Metabolic engineering of the Catharanthus roseus vincristine biosynthesis pathway into Nicotiana benthamiana

A master thesis by Kobus Bosman

2

Laboratory of Plant Physiology Wageningen University and Research Centre

Metabolic engineering of the Catharanthus roseus vincristine biosynthesis pathway into Nicotiana benthamiana

May – December 2011

Msc thesis report Biology (MBI) Wageningen University and Research Centre Course code: Master Thesis Plant Physiology (PPH-80430) Supervisors: Lemeng Dong and Sander van der Krol Laboratory of Plant Physiology

Kobus Bosman Student number: 890512109110 Marijkeweg 28 1D008 6709 PG Wageningen E-Mail: [email protected]

3

Preface

My choice of studying Biology was not a well-defined one. Somehow this field of study attracted me, although I could not pinpoint what exactly interested me most. As I progressed and got to choose my own courses, step by step my interests appeared to be in the field of cell biology. Not surprisingly, in August of 2010 I graduated on my BSc with the specialisation of Cell and Molecular Biology. I attended more courses in this field during my MSc, and soon I could define aspects of this field that appealed to me. To keep up my motivation and interest, I need to be working on a subject that is both topical as well as practical. By this I mean that the practical application of what I’m working on has to be obvious; that there’s a direct link between what I’m working on in the lab and what the outside world has to gain with my findings. I aimed to choose my master thesis accordingly, bringing me to the Wageningen Plant Physiology group. Here the research on antineoplastic drugs caught my interest, where people try to analyse how plants produce certain medicinally interesting compounds. Discovering these pathways itself is a very molecular line of work, but the practical application is just around the corner: if we understand the pathway to our compounds of interest, we may be able to engineer plants to produce these compounds at much larger quantities, eventually leading to cheaper medicine.

Summary

In this thesis an attempt was made to elucidate the biochemistry behind plant secondary metabolism, in particular that of monoterpene biosynthesis. From Catharanthus roseus, partners in the SmartCell consortium identified and extracted several genes expected to be involved in the biosynthesis pathway downstream of geraniol. These candidates are thought to slightly modify intermediate metabolites such as geraniol in a sequential matter, step-by-step ultimately leading to the antineoplastic compound vincristine. Through Agrobacterium tumefaciens transient assays and subsequent GC-MS and LC-MS an analysis was made on if and how these candidates can operate in an alternative production system, Nicotiana benthamiana. The results presented here indicate that the candidate enzymes indeed show activity in this system, albeit mostly on compounds endogenous to N. benthamiana. For the most part, the candidate genes seem to fail at the downstream processing of geraniol. Geraniol synthase (GES) and geraniol-10-hydroxylase (G10h) are suggested to possess a more elaborate enzymatic repertoire than previously considered. 10HGO-candidate 10HGO is thought to degrade these early metabolites rather than enhance their prevalence in the system, possibly explaining the inability to detect metabolites downstream of 10HGO. Follow-up studies should therefore consider excluding any 10HGO candidate from the series of infiltrations of candidate genes that are thought to act on intermediate metabolites downstream of 10HGO. Results indicate that increased prevalence of geraniol somehow favours the conversion into geranic acid. This is probably mediated by plant cell defence mechanisms in response to the potentially toxic geraniol, as geranic acid is more easily sequestered by glycosylation machinery. Phytol and especially squalene are shown to markedly increase in response to several gene combinations, but probably do not regulate each other directly. We demonstrate that plant secondary metabolism is currently far from understood and that many factors have to be considered when aiming to upregulate the production of desired secondary metabolites in plants.

4

Table of contents

Preface

Summary

Table of contents

1. Introduction 1.1 The vincristine pathway in C. roseus 1.2 Upregulating the production in C. roseus and heterologous systems 1.3 Cellular localisation 1.4 Subcellular localization 1.5 The SmartCell project 1.6 Research objective

2. Materials and methods 2.1 Cloning 2.2 Transient expression in leaves of Nicotiana benthamiana 2.3 Photographing leaf phenotypes 2.4 GC-MS analysis of extracts 2.5 LC-MS analysis of extracts 2.6 Analysis of GC-MS and LC-MS data

3. Results 3.1 Leaf phenotypes 3.2 GC-MS analysis of ATTA leaf extracts: products unrelated to the monoterpene pathway 3.3 GC-MS analysis of ATTA leaf extracts: products related to the monoterpene pathway 3.4 LC-MS analysis of ATTA leaf extracts: products related to the monoterpene pathway

4. Discussion 4.1 Candidate genes have an effect on endogenous compounds 4.2 Candidate activity on endogenous substrate is in some cases reduced when precursor enzymes are co-infiltrated 4.3 Fluctuations of other compounds in GC-MS as a measure of candidate gene activity 4.4 G10h-candidate B6 gene activity on pGES products 4.5 pGES products are downregulated by 10HGO and slightly upregulated by CR36-1 4.6 No confirmed identity of MTC, P450, LAMT or SLS activity, some detectable glycosyl- transferase acitivity 4.7 Boosting geraniol synthesis by precursor candidates 4.8 The effect of diluting the Agrobacterium tumefaciens 4.9 Phytol correlates with necrosis 4.10 Accumulation of squalene: potential causes and consequences

5. Conclusions and future implications

7. Acknowledgements

8. References

5

1. Introduction

1.1 The vincristine pathway in C. roseus

For as long as mankind walks the earth we have used plants as medicines to fight diseases. But it was not until recently that we try to elucidate what exactly causes the beneficial effect that some plants possess. For example the medicinal plant Catharanthus roseus (Madagascar periwinkle) has been used in traditional Chinese medicine to treat cancers like leukaemia and Hodgkin’s disease [1, 2]. The suspected antineoplastic compounds that are present in C. roseus have been identified as vinblastine and its chemical analogue vincristine. Although their roles in the plant are poorly characterized, they are suspected to be involved in plant defence against predators [3]. These useful medicinal compounds, however, are produced at a very low level in C. roseus leaves: 5.8 µg/g of fresh weight for vinblastine and only 0.9 µg/g for vincristine [4]. These low yields prevent efficient use of such specific chemicals as it makes the costs for isolating these compounds too high ($2900 per gram for vinblastine and $3200 per gram for vincristine [5]) for general usage.

Because these compounds are only found in C. roseus a lot of research has been done to elucidate their biosynthesis pathway in this evergreen herb. It is thought that not just one protein makes these metabolites, but that there is a whole pathway of sequential enzymatic reactions, each enzyme slightly modifying the intermediates. The indole (or ‘shikimate’) pathway provides the indole group, whereas the monoterpene pathway provides the secoiridoid. Combination of the products of these two pathways gives the first terpene indole alkaloid (TIA) in the TIA pathway, which is called strictosidine. Further processing of this metabolite eventually leads to vindoline and catharanthine, which in turn are combined to form the complex molecule vinblastine (Figure 1) [6].

Figure 1. The biosynthetic pathway towards vinblastine in C. roseus. Metabolites are given as full names in lowercase and enzymes as abbreviations in capitals. Full and dashed arrows mark single and multiple conversion steps between intermediates, respectively. The green square is the part of the pathway on which the thesis work focussed and is shown in more detail in Figure X. From Rischer et al. 2006 (modified).

6

As our knowledge of the enzymes involved in this biosynthetic pathway increases, attempts are made to manipulate the pathway in such a way that the yield of vinblastine and vincristine is increased. However, while elucidating the pathway, other intermediates were found that in itself are of interest for their biological activity. For example, it is now known how to upregulate geraniol production in endogenous and heterologous organisms, which is a compound often used in perfumes and is a key compound in many other monoterpene alkaloids [7].

1.2 Upregulating the production in C. roseus and heterologous systems

In C. roseus, efforts have been made to overexpress presumed bottleneck enzymes like G10H, increasing the accumulated amount of catharanthine [4]. Another approach is to investigate the promoters of genes that code for the enzymes involved in the biosynthesis of vinblastine and vincristine. Gregory Montiel and co-workers were able to confirm that overexpression of the transcription factor AtMYC2 increases the transcription of genes that are preceded by so-called octadecanoid-derivative response Catharanthus APETALA2-domain 3 (ORCA3) promoters [8]. Identifying exactly which genes of the vinblastine-synthetic pathway are monitored by the same family of promoters could provide us with a simple tool to upregulate the expression of all those genes by means of overexpressing only one transcription factor. However not all genes in our pathway are preceded by an ORCA3 promoter: other jasmonate-repsonsive transcription factors like ORCA2 as well as repressors ZCT1, ZCT2 and ZCT3 were shown to play a role in transcription-regulation [2, 9]. Next to this research in the organism where the desired compounds occur naturally, researchers focus their attention on expressing the compounds in heterologous systems; agricultural crops that possess a rapid accumulation of biomass at low costs such as Nicotiana benthamiana (tobacco) [10]. Eventually, elucidating the pathway and introducing it into a more efficient production platform will reduce production cost and speed.

1.3 Cellular localisation

Another field of study within the research on vinblastine/vincristine biosynthesis is the cellular and subcellular localisation of the enzymatic reactions and intermediate metabolites. As for the cellular localisation, it is suggested that several cell types play a role in the biosynthesis pathway. The methyl- erythritol pathway (MEP) which forms the precursor for monoterpene secoiridoid fabrication is executed in vascular cells, in so-called internal phloem parenchyma (IPAP) cells. The final product, geraniol, is converted to secologanin in a series of reactions of the monoterpene secoiridoid pathway. Somewhere along that sequence of reactions the product is moved into the leaf epidermal cells, of which loganic acid is the first product we know for sure to be in the epidermome. The second prerequisite pathway, the Shikimate pathway, is already performed in the leaf epidermis itself. The TIA pathway is further conducted in the epidermome, up until the common intermediate chathenamine. Here the pathway splits into two intermediates involved in vinblastine biosynthesis, being tabersonine and catharanthine. Catharanthine is stored in the wax of the leaf cell surface whereas tabersonine is further processed in mesophyll cells and the final product vindoline is stored in idioblasts and laticifers of the mesophyll cell layer (Figure 2) [3, 11, 12]. It is suggested that the presence of catharanthine on the leaf surface could be an important deterrent to insect herbivory. It might be that catharanthine is the main biological aim of this entire pathway and that storage of the vindoline is just a way of regulating the amount of vinblastine that is made. The plant might benefit from spatially separating these two compounds, as the fusion of these compounds inhibits cell division in Catharanthus as it does in cancer cells. Another hypothesis suggests that when the leaf is wounded, vindoline is released from the intra-epidermal compartments in which it is stored. This enables vindoline to fuse with catharanthine inside the intestinal tract of the herbivore, where it somehow causes the same hurtful effect as it would in planta if Catharanthus would not be able to separate these compounds.

