Biotechnological Approaches on Two High CBD and CBG Cannabis sativa L. (Cannabaceae) Varieties: In Vitro Regeneration and Phytochemical Consistency Evaluation of Micropropagated Plants Using Quantitative 1H-NMR

Plant antibacterials: The challenges and opportunities

Nature possesses an inexhaustible reservoir of agents that could serve as alternatives to combat the growing threat of antimicrobial resistance (AMR). While some of the most effective drugs for treating bacterial infections originate from natural sources, they have predominantly been derived from fungal and bacterial species. However, a substantial body of literature is available on the promising antibacterial properties of plant-derived compounds. In this comprehensive review, we address the major challenges associated with the discovery and development of plant-derived antimicrobial compounds, which have acted as obstacles preventing their clinical use. These challenges encompass limited sourcing, the risk of agent rediscovery, suboptimal drug metabolism, and pharmacokinetics (DMPK) properties, as well as a lack of knowledge regarding molecular targets and mechanisms of action, among other pertinent issues. Our review underscores the significance of these challenges and their implications in the quest for the discovery and development of effective plant-derived antimicrobial agents. Through a critical examination of the current state of research, we give valuable insights that will advance our understanding of these classes of compounds, offering potential solutions to the global crisis of AMR. © 2017 Elsevier Inc. All rights reserved.

Challenges and potentials of new breeding techniques in Cannabis sativa

Cannabis sativa L. is an ancient crop used for fiber and seed production and not least for its content of cannabinoids used for medicine and as an intoxicant drug. Due to the psychedelic effect of one of the compounds, tetrahydrocannabinol (THC), many countries had regulations or bands on Cannabis growing, also as fiber or seed crop. Recently, as many of these regulations are getting less tight, the interest for the many uses of this crop is increasing. Cannabis is dioecious and highly heterogenic, making traditional breeding costly and time consuming. Further, it might be difficult to introduce new traits without changing the cannabinoid profile. Genome editing using new breeding techniques might solve these problems. The successful use of genome editing requires sequence information on suitable target genes, a genome editing tool to be introduced into plant tissue and the ability to regenerate plants from transformed cells. This review summarizes the current status of Cannabis breeding, uncovers potentials and challenges of Cannabis in an era of new breeding techniques and finally suggests future focus areas that may help to improve our overall understanding of Cannabis and realize the potentials of the plant.

Use of near-infrared spectroscopy for the classification of medicinal cannabis cultivars and the prediction of their cannabinoid and terpene contents

Cannabis sativa L. is used to treat a wide variety of medical conditions, in light of its beneficial pharmacological properties of its cannabinoids and terpenes. At present, the quantitative chemical analysis of these active compounds is achieved through the use of laborious, expensive, and time-consuming technologies, such as high-pressure liquid-chromatography- photodiode arrays, mass spectrometer detectors (HPLC-PDA or MS), or gas chromatography-mass spectroscopy (GC-MS). Hence, we aimed to develop a simple, accurate, fast, and cheap technique for the quantification of major cannabinoids and terpenes using Fourier transform near infra-red spectroscopy (FT-NIRS). FT-NIRS was coupled with multivariate classification and regression models, namely partial least square-discriminant analysis (PLS-DA) and partial least squares regression (PLS-R) models. The PLS-DA model yielded an absolute major class separation (high-THC, high-CBD, hybrid, and high-CBG) and perfect class prediction. Using only three latent variables (LVs), the cross-validation and prediction model errors indicated a low probability of over-fitting the data. In addition, the PLS-DA model enabled the classification of chemovars with genetic-chemical similarities. The classification of high-THCA chemovars was more sensitive and more specific than the classifications of the remaining chemovars. The prediction of cannabinoid and terpene concentrations by PLS-R yielded 11 robust models with high predictive capabilities (R2CV and R2pred > 0.8, RPD >2.5 and RPIQ >3, RMSECV/RMSEC ratio <1.2) and additional 15 models whose performance was acceptable for initial screening purposes (R2CV > 0.7 and R2pred < 0.8, RPD >2 and RPIQ <3, 1.2 < RMSECV/RMSEC ratio <2). Our results confirm that there is sufficient information in the FT-NIRS to develop cannabinoid and terpene prediction models and major-cultivar classification models.

