Microbiology & Immunology - Research Publications
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ItemNo Preview AvailableBioinformatic investigation of discordant sequence data for SARS- CoV-2: insights for robust genomic analysis during pandemic surveillance(MICROBIOLOGY SOC, 2023-11)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 the methodology on consensus genome concordance and interpretation. SARS-CoV-2 WGS proficiency testing programme (PTP) data were retrospectively obtained from the 2021 Royal College of Pathologists of Australasia Quality Assurance Programmes (RCPAQAP), which included 11 participating Australian laboratories. The submitted consensus genomes and reads from eight contrived specimens 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-Cτ 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 specimens. 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.
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ItemNo Preview AvailableHigh performance Legionella pneumophila source attribution using genomics-based machine learning classification(AMER SOC MICROBIOLOGY, 2024-02-21)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 revolutionized 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 maximizes the use of genomic variation data and is thus well-suited for supporting Legionnaires' disease outbreak investigations.IMPORTANCEIdentifying the sources of Legionnaires' disease outbreaks is crucial for effective control. Current genomic methods, while useful, often fall short due to the complex ecology and population structure of Legionella pneumophila, the causative agent. Our study introduces a high-performing machine learning approach for more accurate geographical source attribution of Legionnaires' disease outbreaks. Developed using cross-validation on environmental L. pneumophila genomes, our models demonstrate excellent predictive sensitivity and specificity. Importantly, this new approach outperforms traditional methods like phylogenomic trees and core genome multi-locus sequence typing, proving more efficient at leveraging genomic variation data to infer outbreak sources. Our machine learning algorithms, harnessing both core and accessory genomic variation, offer significant promise in public health settings. By enabling rapid and precise source identification in Legionnaires' disease outbreaks, such approaches have the potential to expedite intervention efforts and curtail disease transmission.
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ItemNo Preview AvailablePublic health implementation of pathogen genomics: the role for accreditation and application of ISO standards(MICROBIOLOGY SOC, 2023-08)Pathogen genomics has transitioned rapidly from the research setting into a powerful tool now routinely used in public health microbiology, for surveillance, outbreak investigations and disease control. As these investigations can have significant public health, treatment and legal impacts, we must ensure the accuracy of these results through validation of testing processes. For laboratories working in this space, it is important to approach this work with a quality and accreditation framework in mind, working towards implementation of quality systems and test validation that meet international regulatory standards. Here we outline the key international standards and processes that lead toward accreditation for pathogen genomics.
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ItemPersistence of Rare Salmonella Typhi Genotypes Susceptible to First-Line Antibiotics in the Remote Islands of Samoa(AMER SOC MICROBIOLOGY, 2022-10-26)For decades, the remote island nation of Samoa (population ~200,000) has faced endemic typhoid fever despite improvements in water quality, sanitation, and economic development. We recently described the epidemiology of typhoid fever in Samoa from 2008 to 2019 by person, place, and time; however, the local Salmonella enterica serovar Typhi (S. Typhi) population structure, evolutionary origins, and genomic features remained unknown. Herein, we report whole genome sequence analyses of 306 S. Typhi isolates from Samoa collected between 1983 and 2020. Phylogenetics revealed a dominant population of rare genotypes 3.5.4 and 3.5.3, together comprising 292/306 (95.4%) of Samoan versus 2/4934 (0.04%) global S. Typhi isolates. Three distinct 3.5.4 genomic sublineages were identified, and their defining polymorphisms were determined. These dominant Samoan genotypes, which likely emerged in the 1970s, share ancestry with other 3.5 clade isolates from South America, Southeast Asia, and Oceania. Additionally, a 106-kb pHCM2 phenotypically cryptic plasmid, detected in a 1992 Samoan S. Typhi isolate, was identified in 106/306 (34.6%) of Samoan isolates; this is more than double the observed proportion of pHCM2-containing isolates in the global collection. In stark contrast with global S. Typhi trends, resistance-conferring polymorphisms were detected in only 15/306 (4.9%) of Samoan S. Typhi, indicating overwhelming susceptibility to antibiotics that are no longer effective in most of South and Southeast Asia. This country-level genomic framework can help local health authorities in their ongoing typhoid surveillance and control efforts, as well as fill a critical knowledge gap in S. Typhi genomic data from Oceania. IMPORTANCE In this study, we used whole genome sequencing and comparative genomics analyses to characterize the population structure, evolutionary origins, and genomic features of S. Typhi associated with decades of endemic typhoid fever in Samoa. Our analyses of Samoan isolates from 1983 to 2020 identified a rare S. Typhi population in Samoa that likely emerged around the early 1970s and evolved into sublineages that are presently dominant. The dominance of these endemic genotypes in Samoa is not readily explained by genomic content or widespread acquisition of antimicrobial resistance. These data establish the necessary framework for future genomic surveillance of S. Typhi in Samoa for public health benefit.
