Literature DB >> 21712033

Comparative genome-scale metabolic modeling of actinomycetes: the topology of essential core metabolism.

Mohammad Tauqeer Alam1, Marnix H Medema, Eriko Takano, Rainer Breitling.   

Abstract

Actinomycetes are highly important bacteria. On one hand, some of them cause severe human and plant diseases, on the other hand, many species are known for their ability to produce antibiotics. Here we report the results of a comparative analysis of genome-scale metabolic models of 37 species of actinomycetes. Based on in silico knockouts we generated topological and genomic maps for each organism. Combining the collection of genome-wide models, we constructed a global enzyme association network to identify both a conserved "core network" and an "essential core network" of the entire group. As has been reported for low-degree metabolites in several organisms, low-degree enzymes (in linear pathways) turn out to be generally more essential than high-degree enzymes (in metabolic hubs).
Copyright © 2011 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

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Year:  2011        PMID: 21712033     DOI: 10.1016/j.febslet.2011.06.014

Source DB:  PubMed          Journal:  FEBS Lett        ISSN: 0014-5793            Impact factor:   4.124


  15 in total

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Review 2.  Metabolic network modeling of microbial communities.

Authors:  Matthew B Biggs; Gregory L Medlock; Glynis L Kolling; Jason A Papin
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2015-06-24

3.  MultiMetEval: comparative and multi-objective analysis of genome-scale metabolic models.

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Journal:  Nat Microbiol       Date:  2016-02-01       Impact factor: 17.745

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Journal:  Metabolites       Date:  2021-05-11

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Journal:  PLoS Comput Biol       Date:  2014-07-17       Impact factor: 4.475

10.  redGEM: Systematic reduction and analysis of genome-scale metabolic reconstructions for development of consistent core metabolic models.

Authors:  Meric Ataman; Daniel F Hernandez Gardiol; Georgios Fengos; Vassily Hatzimanikatis
Journal:  PLoS Comput Biol       Date:  2017-07-20       Impact factor: 4.475

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