Literature DB >> 27683361

Phenotypic innovation through recombination in genome-scale metabolic networks.

Sayed-Rzgar Hosseini1, Olivier C Martin2, Andreas Wagner3.   

Abstract

Recombination is an important source of metabolic innovation, especially in prokaryotes, which have evolved the ability to survive on many different sources of chemical elements and energy. Metabolic systems have a well-understood genotype-phenotype relationship, which permits a quantitative and biochemically principled understanding of how recombination creates novel phenotypes. Here, we investigate the power of recombination to create genome-scale metabolic reaction networks that enable an organism to survive in new chemical environments. To this end, we use flux balance analysis, an experimentally validated computational method that can predict metabolic phenotypes from metabolic genotypes. We show that recombination is much more likely to create novel metabolic abilities than random changes in chemical reactions of a metabolic network. We also find that phenotypic innovation is more likely when recombination occurs between parents that are genetically closely related, phenotypically highly diverse, and viable on few rather than many carbon sources. Survival on a new carbon source preferentially involves reactions that are superessential, that is, essential in many metabolic networks. We validate our observations with data from 61 reconstructed prokaryotic metabolic networks. Our systematic and quantitative analysis of metabolic systems helps understand how recombination creates innovation.
© 2016 The Author(s).

Entities:  

Keywords:  genome-scale metabolic networks; metabolic genotype; metabolic innovation; metabolic phenotype; recombination; superessential reactions

Year:  2016        PMID: 27683361      PMCID: PMC5046906          DOI: 10.1098/rspb.2016.1536

Source DB:  PubMed          Journal:  Proc Biol Sci        ISSN: 0962-8452            Impact factor:   5.349


  62 in total

1.  LIGAND: chemical database of enzyme reactions.

Authors:  S Goto; T Nishioka; M Kanehisa
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

Review 2.  Evolution of a metabolic pathway for degradation of a toxic xenobiotic: the patchwork approach.

Authors:  S D Copley
Journal:  Trends Biochem Sci       Date:  2000-06       Impact factor: 13.807

Review 3.  Lateral gene transfer and the nature of bacterial innovation.

Authors:  H Ochman; J G Lawrence; E A Groisman
Journal:  Nature       Date:  2000-05-18       Impact factor: 49.962

4.  Evolution of a cytokine using DNA family shuffling.

Authors:  C C Chang; T T Chen; B W Cox; G N Dawes; W P Stemmer; J Punnonen; P A Patten
Journal:  Nat Biotechnol       Date:  1999-08       Impact factor: 54.908

5.  Domain recombination: a workhorse for evolutionary innovation.

Authors:  Gordana Apic; Robert B Russell
Journal:  Sci Signal       Date:  2010-09-14       Impact factor: 8.192

6.  Recombination shapes the natural population structure of the hyperthermophilic archaeon Sulfolobus islandicus.

Authors:  Rachel J Whitaker; Dennis W Grogan; John W Taylor
Journal:  Mol Biol Evol       Date:  2005-08-10       Impact factor: 16.240

7.  In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data.

Authors:  J S Edwards; R U Ibarra; B O Palsson
Journal:  Nat Biotechnol       Date:  2001-02       Impact factor: 54.908

8.  Genotype networks, innovation, and robustness in sulfur metabolism.

Authors:  João F Matias Rodrigues; Andreas Wagner
Journal:  BMC Syst Biol       Date:  2011-03-07

9.  From genomics to chemical genomics: new developments in KEGG.

Authors:  Minoru Kanehisa; Susumu Goto; Masahiro Hattori; Kiyoko F Aoki-Kinoshita; Masumi Itoh; Shuichi Kawashima; Toshiaki Katayama; Michihiro Araki; Mika Hirakawa
Journal:  Nucleic Acids Res       Date:  2006-01-01       Impact factor: 16.971

10.  RefSeq microbial genomes database: new representation and annotation strategy.

Authors:  Tatiana Tatusova; Stacy Ciufo; Boris Fedorov; Kathleen O'Neill; Igor Tolstoy
Journal:  Nucleic Acids Res       Date:  2013-12-06       Impact factor: 16.971

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  6 in total

1.  Constraint and Contingency Pervade the Emergence of Novel Phenotypes in Complex Metabolic Systems.

Authors:  Sayed-Rzgar Hosseini; Andreas Wagner
Journal:  Biophys J       Date:  2017-08-08       Impact factor: 4.033

2.  Erroneous energy-generating cycles in published genome scale metabolic networks: Identification and removal.

Authors:  Claus Jonathan Fritzemeier; Daniel Hartleb; Balázs Szappanos; Balázs Papp; Martin J Lercher
Journal:  PLoS Comput Biol       Date:  2017-04-18       Impact factor: 4.475

3.  Exosomes in mammals with greater habitat variability contain more proteins and RNAs.

Authors:  Kazuhiro Takemoto; Miku Imoto
Journal:  R Soc Open Sci       Date:  2017-04-26       Impact factor: 2.963

4.  Protein cost minimization promotes the emergence of coenzyme redundancy.

Authors:  Joshua E Goldford; Ashish B George; Avi I Flamholz; Daniel Segrè
Journal:  Proc Natl Acad Sci U S A       Date:  2022-03-28       Impact factor: 12.779

5.  Nutrition or nature: using elementary flux modes to disentangle the complex forces shaping prokaryote pan-genomes.

Authors:  Daniel R Garza; F A Bastiaan von Meijenfeldt; Bram van Dijk; Annemarie Boleij; Martijn A Huynen; Bas E Dutilh
Journal:  BMC Ecol Evol       Date:  2022-08-16

6.  Transcriptome Profiling Based on Larvae at Different Time Points After Hatching Provides a Core Set of Gene Resource for Understanding the Metabolic Mechanisms of the Brood-Care Behavior in Octopus ocellatus.

Authors:  Xiaokai Bao; Xiumei Liu; Benshu Yu; Yan Li; Mingxian Cui; Weijun Wang; Yanwei Feng; Xiaohui Xu; Guohua Sun; Bin Li; Zan Li; Jianmin Yang
Journal:  Front Physiol       Date:  2022-01-07       Impact factor: 4.566

  6 in total

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