Unveiling the ecological landscape of bacterial ß-lactam resistance in Delhi-national capital region, India: An emerging health concern.

Inappropriate antibiotic use not only amplifies the threat of antimicrobial resistance (AMR), moreover exacerbates the spread of resistant bacterial strains and genes in the environment, underscoring the critical need for effective research and interventions. Our aim is to assess the prevalence and resistance characteristics of ß-lactam resistant bacteria (BLRB) and ß-lactamase resistant bacterial genes (BLRBGs) under various environmental conditions within Delhi NCR, India. Using a culture-dependent method, we isolated 130 BLRB from 75 different environmental samples, including lakes, ponds, the Yamuna River, agricultural soil, aquatic weeds, drains, dumping yards, STPs, and gaushalas. Tests for antibiotic susceptibility were conducted in addition to phenotypic and genotypic identification of BLs and integron genes. The water and sediment samples recorded an average bacterial abundance of 3.6 × 106 CFU/mL and an average ampicillin-resistant bacterial count of 2.2 × 106 CFU/mL, which can be considered a potent reservoir of BLRB and BLRBGs. The majority of the BLRB discovered are opportunistic pathogens from the Bacillus, Aeromonas, Pseudomonas, Enterobacter, Escherichia, and Klebsiella genera, with Multiple Antibiotic Resistance (MAR) index ≥0.2 against a wide variety of ß-lactams and ß-lactamase (BLs) inhibitor combinations. The antibiotic resistance pattern was similar in the case of bacteria isolated from STPs. Meanwhile, bacteria isolated from other sources were diverse in their antibiotic resistance profile. Interestingly, we discovered that 10 isolates of various origins produce both Extended Spectrum BLs and Metallo BLs, as well as found harboring blaTEM, blaCTX, blaOXA, blaSHV, int-1, and int-3 genes. Enterobacter cloacae (S50/A), a common nosocomial pathogen isolated from Yamuna River sediment samples at Nizamuddin point, possesses three BLRBGs (blaTEM, blaCTX, and blaOXA) and a MAR index of 1.0, which is a major cause for concern. Therefore, identifying the source, origin and dissemination of BLRB and BLRGs in the environment is of the utmost importance for designing effective mitigation approaches to reduce a load of antimicrobial resistance factors in the environmental settings.

Risk assessment of trace elements in vegetables grown in river Yamuna floodplain in Delhi.

Urban agriculture is common in fertile river floodplains of many developing countries. However, there is a risk of contamination in highly polluted regions. This study quantifies health risks associated with the consumption of vegetables grown in the floodplain of the urban river 'Yamuna' in the highly polluted yet data-scarce megacity Delhi, India. Six trace elements are analyzed in five kinds of vegetable samples. Soil samples from the cultivation area are also analyzed for elemental contamination. Ni, Mn, and Co are observed to be higher in leafy vegetables than others. Fruit and inflorescence vegetables are found to have higher concentrations of Cr, Pb, and Zn as compared to root vegetables. Transfer Factor indicates that Cr and Co have the highest and least mobility, respectively. Vegetable Pollution Index indicates that contamination levels follow as Cr > Ni > Pb > Zn. Higher Metal Pollution Index of leafy and inflorescence vegetables than root and fruit vegetables indicate that atmospheric deposition is the predominant source. Principal Component Analysis indicates that Pb and Cr have similar sources and patterns in accumulation. Among the analyzed vegetables, radish may pose a non-carcinogenic risk to the age group of 1-5 year. Carcinogenic risk is found to be potentially high due to Ni and Cr accumulation. Consumption of leafy vegetables was found to have relatively less risk than other vegetables due to lower Cr accumulation. Remediation of Cr and Ni in floodplain soil and regular monitoring of elemental contamination is a priority.

Ecological and human health risk from exposure to metal contaminated sediments in a subtropical river affected by anthropogenic activities: A case study from river Yamuna.

Heavy metal enrichment in river sediments poses a significant risk to human and aquatic health. The Yamuna River faces severe challenges due to untreated industrial and domestic wastewater discharge. The study evaluates sediment metal content, ecological and human health risks, and potential sources. Results showed Cd and Pb exhibited moderate to severe contamination and displayed ecological risk based on contamination factor, enrichment factor, and potential ecological risk. According to synergistic indices (pollution load index, PINemerow, toxic risk index, contamination security index, mean probable effects level quotients, and probability of toxicity), the sediment in the Yamuna River doesn't seem to have a risk or enrichment from combined metals. Cd and Pb mainly originate from anthropogenic sources. Hazard index (< 1) and carcinogenic risk (2.2 × 10-7 to 4.7 × 10-5) assessments suggest metal didn't pose any risk to humans exposed to sediment. The present study aids in developing pollution control strategies for the Yamuna River.

