Biology subjects

Ballard, S. A.

Publications and source records attributed to Ballard, S. A..

10 recordsLinked to original sources

bioRxiv2026

Incremental AMR acquisition driving successive genotype replacements and the rise of extensively drug resistant (XDR) Shigella sonnei in Australia over 20 years.

BackgroundIn Australia, the burden of shigellosis is predominantly in returning travellers or in men who have sex with men (MSM). Here, we combine genomic data with comprehensive epidemiological data on sexual exposure and international travel to explore population dynamics of Shigella sonnei and the expansion of multi-drug resistant (MDR) and extensively drug-resistant (XDR) sub-lineages. MethodsA population-level study of all cultured Shigella sonnei isolates in the state of Victoria, Australia, was undertaken between January 2002 and December 2024. Antimicrobial susceptibility testing, whole-genome sequencing, and bioinformatic analyses of 1,305 Shigella sonnei isolates were performed at the Microbiological Diagnostic Unit Public Health Laboratory. Enhanced metadata on source attribution including travel and sexual exposure were collected through surveillance forms or by interviews. ResultsThis study highlights significant shifts in Shigella sonnei cases in Victoria from sensitive strains to MDR and then XDR, particularly in the MSM-associated groups but also associated with a large point source outbreak. We describe an historical pattern of shifting genotype prevalence, and replacement to more varied and higher proportions of antimicrobial resistance over the last decade, resulting in the establishment of two distinct but highly concerning XDR sub-lineages within Victoria. ConclusionsOur genomic-epidemiological analyses highlight that drug-resistant Shigella sonnei remains an ongoing public health threat, and the importance of ongoing surveillance. We determined local evolutionary trajectories and identified expanding sub-lineages that informed shifts in clinical management and antimicrobial recommendations over time, including the use of azithromycin and carbapenems. Placing these local dynamics within the broader global epidemiology, we link how regional evolution interconnects with international dissemination, proving valuable context for guiding local, national and global strategies for prevent outbreaks and antimicrobial resistance.

microbiology↗

bioRxiv2024

Dynamics of antimicrobial resistance and virulence of Salmonella enterica serovar Dublin

Salmonella Dublin is a host-adapted, invasive non-typhoidal Salmonella (iNTS) serovar that causes bloodstream infections in humans and demonstrates increasing prevalence of antimicrobial resistance (AMR). Using a global dataset of 1,303 genomes, coupled with in vitro assays, we examined the evolutionary, resistance, and virulence characteristics of S. Dublin. Our analysis revealed strong geographic associations between AMR profiles and plasmid types, with highly resistant isolates confined predominantly to North America, linked to IncC plasmids co-encoding AMR and heavy metal resistance. By contrast, Australian isolates were largely antimicrobial-susceptible, reflecting differing AMR pressures. We identified two phylogenetically distinct Australian lineages, ST10 and ST74, with a small number of ST10 isolates harbouring a novel hybrid plasmid encoding both AMR and mercuric resistance. Whereas the ST10 lineage remains globally dominant, the ST74 lineage was less prevalent. ST74 exhibited unique genomic features including a larger pan genome compared to ST10 and the absence of key virulence loci including SPI-19 which encodes a type VI secretion system (T6SS). Despite these genomic differences, the ST74 lineage displayed enhanced intracellular replication in human macrophages and induced less pro-inflammatory responses compared with ST10, suggesting alternative virulence strategies that may support systemic dissemination of ST74. The Vi antigen was absent in all ST10 and ST74 genomes, highlighting challenges for serotyping and vaccine development, and has implications for current diagnostic and control strategies for S. Dublin infections. Collectively, this study represents the most comprehensive investigation of S. Dublin to date and importantly, has revealed distinct adaptations of two genotypes within the same serovar, leading to different epidemiological success. The regional emergence and evolution of distinct S. Dublin lineages highlights the need to understand the divergence of intra-serovar virulence mechanisms which may impact the development of effective control measures against this important global pathogen.

microbiology↗

bioRxiv2024

Bridging genomic gaps: A versatile SARS-CoV-2 benchmark dataset for adaptive laboratory workflows