7

Vinblastine

Figure 2. Model for biosynthesis and secretion of

secondary metabolites produced in the epidermis of C.

roseus leaves. From Roepke et al. 2010 (modified).

1.4 Subcellular localisation

Next to this cellular organization, also the subcellular organization is of importance. It is proposed that there is a distinct sequestration of the enzymes involved in the TIA pathway in epidermal cells (Figure 3). Not all separations are because of some kind of biological importance: some enzymes work in clusters like homo- or heterodimers or multimers, thereby simply inhibiting their passive diffusion into other compartments [3]. It is however likely that enzymes function more efficiently in certain environments, considering their charge, optimal alkalinity and availability of substrates and co-factors. The subcellular location of most enzymes can be predicted based on their amino acid sequence. Secologanin synthase (SLS) for example is anchored to the ER by a trans-membrane helix on one side of its sequence, ensuring its position in the pathway [3].

Figure 3. Spatial model depicting the subcellular organization of the strictosidine biosynthetic pathway in epidermal cell of C. roseus leaves. ‘?’ indicates the putative transportation system of tryptamine, secologanin and strictosidine across the tonoplast. The number of repetitions of each enzyme name indicates whether it has been identified as a homodimer (LAMT or TDC) or multimer (SGD). From Guirimand et al. 2011.

8

1.5 The SmartCell project

In 2009 an EU-funded project was started to develop new tools based on plant cells for the synthesis of valuable pharmaceutical molecules, called SmartCell. The project focuses on the terpenoid pathway, as this is the pathway from which many valuable pharmaceutical molecules are derived. The goal is to elucidate how exactly this pathway works. Although many of the genes in this pathway are already known, some are missing. The project tries to fill these gaps and tries to fully understand every aspect involved in terpene biosynthesis. The focus of this pathway is on the production of vinblastine and vincristine, which will probably lead to a more efficient and sustainable way of producing these compounds. This will eventually enable engineering of plant cells or plant production systems into producing desirable terpenoid molecules [13], lowering the prices of all kinds of plant-derived medicines.

1.6 Research objective

In this thesis, an attempt was made to fill the gaps in our knowledge (Figure 4, Figure 5). As work packages in the SmartCell project, several genes were supplied that were candidates for the hypothesised enzymatic conversions of intermediates that lead from geraniol towards secologanin (Table 1). Through transient expression and subsequent chemical profiling we tried to establish if any candidates work at all, which work the best and what are the possible side-effects of tempering with the metabolism of N. benthamiana. In addition, we tried to boost geraniol production. We looked at how geraniol synthase homologues of different species differ in their capability to regulate the production of geraniol and geraniol-derived compounds, and how that capability is affected by manipulating their subcellular localisation. We also tested two candidate precursors of geraniol synthase, geranyl diphosphate synthase, to see if we could boost production of geraniol and geraniol-derived compounds. Finally we also tested how geraniol precursor enzyme HMGR, which acts much further upstream in the pathway and is localised in the cytosol instead of in the chloroplast as is the case for GPPS, changes availability of geraniol synthase substrate in the chloroplast.

Table 1. The candidate genes and their hypothesised position in the pathway

Candidate name Candidate for:

B6 G10h

Cr68 10HGO

Cr36 10HGO

10HGO 10HGO

Cr36-1 10HGO

R4 MTC

R5 MTC

Cr05 (P450) Unknown 1, 2 and 3 and 7DLH

Cr45 (P450) Unknown 1, 2 and 3 and 7DLH

Cr53 (P450) Unknown 1, 2 and 3 and 7DLH

Cr81 (P450) Unknown 1, 2 and 3 and 7DLH

Cr182 (P450) Unknown 1, 2 and 3 and 7DLH

Cr329 (P450) Unknown 1, 2 and 3 and 7DLH

G4 DLGT

GT1 DLGT

GT3 DLGT

GT4 DLGT

Figure 4. The placement of candidate LAMT LAMT gene functions in the secologanin SLS SLS biosynthesis pathway as proposed in the Smartcell 30-month report (modified).

9

Figure 5. The downstream processing and placement of candidate enzymes as proposed in the Smartcell 30-month report (modified).

10

2. Materials and methods

2.1 Cloning

The candidate genes were supplied by Karel Miettinen from Leiden University: initially only four 10HGO candidates and two cyclase candidates. The two cyclase candidates (R4 and R5) and two of the 10HGO candidates (cr36 and cr68) were supplied in the binary vector pCambia1300 which is suitable for Agrobacterium transformation and subsequent transient expression in planta. However, two of the 10HGO candidates (cr36-1 and 10HGO(kelly)), supplied in vector pASK-IBA45plus, still needed cloning into a vector that accommodates them with a promoter and a polyadenylation signal before cloning into the binary vector. Here vector pRT101 was used, which contains the constitutive 35S promoter and the polyadenylation signal of Cauliflower Mosaic Virus (CaMV). Due to unclarity about by which means 10HGO candidates cr36-1 and 10HGO(kelly) were cloned into their pASK-IBA45plus vector, a PCR-based approach was chosen. Primers were designed to partly overlap the start and the end of the genes, with a few extra bases at the N-terminal end for the primers that anneal to the start and at the C-terminal end for the primers that anneal to the end. These extra bases constitute recognition sites for XhoI and EcoRI restriction enzymes, which are sites that are not found in the gene itself, and a few bases for the enzyme to ‘sit’ on. After primer extension by the high-fidelity Phusion™ DNA polymerase, the PCR product consists of the candidate gene with two unique external restriction sites. The PCR product as well as the pRT101 plasmid were simultaneously digested with EcoRI and XhoI, 10 units/µg for 2 hours at 37 ºC. The vector was dephosphorylated by alkaline-phosphatase to prevent re-ligation of the vector with the excised stretch of DNA. The digests were purified using the BioKé purification kit and ligated for 1 hour at room temperature by 5 units of T4 DNA ligase per µg of ligation mix with an insert/vector ratio of 3. Ligation products were purified and used to transform E.coli by means of heat shock to produce more available plasmids. Next, digestion enzymes were chosen so that they would excise the candidate genes with both a 35S promoter and a polyadenylation signal attached. The restriction enzymes were chosen so that they would only digest outside of the desired construct: HindIII for pRT101+cr36-1 and PstI for pRT101+10HGO(kelly), 300 units/µg for 1 hour at 37 ºC. Empty pCambia1300 vectors were simultaneously digested with these enzymes and dephosphorylated. Digests were purified from gel using the BioKé purification kit and ligated for 30 minutes at room temperature by 7 units of T4 DNA ligase per µg of ligation mix with an insert/vector ratio of 3. Ligation mixes were subsequently purified and electroporated into Agrobacterium tumefaciens of which the Ti-plasmid was disarmed of its T-DNA: this bacterium strain will still infect plant cells because it still possesses its virulence genes, but it will integrate the artificial T-DNA region of pCambia1300 into the plant cell genome. Electroporation was performed by adding 1 µl of 100 ng/µl plasmid solution to 50µl of thawed competent A. tumefaciens cells in a 2 mm cuvette and using an electroporation machine set at 2.5V, 250µF and 200Ω. Later on we were supplied with the remaining candidate genes, already in their binary pCambia1300 vector, which were used to infiltrate strains of A. tumefaciens as described above.

2.2 Transient expression in leaves of Nicotiana benthamiana

The following protocol was for the most part derived from the articles by Van Herpen et al. (2010) and Yang et al. (2011) [10, 14]. Agrobacterium tumefaciens strains were grown at 28ºC at 220 rpm for 24 hours in LB media with kanamycin (50 mg/L) and rifampicillin (34 mg/L). Cells were harvested by centrifugation for 20 min at 4000 g and 20ºC and then resuspended in 10 mM MES buffer containing 10 mM MgCl2 and 100 mM acetosyringone (49-hydroxy-39,59-dimethoxyacetophenone, Sigma). OD600 was set at 0.9 in the candidate experiments and to OD600 of 0.9 in the targeting experiment, followed by incubation on a roller-bank at room temperature for 150 minutes. For co-infiltration, equal volumes of the A. tumefaciens strains were mixed. To ensure equal concentrations and thus comparability between combinations, combinations with less unique candidate genes were supplemented with A. tumefaciens cultures containing the empty pCambia1300 vector. In all experiments, an A. tumefaciens strain harbouring a gene encoding the TBSV P19 protein was added to maximize protein production by suppression of gene silencing [15]. Nicotiana benthamiana plants were grown from seeds on soil in a greenhouse with 16 hours of light at 28ºC (16 h) / 25ºC (8 h). Strain mixtures were infiltrated into leaves of five-week-old N. benthamiana plants using a 1 mL syringe. The bacteria were slowly injected into the abaxial side of the leaf. The plants were grown under greenhouse conditions and harvested 10 days (candidates experiments) or 7 days (targeting experiments) after infiltration.

11

2.3 Photographing leaf phenotypes

Leaf phenotypes were observed and photographed after separating them from the plant and just before folding them into aluminium foil and snapfreezing in liquid nitrogen.

2.4 GC-MS analysis of extracts

The following protocol was for the most part derived from the articles by Van Herpen et al. (2010) and Yang et al. (2011) [10, 14]. Compounds accumulated in the leaves were analysed by snapfreezing and grinding 200 mg infiltrated leaf material from each replicate in liquid nitrogen and extracting with 1 mL citrate phosphate buffer, pH 5.4. The extracts were prepared by brief vortexing and sonication for 15 minutes. Then 200 µl of Viscozyme L (Sigma) was added and the sample was again vortexed. The mixture was incubated overnight at 37ºC, and subsequently extracted three times with 1 mL of ethyl acetate. The extracts were dehydrated by filtrating through anhydrous Na2SO4. The samples were analysed by GC-MS using a gas chromatograph (5890 series II, Hewlett-Packard) equipped with a 30 m x 0.25 mm, 0.25 mm film thickness column (5MS, Hewlett-Packard) and a mass-selective detector (model 5972A, Hewlett-Packard). For analysis, 1 µl was injected, and the column temperature was increased from 45ºC to 280ºC in 20 minutes.

