Quantitative single-cell interactomes in normal and virus-infected mouse lungs

Margo P. Cain, Belinda J. Hernandez, Jichao Chen

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Mammalian organs consist of diverse, intermixed cell types that signal to each other via ligand-receptor interactions – an interactome – to ensure development, homeostasis and injury-repair. Dissecting such intercellular interactions is facilitated by rapidly growing single-cell RNA sequencing (scRNA-seq) data; however, existing computational methods are often not readily adaptable by bench scientists without advanced programming skills. Here, we describe a quantitative intuitive algorithm, coupled with an optimized experimental protocol, to construct and compare interactomes in control and Sendai virus-infected mouse lungs. A minimum of 90 cells per cell type compensates for the known gene dropout issue in scRNA-seq and achieves comparable sensitivity to bulk RNA sequencing. Cell lineage normalization after cell sorting allows cost-efficient representation of cell types of interest. A numeric representation of ligand-receptor interactions identifies, as outliers, known and potentially new interactions as well as changes upon viral infection. Our experimental and computational approaches can be generalized to other organs and human samples.

Original languageEnglish (US)
Article numberdmm044404
JournalDMM Disease Models and Mechanisms
Volume13
Issue number6
DOIs
StatePublished - Jun 2020

Keywords

  • Bioinformatics
  • Ligand-receptor interaction
  • Lung viral injury
  • ScRNA-seq

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Medicine (miscellaneous)
  • Immunology and Microbiology (miscellaneous)
  • General Biochemistry, Genetics and Molecular Biology

MD Anderson CCSG core facilities

  • Flow Cytometry and Cellular Imaging Facility
  • Research Animal Support Facility

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