dPCR System Research Articles

Mammalian and avian species quantification in homogenized foods: real time PCR and digital PCR as tools for label compliance controls

Currently food fraud and authenticity of products composition are topics of great concern; ingredients quantification could allow to identify small amounts of contaminats or voluntary addition of improper components. Many molecular methods are available for species identification in foodstuffs but, for a better application, they should not be affected by the interference of other ingredients. The main purpose of this work was to verify the Real Time PCR and the Digital PCR (dPCR) quantification performances on baby food samples, specifically selected for their high miscibility to limit variability; chicken was selected as target to verify the performance of quantification of methods after having spiked the same quantity in different baby foods. The other aims were: (1) to verify a constant genome copies ratio existence between mammalian and avian species (2) to verify the dPCR performance, set up on housekeeping, to quantify mammalian and avian species in commercial products. Digital PCR showed fewer differences respect to Real Time PCR, at the same 15% w/w chicken spiking level. Despite the constant difference between mammalian and avian genome copies, in samples with the same spiking weight, the confidence intervals increasing towards the extreme values, made impossible to use genome copies ratio as a sort of correction factor between species. Finally, the dPCR system using the myostatin housekeeping gene to determine the chicken content seemed reliable to verify the labelling compliance in meat-based commercial products.

All-In-One OsciDrop Digital PCR System for Automated and Highly Multiplexed Molecular Diagnostics.

Digital PCR (dPCR) holds immense potential for precisely detecting nucleic acid markers essential for personalized medicine. However, its broader application is hindered by high consumable costs, complex procedures, and restricted multiplexing capabilities. To address these challenges, an all-in-one dPCR system is introduced that eliminates the need for microfabricated chips, offering fully automated operations and enhanced multiplexing capabilities. Using this innovative oscillation-induced droplet generation technique, OsciDrop, this system supports a comprehensive dPCR workflow, including precise liquid handling, pipette-based droplet printing, in situ thermocycling, multicolor fluorescence imaging, and machine learning-driven analysis. The system's reliability is demonstrated by quantifying reference materials and evaluating HER2 copy number variation in breast cancer. Its multiplexing capability is showcased with a quadruplex dPCR assay that detects key EGFR mutations, including 19Del, L858R, and T790M in lung cancer. Moreover, the digital stepwise melting analysis (dSMA) technique is introduced, enabling high-multiplex profiling of seven major EGFR variants spanning 35 subtypes. This innovative dPCR system presents a cost-effective and versatile alternative, overcoming existing limitations and paving the way for transformative advances in precision diagnostics.

Abstract 5037: Development of multiplexed Absolute Q digital PCR assays to rapidly quantify EGFR and KRAS genotype in advanced non-small cell lung cancer (NSCLC) patients’ plasma

