Whole genome sequencing of drug-resistant Mycobacterium tuberculosis isolates in Victoria, Australia.

OBJECTIVES: Whole genome sequencing (WGS) can identify clusters, transmission patterns, and drug resistance mutations. This is important in low-burden settings such as Australia, as it can assist in efficient contact tracing and surveillance. METHODS: We conducted a retrospective cohort study using WGS from 155 genomically defined drug-resistant Mycobacterium tuberculosis (DR-TB) isolates collected between 2018-2021 in Victoria, Australia. Bioinformatic analysis was performed to identify resistance-conferring mutations, lineages, clusters and understand how local sequences compared with international context. RESULTS: Of the 155 sequences, 42% were identified as lineage 2 and 35% as lineage 1; 65.8% (102/155) were isoniazid mono-resistant, 8.4% were multi-drug resistant TB and 5.8% were pre-extensively drug-resistant / extensively drug-resistant TB. The most common mutations were observed in katG and fabG1 genes, especially at Ser315Thr and fabG1 -15 C>T for first-line drugs. Ser450Leu was the most frequent mutation in rpoB gene. Phylogenetic analysis confirmed that Victorian DR-TB were associated with importation events. There was little evidence of local transmission with only five isolate pairs. CONCLUSION: Isoniazid-resistant TB is the commonest DR-TB in Victoria, and the mutation profile is similar to global circulating DR-TB. Most cases are diagnosed among migrants with limited transmission. This study highlights the value of WGS in identification of clusters and resistance-conferring mutations. This information is crucial in supporting disease mitigation and treatment strategies.

Comparison of contemporary invasive and non-invasive Streptococcus pneumoniae isolates reveals new insights into circulating anti-microbial resistance determinants.

Streptococcus pneumoniae is a major human pathogen with a high burden of disease. Non-invasive isolates (those found in non-sterile sites) are thought to be a key source of invasive isolates (those found in sterile sites) and a reservoir of anti-microbial resistance (AMR) determinants. Despite this, pneumococcal surveillance has almost exclusively focused on invasive isolates. We aimed to compare contemporaneous invasive and non-invasive isolate populations to understand how they interact and identify differences in AMR gene distribution. We used a combination of whole-genome sequencing and phenotypic anti-microbial susceptibility testing and a data set of invasive (n = 1,288) and non-invasive (n = 186) pneumococcal isolates, collected in Victoria, Australia, between 2018 and 2022. The non-invasive population had increased levels of antibiotic resistance to multiple classes of antibiotics including beta-lactam antibiotics penicillin and ceftriaxone. We identified genomic intersections between the invasive and non-invasive populations and no distinct phylogenetic clustering of the two populations. However, this analysis revealed sub-populations overrepresented in each population. The sub-populations that had high levels of AMR were overrepresented in the non-invasive population. We determined that WamR-Pneumo was the most accurate in silico tool for predicting resistance to the antibiotics tested. This tool was then used to assess the allelic diversity of the penicillin-binding protein genes, which acquire mutations leading to beta-lactam antibiotic resistance, and found that they were highly conserved (≥80% shared) between the two populations. These findings show the potential of non-invasive isolates to serve as reservoirs of AMR determinants.

Population structure, serotype distribution and antibiotic resistance of Streptococcus pneumoniae causing invasive disease in Victoria, Australia.