2.5 LC-MS analysis of extracts

The following protocol was for the most part derived from the articles by Van Herpen et al. (2010) and Yang et al. (2011) [10, 14]. Non-volatile compounds were analysed using a protocol for untargeted metabolomics of plant tissues.[16] In brief, 100 mg of infiltrated leaf material from each plant was ground in liquid nitrogen and extracted with 300 µL methanol:formic acid (1000:1,v/v). The extracts were prepared by brief vortexing and sonication for 15 min. Then the extracts were centrifuged and filtered through 0.2 mm inorganic membrane filters (RC4, Sartorius, Germany). LC–PDA–MS analysis was performed using a Waters Alliance 2795 HPLC connected to a Waters 2996 PDA detector and subsequently a QTOF Ultima V4.00.00 mass spectrometer (Waters, MS technologies, UK) operating in negative ionization mode. The column used was an analytical column (2.0 mm x 150 mm; Phenomenex, USA) attached with a C18 pre-column (2.0 mm x 4 mm; Phenomenex, USA). Degassed eluent A (ultra- pure water:formic acid [1000:1,v/v]) and eluent B (acetonitrile:formic acid [1000:1,v/v]) were pumped at 0.19 mL min-1 into the HPLC system. The gradient started at 5% B and increased linearly to 35% B in 45 minutes. Then the column was washed and equilibrated for 15 minutes before the next injection. The injection volume was 5 µL. The MS–MS measurements were done with following collision energies of 10, 15, 25, 35 and 50 eV. Leucine enkaphalin ([M–H]-=554.2620) was used as a lock mass for on-line accurate mass correction.

2.6 Analysis of GC-MS and LC-MS data

The following protocol was for the most part derived from the articles by Van Herpen et al. (2010) and Yang et al. (2011) [10, 14]. GC–MS data were acquired using Xcalibur 1.4 (Thermo Electron Corporation) and LC–MS data using MassLynx 4.0 (Waters). The LC-MS data were first processed using MetAlign version 1.0 (www.metAlign.nl) for baseline correction, noise elimination and subsequent spectral data alignment.[16] Mass-directed LC-MS analysis was done on differential compounds with signal intensities higher than 200 ion counts per scan and lower than 100 ion counts in the empty vector controls.

12

2. Results

3.1 Leaf phenotypes

The A. tumefaciens strains containing the candidate genes listed in (Table 2) were used for agroinfiltration into the leafs of 5-week-old N. benthamiana plants, along with the P19 gene to maximize protein production by suppression of gene silencing [15]. Strains were mixed so that each unique gene represented one/fourteenth of the mixture: combinations of strains that consisted of less than 14 candidate genes were diluted using strains containing only the empty pCambia1300 vector. For the precursor enzyme candidate discovery experiments, a total of four different genes was used, so there the samples with less than 4 different genes were diluted with empty vector strains up to a one-fourth dilution. The leaves were harvested 10 days after infiltration, their phenotype photographed and snapfrozen in liquid nitrogen. The leaf material was used to extract samples for both gas chromatography as well as liquid chromatography and subsequent mass spectrometry.

Table 2. Candidate gene combinations and their effect on leaf necrosis and 4 fluctuating compounds as perceived in GC-MS analyses

Linolenic Candidate gene combinations Necrosis Phytol Squalene Unknown acid

Empty vector - - - - - pGES - - - ++ - pGES+B6 + ++ ++ - +

B6 ++ ++ ++ + ++ pGES+B6+Cr36-1 + ++ ++ - ++

Cr36-1 - - - ++ - pGES+B6+10HGO - + + - -

10HGO - + - ++ - pGES+B6+10HGO+R4 + + - - - pGES+B6+10HGO+R4+Cr05+Cr45+Cr53 ++ ++ + - +

Cr05+Cr45+Cr53 - + - + - pGES+B6+10HGO+R4+Cr81+Cr182+Cr329 + ++ ++ - +

Cr81+Cr182+Cr329 - - - + - pGES+B6+10HGO+R4+Cr05+Cr45+Cr53+G4+GT1+GT3+GT4 + + + + - pGES+B6+10HGO+R4+Cr81+Cr182+Cr329+G4+GT1+GT3+GT4 + + + + -

G4+GT1+GT3+GT4 - - - + - pGES+B6+10HGO+R4+Cr05 + ++ + - + pGES+B6+10HGO+R4+CR05+LAMT+SLS + + - + - pGES+B6+10HGO+R4+Cr05+Cr45+Cr53+G4+GT1+GT3+GT4+LAMT+SLS + + - - - pGES+B6+10HGO+R4+Cr81+Cr182+Cr329+G4+GT1+GT3+GT4+LAMT+SLS + + - - -

LAMT+SLS - - - ++ -

cGES - + - - - pGES - - - - -

IDS1+IDS2+cGES - - - - -

IDS1+IDS2+pGES - + ++ - ++

13

Wildtype Empty vector pGES

pGES+B6 B6 pGES+B6+Cr36-1

Cr36-1 pGES+B6+10HGO 10HGO

pGES+B6+10HGO+R4+ pGES+B6+10HGO+R4 Cr05+Cr45+Cr53 Cr05+CR45+CR53

14

pGES+B6+10HGO+R4+ pGES+B6+10HGO+R4+ Cr81+Cr182+Cr329 Cr05+Cr45+Cr53+ Cr81+Cr182+Cr329 G4+GT1+GT3+GT4

pGES+B6+10HGO+R4+ pGES+B6+10HGO+R4+ Cr81+Cr182+Cr329+ G4+GT1+GT3+GT4 Cr05 G4+GT1+GT3+GT4

pGES+B6+10HGO+R4+ pGES+B6+10HGO+R4+ pGES+B6+10HGO+R4+ Cr05+Cr45+Cr53+ Cr81+Cr182+Cr329+ CR05+LAMT+SLS G4+GT1+GT3+GT4+ G4+GT1+GT3+GT4+ LAMT+SLS LAMT+SLS

LAMT+SLS cGES pGES

15

Figure 6. The observed N. benthamiana leaf phenotypes of all treatments 10 days after

infiltration with OD600 0.9 A. tumefaciens strains. Only one representative leaf for each treatment is shown here. Note the difference in amount of infiltration attempts due to differences in user experience and leaf hydration.

IDS1+IDS2+cGES IDS1+IDS2+pGES

As shown in Figure 6, leaf phenotypes may differ between candidate combinations. Necrosis was mainly associated with the expression any combination with B6 and any combination that included the P450 candidates. It should be noted that the wildtype uninfiltrated leaf depicted here yielded ground leaf material of 2 to 4 times higher than that of infiltrated leaves, as was the case for the leaf surface area. Apparently, agroinfiltration is a procedure that is disruptive to the normal cell elongation of the leaf. This is probably due to stress caused by the invasive pathogen, but based on these experiments it cannot be excluded that the stress is caused by the physical damage of forcing a liquid into the leaf and or possibly osmotic stress of the infiltration medium.

Because of the large number of infiltrations, multiple people helped with the infiltration. This may also cause a difference in observed phenotypes, especially related to the amount of infiltration attempts required to fully infiltrate one leaf. From previous experiments we learned that if the plants had been watered several hours prior to infiltration it was much harder to infiltrate the leaf, which could also affect the amount of stress and thus observed necrosis. Although all but the B6-only leaves were infiltrated on the same day and using the same batch of plants, plants that were used for agroinfiltration later on in the afternoon had had time to dry and to become more receptive and may thus have experienced less stress. Therefore, the differences in leaf phenotype may not be directly related to the effect of the integrated gene.

3.2 GC-MS analysis of ATTA leaf extracts: products unrelated to the monoterpene pathway

After freezing the leaves in liquid nitrogen and weighing equal amounts of ground leaf material, GC- analysis was performed. Leaf samples were extracted, an internal standard was added to enable correction for differences in extraction efficiency and samples were deglycosylated by adding Visozyme L (Sigma-Aldrich). Peak heights were visually analysed, resulting in the identification of four peaks that greatly differed between combinations. Sadly, no consistent new large peaks could be observed in the samples infiltrated with the candidate genes. The compounds related to the two potentially interesting peaks were identified as squalene and phytol by comparing their fragmentation pattern to the library. Peak areas were integrated to approximate the total amount of these compounds in each of the samples. The results were corrected for the differences in internal standard yield from each of the extractions due to evaporation during extraction.

16

0 100000000 200000000 300000000 Wildtype Squalene EV pGES B6 pGES+B6 CR36-1 pGES+B6+CR361 10HGO pGES+B6+10HGO pGES+B6+10HGO+R4 CR05+CR45+CR53 pGES+B6+10HGO+R4+CR05 pGES+B6+10HGO+R4+CR05+CR45+CR53 CR81+CR182+CR329 pGES+B6+10HGO+R4+CR81+CR182+CR329 G4+GT1+GT3+GT4 pGES+B6+10HGO+R4+CR05+CR45+CR53+G4+GT1+GT3+GT4 pGES+B6+10HGO+R4+CR81+CR182+CR329+G4+GT1+GT3+GT4 LAMT+SLS pGES+B6+10HGO+R4+CR05+LAMT+SLS pGES+B6+10HGO+R4+CR05+CR45+CR53+G4+GT1+GT3+GT4+LAMT+SLS pGES+B6+10HGO+R4+CR81+CR182+CR329+G4+GT1+GT3+GT4+LAMT+SLS

Figure 7. Fluctuations of the squalene level as measured in GC-MS. Error bars indicate standard error.

0 10000000 20000000 30000000 40000000 Wildtype Phytol EV pGES B6 pGES+B6 CR36-1 pGES+B6+CR36-1 10HGO pGES+B6+10HGO pGES+B6+10HGO+R4 CR05+CR45+CR53 pGES+B6+10HGO+R4+CR05 pGES+B6+10HGO+R4+CR05+CR45+CR53 CR81+CR182+CR329 pGES+B6+10HGO+R4+CR81+CR182+CR329 G4+GT1+GT3+GT4 pGES+B6+10HGO+R4+CR05+CR45+CR53+G4+GT1+GT3+GT4 pGES+B6+10HGO+R4+CR81+CR182_CR329+G4+GT1+GT3+GT4 LAMT+SLS pGES+B6+10HGO+R4+CR05+LAMT+SLS pGES+B6+10HGO+R4+CR05+CR45+CR53+G4+GT1+GT3+GT4+LAMT+SLS pGES+B6+10HGO+R4+CR81+CR182+CR329+G4+GT1+GT3+GT4+LAMT+SLS

Figure 8. Fluctuations of the phytol level as measured in GC-MS. Error bars indicate standard error.

17

All samples, except for the B6-only sample, were infiltrated using the same batch of plants and analysed in one and the same GC-MS run. Combined results show that necrosis and squalene levels are associated with agroinfiltration of pGES+B6, raising the question whether it was B6 acting on geraniol or B6 acting on an endogenous compound that caused the stress response. Therefore, B6 was tested alone or in combination with pGES in a separate experiment. The levels of the four selected compounds in the B6- only were corrected for the differences in GES+B6 results of the two runs.

