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.

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.

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.

Genome entropy and network centrality contrast exploration and exploitation in evolution of foodborne pathogens.

Modelling evolution of foodborne pathogens is crucial for mitigation and prevention of outbreaks. We apply network-theoretic and information-theoretic methods to trace evolutionary pathways ofSalmonellaTyphimurium in New South Wales, Australia, by studying whole genome sequencing surveillance data over a five-year period which included several outbreaks. The study derives both undirected and directed genotype networks based on genetic proximity, and relates the network's structural property (centrality) to its functional property (prevalence). The centrality-prevalence space derived for the undirected network reveals a salient exploration-exploitation distinction across the pathogens, further quantified by the normalised Shannon entropy and the Fisher information of the corresponding shell genome. This distinction is also analysed by tracing the probability density along evolutionary paths in the centrality-prevalence space. We quantify the evolutionary pathways, and show that pathogens exploring the evolutionary search-space during the considered period begin to exploit their environment (their prevalence increases resulting in outbreaks), but eventually encounter a bottleneck formed by epidemic containment measures.

LncRNA PVT1 Confers Cisplatin Resistance of Esophageal Cancer Cells through Modulating the miR-181a-5p-Glutaminase (GLS) Axis.

Esophageal carcinoma (ESCA) is one of the prevalent malignancies worldwide. Cisplatin (CDDP) is a conventional chemotherapy drug. However, the acquired cisplatin resistance limits its extensively clinical applications. In this study, the roles and underlying mechanisms of lncRNA PVT1 in cisplatin-resistant ESCA are investigated. PVT1 was significantly upregulated in ESCA patient specimens and cell lines. Higher PVT1 level was associated with a poor survival rate of ESCA patients. Silencing PVT1 effectively increased cisplatin sensitivity of ESCA cells. We established cisplatin-resistant ESCA cell line (EC109 CDDP Res) and detected that PVT1 and glutamine metabolism were remarkedly elevated in CDDP-resistant esophageal cancer cells. Bioinformatical analysis and luciferase assay illustrated that PVT1 sponged miR-181a-5p to form a ceRNA network, resulting in the downregulation of miR-181a-5p expression in ESCA cells. Glutaminase (GLS), which is a key enzyme in the glutamine metabolism, was identified and validated as a direct target of miR-181-5p in ESCA cells. Inhibiting glutamine metabolism effectively re-sensitized CDDP-resistant cells. Rescue experiments demonstrated that restoration of miR-181a-5p in PVT1-overexpressing CDDP-resistant ESCA cells successfully overcame the PVT1-promoted cisplatin resistance through targeting GLS. Summarily, our study revealed molecular mechanisms of the lncRNA PVT1-promoted cisplatin resistance in ESCA by modulating the miR-181a-5p-GLS axis.

Multistate Outbreak of Salmonella enterica Serovar Heidelberg with Unidentified Source, Australia, 2018-2019.

We report a multistate Salmonella enterica serovar Heidelberg outbreak in Australia during 2018-2019. Laboratory investigation of cases reported across 5 jurisdictions over a 7-month period could not identify a source of infection but detected indicators of severity and invasiveness. The hospitalization rate of 36% suggested a moderately severe clinical picture.

Genomic Surveillance Enables Suitability Assessment of Salmonella Gene Targets Used for Culture-Independent Diagnostic Testing.

Salmonella is a highly diverse genus consisting of over 2,600 serovars responsible for high-burden food- and waterborne gastroenteritis worldwide. Sensitivity and specificity of PCR-based culture-independent diagnostic testing (CIDT) systems for Salmonella, which depend on a highly conserved gene target, can be affected by single nucleotide polymorphisms (SNPs), indels, and genomic rearrangements within primer and probe sequences. This report demonstrates the value of prospectively collected genomic data for verifying CIDT targets. We utilized the genomes of 3,165 Salmonella isolates prospectively collected and sequenced in Australia. The sequences of Salmonella CIDT PCR gene targets (ttrA, spaO, and invA) were systematically interrogated to measure nucleotide dissimilarity. Analysis of 52 different serovars and 79 multilocus sequencing types (MLST) demonstrated dissimilarity within and between PCR gene targets ranging between 0 and 81.3 SNP/kbp (0 and 141 SNPs). The lowest average dissimilarity was observed in the ttrA target gene used by the Roche LightMix at 2.0 SNP/kbp (range, 0 to 46.7); however, entropy across the gene demonstrates that it may not be the most stable CIDT target. While debate continues over the benefits and pitfalls of replacing bacterial culture with molecular assays, the growing volumes of genomic surveillance data enable periodic regional reassessment and validation of CIDT targets against both prevalent and emerging serovars. If PCR systems are to become the primary screening and diagnostic tool for laboratory diagnosis of salmonellosis, ongoing monitoring of the genomic diversity in PCR target regions is warranted, as is the potential inclusion of two Salmonella PCR targets in frontline diagnostic systems.

