We are proud to present a true whole-genome schema for multi-locus sequence typing (wgMLST) of Staphylococcus aureus. The schema is available in BioNumerics and in combination with our cloud-based Calculation Engine, typing S. aureus isolates up to strain level using whole genome sequencing data is now easily accessible to everyone.
Our scientists have taken up the challenge to build a genome-wide schema for multi-locus sequence typing (MLST) of Staphylococcus aureus isolates. Following the recent developments on the core genome MLST in Leopold et al., 2014 and using same the set of 31 publicly available reference sequences that capture the known diversity of S. aureus, they extended the core genome MLST schema to a pan-genomic schema. By also capturing the accessory loci, they increased the discriminatory power of the schema. At the same time, the extended schema also allows for the detection of subtype- or outbreak-specific markers, thus enabling more powerful classification and outbreak definition tools.
|Number of core loci||1861|
|Number of accessory loci||2036|
|Total number of loci||3897|
Starting from the 31 annotated reference genomes, an in-house developed schema creation procedure uses a sampling-based multi-reciprocal BLAST procedure to determine those sets of alleles that make up the stable loci in the accessory genome. A per-locus allele assessment procedure then determines the central prototype allele, and thus the definition of the locus. The accessory schema is then complemented with the core loci and the classical MLST loci to obtain maximal consistency with classical and novel multi-locus sequence typing initiatives for S. aureus.
Using BioNumerics and our high-throughput calculation infrastructure, analyzing whole genome sequencing data for S. aureus is now within everyone’s reach. The Cloud Calculation Engine, managed by us and accessible through BioNumerics, offers a high-throughput environment for all your sample processing needs. Its quality-controlled de novo assembly possibilities allow you to easily assemble whole-genome sequencing data without the need of local computing power. The two allele detection procedures — assembly-based and assembly-free — allow you to do fast and reliable allele detection, and overcome the issues caused by the use of draft assemblies. With turnaround times below 20 minutes for a sample, and the ability to process many samples simultaneously, the horsepower of high-performance computing is brought to your desktop by a few simple clicks.
The whole-genome multi-locus sequence typing schema for S. aureus has been tried and tested by our biologists. Great care has been taken to create an analysis procedure that minimizes sample artifacts, while maintaining an enormous discriminatory power that supersedes the core genome schema. The schema has been used in a real-life setting, by assisting in resolving a S. aureus outbreak in a neonatal care unit (Roisin et al., 2016).
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To start using this whole-genome approach to typing S. aureus, simply request a Calculation Engine project. We look forward to your discoveries!
Part of this work has been done in the framework of the Patho-NGen-Trace project. Patho-NGen-Trace is funded by the EC under the 7th Framework Programme of the European Union.
Leopold S. R., Goering R. V., Witten A., Harmsen D., Mellmann A. (2014) Bacterial whole-genome sequencing revisited: portable, scalable, and standardized analysis for typing and detection of virulence and antibiotic resistance genes. J Clin Microbiol. 2014 Jul;52(7):2365-70.
Roisin S., Gaudin C., De Mendonça R., Bellon J., Van Vaerenbergh K., De Bruyne K., Byl B., Pouseele H., Denis O., Supply P. (2016) Pan-genome multilocus sequence typing and outbreak-specific reference-based single nucleotide polymorphism analysis to resolve two concurrent Staphylococcus aureus outbreaks in neonatal services. Clin Microbiol Infect. Jun;22(6):520-526.