Multiomics Evaluation of Gastrointestinal and Other Clinical Characteristics of COVID-19

Since December 2019, coronavirus disease 2019 (COVID-19) outbreak caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has produced a worldwide panic. Beyond the principal human-to-human transmission method by droplet and contact, there is still limited knowledge about possible alternate transmission methods to guide clinical care. Recent clinical studies have observed digestive symptoms in patients with COVID-19,1 possibly because of the enrichment and infection of SARS-CoV-2 in the gastrointestinal tract, mediated by virus receptor of angiotensin converting enzyme 2 (ACE2),2 which suggests the potential for a fecal-oral route of SARS-CoV-2 transmission.3,4 However, there is still a large gap in the biological knowledge of COVID-19. In this study, via a bulk-to-cell strategy focusing on ACE2, we performed an integrated omics analysis at the genome, transcriptome, and proteome levels in bulk tissues and single cells across species to decipher the potential routes for SARS-CoV-2 infection in depth.

[1]  Y. Bossé,et al.  Tobacco Smoking Increases the Lung Gene Expression of ACE2, the Receptor of SARS-CoV-2 , 2020, American journal of respiratory and critical care medicine.

[2]  Huiying Liang,et al.  Characteristics of pediatric SARS-CoV-2 infection and potential evidence for persistent fecal viral shedding , 2020, Nature Medicine.

[3]  G. Herrler,et al.  SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor , 2020, Cell.

[4]  Bing Han,et al.  COVID-19: Gastrointestinal Manifestations and Potential Fecal–Oral Transmission , 2020, Gastroenterology.

[5]  K. Yuen,et al.  Clinical Characteristics of Coronavirus Disease 2019 in China , 2020, The New England journal of medicine.

[6]  H. Shan,et al.  Evidence for Gastrointestinal Infection of SARS-CoV-2 , 2020, Gastroenterology.

[7]  Sumiko Mekaru,et al.  Open access epidemiological data from the COVID-19 outbreak , 2020, The Lancet Infectious Diseases.

[8]  E. Robert McDonald,et al.  Quantitative Proteomics of the Cancer Cell Line Encyclopedia , 2020, Cell.

[9]  Haojia Wu,et al.  Advantages of Single-Nucleus over Single-Cell RNA Sequencing of Adult Kidney: Rare Cell Types and Novel Cell States Revealed in Fibrosis. , 2018, Journal of the American Society of Nephrology : JASN.

[10]  Samantha A. Morris,et al.  Comparative Analysis and Refinement of Human PSC-Derived Kidney Organoid Differentiation with Single-Cell Transcriptomics. , 2018, Cell stem cell.

[11]  Haojia Wu,et al.  Single-Cell Transcriptomics of a Human Kidney Allograft Biopsy Specimen Defines a Diverse Inflammatory Response. , 2018, Journal of the American Society of Nephrology : JASN.

[12]  Jianxin Shi,et al.  SummaryAUC: a tool for evaluating the performance of polygenic risk prediction models in validation datasets with only summary level statistics , 2018, bioRxiv.

[13]  M. Kanai,et al.  Genetic analysis of quantitative traits in the Japanese population links cell types to complex human diseases , 2018, Nature Genetics.

[14]  Yarden Katz,et al.  A single-cell survey of the small intestinal epithelium , 2017, Nature.

[15]  Cheng Li,et al.  GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses , 2017, Nucleic Acids Res..

[16]  J. Potter,et al.  Tissue-specific patterns of gene expression in the epithelium and stroma of normal colon in healthy individuals in an aspirin intervention trial , 2015, Genomics data.

[17]  Piero Carninci,et al.  Complementing tissue characterization by integrating transcriptome profiling from the Human Protein Atlas and from the FANTOM5 consortium , 2015, Nucleic acids research.

[18]  Joris M. Mooij,et al.  MAGMA: Generalized Gene-Set Analysis of GWAS Data , 2015, PLoS Comput. Biol..

[19]  G. von Heijne,et al.  Tissue-based map of the human proteome , 2015, Science.

[20]  Ellen T. Gelfand,et al.  The Genotype-Tissue Expression (GTEx) project , 2013, Nature Genetics.

[21]  Adam A. Margolin,et al.  The Cancer Cell Line Encyclopedia enables predictive modeling of anticancer drug sensitivity , 2012, Nature.

[22]  T. Nikolskaya,et al.  A comprehensive functional analysis of tissue specificity of human gene expression , 2008, BMC Biology.

[23]  H. Aburatani,et al.  Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues. , 2005, Genomics.