Submitted on December 20, 2007
Accepted on March 25, 2008
Predictive Behavior Within Microbial Genetic Networks
Ilias Tagkopoulos 1
, Yir-Chung Liu 2, Saeed Tavazoie 2*
1 Department of Electrical Engineering, Princeton University, Princeton, NJ 08544, USA.; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.
2 Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.; Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA.
* To whom correspondence should be addressed.
Saeed Tavazoie , E-mail: tavazoie{at}genomics.princeton.edu
These authors contributed equally to this work.
We question whether homeostasis alone adequately explains microbial responses to environmental stimuli, and explore the capacity of intra-cellular 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, multi-dimensional structure of diverse environments by forming internal models 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 co-variation 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, since they show rapid de-coupling upon exposure to novel environments.
