Biology subjects

Shatadru, R. N.

Publications and source records attributed to Shatadru, R. N..

3 recordsLinked to original sources

bioRxiv2025

Virus community response rewires methane-suppressed peat microcosm carbon metabolism

Human activities are accelerating permafrost thaw and subsequent methane emissions from increased microbial activity, prompting microbiome engineering efforts as an emissions mitigation strategy. We recently demonstrated that catechin amendment could drastically reduce methane emissions (>80%) in peat microcosms by enriching catechin-degrading prokaryotes that outcompeted methanogens for hydrogen. However, viral contributions to such microbiome-level responses remain unexplored and we hypothesized that viral dynamics could help shape the microbiome response as nutrient amendments may alter cellular physiology in ways that could induce lytic viral activity. Here, we performed virus ecogenomics analyses of the previously-studied time-resolved multi-omics data collected from catechin-amended peat microcosms. We conservatively identified 900 putatively lytic viral operational taxonomic units (vOTUs), with 41% predicted to infect active host genomes including the most transcriptionally active vOTUs predicted to infect key catechin-degrading genera (Clostridium and undescribed Bacillota JAGFXR01). Notably, a single JAGFXR01-targeting vOTU dominating the viral response (>40% of community viral transcription; 20-156-fold more abundant than its host), which we interpreted as induction resulting in intense lytic activity that could release catechin-degradation intermediates to other community members. Consistent with this, gene expression analysis revealed elevated catechin-intermediate degradation and hydrogenase signals in 34 additional polyphenol-degrading metagenome-assembled genomes. These findings support a model consistent with a viral shunt-like process that extends our previous prokaryote-centric model: viral lysis of fast-growing catechin degraders redistributes phenolic intermediates to diverse phenol-degrading taxa that sustain methane suppression via hydrogen consumption. Beyond carbon-cycling importance in this system, elucidating unintended virus-mediated responses to nutrient and prebiotic interventions will enable more predictable and effective microbiome engineering strategies across soil, ocean, and human ecosystems.

microbiology↗

bioRxiv2025

Synthetic community Hi-C benchmarking provides a baseline for virus-host inferences

Microbiomes influence diverse ecosystems, and viruses increasingly appear to impose key constraints. While viromics has expanded genomic catalogs, host identification for these viruses remains challenging due to the limitations in scaling cultivation-based approaches and the uncertain reliability and relative low resolution of in silico predictions - particularly for understudied viral taxa. Towards this, Hi-C proximity ligation uses sequenced, cross-linked virus and host genomic fragments to infer virus-host linkages and has now been applied in at least ten studies. However, its accuracy remains unknown. Here we assess Hi-C performance in recovering virus-host interactions using synthetic communities (SynComs) composed of four marine bacterial strains and nine phages with known interactions and then apply optimized bioinformatic protocols to natural soil samples. In SynComs, standard Hi-C sample preparations and analyses showed poor normalized contact score performance (26% specificity, 100% sensitivity, incorrect matches up to class level) that could be dramatically improved by Z-score filtering (Z [≥] 0.5, 99% specificity), though at reduced sensitivity (62% down from 100%). Detection limits were established as reproducibility was poor below minimal phage abundances of 105 PFU/mL. Applying optimized bioinformatic protocols to natural soil samples, we compared virus-host linkages inferred from proximity-ligated Hi-C sequencing with predictions generated by in silico homology-based and machine learning-based bioinformatic approaches. Prior to Z-score thresholding, agreement was relatively high at the phylum to family levels (72%), but not at the genus (43%) or species (15%) levels. Z-score thresholding reduced sensitivity (only 34% of predictions were retained), with only modest improvements in congruence with bioinformatic methods (48% or 18% at genus or species levels, respectively). Regardless, this led to 79 genus-level-congruent virus-host linkages and 293 new ones revealed by Hi-C alone - i.e., providing many new virus-host interactions to explore in already well-studied climate-critical soils. Overall, these findings provide empirical benchmarks and methodological guidelines to improve the accuracy and reliability of Hi-C for virus-host linkage studies in complex microbial communities.

microbiology↗

bioRxiv2020

Temporal landscape of mutation accumulation in SARS-CoV-2 genomes from Bangladesh: possible implications from the ongoing outbreak in Bangladesh

Along with intrinsic evolution, adaptation to selective pressure in new environments might have resulted in the circulatory SARS-CoV-2 strains in response to the geoenvironmental conditions of a country and the demographic profile of its population. Thus the analysis of genomic mutations of these circulatory strains may give an insight into the molecular basis of SARS-CoV-2 pathogenesis and evolution favoring the development of effective treatment and containment strategies. With this target, the current study traced the evolutionary route and mutational frequency of 198 Bangladesh originated SARS-CoV-2 genomic sequences available in the GISAID platform over a period of 13 weeks as of 14 July 2020. The analyses were performed using MEGA 7, Swiss Model Repository, Virus Pathogen Resource and Jalview visualization. Our analysis identified that majority of the circulating strains in the country belong to B and/or L type among cluster A to Z and strikingly differ from both the reference genome and the first sequenced genome from Bangladesh. Mutations in Nonspecific protein 2 (NSP2), NSP3, RNA dependent RNA polymerase (RdRp), Helicase, Spike, ORF3a, and Nucleocapsid (N) protein were common in the circulating strains with varying degrees and the most unique mutations(UM) were found in NSP3 (UM-18). But no or limited changes were observed in NSP9, NSP11, E (Envelope), NSP7a, ORF 6, and ORF 7b suggesting the possible conserved functions of those proteins in SARS-CoV-2 propagation. However, along with D614G mutation, more than 20 different mutations in the Spike protein were detected basically in the S2 domain. Besides, mutations in SR-rich region of N protein and P323L in RDRP were also present. However, the mutation accumulation showed an association with sex and age of the COVID-19 positive cases. So, identification of these mutational accumulation patterns may greatly facilitate drug/ vaccine development deciphering the age and the sex dependent differential susceptibility to COVID-19.

bioinformatics↗