A comprehensive assessment of macro and microplastics from Rivers Ganga and Yamuna: Unveiling the seasonal, spatial and risk factors.

There have been growing apprehensions and concerns regarding the increasing presence of plastic pollutants in the holiest river of India, the Ganga, and its major tributary, Yamuna. In response to this issue, the current study aimed to conduct a comprehensive investigation of the seasonal and spatial distribution of macro to microplastics (MPs) in the surface water, water column, and sediments from the River Ganga and Yamuna. MP samples were collected from various points of these Rivers, including upstream, downstream, and drainage points around the vicinity of Haridwar, Agra, Prayagraj, and Patna cities. With a significant seasonal variation, the estimated MPs and plastic flux were higher during the wet season than during the dry season. MPs sized 300 µm-1 mm and fibre-shaped blue and black colored MPs were pre-dominant in both rivers. Polyacrylamide, polyamide, and polyvinyl chloride were the most ascertained polymers. MPs including hazardous polymers (hazard score >1000) may pose a risk to the population of Indo-Gangetic Plain via direct and indirect exposure to MPs. The information provided in this study could serve as a starting point for the action plan required by municipal corporations to mitigate plastic pollution and target the possible sources at each location.

Phosphorus distribution in the water and sediments of the Ganga and Yamuna Rivers, Uttar Pradesh, India: insights into pollution sources, bioavailability, and eutrophication implications.

River nutrient enrichment is a significant issue, and researchers worldwide are concerned about phosphorus. The physicochemical characteristics and phosphorus (P) fractions of 36 sediment and water samples from the Ganga (Kanpur, Prayagraj, Varanasi) and Yamuna (Mathura, Agra, Prayagraj) rivers were examined. Among the physicochemical parameters, pH exceeded the permissible limit in Ganga and Yamuna River water and sediment samples. Electrical conductivity (EC) and alkalinity were within the permissible limits, whereas total nitrogen (TN) exceeded the limit in Yamuna water. The analysis of phosphorus fractions indicated the dominance of inorganic phosphorus (IP) (76% in Ganga and 96% in Yamuna) over organic phosphorus in both rivers, suggesting the mineralization and microbial degradation as major processes responsible for transforming OP to IP. The positive correlation of pH with IP, AP (apatite phosphorus), and NAIP (non-apatite inorganic phosphorus) explains the release of inorganic phosphorus under alkaline conditions. The correlation between total organic carbon (TOC), TN, and organic phosphorus (OP) indicated the organic load in the rivers from allochthonous and autochthonous sources. Phosphorus released from river sediments and the concentration of phosphate in overlying river water show a positive correlation, suggesting that river sediments may serve as phosphorus reservoirs. The average phosphorus pollution index (PPI) was above one in both rivers, with relatively higher PPI values observed in the Yamuna River, indicating the contamination of sediment with phosphorus, indicating the contamination of sediment with phosphorus. This study revealed variations in the P fractionation of the sediment in both rivers, primarily as a result of contributions from different P sources. This information will be useful for applying different mitigation techniques to lower the phosphorus load in both river systems.

Metagenomics analysis of water samples collected from the Yamuna River of Agra city, India.

Yamuna River water in Agra city of India is contaminated with toxic pollutants, including heavy metals that cause damage to the environment and human health. At present, the direct use of river water for drinking purposes and household activities lead to the direct exposure of society to the contaminants. In this study, Yamuna River water samples were collected from three different sites in Agra city during the monsoon, summer, and winter seasons. The physico-chemical parameters were estimated along with heavy metals. In physico-chemical parameter, the values found were mostly above the permissible limits. The results water samples contain high levels of cadmium, chromium, lead, and nickel above the desirable levels in most cases. The metagenomic analysis revealed that Proteobacteria, Bacteroidetes, Verrucomicrobia, Actinobacteria, and Planctobacteria were the most abundant phyla with a relative abundance of 61%, 9.34%, 5.23%, 4.64%, and 4.3%, respectively. The Comamonadaceae, the most abundant family consists of the genera involved in hydrogen oxidation, iron reduction, degraders of polycyclic aromatic hydrocarbons, and fermentation. The presence of Pseudomonas, Nitrosomonas sp., Thauera humireducens and Dechloromonas denitrificans (decomposition of sewage and organic matter) and Pseudomonas aeruginosa indicates the presence of heavy metal degrading bacteria in water sample. Functional prediction showed the presence of genes responsible for different metabolic pathways that could help developing new bioremediation strategies. The study concludes the status of water contamination, the presence of complex microbial community and suggests the futuristic use and their role in bioremediation.