Abstract Introduction: There are needs to identify and serially monitor driver and resistance mutations (muts) in therapy-treated cancer patients (pts). Quantitative liquid biopsy in cell-free (cf)DNA has been widely adopted. We have developed and clinically validated droplet digital PCR (ddPCR) assays to detect common driver/resistance muts such as EGFR del19, L858R, T790M and KRAS G12X in the cfDNA of advanced NSCLC pts. We have established ddPCR assays for 30+ driver/resistance muts in multiple genes (BRAF, MET, ESR1, etc.) relevant to melanoma, breast, and colorectal cancer. Our assays use tumor/cell line DNA as positive controls and serve as benchmarks to develop newer assays such as plasma NGS. In this study, we converted existing/validated EGFR and KRAS G12X ddPCR assays to the QuantStudio Absolute Q digital PCR (dPCR) system. The selected mutations maximize actionable clinical information and are designed to study oncogenic and resistance mutations in NSCLC efficiently. dPCR’s accuracy and efficiency enables target multiplexing, providing comprehensive information from limited materials and contributing to liquid biopsy research progress. Methods: Plasma from pts with tumors harboring EGFR and KRAS muts was collected at progression with advanced disease following consent to protocol DFCI #14-147. We designed a multiplex dPCR assay that identifies the most common and therapy-relevant KRAS muts in NSCLC, G12C/D/V, and detects other G12X using a drop-off probe. We also designed 2 EGFR kits, one identifying driver muts, the other resistance muts. Results: To validate assay performance, we used gDNA derived from cell lines with EGFR or KRAS muts. We serially diluted mut gDNA samples in background wt gDNA (16 ~ 1000 mut copies in 1000 wt copies) and performed KRAS and EGFR dPCR assays. We detected 16 mut copies with sensitivities similar to those of ddPCR assays. We then studied 48 cfDNA samples from plasma of NSCLC pts with tumor confirmed KRAS G12X or EGFR L858R, del19, T790M muts. No samples had both EGFR and KRAS muts detected, suggesting our assays are specific. We detected muts in samples with an allele frequency median of 0.9% for KRAS mut, 11.9% for EGFR driver mut, 2.9% for EGFR T790M. The concordance rate is 91.3% between dPCR and ddPCR results. Our findings suggest these assays are as sensitive and specific as our validated ddPCR assays. Multiplexed Absolute Q dPCR saves cfDNA and cuts turnaround time (TAT) to 90 min for KRAS assay and 3hr for EGFR assays. Conclusions: We developed rapid, sensitive and specific quantitative dPCR assays for KRAS and EGFR muts on the QuantStudio Absolute Q platform to quantify plasma genotyping in NSCLC. We will clinically pilot our validated rapid genotyping approach and quantify TAT advantage of multiplexed genotyping in NSCLC pts undergoing standard-of-care tumor genotyping. Citation Format: Benjamin Hanna, Shidong Xu, Cloud P. Paweletz, Yanan Kuang. Development of multiplexed Absolute Q digital PCR assays to rapidly quantify EGFR and KRAS genotype in advanced non-small cell lung cancer (NSCLC) patients’ plasma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5037.

A highly integrated digital PCR system with on-chip heating for accurate DNA quantitative analysis

Digital polymerase chain reaction (dPCR) is extensively used for highly sensitive disease diagnosis due to its single-molecule detection ability. However, current dPCR systems require intricate DNA sample distribution, rely on cumbersome external heaters, and exhibit sluggish thermal cycling, hampering efficiency and speed of the dPCR process. Herein, we presented the development of a microwell array based dPCR system featuring an integrated self-heating dPCR chip. By utilizing hydrodynamic and electrothermal simulations, the chip's structure is optimized, resulting in improved partitioning within microwells and uniform thermal distribution. Through strategic hydrophilic/hydrophobic modifications on the chip's surface, we effectively secured the compartmentalization of sample within the microwells by employing an overlaying oil phase, which renders homogeneity and independence of samples in the microwells. To achieve precise, stable, uniform, and rapid self-heating of the chip, the ITO heating layer and the temperature control algorithm are deliberately designed. With a capacity of 22,500 microwells that can be easily expanded, the system successfully quantified EGFR plasmid solutions, exhibiting a dynamic linear range of 105 and a detection limit of 10 copies per reaction. To further validate its performance, we employed the dPCR platform for quantitative detection of BCR-ABL1 mutation gene fragments, where its performance was compared against the QuantStudio 3D, and the self-heating dPCR system demonstrated similar analytical accuracy to the commercial dPCR system. Notably, the individual chip is produced on a semiconductor manufacturing line, benefiting from mass production capabilities, so the chips are cost-effective and conducive to widespread adoption and accessibility.

IGH::NSD2 Fusion Gene Transcript as Measurable Residual Disease Marker in Multiple Myeloma.

Multiple myeloma (MM) is the second most common hematological malignancy. Approximately 15% of MM patients are affected by the t(4;14) translocation resulting in the IGH::NSD2 fusion transcript. Breakage occurs in three major breakpoint regions within the NSD2 gene (MB4-1, MB4-2, and MB4-3), where MB4-1 leads to the production of full-length protein, while truncated proteins are expressed in the other two cases. Measurable residual disease (MRD) has been conclusively established as a crucial prognostic factor in MM. The IGH::NSD2 fusion transcript can serve as a sensitive MRD marker. Using bone marrow (BM) and peripheral blood (PB) samples from 111 patients, we developed a highly sensitive quantitative real-time PCR (qPCR) and digital PCR (dPCR) system capable of detecting fusion mRNAs with a sensitivity of up to 1:100,000. PB samples exhibited sensitivity three orders of magnitude lower compared to BM samples. Patients with an MB4-2 breakpoint demonstrated significantly reduced overall survival (p = 0.003). Our novel method offers a simple and sensitive means for detecting MRD in a substantial proportion of MM patients. Monitoring may be carried out even from PB samples. The literature lacks consensus regarding survival outcomes among patients with different NSD2 breakpoints. Our data align with previous findings indicating that patients with the MB4-2 breakpoint type tend to exhibit unfavorable overall survival.

