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Azerbaijan's Fight Against Drug Trafficking: A Detailed Look at the Seven Months 2024 Results
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Official websites use. Share sensitive information only on official, secure websites. This article was submitted to Plant Metabolism and Chemodiversity, a section of the journal Frontiers in Plant Science. The use, distribution or reproduction in other forums is permitted, provided the original author s and the copyright owner s are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. This study investigated the utility of the full spectrum of secondary metabolites in different plant parts in three cannabis chemotypes THC dominant, intermediate, and CBD dominant for chemotaxonomic discrimination. Hierarchical clustering, principal component analysis PCA , and canonical correlation analysis assigned 21 cannabis varieties into three chemotypes using the content and ratio of cannabinoids, terpenoids, flavonoids, sterols, and triterpenoids across inflorescences, leaves, stem bark, and roots. Significant chemical differences were identified in these three chemotypes. Cannabinoids, terpenoids, flavonoids had differentiation power while sterols and triterpenoids had none. Compound levels in intermediate strains were generally equal to or in between those in CBD dominant and THC dominant strains. The results of this study provide a comprehensive profile of bioactive compounds in three chemotypes for medical purposes. The simultaneous presence of a predominant number of identified chemotype markers with or without THC and CBD could be used as chemical fingerprints for quality standardization or strain identification for research, clinical studies, and cannabis product manufacturing. Cannabis is a complex herbal medicine containing several classes of secondary metabolites, including cannabinoids, terpenoids, flavonoids, and steroids among identified compounds Turner et al. For medical applications, researchers widely adopt a chemotaxonomic perspective that describes three chemotypes chemical phenotypes based on the content of two major cannabinoids: psychoactive tetrahydrocannabinol THC and non-psychoactive cannabidiol CBD Small and Beckstead, ; Turner et al. Although most clinical studies focus on THC and CBD, increasing amounts of evidence show that whole plant extract has additional benefits when compared to single cannabinoids. In one study, whole cannabis extract was more effective in inducing cancer cell death than applying pure THC on cancer cell lines Baram et al. In addition, individual cannabis extracts with similar amounts of THC produced significantly different effects on the survival of specific cancer cells, and specific cannabis extracts may selectively and differentially affect different cancer cells lines Baram et al. In another study, extracts from five strains with similar CBD concentrations had different anticonvulsant properties in mice Berman et al. It is therefore essential to have a comprehensive, full spectrum metabolic fingerprinting of secondary metabolites in cannabis materials for research and clinical studies. Previous research also focused on female inflorescences, however, each part of the plant has a wide range of indications, primarily related with pain and inflammation, as ancient herbal medicines in various cultures Smith and Stuart, ; Brand and Wiseman, ; Brand and Zhao, ; Ryz et al. Our previous study profiled cannabinoids, terpenoids, flavonoids, sterols, and triterpenoids, not only in cannabis inflorescences, but also in leaves, stem bark, and roots Jin et al. By profiling these compounds in each cannabis plant part and associating them with therapeutic benefits, cannabis plant material that is currently treated as waste has potential to be developed into natural health products or medications. Cannabis classification is a fundamental requirement for future medical research and applications, and it is best enabled through an overview of the class and content of potentially therapeutic secondary metabolites in each plant part. However, certain terpenoids were more prominent in some strains than others Hillig, b ; Fischedick et al. The mixed results in the current body of literature may be due to experimental design shortcomings. Secondly, samples in most classification studies were collected from disparate sources Fischedick et al. Additionally, inappropriate sample preparation and extraction procedures during laboratory analysis may affect classification results Jin et al. All these factors contribute to the variation in chemical profiles of the final products, which in turn leads to inconsistent results and poor classification accuracy. More accurate classification results are obtainable when plants are grown in a single location, under identical environmental conditions, and uniformly processed McPartland, In this study, we used unsupervised hierarchical clustering and