2. Abstract Streptococcus pneumoniae is the leading cause of empyema and pneumonia in children, and monitoring of effectiveness of polyvalent pneumococcal vaccines has been essential for controlling invasive pneumococcal disease (IPD) in children and elderly adults. Conventional serotyping of pneumococci has relied on Quellung reaction following laboratory culture, however more recently whole genome sequencing (WGS) has been implemented in many reference laboratories to enhance traditional typing. Pleural fluid samples from cases with empyema are often culture negative, limiting the utility of WGS and requiring polymerase chain reaction (PCR) or 16S rRNA sequencing to detect S. pneumoniae . These molecular methods have limited sensitivity and capacity to characterise pneumococcus in clinical samples, especially in specimens with a low pathogen abundance. This study applied capture-based enrichment (tNGS) to identify and characterise S. pneumoniae directly from pleural fluid samples. A total of 51 pleural fluid samples were subjected to tNGS with a custom probe panel, for 39 known positive fluids collected from IPD cases between 2018-2025 in New South Wales, Australia. tNGS results were benchmarked against molecular-based serotyping. Our tNGS achieved 100% sensitivity and specificity in detecting S. pneumoniae . Serotyping results were concordant with PCR and 95% (37/39) of S. pneumoniae PCR positive pleural fluid cases could be serotyped using tNGS. Standard molecular methods however could only determine serotype in 56% (22/39) of samples. This tNGS enabled 39% improvement in ability to directly identify and serotype IPD-associated serotypes of S. pneumoniae in difficult-to-culture pleural fluids can significantly enhance laboratory surveillance of IPD as well as our understanding of vaccine effectiveness. 3. Impact statement There is currently a gap in understanding the pneumococcus serotype diversity causing infection within the pleural fluid space. The gold-standard Quellung method to determine serotype relies on culturing the pneumococci first. However, pleural fluids often remain culture-negative, and cases of pneumococcal empyema have been a historical ‘blind spot’ in pneumococcal surveillance. This study offers a new methodology to close this gap and allow serotyping of previously untypable cases. The study demonstrated a targeted next generation sequencing (tNGS) approach to determine serotype without the need to first culture the bacteria. This novel use of tNGS targets part of the cps gene cluster, which determines serotype. To the best of our knowledge this is the first panel to do so. We have successfully serotyped 95% of pleural fluid S.pneumoniae PCR positive samples, where previously only 56% could be determined using conventional PCR typing methods. This demonstrates for the first time a novel tNGS method capable of determining the full serotype landscape causing pleural fluid infection. This development will enhance the understanding of vaccine effectiveness and contribute to the prevention of invasive pneumococcal disease. 4. Data summary Supplementary data containing reference cpsB genomes are available within this article. The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. 1.5 Repositories ENA project accession number PRJEB111154. All supporting data has been provided within the article or in supplementary data files. One supplementary data file is available with the online version of this article.

Horizontal gene transfer introduces foreign DNA that can disrupt cellular processes and is therefore subject to xenogeneic silencing by nucleoid-associated proteins such as H-NS and Hha. In Enterohaemorrhagic Escherichia coli (EHEC), prophages make up a large fraction of the accessory genome and encode many virulence factors, yet their expression must overcome this silencing. We identify a prophage-encoded small RNA (sRNA), HnrS, that functions as an anti-silencing factor by targeting the H-NS paralogue Hha. HnrS is a short (66-nt) sRNA that is enriched in the locus of enterocyte effacement (LEE⁺) E. coli strains and present in up to nine copies in EHEC and Enteropathogenic Escherichia coli (EPEC) genomes. HnrS base-pairs with the hha ribosome-binding site to inhibit translation, thereby modulating Hha-H-NS repression of virulence loci including the LEE type III secretion system. Loss of HnrS alters motility, T3SS expression, and a subset of Hha-regulated genes. These findings reveal an RNA-based counter-silencing strategy encoded by prophage to relieve xenogenic silencing.