Environmental health risk assessment and source apportion of heavy metals using chemometrics and pollution indices in the upper Yamuna river basin, India.

River Yamuna is the largest tributary of the Ganges with great economic importance, and provides water for about 57 million people and accounts for more than 70% of Delhi's water supply. Various pollution indices and chemometric methods were used to investigate heavy metal pollution, associated risks, and probable sources in the upper Yamuna river water. A total of 56 river water samples, 28 each in pre and post-monsoon season were collected and analysed for 15 heavy metals. The findings reveal that Al (38.66 ± 21.14 µg/L), As (16.52 ± 15.81 µg/L), and Mn (41.06 ± 89.25 µg/L) in pre-monsoon and Al (45.77 ± 29.46 µg/L), As (10.30 ± 12.15 µg/L), Fe (48.03 ± 81.11 µg/L), and Mn (31.02 ± 70.13 µg/L) in post-monsoon exceeded the Bureau of Indian Standards (BIS) acceptable limits. The pollution indices (HPI, NPI, HEI, and Cd) indicate that most locations are low to moderately polluted, except for the lower catchment. Health indices, i.e., hazard Index (HI) and incremental lifetime cancer risk (ILCR), suggest that the prolonged consumption of river water may cause potential human health hazards. In contrast, the water is suitable for domestic and other uses as the dermal risk is less prominent. The ecological risk index (ERI) of pre (0.22-58.75) and post-monsoon (0.12-44.21) were in the low-risk category (<110), indicating no ecological risk associated with heavy metals. In pre and post-monsoon, four principal components (PCs) described 73.97% and 76.18% of the total variance respectively, suggesting the mixed impact of numerous geogenic and anthropogenic sources in the region's water chemistry. Cluster analysis demonstrates that the lower catchment samples (National Capital Region, Delhi) significantly vary from each other due to wastewater discharge, industrialisation, and rapid urbanization, while the upper and mid-catchment samples are less distinct. Hence, more than 90% of the Yamuna water is extracted from the upper region; present findings may aid in developing an effective catchment scale management strategy.

Groundwater potential mapping in Trans Yamuna Region, Prayagraj, using combination of geospatial technologies and AHP method.

In this study, the combination of Remote Sensing and Geographic Information System (GIS) was utilized to identify the Groundwater Potential Zones (GPZs) of the Trans-Yamuna region. The Groundwater Potential Zones (GPZ) were mapped by integrating drainage density, slope, geology, geomorphology, NDVI, lineament density, rainfall, soil types, land use & land cover, and topographic wetness index maps. For the prediction output to have a non-trivial degree of accuracy, multicollinearity tests were run before integrating the layers. Using the Analytical Hierarchy Process (AHP), groundwater recharge-affecting parameters and classes of each parameter were scored. All thematic layers were integrated using weighted linear combination on a GIS platform to create a groundwater potential zone map. The outcomes of the model indicate that the research region exhibits three distinct groundwater potential zones, namely low (11.928%; 354.884 km2), moderate (76.44%; 2274.4 km2), and high (11.267%; 345.943 km2), in sequential sequence. These categories define the model's output in descending order of how closely it matches the actual conditions. After that, a map removal sensitivity analysis was also executed and found that geology, geomorphology, lineament density and drainage density strongly influence the prediction model for groundwater potential zone identification. The reliability of the results is established by employing a Receiver Operating Characteristic (ROC) curve for evaluation, which demonstrates a prediction accuracy of 81.3%. Authorities responsible for groundwater resource management can use this study's findings to better inform future regulatory initiatives.

Perspective: The unexplored dimensions behind the foam formation in River Yamuna, India.

