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Jennison, A. V.

Publications and source records attributed to Jennison, A. V..

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Bioinformatic investigation of discordant sequence data for SARS-CoV-2: insights for robust genomic analysis during pandemic surveillance

The COVID-19 pandemic has necessitated the rapid development and implementation of whole genome sequencing (WGS) and bioinformatic methods for managing the pandemic. However, variability in methods and capabilities between laboratories has posed challenges in ensuring data accuracy. A national working group comprising 18 laboratory scientists and bioinformaticians from Australia and New Zealand was formed to improve data concordance across public health laboratories (PHLs). One effort, presented in this study, sought to understand the impact of methodology on consensus genome concordance and interpretation. Data were retrospectively obtained from the 2021 Royal College of Pathologists of Australasia Quality Assurance Programs (RCPAQAP) SARS-CoV-2 WGS proficiency testing program (PTP), which included 11 participating Australian laboratories. The submitted consensus genomes and reads from eight contrived specimen were investigated, focusing on discordant sequence data, and findings were presented to the working group to inform best practices. Despite using a variety of laboratory and bioinformatic methods for SARS-CoV-2 WGS, participants largely produced concordant genomes. Two participants returned five discordant sites in a high Ct replicate which could be resolved with reasonable bioinformatic quality thresholds. We noted ten discrepancies in genome assessment that arose from nucleotide heterogeneity at three different sites in three cell-culture derived control specimen. While these sites were ultimately accurate after considering the participants bioinformatic parameters, it presented an interesting challenge for developing standards to account for intrahost single nucleotide variation (iSNV). Observed differences had little to no impact on key surveillance metrics, lineage assignment and phylogenetic clustering, while genome coverage <90% affected both. We recommend PHLs bioinformatically generate two consensus genomes with and without ambiguity thresholds for quality control and downstream analysis, respectively, and adhere to a minimum 90% genome coverage threshold for inclusion in surveillance interpretations. We also suggest additional PTP assessment criteria, including primer efficiency, detection of iSNVs, and minimum genome coverage of 90%. This study underscores the importance of multidisciplinary national working groups in informing guidelines in real time for bioinformatic quality acceptance criteria. It demonstrates the potential for enhancing public health responses through improved data concordance and quality control in SARS-CoV-2 genomic analysis during pandemic surveillance. Data summaryThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. Impact statementAmidst the COVID-19 pandemic, a unique collaboration between a national multidisciplinary working group and a quality assurance program facilitated ongoing development of standardized quality control criteria and analysis methods for high-quality SARS-CoV-2 genomic approaches across Australia. With this article, we shed light on the robustness of amplicon sequencing and analysis methods to produce highly concordant genomes, while also presenting additional assessment criteria to guide laboratories in identifying areas for improvement. Insights from this nationwide collaboration underscore the need for real-time knowledge-sharing and iterative refinements to quality standards, particularly as situations and methods evolve during a pandemic. While the spotlight is on SARS-CoV-2, the analyses and findings have universal implications for genomic surveillance during infectious disease outbreaks. As WGS becomes increasingly central in outbreak surveillance, continuous evaluation and collaboration, like that described here, are vital to ensure data accuracy and inform future public health responses.

genomics↗

Genomic epidemiology and multilevel genome typing of Australian Salmonella enterica serovar Enteritidis