3.3 GC-MS analysis of ATTA leaf extracts: products related to the monoterpene pathway

Candidate gene activity on geraniol related products could only be traced as far downstream as B6. The production of geraniol, geranial and geranic acid was observed in the pGES-only samples, and its subsequent degradation by B6 in the pGES+B6 samples (Figure 9). Manual analysis of activity by candidate enzymes downstream of B6 using the library could not identify fluctuations of monoterpene- related products.

Figure 9. GC-MS spectrum analysis of empty vector, wildtype, pGES and pGES+B6 samples. Geraniol and geraniol-derivatives geranic acid and geranial are upregulated in pGES and degraded in pGES+B6.

Quite remarkably, we could detect a small amount of geranial. This is strange, since aldehyde groups cannot be glycosylated due to the double bond with the oxygen group, as opposed to a single bond in case of an alcohol or acid group. This could either mean that the extraction solvent or procedure as described earlier not only extracts the glycoside forms but also some volatiles, or that after deglycosylation a small part of the geraniol is spontaneously converted to geranial.

18

3.4 LC-MS analysis of ATTA leaf extracts: products related to the monoterpene pathway

LC-MS analysis revealed several compounds that were upregulated in pGES compared to the empty vector samples. Subsequent comparison with pGES+B6 samples showed that most of those compounds were again downregulated by B6. Other compounds were found to show increased prevalence in pGES+B6 samples. A large proportion of the upregulated masses found when comparing the B6-only samples with the empty vector samples were also found to be upregulated when comparing pGES+B6 with pGES. These masses were used to correct pGES+B6 for activity on endogenous compounds (Figure 10).

6000

5000

4000 3000 Empty vector

2000 pVoGES Mass intensity Mass 1000 pVoGES+B6 0

Figure 10. LC-MS analysis of pGES and pGES+B6 products. Several compounds are upregulated by pGES, which are subsequently downregulated by B6. pGES+B6 products were corrected for B6-only products.

Several of the masses demonstrated to have an increased intensity in pGES+B6 were found to get downregulated by 10HGO-candidate 10HGO but not by CR36-1 (Figure 11).

2000

1800

1600 EV 1400 VoGES

1200 CR36-1 1000 10HGO 800

Mass intensity Mass VoGES+B6 600 VoGES+B6+CR36-1 400 VoGES+B6+10HGO 200

0

531.2823 309.2032 559.3146 327.2200 721.3681 559.3149

Figure 11. LC-MS analysis of pGES+B6 products and subsequent degradations by 10HGO. All six depicted masses can be found in Figure 10.

19

4. Discussion

4.1 Candidate genes have an effect on endogenous compounds.

For most candidate genes control samples were included. These controls were used to verify which of the upregulated compounds are compounds specific to the geraniol pathway, and which compounds are products of candidate gene activity on endogenous substrates. Indeed we found enzyme activity in some of the controls as shown in Figure 12. This confirms that the genes were successfully transcribed and translated. On the other hand this calls for caution when interpreting data: stress caused by the products of candidate enzyme activity on endogenous substrates may cause the plant to re-route its metabolism in favour of basic processes needed for the stress response and survival, at the cost of secondary metabolism. Furthermore, the capacity of enzyme conversion rates may be limited: depending on enzyme specificity, endogenous substrates may be competing with the monoterpene substrates provided by the precursor (candidate) enzymes, resulting in a lower conversion rate of monoterpene substrates.

Ret(umin) Mass(uD)

- - EV_2 LAMT+SLS_1 16 LAMT+SLS_2 16 LAMT+SLS_3 16 - - EV_1 36522583 721367249

40691818 559314636

17570616 415212311

15277766 312123535

Ret(umin) Mass(uD)

- EV_2 Cr05+Cr45+Cr53_1 14 Cr05+Cr45+Cr53_2 14 Cr05+Cr45+Cr53_3 14 Cr81+Cr182+Cr329_1 15 Cr81+Cr182+Cr329_2 15 Cr81+Cr182+Cr329_3 15 - EV_1 25095934 523315491

24879717 477309143

22749500 769350952

24663500 477309052

Ret(umin) Mass(uD)

- EV_2 G4+GT1+GT3+GT4_1 18 G4+GT1+GT3+GT4_2-2 18 G4+GT1+GT3+GT4_3 18 - EV_1 16469784 569246643

21956083 1407614502

10656333 431157806

22678049 1245562134 24139866 1083517090

25439051 485241425

17570616 415212311

15277766 312123535

10350833 299079620 Figure 12. LC-MS analysis of several 19195066 730270874 candidate enzyme effects on endogenous N. benthamiana compounds. Relative 15964033 311114532 intensity from low to high is shown from 23092617 435096161 light green to dark green/red to light red, 22118717 419099823 respectively.

20

This is especially a problem for the P450 candidates as they participate in the biosynthesis of a wide variety of compounds, are part of a large gene family and may thus show homology to endogenous N. benthamiana P450’s [17]. In addition, unspecific activity of the glucosyl transferase candidates may sequester intermediate metabolites and render them inaccessible to other candidate genes.

4.2 Candidate activity on endogenous substrate is in some cases reduced when precursor enzymes are co-infiltrated.

Not all, but some of the compounds that are upregulated by candidate gene activity on endogenous compounds are less (CR05+CR45+CR53) or not (G4+GT1+GT3+GT4 and LAMT+SLS) upregulated when the candidate genes are co-infiltrated with their preceding candidate genes (Figure 13). This indicates a potential competition between endogenous substrates on the one hand and geraniol-related compounds supplied by the preceding enzymes on the other hand. The notion that the preference of the candidate enzyme is towards its ‘real’ substrate may be explained because the supplied geraniol-related compounds are more abundant than the endogenous substrate, and that they are possibly more compatible with the active part of the enzyme than the endogenous substrate.

Ret(umin) Mass(uD)

- EV_2 - pGES+B6+10HGO+R4+Cr05+Cr45+Cr53+G4+GT1+GT3+GT4_1 17 pGES+B6+10HGO+R4+Cr05+Cr45+Cr53+G4+GT1+GT3+GT4_2 17 pGES+B6+10HGO+R4+Cr05+Cr45+Cr53+G4+GT1+GT3+GT4_3 17 G4+GT1+GT3+GT4_1 18 G4+GT1+GT3+GT4_2-2 18 G4+GT1+GT3+GT4_3 18 pGES+B6+10HGO+R4+Cr81+Cr182+Cr329+G4+GT1+GT3+GT4_1 18 pGES+B6+10HGO+R4+Cr81+Cr182+Cr329+G4+GT1+GT3+GT4_2 18 pGES+B6+10HGO+R4+Cr81+Cr182+Cr329+G4+GT1+GT3+GT4_3 18 - EV_1 - 16469784 569246643

25439051 485241425

17570616 415212311 15277766 312123535

Ret(umin) Mass(uD)

- EV_2 - LAMT+SLS_1 16 LAMT+SLS_2 16 LAMT+SLS_3 16 pGES+B6+10HGO+R4+Cr05+Cr45+Cr53+G4+GT1+GT3+GT4+LAMT+SLS_1 19 pGES+B6+10HGO+R4+Cr05+Cr45+Cr53+G4+GT1+GT3+GT4+LAMT+SLS_2 19 pGES+B6+10HGO+R4+Cr05+Cr45+Cr53+G4+GT1+GT3+GT4+LAMT+SLS_3 19 pGES+B6+10HGO+R4+Cr81+Cr182+Cr329+G4+GT1+GT3+GT4+LAMT+SLS_1 20 pGES+B6+10HGO+R4+Cr81+Cr182+Cr329+G4+GT1+GT3+GT4+LAMT+SLS_2 20 pGES+B6+10HGO+R4+Cr81+Cr182+Cr329+G4+GT1+GT3+GT4+LAMT+SLS_3 20 EV_1 - 17570616 415212311

15277766 312123535

Ret(umin) Mass(uD)

Figure 13. LC-MS analysis demonstrating

- EV_2 GES+B6+10HGO+R4+Cr05+Cr45+Cr53_2 11 pGES+B6+10HGO+R4+Cr05+Cr45+Cr53_1 11 pGES+B6+10HGO+R4+Cr05+Cr45+Cr53_3 11 Cr05+Cr45+Cr53_1 14 Cr05+Cr45+Cr53_2 14 Cr05+Cr45+Cr53_3 14 - EV_1 that co-infiltration of precursor candidates 25095934 523315491 reduces candidate activity on endogenous

24879717 477309143 substrates. Relative intensity from low to

22749500 769350952 high is shown from light green to dark

green/red to light red, respectively. 24663500 477309052

21

It should be noted however that not all compounds that are upregulated by enzyme activity on endogenous substrates are back to low levels after co-infiltration with the preceding gene. This could either indicate that in these cases the capacity of the enzyme is not maxed out by supplying the geraniol-related substrate, or that some of the endogenous substrate has more affinity with the enzyme than the geraniol-related substrate and may thus outcompete this geraniol-related substrate. The first scenario is less of a problem, since in that scenario most or all of the supplied geraniol-related product can be converted; the second scenario is more of a problem when aiming to upregulate production of the geraniol-related product of the candidate enzyme.

4.3 Fluctuations of other compounds in GC-MS as a measure of candidate gene activity

Although our GC-MS measurements could not detect any new compounds after administering the candidate genes, we could detect the fluctuation of several other compounds of which only squalene and phytol are shown in the results. When the results of squalene quantification are ordered in groups of infiltrations without B6, infiltrations with B6 without 10HGO and infiltrations with B6 with 10HGO, it seems like squalene is induced by B6 activity and that 10HGO acts on the compound that results in the induction of squalene. The product of B6 activity is coming from activity on endogenous compounds as B6 alone is sufficient to induce the accumulation of squalene. The product of B6 could be involved in inhibiting the conversion of squalene further downstream into steroid alkaloids such as cholesterol. This blocking of squalene epoxidase has been described as a mode of action for several antifungal agents as squalene is the precursor to ergosterol, a compound found in the cell membranes of fungi but not in those of animals [18]. Further downstream in the pathway, squalene levels remain stationary at a level higher than that of empty vector and lower than that of B6, pGES+B6 and pGES+B6+CR36-1: it is not until after adding CR81+CR182+CR329 that the amount of squalene rises to match that of B6, pGES+B6 and pGES+B6+CR36-1. Remarkably, the level of squalene in the CR81+CR182+CR329-only sample is just as low as the empty vector control. So in this case, it is not the candidate enzyme by itself that causes the accumulation but the effect of (at least one of) the candidate genes. It should be noted that a sudden rise in squalene accumulation after adding CR81+CR182+CR329 to the series does not necessarily mean that the candidates are working on the products of R4, because they could also work on any of the products of pGES, B6, 10HGO, a combination of those or even on the products of those preceding candidate genes acting on endogenous substrate. After adding LAMT+SLS, squalene levels again drop to an intermediate level, indicating some sort of LAMT+SLS activity. Remarkably, we see a similar fluctuation pattern when looking at phytol but this will be discussed later on. All of this does not tell us much about which genes are the preferred candidates but it is a clear indication that these candidates do indeed show activity in our system.

