Literature DB >> 29308439

Robustness, Accuracy, and Cell State Heterogeneity in Biological Systems.

Roy Wollman.   

Abstract

The robustness of biological systems is often depicted as a key system-level emergent property that allows uniform phenotypes in fluctuating environments. Yet, analysis of single-cell signaling responses identified multiple examples of cellular responses with high degrees of heterogeneity. Here we discuss the implications of the observed lack of response accuracy in the context of new observations coming from single-cell approaches. Single-cell approaches provide a new way to measure the abundance of thousands of molecular species in a single-cell. Repeatedly, analysis of cell distributions identifies clusters within these distributions where cells can be grouped into specific cell states. If cells in a population occupy distinct cell states, the observed variable response could in fact be accurate for each cell conditioned on its own internal state. In this view, the observed lack of accuracy, i.e. response heterogeneity, could in fact be beneficial and a potentially regulated feature of cell state variability. Therefore, to truly determine whether the observed response heterogeneity is a desired property or a physical limitation, future analysis of signaling heterogeneity must take into account the internal states of cells in the population.

Entities:  

Year:  2017        PMID: 29308439      PMCID: PMC5752152          DOI: 10.1016/j.coisb.2017.11.009

Source DB:  PubMed          Journal:  Curr Opin Syst Biol        ISSN: 2452-3100


  46 in total

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6.  Fundamental trade-offs between information flow in single cells and cellular populations.

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Journal:  Proc Natl Acad Sci U S A       Date:  2017-05-12       Impact factor: 11.205

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Journal:  Curr Opin Biotechnol       Date:  2014-05-19       Impact factor: 9.740

Review 8.  Design principles of regulatory networks: searching for the molecular algorithms of the cell.

Authors:  Wendell A Lim; Connie M Lee; Chao Tang
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4.  Temporal perturbation of ERK dynamics reveals network architecture of FGF2/MAPK signaling.

Authors:  Yannick Blum; Jan Mikelson; Maciej Dobrzyński; Hyunryul Ryu; Marc-Antoine Jacques; Noo Li Jeon; Mustafa Khammash; Olivier Pertz
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5.  Inferring the structures of signaling motifs from paired dynamic traces of single cells.

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Journal:  PLoS Comput Biol       Date:  2021-02-04       Impact factor: 4.475

  5 in total

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