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PMID: 18787117 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Large-scale reconstruction and phylogenetic analysis of metabolic environments.

Borenstein E, Kupiec M, Feldman MW, Ruppin E

Abstract

The topology of metabolic networks may provide important insights not only into the metabolic capacity of species, but also into the habitats in which they evolved. Here we introduce the concept of a metabolic network's "seed set"--the set of compounds that, based on the network topology, are exogenously acquired--and provide a methodological framework to computationally infer the seed set of a given network. Such seed sets form ecological "interfaces" between metabolic networks and their surroundings, approximating the effective biochemical environment of each species. Analyzing the metabolic networks of 478 species and identifying the seed set of each species, we present a comprehensive large-scale reconstruction of such predicted metabolic environments. The seed sets' composition significantly correlates with several basic properties characterizing the species' environments and agrees with biological observations concerning major adaptations. Species whose environments are highly predictable (e.g., obligate parasites) tend to have smaller seed sets than species living in variable environments. Phylogenetic analysis of the seed sets reveals the complex dynamics governing gain and loss of seeds across the phylogenetic tree and the process of transition between seed and non-seed compounds. Our findings suggest that the seed state is transient and that seeds tend either to be dropped completely from the network or to become non-seed compounds relatively fast. The seed sets also permit a successful reconstruction of a phylogenetic tree of life. The "reverse ecology" approach presented lays the foundations for studying the evolutionary interplay between organisms and their habitats on a large scale.

MeSH Terms
Animals Archaea/classification,metabolism Bacteria/classification,metabolism Environment Eukaryota/classification,metabolism Fungi/classification,metabolism Metabolism Phylogeny Plants/classification,metabolism
Authors & Affiliations
4 authors, click to expand affiliations / ORCID
Borenstein Elhanan
Department of Biological Sciences, Stanford University, Stanford, CA 94305, USA. [email protected]
Kupiec Martin
Feldman Marcus W
Ruppin Eytan
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Article Info
Journal
Proceedings of the National Academy of Sciences of the United States of America
Abbr.
Proc Natl Acad Sci U S A
ISSN
1091-6490
Published
2008-09-23
Epub
2008-00-11
Pages
14482-7
Language
English
Region
United States
NLM ID
7505876
PMCID
PMC2567166
Subset
IM
Grants
NIGMS NIH HHS · R01 GM028016 · United States
NIGMS NIH HHS · GM28016 · United States
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