4.4 G10h-candidate B6 gene activity on pGES products

By means of LC-MS/MS several masses were found that are upregulated by pGES, masses that are subsequently downregulated by B6 and masses that are produced by B6 (Figure 10). The masses depicted are masses that are either upregulated 5 times or more in pGES compared to the empty vector control or upregulated 5 times or more in pGES+B6 compared to pGES. The suspected B6-product- glycosides that are upregulated 5 times or more in B6-only compared to empty vector were omitted from Figure 10 as these masses probably represent products of B6 acting on unrelated endogenous substrates. Because of a lower ionisation energy used in LC-MS compared to GC-MS, the compounds do not break down into predictable subunits. The masses shown in Figure 10 and Table 3 represent the ‘parent ion’, the biggest fragment after ionisation which is generally assumed to be the unfragmented molecule. Using several known masses of sugar groups that are usually used for glycosylation we could make an educated guess about the identity of the glycosides (Table 3).

22

Table 3. Calculations on masses found by LC-MS indicate a potential identity of glycosides.

pGES products pGES+B6 products

Mass Proposed glycoside Mass Proposed glycoside

803.3651 geraniol 359.1316 10-hydrogeranic acid 493.2316 10-hydroxygeraniol 391.1607 iridodial 519.2471 10-hydroxygeraniol 521.1889 10-hydrogeranic acid 477.2355 geraniol 531.2823 10-oxogeranic acid or 10-hydrogeranial 831.3270 geranic acid 417.1778 10-hydroxygeraniol 463.2192 10-hydroxygeraniol

Unfortunately we were unable to identify the rest of the upregulated compounds that we found. Calculation of monoterpene-glycosides can by no means conclusively establish the identity of the glycosides: for most masses we could find multiple calculations of which only the most plausible are presented here. These results confirm the first part of the pathway: geraniol-synthase seems to actually produce geraniol and B6 degrades these products to a level similar to that of empty vector. Even though it was found in C. roseus that overexpression of B6 increases the flux through the pathway downstream of geraniol [4], there is still the possibility that B6 does not degrade GES-products, but that it just inhibits GES-activity either directly or indirectly through activity on endogenous compounds and subsequent disruption of the system. Interestingly, next to the expected geraniol glycosides and geranic acid glycosides we observe the presence of 10-hydroxygeraniol glycosides in the samples infiltrated only with pGES. This could indicate a role for endogenous enzymes that may hydroxylate the geraniol molecule, or the much more likely role of pGES being capable to hydroxylate GPP on both the first and the tenth carbon atom. This would mean that pGES is capable of doing that which has been hypothesised to be B6-activity. Overexpression of G10h-candidate B6 is then expected to either increase the production of 10-hydroxygeraniol glycosides or not to have an effect on 10-hydroxygeraniol accumulation if the supply of geranyl diphosphate is the limiting factor. Quite amazingly however, in the pGES+B6 samples we observe a decline in 10- hydroxygeraniol and an upregulation of 10-oxogeranial with two acid instead of aldehyde groups, which we named 10-hydrogeranic acid. Also 10-oxogeranial with one of its aldehyde groups converted to the acid group, which was named 10-oxogeranic acid or 10-hydrogeranial, is upregulated, and a mass that could represent iridodial with one acid group instead of aldehyde. This contradicts the hypothetical pathway as described in Figure 5: B6 seems to perform the tasks previously predicted to belong to 10HGO activity. Although some masses could not be identified and even though the calculation of potential glycosides leaves a lot of room for uncertainty, the fact that 4 out of 7 calculations of pGES- products indicate 10-hydroxygeraniol glycosides and that 3 out of 4 calculations of pGES+B6 products indicate acidified 10-oxogeranial glycosides supports these calculations. As shown in Figure 10, some of the masses that are upregulated after including B6 are already slightly upregulated in pGES-only. This could mean that endogenous enzymes are present with a function similar to that of B6, and that B6- overexpression further increases the turnover of 10-hydroxygeraniol to 10-oxogeranial or even 10- hydrogeranic acid. It remains unclear to which extent this conversion can be ascribed to B6 activity: it may be that activity of endogenous enzymes is involved, or that some reactions may happen spontaneously. It is assumed that an alcohol group can (be) turn(ed) into an aldehyde and subsequently into an acid group, and that this is generally a one-way reaction (S. van der Krol, personal communications). The observation of geraniol, geranial as well as geranic acid after infiltration with pGES lead to suspect that the originally produced geraniol can (be) turn(ed) into its variants geranial and geranic acid. However, in the pGES- samples 10-hydroxygeraniol does not spontaneously or through endogenous enzyme activity turn into an LC-MS-detectable derivative with at least one alcohol or acid group. This invalidates the possibility that any alcohol-group can spontaneously turn into its aldehyde or acid form, and we therefore suggest that endogenous enzyme activity causes geraniol turnover into geranial and geranic acid.

23

Summarizing the results obtained and presented in this study regarding the first part of the secologanin synthesis pathway downstream of geraniol, we propose an alternative hypothetical pathway to the one presented in Figure 5 (Figure 14).

4.5 pGES+B6 products are downregulated by 10HGO and slightly upregulated by CR36-1

As shown in Figure 11 we observed that 10HGO-candidate 10HGO downregulates quite some products that are high in pGES+B6 samples, whereas 10HGO-candidate CR36-1 does not. However, in both the pGES+B6+10HGO samples and the pGES+B6+CR36-1 samples no significantly upregulated compounds were detected. The observation that 10HGO-candidate 10HGO significantly downregulates pGES+B6 products may indicate that 10HGO is the most likely active 10HGO-candidate. However, the results presented earlier indicate that B6 already fullfills the hypothetical functions of 10HGO by converting 10- hydroxygeraniol. So in that case, the observation that 10HGO downregulates the masses we believe to be 10HGO-products leads to suspect that 10HGO is not a preferred candidate. CR36-1 on the other hand is generally shown to slightly increase pGES+B6 products. Based on these results we suggest that either not including a 10HGO-candidate or including 10HGO-candidate CR36-1 will provide the precursor metabolites for further downstream processing, whereas including 10HGO-candidate 10HGO might reduce the availability of these precursors.

24

GES

Geraniol Geranial Geranic acid

GES

10-hydroxygeranial B6

B6

10-hydroxygeraniol

B6

10-oxogeranial B6

B6 10-oxogeraniol or

10-hydrogeranic acid

Figure 14. An alternative pathway for the downstream

processing of geraniol towards oxo-geranial based on

the results presented in this thesis. Red arrows indicate

conversions by endogenous enzymes, blue arrows

position the role of GES and B6.

25

4.6 No confirmed identity of MTC, P450, LAMT or SLS activity, some detectable glycosyl transferase activity

Further downstream of the 10HGO-candidates, we could not observe any significant down- or upregulations by MTC-candidate R4, P450-candidates CR05/CR45/CR53/CR81/CR182/CR329 or previously annotated enzymes LAMT and SLS. This might be because the intermediate products could not be detected by LC-MS. As was the experience with similar experiments on candidate genes in the sesquiterpene pathway performed by colleague L. Qing, co-infiltrating candidate genes that are thought to act further downstream in the pathway might lead to compounds that are detectable. Indeed, glucosyltransferase-candidates G4/GT1/GT3/GT4 did show an upregulation of several different compounds. As shown in Figure 15 these upregulations are not products of (one of) the GTs acting on endogenous substrate. However, based on these results it cannot be excluded that the GTs act solely on the products of the chain of enzymatic reactions up to and including the P450-candidates. It is evident that the GTs act on something related to this pathway, but the observed upregulations may just as easily be products of GTs acting on products of pGES, B6, 10HGO or R4 that have acted upon monoterpene or even endogenous substrates. Indeed we observed that the compounds shown to be upregulated in Figure 15 are equally high in the samples that were infiltrated with all the candidates up to and including LAMT and SLS (data not shown). This suggests that these compounds are not the expected loganic acid and thus cannot be processed by LAMT and SLS. If the GTs act on monoterpene products of precursor candidate enzymes, intermediates are glycosylated and subsequently sequestered in the vacuole, rendering them inaccessible to downstream enzyme activity.

Ret(umin) Mass(uD)

11pGES+B6+10HGO+R4+Cr05+Cr45+Cr53_1 11pGES+B6+10HGO+R4+Cr05+Cr45+Cr53_3 12pGES+B6+10HGO+R4+Cr81+Cr182+Cr329_1 12pGES+B6+10HGO+R4+Cr81+Cr182+Cr329_2 12pGES+B6+10HGO+R4+Cr81+Cr182+Cr329_3 17pGES+B6+10HGO+R4+Cr05+Cr45+Cr53+G4+GT1+GT3+GT4_1 17pGES+B6+10HGO+R4+Cr05+Cr45+Cr53+G4+GT1+GT3+GT4_2 17pGES+B6+10HGO+R4+Cr05+Cr45+Cr53+G4+GT1+GT3+GT4_3 18G4+GT1+GT3+GT4_1 18G4+GT1+GT3+GT4_2-2 18G4+GT1+GT3+GT4_3 18pGES+B6+10HGO+R4+Cr81+Cr182+Cr329+G4+GT1+GT3+GT4_1 18pGES+B6+10HGO+R4+Cr81+Cr182+Cr329+G4+GT1+GT3+GT4_2 18pGES+B6+10HGO+R4+Cr81+Cr182+Cr329+G4+GT1+GT3+GT4_3 11GES+B6+10HGO+R4+Cr05+Cr45+Cr53_2 11650017 1023353394

9791483 462165070 14375283 477200226

13581866 507209656

15224183 463219238

Figure 15. LC-MS analysis of the effect of the glycosyl-transferase candidates, showing GT activity that cannot be related to activity on endogenous substrate. Relative intensity from low to high is shown from light green to dark green/red to light red, respectively.

26

4.7 Boosting geraniol synthesis by precursor candidates

N. benthamiana engineered only with geraniol synthase is sufficient to allow production of geraniol: N. benthamiana apparently possesses all the enzymes needed to produce the precursor of geraniol, geranyl-diphosphate. However, co-infiltrating geranyl-diphosphate synthase (GPPS) might increase the supply of geraniol synthase substrate and subsequently increase the production of geraniol and in turn increase the levels of downstream intermediate metabolites. Two GPPS-candidates IDS1 and IDS2 isolated from Pinus (pine tree) were infiltrated along with GES targeted to the plastid or to the cytosol. The change in geraniol production was measured using GC-MS, the samples were deglycosylated prior to the measurement.

