Evolution · 2014 · 262 citations · 54 references
Life SciencesEvolutionary BiologyMicrobiologyMetabolismMicrobial EvolutionMicrobial MetabolismBacterial MetabolismBacterial SurvivalEvolution Of Metabolic PathwaysGenome ReductionMicrobial Metabolic EngineeringAnabolic Pathway EvolutionBacterial Genome EvolutionEscherichia ColiFree-living MicrobesGenomic Adaptations Of SymbiontsLoss Of Metabolic PathwaysMetabolic Pathway LossNatural Selection In Microbes
Bacteria that have adapted to nutrient-rich, stable environments are typically characterized by reduced genomes. The loss of biosynthetic genes frequently renders these lineages auxotroph, hinging their survival on an environmental uptake of certain metabolites. The evolutionary forces that drive this genome degradation, however, remain elusive. Our analysis of 949 metabolic networks revealed auxotrophies are likely highly prevalent in both symbiotic and free-living bacteria. To unravel whether selective advantages can account for the rampant loss of anabolic genes, we systematically determined the fitness consequences that result from deleting conditionally essential biosynthetic genes from the genomes of Escherichia coli and Acinetobacter baylyi in the presence of the focal nutrient. Pairwise competition experiments with each of 20 mutants auxotrophic for different amino acids, vitamins, and nucleobases against the prototrophic wild type unveiled a pronounced, concentration-dependent growth advantage of around 13% for virtually all mutants tested. Individually deleting different genes from the same biosynthesis pathway entailed gene-specific fitness consequences and loss of the same biosynthetic genes from the genomes of E. coli and A. baylyi differentially affected the fitness of the resulting auxotrophic mutants. Taken together, our findings suggest adaptive benefits could drive the loss of conditionally essential biosynthetic genes.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
KEGG: Kyoto Encyclopedia of Genes and Genomes
Hiroyuki Ogata, Susumu Goto, Kazushige Sato et al. · Nucleic Acids Research · 1999 · 32.4K citations · Full text