Predictive Behavior Within Microbial Genetic Networks

The homeostatic framework has dominated our understanding of cellular physiology. We question whether homeostasis alone adequately explains microbial responses to environmental stimuli, and explore the capacity of intracellular networks for predictive behavior in a fashion similar to metazoan nervou...

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Bibliographic Details
Published in:Science (American Association for the Advancement of Science) 2008-06, Vol.320 (5881), p.1313-1317
Main Authors: Tagkopoulos, Ilias, Liu, Yir-Chung, Tavazoie, Saeed
Format: Article
Language:English
Subjects:
Adaptation, Physiological
Aerobiosis
Anaerobiosis
Bacteriology
Biochemistry
Biological and medical sciences
Cellular biology
Computer Simulation
Cytochromes
Directed Molecular Evolution
E coli
Ecological competition
Ecosystem
Escherichia coli
Escherichia coli - genetics
Escherichia coli - growth & development
Escherichia coli - physiology
Evolution
Fundamental and applied biological sciences. Psychology
Gene Regulatory Networks
Genetics
Homeostasis
Kinetics
Metabolic Networks and Pathways
Metazoa
Microbiology
Models, Biological
Models, Statistical
Mutation
Natural resources
Oligonucleotide Array Sequence Analysis
Oxygen
Oxygen - analysis
Phenotypes
Renewable energy
RNA
Temperature
Transcription, Genetic
Transition temperature
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Summary:The homeostatic framework has dominated our understanding of cellular physiology. We question whether homeostasis alone adequately explains microbial responses to environmental stimuli, and explore the capacity of intracellular networks for predictive behavior in a fashion similar to metazoan nervous systems. We show that in silico biochemical networks, evolving randomly under precisely defined complex habitats, capture the dynamical, multidimensional structure of diverse environments by forming internal representations that allow prediction of environmental change. We provide evidence for such anticipatory behavior by revealing striking correlations of Escherichia coli transcriptional responses to temperature and oxygen perturbations--precisely mirroring the covariation of these parameters upon transitions between the outside world and the mammalian gastrointestinal tract. We further show that these internal correlations reflect a true associative learning paradigm, because they show rapid decoupling upon exposure to novel environments.
ISSN:0036-8075
1095-9203
DOI:10.1126/science.1154456