Microfluidic Genotyping by Rapid Serial PCR and High-Speed Melting Analysis

Demonstration of Neural Networks to Reconstruct Temperatures from Simulated Fluorescent Data Toward Use in Bio-microfluidics

Biological systems often have a narrow temperature range of operation, which require highly accurate spatially resolved temperature measurements, often near ±0.1 K. However, many temperature sensors cannot meet both accuracy and spatial distribution requirements, often because their accuracy is limited by data fitting and temperature reconstruction models. Machine learning algorithms have the potential to meet this need, but their usage in generating spatial distributions of temperature is severely lacking in the literature. This work presents the first instance of using neural networks to process fluorescent images to map the spatial distribution of temperature. Three standard network architectures were investigated using non-spatially resolved fluorescent thermometry (simply-connected feed-forward network) or during image or pixel identification (U-net and convolutional neural network, CNN). Simulated fluorescent images based on experimental data were generated based on known temperature distributions where Gaussian white noise with a standard deviation of ±0.1 K was added. The poor results from these standard networks motivated the creation of what is termed a moving CNN, with an RMSE error of ±0.23 K, where the elements of the matrix represent the neighboring pixels. Finally, the performance of this MCNN is investigated when trained and applied to three distinctive temperature distributions characteristic within microfluidic devices, where the fluorescent image is simulated at either three or five different wavelengths. The results demonstrate that having a minimum of 10 ^3.5 data points per temperature and the broadest range of temperatures during training provides temperature predictions nearest to the true temperatures of the images, with a minimum RMSE of ±0.15 K. When compared to traditional curve fitting techniques, this work demonstrates that greater accuracy when spatially mapping temperature from fluorescent images can be achieved when using convolutional neural networks.

VIR-CRISPR: Visual in-one-tube ultrafast RT-PCR and CRISPR method for instant SARS-CoV-2 detection

Until now, corona virus disease 2019 (COVID-19) remained to be an enormous threat for global health. As one viral illness induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), versatile, rapid and sensitive method for SARS-CoV-2 detection in early stage is urgently needed. Here, we reported an ultrasensitive and visual in-one-tube detection method which could be accomplished within half an hour from sampling-to-result. By integrating all reactions in one tube, liquid handling steps were omitted and amplicon contamination could be totally avoided. Magnetic beads were employed to achieve the fast extraction of viral nucleic acid and increase the sensitivity. Using portable thermocycler and blue light, the fluorescent results could be directly observed by naked eyes. The proposed method is of higher specificity and sensitivity, nearly at single molecule level. More important, results demonstrated 100% positive detection rate for 40 clinical samples, which was consistent with standard RT-PCR. Thus, our method is considerably simple, rapid, sensitive and accurate, holding great promise for the instant detecting of viruses including SARS-CoV-2 and the next generation of molecular diagnosis.

Extraction-Free Rapid Cycle Quantitative RT-PCR and Extreme RT-PCR for SARS-CoV-2 Virus Detection

Since the start of the coronavirus disease 2019 (COVID-19) pandemic, molecular diagnostic testing for detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has faced substantial supply chain shortages and noteworthy delays in result reporting after sample collection. Supply chain shortages have been most evident in reagents for RNA extraction and rapid diagnostic testing. This study explored the kinetic limitations of extraction-free rapid cycle quantitative real-time RT-PCR for SARS-CoV-2 virus detection using the commercially available capillary-based LightCycler. After optimizing for time and reaction conditions, a protocol for sensitive and specific quantitative RT-PCR of SARS-CoV-2 RNA from nasopharyngeal swabs in <20 minutes was developed, with minimal hands-on time requirements. This protocol improves detection speed while maintaining the sensitivity and specificity of hydrolysis probe-based detection. Percentage agreement between the developed assay and previously tested positive patient samples was 97.6% (n = 40/41), and negative patient samples was 100% (40/40). The study further demonstrates that using purified RNA, SARS-CoV-2 testing using extreme RT-PCR, and product verification by melting can be completed in <3 minutes. Overall, these studies provide a framework for increasing the speed of SARS-CoV-2 and other infectious disease testing.