Evaluating Cannabis sativa L.'s neuroprotection potential: From bench to bedside

BACKGROUND

Neurodegenerative diseases and dementia pose a global health challenge in an aging population, exemplified by the increasing incidence and prevalence of its most common form, Alzheimer's disease. Although several approved treatments exist for Alzheimer's disease, they only afford transient symptomatic improvements and are not considered disease-modifying. The psychoactive properties of Cannabis sativa L. have been recognized for thousands of years and now with burgeoning access to medicinal formulations globally, research has turned to re-evaluate cannabis and its myriad phytochemicals as a potential treatment and adjunctive agent for neurodegenerative diseases.

PURPOSE

This review evaluated the neuroprotective potential of C. sativa's active constituents for potential therapeutic use in dementia and Alzheimer's disease, based on published studies demonstrating efficacy in experimental preclinical settings associated with neurodegeneration.

STUDY DESIGN

Relevant information on the neuroprotective potential of the C. sativa's phytoconstituents in preclinical studies (in vitro, in vivo) were included. The collated information on C. sativa's component bioactivity was organized for therapeutic applications against neurodegenerative diseases.

METHODS

The therapeutic use of C. sativa related to Alzheimer's disease relative to known phytocannabinoids and other phytochemical constituents were derived from online databases, including PubMed, Elsevier, The Plant List (TPL, www.theplantlist.org), Science Direct, as well as relevant information on the known pharmacological actions of the listed phytochemicals.

RESULTS

Numerous C. sativa -prevalent phytochemicals were evidenced in the body of literature as having efficacy in the treatment of neurodegenerative conditions exemplified by Alzheimer's disease. Several phytocannabinoids, terpenes and select flavonoids demonstrated neuroprotection through a myriad of cellular and molecular pathways, including cannabinoid receptor-mediated, antioxidant and direct anti-aggregatory actions against the pathological toxic hallmark protein in Alzheimer's disease, amyloid β.

CONCLUSIONS

These findings provide strong evidence for a role of cannabis constituents, individually or in combination, as potential neuroprotectants timely to the emergent use of medicinal cannabis as a novel treatment for neurodegenerative diseases. Future randomized and controlled clinical studies are required to substantiate the bioactivities of phytocannabinoids and terpenes and their likely synergies.

Multivariate classification of cannabis chemovars based on their terpene and cannabinoid profiles

Cannabis is used to treat various medical conditions, and lines are commonly classified according to their total concentrations of Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD). Based on their ratio of total THC to total CBD, cannabis cultivars are commonly classified into high-THC, high-CBD, and hybrid classes. While cultivars from the same class have similar compositions of major cannabinoids, their levels of other cannabinoids and their terpene compositions may differ substantially. Therefore, a more comprehensive and accurate classification of medicinal cannabis cultivars, based on a large number of cannabinoids and terpenes is needed. For this purpose, three different chemometric-based classification models were constructed using three sets of chemical profiles. We examined those models to determine which provides the most accurate "chemovar" classification. This was done by analyzing profiles of cannabinoids, terpenes, and the combination of these substances using the partial least square-discriminant analysis multivariate (PLS-DA) technique. The chemical profiles were selected from the three major classes of medicinal cannabis that are most commonly prescribed to patients in Israel: high-THC, high-cannabigerol (CBG), and hybrid. We studied the correlations between cannabinoids and terpenes to identify major bio-indicators representing the plant's terpene and cannabinoid content. All three PLS-DA models provided highly accurate classifications, utilizing six to nine latent variables with an overall accuracy ranging from 2 to 11% CV. The PLS-DA model applied to the combined cannabinoid-and-terpene profile did the best job of differentiating between the chemovars in terms of misclassification error, sensitivity, specificity, and accuracy. The combined cannabinoid-and-terpene PLS-DA profile had cross-validation and prediction misclassification errors of 4% and 0%, respectively. This is the first study to demonstrate the highly accurate classification of samples of medicinal cannabis based on their cannabinoid and terpene profiles, as compared to cannabinoid profiles alone. Furthermore, our correlation analysis indicated that 11 cannabinoids and terpenes might serve as bio-indicators for 32 different active compounds. These findings suggest that the use of multivariate statistics could assist in breeding studies and serve as a tool for minimizing the mislabeling of cannabis inflorescences.

