When PCR Gets Dirty – Tackling PCR Inhibitors

In this first Absolute Gene-ius: Science Snapshot episode, hosts Jordan Ruggieri and Lisa Crawford revisit expert insights on one persistent molecular biology challenge: PCR inhibitors. Across wastewater surveillance, environmental microbiology, and gene therapy manufacturing, inhibitors can distort PCR data and complicate quantification.

Featuring perspectives from Ray Ketchum, PhD; Sarah Philo, PhD; Patrick Hanington, PhD; Dave Bauer, PhD; Kimberly Gomez; and Min Jin Kim, PhD, this episode explores why inhibition happens and how digital PCR (dPCR) can be a resilient method when accuracy is critical.

Listen to the full episode at thermofisher.com/absolutegeneius.

What Are PCR Inhibitors, and Why Do They Matter?

How do PCR inhibitors impact molecular workflows?

PCR inhibitors are substances co-extracted with DNA or RNA that interfere with polymerase activity, amplification efficiency, or fluorescence detection. They are especially common in complex matrices like wastewater, soil, and viral vector preparations.

Sample preparation is often the first line of defense, but it doesn’t always solve the problem.

Can DNA extraction introduce bias?

In Season 1, Episode 5, Ray Ketchum, PhD discussed a lesser-known issue: DNA extraction bias in complex microbial samples.

How can DNA extraction bias affect quantification results?

Ray Ketchum, PhD explains:

“We haven’t actually done the real time PCR versus the digital PCR comparison to see if there’s, there’s a difference there. I don’t suspect that there is simply because of the way the DNA is extracted. Most of those inhibitors should be removed. But there is another issue that we have run into recently, and I think it’s something that the industry as a whole is starting to notice a little bit more, and that is that, you know, when you take this complex collection of bacteria and you’re doing a consortium on them, whether it’s from a gut, human gut microbiome, the soil microbiome, or whatever, there has been this assumption that your DNA extraction is extracting the DNA from all of the bacteria equally well. And that’s simply not the case. In our case, what we found is that a lot of our bacteria are spore forming. And if they’ve formed spores, we just have a heck of a time really getting the DNA out representative of what’s actually in the, in the product. It turns out that we’ve been way under counting what our product actually has. So those are some of the, some of the issues that we run into.”

This highlights two key challenges in PCR workflows:

• Inhibitors may not be fully removed.
• Extraction inefficiencies can distort true biological representation.

Both issues directly impact accurate quantification.

Why Is Digital PCR A Resilient Method?

Across multiple seasons of Absolute Gene-ius, scientists consistently report higher confidence in digital PCR results when working with inhibitor-rich samples.

What happens in wastewater surveillance?

Wastewater is notoriously complex, containing organic matter, chemicals, and microbial debris that can interfere with qPCR efficiency.

Why did dPCR outperform qPCR in wastewater samples?

Sarah Philo, PhD shares:

“We tested for some different antimicrobial resistance genes with qPCR and dPCR. And pretty much all of them had a higher quantification with dPCR than with qPCR, which makes sense, at least, knowing all of the inhibitors in wastewater and environmental samples tend to make qPCR a little bit less efficient. I will say that the gene copies that we detected in digital PCR were higher than what we detected with qPCR. So this is a big problem with wastewater. It’s just like when you extract everything, a lot of times, the inhibitors are also still present. Just because there’s a lot of things in wastewater that can be kind of hard to clean up. It’s pretty well established that like PCR and qPCR do have some effects from those inhibitors, but with digital PCR, that tends to be less of an issue.” In wastewater surveillance and antimicrobial resistance monitoring, this difference can significantly affect data interpretation and public health decisions.

What about environmental water samples with cyanobacteria?

Environmental researchers frequently encounter inhibition from sediment and algal blooms.

How does digital PCR help with environmental PCR inhibition?

Patrick Hanington, PhD explains:

“We have a lot of experience using qPCR, quantitative polymerase chain reaction. And it was a just a few years ago now that we, we realized, you know, that some of the limitations of using qPCR in an environmental context, a lot of them have been addressed by digital PCR. The big one that we often struggle with is PCR inhibitors in a sample. Because we’re often working with either water samples. And I mean, you guys probably haven’t been to Alberta before, but the lakes here are pretty gunky. I don’t want to, like, I don’t want to bash them too badly. We have cyanobacterial blooms, like blue green algae blooms in every one of our central Alberta lakes. We’re always wrestling with PCR inhibitors, cyanobacteria. And you know, we can do cleanup procedures of the DNA. When we do the DNA extraction, we can try to clean that sample up a little bit. And often those work pretty well to get rid of inhibitors. But it doesn’t take much to impact the qPCR reaction and digital PCR, one of the big advantages from our perspective, anyways, is that it does a much better job of minimizing the impact of inhibitors on your reaction. That is the number one big advantage for us in the environmental space I think.”

