Multilocus sequence typing of Ochrobactrum spp. isolated from gastric niche - Kulkarni, Girish (Journal of Infection and Public Health, 2017)
The human stomach is colonized by diverse bacterial species. The presence of non-Helicobacter pylori bacteria in urease-positive biopsies of individuals has been reported. Bacteria belonging to the Ochrobactrum genus have been documented in the human gastric niche. The co-occurrence of Ochrobactrum spp. with H. pylori was previously reported in an antral biopsy of a non-ulcer dyspeptic (NUD) subject from Northern India. There is no information on the genetic diversity of Ochrobactrum spp. isolated from the gastric niche in the stomach. We aimed to study the species distribution and diversity of Ochrobactrum spp. with and without H. pylori in urease-positive biopsies across three different geographical regions in India. Sixty-two Ochrobactrum isolates recovered from patients with an upper gastric disorder (n=218) were subjected to molecular identification and multilocus sequence typing. H. pylori DNA was found in the majority of biopsies, which had a variable degree of Ochrobactrum spp present. Interestingly, some of the urease-positive biopsies only had Ochrobactrum without any H. pylori DNA. Based on phylogenetic analysis, the Ochrobactrum isolates were distributed into the O. intermedium, O. anthropi and O. oryzae groups. This indicates there are multiple species in the gastric niche irrespective of the presence or absence of H. pylori. Antibiotyping based on colistin and polymyxin B could differentiate between O. intermedium and O. anthropi without revealing the resistance-driven diversity. Considering the prevalence of multiple Ochrobactrum spp. in the human gastric niche, it is important to evaluate the commensal and/or pathogenic nature of non-H. pylori bacteria with respect to their geographical distribution, lifestyle and nutrition needs.
Keywords: Helicobater Pyroli; MLST; Non-Ulcer Dyspepsia; Ochrobactrum

Mixed bacterial culture mediated direct conversion of bio-glycerol to diols - Parate, Roopa; Mane, Rasika; Dharne, Mahesh; Rode, Chandrashekhar (Bioresource Technology, 2018)
Direct and economic transformation of biodiesel derived crude glycerol is gaining more significance. During screening of bacterial cultures Klebsiella pneumoniae and Enterobacter aerogenes were able to convert crude bio-glycerol to 2,3-butanediol (2,3-BDO) and 1,3-propanediol (1,3-PDO), as major compounds, ethanol and acetoin as minor compounds, with a conversion of 69% and 79% respectively. Process optimization could achieve maximum conversion at pH 7.0, 37 degrees C, 30-40 g/L glycerol and 1.5 g of inoculum until 120 h. Mixed cultures led to complete glycerol conversion with optimal yield and productivity. An innovative approach of using crude glycerol for sustained growth and tolerance of bacteria as source of carbon and energy makes this study more significant. In addition to this, a mixed culture concept introduced here is expected to make impact in process economics for industrial scale synthesis for direct transformation of glycerol into C3 and specifically, C4 diols.
Keywords: 1; 2; 3-Butanediol; 3-Propanediol; Bioconversion; Bioglycerol; Mixed culture

Metagenome sequencing to unveil microbial community composition and prevalence of antibiotic and metal resistance genes in hypersaline and hyperalkaline Lonar Lake, India - Chakraborty, Jaya; Sapkale, Vibhavari; Shah, Manan; Rajput, Vinay; Mehetre, Gajanan; Agawane, Sachin; Kamble, Sanjay; Dharne, Mahesh (Ecological Indicators, 2020)
Lonar Lake (India) is a hyperalkaline and hypersaline soda lake encompassing unique microbial composition and functions. This ecosystem has not been explored for taxonomic diversity and functional aspects (with emphasis on antibiotic and metal resistance genes) using whole metagenome sequencing for multiple years. Bacterial diversity analysis during year 2013, 2016, and 2018 depicted differences in the dominance of Proteobacteria, Firmicutes and Bacteroidetes. For archaeal diversity, a similar pattern persisted with higher abundance of Euryarchaeota. Functional metagenome analyses, indicated presence of antibiotic resistance gene (ARG) and metal resistance gene (MRG) profiles in the lake. A wider continuum of resistance genes with dominant ARG types as multidrug resistance efflux pumps and beta-lactams were also observed. The lake resistome demonstrated fluoroquinolone and acriflavine resistance genes indicating sewage water contamination in the lake. The MRGs linked with resistance to toxic metals (arsenic, cobalt, cadmium, copper, and zinc) and cation efflux protein CusA and cobalt-zinc-cadmium resistance protein revealed metal contamination. This study could be a baseline for understanding prevalence of antibiotic and metal resistance mechanisms resulting from various anthropogenic activities nearby lake, and find integrated approaches for conservation of the precious Lonar Lake ecosystem.
Keywords: Archaeal diversity; ARGs; Bacterial diversity; Illumina sequencing; Lonar lake; MRGs

