# Uncovering the mechanisms of heartwood formation and wood resistance to fungal degradation in the tropical Lauraceae tree Sextonia rubra (Mez.) van der Werff

Marceau Levasseur, Ambre Senelis, Flavien Zannini, Muriel Barbier, Elsa van Elslande, Nadine Amusant, Yannick Estevez, Véronique Eparvier, Éric Gelhaye, David Touboul, et al.

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## To cite this version:

Marceau Levasseur, Ambre Senelis, Flavien Zannini, Muriel Barbier, Elsa van Elslande, et al. "Uncovering the mechanisms of heartwood formation and wood resistance to fungal degradation in the tropical Lauraceae tree Sextonia rubra (Mez.) van der Werff." Tree Physiology, In press, 10.1093/treephys/tpaf079. hal-05210816

HAL Id: hal-05210816

https://hal.science/hal-05210816v1

Submitted on 14 Aug 2025

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1 The article corresponding to this submitted revised copy was published by *Tree Physiology*

2 under the reference: tpaf079; https://doi.org/10.1093/treephys/tpaf079

3

4 Uncovering the mechanisms of heartwood formation and wood resistance to fungal

5 degradation in the tropical Lauraceae tree *Sextonia rubra* (Mez.) van der Werff

6

7 Marceau Levasseur¹, Ambre Senelis¹, Flavien Zannini², Muriel Barbier², Elsa Van Elslande¹,

8 Nadine Amusant³, Yannick Estevez⁴, Véronique Eparvier¹, Éric Gelhaye², David Touboul¹,⁵,*

9 Emeline Houël⁴,⁶,*

10 ¹ Université Paris-Saclay, CNRS, Institut de Chimie des Substances Naturelles, UPR 2301, 91

11 198, Gif-sur-Yvette, France

12 ² Université de Lorraine, INRAE, Interactions Arbres-Microorganismes, UMR 1136, F-54500

13 Vandoeuvre-lès-Nancy, France

14 ³ Cirad, CNRS, AgroParisTech, INRAE, UMR EcoFoG, Université des Antilles, Université de

15 Guyane, 97 300 Cayenne, France

16 ⁴ CNRS, Cirad, AgroParisTech, INRAE, UMR EcoFoG, Université des Antilles, Université de

17 Guyane, 97 300 Cayenne, France

18 ⁵ Laboratoire de Chimie Moléculaire (LCM), CNRS, École polytechnique, Institut

19 Polytechnique de Paris, 91 120 Palaiseau, France

20 ⁶ Sorbonne Université, CNRS, Laboratoire de Biodiversité et Biotechnologie Microbienne,

21 UAR 3579, Observatoire Océanologique, 66650 Banyuls-sur-Mer, France

22

23 Running title

24 Heartwood formation in *Sextonia rubra*

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* For correspondence. E-mail emeline.houel@cnrs.fr; david.touboul@cnrs.fr

**Abstract**

Heartwood formation is a complex process that contributes to ensuring the integrity of trunks and the longevity of trees. We examined this mechanism in the tropical angiosperm *Sextonia rubra* in relation to the spatial distribution of specialised metabolites and their functional role at the scale of a mature individual. Heartwood formation was analysed starting from the examination of one of its properties, namely the decay resistance, of the different *S. rubra* wood tissues (sapwood, heartwood, and pith) using soil bed tests. Annotation and identification of the metabolites present in ethyl acetate extracts were carried out by reverse-phase liquid chromatography coupled to a tandem mass spectrometer (RPLC-ESI-MS/MS) and molecular networks. Following the application of supervised statistical analyses and the use of Glutathione S-transferases enzymatic assays, the specialised metabolites of interest were quantified radially and longitudinally in the different tissues using RPLC-ESI-HRMS system. Heartwood and pith were shown to resist degradation after a ten-months exposure to forest soil, with no effect of the heartwood cambial age. Molecular diversity was specific to each tissue type, with flavonoids and butanolides detected in bark and sapwood, while alkaloids and butyrolactones were identified in heartwood and pith. Supervised analyses and enzyme assays suggested that alkaloids and butyrolactones play a role in the resistance of internal tissues to degradation. Butyrolactone concentrations peaked in the middle heartwood but remained homogeneous longitudinally, while alkaloid concentrations were uniform longitudinally and radially in the heartwood. In conclusion, the resistance of heartwood and pith to fungal degradation was correlated with the accumulation of lactones and alkaloids. While butanolide precursors of butyrolactones have been detected in the sapwood, alkaloids appear to be directly
biosynthesis in the heartwood. This suggests that the biosynthesis and accumulation of
specialised metabolites during heartwood formation is specific to each molecular family.

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### Keywords

Antifungal activity; Chemical defence; Glutathione S-transferases; Molecular networks; Soil
bed assays; Specialised metabolites; Wood decay resistance

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## 58 INTRODUCTION

59 Tree defences include mechanisms and intrinsic properties by which a tree can passively or
60 actively defend itself against wood-decomposing organisms. These mechanisms include
61 chemical factors such as the biosynthesis of specialised metabolites, and anatomical and
62 physicochemical factors such as compartmentalisation of decay in trees (Loehle, 1988; Petit
63 and Hampe, 2006; Morris et al., 2016, 2020; De Ligne et al., 2021). Heartwood specialised
64 metabolites are biosynthetised during heartwood formation, following various models that are
65 continuously implemented (Kampe and Magel, 2013; Celedon and Bohlmann, 2018). Genetic
66 factors associated with the biosynthesis of specialised metabolites implicated in wood decay
67 resistance in the Lauraceae family have recently been investigated (Tian et al., 2023). Indeed,
68 tropical species are known for their high content of wood extractives (Gérard et al., 2019).
69 Numerous studies have explored the chemical diversity of tropical tree species, many of which
70 are capable of accumulating metabolites with fungicidal activity, therefore potentially involved
71 in the natural durability of wood (Rodrigues et al., 2012; Royer et al., 2012; Amusant et al.,
72 2014; Basset et al., 2015; Anouhe et al., 2018; Erb and Kliebenstein, 2020; Gouveia et al.,
73 2021). However, radial and longitudinal variations of wood properties are to be expected due
74 to wood anisotropic formation process in the tree (Plomion et al., 2001; Adutwum et al., 2023).
75 Some of these variations, including the difference between sapwood and heartwood extractives
content, have been studied from a valorisation perspective (Morais and Pereira, 2012; Wijayanto et al., 2015; Martins et al., 2020; Verkasalo et al., 2021). Intra-tree changes in bark chemistry of some temperate species of economic interest have also been investigated (Brennan et al., 2020a, 2020b; Fritsch et al., 2022). Several studies examined the intra-individual gradients in wood chemical composition or durability for temperate and tropical species (Gartner et al., 1999; Freitag and Morrell, 2001; Amusant et al., 2004, 2008; Čabalová et al., 2021). A thorough examination of the intra-tree variations and identification of wood extractives is however often lacking, notably for tropical species.

In this context, we conducted the presented research on *Sextonia rubra* (Mez.) Van der Werff (Lauraceae). This neotropical shade-tolerant rainforest tree species is endemic to the Guiana Shield and Brazilian Amazon (van der Werff, 1997). It holds ecological and economic importance and is the fourth most exploited species in French Guiana, valued for heartwood natural durability (Scotti et al., 2010; Clervil et al., 2023). This property has long been attributed to the presence of two butyrolactones, namely rubrynolide and rubrenolide, both of which have fungicidal and termiticidal activities (Rodrigues et al., 2011, 2012). Recent studies using Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) imaging revealed that other butyrolactones are biosynthesised and/or bioaccumulated in the sapwood and are likely involved in the biosynthesis of rubrynolide and rubrenolide metabolites (Fu et al., 2018, 2019). However, the previous studies only encompassed the examination of isolated wood samples, and did not comprehensively investigate the chemical defences at the scale of the whole tree. To address this gap, analytical techniques such as the coupling of liquid chromatography and mass spectrometry have proved effective in various fields of wood or bark chemistry. Untargeted metabolomic approaches, that enable the simultaneous exploration of a large number of low molecular weight compounds in a biological sample, are of particular interest. Ecological and economic issues have been addressed, in particular to study the metabolic
response of certain species to abiotic stresses (Siqueira *et al.*, 2023), the discovery of geographical discrimination markers (Creydt *et al.*, 2021, 2022), the chemotyping of different tissues (Li *et al.*, 2022) or the characterisation of bioactive compounds (Patyra *et al.*, 2022). Interestingly, processes associated with the implementation of characteristic wood properties, such as fragrance or colour, have also been studied, leading to informative data on heartwood formation and natural durability (Cao *et al.*, 2020; Yang *et al.*, 2020, 2022a, 2022b).

