Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

Browse

Author: search.filters.author.Biggs PJSubject: search.filters.subject.comparative genomics

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    The Host Adaptation of Staphylococcus aureus to Farmed Ruminants in New Zealand, With Special Reference to Clonal Complex 1
    (John Wiley and Sons Ltd, 2025-06) Nesaraj J; Grinberg A; Laven R; Chanyi R; Altermann E; Bandi C; Biggs PJ
    Genetic features of host adaptation of S. aureus to ruminants have been extensively studied, but the extent to which this adaptation occurs in nature remains unknown. In New Zealand, clonal complex 1 (CC1) is among the most common lineages in humans and the dominant lineage in cattle, enabling between-, and within-CC genomic comparisons of epidemiologically cohesive samples of isolates. We assessed the following genomic benchmarks of host adaptation to ruminants in 277 S. aureus from cattle, small ruminants, humans, and pets: 1, phylogenetic clustering of ruminant strains; 2, abundance of homo-specific ruminant-adaptive factors, and 3, scarcity of heterospecific factors. The genomic comparisons were complemented by comparative analyses of the metabolism of carbon sources that abound in ruminant milk. We identified features fulfilling the three benchmarks in virtually all ruminant isolates, including CC1. Data suggest the virulomes adapt to the ruminant niche sensu lato accross CCs. CC1 forms a ruminant-adapted clade that appears better equipped to utilise milk carbon sources than human CC1. Strain flow across the human–ruminant interface appears to only occur occasionally. Taken together, the results suggest a specialisation, rather than mere adaptation, clarifying why zoonotic and zoo-anthroponotic S. aureus transmission between ruminants and humans has hardly ever been reported.
  • Thumbnail Image
    Item
    Pangenome graphs in infectious disease: a comprehensive genetic variation analysis of Neisseria meningitidis leveraging Oxford Nanopore long reads.
    (Frontiers Media S.A., 2023-08-10) Yang Z; Guarracino A; Biggs PJ; Black MA; Ismail N; Wold JR; Merriman TR; Prins P; Garrison E; de Ligt J; Hane J
    Whole genome sequencing has revolutionized infectious disease surveillance for tracking and monitoring the spread and evolution of pathogens. However, using a linear reference genome for genomic analyses may introduce biases, especially when studies are conducted on highly variable bacterial genomes of the same species. Pangenome graphs provide an efficient model for representing and analyzing multiple genomes and their variants as a graph structure that includes all types of variations. In this study, we present a practical bioinformatics pipeline that employs the PanGenome Graph Builder and the Variation Graph toolkit to build pangenomes from assembled genomes, align whole genome sequencing data and call variants against a graph reference. The pangenome graph enables the identification of structural variants, rearrangements, and small variants (e.g., single nucleotide polymorphisms and insertions/deletions) simultaneously. We demonstrate that using a pangenome graph, instead of a single linear reference genome, improves mapping rates and variant calling for both simulated and real datasets of the pathogen Neisseria meningitidis. Overall, pangenome graphs offer a promising approach for comparative genomics and comprehensive genetic variation analysis in infectious disease. Moreover, this innovative pipeline, leveraging pangenome graphs, can bridge variant analysis, genome assembly, population genetics, and evolutionary biology, expanding the reach of genomic understanding and applications.