principal component analysis PCA as well as supervised canonical correlation analysis to test the goodness of fit between chemotype labeling THC dominant, intermediate, and CBD dominant and chemotypic variation of the full spectrum of secondary metabolites in various plant parts of 21 strains. This study also identifies chemotypic markers within each chemotype, which will facilitate strain selection for further clinical and research studies. In this project, 21 commercially available cannabis strains were grown in a commercial greenhouse Figure 1 under a cannabis research license issued by Health Canada. Three to five cuttings per strain were rooted for 2 weeks, followed by vegetative growth under 24 h photoperiod for 2 months, and then flowered under 12 h photoperiod. After 2 months of flowering, the plants were harvested and hung to dry in a closed environment. Cannabis roots were removed and dried in the same room together with the other plant parts. The plants were dried for 7 days until the leaves and stems became brittle. Cannabis grown in a commercial greenhouse. A—C Cannabis plants before harvest. D Whole cannabis plants were cut above the ground and hang to dry in a drying room. E Cannabis roots were individually labeled and dried in the drying room with the other plant parts. A total of 82 plants representing 21 strains were harvested. Inflorescences, leaves fan leaves , stem bark, and roots were separately collected for each plant and analyzed for the full spectrum of secondary metabolites. Sugar leaves small leaves extending from the inflorescences were treated as a part of the inflorescences. Samples were prepared and analyzed according to previously developed and validated methodologies Jin et al. Dried leaf material was crushed using a mortar and pestle and sifted through a 1. One aliquot of the extract was used to quantify mono- and sesquiterpenoids using GC-MS. For flavonoids extraction, mg of the sample was extracted with 5 mL of ethanol, water, and hydrochloric acid at a volume ratio. The tube was then repeatedly rinsed with methanol, and the rinses were combined with the extract in a 50 mL volumetric flask, which was filled to volume with methanol. For the flavonoids assay, HPLC was used with an UV detector at nm for the quantification of seven flavonoids and MS detector for compound identification. For triterpenoids and sterols extraction, 1 g of dried sample was extracted with 20 mL ethyl acetate by sonication for 1 h, followed by maceration for one day at room temperature. In total, 82 plants representing 21 strains were included in the following analysis. Cannabinoids were calculated as the sum of their neutral forms, metabolites if applicable , and cannabinoid acids multiplied by a factor converting acids into their corresponding neutral forms. Total cannabinoids was calculated as the sum of 14 cannabinoids. Total monoterpenoids terpenoids with two isoprene units in the chemical structure was the sum of the 29 monoterpenoids in Supplementary Table 2. Total terpenoids was the sum of total mono- and sesquiterpenoids. Total flavonoids was the sum of seven flavonoids after acid hydrolysis, including orientin, vitexin, isovitexin, quercetin, luteolin, kaempferol, and apigenin. Compound ratios were calculated by dividing the content of one compound by the total content of that metabolite group. Secondary metabolites were quantified in each plant part. The following analyses were carried out only on the metabolites in the plant part where they were of highest levels among all plant parts. This distinction is made for isolating metabolites where they are present in sufficiently high concentrations above 0. First, correlations were calculated between individual cannabinoids, terpenes, flavonoids, sterols, and triterpenoids. Because absolute values vary with environmental factors and relative proportions are more stable Hillig, a , compound ratios were used. Finally, the data were subjected to supervised with preassigned categories as constraints canonical correlation analysis with preassigned chemotypes in Table 1. Canonical correlation analysis is also called canonical variates analysis, and is a multiple discriminant analysis that calculates the correlation between preassigned clusters and the set of covariates chemical compounds in this study describing the observations Hotelling, The first canonical variable is the linear combination of the covariates that maximizes the multiple correlation between the clusters and the covariates. The second canonical variable is a linear combination uncorrelated with the first canonical variable that maximizes the multiple correlation. The analysis outputs a biplot with the first two canonical variables that provide maximum separation among the clusters. Statistical analysis was performed with JMP Secondary metabolites profiled in inflorescences, leaves, stem bark, and roots are provided in Supplementary Table 9. Average total cannabinoids content