Dataset Information

Comprehensive visualization of cell-cell interactions in single-cell and spatial transcriptomics with NICHES.

ABSTRACT:

Motivation

Recent years have seen the release of several toolsets that reveal cell-cell interactions from single-cell data. However, all existing approaches leverage mean celltype gene expression values, and do not preserve the single-cell fidelity of the original data. Here, we present NICHES (Niche Interactions and Communication Heterogeneity in Extracellular Signaling), a tool to explore extracellular signaling at the truly single-cell level.

Results

NICHES allows embedding of ligand-receptor signal proxies to visualize heterogeneous signaling archetypes within cell clusters, between cell clusters and across experimental conditions. When applied to spatial transcriptomic data, NICHES can be used to reflect local cellular microenvironment. NICHES can operate with any list of ligand-receptor signaling mechanisms, is compatible with existing single-cell packages, and allows rapid, flexible analysis of cell-cell signaling at single-cell resolution.

Availability and implementation

NICHES is an open-source software implemented in R under academic free license v3.0 and it is available at http://github.com/msraredon/NICHES. Use-case vignettes are available at https://msraredon.github.io/NICHES/.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Raredon MSB

PROVIDER: S-EPMC9825783 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Publications

Comprehensive visualization of cell-cell interactions in single-cell and spatial transcriptomics with NICHES.

Raredon Micha Sam Brickman MSB Yang Junchen J Kothapalli Neeharika N Lewis Wesley W Kaminski Naftali N Niklason Laura E LE Kluger Yuval Y

Bioinformatics (Oxford, England) 20230101 1

<h4>Motivation</h4>Recent years have seen the release of several toolsets that reveal cell-cell interactions from single-cell data. However, all existing approaches leverage mean celltype gene expression values, and do not preserve the single-cell fidelity of the original data. Here, we present NICHES (Niche Interactions and Communication Heterogeneity in Extracellular Signaling), a tool to explore extracellular signaling at the truly single-cell level.<h4>Results</h4>NICHES allows embedding of ...[more]

PMID: 36458905

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Project description:BackgroundFunctional placental niches are presumed to spatially separate maternal-fetal antigens and restrict the vertical transmission of pathogens. We hypothesized a high-resolution map of placental transcription could provide direct evidence for niche microenvironments with unique functions and transcription profiles.MethodsWe utilized Visium Spatial Transcriptomics paired with H&E staining to generate 17,927 spatial transcriptomes. By integrating these spatial transcriptomes with 273,944 placental single-cell and single-nuclei transcriptomes, we generated an atlas composed of at least 22 subpopulations in the maternal decidua, fetal chorionic villi, and chorioamniotic membranes.FindingsComparisons of placentae from uninfected healthy controls (n = 4) with COVID-19 asymptomatic (n = 4) and symptomatic (n = 5) infected participants demonstrated that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection in syncytiotrophoblasts occurred in both the presence and the absence of maternal clinical disease. With spatial transcriptomics, we found that the limit of detection for SARS-CoV-2 was 1/7,000 cells, and placental niches without detectable viral transcripts were unperturbed. In contrast, niches with high SARS-CoV-2 transcript levels were associated with significant upregulation in pro-inflammatory cytokines and interferon-stimulated genes, altered metallopeptidase signaling (TIMP1), with coordinated shifts in macrophage polarization, histiocytic intervillositis, and perivillous fibrin deposition. Fetal sex differences in gene expression responses to SARS-CoV-2 were limited, with confirmed mapping limited to the maternal decidua in males.ConclusionsHigh-resolution placental transcriptomics with spatial resolution revealed dynamic responses to SARS-CoV-2 in coordinate microenvironments in the absence and presence of clinically evident disease.FundingThis work was supported by the NIH (R01HD091731 and T32-HD098069), NSF (2208903), the Burroughs Welcome Fund and the March of Dimes Preterm Birth Research Initiatives, and a Career Development Award from the American Society of Gene and Cell Therapy.

Dataset Information

Comprehensive visualization of cell-cell interactions in single-cell and spatial transcriptomics with NICHES.

Motivation

Results

Availability and implementation

Supplementary information

Publications

Comprehensive visualization of cell-cell interactions in single-cell and spatial transcriptomics with NICHES.

Similar Datasets

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