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Data Note

In silico discovery of terpenoid metabolism in Cannabis sativa

[version 1; peer review: 2 approved, 1 approved with reservations]
PUBLISHED 06 Feb 2017
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This article is included in the Data: Use and Reuse collection.

Abstract

Due to their efficacy, cannabis based therapies are currently being prescribed for the treatment of many different medical conditions. Interestingly, treatments based on the use of cannabis flowers or their derivatives have been shown to be very effective, while therapies based on drugs containing THC alone lack therapeutic value and lead to increased side effects, likely resulting from the absence of other pivotal entourage compounds found in the Phyto-complex. Among these compounds are terpenoids, which are not produced exclusively by cannabis plants, so other plant species must share many of the enzymes involved in their metabolism. In the present work, 23,630 transcripts from the canSat3 reference transcriptome were scanned for evolutionarily conserved protein domains and annotated in accordance with their predicted molecular functions. A total of 215 evolutionarily conserved genes encoding enzymes presumably involved in terpenoid metabolism are described, together with their expression profiles in different cannabis plant tissues at different developmental stages. The resource presented here will aid future investigations on terpenoid metabolism in Cannabis sativa.

Keywords

terpenoid metabolism, cannabis sativa, in silico gene expression, evolutionarily conserved genes,

Introduction

Due to its astonishing efficacy1, nowadays cannabis is prescribed by physicians for the treatment of neurological, psychiatric, immunological, cardiovascular, gastrointestinal, and oncological conditions27. Although therapies based on the use of cannabis flowers or their derivatives are recognized to be very effective, treatments centered on drugs containing Δ9-tetrahydrocannabinol (THC) alone lack efficacy and lead to increased side effects8,9. This discrepancy seems to result from the absence of the synergistic effects of additional pivotal compounds found in the Phyto-complex, the so-called entourage effect10. Among these molecules are other cannabinoids and terpenoids, which are thought to play major roles in the modulation of THC11.

Terpenes are small hydrocarbon (isoprenoid) molecules classified as either as monoterpenes, sesquiterpenes, diterpenes or carotenoids, depending on the number of isoprene units (C5) used to synthetize them. Terpenoids are small lipids derived from terpenes, often accompanied by a strong odor useful for the plants to protect themselves against possible predators12. Terpenoids not only have important functions when working in concert with cannabinoids; they have been widely investigated in many different plant species and are being exploited as anti-fungal, anti-bacterial, anti-oxidant, anti-inflammatory, anti-stress, anti-cancer and analgesic agents1318. However, whilst the gene networks controlling the biosynthesis of cannabinoids and their precursors have been extensively studied1922, the biosynthetic pathway of terpenoid molecules in Cannabis sativa is only recently being elucidated. Only two genes have been characterized, one encoding (-)-limonene synthase, the other (+)-α-pinene synthase23, two enzymes responsible for the conversion of geranyl pyrophosphate into limonene and pinene, respectively24,25. Remarkably, while cannabinoids are only found in cannabis plants, terpenoids are also produced by a variety of other plant species, so they must share many of the enzymes involved in their metabolism.

In the present work, evolutionarily conserved genes encoding enzymes predicted to be involved in terpenoid metabolism have been identified within the transcripts of the canSat3 reference transcriptome of Cannabis sativa21. Moreover, by taking advantage of available gene expression data26, gene expression profiling of these enzymes was performed in cannabis plant tissue at different developmental stages. The data note presented here will provide researchers with a corollary of candidate genes that will considerably accelerate future investigations on terpenoid metabolism in Cannabis sativa.

Material and methods

Analysis of evolutionarily conserved transcripts

Cannabis sativa transcript sequences (n=23,630) taken from the canSat3 genome assembly (http://genome.ccbr.utoronto.ca/)21 were annotated with Blast2GO 4.0.727 using NCBI blastx and InterProScan databases. Terpene metabolism related genes were selected if found to be present in datasets downstream of the “terpene metabolic process” gene ontology category from the AmiGO 2 repository (GO:0042214), including the carotene metabolic process (GO:0016119), ent-kaurene metabolic process (GO:0033331), ent-pimara-8(14),15-diene metabolic process (GO:1901539), isoprene metabolic process (GO:0043611), miltiradiene metabolic process (GO:1901944), monoterpene metabolic process (GO:0043692), sesquarterpene metabolic process (GO:1903192), sesquiterpene metabolic process (GO:0051761), terpene biosynthetic process (GO:0046246), and terpene catabolic process (GO:0046247)28.