Multilevel genome typing: genomics-guided scalable resolution typing of microbial pathogens.

BackgroundBoth long- and short-term epidemiology are fundamental to disease control and require accurate bacterial typing. Genomic data resulting from implementation of whole genome sequencing in many public health laboratories can potentially provide highly sensitive and accurate descriptions of strain relatedness. Previous typing efforts using these data have mainly focussed on outbreak detection.AimWe aimed to develop multilevel genome typing (MGT), using consecutive multilocus sequence typing (MLST) schemes of increasing sizes, stepping up from seven-gene MLST to core genome MLST, to allow examination of genetic relatedness at multiple resolution levels.MethodsThe system was applied to Salmonellaenterica serovar Typhimurium. The MLST scheme used at each step (MGT level), defined a given MGT-level specific sequence type (ST). The list of STs generated from all of these increasing MGT levels, was named a genome type (GT). Using MGT, we typed 9,096 previously characterised isolates with publicly available data.ResultsOur approach could identify previously described S. Typhimurium populations, such as the DT104 multidrug resistance lineage (GT 19-2-11) and two invasive lineages of African isolates (GT 313-2-3 and 313-2-752). Further, we showed that MGT-derived clusters can accurately distinguish five outbreaks from each other and five background isolates.ConclusionMGT provides a universal and stable nomenclature at multiple resolutions for S. Typhimurium strains and could be implemented as an internationally standardised strain identification system. While established so far only for S. Typhimurium, the results here suggest that MGT could form the basis for typing systems in other similar microorganisms.

A series of three cases of severe Clostridium difficile infection in Australia associated with a binary toxin producing clade 2 ribotype 251 strain.

Three patients with severe Clostridium difficile infection (CDI) caused by an unusual strain of C. difficile, PCR ribotype (RT) 251, were identified in New South Wales, Australia. All cases presented with severe diarrhoea, two had multiple recurrences and one died following a colectomy. C. difficile RT251 strains were isolated by toxigenic culture. Genetic characterisation was performed using techniques including toxin gene profiling, PCR ribotyping, whole genome sequencing (WGS), in-silico multi-locus-sequence-typing (MLST) and core-genome single nucleotide variant (SNV) analyses. Antimicrobial susceptibility was determined using an agar incorporation method. In vitro toxin production was confirmed by Vero cell cytotoxicity assay and pathogenicity was assessed in a murine model of CDI. All RT251 isolates contained toxin A (tcdA), toxin B (tcdB) and binary toxin (cdtA and cdtB) genes. Core-genome analyses revealed the RT251 strains were clonal, with 0-5 SNVs between isolates. WGS and MLST clustered RT251 in the same evolutionary clade (clade 2) as RT027. Despite comparatively lower levels of in vitro toxin production, in the murine model RT251 infection resembled RT027 infection. Mice showed marked weight loss, severe disease within 48 h post-infection and death. All isolates were susceptible to metronidazole and vancomycin. Our observations suggest C. difficile RT251 causes severe disease and emphasise the importance of ongoing surveillance for new and emerging strains of C. difficile with enhanced virulence.

Novel Salmonella enterica Serovar Typhimurium Genotype Levels as Herald of Seasonal Salmonellosis Epidemics.

We examined the population dynamics of Salmonella enterica serovar Typhimurium during seasonal salmonellosis epidemics in New South Wales, Australia, during 2009-2016. Of 15,626 isolates, 5%-20% consisted of novel genotypes. Seasons with salmonellosis epidemics were associated with a reduction in novel genotypes in the preceding winter and spring.

Burkholderia lata Infections from Intrinsically Contaminated Chlorhexidine Mouthwash, Australia, 2016.

