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Decoupling Environment-Dependent and Independent Genetic Robustness across Bacterial Species

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  • Shiri Freilich
  • Anat Kreimer
  • Elhanan Borenstein
  • Uri Gophna
  • Roded Sharan
  • Eytan Ruppin

Abstract

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.Author Summary: When a species is grown under optimal conditions the single-knockout of most of its genes is not likely to affect its viability. The resilience of biological systems to mutations is termed genetic robustness and its extent across different species has not yet been systematically described. Since the deletion of a gene can have varying consequences depending on the environmental conditions, the extent of species' genetic robustness reflects both the range of conditions (or environments) in which it can survive as well as the availability of alternative cellular routes (compensating for a gene's loss of function). Here, we developed a computational model for estimating the essentiality of metabolic reactions across natural-like environments and applied it to chart species' level of genetic robustness, providing the first systematic description of genetic robustness across species. Studying robustness across a wide collection of natural-like environments enables one to stratify, for each species individually, the extent of environmental-dependant and independent robustness and hence advances our understanding of its evolutionary origins. Our main finding is that the level of environmental dependent robustness is associated with the lifestyle of a species (i.e., specialists versus generalist), whereas the level of environmental-independent robustness is associated with its metabolic production capacities.

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  • Shiri Freilich & Anat Kreimer & Elhanan Borenstein & Uri Gophna & Roded Sharan & Eytan Ruppin, 2010. "Decoupling Environment-Dependent and Independent Genetic Robustness across Bacterial Species," PLOS Computational Biology, Public Library of Science, vol. 6(2), pages 1-10, February.
  • Handle: RePEc:plo:pcbi00:1000690
    DOI: 10.1371/journal.pcbi.1000690
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    References listed on IDEAS

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    1. Zhenglong Gu & Lars M. Steinmetz & Xun Gu & Curt Scharfe & Ronald W. Davis & Wen-Hsiung Li, 2003. "Role of duplicate genes in genetic robustness against null mutations," Nature, Nature, vol. 421(6918), pages 63-66, January.
    2. Jörg Stelling & Steffen Klamt & Katja Bettenbrock & Stefan Schuster & Ernst Dieter Gilles, 2002. "Metabolic network structure determines key aspects of functionality and regulation," Nature, Nature, vol. 420(6912), pages 190-193, November.
    3. Balázs Papp & Csaba Pál & Laurence D. Hurst, 2004. "Metabolic network analysis of the causes and evolution of enzyme dispensability in yeast," Nature, Nature, vol. 429(6992), pages 661-664, June.
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    1. Paulien Hogeweg, 2011. "The Roots of Bioinformatics in Theoretical Biology," PLOS Computational Biology, Public Library of Science, vol. 7(3), pages 1-5, March.

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