Cannabis microbiome sequencing reveals several mycotoxic fungi native to dispensary grade Cannabis flowers

Introduction

Our knowledge of the natural microbiome of field-grown Cannabis in terms of rhizosphere bacteria, and endophytic fungi is limited to just a few focused studies^1–3. Very little is known about the potential for bacterial and fungal contamination on medicinal Cannabis. Nevertheless, many states in the U.S. are now crafting regulations for detection of microbial contamination on Cannabis in the absence of any comprehensive survey of actual samples. A few of these regulations are inducing growers to “heat kill” or pasteurize Cannabis flowers to lower microbial content. While this seems a harmless suggestion, we must remain aware of how these drying techniques may create false negatives in culture-based safety tests used to monitor colony-forming units (CFU). Even though pasteurization may be effective at sterilizing some of the microbial content, it does not eliminate various pathogenic toxins or spores. Aspergillus spores and mycotoxins are known to resist pasteurization^4,5. Similar thermal resistance has been reported for E. coli produced Shiga toxin⁶. While pasteurization may reduce CFU’s used in petri-dish or plating based safety tests, it does not reduce the microbial toxins, spores or DNA encoding these toxins.

Monitoring for mycotoxic fungi in cannabis preparations has been recommended as part of routine safety testing by the Cannabis Safety Institute. A major driver for this recommendation has been numerous reported cases of serious or fatal pulmonary Aspergillosis associated with marijuana smoking in immunocompromised patients^7–9. The major cannabinoids have been shown to be potent inhibitors of several cytochrome P450 enzymes at therapeutic concentrations, including 1A1, 1A2, 1B1 2B6, 2C19, 2D6, 3A4 and 3A5¹⁰. Some of these enzymes have been implicated in the metabolism of the fungal toxins aflatoxin and ochratoxin^11–13. This raises questions about potential interactions and appropriate safety tolerances for mycotoxins in patients being treated with cannabinoid therapeutics. In addition, some Fusarium species that produce toxins have proven to be difficult to selectively culture with tailored media^14–16. This is a common problem associated with culture-based systems as carbon sources are not exclusive to certain microbes and only 1% of microbial species are believed to be culturable¹⁷.

While the risks of mycotoxic fungal contamination have been well studied in the food markets, the presence of the fungal populations present on Cannabis flowers has never been surveyed with next generation sequencing techniques^18–23. With the publication of the Cannabis genome^24,25 and many other pathogenic microbial genomes, quantitative PCR assays have been developed that can accurately quantify fungal DNA present in Cannabis samples²⁶. Here, we analyze the yeast and mold species present in 10 real world, dispensary-derived Cannabis samples by quantitative PCR and sequencing, and demonstrate the presence of several mycotoxin producing fungal strains that are not detected by widely used culture-based assays.

Methods

Results

We purified DNA from Cannabis samples obtained from two different geographic regions (Amsterdam and Massachusetts) several years apart (2011 and 2015). The majority of samples purified and screened with ITS qPCR were negative for amplification signal implying reagents clean of fungal contamination. Six of the 17 dispensary-derived Cannabis samples tested positive for yeast and mold in the TYM qPCR assay. These results were compared with the results derived from three commercially available culture-based detection systems for each of the 17 samples (3M Petrifilm^TM 3M Microbiology, St. Paul, MN, USA; SimPlates^TM Biocontrol Systems, Bellevue, WA, USA; BioLumix^TM Neogen, Lansing MI, USA; Figure 1). Of the 6 qPCR positive samples, two tested negative in all 3 culture-based assays and four tested negative in 1 or 2 of the culture-based assays (Table 1). None of the qPCR negative samples tested positive in any of the culture-based assays. Each of the 6 discordant samples was subjected to ITS sequencing to precisely identify the collection of microbes present. Four additional samples from a different geographic origin (Amsterdam) were also subjected to ITS sequencing, for a total of 10 Cannabis samples.

Figure 1. Comparison of 4 different microbial detection technologies.

Figure 1A. qPCR signal from TYM (red line) test run concurrently (multiplexed) with a plant internal control marker (green line). This marker targets a conserved region in the Cannabis genome and should show up in every assay (upper left). SimPlates count the number of discolored wells (purple to pink) as a proxy for CFU/gram. Only total aerobic show growth (upper right). Petrifilm only demonstrate colonies on total aerobic platings (lower left). Biolumix demonstrate no signal across all 4 tests (lower right). Figure 1B. Sample KD8 fails to culture any total yeast and mold yet demonstrates significant TYM qPCR signal. Sample was graduated to ITS based next generation sequencing. Figure 1C. Sample Liberty Haze was tested with 3 culture based methods and compared to qPCR. Sample was graduated to ITS based next generation sequencing.