Burkholderia lata was isolated from 8 intensive care patients at 2 tertiary hospitals in Australia. Whole-genome sequencing demonstrated that clinical and environmental isolates originated from a batch of contaminated commercial chlorhexidine mouthwash. Genomic analysis identified efflux pump-encoding genes as potential facilitators of bacterial persistence within this biocide.

Multidrug-Resistant Salmonella enterica 4,[5],12:i:- Sequence Type 34, New South Wales, Australia, 2016-2017.

Multidrug- and colistin-resistant Salmonella enterica serotype 4,[5],12:i:- sequence type 34 is present in Europe and Asia. Using genomic surveillance, we determined that this sequence type is also endemic to Australia. Our findings highlight the public health benefits of genome sequencing-guided surveillance for monitoring the spread of multidrug-resistant mobile genes and isolates.

Genome Sequencing Links Persistent Outbreak of Legionellosis in Sydney (New South Wales, Australia) to an Emerging Clone of Legionella pneumophila Sequence Type 211.

The city of Sydney, Australia, experienced a persistent outbreak of Legionella pneumophila serogroup 1 (Lp1) pneumonia in 2016. To elucidate the source and guide public health actions, the genomes of clinical and environmental Lp1 isolates recovered over 7 weeks were examined. A total of 48 isolates from human cases and cooling towers were sequenced and compared using single-nucleotide polymorphism (SNP)-based core-genome multilocus sequencing typing (MLST) and pangenome approaches. All three methods confirmed phylogenetic relatedness between isolates associated with outbreaks in the Central Business District (CBD) in March and May and those in suburb 1. These isolates were designated the "main cluster" and consisted of isolates from two patients from the CBD March outbreak, one patient and one tower isolate from suburb 1, and isolates from two cooling towers and three patients from the CBD May outbreak. All main cluster isolates were sequence type 211 (ST211), which previously has only been reported in Canada. Significantly, pangenome analysis identified mobile genetic elements containing a unique type IV A F-type secretion system (T4ASS), which was specific to the main cluster, and cocirculating clinical strains, suggesting a potential mechanism for increased fitness and persistence of the outbreak clone. Genome sequencing enabled linking of the geographically dispersed environmental sources of infection among the spatially and temporally coinciding cases of legionellosis in a highly populated urban setting. The discovery of a unique T4ASS emphasizes the role of genome recombination in the emergence of successful Lp1 clones.IMPORTANCE A new emerging clone has been responsible for a prolonged legionellosis outbreak in Sydney, Australia. The use of whole-genome sequencing linked two outbreaks thought to be unrelated and confirmed the outliers. These findings led to the resampling and subsequent identification of the source, guiding public health actions and bringing the outbreak to a close. Significantly, the outbreak clone was identified as sequence type 211 (ST211). Our study reports this ST in the Southern Hemisphere and presents a description of ST211 genomes from both clinical and environmental isolates. A unique mobile genetic element containing a type IV secretion system was identified in Lp1 ST211 isolates linked to the main cluster and Lp1 ST42 isolates that were cocirculating at the time of the outbreak.

Incorporating Whole-Genome Sequencing into Public Health Surveillance: Lessons from Prospective Sequencing of Salmonella Typhimurium in Australia.

In Australia, the incidence of Salmonella Typhimurium has increased dramatically over the past decade. Whole-genome sequencing (WGS) is transforming public health microbiology, but poses challenges for surveillance. To compare WGS-based approaches with conventional typing for Salmonella surveillance, we performed concurrent WGS and multilocus variable-number tandem-repeat analysis (MLVA) of Salmonella Typhimurium isolates from the Australian Capital Territory (ACT) for a period of 5 months. We exchanged data via a central shared virtual machine and performed comparative genomic analyses. Epidemiological evidence was integrated with WGS-derived data to identify related isolates and sources of infection, and we compared WGS data for surveillance with findings from MLVA typing. We found that WGS data combined with epidemiological data linked an additional 9% of isolates to at least one other isolate in the study in contrast to MLVA and epidemiological data, and 19% more isolates than epidemiological data alone. Analysis of risk factors showed that in one WGS-defined cluster, human cases had higher odds of purchasing a single egg brand. While WGS was more sensitive and specific than conventional typing methods, we identified barriers to uptake of genomic surveillance around complexity of reporting of WGS results, timeliness, acceptability, and stability. In conclusion, WGS offers higher resolution of Salmonella Typhimurium laboratory surveillance than existing methods and can provide further evidence on sources of infection in case and outbreak investigations for public health action. However, there are several challenges that need to be addressed for effective implementation of genomic surveillance in Australia.