Therefore, we investigated heartwood formation in *S. rubra* from one of its effects, i.e., the wood resistance to fungal degradation, to its chemical biomarkers in wood tissues. The objective was to develop a comprehensive approach combining analytical chemistry, biochemistry, and field experiments to describe the intra-individual variability of specialised metabolites in relation to their defence function. A mature individual was felled to collect samples of the various tissues, both longitudinally and radially along the stem. Tissues with the highest resistance to degradation were first targeted, at various stem heights and considering radial position, to locate the metabolites potentially involved in this property. To assess the resistance of wood, soil tests were conducted on samples of sapwood, heartwood, and pith. The wood chemical diversity was subsequently examined in relation to the potential antifungal activity of the wood extractives, using novel biological tools developed to advance towards the understanding of the wood resistance to fungal degradation. Among these is the use of fungal GSTs (Glutathione S-transferases), and more particularly those of *Trametes versicolor*, which are enzymes involved in the detoxification pathways of this lignivorous fungus (Perrot *et al.*, 2018). These enzymes have proven valuable both for screening antifungal compounds (Barbier *et al.*, 2020) and for developing predictive models of natural wood durability in tropical species (Perrot *et al.*, 2018, 2020). This dual role highlights the connection between the functional role of specialized metabolites in tress and technological properties of wood. The metabolic diversity of the different tissues was characterised by Reverse Phase Liquid Chromatography –
ElectroSpray Ionisation – Tandem Mass Spectrometry (RPLC-ESI-MS/MS) for a dereplication
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workflow based on molecular networking (Olivon et al., 2018; Wolfender et al., 2019), in
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parallel with the evaluation of their bioactivity against T. versicolor GSTs (Barbier et al., 2020).
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The selected compounds were quantified to gain insight into the molecular mechanisms
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involved in heartwood formation. Overall, this approach aimed to deepen the understanding of
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the implementation of chemical defence in the stem of S. rubra during heartwood formation
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process, with regard to both the resilience of the tree and the resistance of the wood towards
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fungal degradation.
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135 MATERIALS AND METHODS

136 *Tree sampling*

Field sampling was conducted in French Guiana during the dry season, in October 2020,
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near the Paracou experimental site (5°16'846" N 52°54'938" W, Permit: ABSCH-CNA-FR-
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240495-4), between Kourou and Sinnamary. This site is a typical *terra firme* clay forest of
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French Guiana, a high-resource habitat that supports high species richness and high basal area
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(ter Steege *et al.*, 2006). The site has a tropical climate, with an average annual rainfall of 3,041
141

mm and an average air temperature of 25.7°C. A mature tree, belonging to the species *Sextonia*
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*rubra* (Mez.) Van der Werff (Lauraceae) was felled to obtain the wood samples used for
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chemical extraction and soil-bed testing. The selected individual was 31 m tall, with a diameter
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at breast height (dbh) of 70 cm. Voucher specimens were deposited in Cayenne IRD Herbarium
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under the number CAY-ML-001 (Gonzalez *et al.*, 2021).
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Samples were taken from the trunk at seven different heights (T0 to T6), from 1.30 m
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(dbh, T0) to the first fork (22.6 m, T6), with 3 m between each sample. Diametral planks and
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contiguous 50 cm logs were obtained at each height, with care taken to maintain a constant
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orientation for each height. For chemical extraction, wooden bars were sawn from each of the
150
seven diametric planks along four perpendicular radii. Wooden blocks (approximately 4 x 4 x 4 cm, radial (R), tangential (T), longitudinal (L)) were cut from sapwood, and outer to inner heartwood for each diametric bar from a radius. A pith sample was also taken from each diametric plank. Overall, 207 samples were obtained. All samples were stored at -18°C until analysis. For bed soil assays, a central board (50 x 600 mm T,L) including the pith was sawn from each log and planned to obtain a 12 x 600 mm (T,L) board, subsequently cut in sections (~ 40 x 12 x 600 mm; R,T,L) to represent all wood tissues from sapwood to heartwood and pith, according to the sampling performed from the diametric planks. These samples were allowed to stabilize in an air-conditioned room (25°C, RH 65%) until the wood equilibrium moisture content was reached (MC 12%), and were finally cut to obtain the test specimens (5 x 10 x 100 mm; R,T,L). For each radial position, 6 longitudinally adjacent replicates were made. In total, from 36 to 54 wood pieces were produced from each sampling height for all radial positions (i.e., from sapwood to pith), depending on the log diameter, for a total number of 318 samples. The sampling scheme is shown in [Supplementary Data Fig. S1]. For chemical extraction as well as bed soil tests, pith samples (including pith and the most juvenile wood) were examined separately from heartwood samples. Pith tissue is indeed composed of primary parenchyma cells derived from the apical meristem and, as juvenile wood, has specific cell features and wood properties (Moya *et al.*, 2008; Darmawan *et al.*, 2015).

## Soil bed tests

Wood durability was assessed using long-term soil bed tests (XP CEN/TS, 2006; Jacobs *et al.*, 2019) following a procedure adapted from Amusant *et al.* (Amusant *et al.*, 2014). Prior to exposure to the soil microflora, the dry mass ($m_0$) was measured for all samples after 48 h in an oven (103°C). Terrestrial microcosms (TMCs) were prepared as described by Meyer *et al.* (2014) using unsterile forest soil from the CIRAD research station of Pointe Combi (Sinnamary,
French Guiana, 5°16'846" N 52°54'938" W), which was used at 95% of its water holding capacity determined according to the experimental standard XP ENV 807. Soil tests were then conducted by incubating wood blocks under controlled laboratory conditions (30°C, 75% RH). Eight containers were filled with the unsterile forest soil and all wood samples were buried to 3/4 of their length and incubated for ten months. Each of the first seven containers was assigned to the samples obtained for a given stem height (container 1: T0 to container 7: T6, 7 to 9 radial positions for each height, 6 replicates for each radial position), and six control samples. In the eighth container, 36 control samples were incubated, and collected periodically during the experiment to follow the degradation process and to control the virulence of the soil microflora. The control samples were obtained from *Virola surinamensis* Ward. (Myristicaceae) wood, a non-durable tropical species, according to the experimental standard (EN 350, 2016). At the end of the assay, each test specimen was collected, carefully cleaned, and oven dried (72 h, 103°C). The dry mass after exposure ($m_1$) was measured and used to determine the mass loss due to decay (ML) of the samples according to the following equation, and using the mean values ± SD of the six replicates for each radial position (Equation N°1).

$$ \text{Equation N°1: ML (\%)} = \frac{(m_0 - m_1)}{m_0} \times 100 $$

## Extraction and isolation of compounds

From the 207 samples collected from the four radii of each stem cross-section from T0 to T6, a subset of 56 samples was selected for comprehensive chemical analysis. These samples corresponded to a single radius for each height, respecting the same orientation as those used in the durability tests. This selection was made after a preliminary analysis of the T0 cross-section, which revealed similar profiles for the four radii (data not shown), and to simplify the assessment of the relationship between chemical variability and natural durability (Hassegawa et al., 2016). All samples for chemical analysis were cubes of sapwood, heartwood or pith with
a volume of ~ 64 cm³. For each sample, ~ 10 g of sawdust was collected by drilling with a drill
equipped with a flat head bit. The sawdust was macerated on a rotating plate for 14 to 16 h in
ten times the volume of ethyl acetate (EtOAc) corresponding to the mass of the sample. The
macerates were dried with solid anhydrous Na₂SO₄, then filtered and evaporated under reduced
pressure to obtain crude extracts.

Compound isolation was conducted with a preparative HPLC equipped with a 322 pumping
device, a GX-271 fraction collector, a 171 diode array detector and a prep ELSII (Gilson,
Villiers-le-Bel, France). All solvents were HPLC or MS grade and were purchased from Sigma-
Aldrich (Saint-Quentin-Fallavier, France). Crude heartwood extracts were subjected to
preparative HPLC. An initial fractionation was performed using an acetonitrile (ACN) and
water gradient (solvent A: H₂O/formic acid (99.9/0.1, v/v); solvent B: ACN/formic acid
(99.9/0.1, v/v)) in isocratic mode, 55% B for 8.5 min followed by a second isocratic elution
step, 85% B for 3 min, finished with a final isocratic elution step, 100% B for 2 min.
Rubrynolide (B1) and rubrenolide (B2) molecules, whose identification was confirmed
according to literature data (Rodrigues *et al.*, 2010, 2012), were isolated at *t*<sub>R</sub> = 7.5 min and
*t*<sub>R</sub> = 11.8 min, respectively. Elution of compounds with a *t*<sub>R</sub> between 1.8 min and 3.9 min
resulted in an alkaloid-containing fraction (dry weight 56.6 mg). Its subsequent fractionation
(solvent A: H₂O/formic acid (99.9/0.1, v/v); solvent B: ACN/formic acid (99.9/0.1, v/v)) was
performed using a gradient of 5% B to 45% B in 20 min followed by 100% B during 4 min and
leading to the isolation of *N*-methylcoclaurine (**A3**, 0.6 mg) and reticuline (**A10**, 0.4 mg). For
the structural identification of these compounds, NMR spectra were recorded on Bruker 500
and 600 MHz spectrometers equipped with a TXI 1.7 mm microprobe (Bruker, Rheinstetten,
Germany). Chemical shifts (δ) are reported in ppm based on the solvent signal, coupling
constants (*J*) are expressed in Hz.
N-methylcoclaurine (A3): ¹H NMR (500 MHz, MeOD) δH 4.26 (1H, s, H-1), 3.56-3.18 (2H, m, H-3), 3.04-2.92 (2H, m, H-4), 6.66 (1H, s, H-5), 6.17 (1H, s, H-8), 3.19-2.97 (2H, m, H-1a), 6.97 (1H, d, *J* = 8.2 Hz, H-2'), 6.75 (1H, d, *J* = 8.5 Hz, H-3'), 6.74 (1H, d, *J* = 8.5 Hz, H-5'), 6.98 (1H, d, *J* = 8.2 Hz, H-6'), 2.79 (3H, s, N-CH₃), 3.84 (3H, s, C4'-OCH₃), ¹³C NMR (125 MHz, MeOD) δC 66.3 (CH, C-1), 47.2 (CH₂, C-3), 24.0 (CH₂, C-4), 112.7 (CH, C-5), 149.2 (C, C-6), 146.6 (C, C-7), 115.7 (CH, C-8), 40.9 (CH₂, C-1a), 123.6 (C, C-4a), 128.2 (C, C-8a), 130.3 (C, C-1'), 131.7 (CH, C-2'), 116.6 (CH, C-3'), 157.9 (C, C-4'), 116.6 (CH, C-5'), 131.7 (CH, C-6'), 41.2 (CH₃, N-CH₃), 56.5 (CH₃, C4'-OCH₃), ESI HRMS *m/z* [M + H]⁺ 300.1594 (experimental for C₁₈H₂₂NO₃⁺, 300.1593, err. -0.3 ppm).

