Vikodak - A Modular Framework for Inferring Functional Potential of Microbial Communities from 16S Metagenomic Datasets

• Published in: PloS one Vol. 11; no. 2; p. e0148347
• Main Authors: Nagpal, Sunil, Haque, Mohammed Monzoorul, Mande, Sharmila S.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 05.02.2016; Public Library of Science (PLoS)
• Subjects: Abundance; Algorithms; Automation; Automation, Laboratory; Biology and Life Sciences; Centipeda; Classification; Coding; Communities; Datasets; DNA sequencing; Enzymes; Functional analysis; Genes; Genetic aspects; Genomes; Genomics; Gum disease; Medicine and Health Sciences; Metabolic Networks and Pathways - genetics; Metabolic Networks and Pathways - physiology; Metabolic pathways; Metabolism; Metagenome - genetics; Metagenomics - methods; Microbial activity; Microbiomes; Microbiota - genetics; Microbiota - physiology; Microorganisms; Physical Sciences; Physiological aspects; Proteins; R&D; Research & development; Research and Analysis Methods; RNA, Ribosomal, 16S - genetics; Statistical analysis; Statistical methods; Studies; Taxonomy; India
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0148347

The overall metabolic/functional potential of any given environmental niche is a function of the sum total of genes/proteins/enzymes that are encoded and expressed by various interacting microbes residing in that niche. Consequently, prior (collated) information pertaining to genes, enzymes encoded by the resident microbes can aid in indirectly (re)constructing/ inferring the metabolic/ functional potential of a given microbial community (given its taxonomic abundance profile). In this study, we present Vikodak--a multi-modular package that is based on the above assumption and automates inferring and/ or comparing the functional characteristics of an environment using taxonomic abundance generated from one or more environmental sample datasets. With the underlying assumptions of co-metabolism and independent contributions of different microbes in a community, a concerted effort has been made to accommodate microbial co-existence patterns in various modules incorporated in Vikodak. Validation experiments on over 1400 metagenomic samples have confirmed the utility of Vikodak in (a) deciphering enzyme abundance profiles of any KEGG metabolic pathway, (b) functional resolution of distinct metagenomic environments, (c) inferring patterns of functional interaction between resident microbes, and (d) automating statistical comparison of functional features of studied microbiomes. Novel features incorporated in Vikodak also facilitate automatic removal of false positives and spurious functional predictions. With novel provisions for comprehensive functional analysis, inclusion of microbial co-existence pattern based algorithms, automated inter-environment comparisons; in-depth analysis of individual metabolic pathways and greater flexibilities at the user end, Vikodak is expected to be an important value addition to the family of existing tools for 16S based function prediction. A web implementation of Vikodak can be publicly accessed at: http://metagenomics.atc.tcs.com/vikodak. This web service is freely available for all categories of users (academic as well as commercial).