A B

10 Geranial 500 Geraniol

8 400 Wildtype Wildtype 6 EV 300 EV

4 pGES 200 pGES

cGES

cGES Intensity(millions) 2 Intensity(millions) 100 IDS1+IDS2+pGES IDS1+IDS2+pGES 0 IDS1+IDS2+cGES 0 IDS1+IDS2+cGES

C D

300 Geranic acid 500

250 400 Wildtype 300 200 Geranic acid EV 200 150 100 Geraniol pGES

Intensity(millions) 0 100 Geranial EV

cGES WT

cGES pGES Intensity(millions) 50 IDS1+IDS2+pGES

GPPS+cGES 0 GPPS+pGES IDS1+IDS2+cGES

Figure 16. GC-MS analysis of the effect of co-infiltrating GPPS candidates with GES targeted to the cytosol and to the chloroplast on geranial (A), geraniol (B), geranic acid (C) and the cumulative (D).

Again, geranial was measured but should be neglected since this compound cannot be glycosylated (Figure 16a). Remarkably, geraniol production is reduced when the GPPS candidates are co-infiltrated with the GES targeted to the chloroplast, but slightly boosted when co-infiltrated with the GES targeted to the cytosol (Figure 16b). Whereas geraniol production only fluctuates a little and is hardly significant, geranic acid production shows a large difference when GPPS-candidates are co-infiltrated with GES located to the plastid (Figure 16c). This then indicates that the overall production of GES is increased by co-infiltrating GPPS-candidates, but is shifted in favour of geranic acid and at the cost of geraniol (Figure 16d, Figure 17). Although generally assumed that all enzymes involved in the monoterpene pathway reside in the chloroplast [19], the localisation of these two specific candidates is not yet known and could possibly play in role in explaining this difference.

27

pGES GPPS + pGES

9.0% 1.8% 1.4%

43.5%

55.1%

89.3%

cGES GPPS + cGES

6.4% 2.4% 12.5% 1.5%

91.2% 86.1%

Figure 17. GC-MS analysis of the effect of co-infiltrating GPPS

candidates with GES targeted to the cytosol and to the chloroplast on

the proportion between the geraniol-derivatives.

The same shift towards geranic acid is observed when GES-activity is increased by increasing the amount of A. tumefaciens with 3.5 times (Figure 18).

14 times dilution 4 times dilution

4.6% 2.3% 9.0% 1.8%

geranial

geraniol geranic acid

93.2% 89.3%

Figure 18. GC-MS analysis of the effect of different A. tumefaciens concentrations on the proportion between the geraniol-derivatives.

28

There could be two things happening when the production of GES is increased by co-expressing GPPS or by increasing the concentration of A. tumefaciens. Scenario one: it could be that increased production of geraniol triggers the preferred conversion to geranic acid. The relative proportion is thus changed, causing an increased detection of both geranic acid glycosides and the emitted free form. Scenario 2: it could be that increased synthesis of geraniol does not change the relative proportion of the three variants, but that the glycosylation machinery prefers or has easier access to the acid form. This would then cause an increase in geranic acid glycosides but a decline in the detectable amount of emitted geranic acid. Both scenarios fit with the notion that for plants, an acid group is easier to glycosylate (Thierry Delatte, personal communications). In case of scenario 1, the endogenous mechanism used to convert geraniol to geranic acid is upregulated to deal with an overdose of geraniol by converting the foreign molecule into a compound that the glycosylation machinery can more easily sequester. Or in case of scenario 2: the ratio between geraniol and geranic acid remains the same after increasing GES activity, but the acid variant has a higher affinity with the glycosylation machinery and thus gets glycosylated relatively more. A combination of the two scenarios may also be the case here: increased production causes a shift towards geranic acid in the total production, of which the ratio glycoside/free form of geranic acid is increased.

4.8 What is the effect of diluting the Agrobacterium?

To ensure equal concentrations of A. tumefaciens bacteria, the strain mixes were supplemented with an A. tumefaciens strain containing only the empty vector. This way the exact number of individual A. tumefaciens bacteria was the same for every candidate gene, allowing for a fair comparison between mixes. Because several experiments were performed, two different concentrations were used: a 14 time dilution as part of the candidate experiment downstream of GES and a 4 time dilution as part of the candidate experiment upstream of GES. Given the same OD600, this means a nominal difference of bacteria containing pGES of 3.5 times. Both experiments included a pGES-only sample, in both experiments a final OD600 of 0.9 was used and both experiments were harvested 10 days after infiltration. Assuming equal infiltration success, both for A. tumefaciens bacteria containing the vector harbouring pGES as well as for bacteria containing only the empty vector, one would assume that a 4 times dilution instead of a 14 times dilution would yield 3.5 times more infiltrations of bacteria containing pGES. One would then expect the subsequent transcription, translation and activity of the candidate enzyme to also be 3.5 times as high. Literature suggests that when using the same promoter, a co- infiltration in one plant cell may lead to silencing of the promoter or instability by recombination, which would suggest an increase of lower than 3.5 times [10, 20]. Quite remarkably however, we found that in the GC-MS data geraniol and geraniol-related compounds increased more than 3.5 times (Figure 19).

4.50E+08

4.00E+08

3.50E+08

3.00E+08

2.50E+08 14 times diluted 2.00E+08 Intensity 4 times diluted

1.50E+08

1.00E+08 Figure 19. GC-MS analysis of the

effect of co-infiltrating GPPS 5.00E+07 candidates with GES targeted to the

0.00E+00 cytosol and to the chloroplast on

the proportion between the geranial geraniol geranic acid geraniol-derivatives.

29

For geraniol, its aldehyde form geranial and its acid form geranic acid, a 3.5 times higher concentration resulted in an intensity increase of 8.1, 6.6 and 16.6 times respectively. All three geraniol-variants combined, a 3.5 higher concentration yields 8.4 times more product. This is much more than the expected 3.5 times upregulation, given that if 3.5 times more bacteria with pGES are infiltrated would give 3.5 times more infiltrated plant cells, yielding 3.5 times more product. One could however also argue that it is not so much the number of infiltrated plant cells that increases, but the number of pGES copies per cell. In that theory, the increased number of copies per cell does not decrease expression as postulated earlier, but rather enhances it so that the combined effect is larger than the cumulative effect of having multiple pGES copies in the genome. This would suggest a positive feedback loop of geraniol- related compounds on the transcription or translation of geraniol, or a negative feedback loop on the degradation of geraniol-related compounds. Agrobacterium tumefaciens is known to possess quorum- sensing signal molecules such as 3-oxo-octanoylhomoserine lactone (OC8HSL) [21]. This would explain in both cases why we see a much larger increment than expected. Another explanation would be the hypothesis that enhanced expression promotes the sequestering of geraniol-related compounds into their glycosylated form. Bear in mind that the GC-MS measures compounds after deglycosylation, so most of what we see in (Figure 19) are glycosides. The plant cell may not fully sequester a foreign molecule if it is lowly expressed and its concentration inside the cells is low enough for the cells to tolerate such a molecule. Increasing expression however may trigger the glycosylation machinery so that an increasingly larger part of the total production is glycosylated and ‘sinked’ in the vacuole, denying its emission. This last hypothesis would need to be tested by performing headspace analysis as well as GC-MS analysis on plants with a varying concentration of A. tumefaciens bacteria containing pGES. If the emitted geraniol also increases 8 times instead of the expected 3.5 times then there is something else going on such as quorum-sensing or a positive feedback loop. If however the headspace data shows a decrease in evaporated product when expression is increased then this hypothesis would become likely. Indeed, headspace analysis data from sesquiterpene-synthase experiments have shown a decline in evaporated product when increasing the amount of infiltrated bacteria (results not shown). Three genes were used in equal amounts and the OD600 was changed from

0.5 to 1 to 2. Comparing OD600 0.5 to 1, an increase in evaporated germacrene A was observed whereas it dropped significantly when increasing the OD600 to 2 (Q. Liu, personal communications). Because the O.D. was increased however, the total amount of bacteria applied to the leaf was increased which makes for the possibility that the plant cells are overwhelmed by the amount of invading bacteria and that their normal functionality is subsequently disturbed. It might cause the plant to switch to a much higher state of stress and reroute its metabolism, or cause increased apoptosis and necrosis. Therefore for future experiments it is recommended to increase expression by replacing bacteria containing the empty vector with bacteria containing genes of interest, rather than simply increasing the total amount of applied bacteria.

4.9 Phytol levels correlate with necrosis

Phytol levels vary greatly between candidate combinations, as do leaf phenotypes. The three highest average differences with the phytol level in the uninfiltrated control were a 6.6 times increase for GES+B6+10HGO+R4+CR81+CR81+C182, a 6.3 times increase for GES+B6+10HGO+R4+CR05+CR45+CR53 and a 6.5 increase for the B6-only treatment. Although leaf necrosis is hard to quantify, we observed relatively higher necrosis in leaves that turned out to possess relatively high phytol levels (Figure 20). Earlier findings suggest that phytol is a breakdown product of chlorophyll [7, 22, 23], which would explain this correlation. Probably some products produced by some (combinations of) candidate enzymes are so toxic to the plant that the chlorophyll is damaged. To complicate matters however, phytol is not very distantly related to the terpene backbone synthesis pathway (Figure 21). This leaves room for other hypotheses. For example, if the compounds produced by the candidate enzymes don’t directly damage the chlorophyll but block phytol degradation instead, the production of phytyl diphosphate is limited. If the plant cells then attempt to keep their chlorophyll at normal levels, then that would require a rerouting of the flux of geranyl diphosphate to farnesyl diphosphate, geranyl-geranyl diphosphate and finally to phytyl diphosphate. This would in turn limit the availability of geranyl diphoshpate for geraniol synthesis. For future experiments, the elucidation of these reactive compounds is therefore vital to ensure sufficient leaf growth and health and subsequent optimal production of the desired monoterpene indole alkaloids.

30

B6 pGES+B6 pGES+B6+CR36-1

250 30 Squalene Phytol Wildtype 25 200 EV

20 pGES

150 B6 15 pGES+B6

100 CR36-1 10 pGES+B6+CR36-1 Intensity (millions) Intensity 50 10HGO 5

pGES+B6+10HGO

0 0 pGES+B6+10HGO+R4

Wildtype pGES CR36-1

Figure 20. GC-MS analysis of the effect of the candidate combinations of candidates early in the pathway on squalene and phytol accumulation. These results suggest a possible relation between squalene and phytol and leaf necrosis. The leaf phenotypes of the three gene combinations with the highest phytol levels are shown above; the leaf phenotypes of the three gene combinations with the lowest phytol levels (except for empty vector) are shown below the charts.