Reticuline (A10): ¹H NMR (600 MHz, MeOD) δH 4.24 (1H, s, H-1), 3.41-3.17 (2H, m, H-3), 3.02-2.88 (2H, m, H-4), 6.73 (H, s, H-5), 6.16 (1H, s, H-8), 3.16-2.92 (2H, m, H-1a), 6.65 (1H, s, H-2'), 6.84 (1H, d, *J* = 8.3 Hz, H-5'), 6.57 (1H, d, *J* = 8.1 Hz, H-6'), 2.75 (3H, s, N-CH₃), 3.81 (3H, s, C3'-OCH₃), 3.82 (3H, s, C4'-OCH₃), ¹³C NMR (150 MHz, MeOD) δC 66.3 (CH, C-1), 47.2 (CH₂, C-3), 24.0 (CH₂, C-4), 112.6 (CH, C-5), 149.3 (C, C-6), 146.4 (C, C-7), 115.8 (CH, C-8), 40.7 (CH₂, C-1a), 123.1 (C, C-4a), 125.9 (C, C-8a), 130.7 (C, C-1'), 131.8 (CH, C-2'), 146.2 (C, C-3'), 148.1 (C, C-4'), 116.7 (CH, C-5'), 131.8 (CH, C-6'), 41.3 (CH₃, N-CH₃), 56.5 (CH₃, C3'-OCH₃), 56.5 (CH₃, C4'-OCH₃), ESI HRMS *m/z* [M + H]⁺ 330.1700 (experimental for C₁₉H₂₄NO₃⁺, 330.1705, err. 1.5 ppm).

243

Mass spectrometry analysis

RPLC-ESI(+)-HRMS/MS Analysis – Untargeted analysis

For the untargeted metabolomic analysis of the chemical diversity of *S. rubra* stem, samples were selected from the eastern radius of the T4 cross-section. Four crude extracts corresponding to one sample for each tissue (i.e., bark, sapwood, heartwood and pith) were filtered through a PTFE membrane (0.45 µm) and prepared at 1 mg.mL⁻¹ in methanol. The chromatographic

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system used was a UHPLC 1260 Infinity II (Agilent Technologies, Waldbronn, Germany). It
was coupled to a QToF 6546 tandem mass spectrometer (Agilent Technologies, Waldbronn,
Germany). Chromatographic separation was performed on an Accucore RP-MS column
(100 mm × 2.1 mm, 2.6 µm, Thermo Scientific, Les Ulis, France) with the mobile phase
consisting of H₂O/formic acid (99.9/0.1; V/V) (A) and acetonitrile (B). The column oven was
set at 45°C. Compounds were eluted at a flow rate of 0.4 mL.min⁻¹ with a gradient from 5% B
to 100% in 20 min and then 100% B during 3 min. The injection volume was set at 5 µL for all
analyses. Mass spectra were acquired in positive ion mode. The electrospray source was
configured with the following parameters: gas temperature: 325°C, drying gas flow rate:
10 L.min⁻¹, nebulizer pressure: 30 psi, sheath gas temperature: 350°C, sheath gas flow rate
10 L.min⁻¹, capillary voltage 3500 V, nozzle voltage 500 V, fragmentor voltage 130 V,
skimmer voltage 45 V, Octopole 1 RF voltage 750 V. The use of a calibration solution,
containing two internal reference masses (purine, C₅H₄N₄, *m/z* 121.0509, and HP-921 [hexakis-
(1H,1H,3H-tetrafluoropentoxy)phosphazene], C₁₈H₁₈O₆N₃P₃F₂₄, *m/z* 922.0098), routinely
resulted in mass accuracy below 3 ppm. Data-dependent MS/MS events were acquired for the
five most intense ions detected by full-scan MS, in the *m/z* 200–950 range, above an absolute
threshold of 1000 counts. Selected precursor ions were fragmented with a fixed collision energy
of 15 eV and with an isolation window of 1.3 amu. The mass range of the precursor and
fragment ions was set to *m/z* 200–950 and 50-950, respectively.

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270 RPLC-ESI(+)-HRMS – Targeted analysis

271
Crude extracts corresponding to bark, sapwood, heartwood and pith were filtered through a
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PTFE membrane (0.45 µm) and prepared at 0.5 mg.mL⁻¹ in methanol [Supplementary Data
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Table S1]. The injected volume was 2 µL. Two molecules were used as internal standards:
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papaverine (PPV, 1-[(3,4-dimethoxyphenyl)methyl]-6,7-dimethoxyisoquinoline, C₂₀H₂₁NO₄,
RPLC-ESI(+)-HRMS *m/z* 340.1553, *t*<sub>R</sub> = 4.2 min) and *N*-decanoyl-DL-homoserine lactone (NDHSL, *N*-(2-oxooxolan-3-yl)decanamide, *C*<sub>14</sub>H<sub>25</sub>NO<sub>3</sub>, RPLC-ESI(+)-HRMS *m/z* 256.1907, *t*<sub>R</sub> = 7.0 min) for the external quantification of alkaloids and butyrolactones, respectively. A PPV and NDHSL stock solution was prepared at 3 × 10<sup>-4</sup> mol.L<sup>-1</sup> and 6 × 10<sup>-3</sup> mol.L<sup>-1</sup>, respectively, to be diluted in each sample to reach a final concentration of 7.5 × 10<sup>-6</sup> mol.L<sup>-1</sup> and 1.5 × 10<sup>-6</sup> mol.L<sup>-1</sup>, i.e. 15 pmol and 300 pmol injected, for PPV and NDHSL, respectively. External quantifications were performed using the same chromatographic and analytical system as described in untargeted analysis section. Compounds were eluted at a flow rate of 0.4 mL.min<sup>-1</sup> with a gradient from 5% B to 100% in 9 min and then 100% B during 2 min. External calibration curves were optimized by injecting 1 × 10<sup>5</sup> pmol to 2 × 10<sup>-2</sup> pmol of PPV and NDHSL into the analytical system, in triplicate. A linear model was calculated from the triplicate measurements to ensure that the measured concentration did not exceed a standard deviation of ±15% over a series of consecutive measurements (Gale and Duncan, 2020).

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289 *Chemical data processing and analysis*

The RPLC-ESI(+)-HRMS and HRMS/MS raw data, in .d (Agilent Technologies), were converted to .mzML using the Peak Picking function of MSConvert (v. 3.0.20344), a module of the Proteowizard package (Kessner *et al.*, 2008). All .mzML files were processed using MZmine (v. 2.53) (Pluskal *et al.*, 2010). The mass detection step was performed with the following parameters "MS1 Noise level = 1,000" and "MS² Noise level = 50". A chromatogram construction step according to the ADAP algorithm was performed with the following parameters: "minimum group size = 3 scans", "group intensity threshold = 1,000", "minimum highest intensity = 1,000", "m/z tolerance = 0.005 Da or 15 ppm". Then the chromatogram deconvolution was conducted according to the following parameters: "S/N threshold = 10", "minimum feature height = 1,000", "coefficient area threshold = 50", "peak duration range =
300 0.01-0.09 min" and "retention time (RT) wavelet range = 0.01-0.06" was performed. MS² scan
301 pairing was performed with the following parameters "m/z range for MS² scan pairing = 0.1
302 Da" and "RT range for MS² scan pairing = 0.2 min". Isotopologues were grouped using the
303 "Isotopic peaks grouper" function with the following parameters "m/z tolerance = 0.005 or
304 15 ppm", "RT tolerance = 0.1 min". The peak list was filtered using the "Feature lists row filter"
305 with the option "Keep only peaks with MS²". A list of peaks was generated by alignment using
306 the "Join Aligner" algorithm with the following parameters "m/z tolerance = 0.005 Da or
307 15 ppm", "RT tolerance = 0.1 min", "Weight for m/z = 80" and "Weight for RT = 20". The data
308 were exported as ".mgf" and the metadata as ".csv". Molecular networks were then generated
309 using the t-SNE algorithm of the MetGem software (Olivon et al., 2018). Briefly, this
310 methodology allows MS/MS spectra to be compared in a two-dimensional space. Each
311 precursor ion is represented by a node. If two nodes are close in space, then the precursor ions
312 share spectral and therefore structural similarities. Once this representation is created, it is
313 possible to query databases of standards molecules and annotate known metabolites, a process
314 known as dereplication (Allard et al., 2016; Wolfender et al., 2019). In this work, we used the
315 annotation levels proposed by the Metabolomics Standards Initiative (Godzien et al., 2018).
316 Level 0 corresponds to the identification of the 3D structure of an isolated compound, level 1
317 corresponds to the identification of compounds by comparison with a standard, level 2
318 corresponds to a putative annotation by comparison with spectral libraries, level 3 corresponds
319 to the identification of the molecular family and level 4 corresponds to an unknown molecule.
320 NMR spectra were processed and analysed using TopSpin 3.6.2 (Bruker, Rheinstetten,
321 Germany).

