Biology subjects

Dennis, T.

Publications and source records attributed to Dennis, T..

3 recordsLinked to original sources

bioRxiv2023

A novel approach to exploring the dark genome and its application to mapping of the vertebrate virus 'fossil record'.

BackgroundGenomic regions that remain poorly understood, often referred to as the "dark genome," contain a variety of functionally relevant and biologically informative genome features. These include endogenous viral elements (EVEs) - virus-derived sequences that can dramatically impact host biology and serve as a virus "fossil record". In this study, we introduce a database-integrated genome screening (DIGS) approach to investigating the dark genome in silico, focusing on EVEs found within vertebrate genomes. ResultsUsing DIGS on 874 vertebrate species genomes, we uncovered approximately 1.1 million EVE sequences, with over 99% originating from endogenous retroviruses or transposable elements that contain EVE DNA. We show that the remaining 6038 sequences represent over a thousand distinct horizontal gene transfer events across ten virus families, including some that have not previously been reported as EVEs. We explore the genomic and phylogenetic characteristics of non-retroviral EVEs and determine their rates of acquisition during vertebrate evolution. Our study uncovers novel virus diversity, broadens knowledge of virus distribution among vertebrate hosts, and provides new insights into the ecology and evolution of vertebrate viruses. ConclusionsWe comprehensively catalogue and analyse EVEs within 874 vertebrate genomes, shedding light on the distribution, diversity and long-term evolution of viruses, and revealing their extensive impact on vertebrate genome evolution. Our results demonstrate the power of linking a relational database management system to a similarity search-based screening pipeline for in silico exploration of the dark genome.

genomics↗

bioRxiv2019

Endocytosis of very low-density lipoprotein particles: an unexpected mechanism for lipid acquisition by breast cancer cells

We previously described the expression of CD36 and lipoprotein lipase (LPL) by breast cancer (BC) cells and tissues, and the growth-promoting effect of very low-density lipoprotein (VLDL) supplementation observed in BC cell lines only in the presence of LPL. We now describe the deployment of LPL by BC cells. Our data support a model in which LPL is bound to a heparin-like heparan sulfate proteoglycan motif on the BC cell surface and acts in concert with the VLDL receptor to rapidly internalize intact lipoproteins via receptor-mediated endocytosis. We further observe substantial alterations in gene expression programs related to pathways for lipid acquisition (synthesis vs. uptake) in response to each the availability of exogenous triglyceride in tissue culture media and LPL expression status. Current literature emphasizes de novo fatty acid synthesis as the paramount mechanism for lipid acquisition by cancer cells. Our findings indicate that exogenous lipid uptake can serve as an important method of lipid acquisition for cancer cells, alongside de novo lipogenesis, and that the relative reliance on these two modes of lipid acquisition may vary among different BC cell lines and in response to nutrient availability. This concept has obvious implications for the development of therapies aimed at the lipid dependence of many different cancer types. Moreover, the mechanism that we have elucidated provides a direct connection between dietary fat and tumor biology.

cancer biology↗

bioRxiv2018

Database-integrated genome screening (DIGS): exploring genomes heuristically using sequence similarity search tools and a relational database.

A significant fraction of most genomes is comprised of DNA sequences that have been incompletely investigated. This genomic dark matter contains a wealth of useful biological information that can be recovered by systematically screening genomes in silico using sequence similarity search tools. Specialized computational tools are required to implement these screens efficiently. Here, we describe the database-integrated genome-screening (DIGS) tool: a computational framework for performing these investigations. To demonstrate, we screen mammalian genomes for endogenous viral elements (EVEs) derived from the Filoviridae, Parvoviridae, Circoviridae and Bornaviridae families, identifying numerous novel elements in addition to those that have been described previously. The DIGS tool provides a simple, robust framework for implementing a broad range of heuristic, sequence analysis-based explorations of genomic diversity.\n\nAvailabilityhttp://giffordlabcvr.github.io/DIGS-tool/\n\nContactrobert.gifford@glasgow.ac.uk\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