Leaf metabolic response to water deficit in Pinus pinaster Ait. relies upon ontogeny and genotype

Accepted Manuscript Title: Leaf metabolic response to water deficit in Pinus pinaster Ait. relies upon ontogeny and genotype Authors: Br´ıgida Fern´andez de Sim´on, Miriam Sanz, Mar´ıa Teresa Cervera, Ernani Pinto, Ismael Aranda, Estrella Cadah´ıa PII: DOI: Reference:

S0098-8472(17)30131-4 http://dx.doi.org/doi:10.1016/j.envexpbot.2017.05.017 EEB 3240

To appear in:

Environmental and Experimental Botany

Received date: Revised date: Accepted date:

1-3-2017 9-5-2017 27-5-2017

Please cite this article as: de Sim´on, Br´ıgida Fern´andez, Sanz, Miriam, Cervera, Mar´ıa Teresa, Pinto, Ernani, Aranda, Ismael, Cadah´ıa, Estrella, Leaf metabolic response to water deficit in Pinus pinaster Ait.relies upon ontogeny and genotype.Environmental and Experimental Botany http://dx.doi.org/10.1016/j.envexpbot.2017.05.017 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Leaf metabolic response to water deficit in Pinus pinaster Ait. relies upon ontogeny and genotype Brígida Fernández de Simón*a, Miriam Sanzb, María Teresa Cerverac, Ernani Pintob, Ismael Arandac, Estrella Cadahíaa a

INIA-CIFOR, Departamento de Industrias Forestales, Carretera de A Coruña Km 7.5, 28040, Madrid, Spain School of Pharmaceutical Sciences, University of São Paulo, Bl 17 05508-900, São Paulo, SP, Brazil c INIA-CIFOR, Departamento de Ecología y Genética Forestal, Carretera de A Coruña Km 7.5, 28040, Madrid, Spain b

*Corresponding author. Tel.: +34 913476789; fax: +34 913476767 E-mail addresses: [email protected] (B. Fernández de Simón), [email protected] (M. Sanz), [email protected] (M.T. Cervera), [email protected] (E. Pinto), [email protected] (I. Aranda), [email protected] (E. Cadahía)

Highlights     

Drought effect in metabolome of adult and juvenile P. pinaster needles was studied Drought increased osmotically active substances, flavonoids and terpenoids Observed changes in the metabolome relies ontogeny Juvenile needles are better prepared for adverse growth conditions and stress Genotype drought resistance and ontogeny determine flavonoid levels in needles

ABSTRACT Pinus pimaster Aiton displays marked heteroblasty during its vegetative phase, showing complex interactions between developmental processes and environmental adaptation, with a patent differentiation in functional performance according to leaf type resulting from heteroblasty. In this work, untargeted quantitative metabolic profiling in adult and juvenile needles of four water-deficit stressed P. pinaster genotypes was investigated to know if metabolic responses to drought are genotype-dependent and vary according to the stage of needle ontogeny. Among the changes in metabolome, it highlights the increase of osmotically active substances, as well as the overproduction of antioxidant compounds by up-regulating ascorbate, shikimate/phenylalanine and phenylpropanoid metabolic pathways. Moreover, significant interclonal quantitative variations were also found at different levels, in both primary and secondary metabolism pathways, although terpenoids and specially flavonoids showed the highest significance. A surprising result was the ontogenetic changes in metabolic profiles. Juvenile needles contain significant higher levels of UV screener and antioxidant flavonoids. The level of drought tolerance of a genotype and the ontogenetic stage were important factors in determining 1

the drought-induced level of flavonoid increase in needles of a given genotype. Regarding terpenoids, the significant drought-induced accumulation of neutral diterpenes in juvenile needles, and mono- and sesquiterpenes in adults, was genotype dependent regardless its degree of drought tolerance. These results point to flavonoids as very versatile metabolites in maritime pine needle, acting like important compounds modulating not only drought acclimation but also changes in needle metabolism associated with developmental processes such as heteroblasty. Keywords. Pinus pinaster, metabolic profiling, needle, drought, heteroblasty, genotype

Abbreviations PPMs=plant primary metabolites; PSMs=plant secondary metabolites; A=Adult needle; J=Juvenile needle, WW=well-watered; WS=water stressed; AWS=Adult needle well-watered; AWS=Adult needle water stressed; JWW=Juvenile needle well-watered; JWS=Juvenile needle water stressed; GC-MS=gas chromatography/mass spectrometry; LC-QTOF=liquid chromatography-quadrupole time-of-flight mass spectrometry; PLS-DA=multivariate partial least-squares discriminant analysis

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1. Introduction Maritime pine (Pinus pinaster Aiton) is one of the most widely spread conifer in the southwestern area of the Mediterranean region including the Atlantic zone from the Aquitaine region of France to the West coast of Morocco (Alía and Martin, 2003). It plays an important role in its ecosystems and has a high interest for timber and oleoresin processing industries. In this European region, drought episodes are to become more frequent and severe, by either declining rainfall or higher water stress allied with hot climate, influencing the growth, distribution and survival of trees (Williams et al., 2013). However, phenotypic plasticity and the adaptive potential of the species, determined by their high genetic diversity (Aranda et al., 2010), bring about development of current local adaptations to environmental stressors, and may also help to cope with future climate driven changes (Gaspar et al., 2013; Schaberg et al. 2008). Water stress results in a reduction and reorganization of the tree metabolism in order to assure its high degree of homeostasis, which is often accomplished by maintaining essential metabolism and synthesis of metabolites with stress-protective and signaling properties. That includes production of compatible solutes (e.g. sugars, amino acids, cyclitols, or methylated quaternary ammonium compounds) (Hare et al., 2002). These compounds are able to stabilize proteins and cellular structures and/or maintain cell turgor by osmotic adjustment under water stress. They also take part in redox metabolism to remove excess levels of ROS (reactive oxygen species) and maintain the cellular redox balance (Barchet et al., 2013; Krasensky and Jonak, 2012; Noctor et al., 2015). In forest trees, metabolic response to drought varies significantly depending on the species and their inherent resilience to drought (Piper, 2011; Rodriguez-Calcerrada et al., 2011; Warren et al., 2011). However, intra-specific variations have been also found at provenance, genotype, and organ levels (Aranda et al., 2017; Barchet et al., 2014; Du et al., 2016; Granda et al., 2014, Hamanishi et al., 2015), highlighting the complexity of drought response among conifers. In the specific case of P. pinaster, some compounds such as cyclitols significantly increase in response to drought in roots, stems, and needles, but other metabolites differentially increase or decrease their levels depending on the organ analyzed in stressed trees (de Miguel et al., 2016; Meijón et al., 2016). In roots, a high percentage of metabolites show changes related with its role as a storage repository of sugars and amino acids, while the changes in metabolites from aerial organs 3