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323 X-ray structure determination of compound B1 and B8
324 Crystals of compounds **B1** and **B8** were obtained by slow evaporation at 4°C in methanol.
325 A suitable crystal was selected for each of them, mounted on a nylon loop and fixed with oil.
326 X-ray diffraction and crystallographic data were then collected at 150K for B1 and at room
temperature for B8, using redundant ω scans on a Rigaku XtaLabPro single-crystal
327 diffractometer using microfocus Mo Kα radiation and an HPAD PILATUS3 R 200K detector.
328 Using Olex2 (Dolomanov *et al.*, 2009), the structures were easily solved by intrinsic phasing
329 methods (SHELXT (Sheldrick, 2015a)) and by full-matrix least-squares methods on F² using
330 SHELXL (Sheldrick, 2015b). Non-hydrogen atoms were refined anisotropically, and most of
331 the hydrogen atoms were identified in difference maps and were treated as riding on their parent
332 atoms. For **B1**, the Flack parameter (Flack, 1983) was refined to assess the absolute
333 configuration. To secure the favorable probabilities derived from the subsequent a-posteriori
334 Bijvoet analysis (Hooft *et al.*, 2008), we used a RIGAKU MM007 HF rotating anode providing
335 copper radiation through Osmic CMF confocal optics and equipped with a Rapid II curved
336 Image Plate to record the enhanced weak anomalous signal from redundant ω-scans. Solution
337 and refinement were performed in a similar manner as before, and the Flack parameter was
338 unambiguously confirmed. All the molecular graphics presented were computed using Mercury
339 2023.2.0 (Macrae *et al.*, 2006).
340

341 Crystal data for B1_Cu: C17H28O4 (M =296.39 g.mol-1): monoclinic, space group P21 (no. 4), a = 5.119(5) Å, b = 5.109(12) Å, c = 33.05(2) Å, β = 91.64(5)°, V = 864(2) Å3, Z = 2, T = 293(2) K, µ(CuKα) = 0.639 mm-1, Dcalc = 1.139 g.cm-3, 14540 reflections measured (10.712° ≤ 2Θ ≤ 130.168°), 2882 unique (Rint = 0.0747, Rsigma = 0.0828) which were used in all calculations. The final R1 was 0.0781 (I > 2σ(I)) and wR2 was 0.2664 (all data). Flack parameter = -0.5 (8). Bijvoet Pairs = 1246 (97% coverage): P2 (true) = 1.000. P3 (true) = 0.940, P3 (false) = 0.2.10-6. Hooft parameter = 0.1 (2).
Crystal data for B8: C₁₇H₂₈O₅ (M = 312.39 g.mol⁻¹): orthorhombic, space group P2₁2₁2₁ (no.19), a = 4.9660(2) Å, b = 10.2404(3) Å, c = 34.6204(12) Å, V = 1760.58(11) Å³, Z = 4, T = 293 K, µ(Mo Kα) = 0.085 mm⁻¹, Dcalc = 1.179 g.cm⁻³, 24394 reflections measured (6.164° ≤ 2Θ ≤ 58.196°), 4227 unique (Rint = 0.0397, Rsigma = 0.0223) which were used in all calculations. The final R₁ was 0.0435 (I > 2σ(I)) and wR₂ was 0.1212 (all data). Flack parameter = 0.2 (10). Bijvoet Pairs = 1676 (86% coverage): P2 (true) = 1.000. P3 (true) = 0.937, P3 (false) = 0.110⁻³. Hooft parameter = -0.1 (3).

Crystallographic data of the two structures (B1_Mo/B1_Cu and B8) have been deposited in the Cambridge Crystallographic Data Centre database (the deposition numbers are respectively CCDC 2291176/CCDC 2291177 and CCDC 2291178). Copies of the data can be obtained free of charge from the CCDC at http://www.ccdc.cam.ac.uk.

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Thermal stability assay
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The six glutathione S-transferases from *Trametes versicolor* have been heterologously produced in *Escherichia coli* and purified as previously described (Deroy *et al.*, 2015). The biosynthetic genes have been designed from the sequenced genome and transcriptomic studies of the white-rot *T. versicolor* from the following genes and their corresponding Prot ID accession numbers in the JGI database: TvGSTO-1S, Tv75639; TvGSTO-2S, Tv56280; TvGSTO-3S, Tv48691; TvGSTO-4S, Tv65402; TvGSTO-5S, Tv54358; and TvGSTO-6S, Tv23671. These *in vitro* assays were performed in 384-well plates containing 5 µL of mQ water, 11 µL of Tris-HCl buffer (150 mM, pH = 8), 5 µL of GST solution (50 mM diluted in Tris-HCl buffer), 2 µL of each metabolic extract diluted to 1 mg.mL⁻¹ in DMSO and 2 µL of SYPRO orange, previously diluted (80-fold), for a total volume of 25 µL per well. The metabolic extracts tested are the same as those used for metabolomic analyses. Plates were prepared at +4°C and then centrifuged at 4 000 g for 10 s. Fluorescence (at 485 nm and 530 nm for
excitation and emission wavelengths, respectively) is measured every minute as a function of temperature using a polymerase chain reaction fluorimeter (CFX384 touch, Biorad). The cycle starts at 5°C for 3 minutes, then the temperature increases at a gradient of one degree per minute up to 95°C. Thermal denaturation of the GSTs exposes their hydrophobic regions, enabling the fluorophore, SYPRO orange, to emit measurable fluorescence. The melting temperature ($T_m$) corresponds to the temperature at which 50% of the proteins in the reaction mixture are denatured. This value is calculated by applying a first derivative to the data obtained. Measuring the melting temperature of proteins allowed us to identify any interaction between GSTs and the molecules present in the metabolic extracts. Wells containing only the reaction mixture and DMSO were used to obtain a reference $T_m$ ($T_{m,ref}$). The change in $T_m$ ($\Delta T_m$) between those of the reference and the extracts was then calculated by subtraction. Absolute values were centered reduced for further analysis.

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386 Statistical analysis

Figures and other data analyses were performed using custom R scripts (v. 4.2.3) with various packages (dplyr, GGally, ggExtra, ggplot2, ggpubr, ggrepel, stats). Significance was considered at a threshold of $p$-value $\le 0.01$. The hypothesis of normality of the data was investigated using a Shapiro-Wilk test. When the hypothesis was refuted, a non-parametric Kruskal-Wallis test was applied, followed by a Wilcoxon post-hoc test to determine whether there were differences in distribution ranks between the different groups studied. The PCA and PLS-DA were performed with HRMS spectra of the 56 samples using Metaboanalyst v. 5.0 (Pang *et al.*, 2021). The square-root of intensities was centered-reduced and divided by the standard deviation of each feature. A correlogram was constructed by using the amounts of **A3**, **A10**, **B1** and **B2**, GST reactivity from heartwood and pith EtOAc extracts and mass loss of the corresponding samples with Spearman's coefficient.

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# RESULTS

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Evaluation of the decay resistance of S. rubra sapwood, heartwood and pith through soil bed assays

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Soil bed tests were performed to identify the tree tissues best able to defend themselves against lignivorous organisms, considering potential spatial variations of this property along the trunk.

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Fig. 1 shows the distribution of mass loss (ML) for all samples. After ten months of exposure to unsterile forest soil, controls and sapwood samples were greatly degraded (control: mean, ML 41% ±5%, SW: mean, ML 48% ±6%) while heartwood (mean, ML 10% ±2%) and pith samples (mean, ML 9% ±1%) were significantly less degraded. A non-parametric Kruskal-Wallis test showed that distributions were different ($p_{-value} = 2 \times 10^{-7}$). Following post-hoc comparisons (Wilcoxon pairwise test), the degradations measured between control and sapwood samples are equivalent ($p_{-value} = 5 \times 10^{-2}$) but significantly different from HW and pith samples ($p_{-value} < 1 \times 10^{-2}$). A closer examination of the heartwood and pith samples for each cross-section at the different depths [Supporting Information Fig. S2] and heights [Supporting Information Fig. S3] was performed but did not demonstrate any significant differences according to a Kruskal-Wallis test ($p_{-value} > 1 \times 10^{-2}$). These results highlight the consistency of durability properties for heartwood and pith samples both radially and longitudinally. Sapwood degradation was shown to be variable as a function of height, with no particular trend from the bottom to the top [Supporting Information Fig. S2].

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Chemical diversity of S. rubra bark, sapwood, heartwood and pith

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A molecular network was generated from untargeted RPLC-ESI(+)-HRMS/MS analysis using the t-SNE algorithm of the MetGem software [Supporting Information Fig. S4]. One sample for each tissue was used to qualitatively describe chemical diversity along a radial and
longitudinal gradient, as described in untargeted analysis section (Olivon et al., 2018). Database
queries were used to annotate phenolic compounds, composed of a flavanol skeleton, such as
catechin (F1), procyanidin A1 (F2) and procyanidin B2 (F3) [Supporting Information Figs S5-
7]. However, the majority of the molecular network features were irrelevant annotations (level
4 to 3) or not annotated at all due to the lack of information in online MS/MS databases. The
known compounds rubrynolide (B1) and rubrenolide (B2) [Supporting Information Figs S8-13]
were identified based using previously published information (Fu et al., 2019, 2018; Rodrigues
et al., 2012, 2010). A study of the fragmentation spectra corresponding to the nodes near B1
and B2 allowed to annotate the rubranolide molecule (B3) [Supporting Information Fig. S14],
and the previously described butanolides B1-3 and isozuihoenalide (B4-B7) [Supporting
Information Figs S15-18] (Fu et al., 2019), based on the characteristic successive loss of H₂O
and/or CO followed by the cleavage of each C-C bond after opening the lactone ring (Crotti et
al., 2004, 2009). Finally, rubrynolide (B1) and a new γ-butyrolactone (B8) were isolated and
characterised by X-ray crystallography [Supporting Information Figs S8-10, S19-21; Table S2-
16].

