Kinema is an ethnic, naturally fermented soybean product consumed in the Sikkim Himalayan region of India. In the present study, the whole metagenome sequencing approach was adopted to examine the microbial diversity and related functional potential of Kinema , consumed in different seasons. Firmicutes was the abundant phylum in Kinema , ranging from 82.31 to 93.99% in different seasons, followed by Actinobacteria and Proteobacteria. At the species level, the prevalent microorganisms were Bacillus subtilis , Bacillus amyloliquefaciens , Bacillus licheniformis , Corynebacterium glutamicum , Bacillus pumilus , and Lactococcus lactis . The abundance of microbial species varied significantly in different seasons. Further, the genomic presence of some undesirable microbes like Bacillus cereus, Proteus mirabilis , Staphylococcus aureus , Proteus penneri, Enterococcus faecalis , and Staphylococcus saprophyticus , were also detected in the specific season. The metagenomic analysis also revealed the existence of bacteriophages belonging to the family Siphoviridae , Myoviridae , and Podoviridae . Examination of the metabolic potential of the Kinema metagenome depicted information about the biocatalysts, presumably involved in the transformation of protein and carbohydrate polymers into bioactive molecules of health-beneficial effects. The genomic resource of several desirable enzymes was identified, such as β-galactosidase, β-glucosidase, β-xylosidase, and glutamate decarboxylase, etc. The catalytic function of a novel glutamate decarboxylase gene was validated for the biosynthesis of γ-aminobutyric acid (GABA). The results of the present study highlight the microbial and genomic resources associated with Kinema , and its importance in functional food industry.
Background Himalaya is an ecologically pristine environment. The geo-tectonic activities have shaped various environmental niches with diverse microbial populations throughout the Himalayan biosphere region. Albeit, limited information is available in terms of molecular insights into the microbiome, including the uncultured microbes, of the Himalayan habitat. Hence, a vast majority of genomic resources are still under-explored from this region. Metagenome analysis has simplified the extensive in-depth exploration of diverse habitats. In the present study, the culture-independent whole metagenome sequencing methodology was employed for microbial diversity exploration and identification of genes involved in various metabolic pathways in two geothermal springs located at different altitudes in the Sikkim Himalaya. Results The two hot springs, Polok and Reshi, have distinct abiotic conditions. The average temperature of Polok and Reshi was recorded to be 62 °C and 43 °C, respectively. Both the aquatic habitats have alkaline geochemistry with pH in the range of 7–8. Community profile analysis revealed genomic evidence of plentiful bacteria, with a minute fraction of the archaeal population in hot water reservoirs of Polok and Reshi hot spring. Mesophilic microbes belonging to Proteobacteria and Firmicutes phyla were predominant at both the sites. Polok exhibited an extravagant representation of Chloroflexi, Deinococcus-Thermus, Aquificae, and Thermotogae. Metabolic potential analysis depicted orthologous genes associated with sulfur, nitrogen, and methane metabolism, contributed by the microflora in the hydrothermal system. The genomic information of many novel carbohydrate-transforming enzymes was deciphered in the metagenomic description. Further, the genomic capacity of antimicrobial biomolecules and antibiotic resistance were discerned. Conclusion The study provided comprehensive molecular information about the microbial treasury as well as the metabolic features of the two geothermal sites. The thermal aquatic niches were found a potential bioresource of biocatalyst systems for biomass-processing. Overall, this study provides the whole metagenome based insights into the taxonomic and functional profiles of Polok and Reshi hot springs of the Sikkim Himalaya. The study generated a wealth of genomic data that can be explored for the discovery and characterization of novel genes encoding proteins of industrial importance.
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