DODGE: automated point source bacterial outbreak detection using cumulative long term genomic surveillance.

SUMMARY: The reliable and timely recognition of outbreaks is a key component of public health surveillance for foodborne diseases. Whole genome sequencing (WGS) offers high resolution typing of foodborne bacterial pathogens and facilitates the accurate detection of outbreaks. This detection relies on grouping WGS data into clusters at an appropriate genetic threshold. However, methods and tools for selecting and adjusting such thresholds according to the required resolution of surveillance and epidemiological context are lacking. Here we present DODGE (Dynamic Outbreak Detection for Genomic Epidemiology), an algorithm to dynamically select and compare these genetic thresholds. DODGE can analyse expanding datasets over time and clusters that are predicted to correspond to outbreaks (or "investigation clusters") can be named with established genomic nomenclature systems to facilitate integrated analysis across jurisdictions. DODGE was tested in two real-world Salmonella genomic surveillance datasets of different duration, 2 months from Australia and 9 years from the United Kingdom. In both cases only a minority of isolates were identified as investigation clusters. Two known outbreaks in the United Kingdom dataset were detected by DODGE and were recognized at an earlier timepoint than the outbreaks were reported. These findings demonstrated the potential of the DODGE approach to improve the effectiveness and timeliness of genomic surveillance for foodborne diseases and the effectiveness of the algorithm developed. AVAILABILITY AND IMPLEMENTATION: DODGE is freely available at https://github.com/LanLab/dodge and can easily be installed using Conda.

Can genomics and meteorology predict outbreaks of legionellosis in urban settings?

Legionella pneumophila is ubiquitous and sporadically infects humans causing Legionnaire's disease (LD). Globally, reported cases of LD have risen fourfold from 2000 to 2014. In 2016, Sydney, Australia was the epicenter of an outbreak caused by L. pneumophila serogroup 1 (Lpsg1). Whole-genome sequencing was instrumental in identifying the causal clone which was found in multiple locations across the city. This study examined the epidemiology of Lpsg1 in an urban environment, assessed typing schemes to classify resident clones, and investigated the association between local climate variables and LD outbreaks. Of 223 local Lpsg1 isolates, we identified dominant clones with one clone isolated from patients in high frequency during outbreak investigations. The core genome multi-locus sequence typing scheme was the most reliable in identifying this Lpsg1 clone. While an increase in humidity and rainfall was found to coincide with a rise in LD cases, the incidence of the major L. pneumophila outbreak clone did not link to weather phenomena. These findings demonstrated the role of high-resolution typing and weather context assessment in determining source attribution for LD outbreaks in urban settings, particularly when clinical isolates remain scarce.IMPORTANCEWe investigated the genomic and meteorological influences of infections caused by Legionella pneumophila in Sydney, Australia. Our study contributes to a knowledge gap of factors that drive outbreaks of legionellosis compared to sporadic infections in urban settings. In such cases, clinical isolates can be rare, and thus, other data are needed to inform decision-making around control measures. The study revealed that core genome multi-locus sequence typing is a reliable and adaptable technique when investigating Lpsg1 outbreaks. In Sydney, the genomic profile of Lpsg1 was dominated by a single clone, which was linked to numerous community cases over a period of 40 years. Interestingly, the peak in legionellosis cases during Autumn was not associated with this prevalent outbreak clone. Incorporating meteorological data with Lpsg1 genomics can support risk assessment strategies for legionellosis in urban environments, and this approach may be relevant for other densely populated regions globally.

Increase in invasive Haemophilus influenzae serotype A infections during the COVID-19 pandemic in New South Wales, Australia.

Haemophilus influenzae, a causative agent of severe invasive infections such as meningitis, sepsis and pneumonia, is classified into encapsulated or typeable (represented by serotypes A to F) and non-typeable varieties (NTHi) by the presence or absence of the polysaccharide capsule. Invasive disease caused by H. influenzae type B (HIB) can be prevented through vaccination which remains the main disease control intervention in many countries. This study examined the genomic diversity of circulating H. influenzae strains associated with invasive disease in New South Wales, Australia, before and during the COVID-19 pandemic. Ninety-six isolates representing 95 cases of invasive H. influenzae infections (iHi) diagnosed between January 2017 and September 2022 were typed and characterised using whole genome sequencing. These cases were caused by serotypes A (n=24), B (n=35), E (n=3), F (n=2) and NTHi (n=32). There was an apparent decline in the number of iHi infections during the COVID-19 pandemic, with a corresponding increase in the proportion of iHi cases caused by serotype A (HIA), which returned to pre-pandemic levels in 2022. Fifteen isolates associated with HIB or non-typeable iHi were resistant to ß-lactams due to a PBP3 mutation or carriage of blaTEM-1. Further, capsular gene duplication was observed in HIB isolates but was not found in HIA. These findings provide important baseline genomic data for ongoing iHi surveillance and control.