Efficient In Vitro Sterilization and Propagation from Stem Segment Explants of Cnidoscolus aconitifolius (Mill.) I.M. Johnst, a Multipurpose Woody Plant

Cnidoscolus aconitifolius (Mill.) I.M. Johnst is a multipurpose woody plant. In this study, an in vitro efficient propagation system of stem segment explants derived from field-grown C. aconitifolius plants was established for the first time. The sterilization effect, axillary bud initiation, and proliferation efficiency of stem segments were evaluated. The results showed that the sterilization time of 0.1% mercuric chloride, the concentration of Plant Preservative Mixture (PPM), the pretreatment method, and the sampling season had significant effects on the sterilization of stem segments (p < 0.05). The type of medium and plant growth regulators (PGRs) affected the initiation of axillary buds, and the proliferation efficiency was significantly affected by PGRs. The results showed that the best sterilization method for stem segment explants was as follows: a pretreatment by rinsing with running water for 120 min, soaking in 75% ethanol for 50 s, soaking in 0.1% mercuric chloride for 10 min, and medium supplemented with 3 mL/L PPM. When inoculated on the medium in spring, the contamination rate was as low as 25.56%. The optimal initiation medium for axillary buds in stem segments was half-strength Murashige and Skoog (1/2 MS) medium supplemented with 0.5 mg/L 6-benzyladenine (6-BA). The induction rate was as high as 93.33%, and the mean length of axillary buds was 2.47 cm. The optimal proliferation medium was 1/2 MS medium supplemented with 4.0 mg/L 6-BA and 0.2 mg/L indole-3-butyric acid (IBA). The induction rate was up to 80.00%, the total proliferation coefficient was 4.56, and the net proliferation coefficient was 5.69. The 1/2 MS medium supplemented with 0.1 mg/L 6-BA and 1.5 mg/L indole-3-acetic acid (IAA) was most conducive to the elongation of the adventitious shoot, and the adventitious shoot of approximately 1 cm reached 1.93 cm after culturing for 14 days. The best medium for adventitious shoot rooting was 1/2 MS medium supplemented with 0.1 mg/L α-naphthalene acetic acid (NAA), the highest rooting rate was 82.00%, and the survival rate of transplanting was over 90%.

NMR Spectroscopy Applied to the Metabolic Analysis of Natural Extracts of Cannabis sativa

Cannabis sativa is a herbaceous multiple-use species commonly employed to produce fiber, oil, and medicine. It is now becoming popular for the high nutritional properties of its seed oil and for the pharmacological activity of its cannabinoid fraction in inflorescences. The present study aims to apply nuclear magnetic resonance (NMR) spectroscopy to provide useful qualitative and quantitative information on the chemical composition of seed and flower Cannabis extracts obtained by ultra-sound-assisted extraction, and to evaluate NMR as an alternative to the official procedure for the quantification of cannabinoids. The estimation of the optimal ω-6/ω-3 ratio from the 1H NMR spectrum for the seed extracts of the Futura 75 variety and the quantitative results from the 1H and 13C NMR spectra for the inflorescence extracts of the Tiborszallasi and Kompolti varieties demonstrate that NMR technology represents a good alternative to classical chromatography, supplying sufficiently precise, sensitive, rapid, and informative data without any sample pre-treatment. In addition, different extraction procedures were tested and evaluated to compare the elaboration of spectral data with the principal component analysis (PCA) statistical method and the quantitative NMR results: the extracts obtained with higher polarity solvents (acetone or ethanol) were poor in psychotropic agents (THC < LOD) but had an appreciable percentage of both cannabinoids and triacylgliceroles (TAGs). These bioactive-rich extracts could be used in the food and pharmaceutical industries, opening new pathways for the production of functional foods and supplements.

