Digital Polymerase Chain Reaction and Its Diagnostic Applications
BY: Dr. Roy Lau
Sep 16, 2020

Digital Polymerase Chain Reaction and Its Diagnostic Applications

 

Quantitative real time polymerase chain reaction (RT-PCR) is widely used in clinical detection. However, the limitations of the technology including easy affected by sample inhibitors, poor amplification efficiency, less precision in low-concentration samples, subjective cut-off values and quantification depending on a calibration curve increase the risk of false negative reports1. To overcome the limitations, the digital polymerase chain reaction (dPCR) is developed. The dPCR is considered to be the 3rd generation PCR, as it yields direct, absolute and precise measures of target sequences. Particularly, it has proven useful for accurate detection and quantification of low-abundance nucleic acids2, highlighting its advantages in cancer diagnosis and in predicting recurrence and monitoring minimal residual disease (MRD), mostly coupled with next generation sequencing (NGS). In the current COVID-19 pandemic, dPCR has been employed for the early detection of SARS-CoV-2 infection.


Principle of dPCR

PCR is a technique that amplifies DNA, generating several millions of copies of a specific segment of DNA from a minute amount of starting material. The sensitivity of PCR depends on the enzyme-based amplification, whereas its specificity depends on sequence hybridisation. Practically, PCR consists of a series of temperature cycles repeated 20 to 40 times. In each cycle, thermal denaturation of DNA duplexes occurs followed by hybridisation of 2 DNA oligonucleotides (primers) flanking the target sequence, and the elongation of those primers by a DNA polymerase. Each cycle results in a doubling of the number of target DNA molecules. The amplification process saturates and reaches a plateau as PCR reagents are depleted and accumulated PCR products self-anneal, preventing any further amplification (Figure 1)3.

 

Figure 1. Principle of PCR3

 

Conventional PCR analyses amplified products using gel electrophoresis, whereas RT-PCR measures the amount of PCR product after each round of amplification using fluorescent readout. Particularly, quantitative RT-PCR allows relative quantification of the target sequence by calibrating with a standard curve generated from a sample of known quantity4. Of note, it is important for quantitative RT-PCR to ensure the amplification efficiencies of the sample and the standards are equivalent. Otherwise, the quantification accuracy would be significantly affected5.

 

Instead of relative estimation, dPCR enables absolute quantification of target nucleic acids present in a sample and alleviates the shortcomings of quantitative RT-PCR. Briefly, dPCR is based on the principle of partitioning the sample into several PCR sub-reactions containing single, few or no target-sequences. The partitioning of the DNA template is mainly based on microwell chip, water-in-oil droplet and microfluidic techniques. Among these methods, the water-in-oil droplet technique is the most frequently used. The PCR partitions are read and counted as negative or positive by thresholding based on their fluorescence amplitude. Then, the concentration of target sequence is calculated using the number of positive and negative partitions based on Poisson’s statistics2. A summarised comparison of dPCR and quantitative RT-PCR is illustrated in Figure 2.

 

Figure 2. Comparison between dPCR and quantitative RT-PCR (qPCR)6

 

In dPCR, fluorescent dyes are included in the DNA amplification reaction and thus quantification can be achieved without the need of PCR threshold cycle values and standard curves. Further, compartmentalisation enables quantification with less impact by poor amplification efficiency and inhibitors of amplification that may present in samples. It also reduces any template competition in the reaction mixture, allowing for the detection of rare target sequences1. Hence, dPCR generally gives higher sensitivity, better accuracy and more stable replications as compared with quantitative RT-PCR.

 
Clinical Applications of dPCR

In view of the high precision and sensitivity of dPCR, the technology can be applied in various clinical fields. For instance, dPCR has been applied for the detection of several somatic mutations, both for absolute allele quantification and for rare mutation detection. Fontanelli et al (2015) compared the performance of dPCR and quantitative RT-PCR on detection of the JAK 2V617F mutation, which presents in 50%-95% of Philadelphia-negative chronic myeloproliferative neoplasms (MPNs). The results demonstrated an absolute concordance in terms of specificity between the 2 testing protocols, whereas dPCR exhibited higher sensitivity as compared to quantitative RT-PCR. The results further showed a progressive increase of mutant allele burden from essential thrombocythemia to polycythemia vera, and primary myelofibrosis to secondary myelofibrosis7.