Abstract Targeted metagenomics, where samples are enriched for multiple organisms of interest using oligonucleotide probes, is a highly efficient sequencing methodology that is becoming standard practice for genomics of viruses and complex polymicrobial samples. Efficient enrichment critically requires probes that capture both conserved and highly diverse genomic regions without loss of sensitivity, and with uniform representation in the sequencing pool. Design of optimal probesets poses a challenge: existing computational methods use k-mer hashing to reduce over-abundant sequences, but scalability and efficiency drop with increasing numbers of genomes, while diverse sequences remain under-represented. Here we show that incorporating evolutionary distance to compress probes via a graph-based representation of multiple genomes across species, together with k-mer hashing, reduces overrepresentation of conserved sequences, and yields more uniform coverage even of highly diverse loci. We make the method available in Dampa, an open-source tool that generates probesets in seconds on a standard laptop. Software availability DAMPA is available as an open source package that can be installed with conda, and is free for academic use. https://github.com/MultipathogenGenomics/dampa Data availability Sequences generated as part of the laboratory validation are available from the ENA project PRJNA1466720. Ethics Clinical samples and metadata were collected by the PRL at the NSW Health Pathology-Institute of Clinical Pathology and Medical Research under the Western Sydney Local Health District Human Research Ethics and Governance Committee (Project identifier: 2020/ETH02426). All data was de-identified Funding R.J.R. is supported by NHMRC Investigator grant (GNT2018222). TG is supported by NHMRC Investigator grant GNT2025445. MP is supported by Sydney Infectious Diseases Institute seed funding.

ABSTRACT Campylobacter jejuni is the most common bacterial cause of human gastroenteritis around the world. A stable, scalable, and standardized typing scheme is essential for epidemiological and antimicrobial resistance (AMR) surveillance for prevention and control of C. jejuni infections. We curated, assembled, and quality-filtered a C. jejuni global whole-genome sequencing (WGS) data set of 63,012 publicly available Illumina short-read genomes. A C. jejuni global cgMLST scheme with 1,161 core loci was developed using a representative subset of 2,587 genomes. We compared the HierCC clustering of the cgMLST profiles at every allelic distance, and identified nine epidemiologically meaningful levels to form a novel multilevel HierCC typing (MHT) scheme. AMR prediction was performed for the global data set using AbritAMR and integrated with the MHT scheme. The multilevel design provides flexible typing resolution for both short- and long-term epidemiological investigations and allows natural and genetically discrete clusters to be described consistently at both global and local scales. We showcased the utility of the scheme with the identification of country- and continent-specific clusters at HC264 to HC19 levels and differentiation of farm-animal-specific (specialist) from human infection (generalist) clusters at HC264 to HC55 levels. In the U.S. dataset from 2016 to 2022, a total of 276 antibiotic-resistant clusters were identified, with 22 resistant clusters increasing in frequency in recent years. An increased prevalence of C. jejuni carrying 50S_L22 mutations in the USA was observed from 2016 to 2022, suggesting continuing selection pressure from macrolide use in farm animals.

Staphylococcus aureus is a major source of both hospital- and community-acquired infections worldwide. Advances in whole-genome sequencing (WGS) technologies have recently generated large volumes of S. aureus WGS data. The timely classification of S. aureus WGS data using genomic typing technologies has the potential to describe detailed genomic epidemiology at large and small scales. In this study, a multilevel genome typing (MGT) scheme, consisting of eight levels of multilocus sequence typing (MLST) schemes of increasing resolution, was developed for S. aureus and was used to analyze 50,481 publicly available genomes. The application of MGT to S. aureus epidemiology was shown in three case studies. First, the population structure of the globally disseminated MLST sequence type 8 (ST8) was described by MGT2 and compared with Spa typing. Second, MGT was used to characterize MLST ST8-USA300 isolates that colonized multiple body sites in the same patient. Finally, the MGT was used to describe the transmission of MLST ST239-SCCmec III throughout a single hospital. MGT STs were able to describe both isolates that had spread between wards and those that had colonized different reservoirs within a ward. S. aureus MGT describes S. aureus genomic epidemiology at multiple resolutions ranging from the global spread to local/individual scale using stable and standardized ST assignments. The S. aureus MGT database (https://mgtdb.unsw.edu.au/staphylococcus) is capable of tracking new and existing clones to facilitate the design of new strategies to reduce the global health burden of S. aureus infections. IMPORTANCE:Staphylococcus aureus causes both hospital- and community-acquired infections worldwide. Methicillin-resistant S. aureus is best known and has spread across the globe. Whole-genome sequencing (WGS) can type strains at the highest resolution. To enable best use of WGS data for surveillance of S. aureus, this study developed a multilevel genome typing (MGT) scheme that provides a publicly available, standardized, flexible, and easily communicated system to describe S. aureus strains. MGT has eight typing levels that provide progressively higher resolution. Each of these levels allows subtypes to be accurately identified and tracked. We show that MGT can be used to track well-known S. aureus strains at low resolution while simultaneously being able to track outbreaks in hospital settings at high resolution. The S. aureus MGT will facilitate the use of genomic data for surveillance without the need for bioinformatic expertise, improving efforts to control this important pathogen and prevent infections.

