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

August 22, 2019

This review introduces a quantitative polymerase chain reaction (qPCR) assay and compares its performance to culture-based methods.

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.

Using the Agilent AriaMX Real-Time PCR system, Medicinal Genomics PathoSEEK series of assays detect pathogenic organisms, and has demonstrated robustness, accuracy, and precision for microbial screening in various cannabis flower and cannabinoid product matrices.

To this end, DNA must first be extracted from cannabis plant and microbial cells. To simplify this process, Medicinal Genomics developed SenSATIVAx-a magnetic bead-based DNA extraction kit.

In brief, cannabis flower, leaf, or marijuana-infused product (MIP) is homogenized and, if necessary, allowed to culture in a growth medium, to generate more potential pathogens present on the cannabis product. This culture medium is then subjected to a DNA extraction followed by an optional decontamination step, which rids the sample of any previously amplified DNA.

The extracted and decontaminated DNA sample is then used as a template for the PathoSEEK assay where detection of many of these pathogens is done in multiplex: two to four microbes are targeted in a single PCR reaction. The presence of cannabis DNA and microbial contamination is based on the sample amplification curve achieving an assay-specific fluorescent value within a predetermined number of PCR cycles. Additionally, positive and negative controls show evidence and absence of amplification, respectively. Figure 3 illustrates the assay workflow. (See upper right for Figure 3, click to enlarge.)

Results and Discussion

An Empirical Comparison of PathoSEEK and Culture-Based Methods

Fifteen medicinal cannabis samples were analyzed using PathoSEEK and two commercially available culture-based methods. To enumerate and differentiate bacteria and fungi present before and after growth on culture-based media, all samples were further subjected to next-generation sequencing (NGS) and metagenomic analyses (MA). NGS determines the precise order of nucleotides in a total DNA strand, and MA analyzes genomes collected in environmental samples. These tools respectfully sequence entire genomes of species’, and profile the diversity of genes in a given sample. Figure 4 illustrates MA data collected directly from plant material before and after culture on 3M petrifilm and culture-based platforms. (See upper right for Figure 4, click to enlarge.)

The results demonstrate substantial shifts in bacterial and fungal growth after culturing on the 3M petrifilm and culture-based platforms. Thus, the final composition of microbes after culturing is markedly different from the starting sample. Most concerning is the frequent identification of bacterial species in systems designed for the exclusive quantification of yeast and mold, as quantified by elevated total aerobic count (TAC) Cq values after culture in the total yeast and mold (TYM) medium. The presence of bacterial colonies on TYM growth plates or cartridges may falsely increase the rejection rate of cannabis samples for fungal contamination. These observations call into question the specificity claims of these platforms.

Issues with Aspergillus spp.

Aspergillus spp. grow poorly in culture-based media. One of the common issues is that Aspergillus spp.  clumps over generational growth, so a homogenous spread of the cells in the media is nearly impossible. When Aspergillus niger is plated, clumped conidia cells form heterogeneous macro-colonies which creates significant issues with quantitation (Figure 5). (See upper right for Figure 5, click to enlarge.) What looks like one large colony is hundreds of colonies that are not countable. Additionally, the clumping nature of Aspergillus spp. spores in media makes it difficult to accurately pipette samples. DNA extraction processes performed before running qPCR assays have the benefit of lysis and DNA purification steps that “de-clump” and break open the cells or spores, providing better sampling techniques and therefore more accurate and reliable results.

Marijuana Infused Products Interference and Impact on Results

Marijuana infused products (MIPs) are a very diverse class of matrices that behave very differently than cannabis flowers. Gummy bears, chocolates, oils, and tinctures all present different challenges to culture-based techniques as the sugars and carbohydrates can radically alter the carbon sources available for growth. To assess the impact of MIPs on colony-forming units per gram of sample (CFU/g) enumeration, we spiked in live E. coli cells into various MIPs to measure the qPCR signal. In many of the spiked MIP samples, E. coli failed to grow compared to tryptic soy broth (TSB) controls.

This implies the MIPs are interfering with the reporter assay on the films or that the MIPs are antiseptic in nature.