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ItemSpatial-temporal and phylogenetic analyses of epidemiologic data to help understand the modes of transmission of endemic typhoid fever in Samoa(PUBLIC LIBRARY SCIENCE, 2022-10)Salmonella enterica serovar Typhi (S. Typhi) is either widely distributed or proximally transmitted via fecally-contaminated food or water to cause typhoid fever. In Samoa, where endemic typhoid fever has persisted over decades despite water quality and sanitation improvements, the local patterns of S. Typhi circulation remain unclear. From April 2018-June 2020, epidemiologic data and GPS coordinates were collected during household investigations of 260 acute cases of typhoid fever, and 27 asymptomatic shedders of S. Typhi were detected among household contacts. Spatial and temporal distributions of cases were examined using Average Nearest Neighbor and space-time hotspot analyses. In rural regions, infections occurred in sporadic, focal clusters contrasting with persistent, less clustered cases in the Apia Urban Area. Restrictions to population movement during nationwide lockdowns in 2019-2020 were associated with marked reductions of cases. Phylogenetic analyses of isolates with whole genome sequences (n = 186) revealed one dominant genotype 3.5.4 (n = 181/186) that contains three Samoa-exclusive sub-lineages: 3.5.4.1, 3.5.4.2, and 3.5.4.3. Variables of patient sex, age, and geographic region were examined by phylogenetic groupings, and significant differences (p<0.05) associated genetically-similar isolates in urban areas with working ages (20-49 year olds), and in rural areas with age groups typically at home (<5, 50+). Isolates from asymptomatic shedders were among all three sub-lineages. Whole genome sequencing provided evidence of bacterial genetic similarity, which corroborated 10/12 putative epidemiologic linkages among cases and asymptomatic shedders, as well as 3/3 repeat positives (presumed relapses), with a median of one single nucleotide polymorphism difference. These findings highlight various patterns of typhoid transmission in Samoa that differ between urban and rural regions as well as genomic subtypes. Asymptomatic shedders, detectable only through household investigations, are likely an important reservoir and mobile agent of infection. This study advances a "Samoan S. Typhi framework" that supports current and future typhoid surveillance and control efforts in Samoa.
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ItemAn ISO-certified genomics workflow for identification and surveillance of antimicrobial resistance(NATURE PORTFOLIO, 2023-01-04)Realising the promise of genomics to revolutionise identification and surveillance of antimicrobial resistance (AMR) has been a long-standing challenge in clinical and public health microbiology. Here, we report the creation and validation of abritAMR, an ISO-certified bioinformatics platform for genomics-based bacterial AMR gene detection. The abritAMR platform utilises NCBI's AMRFinderPlus, as well as additional features that classify AMR determinants into antibiotic classes and provide customised reports. We validate abritAMR by comparing with PCR or reference genomes, representing 1500 different bacteria and 415 resistance alleles. In these analyses, abritAMR displays 99.9% accuracy, 97.9% sensitivity and 100% specificity. We also compared genomic predictions of phenotype for 864 Salmonella spp. against agar dilution results, showing 98.9% accuracy. The implementation of abritAMR in our institution has resulted in streamlined bioinformatics and reporting pathways, and has been readily updated and re-verified. The abritAMR tool and validation datasets are publicly available to assist laboratories everywhere harness the power of AMR genomics in professional practice.
