All the morphological parameters measured: plant height, number of nodes on the main stem, stem diameter, and main stem elongation rate, showed a developmental delay in the plants that received 15 ppm K, compared with plants that received higher amounts of K (**Figures 2A**–**H**) presenting as well 15 ppm as a sub-optimal concentration for both varieties. The two varieties demonstrated a similar response to the elevation of K supply. The average rate of plant elongation in the 15 ppm K treatment was 33% lower in RM and 28% lower in DQ (8.17 and 7.82 mm\*day−1, respectively), compared to the remaining treatments (**Figures 2G**, **H**). The average rate of stem thickening in the 15 ppm K treatment was 61% lower in RM and 70% lower in DQ (85 and 56 μm\*day−1, respectively), compared to the higher K supply treatments (**Figures 2E**, **F**). The average rate of node formation on the main stem was only 13% lower in RM and 3% lower in DQ in the 15 ppm K treatment (0.37 and 0.41 nodes\*day−1, respectively), compared to the remaining treatments (**Figures 2C**, **D**). These developmental delays under the restricted K supply of 15 ppm K had a considerable effect

on plant growth, resulting in shorter plants (**Figures 2A**, **B**). The growth restriction in RM and the stimulation in DQ under high K supply (240 ppm), which is statistically significant for leaves and root biomass of the entire plant (**Figure 1**), is not significant for most of the morphological and growth parameters of the main stem (**Figure 2**). This may present lower sensitivity of the main stem compared to the side branches to over-supply of K, and/or present that side branch development is more sensitive to high supply of K than initiation of new branches (new internodes).

# Macronutrient Concentration

The concentration of K supplied caused a variety of responses related to the ability of the plants to take up and accumulate nutrients, demonstrating organ but not cultivar specificity, with both cultivars revealing similar responses. In both cultivars, in all plant parts, K concentration increased significantly with increased K supply (**Figure 3A**). The concentration of the two major cation nutrients, Ca and Mg, tended to decrease with increased K supply, demonstrating competition for uptake (**Figures 3E**, **F**). While K concentration was highest in the stem, Ca and Mg concentration was very low in the stem, and higher in the leaves. Nitrogen and P concentrations in the plant organs were not affected by the level of K supplied, except in the 15 ppm K treatment. Furthermore, the extent of accumulation differed between organs and was higher in the leaves > roots > stem for N, and roots > leaves > stem for P (**Figures 3B**, **C**). Sulfur concentration in the plant organs was low, with preferred accumulation in the root and highest accumulation under 60–175 ppm K supply (**Figure 3D**).

#### Micronutrients and Na

Unlike the considerable effects on macronutrients, K supply had but little effect on micronutrient accumulation in the shoot. Micronutrient concentration in the leaves and stems were generally unaffected by K supply, except Mn which built up to higher concentrations at the 15 ppm K treatment (**Figures 4A**–**F**). In the roots, concentrations of Zn, Fe, and Mn usually decreased with the increase in K supply; Cu and Na concentration followed maximum curves with highest accumulation under 100–175 ppm K supply (**Figures 4A**–**E**); and Cl concentrations which were very low were unaffected by K supply (**Figure 4F**). The concentrations of all micronutrients were higher in the roots compared to the shoot. In the shoot, the concentration of Na, Cl, and Cu were generally higher in the stem, compared to the leaves, while an opposite trend was found for the remaining micronutrients (**Figures 4A**–**F**). The two tested cultivars responded similarly to K fertigation in terms of micronutrient and macronutrient accumulation.

## Gas Exchange and Photosynthesis

The sensitivity of net photosynthetic rate and gas exchange parameters to K supply differed in the two cultivars. In DQ,

net photosynthetic rate increased with the increase in K supply, up to a maximum at the 100 ppm K treatment, and declined with further increase in K (**Figure 5A**) presenting 100 ppm as the optimal concentration for photosynthesis in this cultivar. In contrast, the intercellular CO2 concentration was higher at the 15 ppm K treatment than in all other treatments, and the transpiration rate and stomatal conductance was not affected by K supply (**Figures 5B**–**D**). RM responded differently, with

transpiration rate and stomatal conductance lower at the 15 ppm K treatment compared to all other treatments, and net photosynthetic rate and intercellular CO2 concentration were not affected by the K supply treatments (**Figures 5A**–**D**).

## Water Relations and Photosynthetic Pigments

The effect of K supply on the percentage of dry weight (%DW) in the plant tissues differed between the two varieties. In DQ, %DW of the leaves and stems was higher at the 15 ppm K treatment compared to all other treatments (**Figures 6A,**

**B**), while in RM, %DW of the stem was not affected by the treatments but in the leaves it was higher under 15 and 60 ppm K supply, compared to other K supply treatments. Osmotic potential and relative water content of the leaf were lower under 15 ppm K supply, compared to all other treatments, in both varieties (**Figures 6C, D**). In DQ the osmotic potential increased with additional K supply throughout the concentration range tested, while in RM it stabilized under a lower K supply (60 ppm K; **Figure 6D**). Membrane leakage analyses demonstrated a higher sensitivity of RM tissues to K deficiencies (15 ppm K) compare to DQ, and a lack of response in both varieties to higher K supply (Fig 6E). In RM water use

efficiency was not affected by K supply, while in DQ it was significantly lower in the 15 ppm K treatment, compared to all other higher K treatments (**Figure 6F**).

Concentrations of chlorophyll a and carotenoids in the foliage increased with elevation of K supply (**Figures 7A**, **C**), while chlorophyll b was significantly lower at the 15 ppm K treatment, compared to the remaining treatments, in both varieties (**Figure 7B**).

#### Irrigation and Leachate Solutions

Routine chemical analyses of the fertigation (irrigation) solution demonstrated precise regulation of the treatment solutions. The concentration of K (**Figure 8A**) for both varieties was steady throughout the experiment duration in all five K treatments, and closely followed the designated treatments concentrations (**Figure 8A**). The concentration of K in the leachate solutions positively correlated with K supply in both varieties (**Figures 8B**). In the high K treatments, 175 and 240 ppm, the concentration in the leachate increased over time, suggesting over supply (**Figure 8B**).

## Plant Visual Characteristics

The visual appearance of the plants was affected similarly by the K treatments in the two cultivars, and reflected the morphological,

HSD test at α = 0.05.

between K and genotype.

chemical and physiological characteristics evaluated in the study (**Figures 9**–**10**). In the 15 ppm K treatment, the leaves were smaller, had fewer leaflets (in DQ), and showed advanced chlorosis typical of K deficiency (**Figure 9**). They were also developmentally inhibited, compared to the remaining K treatments that had larger leaves and darker green color (**Figure 9**). The chlorosis and restricted growth of the 15 ppm K treatment affected overall shoot growth, resulting in a smaller and thinner plants, compared to plants of all other treatments (**Figure 10**).

### DISCUSSION

Mineral nutrition is one of the major factors affecting plant growth, development, and function. Optimal concentrations of mineral nutrients in the plant tissues and in the root solution vary for individual nutrients, and may differ between and within species. Furthermore, due to effects of specific nutrients on biochemical, physiological, and molecular processes, nutrition may need to be adjusted for directing a required metabolic process or a preferred developmental scheme, such as a vegetative or reproductive development. In the present study we report changes to the ionome and to plant development and function resulting from the intensity of K supply, comparatively for two cultivars of medical cannabis.

# Plant Growth and Development

Genetic variability within plant species results in genotypes with different developmental, physiological, and biochemical traits. Variability in response of roots and shoots of plant genotypes to growing conditions is well documented for numerous plant species (Antonio et al., 2019; Martins et al., 2016; Queiroz et al., 2019). For *C. sativa*, drug-type strains are known to vary in morphological and chemical characteristics, but responses to cultivation and environmental conditions are not known. In the present study we report that while the response to low, sub-optimal supply of K was similar for the genotypes studied, developmental differences between genotypes emerged under higher K concentration.

In both genotypes, biomass deposition was affected by K inputs but the response varied between the genotypes. In RM, growth positively responded to increase in K supply up to 175 ppm K (**Figures 1A**–**C**), as can be seen from the increase in leaves and root biomass (**Figures 1A**, **C**), stem diameter (**Figure 2E**), and internode elongation rate (**Figures 2E**, **G**), but decreased

membrane leakage (E) and intrinsic water use efficiency (WUEi) (F), of two medical cannabis cultivars, RM and DQ. Presented data are averages ± SE (n = 5). Results of two-way ANOVA indicated as \*\*P < 0.05, F-test; NS, not significant P > 0.05, F-test. In the ANOVA results K'G represents the interaction between K and genotype.

with further increase to 240 ppm K, rendering 175 ppm as the optimum concentration for this genotype. While DQ suffered as well from insufficient K supply under the 15 ppm K treatment, increasing K supply in the range of 60–175 ppm K did not affect plant development. Surprisingly, further increase in K supply, to the level of 240 ppm K, stimulated rather than restricted growth and development of this genotype.

The increase in biomass production with the increase in K at the lower concentration range in both genotypes represent mitigation of restricted supply, satisfying demands for facilitating optimal growth. The concentration range at which plant performance improves with increased supply is defined a "deficiency range," which is well documented to vary between species (Marchner, 2012) and in some cases also between genotypes. The lower requirement of K supply for optimal development in RM may be the outcome of the smaller shoot and root morphology in this genotype, compared to the larger vegetative plant body of DQ. RM might have therefore been less prone to deficiency. Potassium plays an active part in the physiological regulation of crop processes (Wang and Wu, 2017), facilitating functions such as ion uptake and transport, protein synthesis, stomatal regulation, enzymatic activity, and regulation of gene expression. The observed growth stimulation with increased K supply at the low concentration range in the two cannabis genotypes can result from effects of the deficiency on individual factors or combination of mechanisms as was

FIGURE 7 | Effect of K application on the concentration of photosynthetic pigments in two medical cannabis cultivars, RM and DQ. Chlorophyll a (A), chlorophyll b (B), and carotenoids (C). Presented data are averages ± SE (n = 5). Results of two-way ANOVA indicated as \*\*P < 0.05, F-test; NS, not significant P > 0.05, F-test. The bars represent the LSD between means at P ≤ 0.05. In the ANOVA results K'G represents the interaction between K and genotype.

demonstrated for numerous plant species. In tomatoes for example, the suppression of stem expansion under K deficiency, which was apparent in both medical cannabis genotypes as well, was concluded to result from a reduction in water supply to the

growing stem by K-deficiency induced reduction in aquaporins and K-channels activity (Fromm, 2010; Kanai et al., 2011). Similar to our results, addition of K led to development of thicker stems and higher shoot biomass.

Potassium is a major player in regulation of plant water relations (Mengel and Arneke, 1982), osmo-regulation (Lauchli and Pfluger, 1978), and stomatal opening (Fischer, 1968, Fischer, 1971; Outlaw, 1983) and hence plant development (Prajapati and Modi, 2012; Wang et al., 2013). The source of the different development response of the two medical cannabis genotypes to K supply, roots in the impact of K availability on the physiological status, mostly water relations, of the tissue. Although in the RM plants the rate of photosynthesis was not affected by the K treatments, slower transpiration rate with reduced stomatal conductance were induced by K-deficiency (15 ppm K) (**Figure 5**) resulting in restricted growth but higher water use efficiency. Environmental conditions are known to affect carbon fixation (Rodrigues et al., 2016). The change in water relations in the 15 ppm K treatment was apparent also from the lower osmotic potential and relative water content in the leaf tissue, and higher %DW, i.e., lower percentage of water in the tissue. The combined effects of K deficiency and altered water status caused tissue damage, as was apparent from the higher membrane leakage (**Figure 6E**), and resulted in restriction of development. The relative water content and osmotic potential were lower in the 15 ppm K treatment in DQ as well (**Figure 6**), but growth was restricted by a different mechanism. That is, in this genotype, transpiration rate and stomatal conductance were not impaired under the deficient K supply (15 ppm K), but net photosynthesis rate was reduced, resulting in higher CO2 concentration in the intercellular space, due to a decrease in the consumption of CO2 as a substrate for photosynthesis (**Figure 5**). Membrane leakage, i.e., tissue stress was not affected, but the tissue did suffer from water shortage, resulting in lower %DW in the evaporating tissues of the leaves. Despite the variation in net photosynthesis rate and gas exchange parameters between the genotypes, the values obtained are within the range obtained in former measures conducted for indoor grown medical cannabis (Chandra et al., 2011).

In both genotypes, K supply had a significant effect on the photosynthetic pigments in the tissue; positively correlating with chlorophyll a and carotenoids contents (**Figures 7A**, **C**). Moreover, chlorophyll b as well was affected by K supply but K demands for optimal accumulation were satisfied already under 60 ppm K inputs (**Figure 7B**). As K is not a constituent of these molecules, the impact it has on their biosynthesis is indirect, and we suggest that the decrease in concentration of the pigments under 15 ppm K results from inhibition of N availability in the leaf cells, N being a central constituent of these molecules (Taiz and Zeiger, 2010). Furthermore, K, as a cofactor, is involved in the activity of a large number of vital enzymes (Evans and Sorger, 1966; Prajapati and Modi, 2012), that affect also metabolism and catabolism of plant pigments. Reduced chlorophyll concentration induced leaf chlorosis, and the impaired water relations and reduced availability of K resulted in a morphological response with development of smaller leaves and leaflets and fewer leaflets.