Technical evaluation of a novel digital PCR platform for detecting EGFR/KRAS mutations in NSCLC archived plasma specimens

IntroductionKRAS p.G12C hot spot mutations has rapidly modified diagnostic algorithm for lung cancer patients electing Non-Small Cell Lung Cancer (NSCLC) patients to target treatment. As regards, patients that harbor this hallmark showed a clinical benefit in terms of progression-free survival (PFS) and overall survival (OS) in comparison with control group under target treatment. In this scenario, KRAS p.G12C mutation requires optimized testing strategy in diagnostic routine practice. Although the widespread diffusion of NGS platforms, a not negligible percentage of Italian diagnostic institutions adopt singleplex technology (RT-PCR, dPCR) for molecular testing. Here, we aim to technically validate a novel dPCR system (QIAcuity™ Digital PCR System, Qiagen; Hilden, Germany) on a retrospective series of cfDNA samples from previously tested with a custom NGS system. (1,2)Methods: n = 50 liquid biopsy specimens (n = 25 KRAS/EGFR mutated and n = 25 wild type for actionable KRAS/EGFR mutations) from diagnostic routine NSCLC patients previously tested with a custom NGS panel were retrieved from our internal archival. Each sample was tested by adopting n = 5 KRAS and n = 3 EGFR commercially available dPCR assays on QIAcuity™ Digital PCR System (Qiagen; Hilden, Germany); an ultra-deep dPCR walk-away platform that automatizes molecular analysis. Technical sensitivity, technical specificity, and concordance rate between “gold standard” NGS system and QIAcuity™ Digital PCR System (Qiagen; Hilden, Germany) were assessed. ResultsOverall, all specimens were successfully analyzed with dPCR system. In details, 24 out of 25 mutated and 21 out of 24 wild type cases were detected. A technical sensitivity, specificity, and a concordance rate of 96.0 % (24/25), 88.0 % (22/25) and 92.0 % (46/50) were evaluated taking into account a MAF cut-off ≥ 0.2 % and a partition number of 100 positive partitions in wild-type channel. ConclusionQiacuity (Qiagen; Hilden, Germany) platform enables accurate molecular analysis of diagnostic routine specimens. Optimized technical workflow is required to technically implement this platform in diagnostic routine setting.

B-228 Partition-free Digital Polymerase Chain Reaction: A Novel Approach to Enable Rapid Turnaround Time With Digital Accuracy

Abstract Background Partition-free digital PCR (dPCR) is a new approach developed to provide absolute quantification in less than 10 min. Partition-free eliminates the need for droplets or physical wells that need to be filled and sealed. The technique relies on rapid thermal cycling and microfluidics to limit diffusion and enable the identification of individual amplicon clusters originating from a single target nucleotide template. Rapid heating and cooling were achieved with a thermal cycling engine comprised of a broadband LED with a sapphire block that is both a light guide and heatsink. Sample is distributed through a custom microfluidic cartridge containing 64 microchannels for optical quantification. Methods The feasibility of partition-free dPCR was tested with primers targeting MTHFR c.665. A titration was performed on three 4X serial dilutions of cell line genomic DNA in triplicate. Fluorescent profiles were generated for all 64 microchannels from an image captured after 35 PCR cycles, where amplicon clusters were identified. Fluorescent peaks of the amplicon clusters were counted and quantified via a custom analysis algorithm, which uses Poisson statistics to calculate concentration. Results The quantification results obtained from the partition-free dPCR system were compared to concentration measurements taken via a Bio-Rad QX200 platform. Concentrations of 69.4 ± 0.8, 15.4 ± 1.5, and 3.3 ± 0.6 copies/µL (R2 = 0.9997) were measured on the partition-free system, and concentrations of 67.8 ± 3.6, 17.2 ± 1.1, and 2.8 ± 0.2 copies/µL (R2 = 0.9995) were measured on the Bio-Rad QX200. Conclusion It has been demonstrated that absolute quantification can be achieved in less than 10 min with a partition-free dPCR platform, and shows results comparable to a QX200 droplet dPCR system. The partition-free rapid dPCR technology described herein allows for the exploration of new avenues in molecular diagnostics, with the potential to bring absolute quantification of dPCR to a Point-of-Care setting.

