%0 Journal Article %1 Altafini2015Metabolic %A Altafini, Claudio %A Facchetti, Giuseppe %D 2015 %J PLoS computational biology %K biomass flux-analysis optimal %N 9 %R 10.1371/journal.pcbi.1004434 %T Metabolic Adaptation Processes That Converge to Optimal Biomass Flux Distributions. %U http://dx.doi.org/10.1371/journal.pcbi.1004434 %V 11 %X In simple organisms like E.coli, the metabolic response to an external perturbation passes through a transient phase in which the activation of a number of latent pathways can guarantee survival at the expenses of growth. Growth is gradually recovered as the organism adapts to the new condition. This adaptation can be modeled as a process of repeated metabolic adjustments obtained through the resilencings of the non-essential metabolic reactions, using growth rate as selection probability for the phenotypes obtained. The resulting metabolic adaptation process tends naturally to steer the metabolic fluxes towards high growth phenotypes. Quite remarkably, when applied to the central carbon metabolism of E.coli, it follows that nearly all flux distributions converge to the flux vector representing optimal growth, i.e., the solution of the biomass optimization problem turns out to be the dominant attractor of the metabolic adaptation process.

@article{Altafini2015Metabolic, abstract = {In simple organisms like E.coli, the metabolic response to an external perturbation passes through a transient phase in which the activation of a number of latent pathways can guarantee survival at the expenses of growth. Growth is gradually recovered as the organism adapts to the new condition. This adaptation can be modeled as a process of repeated metabolic adjustments obtained through the resilencings of the non-essential metabolic reactions, using growth rate as selection probability for the phenotypes obtained. The resulting metabolic adaptation process tends naturally to steer the metabolic fluxes towards high growth phenotypes. Quite remarkably, when applied to the central carbon metabolism of E.coli, it follows that nearly all flux distributions converge to the flux vector representing optimal growth, i.e., the solution of the biomass optimization problem turns out to be the dominant attractor of the metabolic adaptation process.}, added-at = {2018-12-02T16:09:07.000+0100}, author = {Altafini, Claudio and Facchetti, Giuseppe}, biburl = {https://www.bibsonomy.org/bibtex/25f3e416b2f0f580db5a0fd69aca118d3/karthikraman}, citeulike-article-id = {14093953}, citeulike-linkout-0 = {http://dx.doi.org/10.1371/journal.pcbi.1004434}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/26340476}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=26340476}, doi = {10.1371/journal.pcbi.1004434}, interhash = {fbcc92b55688d1fe9d8d2bec8e8f41af}, intrahash = {5f3e416b2f0f580db5a0fd69aca118d3}, issn = {1553-7358}, journal = {PLoS computational biology}, keywords = {biomass flux-analysis optimal}, month = sep, number = 9, pmid = {26340476}, posted-at = {2016-07-12 17:50:34}, priority = {2}, timestamp = {2018-12-02T16:09:07.000+0100}, title = {Metabolic Adaptation Processes That Converge to Optimal Biomass Flux Distributions.}, url = {http://dx.doi.org/10.1371/journal.pcbi.1004434}, volume = 11, year = 2015 }