Literature DB >> 16731630

A metabolic network in the evolutionary context: multiscale structure and modularity.

Victor Spirin1, Mikhail S Gelfand, Andrey A Mironov, Leonid A Mirny.   

Abstract

The enormous complexity of biological networks has led to the suggestion that networks are built of modules that perform particular functions and are "reused" in evolution in a manner similar to reusable domains in protein structures or modules of electronic circuits. Analysis of known biological networks has revealed several modules, many of which have transparent biological functions. However, it remains to be shown that identified structural modules constitute evolutionary building blocks, independent and easily interchangeable units. An alternative possibility is that evolutionary modules do not match structural modules. To investigate the structure of evolutionary modules and their relationship to functional ones, we integrated a metabolic network with evolutionary associations between genes inferred from comparative genomics. The resulting metabolic-genomic network places metabolic pathways into evolutionary and genomic context, thereby revealing previously unknown components and modules. We analyzed the integrated metabolic-genomic network on three levels: macro-, meso-, and microscale. The macroscale level demonstrates strong associations between neighboring enzymes and between enzymes that are distant on the network but belong to the same linear pathway. At the mesoscale level, we identified evolutionary metabolic modules and compared them with traditional metabolic pathways. Although, in some cases, there is almost exact correspondence, some pathways are split into independent modules. On the microscale level, we observed high association of enzyme subunits and weak association of isoenzymes independently catalyzing the same reaction. This study shows that evolutionary modules, rather than pathways, may be thought of as regulatory and functional units in bacterial genomes.

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Year:  2006        PMID: 16731630      PMCID: PMC1482654          DOI: 10.1073/pnas.0510258103

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  38 in total

1.  Pathway alignment: application to the comparative analysis of glycolytic enzymes.

Authors:  T Dandekar; S Schuster; B Snel; M Huynen; P Bork
Journal:  Biochem J       Date:  1999-10-01       Impact factor: 3.857

2.  Repression of Escherichia coli purB is by a transcriptional roadblock mechanism.

Authors:  B He; H Zalkin
Journal:  J Bacteriol       Date:  1992-11       Impact factor: 3.490

Review 3.  Evidence against the selfish operon theory.

Authors:  Csaba Pál; Laurence D Hurst
Journal:  Trends Genet       Date:  2004-06       Impact factor: 11.639

4.  Filling gaps in a metabolic network using expression information.

Authors:  Peter Kharchenko; Dennis Vitkup; George M Church
Journal:  Bioinformatics       Date:  2004-08-04       Impact factor: 6.937

5.  Computational approaches for the analysis of gene neighbourhoods in prokaryotic genomes.

Authors:  Igor B Rogozin; Kira S Makarova; Yuri I Wolf; Eugene V Koonin
Journal:  Brief Bioinform       Date:  2004-06       Impact factor: 11.622

Review 6.  Variation and evolution of the citric-acid cycle: a genomic perspective.

Authors:  M A Huynen; T Dandekar; P Bork
Journal:  Trends Microbiol       Date:  1999-07       Impact factor: 17.079

7.  Gene co-regulation is highly conserved in the evolution of eukaryotes and prokaryotes.

Authors:  Berend Snel; Vera van Noort; Martijn A Huynen
Journal:  Nucleic Acids Res       Date:  2004-09-07       Impact factor: 16.971

8.  A comprehensive library of DNA-binding site matrices for 55 proteins applied to the complete Escherichia coli K-12 genome.

Authors:  K Robison; A M McGuire; G M Church
Journal:  J Mol Biol       Date:  1998-11-27       Impact factor: 5.469

9.  Comparative genomics of the methionine metabolism in Gram-positive bacteria: a variety of regulatory systems.

Authors:  Dmitry A Rodionov; Alexey G Vitreschak; Andrey A Mironov; Mikhail S Gelfand
Journal:  Nucleic Acids Res       Date:  2004-06-23       Impact factor: 16.971

10.  A Bayesian method for identifying missing enzymes in predicted metabolic pathway databases.

Authors:  Michelle L Green; Peter D Karp
Journal:  BMC Bioinformatics       Date:  2004-06-09       Impact factor: 3.169

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  42 in total

Review 1.  Practical and theoretical advances in predicting the function of a protein by its phylogenetic distribution.

Authors:  Philip R Kensche; Vera van Noort; Bas E Dutilh; Martijn A Huynen
Journal:  J R Soc Interface       Date:  2008-02-06       Impact factor: 4.118

2.  Toolbox model of evolution of prokaryotic metabolic networks and their regulation.

Authors:  Sergei Maslov; Sandeep Krishna; Tin Yau Pang; Kim Sneppen
Journal:  Proc Natl Acad Sci U S A       Date:  2009-05-29       Impact factor: 11.205

Review 3.  FINDSITE: a combined evolution/structure-based approach to protein function prediction.

Authors:  Jeffrey Skolnick; Michal Brylinski
Journal:  Brief Bioinform       Date:  2009-03-26       Impact factor: 11.622

4.  The divergence and natural selection of autocatalytic primordial metabolic systems.

Authors:  Sergey A Marakushev; Ol'ga V Belonogova
Journal:  Orig Life Evol Biosph       Date:  2013-07-17       Impact factor: 1.950

5.  Phylogenetic distances are encoded in networks of interacting pathways.

Authors:  Aurélien Mazurie; Danail Bonchev; Benno Schwikowski; Gregory A Buck
Journal:  Bioinformatics       Date:  2008-09-26       Impact factor: 6.937

6.  The evolution of modularity in bacterial metabolic networks.

Authors:  Anat Kreimer; Elhanan Borenstein; Uri Gophna; Eytan Ruppin
Journal:  Proc Natl Acad Sci U S A       Date:  2008-05-06       Impact factor: 11.205

7.  Reconstructing ancestral gene content by coevolution.

Authors:  Tamir Tuller; Hadas Birin; Uri Gophna; Martin Kupiec; Eytan Ruppin
Journal:  Genome Res       Date:  2009-11-30       Impact factor: 9.043

Review 8.  Evolution of biomolecular networks: lessons from metabolic and protein interactions.

Authors:  Takuji Yamada; Peer Bork
Journal:  Nat Rev Mol Cell Biol       Date:  2009-11       Impact factor: 94.444

9.  Developmental restructuring of the creatine kinase system integrates mitochondrial energetics with stem cell cardiogenesis.

Authors:  Susan Chung; Petras P Dzeja; Randolph S Faustino; Andre Terzic
Journal:  Ann N Y Acad Sci       Date:  2008-12       Impact factor: 5.691

10.  Evolutionary constraints permeate large metabolic networks.

Authors:  Andreas Wagner
Journal:  BMC Evol Biol       Date:  2009-09-11       Impact factor: 3.260

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