from 82 plants of 21 strains decreased in order of inflorescences, leaves, stem bark, and roots, as shown in Supplementary Figure 1. Total cannabinoids were between 7. Total average cannabinoids content in inflorescences were Total cannabinoids content in leaves and stem bark averaged from three chemotypes are summarized in Supplementary Tables 2. Average total terpenoids as the sum of mono- and sesquiterpenoids in the same population decreased in order of inflorescences, leaves, stem bark, and roots Supplementary Figure 1. Total terpenoids in inflorescences was between 0. Average total terpenoids content in inflorescences and leaves for the three chemotypes are summarized in Supplementary Tables 2. Average total flavonoids as the sum of orientin, vitexin, isovitexin, quercetin, luteolin, kaempferol, and apigenin was highest in leaves, lower in inflorescences, and less than 0. Total flavonoids in inflorescences were between 0. All seven flavonoids were quantifiable in inflorescences in three chemotypes Supplementary Table 2. All flavonoids identified in inflorescences and leaves were less than those reported in other studies Flores-Sanchez and Verpoorte, , possibly due to differences in strains and plant growth stage, since flavonoids content fluctuate with plant age Vanhoenacker et al. Total sterols content in roots was between 0. Average total sterols content in stem bark and roots of the three chemotypes are summarized in Supplementary Tables 2. Total triterpenoids in stem bark was between 0. Average total triterpenoids content in stem bark and roots in the three chemotypes are summarized in Supplementary Tables 2. The distribution of secondary metabolites in each plant part agreed with conclusions from our last study Jin et al. Correlation and classification analyses were performed only for metabolites in the plant part where they were present in the highest concentrations representative for that strain. For example, the average terpenoid content in leaves were low 0. As such, using the terpene profile in inflorescences was adequate for clustering purposes. Flavonoids in inflorescences and leaves were included in the analysis because quercetin and kaempferol were quantifiable in inflorescences but not in leaves. For sterols, the content and ratios of three sterols are similar between stem bark and roots. Because total sterols in roots 0. Triterpenoid profile in roots were used because the content of total triterpenoids was above the threshold for pharmacological interest in all plant parts except in roots. To summarize, the most abundant secondary metabolites in individual plant parts were used in the statistical analysis for identifying differences between the three chemotypes. These metabolites were cannabinoids, terpenes, and flavonoids in inflorescences; flavonoids in leaves; and sterols and triterpenoids in roots Supplementary Table 7. Correlations between total THC or total CBD with individual cannabinoids, terpenoids, flavonoids, sterols, and triterpenoids are plotted in Figure 2 and summarized in Supplementary Table 3. Calculations were performed on quantifiable compounds using ratios. The quantitative correlations are plotted in Supplementary Figure 3. Most compounds have similar correlations with total THC and total CBD when calculated using ratios and absolute values. Correlations of total THC and total CBD with cannabinoids in inflorescences , mono- and sesquiterpenoids in inflorescences , flavonoids in inflorescences and leaves , sterols in roots , and triterpenoids in roots on quantifiable compounds using ratios. Flavonoids quantified in inflorescences are labeled F , and flavonoids in leaf are labeled L. The same set of data was used to build a dendrogram of the 82 plants using hierarchical clustering, where almost all plants of the same strains were clustered together, except for one 5-CBD plant that was mixed with 4-CBD plants and plants of THC that were mixed with THC plants Figure 3. The dendrogram shows two major branches: CBD dominant strains and intermediate strains together as one major branch, and THC dominant strains as the other. The dendrogram using absolute values of the secondary metabolites is shown in Supplementary Figure 4. These results both confirmed the minimum within-strain variation between plants within each strain and between-cluster variation between strains within each chemotypes. The full spectrum of secondary metabolites without total THC and total CBD resulted in a dendrogram with the same grouping results Supplementary Figure 5. Dendrogram by hierarchical clustering analysis using the full spectrum of secondary metabolites in ratios of 82 plants representing 21 strains. Plants of the same strains tended to occupy the same region on the plot. The loading matrix in Table 2 lists the compounds that contributed most to the separations along PC1 and PC2 with the absolute value of loadings equal to or greater than 0. THC dominant strains were scattered in