Distinguishing Features of 16S rDNA Gene for Five Dominating Bacterial Genus Observed in Bioremediation

Abstract

Defining a microbial community and identifying bacteria, at least at the genus level, is a first step in predicting the behavior of a microbial community in bioremediation. In biological treatment systems, the most dominating groups observed are Pseudomonas, Moraxella, Acinetobactor, Burkholderia, and Alcaligenes. Our interest lies in identifying the distinguishing features of these bacterial groups based on their 16S rDNA sequence data, which could be used further for generating genus-specific probes. Accordingly, 20 sequences representing different species from each genus above were retrieved, which constituted a training set. A 16-dimensional feature vector comprised of transition probabilities of nucleotides was considered and each sampled sequence was expressed in terms of these features. A stepwise feature selection method was used to identify features that are distinct across the species of these five groups. Wilk's lambda selection criterion was used and resulted in a subset with six distinguishing features. The discriminating efficacy of this subset was tested through multiple group discriminant analysis. Two linear composites, as a function of these features, could discriminate the test set of forty-five sequences from these groups with 95% accuracy, thereby ascertaining the relevance of the identified features. The geometric representation of feature correlation in the reduced discriminant space demonstrated the dominance of identified features in specific groups. These features independently or in combination could be used to generate genus-specific patterns to design probes, so as to develop a tracking tool for the selected group of bacteria.