Fluorescence-coded logarithmic-dilution digital droplet PCR for ultrawide-dynamic-range nucleic acid quantification

Digital PCR (dPCR) is considered the next generation of nucleic acid detection for its ability of absolute quantification and high sensitivity. However, when compared to the current gold standard, quantitative PCR (qPCR), dPCR is falling behind by several orders of magnitude in dynamic range, which limits its clinical applicability. Here we present fluorescence-coded logarithmic-dilution digital droplet PCR (Flodd-PCR) that features a dynamic range across 7 orders of magnitude, over 2 orders higher than conventional dPCR (4–5 log range) and approaching that of qPCR (7–8 log range). Flodd-PCR realizes such a wide dynamic range by dividing ∼20,000 droplets into 4 groups, each featuring a unique dilution factor of the loaded DNA template and thus a shifted dynamic range. This is achieved by a microfluidic chip that performs multi-step serial dilution (20–925 folds) and droplet generation. The post-PCR droplets can be clustered in silico based on their dilution indicator fluorescence and analyzed independently. Experimentally, Flodd-PCR can detect 4–20,000,000 copies/μL (cp./μL) of the synthetic human papillomavirus (HPV) DNA and outperforms standard dPCR when analyzing clinical HPV samples. Furthermore, Flodd-PCR can be implemented with existing dPCR system set-up with minimal adjustment, and therefore will also have wide practicality in different applications which conventional dPCR has already demonstrated.

Digital PCR using a simple PDMS microfluidic chip and standard laboratory equipment.

Digital PCR (dPCR) enables sensitive and precise quantification of template nucleic acid without calibration. However, dPCR is not yet in widespread use, probably due to the need for expensive specialized instruments. In this paper, we describe a dPCR system using a simple microfluidic chip and common laboratory tools. The microfluidic chip consists of two parts: a PDMS part with 24,840 × 0.25 nL microwells and a PDMS-coated flat glass plate. Human RNase P gene was adopted as the model template. Commercial products of human genomic DNA and real-time PCR reagents were mixed to make a PCR mixture. The PCR mixture was confined to the microwells by the PDMS degas-driven liquid control technique. The thermal cycling was performed on a common well-type thermal cycler with a minor modification. During the thermal cycling, evaporation of the PCR mixture was prevented with a handmade water holder. In the fluorescence image, bright (positive) microwells and dim (negative) ones were clearly discriminated. The number of the positive microwells was counted using software, and was used for estimation of the template concentration in the sample based on the theory of the Poisson distribution. The estimated concentrations well agreed with the input template concentrations in the range from 1.32 copies/µL to 13 200 copies/µL. The techniques presented in this paper will pave the way for facile dPCR in a broad range of laboratories without the need for expensive instruments.

Deep learning enables accurate analysis of images generated from droplet-based digital polymerase chain reaction (dPCR)

Accurate analysis of digital polymerase chain reaction (dPCR) images is a key to the successful miniaturization of a dPCR system, which would allow point-of-care testing, but has been hampered by several issues, mainly out-of-focus images, and variations in shape, size, and fluorescence intensities of the droplets. Herein, we performed semantic segmentation by using a deep learning model combined with the circle Hough transform (CHT). For the deep learning model, Attention DeepLabV3+ was modified and used to analyze positive and negative droplets in the low-quality dPCR images, while CHT helps to count the droplets. The modified Attention DeepLabV3+ was trained with augmented 4224 dPCR images, which were sufficient for deep learning model training. As a proof of concept, encapsulated genomic DNA (gDNA) of Escherichia coli O157:H7, a foodborne pathogen, was amplified, and the corresponding droplets were analyzed with the deep learning model to demonstrate its rapid, absolute quantification and accurate identification of the target gDNA. Our analysis method achieved similar accuracy to the commercial, bulky dPCR system, which is based on continuous-flow analysis methods. Furthermore, the deep learning-based approach exhibited a great sensitivity for detecting pathogenic bacteria from low-quality images with a low detection limit of 4.0 × 101 copies/μL. Compared with the commercially available instrument, the deep learning method demonstrated a similar molecular analysis performance. The presented results may lay the ground for efficient absolute quantification of target nucleic acids from the dPCR images as well as the establishment of a point-of-care analysis platform.