Genomic sequencings adoption in public health laboratories (PHLs) for pathogen surveillance is innovative yet challenging, particularly in the realm of bioinformatics. Low- and middle-income countries (LMICs) face increased difficulties due to supply chain volatility, workforce training, and unreliable infrastructure such as electricity and internet services. These challenges also extend to high-income countries (HICs) where bioinformatics is nascent in PHLs and hampered by a lack of specialized skills and computational infrastructure. This underlines the urgency for flexible and resource-aware strategies in genomic sequencing to improve global pathogen surveillance. In response to these challenges, the present research was conducted to identify and analyse key variables influencing the quality and accuracy of amplicon sequence data. An extensive benchmark dataset was developed that encompassed a diverse collection of isolates, viral loads, primer schemes, library preparation methods, sequencing technologies, and basecalling models, totalling 750 sequences. This dataset was analysed with bioinformatic workflows selected for varying levels of technical capacity. The evaluation focused on quality metrics, consensus accuracy, and common genomic epidemiological indicators. The analysis uncovers complex interactions between multiple parameters in laboratory and bioinformatic processes. emphasising resource-constrained PHLs, practical guidelines are proposed. Insights from the benchmark dataset aim to guide the establishment of specific laboratory and bioinformatics protocols for amplicon sequencing in these settings. The findings can also be used to guide the creation of specialised training curricula, further advancing genomic equity. The benchmark dataset itself allows laboratories to customise and evaluate workflows, catering to their distinct requirements and capacities. Such a holistic approach is imperative to build the capacity to monitor pathogens worldwide. Author summaryThis study marks a step toward equity in the field of pathogen genomics, especially for resource-constrained PHLs. It develops and evaluates a comprehensive amplicon sequencing benchmark dataset, offering vital insights for PHLs engaged in genomic surveillance. In particular, the study finds that the choice of basecaller model has a minimal impact on the quality and accuracy of consensus sequences derived from ONT data, which is crucial for labs with limited computational resources. It also highlights the effectiveness of longer amplicons in ensuring consistent coverage and reducing amplicon dropouts at higher viral loads. While Illumina remains a gold standard for data quality, the combination of the Midnight primer scheme with ONTs Rapid library preparation is shown to be a viable alternative, reducing costs, procedural complexity, and hands-on time. The study synthesises these findings into practical guidelines to aid in the development of amplicon sequencing workflows for SARS-CoV-2 with implications for other pathogens.

genomics↗

bioRxiv2023

High performance Legionella pneumophila source attribution using genomics-based machine learning classification

Fundamental to effective Legionnaires disease outbreak control is the ability to rapidly identify the environmental source(s) of the causative agent, Legionella pneumophila. Genomics has revolutionised pathogen surveillance but L. pneumophila has a complex ecology and population structure that can limit source inference based on standard core genome phylogenetics. Here we present a powerful machine learning approach that assigns the geographical source of Legionnaires disease outbreaks more accurately than current core genome comparisons. Models were developed upon 534 L. pneumophila genome sequences, including 149 genomes linked to 20 previously reported Legionnaires disease outbreaks through detailed case investigations. Our classification models were developed in a cross-validation framework using only environmental L. pneumophila genomes. Assignments of clinical isolate geographic origins demonstrated high predictive sensitivity and specificity of the models, with no false positives or false negatives for 13 out of 20 outbreak groups, despite the presence of within-outbreak polyclonal population structure. Analysis of the same 534-genome panel with a conventional phylogenomic tree and a core genome multi-locus sequence type allelic distance-based classification approach revealed that our machine learning method had the highest overall classification performance - agreement with epidemiological information. Our multivariate statistical learning approach maximises use of genomic variation data and is thus well-suited for supporting Legionnaires disease outbreak investigations.

bioinformatics↗

bioRxiv2023

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↗

bioRxiv2022

Bridging the gap between bioinformatics and the clinical and public health microbiology laboratory: An ISO-accredited genomics workflow for antimicrobial resistance