The increasing healthcare burden of enteric fever in a low-incidence setting.

OBJECTIVES: Enteric fever carries appreciable morbidity in non-endemic settings, particularly in returned travelers. This study aimed to characterize the healthcare burden of enteric fever in a low-incidence setting and to identify risk factors and opportunities for preventative interventions. METHODS: Analysis of a retrospective case series from a tertiary pediatric center (2015-2019), augmented by public health notification and microbiological laboratory data (2018-2019), from Western Sydney, Australia, a region with frequent travel links to South Asia. RESULTS: Eighty-nine (89) patients were diagnosed with enteric fever, including 43 children with complete demographic and travel data. Enteric fever cases increased over time (by 4.9 % per year) and incidence was three times higher in the pediatric population (<15 years old) compared to adults. Travel to India and visiting friends and relatives (VFR) travel were risk factors. Few children received enteric fever vaccination prior to travel, as pre-travel advice most commonly was not sought. CONCLUSIONS: Children visiting relatives in high-incidence countries are increasingly at risk for enteric fever, particularly when travelling to South Asia. Targeted health advice to travelers visiting friends and relatives is warranted to mitigate the healthcare burden of enteric fever in low-incidence settings.

Emergence of Poultry-Associated Human Salmonella enterica Serovar Abortusovis Infections, New South Wales, Australia.

Salmonella enterica serovar Abortusovis is a ovine-adapted pathogen that causes spontaneous abortion. Salmonella Abortusovis was reported in poultry in 2009 and has since been reported in human infections in New South Wales, Australia. Phylogenomic analysis revealed a clade of 51 closely related isolates from Australia originating in 2004. That clade was genetically distinct from ovine-associated isolates. The clade was widespread in New South Wales poultry production facilities but was only responsible for sporadic human infections. Some known virulence factors associated with human infections were only found in the poultry-associated clade, some of which were acquired through prophages and plasmids. Furthermore, the ovine-associated clade showed signs of genome decay, but the poultry-associated clade did not. Those genomic changes most likely led to differences in host range and disease type. Surveillance using the newly identified genetic markers will be vital for tracking Salmonella Abortusovis transmission in animals and to humans and preventing future outbreaks.

Impact of Whole-Genome Sequencing of Mycobacterium tuberculosis on Treatment Outcomes for MDR-TB/XDR-TB: A Systematic Review.

The emergence and persistence of drug-resistant tuberculosis is a major threat to global public health. Our objective was to assess the applicability of whole-genome sequencing (WGS) to detect genomic markers of drug resistance and explore their association with treatment outcomes for multidrug-resistant/extensively drug-resistant tuberculosis (MDR/XDR-TB). METHODS: Five electronic databases were searched for studies published in English from the year 2000 onward. Two reviewers independently conducted the article screening, relevant data extraction, and quality assessment. The data of the included studies were synthesized with a narrative method and are presented in a tabular format. RESULTS: The database search identified 949 published articles and 8 studies were included. An unfavorable treatment outcome was reported for 26.6% (488/1834) of TB cases, which ranged from 9.7 to 51.3%. Death was reported in 10.5% (194/1834) of total cases. High-level fluoroquinolone resistance (due to gyrA 94AAC and 94GGC mutations) was correlated as the cause of unfavorable treatment outcomes and reported in three studies. Other drug resistance mutations, like kanamycin high-level resistance mutations (rrs 1401G), rpoB Ile491Phe, and ethA mutations, conferring prothionamide resistance were also reported. The secondary findings from this systematic review involved laboratory aspects of WGS, including correlations with phenotypic DST, cost, and turnaround time, or the impact of WGS results on public health actions, such as determining transmission events within outbreaks. CONCLUSIONS: WGS has a significant capacity to provide accurate and comprehensive drug resistance data for MDR/XDR-TB, which can inform personalized drug therapy to optimize treatment outcomes.