4.10 Accumulation of squalene: potential causes and consequences

As mentioned earlier and as depicted in Figure 20 for the combinations up to and including R4, squalene and phytol fluctuate with a similar pattern in response to the combinations of candidate genes. For a long time during this thesis it remained unclear to which extent squalene and necrosis (and coupled phytol levels) were related. Especially since squalene is also closely related to the terpene backbone biosynthesis pathway, the same mechanism that causes an increase in phytol might be responsible for a coupled increase in squalene. Or in a more causal relationship: the increase in squalene causes chlorophyll degradation or phytol accumulation or vice versa.

31

MEP/DOXP pathway Mevalonic acid pathway

DXP HMG-CoA

Monoterpenes GPP Geraniol

Sesquiterpenes Diterpenes FPP GGPP

Squalene

Phytyl-PP

Cholesterol

Phytol

Chlorophyll a / b

Figure 21. A schematical overview of the relationship

between geraniol, squalene, phytol and their common

precursor GPP. Based on the KEGG database and the

PubChem project.

32

After analysis of the data from the GPPS-candidate experiments, we could however rule out one of the possibilities. When co-infiltrating pGES with the GPPS candidates, a remarkable difference in squalene levels between GPPS+cGES and GPPS+pGES is observed. Apart from this interesting difference, we observed that the leaf phenotype seems unaffected (Figure 22). This is especially interesting when considering that, due to a higher A. tumefaciens concentration used in the GPPS-experiment, the average squalene level in GPPS+pGES is 3.8 times higher than the average squalene level in the heavily necrotic B6-only samples. In this case, the squalene level shows a pattern different to that of phytol; the levels of the latter are more or less equal throughout the samples. These results show that squalene accumulation does not per se cause phytol accumulation, and that phytol accumulation is not needed for squalene accumulation.

cGES IDS1+IDS2+cGES

800

700 Squalene Phytol

600 Wildtype EV 500 cGES 400 pGES 300 IDS1+IDS2+cGES

(millions) Intensity 200 IDS1+IDS2+pGES

100 0

pGES IDS1+IDS2+pGES

Figure 22. GC-MS analysis on squalene levels and a comparison with leaf phenotypes excludes the possibility that squalene induces phytol accumulation or leaf necrosis.

33

Now back to the remarkable observation that squalene is increased explosively in GPPS+pGES and not in GPPS+cGES. As shown in Figure 21, geraniol and squalene share the same precursor, geranyl diphosphate. This is the compound that is supposed to be upregulated by the GPPS-candidates used in this study. Understandably, an upregulation of this compound in combination with GES will not only upregulate geraniol and its derivatives, but also other compounds that are synthesised from geranyl diphosphate. Thus it is not so much remarkable that GPPS+pGES shows such a high accumulation of squalene, but more so that GPPS+cGES does not show the same accumulation. On the contrary: based on results shown earlier one would expect that the weaker activity of cGES would use less geranyl diphosphate and would subsequently leave more geranyl diphosphate for squalene synthesis. Irrespective of the potential localisation of the GPPS-candidates, this is evidence for the crucial role that compartmentalisation plays in terpene biosynthesis. Availability of substrates such as geranyl diphosphate is not completely interchangeable between subcellular compartments, differentially limiting their availability to enzymes depending on the localisation of the enzymes. Although literature is not always conclusive about enzyme subcellular localisation (localisations may differ between species, multiple isomers are often found for one and the same enzyme, and an enzyme isolated from one species may localise differently when expressed in another species), farnesyl diphosphate synthases from C. roseus and A. thaliana have been found to locate to the peroxisomes of S. cerevisiae [24] and tobacco protoplasts [25], respectively, whereas squalene synthase was found to localise to the ER of rat hepatic cells [26] and of A. thaliana [27]. The general consensus concerning enzyme localisation is depicted in Figure 23.

Not depicted in this figure is the possible exchange of substrates between plastid and cytosol. Additionally, FPPS is shown here to directly use IPP/DMAPP instead of GPP which also uses IPP/DMAPP as its precursor metabolite. This is contradictory to the pathway presented in Figure 14 which is based on other resources (the KEGG Pathway database and PubChem). The remarkable lack of a squalene increase in the GPPS+cGES samples is hard to explain based on Figure 23. Assuming that these GPPS-candidates are indeed localised in the chloroplast, one would expect the squalene level not be affected if indeed there is no exchange between the plastid and the cytosol. So clearly, exchange is possible for at least some intermediates. An upregulation in GPP by overexpressing GPPS was shown earlier in this thesis to slightly boost pGES as well as cGES activity, indicating that GPP can be exchanged between compartments. A boost in GPP availability is then expected to increase squalene levels, independent on GES localisation. In case of any difference, one would expect that the Figure 23. Another hypothetical pathway squalene levels in GPPS+pGES samples would demonstrating the relationship between rather be lower than higher: pGES has easy monoterpenes and squalene. From Sapir-Mir et access to GPP before it is exported, which would al., 2008. leave less GPP for squalene synthesis.

Two different stories could explain this phenomenon. One such story is that GPPS is not located in the chloroplast as assumed in Figure 23 but that it is located in the cytosol instead. That way, in GPPS+cGES samples squalene does not go up because cGES uses most of the GPP for geraniol synthesis, not leaving much GPP for squalene synthesis. GPPS+pGES samples then do show increased squalene levels as FPS and squalene synthase have easier and first access to the increased GPP levels and convert GPP to squalene before GPP can get transported into the chloroplast. The second explanation is that geraniol is used as a building block for squalene synthesis. In this scenario, GPPS is indeed localised in the chloroplast as hypothesised in Figure 23, providing pGES with easier access to the increased GPP levels than cGES has. Although earlier in this thesis it was shown that geraniol and geranic acid levels of cGES and pGES samples both seem to profit only little from GPPS overexpression, it is possible that pGES in

34

effect produces more geraniol but that a large part of that geraniol is directly used for squalene synthesis. Indeed other research has found evidence for this possibility. Yeast can convert geraniol to citronellol, but Vaudano et al. (2004) observed that when the production of citronellol is reduced by anaerobiosis an increase in sterols is measured [28]. Additionally, Baistedt (1967) found that the carbon atoms of radioactively labelled geraniol administered to germinating seeds of Pisum sativum were incorporated into three major triterpenes, one of which was squalen [28]. In this last paper published in 1967, a suggestion is put forward which would explain how geraniol could be converted into squalene: ‘’Consequently, an additional and presumably dominant pathway(s) for the metabolism of geraniol appears to be operating. A route involving degradation to acetate would be in accord with the facts (…). Such a degradation would involve an oxidation of geraniol to geranic acid which, via the CoA derivative and involvement of CO2, would be degraded by the repeated removal of C2 units. Interestingly, the unsaturation of geraniol and, in particular, the allylic nature of the alcohol function endows the substrate with a susceptibility towards photolytic oxidation. The geraniol to geranic acid transformation might very well occur by this process. It is possible therefore that some transformation of the substrate may have occurred by these nonenzymatic routes prior to metabolism by the seed.’’ [28]. This concurs with our observations as presented earlier: GPPS greatly shifts the geraniol/geranic acid ratio towards geranic acid. This would also explain why no such exorbitant squalene increase is observed when geraniol production is increased by increasing the concentration of applied A. tumefaciens: the geraniol/geranic acid ratio is shifted somewhat, but not as dramatically as it is by co- infiltrating GPPS.

5. Conclusions and future implications

This thesis could not successfully establish the enzymatic function of candidates for downstream processing of geraniol. However, fluctuations of compounds unrelated to metabolites downstream of geraniol in samples infiltrated only with specific groups of candidate genes are evidence for successful infiltration, transcription, translation and enzyme activity. Additionally, we showed that performing infiltrations with very low concentrations of A. tumefaciens still results in detectable compound fluctuations: O.D. 0.9 in infiltration medium with 13/14th of the volume consisting of bacteria containing the empty pCambia1300 vector and only 1/14th of the volume consisting of bacteria containing pGES still resulted in detectable amounts of geraniol in GC-MS as well as in LC-MS. Calculations on LC-MS mass identifiers suggest that infiltration of pGES does not result only in geraniol, but also in 10- hydroxygeraniol. Production of 10-hydroxygeraniol using geraniol was originally hypothesised to be a function of G10h-candidate B6. The next step in the pathway was earlier hypothesised to be a function of 10HGO: the conversion of 10-hydroxygeraniol to 10-oxogeranial. However, the calculations presented here indicate that B6 can fulfil this step in the pathway although the LC-MS procedure could only detect the glycosylatable variant, 10-hydrogeranic acid. 10HGO-candiate 10HGO seems to downregulate these compounds whereas 10HGO-candiate CR36-1 slightly upregulates them. Because the partners in the project indicated that 10HGO was probably the preferred candidate, all the candidate combinations for downstream enzyme identification were co-infiltrated with pGES+B6+10HGO+R4 instead of pGES+B6+CR36-1+R4. The downregulation of the required metabolites for downstream processing by 10HGO would explain the lack of monoterpene-specific activity of most candidates downstream of R4. Two candidates upstream of GES, GPPS candidates IDS1 and IDS2, seem to have an effect on geraniol and geranic acid. The overall production of geraniol and geranic acid was slightly increased. The combination of GPPS with GES targeted to the plastid drastically tipped the geraniol/geranic acid ratio towards geranic acid. Although not as severe, the same shift towards geranic acid was observed when in pGES-only samples the concentration of A. tumefaciens containing pGES was increased. This indicates that increased prevalence of geraniol somehow favours the conversion into geranic acid. This is probably mediated by plant cell defence mechanisms in response to the potentially toxic geraniol, as geranic acid is more easily sequestered by glycosylation machinery. Another observation when increasing the number of A. tumefaciens bacteria containing pGES-copies, is that overall geraniol and geranic acid intensity is increased disproportionately. Possibly this a normal effect, but it could be that increased geraniol production increases the activity of the glycosylation machinery to combat the toxic compound, allowing us to observe an increased glycosylated product versus free form – ratio since only LC-MS analysis was used. Combined measurements with headspace analyses should be performed to test this hypothesis. Some infiltration combinations showed leaf necrosis. Leaf necrosis seems to correlate with increased phytol levels but this is logical as phytol is a breakdown product of chlorophyll. Phytol levels in turn seem

35

to correlate with squalene, raising the question if the upregulation of squalene might be a cause or consequence of chlorophyll degradation. Samples from the GPPS-experiments however show that high levels of squalene do not necessarily lead to phytol accumulation or leaf necrosis. Samples infiltrated with GPPS+pGES show high levels of squalene as expected since GPP is a precursor for squalene synthesis, whereas samples infiltrated with GPPS+cGES do not. This is evidence for the crucial role that compartmentalisation plays in terpene biosynthesis. The most likely explanation for this observation is that GPPS increases pGES activity, but that the superfluous geraniol is used directly for squalene synthesis. Literature suggests that a conversion of geraniol into geranic acid is needed, which is in agreement with our observation that GPPS co-infiltration with pGES shifts the geraniol/geranic acid-ratio in favour of geranic acid.