Excess of K supply induced contrasting effects on the two genotypes. The difference in plant biomass between the genotypes in the 240 ppm K treatment results from differential effect of the high K supply on development of the side branches. In RM the length of the side branches was inhibited by 21% as K supply increased from 175 to 240 ppm, while in DQ the side branches length increased by 14% (data not shown). K effect on side branch development is known also for other plants (Madgwick, 2011) and is likely to have a large effect on total biomass accumulation even without an effect on branching. The elevated biomass deposition in DQ under high K supply is the outcome of an increase leaf biomass of the side branches as well as in stem diameter (data not shown), resulting in bushier bigger plants. K is known to affect stem diameter and fiber yield and quality in other plant species as well (Derrick et al., 2013).

Accumulation of nutrients above the optimal level required for plant growth and function i.e., "luxury consumption," is a process described for numerous plant species, mostly related to K uptake (Bartholomew and Janssen, 1929). "Luxury consumption" of K usually does not affect growth and development of plants, but it was previously reported for numerous species including cotton, that excessive K fertilizer reduces plant biomass (Chen et al., 2017). In the case of the two medical cannabis genotypes, the mechanisms for the contrasting developmental response are not clear and require further study. Specifically, the higher concentration of K in stems of DQ compared to RM under 240 ppm K, (higher by 20%) is unlikely the cause of the observed growth stimulation in this genotype, because the increased in K concentration in the shoot under 60–175 ppm K supply did not affect plant development, categorizing the increased K uptake in this range as luxury consumption. In RM as well, changes in K concentrations in the shoot do not present a direct cause for growth restriction under 240 ppm K compared to lower supply rates since K concentrations were not affected considerably

(**Figure 3**). No apparent changes in any other macro or micronutrients (**Figures 3**, **4**), carbon fixation and gas exchange parameters (**Figure 5**) or water relations parameters (**Figure 6**) were identified as potential causes for the developmental response and genotypic differences under 240 ppm K.

Interestingly, the distribution of K between plant organs differed for the two genotypes—while in RM concentrations in the roots and the shoot organs were similar, higher levels of K transport to the shoot were apparent in DQ. Consequently, supplied levels of K that restricted growth in RM, stimulated growth in DQ (**Figure 3A**). This suggests differential sensitivity of the cells from both genotypes to K, or more likely, involvement of a secondaryinduced factor in the observed growth restriction. The variability in the response of the two genotypes to K supply, demonstrated by an optimum response curve in RM, and the three distinct response phases in DQ (**Figures 1A**–**C**), reveals as well genetic differences within the *C. sativa* species to mineral nutrition.

Nutrient use efficiency, e.g., the amount of biomass produced per K unit supplied, is a valued tool for evaluating the ability of the plant to utilize environmental inputs into yield or biomass production (Yasuor et al., 2013; Omondi et al., 2018). We report here for medical cannabis, a large decrease in KUE with the increase in K supply (**Figure 1D**). This points again at "luxury consumption" and suggests that, maximum efficiency is obtained under low K concentrations. For a high cash-crop like medical cannabis, it is likely that the marginal addition to the biomass at the vegetative stage, if proven to support better plant architecture for the reproductive phase, will be more significant than the fertilization expenses. Plant genotypes are known to vary also in nutrient use efficiency. In the present study KUE was higher in DQ compared to RM.

#### Mineral Nutrients

The variability in the distribution patterns of the various macronutrient in the plant body result from uptake and translocation mechanisms. The increased concentration of K in the root solution increase overall cation concentration in the solution and hence competition for uptake of the positively charged cations. Reduction in Ca concentration in the plants under high K supply (**Figure 3E**), points at competition for uptake. Ca/K competition for root uptake (Johansen et al., 1968; Maas, 1969) and a resulting reduced Ca concentration in the shoot was documented for a variety of plant species (Fageria, 2001). Moreover, in-planta transport of these two ions is also competitive since high K concentrations decreased the amount of Ca arriving to the foliage, as already seen before (Overstreet et al., 1952; Bar-Tal and Pressman, 1996). Mg is another cation which was identified to compete with K for root uptake and translocation in the plant (Heenana and Campbell, 1981), but in cannabis K has a smaller influence on its translocation since Mg concentration began to decrease only in the 60 ppm K treatments (**Figure 3F**). The uptake and distribution of the two other major macronutrients, N and P, is not sensitive to K supply (**Figures 3B**, **C**), probably since their uptake into the root cells is as anions, in a mechanism less affected by cation concentrations and uptake (most of the N in the present study was supplied as NO3 - ) (White, 2012).

Concentration of K in the leachate solution is another indicator of plant requirement and uptake. In the present study, K concentration in the leachate was higher than in the irrigation solution only at the 175 and 240 ppm K treatments (**Figure 8B**), indicating that K supply under these treatments exceeded plant uptake. Nutrient concentration in the leachate is an integral result of water and mineral uptake by the plants. When water is taken up to a greater extent than a mineral, its concentration in the leachate will exceed the concentration in the irrigation solution. The concentration of K in the leachates of the three lower K treatments was similar to the concentration in the irrigation solution, demonstrating similar uptake rates of K and water. Under 175–240 ppm K application, the higher concentration of K in the leachate compared to the irrigation solution demonstrate that the rate of water uptake was higher than for K, resulting in an increase in K. This suggests that 175 ppm K is higher than the plant requirement.

Micronutrient uptake is a limiting growth factor for foliage and shoot development in many plant species under various growing conditions (Baszyński et al., 1978; Ohki et al., 1980; Clark, 1982; Webb and Loneragan, 1988; Yu and Rengel, 1999). No information is currently available about micronutrient requirements or effects on medical cannabis, and our results present initial understanding. Under the cultivation conditions and rate of nutrient supply at the present study, the two cannabis cultivars examined did not show any signs of micronutrient deficiencies, suggesting sufficient supply (**Figure 4**). Surprisingly, most micronutrients and the beneficial element Na, did not translocate to the shoot but tended to accumulate in the root. Zinc, Mn, Fe, Cu, and Cl as well as Na concentrations were all higher in the root compared to the shoot, suggesting a compartmentation strategy for temporary storage, or for prevention of access concentrations at the shoot tissues. Results of the comparative analyses point at competitive uptake between K and Mn, Zn and Fe, since concentrations of the latter decreased with increased K supply. Na uptake was less affected by this competition (**Figure 4E**), in accord with its known strong competition abilities with K for root uptake (Amtmann and Leigh, 2010), or due to its very low concentration in the fertigation solution, which was prepared with distilled water. The uptake of another micronutrient, Cl, was not affected by cultivar or K supply (**Figure 4F**), probably because its concentrations was low and within the range accepted as optimal to most plants (Parker et al., 1983; Marchner, 2012).

Some information for micronutrient uptake by *C. sativa* L. is available for industrial, fiber-type, Hemp. It is used for phytoremediation, due to its known ability to absorb heavy metals from the soil and tolerate high accumulation in its tissues

#### REFERENCES

(Linger et al., 2002; Ahmad et al., 2016). Contradictory to our expectation for similar high uptake rates of micronutrient cations into the medical cannabis plants, these Hemp properties were not found in the medical type varieties. The difference between the Hemp and medical cannabis response could result from several factors; 1. The distinct plant genetics of Hemp may express enhanced uptake mechanisms for heavy metals; 2. Differences in chemical and physical properties (such as pH, chelate diversion, and cation exchange capacity) between the rhizosphere of the soilless cultivated medical cannabis and the soil-grown Hemp (Landi, 1997; Aubin et al., 2015), may have affected root nutrient availability and uptake; 3. The growth period of the medical cannabis cultivars was short compared to a standard growth period of Hemp (Van der Werf and Van den Berg, 1995; Linger et al., 2002; Vera et al., 2010), resulting in overall lower amounts of metal accumulation in the medical cannabis cultivars.

## AUTHOR CONTRIBUTIONS

NB planned the experiments. AS carried out the experiments. NB and AS wrote the manuscript. MS constructed the fertilizers compositions.

#### ACKNOWLEDGMENTS

The project was funded by the Chief Scientist Fund of the Ministry of Agriculture in Israel, Project No. 20-03-0018. We thank Bezalel Grushka for technical advice and assistance, and Geki Shoef and Ayana Neta for technical assistance. We are grateful for the cooperation of Gerry Kolin from Teva Adir, LTD, a certified commercial cultivation farm in Israel.

genotypes cultivated at high altitude and subjected to low temperature during the winter. *Sci. Hortic. (Amsterdam)* 252, 238–242. doi: 10.1016/j. scienta.2019.03.044

**Conflict of Interest:** The 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.

*Copyright © 2019 Saloner, Sacks and Bernstein. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). 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.*

# Cannabinomics: Application of Metabolomics in Cannabis (Cannabis sativa L.) Research and Development

Konstantinos A. Aliferis1,2 \* and David Bernard-Perron<sup>3</sup>

<sup>1</sup> Laboratory of Pesticide Science, Agricultural University of Athens, Athens, Greece, <sup>2</sup> Department of Plant Science, McGill University, Montreal, QC, Canada, <sup>3</sup> The Green Organic Dutchman, Mississauga, ON, Canada

Cannabis (Cannabis sativa L.) is a complex, polymorphic plant species, which produces a vast array of bioactive metabolites, the two major chemical groups being cannabinoids and terpenoids. Nonetheless, the psychoactive cannabinoid tetrahydrocannabinol (1<sup>9</sup> - THC) and the non-psychoactive cannabidiol (CBD), are the two major cannabinoids that have monopolized the research interest. Currently, more than 600 Cannabis varieties are commercially available, providing access to a multitude of potent extracts with complex compositions, whose genetics are largely inconclusive. Recently introduced legislation on Cannabis cultivation in many countries represents a great opportunity, but at the same time, a great challenge for Cannabis research and development (R&D) toward applications in the pharmaceutical, food, cosmetics, and agrochemical industries. Based on its versatility and unique capabilities in the deconvolution of the metabolite composition of complex matrices, metabolomics represents an ideal bioanalytical tool that could greatly assist and accelerate Cannabis R&D. Among others, Cannabis metabolomics or cannabinomics can be applied in the taxonomy of Cannabis varieties in chemovars, the research on the discovery and assessment of new Cannabisbased sources of bioactivity in medicine, the development of new food products, and the optimization of its cultivation, aiming for improvements in yield and potency. Although Cannabis research is still in its infancy, it is highly foreseen that the employment of advanced metabolomics will provide insights that could assist the sector to face the aforementioned challenges. Within this context, here, the current state-of-the-art and conceptual aspects of cannabinomics are presented.

Keywords: cannabinoids, cannabis terpenoids, chemovars, drug discovery, medicinal cannabis, plant metabolomics, plant chemotaxonomy

# INTRODUCTION

Cannabis (Cannabis sativa L., Cannabaceae) (**Figure 1**) is a highly variable, complex, polymorphic plant species, which originates from Eurasia (Russo et al., 2008; Clarke and Merlin, 2013, 2016). Currently, it is distributed world-wide and grows in variable habitats, altitudes, and soil and climate conditions (Clarke and Merlin, 2016). There is a controversy among botanical taxonomists

#### Edited by:

Donald Lawrence Smith, McGill University, Canada

# Reviewed by:

Hiroshi Noguchi, Nihon Pharmaceutical University, Japan Derek Stewart, The James Hutton Institute, United Kingdom

#### \*Correspondence:

Konstantinos A. Aliferis<EMAIL_ADDRESS><EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Plant Metabolism and Chemodiversity, a section of the journal Frontiers in Plant Science

Received: 05 December 2019 Accepted: 14 April 2020 Published: 08 May 2020

#### Citation:

Aliferis KA and Bernard-Perron D (2020) Cannabinomics: Application of Metabolomics in Cannabis (Cannabis sativa L.) Research and Development. Front. Plant Sci. 11:554. doi: 10.3389/fpls.2020.00554

**Abbreviations:** 1<sup>9</sup> -THC, 1<sup>9</sup> -tetrahydrocannabinol; CB1, CB2, cannabinoid receptors CB1, CB2; CBD, cannabidiol; GC/FID, gas chromatography-flame ionization detector platform; HRMS, high-resolution mass spectrometry; LC-DAD, liquid chromatography-diode array detector platform; MoA, mode(s)-of-action; NMR spectroscopy, nuclear magnetic resonance spectroscopy; PPPs, plant protection products; QC, quality control; R&D, research and development.

on the number of species that compose the Cannabis genus; presently, there is a consensus on the nomenclature proposed by Small and Cronquist (Small and Cronquist, 1976); C. sativa is monotypic, composed of two sub-species (subsp.), namely sativa and indica, based on their 1<sup>9</sup> -tetrahydrocannabinol (1<sup>9</sup> -THC) content. The former is further sub-divided into two varieties (var.), sativa (low 1<sup>9</sup> -THC, domestication traits) and spontanea (low 1<sup>9</sup> -THC, wild-type traits), and the latter into var. indica (high THC, domestication traits) and var. kafiristanica (high 1<sup>9</sup> - THC, wild-type traits). Approximately 600 Cannabis varieties are commercially available (Rahn et al., 2016), whose genetics, for many of these, are only partially known. The plant has a diploid genome (2n = 20) composed of nine autosomes and a pair of sex chromosomes (X and Y) (Ming et al., 2011) and its draft genome has recently been sequenced (Van Bakel et al., 2011).

