Gene Therapy and Mycoplasma: Using Droplet Digital PCR to Precisely Detect Contaminants and Protect Patients

• Bio-Rad

Gene therapies have the potential to bring about the greatest change in medicine since the advent of antibiotics. In 2017, the US Food and Drug Administration approved a gene therapy for the first time, an adeno-associated vector (AAV)-mediated gene replacement therapy that returns sight to those affected by biallelic RPE65 mutation-associated retinal dystrophy.¹ In 2020, gene therapy enabled the development of multiple SARS-CoV-2 vaccines in less than a year.² According to Clinicaltrials.gov, nearly 450 gene therapies are under investigation as treatments for diseases ranging from bleeding disorders such as hemophilia to neurodegenerative disorders such as spinal muscular atrophy.³ The FDA predicts that it will approve 10 to 20 new cell gene therapies by 2025; meanwhile, researchers at the Massachusetts Institute of Technology estimate that 350,000 patients will have been treated by 20-60 cell and gene therapy products by 2030.^4,5

Because of their versatility, AAVs will likely serve as the vehicle for most gene therapies in the future. Despite their potential, however, developing AAV-mediated gene therapies is complex. Unlike small molecule drugs, which are developed using chemical techniques that yield relatively predictable results, AAV-mediated gene therapies are “grown” in living cells, which makes the process of extracting and purifying a safe and effective therapy more complicated. During the purification process, for example, components from the host cells - such as DNA, proteins, bacterial cells and other viruses - can make their way to the final batch. These contaminants can interfere with the effectiveness of the therapy and pose a health risk to patients. Some of these contaminants, such as DNA containing oncogenes, may pose a cancer risk, while others, such as bacteria of the genus Mycoplasma, can cause deadly infections.

Mycoplasma: A Pervasive and Challenging Contaminant

Mycoplasma is a common cell culture contaminant, making it hard to avoid in gene therapy development. Long a source of concern for cell biologists, it is estimated that approximately 30% of cell lines worldwide are contaminated with a Mycoplasma species.⁶ These bacteria impact all areas of cell hysiology and often affect research results.⁷

Mycoplasma is receiving renewed attention because of its potential to contaminate therapeutics. Given the prevalence of Mycoplasmas in laboratories, it is likely that they are present in the cells used to grow AAVs, and in turn, they are likely to turn up in AAV-based therapeutics. It is especially important to detect and screen out these contaminants in therapeutic products because some species, especially M. pneumoniae, can cause respiratory infections in humans. In fact, M. pneumoniae causes an estimated 2 million cases of bacterial pneumonia annually, resulting in about 100,000 hospitalizations of adults in the United States.⁸ Therefore, it is critical to purify vectors as much as possible and then test them for the presence of Mycoplasmas before they enter patients.

Unfortunately, these bacterial species are challenging to detect and remove from cell cultures. Mycoplasma bacteria are gram negative, making them resistant to the beta-lactam-based antibiotics that are commonly used in maintaining cell lines. Furthermore, they pass through filters and cannot be seen using standard light microscopy because they don’t have a cell wall and are very small (2-3 μm).

Traditional Mycoplasma detection methods - including monitoring for colony growth with broth or agar, staining or labeling nucleic acids, or testing for gene products - can take up to 28 days to deliver results.^9,10

More recently, scientists have turned to qPCR, which delivers results in one day. However, qPCR is unable to directly quantify Mycoplasma levels: It is performed by amplifying the target genetic sequence and measuring the number of cycles it takes to reach a certain threshold, and this result is then compared to a standard curve, which yields a relative rather than quantitative answer.

Another limitation of qPCR is its inability to distinguish between Mycoplasma DNA from living cells versus from Mycoplasma DNA floating freely in solution.¹¹ To make this distinction, researchers must measure the ratio of genome copies (GCs) and colony-forming units (CFUs). Unfortunately, the GC:CFU ratio varies between cultures because of variable growth rates and the specific culture conditions. Therefore, it is necessary to obtain an absolute count of genome copies, which qPCR cannot do. In addition, certain SYBR based qPCR tests often produce false positives, which can lead to an overestimation of Mycoplasma concentration.¹²

Advantages of Using Droplet Digital PCR for Mycoplasma Detection

One approach that is more ideally suited for quantifying Mycoplasmas is Droplet Digital PCR (ddPCR) technology. ddPCR technology directly quantifies target nucleic acids - including Mycoplasma DNA.