Next-Generation Digital Polymerase Chain Reaction: High-Dynamic-Range Single-Molecule DNA Counting via Ultrapartitioning.

Digital PCR (dPCR) was first conceived for single-molecule quantitation. However, current dPCR systems often require DNA templates to share partitions due to limited partitioning capacities. Here, we introduce UltraPCR, a next-generation dPCR system where DNA counting is performed in a single-molecule regimen through a 6-log dynamic range using a swift and parallelized workflow. Each UltraPCR reaction is divided into >30 million partitions without microfluidics to achieve single template occupancy. Combined with a unique emulsion chemistry, partitions are optically clear, enabling the use of a three-dimensional imaging technique to rapidly detect DNA-positive partitions. Single-molecule occupancy also allows for more straightforward multiplex assay development due to the absence of partition-specific competition. As a proof of concept, we developed a 222-plex UltraPCR assay and demonstrated its potential use as a rapid, low-cost screening assay for noninvasive prenatal testing for as low as 4% trisomy fraction samples with high precision, accuracy, and reproducibility.

A rapid multiplex assay of human malaria parasites by digital PCR

BackgroundBlood smear examination through traditional optical microscopy is the gold standard for malaria diagnosis. However, it imposes strict requirements for operational staff and its sensitivity cannot perfectly satisfy the needs of clinical requirements. More sensitive and accurate modern technologies should be applied to this field. Digital PCR (dPCR), as an absolute quantification detection method, can serve as an effective tool to facilitate the diagnosis and classification of different malaria species. ObjectiveWe aimed to establish a new multiplex dPCR detection system for four main Plasmodium species: P. vivax, P. falciparum, P. ovale and P. malariae, which can distinguish exact species of malaria by one PCR reaction. MethodsA total of 39 patients were identified as malaria-positive by microscopic examination in Huashan Hospital from 2016 to 2021; seventy blood samples from these patients were collected. Additionally, 20 healthy individuals, 20 patients with fever and 6 patients with other types of blood parasites infection were also included in this study. Each blood sample was subjected to examination by both blood smears and dPCR. By optimizing four different fluorescence-labeled probes in one reaction system, dPCR permitted the performance of accurate quantitation and working out the exact number of copies of malaria DNA per microliter in whole blood. Rapid diagnostic tests were also conducted to verify part of the results obtained by dPCR. ResultsThe dPCR system was able to make rapid diagnosis and quantification of malaria DNA samples. The analytical sensitivity of multiplex dPCR was as low as 0.557 copies/μL (95% CI 0.521 to 0.607), and it had a sensitivity of 98.0% and a specificity of 100% in clinical samples. Additionally, three multiple malaria co-infection samples have been detected by this dPCR system, including one triple malaria infection case. By testing consecutive daily blood samples of Patient 39, dPCR facilitated monitoring the efficacy of drug treatment. It showed that the DNA concentrations of P. falciparum ranged from 5474 copies/μL to 0 copies/μL, which can reflect the efficacy of antimalarials in real time. This study also found that haemocyte samples (plasma removed) rather than whole blood had higher malaria detection capability and an enhanced positive rate. ConclusionThe multiplex dPCR system newly established here made a substantial contribution in detecting malaria infection at low concentrations. It is suitable for mixed-infection diagnosis and multi-sample continuous monitoring, and presents a promising candidate as an absolute quantitative tool in clinical practice.