For researchers working in environmental microbiology, minimizing inhibitor impact is critical to generating reliable quantitative data.

What makes dPCR a method more resilient to inhibitors than other PCR techniques?

At the technical level, the difference lies in how quantification is achieved.

Why are Ct shifts in qPCR problematic when inhibitors are present?

Dave Bauer, PhD breaks it down:

“There’s a handful of, kind of the bullet points I like to think of, as where it’s valuable, and that’s one of the key ones. Is if your samples have inhibitors, if they’re dirtier samples, that might compromise the PCR enzymes for real time PCR, you’re dependent on the efficiency of that reaction from start all the way until the signal crosses your Ct threshold. Any changes to that efficiency down that pathway is going to change your answer, change the concentration. However, with digital PCR, because it’s that binary, ‘do we have signal or not?’ I don’t care if you know, if you were seeing an amp curve in your individual mini reaction, you might see it super sluggishly growing really poor efficiency. That’s fine, as long as by the end of cycling, it gets above the cloud of the background noise that still counted as a positive either way. And so that gives you a lot of robustness against inhibitors. And the other value it adds is multiplexing, because a lot of times with PCR, with real time PCR, if you’re multiplexing, you might compromise the efficiency of the different primer and probe assays in there as you mix more and more together. So it’s hard to make a four-plex quantitative assay with real time PCR, but with digital PCR, it’s so much easier to have multiplex assays, multiple targets with different color dyes, all in the same reaction, because we don’t care about the efficiency.” Because digital PCR relies on endpoint, binary detection rather than amplification efficiency and standard curves, it is inherently less sensitive to partial inhibition.

How do inhibitors affect gene therapy and viral vector workflows?

In AAV production and viral vector manufacturing, inhibitors can originate from buffers, proteins, and complex production matrices.

What advantages does dPCR have in gene therapy workflows?

Kimberly Gomez explains:

“With qPCR, you would usually run a standard curve. You would make a dilution series and run that alongside your sample of unknown concentration and derive your concentration from that standard curve. Big issue with that is sometimes your standard curve could be made from reference material, so a different AAV. Or it could be made from a plasmid. So a lot of the preparation and making that standard curve can really affect the concentration that you get, that you derive from that standard curve. Another thing to consider is that with qPCR, it’s not as robust against inhibitors. We see with dPCR that we have a lot more robustness with different matrices. So that’s a big advantage, especially when you’re pulling your sample from different points of the, from production of the virus.”

Min Jin Kim, PhD adds:

“So basically the summary would be like for qPCR, although it is like, very commonly used, and everybody nowadays in our field at least knows how to use a qPCR. But there are limitations on requiring a standard curve like Kim mentioned, which may affect and impact the actual results, accuracy and precision. Another one is the inhibitory effects that is more prevalent in qPCR than digital PCR, just because it’s in a more bulk sample prep situation. In that case, sometimes for AAV applications, you would pull samples from different stages of the production and which would include different proteins, different buffers, which have different inhibitory effects. In that case, qPCR would be a little bit more limited into neglecting or mitigating that effect, as opposed to digital PCR. And also for precision wise you, it is recommended for qPCR to do at least a triplicate of your sample which increases the sample volume. Digital PCR, especially our Absolute Q, we do have lower sample volume input as well as almost no dead volume, which helps preserve your samples. On top of that, since it is an absolute quantification, it technically, in theory, does not require any replicates to be run, so you could run your one sample in one array. Another advantage is that there are some other analyses that you could do on digital PCR that you can’t on qPCR, but it’s about the molecular integrity of the gene of interest that is being delivered to the subject.”

The Takeaway: When Quantification Matters, Minimize Inhibition Risk

From wastewater surveillance to environmental microbiology and viral vector manufacturing, PCR inhibitors are pervasive. Even with optimized sample preparation, residual inhibition and extraction bias can distort results by shifting Ct values or affecting efficiency.

Digital PCR can be a great method to use to help mitigate some of these biases.

When accurate quantification is mission-critical, selecting technologies that minimize the impact of inhibitors can make a measurable difference.

To hear the full discussion and explore more expert insights on PCR, dPCR, and molecular workflows, listen to this episode of Absolute Gene-ius: Science Snapshot at thermofisher.com/absolutegeneius, and be sure to explore additional episodes in the series.

To learn more about digital PCR and how it could add value to your research, visit thermofisher.com/dPCR.