For nearly two years, a persistent foam cover has been observed during the post-monsoon season in the Yamuna River beneath the barrage near Okhla in Delhi, India. This affair has been a matter of public concern now, after the gigantic appearance of foam in November 2021, as the visibility of foam has awakened people's environmental 'conscience' over the 'concealed' chemical pollution. The mechanisms of agents responsible for foaming in rivers, particularly surfactants and phosphates, have received wide attention in the dynamic community of river pollution. Many studies in the past, around the globe, have evidently provided different rationales behind the dense foam formation in rivers, yet the Concerned Govt. Authorities have highlighted the cause of foam formation in the river Yamuna is associated with the presence of detergents and phosphates as foaming agents. Despite this, an aperture with copious unaccounted factors or underlying agents still exists to rationalize the foam formation and persistence. In this article, we outline these unaccounted factors which might be responsible for the foam formation and stabilization and give indications for future research directives towards the emergence of studies regarding the dense foam formation in river Yamuna.

Spatio-temporal investigation of physico-chemical water quality parameters based on comparative assessment of QUAL 2Kw and WASP model for the upper reaches of Yamuna River stretching from Paonta Sahib, Sirmaur district to Cullackpur, North Delhi districts of North India.

An accurate investigation of bio-physical and chemical parameters as proxy of in situ water quality conditions in the Himalayan region is highly challenging owing to cumbersome, strenuous, and physically exhausting sampling exercises at high altitude locations. The upper stretches of Yamuna River in the Himachal Pradesh are typical examples of such sampling locations that have rarely been examined in the past studies. A widely accepted and recognized QUAL 2Kw model is applied for estimating the water quality parameters on the upper segment of the Yamuna River from Paonta Sahib to Cullackpur. These water quality indicators mainly included electric conductivity, pH, dissolved oxygen, temperature, carbonaceous biological oxygen demand (CBOD), inorganic suspended solids, total nitrogen, total phosphorus, and alkalinity, which were systematically investigated for predicting the spatio-temporal trends during the year 2018. A total of 12 distantly located river sites were identified for sample collection and data validation using QUAL 2Kw model. The present investigation attempts to reveal long-term degraded impact of untreated wastewater and biased agricultural practices on the water quality conditions over the upper stretches of Yamuna River. The QUAL 2Kw-derived values for selected variables were inter-compared with in situ values, and any deviation from measured values was ascertained based on meaningful statistical measures. The lower error of RMSE, MRE, and BIAS, corresponding to < 15%, ± 10%., ± 20%, and ~ 1 slope evidently indicated better matchup of values, wherein, higher slope correlation coefficient (R2) of ~ 90% indicated the robust performance of the QUAL 2Kw algorithm in accurately predicting the chosen variables. A comparative assessment of QUAL 2Kw and WASP has been performed to justify aptness of water quality model in scenarios of lean flow.

Prevalence of organic micropollutants in the Yamuna River, Delhi, India: seasonal variations and governing factors.

This work primarily emphases on evaluating the prevalence of organic micropollutants (OMPs) in the perennial Yamuna River (YR) that flow through the national capital of India, Delhi. Sixteen sampling campaigns (non-monsoon, n = 9; monsoon n = 7) were organized to understand the seasonal variations with special emphasis on monsoon. We have found fifty-five OMPs in the monsoon; while forty-seven were detected in non-monsoon. Fifty-seven screened and quantified OMPs in the most polluted stretch of River Yamuna included the pharmaceutically active compounds, pesticides, endocrine-disrupting chemicals, phthalates, personal care products, fatty acids, food additives, hormones, and trace organics present in hospital wastes. During monsoon months, compounds for which concentrations exceeded 50 µg/L were: adenine (64.6 µg/L), diethyl phthalate (62.9 µg/L), and octamethyltrisiloxane (56.9 µg/L); and the same for non-monsoon months was only for 1-dodecanethiol (52.3 µg/L). The average concentration of OMPs in non-monsoon months indicate PhACs>PCPs>Pesticides>Fatty acids>Hospital waste>Hormones>Pesticides>EDCs. In monsoon months due to surface runoff and high volume of untreated wastewater discharges few more OMPs concentrations were detected which mainly includes PhACs (clofibric acid, diclofenac sodium, gemfibrozil, ketoprofen), pesticides (aldrin, metribuzin, atrazine, simazine). Due to dilution effect in the monsoon months, average concentrations of 3-acetamido-5-bromobenzoic acid (PhACs) was reduced from 45.22 µg/L to 14.07 µg/L, whereas some EDCs such as 2,4- Di-tert-amylphenol, 3,5- di-tert-butyl-4-hydroxybenzyl alcohol, Triphenylphosphine oxide, Benzophenone were found in much higher concentrations in the monsoon months. Octamethyltrisiloxane (PCPs) was detected 50 times higher in concentration in the monsoon months. Interestingly, the concentration of about 50 % of the OMPs was more in the monsoon samples than in non-monsoon samples which is contrary to the general understanding that monsoon-induced dilution lowers the concentrations of OMPs. In RY water higher magnitude of diclofenac sodium, ibuprofen, ketoprofen, and clofibric acid was found than Europe and North America rivers. Hormones such as estriol and estrone in RY water are found 70 to 100 times higher than the maximum reported concentrations in the US streams. Finally, various OMPs responded differently to the monsoon season as evident from multivariate analyses.