both lower left quadrant and upper right quadrant along PC2. Two flavonoids, luteolin and apigenin, were negatively correlated with PC1 and PC2, and were more abundant in THC dominant strains in the left lower quadrant than other THC dominant strains. For example, compounds positively correlated with PC2 and positively correlated with PC1, including orientin L , vitexin L , and isovitexin L , were more abundant in THC dominant strains in the upper right quadrant than strain in C1 and C2, even though these flavonoids were positively correlated with CBD. This may be the result of extensive strain crossing and hybridization. PCA using absolute values of the secondary metabolites are also shown in Supplementary Figure 6. PCA scatter plot left and loading plot right using the full spectrum of secondary metabolites in ratios of 82 plants representing 21 strains. Terpenoids are labeled with T and the number assigned in Supplementary Table 2. Flavonoids are labeled as F and the number assigned in Supplementary Table 2. Flavonoids quantified in inflorescences are labeled F and flavonoids in leaf are labeled L. Sterols are labeled as S and the number assigned in Supplementary Table 2. The canonical correlation analysis of 82 plants showed good separation between the three chemotypes Figure 5. However, the distance between three clusters were smaller along two canonical axes due to reduced differences in the chemical profiles of three chemotypes after removing the THC and CBD data. Canonical correlation analysis using the full spectrum of secondary metabolites using ratios of 82 plants representing 21 strains. The plants were preassigned to three chemotypes in Table 1. The largest number of significant differences Tukey HSD multiple tests at the 0. The most similar pair was C1 and C2, with 14 significant differences. The number of significant differences between C2 and C3 was Most compounds in the C2 strains were at the same level with strains in C1 or C3 or at an intermediate level between C1 and C3. The largest number of significant differences was 38, which was between C1 and C3. The most similar pair was C1 and C2, with 10 differences. Cannabinoids, terpenoids, flavonoids, sterols, and triterpenoids that were significantly higher in C1, C2, and C3 were similar to those identified using ratios. Although numerous significant differences in compounds were found amongst CBD dominant, intermediate, and THC dominant strains, the group means of some compounds differed by less than a factor of two. In addition, some compounds may be significantly different qualitatively in ratios but not quantitatively in absolute values. There are more mono- and sesquiterpenoids that are significantly higher in the THC dominant cluster than in the CBD dominant and intermediate clusters. The simultaneous presence of a collection of compounds can be used to differentiate types of plants. This bias toward higher THC is due to the long history of extensive hybridization for recreational purposes McPartland, Chemotaxonomic research in minor cannabinoids of the three chemotypes are sparse in the current literature. In general, sesquiterpenoids are considered as more stable markers because monoterpenes are more volatile McPartland, According to the correlation analysis in this study, these chemotypic markers for CBD dominant strains and intermediate strains may be related to CBD production. Studies have shown that terpenes in cannabis are derived from two pathways: the plastidial methylerythritol phosphate MEP pathway and the cytosolic mevalonate MVA pathway Andre et al. Geranyl diphosphate GPP is typically derived from the MEP pathway and is the precursor for cannabinoid and monoterpenoid biosynthesis. Farnesyl diphosphate FPP is commonly produced from MVA pathway and is the precursor for sesquiterpenoids, triterpenoids and sterols. Although it is hypothesized that the identified chemotypic markers may be related to CBD or THC production, currently there are no biomedical studies on these correlations. Future studies are needed on the biochemical relationship between CBD or THC production and individual terpenoid production. Based on the reported ancestry, the results of this study seem to contradict other studies. This may lead to mixed results in separating modern strains genetically or chemically Elzinga et al. Flavonoid variation in cannabis was investigated by Clark and Bohm , the only such study that used flavonoids for chemotaxonomy and for supporting a two-species hypothesis: where luteolin was more often detected in C. Clark and Bohm, There have yet to be chemotaxonomic studies of flavonoids across the three cannabis chemotypes. We found that orientin, vitexin, and isovitexin were the signature flavonoids of CBD dominant strains, and quercetin and kaempferol were detected only in inflorescences and tended to be higher in THC dominant strains. The role of sterols and triterpenoids in the chemotaxonomy of cannabis have not yet been