The use and exploitation of Cannabis has sparked controversy, however, the recent legalization of its use for medical and other purposes in many countries within the corresponding legislative framework (Pacula and Smart, 2017; Cox, 2018), in combination with the remarkable bioactivities of the plant, pose an urge for the acceleration and intensification of Cannabis research and development (R&D). Although it is still in its infancy, there is currently an exponentially increasing interest in Cannabis R&D, as it is confirmed by the number of relative publications and citations (**Figure 2**).

Nevertheless, drug discovery, the risk assessment of cannabis products and their quality control (QC), and the research on the plant and its bioactive constituents, necessitate the implementation of advanced bioanalytical tools. Such tools could facilitate the acquisition of the necessary missing knowledge that will be further exploited toward the development of innovative, safe products, and the improvement of the plant's productivity in a timely fashion. Based on its versatility and unique capabilities in the deconvolution of the metabolite composition of complex matrices, metabolomics represents an ideal bioanalytical tool that could greatly accelerate Cannabis R&D. Its successful implementation requires solid expertise in experimental design, analytical and bioanalytical chemistry, advanced statistics, and bioinformatics. To date, metabolomics has been developed for a wide range applications in various fields such as plant (Sumner et al., 2015) and food science (Wishart, 2008; Cevallos-Cevallos et al., 2009; Herrero et al., 2012; Castro-Puyana and Herrero, 2013), medicine (Wishart, 2016), toxicology (Bonvallot et al., 2018; Viant et al., 2019), environmental sciences (Bundy et al., 2009), and plant protection products (PPPs) R&D (Aliferis and Chrysayi-Tokousbalides, 2011; Aliferis and Jabaji, 2011). Nonetheless, since comprehensive reviews on the topics of metabolomics methodologies, analytical platforms, software, and cannabinoid analysis have been recently published (Madsen et al., 2010; Aliferis and Chrysayi-Tokousbalides, 2011; Fuhrer and Zamboni, 2015; Gromski et al., 2015; Markley et al., 2017; Leghissa et al., 2018b; Pellati et al., 2018; Ramirez et al., 2019; Atapattu and Johnson, 2020), these topics are not reviewed here.

For the application of metabolomics in Cannabis R&D we are introducing the term "Cannabinomics" (**Table 1**). Its application could greatly assist the sector via the mapping of the metabolomes of the existing genotypes and their classification into the corresponding chemovars (Hazekamp et al., 2016; Lewis et al., 2018). Additionally, it has been predicted that the contribution of Cannabinomics toward the optimization and standardization of agricultural practices [e.g., application of plant growth regulators (PGR), bioelicitors, fertilizers, light conditions, irrigation events] for the production of superior quality products will be substantial (Magagnini et al., 2018). Similarly, it is expected to have a significant impact in the drug discovery, medicine, food science, functional cosmetics research, and metabolic engineering of microorganisms for the biosynthesis of cannabinoids. Here, the current state-of-the-art on these research topics, as well as conceptual aspects and perspectives, are being presented.

### CANNABIS (CANNABIS SATIVA L.): A UNIQUE FACTORY OF BIOACTIVE METABOLITES AND MULTI-COMPLEX MIXTURES

The plant owes its reputation to the biosynthesis of a vast array of diverse metabolites that exhibit unique structures, physicochemical properties, and bioactivities; cannabinoids, which is a unique class of secondary plant metabolites (**Figures 3**, **5**) and terpenoids (**Figure 4**), are the most important groups of Cannabis-derived metabolites. To date, approximately 600 Cannabis metabolites have been isolated, with more than 20% of them belonging to cannabinoids (Chandra et al., 2017). Among them, seven have been classified as CBD-type metabolites (Morales et al., 2017). In addition to the bioactive metabolites, the plant is a rich source of cellulosic and woody fibers (Andre et al., 2016). Therefore, the discovery and functional characterization of all the genes involved in the biosyntheses of cannabinoids is of paramount importance for the development of various applications, as discussed below. Nonetheless, the application of metabolomics in the field is still in its infancy.

The psychoactive metabolite 1<sup>9</sup> -THC and the nonpsychoactive CBD (**Figure 3**), are the two major cannabinoids present in various concentrations in the different Cannabis chemovars, which largely determine their potency and pharmaceutical properties. The psychoactive and medicinal properties of Cannabis have been known for more than 5,000 years in the Middle East and Egypt, and later in China, India, Ancient Greece, and the Roman Empire (Di Marzo, 2008; Russo et al., 2008; Mechoulam and Parker, 2013; Farag and Kayser, 2015). 1<sup>9</sup> -THC has monopolized the interest of the Cannabis-related R&D since its isolation in 1964 (Gaoni and Mechoulam, 1964) and total synthesis a year later (Mechoulam and Gaoni, 1965). On the other hand, CBD has recently attracted the interest of the scientific community mainly due to its, among others, antioxidant, anti-inflammatory, and analgesic properties (Morales et al., 2017). Based on such properties, it represents a model chemical structure of high potential in the synthesis of chemical analogs. In addition to 1<sup>9</sup> -THC and CBD, other major cannabinoids are the cannabichromene (CBC), cannabidiolic acid (CBDA), cannabigerol (CBG),

FIGURE 1 | Cannabis sativa L.; One-week old seedling of the hemp dioecious strain "Finola" (A), 4 weeks old plant of the strain "BIK" (B), and plants at the flowering stage (C). Close up photo of a flower of the strain "Skunk" (D), and big capitate-sessile trichomes as shown in the stereomicroscope (E).

cannabinol (CBN), cannabidivarin (CBDV), cannabidivarinic acid (CBDVA), cannabigerolic acid (CBGA), cannabicyclol (CBL), 1<sup>8</sup> -THC, tetrahydrocannabinolic acid (THCA), and tetrahydrocannabivarin (THCV) (**Figures 3**, **5**).

A very interesting recent development is the biosynthesis of various cannabinoids by genetically engineered organisms, which could potentially provide solutions to the large-scale production of rare cannabinoids (Carvalho et al., 2017;

a 1H-NMR; proton nuclear magnetic resonance spectroscopy, <sup>1</sup>D DOSY; diffusion-edited <sup>1</sup>H NMR, <sup>1</sup>H-1H COSY; proton/proton correlation spectroscopy, <sup>1</sup>H-13C HMBC; <sup>1</sup>H-13C heteronuclear multiple quantum coherence, GC/FID; gas chromatography-flame ionization detector, GC/MS; GC/mass spectrometry, LC-DAD; liquid chromatography-diode array detector, LC/ESI/MS; liquid chromatography-electrospray ionization-mass spectrometry, LC/TOF/MS; liquid chromatography time-of-flight mass spectrometry, LC/QTOF/MS; quadrupole time-of-flight mass spectrometry, HRMS; high resolution mass spectrometry, LC/QQQ/MS; triple quadrupole LC/MS. <sup>b</sup>Ace, acetone; CHCl3, chloroform; DMSO, dimethyl sulfoxide; EtAc, ethyl acetate; EtOH, ethanol; MeOH, methanol; MTBE, methyl tert-butyl ether.

Luo et al., 2019). The most profound example of such organism is yeast (Saccharomyces cerevisiae), which is a model that has been extensively used in metabolic engineering studies for the production of high-value chemicals (Liu et al., 2013; Nielsen et al., 2013; Carvalho et al., 2017). The biosynthesis of cannabinoids such as, CBGA, 1<sup>9</sup> -tetrahydrocannabinolic acid, CBDA, 1<sup>9</sup> -tetrahydrocannabivarinic acid, and CBDVA by metabolic engineered yeast strain has been recently reported (Luo et al., 2019). In this study, the carbohydrate galactose served as the precursor of cannabinoids, and to the best of our knowledge, this is the first report on the application of metabolite profiling applying liquid chromatography time-of-flight mass spectrometry (LC/TOF/MS)-quadrupole time-of-flight mass spectrometry (LC/QTOF/MS) analysis. The extraction was performed using ethyl acetate (EtAc-formic acid 0.05%, v/v). Within this context, as a functional genomics tool, metabolomics

could ideally employed in the study and monitoring of the metabolism of engineered microorganisms toward the optimization of the biosynthesis of natural cannabinoids or their synthetic analogs.

Additionally, plants biosynthesize a vast array of lipophilic volatile metabolites via the removal of hydrophilic moieties in a series of reactions (e.g., reduction, methylation, acylation) (Pichersky et al., 2006). Such plant volatiles (PVs), among others, regulate their interactions with biotic and abiotic factors (e.g., attraction of pollinators, protection against pests and pathogens) (Dudareva et al., 2013). Among PVs, terpenoids represent the most important and populated chemical group, with the sub-groups of isoprenes (C5), monoterpenes (C10), and sesquiterpenes (C15) being the largest (**Figure 4**).

Terpenoids are synthesized via dimethylallyl diphosphate (DMAPP) and isopentenyl diphosphate (IPP) (**Figure 4**), which are derived from Cannabis biosynthetic pathways that are localized in different cell compartments (Nagegowda, 2010; Russo, 2011), sharing geranyl diphosphate (GPP) as a common precursor with cannabinoids (Grof, 2018). Playing a fundamental role in determining food's flavor and fragrance, Cannabis terpenoids have recently attracted the interest of researchers (Russo and Marcu, 2017), threatening the dominance of 1<sup>9</sup> -THC and CBD as its main potent metabolites. As presented below, the terpenoid profiles can be used in the classification of Cannabis chemovars (Fischedick, 2017) in addition to those of cannabinoids. The transcriptomics analysis of Cannabis trichomes has revealed that the plant is capable of synthesizing all of the known terpenes (Booth et al., 2017). In this study, transcripts that are associated with the biosynthesis of terpenes were found to be highly expressed in trichomes. Their biosynthesis is regulated by terpene synthases, which are organized in large gene families and their activity is spatially and temporally distributed, making them ideal targets for engineering (Tholl, 2006). Nonetheless, the biosynthetic pathway of terpenoids is highly complex, with recent studies highlighting the roles of novel genes that encode participating enzymes (Zager et al., 2019).

Terpenoids are highly potent metabolites, affecting the behavior of animals and even humans when inhaled at very low doses, and their synergy with cannabinoids has been proposed (Russo, 2011). Studies have highlighted the cornerstone role that cannabis mono- and sesquiterpenoids play in the potency of flower extracts and the "entourage effect" (Russo and Marcu, 2017). The in-depth understanding of the mechanism of the latter, although challenging, is highly

anticipated to provide information that could be further exploited in various applications (e.g., medicine R&D). However, comparative study between terpenoid-rich essential oils and CBD confirmed the superior bioactivity and medicinal properties of the latter (Gallily et al., 2018). Terpenoids exhibited a transient immunosuppression and lower bioactivity levels (e.g., ROS scavenging properties) than CBD. In addition to their contribution to the properties of Cannabis extracts, individual terpenoids could be exploited per se as bioactive molecules (e.g., friedelin, canniprene, cannabisin, cannflavin A) (Russo and Marcu, 2017). For example, cannabisin B, which is isolated from the hempseed hull, has been found to induce autophagy human hepatoblastoma HepG2 cells (Chen et al., 2013).

### CANNABINOMICS: APPLICATIONS OF METABOLOMICS IN CANNABIS (CANNABIS SATIVA L.) RESEARCH AND DEVELOPMENT (R&D) AND CURRENT STATE-OF-THE-ART

Nuclear magnetic resonance (NMR) spectroscopy (Smolinska et al., 2012; Nagana Gowda and Raftery, 2016; Markley et al., 2017) and mass spectrometry (MS)-based (Hu et al., 2005; Dettmer et al., 2007; Ramautar et al., 2009; Fuhrer and Zamboni, 2015) analyzers are the two major analytical platforms employed in metabolomics analyses. Nonetheless, the integration of information on the metabolite composition of a certain sample that has been acquired by employing various analytical platforms is highly recommended, especially in the case of cannabis-derived matrices, which have highly complex metabolomes, composed of metabolites with highly diverse physicochemical properties (**Figures 3**–**6**; Andre et al., 2016).

In addition to the routine deconvolution of the composition of Cannabis flower and oil samples, there is an increasing interest on the analyses of the cannabinoid and terpenoid contents of a large array of diverse matrices such as, among others, edibles, medicine, cosmetics, blood, and urine, for research, regulatory, and law enforcement purposes (Jain and Singh, 2016; Meng et al., 2018). For the large-scale isolation of cannabinoid and terpenoid fractions or individual metabolites, the supercritical fluid extraction (SFE) and solid phase extraction (SPE) are the main employed methods (Rovetto and Aieta, 2017; Gallo-Molina et al., 2019). Nonetheless, for analytical and bioanalytical purposes, various extraction protocols have been proposed, with solid-based (e.g., solid-phase microextraction, SPME) and solvent-based (e.g., dispersive liquid-liquid microextraction, DLLME) ones being the preferred (Jain and Singh, 2016; Pellati et al., 2018; Ramirez et al., 2019; Atapattu and Johnson, 2020). Focusing on Cannabis metabolomics, the choice of the extraction protocol depends on the analytical platform and the aim of a given study (**Table 1**); in NMR analyses, chloroform (CHCl3)-d, methanol (MeOH)-d4, or H2O-d<sup>2</sup> are the preferred solvents, ethanol (EtOH) for gas chromatographyflame ionization detector platform (GC/FID), MeOH for LC, and various solvents have been used in GC/MS-based studies. Further optimization of a given bioanalytical protocol (e.g., extraction, QC measures, analytical conditions, bioinformatics software) can lead to improved analytical capacities.