 

On the other hand, dPCR can be applied in monitoring for disease relapse after complete remission (CR). Acute myelogenous leukaemia (AML) frequently relapses after CR. Hence, improved detection and phenotypic characterisation of treatment-resistant residual disease is needed. Parkin et al (2017) employed dPCR to study variant allele fractions of frequently mutated genes in samples from AML patients in CR to evaluate the persistence of mutated clones at a level as low as 0.002%. The results demonstrated that majority of AML cases showed residual aberrant oligoclonal haematopoiesis. Essentially, dPCR was able to detect very rare cells, as 1 in 15,000 cells, which were genomically similar to the dominant blast populations at diagnosis and were fully clonally represented at relapse, identifying these rare cells as one common source of AML relapse8. The report highlights the application of dPCR in detecting rare cell populations that cause AML relapse and hence facilitating improvement in AML treatment outcome.

 

Besides oncologic applications, the ability of dPCR to perform absolute quantitation that does not rely on a well-calibrated standard or highly efficient amplification is useful for the determination of pathogen loads. dPCR has been used to determine the copy numbers of DNA and RNA viruses, bacteria, and parasites in a variety of clinical specimens. Assays have been used to quantify many viruses, including human immunodeficiency virus (HIV) DNA, hepatitis B virus (HBV) and human papillomavirus (HPV)9. Essentially, due to pathogens of latency infection, like Ebola virus, malaria, HIV and tuberculosis, their concentrations in plasma are sometimes too low to be determined by traditional methods like ELISA or blood smear. Although quantitative RT-PCR has been widely used for the tests of clinical samples, its sensitivity, accuracy, and replicability are still not satisfying. Particularly, the accuracy in detection of pathogens of quantitative RT-PCR is disappointing if the pathogen load is very low6.

 

Another useful application of dPCR for the clinical laboratory is characterisation of reference standards. Reference standards that are used in routine quantitative RT-PCR assays can be initially calibrated using dPCR, which does not rely on a calibrator for quantitation10.

 
dPCR in COVID-19

The pandemic of COVID-19 caused by the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a great threat to public health worldwide. The current gold standard for the diagnosis of SARS-CoV-2 infection is based on the quantitative RT-PCR. However, it has been reported that some patients had fever and showed symptoms of suspected viral pneumonia such as lower lobe lesions of the lungs by chest computed tomography (CT), but the nucleic acid test of throat swab using quantitative RT-PCR did not show positive results until 5-6 days after the onset of viral pneumonia. Of note, around 60% of SARS-CoV-2 infections are asymptomatic11. The false negative and asymptomatic cases might be explained by the low viral load in the throat swabs of patients that limits the accuracy of quantitative RT-PCR. Nonetheless, the false negative results would lead to a potential risk of viral transmission.

 

To overcome the limitations of quantitative RT-PCR in detecting SARS-CoV-2, Suo et al (2020) evaluated the performance of dPCR in detecting SARS-CoV-2 RNA from throat swab specimens from 77 patients and compared the results with those obtained with quantitative RT-PCR. The results revealed that 26 patients of COVID-19 with negative RT-PCR reports were reported as positive by dPCR. Moreover, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), negative likelihood ratio (NLR) and accuracy were improved in measurement with dPCR. Besides, 6/14 (42.9%) convalescents were detected as positive by dPCR at 5-12 days post discharge1. Thus, the results indicated the superiority of dPCR for clinical diagnosis of SARS-CoV-2 to reduce the false negative reports as compared with RT-PCR.

 

The choice of the analysis technique should be that of the most precise and sensitive method, whereas dPCR offers a number of clear advantages over the earlier generations of PCR. In the current pandemic of COVID-19, dPCR would facilitate more accurate early diagnosis of SARS-CoV-2 infections and, in turn, help controlling viral transmission. Similar to other diagnostic tests, further technical advancement in the procedures of dPCR, such as automation, and exploration on potential uses of the technology would help expanding the scope of its applications.

 

References

1. Suo et al. Emerg Microbes Infect 2020; 9: 1259-68. 2. Coccaro et al. Int. J. Mol. Sci. 2020; 21. DOI:10.3390/ijms21093141. 3. Quan et al. Sensors (Switzerland). 2018; 18. DOI:10.3390/s18041271. 4. Bustin et al. Clin Chem 2009; 55: 611-22. 5. Svec et al. Biomol Detect Quantif 2015; 3: 9-16. 6. Li et al. Biosci. Rep. 2018; 38: 20181170. 7. Fontanelli et al. Int J Lab Hematol 2015; 37: 766-73. 8. Parkin et al. J Clin Invest 2017; 127: 3484-95. 9. Jeannot et al. J Pathol Clin Res 2016; 2: 201-9. 10. Li et al. Clin Chem Lab Med 2016; 54: 1427-33. 11. Qiu. Nature. 2020; DOI:10.1038/d41586-020-00822-x.

<
>