Literature DB >> 22821452

Metabolic networks and their evolution.

Andreas Wagner1.   

Abstract

Since the last decade of the twentieth century, systems biology has gained the ability to study the structure and function of genome-scale metabolic networks. These are systems of hundreds to thousands of chemical reactions that sustain life. Most of these reactions are catalyzed by enzymes which are encoded by genes. A metabolic network extracts chemical elements and energy from the environment, and converts them into forms that the organism can use. The function of a whole metabolic network constrains evolutionary changes in its parts. I will discuss here three classes of such changes, and how they are constrained by the function of the whole. These are the accumulation of amino acid changes in enzyme-coding genes, duplication of enzyme-coding genes, and changes in the regulation of enzymes. Conversely, evolutionary change in network parts can alter the function of the whole network. I will discuss here two such changes, namely the elimination of reactions from a metabolic network through loss of function mutations in enzyme-coding genes, and the addition of metabolic reactions, for example through mechanisms such as horizontal gene transfer. Reaction addition also provides a window into the evolution of metabolic innovations, the ability of a metabolism to sustain life on new sources of energy and of chemical elements.

Mesh:

Year:  2012        PMID: 22821452     DOI: 10.1007/978-1-4614-3567-9_2

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  13 in total

Review 1.  Evolutionary design principles in metabolism.

Authors:  Gayathri Sambamoorthy; Himanshu Sinha; Karthik Raman
Journal:  Proc Biol Sci       Date:  2019-03-13       Impact factor: 5.349

2.  Evolutionary rate and duplicability in the Arabidopsis thaliana protein-protein interaction network.

Authors:  David Alvarez-Ponce; Mario A Fares
Journal:  Genome Biol Evol       Date:  2012       Impact factor: 3.416

3.  Recent positive selection has acted on genes encoding proteins with more interactions within the whole human interactome.

Authors:  Pierre Luisi; David Alvarez-Ponce; Marc Pybus; Mario A Fares; Jaume Bertranpetit; Hafid Laayouni
Journal:  Genome Biol Evol       Date:  2015-04-02       Impact factor: 3.416

4.  Tracing the Repertoire of Promiscuous Enzymes along the Metabolic Pathways in Archaeal Organisms.

Authors:  Mario Alberto Martínez-Núñez; Zuemy Rodríguez-Escamilla; Katya Rodríguez-Vázquez; Ernesto Pérez-Rueda
Journal:  Life (Basel)       Date:  2017-07-13

5.  The potential for non-adaptive origins of evolutionary innovations in central carbon metabolism.

Authors:  Sayed-Rzgar Hosseini; Andreas Wagner
Journal:  BMC Syst Biol       Date:  2016-10-21

6.  Physiological and genomic evidence that selection on the transcription factor Epas1 has altered cardiovascular function in high-altitude deer mice.

Authors:  Rena M Schweizer; Jonathan P Velotta; Catherine M Ivy; Matthew R Jones; Sarah M Muir; Gideon S Bradburd; Jay F Storz; Graham R Scott; Zachary A Cheviron
Journal:  PLoS Genet       Date:  2019-11-07       Impact factor: 5.917

7.  Exhaustive Analysis of a Genotype Space Comprising 10(15 )Central Carbon Metabolisms Reveals an Organization Conducive to Metabolic Innovation.

Authors:  Sayed-Rzgar Hosseini; Aditya Barve; Andreas Wagner
Journal:  PLoS Comput Biol       Date:  2015-08-07       Impact factor: 4.475

8.  Sequence divergence and diversity suggests ongoing functional diversification of vertebrate NAD metabolism.

Authors:  Toni I Gossmann; Mathias Ziegler
Journal:  DNA Repair (Amst)       Date:  2014-07-29

9.  Relationship between gene duplicability and diversifiability in the topology of biochemical networks.

Authors:  Zhanyong Guo; Wen Jiang; Nuno Lages; Wade Borcherds; Degeng Wang
Journal:  BMC Genomics       Date:  2014-07-08       Impact factor: 3.969

10.  Metabolic Determinants of Enzyme Evolution in a Genome-Scale Bacterial Metabolic Network.

Authors:  José Aguilar-Rodríguez; Andreas Wagner
Journal:  Genome Biol Evol       Date:  2018-11-01       Impact factor: 3.416

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