Related Articles Inferring microenvironmental regulation of gene expression from single cell RNA sequencing data using scMLnet with an application to COVID 19 Brief Bioinform 2020 Dec 21 Authors Cheng J Zhang J Wu Z Sun X Abstract 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 or TNF 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 PMID 33341869 PubMed as supplied by publisher