Streptococcus pneumoniae is a major human pathogen and can cause a range of conditions from asymptomatic colonization to invasive pneumococcal disease (IPD). The epidemiology and distribution of IPD-causing serotypes in Australia has undergone large changes following the introduction of the 7-valent pneumococcal conjugate vaccine (PCV) in 2005 and the 13-valent PCV in 2011. In this study, to provide a contemporary understanding of the IPD causing population in Victoria, Australia, we aimed to examine the population structure and prevalence of antimicrobial resistance using whole-genome sequencing and comprehensive antimicrobial susceptibility data of 1288 isolates collected between 2018 and 2022. We observed high diversity among the isolates with 52 serotypes, 203 sequence types (STs) and 70 Global Pneumococcal Sequencing Project Clusters (GPSCs) identified. Serotypes contained in the 13v-PCV represented 35.3 % (n=405) of isolates. Antimicrobial resistance (AMR) to at least one antibiotic was identified in 23.8 % (n=358) of isolates with penicillin resistance the most prevalent (20.3 %, n=261 using meningitis breakpoints and 5.1 % n=65 using oral breakpoints). Of the AMR isolates, 28 % (n=101) were multidrug resistant (MDR) (resistant to three or more drug classes). Vaccination status of cases was determined for a subset of isolates with 34 cases classified as vaccine failure events (fully vaccinated IPD cases of vaccine serotype). However, no phylogenetic association with failure events was observed. Within the highly diverse IPD population, we identified six high-risk sub-populations of public health concern characterized by high prevalence, high rates of AMR and MDR, or serotype inclusion in vaccines. High-risk serotypes included serotypes 3, 19F, 19A, 14, 11A, 15A and serofamily 23. In addition, we present our data validating seroBA for in silico serotyping to facilitate ISO-accreditation of this test in routine use in a public health reference laboratory and have made this data set available. This study provides insights into the population dynamics, highlights non-vaccine serotypes of concern that are highly resistant, and provides a genomic framework for the ongoing surveillance of IPD in Australia which can inform next-generation IPD prevention strategies.

An ISO-certified genomics workflow for identification and surveillance of antimicrobial resistance.

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.

Mycobacterium tuberculosis Genotypes and Drug Susceptibility Test Results from Timor-Leste: A Pilot Study.

Tuberculosis (TB) is prevalent and a major public health problem in Timor-Leste. The government of Timor-Leste is prioritising the surveillance of TB and drug-susceptibility testing (DST) to understand the burden of TB and TB drug resistance in the country. Moreover, little is known about the origin of Mycobacterium tuberculosis (MTB) in Timor-Leste. This study reports MTB DST and sequencing for Timor-Leste. A pilot study was carried out in which a convenience sample of TB isolates from mucopurulent sputum collected from presumptive TB patients in the capital Dili between July and December 2016 was tested for phenotypic and genotypic evidence of drug resistance. Standard MTB culture was performed at the Timor-Leste National Health Laboratory (NHL). The MTB isolates were sent to the Victorian Infectious Diseases Reference Laboratory (VIDRL) in Australia for DST and sequencing. Overall, 36 MTB isolates were detected at the NHL; 20 isolates were recovered during sub-culturing at VIDRL. All 20 isolates were susceptible to rifampicin, isoniazid, pyrazinamide, and ethambutol, with no genotypic markers of resistance identified. On sequencing, lineage 4 was the most common. The results of this study provide a small snapshot of MTB diversity and resistance in an under-sampled region with very high TB incidence. Future investment in whole-genome sequencing capacity in Timor-Leste will make it possible to undertake further, more representative analyses that may be used to evaluate transmission dynamics and epidemiology of genotypic markers of resistance.

Whole genome sequencing for tuberculosis in Victoria, Australia: A genomic implementation study from 2017 to 2020.

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.

Proficiency testing for SARS-CoV-2 whole genome sequencing.

Extensive studies and analyses into the molecular features of severe acute respiratory syndrome related coronavirus 2 (SARS-CoV-2) have enhanced the surveillance and investigation of its clusters and transmission worldwide. The whole genome sequencing (WGS) approach is crucial in identifying the source of infection and transmission routes by monitoring the emergence of variants over time and through communities. Varying SARS-CoV-2 genomics capacity and capability levels have been established in public health laboratories across different Australian states and territories. Therefore, laboratories performing SARS-CoV-2 WGS for public health purposes are recommended to participate in an external proficiency testing program (PTP). This study describes the development of a SARS-CoV-2 WGS PTP. The PTP assessed the performance of laboratories while providing valuable insight into the current state of SARS-CoV-2 genomics in public health across Australia. Part 1 of the PTP contained eight simulated SARS-CoV-2 positive and negative specimens to assess laboratories' wet and dry laboratory capacity. Part 2 involved the analysis of a genomic dataset that consisted of a multi-FASTA file of 70 consensus genomes of SARS-CoV-2. Participating laboratories were required to (1) submit raw data for independent bioinformatics analysis, (2) analyse the data with their processes, and (3) answer relevant questions about the data. The performance of the laboratories was commendable, despite some variation in the reported results due to the different sequencing and bioinformatics approaches used by laboratories. The overall outcome is positive and demonstrates the critical role of the PTP in supporting the implementation and validation of SARS-CoV-2 WGS processes. The data derived from this PTP will contribute to the development of SARS-CoV-2 bioinformatic quality control (QC) and performance benchmarking for accreditation.