also target the maintenance of the antioxidant machinery (de Miguel et al., 2016). Among needle metabolites, flavonoid levels show strong correlation with the water regime of the geographic origin of the provenance; but also with a long lasting and moderate water shortage; as well as the seasonal patterns of accumulation related to the age of needles (Cañas et al., 2015; de Miguel et al., 2016; Meijón et al., 2016). A marked heterophylly and heteroblasty in P. pinaster has been described during its vegetative phase that shows complex interactions between developmental processes and environmental adaptation, with a patent differentiation in functional performance according to leaf type (Pardos et al., 2009; Zotz et al., 2011). Most studies have addressed the analysis of functional and morphological changes related to the ontogenetic state of needles, and few have studied this important developmental trait in relation to metabolic changes. They have mainly focused on plant primary metabolites (PPMs), with only a slight look over plant secondary metabolites (PSMs) such as some polyphenols and flavonoids, showing changes in flavonoid content in response to drought regarding the different ontogenetic stages of the needles (de Miguel et al., 2016). The flavonoid activity in plant adaptive response against diverse environmental stresses has been extensively studied (Cannac et al., 2011; Dixon and Paiva, 1995; Popovic et al., 2016; Winkel-Shirley, 2002). Recently, the antioxidant function of flavonoids was experimentally identified showing that the over-accumulation of flavonoids with strong antioxidant activity in vitro and in vivo enhanced the plants’ oxidative-stress and drought-stress tolerance (Nakabayashi et al., 2014; Nakabayashi and Saito, 2015), due to the antioxidant chemical character of overaccumulated flavonoids. It is inferred that the flavonoid accumulation in accordance with abiotic stress exposure is a late response implemented to protect plants. Despite their tremendous importance, flavonoids, phenylpropanoids and other phenolic compounds remain poorly characterized in needles from Pinus spp., highlighting the few published data about P. pinaster (Cannac et al., 2011; Kan & Howard, 2010; Karapandzova et al., 2015). Thus, it is necessary to perform a deeper study on phenolic composition of P. pinaster needles and their changes in response to drought, in order to understand their role in the drought resistance/tolerance mechanism. Taking into account that both phenolics and terpenoids are PSMs related with the reprogramming of plant metabolism in drought stressed plants (Niinemets, 2016), it is striking 4

that PSMs such as terpenoids have received scarce attention in the metabolomics studies of conifer drought response. In general, terpenoid needle profiles show changes regarding climatic conditions such as water availability, temperature and seasonality, suggesting different sensitivity to environmental conditions (Arrabal et al 2014; Blanch et al., 2009; Llusiá et al., 2006: Wallis et al., 2011). Water stress increases the concentration of monoterpenes in needles from different conifers (Llusiá et al., 2006; Turtola et al., 2003), but most of the published studies have been focused on terpenoid emission regarding stress, and therefore on those terpenes exhibiting a greater volatility, such as mono and sesquiterpenoids (Llusiá et al., 2016; Peñuelas and Staud, 2010). Thus, information on the evolution of the metabolic profile of other less volatile terpenoids, such as neutral and acid diterpenes, in drought response of conifer species is almost missing. These compounds are part of the mechanism of antioxidative protection in droughtstressed leaves, besides ascorbate and alpha-tocopherol, decreasing their levels as the drought progressed, giving rise to increased levels of its oxidation products (Munné-Bosch & Alegre, 2003). In this paper, adult (A) and juvenile (J) needles of four water-deficit stressed P. pinaster genotypes were analyzed. We carried out an untargeted metabolite profiling on both PPMs and PSMs, with two independent approaches, gas chromatography/mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-QTOF). The specific aim of this research was to study the variation in the metabolome associated to: i) a moderate water stress; ii) the needle heteroblasty and their different response to drought; and iii) the genotype-specific response to drought. We expect that water limitation led to the variation in the levels of different metabolites in a general drought metabolic response, showing also intra-specific variations, in an ontogenetic and genotypic-dependent way. 2. Materials and Methods 2.1. Plant material and experimental setting The genotypes of the study (see de Miguel et al., 2012 for details) derived from a F1 full-sib cross of maritime pine between a “drought tolerant” male parent from Oria (south-east of Spain: 37º31´N 2º21´W) and a “drought sensitive” female parent from Pontevedra (north-west of Spain: 42º10´N 8º30´W). Original provenance of parental material represents extremes in the range of 5

distribution of the species regarding dryness of climate. In the specific case of the studied clones they have shown differences in the functional response to drought (de Miguel et al., 2012; Sánchez-Gómez et al. 2017, under review). Several ramets (clonal replicates of each clonegenotype) were obtained from two year rooted cuttings of the four selected clones (6-7 healthy ramets per genotype). Rooting of the cuttings was done as described in de Miguel et al. (2012). At the beginning of the experiment two-year cuttings were transplanted to 6 L pots with a media growth of peat (Floratorf, 0-7 mm, Floragard Vertriebs GmbH, Oldenburg, Germany) and washed river sand (3:1 v/v mixture). Growth soil substrate was fertilized by adding a slowreleasing fertilizer in a ratio of 2 gr L-1 of growth substrate (Osmocote Plus fertilizer, 16-9-12 NPK+2 micronutrients, Scotts, Heerlen, Netherlands). Clones were transferred to a controlled environmental room after transplanting (Fitoclima 10000EHHF, Aralab Ltd, Sintra, Portugal), and were grown under optimal conditions during two months. Environmental conditions in the growth rooms were of 16h light/8 h dark for photoperiod. The photosynthetic photon flux density during light period was 800 μmol photons m-2 s-1 at the top of plants, and provided by a mixture of fluorescent tubes (Philips, Master TL-D, Super 80, 58W/840) and metal halide-sodium lamps (Osram, HQI-T, 250 W/D Pro+). Temperature was maintained to 20 ºC and 25 ºC in the dark and light period respectively, and relative humidity was on average around 70% inside the “walkin” controlled environmental room. The CO2 concentration of air was 400 μmolmol-1. Plants were well-watered to field capacity when soil volumetric water content –VWCs- dropped below 20 vol. % during an establishment phase lasting two months. The experimental layout was based on a factorial design with two factors: genotype (four different genotypes) and water availability (two levels: “well-watered conditions”: WW, and “water stressed conditions”: WS). Afterwards, water deficit was imposed for two months to half of the ramets that were randomly assigned. VWCs was individually monitored by soil moisture sensors (CS650-L, Campbell Scientific Inc., Logan, UT, USA) connected to data loggers (CR1000, Campbell Scientific Inc., Logan, UT, USA). Well-watered plants (WW-plants) were kept at a VWCs higher than 20 vol.% throughout the experiment while plants submitted to water deficit (WS-plants) were allowed to progressively deplete soil water content down to 5 vol.% from 15th March to 14th May. Intermediate targets (18, 15, 10, 8 vol.%) were established to homogenized the drought imposition rate among different ramets at the same pace whichever size of plants. Every day, VWCs was recorded and the water needed for each plant to reach the target was calculated based on current VWC s and 6

individual evapotranspiration rates. The target 5 vol.% for WS-plants was reached after 19 days water deficit was initiated and plants were kept at this stage for the rest of the water deficit period (43 additional days). The protocol allowed intensity, duration and effectiveness of water stress to be evenly applied regardless of plant size or genotypic-specific water consumption rates. Differences between individuals were only explained by watering and VWCs (29 ± 2 % and 4.8 ± 0.2 % for WW and WS plants respectively). The variation in needle gas exchange, chlorophyll fluorescence derived traits, and growth patterns in response to water deficit confirmed clonespecific response to water stress for the four tested genotypes: 4 and 147 were the most sensitive genotypes in response to water deficit while clones 132 and 144 were less sensitive (SanchezGómez et al., 2017, under review). 2.2. Extraction metabolites At the end of the drought period, adult forms (A) and juvenile forms (J) needles (Supplemental Fig. A1) were harvested from 25 studied plants, frozen immediately in liquid nitrogen, and stored at -80 ºC for the metabolomics study. They were then freeze-dried and stored in a dry and dark atmosphere until use. Before extraction, the freeze-dried leaves were ground to powder in a ball mill (Retsch Mm 300). It is well known that stomatal behavior and in general, leaf gas exchange follows a circadian rhythm. Thus, several physiological responses to drought are expected to vary along the day as well. For this reason, sample collection (harvest) was carried out within the time window 10am-12am, when stomatal conductance and photosynthetic rates are at their maximum. The extraction of terpenic compounds and fatty acids from needles was performed similarly to as in Fernández de Simón et al. (2001), by using 1 mL of petroleum ether/diethyl ether (1:1 v/v) to extract approx. 250 mg of needles. The extract was used for the neutral volatile terpene analysis directly by GC-MS, as well as fatty and resin acid methyl esters, after removal of solvent, redissolving with 1 ml of methanol, and adding 50 L of methylation reagent (tetra methyl ammonium hydroxide). The extraction of the remainder metabolites was as in Cadahía et al. (2015), by using firstly 200 μL of chloroform into ultrasonication bath for 15 min at room temperature, and thereafter 800 μL of water/methanol (1:3 v/v) containing the internal standard (methyl-β-D-galactopyranoside at 2 mg mL-1) to extract 5 mg of needles, applying again ultrasonication for 20 min. The extract was centrifuged, and two aliquot of 300 μL from obtained

