SaLTy: a novel Staphylococcus aureus Lineage Typer.

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.

Feasibility of Targeted Next-Generation DNA Sequencing for Expanding Population Newborn Screening.

BACKGROUND: Newborn screening (NBS) is an effective public health intervention that reduces death and disability from treatable genetic diseases, but many conditions are not screened due to a lack of a suitable assay. Whole genome and whole exome sequencing can potentially expand NBS but there remain many technical challenges preventing their use in population NBS. We investigated if targeted gene sequencing (TGS) is a feasible methodology for expanding NBS. METHODS: We constructed a TGS panel of 164 genes which screens for a broad range of inherited conditions. We designed a high-volume, low-turnaround laboratory and bioinformatics workflow that avoids the technical and data interpretation challenges associated with whole genome and whole exome sequencing. A methods-based analytical validation of the assay was completed and test performance in 2552 newborns examined. We calculated annual birth estimates for each condition to assess cost-effectiveness. RESULTS: Assay analytical sensitivity was >99% and specificity was 100%. Of the newborns screened, 1.3% tested positive for a condition. On average, each individual had 225 variants to interpret and 1.8% were variants of uncertain significance (VUS). The turnaround time was 7 to 10 days. Maximum batch size was 1536 samples. CONCLUSIONS: We demonstrate that a TGS assay could be incorporated into an NBS program soon to increase the number of conditions screened. Additionally, we conclude that NBS using TGS may be cost-effective.

Multilevel Genome Typing Describes Short- and Long-Term Vibrio cholerae Molecular Epidemiology.

Since 1817, cholera, caused by Vibrio cholerae, has been characterized by seven distinct pandemics. The ongoing seventh pandemic (7P) began in 1961. In this study, we developed a Multilevel Genome Typing (MGT) tool for classifying the V. cholerae species with a focus on the 7P. MGT is based on multilocus sequence typing (MLST), but the concept has been expanded to include a series of MLST schemes that compare population structure from broad to fine resolutions. The V. cholerae MGT consists of eight levels, with the lowest, MGT1, composed of 7 loci and the highest, MGT8, consisting of the 7P core genome (3,759 loci). We used MGT to analyze 5,771 V. cholerae genomes. The genetic relationships revealed by lower MGT levels recapitulated previous findings of large-scale 7P transmission across the globe. Furthermore, the higher MGT levels provided an increased discriminatory power to differentiate subgroups within a national outbreak. Additionally, we demonstrated the usefulness of MGT for non-7P classification. In a large non-7P MGT1 type, MGT2 and MGT3 described continental and regional distributions, respectively. Finally, MGT described trends of 7P in virulence, and MGT2 to MGT3 sequence types (STs) grouped isolates of the same ctxB, tcpA, and ctxB-tcpA genotypes and characterized their trends over the pandemic. MGT offers a range of resolutions for typing V. cholerae. The MGT nomenclature is stable, transferable, and directly comparable between investigations. The MGT database (https://mgtdb.unsw.edu.au/) can accept and process newly submitted samples. MGT allows tracking of existing and new isolates and will be useful for understanding future spread of cholera. IMPORTANCE In 2017, the World Health Organization launched the "Ending Cholera" initiative to reduce cholera-related deaths by 90% by 2030. This strategy emphasized the importance of the speed and accessibility of newer technologies to contain outbreaks. Here, we present a new tool named Multilevel Genome Typing (MGT), which classifies isolates of the cholera-causing agent, Vibrio cholerae. MGT is a freely available online database that groups genetically similar V. cholerae isolates to quickly indicate the origins of outbreaks. We validated the MGT database retrospectively in an outbreak setting, showcasing rapid confirmation of the Nepalese origins for the 2010 Haiti outbreak. In the past 5 years, thousands of V. cholerae genomes have been submitted to the NCBI database, which underscores the importance of and need for proper genome data classification for cholera epidemiology. The V. cholerae MGT database can assist in early decision making that directly impacts controlling both the local and global spread of cholera.

Elucidation of global and national genomic epidemiology of Salmonella enterica serovar Enteritidis through multilevel genome typing.

Salmonella enterica serovar Enteritidis is a major cause of foodborne Salmonella infections and outbreaks in humans. Effective surveillance and timely outbreak detection are essential for public health control. Multilevel genome typing (MGT) with multiple levels of resolution has been previously demonstrated as a promising tool for this purpose. In this study, we developed MGT with nine levels for S. Enteritidis and characterised the genomic epidemiology of S. Enteritidis in detail. We examined 26 670 publicly available S. Enteritidis genome sequences from isolates spanning 101 years from 86 countries to reveal their spatial and temporal distributions. Using the lower resolution MGT levels, globally prevalent and regionally restricted sequence types (STs) were identified; avian associated MGT4-STs were found that were common in human cases in the USA; temporal trends were observed in the UK with MGT5-STs from 2014 to 2018 revealing both long lived endemic STs and the rapid expansion of new STs. Using MGT3 to MGT6, we identified multidrug resistance (MDR) associated STs at various MGT levels, which improves precision of detection and global tracking of MDR clones. We also found that the majority of the global S. Enteritidis population fell within two predominant lineages, which had significantly different propensity of causing large scale outbreaks. An online open MGT database has been established for unified international surveillance of S. Enteritidis. We demonstrated that MGT provides a flexible and high-resolution genome typing tool for S. Enteritidis surveillance and outbreak detection.