An Alternative In Vitro Propagation Protocol of Cannabis sativa L. (Cannabaceae) Presenting Efficient Rooting, for Commercial Production

An alternative in vitro propagation protocol for medical Cannabis sativa L. cultivars for pharmaceutical industrial use was established. The aim of the protocol was to reduce the culture time, offering healthy and aseptic propagating material, while making the whole process more economic for industrial use. The propagation procedure was performed using plastic autoclavable vented and non-vented vessels, containing porous rooting fine-milled sphagnum peat moss-based sponges, impregnated in ½ Murashige and Skoog liquid growth medium, supplemented with indole-3-butyric acid (IBA) at various concentrations (0, 2.46, 4.92, and 9.84 µM) or by dipping nodal cuttings into 15 mM IBA aqueous solution. The highest average root numbers per cutting, 9.47 and 7.79 for high cannabidiol (H_CBD) and high cannabigerol (H_CBG) varieties, respectively, were achieved by dipping the cuttings into IBA aqueous solution for 4 min and then placing them in non-vented vessels. The maximum average root length in H_CBD (1.54 cm) and H_CBG (0.88 cm) was ascertained using 2.46 μM filter sterilized IBA in non-vented vessels. Filter-sterilized IBA at concentrations of 2.46 μM in vented and 4.92 μM in non-vented vessels displayed the maximum average rooting percentages in H_CBD (100%) and H_CBG (95.83%), respectively. In both varieties, maximum growth was obtained in non-vented vessels, when the medium was supplemented with 4.92 μM filter-sterilized IBA. Significant interactions between variety and vessel type and variety and IBA treatments were observed in relation to rooting traits. Approximately 95% of plantlets were successfully established and acclimatized in field. This culture system can be used not only for propagating plant material at an industrial scale but also to enhance the preservation and conservation of Cannabis genetic material.

Direct Quantitation of Phytocannabinoids by One-Dimensional 1H qNMR and Two-Dimensional 1H-1H COSY qNMR in Complex Natural Mixtures

The widespread use of phytocannabinoids or cannabis extracts as ingredients in numerous types of products, in combination with the legal restrictions on THC content, has created a need for the development of new, rapid, and universal analytical methods for their quantitation that ideally could be applied without separation and standards. Based on previously described qNMR studies, we developed an expanded ¹H qNMR method and a novel 2D-COSY qNMR method for the rapid quantitation of ten major phytocannabinoids in cannabis plant extracts and cannabis-based products. The ¹H qNMR method was successfully developed for the quantitation of cannabidiol (CBD), cannabidiolic acid (CBDA), cannabinol (CBN), cannabichromene (CBC), cannabichromenic acid (CBCA), cannabigerol (CBG), cannabigerolic acid (CBGA), Δ9-tetrahydrocannabinol (Δ9-THC), Δ9-tetrahydrocannabinolic acid (Δ9-THCA), Δ8-tetrahydrocannabinol (Δ8-THC), cannabielsoin (CBE), and cannabidivarin (CBDV). Moreover, cannabidivarinic acid (CBDVA) and Δ9-tetrahydrocannabivarinic acid (Δ9-THCVA) can be distinguished from CBDA and Δ9-THCA respectively, while cannabigerovarin (CBGV) and Δ8-tetrahydrocannabivarin (Δ8-THCV) present the same ¹H-spectra as CBG and Δ8-THC, respectively. The COSY qNMR method was applied for the quantitation of CBD, CBDA, CBN, CBG/CBGA, and THC/THCA. The two methods were applied for the analysis of hemp plants; cannabis extracts; edible cannabis medium-chain triglycerides (MCT); and hemp seed oils and cosmetic products with cannabinoids. The ¹H-NMR method does not require the use of reference compounds, and it requires only a short time for analysis. However, complex extracts in ¹H-NMR may have a lot of signals, and quantitation with this method is often hampered by peak overlap, with 2D NMR providing a solution to this obstacle. The most important advantage of the COSY NMR quantitation method was the determination of the legality of cannabis plants, extracts, and edible oils based on their THC/THCA content, particularly in the cases of some samples for which the determination of THC/THCA content by ¹H qNMR was not feasible.

