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Single-cell transcriptomics reveals immune response of intestinal cell types to viral infection.

ABSTRACT: Human intestinal epithelial cells form a primary barrier protecting us from pathogens, yet only limited knowledge is available about individual contribution of each cell type to mounting an immune response against infection. Here, we developed a framework combining single-cell RNA-Seq and highly multiplex RNA FISH and applied it to human intestinal organoids infected with human astrovirus, a model human enteric virus. We found that interferon controls the infection and that astrovirus infects all major cell types and lineages and induces expression of the cell proliferation marker MKI67. Intriguingly, each intestinal epithelial cell lineage exhibits a unique basal expression of interferon-stimulated genes and, upon astrovirus infection, undergoes an antiviral transcriptional reprogramming by upregulating distinct sets of interferon-stimulated genes. These findings suggest that in the human intestinal epithelium, each cell lineage plays a unique role in resolving virus infection. Our framework is applicable to other organoids and viruses, opening new avenues to unravel roles of individual cell types in viral pathogenesis.

SUBMITTER: Triana S

PROVIDER: S-EPMC8311733 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Single-cell transcriptomics reveals immune response of intestinal cell types to viral infection.

Triana Sergio S Stanifer Megan L ML Metz-Zumaran Camila C Shahraz Mohammed M Mukenhirn Markus M Kee Carmon C Serger Clara C Koschny Ronald R Ordoñez-Rueda Diana D Paulsen Malte M Benes Vladimir V Boulant Steeve S Alexandrov Theodore T

Molecular systems biology 20210701 7

Human intestinal epithelial cells form a primary barrier protecting us from pathogens, yet only limited knowledge is available about individual contribution of each cell type to mounting an immune response against infection. Here, we developed a framework combining single-cell RNA-Seq and highly multiplex RNA FISH and applied it to human intestinal organoids infected with human astrovirus, a model human enteric virus. We found that interferon controls the infection and that astrovirus infects al ...[more]

PMID: 34309190

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Project description:BK virus (BKV) is a human polyomavirus that is generally harmless but can cause devastating disease in immunosuppressed individuals. BKV infection of renal cells is a common problem for kidney transplant patients undergoing immunosuppressive therapy. In cultured primary human renal proximal tubule epithelial (RPTE) cells, BKV undergoes a productive infection. The BKV-encoded large T antigen (LT) induces cell cycle entry, resulting in the upregulation of numerous genes associated with cell proliferation. Consistently, microarray and transcriptome sequencing (RNA-seq) experiments performed on bulk infected cell populations identified several proliferation-related pathways that are upregulated by BKV. These studies revealed few genes that are downregulated. In this study, we analyzed viral and cellular transcripts in single mock- or BKV-infected cells. We found that the levels of viral mRNAs vary widely among infected cells, resulting in different levels of LT and viral capsid protein expression. Cells expressing the highest levels of viral transcripts account for approximately 20% of the culture and have a gene expression pattern that is distinct from that of cells expressing lower levels of viral mRNAs. Surprisingly, cells expressing low levels of viral mRNA do not progress with time to high expression, suggesting that the two cellular responses are determined prior to or shortly following infection. Finally, comparison of cellular gene expression patterns of cells expressing high levels of viral mRNA with those of mock-infected cells or cells expressing low levels of viral mRNA revealed previously unidentified pathways that are downregulated by BKV. Among these are pathways associated with drug metabolism and detoxification, tumor necrosis factor (TNF) signaling, energy metabolism, and translation.IMPORTANCE The outcome of viral infection is determined by the ability of the virus to redirect cellular systems toward progeny production countered by the ability of the cell to block these viral actions. Thus, an infected culture consists of thousands of cells, each fighting its own individual battle. Bulk measurements, such as PCR or RNA-seq, measure the average of these individual responses to infection. Single-cell transcriptomics provides a window to the one-on-one battle between BKV and each cell. Our studies reveal that only a minority of infected cells are overwhelmed by the virus and produce large amounts of BKV mRNAs and proteins, while the infection appears to be restricted in the remaining cells. Correlation of viral transcript levels with cellular gene expression patterns reveals pathways manipulated by BKV that may play a role in limiting infection.

Project description:Single-cell analysis has the potential to provide us with a host of new knowledge about biological systems, but it comes with the challenge of correctly interpreting the biological information. While emerging techniques have made it possible to measure inter-cellular variability at the transcriptome level, no consensus yet exists on the most appropriate method of data analysis of such single cell data. Methods for analysis of transcriptional data at the population level are well established but are not well suited to single cell analysis due to their dependence on population averages. In order to address this question, we have systematically tested combinations of methods for primary data analysis on single cell transcription data generated from two types of primary immune cells, neutrophils and T lymphocytes. Cells were obtained from healthy individuals, and single cell transcript expression data was obtained by a combination of single cell sorting and nanoscale quantitative real time PCR (qRT-PCR) for markers of cell type, intracellular signaling, and immune functionality. Gene expression analysis was focused on hierarchical clustering to determine the existence of cellular subgroups within the populations. Nine combinations of criteria for data exclusion and normalization were tested and evaluated. Bimodality in gene expression indicated the presence of cellular subgroups which were also revealed by data clustering. We observed evidence for two clearly defined cellular subtypes in the neutrophil populations and at least two in the T lymphocyte populations. When normalizing the data by different methods, we observed varying outcomes with corresponding interpretations of the biological characteristics of the cell populations. Normalization of the data by linear standardization taking into account technical effects such as plate effects, resulted in interpretations that most closely matched biological expectations. Single cell transcription profiling provides evidence of cellular subclasses in neutrophils and leukocytes that may be independent of traditional classifications based on cell surface markers. The choice of primary data analysis method had a substantial effect on the interpretation of the data. Adjustment for technical effects is critical to prevent misinterpretation of single cell transcript data.

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Single-cell transcriptomics reveals immune response of intestinal cell types to viral infection.

Publications

Single-cell transcriptomics reveals immune response of intestinal cell types to viral infection.

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