Seven Salmonella Typhimurium Outbreaks in Australia Linked by Trace-Back and Whole Genome Sequencing.

Salmonella Typhimurium is a common cause of foodborne illness in Australia. We report on seven outbreaks of Salmonella Typhimurium multilocus variable-number tandem-repeat analysis (MLVA) 03-26-13-08-523 (European convention 2-24-12-7-0212) in three Australian states and territories investigated between November 2015 and March 2016. We identified a common egg grading facility in five of the outbreaks. While no Salmonella Typhimurium was detected at the grading facility and eggs could not be traced back to a particular farm, whole genome sequencing (WGS) of isolates from cases from all seven outbreaks indicated a common source. WGS was able to provide higher discriminatory power than MLVA and will likely link more Salmonella Typhimurium cases between states and territories in the future. National harmonization of Salmonella surveillance is important for effective implementation of WGS for Salmonella outbreak investigations.

Francisella tularensis ssp. holarctica in Ringtail Possums, Australia.

The occurrence of Francisella tularensis outside of endemic areas, such as North America and Eurasia, has been enigmatic. We report the metagenomic discovery and isolation of F. tularensis ssp. holarctica biovar japonica from diseased ringtail possums in Sydney, Australia. This finding confirms the presence of F. tularensis in the Southern Hemisphere.

Whole genome sequencing of Salmonella Typhimurium illuminates distinct outbreaks caused by an endemic multi-locus variable number tandem repeat analysis type in Australia, 2014.

BACKGROUND: Salmonella Typhimurium (STM) is an important cause of foodborne outbreaks worldwide. Subtyping of STM remains critical to outbreak investigation, yet current techniques (e.g. multilocus variable number tandem repeat analysis, MLVA) may provide insufficient discrimination. Whole genome sequencing (WGS) offers potentially greater discriminatory power to support infectious disease surveillance. METHODS: We performed WGS on 62 STM isolates of a single, endemic MLVA type associated with two epidemiologically independent, food-borne outbreaks along with sporadic cases in New South Wales, Australia, during 2014. Genomes of case and environmental isolates were sequenced using HiSeq (Illumina) and the genetic distance between them was assessed by single nucleotide polymorphism (SNP) analysis. SNP analysis was compared to the epidemiological context. RESULTS: The WGS analysis supported epidemiological evidence and genomes of within-outbreak isolates were nearly identical. Sporadic cases differed from outbreak cases by a small number of SNPs, although their close relationship to outbreak cases may represent an unidentified common food source that may warrant further public health follow up. Previously unrecognised mini-clusters were detected. CONCLUSIONS: WGS of STM can discriminate foodborne community outbreaks within a single endemic MLVA clone. Our findings support the translation of WGS into public health laboratory surveillance of salmonellosis.

Delineating community outbreaks of Salmonella enterica serovar Typhimurium by use of whole-genome sequencing: insights into genomic variability within an outbreak.

Whole-genome next-generation sequencing (NGS) was used to retrospectively examine 57 isolates from five epidemiologically confirmed community outbreaks (numbered 1 to 5) caused by Salmonella enterica serovar Typhimurium phage type DT170. Most of the human and environmental isolates confirmed epidemiologically to be involved in the outbreaks were either genomically identical or differed by one or two single nucleotide polymorphisms (SNPs), with the exception of those in outbreak 1. The isolates from outbreak 1 differed by up to 12 SNPs, which suggests that the food source of the outbreak was contaminated with more than one strain while each of the other four outbreaks was caused by a single strain. In addition, NGS analysis ruled in isolates that were initially not considered to be linked with the outbreak, which increased the total outbreak size by 107%. The mutation process was modeled by using known mutation rates to derive a cutoff value for the number of SNP difference to determine whether or not a case was part of an outbreak. For an outbreak with less than 1 month of ex vivo/in vivo evolution time, the maximum number of SNP differences between isolates is two or four using the lowest or highest mutation rate, respectively. NGS of S. Typhimurium significantly increases the resolution of investigations of community outbreaks. It can also inform a more targeted public health response by providing important supplementary evidence that cases of disease are or are not associated with food-borne outbreaks of S. Typhimurium.