Literature DB >> 15210350

Analysis of phenetic trees based on metabolic capabilites across the three domains of life.

Daniel Aguilar1, Francesc X Aviles, Enrique Querol, Michael J E Sternberg.   

Abstract

Here, we used data of complete genomes to study comparatively the metabolism of different species. We built phenetic trees based on the enzymatic functions present in different parts of metabolism. Seven broad metabolic classes, comprising a total of 69 metabolic pathways, were comparatively analyzed for 27 fully sequenced organisms of the domains Eukarya, Bacteria and Archaea. Phylogenetic profiles based on the presence/absence of enzymatic functions for each metabolic class were determined and distance matrices for all the organisms were then derived from the profiles. Unrooted phenetic trees based upon the matrices revealed the distribution of the organisms according to their metabolic capabilities, reflecting the ecological pressures and adaptations that those species underwent during their evolution. We found that organisms that are closely related in phylogenetic terms could be distantly related metabolically and that the opposite is also true. For example, obligate bacterial pathogens were usually grouped together in our metabolic trees, demonstrating that obligate pathogens share common metabolic features regardless of their diverse phylogenetic origins. The branching order of proteobacteria often did not match their classical phylogenetic classification and Gram-positive bacteria showed diverse metabolic affinities. Archaea were found to be metabolically as distant from free-living bacteria as from eukaryotes, and sometimes were placed close to the metabolically highly specialized group of obligate bacterial pathogens. Metabolic trees represent an integrative approach for the comparison of the evolution of the metabolism and its correlation with the evolution of the genome, helping to find new relationships in the tree of life. Copyright 2004 Elsevier Ltd.

Mesh:

Substances:

Year:  2004        PMID: 15210350     DOI: 10.1016/j.jmb.2004.04.059

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  12 in total

1.  Prediction of novel synthetic pathways for the production of desired chemicals.

Authors:  Ayoun Cho; Hongseok Yun; Jin Hwan Park; Sang Yup Lee; Sunwon Park
Journal:  BMC Syst Biol       Date:  2010-03-28

2.  Functional Redundancy in Bat Microbial Assemblage in the Presence of the White Nose Pathogen.

Authors:  Matthew Grisnik; Joshua B Grinath; John P Munafo; Donald M Walker
Journal:  Microb Ecol       Date:  2022-08-11       Impact factor: 4.192

3.  Decoupling Environment-Dependent and Independent Genetic Robustness across Bacterial Species.

Authors:  Shiri Freilich; Anat Kreimer; Elhanan Borenstein; Uri Gophna; Roded Sharan; Eytan Ruppin
Journal:  PLoS Comput Biol       Date:  2010-02-26       Impact factor: 4.475

4.  The large-scale organization of the bacterial network of ecological co-occurrence interactions.

Authors:  Shiri Freilich; Anat Kreimer; Isacc Meilijson; Uri Gophna; Roded Sharan; Eytan Ruppin
Journal:  Nucleic Acids Res       Date:  2010-03-01       Impact factor: 16.971

5.  Functional classification of genome-scale metabolic networks.

Authors:  Oliver Ebenhöh; Thomas Handorf
Journal:  EURASIP J Bioinform Syst Biol       Date:  2009-03-17

6.  Reconstructing phylogeny from metabolic substrate-product relationships.

Authors:  Che-Wei Chang; Ping-Chiang Lyu; Masanori Arita
Journal:  BMC Bioinformatics       Date:  2011-02-15       Impact factor: 3.169

7.  Phylophenetic properties of metabolic pathway topologies as revealed by global analysis.

Authors:  Yong Zhang; Shaojuan Li; Geir Skogerbø; Zhihua Zhang; Xiaopeng Zhu; Zefeng Zhang; Shiwei Sun; Hongchao Lu; Baochen Shi; Runsheng Chen
Journal:  BMC Bioinformatics       Date:  2006-05-09       Impact factor: 3.169

8.  Reconstruction of phyletic trees by global alignment of multiple metabolic networks.

Authors:  Cheng-Yu Ma; Shu-Hsi Lin; Chi-Ching Lee; Chuan Yi Tang; Bonnie Berger; Chung-Shou Liao
Journal:  BMC Bioinformatics       Date:  2013-01-21       Impact factor: 3.169

9.  Metabolic innovations towards the human lineage.

Authors:  Shiri Freilich; Leon Goldovsky; Christos A Ouzounis; Janet M Thornton
Journal:  BMC Evol Biol       Date:  2008-09-09       Impact factor: 3.260

10.  The mosaic genome of Anaeromyxobacter dehalogenans strain 2CP-C suggests an aerobic common ancestor to the delta-proteobacteria.

Authors:  Sara H Thomas; Ryan D Wagner; Adrian K Arakaki; Jeffrey Skolnick; John R Kirby; Lawrence J Shimkets; Robert A Sanford; Frank E Löffler
Journal:  PLoS One       Date:  2008-05-07       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.