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Radon and heavy metal (HM) contamination in drinking water and their impact on health have been reported earlier. However, relatively little is known about the microbial community in drinking water with gradients of radon and the drivers of microbial community patterns in such water. With this view, we first examine microbial dynamics of drinking water in the permissible level of 93 ± 2 Bq/l as control, 510 ± 1.5 6 Bq/l and 576 ± 2 Bq/l as medium, and 728 ± 3 Bq/l as high radon-containing tube wells from Dumka and Godda districts, which comes under a major fault of the eastern fringes of India. Attempts have also been made to predict the impact of the radon contamination gradient and other water environmental parameters on community structure. The measured physicochemical character revealed strong clustering by the sampling site with respect to its radon and HM content. The radon-contaminated sites represent HM-rich nutrient-limited sites compared to the control. Radon (Rn), HM (Pb, Cu, and As), and total suspended solids (TSSs) were the most determinant variable among the parameters and influenced the microbial community composition of that region. The microbial diversity of those sites was lower, and this measured diversity decreased gradually on the sites with an increased gradient of radon contamination. The dominant microbial families in the contaminated sites were Moraxellaceae, Chitinophagaceae, unclassified Candidatus Azambacteria, unclassified Candidatus Moranbacteria, unclassified Candidatus Collierbacteria, and Gammaproteobacterial members, which are reported to abundantly inhabit radiation and chemolithotrophic environments and pose better radionuclide protective mechanisms, while the bacterial members dominant in the control site were Comamonadaceae, Rhodocyclaceae, Nitrospirales Incertae Sedis, cvE6, unclassified Woesearchaeota (DHVEG-6), and Holophagaceae, which are reported to be abundant in natural soil and drinking water, and labile in harsh environments. Relative sequence abundance of Comamonadaceae was decreasing on the sites with an increasing radon gradient, while the opposite trend was observed for Chitinophagaceae. The distribution of such microbial assemblages is linked to radon and heavy metal, highlighting that taxa with distinct environmental preferences underlie apparent clustering by sites; thus, we can utilize them for biostimulation-based in situ bioremediation purposes.

Type 2 diabetes (T2D) is a serious public health issue and may also contribute to modification in the structure of the intestinal microbiota, implying a link between T2D and microbial inhabitants in the digestive tract. This work aimed to develop efficient models for identifying essential physiological markers for improved T2D classification using machine learning algorithms. Using amplicon metagenomic approaches, an effort has also been made to understand the alterations in core gut microbial members in Indian T2D patients with respect to their control normal glucose tolerance (NGT). Our data indicate the level of fasting blood glucose (FBG) and glycated hemoglobin (HbA1c) were the most useful physiological indicators while random forest and support vector machine with RBF Kernel were effective predictions models for identifications of T2D. The dominating gut microbial members Allopreotella, Rikenellaceae RC9 gut group, Haemophilus, Ruminococcus torques group, etc. in Indian T2D patients showed a strong association with both FBG and HbA1c. These members have been reported to have a crucial role in gut barrier breakdown, blood glucose, and lipopolysaccharide level escalation, or as biomarkers. While the dominant NGT microbiota (Akkermansia, Ligilactobacillus, Enterobacter, etc.) in the colon has been shown to influence inflammatory immune responses by acting as an anti-inflammatory agent and maintaining the gut barrier. The topology study of co-occurrence network analysis indicates that changes in network complexity in T2D lead to variations in the different gut microbial members compared to NGT. These studies provide a better understanding of the gut microbial diversity in Indian T2D patients and show the way for the development of valuable diagnostics strategies to improve the prediction and modulation of the T2D along with already established methods.

Novel coronavirus SARS-CoV-2 was recently outbreak worldwide causes severe acute respiratory syndrome along with gastrointestinal symptoms for some infected patients. Information on detail pathogenesis, host immune responses and responsible biological pathways are limited. Therefore, infection specific host gut responses and dietary supplements to neutralize immune inflammation demand extensive research. This study aimed to find differences in global co-expression protein-protein interaction sub-network and enriched biological processes in SARS-CoV and SARS-CoV-2 infected gut enterocytes cell line. Attempts have also been made to predict some dietary supplements to boost human health. The SARS-CoV and SARS-CoV-2 infected differential express proteins were integrated with the human protein interaction network and co-expression subnetworks were constructed. Common hubs of these sub-networks reshape central cellular pathways of metabolic processes, lipid localization, hypoxia response to decrease oxygen level and transport of bio-molecules. The major biological process enriched in the unique hub of SARS-CoV-2 significantly differ from SARS-CoV, related to interferon signaling, regulation of viral process and influenza-A enzymatic pathway. Predicted dietary supplements can improve SARS-CoV-2 infected person's health by boosting the host immunity/reducing inflammation. To the best of our knowledge this is the first report on co-expression network mediated biological process in human gut enterocytes to predict dietary supplements/compounds.