Journal Articles

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

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    20 years later: unravelling the genomic success of New Zealand’s home-grown AK3 community-associated methicillin-resistant Staphylococcus aureus
    (Microbiology Society, 2025-07-25) White RT; Bakker S; Bloomfield M; Burton M; Elvy J; Eustace A; French NP; Grant J; Greening SS; Grinberg A; Harland C; Hutton S; Karkaba A; Martin J; Matthews B; Miller H; Straub C; Tarring C; Taylor WT; Ussher J; Velasco C; Voss EM; Dyet K
    Methicillin-resistant Staphylococcus aureus (MRSA) represents a significant public health challenge. In New Zealand, the community-associated MRSA sequence type (ST)5, carrying the staphylococcal cassette chromosome mec (SCCmec) type IV genetic element (which confers methicillin resistance), has been predominant since its detection in 2005. Known informally as the AK3 strain, it also exhibits resistance to fusidic acid. Here, we investigated the genomic evolution of the AK3 strain by analysing 397 genomes, comprising 361 MRSA and 36 closely related methicillin-susceptible S. aureus (MSSA) genomes, including 285 recently sequenced isolates from New Zealand spanning 2020 (n=30), 2021 (n=77), 2022 (n=88), 2023 (n=73) and 2024 (n=17). Phylogenetic analysis revealed that the AK3 strain evolved through stepwise acquisition of mobile genetic elements, with an MSSA ancestor likely introduced to New Zealand in the late 1970s. The lineage first acquired a SaPITokyo12571-like pathogenicity island, which contains the staphylococcal enterotoxin C bovine variant (sec-bov) and an enterotoxin-like protein (sel), between 1984 and 1991. This was followed by the integration of SCCmec type IV and adjacent fusidic acid resistance operon between 1997 and 2000. This timing coincides with increased community fusidic acid use in New Zealand. The AK3 strain then diversified into three major clades, spreading throughout New Zealand and Australia, with sporadic detection in European countries and Samoa. Our findings demonstrate how the sequential acquisition of mobile genetic elements, combined with antibiotic selection pressure, likely contributed to the successful emergence of AK3 and its spread in the South Pacific region.
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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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    Tracking the international spread of SARS-CoV-2 lineages B.1.1.7 and B.1.351/501Y-V2 with grinch
    (F1000 Research Limited, 2021-09-17) O'Toole Á; Hill V; Pybus OG; Watts A; Bogoch II; Khan K; Messina JP; COVID-19 Genomics UK (COG-UK) consortium; Network for Genomic Surveillance in South Africa (NGS-SA); Brazil-UK CADDE Genomic Network; Tegally H; Lessells RR; Giandhari J; Pillay S; Tumedi KA; Nyepetsi G; Kebabonye M; Matsheka M; Mine M; Tokajian S; Hassan H; Salloum T; Merhi G; Koweyes J; Geoghegan JL; de Ligt J; Ren X; Storey M; Freed NE; Pattabiraman C; Prasad P; Desai AS; Vasanthapuram R; Schulz TF; Steinbrück L; Stadler T; Swiss Viollier Sequencing Consortium; Parisi A; Bianco A; García de Viedma D; Buenestado-Serrano S; Borges V; Isidro J; Duarte S; Gomes JP; Zuckerman NS; Mandelboim M; Mor O; Seemann T; Arnott A; Draper J; Gall M; Rawlinson W; Deveson I; Schlebusch S; McMahon J; Leong L; Lim CK; Chironna M; Loconsole D; Bal A; Josset L; Holmes E; St George K; Lasek-Nesselquist E; Sikkema RS; Oude Munnink B; Koopmans M; Brytting M; Sudha Rani V; Pavani S; Smura T; Heim A; Kurkela S; Umair M; Salman M; Bartolini B; Rueca M; Drosten C; Wolff T; Silander O; Eggink D; Reusken C; Vennema H; Park A; Carrington C; Sahadeo N; Carr M; Gonzalez G; SEARCH Alliance San Diego; National Virus Reference Laboratory; SeqCOVID-Spain; Danish Covid-19 Genome Consortium (DCGC); Communicable Diseases Genomic Network (CDGN); Dutch National SARS-CoV-2 surveillance program; Division of Emerging Infectious Diseases (KDCA); de Oliveira T; Faria N; Rambaut A; Kraemer MUG
    Late in 2020, two genetically-distinct clusters of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with mutations of biological concern were reported, one in the United Kingdom and one in South Africa. Using a combination of data from routine surveillance, genomic sequencing and international travel we track the international dispersal of lineages B.1.1.7 and B.1.351 (variant 501Y-V2). We account for potential biases in genomic surveillance efforts by including passenger volumes from location of where the lineage was first reported, London and South Africa respectively. Using the software tool grinch (global report investigating novel coronavirus haplotypes), we track the international spread of lineages of concern with automated daily reports, Further, we have built a custom tracking website (cov-lineages.org/global_report.html) which hosts this daily report and will continue to include novel SARS-CoV-2 lineages of concern as they are detected.