Salmonella enterica serovar Typhimurium (STm) is a globally prevalent pathogen, causing foodborne illnesses in humans through contaminated food products. Poultry products are known reservoirs of STm. This study performed a comparative genomic analysis of STm isolates from different stages of the Australian broiler chicken production chain and table egg livestock, to investigate their transmission dynamics within the production chain. We sequenced a total of 959 STm isolates (2021-2022) obtained from tier 1 breeder farms, tier 2 breeder farms, hatcheries, processing plants, value-added products, and table egg livestock. The genomes were typed and analysed using multilevel genome typing (MGT). At MGT1, isolates were divided into sequence type (ST), ST19 (72.8 %) and ST2066 (27.2 %). At MGT9 (highest resolution level) they were divided into 545 STs. Some MGT5 (intermediate resolution level) and MGT9 STs spanned two or more production stages while others were production stage specific. At MGT5, over 80 % of the dataset shared across two to six stages while at MGT9, over 30 STs exhibited 18 transmission patterns, with hatchery and breeder farms as potential points of STm dissemination. Non-singleton MGT9 STs from table egg livestock were also shared across meat chicken production stages excluding tier 1 breeder farms. A beta-lactamase gene (blaTEM-1) was the only antimicrobial resistant (AMR) gene identified and was found in 5 % (48/959) of the isolates. Our findings highlight the power of genomics for timely detection of STm transmissions and emergence of novel strains, supporting real-time biosecurity responses to reduce their public health burden.

IntroductionSalmonella Typhimurium (STm) is a globally distributed foodborne pathogen showing increasing antimicrobial resistance (AMR), particularly to fluoroquinolones and third-generation cephalosporins. Multiple countries have implemented ongoing genomic surveillance programs for Salmonella, but comprehensive global analyses integrating genomic typing and AMR in STm remain scarce.MethodsPublicly available genomes of ~65,000 STm isolates were characterized using Multilevel Genome Typing (MGT). Resistance was predicted to 14 clinically-relevant antibiotics. Resistance patterns were analyzed by MGT sequence type (ST), geographic location, year of collection, and source. MGT ST where ≥80% isolates were predicted to be resistant to an antibiotic were defined as a resistant ST for that antibiotic.ResultsAbout half of all STm isolates were predicted to be resistant to ≥1 antibiotic. Resistance frequencies varied substantially by country, collection year and MGT ST, and 407 resistant MGT STs were identified. Among the most recent isolates (2021–2022), eight MGT STs were classified as cefotaxime resistant and three as ciprofloxacin intermediate. Cefotaxime resistant MGT STs predominantly included isolates from cattle/poultry in the USA. Ciprofloxacin intermediate MGT STs were mainly linked to swine from the UK.DiscussionThis large-scale genomic analysis highlights substantial diversity in AMR patterns among STm genomic types globally. The identification of recently emerged cefotaxime resistant and ciprofloxacin intermediate STs underscores the continued threat of resistance to antibiotics critical for treatment of severe salmonellosis. Integration of MGT strain typing with AMR prediction provides scalable, sharable, standardised and precise tracking of resistant isolates/STs, offering a powerful framework for global AMR surveillance.

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.

