Comparative taxonomic and functional microbiome profiling of anthrospheric river tributary for xenobiotics degradation study

Abstract

A metagenomic approach was used to initiate a comparative taxonomical and functional microbial profiling of a polluted site Amlakhadi. After sequencing on Oxford's Nanopore platform, a total of 7864 reads with an average read length of 2800bp, and a mean G + C% of 50 ± 7 were observed. STAMP, METAGENassist, MG RAST, PAST, MEGAN, and Community analyzer were used for the taxonomic and functional screening. The dominant phyla Proteobacteria, Bacteroidetes, Firmicutes, Chlorobi, Actinobacteria and dominant species Sulfuricurvum kujiense, Chlorobaculum tepidum, Allochromaticum vinosum, Desulfomicrobium baculatum, Thiobacillus denitrificans were observed. The metagenomic data was then compared to four metagenomes from the same site which are publicly available on EBI Metagenomics with run accession numbers ERR947518, ERR947519, ERR947520, and ERR947521. At the phyla level, all five metagenomes consist of Proteobacteria, Acidobacteria, Thermotogae, Planctomycetes, Bacteroidetes, Actinobacteria, and at the species level Serratia proteamaculans, T. denitrificans, Serratia odorifera, Strenotrophomonas maltophilia as the core microbes. The functional analysis shows that all metagenomes contain pathways for the degradation of benzene, nitrotoluene, and DDT with the detection of other xenobiotic remediation pathways through MG RAST. While degradation pathways of dehalogenation, atrazine, and aromatic hydrocarbon were commonly found in all five metagenomes through METAGENassist. Enzymes mapped on xenobiotic degradation pathways commonly belong to the class oxidoreductase, lyase, and transferase. Along with basic cell metabolism, genes involved in xenobiotics degradation were also annotated prevalently. This omics-based comparative metagenomic characterization drains out information about pollutants removing novel microbes and will also help in the development of a clean-up scheme for xenobiotics contaminated environments.