Many MIPs use citric acid as a flavoring ingredient which may interfere with 3M reporter chemistry. In contrast the qPCR signal was constant, implying there is microbial contamination present on the films, but the colony formation or reporting is inhibited.

Figure 6 compares plating E. coli with and without MIP on 3M coliform films. (See upper right for Figure 6, click to enlarge.) Growth of E. coli CFU was severely hindered in presence of oil or candy.

Method Accuracy

To show that the SenSATIVAx DNA extraction method is efficient in different matrices, DNA was spiked into various MIPs as shown in Table I, and at different numbers of DNA copies into chocolate (Table II). (See upper right for Tables I and II, click to enlarge.) The SenSATIVAx DNA extraction kit successfully captures the varying levels of DNA, and our PathoSEEK detection assay can successfully detect that range of DNA. Table III demonstrates that SenSATIVAx DNA extraction can successfully lyse the cells of the microbes that may be present on cannabis for a  variety of organisms spiked onto cannabis flower samples. (See upper right for Table III, click to enlarge.)

Specificity

More than 60 species in total were used to verify the specificity of the PathoSEEK Microbial Safety Testing Solution, with a minimum of 6 to 10 and a maximum of 45 for each detection assay. The data shows 100% concordance with the current list of species tested. A subset of the data is shown in Table IV. (See upper right for Table IV, click to enlarge.)

Linearity

Linearity shows the relationship between a group of known dilutions and resulting Cq. To test the linearity of our PathoSEEK assays, we conducted 12, two-fold serial dilutions of a known DNA concentration in triplicate. Figures 7a and 7b show the results of the total aerobic count (TAC) assay and the qPCR efficiency (E) of the assays as inferred by the linear coefficient of determination (R2) which is a measure of how well a dependent variable fits a linear model. (See upper right for Figure 7, click to enlarge.)

Limit of Detection

Using PathoSEEK to determine the presence or absence of E. coli, STEC, Salmonella, and Aspergillus spp. a limit of detection (LOD) was determined by performing triplicate analyses of 12, two-fold serial dilutions starting at two copies through 5000 copies. In each case, a LOD of 10 copies were determined.

Conversion of Cq to CFU Equations

Correlation of qPCR results with plating live species will result in an equation that enables conversion of Cq/g to CFU/g as given in equation 1:
CFU/g = 10 * [(42.185 – Cq Value)/3.691]

Molecular methods often leverage amplification of ribosomal DNA, internal transcribed spacers (ITS) regions (3,6). As a result, these PCR products can detect unculturable organisms and organisms that clump and distort CFU/g enumeration such as Aspergillus species (Figure 9).  (See upper right for Figure 9, click to enlarge.) Aspergillus spp. demonstrate logarithmically slower growth at room temperature than most other yeast. You can see in this comparison to the qPCR PathoSEEK assay results, the CFU plated and the growth on plating media does not appear linear and significantly underestimates Aspergillus spp. growth. However, the plated CFU does compare accurately to the qPCR quantitative cycle (Cq) result for other species.

Summary

Accurate methods are required to assess exposure risk across diverse cannabis samples and matrices. Traditional testing methods include culture on nonspecific media, such that many microbial organisms can grow, resulting in false positive results. Further, certain organisms do not grow on media, and their apparent culture and growth are not representative of true organism density, thus causing under-reporting or false negatives. qPCR is being repurposed for its ability to detect small amounts of specific pathogenic microbial organisms potentially present in these myriad sample presentations. To meet this new demand, Medicinal Genomics (MGC) has partnered with Agilent to employ their PCR technology on the Agilent qPCR system. This chemistry includes the SenSATIVAx DNA purification kit and the PathoSEEK qPCR reagents, which include the appropriate positive and negative controls.

References:

  1. C. De Bekker, G.J.  van Veluw, A. Vinck, L.A Wiebenga, and H.A. Wosten, Applied and Environmental Microbiology77(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 One9(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: scott.leppanen@agilent com and heather.ebling@medicinalgenomics.

How to Cite This Article

S.D. Leppanen, H. Ebling, and A. Macherone, Cannabis Science and Technology2(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.

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