Literature DB >> 30110764

Optimized bacteria are environmental prediction engines.

Sarah E Marzen1, James P Crutchfield2.   

Abstract

Experimentalists observe phenotypic variability even in isogenic bacteria populations. We explore the hypothesis that in fluctuating environments this variability is tuned to maximize a bacterium's expected log-growth rate, potentially aided by epigenetic (all inheritable nongenetic) markers that store information about past environments. Crucially, we assume a time delay between sensing and action, so that a past epigenetic marker is used to generate the present phenotypic variability. We show that, in a complex, memoryful environment, the maximal expected log-growth rate is linear in the instantaneous predictive information-the mutual information between a bacterium's epigenetic markers and future environmental states. Hence, under resource constraints, optimal epigenetic markers are causal states-the minimal sufficient statistics for prediction-or lossy approximations thereof. We propose new theoretical investigations into and new experiments on bacteria phenotypic bet-hedging in fluctuating complex environments.

Mesh:

Year:  2018        PMID: 30110764     DOI: 10.1103/PhysRevE.98.012408

Source DB:  PubMed          Journal:  Phys Rev E        ISSN: 2470-0045            Impact factor:   2.529


  2 in total

1.  Probing complexity: thermodynamics and computational mechanics approaches to origins studies.

Authors:  Stuart J Bartlett; Patrick Beckett
Journal:  Interface Focus       Date:  2019-10-18       Impact factor: 3.906

2.  Infinitely large, randomly wired sensors cannot predict their input unless they are close to deterministic.

Authors:  Sarah Marzen
Journal:  PLoS One       Date:  2018-08-29       Impact factor: 3.240

  2 in total

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