts were manually examined and compared to the term placenta atlas in addition to using EnrichR(58), PlacentaCellEnrich(110), and the Human Protein Atlas(111) to annotate clusters. Pseudotime trajectory analysis was done using Monocle3 (v1.0.0) utilizing gene sets and starting points denoted in the text. Spatial and scRNA-seq datasets were integrated using reciprocal PCA of 3,000 reference transcripts prior to clustering.
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| Web link |
https://pubmed.ncbi.nlm.nih.gov/37423216/
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| Contributor(s) |
Aagaard K, Barrozo E, Jochum M |
| Citation(s) |
37423216 |
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| Submission date |
Jan 16, 2023 |
| Last update date |
Oct 04, 2023 |
| Contact name |
Michael Jochum |
| E-mail(s) |
michael.jochum@bcm.edu, michaeljochumjr@gmail.com
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| Phone |
5127698372
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| Organization name |
Baylor College of Medicine
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| Department |
Obstetrics and Gynecology
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| Lab |
Aagaard
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| Street address |
1 Baylor Plaza
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| City |
Houston |
| State/province |
TX |
| ZIP/Postal code |
77401 |
| Country |
USA |
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| Platforms (1) |
| GPL29320 |
Illumina NovaSeq 6000 (Homo sapiens; Severe acute respiratory syndrome coronavirus 2) |
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| Samples (16)
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| Relations |
| BioProject |
PRJNA924338 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE222987_RAW.tar |
369.2 Mb |
(http)(custom) |
TAR (of H5, JPG, PNG) |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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