The capacity of NMR platforms in the recording of primary and secondary metabolites, and the integration of data acquired in various operating modes [e.g., proton NMR ( <sup>1</sup>H-NMR), <sup>13</sup>C-NMR, proton/proton correlation spectroscopy ( <sup>1</sup>H-1H-COSY), heteronuclear multiple quantum coherence (HMQC), heteronuclear multiple bond correlation (HMBC)] for the structure elucidation of complex metabolites, represent major advantages in Cannabis R&D (Choi et al., 2004). The lyophilization is an important step in the pipeline of NMR

analyses for the removal of water from the samples. NMR metabolomics has been applied in the classification and analyses of C. sativa L. plants and cell suspension cultures based on the recorded profiles of primary and secondary metabolites (Flores-Sanchez et al., 2012). In this study, following lyophilization, an indirect fractionation protocol was applied, which involves extraction of the dry plant material in a biphasic system (CHCl3- MeOH:H2O), evaporation of the extracts and finally dissolution in CHCl3-d or MeOH-d4:KH2PO4. A similar methodology has been applied in the study of the effects of jasmonic acid (JA) and pectin on two cell lines of Cannabis, which revealed a substantial impact of the treatments on the cells' metabolism (Pec et al., ˇ 2010). In a first step, extraction of the lyophilized material was performed using MeOH:H2O (1:1, v/v) or CDCl3, followed by evaporation and dissolution in CHCl3-d or MeOH-d4: H2O-d2.

In another study, the potential of diffusion-edited (1D DOSY) <sup>1</sup>H NMR metabolomics in the assessment and optimization of extraction protocols was investigated (Politi et al., 2008). The developed protocol enabled the recording of metabolite profiles of H2O and H2O:EtOH extracts that could be used to discover differences among cultivars and the effects of parameters, such as temperature and solvent polarity on the cannabinoid content of extracts. Furthermore, <sup>1</sup>H NMR, using deuterated dimethyl sulfoxide (DMSO-d6) as the extraction solvent, has a proven capacity and potential in the high-throughput discrimination between Cannabis chemovars, following chemotaxonomy approaches. Its integration with liquid chromatography-diode array detector (LC/DAD) analyses has enabled the discrimination among four chemovars based on their cannabinoid and phenolic contents (Peschel and Politi, 2015).

Cannabinoids can be analyzed by employing both GCand LC-based analyzers (Giese et al., 2015; Leghissa et al., 2018b). However, issues with their conversion under the high temperatures of the injection port of the former, make their absolute quantification tricky, and their analyses preferable by using LC-based analyzers. On the other hand, although terpenoids can be recorded by EI detectors, their structural similarities make their absolute identification challenging. Thus, GC/FID platforms are suitable for the analyses of terpenoid profiles (Giese et al., 2015; Leghissa et al., 2018b). Additionally, the linear range of the detector facilitates the recording of the wide range of terpene concentrations in Cannabis extracts. The aforementioned, make its employment important in the recording of terpenoid profiles and the assessment of the bioactivity and potency of the analyzed samples.

Furthermore, analyzers equipped with triple quadrupole (QQQ) detectors such as LC/QQQ/MS and GC/QQQ/MS systems, are very important in Cannabis research due to their superior selectivity and sensitivity in quantitative analyses (Leghissa et al., 2018b; Ramirez et al., 2019). The ability to operate these detectors in different modes such as, multiple reaction monitoring (MRM) or selected reaction monitoring (SRM), represents an advantage for Cannabis metabolomics. MRM is the most commonly employed method for the quantification and identification of metabolite features, owning its potential to the sensitivity, linear dynamic range, and specificity (Leghissa et al., 2018a). However, their performance declines during the analyses of large numbers of metabolites. Such disadvantage could be addressed by the employment of time-of-flight analyzers (ToF), which offer superior mass resolution and accuracy, facilitating fast scan speeds and enable the deconvolution of overlapping analytes (Beale et al., 2018). Furthermore, two-dimensional gas chromatography (GC × GC) systems could improve the separation of co-eluting metabolites (Mondello et al., 2008; Beale et al., 2018) and improve our capacities in deconvoluting complex Cannabis-derived matrices.

Interestingly, during the injection of cannabinoid-containing samples in GC-based systems, their acidic forms (e.g., THCA, CBDA, CBCA) entirely convert (decarboxylation) to their neutral products (e.g., 1<sup>9</sup> -THC, CBD, CBC) (**Figure 5**). This is probably the result of the high temperatures being applied in the injector, which commonly exceed 260◦C. Although EI coupled with GC/MS analyzers seems to be more efficient than APCI or ESI in cannabinoid analysis due to the improved fragmentation (Leghissa et al., 2018b), the observed conversions could possibly result in the recording of false-positives for 1<sup>9</sup> -THC, CBD, or CBC. This, in turn, jeopardizes analyses, posing serious risks toward the successful QC and the validity of research results. Such conversions can be avoided by appropriate silylation of the analyzed samples (Leghissa et al., 2018a) and further measures such as the use of isotopically-labeled standards, could greatly improve the accuracy of analyses.

For QC purposes, the implementation of different analyzers is required for the monitoring of metabolites across the various groups of Cannabis metabolites, which exhibit highly diverse physicochemical properties, making their detection and quantification challenging tasks. The employment of LC-diode array detector (LC-DAD) and GC/FID platforms have enabled the repeatable detection of cannabinoids and terpenes with low relative standard deviations (RSDs), using EtOH for extraction (Giese et al., 2015).

Additionally, high-resolution mass spectrometry (HRMS) [e.g., Fourier-transform ion cyclotron resonance (FT-ICR)-MS, Orbitrap analyzers] represents one of the latest developments in analytics. Commonly hyphened with LC, HRMS analyzers facilitate the coverage of a larger portion of the metabolite composition of the analyzed samples than that achieved by the conventional analyzers. Although optimization of the analytical conditions is required (e.g., binning, resolving powers), HRMS has a great potential in the chemotaxonomy of Cannabis chemovars and the assessment of the quality of Cannabis products (e.g., potency, authentication) (Wang et al., 2018).

#### Dissection of the Cannabinoid Biosynthesis by the Glandular Trichomes

Cannabinoids naturally occur in plants in the acidic form, with their corresponding decarboxylated analogs being the result of non-enzymatic catalyzed reactions during their storage or heating (**Figure 5**). The olivetolic acid cyclase (OAC, EC <IP_ADDRESS>) is a unique type III polyketide synthase (PKS) and key enzyme in the cannabinoid biosynthetic pathway (Morita et al., 2019) together with a tetraketide synthase (C. sativa TKS; CsTKS) (Taura et al., 2009). OAC is a dimeric α + β barrel (DABB)

protein, which exhibits structural similarities to polyketide cyclases of Streptomyces sp. (Gagne et al., 2012). Interestingly, it is the only known plant polyketide cyclase that can accept directly a linear poly-β-ketide intermediate, which is required for the biosynthesis of olivetolic acid (OA) (Marks et al., 2009; Gagne et al., 2012; Morita et al., 2019). The enzyme is overexpressed in the glandular trichomes (Gagne et al., 2012) and its structure has been recently studied (Yang et al., 2016). OA, in turn, forms the polyketide nucleus of cannabinoids (**Figure 5**). The precursor of cannabinoids hexanoyl-CoA, has been primarily detected in female Cannabis flowers by employing LC-MS/MS, with lower amounts recorded in the leaves, stems, and roots (Stout et al., 2012). Such pattern follows the accumulation of the end-products of cannabinoids. Hexanoyl-CoA can be synthesized via the de novo biosynthesis of fatty acids or the breakdown of lipids. Nonetheless, the potential of metabolomics in the dissection of PKS and the discovery of the functional links between the Cannabis genome, transcriptome, and metabolome is largely unexploited.

The plant has a variety of non-glandular and glandular trichomes on its flowers, which are the production sites of phytochemicals; the biosyntheses and accumulation of cannabinoids and essential oils take place in the glandular trichomes, where a terpene-rich resin is produced (**Figure 1E**). Three types of glandular trichomes occur in Cannabis; capitatestalked (**Figure 1E**), capitate-sessile, and bulbous trichomes. The development of the secretory cavities and the fine structure of trichomes have been thoroughly examined in the course of flowering by transmission electron microscopy (TEM) (Kim and Mahlberg, 1991) and scanning electron microscopy (SEM) (Happyana et al., 2013). There are two major groups of glandular trichomes, the first includes those with glands whose heads are composed of eight cells and the second, glands whose heads are usually composed of two cells, with a maximum of four (Dayanandan and Kaufman, 1976).

The superior capacity of metabolomics in the deconvolution of complex matrices is a major advantage in the study of the biosynthesis of cannabinoids by the glandular trichomes of the plant. <sup>1</sup>H NMR-based metabolomics combined with realtime PCR analyses have been employed in the study of the metabolite profiles of the trichomes of the C. sativa varieties Bediol, Bedica, Bedrobinol, and Bedrocan, during the last 4 weeks of their flowering (Happyana and Kayser, 2013). In the chloroform extracts, the cannabinoids 1<sup>9</sup> -THC, THCA, CBD, CBDA, and CBCA were identified, whereas in the water extracts, several amino acids, carbohydrates, and various other metabolites were detected. The similar fluctuations of the levels of cannabinoids with those of the corresponding encoding genes suggested a decline in the cannabinoid biosynthesis of the plant near the end of the flowering period. THCA and CBDA were discovered as the cannabinoids with the highest leverage in the observed fluctuation of the metabolite profiles of the trichomes. LC/QQQ/MS (solvent; MeOH) and NMR analyses (solvent; CHCl3-d) have also revealed the presence of several major as well as minor cannabinoids in the plant's trichomes, which further confirm their importance and role in their biosynthesis (Happyana et al., 2013). The employment of these two analyzers following the developed analytical protocols resulted in the detection of the acidic forms of the metabolites, with only minor quantities of their corresponding forms detected.

Such studies highlight the potential of metabolomics in the determination of the optimal time of harvesting of a given strain under specified conditions in order to improve the yield and quality of the obtained products.

# Chemotaxonomy of Varieties: Chemovars

The domestication of Cannabis and the, until recently, illegal status of its cultivation, have resulted in a vast number of genotypes, which exhibit largely unknown properties and genotypic and metabolic backgrounds (Mudge et al., 2018). Although from a botanical perspective, the conventional taxonomy classification system is relevant, focusing on Cannabis, the taxonomy of its strains based on their content in potent metabolites (e.g., cannabinoids, terpenoids) in the so-called chemovars, seems to be the most appropriate for R&D purposes. A data survey suggests that there has been a steady trend in favor of higher 1<sup>9</sup> -THC content in herbal and resin samples; from 13 to 23% in mid-2016, compared to 7–10% in 2009. That indicates a biased selection in favor of high potency chemovars of medicinal Cannabis (Dujourdy and Besacier, 2017). The differentiation between chemovars in their cannabinoid content is explained by the differences in the expression of genes that encode their biosyntheses (Van Bakel et al., 2011). To date, GC/FID platforms have been mainly employed in chemotaxonomy studies on Cannabis.

Cannabis strains are grouped in three types, Type I (high 1<sup>9</sup> -THC content), Type II (various 1<sup>9</sup> -THC to CBC ratios), and Type III (high CBD content) (Lewis et al., 2018). However, since additional Cannabis metabolites are bioactive, with a major group being the terpenoids, the classification of chemovars that takes into account the sum of its bioactive components has also been proposed (Hazekamp and Fischedick, 2012; Hazekamp et al., 2016; Fischedick, 2017), and probably best describes their properties.

Employing a GC/FID platform for the chemotaxonomy of high 1<sup>9</sup> -THC-producing Cannabis strains, and using MeOH as the extraction solvent (Fischedick, 2017), the application of multivariate analysis enabled their grouping into 13 chemovars based on their terpenoid profiles. GC/MS has been employed in the classification of C. sativa var sativa or C. sativa var indica strains based on their 1<sup>9</sup> -THC to CBD ratio (Hillig and Mahlberg, 2004). Samples were extracted in CHCl3, followed by evaporation of the extracts and finally, addition of acetone (Ace). Most chemovars with 1<sup>9</sup> -THC/CBD ratio greater than 25% were grouped as C. sativa var indica, while those with a ratio lower than 25% as C. sativa var sativa. Additionally, there was a high correlation between the content of chemovars in tetrahydrocannabivarin (THCV) and cannabidivarin (CBDV) and their grouping as C. sativa var indica.

