Deduction of signaling mechanisms from cellular responses to multiple cues

Soutick Saha, Hye ran Moon, Bumsoo Han, Andrew Mugler

Research output: Contribution to journalArticlepeer-review

Abstract

Cell signaling networks are complex and often incompletely characterized, making it difficult to obtain a comprehensive picture of the mechanisms they encode. Mathematical modeling of these networks provides important clues, but the models themselves are often complex, and it is not always clear how to extract falsifiable predictions. Here we take an inverse approach, using experimental data at the cell level to deduce the minimal signaling network. We focus on cells’ response to multiple cues, specifically on the surprising case in which the response is antagonistic: the response to multiple cues is weaker than the response to the individual cues. We systematically build candidate signaling networks one node at a time, using the ubiquitous ingredients of (i) up- or down-regulation, (ii) molecular conversion, or (iii) reversible binding. In each case, our method reveals a minimal, interpretable signaling mechanism that explains the antagonistic response. Our work provides a systematic way to deduce molecular mechanisms from cell-level data.

Original languageEnglish (US)
Article number48
Journalnpj Systems Biology and Applications
Volume8
Issue number1
DOIs
StatePublished - Dec 2022
Externally publishedYes

ASJC Scopus subject areas

  • Modeling and Simulation
  • General Biochemistry, Genetics and Molecular Biology
  • Drug Discovery
  • Computer Science Applications
  • Applied Mathematics

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