Molecular evolution of pathogenic bacteria based on rrsA gene

• Main Authors: Aravind Setti, T A Phazna Devi, Smita C Pawar, G Rajesh, S Srikanth, S Kalyan
• Format: Article
• Language: English
• Published: Deccan College of Medical Sciences 2012-01-01
• Series: Journal of Medical and Allied Sciences
• Subjects: Phylogeny; Maximum Likelihood (ML); Maximum Parsimony (MP); rrsA gene; Transition transversion bias; Ribotyping
• Online Access: http://www.jmas.in/Vol2Issue1/Molecular%20evolution%20of%20pathogenic%20bacteria%20based%20on%20rrsA%20gene.pdf
• ISSN: 2231-1696; 2231-170X

Evolution of pathogens in prokaryotic bacteria was studied by 16srRNA genes. In this study rrsA genes of 45 bacteria were considered, which includes pathogens, non-pathogens and out-group bacteria. We considered non-pathogenic bacteria, for each class in bacterial classification, to support the pathogenic evolution. In this investigation, aligned nucleotide sequences of rrsA genes were used for Phylogenetic analysis and they have been clustered precisely. Maximum Likelihood (ML) and Maximum Parsimony (MP) methods were employed for the molecular evolution of pathogenic bacteria. The best-fit substitution model with the lowest Bayesian Information Criterion scores is considered to describe the substitution pattern the best, and non-uniformity of evolutionary rates among sites were modeled by using a discrete Gamma distribution. Nearest Neighbor Interchange (NNI) heuristic method was used to generate the tree for ML and Close Neighbor Interchange (CNI) on random trees search methods for MP. Further both the phylogenetic trees were statistically evaluated for accuracy by bootstrap value. Transition and transversion ratio of the rrsA genes have been estimated for the mutation frequency over the evolution by Maximum Composite Likelihood (MCL) bias and ML bias. Combined pathogenic and non pathogenic bacteria analysis reflected the clear diversity of bacteria over time and agrees with morphological and cytological data. These molecular evolution results should be useful to study the evolution pattern of pathogenic bacteria.