Metabolic classification of microbial genomes using functional probes

BMC Genomics

Research Article

Wei-Cheng Lo¹  Yi-Ping Phoebe Chen²  Chuan Yi Tang³  Szu-Ming Lai⁴  Chi-Ching Lee⁵  Ping-Chiang Lyu⁶ 

[1] Department of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan;Department of Computer Science and Computer Engineering, La Trobe University, Melbourne, Australia;Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan;Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan;Graduate Institute of Molecular Systems Biomedicine, China Medical University, Taichung, Taiwan;Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, Taiwan;Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, Taiwan;Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan;Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, Taiwan;Department of Medical Science, National Tsing Hua University, Hsinchu, Taiwan;Graduate Institute of Molecular Systems Biomedicine, China Medical University, Taichung, Taiwan;

关键词: Horizontal Gene Transfer;    Frequency Pattern;    Classification Tree;    Enzyme Commission;    Correlation Coefficient;   

DOI  :  10.1186/1471-2164-13-157

 received in 2011-10-12, accepted in 2012-04-27,  发布年份 2012

来源: Springer

【 摘 要 】

BackgroundMicroorganisms able to grow under artificial culture conditions comprise only a small proportion of the biosphere's total microbial community. Until recently, scientists have been unable to perform thorough analyses of difficult-to-culture microorganisms due to limitations in sequencing technology. As modern techniques have dramatically increased sequencing rates and rapidly expanded the number of sequenced genomes, in addition to traditional taxonomic classifications which focus on the evolutionary relationships of organisms, classifications of the genomes based on alternative points of view may help advance our understanding of the delicate relationships of organisms.ResultsWe have developed a proteome-based method for classifying microbial species. This classification method uses a set of probes comprising short, highly conserved amino acid sequences. For each genome, in silico translation is performed to obtained its proteome, based on which a probe-set frequency pattern is generated. Then, the probe-set frequency patterns are used to cluster the proteomes/genomes.ConclusionsFeatures of the proposed method include a high running speed in challenge of a large number of genomes, and high applicability for classifying organisms with incomplete genome sequences. Moreover, the probe-set clustering method is sensitive to the metabolic phenotypic similarities/differences among species and is thus supposed potential for the classification or differentiation of closely-related organisms.

【 授权许可】

Unknown   
© Lee et al; licensee BioMed Central Ltd. 2012. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.