Journal Articles

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

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Start date: 2021Subject: search.filters.subject.comparative genomics

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    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.
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    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.
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    Genomic Insights Into Clinical Shiga Toxin-Producing Escherichia coli Strains: A 15-Year Period Survey in Jönköping, Sweden
    (Frontiers Media S.A., 2021-02-05) Bai X; Zhang J; Hua Y; Jernberg C; Xiong Y; French N; Löfgren S; Hedenström I; Ambikan A; Mernelius S; Matussek A; González-Escalona N
    Shiga toxin-producing Escherichia coli (STEC) are important foodborne pathogens that can cause human infections ranging from asymptomatic carriage to bloody diarrhea (BD) and fatal hemolytic uremic syndrome (HUS). However, the molecular mechanism of STEC pathogenesis is not entirely known. Here, we demonstrated a large scale of molecular epidemiology and in-depth genomic study of clinical STEC isolates utilizing clinical and epidemiological data collected in Region Jönköping County, Sweden, over a 15-year period. Out of 184 STEC isolates recovered from distinct patients, 55 were from patients with BD, and 129 were from individuals with non-bloody stools (NBS). Five individuals developed HUS. Adults were more associated with BD. Serotypes O157:H7, O26:H11, O103:H2, O121:H19, and O104:H4 were more often associated with BD. The presence of Shiga toxin-encoding gene subtypes stx 2a, stx 2a + stx 2c, and stx 1a + stx 2c was associated with BD, while stx 1 a was associated with milder disease. Multiplex virulence and accessory genes were correlated with BD; these genes encode toxins, adhesion, autotransporters, invasion, and secretion system. A number of antimicrobial resistance (AMR) genes, such as aminoglycoside, aminocoumarin, macrolide, and fluoroquinolone resistance genes, were prevalent among clinical STEC isolates. Whole-genome phylogeny revealed that O157 and non-O157 STEC isolates evolved from distinct lineages with a few exceptions. Isolates from BD showed more tendency to cluster closely. In conclusion, this study unravels molecular trait of clinical STEC strains and identifies genetic factors associated with severe clinical outcomes, which could contribute to management of STEC infections and disease progression if confirmed by further functional validation.