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Single-cell RNA sequencing analysis of SARS-CoV-2 entry receptors in human organoids.

ABSTRACT: Coronavirus disease-2019 (COVID-19) is a global pandemic and caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has resulted in millions of deaths worldwide. Reports denote SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2), transmembrane serine protease 2 (TMPRSS2) as its primary entry point into the host cell. However, understanding the biology behind this viral replication, disease mechanism and drug discovery efforts are limited due to the lack of a suitable experimental model. Here, we used single-cell RNA sequencing data of human organoids to analyze expressions of ACE2 and TMPRSS2, in addition to an array of RNA receptors to examine their role in SARS-CoV-2 pathogenesis. ACE2 is abundant in all organoids, except the prostate and brain, and TMPRSS2 is omnipresent. Innate immune pathways are upregulated in ACE2(+) cells of all organoids, except the lungs. Besides this, the expression of low-density lipoprotein receptor is highly enriched in ACE2(+) cells in intestinal, lung, and retinal organoids, with the highest expression in lung organoids. Collectively, this study demonstrates that the organoids can be used as an experimental platform to explore this novel virus disease mechanism and for drug development.

SUBMITTER: Mahalingam R

PROVIDER: S-EPMC7537521 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Single-cell RNA sequencing analysis of SARS-CoV-2 entry receptors in human organoids.

Mahalingam Rajasekaran R Dharmalingam Prakash P Santhanam Abirami A Kotla Sivareddy S Davuluri Gangarao G Karmouty-Quintana Harry H Ashrith Guha G Thandavarayan Rajarajan A RA

Journal of cellular physiology 20200917 4

Coronavirus disease-2019 (COVID-19) is a global pandemic and caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has resulted in millions of deaths worldwide. Reports denote SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2), transmembrane serine protease 2 (TMPRSS2) as its primary entry point into the host cell. However, understanding the biology behind this viral replication, disease mechanism and drug discovery efforts are limited due to the lack of a suitable ex ...[more]

PMID: 32944935

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Project description:Single cell RNA sequencing (scRNAseq) studies have provided critical insight into the pathogenesis of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2), the causative agent of COronaVIrus Disease 2019 (COVID-19). scRNAseq workflows are generally designed for the detection and quantification of eukaryotic host mRNAs and not viral RNAs. The performance of different scRNAseq methods to study SARS-CoV-2 RNAs has not been thoroughly evaluated. Here, we compare different scRNAseq methods for their ability to quantify and detect SARS-CoV-2 RNAs with a focus on subgenomic mRNAs (sgmRNAs), which are produced only during active viral replication and not present in viral particles. We present a data processing strategy, single cell CoronaVirus sequencing (scCoVseq), which quantifies reads unambiguously assigned to sgmRNAs or genomic RNA (gRNA). Compared to standard 10X Genomics Chromium Next GEM Single Cell 3' (10X 3') and Chromium Next GEM Single Cell V(D)J (10X 5') sequencing, we find that 10X 5' with an extended R1 sequencing strategy maximizes the unambiguous detection of sgmRNAs by increasing the number of reads spanning leader-sgmRNA junction sites. Differential gene expression testing and KEGG enrichment analysis of infected cells compared with bystander or mock cells showed an enrichment for COVID19-associated genes, supporting the ability of our method to accurately identify infected cells. Our method allows for quantification of coronavirus sgmRNA expression at single-cell resolution, and thereby supports high resolution studies of the dynamics of coronavirus RNA synthesis.ImportanceSingle cell RNA sequencing (scRNAseq) has emerged as a valuable tool to study host-viral interactions particularly in the context of COronaVIrus Disease-2019 (COVID-19). scRNAseq has been developed and optimized for analyzing eukaryotic mRNAs, and the ability of scRNAseq to measure RNAs produced by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has not been fully characterized. Here we compare the performance of different scRNAseq methods to detect and quantify SARS-CoV-2 RNAs and develop an analysis workflow to specifically quantify unambiguous reads derived from SARS-CoV-2 genomic RNA and subgenomic mRNAs. Our work demonstrates the strengths and limitations of scRNAseq to measure SARS-CoV-2 RNA and identifies experimental and analytical approaches that allow for SARS-CoV-2 RNA detection and quantification. These developments will allow for studies of coronavirus RNA biogenesis at single-cell resolution to improve our understanding of viral pathogenesis.

Project description:Single-cell RNA sequencing (scRNA-Seq) studies have provided critical insight into the pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19). scRNA-Seq library preparation methods and data processing workflows are generally designed for the detection and quantification of eukaryotic host mRNAs and not viral RNAs. Here, we compare different scRNA-Seq library preparation methods for their ability to quantify and detect SARS-CoV-2 RNAs with a focus on subgenomic mRNAs (sgmRNAs). We show that compared to 10X Genomics Chromium Next GEM Single Cell 3' (10X 3') libraries or 10X Genomics Chromium Next GEM Single Cell V(D)J (10X 5') libraries sequenced with standard read configurations, 10X 5' libraries sequenced with an extended length read 1 (R1) that covers both cell barcode and transcript sequence (termed "10X 5' with extended R1") increase the number of unambiguous reads spanning leader-sgmRNA junction sites. We further present a data processing workflow, single-cell coronavirus sequencing (scCoVseq), which quantifies reads unambiguously assigned to viral sgmRNAs or viral genomic RNA (gRNA). We find that combining 10X 5' with extended R1 library preparation/sequencing and scCoVseq data processing maximizes the number of viral UMIs per cell quantified by scRNA-Seq. Corresponding sgmRNA expression levels are highly correlated with expression in matched bulk RNA-Seq data sets quantified with established tools for SARS-CoV-2 analysis. Using this scRNA-Seq approach, we find that SARS-CoV-2 gene expression is highly correlated across individual infected cells, which suggests that the proportion of viral sgmRNAs remains generally consistent throughout infection. Taken together, these results and corresponding data processing workflow enable robust quantification of coronavirus sgmRNA expression at single-cell resolution, thereby supporting high-resolution studies of viral RNA processes in individual cells. IMPORTANCE Single-cell RNA sequencing (scRNA-Seq) has emerged as a valuable tool to study host-virus interactions, especially for coronavirus disease 2019 (COVID-19). Here we compare the performance of different scRNA-Seq library preparation methods and sequencing strategies to detect SARS-CoV-2 RNAs and develop a data processing workflow to quantify unambiguous sequence reads derived from SARS-CoV-2 genomic RNA and subgenomic mRNAs. After establishing a workflow that maximizes the detection of SARS-CoV-2 subgenomic mRNAs, we explore patterns of SARS-CoV-2 gene expression across cells with variable levels of total viral RNA, assess host gene expression differences between infected and bystander cells, and identify non-canonical and lowly abundant SARS-CoV-2 RNAs. The sequencing and data processing strategies developed here can enhance studies of coronavirus RNA biology at single-cell resolution and thereby contribute to our understanding of viral pathogenesis.

Dataset Information

Single-cell RNA sequencing analysis of SARS-CoV-2 entry receptors in human organoids.

Publications

Single-cell RNA sequencing analysis of SARS-CoV-2 entry receptors in human organoids.

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