Advancing pathogen genomics in resource-limited settings.

Genomic sequencing has emerged as a powerful tool to enhance early pathogen detection and characterization with implications for public health and clinical decision making. Although widely available in developed countries, the application of pathogen genomics among low-resource, high-disease burden settings remains at an early stage. In these contexts, tailored approaches for integrating pathogen genomics within infectious disease control programs will be essential to optimize cost efficiency and public health impact. We propose a framework for embedding pathogen genomics within national surveillance plans across a spectrum of surveillance and laboratory capacities. We adopt a public health approach to genomics and examine its application to high-priority diseases relevant in resource-limited settings. For each grouping, we assess the value proposition for genomics to inform public health and clinical decision-making, alongside its contribution toward research and development of novel diagnostics, therapeutics, and vaccines.

A laboratory framework for ongoing optimization of amplification-based genomic surveillance programs.

IMPORTANCE: This study provides a laboratory framework to ensure ongoing relevance and performance of amplification-based whole genome sequencing to strengthen public health surveillance during extended outbreaks or pandemics. The framework integrates regular reviews of the performance of a genomic surveillance system and highlights the importance of ongoing monitoring and the identification and implementation of improvements to whole genome sequencing methods to enhance public health responses to pathogen outbreaks.

The altered sputum microbiome profile in patients with moderate and severe COPD exacerbations, compared to the healthy group in the Indian population.

Background: Microbial culture-independent sequencing techniques have advanced our understanding of host-microbiome interactions in health and disease. The purpose of this study was to explore the dysbiosis of airway microbiota in patients with moderate or severe chronic obstructive pulmonary disease (COPD) and compare them with healthy controls. Methods: The COPD patients were investigated for disease severity based on airflow limitations and divided into moderate (50%≤FEV1<80% predicted) and severe groups (FEV1<50% predicted). Spontaneous sputum samples were collected and, the V3-V4 regions of the 16S rRNA coding gene were sequenced to examine the microbiome profile of COPD and healthy participants. Results: A total of 45 sputum samples were collected from 17 severe COPD, 12 moderate COPD cases, and 16 healthy volunteers. The bacterial alpha diversity (Shannon and Simpson's index) significantly decreased in the moderate and severe COPD groups, compared to healthy samples. A significantly higher proportion of Firmicutes and Actinobacteria were present in moderate COPD, and Proteobacteria numbers were comparatively increased in severe COPD. In healthy samples, Bacteroidetes and Fusobacteria were more abundant in comparison to both the COPD groups. Among the most commonly detected 20 bacterial genera, Streptococcus was predominant among the COPD sputum samples, whereas Prevotella was the top genus in healthy controls. Linear discriminant analysis (LDA>2) revealed that marker genera like Streptococcus and Rothia were abundant in moderate COPD. For severe COPD, the genera Pseudomonasand Leptotrichia were most prevalent, whereas Fusobacterium and Prevotella were dominant in the healthy group. Conclusions: Our findings suggest a significant dysbiosis of the respiratory microbiome in COPD patients. The decreased microbial diversity may influence the host immune response and provide microbiological biomarkers for the diagnosis and monitoring of COPD.

First documented gymnasium cluster of COVID-19 with whole genome sequencing in Australia.

Background: Transmission of coronavirus disease 2019 (COVID-19) has been demonstrated in fitness settings internationally. We report the first documented case of transmission of COVID-19 in a gymnasium in Australia in 2020. Methods: Case finding and case interviews were conducted among attendees in a Western Sydney gymnasium, Australia. Whole genome sequencing using an amplicon-based approach was performed on all SARS CoV-2 polymerase chain reaction positive samples detected through surveillance. Results: We show that five cases of COVID-19 were linked to the gymnasium, with transmission occurring on 7 July 2020, when the index case transmitted the infection to four other gymnasium attendees through the sharing of an enclosed space. Conclusions: There is an ongoing risk of transmission of COVID-19 within gymnasium environments and they are justifiably classified as a 'high-risk' venue. There may be a need to expand ventilation and space requirements to prevent transmission of COVID-19 in such settings in the context of severe COVID-19 variants or to prevent respiratory disease transmission in general.

