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Open Access Highly Accessed Research article

Inferring ancient metabolism using ancestral core metabolic models of enterobacteria

David J Baumler1*, Bing Ma14, Jennifer L Reed2 and Nicole T Perna13

Author Affiliations

1 Genome Center of Wisconsin, University of Wisconsin-Madison, Madison, Wisconsin, USA

2 Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, USA

3 Department of Genetics, University of Wisconsin-Madison, Madison, USA

4 Current affiliation: Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA

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BMC Systems Biology 2013, 7:46  doi:10.1186/1752-0509-7-46

Published: 11 June 2013



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.


Here 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.


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.

Constraint-based modeling; Enterobacteria; Metabolic network reconstruction; Ancient metabolism; Paleo systems biology; Ancestral core