Stochasticity in cellular metabolism and growth

Approaches and consequences

Review (2018)

Authors

M. Wehrens AMOLF
F. Büke BN/Greg Bokinsky Lab - AS , AMOLF
S.J. Tans BN/Sander Tans Lab - AS , AMOLF
Research Group
BN/Greg Bokinsky Lab (AS) (TU Delft)
Metabolism Stochasticity Cellular growth Enzyme expression Single cells Time-lapse microscopy
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Published Date

2018

Language

English

Reuse Rights

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Faculty

Applied Sciences

Department

BN/Bionanoscience

Research Group

BN/Greg Bokinsky Lab

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.