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Exploiting the potential of micropropagated durum wheat organs as modified mycotoxin biofactories: The case of deoxynivalenol
Phytochemistry 170 (2020) 112194
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Exploiting the potential of micropropagated durum wheat organs as modified mycotoxin biofactories: The case of deoxynivalenol
T
Laura Righettia,∗, Tito Damiania, Enrico Rollib, Gianni Galavernaa, Michele Sumanc, Renato Brunia, Chiara Dall’Astaa a
Department of Food and Drug, University of Parma, Parco Area delle Scienze 27/A, 43124, Parma, Italy Deparment of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Via Università 12, 43121, Parma, Italy c Barilla G.R. F.lli SpA, Advanced Laboratory Research, via Mantova 166, Parma, Italy b
A R T I C LE I N FO
A B S T R A C T
Keywords: Metabolism Wheat Biotransformation High resolution mass spectrometry Masked mycotoxins Plant defense
This study aimed to investigate the potential of in vitro wheat model as biofactory for masked mycotoxin production. Micropropagated durum wheat organs (leaves and roots) were treated during a 14-day time span on a proper medium spiked with deoxynivalenol (DON). After the treatment, DON absorption from culture media was evaluated while roots and leaves were profiled by UHPLC-HRMS to investigate the DON biotransformation products. A total of 10 metabolites have been annotated in both roots and leaves. In particular, 5 phase I metabolites never reported before were putatively identified, suggesting the viability of the model as a tool to investigate the interplay between mycotoxins and wheat. In addition, 5 phase II metabolites previously reported in wheat grown under open field conditions, were identified in both roots and leaves, thus demonstrating the reliability of the cultured organs as model system for wheat plants. An organ-dependent difference in DON uptake and biotransformation was observed, since roots contained a high amount of untransformed DON, while leaves were able to effectively biotransform DON to its glycosylated form and other relevant metabolites. With the perspective of using cultured organs as biofactories for modified mycotoxin production, leaves seemed therefore to offer the best absorption and production yield.
1. Introduction Trichothecenes constitute a large family of stable and persistent sesquiterpenoids produced by widely distributed fungal genera including Fusarium, Trichoderma, Cephalosporium and Stachybotrys (Ferrigo et al., 2016). These mycotoxins represent a key weapon in the chemical warfare between fungi and plants and, albeit presenting different abundances and toxicities, they share an extremely reactive epoxy group between C-12 and C-13, whose presence is deemed essential to exert a toxic behavior in eukaryotic organisms (Van der Leet et al., 2015). Deoxynivalenol, in particular, is actively involved in the spread and establishment of Fusarium in infected plants. Produced in a cocktail that may also include nivalenol, 3-acetyl-deoxynivalenol and 15-acetyl-deoxynivalenol, DON is both the most frequently found and the most abundantly detected mycotoxin biosynthesized by toxigenic strains of Fusarium graminearum and to a minor degree by F. nivale, F.
culmorum and F. sambucinum (Asam et al., 2017). Both DON and related compounds act in eukaryotic cells by inhibiting 60S ribosomial subunits and protein, DNA and RNA synthesis, impairing the mitochondrial function and hampering the plant defensive process of apoptosis (Diamond et al., 2013). In mammalians, following chronic or acute exposure, DON may induce a broad spectrum of symptoms including necrosis of intestinal tract, liver and bone marrow with leukopenia, emesis and diarrhea, ultimately resulting in potential deadly relapses (Escrivá et al., 2015). Following its common presence in foods, DON is therefore considered a worldwide target for risk assessment and food safety (Visconti and Pascale, 2010; Zachariasova et al., 2012). In view of consumer protection, the European Community has defined maximum contamination levels accepted for human consumption (EC 1126/2007). As most xenobiotics, mycotoxins as DON may undergo biotransformation as the result of regio-selective and stereospecific
Abbreviations: DON, deoxynivalenol; DON-Glc, deoxynivalenol glucoside; DON-MalGlc, deoxynivalenol malonyl-glucoside; DON-GSH, deoxynivalenol glutathione; rpm, revolutions/min; DMSO, dimethyl sulfoxide; UHPLC, ultra high performance liquid chromatography; HRMS, high-resolution mass spectrometry; PCA, Principal Component Analysis; cv, cultivar ∗ Corresponding author. E-mail address: [email protected] (L. Righetti). https://doi.org/10.1016/j.phytochem.2019.112194 Received 8 August 2019; Received in revised form 23 October 2019; Accepted 31 October 2019 0031-9422/ © 2019 Elsevier Ltd. All rights reserved.
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reactions mediated by plant enzymes (Sandermann, 1994; Berthiller et al., 2013). To facilitate (or prevent) translocation, compartmentation, storage and eventual disposal, mycotoxins are often biochemically conjugated to endogenous aminoacidic, sugar, malonyl, sulphate, gluthatione moieties to organic xenobiotics, often reducing their in planta toxicity. These conjugated metabolites may then be deposited in the apoplast, bound to cell wall or segregated in the vacuole of infected plants according to their reactivity and water solubility (Siminszky, 2006; Edwards et al., 2011). This masking mechanism, responsible for the formation in planta of the so called “masked mycotoxins”, represents an effective and well-known plant strategy to cope with the toxicity of trichothecenes (Freire and Sant’Ana, 2018). In Fusarium-infected cereals or spikelets injected with DON, the mycotoxin undergoes phase II conjugation to its most common masked form DON-3-glucoside, while other conjugated forms like DON-hexitol and DON-hexosides, or DON-gluthatione and its degradation products DON-S-cysteinyl-glycine, DON-S-cysteine, DON-3-sulphate and DON15-sulphate have been described (Warth et al., 2015; Kluger et al., 2015). Detecting and quantifying masked forms of DON, along with a clear definition of their actual toxicity as single compounds or as cocktails, is currently deemed critical in determining safe consumption levels. In fact, masked forms of DON are not monitored in routine food control, no maximum contamination levels accepted for human consumption may be properly assessed and their actual toxicity in both humans and animals is de facto uncertain. However, the consensus is that their disregarding may lead to a consistent underestimation of actual intake and impact on human and animal health (Dellafiora and Dall’Asta, 2016; Gratz, 2017). Accordingly, the European Food Safety Authority has recently released a scientific opinion on DON and its modified forms, stating that the occurrence of these compounds should be evaluated in pool for risk assessment purposes, and therefore forthcoming regulation should cover the sum of DON and its modified forms instead of the single parent compound (EFSA, 2017). At the same time, the development of comprehensive screening of their presence in foods and the precise evaluation of in vivo bioactivity of the masked mycotoxin cocktail is made difficult by some practical limitations (Krska et al., 2017). For instance, the lack of readily available of masked mycotoxins in pure form or in nature-like mixtures, as well as of reference materials for validation or to be used as standard calibrants (Tangni et al., 2017). On this regard, plant cell, organ cultures or entire plants may be investigated as potential biofactories to produce pure masked mycotoxins or their calibrated mixtures, using an approach similar to the one developed for pesticides and pharmaceuticals, but few investigations are available to evaluate the feasibility of such process (Bártíková et al., 2015). If properly scaled, a model based on wheat may allow the controlled production of specific biotransformation products, both in isolate forms or in nature-like mixtures that can be used for analytical and toxicological purposes and which are not realistically attainable by chemical semi-synthesis (Berthiller et al., 2006; Righetti et al., 2017; Abhilash et al., 2009). Therefore, this research was performed to investigate the potential radical and leaf absorption, assimilation and metabolic fate of different DON administrations in two micropropagated Triticum durum Desf cultivars by monitoring the eventual production of masked mycotoxins with a targeted-untargeted approach.