Exploring programmatic indicators of tuberculosis control that incorporate routine Mycobacterium tuberculosis sequencing in low incidence settings: a comprehensive (2017-2021) patient cohort analysis.

Background: Routine whole genome sequencing of Mycobacterium tuberculosis has been implemented with increasing frequency. However, its value for tuberculosis (TB) control programs beyond individual case management and enhanced drug resistance detection has not yet been explored. Methods: We analysed routine sequencing data of culture-confirmed TB cases notified between 1st January 2017 and 31st December 2021 in New South Wales (NSW), Australia. Genomic surveillance included evidence of local TB transmission, defined by single nucleotide polymorphism (SNP) clustering over a variable (0-25) SNP threshold, and drug resistance conferring mutations. Findings: M. tuberculosis sequences from 1831 patients were examined, representing 64.8% of all notified TB cases and 96.2% of culture-confirmed cases. Applying a traditional 5-SNP cluster threshold identified 62 transmission clusters with 183 clustered cases; 101/183 (55.2%) had 0 SNP differences. Cluster assessment over a 5-year period, using a 5-SNP threshold, provided a comprehensive overview of likely recent transmission within NSW, Australia, as an indicator of local TB control. Genotypic drug susceptibility testing (DST) was highly concordant with phenotypic DST and provided a 6.8% increase in antimycobacterial resistance detection. Importantly, it detected mutations missed by routine molecular tests. Lineage 2 strains were more likely to be drug resistant (p < 0.0001) and locally transmitted if drug resistant (p < 0.0001). Interpretation: Performing routine prospective WGS in a low incidence country like Australia, provides genomically informed programmatic indicators of local TB control. A rolling 5-year cluster assessment reflects epidemic containment and progress towards 'zero TB transmission'. Genomic DST also provides valuable information for clinical care and drug resistance surveillance. Funding: NHMRC Centre for Research Excellence in Tuberculosis (www.tbcre.org.au) and NSW Health Prevention Research Support Program.

Genomic markers of drug resistance in Mycobacterium tuberculosis populations with minority variants.

Minority variants of Mycobacterium tuberculosis harboring mutations conferring resistance can become dominant populations during tuberculosis (TB) treatment, leading to treatment failure. Our understanding of drug-resistant within-host subpopulations and the frequency of resistance-conferring mutations in minority variants remains limited. M. tuberculosis sequences recovered from liquid cultures of culture-confirmed TB cases notified between January 2017 and December 2021 in New South Wales, Australia were examined. Potential drug resistance-conferring minority variants were identified using LoFreq, and mixed populations of different M. tuberculosis strains (≥100 SNPs apart) were examined using QuantTB. A total of 1831 routinely sequenced M. tuberculosis strains were included in the analysis. Drug resistance-conferring minority variants were detected in 3.5% (65/1831) of sequenced cultures; 84.6% (55/65) had majority strains that were drug susceptible and 15.4% (10/65) had majority strains that were drug resistant. Minority variants with high-confidence drug resistance-conferring mutations were 1.5 times more common when the majority strains were drug resistant. Mixed M. tuberculosis strain populations were documented in 10.0% (183/1831) of specimens. Minority variants with high-confidence drug resistance-conferring mutations were more frequently detected in mixed M. tuberculosis strain populations (2.7%, 5/183) than in single strain populations (0.6%, 10/1648; P = 0.01). Drug-resistant minority variants require monitoring in settings that implement routine M. tuberculosis sequencing. The frequency with which drug-resistant minority variants are detected is likely influenced by pre-culture requirement. Culture-independent sequencing methods should provide a more accurate reflection of drug-resistant subpopulations.

Community Outbreak of Pseudomonas aeruginosa Infections Associated with Contaminated Piercing Aftercare Solution, Australia, 2021.

In April 2021, the South Eastern Sydney Local Health District Public Health Unit (Sydney, New South Wales, Australia) was notified of 3 patients with Pseudomonas aeruginosa infections secondary to skin piercings performed at the same salon. Active case finding through laboratories, clinician alerts, and monitoring hospital visits for piercing-related infections identified additional cases across New South Wales, and consumers were alerted. We identified 13 confirmed and 40 probable case-patients and linked clinical isolates by genomic sequencing. Ten confirmed case-patients had used the same brand and batch of aftercare solution. We isolated P. aeruginosa from opened and unopened bottles of this solution batch that matched the outbreak strain identified by genomic sequencing. Piercing-related infections returned to baseline levels after this solution batch was recalled. Early outbreak detection and source attribution via genomic sequencing are crucial for controlling outbreaks linked to contaminated products. Manufacturing standards for nonsterile cosmetic products and guidance for piercing aftercare warrant review.