Degradation effectiveness of hexachlorohexane (ϒ-HCH) by bacterial isolate Bacillus cereus SJPS-2, its gene annotation for bioremediation and comparison with Pseudomonas putida KT2440.

The contamination of Hexachlorohexane (Lindane) in soil and water has toxic effects due to its persistent nature. In our study, an indigenous HCH (gamma isomer) degrading bacterium viz Bacillus cereus SJPS-2 was isolated from Yamuna river water using enrichment culture method. The growth curve indicated that Bacillus cereus SJPS-2 was able to degrade ϒ-HCH effectively with 80.98% degradation. Further, process was improved by using immobilization using alginate beads which showed enhanced degradation (89.34%). Interestingly, in presence of fructose, the ϒ-HCH degradation was up to 79.24% with exponential growth curve whereas the degradation was only 5.61% in presence of glucose revealing diauxic growth curve. Furthermore, The FTIR results confirmed the potential lindane degradation capability of Bacillus cereus SJPS-2 and the bonds were recorded at wavelengths viz. 2900-2500 cm-1, 3300-2800 cm-1 and 785-540 cm-1. Similarity, the GC studies also reconfirmed the degradation potential with retention time (RT) of ethyl acetate and lindane was 2.12 and 11.0 respectively. Further, we studied the metabolic pathway involved for lindane utilization in Bacillus cereus using KEGG-KASS and functional gene annotation through Rapid Annotation using Subsystems Technology (RAST) resulted in the annotation of the lin genes (lin A, lin B, lin C, lin X, lin D, lin E) and respective encoding enzymes. The comparative ϒ-HCH degradation potential of B. cereus and P. putida KT2440 was also evaluated. The island viewer showed the different colors on circular genome indicate the coordinates of genomic islands resulted with some common genomic islands (GEIs) between both bacteria indicating the possibility of horizontal gene transfer at contaminated site or natural environment. These genomic islands (GEIs) contribute in the rearrangement genetic material or to evolve bacteria in stress conditions, as a result the metabolic pathways evolve by formation of catabolic genes. This study establishes the potential of Bacillus cereus SJPS-2 for effectual ϒ-HCH degradation.

Taxonomic and genomic characterization of Sporosarcina cyprini sp. nov., moderately tolerant of Cr+6 and Cd+2 isolated from the gut of invasive fish Cyprinus carpio var. communis (Linn., 1758).

A Gram-stain-positive, motile, and rod-shaped bacterium, designated as strain MB25T, was isolated from the gut of Cyprinus carpio from the highly polluted river Yamuna, India. Phylogenetic analysis based on 16S rRNA gene sequence revealed that strain MB25T belonged to the genus Sporosarcina, sharing the highest sequence similarity with S. luteola Y1T (98.98%) and S. koreensis S-K12T (98.91%). Digital DNA-DNA hybridization and average nucleotide identity values of strain MB25T with strain Y1T and S-K12T were 18.9, 77.69, and 18.2, 76.80 respectively. Genome analysis of strain MB25T revealed its biotechnological properties such as tolerance to potent heavy metals, genes for the production of carbohydrate-active enzymes, antimicrobial compounds, and also degradation of aromatic compounds. The G + C content of strain MB25T genome was 45%. Growth observed at 10-40 °C (optimum, 28-30 °C), pH 6.0-8.5 (optimum pH 7.5-8.0); NaCl concentrations up to 6.0% (w/v). The dominant respiratory quinone was MK-7, cell wall peptidoglycan is of the A-4 type containing amino acids Lys-Glu and the major fatty acids are anteiso-C11:0 and iso-C15: 0. The major polar lipids of strain MB25T are diphosphatidylglycerol, phosphatidylglycerol, and phosphatidylethanolamine. On the basis of phenotypic, chemotaxonomic, phylogenetic, and phylogenomic data, strain MB25T represents a novel species of the genus Sporosarcina, for which the name Sporosarcina cyprini sp. nov. is proposed. The type strain is MB25T (= MCC 4366 T = JCM 34521 T = CCM 9113 T).