State-wide genomic epidemiology investigations of COVID-19 in healthcare workers in 2020 Victoria, Australia: Qualitative thematic analysis to provide insights for future pandemic preparedness.

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.

Optimising genomic approaches for identifying vancomycin-resistant Enterococcus faecium transmission in healthcare settings.

Vancomycin-resistant Enterococcus faecium (VREfm) is a major nosocomial pathogen. Identifying VREfm transmission dynamics permits targeted interventions, and while genomics is increasingly being utilised, methods are not yet standardised or optimised for accuracy. We aimed to develop a standardized genomic method for identifying putative VREfm transmission links. Using comprehensive genomic and epidemiological data from a cohort of 308 VREfm infection or colonization cases, we compared multiple approaches for quantifying genetic relatedness. We showed that clustering by core genome multilocus sequence type (cgMLST) was more informative of population structure than traditional MLST. Pairwise genome comparisons using split k-mer analysis (SKA) provided the high-level resolution needed to infer patient-to-patient transmission. The more common mapping to a reference genome was not sufficiently discriminatory, defining more than three times more genomic transmission events than SKA (3729 compared to 1079 events). Here, we show a standardized genomic framework for inferring VREfm transmission that can be the basis for global deployment of VREfm genomics into routine outbreak detection and investigation.

Neisseria gonorrhoeae-derived outer membrane vesicles package ß-lactamases to promote antibiotic resistance.

Neisseria gonorrhoeae causes the sexually transmitted disease gonorrhoea. The treatment of gonorrhoea is becoming increasingly challenging, as N. gonorrhoeae has developed resistance to antimicrobial agents routinely used in the clinic. Resistance to penicillin is wide-spread partly due to the acquisition of ß-lactamase genes. How N. gonorrhoeae survives an initial exposure to ß-lactams before acquiring resistance genes remains to be understood. Here, using a panel of clinical isolates of N. gonorrhoeae we show that the ß-lactamase enzyme is packaged into outer membrane vesicles (OMVs) by strains expressing blaTEM-1B or blaTEM-106, which protects otherwise susceptible clinical isolates from the ß-lactam drug amoxycillin. We characterized the phenotypes of these clinical isolates of N. gonorrhoeae and the time courses over which the cross-protection of the strains is effective. Imaging and biochemical assays suggest that OMVs promote the transfer of proteins and lipids between bacteria. Thus, N. gonorrhoeae strains secret antibiotic degrading enzymes via OMVs enabling survival of otherwise susceptible bacteria.

Genomic Epidemiology and Antimicrobial Resistance Mechanisms of Imported Typhoid in Australia.

Typhoid fever is an invasive bacterial disease of humans that disproportionately affects low- and middle-income countries. Antimicrobial resistance (AMR) has been increasingly prevalent in recent decades in Salmonella enterica serovar Typhi (S. Typhi), the causative agent of typhoid fever, limiting treatment options. In Australia, most cases of typhoid fever are imported due to travel to regions where typhoid fever is endemic. Here, all 116 isolates of S. Typhi isolated in Victoria, Australia, between 1 July 2018 and 30 June 2020, underwent whole-genome sequencing and antimicrobial susceptibility testing. Genomic data were linked to international travel data collected from routine case interviews. Travel to South Asia accounted for most cases, with 92.2% imported from seven primary countries (the top two were India, n = 87, and Pakistan, n = 12). A total of 17 S. Typhi genotypes were detected in the 2-year cohort, with 48.2% genotyped as part of global AMR lineages. Ciprofloxacin resistance was detected in two lineages, 3.3 and 4.3.1.2, all from cases with reported travel to India. Nearly all multidrug and extensively drug resistant isolates (90%) were from cases with reported travel to Pakistan in genotypes 4.3.1.1 and 4.3.1.1.P1. Extended spectrum beta-lactamases, blaCTX-M-15 and blaSHV-12, were detected in cases with travel to Pakistan and India, respectively. Linking epidemiological data with genomic studies of S. Typhi provides an opportunity to improve understanding of the emergence, spread and risk of drug-resistant S. Typhi infections and to better inform empirical treatment guidelines in returned travelers.

