Influence of Geochemistry in the Tropical Hot Springs on Microbial Community Structure and Function

Abstract

Thermophiles inhabiting high temperatures are considered primitive microorganisms on early Earth. In this regard, several works have demonstrated microbial community composition in geothermal environments. Despite that, studies on hot springs located in the Indian subcontinent viz., Surajkund in the district Hazaribag, Jharkhand; Bakreshwar in the district Birbhum, West Bengal; Tantloi in the district Dumka, and Sidpur in the district Pakur, Jharkhand are scanty. Nonetheless, the metagenomic analysis of these hot springs showed significant differences in the predominant phyla corresponding to geochemical properties. The Chloroflexi, Proteobacteria, Actinobacteria, Deinococcus-Thermus, and Firmicutes were dominant phyla in all the samples. In contrast, Meiothermus was more in comparatively low-temperature hot springs. In addition, archaeal phyla, Euryarchaeota, Candidatus Bathyarchaeota, and Crenarchaeota were predominant in all samples. The canonical correspondence analysis (CCA) showed the abundance of Deinococcus, Thermus, Pyrobaculum, Kocuria, and Geodermatophilus positively correlated with the aqueous concentration of sulfate, fluoride, and argon in relatively high-temperature (≥ 72 °C) hot springs. However, at a lower temperature (≤ 63 °C), Thermodesulfovibrio, Caldilinea, Chloroflexus, Meiothermus, and Tepidimonas are positively correlated with the concentration of zinc, iron, and dissolved oxygen. Further, hierarchical clustering exhibits variations in its functional attributes depending on the temperature gradients. Metagenome analysis predicted carbon, methane, sulfur, and nitrogen metabolism genes, indicating a wide range of bacteria and archaea habitation in these hot springs. In addition, identified several genes encode polyketide biosynthesis pathways. The present study described the microbial community composition and function in the tropical hot springs and their relationship with the environmental variables.