Additionally, the terpenoid profiles can be used in the chemotaxonomy of the various Cannabis chemovars. Plants of diverse genetic backgrounds of C. sativa var sativa and

C. sativa var indica, can be discriminated based on the terpenoid profiles of their essential oils using a GC/FID platform (Hillig, 2004). Plant material was extracted in CHCl3, followed by extraction in Ace. Employing the same analyzer, Cannabis terpenoids and cannabinoids following the extraction of plant material with EtOH, were quantitatively analyzed for the classification of 11 strains into chemovars (Fischedick et al., 2010). The profiling based on 36 compounds was successful in discriminating the varieties applying multivariate analysis. Based on a similar bioanalytical protocol, employing LC-DAD and GC/FID analyzers, nine strains of commercial Cannabis were grouped in C. indica-dominant and C. sativa-dominant, based on their cannabinoid and terpenoid contents (Zager et al., 2019). The plant tissues were extracted using methyl tertbutyl ether and 1-octanol as the internal standard. Results of metabolite profiling were combined with results of RNA-seq for the transcriptome of the glandular trichomes. Interestingly, the study revealed similar patterns between the fluctuations of metabolite and transcript levels. Such observation confirms the applicability and potential of metabolomics in multi-level omics studies toward the understanding of the metabolism regulation, which is crucial in Cannabis research. A GC/FID analyzer and multivariate analysis were also employed in the discrimination of a large number of Cannabis flower samples and extracts into chemovars based on the analysis of their EtOH extracts (Elzinga et al., 2015). The analyzed strains exhibited variable reproducibility in the obtained metabolite profiles, with several terpenoids serving as biomarkers for the discrimination between the analyzed strains. Interestingly, it was also discovered that although quantitatively different, the chemical profiles of flowers and those of the extracts were qualitatively similar. Following a similar bioanalytical protocol using EtOH as the extraction solvent, 28 monoterpenoids, sesquiterpenoids, and cannabinoids were used for the classification of commercial Cannabis strains in various chemovars and the assessment of their quality (Hazekamp and Fischedick, 2012). The same research group has successfully analyzed 460 Cannabis accessions by GC/FID, aiming in their classification as "sativa" or "indica" based on their cannabinoid and terpenoid contents (Hazekamp et al., 2016). The extraction was performed using EtOH and 1 octanol served as the internal standard. The chemotaxonomy of Cannabis in chemovars based on their terpenoid profiles has also been performed by headspace GC/MS analysis, using MeOH (80%, v/v) for the extraction (Mudge et al., 2019). The applied protocol enabled the grouping of the analyzed strains in 33 chemovars, with their content in the sesquiterpene caryophyllene oxide to be strongly correlated with high 1<sup>9</sup> -THC content. LC hyphened to UV detectors has also been employed in the rapid grouping of strains in chemovars based on their content in major cannabinoids (Mudge et al., 2016).

# Cannabis as a Source of Novel and Unique Bioactive Compounds

There is no doubt that Cannabis with the chemical diversity, unique structures (**Figures 3**, **4**), physicochemical properties, and diverse bioactivities of its metabolites, represents an invaluable source for the development of novel applications in various sectors, such as, medicine, cosmetics, and the food industry. Although such applications are yet in their infancy, it is anticipated that Cannabis-based or Cannabis-infused products will provide solutions to major human health conditions, and lead to the development of new functional food and beverage products.

Nonetheless, the complexity of the plant's extracts and the in-depth understanding of interactions between their components (e.g., entourage effect) and synergism, represent major challenges. The development of pharmaceuticals based on Cannabis extracts is challenging for the medicinal research, which operates according to the principle "single compound-single target" (Hazekamp et al., 2016). However, the ineffectiveness of individual compound-based medicine against multigenic diseases (e.g., cancer) or diseases that affect multiple tissues dictate the need for the discovery of drugs that will act on multiple targets (Zimmermann et al., 2007; Giordano and Petrelli, 2008). Therefore, it is of paramount importance to distinguish between the bioactivities of mixtures and those of the individual bioactive metabolites based on appropriate protocols, which could be greatly assisted by high-throughput metabolomics. Examples of Cannabis-derived pharmaceuticals are displayed in the **Table 2**.

Within this context, the discovery, assessment, and development of new sources of bioactivity as drugs for the treatment of various conditions, represent key priorities for the

TABLE 2 | Examples of Cannabis-derived pharmaceuticals.

medicinal R&D (Chin et al., 2006; Dittrich and Manz, 2006; Harvey, 2008). Based on results of recent research, there is a growing amount of evidence that supports the effectiveness of various Cannabis-derived cannabinoids in the treatment of a wide range of conditions, including, among others, chronic and acute pain, epilepsy, sleep disorders, multiple sclerosis, gastrointestinal reflux disease, irritable bowel syndrome (IBS), spasticity, hypertension, and schizophrenia (Pacher et al., 2005; Hazekamp and Grotenhermen, 2010; Caraceni et al., 2014; Bruni et al., 2018).

The psychoactive and medicinal properties of Cannabis have been known for more than 5 millennia by major civilizations of the Middle East, Egypt, China, India, Ancient Greece, and the Romaine Empire (Di Marzo, 2008; Mechoulam and Parker, 2013; Farag and Kayser, 2015). Cannabinoids were the first identified group of potent Cannabis metabolites, with the medicinal properties of its major representatives being attributed to their interference with the G protein-coupled cannabinoid receptors (GPCRs) CB1 and CB2 of the endocannabinoid system (Di Marzo et al., 2004; Mechoulam and Parker, 2013). The CB1 receptors are amongst the most abundant GPCRs in the brain of mammals and are also present, to a lesser extent, in various peripheral organs, whereas the CB2 receptors have been identified throughout the central nervous system (CNS) and cells of the immune system, being part of a general protective system (Di Marzo et al., 2004; Di Marzo, 2008; Mechoulam and Parker, 2013) and modulating cytokine release (Pertwee, 2005).

Although 1<sup>9</sup> -THC was isolated and synthesized in the mid 60s' (Gaoni and Mechoulam, 1964; Mechoulam and Gaoni, 1965), the research on the mode(s)-of-action (MoA) of cannabinoids remained inconclusive for more than 20 years (Mechoulam and Parker, 2013). The similarities between the physicochemical properties and structures of cannabinoids (**Figure 3**), pose an obstacle toward their isolation in pure chemical form (Mechoulam and Hanuš, 2000) and the subsequent investigation of their bioactivities, MoA, and pharmacokinetics.

Furthermore, the cannabinoid interconversions during storage and heating are complex (**Figure 5**), which represents a major challenge for the development of new Cannabis-based products, such as drugs, cosmetics, beverages, and edibles. Additionally, of great interest is the fact that non-psychoactive Cannabis metabolites (e.g., terpenoids) can act synergistically with 1<sup>9</sup> -THC, contributing to the so-called "entourage effect" of medicinal Cannabis extracts (Ben-Shabat et al., 1998; Russo, 2011, 2018), with the undergoing operating mechanism(s) being largely unexplored.

Another major challenge for the Cannabis industry related to drug development is the production of standardized extracts that will meet the standards set by the corresponding regulatory agencies (e.g., Cannabis Act, Canada)<sup>1</sup> . The agricultural practices, plant growth conditions, and extraction processes all play key roles in achieving consistency of the extracts' content, however, discussion on those factors are beyond the aim of the present review. The robust QC of Cannabis preparations and assessment of their consistency and potency could be achieved by applying metabolomics for the various batches of a given product. The application of metabolomics employing and integrating information acquired by various analyzers (e.g., LC and GCbased platforms) could lead to the deconvolution of the complex chemical composition of Cannabis extracts and the monitoring of the consistency across batches, facilities, and different cultivation periods. For R&D purposes, metabolomics could be employed in the optimization of agricultural practices, growth conditions, and extraction processes in order to achieve the desired composition of extracts with proven medicinal properties, as discussed below. To the best to our knowledge, such approach is in its infancy, and no reports are currently available.

Cannabinoids exert palliative effects in cancer patients by, among others, preventing nausea and pain, and stimulating appetite (Guzman, 2003). Additionally, it has been shown that they inhibit the growth of tumor cells in vitro and in vivo in animal models (Guzman, 2003) and exhibit antitumor activity (Velasco et al., 2012; Dando et al., 2013). Such bioactivities have been supported by Phase III clinical trials, however, the corresponding mechanism(s) of action remain inconclusive. In the case of pancreatic adenocarcinoma it seems that cannabinoids induce autophagy and inhibit cell growth (Dando et al., 2013).

CBD, the second-most studied cannabinoid, and various of its synthetic derivatives have attracted the interest of the pharmaceutical industry and that of academic researchers, with specific focus on the understanding of their MoA, potency, and pharmacokinetics (Morales et al., 2017). It exhibits remarkable potency, including sedative, anxiolytic, anticonvulsive, hypnotic, anti-psychotic, anti-nausea, and antiinflammatory effects (Mechoulam et al., 2002). Preclinical studies have highlighted the inflammatory potential of CBD in mouse models (Morales et al., 2017), without causing behavioral changes (Viudez-Martínez et al., 2018). It exerts a well-documented anti-seizure and anti-epileptogenic properties against epilepsy independent of the CB1/CB2R, which is supported by Phase III clinical trials on treatment-resistant epilepsies (Rosenberg et al., 2017). Additionally, information on the action of 1<sup>9</sup> - THC containing Cannabis preparations in the treatment of pediatric epilepsies remains largely fragmented (Rosenberg et al., 2017). On the other hand, 1<sup>9</sup> -THC or synthetic cannabinoidinduced seizures in mice have been observed following their intraperitoneal administration, which can be prevented by a CB1-selective antagonist (Malyshevskaya et al., 2017).

In addition to the two major cannabinoids 1<sup>9</sup> -THC and CBD, other cannabinoids with limited or no psychoactive properties could exhibit interesting pharmaceutical properties and bioactivities.  Several cannabinoids (e.g., 1<sup>9</sup> -THC, CBD, CBC, CBG, CBN), exhibit antibiotic activity to Staphylococcus aureus, highly correlated to the stereochemistry of the molecules and the groups of substitution (Appendino et al., 2008).

Additionally, the biotransformation of cannabinoids in the human body, which determines their potency and medicinal properties, is a largely unexplored topic and could lead to the discovery of novel bioactive metabolites (Dinis-Oliveira,

<sup>1</sup>https://laws-lois.justice.gc.ca/PDF/C-24.5.pdf

2016). Due to their high lipophilicity, cannabinoids could remain in the plasma and fat tissue for prolonged periods. Focusing on the 1<sup>9</sup> -THC, in a first phase (Phase I, oxidative metabolism), it is metabolized to 11-hydroxy-1<sup>9</sup> -THC, which is further metabolized to the inactive 11-nor-9-carboxy-1<sup>9</sup> - THC. The Phase II (conjugation metabolism), includes reactions such as conjugation which lead to the detoxification of the molecule (Dinis-Oliveira, 2016). More than 80 1<sup>9</sup> -THC-derived metabolites have been identified as products of its transformation (Mazur et al., 2009).

The integration of information from clinical trials in which patients provide feedback following treatments with various Cannabis chemovars and information on the corresponding metabolite profiles employing metabolomics is very important for the selection of the best varieties and their standardization for medical use and drug discovery purposes. Based on this approach, applying GC/FID/MS metabolomics, Dutch researchers evaluated 460 accessions based on their content in major cannabinoids and terpenes (Hazekamp et al., 2016). Results revealed a strong correlation between Cannabis phenotypes and their terpene content, as it can be evaluated by their smell, taste, and medicinal properties, as well the importance of gibberellic acid (GAs) in terpenoid biosynthesis.

LC/ESI/MS-based metabolomics has been employed in the study of pharmacokinetics of major cannabinoids in rat brains, following their oral administration (Citti et al., 2018). Brains were initially homogenized in deionized H2O, followed by the addition of ACN:MeOH 70:30 (v/v) containing formic acid (0.1%, v/v). Following the removal of phospholipids, the extracts were dried and finally an ammonium acetate (2.0 mM):acetonitrile (70:30, v/v) solution was added. Analysis revealed the formation of novel, unique CBD-derived metabolites and fluctuations in the levels of several other endogenous metabolites as a result. Such application confirms the potential of metabolomics in the acquisition of fundamental knowledge related to the study of the mode(s)-of-action and bioactivity of cannabinoids for medical purposes.

The function of the endocannabinoid system and its regulation by endocannabinoids are complex, and yet relative information is largely fragmented. Their levels and relative composition vary depending and their role, which could shift from protective to deregulator of the physiological state of an individual. Therefore, compounds that could prolong the lifespan or suppress endocannabinoids could be extremely important in treating various conditions (Di Marzo, 2008).

#### Cannabis in the Food Industry: Exploring the Potential and Assessing the Associated Risks

Canada (Federal level) (Cox, 2018), the United States of America (Individual States) (Pacula and Smart, 2017), and Uruguay, have pioneered the legislation on Cannabis use for medicinal and recreational purposes. In contrast to the research on the plant as a source of bioactivity for applications in medicine as described above, the corresponding research on its use as a food ingredient is in its first steps (Charlebois et al., 2018). A wide variety of methods exist for consuming Cannabis edibles for medical purposes such as, concentrated oils, tinctures, and oil capsules, whereas from a recreational perspective, edibles could be considered cannabis-infused food products and beverages, with the latter being less popular (Blake and Nahtigal, 2019).

Food metabolomics, or foodomics, has established itself as a robust and precise bioanalytical tool in the assessment of quality and safety of raw materials and food products, as well as in the assessment and optimization of processing protocols and procedures (Wishart, 2008; Cevallos-Cevallos et al., 2009; Herrero et al., 2012; Castro-Puyana and Herrero, 2013). MSbased analytical platforms hyphened with various detectors and NMR have been employed in food research and also the routine QC of food products (Cevallos-Cevallos et al., 2009; Ibáñez et al., 2013). Food samples could be solid, semi-solid or liquid, and they are composed of a vast number of compounds such as, small molecular weight metabolites (e.g., amino acids, carbohydrates, carboxylic acids, fatty acids), proteins, and peptides, thus, generating very complex matrices. In the case of Cannabis, the presence of a large number of lipophilic cannabinoids and terpenoids, together with primary and secondary metabolites, results in one of the most challenging matrices to be analyzed (**Figure 6**). Therefore, the analyses of cannabis-infused food becomes extremely challenging, requiring the implementation and integration of advanced analyzers.