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supernatant were taken. One of them was evaporated to dryness under nitrogen stream. This dry extract was derivatised by adding 30 μL of a 20 mg/mL solution of methoxyamine hydrochloride in pyridine, heating at 60 °C for 4 h, and subsequent trimethylsilylated with 30 μL of MSTFA for 1 h at room temperature. Finally, 3 μL of supernatant were injected into the GC–MS. The other aliquot of 300 μL was also evaporated to dryness under a nitrogen stream, the residue redissolved in water:methanol (1:1), and 10 μL analyzed by LC–QTOF. The extractions were carried out in duplicate. 2.3. Non-targeted metabolic profiling by gas chromatography-mass spectrometry (GC-MS) and targeted metabolic profiling by liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF) The extracts were analyzed using an Agilent 6890N GC system (Palo Alto, CA) equipped with a quadrupole mass spectrometer Agilent 5973N, working always in retention time locking mode, in order to reduce run-to-run retention time variation. A HP-5 capillary column (30 m x 0.25 mm i. d., film thickness of 0.25 µm, Agilent, Madrid, Spain) was used with helium as carrier gas. Chromatographic conditions for analysis of terpenoids and free fatty acids were as in Arrabal et al (2014): injector temperature, 260 ºC; column temperature, 60 ºC during the split period (2 min, 5:1) and then heated, at 4 ºC min–1, to 272 ºC (hold 10 min); constant flow rate 1 mL min-1; MSD transfer line, 290 ºC (MS source at 230 °C and MS quadrupole at 150 °C); detection was performed by electron impact mode with an ionization energy of 70 eV in a range of m/z 35-400. For the trimethylsilylated extract we used the preprogrammed Fiehn method, supplied in Agilent G1676AA Fiehn GC/MS Metabolomics RTL Library Software (2013). The chromatographic conditions were: injector temperature, 250 ºC; column temperature, 60 ºC during the split period (1 min, 10:1), and then heated, at 10 ºC min–1, to 325 ºC (hold 10 min); constant flow rate of 0.8 mL min-1; MSD transfer line, 290 ºC (MS source at 230 °C and MS quadrupole at 150 °C); detection was performed by electron impact mode with an ionization energy of 70 eV in a range of m/z 50-600. Compounds were identified by comparing their retention index (RI) (using C8 to C40 hydrocarbons as internal standards) and MS fragmentation patterns with: i) an in-house reference library built with near 300 commercial standards and analyzed in the same conditions; ii) commercial MS libraries (Agilent Fiehn GC-MS Metabolomics RTL Library, Wiley7/Nist05 8

GC/MS Library, and Adams, 1989) matching more than 95%; and iii) literature data. Supplemental Table A1 describes all these data for each detected peak. The LC system used was a Shimadzu Prominence (Shimadzu, Kyoto, Japan) equipped with a SPD-M20A photodiode-array detector, and coupled to a quadrupole time-of-flight mass spectrometer (Micro TOF-QII; Bruker Daltonics, MA) with an electrospray source. The column used was a Synergy Polar-RP 80A (150×2.00 mm inner diameter, 4 μm) (Phenomenex, Torrence, CA, USA) protected with a guard column of the same material, at room temperature. Samples were eluted using a mobile phase A, consisting of formic acid in water to 0.5% and 5mM of ammonium formiate, and a mobile phase B, consisting of methanol:water 95:5 (v/v). The gradient increased linearly from 5 to 15% of B in 10 min., from 15 to 35% in 10 min, from 35 to 50% in 10 min, up to 95% in 20 min, and maintained at a flow rate of 0.2 mL/min for 5 min. The electrospray mass spectrometer conditions were as follows: negative ion mode; capillary voltage, +4000 V; drying gas (N2) flow, 8 L/min; drying gas temperature, 220 °C, nebulizer pressure 34.8 psi (380 Pa); fragmentation voltage, 20 eV (m/z 0–100), 30 eV (m/z 100–500); 35 eV (m/z 500– 1000), 75–150% collision energy sweep; and scan range of m/z 100–1700. The mass spectrometer was calibrated externally with a 5mM acetate cluster solution in water:isopropanol 1:1 (v:v). The accurate mass data were processed using Data Analysis 4.0 software (Bruker Daltonics, Bremen, Germany). Elementary composition, deviations from theoretical value (error) and comparison of the theoretical with the measured isotope pattern (sigma-value), were calculated by using Smart Formula Editor. Confirmation of the elemental formula was based on the widely accepted thresholds of 5 ppm and 20 mSigma. The retention time (tR), wavelength (nm) of maximum absorbance (λmax) and relevant shoulders, exact mass of deprotonated molecular ion ([M-H]-), and major fragment ions, as well as experimental m/z for the molecular formula provided, errors and mSigma values for the major peaks are summarized in Supplemental Table A2. Peak identification was established based on these data, using commercial standards and previously published data in the literature. Quantitative determinations were carried out by the internal (GC-MS) or external (LC-MS) standard methods, using peak areas obtained from selected ion monitoring and selected wavelength, and linear or polynomial regression coefficients between 0.9622 and 0.9999 were obtained. Calibration of a similar compound was used when the pure reference standard was not 9

available, or for not fully identified compounds, as we shown in Supplemental Tables A1 and A2. Metabolite mapping was performed into general biochemical pathways according to the Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.genome.jp/kegg/), the Human Metabolome Database (HMDB, http://www.hmdb.ca/), PubChem project (PubChem, http://pubchem.ncbi.nlm.nih.gov/), and MetaCyc Metabolic Pathway Database (MetaCyc, http://metacyc.org/). 2.4. Statistical analysis The obtained data were analyzed by carrying out univariate analysis of variance using the SAS program (version 9.3; SAS Institute, Cary, NC). Two-way ANOVA analyzes considering form factor, water regime factor, and form and water regime factors together, were carried out and a post hoc Student Newman–Keuls multiple range test was applied to separate the means. Moreover, we carried out other two-way ANOVA analyses, separately in adults and juvenile needles, considering water regime and genotype factors together, afterwards the post hoc Student Newman–Keuls multiple range test. Heat map using log2 transformation for the fold-change of metabolite concentration in WS regarding WW, and multivariate partial least-squares discriminant analysis (PLS-DA) were also carried out using the Excel add in Multibase package (version 2015, RIKEN Plant Science Center, Hiroshi TSUGAWA). 3. Results The sequential extraction coupled to GC-MS and LC-QTOF analyzes, allowed the detection of 322 different compounds, resulting in the reliable identification of 211 metabolites, and the tentative assignment of a possible structure to other 97, remaining 14 unidentified. That provide us a broad description of metabolome of P. pinaster needles including amino acids and other nitrogen compounds, carbohydrates, lipids and free fatty acids, cofactors, prosthetic groups and electron carriers in primary metabolism pathways, as well as polyphenolic compounds, neutral and acid terpenoids, from secondary metabolism pathways. Regarding the identification of phenolic compounds, we have detected 67 compounds classified as phenolic precursors (2), benzoic and cinnamic acids (6), benzoic and cinnamic glycosides (8), benzoic derivatives not 10