Metagenomic insights to understand the role of polluted river Yamuna in shaping the gut microbial communities of two invasive fish species.

The gastrointestinal microbial community plays a crucial role in host health, immunity, protection, development and provides nutrients to the host. The rising human-induced pollution and heavy metal contamination in all aquatic systems globally has led us to explore the gut microbial diversity of two exotic invasive fish Cyprinus carpio (Linnaeus, 1858) and Oreochromis niloticus (Linnaeus,1857) from river Yamuna, India. These fishes are aquatic bioindicators with high demographic resilience. Exploring these associations would pave the way for addressing problems that inhabitant fishes are facing due to the increasing pollution load in the River Yamuna. Based on 16S rRNA gene amplicon sequencing, our results deliver comparative information on the gut microbiome of these fishes and highlight connotations between the microbiome of gut and water samples. The gut of C. carpio and O. niloticus was dominated by phyla Proteobacteria whereas Bacteroidetes dominated the water sample. Microbial communities showed predicted roles such as pathogenicity (Escherichia-Shigella, Aeromonas veronii, Vibrio cholerae, Streptococcus iniae, Flavobacterium columnare, Klebsiella pneumoniae, Mycobacterium sp.), probiotic applications (Bacillus velezensis, Lactobacillus plantarum, Enterococcus faecalis, Bifidobacterium longum, Lactococcus lactis, Leuconostoc falkenbergense) and involvement in sewage and organic matter decomposition (Nitrosomonas sp., Methanosaeta harundinacea, Dechloromonas agitata, Thauera humireducens, Zoogloea ramigera). Heavy metal degrading members (Leucobacter chromiireducens, Pseudomonas fluorescens, P. aeruginosa, Klebsiella pneumoniae, and Micrococcus luteus) were detected in gut microbiome samples thus supporting the notion that fish shapes its gut microbiota with changing ecology. Functional profiling showed that microbial communities are specialized in metabolic functions thus reflecting the dietary profile of these invasive fishes.

The plight of Najafgarh drain in NCT of Delhi, India: assessment of the sources, statistical water quality evaluation, and fate of water pollutants.

The Najafgarh drain is the first major drain that joins the Yamuna River at Wazirabad in Delhi, India, and is known to contribute to the maximum pollution load to this river. The drain is originally an extension of the Sahibi River and was intentionally constructed as a canal to carry stormwater, but presently, it is carrying more of sewage, agricultural, and industrial effluents received through various small and large secondary drains. The present study has analyzed the water quality status of this interconnected system, i.e., the Najafgarh drain, its associated secondary drains, and the Yamuna River for physicochemical parameters (n = 16), microbiological parameter (n = 1), and heavy metal concentrations (n = 8). The analysis of the surface water samples collected during pre- and post-monsoon seasons showed that secondary drain discharges significantly impacted the water quality of the Najafgarh drain, which in turn affected the Yamuna River. Out of the eight selected secondary drains for this study, the Goyla dairy outlet came out as the most polluted site in terms of organic pollutants while the Basaidarapur drain was loaded with heavy metal contaminants. Statistical tools comprising hierarchical cluster analysis (HCA), Pearson's correlation, and principal component analysis (PCA) were further implemented on the water quality dataset for a better understanding of the possible sources of contamination for organic and inorganic pollutants in the selected sampling sites. The present study, thus, might help in providing key highlights to the policymakers for effective regulation and management of the point source discharges in Najafgarh drain, which will ultimately restrict its pollution loadings in Yamuna River, Delhi, and also help in the restoration of this important water body.

Metagenomic mining of Indian river confluence reveal functional microbial community with lignocelluloytic potential.

