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Deduction of signaling mechanisms from cellular responses to multiple cues.
Saha, Soutick; Moon, Hye-Ran; Han, Bumsoo; Mugler, Andrew.
Afiliação
  • Saha S; Department of Physics and Astronomy, Purdue University, West Lafayette, IN, 47907, USA.
  • Moon HR; School of Mechanical Engineering, Purdue University, West Lafayette, IN, 47907, USA.
  • Han B; School of Mechanical Engineering, Purdue University, West Lafayette, IN, 47907, USA.
  • Mugler A; Purdue Center for Cancer Research, Purdue University, West Lafayette, IN, 47907, USA.
NPJ Syst Biol Appl ; 8(1): 48, 2022 11 30.
Article em En | MEDLINE | ID: mdl-36450797
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Transdução de Sinais / Sinais (Psicologia) Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Transdução de Sinais / Sinais (Psicologia) Idioma: En Ano de publicação: 2022 Tipo de documento: Article