Staphylococcus aureus asymptomatically colonises 30 % of humans but can also cause a range of diseases, which can be fatal. In 2017 S. aureus was associated with 20 000 deaths in the USA alone. Dividing S. aureus isolates into smaller sub-groups can reveal the emergence of distinct sub-populations with varying potential to cause infections. Despite multiple molecular typing methods categorising such sub-groups, they do not take full advantage of S. aureus genome sequences when describing the fundamental population structure of the species. In this study, we developed Staphylococcus aureus Lineage Typing (SaLTy), which rapidly divides the species into 61 phylogenetically congruent lineages. Alleles of three core genes were identified that uniquely define the 61 lineages and were used for SaLTy typing. SaLTy was validated on 5000 genomes and 99.12 % (4956/5000) of isolates were assigned the correct lineage. We compared SaLTy lineages to previously calculated clonal complexes (CCs) from BIGSdb (n=21 173). SALTy improves on CCs by grouping isolates congruently with phylogenetic structure. SaLTy lineages were further used to describe the carriage of Staphylococcal chromosomal cassette containing mecA (SCCmec) which is carried by methicillin-resistant S. aureus (MRSA). Most lineages had isolates lacking SCCmec and the four largest lineages varied in SCCmec over time. Classifying isolates into SaLTy lineages, which were further SCCmec typed, allowed SaLTy to describe high-level MRSA epidemiology. We provide SaLTy as a simple typing method that defines phylogenetic lineages (https://github.com/LanLab/SaLTy). SaLTy is highly accurate and can quickly analyse large amounts of S. aureus genome data. SaLTy will aid the characterisation of S. aureus populations and ongoing surveillance of sub-groups that threaten human health.

Whooping cough (pertussis) has re-emerged despite high vaccine coverage in Australia and many other countries worldwide, partly attributable to genetic adaptation of the causative organism, Bordetella pertussis, to vaccines. Therefore, genomic surveillance has become essential to monitor circulating strains for these genetic changes. However, increasing uptake of PCR for the diagnosis of pertussis has affected the availability of cultured isolates for typing. In this study, we evaluated the use of targeted multiplex PCR (mPCR) amplicon sequencing and shotgun metagenomic sequencing for culture-independent typing of B. pertussis directly from respiratory swabs. We developed a nine-target mPCR amplicon assay that could accurately type major lineages [ptxP3/non-ptxpP3, fim3A/B, fhaB3/non-fhaB3, and epidemic lineages (ELs) 1-5] circulating in Australia. Validation using DNA from isolates and 178 residual specimens collected in 2010-2012 (n = 87) and 2019 (n = 91) showed that mPCR amplicon sequencing was highly sensitive with a limit of detection of 4.6 copies [IS481 cycle threshold (Ct) 27.3]. Shotgun metagenomic sequencing was successful in genotyping B. pertussis in 84% of clinical specimens with PCR Ct < 24 and was concordant with mPCR typing results. The results revealed an expansion of EL4 strains from 2010 to 2012 to 2019 in Australia and identified unrecognized co-circulating cases of Bordetella holmesii. This study provides valuable insight into the circulating lineages in Australia prior to the COVID-19 pandemic during which border closure and other interventions reduced pertussis cases to an all-time low, and paves the way for the genomic surveillance of B. pertussis in the era of culture-independent PCR-based diagnosis. IMPORTANCE:In this paper, we evaluated the use of targeted multiplex PCR (mPCR) amplicon sequencing and shotgun metagenomic sequencing for culture-independent typing of Bordetella pertussis directly in respiratory swabs. We first developed a novel targeted mPCR amplicon sequencing assay that can type major circulating lineages and validated its accuracy and sensitivity on 178 DNA extracts from clinical swabs. We also demonstrate the feasibility of using deep metagenomic sequencing for determining strain lineage and markers of virulence, vaccine adaptation, macrolide resistance, and co-infections. Our culture-independent typing methods applied to clinical specimens revealed the expansion of a major global epidemic lineage in Australia (termed EL4) just prior to the COVID-19 pandemic. It also detected cases of previously hidden co-infections from another Bordetella species called Bordetella holmesii. These findings offer valuable insight into the circulating pertussis lineages in Australia prior to the COVID-19 pandemic during which border closure and other interventions reduced pertussis cases to an all-time low. It also provides comparative data for future surveillance as pertussis resurgence after the COVID-19 pandemic has been reported this year in Australia and many other countries. Overall, our paper demonstrates the utility, sensitivity, and specificity of mPCR amplicon and metagenomic sequencing-based culture-independent typing of B. pertussis, which not only paves the way for culture-independent genomic surveillance of B. pertussis but also for other pathogens in the era of PCR-based diagnosis.