Salmonella enterica serovar Enteritidis is one of the leading causes of salmonellosis in Australia. However, the majority of S. Enteritidis cases in Australia are travel-related with a small proportion being locally acquired. This study aimed to characterise the genomic features of Australian S. Enteritidis and compare them with international strains using multilevel genome typing (MGT). A total of 568 S. Enteritidis isolates from two Australian states across two consecutive years were analysed using the S. Enteritidis MGT scheme and database (MGTdb) - which contained 40,390 publicly available genomes from 99 countries. The Australian S. Enteritidis strains were divided into three phylogenetic clades (A, B and C). Clades A and C represented 16.4% and 3.5% of the total isolates, respectively, and were of local origin. Clade B accounted for 80.1% of the isolates which belonged to seven previously defined lineages but was dominated by the global epidemic lineage (MGT4-CC1). At MGT5 level, three out of five top sequence types (STs) in Australia were also top STs in Asia, suggesting that a fair proportion of Australian S. Enteritidis cases may be epidemiologically linked with Asian strains. In 2018, a large egg-associated local outbreak was caused by a recently defined clade B lineage prevalent in Europe and was closely related, but not directly linked, to three isolates from Europe. Additionally, antimicrobial-resistance genes were only found in Australian clade B isolates, with a predicted multidrug resistance (MDR) rate of 11.7%. Over half (54.8%) of the MDR isolates belonged to 10 MDR-associated MGT-STs, which were also frequent in Asian S. Enteritidis. IncX1 plasmids were frequently present in the Australian MDR isolates. Overall, this study investigated the genomic epidemiology of S. Enteritidis in Australia, including the first large local outbreak, using MGT. The open MGT platform enables a standardised and sharable nomenclature that can be effectively applied to public health for unified surveillance of S. Enteritidis nationally and globally. ImportanceSalmonella enterica serovar Enteritidis is a leading cause of foodborne infections. We previously developed a genomic typing database - MGTdb for S. Enteritidis to facilitate global surveillance of this pathogen. In this study we examined the genomic features of Australian S. Enteritidis using the MGTdb and found that Australian S. Enteritidis is mainly epidemiologically linked with Asian strains (especially strains carrying antimicrobial resistance genes) followed by European strains. The first large-scale egg-associated local outbreak in Australia was caused by a recently defined lineage prevalent in Europe, and three European isolates in the MGTdb were closely related but not directly linked to this outbreak. In summary, the S. Enteritidis MGTdb open platform is shown to be a potential powerful tool for national and global public health surveillance of this pathogen.

genomics↗

Complete microbial genomes for public health in Australia and Southwest Pacific

Complete genomes of microbial pathogens are essential for the phylogenomic analyses that increasingly underpin core public health lab activities. Here, we present complete genomes of pathogen strains of regional importance to the Southwest Pacific and Australia. These enrich the catalogue of globally available complete genomes for public health while providing valuable strains to regional public health labs.\n\nAnnouncementWhole-genome sequence (WGS) data is increasingly important in public health microbiology (1-4). The data can be used to replicate many of the basic bacterial sub-typing approaches, as well as support epidemiological investigations, such as surveillance and outbreak investigation (5-7). The appeal of WGS data comes from the promise of a single workflow to process all microbial pathogens that can provide easily portable data that promotes deeper integration of surveillance and investigation efforts across jurisdictions. This promise is leading to a concerted effort to move microbial public health to a primarily genome-based workflow at numerous jurisdictions (8-10), including Australia (11).

genomics↗

Genomic investigation reveals contaminated detergent as the source of an ESBL-producing Klebsiella michiganensis outbreak in a neonatal unit

BackgroundKlebsiella species are problematic pathogens in neonatal units and may cause outbreaks, for which sources of transmission can be challenging to elucidate. We describe the use of whole genome sequencing (WGS) to investigate environmental sources of transmission during an outbreak of extended-spectrum-{beta}-lactamase (ESBL)-producing Klebsiella michiganensis colonizing neonates. MethodsCeftriaxone-resistant Klebsiella spp. isolated from neonates (or their mothers) and the hospital environment were included. Short-read (Illumina) and long-read (MinION, Oxford Nanopore Technologies) sequencing was used to confirm species taxonomy, define antimicrobial resistance genes and determine phylogenetic relationships using single nucleotide polymorphism (SNP) profiling. ResultsA total of 21 organisms (10 patient-derived and 11 environmental isolates) were sequenced. Standard laboratory methods identified the outbreak strain as an ESBL-producing Klebsiella oxytoca, but taxonomic assignment from WGS data suggested closer identity to Klebsiella michiganensis. Strains isolated from baby bath drains and multiple detergent dispensing bottles were either identical or closely related by SNP comparison. Detergent bottles contaminated by K. michiganensis had been used for washing milk-expressing equipment. No new cases were identified once the detergent bottles were removed and the baby baths decommissioned. ConclusionsEnvironmental reservoirs may be an important source in outbreaks of multi-drug resistant organisms. WGS, in conjunction with traditional epidemiological investigation, can be instrumental in revealing routes of transmission and guiding infection control responses. Key pointsO_LIK. michiganensis can be misidentified as K. oxytoca and is probably under-recognized as a nosocomial pathogen C_LIO_LIWhole genome sequencing of neonatal and environmental isolates during an outbreak of ESBL-producing K. michiganensis confirmed contaminated detergent and sinks to be the source C_LI

microbiology↗