Realising the promise of genomics to revolutionise routine AMR diagnosis and surveillance has been a long-standing challenge in clinical and public health microbiology. We have directly addressed this issue by creating and validating abritAMR, an ISO-accredited bioinformatics platform for genomics-based bacterial AMR gene detection. abritAMR utilises the NCBI AMRFinderPlus for detection of AMR genes and mutations, with additional features to classify AMR determinants into an antibiotic class. We validated abritAMR by comparing with multiplex PCR or gold-standard reference genomes, together representing 1500 different bacteria across 29 genera and covering 415 antibiotic resistance alleles. We also assessed inference of phenotypic resistance by comparing genomic predictions with agar dilution results for 864 Salmonella spp. Performance of abritAMR was excellent, detecting AMR genes with 99.9% accuracy (95% CI 99.9-99.9%), 97.9% sensitivity (95% CI 97.5-98.4%) and 100% specificity (100-100%). Phenotypic inference of resistance for Salmonella spp. was equally impressive, with 98.9% accuracy (98.7-99.1%). Validation data were submitted to the governing authority and ISO15189 accreditation was achieved. Implementation of abritAMR resulted in streamlined bioinformatics and reporting pathways, and it was readily updated and re-verified with database revisions or changes in reporting requirements. abritAMR is publicly and freely available to assist clinical and public health microbiology laboratories everywhere harness the power of AMR genomics in their professional practice.

microbiology↗

bioRxiv2020

Proficiency Testing for bacterial whole genome sequencing in assuring the quality of microbiology diagnostics in clinical and public health laboratories

The adoption of whole genome sequencing (WGS) data over the past decade for pathogen surveillance, and decision-making for infectious diseases has rapidly transformed the landscape of clinical microbiology and public health. However, for successful transition to routine use of these techniques, it is crucial to ensure the WGS data generated meet defined quality standards for pathogen identification, typing, antimicrobial resistance detection and surveillance. Further, the ongoing development of these standards will ensure that the bioinformatic processes are capable of accurately identifying and characterising organisms of interest, and thereby facilitate the integration of WGS into routine clinical and public health laboratory setting. A pilot proficiency testing (PT) program for WGS of infectious agents was developed to facilitate widely applicable standardisation and benchmarking standards for WGS across a range of laboratories. The PT participating laboratories were required to generate WGS data from two bacterial isolates, and submit the raw data for independent bioinformatics analysis, as well as analyse the data with their own processes and answer relevant questions about the data. Overall, laboratories used a diverse range of bioinformatics tools and could generate and analyse high-quality data, either meeting or exceeding the minimum requirements. This pilot has provided valuable insight into the current state of genomics in clinical microbiology and public health laboratories across Australia. It will provide a baseline guide for the standardisation of WGS and enable the development of a PT program that allows an ongoing performance benchmark for accreditation of WGS-based test processes.

bioinformatics↗

bioRxiv2020

Validation of a Single-step, Single-tube Reverse Transcription-Loop-Mediated Isothermal Amplification Assay for Rapid Detection of SARS-CoV-2 RNA

2.IntroductionThe SARS-CoV-2 pandemic of 2020 has resulted in unparalleled requirements for RNA extraction kits and enzymes required for virus detection, leading to global shortages. This has necessitated the exploration of alternative diagnostic options to alleviate supply chain issues. AimTo establish and validate a reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay for the detection of SARS-CoV-2 from nasopharyngeal swabs. MethodologyWe used a commercial RT-LAMP mastermix from OptiGene Ltd in combination with a primer set designed to detect the CDC N1 region of the SARS-CoV-2 nucleocapsid (N) gene. A single-tube, single-step fluorescence assay was implemented whereby as little as 1 L of universal transport medium (UTM) directly from a nasopharyngeal swab could be used as template, bypassing the requirement for RNA purification. Amplification and detection could be conducted in any thermocycler capable of holding 65{degrees}C for 30 minutes and measure fluorescence in the FAM channel at one-minute intervals. ResultsAssay evaluation by assessment of 157 clinical specimens previously screened by E-gene RT-qPCR revealed assay sensitivity and specificity of 87% and 100%, respectively. Results were fast, with an average time-to-positive (Tp) for 93 clinical samples of 14 minutes (SD {+/-}7 minutes). Using dilutions of SARS-CoV-2 virus spiked into UTM, we also evaluated assay performance against FDA guidelines for implementation of emergency-use diagnostics and established a limit-of-detection of 54 Tissue Culture Infectious Dose 50 per ml (TCID50 mL-1), with satisfactory assay sensitivity and specificity. A comparison of 20 clinical specimens between four laboratories showed excellent interlaboratory concordance; performing equally well on three different, commonly used thermocyclers, pointing to the robustness of the assay. ConclusionWith a simplified workflow, N1-STOP-LAMP is a powerful, scalable option for specific and rapid detection of SARS-CoV-2 and an additional resource in the diagnostic armamentarium against COVID-19. 3. Data summaryThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