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.

Background: Salmonella Typhimurium (STm) is a globally prevalent pathogen causing disease in both humans and animals. Antibiotics are required for the treatment of invasive salmonellosis and increasing resistance poses a treatment challenge. Comprehensive whole-genome sequencing based surveillance efforts, especially of USA and UK, and open access databases presented an opportunity to comprehensively analyse the genomic antimicrobial resistance (AMR) to key clinically-relevant antibiotics within this dataset. Methods: In this study, we identified and analysed resistance to fourteen key antibiotics using AbritAMR, and integrated the identified resistance with multilevel genome typing (MGT). AMR carriage and trends were assessed by genomic types at different MGT levels. Findings: In the complete dataset, 47% of the isolates were resistant to at least one drug - however resistance varied considerably by genomic types, geography, and time. When comparing data from 2019-2022, we observed USA had higher resistance to cefotaxime (AmpC) and gentamicin, whereas UK had higher resistance to multiple drugs including azithromycin and cefotaxime (ESBL). Within the 2015-2022 isolates, we identified 166 sequence types (STs) at different MGT levels with >80% resistance to at least one drug. We grouped these STs over time to reveal 20 predominant temporal patterns. We also identified STs that were expanding regionally, and those were source specific. Interpretation: The availability of global datasets enabled delineation of AMR trends within STm. Furthermore, integration of AMR with MGT genome typing provided sharable, standardised, and specific identification and tracking of resistant genomic types. This integrated analysis presents a unique approach for global surveillance of AMR and AMR strains.### Competing Interest StatementThe authors have declared no competing interest.

Xanthomonas citri is a plant-pathogenic bacterium associated with a diverse range of host plant species. It has undergone substantial reclassification and currently consists of 14 different subspecies or pathovars that are responsible for a wide range of plant diseases. Whole-genome sequencing (WGS) provides a cutting-edge advantage over other diagnostic techniques in epidemiological and evolutionary studies of X. citri because it has a higher discriminatory power and is replicable across laboratories. WGS also allows for the improvement of multilocus sequence typing (MLST) schemes. In this study, we used genome sequences of Xanthomonas isolates from the NCBI RefSeq database to develop a seven-gene MLST scheme that yielded 19 sequence types (STs) that correlated with phylogenetic clades of X. citri subspecies or pathovars. Using this MLST scheme, we examined 2,911 Xanthomonas species assemblies from NCBI GenBank and identified 15 novel STs from 37 isolates that were misclassified in NCBI. In total, we identified 545 X. citri assemblies from GenBank with 95% average nucleotide identity to the X. citri type strain, and all were classified as one of the 34 STs. All MLST classifications correlated with a phylogenetic position inferred from alignments using 92 conserved genes. We observed several instances where strains from different pathovars formed closely related monophyletic clades and shared the same ST, indicating that further investigation of the validity of these pathovars is required. Our MLST scheme described here is a robust tool for rapid classification of X. citri pathovars using WGS and a powerful method for further comprehensive taxonomic revision of X. citri pathovars.

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 blaTEM-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.