fully identified (9), lignols and lignol glycosides (6), simple flavanols and proanthocyanidins (8), and flavonols (28). The most prevalent phenolic components were flavonols, including myricetin, quercetin, kaempferol, isorhamnetin, laricitrin, and syringetin derivatives, the same flavonol aglycones detected in needles from other Pinus species (Cannac et al., 2011; Kang & Howard, 2010; Karapandzova et al., 2015). They were detected as mono and diglycosylated, methylated, and mono and diacylated glycosides with ferulic and p-coumaric acids. Proanthocyanidins were identified as (epi)catechin and (epi)gallocatechin derivatives, both dimers and trimers. Concerning terpenoid compounds, their identification was as in Arrabal et al (2014), including 73 neutral terpenes and 39 resin acids, although on some of them we did not reach a complete identification. The detailed list of these metabolites, including their chromatographic, spectroscopic and spectrometric data is shown in Supplemental Tables A1 and A2. The quinic and shikimic acids were the most abundant components of P. pinaster dry needle metabolome. Their levels ranging from 60 and 50 mg g-1 until 230 and 140 mg g-1, respectively, shaping an average close to 72% of total organic solutes. These high ranges of concentration of both acids were observed regardless the different studied factors: ontogenetic stage of needles, genotype, or water regime. Concentration of the other 28% of compounds comprised mainly carbohydrates and related compounds, with fructose (15-35 mg g-1), glucose (12-32 mg g-1) and pinitol (6-20 mg g-1) showing the highest levels in all samples. The remaining metabolites were much less abundant (Fig. 1). Other cyclitols, such as sequoyitol (0.9-7.5 mg g-1) and myo-inositol (0.8-4.2 mg g-1); cofactors such as phosphate (2-14.5 mg g-1); and some flavonoids (myricetin3-O-glucoside (0.9-4.2 mg g-1), kaempferol-O-coumaroyl-feruloyl-hexoside (1.2-3.4 mg g-1), and isorhamnetin-O-derivative (0.5-3.06 mg g-1)) were the metabolites showing the following higher concentrations. Overall, amino acids, lipids and free fatty acids, neutral terpenes, and resin acids were minority compounds, accounting for less than 6% of total organic solutes. In these groups, the most abundant compounds were aspartic acid and 5-oxoproline among amino acids; glycerol and -sitosterol among lipids; 2-hydroxyglutaric and palmitic among free fatty acids; squalene, - and -pinene, and 2-phenyl ethyl isovalerate among neutral terpenes; and dehydroabietic, levopimaric+palustric, neoabietic and abietic among resin acids.

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3.1. Metabolic response to a moderate water stress In response to the moderate and slowly imposed drought stress, many metabolic changes were observed, in both primary and secondary pathways of metabolism (Fig. 2 and 3). Based on ANOVA results only considering water regime (WW vs WS, regardless form or genotype) (Supplemental Table A3), water deficit triggers a statistically significant increase in the needles in over 30% of detected metabolites, and the decrease in almost 13% (p<0.01). Among PPMs (Fig. 2), there was a general trend of increased amounts of numerous amino acids and other nitrogen compounds in WS needles. It highlights the significance of the increases on L-alanine, L-valine, aspartic acid and 5-oxoproline levels, as well as those in amines such as betaine, putrescine or ethanolamine, and in urea levels (p<0.0001, 43
tocopherol) (Noctor et al., 2015), in contrast with increases detected in roots (de Miguel et al., 2016).

As described above, flavonols were the main PSMs in P. pinaster needles, increasing because of water shortage the concentrations of almost every myricetin, quercetin, kaempferol isorhamentin, laricitrin and syringetin derivatives (Fig. 3). However, the F-values for these compounds were not very high in ANOVA carried out regardless the needle kind (between 21.6 and 8.4) (Supplemental Table A3). Probably this is due to the great influence of the kind of needle whichever water stress endured. We also detected in WS needles significant increased levels of some minor phenolic compounds, such as benzoic (p<0.01, F=10.5) and 4-hydroxycinnamic acids (p<0.0001, F=52.2), and a caffeoyl hexoside (p<0.001, F=15.5). Other compounds showed significant decreased levels such as three 3,4-dihydroxyphenyl derivatives, two 4-hydroxy-3methoxyphenyl

derivatives,

vanilloyl

hexoside

(p<0.01,

8
and

specially

coumaroylquinic acid (p<0.0001, F=69.5). Similar to flavonols, significant differences in the levels of compounds such as lignans and some low molecular weight polyphenols depended on the needle ontogenetic stage. Water stress also triggered a significant decrease of concentrations of diterpene acids (resin acids), (p<0.01, 10
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3.2. Adult and juvenile needle metabolomes: influence of heteroblasty in the metabolomics response Regarding the needle ontogenetic stage, 29% of the detected metabolites showed statistically significant differences higher than 99% (p<0.01): 39 compounds from primary metabolism and 54 from secondary (Supplemental Table A3). Among PPMs, the pool of carbohydrates showed the higher number of compounds with statistical significant differences regarding the form of the needle (F-values between 7 and 27). Thus, erythritol and chiro-inositol, together with xylitol, scyllo-inositol, arabitol, pinitol and levoglucosan showed significant higher levels in JWW needles. In AWW needles, we detected a significant higher accumulation of sugars such as raffinose, lactose, sucrose, L-fucose, melibiose, and twelve not fully identified sugars. Eight free fatty acids (2-hydroxyglutaric, capric, myristic, palmitic, stearic, oleic, 10,13-octadecadienoic and 2-methoxyhexadecanoic), shikimic and glucaric acids, alpha-tocopherol, and phytol also showed higher concentrations in AWW than in JWW needles, with important significant differences that arrived at two-three fold higher concentrations according to the compound (p<0.01 and F-values between 7.6 and 26.4) (Supplemental Fig.A2). The significant differences regarding the ontogenetic state of needles were very much important in PSMs (Supplemental Table A3, Supplemental Fig. A3), with important changes (p<0.01) in 35 out of the 67 polyphenolic compounds according to the type of needle. Thus, kaempferol-3-O-rutinoside,

myricetin-3-O-glucoside,

laricitrin-O-deoxyhexoside-hexoside,

myricetin-O-deoxyhexoside and laricitrin-O-hexoside showed 9740 (p<0.0001). The most significant differences were due to the higher accumulation of 25 compounds in JWW needles, 18 of them flavonol derivatives (p<0.01, 8
14

sesquiterpenes (p<0.01, 7
Regarding the metabolites showing higher loading, both PPMs and PSMs contribute to this increased differentiation (Supplemental Fig. A4). Among metabolites with highest weight to discriminate WS from WW needles (PC1) we found some N compounds, carbohydrates and flavonol derivatives, all them with negative coefficients, i.e. their concentrations increased with water deficit; and resin acids, that decreased in response to drought (positive coefficients). Some flavonol derivatives and amino acids (negative coefficients in PC2), besides some unidentified saccharides, linoleic, linolenic, gallic and benzoic acids (positive coefficients in PC3), contributed to discriminate between AWS and JWS, all them showing significant higher increases in JWS than in AWS, except the unidentified saccharides that showed significant lower levels and lower decreases in JWS. It also highlights the loading of d-erythronic acid, stearic acid and alpha-tocopherol, showing higher concentrations in AWS. Neutral terpenes also contributed to increased distances between AWS and JWS samples, showing mono- and sesquiterpenes higher increases in AWS, while diterpenes in JWS.

3.3. Adults and Juvenile needles from different genotype: clonal variation The models from PLS-DA comparing the metabolomics data from A or J needles, grouping the samples according to genotypes and water regimes, revealed that the different genotypes show a particular metabolic acclimation to water scarcity, confirming the importance of genotype

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in determining drought response (Fig. 5 and 6). In both models, the distribution of samples throughout PC1 allowed discriminating between WW and WS needles.

