Development of novel digital PCR assays for the rapid quantification of Gram-negative bacteria biomarkers using RUCS algorithm.

Rapid and accurate identification of bacterial pathogens is crucial for effective treatment and infection control, particularly in hospital settings. Conventional methods like culture techniques and MALDI-TOF mass spectrometry are often time-consuming and less sensitive. This study addresses the need for faster and more precise diagnostic methods by developing novel digital PCR (dPCR) assays for the rapid quantification of biomarkers from three Gram-negative bacteria: Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa. Utilizing publicly available genomes and the rapid identification of PCR primers for unique core sequences or RUCS algorithm, we designed highly specific dPCR assays. These assays were validated using synthetic DNA, bacterial genomic DNA, and DNA extracted from clinical samples. The developed dPCR methods demonstrated wide linearity, a low limit of detection (∼30 copies per reaction), and robust analytical performance with measurement uncertainty below 25 %. The assays showed high repeatability and intermediate precision, with no cross-reactivity observed. Comparison with MALDI-TOF mass spectrometry revealed substantial concordance, highlighting the methods' suitability for clinical diagnostics. This study underscores the potential of dPCR for rapid and precise quantification of Gram-negative bacterial biomarkers. The developed methods offer significant improvements over existing techniques, providing faster, more accurate, and SI-traceable measurements. These advancements could enhance clinical diagnostics and infection control practices.

The performance of human cytomegalovirus digital PCR reference measurement procedure in seven external quality assessment schemes over four years.

A candidate digital PCR (dPCR)-based reference measurement procedure for quantification of human cytomegalovirus (hCMV) was evaluated in 10 viral load comparison schemes (seven external quality assessment (EQA) and three additional training schemes) organized by INSTAND e.V. over four years (between September 2014 and March 2018). Four metrology institutes participated in these schemes using the same extraction method and dPCR measurement procedure for the hCMV specific target sequence of UL54 gene. The calibration independent reference measurement procedure results from the metrology institutes were compared to the results of the clinical diagnostic laboratories applying hCMV qPCR measurement procedures calibrated to reference materials. While the criteria for the acceptable deviation from the target value interval for INSTAND's EQA schemes is from -0.8 log10 to +0.8 log10, the majority of dPCR results were between -0.2 log10 to +0.2 log10. Only 4 out of 45 results exceeded this interval with the maximum deviation of -0.542 log10. In the training schemes containing samples with lower hCMV concentrations, more than half of the results deviated less than ±0.2 log10 from the target value, while more than 95% deviated less than ±0.4 log10 from the target value. Evaluation of intra- and inter-laboratory variation of dPCR results confirmed high reproducibility and trueness of the method. This work demonstrates that dPCR has the potential to act as a calibration independent reference measurement procedure for the value assignment of hCMV calibration and reference materials to support qPCR calibration as well as ultimately for routine hCMV load testing.

Multiplex quantification of 12 European Union authorized genetically modified maize lines with droplet digital polymerase chain reaction.

Presence of genetically modified organisms (GMO) in food and feed products is regulated in many countries. The European Union (EU) has implemented a threshold for labeling of products containing more than 0.9% of authorized GMOs per ingredient. As the number of GMOs has increased over time, standard-curve based simplex quantitative polymerase chain reaction (qPCR) analyses are no longer sufficiently cost-effective, despite widespread use of initial PCR based screenings. Newly developed GMO detection methods, also multiplex methods, are mostly focused on screening and detection but not quantification. On the basis of droplet digital PCR (ddPCR) technology, multiplex assays for quantification of all 12 EU authorized GM maize lines (per April first 2015) were developed. Because of high sequence similarity of some of the 12 GM targets, two separate multiplex assays were needed. In both assays (4-plex and 10-plex), the transgenes were labeled with one fluorescence reporter and the endogene with another (GMO concentration = transgene/endogene ratio). It was shown that both multiplex assays produce specific results and that performance parameters such as limit of quantification, repeatability, and trueness comply with international recommendations for GMO quantification methods. Moreover, for samples containing GMOs, the throughput and cost-effectiveness is significantly improved compared to qPCR. Thus, it was concluded that the multiplex ddPCR assays could be applied for routine quantification of 12 EU authorized GM maize lines. In case of new authorizations, the events can easily be added to the existing multiplex assays. The presented principle of quantitative multiplexing can be applied to any other domain.