Fig. 1. Residual DON in culture medium during growth of micropropagated organs of T. durum cultivars Kova and Svevo. A) leaves; B) roots.
media, a semi-quantitative determination of DON and DON3Glc, followed by an untargeted monitoring of phase I and II plant metabolites of DON. Two durum wheat cultivars were selected as model system, Kofa and Svevo, found as more and less resistant towards Fusarium spp. infection in previous studies (Cirlini et al., 2013). 2.1. Evidence of plant uptake and absorption The uptake of DON from medium in cultured organs is generally lower in roots than in leaves, as shown in Fig. 1. The average residual DON in the medium after 14 days is about 79–83% and 40–53% of the administered dose in Kofa and Svevo cv., respectively. Consistent with this, the DON uptake is lower in Kofa than in Svevo. 2.2. Biotransformation of DON in cultured roots and leaves After 14 days of incubation with DON, leaves and roots were analysed by UHPLC-HRMS to evaluate the formation of metabolites. The parent compound was found in both cultured organs, although at lower amounts compared to other metabolites, confirming its intensive biotransformation. Semiquantitative data collected within the study are represented in Fig. 2. In both cultivars, residual DON is higher in roots than in leaves (9.3% vs 2.9%, respectively), while DON-3Glc and other metabolites are more abundant in leaves. In both Kofa and Svevo cv, DON-3Glc is the main metabolite in roots (68% and 57%, respectively), while in leaves the biotransformation process has led mainly to the accumulation of other metabolites (78% and 66%, respectively).
2. Results
2.3. Untargeted screening of phase I and phase II DON conjugates in roots and leaves
The approach presented herein is based on the assumption that healthy, micropropagated wheat plants may absorb and metabolize DON from isolated organs (leaves and roots) during a 14-day time span growth on a proper medium, as already demonstrated in our previous papers (Righetti et al., 2017; Rolli et al., 2018). To demonstrate that and to evaluate the potential of the model, three separate steps were undertaken: an evaluation of the actual uptake/absorption from culture
In order to identify the biotransformation products obtained in roots and leaves, UHPLC-HRMS analysis was performed as previously reported (Righetti et al., 2017, 2018). A total of 10 metabolites have been annotated in both roots and leaves. In particular, 5 phase I and 5 phase II metabolites are reported in Table 1, Table 2 and Table S1. In some cases, different peaks were assigned to a single putative metabolite, in 2
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Fig. 2. Pie chart representing the % of DON biotransformation after 14 days exposure. Each ring represents the total % of derivatives in each organ considering semiquantitative data of unaltered DON, DON-3-Glucoside and the whole spectra of phase I and phase II derivates detected in roots and leaves.
such as oxidation, giving rise to the formation of carbox-DON. Furthermore, the involvement of epoxidation and de-epoxidation reactions has been highlighted for several xenobiotics in plant (Bártíková et al., 2015) and in mammals, with the conversion of DON into de-epoxy-DON (DOM). DON phase I metabolite HRMS/MS data were compared with in silico fragmentation obtained uploading in-house generated SDF files into MetFrag (Ruttkies et al., 2016), since reference spectra were not available in literature. Putatively identified metabolites are listed in Table 1 and Table S1 and the HRMS/MS spectra are reported in Fig S3–S7 (Supplementary Data). Among considered metabolites, DON-3Glc, DON-diGlc, DONMalGlc, DON-GSH, and Hydroxyl-DON have been found at relevant abundance in all the considered samples. For this reason, their abundance has been used for chemometric analysis. A factorial ANOVA followed by post hoc Tukey's test, was carried out to highlight possible organ-, cultivar- and dose-dependent effects. Data were log-transformed before analysis. Both the administration dose (12.5 μg and 100 μg) and organ (root and leaf) were found significant factors (p = 0.016 and 0.006, respectively), whereas no effect was found for the cultivar and the combination of factors. Significant differences between groups are reported in Fig. 4. The same data have been later used for Principal Component Analysis (PCA), in order to identify further clusterization between samples. Score and Loading plots are reported in Fig. 5A and B. Variance is well explained by Factor 1 and Factor 2 (overall 85.02%). From score and loading plot, it can be noticed that the administered dose is the main affecting parameters, allowing for the separation along Factor 1. However, Factor 2 pinpoints a very clear sample clustering according to the organ and based on the content of single compounds.
