Note to users. If you're seeing this message, it means that your browser cannot find this page's style/presentation instructions -- or possibly that you are using a browser that does not support current Web standards. Find out more about why this message is appearing, and what you can do to make your experience of our site the best it can be.

Site Tools

  • AAAS
  • Subscribe
  • Feedback

Site Search

Search Advanced

Originally published in Science Express on 8 May 2008
Science 6 June 2008:
Vol. 320. no. 5881, pp. 1313 - 1317
DOI: 10.1126/science.1154456

Research Articles

Predictive Behavior Within Microbial Genetic Networks

Ilias Tagkopoulos,1,2* Yir-Chung Liu,2,3* Saeed Tavazoie2,3{dagger}

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.

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.

{dagger} To whom correspondence should be addressed. E-mail: tavazoie{at}genomics.princeton.edu

Read the Full Text



THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES:
Molecular circuits for associative learning in single-celled organisms.
C. T Fernando, A. M.L Liekens, L. E.H Bingle, C. Beck, T. Lenser, D. J Stekel, and J. E Rowe (2009)
J R Soc Interface 6, 463-469
   Abstract »    Full Text »    PDF »
Decomposition of complex microbial behaviors into resource-based stress responses.
R. P. Carlson (2009)
Bioinformatics 25, 90-97
   Abstract »    Full Text »    PDF »



To Advertise     Find Products


Science. ISSN 0036-8075 (print), 1095-9203 (online)