The unsafe disposal of hospital effluents contributes to gross contamination of water bodies with antibiotic residues, antibiotic resistance genes and antibiotic resistance bacteria. This study reports the microbial community profile of hospital wastes collected from various regions of West Bengal, India, using 16S rRNA gene amplicon sequencing. The data set Liquid Sludge (LS) contains 15,372,973 reads with an average length of 301 bps with average 52 ± 5% GC content. The data set Solid Sludge (SS) contains 16,071,594 reads with an average length of 301 bps with average 53 ± 4% GC content. Data of this study are available at NCBI BioProject (PRJNA360379). In sample LS, an abundance of 19.3% for the members of Bacteroidetes was observed. In sample SS, an abundance of 19.7% for the members of Euryarchaeota was observed.

Aims: This study aims at comparative identification of antibiotic resistance patterns in bacteria isolated from samples collected from rural environment (LS) and urban environments (SS). Metagenomic profiling gave us insights into the microbial abundance of the two samples. This study focused on culture-based methods for complete identification of antibiotic resistant isolates and estimation of comparative antibiotic resistance among the two samples. Study Design: Untreated medical waste and anthropogenic waste disposal can lead to the propagation of different antibiotic resistant strains in wastewater environments both in urban and rural set ups which provide an insight towards this study approach mentioned in the methodology segment. Place and Duration of Study: Sewer system of a medical facility located in Purulia, India was the collection site for liquid sludge. Solid sludge and associated wastewater were collected in vicinity of a large urban medical facility from central Kolkata, India. Methodology: Physico-chemical properties were analyzed followed by microbiological and biochemical characterization. The antibiotic resistance patterns were determined by Kirby-Bauer disc diffusion assay. Potent multidrug resistant isolates were identified using 16srRNA gene amplification followed by Phylogenetic profiling, using CLC Genomics workbench. Results: We observed maximum resistance in an E. coli isolate which was resistant up to 22 antibiotics. Combined data for resistance from urban and rural samples were found to exhibit 83.9% resistance to beta lactams, 85.7% to macrolides, 44.2% to fluoroquinolones, 50% to glycopeptides and cephalosporins, 35.7 % to carbapenems and sulfonamides, 28.5 % to tetracycline, and 23.8 % to aminoglycosides. Conclusion: The high prevalence of antibiotic-resistant bacteria harbouring diverse resistance traits across samples indicated towards probable horizontal gene transfer across environmental niches. This study can prove to be useful to understand and map the patterns of resistance and stringently apply the counter measures related to public health practices.

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Antibiotic-resistant bacteria (ARB) are becoming more prevalent in the environment and are efficiently disseminating through contaminated wastewater resulting in resistome cycling. This chapter compares the bacterial profile of hospital effluents collected from rural, urban, and delta regions of West Bengal, India. Comparative metagenomics analysis identified pathogenic bacterial genera like pseudomonas, escherichia, staphylococcus, lactobacillus, prevotella, acinetobacter across the samples. Delta sample showed highest abundance of pseudomonas whereas rural sample had lower titre of all the common bacterial genera. Urban sample reflected more diversity of different genera in terms of abundance. Pathogenic load prediction revealed significant occurrence of diarrhea, irritable bowel syndrome, liver cirrhosis, ulcerative colitis in the disease network. This chapter proposes a monitoring programme for assessing wastewater health using a combination of culture independent and culture-dependent molecular techniques in order to prevent the spread of pollutants in tropical environments.