In the molecular network, two clusters containing 15 nodes characterised by an even
nominal mass were annotated as benzylisoquinolines and aporphines [Supporting Information
Fig. S4]. This suggests that these ions are protonated alkaloids with an odd number of nitrogen
atoms. Despite the use of an alkaloid spectral library, only one node was annotated as a
benzylisoquinoline corresponding to reticuline (A10) (Agnès et al., 2022). Analysis of crude
heartwood and pith extracts revealed a number of compounds, including two isomers with *m/z*
286.1438 (A1-2) [Supporting Information Fig. S22], two isomers with *m/z* 300.1594 (A3-4)
Supporting Information Fig. S23], two isomers with *m/z* 314.1751 (A5-6) [Supporting
Information Fig. S24], three isomers with *m/z* 328.1543 (A7-9) [Supporting Information
Fig. S25), one ion with *m/z* 330.1700 (A10) [Supporting Information Fig. S26], two isomers
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with *m/z* 342.1700 (**A11-12**) [Supporting Information Fig. S27], one ion with *m/z* 344.1856 (**A13**) [Supporting Information Fig. S28] and two isomers with *m/z* 356.1856 (**A14-15**) [Supporting Information Fig. S29]. All these compounds were eluted between 3.0 and 5.5 min [Supporting Information Fig. S22-29].

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Ions corresponding to alkaloids of the benzylisoquinoline subfamily exhibit a distinctive fragmentation pattern (Fig. 2) (Schmidt *et al.*, 2005). The initial step is the formation of an **a-type** ion corresponding to the loss of the nitrogen atom as ammonia (**A1-2**), methylamine (**A3-4**, **A6**, **A10**) or dimethylamine (**A5**, **A13**) generating diphenylethylene derivatives by opening the tetrahydropyridine ring. The generation of the **b-type** ion is due to an "even electron"-type MacLafferty rearrangement. It involves the proton on the tetrahydroisoquinoline nitrogen and the aromatic ring of the benzyl substituent. The **e-type** ion corresponds to the benzyl moiety and is complementary to the **b-type** ion but can also be generated after fragmentation of the **a-type** ion. Since different substituents are described for this molecular class, different masses are expected depending on the chemical functions. Fragmentation of compounds **A1**, **2**, **3**, **4** and **5** generated an **e-type** ion with *m/z* 107, indicating the presence of a hydroxyl function on the ring C. Fragmentation of compound **A6** generated an **e-type** ion with *m/z* 121, indicating the presence of a methoxy group on the C ring. Fragmentation of compounds **A10** and **13** generated an **e** ion with *m/z* 131 indicating the presence of a -OH and -OCH₃ group on the C ring. The generation of the **d-type** ion is due to the fragmentation of the **a-type** ion. The same patterns are observed for the **c-type** ions, generated by a rearrangement following the loss of benzyl groups. All benzylisoquinolines (**A1-6**, **10** and **13**) exhibited a **c-type** ion with *m/z* 175, suggesting the presence of vicinal -OH and -OCH₃ groups on the A ring.

Compounds **A3-4** (*m/z* 300.1594) were identified as tertiary amines with the neutral loss of 31 Da, [M + H - NH₂CH₃]⁺ showing a similar fragmentation pattern as **A1-2**. Both of them
showed type **a** ion with *m/z* 269, **b** with *m/z* 192, **c** with *m/z* 175 and **e** with *m/z* 107. Following the isolation of A3 and its characterisation by NMR [Supporting Information Figs S30-35; Tables S17-18], **A3** was identified as *N*-methylcoclaurine (Guo *et al.*, 2015) and **A4** was annotated as *N*-methylisococlaurine. Indeed, the C ring of compound **A3** shows three COSY correlations between H-3 and H-4, on the B ring, and H-2' and H-3' and H-5' and H-6' suggesting that C-4' has an OH group, which is consistent with the nominal mass of the **e** ion.
Based on these results, compounds **A1** and **A5**, which were identified as a secondary amine (neutral loss of 17 Da ([M + H – NH₃]⁺) and a quaternary amine (neutral loss of 45 Da ([M + H –(CH₃)₂NH]⁺), respectively, were annotated as coclaurine and magnocurarine.
Compound **A6**, which exhibited an **e**-type ion at *m/z* 121 suggesting the presence of an -OCH₃ group on the C ring and shared a similar fragmentation spectrum with **A3**, was annotated as *O*-methyl-*N*-methylcoclaurine. Compound **A10** was isolated and characterised by NMR as reticuline by comparison with literature data (Guo *et al.*, 2015) [Supporting Information Figs S36-41; Tables S17-18]. **A13** has a fragmentation spectrum similar to that of **A10**, except for the first neutral loss corresponding to a quaternary amine, allowing **A13** to be annotated as tembetarin. Compound **A2** has the same fragmentation spectrum as compound **A1** and can be annotated as an isomer of **A2**.

The alkaloids of the aporphine subfamily show a more complex fragmentation pattern than the benzylisoquinolines (Conceição *et al.*, 2020, 2021). Seven compounds have been annotated as belonging to this alkaloid subfamily (**A7-9**, **11-12**, **14-15**). The analysis of a boldine standard enabled us to annotate **A7**, due to identical retention times (*t*<sub>R</sub> = 3.0 min) and similar fragmentation spectra [Supporting Information Figs S25 and S42]. Compounds **A11** and **A12** have a similar fragmentation spectrum to boldine (**A7**) except for the first neutral loss corresponding to a quaternary amine. **A11** and **A12** were therefore annotated as *N*-methylboldine and *N*-methylisoboldine, respectively [Supporting Information Fig. S27]. The
presence of a fragment with *m/z* 279 for compound **A14** suggests the presence of -OH and -OCH₃ groups on the A ring and thus of two -OH groups on the C ring, in agreement with the fragmentation spectra obtained by Conceição *et al*. following the fragmentation of *N*-methylpredicentrine [Supporting Information Fig. S29]. Finally, **A15** was annotated as xanthoplanine due to the presence of the ion with *m/z* 280, which is characteristic for this compound [Supporting Information Fig. S30]. All annotated molecules are listed in Supporting Information Table S19 and Fig. 3.

To complement these results, and to explore the chemical variability of *S. rubra* wood and bark along the stem, taking into account radial and longitudinal directions, RPLC-ESI(+)-HRMS data were obtained for the subset of 56 samples [Supporting Information Table S1]. Principal component analysis (PCA) was performed on this dataset, but was of little use due to redundant chemical diversity between the 4 tissues analysed [Supporting Information Fig. S43]. A partial least square discriminant analysis (PLS-DA) (Fig. 4) however showed distinctions between the four tissues regardless of trunk height or depth. PLS-DA explained 17.8% of the data variability and components 1 and 2 explained 7.5% and 10.3%, respectively. The VIP (Variable of Importance in Projection) search revealed 4 ions, corresponding to the sodium and ammonium adducts of the two butanolide compounds **B4** and **B5**, and whose respective intensities allowed us to categorise the samples into 3 groups according to their tissue of origin: bark, sapwood, and heartwood and pith [Supporting Information Fig. S44]. A complementary VIP analysis performed only on heartwood and pith tissues highlighted a quantitative difference of the ions corresponding to a benzylisoquinoline (not listed in the database) annotated as *O*-methyl-*N*-dimethylcoclaurine, based on the fragments obtained in the MS² analysis, an aporphine alkaloid (boldine, **A7**) and the butyrolactone rubrynolide (**B1**) with a relative intensity greater in pith compared to heartwood [Supporting Information Figs S45-46]. PEGs
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were detected and annotated but discarded from the previous analyses [Supporting Information Fig. S47].

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*Correlation of wood decay resistance with the chemical diversity using fungal glutathione S-transferases*

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The reactivity of wood extracts against Glutathione S-Transferases from the *T. versicolor* Omega family (GSTO) served as a tool to correlate the wood decay resistance property with the chemical diversity of the samples. All crude EtOAc extracts corresponding to those used for the targeted analyses were tested against 6 GSTOs. This experiment demonstrated that EtOAc crude extracts from heartwood and pith were more reactive against the GST used than those from sapwood [Supporting Information Fig. S48]. Alkaloids and the butyrolactones rubrynolide (**B1**) and rubrenolide (**B2**) are specific to both heartwood and pith.

After fractionation of crude EtOAc extracts of heartwood and pith, two subfractions were obtained: one containing only alkaloids and the other containing only butyrolactones.

Molecules **A3** (*N*-methylcoclaurine), **A10** (reticuline), **B1** and **B2** were isolated and tested against *T. versicolor* GSTs (Table 1). The alkaloids **A3** and **A10** destabilised GSTO3S with $\Delta T_m = -16^\circ C$ in contrast to the two butyrolactones **B1** and **B2**, for which no effect was observed.

The determination of the GST reactivity values for each radially organised sample is shown in [Supporting Information Figs S49-50].

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*Radial and longitudinal quantification of alkaloid and butyrolactone compounds in S. rubra heartwood and pith*

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We quantified **A3** and **A10** alkaloids as well as **B1** and **B2** butyrolactones in the samples to understand the distribution of bioactive molecules within the studied tree [Supporting Information Figs S51-55]. The amounts of **A3** and **A10** were 60 ±19 mg.kg⁻¹ and

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122 ±44 mg.kg⁻¹ (Fig. 5A) and the quantities of **B1** and **B2** are respectively 7 ±2 g.kg⁻¹ and 4 ±1 g.kg⁻¹, respectively (Fig. 5B), when the amounts are averaged radially and compared longitudinally. There is no difference between the mean quantities of the different molecules for the different heights analysed after applying a Kruskall-Wallis test (*p*-value > 1 × 10⁻²). The amounts of **A3**, **A10**, **B1** and **B2** do not differ according to the depth (*p*-value > 1 × 10⁻²). Their average radial amounts are 56 ±15 mg.kg⁻¹, 110 ±31 mg.kg⁻¹, 7 ±2 g.kg⁻¹ and 4 ±2 g.kg⁻¹, respectively (Figs 5C-D).