Microbial carbohydrate-active enzymes (CAZyme) can be harnessed for valorization of Lignocellulosic biomass (LCB) to value-added chemicals/products. The two Indian Rivers Ganges and the Yamuna having different origins and flow, face accumulation of carbon-rich substrates due to the discharge of wastewater from adjoining paper and pulp industries, which could potentially contribute to the natural enrichment of LCB utilizing genes, especially at their confluence. We analyzed CAZyme diversity in metagenomic datasets across the sacred confluence of the Rivers Ganges and Yamuna. Functional annotation using CAZyme database identified a total of 77,815 putative genes with functional domains involved in the catalysis of carbohydrate degradation or synthesis of glycosidic bonds. The metagenomic analysis detected ~ 41% CAZymes catalyzing the hydrolysis of lignocellulosic biomass polymers- cellulose, hemicellulose, lignin, and pectin. The Beta diversity analysis suggested higher CAZyme diversity at downstream region of the river confluence, which could be useful niche for culture-based studies. Taxonomic origin for CAZymes revealed the predominance of bacteria (97%), followed by archaea (1.67%), Eukaryota (0.63%), and viruses (0.7%). Metagenome guided CAZyme diversity of the microflora spanning across the confluence of Ganges-Yamuna River, could be harnessed for biomass and bioenergy applications. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-022-03190-7.

Community structure and function of microbiomes in polluted stretches of river Yamuna in New Delhi, India, using shotgun metagenomics.

The large population residing in the northern region of India surrounding Delhi mostly depends on water of River Yamuna, a tributary of mighty Ganga for agriculture, drinking and various religious activities. However, continuous anthropogenic activities mostly due to pollution mediated by rapid urbanization and industrialization have profoundly affected river microflora and their function thus its health. In this study, potential of whole-genome metagenomics was exploited to unravel the novel consortia of microbiome and their functional potential in the polluted sediments of the river at Delhi. Analysis of high-quality metagenome data from Illumina NextSeq500 revealed substantial differences in composition of microbiota at different sites dominated by Proteobacteria, Bacteroidetes, Firmicutes, Actinobacteria and Chloroflexi phyla. The presence of highly dominant anaerobic bacteria like Dechloromonas aromatica (benzene reducing and denitrifying), Rhodopseudomonas palustris (organic matter reducing), Syntrophus aciditrophicus (fatty acid reducing) and Syntrophobacter fumaroxidans (sulphate reducing) in the polluted river Yamuna signifies the impact of unchecked pollution in declining health of the river ecosystem. A decline in abundance of phages was also noticed along the downstream river Yamuna. Mining of mycobiome reads uncovered plethora of fungal communities (i.e. Nakaseomyces, Aspergillus, Schizosaccharomyces and Lodderomyces) in the polluted stretches due to the availability of higher organic carbon and total nitrogen (%) could be decoded as promising bioindicators of river trophic status. Pathway analysis through KEGG revealed higher abundance of genes involved in energy metabolism (nitrogen and sulphur), methane metabolism, degradation of xenobiotics (Nitrotoluene, Benzoate and Atrazine), two-component system (atoB, cusA and silA) and membrane transport (ABC transporters). Catalase-peroxidase and 4-hydroxybenzoate 3-monooxygenase were the most enriched pollution degrading enzymes in the polluted study sites of river Yamuna. Overall, our results provide crucial insights into microbial dynamics and their function in response to high pollution and could be insightful to the ongoing remediation strategies to clean river Yamuna.

Impact of COVID-19 on Water Quality Index of river Yamuna in Himalayan and upper segment: analysis of monsoon and post-monsoon season.

Rivers are the lifeline of every living being, be it humans or animals. Clean water is essential for everyone. However, increased urbanization and rapid industrialization have led to rising pollution level in rivers. COVID-19 on the contrary has changed the entire ecosystem. Limited industrial activities, reduced people movement during COVID times has led to improvement in environment, be it atmosphere or hydrosphere. Present work aims to study the impact of COVID-19 on water quality index of river Yamuna as it traverses from Himalayan segment to Upper segment. Five sites are chosen between a stretch of 60+ km, and samples are collected during monsoon and post-monsoon seasons. Physico-chemical parameters (pH, Turbidity, Sulphate, Phosphate, Fluoride, Chloride, Total Hardness, Calcium, Magnesium, Dissolved Oxygen, BOD, COD, Alkalinity), water quality index and Pearson correlation coefficient were calculated for all chosen sites. Since the study was initiated during COVID, initial results show the impact of reduced industrial and urban activities in improving the overall water quality.

Water quality assessment of a river using deep learning Bi-LSTM methodology: forecasting and validation.