investigated. In this study, CBD dominant strains had significantly higher ratios of three sterols, but they differed by less than a factor of two and may not provide a firm basis for chemotaxonomic distinction. Similarly, for triterpenoids, although the ratio of epifriedanol was higher in CBD dominant strains and friedelin was higher in THC dominant strains, the differences were not sufficiently large for these compounds to be used as chemotype markers. Because cannabinoids are concentrated in cannabis inflorescences, cannabis leaves, stems, and roots are normally discarded by cannabis growers. However, in traditional Chinese medicine, cannabis leaves were used for treating conditions such as malaria, panting, roundworm, scorpion stings, hair loss, graying of hair. Cannabis stem bark was used for strangury and physical injury. Cannabis roots were used for gout, arthritis, joint pain, fever, skin burns, hard tumors, childbirth, and physical injury Smith and Stuart, ; Brand and Wiseman, ; Ryz et al. Their traditional uses may serve as points of reference for investigating the medical potential of what is currently a byproduct or plant waste. To link the traditional therapeutic uses for each part with the chemistry, we had identified the major groups of compounds in each plant part for correlation with benefits described in the literature. Increasing numbers of studies have shown that minor cannabinoids significantly contribute to the variance among cannabis extract, which further alter or enhance targeted therapeutic effects comparing to pure THC or CBD alone Berman et al. Terpenoids are widely distributed in highly fragrant fruits, plants, and herbs and they have anti-inflammatory Miguel, ; Xiao et al. If a cannabinoid-terpenoid entourage effect exists, it may not be at the CB1 or CB2 receptor level, but rather the terpenoids may act at different molecular targets in neuronal circuits Santiago et al. Flavonoids share a wide range of biological effects with cannabinoids and terpenoids, including anti-inflammatory He et al. Ginkgo leaves are one of the prominent sources of flavonoids, with 0. In this study, the mean of total flavonoids was 0. Sterols and triterpenoids are mainly present in cannabis stem bark and roots. Friedelin is the most abundant and most studied triterpenoids in cannabis, and has anti-inflammatory, antioxidant, estrogenic, anti-cancer, and liver protectant properties Ryz et al. Phytosterols are widely recognized as lowering the levels of low-density lipoprotein cholesterol Gylling et al. These groups of identified bioactive compounds may underpin the traditional applications indicated for each plant part, but most of the therapeutic properties for these individual compounds have been studied in other herbal medicine and not in cannabis. The pharmaceutical values and the potential synergies of these bioactive compounds need to be directly investigated using cannabis material. Well-designed clinical studies are necessary to convert each part of the cannabis plant into evidence-based medicine. The chemotypic markers identified in this study will facilitate strain selection in research and clinical studies when the optimal combination of the chemical compounds is determined for treating certain conditions. The chemical variation in CBD dominant and intermediate strains has yet to be studied or compared to THC dominant strains in the literature. This comprehensive chemotaxonomic investigation profiled cannabinoids, terpenoids, flavonoids, sterols, and triterpenoids in inflorescences, leaves, stem bark, and roots in 82 plants of 21 cannabis strains. These chemical data were subjected to correlation analysis, unsupervised clustering analysis hierarchical clustering and PCA and supervised canonical correlations analysis. In unsupervised clustering, 82 plants were clustered in accordance with their chemotypes. Numerous significant differences that could be used as chemotypic markers were found amongst CBD dominant, intermediate, and THC dominant strains. These identified compounds were largely consistent with results from correlation analysis, hierarchical clustering, PCA, and by comparing concentration and ratio averages between chemotypes. At each step of the clustering analysis, it was found that secondary metabolites without total THC and total CBD could continue to sort strains into their defined chemotypes and achieve the same clustering results. This demonstrated that the clustering results were not solely driven by THC and CBD content or ratio, and that other metabolites can be used as chemotypic markers. However, the robustness of these markers should be tested in different growing environments to truly elucidate the chemical differences in terms of chemotypes or intra-chemotype sub-clusters. The results of this study provide a proof-of-concept for further collaboration between academia and the industry for leveraging chemotypic markers in medical studies and clinical trials. DJ conceived the project, designed the experiments, preformed the experiments, collected and analyzed the data, and wrote the manuscript. PH contacted the licensed cultivator for this project and proofread the manuscript. JS provided funding, provided suggestions, and proofread the manuscript. JC was the supervisory author and monitored the research progress, provided suggestions, and finalized the manuscript. All authors contributed to the article and approved the submitted version. