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    July 10

    磷酸化的信息观点--很有意思

    Editor's Summary

    9 July 2009

    Cellular information processing


    While naked DNA has a relatively static and easy to grasp information capacity — 2 bits per nucleotide—reversible chemical modification at multiple sites in even a single protein encodes a potentially large and so far untractable amount of information. Here Matthew Thomson and Jeremy Gunawardena reduce the 3 times 2n nonlinear differential equations describing dynamic phosphorylation at n sites on a given protein (n varying from less than 7 in bacteria to more than 150 in eukaryotes) to just two algebraic equations. The method allows them to estimate the information capacity of a signalling protein as a function of varying amounts of modifying enzymes (kinases and phosphatases). Algebraic geometry could extend the method to diverse and parallel enzymatic modifications such as those governing the 'histone code' of gene regulation.

    Letter: Unlimited multistability in multisite phosphorylation systems

    Matthew Thomson & Jeremy Gunawardena

    doi:10.1038/nature08102

    First paragraph | Full Text | PDF (397K) | Supplementary information

    J.J. collins: 跟memory有关的

    James J. Collins1

    A bioengineer gets schooled by Escherichia coli.

    The ability to learn from situations and to predict certain outcomes sets us apart from many living things. It prevents many of us from chasing balls into busy streets or placing bottles of ethanol near Bunsen burners. Still, it didn't stop thousands of US researchers submitting applications for the National Institutes of Health's Challenge Grants — funded by President Barack Obama's economic stimulus package — despite an expected success rate little better than one or two per cent.

    To enjoy the benefits of learning and predictive behaviour, we usually assume that you need a nervous system or at least a neuron. So it was surprising to read that Saeed Tavazoie at Princeton University, New Jersey, and his colleagues have demonstrated that bacteria can learn and exhibit anticipatory behaviour (I. Tagkopoulos et al. Science 320, 1313–1317; 2008). They show computationally and experimentally that Escherichia coli can learn temporal correlations between environmental stimuli — for example, that an increase in temperature is followed by a decrease in oxygen levels — allowing the bacteria to predict and prepare for future environmental changes.

    The researchers show that this associative learning is accomplished by rewiring of biochemical networks. Strikingly, they also show that, like many of us, E. coli quickly 'unlearn' (in fewer than 100 generations) what they had learned in a new situation.

    Now we know that bacteria can be taught such tricks, it will be interesting to see if we can use novel combinations of environmental stimuli to train microbes to efficiently convert biomass into energy sources, such as hydrogen or butanol. By providing E. coli with such an educational stimulus package, we may be able to boost the global economy.

    ========================================================

    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.