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ItemState-wide genomic epidemiology investigations of COVID-19 in healthcare workers in 2020 Victoria, Australia: Qualitative thematic analysis to provide insights for future pandemic preparedness(ELSEVIER, 2022-08)BACKGROUND: COVID-19 has affected many healthcare workers (HCWs) globally. We performed state-wide SARS-CoV-2 genomic epidemiological investigations to identify HCW transmission dynamics and provide recommendations to optimise healthcare system preparedness for future outbreaks. METHODS: Genome sequencing was attempted on all COVID-19 cases in Victoria, Australia. We combined genomic and epidemiologic data to investigate the source of HCW infections across multiple healthcare facilities (HCFs) in the state. Phylogenetic analysis and fine-scale hierarchical clustering were performed for the entire dataset including community and healthcare cases. Facilities provided standardised epidemiological data and putative transmission links. FINDINGS: Between March-October 2020, approximately 1,240 HCW COVID-19 infection cases were identified; 765 are included here, requested for hospital investigations. Genomic sequencing was successful for 612 (80%) cases. Thirty-six investigations were undertaken across 12 HCFs. Genomic analysis revealed that multiple introductions of COVID-19 into facilities (31/36) were more common than single introductions (5/36). Major contributors to HCW acquisitions included mobility of staff and patients between wards and facilities, and characteristics and behaviours of patients that generated numerous secondary infections. Key limitations at the HCF level were identified. INTERPRETATION: Genomic epidemiological analyses enhanced understanding of HCW infections, revealing unsuspected clusters and transmission networks. Combined analysis of all HCWs and patients in a HCF should be conducted, supported by high rates of sequencing coverage for all cases in the population. Established systems for integrated genomic epidemiological investigations in healthcare settings will improve HCW safety in future pandemics. FUNDING: The Victorian Government, the National Health and Medical Research Council Australia, and the Medical Research Future Fund.
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ItemWhole genome sequencing for tuberculosis in Victoria, Australia: A genomic implementation study from 2017 to 2020(ELSEVIER, 2022-11)BACKGROUND: Whole genome sequencing (WGS) is increasingly used by tuberculosis (TB) programs to monitor Mycobacterium tuberculosis (Mtb) transmission. We aimed to characterise the molecular epidemiology of TB and Mtb transmission in the low-incidence setting of Victoria, Australia, and assess the utility of WGS. METHODS: WGS was performed on all first Mtb isolates from TB cases from 2017 to 2020. Potential clusters (≤12 single nucleotide polymorphisms [SNPs]) were investigated for epidemiological links. Transmission events in highly-related (≤5 SNPs) clusters were classified as likely or possible, based on the presence or absence of an epidemiological link, respectively. Case characteristics and transmission settings (as defined by case relationship) were summarised. Poisson regression was used to examine associations with secondary case number. FINDINGS: Of 1844 TB cases, 1276 (69.2%) had sequenced isolates, with 182 (14.2%) in 54 highly-related clusters, 2-40 cases in size. Following investigation, 140 cases (11.0% of sequenced) were classified as resulting from likely/possible local-transmission, including 82 (6.4%) for which transmission was likely. Common identified transmission settings were social/religious (26.4%), household (22.9%) and family living in different households (7.1%), but many were uncertain (41.4%). While household transmission featured in many clusters (n = 24), clusters were generally smaller (median = 3 cases) than the fewer that included transmission in social/religious settings (n = 12, median = 7.5 cases). Sputum-smear-positivity was associated with higher secondary case numbers. INTERPRETATION: WGS results suggest Mtb transmission commonly occurs outside the household in our low-incidence setting. Further work is required to optimise the use of WGS in public health management of TB. FUNDING: The Victorian Tuberculosis Program receives block funding for activities including case management and contact tracing from the Victorian Department of Health. No specific funding for this report was received by manuscript authors or the Victorian Tuberculosis Program, and the funders had no role in the study design, data collection, data analysis, interpretation or report writing.