Each discordant sample presented with an array of microbial species, as shown in Figure 2. No sample presented with a single dominant species, and each sample displayed multiple species of interest. Of particular concern were the identified DNA sequences from toxin producing species: Aspergillus versicolor^32–36, Aspergillus terreus³⁷, Penicillium citrinum^38–40, Penicillium paxilli^41,42.

Figure 2. Detection of fungal species by ITS2 sequencing and MG-RAST analysis.

Histograms are provided for each of the Cannabis samples that tested negative by at least one culture based method and positive using a qPCR-based total yeast and mold test. The number of reads corresponding to each detected fungal species is indicated to the right of each bar. Species detected with less than 10 reads are not included. The overall read counts per sample are more a reflection of sample normalization for sequencing than of the absolute fungal DNA levels.

We further analyzed the ITS sequence alignments using the whole genome shotgun based microbiome classification software known as One Codex⁴³. Nine of the ten samples sequenced showed the presence of P. paxilli (Figure 3). To verify the accuracy of this ITS phylotyping, a gene involved in the paxilline toxin biosynthesis pathway of P. paxilli was amplified with PaxPss1 and PaxPss2 primers described by Saikia et al.⁴⁴. The resulting 725bp amplicon (expected size) was sequenced to confirm the presence of the P. paxilli biosynthesis gene in the Cannabis sample KD8 (Figure 4). This was successfully repeated with primers designed to target genes in the citrinin pathway of P. citrinum. There were some discrepancies between the results derived from the two software platforms (One Codex and MG-RAST). The MG-RAST analysis, using merged, paired reads correlated better with the PCR results. While One Codex predicted and confirmed KD8 as having the highest P. paxilli content, the One Codex platform is optimized for whole genome shotgun data and may not be able to differentiate the 18S sequence differences (391/412 aligned bases) between these two species with a K-mer based approach.

Figure 3. One Codex classification of ITS reads.

P. paxilli is the most frequently found contaminant in Cannabis flowers. P. citrinum is not in the One Codex database at this time. One Codex utilizes a fast k-mer based approach for whole genome shotgun classification and can be influenced by read trimming and database content. The reads provided to MG-RAST were trimmed and FLASH’d (paired end reads merged when overlapping) prior to classification. K-mer based approaches can significantly differ from longer word size methods and this underscores the importance of confirmatory PCR in microbiome analysis.

Figure 4. PCR of genes encoding Paxilline and Citrinin demonstrates amplification of the expected size.

Citrinum primers we designed from Genbank accession number LKUP01000753. Paxilline primers were used as described in Saikia et al. PCR products were made into shotgun libraries with Nextera and sequenced on an Illumina MiSeq with 2×75bp reads to over 10,000X coverage. Reads were mapped with CLCbio 4 to NCBI accession number HM171111.1 (A) and LKUP01000000 respectively (B). Paired reads are displayed as blue lines, green and red lines are unpaired reads. Read coverage over the amplicons are depicted in a blue histogram over the cluster while paired end read distance is measured in a red histogram over the region. Off target read mapping is limited. P. paxilli mappings are displayed on top (A) and P. citrinum mappings are displayed on bottom (B). Alignment of PCR primers to P. paxilli reference shows a 5 prime mismatch that is a result of the primers being designed to target spliced RNA according to Saikia et al.

With the confirmed presence of P. paxilli, we are curious to find out whether the toxin, paxilline, is present in the samples. Development of monoclonal antibodies to paxilline has recently been described⁴⁵, but commercial ELISA assays with sensitivity under 50ppb do not appear to be available at this time. A >50ppb multiplexed ELISA assay is available from Randox Food Diagnostics (Crumlin, UK). Detection with LC-MS/MS has also been described^46,47, however, and experiments are underway to determine whether paxilline can be identified in the background of cannabinoids and terpenes present in Cannabis samples.

