Implementing Digital PCR in the Lab

Since its inception, polymerase chain reaction (PCR) has had a profound impact on biological research, becoming an integral part of countless scientific workflows. Over the years, a variety of PCR techniques have been developed to meet diverse application needs. Among these innovations, digital PCR (dPCR) has emerged as an advanced method for nucleic acid quantification that is rapidly growing in adoption. This article will explore the fundamental principles of dPCR, highlight its advantages over common alternatives, and discuss practical considerations for its implementation.

Fundamentals of dPCR and qPCR

While the adoption of dPCR is increasing, quantitative PCR (qPCR), also referred to as quantitative real-time PCR, is still a widely used alternative method. Yu Zhao, Sr. Applications Specialist at Roche Diagnostics, shared that qPCR and dPCR build on traditional PCR concepts. “With qPCR, instead of looking at the reaction at the endpoint, the amount of product is tracked in real-time during each cycle,” Zhao noted. Fluorescence dyes like SYBR Green or sequence-specific probes such as TaqMan track the presence of double-stranded DNA. Then, the amplified product and the initial target template can be quantified by analyzing the fluorescence intensity relative to cycle numbers and a standard curve.

For dPCR, samples are separated into thousands of individual partitions, or in the case of droplet digital PCR (ddPCR), individual droplets. “Each partition or droplet is considered an individual reaction with a yes/no answer,” explained Chelsea B. Pratt, BioPharma Segment Marketing Manager at Bio-Rad. If a reaction contains the target sequence, the presence of a dye or probe will cause it to fluoresce. Then, the total number of fluorescing reactions is compared to non-fluorescing reactions. “This enables absolute quantification, without the use of a standard curve that is required by qPCR,” stated Pratt.

Advantages and applications

“Both qPCR and dPCR are extremely valuable for estimating the amount of target molecules in a sample and allow researchers to perform a host of applications,” explained Zhao. Researchers should consider various factors when choosing between these methods, including the number of samples, the required speed and throughput of analysis, their familiarity with the method, and the technique best suited for the research application.

Pratt noted that many molecular labs utilize qPCR for its affordability per sample, rapid turnaround time for results, and ability to manage samples with high concentrations. This technique is extensively used for applications like pathogen detection in clinical samples and gene expression studies. Zhao added that researchers may favor qPCR due to its cost-effectiveness, ease of automation, increased throughput, and well-established protocols and assays.

Conversely, dPCR offers distinct advantages over qPCR. Zhao emphasized that these advantages include high tolerance to PCR inhibitors, high precision over a wide dynamic range, and high sensitivity, which increases further with more partitions. Pratt pointed out that due to its high precision, dPCR is particularly beneficial for analyzing very low input samples, detecting rare target gene, and designing highly multiplexed assays. Furthermore, Pratt emphasized that ddPCR is considered the gold standard for measuring viral titer. Due to its dependence on a standard curve and the need for nearly perfect amplification efficiency, qPCR may inaccurately estimate viral titers in vaccines and gene therapies, while ddPCR is currently preferred for this application to ensure safety, efficacy, and potency.

Considerations and integrations

As an increasing number of labs are making the switch to dPCR for their research, Pratt shared that transitioning to a dPCR platform requires several key considerations. The first involves understanding the core principles of dPCR technology because it operates differently from qPCR and, owing to its high sensitivity, needs careful handling to avoid cross-contamination. Secondly, dPCR offers the absolute quantification of nucleic acids, thereby avoiding the traditional dependence on standard curves. In addition, while dPCR technology may simplify some aspects of normalization, meticulous planning of normalization strategies is still essential, especially for complex samples.

Finally, Pratt shared that researchers must learn to navigate the data analysis software because the data output changes from traditional Cq measurements or delta-delta Cq ratios to concentrations of target copies per microliter. “Adoption of dPCR technology is similar to any new technology in the lab requiring evaluation of how to incorporate the technique in the laboratory ecosystem in order to obtain reliable and reproducible results,” Pratt explained.

Along with these considerations, Zhao noted that dPCR integrates well with other techniques and technologies as a valuable complement or method for monitoring. For instance, the higher sensitivity and precision of dPCR can enhance qPCR results, validate standards, and accurately quantify next-generation sequencing (NGS) libraries. Furthermore, Pratt added that dPCR integrates well with liquid biopsy applications, and in medical diagnostics, it’s particularly effective in the detection of rare mutations in cancer and copy number variations (CNVs), serving as a valuable complement to traditional PCR and qPCR in clinical settings. dPCR also contributes to food safety by detecting harmful contaminants and allergens and supports agricultural breeding programs through crop genotyping. “These examples underscore dPCR's versatility across diverse applications in research, diagnostics, and beyond,” Pratt emphasized.

Final thoughts

For researchers considering making the switch to dPCR, Zhao stressed the importance of assessing the intended application or area of focus. “If the application requires more accuracy and precision, then dPCR would be a good choice,” stated Zhao. This technology is particularly useful for detecting single nucleotide polymorphisms (SNPs), genome edits, and CNVs, as well as for numerous applications in oncology.

Finally, Pratt offered guidance for newer dPCR users, stating how it’s necessary to accurately set thresholds to distinguish between positive and negative partitions. Pratt also recommended incorporating controls, including no-template and positive controls, and validating dPCR assays by comparison with an orthogonal method to ensure reliable results.

The adoption of dPCR will continue growing as more labs recognize the potential of this technology to improve their research efforts.