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Tithi, S. S.

Publications and source records attributed to Tithi, S. S..

3 recordsLinked to original sources

Parallel Evolution of Key Genomic Features and Cellular Bioenergetics Across the Marine Radiation of a Bacterial Phylum

Diverse bacterial and archaeal lineages drive biogeochemical cycles in the global ocean, but the evolutionary processes that have shaped their genomic properties and physiological capabilities remain obscure. Here we track the genome evolution of the globally-abundant marine bacterial phylum Marinimicrobia across its diversification into modern marine environments and demonstrate that extant lineages have repeatedly switched between epipelagic and mesopelagic habitats. Moreover, we show that these habitat transitions have been accompanied by repeated and fundamental shifts in genomic organization, cellular bioenergetics, and metabolic modalities. Lineages present in epipelagic niches independently acquired genes necessary for phototrophy and environmental stress mitigation, and their genomes convergently evolved key features associated with genome streamlining. Conversely, lineages residing in mesopelagic waters independently acquired nitrate respiratory machinery and a variety of cytochromes, consistent with the use of alternative terminal electron acceptors in oxygen minimum zones (OMZs). Further, while surface water clades have retained an ancestral Na+-pumping respiratory complex, deep water lineages have largely replaced this complex with a canonical H+-pumping respiratory complex I, potentially due to the increased efficiency of the latter together with more energy-limiting environments deep in the oceans interior. These parallel evolutionary trends across disparate clades suggest that the evolution of key features of genomic organization and cellular bioenergetics in abundant marine lineages may in some ways be predictable and driven largely by environmental conditions and nutrient dynamics.

microbiology

Biopipe: A Lightweight System Enabling Comparison of Bioinformatics Tools and Workflows

Analyzing next generation sequencing data always requires researchers to install many tools, prepare input data compliant to the required data format, and execute the tools in specific orders. Such tool installation and workflow execution process is tedious and error-prone, and becomes very challenging when researchers need to compare multiple alternative tool chains. To mitigate this problem, we developed a new lightweight and portable system, Biopipe, to simplify the creation and execution of bioinformatics tools and workflows, and to further enable the comparison between alternative tools or workflows. Biopipe allows users to create and edit workflows with user-friendly web interfaces, and automates tool installation as well as workflow synthesis by downloading and executing predefined Docker images. With Biopipe, biologists can easily experiment with and compare different bioinformatics tools and workflows without much computer science knowledge. There are mainly two parts in Biopipe: a web application and a standalone Java application. They are freely available at http://bench.cs.vt.edu:8282/Biopipe-Workflow-Editor-0.0.1/index.xhtml and https://code.vt.edu/saima5/Biopipe-Run-Workflow\n\nContactnm8247@cs.vt.edu\n\nSupplementary informationSupplementary data are available online.

bioinformatics

FastViromeExplorer: A Pipeline for Virus and Phage Identification and Abundance Profiling in Metagenomics Data

Identifying viruses and phages in a metagenomics sample has important implication in improving human health, preventing viral outbreaks, and developing personalized medicine. With the rapid increase in data files generated by next generation sequencing, existing tools for identifying and annotating viruses and phages in metagenomics samples suffer from expensive running time. In this paper, we developed a stand-alone pipeline, FastViromeExplorer, for rapid identification and abundance quantification of viruses and phages in big metagenomic data. Both real and simulated data validated FastViromeExplorer as a reliable tool to accurately identify viruses and their abundances in large data, as well as in a time efficient manner.

bioinformatics