Gene expression analysis

Gene expression profiles from cannabis plant tissue at different developmental stages were downloaded from the NCBI GEO repository (https://www.ncbi.nlm.nih.gov/geo/). Gene expression heatmaps and unsupervised hierarchical clustering were performed with GENE-E 3.0.21329.

Results

Although the Cannabis sativa reference genome and transcriptome has been publicly released21, only a few genes have been characterized and surveyed for their molecular functions. To define the possible roles of these genes, 40,197 canSat3 transcript sequences were downloaded from the cannabis genome browser (http://genome.ccbr.utoronto.ca/), translated in silico, and scanned for evolutionarily conserved protein domains for functional annotation (Figure 1). To identify the genes presumably playing a role in terpenoid metabolism, annotated transcripts were filtered for gene ontology (GO) categories involved in terpene biosynthesis and catabolism using the AmiGO 2 reference database. A total of 288 transcripts representing 215 different genes were predicted to be involved in the metabolism of bisabolene, cadinene, carotene, copaene, ent-kaurene, farnesol, geraniol, germacrene, lycopene, limonene, myrcene, phytoene, pinene, squalene, and others (Supplementary table 1). Functional characterization of this subset confirmed an enrichment for GO categories involved in different terpene biosynthetic and catabolic processes (Figure 2).

0bb76123-f1b0-4cae-b2b8-c3595ee6c884_figure1.gif

Figure 1. Workflow analysis.

Schematic of bioinformatics pipeline utilized in this work. Cannabis sativa transcript sequences were taken from the canSat3 reference genome, functionally annotated with Blast2GO 4.0.7, filtered for terpenoid metabolism categories (AmiGO 2), and integrated with gene expression data downloaded from NCBI.

0bb76123-f1b0-4cae-b2b8-c3595ee6c884_figure2.gif

Figure 2. Gene ontology analysis of putative terpenoid metabolism related transcripts.

Functional enrichment analysis of putative terpenoid metabolism related transcripts taken from the canSat3 reference genome. Enrichment for terpene biosynthesis and catabolism is shown for Biological Process (A) and Molecular function (B) Gene ontology categories.

Terpenoids are produced by several plants species and in several types of plant tissue as defense against predators30. Similar to other biological compounds, their abundance directly correlates with the expression levels of the enzymes involved in their metabolism. To this end, gene expression analysis of genes likely to be involved in terpenoid metabolism was performed using previously published datasets (Figure 3; Supplementary table 2)26. Notably, unsupervised hierarchical clustering identified four gene clusters. Cluster 1 genes display high expression in roots and stems; cluster 3 genes in hemp flowers; cluster 4 genes in leaves and flowers. Cluster 2 genes were constitutively expressed in all tissues. These results highlight which enzymes are expressed by specific tissues and will provide a strong rationale for further investigations on the molecular basis of terpenoid metabolism.

0bb76123-f1b0-4cae-b2b8-c3595ee6c884_figure3.gif

Figure 3. Gene expression analysis of terpenoid metabolism related genes.

Heatmap showing relative expression values (log2 RPKM) of putative terpenoid metabolism related genes from cannabis plant tissue taken at different developmental stages (shoot, root, stem, young and mature leaf, early-, mid- and mature-stage flower). Five gene clusters were defined in accordance to unsupervised hierarchical clustering.

Discussion

The active principles inside plants have been exploited by humans for centuries, with Cannabis sativa being one of the oldest ever used for medicinal purposes31. Surprisingly, contrary to whole plant extracts, medicinal products containing exclusively THC have been found to lack efficacy and lead to unbearable side effects8,9. These results arise from the fact that these products lack other important co-factors typically found in the Phyto-complex, such as terpenoids and other cannabinoids10 that contribute to the synergistic effects seen with whole plant extracts.

While genes involved in cannabinoid biosynthesis have been widely investigated1922, the gene network controlling terpenoid metabolism is only recently being elucidated, with genes encoding (-)-limonene synthase and (+)-α-pinene synthase being the only two characterized23. To this end, Cannabis sativa transcripts21 have been scanned for evolutionarily conserved protein domains and annotated according to their presumptive molecular function. As a result, 215 evolutionarily conserved genes were predicted to be involved in terpenoid metabolism. Furthermore, in silico gene expression profiling26 of these enzymes in cannabis plant tissue at different developmental stages highlighted different gene clusters with peculiar expression patterns. For instance, cluster 3 genes (Figure 3) displayed high expression specifically in hemp flowers, which could be of great interest as different cannabis strains harbor different entourage effects.

