Exploring microbial diversity in hot springs of Surajkund, India through 16S rRNA analysis and thermozyme characterization from endogenous isolates.

Hot springs are a valuable source of biologically significant chemicals due to their high microbial diversity. To investigate the possibilities for industrial uses of these bacteria, researchers collected water and sediment samples from variety of hot springs. Our investigation employed both culture-dependent and culture-independent techniques, including 16S-based marker gene analysis of the microbiota from the hot springs of Surajkund, Jharkhand. In addition, we cultivated thermophilic isolates and screened for their ability to produce amylase, xylanase, and cellulase. After the optimized production of amylase the enzyme was partially purified and characterized using UPLC, DLS-ZP, and TGA. The retention time for the amylase was observed to be around 0.5 min. We confirmed the stability of the amylase at higher temperatures through observation of a steady thermo gravimetric profile at 400 °C. One of the thermophilic isolates obtained from the kund, demonstrated the potential to degrade lignocellulosic agricultural waste.

Next generation sequencing analysis of lung cancer datasets: A functional genomics perspective.

Cigarette smoking leads to serious epidemics in humans, creating torsion of infection in epithelial cells lining the respiratory tracts. Several researchers in the recent past have theorized that the next generation sequencing (NGS), especially transcriptome sequencing has enhanced understanding lung cancers and other epithelial epidemics. Conversely, pathogenesis specific to lung cancer with respect to molecular fraction of genomic ribonucleic acid has some mutant effect in various populations like smokers with lung cancer, healthy never smokers and vice versa. We review the impending impact of NGS data while providing insights into the biology of lung cancer affecting various populations, which we believe would be an add-on service for predictive biology approaches. Furthermore, we conclude what would be the outcome of such analysis for Indian population. Bioinformatics analysis was performed using various tools. We identified five genes namely epidermal growth factor receptor, Kirsten rat sarcoma, adenomatosis polyposis down regulated-1, N-ethylmaleimide-sensitive factor attachment protein, gamma and Piezo type mechanosensitive ion channel component 2 whose role was implicated in lung cancer and further analysis has to be performed to check whether or not the genes are indeed completely involved in causing lung cancer.