Nevertheless, the application of advanced metabolomics in the monitoring of the global metabolite profiles of Cannabisinfused edibles and beverages could provide valuable insights into the stability of cannabinoids and other Cannabis-derived metabolites in the food matrices, their fate and interconversions during processing, and possible toxicity issues. Additionally, it could reveal the links between their organoleptic and medicinal properties, and potency with their metabolite composition, that could be further exploited in drug discovery and the development of new food products. Nonetheless, the task of developing validated protocols for the analyses of a large array of Cannabis metabolites in food matrices is challenging, and currently, only a few relative studies have been published (Escrivá et al., 2017; Meng et al., 2018). Although THC-infused food could spark public and scientific controversy, the fact that CBD exhibits interesting bioactivities, while at the same time being nonpsychoactive, possibly makes it a promising candidate for the large-scale production of functional CBD-infused edibles or beverages. However, since research in the field in its first steps, the use of cannabinoids in food should undergo thorough research and assessment prior to the commercialization of related products.

#### Regulation of Cannabis Metabolism Toward the Optimization of the Yield and the Biosynthesis of Bioactive Products Effect of Light Conditions on Cannabis Growth: Phenotypes and Metabolomes

As it is the case with all plant species, the light regime is an important growth factor in Cannabis cultivation, being a fundamental component for the optimization of every successful

growth protocol. The intensity, quality, and duration of light are among the most important factors that regulate plants' physiology, development, and morphogenesis (Burgie et al., 2014; Galvão and Fankhauser, 2015; Krahmer et al., 2018). For the processing of the information relative to light regimes, plants are equipped with a series of photoreceptors capable of sensing a broad light spectrum (280–750 nm, UV-B to farred) that are present in all of their compartments (Kami et al., 2010; Galvão and Fankhauser, 2015). Based on research using Arabidopsis as the model organism, it has been discovered that the phytochromes A-E (PhyA-PhyE) are responsible for sensing the red (R) and the far-red (FR) light, three classes of photoreceptors were assigned as sensors of the UV-A/blue light, whereas data on UV-B were inconclusive (Kami et al., 2010). An early study on Cannabis, has indicated a linear increase in the 1<sup>9</sup> -THC content of leaves and flowers of medicinal chemovars with the UV-B irradiation level (Lydon et al., 1987). However, treatments had no effect on the levels of other cannabinoids in both the medicinal and industrial chemovars being studied.

In Cannabis research, among others, the in-depth understanding of its transition to the flowering stage is of great importance. Light as well as temperature, regulate the transition to the reproductive growth through their effects on the complex regulatory plant metabolic networks (Kami et al., 2010). Although evidence offers some understanding on the roles of phytochromes in plants' development and morphogenesis, information on the correlation between their function and the regulation of plants' primary and secondary metabolism is still largely fragmented. The acquisition of such knowledge represents a challenge but at the same time a great opportunity for Cannabis metabolomics. Furthermore, the recent developments related to the study of the effects of light on plants have been tremendous since the introduction of light-emitting diodes (LEDs), which are replacing the gas-discharge lamps. National Aeronautics and Space Administration (NASA) researchers discovered LEDs in their effort to grow plants in space (Stutte, 2015). LED technology enables a vast variety of light regimes to be applied on plants in order to regulate photosynthesis, morphogenesis, and growth according to our needs, with a low thermal energy output.

Experiments with tomato (Solanum lycopersicum L.) have shown that the blue and purple lights reduce photosynthesis, enhance the cyclic electron flow (CEF) and induce energy dissipation for photoprotection of the photosystems I and II (PSI and PSII, respectively) (Yang et al., 2018). The exposure of plants in different intensities of monochromatic red-LED affect their central metabolism and the size of the fruits produced (Fukushima et al., 2018). Additionally, LEDs have been reported to affect the reactive oxygen species (ROS) redox, antioxidant responses, and the in vitro regeneration of plants (Gupta and Agarwal, 2017).

The urge to improve Cannabis yield and quality has resulted in an exponentially increasing interest by the scientific community and the Cannabis industry on the study of the effects of LEDs on the plants' metabolism. The potential of LED lighting in the Cannabis sector has been recently reviewed (Lefsrud et al., 2019), in a review that confirms the lack of solid evidence on the effects of light on cannabinoid and terpenoid yields. Treatments of Cannabis plants with high-pressure sodium (HPS) and different LED types affected their morphology but had a minor impact on their cannabinoids yields (e.g., CBG, CBD, 1<sup>9</sup> -THC content), as revealed by the GC/FID analyses of the EtOH extracts (Magagnini et al., 2018). However, plants that were grown under LED light had improved 1<sup>9</sup> -THC and CBD concentrations. Additionally, the study concluded that the red to far-red light ratio had no substantial effect on flowering. Based on evidence that was acquired by another study, it has been concluded that different strains exhibiting high 1<sup>9</sup> -THC yield capacity are able to use high levels of photosynthetic photon flux densities (PPFDs). Such observation indicates that the chemovars being tested can be cultivated under high light intensity regimes outdoors or in the greenhouse, under controlled conditions (Chandra et al., 2015).

Nonetheless, although in the literature there is a handful of studies on the effects of environmental parameters (e.g., light, temperature) on the growth of Cannabis, there is only a few on the investigation of such effects applying metabolomics. Yet, their impact on Cannabis potency and global metabolism is largely unknown. Thus, it is highly expected that the employment of such tool could greatly assist toward the optimization and customization of growth parameters for the production of high quality and standardized products from the various Cannabis chemovars.

#### Cannabis Plant Protection and Interactions With Biotic and/or Abiotic Factors

Plant pathogenic fungi and pests affect the yield of Cannabis cultivations in the greenhouse and outdoors, resulting in devastating quantitative and qualitative losses (McPartland, 1996a,b). Therefore, the optimization of agricultural practices such as foliar or soil applications of registered PPPs (including bioelicitors and biological control agents), that could improve the plants' productivity and cannabinoid-biosynthetic capacity, and reduce the levels of xenobiotics in the final product (McPartland and McKernan, 2017), are of paramount importance. Such an endeavor could be accomplished through the comprehensive monitoring of plants' metabolism applying metabolomics, which has a great potential in PPPs' R&D (Aliferis and Chrysayi-Tokousbalides, 2011; Aliferis and Jabaji, 2011). Nevertheless, Cannabis producers, and especially those applying organic farming, currently lack information and guidance on the efficient application of such products (Sandler et al., 2019).

Although the primary MoA for most a.i. of PPPs is known, information on their secondary ones, if non-existent, is largely fragmented (Casida, 2009, 2010; Aliferis and Jabaji, 2011). Although fungicides and insecticides act on functions of the target-organisms that are vital for their survival, they additionally could impact the metabolism of plants (Lydon and Duke, 1989; Garcia et al., 2003; Petit et al., 2012), with the relative knowledge on the undergoing mechanisms being limited. Within this context, the study of the effects of registered PPPs for applications in Cannabis cultivation on its metabolism and potency could contribute to the optimization of the agricultural practice (frequency, time of application in relation to the plant's

vegetative stage, dosage) and the selection of the most efficient and safe products.

Of specific interest is the use of phytohormones and PGR, which is a group of PPPs that are integral parts of the agricultural practice for many crops. Phytohormones, in minute amounts, can substantially impact plant processes such as growth, dormancy, and flowering. Abscisic acid (ABA), is a phytohormone that plays a key role as a messenger-molecule by regulating plant responses to biotic and abiotic stimuli, including, among others, salinity, drought, heat, cold, and pathogen infections (Raghavendra et al., 2010). Its application to Cannabis at the flowering stage has shown to increase its 1<sup>9</sup> -THC content, however, it causes a decrease in its chlorophyll, steroid, and sterol contents (Mansouri et al., 2009b). Gibberellic acid (GA3), another major plant phytohormone, has shown to stimulate the biosynthesis of Cannabis terpenoids via the mevalonic acid biosynthetic pathway, but it inhibits the biosynthesis of those that are synthesized via the plastidial methylerythritol phosphate biosynthetic pathway (Mansouri et al., 2009a). Furthermore, in both sexes, GA3 application results in decreased levels of chlorophylls, carotenoids, and 1<sup>9</sup> - THC. The PGR ethephon, which is used in the agricultural practice to regulate plants' metabolism (e.g., promotion of fruit ripening, flower induction, initiation of reproductive development), has shown to greatly affect the plants' metabolite composition, including their 1<sup>9</sup> -THC, CBD, and terpenoid content (Mansouri et al., 2016). Although the study was inconclusive on the exact effect of the levels of ethephon on the global Cannabis metabolism, it highlighted the potential of this PGR toward the improvement of yield via the regulation of the plant's metabolism.

PGR are bioactive in very low concentrations and their bioactivity is highly correlated to factors such as the genotypes, the growth stage of the plants and their physiological condition, and environmental factors (e.g., humidity, light, temperature). Therefore, comprehensive studies are further required for the standardization of their applications in Cannabis cultivation and the determination of the optimal treatments (e.g., time, doses) under specified environmental conditions, in order to achieve optimum yield and quality.

In addition to the traditional PPPs and biological control agents, the group of endophytes is an alternative source of bioactivity for potential applications in plant protection. They are microorganisms that have developed a mutually beneficial symbiotic relationship with their host, living inside their organism, without causing symptoms (Porras-Alfaro and Bayman, 2011). Numerous Cannabis endophytes have been found to compose the Cannabis microbiome (Kusari et al., 2013; Scott et al., 2018). Such organisms could be used to increase the resistance of plants to pests and pathogens and possibly in order to modulate the biosynthesis of cannabinoids and other Cannabis potent metabolites such as the terpenoids (Gorelick and Bernstein, 2017).

#### Biomarker-Assisted Selection in Cannabis Breeding

Through millennia, Cannabis cultivation has spread worldwide, resulting in the generation of numerous landrace varieties (strains resulting from human and/or natural selection), and was amongst the first plant species to be domesticated (Clarke and Merlin, 2016; Rahn et al., 2016). The Cannabis gene pool has been significantly reduced due to the asexual propagation of strains exhibiting improved yields and potency, inbreeding, the lack of comprehensive germplasm collections (Clarke and Merlin, 2016), and the production of modern strains based on a limited genotypes (Rahn et al., 2016). This, in turn, has additionally resulted in the reduction of its chemical diversity (Mudge et al., 2016, 2018).

Nonetheless, the prohibition of Cannabis cultivation and the related research has created a large gap of knowledge on the genetics of the varieties and breeding for desired traits. Currently, a vast number of Cannabis strains exist, whose genotypic and metabolic backgrounds are largely unknown. The term "strain" refers to slight phenotypic differences and branding rather than distinct genotypic compositions. The above represent a bottleneck for Cannabis R&D toward the development of hybrids exhibiting improved fiber, seed, bioactive molecule-producing capacities, and/or improved resistance to pests and pathogens. There are numerous examples of strains susceptible to pest and pathogen infections, leading to severe yield losses (McPartland et al., 2000; Clarke and Merlin, 2016).

All the above underline the necessity for the comprehensive genetic and metabolic mapping of the existent Cannabis strains in order to unravel the relationships between sub-species, the similarities among strains and phenotypes, and to discover single or sets of metabolites-biomarkers that could be further exploited in Cannabis breeding programs following biomarker-assisted approaches. Furthermore, the recently introduced legislation on the cultivation of industrial and medicinal Cannabis in many countries necessitates the use of certified genetic material from a scientific and industrial perspective.

Within this context, metabolomics represents a bioanalytical tool of high potential that could greatly assist and complement the currently applied breeding tools (Taylor et al., 2002; Fernie and Schauer, 2009; Herrmann and Schauer, 2013). This task could be further assisted by the employment of QQQ detectors, which exhibit superior capacities in metabolite quantification and identification (see §3). Although a significant effort has been made toward the improvement of crops via breeding, its capacities in plants' selection for certain traits have been exploited only recently (Fernie and Schauer, 2009). Being the link between genotypes and phenotypes (Fiehn, 2002; Bino et al., 2004), metabolomics could greatly reduce the required time and the corresponding costs being an integrated component of plant-breeding programs (**Figure 7**). Focusing on Cannabis, its yield, potency, cannabinoid content, flowering, and resistance to pest and pathogen infections, are among the major traits of interest for breeding. In a recent metabolomics study (Mudge et al., 2018), it was shown that Cannabis domestication has resulted in an alteration of its metabolism involving the CBDA and THCA biosynthetic pathways. Additionally, the biomarker-assisted breeding could provide insights into attributes such as the "entourage effect," by breeding for traits related to cannabinoid and terpenoid contents (Grof, 2018).

### CONCLUSION

Cannabis is a species whose exploitation for applications in various fields has sparked great controversy. Nonetheless, there is a consensus that from a scientific perspective, the research on the plant could lead to significant advances for applications of extracts or individual metabolites in medicine, cosmetics, and the food industry. Currently, the recently introduced legislation on Cannabis in many countries around the world has enabled research on the plant and the vast array of its products. Cannabis matrices are extremely complex, requiring the implementation of advanced bioanalytical tools in order to gain meaningful insights into their bioactivity, medicinal properties, and risk assessment.

Based on its unique capacities and the developments in bioanalytics, is expected that metabolomics will greatly assist in impending Cannabis R&D contributing to the development of new, superior, efficient, and safe for the consumer, products. As a functional genomics tool, metabolomics could be ideally employed in the monitoring of cannabinoid and terpenoid profiles and their alterations in response to genotypic changes or agricultural treatments (e.g., fertilizers, bioelicitors, environmental conditions) and also in the biomarker-assisted selection of chemovars.

