Digital PCR is more accurate at measuring low quantities of target DNA.Credit: majcot/Shutterstock
In the early days of the COVID-19 pandemic, Warish Ahmed, senior scientist at the Commonwealth Scientific and Industrial Research Organization (CSIRO), used a qPCR-based method to detect SARS-CoV-2 from wastewater in Brisbane, Australia1. This type of analysis is increasingly used to detect local disease outbreaks, even before any cases are reported from clinical samples. And when cases are high, this method works well.
However, real-time or quantitative PCR (qPCR) loses its accuracy if the sample contains many other components, such as proteins, polysaccharides or RNases that inhibit the PCR reaction, or if the target molecule is present in very small amounts. “As vaccines reduce the number of COVID-19 infections, it will become harder to detect in the wastewater, as the viral concentration will be very low,” Ahmed says. He needed a more sensitive detection method and turned to digital PCR (dPCR), discovering that it was able to detect viruses in samples that were negative with qPCR2,3.
Picking up the smallest traces
The principle behind dPCR involves splitting each sample into thousands of smaller sections. Some will include one or more copies of the target molecule, whereas others will have none. After running a PCR reaction on all partitions, the readout shows whether each contained a target or not. This digital readout is a representation of the amount of target in the sample; in samples with fewer target molecules, more partitions will be empty.
Unlike qPCR, dPCR doesn’t require a standard curve, it’s more accurate when measuring very low amounts of a target, and it’s less vulnerable to PCR inhibitors that might be present in the sample.
“We've seen digital PCR excelling in lots of fields,” says Afif Abdel Nour, Associate Director, Global Strategic Marketing dPCR at QIAGEN. That includes liquid biopsies, where dPCR can detect copy number variation, and biopharma applications, such as quantifying the number of AAV vectors in gene therapy or vector copy number assessment in CAR-T cell products4. And, as Ahmed discovered, it can even handle the complexities of wastewater samples.
Wastewater can contain PCR inhibitors, making it challenging to analyse using qPCR.Credit: Felipe Caparros/Shutterstock
Nanoplates, not droplets
The system that Ahmed used was the QIAcuity nanoplate-based system from QIAGEN. "Initially, most people were using droplet dPCR," says Abdel Nour. But the company’s nanoplate system introduced several improvements to the dPCR method. It's more automated, allows for a higher throughput of samples, and is more accurate.
The increased accuracy is due to the way dPCR calculates the amount of target molecules in the sample. It uses Poisson's distribution law, which assumes that each partition is the same size. “That's what we're offering with the nanoplate," says Abdel Nour. Here, samples are split into 26,000 fixed partitions of equal size, rather than in droplets, which are unstable and can vary in size, skewing the distribution of target molecules.
In addition to achieving increased accuracy, the nanoplate system also more closely resembles the high-throughput sample handling of qPCR, making it easier to cope with bigger jobs.
That is good news for researchers and labs working with liquid biopsies, carrying out wastewater surveillance, or pursuing other hard-to-detect genetic targets. Thanks to these technological advances, dPCR will likely be the method of choice for many of these applications.