Dual pathogenicity island transfer by piggybacking lateral transduction

Lateral transduction (LT) is the process by which temperate phages mobilize large sections of bacterial genomes. Despite its importance, LT has only been observed during prophage induction. Here, we report that superantigen-carrying staphylococcal pathogenicity islands (SaPIs) employ a related but more versatile and complex mechanism of gene transfer to drive chromosomal hypermobility while self-transferring with additional virulence genes from the host. We found that after phage infection or prophage induction, activated SaPIs form concatamers in the bacterial chromosome by switching between parallel genomic tracks in replication bubbles. This dynamic life cycle enables SaPIbov1 to piggyback its LT of staphylococcal pathogenicity island vSaα, which encodes an array of genes involved in host-pathogen interactions, allowing both islands to be mobilized intact and transferred in a single infective particle. Our findings highlight previously unknown roles of pathogenicity islands in bacterial virulence and show that their evolutionary impact extends beyond the genes they carry

Visualising the Bacterial Pangenome: an analysis of the genetic content of Staphylococcus aureus (2022 Thesis Supplementary Data s1856921)

This dataset includes Supplementary Data in support of the University of Edinburgh thesis titled “Visualising the Bacterial Pangenome: an analysis of the genetic content of Staphylococcus aureus”. # Graphia software # Tom C. Freeman, Sebastian Horsewell, Anirudh Patir, Josh Harling-Lee, Tim Regan, Barbara B. Shih, James Prendergast, David A. Hume, Tim Angus; "Graphia: A platform for the graph-based visualisation and analysis of high dimensional data" https://doi.org/10.1371/journal.pcbi.1010310 . The ".graphia" format is a compressed network graph file format for use in the software Graphia. The User Guide is available at: https://graphia.app/. The software is open source and available to all users free of any charge

Graphia:A platform for the graph-based visualisation and analysis of high dimensional data

Graphia is an open-source platform created for the graph-based analysis of the huge amounts of quantitative and qualitative data currently being generated from the study of genomes, genes, proteins metabolites and cells. Core to Graphia’s functionality is support for the calculation of correlation matrices from any tabular matrix of continuous or discrete values, whereupon the software is designed to rapidly visualise the often very large graphs that result in 2D or 3D space. Following graph construction, an extensive range of measurement algorithms, routines for graph transformation, and options for the visualisation of node and edge attributes are available, for graph exploration and analysis. Combined, these provide a powerful solution for the interpretation of high-dimensional data from many sources, or data already in the form of a network or equivalent adjacency matrix. Several use cases of Graphia are described, to showcase its wide range of applications in the analysis biological data. Graphia runs on all major desktop operating systems, is extensible through the deployment of plugins and is freely available to download from https://graphia.app/