Additionally, the monitoring and comprehensive mapping of terpenoids could greatly assist the efforts toward understanding their synergy with cannabinoids. The modulation of the potency and medicinal properties of Cannabis extracts by their terpenoid content is largely unexplored. The acquisition of information on the effect of terpenoids on the medicinal properties of extracts could accelerate the discovery of novel drugs. The multistep engineering of the terpenoid biosynthetic pathway (Aharoni et al., 2005) and the generation of plants with knockout mutations via technologies such as the clustered regularly interspaced short palindromic repeats CRISPR (Ran et al., 2013) is feasible (Russo, 2018), and represents a great opportunity. Nonetheless, caution is required in applications of Cannabis for commercial purposes, which is expected to spark great controversy and face many regulatory hurdles.

Moreover, metabolomics is an invaluable tool that can be employed in the high-throughput chemotaxonomy or chemotyping of Cannabis strains into the corresponding chemovars based on their cannabinoid, terpenoid, and/or global metabolite profiles. Such classification is important not only for research but also for QC purposes. The correlation between Cannabis chemovars, their chemical composition, and their medicinal properties, is highly expected to accelerate drug discovery and development. From the current evidence, it is apparent that further experimentation is required for the development of Cannabis preparations or individual metabolites as drugs based on clinical trials (Soltesz et al., 2015), for which metabolomics should be an integrated component. Additionally, the employment and integration of advanced analyzers applying metabolomics is strongly expected to provide novel insights toward the understanding of the cannabinoid pharmacokinetics.

The comprehensive study of the effect of light on Cannabis metabolism and metabolite profiles could greatly contribute to the deconvolution of the underlying operating mechanisms that regulate the responses of plants to the various light regimes

and their potency. This is expected to add a critical mass of information that could be exploited in the optimization of the light conditions in order to regulate its development toward the achievement of, among others, higher yields, improved and customized potency, and early flowering. Furthermore, the research on the scaling-up of the production of rare cannabinoids, cannabis-derived bioactives, or their synthetic analogs through the metabolic engineering of microorganisms, could be substantially accelerated through the application of metabolomics.

Nonetheless, there is a need for further optimization and validation of the available bioanalytical protocols that could be implemented in the routine analyses of Cannabis matrices for QC but also for R&D purposes. The robustness of the GC-based platforms, which are the golden standard for metabolomics, faces the challenge of the heat-catalyzed conversions of several cannabinoids, which can be addressed by appropriate silylation protocols. Based on the limitations of the available instrumentation, there is not a single analyzer that could cover the remarkably diverse Cannabis metabolome. Additionally, the development of Cannabis-specific bioinformatics software and corresponding metabolite databases, would greatly contribute toward the development of metabolomics applications-Canabinomics in Cannabis-related research disciplines. To the

#### REFERENCES

best of our knowledge, the current is the first overview of the application of metabolomics in Cannabis R&D, which following the legalization of medicinal Cannabis, is highly foreseen to greatly assist Cannabis breeding and selection, being an unparalleled tool to link genotypes with phenotypes and potency, and predict traits based on modeling and machine learning.

#### AUTHOR CONTRIBUTIONS

KA and DB-P conceived the ideas and wrote the manuscript.

#### FUNDING

The work was supported by the Program of Graduate studies of the Agricultural University of Athens.

#### ACKNOWLEDGMENTS

We thank Ms. Hayley Clark for the editorial review of the manuscript.

eds S. Chandra, H. Lata and M. A. Elsohly (Cham: Springer), 79–100. doi: 10.1007/978-3-319-54564-6\_3

Aspects, ed. Á. Máthé (Dordrecht: Springer), 165–186. doi: 10.1007/978-94- 017-9810-5\_9

**Conflict of Interest:** The 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 handling Editor declared a shared affiliation, though no other collaboration with one of the authors KA.

Copyright © 2020 Aliferis and Bernard-Perron. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). 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.

# Propagation of Cannabis for Clinical Research: An Approach Towards a Modern Herbal Medicinal Products Development

#### Suman Chandra<sup>1</sup> , Hemant Lata<sup>1</sup> and Mahmoud A. ElSohly 1,2\*

<sup>1</sup> National Center for Natural Products Research, School of Pharmacy, University of Mississippi, Oxford, MS, United States, <sup>2</sup> Department of Pharmaceutics and Drug Delivery, School of Pharmacy, University of Mississippi, Oxford, MS, United States

Cannabis has been reported to contain over 560 different compounds, out of which 120 are cannabinoids. Among the cannabinoids, D<sup>9</sup> -tetrahydrocannabinol and cannabidiol are the two major compounds with very different pharmacological profile and a tremendous therapeutic potential. However, there are many challenges in bringing cannabis from grow-farms to pharmaceuticals. Among many, one important challenge is to maintain the supply chain of biomass, which is consistent in its cannabinoids profile. To maintain this process, male plants are removed from growing fields as they appear. Even with that practice, still there are fair chances of cross fertilization. Therefore, controlled indoor cultivation for screening, selection of high yielding female plants based on their cannabinoids profile, and their conservation and multiplication using vegetative propagation and/or micropropagation is a suitable path to ensure consistency in biomass material. In this chapter, the botany and propagation of elite cannabis varieties will be discussed.

#### Edited by:

Abraham J. Escobar-Gutie´rrez, Institut National de Recherche pour l'agriculture, l'alimentation et l'environnement (INRAE), France

#### Reviewed by:

Karel Dolezal, Academy of Sciences of the Czech Republic, Czechia Oliver Kayser, Technical University Dortmund, Germany

#### \*Correspondence:

Mahmoud A. ElSohly<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Crop and Product Physiology, a section of the journal Frontiers in Plant Science

> Received: 08 June 2019 Accepted: 10 June 2020 Published: 26 June 2020

#### Citation:

Chandra S, Lata H and ElSohly MA (2020) Propagation of Cannabis for Clinical Research: An Approach Towards a Modern Herbal Medicinal Products Development. Front. Plant Sci. 11:958. doi: 10.3389/fpls.2020.00958 Keywords: cannabis, micropropagation, vegetative propagation, tetrahydrocannabinol, cannabidiol

# INTRODUCTION

For thousands of years, cannabis is being cultivated to be used in day today need such as food, medicine, oil, textile fiber etc. The origin of this plant can be tracked back in China, wherefrom the plant made its way to the rest of the world.

Traditionally, the plant cannabis has been used to treat a wide variety of ailments such as asthma, epilepsy, fatigue, glaucoma, pain, and rheumatism (Mechoulam et al., 1976; Zuardi, 2006). Cannabis derivatives have also been reported to help in HIV/AIDS and multiple sclerosis (Pryce and Baker, 2005; Abrams et al., 2007). Cannabis sativa is the natural source of cannabinoids and D<sup>9</sup> -

Abbreviations: <sup>D</sup><sup>8</sup> -THC, D<sup>8</sup> -Tetrahydrocannabinol; D<sup>8</sup> -THCA, D<sup>8</sup> -Tetrahydrocannabinolic Acid; D<sup>9</sup> -THC, D<sup>9</sup> - Tetrahydrocannabinol; D<sup>9</sup> -THCA, D<sup>9</sup> -Tetrahydrocannabinolic Acid; CBC, Cannabichromene; CBCA, Cannabichromenic Acid; CBD, Cannabidiol; CBDA, Cannabidiolic Acid ; CBE, Cannabielsoin; CBEA, Cannabielsoinic acid; CBG, Cannabigerol; CBGA, Cannabigerolic acid; CBL, Cannabicyclol; CBLA, Cannabicyclolic acid; CBN, Cannabinol; CBNA, Cannabinolic acid; CBND, Cannabinodiol; CBT, Cannabitriol; DOXP, Deoxyxylulose phosphate; GOT, Geranyl diphosphate:olivetolate geranyltransferase; GPP, Geranyl diphosphate; NPP, Neryl diphosphate; OLA, Olivetolic acid; MEP, Methyl-erythritol phosphate; OLA, Olivetolic acid; PKS, Polyketide synthase.

Chandra et al. Propagation of Medical-Grade Cannabis

tetrahydrocannabinol (D<sup>9</sup> -THC) is the primary psychoactive agent. This compound is produced as an acid (D<sup>9</sup> tetrahydrocannabinolic acid, D<sup>9</sup> -THCA, Figure 1) in plant and undergoes decarboxylation with age or heating to form D<sup>9</sup> -THC. The other interesting compound in cannabis is cannabidiol (CBD, Figure 1), which is a non-psychoactive compound and reported to be useful in the treatment of seizures and epilepsy, specifically for the intractable pediatric epilepsy (Mechoulam and Carlini, 1978; Cunha et al., 1980).

Cannabis is also a big source of natural fiber. Earliest cultivation of hemp can be tracked back to the Neolothic Age in China, where it was mainly grown for ropes, paper, and textiles fiber. Nowadays, cannabis is used in making varieties of products such as composites, health foods, cosmetics, clothing, biofuels, and more (Small, 2015).

#### COMPLEX CHEMISTRY

The first compound that was isolated from cannabis was cannabinol (CBN, Wood et al., 1899). Its structure was determined much later in 1930s and 40s (Cahn, 1932; Adams et al., 1940a). CBD was isolated in 1940 and its molecular structure was elucidated in 1963 (Adams et al., 1940b; Mechoulam and Shvo, 1963). Whereas, isolation of D<sup>9</sup> -THC was reported in 1964 (Gaoni and Mechoulam, 1964). The number of compounds isolated from cannabis has been continually increasing. Most recent review shows the plant to be rich in secondary metabolites, with more than 560 constituents reported (ElSohly and Slade, 2005; ElSohly and Gul, 2014; Radwan et al., 2017). Out of which, 120 are cannabinoids those are distributed among more than ten

cannabidiolic acid (CBDA) and cannabidiol (CBD).

subclasses namely, D<sup>9</sup> -THC, D<sup>8</sup> -THC, CBD, CBG, CBN, CBND, CBE, CBL, CBT, and miscellaneous types.

A schematic diagram of the cannabinoids biosynthesis is shown in Figure 2. In the cannabis plant, cannabinoids are normally present in the acid forms such as THCA and CBDA (Shoyama et al., 1975; Fellermeier and Zenk, 1998) and turn in to neutral form after exposure to heat. The cannabinoids and their precursors are synthesized from two different pathways, the polyketide pathway (PKS) and the deoxyxylulose phosphate/ methyl-erythritol phosphate (DOXP/MEP) pathway (Shoyama et al., 1975; Fellermeier et al., 2001). Geranyl diphosphate (GPP) and olivetolic acid (OLA) are synthesized from the DOXP/MEP and PKS pathways, respectively. GPP and OLA in combination form cannabigerolic acid (CBGA) through geranyl diphosphate: olivetolate geranyltransferase (GOT, Fellermeier and Zenk, 1998). Cannabigerolic acid is common substrate for CBDA synthase (Taura et al., 2006), D<sup>9</sup> -THCA synthase (Taura et al., 1995) and CBCA synthase (Morimoto et al., 1998), which ultimately form cannabidiolic acid CBDA, D<sup>9</sup> -THCA and CBCA, respectively (Morimoto et al., 1999; Sirikantaramas et al., 2007).

#### CLASSIFICATION DEBATE

Based on the plant morphology, cannabis can be characterized in two distinct groups, drug type and fiber type. Fiber type varieties grow skinny and tall with very few branches whereas, drug type varieties grow bushy, form a Christmas tree like shape with big branches at the lower part of the stem (Figure 3).

Cannabis can be classified in different varieties/groups qualitatively and quantitatively based on the chemical profile content (Mondolino et al., 2003). The ratio of THC and CBD in the leaves and the flowers of the plant is generally used as a marker to classify cannabis varieties. According to Fetterman et al. (1971), varieties having high THC and low CBD (THC/CBD > 1) were characterized as drug type otherwise (THC/CBD < 1) fiber type variety. Whereas, Small and Beckstead (1973a; 1973b) distinguished C. sativa in three phenotypes with an additional class containing THC~CBD. Further, a separate class of cannabis phenotype with high CBG was characterized by Fournier et al. (1987).

Considering the botanical variations, taxonomists have described cannabis variously. A number of reports proposed cannabis as a polytypic [multiple-species, Hillig (2004; 2005), McPartland and Guy (2004) and Clarke and Merlin (2013)] whereas others suggest as a single genus, (monotypic) but highly polymorphic species, Cannabis sativa L. (Small, 1975a; Small, 1975b; Small and Cronquist, 1976; Small, 2015). Currently, cannabis is considered to belong to one genus and one single, highly diverse species, Cannabis sativa L.

#### BOTANICAL DRUG DEVELOPMENT APPROACHES

Plants have been used as a medicine in all cultures since millennia. To develop natural products as a single molecule

drug in modern medicine is costly and also, time consuming. Therefore, learning from traditional healthcare systems such as Ayurveda and Traditional Chinese Medicine (TCM), scientific focus is being directed to the development of botanical drugs (total plant extracts) used for the treatment of specific disease conditions. In this regard, US food and drug administration (FDA) has developed strict guidelines in 2006 for the development of "Botanical Drugs" products.