We then correlated the mass loss, which is inversely proportional to durability, and the GST reactivity, a proxy for the fungicidal activity of the extracts, with the amounts of compounds **A3**, **A10**, **B1** and **B2** in the crude heartwood and pith EtOAc extracts. Finally, we proposed a variable corresponding to the ratio of the amounts of butyrolactones to alkaloids (Fig. 6). Clearly, the amounts of **B1** and **B2** are positively correlated, as well as **A3** and **A10**, and also between butyrolactones and alkaloids. The amount of butyrolactone had no influence on the GST reactivity, confirming the results obtained (Table 1). On the other hand, the amount of alkaloid was slightly negatively correlated with the GST reactivity, in accordance with the destabilisation previously observed in the GST3S tests (Table 1). The opposite tendency was observed for the correlation between pure compounds and mass loss, with a stronger negative correlation between the content in butyrolactones and mass loss compared to alkaloids, indicating a more prominent role of rubrenolide and rubrynolide against fungal decay in soil bed tests than benzylisoquinolines. Finally, for heartwood and pith, the higher the ratio of butyrolactones to alkaloids, the greater the reactivity of the GSTs and the lower the mass loss observed, in both cases positively affecting the natural durability of *S. rubra* against wood-degrading fungi.
573 DISCUSSION

574 S. rubra is known for its durable to very durable wood (Centre Technique Forestier
575 Tropical, 1984). As heartwood formation involves spatialized processes and different cell
576 lineages across tree tissues, the first aim was to characterise the resultant of this process by
577 studying wood decay resistance along the whole stem. The results obtained from the soil bed
578 tests complemented earlier studies showing that S. rubra heartwood is generally durable against
579 the white rot fungus *Pycnoporus sanguineus* and the brown rot fungus *Antrodia* sp. (Amusant,
580 2003). The increased decay resistance of S. rubra heartwood and pith compared to sapwood
581 aligned with the IC50 previously measured for S. rubra wood extracts against *Trametes
582 versicolor* and *Gloeophyllum trabeum*, with values of 633 and 987 µg.mL-1 for sapwood, and
583 290 and 385 µg.mL-1 for heartwood, respectively (Houël et al., 2017). Furthermore, the
584 measured mass loss averaged 10% ±2% for heartwood and 9% ±1% for pith samples after ten
585 months of incubation (Fig. 1), compared to 3% obtained by Carneiro et al. after a 3-months
586 exposure (Carneiro et al., 2009). The greater durability of pith and heartwood compared to
587 sapwood could result from the nature and relative amount of extractives, and/or the presence of
588 a large amount of reserve material in the sapwood (Amusant et al., 2007, 2014, Kirker et al.,
589 2013), along with complementary physico-chemical factors. Our results showed that the
590 cambial age of the wood and the height of the sample on the trunk did not influence the natural
591 durability of S. rubra wood for the studied individual. Similar observation was made for the
592 tropical Fabaceae *Eperua grandiflora* (Aubl.) Baill., for which the variability observed in the
593 natural durability of the heartwood stemmed from tree-specific effect rather than radial or
594 height-related factors (Amusant et al., 2008). Comparable results were reported for *Cupressus
595 sempervirens* (Palanti et al., 2021). However, such a stable pattern does not apply to all durable
596 tropical tree species. An increased wood resistance to decay has for example previously been
597 observed for teak (*Tectona grandis* L.f.) or basralocus (*Dicorynia guianensis* Amsh.)
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heartwood from juvenile (inner) to mature (outer) heartwood (Amusant *et al.*, 2004; Moya *et al.*, 2014). This highlights in contrast the specificity observed for *S. rubra*.

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Since extractives can be linked to natural durability through the heartwood formation process, we performed a metabolomic analysis on different tissues of a mature *S. rubra* tree (Fig. 3 and Supporting Information Table S19), underscoring that many of these molecules are specific to one or two wood tissues. The known butyrolactones **B1**, **B2** and **B3** (rubrynolide, rubrenolide and rubranolide, respectively) were mainly detected in heartwood and pith (Table S19). These results reinforce the data obtained in the soil bed test assays, supporting the strong resistance to fungal decay in pith and heartwood in view of the known activity of **B1** and **B2** against lignivorous fungi (Rodrigues *et al.*, 2010, 2012; Houël *et al.*, 2017). The newly annotated butanolides **B4**, **B5** and **B6** were predominantly detected in bark and sapwood, consistent with the compartmentalisation hypothesis for **B1-B3** biosynthesis (Fu *et al.*, 2019, 2018). The known compound **B7** (isozuihoenalide) appeared only in the sapwood, consistent with previous data (Fu *et al.*, 2019), while **B8**, a newly described butyrolactone, was detected in heartwood and pith (Fig. 3 and Supporting Information Table S19). Additionally, alkaloids were detected and identified for the first time in the heartwood and pith of this species (Fig. 3 and Supporting Information Table S19). Although molecular networks and the use of an alkaloid-specific database provided limited matches, manual annotation based on HRMS/MS spectra and RMN analysis enabled us to annotate or identify 8 benzylisoquinolines (**A1-6**, **A10**, **A13**, confidence level 3 to 0) and 7 aporphines (**A7-9**, **A11-12**, **A14-15**, confidence level 3 to 1) already reported in related genera. Numerous Lauraceae species biosynthesise these compounds (Custódio and Florêncio da Veiga Junior, 2014; Silva Teles *et al.*, 2019), in particular in *Ocotea*, a genus close to *Sextonia*, where benzylisoquinolines and aporphines coexist (Coy Barrera and Cuca Suárez, 2009; Garcez *et al.*, 2011; Silva Teles *et al.*, 2019).

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Finally, ubiquitous flavonoids were detected and annotated in the bark and sapwood. PLS-DA and VIP analysis of crude EtOAc extracts from samples analysed by RPLC-ESI(+)-HRMS also revealed a slight difference between pith and heartwood samples [Supporting Information Fig. S45]. This could initially be related to specific traits of juvenile wood, defined as the pith and adjacent tissues. These tissues have anatomical features that differ from those of mature wood, resulting in lower physico-mechanical properties (Lachenbruch *et al.*, 2011; Giroud *et al.*, 2021). However, this distinction between corewood and outerwood didn't apply in terms of natural durability in the case of *S. rubra*, as pith and heartwood showed no statistically significant difference in decay resistance or GST reactivity.

The reactivity of *T. versicolor* GSTs towards *S. rubra* extractives was used as a proxy to link wood resistance to decay with the chemical reactivity of the specialised metabolites produced during heartwood formation. These enzymes may allow wood-decomposing fungi to protect themselves from extractives naturally present in wood as part of an intricate detoxification system (Valette *et al.*, 2017; Barbier *et al.*, 2020). They increase the solubility and decrease the reactivity of potentially toxic molecules (Gullner *et al.*, 2018). These tests revealed particularly high GST reactivity in the heartwood and pith EtOAc extracts compared to those of sapwood, suggesting the presence of specialised metabolites protecting these tissues. This supports the natural durability results and aligns with previous findings on this tropical species (Perrot *et al.*, 2020). The destabilisation of GST3 upon exposure to various crude alkaloids suggests an interaction between this molecular family and the enzyme potentially triggering *T. versicolor* defence mechanism when exposed to alkaloids. In the genus *Annona*, alkaloids are thought to be involved in chemical defence, with an induced or increased production following infection of plant tissues by fungal pathogens (Toledo-González *et al.*, 2023). Moreover, a fraction obtained from *D. guianensis* heartwood extracts and containing
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alkaloids was shown to have fungistatic activity against the wood-rotting fungi *Pycnoporus sanguineus* and *Trametes versicolor* in a dose-dependent manner (Anouhe *et al.*, 2018). By contrast, butyrolactones **B1** and **B2**, already known for their fungicidal activity, did not alter the reactivity of the six tested GST, potentially suggesting a different and unknown mechanism of action, warranting further exploration of other isoforms. Potential variation of GST reactivity with trunk height could not be addressed in this experiment.

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To complement these results, the quantification of molecules specific to heartwood and pith, namely butyrolactones and alkaloids, was therefore undertaken. It revealed that there was no significant variation from the bottom of the trunk to the top (Fig. 5). The same is true for alkaloids in the radial direction, regardless of the height examined (Fig. 5). On the other hand, butyrolactones seem to accumulate in the middle heartwood following a saturation function (Fig. 5). Few data are available on the radial or longitudinal variations of wood extractives, either qualitatively or quantitatively. In contrast to our results, an increase in extractives content from juvenile to mature heartwood was observed for different tree species, including the tropical Moraceae *Bagassa guianensis* Aubl. (Bossu *et al.*, 2016). However, positive or negative variations have been shown depending on both the tree species and the type of extractives, either radially or longitudinally (Gominho *et al.*, 2001; Gierlinger and Wimmer, 2004; Latorraca *et al.*, 2011; Lehnebach *et al.*, 2019; Čabalová *et al.*, 2021). In the case of *S. rubra*, it is possible that this individual has regulated the biosynthesis of these metabolites according to environmental conditions or individual history. Lehnebach *et al.* highlighted that heartwood formation in the commercial species *Dicorynia guianensis* Amsh. is an ontogenetic process that regulated the amount of sapwood, which is continuously and increasingly produced within the crown as the tree grows (Lehnebach *et al.*, 2017). For the same species, it has also
672

been shown that tree architecture, which is the expression of tree growth dynamics, is associated
with changes in the extractives content and natural durability (Amusant *et al.*, 2013).

