Fungal molecular diagnostics still lags behind bacterial and viral counterparts for several good reasons. Fungal titers are low in infected samples, fungi have refractory cell walls, and target genes have much more homology to competing and numerically dominant human sequences. In addition, the incidence of life-threatening infections is low, imposing a requirement that the molecular assays need to be very economical. Nevertheless, fungal infections are often life-threatening and their early detection, identification of species and resistance mutations, is crucial to successful intervention. Individual fungal species are resistant to some of the growing list of antifungal agents, or have acquired resistance mutations that make specific agents ineffective or less effective. Culture based identification of fungi, species, or susceptibilities are not adequate, since incubation times exceed the window of opportunity for effective therapy, and since many samples from infected patients are cultures negative. What is needed is a high throughput PCR based method that is independent of culture, sensitive to the level of one fungal cell per ml of blood or other tissue types, and capable of detecting species and resistance mutations. This goal is very demanding, explaining the lack of a reliable commercial tool. The absence of a commercially available PCR diagnostic modality has been a major disappointment to clinicians, revealing a major deficiency in diagnostic capability. We propose to test and optimize the use of a new tool, high resolution melt analysis, in combination with more effective panfungal primers, to address these needs. Early indications suggest that HRM analysis can distinguish all major fungal species of major clinical significance directly from the PCR reaction without any additional hands-on efforts, costs, or delays. Multiple studies confirm that DELAY in diagnosis particularly accurate diagnosis is directly responsible for increased morbidity and mortality. New methods are urgently needed.
There is an unfulfilled clinical mandate to establish and implement sensitive, rapid, and specific diagnostic tools for detecting, quantifying, and identifying fungal species directly from clinical samples. Fungal infections are still frequent among high risk patient populations and their attributed mortality rates are alarmingly high. Early, presymptomatic detection and identification is crucial to reduce those rates. It should surprise no one, given problems with low specificity and poor viability in conventional assays for mold infections, that many more species of molds will be identified in the future by PCR as infectious, and that these misidentified species may respond poorly to antifungals. Furthermore, as new antifungals are being developed and tested, PCR detection and identification will be a crucial tool in selecting the most appropriate drug, and in following the progression of therapy. Logistics of these infections (low incidence but high mortality;imprecise identification of highest risk patients) demands tests that are both precise and very economical. All current tests require multiple assays or expensive follow-up tests to identify species and resistance. We propose to test whether high resolution melt curve analysis (HRM analysis), coupled with quantitative PCR using panfungal primers, offers a solution to this long-standing clinical need.
| Mandviwala, Tasneem; Shinde, Rupali; Kalra, Apoorv et al. (2010) High-throughput identification and quantification of Candida species using high resolution derivative melt analysis of panfungal amplicons. J Mol Diagn 12:91-101 |
