Biology subjects

Yooseph, S.

Publications and source records attributed to Yooseph, S..

3 recordsLinked to original sources

bioRxiv2025

Evidence for trace gas metabolism and widespread antibiotic synthesis in an abiotically-1 driven, Antarctic soil ecosystem

The McMurdo Dry Valleys (MDVs) of Antarctica offer microbial ecologists a uniquely pristine, low-biodiversity model system for understanding fundamental ecological phenomena, the impact of a warming climate on ecosystem functioning, community structure and composition, and the dynamics of adaptation. Despite the scientific value of this system, we still know little about the functional ecology of its biota, especially the bacteria. Here, we analyzed the bacterial taxonomic and functional diversity of 18 shotgun metagenomes using the VEBA metagenome processing pipeline. We recovered 701 medium-to-high quality MAGs ([≥] 50% completeness and contamination < 10%) and 201 high-quality MAGs ([≥] 80% completeness and < 10% contamination), almost 50% more than found in similar sites previously. We found that: 1) community composition shifts along environmental gradients correlated with soil moisture, elevation, and distance to the coast; 2) many MDV bacteria are capable of performing trace gas metabolism; 3) genes associated with antibiotic-mediated competitive interactions (e.g., antibiotic biosynthesis and antibiotic resistance genes) are widespread; and 4) MDV bacteria employ survival strategies common to bacteria in similarly extreme environments. This study provides novel insight into microbial survival strategies in extreme environments and lays the groundwork for a more comprehensive understanding of the autecology of MDV bacteria.

microbiology↗

bioRxiv2021

Integrated de novo Gene Prediction and Peptide Assembly of Metagenomic Sequencing Data

Metagenomics is the study of all genomic content presented in given microbial communities. Metagenomic functional analysis aims to quantify protein families and reconstruct metabolic pathways from the metagenome. It plays a central role in understanding the interaction between the microbial community and its host or environment. De novo functional analysis, which allows the discovery of novel protein families, remains challenging for high-complexity communities. There are currently three main approaches for recovering novel genes or proteins: de novo nucleotide assembly, gene calling, and peptide assembly. Unfortunately, their informational connection and dependency have been overlooked, and each has been formulated as an independent problem. In this work, we develop a sophisticated workflow called integrated Metagenomic Protein Predictor (iMPP), which leverages the informational dependencies for better de novo functional analysis. iMPP contains three novel modules: a hybrid assembly graph generation module, a graph-based gene calling module, and a peptide assembly-based refinement module. iMPP significantly improved the existing gene calling sensitivity on unassembled fragmented reads, achieving a 92% - 97% recall rate at a high precision level (>90%). iMPP further allowed for more sensitive and accurate peptide assembly, recovering more reference proteins and delivering more hypothetical protein sequences. The high performance of iMPP can provide a more comprehensive and unbiased view of the microbial communities under investigation. iMPP is freely available from https://github.com/Sirisha-t/iMPP.

bioinformatics↗

bioRxiv2019

Global ecotypes in the ubiquitous marine clade SAR86

SAR86 is an abundant and ubiquitous heterotroph in the surface ocean that plays a central role in the function of marine ecosystems. We hypothesized that despite its ubiquity, different SAR86 subgroups may be endemic to specific ocean regions and functionally specialized for unique marine environments. However, the global biogeographical distributions of SAR86 genes, and the manner in which these distributions correlate with marine environments, have not been investigated. We quantified SAR86 gene content across globally-distributed metagenomic samples and modeled these gene distributions as a function of 51 environmental variables. We identified five distinct clusters of genes within the SAR86 pangenome, each with a unique geographic distribution associated with specific environmental characteristics. Gene clusters are characterized by strong taxonomic enrichment of distinct SAR86 genomes and partial assemblies, as well as differential enrichment of certain functional groups, suggesting differing functional and ecological roles of SAR86 ecotypes. We then leveraged our models and high-resolution, remote sensing-derived environmental data to predict the distributions of SAR86 gene clusters across the worlds oceans, creating global maps of SAR86 ecotype distributions. Our results reveal that SAR86 exhibits previously unknown, complex biogeography, and provide a framework for exploring geographic distributions of genetic diversity from other microbial clades.

ecology↗