SaQuant: a real-time PCR assay for quantitative assessment of Staphylococcus aureus

Background Molecular assays are important tools for pathogen detection but need to be periodically re-evaluated with the discovery of additional genetic diversity that may cause assays to exclude target taxa or include non-target taxa. A single well-developed assay can find broad application across research, clinical, and industrial settings. Pathogen prevalence within a population is estimated using such assays and accurate results are critical for formulating effective public health policies and guiding future research. A variety of assays for the detection of Staphylococcus aureus are currently available. The utility of commercial assays for research is limited, given proprietary signatures and lack of transparent validation. Results In silico testing of existing peer-reviewed assays show that most suffer from a lack of sensitivity and specificity. We found no assays that were specifically designed and validated for quantitative use. Here we present a qPCR assay, SaQuant, for the detection and quantification of S. aureus as might be collected on sampling swabs. Sensitivity and specificity of the assay was 95.6 and 99.9 %, respectively, with a limit of detection of between 3 and 5 genome equivalents and a limit of quantification of 8.27 genome equivalents. The presence of DNA from non-target species likely to be found in a swab sample, did not impact qualitative or quantitative abilities of the assay. Conclusions This assay has the potential to serve as a valuable tool for the accurate detection and quantification of S. aureus collected from human body sites in order to better understand the dynamics of prevalence and transmission in community settings.

Automated summary

Existing molecular assays for Staphylococcus aureus detection lack sensitivity and specificity. The newly developed qPCR assay SaQuant shows high sensitivity and specificity, with potential for accurate detection and quantification of S. aureus. It has the ability to better understand the dynamics of prevalence and transmission in community settings.