Metagenomic analysis of a mega-city river network reveals microbial compositional heterogeneity among urban and peri-urban river stretch - Yadav, Rakeshkumar; Rajput, Vinay; Dharne, Mahesh (Science of the Total Environment, 2021)
The rivers in the megacities face a constant inflow of extremely polluted wastewaters from various sources, and their influence on the connected peri-urban river is still poorly understood. The riverine system in Pune consists of Rivers Mula, Ramnadi, Pawana, Mutha, and Mula-Mutha, traversing through the urban settlements of Pune before joining River Bhima in the peri-urban region. We used MinION-based metagenomic sequencing to generate a comprehensive understanding of the microbial diversity differ-ences between the urban and peri-urban zones, which has not been explored at the meta scale until date. The taxonomic analysis revealed significant enrichment of pollution indicators microbial taxa (Welsch's t-test, p < 0.05, Benjamini-Hochberg FDR test) such as Bacteriodetes, Firmicutes, Spirochaetes, Synergistetes, Euryarcheota in the urban waters as compared to peri-urban waters. Further, the peri-urban waters showed a significantly higher prevalence of ammonium oxidising archaeal groups such as Nitrososphaeraceae (Student's t-test p-value <0.05 with FDR correction), thereby probably suggesting the influence of agricultural runoffs. Besides, the microbial community diversity assessment also indicated the significant dissimilarity in the microbial community of urban and peri-urban waters. Overall, the analysis predicted 295 virulence genes mapping to 38 different path-ogenic bacteria in the riverine system. Moreover, the higher genome coverage (at least 60%) for priority patho-gens such as Pseudomonas, Klebsiella, Acinetobacter, Escherichia, Aeromonas in the sediment metagenome consolidates their dominance in this riverine system. To conclude, our investigation showed that the unre-strained anthropogenic and related activities could potentially contribute to the overall dismal conditions and in-fluence the connected riverine stretches on the outskirts of the city . (c) 2021 Elsevier B.V. All rights reserved.
Keywords: Industrialisation; Peri-urban; Riverine system; Urbanisation; Virulence factors

Machine learning-based approach to determine infection status in recipients of BBV152 (Covaxin) whole-virion inactivated SARS-CoV-2 vaccine for serological surveys - Singh, Prateek; Ujjainiya, Rajat; Prakash, Satyartha; Naushin, Salwa; Sardana, Viren; Bhatheja, Nitin; Singh, Ajay Pratap; Barman, Joydeb; Kumar, Kartik; Gayali, Saurabh; Khan, Raju; Rawat, Birendra Singh; et al. (Computers in Biology and Medicine, 2022)
Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the vaccine effectiveness. Asymptomatic breakthrough infections have been a major problem in assessing vaccine effectiveness in populations globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines since whole virion vaccines generate antibodies against all the viral proteins. Here, we show how a statistical and machine learning (ML) based approach can be used to discriminate between SARS-CoV-2 infection and immune response to an inactivated whole virion vaccine (BBV152, Covaxin). For this, we assessed serial data on antibodies against Spike and Nucleocapsid antigens, along with age, sex, number of doses taken, and days since last dose, for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, our ensemble ML model classified 724 to be infected. For method validation, we determined the relative ability of a random subset of samples to neutralize Delta versus wild-type strain using a surrogate neutralization assay. We worked on the premise that antibodies generated by a whole virion vaccine would neutralize wild type more efficiently than delta strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, neutralization against Delta strain was more effective, indicating infection. We found 71.8% subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%-80.2%) over the same period. Our approach will help in real-world vaccine effectiveness assessments where whole virion vaccines are commonly used.
Keywords: BBV152; Covaxin; COVID-19; Ensemble methods; Infection; machine learning; SARS-CoV-2

Metagenomic mining of Indian river confluence reveal functional microbial community with lignocelluloytic potential - Rajput, Vinay; Samson, Rachel; Yadav, Rakeshkumar; Dastager, Syed; Khairnar, Krishna; Dharne, Mahesh (3 Biotech, 2022)
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 similar to 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.
Keywords: CAZymes; Confluence (Sangam); Lignocellulosic; River Ganges; River Yamuna

Monitoring influenza A (H1N1, H3N2), RSV, and SARS-CoV-2 using wastewater-based epidemiology: A 2-year longitudinal study in an Indian megacity covering omicron and post-omicron phases - Pramanik, Rinka; Nannaware, Kiran; Malik, Vinita; Shah, Priyanki; Sangewar, Poornima; Gogate, Niharika; Shashidhara, L. S.; Boargaonkar, Radhika; Patil, Dhawal; Kale, Saurabh; Bhalerao, Asim; Jain, Nidhi; et al. (Food and Environmental Virology, 2025)
{The bourgeoning field of wastewater-based epidemiology (WBE) for the surveillance of several respiratory viruses which includes Influenza A, H1N1pdm09, H3N2, respiratory syncytial viruses (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of interest for public health concerns. However, there are few long-term monitoring studies globally. In this study, respiratory viruses were detected and quantified from 11 sewer sheds by utilizing reverse transcription-quantitative polymerase chain reaction analysis in Pune city, India, from Jan 2022 to Dec 2023. The RNA fragments of respiratory viruses were detected in sewage samples before clinical cases were reported, underscoring the potential of WBE for early detection and monitoring within the population. The Spearman correlation of wastewater viral copies was positively and significantly correlated with the clinically positive case of H1N1pdm09 (rho = 0.55
Keywords: Influenza A; Quantitative reverse transcription-PCR; Respiratory viruses; SARS-CoV-2; Wastewater-based epidemiology