consideration of the possible isomeric forms. All the annotated phase II metabolites (Table 2) have been previously reported in wheat grown in greenhouse (Kluger et al., 2015; Cirlini et al., 2013) or under open field conditions (Zachariasova et al., 2012; Spaggiari et al., 2019), thus demonstrating the reliability of the cultured organs as model system for wheat plants. Their structures are depicted in Fig. 1, Supplementary Data. DON di- and -tri-glucosides were identified based on in-source fragmentation (Zachariasova et al., 2012), detecting fragments at m/z 589.2124 and 751.2668 corresponding to [M−CH2O–H]− ions of DON di- and -tri-glucosides, respectively with calculated maximum mass errors not higher than 3 ppm. The presence of DON-malonyl-glucoside (DON-MalGlc) and DON-gluthatione (DON-GSH) was confirmed by the comparison of HRMS fragmentation patter previously elucidated by Kluger et al., (2015). The HRMS/MS spectra are reported in Supplementary Data. Five phase I metabolites are, up to our knowledge, reported for first time in plants and are summarized in Table 1 and Table S1. The formation of these compounds is expected when considering the enzymatic machinery of plants. CYPs commonly catalyze monooxygenation, including hydroxylations, epoxidations, dealkylations, decarboxylations and isomerizations of xenobiotics, but they can also act as reductases (Bártíková et al., 2015). Possible structures and the putative enzymes involved are reported in Fig. 3, as obtained by SOM prediction analysis. The major metabolic pathways involved are hydroxylation, oxidation and epoxidation of parent DON. In particular, mono hydroxy-DON was reported as the predominant phase I metabolite, in agreement with previous studies on other mycotoxins. Consistent with this, the hydroxy form of ZEN (Righetti et al., 2017) and other trichothecenes including T2 and HT2 (Righetti et al., 2019) have been already confirmed in planta. Hydroxy-DON may undergo further metabolization reaction, Table 1 Putatively annotated phase I DON metabolites. Formula
RT (min)
Theoretical m/z [M + CH3COO]-
Mass error (ppm)
DON 10en-8,9-dione-demethyl DONb
C15H20O6 C14H16O7
355.1382 355.1023
Carbox-DONb
C15H18O8
Hydroxy-DON/9,10–12,13diepoxy-DONb 9,10di-hydroxy-dehydro DONb Hydroxy-carbox-DONb
C15H20O7 C15H22O8 C15H18O9
8.9 12.5 13.3 13.5 12.2 12.9 13.6 13.5 10.0 6.2
0.2 1.1 1.6 1.5 3.8 1.3 1.7 3.3 1.2 3.9
Metabolites a
a b
Confirmation with standard by comparison of accurate mass, HRMS/MS and RT. Annotation with accurate mass, elemental formula and HRMS/MS spectra. 3
385.1129
371.1342 389.1442 401.1078
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Table 2 Phase II DON metabolites annotated with accurate mass, elemental formula and HRMS/MS spectra compared to those previously reported in literature. Metabolites DON-3-Glc DON-di-Glc DON-tri-Glc DON-malonyl-glucoside DON-glutathione
Formula C21H30O11 C27H40O16 C33H50O21 C24H32O14 C25H37N3O12S
RT (min) 9.2 8.5 7.9 11.28 7.9
Theoretical m/z 517.1915 679.2443 841.2972 567.1684 604.2171
3. Discussion
Adduct [M + CH3COO][M + CH3COO][M + CH3COO][M+Na]+ [M+H]+
Mass error (ppm) 1.1 1.8 2.9 1.6 −0.1
References STD [Zachariasova et al., 2012] [Zachariasova et al., 2012] [Kluger et al., 2015] [Kluger et al., 2015]
2017). This can be explained in consideration of the relatively low logPow of about −0.97 for DON, corresponding to a rather hydrophilic compound and thus consistent with a low root uptake of the chemicals (Briggs et al., 1982; Paterson et al., 1994). On the other hand, leaves offer a higher surface of passive absorption and a quicker biotransformation rate. This could be explained taking into consideration that, under natural field conditions, leaves are mainly exposed to fungal pathogen attack, and therefore could have developed organ-related biological machineries to effectively counteract DON accumulation. Furthermore, once absorbed by the root, DON access to the cellular cytoplasm and its complete exposure to the detoxifying enzymatic pools may be limited by physical absorption to the exodermis or by a higher distribution along the apoplastic route, resulting in a reduced biotransformation. A slight cultivar-dependent difference in uptake from the medium has been observed for both roots and leaves. Differences between cultivars may be explained by factors such as degree of root growth, transpiration rates, and the size and shape of the leaf material. In addition, differences in plant lipid contents may also be important as this can affect the sorption of hydrophobic chemicals. Regarding the DON biotransformation products, the proposed model system was suitable for the production of those modified forms of DON already detected in the field and thus of market relevance as analytical standards as a nature-like mixture. For this reason, more attention was given to those metabolites already reported in literature and, in particular, considered valuable for risk assessment in the scientific opinion on DON and its modified forms, as set by the European Food Safety Authority (EFSA, 2017). It can be noticed that roots contained a high amount of untransformed DON, while leaves are able to effectively biotransform DON to DON-3-Glc and other relevant metabolites. With the perspective of using cultured organs as biofactories for modified mycotoxin production, leaves seemed therefore to offer the best absorption and production yield.
The present study aims at exploring the potential of wheat organs as masked mycotoxin biofactories. Once treated with DON, our model system returned a spectrum of metabolites, among whose the most abundant were the main phase II compounds already observed in cereals in greenhouse experiments and/or in the field (i.e. DON-3Glc, DON-diGlc, DON-triGlc, DONMalGlc, DON-GSH) (Kluger et al., 2015; Cirlini et al., 2013; Zachariasova et al., 2012; Spaggiari et al., 2019), thus ensuring the reliability of wheat cultured organs in producing compounds relevant for risk assessment by mere exposure to such mycotoxin without being mechanically inoculated nor in presence of an actual infection. In addition, the model system was able to return several phase I metabolites never observed before. The formation of these compounds is expected when considering the enzymatic machinery of plants. However, since they act as intermediate structures for further biotransformations by phase II metabolism, their accumulation in crops is unlikely. For this reason, organ models proposed herein could be successfully used for the full elucidation of plant metabolic pathways as well. In order to evaluate the costs and upscaling conditions, several factors have been considered within this study, among them the cultivar, the organ and the dose. While an expected dose-related accumulation was observed, the one-order magnitude difference in administered dose (12.5 μg and 100 μg) was not reflected in a comparable difference in uptake and production. Therefore, for the exploitation of cultured wheat organs as biofactories for masked DON production, the lower dose could be successfully used. Furthermore, the non-absorbed standard remaining in the growing medium, ranging from 40% to 83% of the initial dose depending on the organ, could be re-used for further experiments, as in a circular model. On this account, a relevant organ dependent difference in uptake and production has been observed, with the residual amount in the medium higher in roots than in leaves. In addition, DON uptake observed in this work was significantly lower than the uptake reported for ZEN in our previous work (Righetti et al.,
Fig. 3. Proposed structures and route of formation of DON phase I metabolites. 4
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Fig. 4. Log-transformed UHPLC-HRMS relative abundance of DON and its main metabolites according to organ and administered dose.
4. Conclusion
5.2. Culture medium and plant materials
The present studies deepen our understandings of the contribution of plant metabolism in the biosynthesis of masked mycotoxins. A total of 10 DON metabolites were annotated in both roots and leaves. In particular, 5 phase II metabolites were confirmed from previous studies, while 5 phase I metabolites were reported for the first time. Furthermore, the in vitro wheat model prooved its potential to foresee the development of biocatalytic tools for the production of masked mycotoxins to be used as reference materials, with leaves representing the most likely candidate organ.
