Use of self-obtained vaginal specimens processed by nucleic acid amplification tests (NAATs) has significantly increased the utilization of nontraditional locations for Chlamydia trachomatis and Neisseria gonorrhoeae screening programs. One important emerging source of such venues includes home-based self-sampling kits available via the Internet. The objective of our study was to evaluate the performance of three commercially available NAATs (Becton-Dickinson ProbeTec SDA, Gen-Probe Aptima Combo2 TMA, and Roche Amplicor PCR) for detection of C. trachomatis and N. gonorrhoeae in vaginal samples obtained via an Internet-based screening program. From July 2004 to August 2005, 500 self-collected vaginal swabs were tested for C. trachomatis and N. gonorrhoeae by using all three NAATs. Another 500 samples were collected between August 2005 and November 2007 and tested by ProbeTec and Combo2; PCR testing was discontinued due to low specificity for N. gonorrhoeae. All tests were conducted according to the manufacturers' procedures; the "gold standard" for an infected C. trachomatis or N. gonorrhoeae patient was defined as >2 positive NAAT results. Of the first 500 swabs submitted, 46 were C. trachomatis infected (9.2%) and 5 were N. gonorrhoeae infected (1.0%), and 3 of these were coinfected (0.6%). All C. trachomatis and N. gonorrhoeae Combo2-positive/ProbeTec-negative samples were confirmed as true positives by an alternative NAAT. For C. trachomatis, ProbeTec, Combo2, and PCR had sensitivities of 82.6%, 100%, and 100%, with specificities of 100%, 100%, and 99.3%, respectively. For N. gonorrhoeae, ProbeTec, Combo2, and PCR had sensitivities of 80%, 100%, and 100%, with specificities of 100%, 100%, and 98.8%, respectively. Of the total 1,000 swabs submitted, 92 were C. trachomatis infected (9.2%) and 15 were N. gonorrhoeae infected (1.5%), and 7 of these were coinfected (0.7%). There were no ProbeTecpositive/Combo2-negative samples. For C. trachomatis, ProbeTec and Combo2 had sensitivities of 81.5% and 100%, with specificities of 100% and 100%, respectively. For N. gonorrhoeae, ProbeTec and Combo2 had sensitivities of 80% and 100%, with specificities of 100% and 100%, respectively. Overall, ProbeTec had 17 C. trachomatis false-negative results (1.7%) and 3 N. gonorrhoeae false-negative results (0.3%), while Combo2 had none. Our results were consistent with the sensitivities and specificities stated by the manufacturers. NAATs perform well for detection of chlamydia and gonorrhea with self-obtained vaginal swabs shipped in a dry state to a laboratory. For 1,000 self-collected vaginal swabs tested by NAATs, the sensitivities for C. trachomatis and N. gonorrhoeae for Combo2 were 100% and 100%, while they were 81.5% and 80%, respectively, for ProbeTec. For 500 PCR samples, the C. trachomatis sensitivity was 100% and the N. gonorrhoeae sensitivity was 100%, with specificities of 99.3% and 98.8%, respectively.

Comprehensive profiling of nucleic acids in genetically heterogeneous samples is important for clinical and basic research applications. Universal digital high-resolution melt (U-dHRM) is a new approach to broad-based PCR diagnostics and profiling technologies that can overcome issues of poor sensitivity due to contaminating nucleic acids and poor specificity due to primer or probe hybridization inaccuracies for single nucleotide variations. The U-dHRM approach uses broad-based primers or ligated adapter sequences to universally amplify all nucleic acid molecules in a heterogeneous sample, which have been partitioned, as in digital PCR. Extensive assay optimization enables direct sequence identification by algorithm-based matching of melt curve shape and Tm to a database of known sequence-specific melt curves. We show that single-molecule detection and single nucleotide sensitivity is possible. The feasibility and utility of U-dHRM is demonstrated through detection of bacteria associated with polymicrobial blood infection and microRNAs (miRNAs) associated with host response to infection. U-dHRM using broad-based 16S rRNA gene primers demonstrates universal single cell detection of bacterial pathogens, even in the presence of larger amounts of contaminating bacteria; U-dHRM using universally adapted Lethal-7 miRNAs in a heterogeneous mixture showcases the single copy sensitivity and single nucleotide specificity of this approach.

High Resolution Melt (HRM) is a versatile and rapid post-PCR DNA analysis technique primarily used to differentiate sequence variants among only a few short amplicons. We recently developed a one-vs-one support vector machine algorithm (OVO SVM) that enables the use of HRM for identifying numerous short amplicon sequences automatically and reliably. Herein, we set out to maximize the discriminating power of HRM + SVM for a single genetic locus by testing longer amplicons harboring significantly more sequence information. Using universal primers that amplify the hypervariable bacterial 16 S rRNA gene as a model system, we found that long amplicons yield more complex HRM curve shapes. We developed a novel nested OVO SVM approach to take advantage of this feature and achieved 100% accuracy in the identification of 37 clinically relevant bacteria in Leave-One-Out-Cross-Validation. A subset of organisms were independently tested. Those from pure culture were identified with high accuracy, while those tested directly from clinical blood bottles displayed more technical variability and reduced accuracy. Our findings demonstrate that long sequences can be accurately and automatically profiled by HRM with a novel nested SVM approach and suggest that clinical sample testing is feasible with further optimization.

There is still an ongoing demand for a simple broad-spectrum molecular diagnostic assay for pathogenic bacteria. For this purpose, we developed a single-plex High Resolution Melt (HRM) assay that generates complex melt curves for bacterial identification. Using internal transcribed spacer (ITS) region as the phylogenetic marker for HRM, we observed complex melt curve signatures as compared to 16S rDNA amplicons with enhanced interspecies discrimination. We also developed a novel Naïve Bayes curve classification algorithm with statistical interpretation and achieved 95% accuracy in differentiating 89 bacterial species in our library using leave-one-out cross-validation. Pilot clinical validation of our method correctly identified the etiologic organisms at the species-level in 59 culture-positive mono-bacterial blood culture samples with 90% accuracy. Our findings suggest that broad bacterial sequences may be simply, reliably and automatically profiled by ITS HRM assay for clinical adoption.