Abstract

BackgroundEnterobacteriaceae diversified from an ancestral lineage ~300-500 million years ago (mya) into a wide variety of free-living and host-associated lifestyles. Nutrient availability varies across niches, and evolution of metabolic networks likely played a key role in adaptation.ResultsHere we use a paleo systems biology approach to reconstruct and model metabolic networks of ancestral nodes of the enterobacteria phylogeny to investigate metabolism of ancient microorganisms and evolution of the networks. Specifically, we identified orthologous genes across genomes of 72 free-living enterobacteria (16 genera), and constructed core metabolic networks capturing conserved components for ancestral lineages leading to E. coli/Shigella (~10 mya), E. coli/Shigella/Salmonella (~100 mya), and all enterobacteria (~300-500 mya). Using these models we analyzed the capacity for carbon, nitrogen, phosphorous, sulfur, and iron utilization in aerobic and anaerobic conditions, identified conserved and differentiating catabolic phenotypes, and validated predictions by comparison to experimental data from extant organisms.ConclusionsThis is a novel approach using quantitative ancestral models to study metabolic network evolution and may be useful for identification of new targets to control infectious diseases caused by enterobacteria.

Highlights

  • Enterobacteriaceae diversified from an ancestral lineage ~300-500 million years ago into a wide variety of free-living and host-associated lifestyles

  • This is a novel approach using quantitative ancestral models to study metabolic network evolution and may be useful for identification of new targets to control infectious diseases caused by enterobacteria

  • K-12 MG1655 genome-scale metabolic models (GEMs) [4] based on the retained metabolic capability determined through a comparative genomic analysis of 72 enterobacterial genomes

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Summary

Introduction

Enterobacteriaceae diversified from an ancestral lineage ~300-500 million years ago (mya) into a wide variety of free-living and host-associated lifestyles. Nutrient availability varies across niches, and evolution of metabolic networks likely played a key role in adaptation. Enterobacteria have been extensively studied in the laboratory due to their importance to human health and as standard laboratory strains for molecular biology. The family includes 44 distinct genera and 176 named species [1], and there are over 150 complete or nearly complete genomes currently available for enterobacteria. Full list of author information is available at the end of the article has revealed some of the genomic variations linked to host/niche specialization. The metabolic gene content of these genomes is complex, with each strain predicted to contain over 800 genes encoding metabolic enzymes and transporters. One method to investigate the complexity of genome-scale metabolic networks is through the construction of computational models

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