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Comprehensive exploration of the enzymes catalysing oxygen‐involved reactions and COGs relevant to bacterial oxygen utilization
Author(s) -
Liu Shuo,
Du MengZe,
Wen QingFeng,
Kang Juanjuan,
Dong Chuan,
Xiong Lifeng,
Huang Jian,
Guo FengBiao
Publication year - 2018
Publication title -
environmental microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.954
H-Index - 188
eISSN - 1462-2920
pISSN - 1462-2912
DOI - 10.1111/1462-2920.14399
Subject(s) - biology , gene , phylogenetic tree , enzyme , adaptation (eye) , oxygen , bacteria , phylogenetics , function (biology) , genetics , computational biology , biochemistry , chemistry , organic chemistry , neuroscience
Summary To better understand the mechanisms of bacterial adaptation in oxygen environments, we explored the aerobic living‐associated genes in bacteria by comparing Clusters of Orthologous Groups of proteins’ (COGs) frequencies and gene expression analyses and 38 COGs were detected at significantly higher frequencies ( p ‐value less than 1e−6) in aerobes than in anaerobes. Differential expression analyses between two conditions further narrowed the prediction to 27 aerobe‐specific COGs. Then, we annotated the enzymes associated with these COGs. Literature review revealed that 14 COGs contained enzymes catalysing oxygen‐involved reactions or products involved in aerobic pathways, suggesting their important roles for survival in aerobic environments. Additionally, protein–protein interaction analyses and step length comparisons of metabolic networks suggested that the other 13 COGs may function relevantly with the 14 enzymes‐corresponding COGs, indicating that these genes may be highly associated with oxygen utilization. Phylogenetic and evolutionary analyses showed that the 27 COGs did not have similar trees, and all suffered purifying selection pressures. The divergent times of species containing or lacking aerobic COGs validated that the appearing time of oxygen‐utilizing gene was approximately 2.80 Gyr ago. In addition to help better understand oxygen adaption, our method may be extended to identify genes relevant to other living environments.