title: The degree of redundancy in metabolic genes is linked to mode of metabolism.
abstract: An understanding of the factors favoring the maintenance of duplicate genes in microbial genomes is essential for developing models of microbial evolution. A genome-scale flux-balance analysis of the metabolic network of Saccharomyces cerevisiae has suggested that gene duplications primarily provide increased enzyme dosage to enhance metabolic flux because the incidence of gene duplications in essential genes is no higher than that in nonessential genes. Here, we used genome-scale metabolic models to analyze the extent of genetic and biochemical redundancy in prokaryotes that are either specialists, with one major mode of energy generation, or generalists, which have multiple metabolic strategies for conservation of energy. Surprisingly, the results suggest that generalists, such as Escherichia coli and Bacillus subtilis, are similar to the eukaryotic generalist, S. cerevisiae, in having a low percentage (<10%) of essential genes and few duplications of these essential genes, whereas metabolic specialists, such as Geobacter sulfurreducens and Methanosarcina barkeri, have a high percentage (>30%) of essential genes and a high degree of genetic redundancy in these genes compared to nonessential genes. Furthermore, the specialist organisms appear to rely more on gene duplications rather than alternative-but-equivalent metabolic pathways to provide resilience to gene loss. Generalists rely more on alternative pathways. Thus, the concept that the role of gene duplications is to boost enzymatic flux rather than provide metabolic resilience may not be universal. Rather, the degree of gene duplication in microorganisms may be linked to mode of metabolism and environmental niche.
authors.affiliation: Department of Chemical Engineering and Applied Chemistry, Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada. krishna.mahadevan@utoronto.ca
authors.forename: R
authors.initials: R
authors.lastname: Mahadevan
authors.forename: D R
authors.initials: DR
authors.lastname: Lovley
mesh_terms: D018407:Bacterial Physiological Phenomena; D001426:Bacterial Proteins / Q000378:metabolism*; D003198:Computer Simulation; D015964:Gene Expression Regulation, Bacterial / Q000502:physiology*; D020131:Genes, Duplicate / Q000502:physiology*; D008954:Models, Biological; D015398:Signal Transduction / Q000502:physiology*
chemical_list: D001426:Bacterial Proteins