Digital polymerase chain reaction strategies for accurate and precise detection of vector copy number in chimeric antigen receptor T-cell products

Background aimsVector copy number (VCN), an average quantification of transgene copies unique to a chimeric antigen receptor (CAR) T-cell product, is a characteristic that must be reported prior to patient administration, as high VCN increases the risk of insertional mutagenesis. Historically, VCN assessment in CAR T-cell products has been performed via quantitative polymerase chain reaction (qPCR). qPCR is reliable along a broad range of concentrations, but quantification requires use of a standard curve and precision is limited. Digital PCR (dPCR) methods were developed for absolute quantification of target sequences by counting nucleic acid molecules encapsulated in discrete, volumetrically defined partitions. Advantages of dPCR compared with qPCR include simplicity, reproducibility, sensitivity and lack of dependency on a standard curve for definitive quantification. In the present study, the authors describe a dPCR assay developed for analysis of the novel bicistronic CD19 × CD22 CAR T-cell construct. MethodsThe authors compared the performance of the dPCR assay with qPCR on both the QX200 droplet dPCR (ddPCR) system (Bio-Rad Laboratories, Inc, Hercules, CA, USA) and the QIAcuity nanoplate-based dPCR (ndPCR) system (QIAGEN Sciences, Inc, Germantown, MD, USA). The primer–probe assay was validated with qPCR, ndPCR and ddPCR using patient samples from pre-clinical CAR T-cell manufacturing production runs as well as Jurkat cell subclones, which stably express this bicistronic CAR construct. ResultsddPCR confirmed the specificity of this assay to detect only the bicistronic CAR product. Additionally, the authors’ assay gave accurate, precise and reproducible CAR T-cell VCN measurements across qPCR, ndPCR and ddPCR modalities. ConclusionsThe authors demonstrate that dPCR strategies can be utilized for absolute quantification of CAR transgenes and VCN measurements, with improved test–retest reliability, and that specific assays can be developed for detection of unique constructs.

An integrated digital PCR system with high universality and low cost for nucleic acid detection.

Digital PCR is the most advanced PCR technology. However, due to the high price of the digital PCR analysis instrument, this powerful nucleic acid detection technology is still difficult to be popularized in the general biochemistry laboratory. Moreover, one of the biggest disadvantages of commercial digital PCR systems is the poor versatility of reagents: each instrument can only be used for a few customized kits. Herein, we built a low-cost digital PCR system. The system only relies on low-cost traditional flat-panel PCR equipment to provide temperature conditions for commercial dPCR chips, and the self-made fluorescence detection system is designed and optically optimized to meet a wide range of reagent requirements. More importantly, our system not only has a low cost (<8000 US dollars) but also has a much higher universality for nucleic acid detection reagents than the traditional commercial digital PCR system. In this study, several samples were tested. The genes used in the experiment were plasmids containing UPE-1a fragment, TP53 reference DNA, hepatitis B virus DNA, leukemia sample, SARS-COV-2 DNA, and SARS-COV-2 RNA. Under the condition that DNA can be amplified normally, the function of the dPCR system can be realized with simpler and low-price equipment. Some DNA cannot be detected by using the commercial dPCR system because of the special formula when it is configured as the reaction solution, but these DNA fluorescence signals can be clearly detected by our system, and the concentration can be calculated. Our system is more applicable than the commercial dPCR system to form a new dPCR system that is smaller and more widely applicable than commercially available machinery.

Digital PCR system development accelerator—A methodology to emulate dPCR results

The development of a digital polymerase chain reaction (dPCR) system typically begins with an idea for the system configuration and chip layout, followed by design, fabrication, and hardware testing. The image processing software can be developed and verified based on the test results. In this paper, we proposed a dPCR emulation methodology to train the developed image processing software before building the dPCR system hardware. We developed a script in a MATLAB environment to generate artificial dPCR images and emulate the dPCR results. First, we defined the number of parameters corresponding to the emulated results, such as the number of partitions with targets, background fluorescence distribution and intensity, image defects, image rotation angle, shift, non-uniform light distribution, and temperature sensitivity. We then implemented the defined parameters and generated an artificial dPCR chip image based on layout design or pattern recognition algorithm. Finally, we obtained a dataset from the artificial image for subsequent result analysis. The generated images could then be used to train the image processing algorithms based on the requirements. We verified the proposed method using various designs of dPCR chips from recently published papers, demonstrating the method's versatility. The proposed method also demonstrated the capability for separating the software and hardware development. Thus, our method allowed the image processing and hardware to be concurrently designed and tested simplifying and speeding up the dPCR system development.

Development of an IoT-integrated multiplexed digital PCR system for quantitative detection of infectious diseases.