Two commercial durum wheat (Triticum durum Desf.) varieties, namely Kofa and Svevo, were selected for their different Fusarium Head Blight resistance (Cirlini et al., 2013). Culture medium was prepared as previously reported (Righetti et al., 2017). Experiments were performed in triplicate and repeated three times. For organ micropropagation and mycotoxin administration, the protocols reported by Righetti et al. (2017) and Rolli et al. (2018) were followed. Briefly, DON was dissolved in an adequate amount of DMSO so that the final concentration of the solvent in culture medium did not exceed the one considered toxic (0.2%) with mycotoxin being at the final concentration of 12.5 μg/L and 100 μg/L. Solutions were sterilized by 0.2-μm filters and dissolved in the liquid Murashige-Skoog medium. At the end of the experiment organ cultures exposed up to 100 μg/L DON showed no visible degradation.
5. Experimental 5.1. Chemicals Analytical standards of DON (100 μg mL−1 in acetonitrile), and DON-3Glc (solution in acetonitrile 50.6 μg mL−1) were purchased from Romer Labs® (Tulln, Austria). HPLC-grade methanol, acetonitrile and acetic acid, as well as dimethylsulfoxide (DMSO) were purchased from Sigma-Aldrich (Taufkirchen, Germany); bidistilled water was obtained using a Milli-Q System (Millipore, Bedford, MA, USA). MS-grade formic acid from Fisher Chemical (Thermo Fisher Scientific Inc., San Jose, CA, USA) and ammonium acetate (Fluka, Chemika-Biochemika, Basil, Switzerland) were also used.
5.3. Sample preparation Plant samples were freeze dried for 24 h using a laboratory lyophylizator (LIO-5PDGT, 5 Pa s.r.l., Trezzano sul Naviglio, Italy) and then milled. 50 mg of homogenized plant material were extracted by adding 1500 μL of solvent mixture of H2O/MeOH/HCOOH (79:20:1, v/ v) and stirred for 90 min at 200 strokes/min on a shaker. The extract was centrifuged for 10 min at 14000 rpm at room temperature and
Fig. 5. Scores and Loadings plots obtained for PCA analysis of roots and leaves treated with DON. (L: leaves; R: roots; high: 100 μg DON; low: 12.5 μg DON). 5
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Appendix A. Supplementary data
subjected to UHPLC-HRMS analysis. All medium samples were diluted with H2O/MeOH (80:20, v/v) to achieve a final ratio of 1:1 (v/v), vortexed for 1 min and then subjected to UHPLC-HRMS analysis.
Supplementary data to this article can be found online at https:// doi.org/10.1016/j.phytochem.2019.112194.
5.4. UHPLC/HRMS analysis References Roots and leaves extracts were subjected to HRMS in order to investigate the formation of DON biotransformation products. For the chromatographic separation, a Synergi 4U Hydro-RP 150 × 2.0 mm (Phenomenex, Torrance, CA, USA) heated to 30 °C was used. 3 μl of sample extract was injected into the system; the flow rate was 0.3 mL/ min. Gradient elution was performed by using 1 mM ammonium acetate in H2O (eluent A) and MeOH (eluent B) both acidified with 0.5% acetic acid. Initial conditions were set at 5% B followed by a linear change to 10% B in 2 min. After 2 min of isocratic step (10%B) B% increased up to 69% in 20 min. Column was then washed for 4 min with 100% B followed by a reconditioning step for 5 min using initial composition of mobile phases. The total run time was 29 min. UHPLC-HRMS full scan spectra were recorded both in positive and negative ionization mode using Q-Exactive™ high resolution mass spectrometer (Thermo Scientific, Bremen, Germany) equipped with electrospray ionization. The Q-Exactive mass analyzer was operated in the full MS/data dependent MS/MS mode (full MS–dd-MS/MS) at following parameters: sheath and auxiliary gas flow rates 32 and 7 arbitrary units, respectively; spray voltage 3.3 kV; heater temperature 220 °C; capillary temperature 250 °C, and S-lens RF level 60. Following parameters were used in full MS mode: resolution 70,000 FWHM (defined for m/z 200; 3 Hz), scan range 100–1000 m/z, automatic gain control (AGC) target 3e6, maximum inject time (IT) 200 ms. Parameters for dd-MS/MS mode: intensity threshold 1e4, resolution 17,500 FWHM (defined for m/z 200; 12 Hz), scan range 50 – fragmented mass m/z (m/ z +25), AGC target 2e5, maximum IT 50 ms, normalized collision energy (NCE) 35% with ± 25% step.
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Righetti, L., Dellafiora, L., Cavanna, D., Rolli, E., Galaverna, G., Bruni, R., Suman, M., Dall'Asta, C., 2018. Identification of acetylated derivatives of zearalenone as novel plant metabolites by high-resolution mass spectrometry. Analytical and Bionalytical Chemistry 410, 5583–5592. Righetti, L., Körber, T., Rolli, E., Galaverna, G., Suman, M., Bruni, R., Dall'Asta, C., 2019. Plant biotransformation of T2 and HT2 toxin in cultured organs of Triticum durum Desf. Sci. Rep. 9, 14320. Rolli, E., Righetti, L., Galaverna, G., Suman, M., Dall'Asta, C., Bruni, R., 2018. Zearalenone uptake and biotransformation in micropropagated Triticum durum Desf. Plants: a xenobolomic approach. J. Agric. Food Chem. 66, 1523–1532. Ruttkies, C., Schymanski, E.L., Wolf, S., Hollender, J., Neumann, S., 2016. MetFrag relaunched: incorporating strategies beyond in silico fragmentation. J. Cheminf. 29 (8), 3. Sandermann Jr., H., 1994. Higher plant metabolism of xenobiotics: the 'green liver' concept. 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5.5. DON metabolite prediction and putative identification Phase I and phase II DON metabolites were computed by using MetaSite (http://moldiscovery.com, Borehamwood, UK) accounting only for the first generation of metabolites. The full identification by using commercial standards has been performed only for DON and DON-Glc while phase II metabolites were identified by comparison of the fragments experimentally obtained with those previously reported in literature (Kluger et al., 2015; Zachariasova et al., 2012; Spaggiari et al., 2019). Since DON phase I metabolites have been never observed before, experimentally acquired HRMS/MS data were compared with in silico fragmentation obtained uploading in-house generated SDF files into MetFrag (Ruttkies et al., 2016). Tentative and identified metabolites are listed in Tables 1 and 2. 5.6. Statistical analysis All statistical analyses were performed using IBM SPSS v.23.0 (SPSS Italia. Bologna. Italy). Data were analysed by Kruskal-Wallis test followed by Duncan post-hoc test (α = 0.05). Metabolite intensities in roots and leaves were pre-processed using the logarithmic transformation then unsupervised PCA model was built using SPSS. Acknowledgements This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The authors acknowledge with gratitude Dr. Luca Dellafiora for the bioinformatic support and Mr. Daniele Cavanna (Advanced Laboratory Research Barilla G.R. F.lli SpA) for the technical assistance. 6
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Hametner, C., Fröhlich, J., Adam, G., Krska, R., Schuhmacher, R., 2015. Deoxynivalenol-sulfates: identification and quantification of novel conjugated (masked) mycotoxins in wheat. Anal. Bioanal. Chem. 407, 1033–1039. Zachariasova, M., Vaclavikova, M., Lacina, O., Vaclavik, L., Hajslova, J., 2012. Deoxynivalenol oligoglycosides: new “masked” Fusarium toxins occurring in malt, beer, and breadstuff. J. Agric. Food Chem. 60, 9280–9291.