Discussion

This study demonstrates detection of numerous fungal species by molecular screening of ITS2 in several dispensary-derived Cannabis samples. These included the toxigenic Penicillium species: P. paxilli, P. citrinum, P. commune, P. chrysogenum, P. corylophilum, Aspergillus species: A. terreus, A. niger, A. flavus, A. versicolor and Eurotium repens. In addition, a pathogenic species Cryptococcus liquefaciens was detected. The fungal microbiomes of the different samples differed significantly in the number and diversity of species present. Two samples contained a large diversity of species, similar to previous studies that used field-grown samples and culture-based outgrowth methods^2,3,48. Other samples contained only a few species at significant levels. This is perhaps not surprising given the prevalence of indoor culture methods using artificial growth media for medicinal Cannabis. However, we do not have any knowledge of the specific growth conditions that were used for the samples analyzed.

Three different culture-based assays failed to detect all of the positive samples and one, BioLumix^TM, detected only one out of 7 positive samples. A review of the literature suggests that Penicillium microbes can be cultured on CYA media, but some may require colder temperatures (21-24C) and 7 day growth times⁴⁹. Of the Penicillium, only P. citrinum has been previously reported to culture with 3M Petri-Film⁵⁰. It is possible the different water activity of the culture assay compared to the natural flower environment is contributing to the false negative test results.

Quantitative PCR is agnostic to water activity and can be performed in hours instead of days. The specificity and sensitivity provides important information on samples that present risks invisible to culture based systems. The drawback to qPCR is the method’s indifference to living or non-living DNA. While techniques exist to perform live-dead qPCR, the live status of the microbes is unrelated to toxin potentially produced while the microbes were alive. ELISA assays exist to screen for some toxins⁵¹. Current state-recommended ELISA’s do not detect citrinin or paxilline, the toxins produced by P. citrinum and P. paxilli, respectively. The predominance of these Penicillium species in a majority of the samples tested is interesting. Several Penicillium species are known to be endophytes on various plant species, including P. citrinum¹⁸, and this raises the question of whether they may be common Cannabis endophytes. Indeed, P. citrinum and a species identified as P. copticola (a member of the citrinun section⁵¹) have previously been identified as Cannabis endophytes, along with several Aspergillus species^2,3.

Paxilline is a tremorgenic and ataxic potassium channel blocker and has been shown to attenuate the anti-seizure properties of cannabidiol in certain mouse models^52–54. Paxilline is reported to have tremorgenic effects at nanomolar concentrations and is responsible for Ryegrass-staggers disease⁵⁵. Cannabidiol is often used at micromolar concentrations for seizure reduction and contamination with paxilline, if confirmed, would be a cause for concern. Citrinin is a mycotoxin that disrupts Ca2+ efflux in the mitochondrial permeability transition pore (mPTP)^56–63. Ryan et al. demonstrated that cannabidiol affects this pathway suggesting a similar potential cause for concern regarding CBD-citrinin interaction⁶⁴. Considering the hydrophobicity of these mycotoxins and the growing interest in the use of extracted oils from CBD-rich Cannabis strains for treatment of drug resistant epilepsy^65–70, more precise molecular screening of fungal toxins in these products might be warranted.

ITS amplification and sequencing offers a hypothesis-free testing approach that can be employed to identify a broad range of fungal species present in a given sample. Appropriate primer design can survey a broad spectrum of fungal genomes while affording rapid iteration of design. Quantitative PCR has also demonstrated single molecule sensitivity and linear dynamic range over 5 orders of magnitude offering a very sensitive approach for detection of microbial risks. Our survey of Cannabis flowers in this study was limited, however. Further studies are required to survey a broader range of samples, and to determine whether paxilline, citrinin, aflatoxin or ochratoxin can be detected at concentrations that represent a clinical risk in Cannabis samples or extracts derived from plants that test positive for the fungi known to produce those toxins.

Conclusions

Several toxigenic fungi were detected in dispensary-derived Cannabis samples using molecular amplification and sequencing techniques. These microbes were not detected using traditional culture-based platforms. These results suggest that culture based techniques borrowed from the food industry should be re-evaluated for Cannabis testing to ensure that they are capable of detecting the prevalent species detected by molecular methods with adequate sensitivity. We recommend that additional sequencing studies be performed to characterize the fungal and bacterial microbiomes of a more diverse selection of Cannabis samples. Such sampling should include dispensary-derived samples from both indoor and outdoor crops, as well as samples from police seizures from well-provenanced foreign sources, such as Mexico. Finally, further studies should be performed to measure toxin levels in strains that test positive for toxigenic species.