Campylobacter species are typically helical shaped, Gram-negative, and non-spore-forming bacteria. Species in this genus include established foodborne and animal pathogens as well as emerging pathogens. The accumulation of genomic data from the Campylobacter genus has increased exponentially in recent years, accompanied by the discovery of putative new species. At present, the lack of a standardized species boundary complicates distinguishing established and novel species. We defined the Campylobacter genus core genome (500 loci) using publicly available Campylobacter complete genomes (n = 498) and constructed a core genome phylogeny using 2,193 publicly available Campylobacter genomes to examine inter-species diversity and species boundaries. Utilizing 8,440 Campylobacter genomes representing 33 species and 8 subspecies, we found species delineation based on an average nucleotide identity (ANI) cutoff of 94.2% is consistent with the core genome phylogeny. We identified 60 ANI genomic species that delineated Campylobacter species in concordance with previous comparative genetic studies. All pairwise ANI genomic species pairs had in silico DNA-DNA hybridization scores of less than 70%, supporting their delineation as separate species. We provide the tool Campylobacter Genomic Species typer (CampyGStyper) that assigns ANI genomic species to query genomes based on ANI similarities to medoid genomes from each ANI genomic species with an accuracy of 99.96%. The ANI genomic species definitions proposed here allow consistent species definition in the Campylobacter genus and will facilitate the detection of novel species in the future. IMPORTANCE In recent years, Campylobacter has gained recognition as the leading cause of bacterial gastroenteritis worldwide, leading to a substantial rise in the collection of genomic data of the Campylobacter genus in public databases. Currently, a standardized Campylobacter species boundary at the genomic level is absent, leading to challenges in detecting emerging pathogens and defining putative novel species within this genus. We used a comprehensive representation of genomes of the Campylobacter genus to construct a core genome phylogenetic tree. Furthermore, we found an average nucleotide identity (ANI) of 94.2% as the optimal cutoff to define the Campylobacter species. Using this cutoff, we identified 60 ANI genomic species which provided a standardized species definition and nomenclature. Importantly, we have developed Campylobacter Genomic Species typer (CampyGStyper), which can robustly and accurately assign these ANI genomic species to Campylobacter genomes, thereby aiding pathogen surveillance and facilitating evolutionary and epidemiological studies of existing and emerging pathogens in the genus Campylobacter.

The seventh cholera pandemic started in 1961 in Indonesia and spread across the world in three waves in the decades that followed. Here, we utilised genomic evidence to detail the first wave of the seventh pandemic. Genomes of 22 seventh pandemic Vibrio cholerae isolates from 1961 to 1979 were completely sequenced. Together with 152 publicly available genomes from the same period, they fell into seven phylogenetic clusters (CL1-CL7). By multilevel genome typing (MGT), all were assigned to MGT2 ST1 (Wave 1) except three isolates in CL7 which were typed as MGT2 ST2 (Wave 2). The Wave 1 seventh pandemic expanded in two stages, with Stage 1 (CL1-CL5) spread across Asia and Stage 2 (CL6 and CL7) spread to the Middle East and Africa. Three non-synonymous mutations, one each, in three regulatory genes, csrD (global regulator), acfB (chemotaxis), and luxO (quorum sensing) may have critically contributed to its pandemicity. The three MGT2 ST2 isolates in CL7 were the progenitors of Wave 2 and evolved from within Wave 1 with acquisition of a novel IncA/C plasmid. Our findings provide new insight into the evolution and transmission of the early seventh pandemic, which may aid future cholera prevention and control. The seventh cholera pandemic spread across the globe in three waves from 1961. Here, the authors sequence 22 genomes from 1961 to 1979 and show that the first wave of the pandemic occurred in two distinct stages with different geographic and genomic characteristics.

AbstractStaphylococcus aureusasymptomatically colonises 30% of humans and in 2017 was associated with 20,000 deaths in the USA alone. DividingS. aureusinto smaller sub-groups can reveal the emergence of distinct sub-populations with varying potential to cause infections. Despite multiple molecular typing methods categorising such sub-groups, they do not take full advantage ofS. aureusWGS when describing the fundamental population structure of the species.In this study, we developedStaphylococcus aureusLineage Typing (SaLTy), which rapidly divides the species into 61 phylogenetically congruent lineages. Alleles of three core genes were identified that uniquely define the 61 lineages and were used for SaLTy typing. SaLTy was validated on 5,000 genomes and 99.12% (4,956/5,000) of isolates were assigned the correct lineage.We compared SaLTy lineages to previously calculated clonal complexes (CCs) from BIGSdb (n=21,173). SALTy improves on CCs by grouping isolates congruently with phylogenetic structure. SaLTy lineages were further used to describe the carriage ofStaphylococcalchromosomal cassette containingmecA(SCCmec) which is carried by methicillin-resistantS. aureus(MRSA). Most lineages had isolates lacking SCCmecand the four largest lineages varied in SCCmecover time. Classifying isolates into SaLTy lineages, which were further SCCmectyped, allowed SaLTy to describe high-level MRSA epidemiologyWe provide SALTy as a simple typing method that defines phylogenetic lineages (https://github.com/LanLab/SaLTy). SALTy is highly accurate and can quickly analyse large amounts ofS. aureusWGS. SALTy will aid the characterisation ofS. aureuspopulations and the ongoing surveillance of sub-groups that threaten human health.