They showed the common feature that the metabolites with the highest loading were diterpene resin acids and sequoyitol (positive coefficients), as well as some N compounds (glycine, betaine, L-alanine, L-threonine, L-valine), polyols (chiro-inositol, pinitol, xylitol), lipids (glycerol-2-P, C18:2 (9,11)), and flavonol derivatives (kaempferol-O-dicoumaroyl-hexoside), with negative coefficients (Supplementary Fig. A5 and A6). Whereas the metabolome of WW needles was similar among genotypes, metabolomes of AWS and JWS needles show differences associated to their genotypes, distributing separately the four groups throughout PC2 and PC3. In A needles, PPMs and PSMs have high weight to discriminate among the four AWS genotypes (PC2 and PC3) (Fig. 5 and Supplemental Fig. A5), including metabolites such as osmotically active substances from the altered carbon, nitrogen and/or energy metabolism, lipids contributing to cell membrane stability, and ROS scavenging compounds. Adults needles from 132WS and 4WS were the two closest groups, showing similar drought metabolomes, whereas 144 and 147 were more divergent, displaying a clear separation throughout PC2 (147WS) and PC3 (144WS). In J needles, metabolites from PPM only were implied in the discrimination between JWW and JWS (PC1), and have not high loading to discriminating genotypes after stress (PC2 and PC3), in which some lipids, phenylpropanoids, flavonoids and neutral terpenes showed the highest correlations (Fig. 6 and Supplemental Fig. A6). The accumulation levels in needles from the four studied genotypes of the most significant flavonoid and terpenoid metabolites (Fig. 7 and 8) highlighted that flavonoids increased more in 147 and 4 genotypes than in 132 and 144 ones, even decreasing slightly in some cases, both in A and J needles. However, the accumulation of terpenoids showed a different pattern. Thus, monoterpenes such as linalyl acetate increased more in A132, A4 and J147, sesquiterpenes such as farnesol derivatives increased in A132 and A147, while alpha-muurolene increased in A147

16

and decreased in all others. Finally, diterpenes increased in J144 and J147, showing a low accumulation and even decreases of almost all them in A4 and J4.

4. Discussion We showed the qualitative and quantitative metabolite profiling of P. pinaster needles developed chronologically at similar times, but showing adult and juvenile forms from the species heteroblasty. In previous studies on the metabolome of maritime pine needles (Cañas et al., 2015; de Miguel et al., 2016; Meijón et al., 2016) semi-quantitative data have been published. In all considered needles, it highlights the abundance of common organic acids (quinic and shikimic) and, in a minor scale, two monosaccharides (fructose and glucose) and one cyclitol (pinitol), in this order. In other forest trees, conifers and angiosperm, leaf metabolome also shows a profile dominated by organic acids (shikimic, quinic, malic) and common carbohydrates (fructose, glucose, sucrose), including cyclitols (pinitol, myo-inositol), e.g. Fagus spp. (sucrose, myo-inositol, glucose, quinic acid), Douglas fir (sucrose, quinic and shikimic acids, pinitol), Quercus spp. (sucrose, quercitol, scyllo-inositol, quinic acid, fructose, glucose), Eucalyptus spp. (shikimic and quinic acids, fructose, glucose, sucrose, proto-quercitol), and Acacia spp. (malic acid, fructose, sucrose, myo-inositol, ononitol, pinitol) (Cadahia et al., 2015; Du et al., 2016; Rivas-Ubach et al., 2014; Warren et al., 2011) 4.1. Metabolomics response to a moderate water stress The complex adjustment that needles undergo to cope water stress in P. pinaster is shown at physiological level, showing variations in needle gas exchange, chlorophyll fluorescence derived traits, growth patterns and stomatal closure (stomatal conductance decrease by 68% on average) (Sánchez-Gómez et al., 2017, under review). Also at metabolomics level, by the statistically significant accumulation in over 30% of metabolites from all class of studied compounds, and the decrease in almost 13% (Fig. 2 and 3). Thus, as in non-woody plants (Krasensky and Jonak, 2012), P. pinaster needles have developed a widespread range of strategies to adapt their 17

metabolism to water scarcity and accomplish their acclimation, accumulating different metabolites and not only a group of specific metabolites. Among those overall changes, it stand out the increase of osmotically active substances, highlighting the role of pinitol as a speciesspecific osmotica over carbohydrates. Similar variations have been described in other forest trees (Du et al., 2016; Merchant et al., 2006) including maritime pine, since pinitol plays a major role in osmoregulation under drought conditions (de Miguel et al., 2016; Nguyent & Lamant, 1988). Other carbohydrates also contributing to osmotic adjustment but because their low-abundance, we can only expect a small impact, although they also help stabilizing cell membranes and preventing protein degradation (Warren et al., 2011). Quantitatively most important carbohydrates and other minor disaccharides showed no significant differences after water shortage, despite that most of them increased in response to drought in other forest trees (Aranda et al., 2017; Barchet et al., 2014; Hamanishi et al., 2015; Krasensky and Jonak, 2012; Warren et al., 2011), and where they play an important role in osmotic adjustment. In P. pinaster needles, they would not have a noteworthy role. The relevance of soluble sugars vs. cyclitols as main osmoregulators has been related with the aridity characteristics of the species origin: those species from xeric ecosystem would rely mainly on accumulation of cyclitols, while those species from mesic habitat would use soluble sugars as osmolites. These differences also show a genetic control (Barchet et al., 2014; Merchant et al., 2006; Warren et al., 2011), but it has not been established at the intra-specific level when considering genotypes from ecologically different populations of P. pinaster (Meijon et al., 2016). From the altered nitrogen metabolism, it highlights the increased amino acid and amine levels because of drought stress, as previously described in leaves (e.g. Aranda et al., 2017; Barchet et al., 2014; Du et al., 2016; Krasensky and Jonak, 2012). Most of these N compounds are wellknown osmotically active metabolites. They have also been associated with carbon-nitrogen balance and ROS scavenging, have been implicated in protecting membranes and supplying respiratory substrates during stress etc., aiming to their beneficial roles in stress tolerance (Araújo et al., 2011; Ashraf and Foolad, 2007; D’Andrea et al., 2014; Selmar & Kleinwächter, 2013). Energy requirements for plant growth and synthesis of fundamental metabolites is achieved through the glycolysis-TCA cycle (Fernie et al., 2004; Li et al., 2016; Zhao et al., 2016), and the metabolites involved showed pronounced and steady increases in response to water deficit, 18