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ItemFeasibility of a refurbished shipping container as a transportable laboratory for rapid SARS-CoV-2 diagnostics.(Microbiology Society, 2022)BACKGROUND: Australia's response to the coronavirus disease 2019 (COVID-19) pandemic relies on widespread availability of rapid, accurate testing and reporting of results to facilitate contact tracing. The extensive geographical area of Australia presents a logistical challenge, with many of the population located distant from a laboratory capable of robust severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection. A strategy to address this is the deployment of a mobile facility utilizing novel diagnostic platforms. This study aimed to evaluate the feasibility of a fully contained transportable SARS-CoV-2 testing laboratory using a range of rapid point-of-care tests. METHOD: A 20 ft (6.1 m) shipping container was refurbished (GeneWorks, Adelaide, South Australia) with climate controls, laboratory benches, hand-wash station and a class II biosafety cabinet. Portable marquees situated adjacent to the container served as stations for registration, sample acquisition and personal protective equipment for staff. Specimens were collected and tested on-site utilizing either the Abbott ID NOW or Abbott Panbio rapid tests. SARS-CoV-2 positive results from the rapid platforms or any participants reporting symptoms consistent with COVID-19 were tested on-site by GeneXpert Xpress RT-PCR. All samples were tested in parallel with a standard-of-care RT-PCR test (Panther Fusion SARS-CoV-2 assay) performed at the public health reference laboratory. In-laboratory environmental conditions and data management-related factors were also recorded. RESULTS: Over a 3 week period, 415 participants were recruited for point-of-care SARS-CoV-2 testing. From time of enrolment, the median result turnaround time was 26 min for the Abbott ID NOW, 32 min for the Abbott Panbio and 75 min for the Xpert Xpress. The environmental conditions of the refurbished shipping container were found to be suitable for all platforms tested, although humidity may have produced condensation within the container. Available software enabled turnaround times to be recorded, although technical malfunction resulted in incomplete data capture. CONCLUSION: Transportable container laboratories can enable rapid COVID-19 results at the point of care and may be useful during outbreak settings, particularly in environments that are physically distant from centralized laboratories. They may also be appropriate in resource-limited settings. The results of this pilot study confirm feasibility, although larger trials to validate individual rapid point-of-care testing platforms in this environment are required.
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ItemThe interplay between community and hospital Enterococcus faecium clones within health-care settings: a genomic analysis(ELSEVIER, 2022-02)BACKGROUND: The genomic relationships among Enterococcus faecium isolates are the subject of ongoing research that seeks to clarify the origins of observed lineages and the extent of horizontal gene transfer between them, and to robustly identify links between genotypes and phenotypes. E faecium is considered to form distinct groups-A and B-corresponding to isolates derived from patients who were hospitalised (A) and isolates from humans in the community (B). The additional separation of A into the so-called clades A1 and A2 remains an area of uncertainty. We aimed to investigate the relationships between A1 and non-A1 groups and explore the potential role of non-A1 isolates in shaping the population structure of hospital E faecium. METHODS: We collected short-read sequence data from invited groups that had previously published E faecium genome data. This hospital-based isolate collection could be separated into three groups (or clades, A1, A2, and B) by augmenting the study genomes with published sequences derived from human samples representing the previously defined genomic clusters. We performed phylogenetic analyses, by constructing maximum-likelihood phylogenetic trees, and identified historical recombination events. We assessed the pan-genome, did resistome analysis, and examined the genomic data to identify mobile genetic elements. Each genome underwent chromosome painting by use of ChromoPainter within FineSTRUCTURE software to assess ancestry and identify hybrid groups. We further assessed highly admixed regions to infer recombination directionality. FINDINGS: We assembled a collection of 1095 hospital E faecium sequences from 34 countries, further augmented by 33 published sequences. 997 (88%) of 1128 genomes clustered as A1, 92 (8%) as A2, and 39 (4%) as B. We showed that A1 probably emerged as a clone from within A2 and that, because of ongoing gene flow, hospital isolates currently identified as A2 represent a genetic continuum between A1 and community E faecium. This interchange of genetic material between isolates from different groups results in the emergence of hybrid genomes between clusters. Of the 1128 genomes, 49 (4%) hybrid genomes were identified: 33 previously labelled as A2 and 16 previously labelled as A1. These interactions were fuelled by a directional pattern of recombination mediated by mobile genetic elements. By contrast, the contribution of B group genetic material to A1 was limited to a few small regions of the genome and appeared to be driven by genomic sweep events. INTERPRETATION: A2 and B isolates coming into the hospital form an important reservoir for ongoing A1 adaptation, suggesting that effective long-term control of the effect of E faecium could benefit from strategies to reduce these genomic interactions, such as a focus on reducing the acquisition of hospital A1 strains by patients entering the hospital. FUNDING: Wellcome Trust.