van der Lee, T., Zhang, H., van Diepeningen, A., Waalwijk, C., 2015. Biogeography of Fusarium graminearum species complex and chemotypes: a review. Food Addit. Contam. A 32 (4), 453–460. Visconti, A., Pascale, M., 2010. An overview on Fusarium mycotoxins in the durum wheat pasta production chain. Cereal Chem. 87, 21–27. Warth, B., Fruhmann, F., Wiesenberger, G., Kluger, B., Sarkanj, B., Lemmens, M.,
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Exploiting the potential of micropropagated durum wheat organs as modified mycotoxin biofactories: The case of deoxynivalenol
T
Laura Righettia,∗, Tito Damiania, Enrico Rollib, Gianni Galavernaa, Michele Sumanc, Renato Brunia, Chiara Dall’Astaa a
Department of Food and Drug, University of Parma, Parco Area delle Scienze 27/A, 43124, Parma, Italy Deparment of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Via Università 12, 43121, Parma, Italy c Barilla G.R. F.lli SpA, Advanced Laboratory Research, via Mantova 166, Parma, Italy b
A R T I C LE I N FO
A B S T R A C T
Keywords: Metabolism Wheat Biotransformation High resolution mass spectrometry Masked mycotoxins Plant defense
This study aimed to investigate the potential of in vitro wheat model as biofactory for masked mycotoxin production. Micropropagated durum wheat organs (leaves and roots) were treated during a 14-day time span on a proper medium spiked with deoxynivalenol (DON). After the treatment, DON absorption from culture media was evaluated while roots and leaves were profiled by UHPLC-HRMS to investigate the DON biotransformation products. A total of 10 metabolites have been annotated in both roots and leaves. In particular, 5 phase I metabolites never reported before were putatively identified, suggesting the viability of the model as a tool to investigate the interplay between mycotoxins and wheat. In addition, 5 phase II metabolites previously reported in wheat grown under open field conditions, were identified in both roots and leaves, thus demonstrating the reliability of the cultured organs as model system for wheat plants. An organ-dependent difference in DON uptake and biotransformation was observed, since roots contained a high amount of untransformed DON, while leaves were able to effectively biotransform DON to its glycosylated form and other relevant metabolites. With the perspective of using cultured organs as biofactories for modified mycotoxin production, leaves seemed therefore to offer the best absorption and production yield.
1. Introduction Trichothecenes constitute a large family of stable and persistent sesquiterpenoids produced by widely distributed fungal genera including Fusarium, Trichoderma, Cephalosporium and Stachybotrys (Ferrigo et al., 2016). These mycotoxins represent a key weapon in the chemical warfare between fungi and plants and, albeit presenting different abundances and toxicities, they share an extremely reactive epoxy group between C-12 and C-13, whose presence is deemed essential to exert a toxic behavior in eukaryotic organisms (Van der Leet et al., 2015). Deoxynivalenol, in particular, is actively involved in the spread and establishment of Fusarium in infected plants. Produced in a cocktail that may also include nivalenol, 3-acetyl-deoxynivalenol and 15-acetyl-deoxynivalenol, DON is both the most frequently found and the most abundantly detected mycotoxin biosynthesized by toxigenic strains of Fusarium graminearum and to a minor degree by F. nivale, F.
culmorum and F. sambucinum (Asam et al., 2017). Both DON and related compounds act in eukaryotic cells by inhibiting 60S ribosomial subunits and protein, DNA and RNA synthesis, impairing the mitochondrial function and hampering the plant defensive process of apoptosis (Diamond et al., 2013). In mammalians, following chronic or acute exposure, DON may induce a broad spectrum of symptoms including necrosis of intestinal tract, liver and bone marrow with leukopenia, emesis and diarrhea, ultimately resulting in potential deadly relapses (Escrivá et al., 2015). Following its common presence in foods, DON is therefore considered a worldwide target for risk assessment and food safety (Visconti and Pascale, 2010; Zachariasova et al., 2012). In view of consumer protection, the European Community has defined maximum contamination levels accepted for human consumption (EC 1126/2007). As most xenobiotics, mycotoxins as DON may undergo biotransformation as the result of regio-selective and stereospecific
Abbreviations: DON, deoxynivalenol; DON-Glc, deoxynivalenol glucoside; DON-MalGlc, deoxynivalenol malonyl-glucoside; DON-GSH, deoxynivalenol glutathione; rpm, revolutions/min; DMSO, dimethyl sulfoxide; UHPLC, ultra high performance liquid chromatography; HRMS, high-resolution mass spectrometry; PCA, Principal Component Analysis; cv, cultivar ∗ Corresponding author. E-mail address: [email protected] (L. Righetti). https://doi.org/10.1016/j.phytochem.2019.112194 Received 8 August 2019; Received in revised form 23 October 2019; Accepted 31 October 2019 0031-9422/ © 2019 Elsevier Ltd. All rights reserved.
