ArticleProceedings. Biological sciences2016
Phenotypic innovation through recombination in genome-scale metabolic networks.
Article in Proceedings. Biological sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Nutrition or nature: using elementary flux modes to disentangle the complex forces shaping prokaryote pan-genomes.BMC ecology and evolution · 2022Article
- Protein cost minimization promotes the emergence of coenzyme redundancy.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- 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 inFrontiers in physiology · 2021Article
- Constraint and Contingency Pervade the Emergence of Novel Phenotypes in Complex Metabolic Systems.Biophysical journal · 2017Article
- Erroneous energy-generating cycles in published genome scale metabolic networks: Identification and removal.PLoS computational biology · 2017Article
- Exosomes in mammals with greater habitat variability contain more proteins and RNAs.Royal Society open science · 2017Article
Corrections and comments
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Authors and funding
3 authors.
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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.
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