This method is based on partitioning (Figure 1): After a researcher loads a 10 μL sample of DNA, it gets divided into approximately 20,000 uniform 1-nL droplets, each containing one or a few nucleic acid strands. The nucleic acids in each droplet are amplified using a probe targeting a genetic sequence that is unique to Mycoplasma species. If a droplet contains the target sequence, the probe will be cleaved as the DNA amplifies, and a reporter dye will emit a fluorescent signal. In contrast, droplets that do not contain the target strand will not emit a strong signal. Unlike qPCR, ddPCR technology uses probe-based chemistry and utilizes three primers instead of two, reducing the chance of non-specific DNA amplification.

Subscribe to our e-Newsletters
Stay up to date with the latest news, articles, and events. Plus, get special offers
from Pharmaceutical Outsourcing – all delivered right to your inbox! Sign up now!

The droplets are then streamed in series through a reader that counts fluorescent versus non-fluorescent droplets. Using Poisson statistics, software can calculate the concentration of Mycoplasma DNA in the sample and thereby aid a manufacturer in determining the presence and level of Mycoplasma contamination in their batch.

ddPCR is already used to detect microbial contamination in other areas. For example, the technology is more precise than qPCR at detecting Spiroplasma citri, a pathogenic bacterium found in citrus fruits.¹³ In wastewater, it identifies norovirus and poliovirus before patients present symptoms.¹⁴ It can detect E. coli contamination in food, and it can also detect and quantify SARS-CoV-2 in both wastewater and nasopharyngeal samples.^15,16

ddPCR has also been shown to be more sensitive and specific than qPCR in the detection of several bacterial species that causes illness in humans. These include:

1. L. monocytogenes, a gram-positive bacterium that causes listeriosis and that is pathogenic at concentrations below the detection limit of most assays
2. F. tularensis, a gram-negative bacterium that causes tularemia and is lethal at small doses
3. Mycobacterium avium subsp. Paratuberculosis, which causes disease in ruminant animals

In one study, researchers directly compared the ability of qPCR and ddPCR to accurately quantify these three species in suspension and found that qPCR overestimated the quantity of all three by at least two-fold.¹⁷ In a study looking at the concentration of Mycobacterium tuberculosis in the blood of rhesus monkeys, researchers using a ddPCR assay were able to detect the bacterial species only three weeks after infection, two weeks before it became detectable via qPCR.¹⁸

Recently, researchers examined the ability of ddPCR technology to detect several Mycoplasma species. In the study, they tested samples containing three species that are representative of the range of Mycoplasma found in nature, A. laidlawii, M. pneumoniae, and M. hyorhinis, and found the limit of detection of A. laidlawii was 4.19GC/well, M. pneumoniae was 6.29 GC/well, and M. hyorhinis was 5.63GC/well.¹⁹

The same group wanted to ensure that the technology was not detecting other species of bacteria, so they tested assay crossreactivity. They tested samples containing the three representative Mycoplasma species and three control species, C. sporogenes, L. acidophilus, S. bovis, and confirmed that ddPCR was only detecting Mycoplasma.¹⁹

In a side-by-side comparison of qPCR and ddPCR, ddPCR was able to detect A. laidlawii standards at 1 CFU/ml, whereas qPCR yielded a negative result at this concentration. (Figure 2).¹¹

Conclusion

Rapid and sensitive assays that can detect contaminants like Mycoplasma will become critical as gene therapies become more widely adopted. These more sensitive quality control tools will ensure that gene therapy developers can more easily deliver safe products to their patients. The creation of a sensitive Mycoplasma detection assay is just one step in measuring a products’ safety, but it is indicative of the industry’s larger push to optimize quality control during gene therapy development. With the proper tools, techniques, and policies in place, the complicated generation of gene therapies should evolve into a highly standardized and simplified process like those for biologics and small molecule drugs did decades before.