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reactions mediated by plant enzymes (Sandermann, 1994; Berthiller et al., 2013). To facilitate (or prevent) translocation, compartmentation, storage and eventual disposal, mycotoxins are often biochemically conjugated to endogenous aminoacidic, sugar, malonyl, sulphate, gluthatione moieties to organic xenobiotics, often reducing their in planta toxicity. These conjugated metabolites may then be deposited in the apoplast, bound to cell wall or segregated in the vacuole of infected plants according to their reactivity and water solubility (Siminszky, 2006; Edwards et al., 2011). This masking mechanism, responsible for the formation in planta of the so called “masked mycotoxins”, represents an effective and well-known plant strategy to cope with the toxicity of trichothecenes (Freire and Sant’Ana, 2018). In Fusarium-infected cereals or spikelets injected with DON, the mycotoxin undergoes phase II conjugation to its most common masked form DON-3-glucoside, while other conjugated forms like DON-hexitol and DON-hexosides, or DON-gluthatione and its degradation products DON-S-cysteinyl-glycine, DON-S-cysteine, DON-3-sulphate and DON15-sulphate have been described (Warth et al., 2015; Kluger et al., 2015). Detecting and quantifying masked forms of DON, along with a clear definition of their actual toxicity as single compounds or as cocktails, is currently deemed critical in determining safe consumption levels. In fact, masked forms of DON are not monitored in routine food control, no maximum contamination levels accepted for human consumption may be properly assessed and their actual toxicity in both humans and animals is de facto uncertain. However, the consensus is that their disregarding may lead to a consistent underestimation of actual intake and impact on human and animal health (Dellafiora and Dall’Asta, 2016; Gratz, 2017). Accordingly, the European Food Safety Authority has recently released a scientific opinion on DON and its modified forms, stating that the occurrence of these compounds should be evaluated in pool for risk assessment purposes, and therefore forthcoming regulation should cover the sum of DON and its modified forms instead of the single parent compound (EFSA, 2017). At the same time, the development of comprehensive screening of their presence in foods and the precise evaluation of in vivo bioactivity of the masked mycotoxin cocktail is made difficult by some practical limitations (Krska et al., 2017). For instance, the lack of readily available of masked mycotoxins in pure form or in nature-like mixtures, as well as of reference materials for validation or to be used as standard calibrants (Tangni et al., 2017). On this regard, plant cell, organ cultures or entire plants may be investigated as potential biofactories to produce pure masked mycotoxins or their calibrated mixtures, using an approach similar to the one developed for pesticides and pharmaceuticals, but few investigations are available to evaluate the feasibility of such process (Bártíková et al., 2015). If properly scaled, a model based on wheat may allow the controlled production of specific biotransformation products, both in isolate forms or in nature-like mixtures that can be used for analytical and toxicological purposes and which are not realistically attainable by chemical semi-synthesis (Berthiller et al., 2006; Righetti et al., 2017; Abhilash et al., 2009). Therefore, this research was performed to investigate the potential radical and leaf absorption, assimilation and metabolic fate of different DON administrations in two micropropagated Triticum durum Desf cultivars by monitoring the eventual production of masked mycotoxins with a targeted-untargeted approach.
Fig. 1. Residual DON in culture medium during growth of micropropagated organs of T. durum cultivars Kova and Svevo. A) leaves; B) roots.
media, a semi-quantitative determination of DON and DON3Glc, followed by an untargeted monitoring of phase I and II plant metabolites of DON. Two durum wheat cultivars were selected as model system, Kofa and Svevo, found as more and less resistant towards Fusarium spp. infection in previous studies (Cirlini et al., 2013). 2.1. Evidence of plant uptake and absorption The uptake of DON from medium in cultured organs is generally lower in roots than in leaves, as shown in Fig. 1. The average residual DON in the medium after 14 days is about 79–83% and 40–53% of the administered dose in Kofa and Svevo cv., respectively. Consistent with this, the DON uptake is lower in Kofa than in Svevo. 2.2. Biotransformation of DON in cultured roots and leaves After 14 days of incubation with DON, leaves and roots were analysed by UHPLC-HRMS to evaluate the formation of metabolites. The parent compound was found in both cultured organs, although at lower amounts compared to other metabolites, confirming its intensive biotransformation. Semiquantitative data collected within the study are represented in Fig. 2. In both cultivars, residual DON is higher in roots than in leaves (9.3% vs 2.9%, respectively), while DON-3Glc and other metabolites are more abundant in leaves. In both Kofa and Svevo cv, DON-3Glc is the main metabolite in roots (68% and 57%, respectively), while in leaves the biotransformation process has led mainly to the accumulation of other metabolites (78% and 66%, respectively).
2. Results
2.3. Untargeted screening of phase I and phase II DON conjugates in roots and leaves
The approach presented herein is based on the assumption that healthy, micropropagated wheat plants may absorb and metabolize DON from isolated organs (leaves and roots) during a 14-day time span growth on a proper medium, as already demonstrated in our previous papers (Righetti et al., 2017; Rolli et al., 2018). To demonstrate that and to evaluate the potential of the model, three separate steps were undertaken: an evaluation of the actual uptake/absorption from culture
In order to identify the biotransformation products obtained in roots and leaves, UHPLC-HRMS analysis was performed as previously reported (Righetti et al., 2017, 2018). A total of 10 metabolites have been annotated in both roots and leaves. In particular, 5 phase I and 5 phase II metabolites are reported in Table 1, Table 2 and Table S1. In some cases, different peaks were assigned to a single putative metabolite, in 2
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Fig. 2. Pie chart representing the % of DON biotransformation after 14 days exposure. Each ring represents the total % of derivatives in each organ considering semiquantitative data of unaltered DON, DON-3-Glucoside and the whole spectra of phase I and phase II derivates detected in roots and leaves.
such as oxidation, giving rise to the formation of carbox-DON. Furthermore, the involvement of epoxidation and de-epoxidation reactions has been highlighted for several xenobiotics in plant (Bártíková et al., 2015) and in mammals, with the conversion of DON into de-epoxy-DON (DOM). DON phase I metabolite HRMS/MS data were compared with in silico fragmentation obtained uploading in-house generated SDF files into MetFrag (Ruttkies et al., 2016), since reference spectra were not available in literature. Putatively identified metabolites are listed in Table 1 and Table S1 and the HRMS/MS spectra are reported in Fig S3–S7 (Supplementary Data). Among considered metabolites, DON-3Glc, DON-diGlc, DONMalGlc, DON-GSH, and Hydroxyl-DON have been found at relevant abundance in all the considered samples. For this reason, their abundance has been used for chemometric analysis. A factorial ANOVA followed by post hoc Tukey's test, was carried out to highlight possible organ-, cultivar- and dose-dependent effects. Data were log-transformed before analysis. Both the administration dose (12.5 μg and 100 μg) and organ (root and leaf) were found significant factors (p = 0.016 and 0.006, respectively), whereas no effect was found for the cultivar and the combination of factors. Significant differences between groups are reported in Fig. 4. The same data have been later used for Principal Component Analysis (PCA), in order to identify further clusterization between samples. Score and Loading plots are reported in Fig. 5A and B. Variance is well explained by Factor 1 and Factor 2 (overall 85.02%). From score and loading plot, it can be noticed that the administered dose is the main affecting parameters, allowing for the separation along Factor 1. However, Factor 2 pinpoints a very clear sample clustering according to the organ and based on the content of single compounds.
