Publications by authors named "Narendrakumar M Chaudhari"

Heavy precipitation, drought, and other hydroclimatic extremes occur more frequently than in the past climate reference period (1961-1990). Given their strong effect on groundwater recharge dynamics, these phenomena increase the vulnerability of groundwater quantity and quality. Over the course of the past decade, we have documented changes in the composition of dissolved organic matter in groundwater.

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More than 90% of earth's microbial biomass resides in the continental subsurface, where sedimentary rocks provide the largest source of organic carbon (C). While many studies indicate microbial utilization of fossil C sources, the extent to which rock-organic C is driving microbial activities in aquifers remains largely unknown. Here we incubated oxic and anoxic groundwater with crushed carbonate rocks from the host aquifer and an outcrop rock of the unsaturated zone characterized by higher organic C content, and compared the natural abundance of radiocarbon (C) of available C pools and microbial biomarkers.

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Background: To better understand the influence of habitat on the genetic content of bacteria, with a focus on members of Candidate Phyla Radiation (CPR) bacteria, we studied the effects of transitioning from soil via seepage waters to groundwater on genomic composition of ultra-small Parcubacteria, the dominating CPR class in seepage waters, using genome resolved metagenomics.

Results: Bacterial metagenome-assembled genomes (MAGs), (318 total, 32 of Parcubacteria) were generated from seepage waters and compared directly to groundwater counterparts. The estimated average genome sizes of members of major phyla Proteobacteria, Bacteroidota and Cand.

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The measurement of uncharacterized pools of biological molecules through techniques such as metabarcoding, metagenomics, metatranscriptomics, metabolomics, and metaproteomics produces large, multivariate datasets. Analyses of these datasets have successfully been borrowed from community ecology to characterize the molecular diversity of samples (ɑ-diversity) and to assess how these profiles change in response to experimental treatments or across gradients (β-diversity). However, sample preparation and data collection methods generate biases and noise which confound molecular diversity estimates and require special attention.

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Background: The highly diverse Cand. Patescibacteria are predicted to have minimal biosynthetic and metabolic pathways, which hinders understanding of how their populations differentiate in response to environmental drivers or host organisms. Their mechanisms employed to cope with oxidative stress are largely unknown.

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family, comprising diverse thermoacidophilic and aerobic sulfur-metabolizing Archaea from various geographical locations, offers an ideal opportunity to infer the evolutionary dynamics across the members of this family. Comparative pan-genomics coupled with evolutionary analyses has revealed asymmetric genome evolution within the family. The trend of genome streamlining followed by periods of differential gene gains resulted in an overall genome expansion in some species of this family, whereas there was reduction in others.

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Genome and transcriptome sequencing data are extremely useful resources for researchers in carrying out biological experiments that involves cloning and characterizing genes. We are presenting here genome sequence data from different clades of life including photosynthetic prokaryotes; oomycetes pathogens; probiotic bacteria; endophytic yeasts and filamentous fungus and pathogenic protozoa . In addition, we are also presenting paired control and treated stress response transcriptomes of Cyanobacteria growing in extreme conditions.

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Next generation sequencing techniques produce enormous data but its analysis and visualization remains a big challenge. To address this, we have developed Genome Annotator Light(GAL), a Docker based package for genome analysis and data visualization. GAL integrated several existing tools and in-house programs inside a Docker Container for systematic analysis and visualization of genomes through web browser.

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The conglomerate of microorganisms inhabiting various body-sites of human, known as the human microbiome, is one of the key determinants of human health and disease. Comprehensive pan-genomic and functional analysis approach for human microbiome components can enrich our understanding about impact of microbiome on human health. By utilizing this approach we developed PanGFR-HM (http://www.

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Recent advances in ultra-high-throughput sequencing technology and metagenomics have led to a paradigm shift in microbial genomics from few genome comparisons to large-scale pan-genome studies at different scales of phylogenetic resolution. Pan-genome studies provide a framework for estimating the genomic diversity of the dataset, determining core (conserved), accessory (dispensable) and unique (strain-specific) gene pool of a species, tracing horizontal gene-flux across strains and providing insight into species evolution. The existing pan genome software tools suffer from various limitations like limited datasets, difficult installation/requirements, inadequate functional features etc.

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Background: The community composition of the human microbiome is known to vary at distinct anatomical niches. But little is known about the nature of variations, if any, at the genome/sub-genome levels of a specific microbial community across different niches. The present report aims to explore, as a case study, the variations in gene repertoire of 28 Prevotella reference genomes derived from different body-sites of human, as reported earlier by the Human Microbiome Consortium.

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