Optimized Cannabis Microbial Testing: Combined Use of Extraction Methods and Pathogen Detection Tests Using Quantitative Polymerase Chain Reaction

August 22, 2019
Volume: 
2
Issue: 
4
Figure 1
Figure 1 (click to enlarge): Real-time quantitative PCR (qPCR) for one cycle of qPCR using a multiplex system of primers to detect potential pathogens within the plant material sample.
Figure 2
Figure 2 (click to enlarge): qPCR amplification plots for high versus low target DNA levels. Fluorescence across 40 cycles of qPCR occurs earlier for higher titer samples (blue line) compared to low titer samples (yellow). The cycle at which the signal crosses a pre-established threshold (red line) is the quantitative cycle (Cq).
Abstract / Synopsis: 

With the introduction of legal cannabis available for sale in the U.S., providing safe, high-quality products defines the industry standard. As part of compliance testing, each state has different requirements for detection of microbial species in cannabis products. An ideal test is one that can be performed quickly with small amounts of cannabis product, is specific for the microbes required, can differentiate between live and dead microbes, and can be automated for high sample throughput. Medicinal Genomics developed a novel quantitative polymerase chain reaction (qPCR)-based test, in a 96-well plate format, that relies on fluorescence to detect amplified deoxyribonucleic acid (DNA). Fluorescence detection indicates the presence of microbial contamination on cannabis. This quantitative PCR method has been adapted for multiple matrices such as flower, leaf, concentrates, and an array of non-flower marijuana infused products (MIP). This review introduces the qPCR assay and compares its performance to culture-based methods.

Recent legislation legalizing the medicinal or recreational use of cannabis or cannabinoid products in the United States and Canada has led to mandated testing of cannabis products for certain microbes. The presence of bacteria and fungi in cannabis poses a potential threat if those microbes include pathogenic species. The current industry standard for detecting harmful microbes on cannabis flower is culture-based testing. However, most culture-based methods were not developed for use in the presence of a complex cannabis matrix. Culture-based yeast and mold tests have shown false positives in cannabis matrices due to off-target bacterial species growth. Most alarming, toxic Aspergillus spp. grows poorly in culture mediums and is severely underreported by current culture-based platforms (1). This review highlights the shortcomings of culture-based methods that have been borrowed from the food industry, and the advantages of using quantitative polymerase chain reaction (qPCR) detection when applied to cannabis matrix.

What is qPCR?

PCR amplifies a segment of deoxyribonucleic acid (DNA) to create exact copies in an abundance that allows for further analyses. Kerry Mullis invented PCR in 1988, for which he and his colleagues won the Nobel Prize for chemistry in 1993. PCR is extremely sensitive, requiring only a few DNA molecules in a single reaction for amplification across several orders of magnitude of detection. Of importance, qPCR analyses are the design of the primers and probes—the short DNA sequences that determine what part of the target DNA will be amplified. Primers are designed to bind adjacent to the target sequence and are specific to the target DNA such that a single DNA base difference can determine whether binding does or does not occur. This specificity is what makes qPCR a powerful tool for the detection of pathogens in cannabis. This reduces the frequency of false positives in pathogen detection, a frequent problem with current culture-based cannabis testing methods.

qPCR takes advantage of the linearity of DNA amplification to quantify unique sequences in a DNA sample. Using a fluorescent probe reporter, it is possible to measure the amplification of a targeted DNA molecule occurring in real time (Figure 1). (See upper right for Figure 1, click to enlarge.) The real-time increase in fluorescent signal translates into quantification. In brief, if a targeted DNA molecule is present, fluorescence will increase until the signal exceeds a predetermined value. When more DNA is present in the sample, the threshold is exceeded earlier in the application process compared to samples containing less DNA. The quantitative cycle number (Cq) at which the signal curve exceeds the threshold is used to quantify the amount of DNA present in the sample when compared to a known DNA reference standard. This result is then converted to common microbial terms such as colony forming unit (CFU).

Agilent and Medicinal Genomics have partnered to provide sensitive and specific assays for the identification and quantification of microbial species regulated by agencies in the United States and Canada.

References: 
  1. C. De Bekker, G.J.  van Veluw, A. Vinck, L.A Wiebenga, and H.A. Wosten, Applied and Environmental Microbiology 77(4),1263–7 (2011). PubMed PMID: 21169437. PubMed Central PMCID: 3067247.
  2. K.J. McKernan, J. Spangler, and L. Zhang et. al., F1000 Research. 4(1422) https://doi.org/10.12688/f1000research.7507.2
  3. Medicinal Genomics, “PathogINDICAtor qPCR microbial detection Assay on the AriaMX Real-Time PCR System optional decontamination step,” Document EUD-00021 1.4.  (2017). (Medicinal Genomics Corporation).
  4. K.J. McKernan, et. al., PLoS One 9(5)e, 96492 (2014).
  5. K.J. McKernan, J. Spangler, and Y. Helbert et. al.,“Metagenomic analysis of medicinal Cannabis samples; pathogenic bacteria, toxigenic fungi, and beneficial microbes grow in culture-based yeast and mold tests,” F1000Res. 5(2471) https://doi.org/10.12688/f1000research.7507.2.
  6. S.D. Leppanen and H. Ebling, “Optimized Cannabis Microbial Testing: Combined Use of Medicinal Genomics Extraction Methods with the AriaMx qPCR Instrument,” Application Note 5994-0430EN, Agilent Technologies (2018).

Scott Leppanen is the Senior Field Applications Scientist and Anthony Macherone is the Senior Scientist for Agilent Technologies, Inc.  Heather Ebling is the Senior Applications and Support Manager for Medicinal Genomics. Direct correspondence to: [email protected] com and h[email protected].

How to Cite This Article

S.D. Leppanen, H. Ebling, and A. Macherone, Cannabis Science and Technology 2(4), 69-76 (2019).

Editor's Note:

The print version of this article mistakenly left off Figure 7a and Table IV. Those elements are included in the correct version found here.