Combined visualization of genomic and epidemiological data for outbreaks.

In epidemiological investigations, pathogen genomics can provide insights and test epidemiological hypotheses that would not have been possible through traditional epidemiology. Tools to synthesize genomic analysis with other types of data are a key requirement of genomic epidemiology. We propose a new 'phylepic' visualization that combines a phylogenomic tree with an epidemic curve. The combination visually links the molecular time represented in the tree to the calendar time in the epidemic curve, a correspondence that is not easily represented by existing tools. Using an example derived from a foodborne bacterial outbreak, we demonstrated that the phylepic chart communicates that what appeared to be a point-source outbreak was in fact composed of cases associated with two genetically distinct clades of bacteria. We provide an R package implementing the chart. We expect that visualizations that place genomic analyses within the epidemiological context will become increasingly important for outbreak investigations and public health surveillance of infectious diseases.

Genomic diversity of Salmonella enterica serovar Typhimurium isolated from chicken processing facilities in New South Wales, Australia.

Contamination of poultry products by Salmonella enterica serovar Typhimurium (STm) is a major cause of foodborne infections and outbreaks. This study aimed to assess the diversity and antimicrobial resistance (AMR) carriage of STm in three chicken processing plants using genomic sequencing. It also aimed to investigate whether any particular strain types were associated with cases of human illness. Multilevel genome typing (MGT) was used to analyze 379 STm isolates from processed chicken carcasses. The diversity of chicken STm sequence types (STs) increased from MGT1 (2 STs) to MGT9 (257 STs). STs at MGT5 to MGT9 levels that were unique to one processing plant and shared among the processing plants were identified, likely reflecting the diversity of STm at their farm source. Fifteen medium resolution MGT5 STs matched those from human infections in Australia and globally. However, no STs matched between the chicken and human isolates at high resolution levels (MGT8 or MGT9), indicating the two STm populations were phylogenetically related but were unlikely to be directly epidemiologically linked. AMR genes were rare, with only a bla TEM-1 gene carried by a 95 kb IncI1 Alpha plasmid being identified in 20 isolates. In conclusion, subpopulations that were widespread in processing plants and had caused human infections were described using MGT5 STs. In this STM population, AMR was rare with only sporadic resistance to a single drug class observed. The genomic analysis of STm from chicken processing plants in this study provided insights into STm that contaminate meat chickens early in the food production chain.

Respiratory diphtheria in the time of Omicron.

Abstract: Diphtheria is a potentially fatal bacterial infection caused by toxin-producing strains of corynebacteria, most often Corynebacterium diphtheriae and less commonly Corynebacterium ulcerans. Incidence of the disease has fallen significantly since the introduction of vaccination programs; it is now rare in countries with high vaccination coverage such as Australia. This article presents the most recent respiratory cases of diphtheria in two children in New South Wales-the first locally acquired childhood cases in Australia in 30 years-and discusses potential contributing factors. These encompass the lack of clinical awareness and the delays in laboratory diagnosis in regional laboratories. The cases also highlight the problem of vaccine hesitancy and the role that primary carers play in addressing these anxieties. While clinical management of the cases progressed well, factors in the public health responses were complicated by access to appropriate care and by delays in antibiotic sensitivity profiles. The public health response to these cases raises important considerations for clinicians and public health practitioners, including preparedness for rare and re-emerging diseases, the need for culturally safe environments and the importance of addressing vaccine hesitancy. Preparedness requires consideration of the capacity of regional health systems with fewer resources and of how public health departments can support response to multiple crises. Preparedness also relies on access to necessary diagnostic laboratory resources, on up-to-date guidelines, and on maintaining awareness among clinicians for these rare infections.

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.

Genomic characteristics of prospectively sequenced Mycobacterium tuberculosis from respiratory and non-respiratory sources.

Understanding the differences between Mycobacterium tuberculosis strains isolated from respiratory and non-respiratory sources may inform clinical care and control strategies. We examined demographic and genomic characteristics of all culture-confirmed M. tuberculosis cultures isolated from respiratory and non-respiratory sources in New South Wales, Australia, from January 2017 to December 2021, using logistic regression models. M. tuberculosis strains from 1,831 patients were sequenced; 64.7% were from respiratory, 32.1% from non-respiratory, and 2.2% from both sources. Female patients had more frequent isolation from a non-respiratory source (p = 0.03), and older adults (≧65 years) from a respiratory source (p < 0.0001). Lineage 2 strains were relatively over-represented among respiratory isolates (p = 0.01). Among 39 cases with sequenced isolates from both sources, 43.6% had 1-10 single nucleotide polymorphism differences. The finding that older adults were more likely to have M. tuberculosis isolated from respiratory sources has relevance for TB control given the expected rise of TB among older adults.

Sustained transmission over two decades of a previously unrecognised MPT64 negative Mycobacterium tuberculosis strain in Queensland, Australia: a whole genome sequencing study.

Background: MPT64 is a key protein used for Mycobacterium tuberculosis (MTB) complex strain identification. We describe protracted transmission of an MPT64 negative MTB strain in Queensland, Australia, and explore genomic factors related to its successful spread. Methods: All MPT64 negative strains identified between 2002 and 2022 by the Queensland Mycobacteria Reference Laboratory, and an additional 2 isolates from New South Wales (NSW), were whole genome sequenced. Bayesian modelling and phylogeographical analyses were used to assess their evolutionary history and transmission dynamics. Protein structural modelling to understand the putative functional effects of the mutated gene coding for MPT64 protein was performed. Findings: Forty-three MPT64 negative isolates were sequenced, belonging to a single MTB cluster of Lineage 4.1.1.1 strains. Combined with a UK dataset of the same lineage, molecular dating estimated 1990 (95% HPD 1987-1993) as the likely time of strain introduction into Australia. Although the strain has spread over a wide geographic area and new cases linked to the cluster continue to arise, phylodynamic analysis suggest the outbreak peaked around 2003. All MPT64 negative strains had a frame shift mutation (delAT, p.Val216fs) within the MPT64 gene, which confers two major structural rearrangements at the C-terminus of the protein. Interpretation: This study uncovered the origins of an MPT64 negative MTB outbreak in Australia, providing a richer understanding of its biology and transmission dynamics, as well as guidance for clinical diagnosis and public health action. The potential spread of MPT64 negative strains undermines the diagnostic utility of the MPT64 immunochromatographic test. Funding: This study was funded from an operational budget provided to the Queensland Mycobacterium Reference Laboratory by Pathology Queensland, Queensland Department of Health.

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.

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.

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.