consideration of the possible isomeric forms. All the annotated phase II metabolites (Table 2) have been previously reported in wheat grown in greenhouse (Kluger et al., 2015; Cirlini et al., 2013) or under open field conditions (Zachariasova et al., 2012; Spaggiari et al., 2019), thus demonstrating the reliability of the cultured organs as model system for wheat plants. Their structures are depicted in Fig. 1, Supplementary Data. DON di- and -tri-glucosides were identified based on in-source fragmentation (Zachariasova et al., 2012), detecting fragments at m/z 589.2124 and 751.2668 corresponding to [M−CH2O–H]− ions of DON di- and -tri-glucosides, respectively with calculated maximum mass errors not higher than 3 ppm. The presence of DON-malonyl-glucoside (DON-MalGlc) and DON-gluthatione (DON-GSH) was confirmed by the comparison of HRMS fragmentation patter previously elucidated by Kluger et al., (2015). The HRMS/MS spectra are reported in Supplementary Data. Five phase I metabolites are, up to our knowledge, reported for first time in plants and are summarized in Table 1 and Table S1. The formation of these compounds is expected when considering the enzymatic machinery of plants. CYPs commonly catalyze monooxygenation, including hydroxylations, epoxidations, dealkylations, decarboxylations and isomerizations of xenobiotics, but they can also act as reductases (Bártíková et al., 2015). Possible structures and the putative enzymes involved are reported in Fig. 3, as obtained by SOM prediction analysis. The major metabolic pathways involved are hydroxylation, oxidation and epoxidation of parent DON. In particular, mono hydroxy-DON was reported as the predominant phase I metabolite, in agreement with previous studies on other mycotoxins. Consistent with this, the hydroxy form of ZEN (Righetti et al., 2017) and other trichothecenes including T2 and HT2 (Righetti et al., 2019) have been already confirmed in planta. Hydroxy-DON may undergo further metabolization reaction, Table 1 Putatively annotated phase I DON metabolites. Formula
RT (min)
Theoretical m/z [M + CH3COO]-
Mass error (ppm)
DON 10en-8,9-dione-demethyl DONb
C15H20O6 C14H16O7
355.1382 355.1023
Carbox-DONb
C15H18O8
Hydroxy-DON/9,10–12,13diepoxy-DONb 9,10di-hydroxy-dehydro DONb Hydroxy-carbox-DONb
C15H20O7 C15H22O8 C15H18O9
8.9 12.5 13.3 13.5 12.2 12.9 13.6 13.5 10.0 6.2
0.2 1.1 1.6 1.5 3.8 1.3 1.7 3.3 1.2 3.9
Metabolites a
a b
Confirmation with standard by comparison of accurate mass, HRMS/MS and RT. Annotation with accurate mass, elemental formula and HRMS/MS spectra. 3
385.1129
371.1342 389.1442 401.1078
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Table 2 Phase II DON metabolites annotated with accurate mass, elemental formula and HRMS/MS spectra compared to those previously reported in literature. Metabolites DON-3-Glc DON-di-Glc DON-tri-Glc DON-malonyl-glucoside DON-glutathione
Formula C21H30O11 C27H40O16 C33H50O21 C24H32O14 C25H37N3O12S
RT (min) 9.2 8.5 7.9 11.28 7.9
Theoretical m/z 517.1915 679.2443 841.2972 567.1684 604.2171
3. Discussion
Adduct [M + CH3COO][M + CH3COO][M + CH3COO][M+Na]+ [M+H]+
Mass error (ppm) 1.1 1.8 2.9 1.6 −0.1
References STD [Zachariasova et al., 2012] [Zachariasova et al., 2012] [Kluger et al., 2015] [Kluger et al., 2015]
2017). This can be explained in consideration of the relatively low logPow of about −0.97 for DON, corresponding to a rather hydrophilic compound and thus consistent with a low root uptake of the chemicals (Briggs et al., 1982; Paterson et al., 1994). On the other hand, leaves offer a higher surface of passive absorption and a quicker biotransformation rate. This could be explained taking into consideration that, under natural field conditions, leaves are mainly exposed to fungal pathogen attack, and therefore could have developed organ-related biological machineries to effectively counteract DON accumulation. Furthermore, once absorbed by the root, DON access to the cellular cytoplasm and its complete exposure to the detoxifying enzymatic pools may be limited by physical absorption to the exodermis or by a higher distribution along the apoplastic route, resulting in a reduced biotransformation. A slight cultivar-dependent difference in uptake from the medium has been observed for both roots and leaves. Differences between cultivars may be explained by factors such as degree of root growth, transpiration rates, and the size and shape of the leaf material. In addition, differences in plant lipid contents may also be important as this can affect the sorption of hydrophobic chemicals. Regarding the DON biotransformation products, the proposed model system was suitable for the production of those modified forms of DON already detected in the field and thus of market relevance as analytical standards as a nature-like mixture. For this reason, more attention was given to those metabolites already reported in literature and, in particular, considered valuable for risk assessment in the scientific opinion on DON and its modified forms, as set by the European Food Safety Authority (EFSA, 2017). It can be noticed that roots contained a high amount of untransformed DON, while leaves are able to effectively biotransform DON to DON-3-Glc and other relevant metabolites. With the perspective of using cultured organs as biofactories for modified mycotoxin production, leaves seemed therefore to offer the best absorption and production yield.
The present study aims at exploring the potential of wheat organs as masked mycotoxin biofactories. Once treated with DON, our model system returned a spectrum of metabolites, among whose the most abundant were the main phase II compounds already observed in cereals in greenhouse experiments and/or in the field (i.e. DON-3Glc, DON-diGlc, DON-triGlc, DONMalGlc, DON-GSH) (Kluger et al., 2015; Cirlini et al., 2013; Zachariasova et al., 2012; Spaggiari et al., 2019), thus ensuring the reliability of wheat cultured organs in producing compounds relevant for risk assessment by mere exposure to such mycotoxin without being mechanically inoculated nor in presence of an actual infection. In addition, the model system was able to return several phase I metabolites never observed before. The formation of these compounds is expected when considering the enzymatic machinery of plants. However, since they act as intermediate structures for further biotransformations by phase II metabolism, their accumulation in crops is unlikely. For this reason, organ models proposed herein could be successfully used for the full elucidation of plant metabolic pathways as well. In order to evaluate the costs and upscaling conditions, several factors have been considered within this study, among them the cultivar, the organ and the dose. While an expected dose-related accumulation was observed, the one-order magnitude difference in administered dose (12.5 μg and 100 μg) was not reflected in a comparable difference in uptake and production. Therefore, for the exploitation of cultured wheat organs as biofactories for masked DON production, the lower dose could be successfully used. Furthermore, the non-absorbed standard remaining in the growing medium, ranging from 40% to 83% of the initial dose depending on the organ, could be re-used for further experiments, as in a circular model. On this account, a relevant organ dependent difference in uptake and production has been observed, with the residual amount in the medium higher in roots than in leaves. In addition, DON uptake observed in this work was significantly lower than the uptake reported for ZEN in our previous work (Righetti et al.,
Fig. 3. Proposed structures and route of formation of DON phase I metabolites. 4
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Fig. 4. Log-transformed UHPLC-HRMS relative abundance of DON and its main metabolites according to organ and administered dose.