Persistent Salmonella enterica serovar Typhi sub-populations within host interrogated by whole genome sequencing and metagenomics.

Salmonella enterica serovar Typhi (S. Typhi) causes typhoid fever and, in some cases, chronic carriage after resolution of acute disease. This study examined sequential isolates of S. Typhi from a single host with persistent asymptomatic infection. These isolates, along with another S. Typhi isolate recovered from a household contact with typhoid fever, were subjected to whole genome sequencing and analysis. In addition, direct sequencing of the bile fluid from the host with persistent infection was also performed. Comparative analysis of isolates revealed three sub-populations of S. Typhi with distinct genetic patterns. Metagenomic sequencing recognised only two of the three sub-populations within the bile fluid. The detection and investigation of insertion sequences IS10R and associated deletions complemented analysis of single nucleotide polymorphisms. These findings improve our understanding of within-host dynamics of S. Typhi in cases of persistent infection and inform epidemiological investigations of transmission events associated with chronic carriers.

Genomic epidemiology and multilevel genome typing of Bordetella pertussis.

Bordetella pertussis causes pertussis (or whooping cough), a severe respiratory infectious disease in infants, although it can be prevented by whole cell and acellular vaccines. The recent pertussis resurgence in industrialised countries is partly attributed to pathogen adaptation to vaccines, while emergence of antimicrobial resistance, specifically to macrolides in China, has become a concern. Surveillance of current circulating and emerging strains is therefore vital to understand the risks they pose to public health. Although the use of genomics-based typing is increasing a genomic nomenclature for this pathogen has not been well established. Here, we implemented the multilevel genome typing (MGT) system for B. pertussis with five levels of resolution, which provide targeted typing of relevant lineages and discrimination of closely related strains at the finest scale. The lower resolution levels (MGT2 and MGT3) describe the distribution of major vaccine antigen alleles including ptxP, fim3, fhaB and prn, as well as temporal and spatial trends within the B. pertussis global population. Mid-resolution levels (MGT3 and MGT4) enable typing of antibiotic-resistant lineages and Prn deficient lineages within the ptxP3 clade. The high-resolution level (MGT5) can capture finer-scale epidemiology such as outbreaks and local transmission events, with comparable resolution to existing genomic methods of strain-relatedness assessment. The scheme offers stable MGT-type assignments aiding harmonisation of typing and communication between laboratories. The scheme is available at https://mgtdb.unsw.edu.au/pertussis, is regularly updated from global data repositories and accepts public submissions. The MGT scheme provides a comprehensive, robust, and scalable system for global surveillance of B. pertussis.

SABRes: in silico detection of drug resistance conferring mutations in subpopulations of SARS-CoV-2 genomes.

The emergence of resistance to antiviral drugs increasingly used to treat SARS-CoV-2 infections has been recognised as a significant threat to COVID-19 control. In addition, some SARS-CoV-2 variants of concern appear to be intrinsically resistant to several classes of these antiviral agents. Therefore, there is a critical need for rapid recognition of clinically relevant polymorphisms in SARS-CoV-2 genomes associated with significant reduction of drug activity in virus neutralisation experiments. Here we present SABRes, a bioinformatic tool, which leverages on expanding public datasets of SARS-CoV-2 genomes and allows detection of drug resistance mutations in consensus genomes as well as in viral subpopulations. We have applied SABRes to detect resistance-conferring mutations in 25,197 genomes generated over the course of the SARS-CoV-2 pandemic in Australia and identified 299 genomes containing resistance conferring mutations to the five antiviral therapeutics that retain effectiveness against currently circulating strains of SARS-CoV-2 - Sotrovimab, Bebtelovimab, Remdesivir, Nirmatrelvir and Molnupiravir. These genomes accounted for a 1.18% prevalence of resistant isolates discovered by SABRes, including 80 genomes with resistance conferring mutations found in viral subpopulations. Timely recognition of these mutations within subpopulations is critical as these mutations can provide an advantage under selective pressure and presents an important step forward in our ability to monitor SARS-CoV-2 drug resistance.