חיפוש מתקדם
PLoS Computational Biology
Freilich, S., Blavatnik School of Computer Sciences, Faculty of Life Sciences, Ramat Aviv, Israel, Sackler School of Medicine, Faculty of Life Sciences, Ramat Aviv, Israel
Kreimer, A., School of Mathematical Science, Faculty of Life Sciences, Ramat Aviv, Israel, Department of Biomedical Informatics, Columbia University, New York, NY, United States
Borenstein, E., Department of Biological Sciences, Stanford University, Stanford, CA, United States, Santa Fe Institute, Santa Fe, NM, United States
Gophna, U., Department of Molecular Microbiology and Biotechnology, Faculty of Life Sciences, Ramat Aviv, Israel
Sharan, R., Blavatnik School of Computer Sciences, Faculty of Life Sciences, Ramat Aviv, Israel
Ruppin, E., Blavatnik School of Computer Sciences, Faculty of Life Sciences, Ramat Aviv, Israel, Sackler School of Medicine, Faculty of Life Sciences, Ramat Aviv, Israel
The evolutionary origins of genetic robustness are still under debate: it may arise as a consequence of requirements imposed by varying environmental conditions, due to intrinsic factors such as metabolic requirements, or directly due to an adaptive selection in favor of genes that allow a species to endure genetic perturbations. Stratifying the individual effects of each origin requires one to study the pertaining evolutionary forces across many species under diverse conditions. Here we conduct the first large-scale computational study charting the level of robustness of metabolic networks of hundreds of bacterial species across many simulated growth environments. We provide evidence that variations among species in their level of robustness reflect ecological adaptations. We decouple metabolic robustness into two components and quantify the extents of each: the first, environmental-dependent, is responsible for at least 20% of the non-essential reactions and its extent is associated with the species' lifestyle (specialized/generalist); the second, environmental- independent, is associated (correlation = ∼0.6) with the intrinsic metabolic capacities of a species-higher robustness is observed in fast growers or in organisms with an extensive production of secondary metabolites. Finally, we identify reactions that are uniquely susceptible to perturbations in human pathogens, potentially serving as novel drug-targets. © 2010 Freilich et al.
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הספר "אוצר וולקני"
אודות
תנאי שימוש
Decoupling environment-dependent and independent genetic robustness across bacterial species
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Freilich, S., Blavatnik School of Computer Sciences, Faculty of Life Sciences, Ramat Aviv, Israel, Sackler School of Medicine, Faculty of Life Sciences, Ramat Aviv, Israel
Kreimer, A., School of Mathematical Science, Faculty of Life Sciences, Ramat Aviv, Israel, Department of Biomedical Informatics, Columbia University, New York, NY, United States
Borenstein, E., Department of Biological Sciences, Stanford University, Stanford, CA, United States, Santa Fe Institute, Santa Fe, NM, United States
Gophna, U., Department of Molecular Microbiology and Biotechnology, Faculty of Life Sciences, Ramat Aviv, Israel
Sharan, R., Blavatnik School of Computer Sciences, Faculty of Life Sciences, Ramat Aviv, Israel
Ruppin, E., Blavatnik School of Computer Sciences, Faculty of Life Sciences, Ramat Aviv, Israel, Sackler School of Medicine, Faculty of Life Sciences, Ramat Aviv, Israel
Decoupling environment-dependent and independent genetic robustness across bacterial species
The evolutionary origins of genetic robustness are still under debate: it may arise as a consequence of requirements imposed by varying environmental conditions, due to intrinsic factors such as metabolic requirements, or directly due to an adaptive selection in favor of genes that allow a species to endure genetic perturbations. Stratifying the individual effects of each origin requires one to study the pertaining evolutionary forces across many species under diverse conditions. Here we conduct the first large-scale computational study charting the level of robustness of metabolic networks of hundreds of bacterial species across many simulated growth environments. We provide evidence that variations among species in their level of robustness reflect ecological adaptations. We decouple metabolic robustness into two components and quantify the extents of each: the first, environmental-dependent, is responsible for at least 20% of the non-essential reactions and its extent is associated with the species' lifestyle (specialized/generalist); the second, environmental- independent, is associated (correlation = ∼0.6) with the intrinsic metabolic capacities of a species-higher robustness is observed in fast growers or in organisms with an extensive production of secondary metabolites. Finally, we identify reactions that are uniquely susceptible to perturbations in human pathogens, potentially serving as novel drug-targets. © 2010 Freilich et al.
Scientific Publication
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