Real-time and digital PCR assays for the detection of Aspergillus DNA in contrived and clinical samples-a bi-center evaluation.

Aspergillus real-time PCR (qPCR) is well-established, but limitations persist. These may be overcome by digital PCR (dPCR) technology, with its potential to be more analytically sensitive, more precise, and less affected by inhibition compared to qPCR, all of which could benefit the detection of low DNA concentrations present in many invasive fungal infections. In this study, two well-validated local qPCR assay protocols to detect Aspergillus spp. were transformed into a digital format, with analytical and clinical performance assessed by testing contrived (n = 30) and clinical samples (n = 19) and a range of negative control materials. PCR positivity was determined based on the reported dPCR copy numbers, assay concordance, and correlation between the burdens (copies/μL) measured by both dPCR assays. Both dPCR assays generated 100% agreement across the contrived samples, detecting all the positive samples with a significant positive correlation (rho: 0.9605, P < 0.001) between the fungal burdens calculated between assays. When testing clinical samples, the overall qualitative agreement between the dPCR assays was 84%, with discordant and false positive results associated with very low DNA concentrations (one positive partition). There was a strong correlation (rho 0.887, P < 0.001) between the DNA concentrations calculated by both dPCR assays when testing clinical samples.IMPORTANCEFor aspergillosis, available DNA burdens can be low, and quantification is required to differentiate colonization from disease. Real-time PCR (qPCR) has been widely used to aid the diagnosis of aspergillosis, but performance can be hampered when targeting burdens at or near the limit of qPCR detection, and quantification requires the use of standard curves that may be impacted by the sample matrix. The robust cross-platform quantification of low DNA concentration provided by digital PCR (dPCR) platforms offers an enhanced diagnostic option to real-time PCR, with the potential to enhance the molecular diagnosis of this disease. The ability to detect low DNA burdens, coupled with the potential for genotyping, could be further exploited to detect genetic mechanisms of antifungal resistance.