High-content imaging and network modeling maps drug-induced regulation of cardiac fibroblast phenotype

Anders R. Nelson, Steven L. Christiansen, Jeffrey J. Saucerman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Cardiac fibroblast activation is necessary for wound healing following myocardial infarction. To better understand how candidate fibrosis therapeutics affect fibroblast signaling, we treated human cardiac fibroblasts with combinations of drugs and pathologically relevant cytokines. Using high-content microscopy, we measured 137 image features at the single cell level. Using dimensionality reduction and clustering on these features, we identified fibroblast phenotypic responses that deviate from the classical axis of fibroblast quiescence and activation. We then employed a regression-coupled network modeling approach to predict regulators of cell features that were affected by candidate drugs.

Original languageEnglish (US)
Title of host publicationIFAC-PapersOnLine
EditorsMaria Klapa, Daniel P. Howsmon, Ioannis P. Androulakis
PublisherElsevier B.V.
Pages25-26
Number of pages2
Edition23
ISBN (Electronic)9781713867890
DOIs
StatePublished - Sep 1 2022
Event9th IFAC Conference on Foundations of Systems Biology in Engineering, FOSBE 2022 - Cambridge, United States
Duration: Aug 28 2022Aug 31 2022

Publication series

NameIFAC-PapersOnLine
Number23
Volume55
ISSN (Electronic)2405-8963

Conference

Conference9th IFAC Conference on Foundations of Systems Biology in Engineering, FOSBE 2022
Country/TerritoryUnited States
CityCambridge
Period8/28/228/31/22

Keywords

  • Modelling of complex biological systems
  • Network inference and modeling (signaling, regulation, metabolic)

ASJC Scopus subject areas

  • Control and Systems Engineering

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