Tuberculosis in Australia's tropical north: a population-based genomic epidemiological study.

BACKGROUND: The Northern Territory (NT) has the highest tuberculosis (TB) rate of all Australian jurisdictions. We combined TB public health surveillance data with genomic sequencing of Mycobacterium tuberculosis isolates in the tropical 'Top End' of the NT to investigate trends in TB incidence and transmission. METHODS: This retrospective observational study included all 741 culture-confirmed cases of TB in the Top End over three decades from 1989-2020. All 497 available M. tuberculosis isolates were sequenced. We used contact tracing data to define a threshold pairwise SNP distance for hierarchical single linkage clustering, and examined putative transmission clusters in the context of epidemiologic information. FINDINGS: There were 359 (48%) cases born overseas, 329 (44%) cases among Australian First Nations peoples, and 52 (7%) cases were Australian-born and non-Indigenous. The annual incidence in First Nations peoples from 1989-2019 fell from average 50.4 to 11.0 per 100,000 (P<0·001). First Nations cases were more likely to die from TB (41/329, 12·5%) than overseas-born cases (11/359, 3·1%; P<0·001). Using a threshold of ≤12 SNPs, 28 clusters of between 2-64 individuals were identified, totalling 250 cases; 214 (86%) were First Nations cases and 189 (76%) were from a remote region. The time between cases and past epidemiologically- and genomically-linked contacts ranged from 4·5 months to 24 years. INTERPRETATION: Our findings support prioritisation of timely case detection, contact tracing augmented by genomic sequencing, and latent TB treatment to break transmission chains in Top End remote hotspot regions.

Genomics-informed responses in the elimination of COVID-19 in Victoria, Australia: an observational, genomic epidemiological study.

BACKGROUND: A cornerstone of Australia's ability to control COVID-19 has been effective border control with an extensive supervised quarantine programme. However, a rapid recrudescence of COVID-19 was observed in the state of Victoria in June, 2020. We aim to describe the genomic findings that located the source of this second wave and show the role of genomic epidemiology in the successful elimination of COVID-19 for a second time in Australia. METHODS: In this observational, genomic epidemiological study, we did genomic sequencing of all laboratory-confirmed cases of COVID-19 diagnosed in Victoria, Australia between Jan 25, 2020, and Jan 31, 2021. We did phylogenetic analyses, genomic cluster discovery, and integrated results with epidemiological data (detailed information on demographics, risk factors, and exposure) collected via interview by the Victorian Government Department of Health. Genomic transmission networks were used to group multiple genomic clusters when epidemiological and genomic data suggested they arose from a single importation event and diversified within Victoria. To identify transmission of emergent lineages between Victoria and other states or territories in Australia, all publicly available SARS-CoV-2 sequences uploaded before Feb 11, 2021, were obtained from the national sequence sharing programme AusTrakka, and epidemiological data were obtained from the submitting laboratories. We did phylodynamic analyses to estimate the growth rate, doubling time, and number of days from the first local infection to the collection of the first sequenced genome for the dominant local cluster, and compared our growth estimates to previously published estimates from a similar growth phase of lineage B.1.1.7 (also known as the Alpha variant) in the UK. FINDINGS: Between Jan 25, 2020, and Jan 31, 2021, there were 20 451 laboratory-confirmed cases of COVID-19 in Victoria, Australia, of which 15 431 were submitted for sequencing, and 11 711 met all quality control metrics and were included in our analysis. We identified 595 genomic clusters, with a median of five cases per cluster (IQR 2-11). Overall, samples from 11 503 (98·2%) of 11 711 cases clustered with another sample in Victoria, either within a genomic cluster or transmission network. Genomic analysis revealed that 10 426 cases, including 10 416 (98·4%) of 10 584 locally acquired cases, diagnosed during the second wave (between June and October, 2020) were derived from a single incursion from hotel quarantine, with the outbreak lineage (transmission network G, lineage D.2) rapidly detected in other Australian states and territories. Phylodynamic analyses indicated that the epidemic growth rate of the outbreak lineage in Victoria during the initial growth phase (samples collected between June 4 and July 9, 2020; 47·4 putative transmission events, per branch, per year [1/years; 95% credible interval 26·0-85·0]), was similar to that of other reported variants, such as B.1.1.7 in the UK (mean approximately 71·5 1/years). Strict interventions were implemented, and the outbreak lineage has not been detected in Australia since Oct 29, 2020. Subsequent cases represented independent international or interstate introductions, with limited local spread. INTERPRETATION: Our study highlights how rapid escalation of clonal outbreaks can occur from a single incursion. However, strict quarantine measures and decisive public health responses to emergent cases are effective, even with high epidemic growth rates. Real-time genomic surveillance can alter the way in which public health agencies view and respond to COVID-19 outbreaks. FUNDING: The Victorian Government, the National Health and Medical Research Council Australia, and the Medical Research Future Fund.