Metrological evaluation of DNA extraction method effects on the bacterial microbiome and resistome in sputum.

Targeted high-throughput sequencing (HTS) has revolutionized the way we look at bacterial communities. It can be used for the species-specific detection of bacteria as well as for the determination of the microbiome and resistome and can be applied to samples from almost any environment. However, the results of targeted HTS can be influenced by many factors, which poses a major challenge for its use in clinical diagnostics. In this study, we investigated the impact of the DNA extraction method on the determination of the bacterial microbiome and resistome by targeted HTS using principles from metrology and diagnostics such as repeatability and analytical sensitivity. Sputum samples spiked with Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa at three different concentrations (103-106 cells/mL) were used. DNA was extracted from each sample on 2 separate days in three replicates each using three different extraction methods based on cetrimonium bromide, magnetic beads, and silica membranes. All three spiked bacteria were detected in sputum, and the DNA extraction method had no significant effect on detection. However, the DNA extraction method had significant effects on the composition of the microbiome and the resistome. The sequencing results were repeatable in the majority of cases. The silica membrane-based DNA extraction kit provided the most repeatable results and the highest diversity of the microbiome and resistome. Targeted HTS has been shown to be a reliable tool for determining the microbiome and resistome; however, the method of DNA extraction should be carefully selected to minimize its impact on the results. IMPORTANCE: High-throughput sequencing (HTS) is one of the crucial new technologies that gives us insights into previously hidden parts of microbial communities. The DNA extraction method is an important step that can have a major impact on the results, and understanding this impact is of paramount importance for their reliable interpretation. Our results are of great value for the interpretation of sputum microbiome and resistome results obtained by targeted HTS. Our findings allow for a more rational design of future microbiome studies, which would lead to higher repeatability of results and easier comparison between different laboratories. This could also facilitate the introduction of targeted HTS in clinical microbiology for reliable identification of pathogenic bacteria and testing for antimicrobial resistance (AMR). As AMR is a major threat to public health, the improved methods for determining AMR would bring great benefits to both the healthcare system and society as a whole.

Evaluation of DNA Extraction Methods for Reliable Quantification of Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa.

Detection and quantification of DNA biomarkers relies heavily on the yield and quality of DNA obtained by extraction from different matrices. Although a large number of studies have compared the yields of different extraction methods, the repeatability and intermediate precision of these methods have been largely overlooked. In the present study, five extraction methods were evaluated, using digital PCR, to determine their efficiency in extracting DNA from three different Gram-negative bacteria in sputum samples. The performance of two automated methods (GXT NA and QuickPick genomic DNA extraction kit, using Arrow and KingFisher Duo automated systems, respectively), two manual kit-based methods (QIAamp DNA mini kit; DNeasy UltraClean microbial kit), and one manual non-kit method (CTAB), was assessed. While GXT NA extraction kit and the CTAB method have the highest DNA yield, they did not meet the strict criteria for repeatability, intermediate precision, and measurement uncertainty for all three studied bacteria. However, due to limited clinical samples, a compromise is necessary, and the GXT NA extraction kit was found to be the method of choice. The study also showed that dPCR allowed for accurate determination of extraction method repeatability, which can help standardize molecular diagnostic approaches. Additionally, the determination of absolute copy numbers facilitated the calculation of measurement uncertainty, which was found to be influenced by the DNA extraction method used.

Fast and Accurate Multiplex Identification and Quantification of Seven Genetically Modified Soybean Lines Using Six-Color Digital PCR.

The proliferation of genetically modified organisms (GMOs) presents challenges to GMO testing laboratories and policymakers. Traditional methods, like quantitative real-time PCR (qPCR), face limitations in quantifying the increasing number of GMOs in a single sample. Digital PCR (dPCR), specifically multiplexing, offers a solution by enabling simultaneous quantification of multiple GMO targets. This study explores the use of the Naica six-color Crystal dPCR platform for quantifying five GM soybean lines within a single six-plex assay. Two four-color assays were also developed for added flexibility. These assays demonstrated high specificity, sensitivity (limit of detection or LOD < 25 copies per reaction) and precision (bias to an estimated copy number concentration <15%). Additionally, two approaches for the optimization of data analysis were implemented. By applying a limit-of-blank (LOB) correction, the limit of quantification (LOQ) and LOD could be more precisely determined. Pooling of reactions additionally lowered the LOD, with a two- to eight-fold increase in sensitivity. Real-life samples from routine testing were used to confirm the assays' applicability for quantifying GM soybean lines in complex samples. This study showcases the potential of the six-color Crystal dPCR platform to revolutionize GMO testing, facilitating comprehensive analysis of GMOs in complex samples.

