Integration of Multiple Metabolic Signals Determines Cell Fate Prior to Commitment

Orlando Argüello-Miranda, Yanjie Liu, N. Ezgi Wood, Piya Kositangool, Andreas Doncic

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

Cell-fate decisions are central to the survival and development of both uni- and multicellular organisms. It remains unclear when and to what degree cells can decide on future fates prior to commitment. This uncertainty stems from experimental and theoretical limitations in measuring and integrating multiple signals at the single-cell level during a decision process. Here, we combine six-color live-cell imaging with the Bayesian method of statistical evidence to study the meiosis/quiescence decision in budding yeast. Integration of multiple upstream metabolic signals predicts individual cell fates with high probability well before commitment. Cells “decide” their fates before birth, well before the activation of pathways characteristic of downstream cell fates. This decision, which remains stable through several cell cycles, occurs when multiple metabolic parameters simultaneously cross cell-fate-specific thresholds. Taken together, our results show that cells can decide their future fates long before commitment mechanisms are activated. We developed a novel framework that combines long-term six-color imaging of the meiosis/quiescence cell-fate decision in budding yeast with a mathematical method for rigorously converting information from multiple metabolic biomarkers into cell-fate probabilities. We show that cell fate can be determined well before the commitment occurs.

Original languageEnglish (US)
Pages (from-to)733-744.e11
JournalMolecular cell
Volume71
Issue number5
DOIs
StatePublished - Sep 6 2018

Keywords

  • Bayesian analysis
  • cell size
  • cellular decision-making
  • deterministic
  • meiosis
  • quantitative imaging
  • quiescence
  • sporulation
  • statistical evidence
  • stochastic

ASJC Scopus subject areas

  • Molecular Biology
  • Cell Biology

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