scholarly journals Single cell transcriptomics reveals a heterogeneous cellular response to BKV infection

2020 ◽  
Author(s):  
Ping An ◽  
Paul G. Cantalupo ◽  
Wenshan Zheng ◽  
Maria Teresa Sáenz-Robles ◽  
Alexis M. Duray ◽  
...  

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 cells (RPTE), 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 RNA-seq experiments performed in 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 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 mock-infected cells, or with 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, TNF-signaling, energy metabolism, and translation. IMPORTANCE The outcome of viral infection is determined by the ability of the virus to redirect cellular systems towards 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 their 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.

2020 ◽  
Author(s):  
Timothy J. Durham ◽  
Riza M. Daza ◽  
Louis Gevirtzman ◽  
Darren A. Cusanovich ◽  
William Stafford Noble ◽  
...  

AbstractRecently developed single cell technologies allow researchers to characterize cell states at ever greater resolution and scale. C. elegans is a particularly tractable system for studying development, and recent single cell RNA-seq studies characterized the gene expression patterns for nearly every cell type in the embryo and at the second larval stage (L2). Gene expression patterns are useful for learning about gene function and give insight into the biochemical state of different cell types; however, in order to understand these cell types, we must also determine how these gene expression levels are regulated. We present the first single cell ATAC-seq study in C. elegans. We collected data in L2 larvae to match the available single cell RNA-seq data set, and we identify tissue-specific chromatin accessibility patterns that align well with existing data, including the L2 single cell RNA-seq results. Using a novel implementation of the latent Dirichlet allocation algorithm, we leverage the single-cell resolution of the sci-ATAC-seq data to identify accessible loci at the level of individual cell types, providing new maps of putative cell type-specific gene regulatory sites, with promise for better understanding of cellular differentiation and gene regulation in the worm.


iScience ◽  
2021 ◽  
Vol 24 (4) ◽  
pp. 102357
Author(s):  
Brenda Morsey ◽  
Meng Niu ◽  
Shetty Ravi Dyavar ◽  
Courtney V. Fletcher ◽  
Benjamin G. Lamberty ◽  
...  

2012 ◽  
Vol 7 (5) ◽  
pp. 829-838 ◽  
Author(s):  
Veronica Sanchez-Freire ◽  
Antje D Ebert ◽  
Tomer Kalisky ◽  
Stephen R Quake ◽  
Joseph C Wu

2017 ◽  
Vol 4 (1) ◽  
pp. e000202 ◽  
Author(s):  
Zhongbo Jin ◽  
Wei Fan ◽  
Mark A Jensen ◽  
Jessica M Dorschner ◽  
George F Bonadurer ◽  
...  

2019 ◽  
Author(s):  
Alexandra Grubman ◽  
Gabriel Chew ◽  
John F. Ouyang ◽  
Guizhi Sun ◽  
Xin Yi Choo ◽  
...  

AbstractAlzheimer’s disease (AD) is a heterogeneous disease that is largely dependent on the complex cellular microenvironment in the brain. This complexity impedes our understanding of how individual cell types contribute to disease progression and outcome. To characterize the molecular and functional cell diversity in the human AD brain we utilized single nuclei RNA- seq in AD and control patient brains in order to map the landscape of cellular heterogeneity in AD. We detail gene expression changes at the level of cells and cell subclusters, highlighting specific cellular contributions to global gene expression patterns between control and Alzheimer’s patient brains. We observed distinct cellular regulation of APOE which was repressed in oligodendrocyte progenitor cells (OPCs) and astrocyte AD subclusters, and highly enriched in a microglial AD subcluster. In addition, oligodendrocyte and microglia AD subclusters show discordant expression of APOE. Integration of transcription factor regulatory modules with downstream GWAS gene targets revealed subcluster-specific control of AD cell fate transitions. For example, this analysis uncovered that astrocyte diversity in AD was under the control of transcription factor EB (TFEB), a master regulator of lysosomal function and which initiated a regulatory cascade containing multiple AD GWAS genes. These results establish functional links between specific cellular sub-populations in AD, and provide new insights into the coordinated control of AD GWAS genes and their cell-type specific contribution to disease susceptibility. Finally, we created an interactive reference web resource which will facilitate brain and AD researchers to explore the molecular architecture of subtype and AD-specific cell identity, molecular and functional diversity at the single cell level.HighlightsWe generated the first human single cell transcriptome in AD patient brainsOur study unveiled 9 clusters of cell-type specific and common gene expression patterns between control and AD brains, including clusters of genes that present properties of different cell types (i.e. astrocytes and oligodendrocytes)Our analyses also uncovered functionally specialized sub-cellular clusters: 5 microglial clusters, 8 astrocyte clusters, 6 neuronal clusters, 6 oligodendrocyte clusters, 4 OPC and 2 endothelial clusters, each enriched for specific ontological gene categoriesOur analyses found manifold AD GWAS genes specifically associated with one cell-type, and sets of AD GWAS genes co-ordinately and differentially regulated between different brain cell-types in AD sub-cellular clustersWe mapped the regulatory landscape driving transcriptional changes in AD brain, and identified transcription factor networks which we predict to control cell fate transitions between control and AD sub-cellular clustersFinally, we provide an interactive web-resource that allows the user to further visualise and interrogate our dataset.Data resource web interface:http://adsn.ddnetbio.com


2017 ◽  
Author(s):  
Nisar Wani ◽  
Khalid Raza

AbstractGene expression patterns determine the manner whereby organisms regulate various cellular processes and therefore their organ functions.These patterns do not emerge on their own, but as a result of diverse regulatory factors such as, DNA binding proteins known as transcription factors (TF), chromatin structure and various other environmental factors. TFs play a pivotal role in gene regulation by binding to different locations on the genome and influencing the expression of their target genes. Therefore, predicting target genes and their regulation becomes an important task for understanding mechanisms that control cellular processes governing both healthy and diseased cells.In this paper, we propose an integrated inference pipeline for predicting target genes and their regulatory effects for a specific TF using next-generation data analysis tools.


Gene ◽  
2021 ◽  
pp. 146090
Author(s):  
Karolina Wiśniewska ◽  
Lidia Gaffke ◽  
Karolina Krzelowska ◽  
Grzegorz Węgrzyn ◽  
Karolina Pierzynowska

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