4. Conclusion
5.2. Culture medium and plant materials
The present studies deepen our understandings of the contribution of plant metabolism in the biosynthesis of masked mycotoxins. A total of 10 DON metabolites were annotated in both roots and leaves. In particular, 5 phase II metabolites were confirmed from previous studies, while 5 phase I metabolites were reported for the first time. Furthermore, the in vitro wheat model prooved its potential to foresee the development of biocatalytic tools for the production of masked mycotoxins to be used as reference materials, with leaves representing the most likely candidate organ.
Two commercial durum wheat (Triticum durum Desf.) varieties, namely Kofa and Svevo, were selected for their different Fusarium Head Blight resistance (Cirlini et al., 2013). Culture medium was prepared as previously reported (Righetti et al., 2017). Experiments were performed in triplicate and repeated three times. For organ micropropagation and mycotoxin administration, the protocols reported by Righetti et al. (2017) and Rolli et al. (2018) were followed. Briefly, DON was dissolved in an adequate amount of DMSO so that the final concentration of the solvent in culture medium did not exceed the one considered toxic (0.2%) with mycotoxin being at the final concentration of 12.5 μg/L and 100 μg/L. Solutions were sterilized by 0.2-μm filters and dissolved in the liquid Murashige-Skoog medium. At the end of the experiment organ cultures exposed up to 100 μg/L DON showed no visible degradation.
5. Experimental 5.1. Chemicals Analytical standards of DON (100 μg mL−1 in acetonitrile), and DON-3Glc (solution in acetonitrile 50.6 μg mL−1) were purchased from Romer Labs® (Tulln, Austria). HPLC-grade methanol, acetonitrile and acetic acid, as well as dimethylsulfoxide (DMSO) were purchased from Sigma-Aldrich (Taufkirchen, Germany); bidistilled water was obtained using a Milli-Q System (Millipore, Bedford, MA, USA). MS-grade formic acid from Fisher Chemical (Thermo Fisher Scientific Inc., San Jose, CA, USA) and ammonium acetate (Fluka, Chemika-Biochemika, Basil, Switzerland) were also used.
5.3. Sample preparation Plant samples were freeze dried for 24 h using a laboratory lyophylizator (LIO-5PDGT, 5 Pa s.r.l., Trezzano sul Naviglio, Italy) and then milled. 50 mg of homogenized plant material were extracted by adding 1500 μL of solvent mixture of H2O/MeOH/HCOOH (79:20:1, v/ v) and stirred for 90 min at 200 strokes/min on a shaker. The extract was centrifuged for 10 min at 14000 rpm at room temperature and
Fig. 5. Scores and Loadings plots obtained for PCA analysis of roots and leaves treated with DON. (L: leaves; R: roots; high: 100 μg DON; low: 12.5 μg DON). 5
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Appendix A. Supplementary data
subjected to UHPLC-HRMS analysis. All medium samples were diluted with H2O/MeOH (80:20, v/v) to achieve a final ratio of 1:1 (v/v), vortexed for 1 min and then subjected to UHPLC-HRMS analysis.
Supplementary data to this article can be found online at https:// doi.org/10.1016/j.phytochem.2019.112194.
5.4. UHPLC/HRMS analysis References Roots and leaves extracts were subjected to HRMS in order to investigate the formation of DON biotransformation products. For the chromatographic separation, a Synergi 4U Hydro-RP 150 × 2.0 mm (Phenomenex, Torrance, CA, USA) heated to 30 °C was used. 3 μl of sample extract was injected into the system; the flow rate was 0.3 mL/ min. Gradient elution was performed by using 1 mM ammonium acetate in H2O (eluent A) and MeOH (eluent B) both acidified with 0.5% acetic acid. Initial conditions were set at 5% B followed by a linear change to 10% B in 2 min. After 2 min of isocratic step (10%B) B% increased up to 69% in 20 min. Column was then washed for 4 min with 100% B followed by a reconditioning step for 5 min using initial composition of mobile phases. The total run time was 29 min. UHPLC-HRMS full scan spectra were recorded both in positive and negative ionization mode using Q-Exactive™ high resolution mass spectrometer (Thermo Scientific, Bremen, Germany) equipped with electrospray ionization. The Q-Exactive mass analyzer was operated in the full MS/data dependent MS/MS mode (full MS–dd-MS/MS) at following parameters: sheath and auxiliary gas flow rates 32 and 7 arbitrary units, respectively; spray voltage 3.3 kV; heater temperature 220 °C; capillary temperature 250 °C, and S-lens RF level 60. Following parameters were used in full MS mode: resolution 70,000 FWHM (defined for m/z 200; 3 Hz), scan range 100–1000 m/z, automatic gain control (AGC) target 3e6, maximum inject time (IT) 200 ms. Parameters for dd-MS/MS mode: intensity threshold 1e4, resolution 17,500 FWHM (defined for m/z 200; 12 Hz), scan range 50 – fragmented mass m/z (m/ z +25), AGC target 2e5, maximum IT 50 ms, normalized collision energy (NCE) 35% with ± 25% step.
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5.5. DON metabolite prediction and putative identification Phase I and phase II DON metabolites were computed by using MetaSite (http://moldiscovery.com, Borehamwood, UK) accounting only for the first generation of metabolites. The full identification by using commercial standards has been performed only for DON and DON-Glc while phase II metabolites were identified by comparison of the fragments experimentally obtained with those previously reported in literature (Kluger et al., 2015; Zachariasova et al., 2012; Spaggiari et al., 2019). Since DON phase I metabolites have been never observed before, experimentally acquired HRMS/MS data were compared with in silico fragmentation obtained uploading in-house generated SDF files into MetFrag (Ruttkies et al., 2016). Tentative and identified metabolites are listed in Tables 1 and 2. 5.6. Statistical analysis All statistical analyses were performed using IBM SPSS v.23.0 (SPSS Italia. Bologna. Italy). Data were analysed by Kruskal-Wallis test followed by Duncan post-hoc test (α = 0.05). Metabolite intensities in roots and leaves were pre-processed using the logarithmic transformation then unsupervised PCA model was built using SPSS. Acknowledgements This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The authors acknowledge with gratitude Dr. Luca Dellafiora for the bioinformatic support and Mr. Daniele Cavanna (Advanced Laboratory Research Barilla G.R. F.lli SpA) for the technical assistance. 6
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