Structural, functional, resistome and pathogenicity profiling of the Cooum river

Utility of metagenomics for bioremediation: a comprehensive review on bioremediation mechanisms and microbial dynamics of river ecosystem

Global industrialization has contributed substantial amounts of chemical pollutants in rivers, resulting in an uninhabitable state and impacting different life forms. Moreover, water macrophytes, such as water hyacinths, are abundantly present in polluted rivers, significantly affecting the overall water biogeochemistry. Bioremediation involves utilizing microbial metabolic machinery and is one of the most viable approaches for removing toxic pollutants. Conventional techniques generate limited information on the indigenous microbial population and their xenobiotic metabolism, failing the bioremediation process. Metagenomics can overcome these limitations by providing in-depth details of microbial taxa and functionality-related information required for successful biostimulation and augmentation. An in-depth summary of the findings related to pollutant metabolizing genes and enzymes in rivers still needs to be collated. The present study details bioremediation genes and enzymes functionally mined from polluted river ecosystems worldwide using a metagenomic approach. Several studies reported a wide variety of pollutant-degrading enzymes involved in the metabolism of dyes, plastics, persistent organic pollutants, and aromatic hydrocarbons. Additionally, few studies also noted a shift in the microbiome of the rivers upon exposure to contaminants, crucially affecting the ecological determinant processes. Furthermore, minimal studies have focused on the role of water-hyacinth-associated microbes in the bioremediation potentials, suggesting the need for the bioprospecting of these lesser-studied microbes. Overall, our study summarizes the prospects and utilities of the metagenomic approach and proposes the need to employ it for efficient bioremediation.

Sex, health status and habitat alter the community composition and assembly processes of symbiotic bacteria in captive frogs

BACKGROUND

Frogs are critical economic animals essential to agricultural ecosystem equilibrium. However, Meningitis-like Infectious Disease (MID) often affects them in agricultural settings. While frog-associated microbiota contribute to elemental cycling and immunity, the effects of frog sex and health on gut bacteria remain understudied, and the relationship between frog habitat and soil microbes is unclear. We aimed to determine how frog sex, health status and habitat influence symbiotic bacteria and community assembly mechanism to provide guidance for sustainable frog farming and conservation.

RESULTS

We employed 16S rRNA sequencing to investigate gut microbiota differences in relation to frog sex and health status. We also compared symbiotic communities in frog-aggregation, native and soybean soil on the farm. Results showed that gut bacterial β-diversity and taxonomy were markedly influenced by frog sex and health. Healthy frogs had more robust gut bacterial metabolism than frogs infected with MID. Cooccurrence network analysis revealed that healthy female frogs had more complex microbial network structure than males; however, diseased males showed the greatest network complexity. The assembly mechanism of gut bacteria in male frogs was dominated by deterministic processes, whereas in female frogs it was dominated by stochastic processes. Among symbiotic bacteria in frog habitat soils, deterministic processes predominantly shaped the community assembly of soybean soil. In particular, soybean soil was enriched in pathogens and nitrogen functions, whereas frog-aggregation soil was markedly increased in sulphur respiration and hydrocarbon degradation.

CONCLUSION

Our study reveals that sex mainly alters the interaction network and assembly mechanism of frog intestinal bacteria; MID infection significantly inhibits the metabolic functions of intestinal bacteria. Furthermore, diverse frog habitat soils could shape more symbiotic bacteria to benefit frog farming. Our findings provide new horizons for symbiotic bacteria among frogs, which could contribute to sustainable agriculture and ecological balance.

Bacterial diversity in the aquatic system in India based on metagenome analysis-a critical review

Microbial analysis has become one of the most critical areas in aquatic ecology and a crucial component for assessing the contribution of microbes in food web dynamics and biogeochemical processes. Initial research was focused on estimating the abundance and distribution of the microbes using microscopy and culture-based analysis, which are undoubtedly complex tasks. Over the past few decades, microbiologists have endeavored to apply and extend molecular techniques to address pertinent questions related to the function and metabolism of microbes in aquatic ecology. Metagenomics analysis has revolutionized aquatic ecology studies involving the investigation of the genome of a mixed community of organisms in an ecosystem to identify microorganisms, their functionality, and the discovery of novel proteins. This review discusses the metagenomics analysis of bacterial diversity in and around different aquatic systems in India.

Assessment of physico-chemical parameters of surface waters of a tropical brackish water lake in South Asia

Brackish lake systems and estuaries are unique aquatic systems that support diversified life forms and strongly influence a region's economy. Major chemical water quality parameters of India's second-largest brackish water lake, Pulicat were assessed. Physico-chemical parameters like pH, temperature, suspended solid concentrates, total dissolved solids, salinity, nitrogenous nutrients, phosphate, silicate, and chlorophyll a were analysed. The results obtained for different parameters were compared and interpreted with statistical software SPSS version 20 and images were plotted using the Arc GIS spatial analyst tool. During the summer months, the nitrogen to phosphorus ratio ranges from a minimum of 1.96 to a maximum of 16.64 (9.55 ± 4.01) while it ranges from a minimum of 7.98 to a maximum of 15.52 (12.47 ± 2) during the pre-monsoon. In the monsoon season, the nitrogen to phosphorus ratio of surface water suggests a range from a minimum of 8.64 to a maximum of 17.58 (13.87 ± 2.14). During the post-monsoon season, the nitrogen to phosphorus ratio ranges from 4.98 to 17.34 (11.77 ± 3.68). The average nitrogen to phosphorus ratios were 9.6, 12.5, 13.9 and 11.8 in summer, pre-monsoon, monsoon, and post-monsoon respectively. The nitrogen to phosphorus ratio was lower than the Redfield ratio for all the seasons. The average concentration of chlorophyll a was 14.9, 13.4, 12.8 and 11.8 in summer, pre-monsoon, monsoon, and post-monsoon respectively. As per the Pearson Correlation Coefficient, there was no significant correlation among nitrogen, phosphorus, and chlorophyll a. This suggests the influence of suspended solid concentrates, and nitrogen and phosphorus flux in the sediment-water interface might be interfering with the nutrient cycles and primary productivity.

Meta-analysis of the microbial biomarkers in the gut - lung crosstalk in COVID-19, community acquired pneumonia and Clostridium difficile infections

Respiratory infections are the leading causes of mortality and the current pandemic COVID-19 is one such trauma that imposed catastrophic devastation to the health and economy of the world. Unraveling the correlations and interplay of the human microbiota in the gut- lung axis would offer incredible solutions to the underlying mystery of the disease progression. The study compared the microbiota profiles of six samples namely healthy gut, healthy lung, COVID-19 infected gut, COVID-19 infected lungs, Clostridium difficile infected gut and community acquired pneumonia infected lungs. The metagenome datasets were processed, normalized, classified and the rarefaction curves were plotted. The microbial biomarkers for COVID-19 infections were identified as the abundance of Candida and Escherichia in lungs with Ruminococcus in the gut. Candida and Staphylococcus could play a vital role as putative prognostic biomarkers of community acquired pneumonia whereas abundance of Faecalibacterium and Clostridium are associated with the Clostridium difficile infections in gut. A machine learning random forest classifier applied to the datasets efficiently classified the biomarkers. The study offers an extensive and incredible understanding of the existence of gut lung axis during dysbiosis of two anatomically different organs.