In the case of cannabis, variability in the botanical aspects translates into variability in the chemical makeup and the ratios of the different constituents for the different varieties. It follows that the pharmacological activities of the different varieties of cannabis must be different. Therefore, when one speaks about medicinal cannabis or medicinal cannabis preparations, it has to be chemically defined with specific therapeutic activity. In terms of the product development, any preparation of cannabis (plant material or extract) would be considered a botanical drug and must be fully characterized. Not only that the chemical makeup of the product would have to be defined, but one would have to show consistency in the chemical composition from one batch to the other. Furthermore, botanical drugs have to be approved for specific medical conditions through clinical trials. The most notable example of botanical drug from cannabis is Sativex®, also marketed with the name of nabiximols, developed by G.W. Pharma, which is a combination of THC and CBD extracts in equal ratio (1:1).

Another example is cannabis preparations sold by "Bedrocan", a Netherlands based cannabis company. In Netherlands, the company sells chemically characterized cannabis biomass (buds) to patients through pharmacies with a valid doctor's prescription. Whereas, these products are directly available in Canada (without prescription). Bedrocan has three high THC variety-based products namely Bedrocan®, Bedica ® and Bedrobinol®, one (Bediol®) from intermediate variety (THC~CBD) and one (Bedrolite®) from high CBD variety. All these products are well

FIGURE 3 | Representative cannabis varieties, (A) Drug type variety and (B) Fiber type variety.

characterized based on specific THC, CBD, and terpenes content. Although the company is certified in Europe, their products are not tested for specific disease conditions and not approved or accepted in the USA.

On the other hand, there are several formulations/drugs/ cannabis preparations/products on the market (available in different States of America and on the internet) claiming their use for curing several disease conditions without any scientific proof of clinically efficacy. Not following the requirements of a true botanical drug means that the patients basically do not know what they are getting, with the possibility of dangerous side effects and possible exacerbation of their medical condition.

Cannabis botanical formulations are considered by many as more effective than the individual cannabinoids citing the "entourage" effect as the reason (Ben-Shabat et al., 1998; Mechoulam and Hanus, 2000). That is, the contribution of other cannabis constituents, such as other cannabinoids, terpenes and flavonoids, provide synergetic effects with the major cannabinoid's activity. However, this assertion has been clinically proven.

#### REGULATORY ASPECTS OF CANNABIS CULTIVATION

The process of Plant based drug development face unusual challenges at every step from cultivation, harvesting, and processing to quality and consistency of biomass product. Cannabis in particular, faces a significant additional complexity due to being characterized as a schedule I drug.

In the United States, individual states have regulated cannabis through state legislation. Many states have legalized cannabis only for medicinal purposes but some of them have opened it for both medicinal and recreational uses. As this article is being written, 33 US states and DC have legalized cannabis for medical purposes and among them, 10 states and DC have opened it for both medical and recreational purposes. While cultivation of cannabis in these states is perfectly legal under the state laws, it is still illegal under the federal regulation. This creates an unusual situation for an authentic drug development. If a pure/botanical drug is developed under the federal regulation, it goes through a strict review by FDA. That covers all safety and efficacy issues of that product. However, medications/remedies under states legislations are bypassing all the FDA safety barriers.

#### CANNABIS: A DIOCEOUS PLANT

Cannabis is normally a dioecious plant. At the early (juvenile) stages of plant life cycle it is difficult, in fact impossible to discriminate morphologically between male and female plants. Some molecular techniques are reported to differentiate between male and female's plant at early growth stage (Sakamoto et al., 1995; Flachowsky et al., 2001; Törjé k et al., 2002; Sakamoto et al., 2005; Techen et al., 2010). These techniques however, have limited practical applications in case of a large-scale cultivation.

Cannabis is a wind pollinated species. If grown from seed, roughly 50% of the plants will be males and 50% females. To maintain consistency in cannabinoids profile and content in the final product (biomass or resin), cannabis cultivation is currently mostly carried out through vegetative propagation. The quality and quantity of biomass produced is highly variable due to the allogamous nature of the cannabis plant. To maximize cannabinoids production and to maintain consistency in cannabis biomass production female plants are preferred over male plants. Male plants release pollen grains that set seeds in female plants which affects cannabinoids production negatively. Further, if several varieties of cannabis are grown together through seeds, the final biomass product of those plants will not be consistent due to cross pollination. Therefore, male plants are removed from cultivation area as soon they appear to avoid cross fertilization. In modern cultivation practices, seed free (sinsemilla) cannabis plants are preferred for maximizing the production of phytocannabinoids.

### SCREENING AND SELECTION OF ELITE CLONES FOR MASS PROPAGATION

As stated above, Cannabis is chemically complex and a highly variable plant due to its cross-fertilization nature. Different varieties of cannabis plants contain a wide-range of cannabinoids and other chemical components ranging from hemp (low in THC, <0.3%) to highly potent drug type varieties with THC far exceeding 10% in some varieties. These levels are mostly determined by the plant genetics and influenced by several parameters such as growth environment, fertilization, harvesting time etc. (Valle et al., 1978; Hemphill et al., 1980; de Meijer et al., 1992; Pate, 1994; BóCsa et al., 1997; de Meijer et al., 2003; Chandra et al., 2008; Chandra et al., 2010; Mendoza et al., 2009). Variations in cannabinoids content among different plant parts have also been reported by Hemphill et al. (1980). For a pharmaceutical drug development, a stable source of biomass which is consistent in the production of secondary metabolite and a standardized growing protocol is of utmost importance. In case of cannabis, a batch to batch consistency in cannabinoids profile and content in particular, is very important for the development of a pharmaceutical or botanical drug. This can be achieved by selecting and germinating a desirable seed lot, removing male plants from growing area as they appear (since male flowers are morphologically different and appear earlier than female flowers, they are easy to recognize), making backup cuttings from female plants (kept in vegetative environment, 18 h photoperiod) and letting female plants flower (12 h photoperiod) up to maturity. Biomass sample from fully mature plants were then taken and tested for their cannabinoids profile and content. Based on cannabinoids analysis high yielding female mother plants are identified and their backup cuttings are used for the future cultivation. Monitoring cannabinoids content for genetic material selection could be carried out by one of several analytical methods such as GC-FID (Ross and ElSohly, 1995), HPLC (Gul et al., 2015), UPLC (Wang et al., 2018).

Once high potency mother plants are identified and selected based on their cannabinoids profile they are multiplied asexually, yielding identical clones using conventional (vegetative cutting) and/or biotechnological tools (tissue culture) to ensure a batch to batch consistency in the final product. A schematic diagram of screening and selection process of elite mother plants is shown in Figure 4.

# CANNABIS HORTICULTURE

# Plant Life Cycle in Nature

Cannabis is an annual plant. In nature, sprouting of seeds starts during early spring (March–April). Plants continue to grow vegetatively during long days. It starts flowering as days start becoming shorter and set seeds before the arrival of winter. Some auto-flowering varieties flower on their own rhythm, not depending on the photoperiod. During the flowering stage, big leaves start yellowing and start falling from plants. On maturity, flowers/inflorescence are eventually developed in the form of buds. The maturity of plants depends upon the variety and the geographical area. Some early maturing varieties are ready to harvest by August-September and others get ready during October-November. The male plants if not removed at early stage, normally die after setting their pollens. Buds are harvested for phytocannabinoids and seeds for future crop or for seed oil. Plants eventually die if not harvested. Cannabis crop can be easily grown indoor or outdoor.

#### Indoor Cultivation

Depending upon the choice, three to four cycles of crop can be produced indoor annually. Light (quality and quantity),

photoperiod, temperature, relative humidity, air circulation, and carbon dioxide level are the major environmental parameters that play an important role in cannabis cultivation. Under indoor climatic controlled conditions screened and selected high yielding female clones can be mass-propagated in soil or in liquid medium (Chandra et al., 2008; Chandra et al., 2015, Figure 5).

Vegetative Propagation For vegetative propagation (in soil or in soilless medium), a sturdy, fresh, and healthy stem cutting containing one or more nodal segments and leaves, is used. To maximize the surface area of the rooting space, a diagonal cut is made on stem below a node. Cuttings are then immediately placed in clean water to prevent formation of air bubbles in the stems. Rooting hormone (such as "Garden Safe", www.gardensafe.com, that contains 0.1% Indole-3-butyric acid, IBA) is applied to the base of cutting to promote rooting before planting in soil. Similarly, in hydroponics system 8–10-inch tall cuttings with one or more nodes are dipped in rooting hormone and wrapped by rock-wool or planted in hydrotone clay ball that serves as supporting medium. In both systems (soil or hydroponics) rooting initiates in 2–3 weeks. Eight-week old rooted plants are normally ready to be transplanted in bigger regular size pots.

To maintain vegetative growth plants are exposed to long photoperiods (normally > 12 h, preferably 18 or in some cases 24 h, Chandra et al., 2008; Chandra et al., 2015; Potter, 2015). Plants are supplied with vegetative fertilizer formula, comparably with higher nitrogen than flowering stage. Plants are exposed to a photoperiod <12 h to induce flowering. Once exposed to the flowering light cycle, plants start flowering within 10–15 days and ultimately form buds with highest cannabinoids content in overall plant life cycle (Chandra et al., 2008; Chandra et al., 2015). Depending on the variety, plants normally mature in 6 to 9 weeks. Length of vegetative growth period can be increased or decreased based on the plant growth and biomass yield/plant projected.

To achieve optimum growth and productivity, cannabis is best grown under (depending on genetics) 25 to 30°C growth temperature, high light intensity, and higher CO2 concentration (Chandra et al., 2008; Chandra et al., 2011a). Our studies show that cannabis exhibits higher rate of photosynthesis at high photosynthetic photon flux density (PPFD, ~1500 µmolm<sup>2</sup> s -1), which is typically sunny summer day in Mississippi (Chandra et al., 2008; Chandra et al., 2015). Further, about a 50% increase in the rate of photosynthesis was observed under doubling of CO2 concentration as compared to ambient CO2 concentration (Chandra et al., 2008; Chandra et al., 2011b). Higher humidity is generally ~60–75% is recommended at the young vegetative stage of plants whereas a lower range of 50 to 55% is recommended during the flowering stage.

Micropropagation Micropropagation has been used for decades for propagating plants of medicinal and agricultural value.  Limited work on micropropagation of Cannabis sativa has been done prior to last decade. In our laboratory at The University of Mississippi, efficient protocols for production of clonal plants of C. sativa have been developed using nodal segments as well as leaf discs (Figure 6, Lata et al., 2009a; Lata et al., 2009b; Chandra et al., 2010; Lata et al., 2010; Lata et al., 2016). The protocols developed would be helpful for large scale mass propagation of elite cannabis varieties and will allow the breeders saving time and resource in mass propagation of healthy and uniform cannabis plants.

### Outdoor Cultivation

Cannabis is an annual herb. It grows vegetatively during summertime due to long days and flowers during fall/winter with days turning shorter (Figure 7). If not harvested, plants go to senescence and eventually die. Cannabis can be grown by planting seeds directly in the ground, by planting them in biodegradable jiffy pots for germination and then planting the

FIGURE 6 | Micropropagation of Cannabis sativa L. (A, B) Formation of shoots, (C, D) Initiation of rooting, (E) Well acclimatized rooted plants in jiffy pots, and (F) Fully grown in vitro raised plants at vegetative stage.

FIGURE 7 | Outdoor cultivation of Cannabis sativa L.

seedlings in the ground or by planting rooted cuttings. A big disadvantage of growing from seeds is that half of the crop will be male plants. To avoid pollination and seed production, male plants are removed from the field which makes almost half of the field empty. To avoid this situation, rooted cuttings of screened and selected high yielding female plants are preferred for the production of biomass due for consistency of the cannabinoids profile.

Determination of plant maturity and optimum harvesting time is a crucial step of any crop. With cannabis, optimum harvesting time can be determined by visual observation and/or cannabinoids content analysis. Cannabinoids content increase with plant growth. With the onset of flowering, a tremendous increase in cannabinoids content is observed as compared to the vegetative stage. The plants are harvested at peak flowering stage, following one of two methods. In one of the methods, whole plants are harvested and processed, and in the second method, selected mature buds are harvested first and more time is given to lower branches to form buds to maximize the harvest.

Once harvested, branches are separated from the main stem and cut into small pieces before drying. Dried or dead leaves are removed before drying. Depending upon the harvest size, drying of biomass can be done either by hanging the whole plants or large branches upside down in a well ventilated barn until drying or using an industrial grade "forced-hot air dryers" (similar to tobacco processing) used for large scale drying.

Adequately dried biomass is stored at 18–20 °C for short term and at ≤-10 °C for long term storage in the dark to avoid oxidation. In a study, Trofin et al. (2012) have shown a steady decay of D<sup>9</sup> - THC content in cannabis biomass for up to four years stored at room temperature (~220 C). The decay in THC was reported more pronounced under light conditions as compared to that stored in the dark. Cannabis biomass for scientific investigations is used either as the processed plant material or is used as the starting material for the preparation of extracts.

#### DATA AVAILABILITY STATEMENT

The datasets generated for this study are available on request to the corresponding author.

#### REFERENCES

#### AUTHOR CONTRIBUTIONS

SC and HL wrote and ME reviewed the manuscript.

#### ACKNOWLEDGMENTS

This work was supported in part by the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), Department of Health and Human Services, USA, under contract no. N01DA-15-7793.

Potter, D. (2015). "Cannabis horticulture," in Handbook of Cannabis. Ed. R. G. Pertwee (U.K.: Oxford University Press), 64–88.

Conflict of Interest: The 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.

Copyright © 2020 Chandra, Lata and ElSohly. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). 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.

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