For rapid detection of the COVID-19 infection, the digital polymerase chain reaction (dPCR) with higher sensitivity and specificity has been presented as a promising method of point-of-care testing (POCT). Unlike the conventional real-time PCR (qPCR), the dPCR system allows absolute quantification of the target DNA without a calibration curve. Although a number of dPCR systems have previously been reported, most of these previous assays lack multiplexing capabilities. As different variants of COVID-19 have rapidly emerged, there is an urgent need for highly specific multiplexed detection systems. Additionally, the advances in the Internet of Things (IoT) technology have enabled the onsite detection of infectious diseases. Here, we present an IoT-integrated multiplexed dPCR (IM-dPCR) system involving sample compartmentalization, DNA amplification, fluorescence imaging, and quantitative analysis. This IM-dPCR system comprises three modules: a plasmonic heating-based thermal cycler, a multi-color fluorescence imaging set-up, and a firmware control module. Combined with a custom-developed smartphone application built on an IoT platform, the IM-dPCR system enabled automatic processing, data collection, and cloud storage. Using a self-priming microfluidic chip, 9 RNA groups (e.g., H1N1, H3N2, IFZ B, DENV2, DENV3, DENV4, OC43, 229E, and NL63) associated with three infectious diseases (e.g., influenza, dengue, and human coronaviruses) were analyzed with higher linearity (>98%) and sensitivity (1 copy per μL). The IM-dPCR system exhibited comparable analytical accuracy to commercial qPCR platforms. Therefore, this IM-dPCR system plays a crucial role in the onsite detection of infectious diseases.

Construction of dPCR and qPCR integrated system based on commercially available low-cost hardware.

Fluorescent quantitative PCR (qPCR) and digital PCR (dPCR) are two mainstream nucleic acid quantification technologies. However, commercial dPCR and qPCR instruments have a low integration, a high price, and a large footprint. To solve these shortcomings, we introduce a compound PCR system with both qPCR and dPCR functions. All the hardware used in this compound PCR system is commercially available and low-cost, and free software was used to realize the absolute quantification of nucleic acids. The compound PCR provides two working modes. In the qPCR mode, thermal cycling is realized by controlling the reciprocating motion of the x axis. The heating rate is 1.25 °C s-1 and the cooling rate is 1.75 °C s-1. We performed amplification experiments of the PGEM-3zf (+)1 gene. The performance level was similar to commercial qPCR instruments. In the dPCR mode, the heating rate is 0.5 °C s-1 and the cooling rate is 0.6 °C s-1. We performed the UPE-Q gene amplification and used the sequential actions of the two-dimensional mechanical sliders to scan the reaction products and used the method of regional statistics and back-inference threshold to get test results. The result we got was 1208 copies per μL-1, which was similar to expectations.

Duplex dPCR System for Rapid Identification of Gram-Negative Pathogens in the Blood of Patients with Bloodstream Infection: A Culture-Independent Approach.

Early and accurate detection of pathogens is important to improve clinical outcomes of bloodstream infections (BSI), especially in the case of drug-resistant pathogens. In this study, we aimed to develop a culture-independent digital PCR (dPCR) system for multiplex detection of major sepsiscausing gram-negative pathogens and antimicrobial resistance genes using plasma DNA from BSI patients. Our duplex dPCR system successfully detected nine targets (five bacteria-specific targets and four antimicrobial resistance genes) through five reactions within 3 hours. The minimum detection limit was 50 ag of bacterial DNA, suggesting that 1 CFU/ml of bacteria in the blood can be detected. To validate the clinical applicability, cell-free DNA samples from febrile patients were tested with our system and confirmed high consistency with conventional blood culture. This system can support early identification of some drug-resistant gram-negative pathogens, which can help improving treatment outcomes of BSI.

Absolute quantification of SARS-CoV-2 with Clarity Plus™ digital PCR.

In recent years, the usage of digital polymerase chain reaction (dPCR) for various clinical applications has increased exponentially. In this study, a dPCR assay optimized on the Clarity Plus™ dPCR system was evaluated for the absolute quantification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the global coronavirus disease 2019 (COVID-19) outbreak. The assay demonstrated good inter- and intra- assay precision, accuracy, as well as excellent linearity across a range of over 6 orders of magnitude for target gene quantification. In addition, a comparison of the assay on both dPCR and qPCR platforms revealed that dPCR exhibited a slightly higher sensitivity compared to its qPCR counterpart when quantifying SARS-CoV-2 at a lower concentration. Overall, the results showed that the dPCR assay is a reliable and effective approach for the absolute quantification of SARS-CoV-2 and can be a valuable molecular tool in clinical applications such as detecting low viral loads in patients as well as in wastewater surveillance of COVID-19.

