Massively parallel digital high resolution melt for rapid and absolutely quantitative sequence profiling

Abstract

In clinical diagnostics and pathogen detection, profiling of complex samples for low-level genotypes represents a significant challenge. Advances in speed, sensitivity, and extent of multiplexing of molecular pathogen detection assays are needed to improve patient care. We report the development of an integrated platform enabling the identification of bacterial pathogen DNA sequences in complex samples in less than four hours. The system incorporates a microfluidic chip and instrumentation to accomplish universal PCR amplification, High Resolution Melting (HRM), and machine learning within 20,000 picoliter scale reactions, simultaneously. Clinically relevant concentrations of bacterial DNA molecules are separated by digitization across 20,000 reactions and amplified with universal primers targeting the bacterial 16S gene. Amplification is followed by HRM sequence fingerprinting in all reactions, simultaneously. The resulting bacteria-specific melt curves are identified by Support Vector Machine learning, and individual pathogen loads are quantified. The platform reduces reaction volumes by 99.995% and achieves a greater than 200-fold increase in dynamic range of detection compared to traditional PCR HRM approaches. Type I and II error rates are reduced by 99% and 100% respectively, compared to intercalating dye-based digital PCR (dPCR) methods. This technology could impact a number of quantitative profiling applications, especially infectious disease diagnostics.

Real-time kinetics and high-resolution melt curves in single-molecule digital LAMP to differentiate and study specific and non-specific amplification

“…Future efforts should investigate the combination of realtime dLAMP (and other digital isothermal amplification technologies) and HRM as a way to increase multiplexing of dLAMP when using a single reporter. In PCR, HRM has been used to differentiate among multiple amplification products by measuring differences in T m (42)(43)(44)(45)(46), with applications that include among others multiplexed pathogen identification and antibiotic susceptibility testing. Finally, studies with clinical samples should be performed using the dLAMP with HRM method to understand the carryover effects from relevant matrices.…”

Emerging Technologies for Molecular Diagnosis of Sepsis

“…A supervised machine learning algorithm automatically identifies the microbial species by its melt curve. U-dHRM has reported a classification accuracy of 99.9% for the 37 pathogens tested, with load quantification for individual pathogens (165). This technology was validated by using mock blood samples, demonstrating its ability to identify pathogens in the presence of excessive human DNA (165).…”

“…The universal digital high-resolution melt (U-dHRM) platform is a broad-based microbial identification technology used with whole-blood samples. It can currently detect 37 bacterial pathogens with single-organism and single-genome sensitivity as well as resolve polymicrobial infections in Ͻ4 h using Ͻ1 ml whole blood (164,165). This technology is in the validation phase (University of California, San Diego) and is not yet commercially available.…”

“…U-dHRM integrates universal digital PCR (dPCR) with high-resolution melt (HRM) analysis on a microfluidic chip to enable probe-free differentiation and quantification of bacteria within a sample (165). The test procedure begins with DNA extraction followed by sample "digitization," which separates all pathogen genomes into their own PCR mixtures by spreading the sample across a microfluidic chip containing 20,000 picolitersized reaction mixtures.…”

“…Typically, PCR-based methods are unable to differentiate between viable and nonviable DNA (173). On the contrary, the use of 16S gene primers to amplify long 1-kb amplicons by U-dHRM may allow the differentiation of intact DNA relevant to active infection from the degraded DNA of dead pathogens or from the environment (165,174). This can be a significant advantage over other molecular diagnostic tests, including sequencing technologies, which detect a high background level of organisms; clinical trials are pending.…”