ABSTRACT Vibrio cholerae O1 has caused cholera pandemics. Non-pandemic V. cholerae O1 strains, which are genetically distinctive from the pandemic clones, have been isolated from both human infections and the environment. We aimed to better understand the non-pandemic O1 strains and their pandemic potential. We sequenced 109 non-pandemic O1 isolates from Zhejiang, China (from 1963 to 1996) and compared them with 62 publicly available non-pandemic O1 genomes. The isolates from Zhejiang can be classified into three lineages (L1–L3). All grouped together with L3 sharing the most recent common ancestor with the pandemic clones. L2 and L3 emerged in the 1960s while L1 emerged in the 1970s. L1 and L2 disappeared after the 1990s, but L3 persisted until recently. All isolates contained the type VI secretion system. The Vibrio pathogenicity island was present in all L3 isolates, whereas the type III secretion system was present in all L1 isolates. L2 did not carry any unique virulence genes. An intact CTXφ was present in only two L3 isolates. An intact Vibrio seventh pandemic island 1 was present in only three L3 isolates. The blaCARB-7 gene was identified in 96.3% of L2 isolates. Each of the non-pandemic O1 lineages has unique properties contributing to their capacity to cause disease. Our findings offer new insight into the evolution of O1 V. cholerae for cholera prevention and control. IMPORTANCE It is well recognized that only Vibrio cholerae O1 causes cholera pandemics. However, not all O1 strains cause pandemic-level disease. In this study, we analyzed non-pandemic O1 V. cholerae isolates from the 1960s to the 1990s from China and found that they fell into three lineages, one of which shared the most recent common ancestor with pandemic O1 strains. Each of these non-pandemic O1 lineages has unique properties that contribute to their capacity to cause cholera. The findings of this study enhanced our understanding of the emergence and evolution of both pandemic and non-pandemic O1 V. cholerae.

Salmonella enterica serovar Enteritidis is a leading cause of foodborne infections. We previously developed a genomic typing database (MGTdb) for S. Enteritidis to facilitate global surveillance of this pathogen.

Innovation in laboratory testing algorithms to address seemingly uncontrollable global supply chain shortages in plastics and other consumables during emergencies such as the current COVID-19 pandemic have been urgently needed. We report our experience with specimen pooling on SARS-CoV-2 testing in an acute care hospital microbiology laboratory during a high testing demand period that exceeded available processing capacity. A fully automated four-in-one pooling algorithm was designed and validated. Correlation and agreement were calculated. A custom Microsoft Excel tool was designed for use by the technologists to aid interpretation, verification and result entry. Cost-per-test impact for pooling was measured in reference to the consumable cost and was denoted as the percentage reduction of cost versus the baseline cost-per-test of testing specimens individually. Validation showed a strong correlation between the signals observed when testing specimens individually versus those that were pooled. Average crossing point difference was 1.352 cycles (95% confidence interval of -0.235 and 2.940). Overall agreement observed between individually and pooled tested specimens was 96.8%. Stratified agreement showed an expected decreased performance of pooling for weakly positive specimens dropping below 60% after a crossing point of 35. Post-implementation data showed the consumable cost-savings achieved through this algorithm was 85.5% after 8 months, creating both testing and resource capacity. Pooling is an effective method to be used for SARS-CoV-2 testing during the current pandemic to address resource shortages and provide quick turnaround times for high test volumes without compromising performance.