One-Step Reverse-Transcription Digital PCR for Reliable Quantification of Different Pepino Mosaic Virus Genotypes.

In recent years, pepino mosaic virus (PepMV) has rapidly evolved from an emerging virus to an endemic pathogen, as it causes significant loses to tomato crops worldwide. At present, the main control strategy for prevention of PepMV disease in tomato production remains based on strict hygiene measures. To prevent damage caused by PepMV, cross-protection is used in some countries. Reliable characterisation, detection and quantification of the pathogen are vital for disease control. At present, reverse-transcription real-time quantitative polymerase chain reaction (RT-qPCR) is generally used for this purpose. However, quantitative use of RT-qPCR is linked to standardised reference materials, which are not available for PepMV. In addition, many factors can influence RT-qPCR efficiencies and lead to lower accuracy of the quantification. In this study, well-characterised PepMV-genotype-specific RT-qPCR assays were transferred to two digital PCR (dPCR) platforms. dPCR-based assays allow absolute quantification without the need for standard curves, and due to the binary nature of the reaction, dPCR also overcomes many of the other drawbacks of RT-qPCR. We have shown that these newly developed and validated PepMV-genotype-specific dPCR assays are suitable candidates for higher-order methods for quantification of PepMV RNA, as they show lower measurement variability, with sensitivity and specificity comparable to RT-qPCR.

Digital PCR method for detection and quantification of specific antimicrobial drug-resistance mutations in human cytomegalovirus.

Antimicrobial drug resistance is one of the biggest threats to human health worldwide. Timely detection and quantification of infectious agents and their susceptibility to antimicrobial drugs are crucial for efficient management of resistance to antiviral drugs. In clinical settings, viral drug resistance is most often associated with prolonged treatment of chronic infections, and assessed by genotyping methods; e.g., sequencing and PCR. These approaches have limitations: sequencing can be expensive and does not provide quantification; and qPCR quantification is hampered by a lack of reference materials for standard curves. In recent years, digital PCR has been introduced, which provides absolute quantification without the need for reference materials for standard curves. Using digital PCR, we have developed a rapid, sensitive and accurate method for genotyping and quantification of the most prevalent mutations that cause human cytomegalovirus resistance to ganciclovir.

Digital PCR as an effective tool for GMO quantification in complex matrices.

The increased use of genetically modified organisms (GMOs) is accompanied by increased complexity of the matrices that contain GMOs. The most common DNA-based approach for GMO detection and quantification is real-time quantitative polymerase chain reaction (qPCR). However, as qPCR is sensitive to inhibitors and relies on standard curves for quantification, it has limited application in GMO quantification for complex matrices. To overcome this hurdle in DNA quantification, we present droplet digital PCR (ddPCR) assays that were designed to target 'Roundup Ready' soybean and the soybean reference gene. Three ddPCR assays were transferred from qPCR to QX100/QX200 ddPCR platforms and characterised. Together, the fitness-for-purpose study on four real-life samples and the use of a chamber-based PCR system, showed that dPCR has great potential to improve such measurements in GMO testing and monitoring of food authenticity.

Multiplex Droplet Digital PCR Protocols for Quantification of GM Maize Events.

The standard-curve based simplex quantitative polymerase chain reaction (qPCR) has been the gold standard for DNA target quantification for more than a decade. The large and growing number of individual analyses needed to test for genetically modified organisms (GMOs) is reducing the cost-effectiveness of qPCR. Droplet digital PCR (ddPCR) enables absolute quantification without standard curves, avoids the amplification efficiency bias observed with qPCR, allows more accurate estimations at low target copy numbers and, in combination with multiplexing, significantly improves cost efficiency. Here we describe two protocols for multiplex quantification of GM maize events: (1) nondiscriminating, with multiplex quantification of targets as a group (12 GM maize lines) and (2) discriminating, with multiplex quantification of individual targets (events). The first enables the quantification of twelve European Union authorized GM maize events as a group with only two assays, but does not permit determination of the individual events present. The second protocol enables the quantification of four individual targets (three GM events and one endogene) in a single reaction. Both protocols can be modified for quantification of any other DNA target.