References

1. Food and Drug Administration. FDA approves novel gene therapy to treat patients with a rare form of inherited vision loss. https://www.fda.gov/news-events/pressannouncements/fda-approves-novel-gene-therapy-treat-patients-rare-form-inheritedvision-loss. Accessed February 3, 2020.
2. American Society of Cell + Gene Therapy. COVID-19 Vaccine Candidates Show Gene Therapy is a Viable Strategy. https://www.asgct.org/research/news/november-2020/covid-19-moderna-nih-vaccine. Accessed February 9, 2020.
3. U.S. National Library of Medicine Search Engine, ClinicalTrials.gov. https://clinicaltrials.gov/ct2/results?term=%22gene+therapy%22&Search=Apply&recrs=b&recrs=a&recrs=f&recrs=d&age_v=&gndr=&type=&rslt=. Accessed February 3, 2020.
4. Food and Drug Administration. Statement from FDA Commissioner Scott Gottlieb, M.D. and Peter Marks, M.D., Ph.D., Director of the Center for Biologics Evaluation and Research on new policies to advance development of safe and effective cell and gene therapies. https://www.fda.gov/news-events/press-announcements/statement-fda-commissionerscott-gottlieb-md-and-peter-marks-md-phd-director-center-biologics. Accessed February 3, 2020
5. Quinn C. et al. Estimating the clinical pipeline of cell and gene therapies and their potential economic impact on the US healthcare system. Value Health, 22(6):621-626, 2019.
6. Bolske G. Survey of mycoplasma infections in cell cultures and a comparison of detection methods. Zentralbl Bakteriol Mikrobiol Hyg A, 269(3):331–340, 1988.
7. Nikfarjam L, Farzaneh P. Prevention and detection of Mycoplasma contamination in cell culture. Cell J 13:203–212, 2012.
8. Waites K. et al. Mycoplasma pneumoniae from the respiratory tract and beyond. Clin Microbiol Rev, 30 (3), 747–809, 2017.
9. Drexler HG, Uphoff CC. Mycoplasma contamination of cell cultures: Incidence, sources, effects, detection, elimination, and prevention. Cytotechnolog, 39(2):75–90, 2002.
10. Armstrong SE, et al. The scope of Mycoplasma detection within the biopharmaceutical industry. Biologicals, 38(2):211–213, 2010.
11. Wu M, et al. Poster: Transitioning from qPCR to ddPCR for Mycoplasma Detection.
12. Gattinger, et al. Detection of Mycoplasma (Eperythrozoon) suis by real-time PCR. Vet Med Australia, 95:22-27, 2008.
13. Maheshwari Y et al. Application of droplet digital PCR for quantitative detection of Spiroplasma citri in comparison with real time PCR. PLoS ONE, 12:e0184751, 2017.
14. Tang A, et al. Detection of Novel Coronavirus by RT-PCR in Stool Specimen from Asymptomatic Child, China. Emer Inf Dis, 26(6):1337-1339, 2020.
15. Gonzalez R et al. COVID-19 surveillance in Southeastern Virginia using wastewater-based epidemiology. Water Res, 186(1):e11629, 2020.
16. Alteri, C et al. Detection and quantification of SARS-CoV-2 by droplet digital PCR in realtime PCR negative nasopharyngeal swabs from suspected COVID-19 patients. PLOS ONE, 15(9):e0236311, 2020.
17. Ricchi M et al. Comparison among the quantification of bacterial pathogens by qPCR, dPCR, and culture methods. Front Microbiol, 8:1174, 2017.
18. Song N et al. Detection of circulating Mycobacterium tuberculosis-specific DNA by droplet digital PCR for vaccine evaluation in challenged monkeys and TB diagnosis Emerg Microbes Infect. 7(1):78, 2018.
19. Scherr M et al. Vericheck ddPCR Mycoplasma Detection Kit: Probe-based Mycoplasma Detection to Reduce False-Positives Results. https://www.bio-rad.com/webroot/web/pdf/lsr/literature/Mycoplasma_Poster.pdf. Accessed February 3, 2021.

Author Biography

Mark White is the Associate Director of Biopharma Product Marketing at Bio- Rad. He has played a key role in the development of multiple core technology capabilities, assays and software alongside a multidisciplinary team of biologists and engineers at Bio-Rad and previously at Berkeley Lights Inc. Mark obtained his Ph.D. in Biomedical Sciences at the University of California, San Francisco.