Inferring microenvironmental regulation of gene expression from single-cell RNA sequencing data using scMLnet with an application to COVID-19
Open accessAbstract
Inferring how gene expression in a cell is influenced by cellular microenvironment is of great importance yet challenging. In this study, we present a single-cell RNA-sequencing data based multilayer network method (scMLnet) that models not only functional intercellular communications but also intracellular gene regulatory networks (https://github.com/SunXQlab/scMLnet). scMLnet was applied to a scRNA-seq dataset of COVID-19 patients to decipher the microenvironmental regulation of expression of SARS-CoV-2 receptor ACE2 that has been reported to be correlated with inflammatory cytokines and COVID-19 severity. The predicted elevation of ACE2 by extracellular cytokines EGF, IFN-γ or TNF-α were experimentally validated in human lung cells and the related signaling pathway were verified to be significantly activated during SARS-COV-2 infection. Our study provided a new approach to uncover inter-/intra-cellular signaling mechanisms of gene expression and revealed microenvironmental regulators of ACE2 expression, which may facilitate designing anti-cytokine therapies or targeted therapies for controlling COVID-19 infection. In addition, we summarized and compared different methods of scRNA-seq based inter-/intra-cellular signaling network inference for facilitating new methodology development and applications.
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- Authors
- Cheng, J., Zhang, J., Wu, Z., & Sun, X.
- Affiliations
- Sun Yat-sen University (CN)
- Sun Yat-sen University Cancer Center (CN)
- Corresponding author
- Sun, Xiaoqiang
- Venue
- Briefings in Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-12-21
- Volume
- 22
- Issue
- 2
- Pages
- 988-1005
- ISSN
- 1467-5463 (ISSN-L)
- 1477-4054
- PMC
- PMC7799217
- OpenAlex
- W3114457750
- Cited by
- 125
- References
- 5
- Citations by year
- 2026: 12 · 2025: 20 · 2024: 27 · 2023: 19 · 2022: 35 · 2021: 12
- FWCI
- 5.35
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Briefings in Bioinformatics (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, cc-by)
- Funders
- National Natural Science Foundation of China (11871070)
- Guangdong Basic and Applied Basic Research Foundation (2020B1515020047)
- Central Universities (20ykzd20)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- gene regulatory networks, intercellular communication, intracellular signaling, cell microenvironment, gene expression regulation, COVID-19 pandemic, ACE2 expression, SARS-CoV-2, inflammatory cytokines, epidermal growth factor, interferon-gamma, TNF-α, lung cells, anti-cytokine therapy
- MeSH terms
- Angiotensin-Converting Enzyme 2, COVID-19, Gene Expression Regulation, Humans, Cytokines, Sequence Analysis, RNA, Single-Cell Analysis, Datasets as Topic
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