Standardization of Two Dpcr Platforms for Detection of BCR/ABL1 - Minimal Residual Disease (MRD) in Ph+ Chronic Myeloid Leukemia (CML)

Background: despite the international efforts on standardization, qPCR has some intrinsic limitations of accuracy and sensitivity that make it suboptimal to assess lower levels of BCR-ABL1. In recent years, digital PCR (dPCR) has emerged to provide a more sensitive and accurate detection of minimal residual disease (MRD), that accounts for the increasing interest for its use in the clinic. The Qx100/Qx200 Droplet Digital PCR System (ddPCR, Biorad) and Quant Studio 3D dPCR System (Thermofisher) are the most widespread platforms commonly used. However nowadays internationally recognized operational protocols are not available.Aim: Aim of our study was: to assess the consistency of the results between two different laboratories that relied on two different platforms; to verify and validate the possible existence of a conversion factor (CF) between the results obtained in the two different laboratories.Material and methods: 16 RNA pools were prepared at different levels of disease (4 pools for 10% level, 4 pools for 1% level, 4 pools for 0.1% level, 4 pools for 0.01% level). dPCR analysis were performed and repeated in 4 separate sessions (hereafter, Exp1, Exp2, Exp3 and Exp4) from the 2 involved laboratories. ddPCR analysis were performed in triplicate for BCR-ABL1 using 200 ng of cDNA for each replicate and in duplicate for ABL1 using 100 ng of cDNA for each replicate; the QuantStudio 3D dPCR analysis were performed in duplicate for both genes using 50 ng of cDNA for each replicate of BCR-ABL1 and 25 ng of cDNA for each replicate of ABL1.Results: In order to assess the consistency of the results between the two different labs we first analyzed multiple replicates of 8/16 samples (2 samples of each disease level were selected) - Exp 1: 10 replicates by ddPCR and 6 replicates by Quant Studio 3D dPCR were performed. Results of each single replicate were expressed as BCR-ABL1/ABL1%. We assessed the compatibility between the values obtained in the two laboratories by linear regression and we obtained R2 = 0.9869. In order to confirm the compatibility we compared the measures through the Bland-Altman bias-plot and we carried out the Mann-Whitney nonparametric test. The results of these 2 tests confirmed the compatibility of the different measures thus we computed the conversion factor (CF) value as the antilog of the average of the differences and obtained a CF value of 1.41.[IC 95% 1.3597- 1.4661]. The mean of the differences before the conversion was 0.1498 (sd 0.1723) and after conversion became zero. The obtained CF value was then validated on different series of experiments, i.e. Exp2, Exp3, Exp4 and it proved to be very satisfactory. For each experiment we used the fold difference to compare the results before and after conversion. We also computed the 95% confidence interval (CI) for the average difference before and after conversion. We saw that the average differences after conversion were closer to 1 with a narrowing of the width of the data distribution. Finally we computed the percentage of measures before and after conversion which were included in a 2-fold range, in a 3-fold range and in a 5-fold range. We observed that the conversion led to a general improvement of the percentage of measures included in the 2-fold-range (73% in Exp2; 88% in Exp 3; 95% in Exp 4).Conclusion: In our study we showed that it is possible to obtainequivalent results from different dPCR platforms by the introduction of a conversion factor. This consistency of the data is mandatory in order to introduce this new technology beside qPCR in CML MRD monitoring. DisclosuresFava:Incyte: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Novartis: Consultancy, Honoraria. Varotto:Bioclarma s.r.l.: Employment. Barberio:Bioclarma s.r.l.: Equity Ownership. Galeotti:Phymtech Srl: Equity Ownership. Ceccherini:Phymtech Srl: Equity Ownership. Cordoni:Phymtech Srl: Employment. Rege-Carmbrin:Incyte: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Novartis: Consultancy, Honoraria. Saglio:BMS: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Ariad: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Ariad: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Roche: Consultancy, Honoraria.