clearly suggesting that their metabolic rate is influenced by drought. Reinforcing this thought, we detected decreased levels of some not fully identified mono-, di-, and trisaccharides, as well as 2-hydroxyglutaric acid, likely to serve as intermediates in glycolysis and TCA respectively, and meet metabolic demands (Maurino and Engqvist, 2015). We also detected significant increased levels of the branched-chain amino acids, which could be associated with their increased demand as substrates for the TCA cycle under water stress (Pires et al., 2016), but also to activate secondary metabolism as a consequence of water stress. Increased energy requirement for cellular metabolism has been associated to stress tolerance (Janz et al., 2010), thus these metabolic changes may play an important role in P. pinaster adaptation/tolerance to drought. Competition between photorespiration and those processes leading to CO2 assimilation as electron sinks in WS needles was associated with increased levels of glycolic acid (Maurino and Engqvist, 2015), which has been linked to a better functioning and possibly more resistant metabolic system (Barchet et al., 2014). Other free fatty acids showed variations in saturated and unsaturated acids in response to water shortage, probably in order to adjust membrane fluidity, such as in other plant species (Zhong et al., 2011 and references therein). We have found no data in conifer, but the seasonal variation, which also implies temperature and light availability effect, caused a similar response (Arrabal et al., 2014). Needles activate ROS scavenging mechanisms to remove high levels of ROS, and thus reestablish the cellular redox balance. Therefore, they overproduce antioxidant compounds, upregulating ascorbate, shikimate/phenylalanine and phenylpropanoid metabolic pathways, as well as the diterpenoid acid catabolism or their mobilization towards other tissues. Changes in polyphenol levels due to water scarcity depend on needle ontogeny (i.e. juvenile vs. adult forms). Therefore, special attention should be paid to the needle ontogenetic stage when analyzing the flavonoids in response to water deficit. In general, the changes triggered by water deficit rely on the synthesis and accumulation of those phenolic compounds with higher antioxidant activity, such as flavonols and dihydroxycinnamates, as well as the precursor 4-hydroxycinnamic, probably to improve stress tolerance (Nakabayashi et al., 2014; Tattini et al., 2004). Displaying a temporal correlation between flavonoid biosynthesis and oxidative stress events, flavonoids might constitute a secondary antioxidant system (Agati et al., 2012), enhancing the oxidative and drought tolerance by flavonoid over-accumulation (Meijon et al., 2016; Nakabayashi et al., 2014). These compounds scavenge ROS in the nM to low M concentration range (Agati et al., 19

2012), much smaller than that detected in P. pinaster needles. Regarding hydroxycinnamates, the water shortage favors the accumulation of caffeoyl (dihydroxylated) vs coumaroyl (monohydroxylated) derivatives, improving stress tolerance (Nakabayashi et al., 2014; Tattini et al., 2004). Related with the antioxidant protection of cellular components by scavenging ROS, the redox state of ascorbic acid remained constant or shifted toward the increase of its reduced state in WS needles. This effect was linked to the decrease on diterpene acids displaying antioxidant properties in some species (Munné-Bosch and Alegre, 2003), so it could also be linked to the presence of these compounds in P. pinaster needles. Thus, water stress triggered a significant decrease of diterpene acids with concomitant increase of neutral diterpenes, although scarce data have been published about antioxidant activity of pimaran and abietan structures detected in this study (Mikozami et al., 2016; Saijo et al., 2015). No studies have been published about the effects of drought stress on resin acid levels in needles, but a similar behavior was found regarding seasonal variations (Arrabal et al., 2014). It’s known that drought causes the increase of resin acids in the conifer wood (Turtola et al., 2003) as well as the oleoresin accumulation in woody tissues of P. pinaster (Rodríguez-García et al., 2015). Thus, resin acids accumulation could be highly organ dependent, and even could be mobilized towards resin canals in wood as result of water deficit. Regarding neutral terpenes, most of them showed higher levels in WS needles, as in other conifers (Turtola et al., 2003 and references therein), with a different strength in relation to their ontogenetic stage. The accumulation of many terpenes in water stressed leaves has been associated with the allocation of carbon because the decrease of growth, as well as a protection against oxidative stress (Blanch et al., 2009). 4.2. Adult and juvenile needle metabolomes: influence of heteroblasty in the metabolomics response Several studies have found morphological and functional differences associated with the needle heteroblasty in maritime pine, in which the transition from juvenile to adult needles has a genetic basis (Sánchez-Gómez et al. 2010; Climent et al., 2013). Metabolome has been studied with regard the genetic background or chronological age of needle (Cañas et al, 2015; de Miguel et al., 2016), and our works complements these studies linking these important ontogenetic processes with the differentiation in the metabolome. The two kinds of needles that respond to 20

the heteroblasty of the species translated their diversity in a quantitative differentiation at metabolic level (Fig. 2 and 3, Supplemental Fig. A2 and A3). Thus, ontogenetic stage appears to be a variable that strongly influences carbohydrate levels in needles. These differences may be related to a high metabolic rate, and thus a very dynamic carbohydrate catabolism in JWW needles, while AWW needles could assimilate surplus carbon and play a role as metabolic sinks. Moreover, we have also found that there is a relation between ontogenetic stage and PSMs levels. Our data could correspond to a sharp change in the regulation of the biochemical pathways controlling synthesis of PSMs with the ontogenetic transition from juvenile to adult needle, in a similar way to the effect of development time, seasonality, as well as the water regime of the geographic origin of the provenance (Cañas et al., 2015; Meijón et al., 2016). Thus, Cañas et al (2015) found that the expression of genes encoding main enzymes of the KEGG flavonoid synthesis pathway, together with key enzymes of shikimate/phenylalanine and phenylpropanoid pathways, correlated with the development time of needles. Flavonoids have many physiological roles in plants, and influence transcriptional and signalling processes (Agati et al., 2012, 2013; Brunetti et al., 2013; Karabourniotis et al., 2014). High concentrations in juvenile needles may provide an ecological benefit to the plant at early ages, as it may enhance their tolerance to multiple stressors of the typical regeneration environments of maritime pine, characterized by poor soils and high radiation loads. In fact, P. pinaster stressed plants resulted in a greater fraction of juvenile needles and delaying of the ontogenetic change and development of adult needles (de la Mata et al., 2014). Nevertheless, it has been described a minor tolerance to frost (Climent et al., 2009), and probably to drought because their higher rate of cuticular transpiration, even though they contain more water and can maintain a higher rate of water loss for a longer period of time before limiting factors come into play (Pardos et al 2009). On the contrary, some flavonol glycosides are known to be located in the epidermal tissue of the P. sylvestris needles (Schnitzler et al. 1996), exhibiting an important UV-B absorbing capacity (Lavola et al. 2003; Karabourniotis et al., 2014; Rummukainen et al., 2013). They may also act as antioxidants that reduce the oxidative damage caused by UV radiation, scavenging H2O2 and singlet oxygen generated under excess light-stress (Agati et al., 2012, 2013). Many pines, and in particular maritime pine, are very heliophiles, colonizing and settling in open habitats as juveniles. On the other hand, they have a low photosynthetic capacity that could justify the low amount of carbohydrates. In the past, the need to withstand loads of 21

high radiation would have promoted the maintenance of heteroblasty focused on maintaining an effective secondary metabolism to cope with the oxidative stress caused by high levels of light energy, which exceed the photosynthetic capacity. These functions of flavonoids depend on the presence of the ortho-dihydroxyl (catechol) or ortho-trihydroxyl (pyrogallol) substitution in the B-ring, i. e. quercetin and myricetin derivatives (Agati et al., 2011). The latter was the most abundant in the P. pinaster needles, whereas the sugar and acyl moieties did not appear to be essential (reviewed in Heim et al., 2002 and Seyoum et al., 2006). Taking into account the functional roles of phenolic compounds in photoprotection, their concentration should be functionally integrated with needle photosynthetic capacity because stress factors that limit photosynthesis tend to increase the risk of photodamage (Ashraf and Harris, 2013; Karabourniotis et al., 2014). In fact, the photosynthetic capacity and the leaf phenolic levels showed a negative correlation in 49 different plant species (Sumbele et al., 2012), although unfortunately it has not been studied in conifers. Thus, the concentration of leaf phenolic compounds would reflect the compromise between growth and protection demands, depending on strategy adopted (Karabourniotis et al., 2014; Sumbele et al., 2012). In the case of P. pinaster heteroblasty, this strategy may lead to a delay in ontogenetic development, producing a greater fraction of juvenile needles, better prepared against light stress, although probably with lower photosynthetic capacity, according to the differences detected in carbohydrate levels. Water stress increased these significant differences (Fig. 4), probably not only because growth inhibition in JWS, and the concomitant accumulation of carbon-rich chemicals (Niinemets, 2016), but also to enhancing the oxidative and drought tolerance by the flavonoid and diterpene overaccumulation (Blanch et al., 2009; Meijon et al., 2016; Nakabayashi et al., 2014). The higher increase of some N compounds in JWS that stand out for their beneficial roles in stress tolerance (Krasensky and Jonas, 2012; Noctor et al., 2015), as well as unsaturated fatty acids which are related to a better maintenance of the membrane integrity (Zhong et al., 2011), could also be aimed to reinforce drought tolerance in J needles. These results suggest a differential strategy in water economy at functional scale since the metabolic processes in response to water deficit focus on increase stress tolerance according to the functions and needs at each ontogenetic stage of the needles. As suggested by Cañas et al, (2015) with respect to chronological age, alternative gene packages involved in the same metabolic pathways would coexist in P. pinaster needles, 22

