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Extreme flooding is one of the major risk factors for human health, and it can significantly influence the microbial communities and enhance the mobility of infectious disease agents within the affected areas. The flood crisis in 2018 was one of the severe natural calamities recorded in the southern state of India (Kerala) that significantly affected its economy and ecological habitat. We utilized a combination of shotgun metagenomics and bioinformatics approaches to understand the bacterial profile and the abundance of pathogenic and antibiotic-resistant bacteria in extremely flooded areas of Kuttanad, Kerala (4−10 feet below sea level). Here we report the bacterial profiles of flooded sites that are abundant with virulent and resistant bacteria. The flooded sites were heavily contaminated with faecal contamination indicators such as Escherichia coli and Enterococcus faecalis and multidrug-resistant strains of Pseudomonas aeruginosa, Salmonella typhi/typhimurium, Klebsiella pneumoniae, Vibrio cholerae. The resistome of the flooded sites contains 103 known resistant genes, of which 38% are plasmid-encoded, where most of them are known to be associated with pathogenic bacteria. Our results reveal an overall picture of the bacterial profile and resistome of sites following a devastating flood event, which might increase the levels of pathogens and its associated risks.

Protein misfolding and aggregation play a significant role in several neurodegenerative diseases. In the present work, the spontaneous aggregation of hen egg-white lysozyme (HEWL) in an alkaline pH 12.2 at an ambient temperature was studied to obtain molecular insights. The time-dependent changes in spectral peaks indicated the formation of β sheets and their effects on the backbone and amino acids during the aggregation process. Introducing iodoacetamide revealed the crucial role of intermolecular disulphide bonds amidst monomers in the aggregation process. These findings were corroborated by Molecular Dynamics (MD) simulations and protein-docking studies. MD simulations helped establish and visualize the unfolding of the proteins when exposed to an alkaline pH. Protein docking revealed a preferential dimer formation between the HEWL monomers at pH 12.2 compared with the neutral pH. The combination of Raman spectroscopy and MD simulations is a powerful tool to study protein aggregation mechanisms.