Relative Abundance of SARS-CoV-2 Entry Genes in the Enterocytes of the Lower Gastrointestinal Tract

There is increasing evidence of gastrointestinal (GI) infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We surveyed the co-expression of SARS-CoV-2 entry genes ACE2 and TMPRSS2 throughout the GI tract to assess potential sites of infection. Publicly available and in-house single-cell RNA-sequencing datasets from the GI tract were queried. Enterocytes from the small intestine and colonocytes showed the highest proportions of cells co-expressing ACE2 and TMPRSS2. Therefore, the lower GI tract represents the most likely site of SARS-CoV-2 entry leading to GI infection.

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Relative Abundance of SARS-CoV-2 Entry Genes in the Enterocytes of the Lower Gastrointestinal Tract

10.1101/2020.04.08.033001 ◽

2020 ◽

Cited By ~ 2

Author(s):

Jaewon J. Lee ◽

Scott Kopetz ◽

Eduardo Vilar ◽

John Paul Shen ◽

Ken Chen ◽

...

Keyword(s):

Small Intestine ◽

Gastrointestinal Tract ◽

Mammalian Cells ◽

World Health ◽

Lower Gastrointestinal Tract ◽

Gi Tract ◽

Single Cell Rna Sequencing ◽

The World ◽

Health Organization ◽

Different Parts

COVID-19, the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly spread throughout the world and was declared a pandemic by the World Health Organization, thus leading to a rapid surge in the efforts to understand the mechanisms of transmission, methods of prevention, and potential therapies. While COVID-19 frequently manifests as a respiratory infection,1 there is evidence for infection of the gastrointestinal (GI) tract1–4 with documented viral RNA shedding in the stool of infected patients.2,4 In this study, we aimed to investigate the expression of ACE2 and TMPRSS2, which are required for SARS-CoV-2 entry into mammalian cells,5 from single-cell RNA sequencing (scRNA-seq) datasets of five different parts of the GI tract: esophagus, stomach, pancreas, small intestine, and colon/rectum.

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Single-cell RNA sequencing analysis reveals alginate oligosaccharides preventing chemotherapy-induced mucositis

Mucosal Immunology ◽

10.1038/s41385-019-0248-z ◽

2020 ◽

Vol 13 (3) ◽

pp. 437-448 ◽

Cited By ~ 5

Author(s):

Yong Zhao ◽

Yanni Feng ◽

Ming Liu ◽

Liang Chen ◽

Qingshi Meng ◽

...

Keyword(s):

Small Intestine ◽

Gastrointestinal Tract ◽

Single Cell ◽

Rna Sequencing ◽

Functional Enrichment ◽

Sequencing Analysis ◽

Intestinal Function ◽

Alginate Oligosaccharides ◽

Single Cell Rna Sequencing ◽

Small Intestinal

AbstractWorldwide the incidence of cancer has been continuing increasing. Mucositis of the gastrointestinal tract is a common side effect in patients under chemotherapy. Anticancer drug busulfan, used for treating chronic myeloid leukemia especially in pediatric patients, causes mucositis of the gastrointestinal tract. Alginate oligosaccharides (AOS) are natural products with attractive pharmaceutical potentials. We aimed to investigate, at the single-cell level, AOS preventing small intestine mucositis induced by busulfan. We found that busulfan disturbed the endoplasmic reticulum and mitochondria of cells in the small intestine, damaged cell membranes especially cell junctions, and disrupted microvilli; all of which were rescued by AOS. Single-cell RNA sequencing analysis and functional enrichment analysis showed that AOS could recover small intestinal function. Deep analysis found that AOS improved the expression of transcriptional factors which explained AOS regulating gene expression to improve small intestine function. Further investigation in IPEC-J2 cells found that AOS acts its function through mannose receptor signaling pathway. Moreover, the improved blood metabolome confirmed small intestinal function was recovered by AOS. As a natural product with many advantages, AOS could be developed to assist in the recovery of intestinal functions in patients undergoing anticancer chemotherapy or other treatments.

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Differential dropout analysis captures biological variation in single-cell RNA sequencing data

10.1101/2021.02.01.429187 ◽

2021 ◽

Author(s):

Gerard A. Bouland ◽

Ahmed Mahfouz ◽

Marcel J.T. Reinders

Keyword(s):

Single Cell ◽

Differential Expression ◽

Rna Sequencing ◽

Relative Abundance ◽

Differential Expression Analysis ◽

Biological Variation ◽

Sequencing Data ◽

Single Cell Rna Sequencing ◽

Technical Artifacts ◽

Zero Counts

AbstractSingle-cell RNA sequencing data is characterized by a large number of zero counts, yet there is growing evidence that these zeros reflect biological rather than technical artifacts. We propose differential dropout analysis (DDA), as an alternative to differential expression analysis (DEA), to identify the effects of biological variation in single-cell RNA sequencing data. Using 16 publicly available datasets, we show that dropout patterns are biological in nature and can assess the relative abundance of transcripts more robustly than counts.

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