High-Speed Melting Analysis: The Effect of Melting Rate on Small Amplicon Microfluidic Genotyping.

BACKGROUND: High-resolution DNA melting analysis of small amplicons is a simple and inexpensive technique for genotyping. Microfluidics allows precise and rapid control of temperature during melting. METHODS: Using a microfluidic platform for serial PCR and melting analysis, 4 targets containing single nucleotide variants were amplified and then melted at different rates over a 250-fold range from 0.13 to 32 °C/s. Genotypes (n = 1728) were determined manually by visual inspection after background removal, normalization, and conversion to negative derivative plots. Differences between genotypes were quantified by a genotype discrimination ratio on the basis of inter- and intragenotype differences using the absolute value of the maximum vertical difference between curves as a metric. RESULTS: Different homozygous curves were genotyped by melting temperature and heterozygous curves were identified by shape. Technical artifacts preventing analysis (0.3%), incorrect (0.06%), and indeterminate (0.4%) results were minimal, occurring mostly at slow melting rates (0.13-0.5 °C/s). Genotype discrimination was maximal at around 8 °C/s (2-8 °C/s for homozygotes and 8-16 °C/s for heterozygotes), and no genotyping errors were made at rates >0.5 °C/s. PCR was completed in 10-12.2 min, followed by melting curve acquisition in 4 min down to <1 s. CONCLUSIONS: Microfluidics enables genotyping by melting analysis at rates up to 32 °C/s, requiring <1 s to acquire an entire melting curve. High-speed melting reduces the time for melting analysis, decreases errors, and improves genotype discrimination of small amplicons. Combined with extreme PCR, high-speed melting promises nucleic acid amplification and genotyping in < 1 min.

Microfluidic genotyping by rapid serial PCR and high-speed melting analysis.

BACKGROUND: Clinical molecular testing typically batches samples to minimize costs or uses multiplex lab-on-a-chip disposables to analyze a few targets. In genetics, multiple variants need to be analyzed, and different work flows that rapidly analyze multiple loci in a few targets are attractive. METHODS: We used a microfluidic platform tailored to rapid serial PCR and high-speed melting (HSM) to genotype 4 single nucleotide variants. A contiguous stream of master mix with sample DNA was pulsed with each primer pair for serial PCR and melting. Two study sites each analyzed 100 samples for F2 (c.*97G>A), F5 (c.1601G>A), and MTHFR (c.665C>T and c.1286A>C) after blinding for genotype and genotype proportions. Internal temperature controls improved melting curve precision. The platform's liquid-handling system automated PCR and HSM. RESULTS: PCR and HSM were completed in a total of 12.5 min. Melting was performed at 0.5 °C/s. As expected, homozygous variants were separated by melting temperature, and heterozygotes were identified by curve shape. All samples were correctly genotyped by the instrument. Follow-up testing was required on 1.38% of the assays for a definitive genotype. CONCLUSIONS: We demonstrate genotyping accuracy on a novel microfluidic platform with rapid serial PCR and HSM. The platform targets short turnaround times for multiple genetic variants in up to 8 samples. It is also designed to allow automatic and immediate reflexive or repeat testing depending on results from the streaming DNA. Rapid serial PCR provides a flexible genetic work flow and is nicely matched to HSM analysis.

Comprehensive DNA signature discovery and validation.

DNA signatures are nucleotide sequences that can be used to detect the presence of an organism and to distinguish that organism from all other species. Here we describe Insignia, a new, comprehensive system for the rapid identification of signatures in the genomes of bacteria and viruses. With the availability of hundreds of complete bacterial and viral genome sequences, it is now possible to use computational methods to identify signature sequences in all of these species, and to use these signatures as the basis for diagnostic assays to detect and genotype microbes in both environmental and clinical samples. The success of such assays critically depends on the methods used to identify signatures that properly differentiate between the target genomes and the sample background. We have used Insignia to compute accurate signatures for most bacterial genomes and made them available through our Web site. A sample of these signatures has been successfully tested on a set of 46 Vibrio cholerae strains, and the results indicate that the signatures are highly sensitive for detection as well as specific for discrimination between these strains and their near relatives. Our approach, whereby the entire genomic complement of organisms are compared to identify probe targets, is a promising method for diagnostic assay development, and it provides assay designers with the flexibility to choose probes from the most relevant genes or genomic regions. The Insignia system is freely accessible via a Web interface and has been released as open source software at: http://insignia.cbcb.umd.edu.

Automated Microfluidic Platform for Serial Polymerase Chain Reaction and High-Resolution Melting Analysis.

We report the development of an automated genetic analyzer for human sample testing based on microfluidic rapid polymerase chain reaction (PCR) with high-resolution melting analysis (HRMA). The integrated DNA microfluidic cartridge was used on a platform designed with a robotic pipettor system that works by sequentially picking up different test solutions from a 384-well plate, mixing them in the tips, and delivering mixed fluids to the DNA cartridge. A novel image feedback flow control system based on a Canon 5D Mark II digital camera was developed for controlling fluid movement through a complex microfluidic branching network without the use of valves. The same camera was used for measuring the high-resolution melt curve of DNA amplicons that were generated in the microfluidic chip. Owing to fast heating and cooling as well as sensitive temperature measurement in the microfluidic channels, the time frame for PCR and HRMA was dramatically reduced from hours to minutes. Preliminary testing results demonstrated that rapid serial PCR and HRMA are possible while still achieving high data quality that is suitable for human sample testing.

Automated Classification and Cluster Visualization of Genotypes Derived from High Resolution Melt Curves.

INTRODUCTION: High Resolution Melting (HRM) following PCR has been used to identify DNA genotypes. Fluorescent dyes bounded to double strand DNA lose their fluorescence with increasing temperature, yielding different signatures for different genotypes. Recent software tools have been made available to aid in the distinction of different genotypes, but they are not fully automated, used only for research purposes, or require some level of interaction or confirmation from an analyst. MATERIALS AND METHODS: We describe a fully automated machine learning software algorithm that classifies unknown genotypes. Dynamic melt curves are transformed to multidimensional clusters of points whereby a training set is used to establish the distribution of genotype clusters. Subsequently, probabilistic and statistical methods were used to classify the genotypes of unknown DNA samples on 4 different assays (40 VKORC1, CYP2C9*2, CYP2C9*3 samples in triplicate, and 49 MTHFR c.665C>T samples in triplicate) run on the Roche LC480. Melt curves of each of the triplicates were genotyped separately. RESULTS: Automated genotyping called 100% of VKORC1, CYP2C9*3 and MTHFR c.665C>T samples correctly. 97.5% of CYP2C9*2 melt curves were genotyped correctly with the remaining 2.5% given a no call due to the inability to decipher 3 melt curves in close proximity as either homozygous mutant or wild-type with greater than 99.5% posterior probability. CONCLUSIONS: We demonstrate the ability to fully automate DNA genotyping from HRM curves systematically and accurately without requiring any user interpretation or interaction with the data. Visualization of genotype clusters and quantification of the expected misclassification rate is also available to provide feedback to assay scientists and engineers as changes are made to the assay or instrument.