673

674

675

This research lay the groundwork for exploring the link between heartwood formation and
the fungal decay resistance of *S. rubra* wood. (Fig. 6). Notably, these results indicated the
presence of two classes of bioactive metabolites, *i.e.*, butyrolactones and alkaloids, which
confer decay resistance and GST reactivity, and which are specifically present in heartwood
and pith samples. A strong negative correlation (-0.82) was highlighted between the
butyrolactones/alkaloids ratio and the mass loss, and pronounced correlations between the
isolated butyrolactones **B1** and **B2** and the mass loss (0.59 and 0.58, respectively). However, in
regard to the results obtained for GST reactivity, the significant positive correlation between
the butyrolactones/alkaloids and overall GST reactivity (+0.74, *p*-value > 1 × 10⁻³) raises some
questions, as GST reactivity is mostly driven by alkaloids rather than butyrolactones when pure
compounds are evaluated. This could be due to the fact that the ratio is calculated based on the
quantification of only 4 pure compounds, whereas GST reactivity was measured on crude
extracts. Moreover, only six isoforms were tested in this study, and expanding this selection
could provide valuable insights. Furthermore, potential synergies leading to antifungal activity
of wood extracts have been discussed previously, and were not investigated in our study (Royer
*et al.*, 2012). As both qualitative and quantitative parameters intervene in the wood chemical
defence system, three defence models have been proposed by Amusant *et al*. (Amusant *et al.*,
2014). The first, illustrated in *Bocoa prouacensis* Aubl., consists in the biosynthesis of low
amounts of extractives, in terms of extraction yield, with high antifungal activity. The second,
described in *Vouacapoua americana* Aubl., consists in biosynthesising a large amount of
extractives, with potential synergistic antifungal activity. The third, in which molecular
diversity is responsible for the antifungal activity, has been proposed for *Inga alba* (Sw) Wild.

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685

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689

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692

693

694

695

696
Our results suggest that *S. rubra* adopts a distinct, intermediate defence strategy compared to *B. prouacensis* and *V. americana*. Its sapwood is ten times less durable than its heartwood, despite the latter containing only half the extractive content (7% vs. 14%, extracted with AcOEt). However, it defends itself by producing two butyrolactones (**B1** and **B2**) and minor alkaloids, present at concentrations 60 times lower than the butyrolactones.

Eventually, considering heartwood formation process *S. rubra*, the qualitative analysis of pure alkaloids and butyrolactones showed that the biosynthesis of extractives is stable throughout the life of the tree, nor is there any subsequent degradation of the molecules in relation with wood aging or microbial inactivation (Jin *et al.*, 1988; Kampe and Magel, 2013). The presence of butanolides in sapwood, on the one hand, and biosynthetically related butyrolactones in heartwood, on the other hand, allowed to propose a *Juglans*-type heartwood formation for this species as far as lactone derivatives are concerned, with the production of heartwood extractives in the transition zone from precursors accumulated early in the sapwood (Kampe and Magel, 2013; Celedon andBohlmann, 2018). The lack of signals indicating the presence of alkaloids, and their theoretical precursors, in the sapwood and bark suggests that the biosynthesis occurs either in the transition zone or directly in the metabolically active heartwood cells. In this particular scenario, the heartwood formation process closely resembles a type-III (*Santalum*) process (Celedon and Bohlmann, 2018). ToF-SIMS analyses, which allow high spatial resolution MS imaging, should be carried out in the future to validate or challenge this hypothesis and delve deeper into the heartwood formation process of *S. rubra*.

## CONCLUSION

This study enhanced the comprehension of how chemical defences are implemented in the stem of *S. rubra* throughout the heartwood formation process, leading to the resistance of its
722 wood to fungal degradation. The heartwood and pith of *S. rubra* exhibited a stable pattern
723 throughout the stem in terms of resistance to fungal decay, with no influence of cambial age
724 nor trunk height on this technological property. It can be related to the presence of two classes
725 of antifungal compounds in heartwood and pith tissues, namely butyrolactone and alkaloids.
726 GST reactivity tests, however, highlighted that these two types of metabolites exert their
727 influence towards fungal microorganisms based on different mechanisms. The high resistance
728 regardless of spatial sample position in the stem aligned with the continuous and stable
729 biosynthesis of butyrolactones and alkaloids over the tree life, despite slight quantitative
730 variations. Overall, these results allowed to propose two models for chemical defence and
731 heartwood formation. On the one hand, chemical defence against fungal degradation seemed to
732 rely on both abundant butyrolactones and minor but numerous alkaloids, raising questions about
733 potential synergism. On the other hand, these results suggest that the biosynthesis and
734 accumulation of specialised metabolites during the heartwood formation process depend on the
735 molecular families considered, following *Juglans*-type or *Santalum*-type models. In this
736 perspective, complementary analyses of the molecular mechanisms at stake could provide
737 valuable insight into the heartwood formation of this tropical species, to understand the
738 functioning of the tree and promote valorisation perspectives of its wood. From a broader
739 perspective, the use of innovative and integrative tools to tackle both the mechanisms and the
740 effects of heartwood formation process in *S. rubra* allowed to underscore the complexity of this
741 mechanism, notably in relation to the biosynthesis, accumulation, and biological properties of
742 specialized metabolites, thus paving the way for novel strategies to enhance understanding of
743 heartwood formation process, particularly in under-investigated and valuable tropical species.

744

745

ACKNOWLEDGMENTS

746

We thank the CIRAD & UMR EcoFoG team, Michel Baisie, Jocelyn Cazal, Saint-Omer
Cazal, Soepe Koese, Jean-Martin Odan, and Valérie Troispoux for the climbing, pruning,

747
748

felling and sampling of the studied tree and for logistical help. We also thank Emmanuelle

749

Clervil for her help on the field, Julie Bossu for wood sampling scheme [Supplementary Data

750

Fig. S1] and Jacques Beauchêne for allowing the access to the collection site as CIRAD regional

751

representative.

752

753

## AUTHOR'S CONTRIBUTION

754

**Marceau Levasseur:** conceptualization, methodology, formal analysis, investigation, data

755

curation, writing (original draft, review and editing); **Ambre Senelis:** investigation; **Flavien**

756

**Zannini:** investigation; **Muriel Barbier:** methodology, investigation; **Elsa Van Elslande:**

757

investigation; **Nadine Amusant:** resources, investigation; **Yannick Estevez:** resources;

758

**Véronique Eparvier:** conceptualization, methodology, supervision; **Éric Gelhaye:**

759

conceptualization, methodology, resources; **David Touboul:** conceptualization, methodology,

760

supervision, project administration, funding acquisition; **Emeline Houël:** conceptualization,

761

methodology, supervision, resources, investigation, writing (original draft, review and editing).

762

**All authors** contributed to and approved the final manuscript.

763

764

## SUPPORTING INFORMATION

765

The following additional information is available in the online version of this article: Full

766

experimental details, Supporting Information Figures S1-S55, Supporting Information Tables

767

S1-S19.

768

769

## FUNDING INFORMATION

770

This work was supported by the French National Centre for Scientific Research (CNRS) as

771

part of the 80|Prime program. We thank the LABEX CEBA [CEBA ANR-10-LABEX-0025]
772

for supports for the field missions in French Guiana. D.T. acknowledges financial supports of

773

DIM MAP (Région Ile-de-France); ANR Vapobio [ANR-20-CE29-0016].

774

775

## DECLARATION OF COMPETING INTEREST

776

The authors declare no conflict of interest.

777

778

## DECLARATION OF GENERATIVE AI AND AI-ASSISTED TECHNOLOGIES IN THE WRITING PROCESS

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780

During the preparation of this work the authors used DeepL Write (https://www.deepl.com/write) to improve readability and language. After using this tool/service, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.

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## DATA AVAILABILITY

786

The data underlying the findings of this study are available in the article and in its online supplementary material, including full experimental details and the associated literature cited.

Raw data will be made available on request.

787

788

789

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## REFERENCES

791

Adutwum JO, Sakagami H, Koga S, Matsumura J. 2023. Space-time analysis of the longitudinal variation in wood specific gravity of Teak and its effect on tree growth and development. Bioresources 18:2670-2692.

792

793

794

Agnès SA, Okpekon T, Kouadio YA, Jagora A, Bréard D, Costa EV, da Silva FMA, Koolen HHF, Le Ray-Richomme AM, Richomme P, et al. 2022. Implementation of a MS/MS

795
796 database for isoquinoline alkaloids and other annonaceous metabolites. Sci. Data 9:270.

797 https://doi.org/10.1038/s41597-022-01345-y

798 Allard PM., Péresse T, Bisson J, Gindro K, Marcourt L, Pham VC, Roussi F, Litaudon M,

799 Wolfender JL. 2016. Integration of molecular networking and *in-silico* MS/MS

800 fragmentation for natural products dereplication. Anal. Chem. 88:3317-3323.

801 https://doi.org/10.1021/acs.analchem.5b04804

802 Amusant N, Beauchêne J, Fournier M, Janin G, Thevenon MF. 2004. Decay resistance in

803 *Dicorynia guianensis* Amsh.: analysis of inter-tree and intra-tree variability and

804 relations with wood colour. Ann. For Sci. 61:373-380.

805 https://doi.org/10.1051/forest:2004030

806 Amusant N, Fournier M, Beauchêne J. 2008. Colour and decay resistance and its relationships

807 in *Eperua grandiflora*. Ann. For Sci. 65:806-806.