contributing to the essential flexibility in responses to varying environmental and/or developmental conditions regarding heteroblasty. 4.3. Adults and Juvenile needles from different genotype: clonal variation Clonal differences in the metabolome adjustment to cope with stress were associated with differences in the intensity of up/down-regulation of almost all metabolic pathways involved in the response (Hamanishi et al., 2015; de Miguel et al., 2016). In AWS needle metabolome, as PPMs as PSMs were important in discriminating the four studied genotypes, while in JWS the metabolic differences among genotypes were specifically related with those metabolic pathways involved in ROS scavenging compounds, antioxidants, and compounds showing a functional role in the regulation of membrane fluidity and permeability. Therefore, although P. pinaster needles have a similar drought metabolic response, also significant intra-specific variations were found at ontogenetic and genotypic levels. Overall, the four genotypes showed divergent metabolomes in J needles under water stress while in AWS needles, 144 and 147 genotypes were more divergent, but 132 and 4 showed closed metabolomes. Secondary metabolism, in particular terpenoid and flavonoid pathways, clearly contributed to the different metabolomes in response to drought, with many compounds involved. Thus, it highlights the high accumulation of sesquiterpenes in A132 and A147, of diterpenes in J144 and J147, and the low accumulation of all of them in A4 and J4. In addition, needles showed higher increases of flavonoids in 147 and 4 than in 132 and 144 genotypes, both in A and J. That flavonoid accumulation model showed the same divergences found regarding the variation in photosynthetic and growth patterns in response to water deficit: 4 and 147 were the most sensitive genotypes while clones 132 and 144 were less sensitive. Thus, stomatal closure as consequence of water stress was more noticeable in clones 4 and 147 that maintained a more prolific water use under well-watered conditions (higher stomatal conductance). Thus both clones showed a higher decline in stomatal conductance when submitted to water stress (78.7 and 88.6 % in clones 4 and 147 respectively), than in the clones 132 (decrease of 57.3%) and 144 (decrease of 51%) (Sánchez-Gómez et al., 2017, under review). Therefore, the different drought tolerance strategies were not clearly detected on the overall drought metabolome of genotypes, according to the fitted models by PLS-DA. However, sensitive genotypes were characterized by a higher increase of flavonoid levels in both A and J 23

needles than tolerant genotypes (Fig. 7). In literature, drought-tolerant or drought-sensitive clones and provenances display different metabolomes because differ in some specific metabolites (Barchet et al., 2014; Du et al., 2016; Hamanishi et al., 2015; Piper, 2011; Regier et al., 2009). Thus, it has been suggested that the biosynthesis of antioxidant flavonoids increases more in stress-sensitive species than in stress-tolerant species, since stress-sensitive species display a less effective first line of defense against ROS under stressful conditions and are subsequently exposed to a more severe oxidative stress (Agati et al., 2012). In fact, the flavonoid over-accumulation has emerged as a key factor to enhanced tolerance to oxidative and drought stress (Nakabayashi et al., 2014). Particularly, Meijon et al (2016) found strong correlations between needle flavonoids and water regimes of P. pinaster provenances. Therefore, drought tolerance shown by a genotype may be an important factor to determining the level of flavonoid accumulation induced in response to water stress, which is also modulated according the ontogenetic stage of needles. 5. Conclusion The quantitative metabolome of adult and juvenile needles of P. pinaster shows clear differences, standing out those regarding flavonol and neutral diterpene levels, that preadapts juvenile needles to adverse growing conditions and/or multiple stressors (oxidation, UV, etc.). To adapt their metabolism to water scarcity, P. pinaster needles develop a widespread range of strategies, accumulating different metabolites, standing out the increase of osmotically active substances, such as pinitol as a species-specific osmotica, as well as the overproduction of antioxidant compounds to remove excess levels of ROS and re-establish the cellular redox balance. These changes were more intense in juvenile needles. Our study revealed that drought tolerance of a given genotype as well as the ontogenetic stage are two important factor to determine the level of flavonoids accumulated in needles of trees subjected to stress. Significant drought-induced accumulation of neutral diterpenes in juvenile needles, and mono- and sesquiterpenes in adults, were genotype-dependent without regard their level of drought tolerance. These results point out to flavonoids as very versatile metabolites in maritime pine needles, acting as important compounds modulating not only acclimation to drought but also the changes in metabolism in developmental processes such as heteroblasty. 24

Contributions BFS designed and performed the research, analyzed and interpreted data, and wrote the manuscript. MS and EP designed, performed and interpreted LC-MS analysis. MTC designed the research. IA designed the research, interpreted data and wrote the manuscript. EC designed and performed the research and interpreted metabolic data. All authors have read, critical reviewed the intellectual content, corrected and approved the final manuscript. Acknowledgements This study was financed by the Spanish Ministerio de Economía y Competitividad (Project AGL2012-32175 PINCOxSEQ). The authors gratefully thank Dr. David Sanchez-Gómez and Mr Jose Antonio Mancha for helping in setting up the experimental and leaf-sampling material, as well as Ms Rosa de Pedro and Mr. Antonio Sanchez for their help throughout the chemical analysis. References Adams, R.P. 1989. Identification of Essential Oils by Ion Trap Mass Spectroscopy. Academic Press. San Diego, California. http://doi.org/10.1016/B978-0-12-044230-0.50001-0 Agati, G., Gerovic, Z.G., Pinelli, P., Tattini, M., 2011. Light-induced accumulation of ortho-dihydroxylated flavonoids as non-destructively monitored by chlorophyll fluorescence excitation techniques. Env. Exp. Bot. 73, 3-9. http://dx.doi.org/10.1016/j.envexpbot.2010.10.002 Agati, G., Azzarello, E., Pollastri, S., Tattini, M., 2012. Flavonoids as antioxidants in plants: Location and functional significance. Plan Sci. 196, 67-76. http://dx.doi.org/10.1016/j.plantsci.2012.07.014 Agati, G., Brunetti, C., Di Ferdinando, M., Ferrini, F., Pollastri, S., Tattini, M., 2013. Functional roles of flavonoids in photoprotection: New evidence, lesson from the past. Plant Physiol. Biochem. 72, 35-45. http://dx.doi.org/10.1016/j.plaphy.2013.03.014 Alía, R., and Martín, S., 2003. EUFORGEN Technical Guidelines for genetic conservation and use for Maritime pine (Pinus pinaster). International Plant Genetic Resources Institute, Rome, Italy. 6 pages Aranda, I., Alía, R., Ortega, U., Dantas, A.K., Majada, J., 2010. Intra-specific variability in biomass partitioning and carbon isotopic discrimination under moderate drought stress in seedlings from four Pinus pinaster populations. Tree Genet. Genom. 6, 169–178 http://dx.doi.org/10.1051/forest/2010007 Aranda, I., Sánchez-Gómez, D., de Miguel, M., Mancha, JA., Guevara, M.A., Cadahía, E,, Fernández de Simón, B., 2017. Fagus sylvatica L. provenances maintain different leaf metabolic profiles and functional response. Acta Oecologica (in press) Araujo, W.L., Tohge, T., Ishizaki, K., Lever, C.J., Fernie, A.R., 2011. Protein degradation – an alternative respiratory substrate for stressed plants. Trends Plant Sci. 16, 489–498. https://dx.doi.org/10.1016/j.tplants.2011.05.008 Arrabal, C., García-Vallejo, C., Cadahia, E., Cortijo, M., Fernández de Simón, B., 2014. Seasonal variations of lipophilic compounds in needles of two chemotypes of Pinus pinaster Ait. Plant Syst. Evol. 300, 359–367. http://dx.doi.org/10.1007/s00606-013-0888-5 Ashraf, M., and Harris, P.J.C., 2013. Photosynthesis under stressful environments: an overview. Photosynthetica 51, 163-190. http://dx.doi.org/10.1007/s11099-013-0021-6 Ashraf, M., and Foolad, M.R., 2007. Roles of glycine betaine and proline in improving plant abiotic stress resistance. Env. Exp. Bot. 59, 206-216. http://dx.doi.org/10.1016/j.envexpbot.2005.12.006 Barchet, G.L.H., Dauwer, R., Guy, R.D., Schroeder, W.R., Soolanayakanahally, R.Y., Campbell, M.M., Mansfield, S.D., 2014. Investigating the drought-stress response of hybrid poplar genotypes by metabolite profiling. Tree Physiol. 34, 1203–1219. https://dx.doi.org/10.1093/treephys/tpt080