Water is a prime necessity for the survival and sustenance of all living beings. Over the past few years, the water quality of rivers is adversely affected due to harmful wastes and pollutants. This ever-increasing water pollution is a big matter of concern as it deteriorating the water quality, making it unfit for any type of use. Recently, water quality modelling using machine learning techniques has generated a lot of interest and can be very beneficial in ecological and water resources management. However, they suffer many times from high computational complexity and high prediction error. The good performance of a deep neural network like long short-term memory network (LSTM) has been exploited for the time-series data. In this paper, a deep learning-based Bi-LSTM model (DLBL-WQA) is introduced to forecast the water quality factors of Yamuna River, India. The existing schemes do not perform missing value imputation and focus only on the learning process without including a loss function pertaining to training error. The proposed model shows a novel scheme which includes missing value imputation in the first phase, the second phase generates the feature maps from the given input data, the third phase includes a Bi-LSTM architecture to improve the learning process, and finally, an optimized loss function is applied to reduce the training error. Thus, the proposed model improves forecasting accuracy. Data comprising monthly samples of different water quality factors were collected for 6 years (2013-2019) at several locations in the Delhi region. Experimental results reveal that predicted values of the model and the actual values were in a close agreement and could reveal a future trend. The performance of our model was compared with various state of the art techniques like SVR, random forest, artificial neural network, LSTM, and CNN-LSTM. To check the accuracy, metrics like root mean square errors (RMSE), the mean absolute error (MAE), mean square error (MSE), and mean absolute percentage error (MAPE) have been used. Experimental analysis is carried out by measuring the COD and BOD levels. COD analysis reveals the MSE, RMSE, MAE, and MAPE values as 0.015, 0.117, 0.115, and 20.32, respectively, for the Palla region. Similarly, BOD analysis indicates the MSE, RMSE, MAE, and MAPE values as 0.107, 0.108, 0.124, and 18.22, respectively. A comparative analysis reveals that the proposed model outperforms all other models in terms of the best forecasting accuracy and lowest error rates.

Assessment of toxicity and potential health risk from persistent pesticides and heavy metals along the Delhi stretch of river Yamuna.

The present study aims at the assessment of environmental quality of the most polluted stretch of river Yamuna along the megacity of Delhi. The study was conducted in order to examine toxicity and health hazards associated with persistent pollutants present in the fluvial ecosystem. Eighty four sediment and 56 vegetable samples from same locations were collected from the Delhi segment of river Yamuna flood plain in order to examine 20 organochlorine pesticides (OCPs) and 9 heavy metals (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn). Both the organic and inorganic groups of persistent toxic substances were monitored and analysed for the extent of eco-toxicological as well as dietary health risks posed to the local population. Eco-toxicological assessment was done based on sediment quality guidelines, enrichment factor, geo-accumulation index, degree of contamination and Pollution Load Index. The dietary-risk was assessed with the help of translocation factors (TF) of these pollutants in vegetables. Carcinogenic and non-carcinogenic health risks from consumption of vegetables were also investigated. The level of concern for heavy metals was greater than that of OCPs as per the sediment quality guidelines. DDT, Cd, Pb and Zn had maximum concentrations corresponding to level 3 of concern, while Cr and Ni reached up to the highest i.e., 4th level of concern. Sediment samples were found to be enriched and contaminated significantly with Cd and moderately with Pb, as represented respectively by enrichment factors and contamination factors (CF). CF for metals lied in order Zn > Cd > CrNi > PbCu. Pollution load index was highest at the location lying on the exit point of Yamuna in Delhi. TF values greater than 1 were observed in majority of samples analysed for Ni, Cr, Cu and Zn. Spinach topped among vegetables in terms of metal contamination. Cd, Ni and Pb accumulated more in the roots, as against Mn, Zn, Cu and Cr which had higher accumulation in the shoots. Translocation factors were substantially high in vegetables for most of the OCPs, clearly indicating bioaccumulation and potential health risk to the consumers. Health risk to humans was assessed for non-carcinogenic and carcinogenic potentials from ingestion of vegetables. Hazard Quotient (HQ) > 1 due to radish (roots and leaves) and cauliflower consumption in children indicated non-carcinogenic risk. Hazard Index (HI) beyond 1 for all the vegetables (except onion leaves) confirmed substantial cumulative risk. Lifetime cancer risk (LCR) revealed moderate (spinach, radish, beet root and cauliflower) to low (all the others) levels of carcinogenic risk to humans. Cancer risks from γ-HCH, ß- HCH, Hept, Hept Ep, Ald, p,p'-DDT, and Cr exposure through the food chain could be well established.