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Abstract:
The homeostatic framework has dominated our understanding ofcellular physiology. We question whether homeostasis alone adequatelyexplains microbial responses to environmental stimuli, and explorethe capacity of intracellular networks for predictive behaviorin a fashion similar to metazoan nervous systems. We show thatin silico biochemical networks, evolving randomly under preciselydefined complex habitats, capture the dynamical, multidimensionalstructure of diverse environments by forming internal representationsthat allow prediction of environmental change. We provide evidencefor such anticipatory behavior by revealing striking correlationsof Escherichia coli transcriptional responses to temperatureand oxygen perturbations—precisely mirroring the covariationof these parameters upon transitions between the outside worldand the mammalian gastrointestinal tract. We further show thatthese internal correlations reflect a true associative learningparadigm, because they show rapid decoupling upon exposure tonovel environments.
1 Department of Electrical Engineering, Princeton University, Princeton, NJ 08544, USA. 2 Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA. 3 Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA.
* These authors contributed equally to this work.
To whom correspondence should be addressed. E-mail: tavazoie{at}genomics.princeton.edu
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