Skip to main navigation Skip to search Skip to main content

Stochasticity in cellular metabolism and growth: Approaches and consequences

  • FOM Institute for Atomic and Molecular Physics (AMOLF)
  • Delft University of Technology
  • PSL Research University

Research output: Contribution to journalReview articlepeer-review

16 Citations (Scopus)

Abstract

Advances in our ability to zoom in on single cells have revealed striking heterogeneity within isogenic populations. Attention has so far focussed predominantly on underlying stochastic variability in regulatory pathways and downstream differentiation events. In contrast, the role of stochasticity in metabolic processes and networks has long remained unaddressed. Here we review recent studies that have begun to overcome key technical challenges in addressing this issue. First findings have already demonstrated that metabolic networks are stochastic in nature, and highlight the plethora of cellular processes that are critically affected by it.

Original languageEnglish
Pages (from-to)131-136
Number of pages6
JournalCurrent Opinion in Systems Biology
Volume8
DOIs
Publication statusPublished - 1 Apr 2018
Externally publishedYes

Keywords

  • Cellular growth
  • Enzyme expression
  • Metabolism
  • Single cells
  • Stochasticity
  • Time-lapse microscopy

Fingerprint

Dive into the research topics of 'Stochasticity in cellular metabolism and growth: Approaches and consequences'. Together they form a unique fingerprint.

Cite this