COVID-19: Integrating genomic and epidemiological data to inform public health interventions and policy in Tasmania, Australia.

OBJECTIVE: We undertook an integrated analysis of genomic and epidemiological data to investigate a large health-care-associated outbreak of coronavirus disease 2019 (COVID-19) and to better understand the epidemiology of COVID-19 cases in Tasmania, Australia. METHODS: Epidemiological data collected on COVID-19 cases notified in Tasmania between 2 March and 15 May 2020, and positive samples of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or RNA extracted from the samples were included. Sequencing was conducted by tiled amplicon polymerase chain reaction with ARTIC v1 or v3 primers and Illumina sequencing. Consensus sequences were generated, sequences were aligned to a reference sequence and phylogenetic analysis was performed. Genomic clusters were determined and integrated with epidemiological data to provide additional information. RESULTS: All 231 COVID-19 cases notified in Tasmania during the study period and 266 SARS-CoV-2-positive samples, representing 217/231 (94%) notified cases, were included; 184/217 (84%) were clustered, 21/217 (10%) were unique and 12/217 (6%) could not be sequenced. Genomics confirmed the presence of seven clusters already identified through epidemiological links, clarified transmission networks in which the epidemiology had been unclear and identified one cluster that had not previously been recognized. DISCUSSION: Genomic analysis provided useful additional information on COVID-19 in Tasmania, including evidence of a large health-care-associated outbreak linked to an overseas cruise, the probable source of infection in cases with no previously identified epidemiological link and confirmation that there was no identified community transmission from other imported cases. Genomic insights are an important component of the response to COVID-19, and continuing genomic surveillance is warranted.

Complete microbial genomes for public health in Australia and the Southwest Pacific.

Complete genomes of microbial pathogens are essential for the phylogenomic analyses that increasingly underpin core public health laboratory activities. Here, we announce a BioProject (PRJNA556438) dedicated to sharing complete genomes chosen to represent a range of pathogenic bacteria with regional importance to Australia and the Southwest Pacific; enriching the catalogue of globally available complete genomes for public health while providing valuable strains to regional public health microbiology laboratories. In this first step, we present 26 complete high-quality bacterial genomes. Additionally, we describe here a framework for reconstructing complete microbial genomes and highlight some of the challenges and considerations for accurate and reproducible genome reconstruction.

Prolonged Outbreak of Multidrug-Resistant Shigella sonnei Harboring blaCTX-M-27 in Victoria, Australia.

In Australia, cases of shigellosis usually occur in returned travelers from regions of shigellosis endemicity or in men who have sex with men. Resistance to multiple antibiotics has significantly increased in Shigella sonnei isolates and represents a significant public health concern. We investigate an outbreak of multidrug-resistant S. sonnei in Victoria, Australia. We undertook whole-genome sequencing of 54 extended-spectrum-beta-lactamase (ESBL)-producing S. sonnei isolates received at the Microbiological Diagnostic Unit Public Health Laboratory between January 2019 and March 2020. The population structure and antimicrobial resistance profiles were identified by genomic analyses, with 73 previously characterized Australian S. sonnei isolates providing context. Epidemiological data, including age and sex of the shigellosis cases, were also collected. There was a significant increase in cases of ESBL S. sonnei from July 2019. Most of the ESBL S. sonnei isolates (65%) fell within a single cluster that was predominantly comprised of male cases that were characterized by the presence of the blaCTX-M-27 gene conferring resistance to extended-spectrum cephalosporins. These isolates were also multidrug resistant, including resistance to azithromycin and co-trimoxazole and reduced susceptibility to ciprofloxacin. Our data uncovered a prolonged clonal outbreak of ESBL S. sonnei infection that was likely first introduced by returned travelers and has subsequently been circulating locally in Australia. The emergence of a local outbreak of ESBL S. sonnei with a multidrug-resistant profile, including reduced susceptibility to ciprofloxacin, represents a significant public health threat.