Since the current cannabis reference transcriptome is still at preliminary stages21, it is very likely that false negatives have caused important transcripts to still be missing. For example, the two genes encoding for (-)-limonene synthase and (+)-α-pinene synthase23 align on the same transcript predicted to encode for Myrcene synthase (PK25781.1 in Supplementary table 1), and therefore cannot be discriminated. Unfortunately, to overcome this issue at whole genome level we need the complete version of the reference transcriptome to be available. Until that time, researchers are forced to validate single transcripts with classic low-throughput technology, such as molecular cloning followed by Sanger sequencing.

Nevertheless, the data presented here will ease future investigations on terpenoid metabolism in Cannabis sativa by providing researchers with a collection of candidate genes. For instance, one of these genes was predicted to encode for β-bisabolene synthase (PK05069.1 in Supplementary table 1). Bisabolene is being used as an antimicrobial agent32, as well as a biofuel33. However, prior to this report nothing was known about the gene network controlling its metabolism in Cannabis sativa. As soon as future studies will integrate gene expression data with chemical analysis, the complete molecular scenario underlying terpenoid metabolism will be revealed.

Data availability

Processed gene expression data can be found in the NCBI GEO repository (https://www.ncbi.nlm.nih.gov/geo/) with accession number GSE93201.

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Massimino L. In silico discovery of terpenoid metabolism in Cannabis sativa [version 1; peer review: 2 approved, 1 approved with reservations]. F1000Research 2017, 6:107 (https://doi.org/10.12688/f1000research.10778.1)
NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.
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Key to Reviewer Statuses VIEW
ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions
Version 1
VERSION 1
PUBLISHED 06 Feb 2017
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Reviewer Report 19 Jun 2017
Meirong Jia, Roy J. Carver Department of Biochemistry, Biophysics & Molecular Biology, Iowa State University, Ames, IA, USA 
Approved
VIEWS 15
The bioinformatics study here has reported 215 genes that are putatively involved in terpenoid biosynthesis in Cannabis sativa using available genome and transcriptome resources. This knowledge would predictably accelerate the terpenoid investigations in this specific species, or even broader. The ... Continue reading
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CITE
HOW TO CITE THIS REPORT
Jia M. Reviewer Report For: In silico discovery of terpenoid metabolism in Cannabis sativa [version 1; peer review: 2 approved, 1 approved with reservations]. F1000Research 2017, 6:107 (https://doi.org/10.5256/f1000research.11622.r23344)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
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Reviewer Report 09 Jun 2017
Jonathan E Page, Botany Department, University of British Columbia, Vancouver, BC, Canada 
Judith K. Booth, Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada 
Approved with Reservations
VIEWS 18
The present study is appropriate as a data note, and may provide a useful shortcut for future studies on terpenoid biosynthesis in cannabis. The author identifies transcripts putatively involved in terpenoid biosynthesis, including processes of both primary and specialized metabolism. ... Continue reading
CITE
CITE
HOW TO CITE THIS REPORT
Page JE and Booth JK. Reviewer Report For: In silico discovery of terpenoid metabolism in Cannabis sativa [version 1; peer review: 2 approved, 1 approved with reservations]. F1000Research 2017, 6:107 (https://doi.org/10.5256/f1000research.11622.r23373)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
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22
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Reviewer Report 10 Mar 2017
Akan Das, Department of Applied Biology, University of Science and Technology, Meghalaya (USTM), Ri-Bhoi, Meghalaya, India 
Approved
VIEWS 22
In the present work, 23,630 transcripts were scanned for evolutionarily conserved protein domains and annotated using Gene Ontology analysis. A total of 215 evolutionarily conserved genes encoding enzymes presumably involved in terpenoid metabolism are described on the basis of Gene ... Continue reading
CITE
CITE
HOW TO CITE THIS REPORT
Das A. Reviewer Report For: In silico discovery of terpenoid metabolism in Cannabis sativa [version 1; peer review: 2 approved, 1 approved with reservations]. F1000Research 2017, 6:107 (https://doi.org/10.5256/f1000research.11622.r19961)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.

Comments on this article Comments (0)

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Alongside their report, reviewers assign a status to the article:
Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions
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