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors are grateful to Labs-Mart Inc. The authors are grateful to licensed cultivator, the Emerald Flower Farm Inc. The authors are also grateful to Shengxi Jin for proofreading the manuscript. Secondary metabolites profiling in cannabis roots, stem bark, leaves, and inflorescences in 82 plants of 21 strains. Correlations of total THC and total CBD with cannabinoids in inflorescences , mono- and sesquiterpenoids in inflorescences , flavonoids in inflorescences and leaves , sterols and triterpenoids in roots on quantifiable compounds using ratios. Dendrogram by hierarchical clustering analysis using the full spectrum of secondary metabolites absolute values of 82 plants representing 21 strains. Dendrogram by hierarchical clustering analysis using the full spectrum of secondary metabolites using ratios without total THC and total CBD. PCA scatter plot left and loading plot right using the full spectrum of secondary metabolites absolute values of 82 plants representing 21 strains. Canonical correlation analysis using the full spectrum of secondary metabolites absolute values of 82 plants representing 21 strains. Correlations of total THC and total CBD with minor cannabinoids, mono- and sesquiterpenoids, flavonoids, sterols, and triterpenoids only positive correlations are shown. Summary prediction of 82 plants into preassigned chemotypes using Canonical correlation analysis using ratios. This section collects any data citations, data availability statements, or supplementary materials included in this article. As a library, NLM provides access to scientific literature. Front Plant Sci. Find articles by Dan Jin. Philippe Henry 3 Egret Bioscience Ltd. Find articles by Philippe Henry. Find articles by Jacqueline Shan. Find articles by Jie Chen. Reviewed by: David L. Received Apr 23; Accepted Jun 9; Collection date Open in a new tab. Preassigned chemotypes as the working groups for canonical correlation analysis. Supplementary Figure 1 Secondary metabolites profiling in cannabis roots, stem bark, leaves, and inflorescences in 82 plants of 21 strains. Click here for additional data file. Supplementary Figure 3 Correlations of total THC and total CBD with cannabinoids in inflorescences , mono- and sesquiterpenoids in inflorescences , flavonoids in inflorescences and leaves , sterols and triterpenoids in roots on quantifiable compounds using ratios. Supplementary Figure 4 Dendrogram by hierarchical clustering analysis using the full spectrum of secondary metabolites absolute values of 82 plants representing 21 strains. Supplementary Figure 5 Dendrogram by hierarchical clustering analysis using the full spectrum of secondary metabolites using ratios without total THC and total CBD. Supplementary Figure 6 PCA scatter plot left and loading plot right using the full spectrum of secondary metabolites absolute values of 82 plants representing 21 strains. Supplementary Figure 8 Canonical correlation analysis using the full spectrum of secondary metabolites absolute values of 82 plants representing 21 strains. Supplementary Figure 9 Canonical correlation analysis using the full spectrum of secondary metabolites using ratios of 82 plants representing 21 strains. Supplementary Table 1 Strain information and assignment of 21 strains into three chemotypes. Supplementary Table 2. Supplementary Table 3 Correlations of total THC and total CBD with minor cannabinoids, mono- and sesquiterpenoids, flavonoids, sterols, and triterpenoids only positive correlations are shown. Supplementary Table 4 Summary prediction of 82 plants into preassigned chemotypes using Canonical correlation analysis using ratios. Supplementary Table 7 Secondary metabolites used in correlation analysis and classification analysis. Supplementary Table 8 Correlations of cannabinoids and terpenoids in inflorescences and leaves. Supplementary Table 9 Secondary metabolites in all plant parts absolute values. Similar articles. Add to Collections. Create a new collection. Add to an existing collection. Choose a collection Unable to load your collection due to an error Please try again. Add Cancel.
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Azerbaijan's Fight Against Drug Trafficking: A Detailed Look at the Seven Months 2024 Results
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Azerbaijan's Fight Against Drug Trafficking: A Detailed Look at the Seven Months 2024 Results
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