Tracking the COVID-19 pandemic in Australia using genomics.

Genomic sequencing has significant potential to inform public health management for SARS-CoV-2. Here we report high-throughput genomics for SARS-CoV-2, sequencing 80% of cases in Victoria, Australia (population 6.24 million) between 6 January and 14 April 2020 (total 1,333 COVID-19 cases). We integrate epidemiological, genomic and phylodynamic data to identify clusters and impact of interventions. The global diversity of SARS-CoV-2 is represented, consistent with multiple importations. Seventy-six distinct genomic clusters were identified, including large clusters associated with social venues, healthcare and cruise ships. Sequencing sequential samples from 98 patients reveals minimal intra-patient SARS-CoV-2 genomic diversity. Phylodynamic modelling indicates a significant reduction in the effective viral reproductive number (Re) from 1.63 to 0.48 after implementing travel restrictions and physical distancing. Our data provide a concrete framework for the use of SARS-CoV-2 genomics in public health responses, including its use to rapidly identify SARS-CoV-2 transmission chains, increasingly important as social restrictions ease globally.

Structure guided prediction of Pyrazinamide resistance mutations in pncA.

Pyrazinamide plays an important role in tuberculosis treatment; however, its use is complicated by side-effects and challenges with reliable drug susceptibility testing. Resistance to pyrazinamide is largely driven by mutations in pyrazinamidase (pncA), responsible for drug activation, but genetic heterogeneity has hindered development of a molecular diagnostic test. We proposed to use information on how variants were likely to affect the 3D structure of pncA to identify variants likely to lead to pyrazinamide resistance. We curated 610 pncA mutations with high confidence experimental and clinical information on pyrazinamide susceptibility. The molecular consequences of each mutation on protein stability, conformation, and interactions were computationally assessed using our comprehensive suite of graph-based signature methods, mCSM. The molecular consequences of the variants were used to train a classifier with an accuracy of 80%. Our model was tested against internationally curated clinical datasets, achieving up to 85% accuracy. Screening of 600 Victorian clinical isolates identified a set of previously unreported variants, which our model had a 71% agreement with drug susceptibility testing. Here, we have shown the 3D structure of pncA can be used to accurately identify pyrazinamide resistance mutations. SUSPECT-PZA is freely available at: http://biosig.unimelb.edu.au/suspect_pza/.

Single sample scoring of molecular phenotypes.

BACKGROUND: Gene set scoring provides a useful approach for quantifying concordance between sample transcriptomes and selected molecular signatures. Most methods use information from all samples to score an individual sample, leading to unstable scores in small data sets and introducing biases from sample composition (e.g. varying numbers of samples for different cancer subtypes). To address these issues, we have developed a truly single sample scoring method, and associated R/Bioconductor package singscore ( https://bioconductor.org/packages/singscore ). RESULTS: We use multiple cancer data sets to compare singscore against widely-used methods, including GSVA, z-score, PLAGE, and ssGSEA. Our approach does not depend upon background samples and scores are thus stable regardless of the composition and number of samples being scored. In contrast, scores obtained by GSVA, z-score, PLAGE and ssGSEA can be unstable when less data are available (NS < 25). The singscore method performs as well as the best performing methods in terms of power, recall, false positive rate and computational time, and provides consistently high and balanced performance across all these criteria. To enhance the impact and utility of our method, we have also included a set of functions implementing visual analysis and diagnostics to support the exploration of molecular phenotypes in single samples and across populations of data. CONCLUSIONS: The singscore method described here functions independent of sample composition in gene expression data and thus it provides stable scores, which are particularly useful for small data sets or data integration. Singscore performs well across all performance criteria, and includes a suite of powerful visualization functions to assist in the interpretation of results. This method performs as well as or better than other scoring approaches in terms of its power to distinguish samples with distinct biology and its ability to call true differential gene sets between two conditions. These scores can be used for dimensional reduction of transcriptomic data and the phenotypic landscapes obtained by scoring samples against multiple molecular signatures may provide insights for sample stratification.