A High-Resolution Digital DNA Melting Platform for Robust Sequence Profiling and Enhanced Genotype Discrimination

DNA melting analysis provides a rapid method for genotyping a target amplicon directly after PCR amplification. To transform melt genotyping into a broad-based profiling approach for heterogeneous samples, we previously proposed the integration of universal PCR and melt analysis with digital PCR. Here, we advanced this concept by developing a high-resolution digital melt platform with precise thermal control to accomplish reliable, high-throughput heat ramping of microfluidic chip digital PCR reactions. Using synthetic DNA oligos with defined melting temperatures, we characterized sources of melting variability and minimized run-to-run variations. Within-run comparisons throughout a 20,000-reaction chip revealed that high-melting-temperature sequences were significantly less prone to melt variation. Further optimization using bacterial 16S amplicons revealed a strong dependence of the number of melting transitions on the heating rate during curve generation. These studies show that reliable high-resolution melt curve genotyping can be achieved in digital, picoliter-scale reactions and demonstrate that rate-dependent melt signatures may be useful for enhancing automated melt genotyping.

Counting DNA molecules with visual segment-based readouts in minutes

An ultrafast and extremely simple approach was proposed to count the number of DNA molecules without any microfluidic-based device. By directly counting the number of amplicon clusters in a capillary, the absolute amount of DNA molecules could be easily determined.

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.

PCR-Based Detection Methods for Single-Nucleotide Polymorphism or Mutation: Real-Time PCR and Its Substantial Contribution Toward Technological Refinement

Single-nucleotide polymorphisms (SNPs) and single-nucleotide mutations result from the substitution of only a single base. The SNP or mutation can be relevant to disease susceptibility, pathogenesis of disease, and efficacy of specific drugs. It is important to detect SNPs or mutations clinically. Methods to distinguish/detect SNPs or mutations should be highly specific and sensitive. In this regard, polymerase chain reaction (PCR) has provided the necessary analytical performance for many molecular analyses. PCR-based methods for SNP/mutation detection are broadly categorized into two types-(1) polymorphic or mutant allele-directed specific analysis using primers matched with substituted nucleotide or using oligonucleotides to block or clamp the nontargeted template, and (2) melting curve analysis, which is combined with the real-time PCR techniques using hydrolysis probes, hybridization probes, or double-stranded DNA-binding fluorescent dyes. Innovative and novel approaches as well as technical improvements have made SNP- or mutation-detection methods increasingly more sophisticated. These advances include DNA/RNA preparation and subsequent amplification steps, and miniaturization of PCR instruments such that testing may be performed with relative ease in clinical laboratories or as a point-of-care test in clinical settings.

Polymerase chain reaction in microfluidic devices

The invention of the polymerase chain reaction (PCR) has caused a revolution in molecular biology, giving access to a method of amplifying deoxyribonucleic acid (DNA) molecules across several orders of magnitude. Since the first application of PCR in a microfluidic device was developed in 1998, an increasing number of researchers have continued the development of microfluidic PCR systems. In this review, we introduce recent developments in microfluidic-based space and time domain devices as well as discuss various designs integrated with multiple functions for sample preparation and detection. The development of isothermal nucleic acid amplification and digital PCR microfluidic devices within the last five years is also highlighted. Furthermore, we introduce various commercial microfluidic PCR devices.

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.

A handheld flow genetic analysis system (FGAS): towards rapid, sensitive, quantitative and multiplex molecular diagnosis at the point-of-care level

A handheld flow genetic analysis system (FGAS) is proposed for rapid, sensitive, multiplex and real-time quantification of nucleic acids at the point-of-care (POC) level. The FGAS includes a helical thermal-gradient microreactor and a microflow actuator, as well as control circuitry for temperature, fluid and power management, and smartphone fluorescence imaging. All of these features are integrated into a field-portable and easy-to-use molecular diagnostic platform powered by lithium batteries. Due to the unique design of the microreactor, not only steady temperatures for denaturation and annealing/extension but also a linear thermal gradient for spatial high-resolution melting can be achieved through simply maintaining a single heater at constant temperature. The smartphone fluorescence imaging system has a wide field of view that captures all PCR channels of the microreactor in a single snapshot without the need for any mechanical scanning. By these designs, the FGAS enables real-time monitoring of the temporal and spatial fluorescence signatures of amplicons during continuous-flow amplification. On the current FGAS, visual detection of as little as 10 copies per μL of genomic DNA of Salmonella enterica was achieved in 15 min, with real-time quantitative detection of the DNA over 6 orders of magnitude concentration from 10(6) to 10(1) copies per μL also completed in 7.5-15 min. In addition, multiple pathogenic DNA targets could be simultaneously discriminated with direct bar-chart readout or multiplex spatial melting in serial flow. We anticipate that the FGAS has great potential to become a next-generation gene analyzer for POC molecular diagnostics.