microbiology↗

bioRxiv2017

Real-time genomic and epidemiological investigation of a multi-institution outbreak of KPC-producing Enterobacteriaceae: a translational study

BackgroundUntil recently, KPC-producing Enterobacteriaceae were rarely identified in Australia. Following an increase in the number of incident cases across the state of Victoria, we undertook a real-time combined genomic and epidemiological investigation. The scope of this study included identifying risk factors and routes of transmission, and investigating the utility of genomics to enhance traditional field epidemiology for informing management of established widespread outbreaks.\n\nMethods and FindingsAll KPC-producing Enterobacteriaceae isolates referred to the state reference laboratory from 2012 onwards were included. Whole-genome sequencing (WGS) was performed in parallel with a detailed descriptive epidemiological investigation of each case, using Illumina sequencing on each isolate. This was complemented with PacBio long-read sequencing on selected isolates to establish high-quality reference sequences and interrogate characteristics of KPC-encoding plasmids. Initial investigations indicated the outbreak was widespread, with 86 KPC-producing Enterobacteriaceae isolates (K. pneumoniae 92%) identified from 35 different locations across metropolitan and rural Victoria between 2012-2015. Initial combined analyses of the epidemiological and genomic data resolved the outbreak into distinct nosocomial transmission networks, and identified healthcare facilities at the epicentre of KPC transmission. New cases were assigned to transmission networks in real-time, allowing focussed infection control efforts. PacBio sequencing confirmed a secondary transmission network arising from inter-species plasmid transmission. Insights from Bayesian transmission inference and analyses of within-host diversity informed the development of state-wide public health and infection control guidelines, including interventions such as an intensive approach to screening contacts following new case detection to minimise unrecognised colonisation.\n\nConclusionsA real-time combined epidemiological and genomic investigation proved critical to identifying and defining multiple transmission networks of KPC Enterobacteriaceae, while data from either investigation alone were inconclusive. The investigation was fundamental to informing infection control measures in real-time and the development of state-wide public health guidelines on carbapenemase producing Enterobacteriaceae management.

genomics↗

bioRxiv2017

Genome reconstruction and characterisation of extensively drug-resistant bacterial pathogens through direct metagenomic sequencing of human faeces

Whole-genome sequencing of microbial pathogens is revolutionising modern approaches to outbreaks of infectious diseases and is reliant upon organism culture. Culture-independent methods have shown promise in identifying pathogens, but high level reconstruction of microbial genomes from microbiologically complex samples for more in-depth analyses remains a challenge. Here, using metagenomic sequencing of a human faecal sample and analysis by tetranucleotide frequency profiling projected onto emergent self-organising maps, we were able to reconstruct the underlying populations of two extensively-drug resistant pathogens, Klebsiella pneumoniae carbapenemase (KPC)-producing Klebsiella pneumoniae and vancomycin-resistant Enterococcus faecium. From these genomes, we were able to ascertain molecular typing results, such as MLST, and identify highly discriminatory mutations in the metagenome to distinguish closely related strains. These proof-of-principle results demonstrate the utility of clinical sample metagenomics to recover sequences of important drug-resistant bacteria and application of the approach in outbreak investigations, independent of the need to culture the organisms.

genomics↗