Anti-Microbial Activity of Phytocannabinoids and Endocannabinoids in the Light of Their Physiological and Pathophysiological Roles

Antibiotic resistance has become an increasing challenge in the treatment of various infectious diseases, especially those associated with biofilm formation on biotic and abiotic materials. There is an urgent need for new treatment protocols that can also target biofilm-embedded bacteria. Many secondary metabolites of plants possess anti-bacterial activities, and especially the phytocannabinoids of the Cannabis sativa L. varieties have reached a renaissance and attracted much attention for their anti-microbial and anti-biofilm activities at concentrations below the cytotoxic threshold on normal mammalian cells. Accordingly, many synthetic cannabinoids have been designed with the intention to increase the specificity and selectivity of the compounds. The structurally unrelated endocannabinoids have also been found to have anti-microbial and anti-biofilm activities. Recent data suggest for a mutual communication between the endocannabinoid system and the gut microbiota. The present review focuses on the anti-microbial activities of phytocannabinoids and endocannabinoids integrated with some selected issues of their many physiological and pharmacological activities.

Advances and Perspectives in Tissue Culture and Genetic Engineering of Cannabis

For a long time, Cannabis sativa has been used for therapeutic and industrial purposes. Due to its increasing demand in medicine, recreation, and industry, there is a dire need to apply new biotechnological tools to introduce new genotypes with desirable traits and enhanced secondary metabolite production. Micropropagation, conservation, cell suspension culture, hairy root culture, polyploidy manipulation, and Agrobacterium-mediated gene transformation have been studied and used in cannabis. However, some obstacles such as the low rate of transgenic plant regeneration and low efficiency of secondary metabolite production in hairy root culture and cell suspension culture have restricted the application of these approaches in cannabis. In the current review, in vitro culture and genetic engineering methods in cannabis along with other promising techniques such as morphogenic genes, new computational approaches, clustered regularly interspaced short palindromic repeats (CRISPR), CRISPR/Cas9-equipped Agrobacterium-mediated genome editing, and hairy root culture, that can help improve gene transformation and plant regeneration, as well as enhance secondary metabolite production, have been highlighted and discussed.

Synergizing Off-Target Predictions for In Silico Insights of CENH3 Knockout in Cannabis through CRISPR/Cas

The clustered regularly interspaced short palindromic repeats (CRISPR)/Cas-mediated genome editing system has recently been used for haploid production in plants. Haploid induction using the CRISPR/Cas system represents an attractive approach in cannabis, an economically important industrial, recreational, and medicinal plant. However, the CRISPR system requires the design of precise (on-target) single-guide RNA (sgRNA). Therefore, it is essential to predict off-target activity of the designed sgRNAs to avoid unexpected outcomes. The current study is aimed to assess the predictive ability of three machine learning (ML) algorithms (radial basis function (RBF), support vector machine (SVM), and random forest (RF)) alongside the ensemble-bagging (E-B) strategy by synergizing MIT and cutting frequency determination (CFD) scores to predict sgRNA off-target activity through in silico targeting a histone H3-like centromeric protein, HTR12, in cannabis. The RF algorithm exhibited the highest precision, recall, and F-measure compared to all the tested individual algorithms with values of 0.61, 0.64, and 0.62, respectively. We then used the RF algorithm as a meta-classifier for the E-B method, which led to an increased precision with an F-measure of 0.62 and 0.66, respectively. The E-B algorithm had the highest area under the precision recall curves (AUC-PRC; 0.74) and area under the receiver operating characteristic (ROC) curves (AUC-ROC; 0.71), displaying the success of using E-B as one of the common ensemble strategies. This study constitutes a foundational resource of utilizing ML models to predict gRNA off-target activities in cannabis.