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Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.genome.jp/kegg/), Last accessed February 16, 2017 The Human Metabolome Database (HMDB, http://www.hmdb.ca/), Last accessed February 16, 2017 PubChem project (PubChem, http://pubchem.ncbi.nlm.nih.gov/), Last accessed February 16, 2017 MetaCyc Metabolic Pathway Database (MetaCyc, http://metacyc.org/). Last accessed February 16, 2017

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Fig. 1.- Average percentages of different chemical groups on P. pinaster needle metabolome, regardless ontogenetic stage, genotype, or water regime. Quinic and shikimic acids were the main components

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Fig. 2.- Average concentrations (mg g-1) and standard errors of most significant PPMs in P. pinaster dry needles (WW n=12, WS n=13), grouped by chemical families. A=Adults needles; J=Juvenile needles; WW=Well watered; WS=Water stressed. sa=sugar acid; I=inositol; sol=sugar alcohol; sequoy=sequoyitol; monos=monosaccharide; disacc=disaccharide; trisacc=trisaccharide; HO=hydroxy; heneic=heneicosanoic; M=methoxy; FA=fatty acid; P=phosphate; m=methyl; DHA=dehydroascorbic. Different letters for each compound denote a statistical difference with 95% confidence level (Student Newman-Keuls multiple range test), with a being the highest concentration

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Fig. 3.- Average concentrations (mg g-1) and standard errors of most significant PSMs in P. pinaster dry needles (WW n=12, WS n=13), grouped by chemical families. A=Adults needles; J=Juvenile needles; WW=Well watered; WS=Water stressed. dhd=3,4-dihydroxyphenyl derivative; hmd=4-hydroxy-3-methoxyphenyl derivative; H=hexoside; HO=hydroxy; M=methoxy; cou=coumaroyl; PDB=prodelphinidin B; m=myricetin; q=quercetin; k=kaempferol; i=isorhamnetin; l=laricitrin; s=syringetin; p=pentoside; AC=acetate; pet=2-phenyl ethyl; MB=methyl butyrate; isolong=isolongifolene; cadin=cadinene; P=propionate; IV=isovalerate; abd=abietadiene; abtr=abietatriene; 19nabtr=19-Nor-4,8,11,13abietatetraene; dipdha=deisopropyldehydroabietate. Different letters for each compound denote a statistical difference with 95% confidence level (Student Newman-Keuls multiple range test), with a being the highest concentration

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Fig. 4.- Scatterplot of PLS–DA model performed considering quantitative data from metabolome profiles associated with ontogenetic stage and water regime in P. pinaster needles (R2Y=0.78, Q2=0.65). A=Adults needles; J=Juvenile needles; WW=Well watered; WS=Water stressed

Fig. 5.- Scatterplot of PLS–DA model performed considering quantitative data from metabolome profile of adults P. pinaster needles, with respect to genotype and water regime. (R2Y=0.40, Q2=0.21). A=Adults needles; WW=Well watered; WS=Water stressed

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Fig. 6.- Scatterplot of PLS–DA model performed considering quantitative data from metabolome profile of juvenile P. pinaster needles, with respect to genotype and water regime. (R2Y=0.40, Q2=0.17). J=Juvenile needles; WW=Well watered; WS=Water stressed

Fig. 7.- Heat-map of fold-change in concentration changes of most significant flavonoids concentrations in response to water stress. Data are expressed as log2 transformation of ratio of WS over WW. Intense red and blue indicate low and high fold-change, respectively. n=3 except 4WS for which n=4

.

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Fig. 8.- Heat-map of fold-change in concentration changes of most significant terpenes in response to water stress. Data are expressed as log2 transformation of ratio of WS over WW. Intense red and blue indicate low and high fold-change, respectively. n=3 except 4WS for which n=4

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APPENDIX A. SUPPLEMENTARY MATERIAL Supplemental Table A1.- Metabolites detected by GC-MS. Retention time (Rt), retention index (RI), MS fragmentation patterns, selected ion for integration, derivatization (TMS=trimethylsilylation; ME=methylation), Identification mode (S=commercial standard; D=commercial MS databases L=MS from literature; T=tentative identification); Standard used for quantification. Supplemental Table A2.-Metabolites detected by LC-QTOF. Retention time (Rt), MS fragmentation patterns, UV l max (nm); deprotonated molecule, molecular formula, Error, mSigma and Standard used for quantification. Supplemental Table A3.- Biochemical pathways according to the Kyoto Encyclopedia of Genes and Genomes (KEGG), the Human Metabolome Database (HMDB), PubChem project (PubChem), and MetaCyc Metabolic Pathway Database (MetaCyc), and ANOVA results. Appendix A.- Supplemental Information:

Supplemental Figure A1.- Adult and juvenile needles in P. pinaster Ait.

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Supplemental Figure A2.-Box-plot representing the concentration rate (mg g-1) of some of most significant PPMs in Adult (A) and Juvenile (J) needles. The midline of the box represents the median value, the upper and lower bounds of the box represent the interquartile range, and the whiskers extend to the most extreme values that are not outliers.

Supplemental Figure A3.-Box-plot representing the concentration rate (mg g-1) of some of most significant PSMs in Adult (A) and Juvenile (J) needles. The midline of the box represents the median value, the upper and lower bounds of the box represent the interquartile range, and the whiskers extend to the most extreme values that are not outliers.

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Supplemental Figure A4.- Metabolites showing higher correlations according PLS-DA in Figure 4 (WW and WS Adult and Juvenile Needles (M=myricetin; K=kaempferol; I=isorhamnetin; La=laricitrin; S=syringetin; hex=hexoside)

Supplemental Figure A5.- Metabolites showing higher correlations according PLS-DA in Figure 5 (AWW and AWS from four genotypes) (M=myricetin; Q=quercetin; K=kaempferol; I=isorhamnetin; La=laricitrin; S=syringetin; hex=hexoside; pent=pentoside; PD=phenyl derivative)

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Supplemental Figure A6.- Metabolites showing higher correlations according PLS-DA in Figure 6 (JWW and JWS from four genotypes) (M=myricetin; Q=quercetin; K=kaempferol; La=laricitrin; S=syringetin; hex=hexoside; pent=pentoside; PD=phenyl derivative)

APPENDIX B. SUPPLEMENTARY DATA Supplemental Figure B1.- Mass Spectra from GC and LC analysis Supplemental Figure B2.- Chromatograms from GC-MS and LC-MS analysis

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