KRAS genotyping by digital PCR combined with melting curve analysis

StratoLAMP: Label-free, multiplex digital loop-mediated isothermal amplification based on visual stratification of precipitate

Multiplex, digital nucleic acid detections have important biomedical applications, but the multiplexity of existing methods is predominantly achieved using fluorescent dyes or probes, making the detection complicated and costly. Here, we present the StratoLAMP for label-free, multiplex digital loop-mediated isothermal amplification based on visual stratification of the precipitate byproduct. The StratoLAMP designates two sets of primers with different concentrations to achieve different precipitate yields when amplifying different nucleic acid targets. In the detection, deep learning image analysis is used to stratify the precipitate within each droplet and determine the encapsulated targets for nucleic acid quantification. We investigated the effect of the amplification reagents and process on the precipitate generation and optimized the assay conditions. We then implemented a deep-learning image analysis pipeline for droplet detection, achieving an overall accuracy of 94.3%. In the application, the StratoLAMP successfully achieved the simultaneous quantification of two nucleic acid targets with high accuracy. By eliminating the need for fluorescence, StratoLAMP represents a unique concept toward label-free, multiplex nucleic acid assays and an analytical tool with great cost-effectiveness.

A Chamber-Based Digital PCR Based on a Microfluidic Chip for the Absolute Quantification and Analysis of KRAS Mutation

The Kirsten rat sarcoma virus gene (KRAS) is the most common tumor in human cancer, and KRAS plays an important role in the growth of tumor cells. Normal KRAS inhibits tumor cell growth. When mutated, it will continuously stimulate cell growth, resulting in tumor development. There are currently few drugs that target the KRAS gene. Here, we developed a microfluidic chip. The chip design uses parallel fluid channels combined with cylindrical chamber arrays to generate 20,000 cylindrical microchambers. The microfluidic chip designed by us can be used for the microsegmentation of KRAS gene samples. The thermal cycling required for the PCR stage is performed on a flat-panel instrument and detected using a four-color fluorescence system. "Glass-PDMS-glass" sandwich structure effectively reduces reagent volatilization; in addition, a valve is installed at the sample inlet and outlet on the upper layer of the chip to facilitate automatic control. The liquid separation performance of the chip was verified by an automated platform. Finally, using the constructed KRAS gene mutation detection system, it is verified that the chip has good application potential for digital polymerase chain reaction (dPCR). The experimental results show that the chip has a stable performance and can achieve a dynamic detection range of four orders of magnitude and a gene mutation detection of 0.2%. In addition, the four-color fluorescence detection system developed based on the chip can distinguish three different KRAS gene mutation types simultaneously on a single chip.

Efficient and accurate KRAS genotyping using digital PCR combined with melting curve analysis for ctDNA from pancreatic cancer patients

A highly sensitive and highly multiplexed quantification technique for nucleic acids is necessary to predict and evaluate cancer treatment by liquid biopsy. Digital PCR (dPCR) is a highly sensitive quantification technique, but conventional dPCR discriminates multiple targets by the color of the fluorescent dye of the probe, which limits multiplexing beyond the number of colors of fluorescent dyes. We previously developed a highly multiplexed dPCR technique combined with melting curve analysis. Herein, we improved the detection efficiency and accuracy of multiplexed dPCR with melting curve analysis to detect KRAS mutations in circulating tumor DNA (ctDNA) prepared from clinical samples. The mutation detection efficiency was increased from 25.9% of the input DNA to 45.2% by shortening the amplicon size. The limit of detection of mutation was improved from 0.41 to 0.06% by changing the mutation type determination algorithm for G12A, resulting in a limit of detection of less than 0.2% for all the target mutations. Then, ctDNA in plasma from pancreatic cancer patients was measured and genotyped. The measured mutation frequencies correlated well with those measured by conventional dPCR, which can measure only the total frequency of KRAS mutants. KRAS mutations were detected in 82.3% of patients with liver or lung metastasis, which was consistent with other reports. Accordingly, this study demonstrated the clinical utility of multiplex dPCR with melting curve analysis to detect and genotype ctDNA from plasma with sufficient sensitivity.

Development and validation of cost-effective one-step multiplex RT-PCR assay for detecting the SARS-CoV-2 infection using SYBR Green melting curve analysis

TaqMan probe-based commercial real-time (RT) PCR kits are expensive but most frequently used in COVID-19 diagnosis. The unprecedented scale of SARS-CoV-2 infections needs to meet the challenge of testing more persons at a reasonable cost. This study developed a simple and cost-effective alternative diagnostic method based on melting curve analysis of SYBR green multiplex assay targeting two virus-specific genes along with a host-specific internal control. A total of 180 randomly selected samples portioning into two subsets based on crude and high-quality RNA extraction were used to compare this assay with a nationwide available commercial kit (Sansure Biotech Inc., (Hunan, China)), so that we could analyze the variation and validity of this in-house developed method. Our customized-designed primers can specifically detect the viral RNA likewise Sansure. We separately optimized SYBR Green RT-PCR reaction of N, E, S, and RdRp genes based on singleplex melting curve analysis at the initial stage. After several rounds of optimization on multiplex assays of different primer combinations, the optimized method finally targeted N and E genes of the SARS-CoV-2 virus, together with the β-actin gene of the host as an internal control. Comparing with the Sansure commercial kit, our proposed assay provided up to 97% specificity and 93% sensitivity. The cost of each sample processing ranged between ~2 and ~6 USD depending on the purification level of extracted RNA template. Overall, this one-step and one-tube method can revolutionize the COVID-19 diagnosis in low-income countries.