Future research should try to focus on the early steps in loganin biosynthesis. Co-infiltrations of downstream candidates with 10HGO-candidate 10HGO were possibly unsuccessful because this 10HGO- candidate seems to limit rather than enhance the availability of intermediates used in downstream conversions. Additionally, the separation of the six P450 candidates into two groups of three might have separated the two or three ideal candidates that should have been combined to enable the detection of the desired compounds further downstream. Evidently, enzyme targeting plays a major role in allowing proper enzyme activity, as shown for the major changes in squalene depending on GES localisation in GPPS+GES experiments and as demonstrated for the 3-fold difference in geraniol content between cGES and pGES. Effects of the candidate enzymes on endogenous compounds should not be underestimated. As observed for B6, this candidate can severely alter plant health and metabolism in a negative way. In mice, phytol feeding has been shown to cause selective midzonal hepatocellular necrosis and inflammation[29]; squalene feeding was shown to cause increased hepatic esterified cholesterol and to strongly inhibit the activity of hydroxymethylglutaryl-coenzyme A (HMG-CoA) reductase, a crucial enzyme for the biosynthesis of sesquiterpenes [30]. On a more positive note, increased squalene intake was shown to reduce cholesterol and LDL levels by 17% and 22% [18], respectively, and recently phytol has been patented as a cholesterol lowering agent [31]. Research on engineering the monoterpene pathway into a more productive platform and on upregulating the production thus holds promise not only with respect to increased production of the intended compounds, but also with respect to related beneficial compounds and will foremost provide insight into the complexity of plant secondary metabolism.

6. Acknowledgements

I would like to thank my supervisor Sander van der Krol for fruitful discussions and feedback on the work, and my supervisor Lemeng Dong for her motivation and guidance in the lab work. Special thanks to the colleagues at the terpene group and Qian Zuo who selflessly helped out on a number of occasions, and to Francel Verstappen and Bert Schipper for their support with the GC-MS and LC-MS procedures.

36

7. References

1. Favretto D., Piovan A., Filippini R. and Caniato R. Monitoring the production yields of vincristine and vinblastine in Catharanthus roseus from somatic embryogenesis. Semiquantitative determination by flow-injection electrospray ionization mass spectrometry. RAPID COMMUNICATIONS IN MASS SPECTROMETRY, 2001. 15: p. 364-369.

2. Suttipanta N., Pattanaik S., Gunjan S., Xie C.H., L.Y. Littleton J. and Yuan L. Promoter analysis of the Catharanthus roseus geraniol 10-hydroxylase gene involved in terpenoid indole alkaloid biosynthesis. Biochimica et Biophysica Acta (BBA) - Gene structure and expression, 2007. 1769(2): p. 139-148.

3. Guirimand G., Guihur A., Ginis O., Poutrain P., Hericourt F., Oudin A. St-Pierre B., Burlat V. and Courdavault V. The subcellular organization of strictosidine biosynthesis in Catharanthus roseus epidermis highlights several trans-tonoplast translocations of intermediate metabolites. FEBS Journal, 2011. 278(5): p. 749-763.

4. Wang C.T., Liu H., Gao X.S., and Zhang H.X. Overexpression of G10H and ORCA3 in the hairy roots of Catharanthus roseus improves catharanthine production. Plant Cell Reports, 2010. 29(8): p. 887-894.

5. World Health Organization (WHO). International Drug Price Indicator Guide 2011 [cited 2011 March 29th]; http://erc.msh.org/mainpage.cfm?file=1.0.htm&module=Dmp&language=English].

6. Rischer H., Oresic M., Seppanen-Laakso T., Katajamaa M., Lammertyn F., Ardiles-Diaz W., Van Montagu M.C.E., Inzé D., Oksman-Caldentey K.M., and Goossens A. Gene-to-metabolite networks for terpenoid indole alkaloid biosynthesis in Catharanthus roseus cells. PNAS, 2006. 103(14): p. 5614-5619.

7. Kanehisa Labs. Kyoto Encyclopedia of Genes and Genomes (KEGG). 2011.

8. Montiel G., Zarei A., Korbes A.P. and Memelink J. The jasmonate-responsive element from the ORCA3 promoter from Catharanthus roseus is active in Arabidopsis and is controlled by the transcription factor AtMYC2. Plant and Cell Physiology, 2011. 52(3): p. 578-587.

9. Dutta A., Singh D., Kumar S., and Sen J. Transcript profiling of terpenoid indole alkaloid pathway genes and regulators reveals strong expression of repressors in Catharanthus roseus cell cultures. Plant Cell Reports, 2007. 26(7): p. 907-915.

10. Van Herpen, T.W.J.M., Cankar K., Nogueira M., Bosch D., Bouwmeester H.J., and Beekwilder J. Nicotiana benthamiana as a production platform for artemisinin precursors. PLoS ONE 2010. 5(12).

11. Guirimand G., Guihur A., Poutraina P., Héricourt F., Mahroug S., St-Pierre B. and Courdavault V. Spatial organization of the vindoline biosynthetic pathway in Catharanthus roseus. Journal of Plant Physiology, 2011. 168(6).

12. Roepkea J., Salim V., Wu M., Thamm A.M.K., Murata J., Ploss K., Boland W. and De Luca V. Vinca drug components accumulate exclusively in leaf exudates of Madagascar periwinkle. PNAS, 2010. 107(34): p. 15287-15292.

13. Twyman, R.M. www.smart-cell.org. 2009 [cited 2011 March 28th].

14. Yang T., Stoopen G., Yalpani N., Vervoort J., de Vos R., Voster A., Verstappen F.W.A., Bouwmeester H.J., Jongsma M.A. Metabolic engineering of geranic acid inmaize to achieve fungal resistance is compromised by novel glycosylation patterns. Metabolic Engineering, 2011. 13(4): p. 414- 425.

37

15. Voinnet O., Rivas S., Mestre P. and Baulcombe D. An enhanced transient expression system in plants based on suppression of gene silencing by the p19 protein of tomato bushy stunt virus. The Plant Journal, 2003. 33(5): p. 949–956

16. De Vos R.C.H., Moco, S., Lommen A., Keurentjes J.J.B., Bino R.J. and Hall R.D. Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry. Nature Protocols, 2007. 2: p. 778-791.

17. Giddings L.A., Liscombe D.K., Hamilton J.P., Childs K.L., DellaPenna D., Buell C.R. and O'Connor S.E. A stereoselective hydroxylation step of alkaloid biosynthesis by a unique cytochrome p450 in Catharanthus Roseus. The Journal of Biological Chemistry 2011. 286: p. 16751-16757.

18. Belter A., Skupinska M., Giel-Pietraszuk M., Grabarkiewicz T., Rychlewski L. and Barciszewski J. Squalene monooxygenase – a target for hypercholesterolemic therapy. Biological Chemistry, 2011. 392(1): p. 1053-1075.

19. Nagegowda, D.A. Plant volatile terpenoid metabolism: Biosynthetic genes, transcriptional regulation and subcellular compartmentation. FEBS Letters, 2010. 584: p. 2965-2973.

20. Bender J. Chromatin-based silencing mechanisms. Current Opinion in Plant Biology, 2004. 7(5): p. 521-526.

21. Haudecoeur E. and Faure D. A fine control of quorum-sensing communication in Agrobacterium tumefaciens. Communicative & Integrative Biology 2010. 3(2): p. 84-88.

22. National Centre for Biotechnology Information (N.C.B.I.). The PubChem project. 2011 [cited 2011 March 28th]; http://pubchem.ncbi.nlm.nih.gov/.

23. Vavilin D., Vermaas W. Continuous chlorophyll degradation accompanied by chlorophyllide and phytol reutilization for chlorophyll synthesis in Synechocystis sp. PCC 6803. Biochimica et Biophysica Acta (BBA) 2007. 1767: p. 920-929.

24. Thabet I., Guirimand.G., Courdavault V., Papon N., Godet S., Dutilleul C., Bouzid S., Giglioli- Guivarc'h N., Clastre M., Simkin A.J. The subcellular localization of periwinkle farnesyl diphosphate synthase provides insight into the role of peroxisome in isoprenoid biosynthesis. Journal of Plant Physiology, 2011. 168(17): p. 2110-2116.

25. Sapir-Mir M., Mett A., Belausov E., Tal-Meshulam S., Frydman A., Gidoni D. and Eyal Y. Peroxisomal localization of Arabidopsis isopentenyl diphosphate isomerases suggests that part of the plant isoprenoid mevalonic acid pathway is compartmentalized to peroxisomes. Plant Physiology, 2008. 148(3): p. 1219-1228.

26. Stamellos K.D., Shackelford J.E., Shechter I., Jiang G., Conrad D., Keller G.A. and Krisans S.K. Subcellular localization of squalene synthase in rat hepatic cells. Biochemical and immunochemical evidence. Journal of Biological Chemistry, 1993. 268: p. 12825-12836.

27. Vaudano E., Moruno E.M. and Di Stefano R. Modulation of geraniol metabolism during alcohol fermentation. Journal of the Institute of Brewing, 2004. 110(3): p. 213-219.

28. Baisted, D.J. Incorporation of label from geraniol into squalene, beta-amyrin and beta-sitosterol in germinating pea seeds. Phytochemistry, 1967. 6: p. 93-97.

29. Mackie J.T., Atshaves B.P., Payne H.R., McIntosh A.L., Schroeder F. and Kier A.B. Phytol induced hepatotoxicity in mice. Toxicology & Pathology, 2009. 37(2): p. 201-208.

30. Strandberg T.E., Tilvis R.S. and Miettinen T.A. Variations of hepatic cholesterol precursors during altered flows of endogenous and exogenous squalene in the rat. Biochimica et Biophysica Acta (BBA) - Gene structure and expression, 1989. 1001(2): p. 150-156.

31. Olofsson P., Hultqivst M., and Holmdahl R. Phytol as a cholesterol lowering agent, in Patent Application Publication 2011: United States p. 14.

38