An image-to-answer algorithm for fully automated digital PCR image processing

The digital polymerase chain reaction (dPCR) is an irreplaceable variant of PCR techniques due to its capacity for absolute quantification and detection of rare deoxyribonucleic acid (DNA) sequences in clinical samples. Image processing methods, including micro-chamber positioning and fluorescence analysis, determine the reliability of the dPCR results. However, typical methods demand high requirements for the chip structure, chip filling, and light intensity uniformity. This research developed an image-to-answer algorithm with single fluorescence image capture and known image-related error removal. We applied the Hough transform to identify partitions in the images of dPCR chips, the 2D Fourier transform to rotate the image, and the 3D projection transformation to locate and correct the positions of all partitions. We then calculated each partition's average fluorescence amplitudes and generated a 3D fluorescence intensity distribution map of the image. We subsequently corrected the fluorescence non-uniformity between partitions based on the map and achieved statistical results of partition fluorescence intensities. We validated the proposed algorithms using different contents of the target DNA. The proposed algorithm is independent of the dPCR chip structure damage and light intensity non-uniformity. It also provides a reliable alternative to analyze the results of chip-based dPCR systems.

Amplification Curve Analysis: Data-Driven Multiplexing Using Real-Time Digital PCR

Information about the kinetics of PCR reactions is encoded in the amplification curve. However, in digital PCR (dPCR), this information is typically neglected by collapsing each amplification curve into a binary output (positive/negative). Here, we demonstrate that the large volume of raw data obtained from real-time dPCR instruments can be exploited to perform data-driven multiplexing in a single fluorescent channel using machine learning methods, by virtue of the information in the amplification curve. This new approach, referred to as amplification curve analysis (ACA), was shown using an intercalating dye (EvaGreen), reducing the cost and complexity of the assay and enabling the use of melting curve analysis for validation. As a case study, we multiplexed 3 carbapenem-resistant genes to show the impact of this approach on global challenges such as antimicrobial resistance. In the presence of single targets, we report a classification accuracy of 99.1% (N = 16188), which represents a 19.7% increase compared to multiplexing based on the final fluorescent intensity. Considering all combinations of amplification events (including coamplifications), the accuracy was shown to be 92.9% (N = 10383). To support the analysis, we derived a formula to estimate the occurrence of coamplification in dPCR based on multivariate Poisson statistics and suggest reducing the digital occupancy in the case of multiple targets in the same digital panel. The ACA approach takes a step toward maximizing the capabilities of existing real-time dPCR instruments and chemistries, by extracting more information from data to enable data-driven multiplexing with high accuracy. Furthermore, we expect that combining this method with existing probe-based assays will increase multiplexing capabilities significantly. We envision that once emerging point-of-care technologies can reliably capture real-time data from isothermal chemistries, the ACA method will facilitate the implementation of dPCR outside of the lab.

10-Plex Digital Polymerase Chain Reaction with Four-Color Melting Curve Analysis for Simultaneous KRAS and BRAF Genotyping

Digital PCR (dPCR) is a promising method for performing liquid biopsies that quantifies nucleic acids more sensitively than real-time PCR. However, dPCR shows large fluctuations in the fluorescence intensity of droplets or wells due to insufficient PCR amplification in the small partitions, limiting the multiplexing capability of using the fluorescence intensity. In this study, we propose a measurement method that combines dPCR with melting curve analysis for highly multiplexed genotyping. A sample was digitized into a silicon chip with up to 2 × 10⁴ wells in which asymmetric PCR was performed to obtain more single-stranded amplicons that were complementary to molecular beacon probes. Fluorescence images were captured while controlling the temperature of the chip, and the melting curve was measured for each well. Then, genotyping was performed by using the fluorescence intensity, the dye color of the probe, and the melting temperature (T_m). Because the T_m of the PCR products is not highly dependent on the amplification efficiency of PCR, genotyping accuracy is improved by using T_m values, enabling highly multiplexed genotyping. The concept was confirmed by simultaneously identifying wild-type KRAS, BRAF, and eight mutants of these genes (G12D, G12R, G12V, G13D, G12A, G12C, G12S, and V600E) through four-color melting curve analysis. To the best of our knowledge, this is the first demonstration of the genotyping of 10 DNA groups including single mutations of cancer-related genes by combining dPCR with four-color melting curve analysis.

Rapid Characterization of Biomolecules' Thermal Stability in a Segmented Flow-Through Optofluidic Microsystem

Optofluidic devices combining optics and microfluidics have recently attracted attention for biomolecular analysis due to their high detection sensitivity. Here, we show a silicon chip with tubular microchannels buried inside the substrate featuring temperature gradient (∇T) along the microchannel. We set up an optical fluorescence system consisting of a power-modulated laser light source of 470 nm coupled to the microchannel serving as a light guide via optical fiber. Fluorescence was detected on the other side of the microchannel using a photomultiplier tube connected to an optical fiber via a fluorescein isothiocyanate filter. The PMT output was connected to a lock-in amplifier for signal processing. We performed a melting curve analysis of a short dsDNA - SYBR Green I complex with a known melting temperature (TM) in a flow-through configuration without gradient to verify the functionality of the proposed detection system. We then used the segmented flow configuration and measured the fluorescence amplitude of a droplet exposed to ∇T of ≈ 2.31 °C mm-1, determining the heat transfer time as ≈ 554 ms. The proposed platform can be used as a fast and cost-effective system for performing either MCA of dsDNAs or for measuring protein unfolding for drug-screening applications.