808 https://doi.org/10.1051/forest:2008061

809 Amusant N, Moretti C, Richard B, Prost E, Nuzillard JM, Thévenon MF. 2007. Chemical

810 compounds from *Eperua falcata* and *Eperua grandiflora* heartwood and their biological

811 activities against wood destroying fungus (*Coriolus versicolor*). Holz. Roh. Werkst

812 65:23-28. https://doi.org/10.1007/s00107-006-0120-1

813 Amusant N, Nigg M, Thibaut B, Beauchêne J. 2014. Diversity of decay resistance strategies of

814 durable tropical woods species: *Bocoa prouacencsis* Aublet, *Vouacapoua americana*

815 Aublet, *Inga alba* (Sw.) Wild. Int. Biodeterior. Biodegradation 94:103-108.

816 https://doi.org/10.1016/j.ibiod.2014.06.012

817 Amusant N, Anouhé JBS, Augustin A, Beauchêne J, Nicolini E. 2000. Tree crown architecture:

818 a tool for decay resistance evaluation. Proceedings IRG Annual Meeting, IRG/WP 13-

819 10793.
820 Anouhe JBS, Niamké FB, Faustin M, Virieux D, Pirat JL, Adima AA, Kati-Coulibaly Z,
821 Amusant N. 2018. The role of extractives in the natural durability of the heartwood of
822 *Dicorynia guianensis* Amsh: new insights in antioxydant and antifungal properties.
823 Ann. For Sci. 75:15. https://doi.org/10.1007/s13595-018-0691-0

824 Barbier M, Perrot T, Salzet G, Amusant N, Dumarçay S, Gérardin P, Morel-Rouhieer M,
825 Sormani R, Gelhaye E. 2020. Glutathione Transferases: Surrogate targets for
826 discovering biologically active compounds. J. Nat. Prod. 83:2960-2966.
827 https://doi.org/10.1021/acs.jnatprod.0c00480

828 Basset C, Eparvier V, Espindola LS. 2015. The search for antifungals from Amazonian trees:
829 A bio-inspired screening. Nat. Prod. Commun. 10:605-608.
830 https://doi.org/10.1177/1934578X1501000417

831 Bossu J, Beauchêne J, Estevez Y, Duplais C, Clair B. 2016. New insights on wood dimensional
832 stability influenced by secondary metabolites: The case of a fast-growing tropical
833 species *Bagassa guianensis* Aubl. PLoS ONE 11:e0150777.
834 https://doi.org/10.1371/journal.pone.0150777

835 Brennan M, Fritsch C, Cosgun S, Dumarcay S, Colin F, Gérardin P. 2020a. Quantitative and
836 qualitative composition of bark polyphenols changes longitudinally with bark maturity
837 in *Abies alba* Mill. Ann. For Sci. 77:9. https://doi.org/10.1007/s13595-019-0916-x

838 Brennan M, Fritsch C, Cosgun S, Dumarcay S, Colin F, Gérardin P. 2020b. Yield and
839 compositions of bark phenolic extractives from three commercially significant
840 softwoods show intra- and inter-specific variation. Plant Physio. Biochem. 155:346-
841 356. https://doi.org/10.1016/j.plaphy.2020.07.033

842 Čabalová I, Bélik M, Kučerová V, Jurczyková T, 2021. Chemical and morphological
843 composition of Norway Spruce wood (*Picea abies*, L.) in the dependence of its storage.
844 Polymers 13:1619. https://doi.org/10.3390/polym13101619
845 Cao S, Zhang Z, Sun Y, Li Y, Zheng H, 2020. Profiling of widely targeted metabolomics for
846 the identification of secondary metabolites in heartwood and sapwood of the red-heart
847 Chinese Fir (Cunninghamia lanceolata). Forests 11:897.
848 https://doi.org/10.3390/f11080897

849 Carneiro JS, Emmert L, Sternadt GH, Mendes JC, Almeida GF. 2009. Decay susceptibility of
850 Amazon wood species from Brazil against white rot and brown rot decay fungi 10th
851 EWLP, Stockholm, Sweden, August 25–28, 2008. Holzforschung 63:767-772.
852 https://doi.org/10.1515/HF.2009.119

853 Celedon JM,Bohlmann J. 2018. An extended model of heartwood secondary metabolism
854 informed by functional genomics. Tree Physiol. 38:311-319.
855 https://doi.org/10.1093/treephys/tpx070

856 CTFT, Centre Technique Forestier Tropical (Tropical Forestry Technical Center), 1984. Fiches
techniques sur les bois guyanais: Grignon franc. Bois For. Trop. 204: 53-56.

858 Clervil E, Bossu J, Duchemin JB, Passelande J, Brunaux O, Dusfour I, Amusant N, Houël E.
859 2023. *Sextonia rubra* (Mez.) van der Werff sawmills residues as a valuable resource for
860 the production of larvicidal extracts against *Ae. aegypti* Linnaeus (Diptera: Culicidae).
861 Ind. Crop Prod. 193: 116162. https://doi.org/10.1016/j.indcrop.2022.116162

862 Conceição RS, Perez CJ, Branco A, Botura MB, Ifa DR. 2021. Identification of *Sassafras
863 albidum* alkaloids by high-performance thin-layer chromatography tandem mass
864 spectrometry and mapping by desorption electrospray ionization mass spectrometry
865 imaging. J. Mass Spectrom. 56:e4674. https://doi.org/10.1002/jms.4674

866 Conceição RS, Reis IMA, Cerqueira APM, Perez CJ, dos Santos Junior MC, Branco A, Ifa DR,
867 Botura MB. 2020. Rapid structural characterisation of benzylisoquinoline and
868 aporphine alkaloids from *Ocotea spixiana* acaricide extract by HPTLC-DESI-MS".
869 Phytochem. Analysis 31:711-721. https://doi.org/10.1002/pca.2935
870 Coy Barrera ED, Cuca Suárez LE. 2009. Aporphine alkaloids from leaves of *Ocotea macrophylla* (Kunth) (Lauraceae) from Colombia. Biochem. Syst. Ecol. 37:522-524.
871 https://doi.org/10.1016/j.bse.2009.05.002
872

873 Creydt M, Lautner S, Fromm J, Fischer M. 2022. Wood profiling by non-targeted liquid chromatography high-resolution mass spectrometry: Part 2, Detection of the geographical origin of spruce wood (*Picea abies*) by determination of metabolite pattern. J. Chromatogr. A 1663:462737. https://doi.org/10.1016/j.chroma.2021.462737

877 Creydt M, Ludwig L, Köhl M, Fromm J, Fischer M. 2021. Wood profiling by non-targeted high-resolution mass spectrometry: Part 1, Metabolite profiling in *Cedrela* wood for the determination of the geographical origin. J. Chromatogr. A 1641:461993.
878
879
880 https://doi.org/10.1016/j.chroma.2021.461993

881 Crotti AEM, Bronze-Uhle ES, Nascimento PGBD, Donate PM, Galembeck, SE, Vessecchi R, Lopes NP. 2009. Gas-phase fragmentation of γ-lactone derivatives by electrospray ionization tandem mass spectrometry. J. Mass Spectrom. 44:1733-1741.
882
883
884 https://doi.org/10.1002/jms.1682

885 Crotti AEM, Fonseca T, Hong H, Staunton J, Galembeck SE, Lopes NP, Gates PJ. 2004. The fragmentation mechanism of five-membered lactones by electrospray ionisation tandem mass spectrometry. Int. J. Mass Spectrom. 232:271-276.
886
887
888 https://doi.org/10.1016/j.ijms.2004.02.009

889 Custódio DL, da Veiga Junior VF. 2014. Lauraceae alkaloids. RSC Advances 4:21864-21890.
890 https://doi.org/10.1039/C4RA01904K

891 Darmawan W, Nandika D, Sari RK, Sitompul A, Rahayu I, Gardner D. 2015. Juvenile and mature wood characteristics of short and long rotation teak in Java. IAWA J. 36:428-442. https://doi.org/10.1163/22941932-20150112
894 De Ligne L, Van den Bulcke J, Baetens JM, De Baets B, Wang G, De Windt I, Beeckman H, 895 Van Acker J. 2021. Unraveling the natural durability of wood: revealing the impact of 896 decay-influencing characteristics other than fungicidal components. Holzforschung 897 75:368–378. https://doi.org/10.1515/hf-2020-0109

898 Deroy A, Saiag F, Kebbi-Benkeder Z, Touahri N, Hecker A, Morel-Rouhier M, Colin F, 899 Dumarçay S, Gérardin P, Gelhaye E. 2015. The GSTome reflects the chemical 900 environment of white-rot fungi. PLoS ONE 10:e0137083. 901 https://doi.org/10.1371/journal.pone.0137083

902 Dolomanov OV, Bourhis LJ, Gildea RJ, Howard JAK, Puschmann H. 2009. OLEX2: a 903 complete structure solution, refinement and analysis program. J. Appl. Cryst. 42:339– 904 341. https://doi.org/10.1107/S0021889808042726

905 Erb M, Kliebenstein DJ. 2020. Plant secondary metabolites as defences, regulators, and primary 906 metabolites: the blurred functional trichotomy. Plant Physiol. 184:39–52. 907 https://doi.org/10.1104/pp.20.00433

908 Firmino AV, Vidaurre GB, Oliveira JTDS, Guedes M, de Almeida MNF, da Silva JGM, 909 Latorraca JCF, Zanuncio JC. 2019. Wood properties of *Carapa guianensis* from 910 floodplain and upland forests in Eastern Amazonia, Brazil. Sci. Rep. 9:10641. 911 https://doi.org/10.1038/s41598-019-46943-w

912 Flack HD. 1983. On enantiomorph-polarity estimation. Acta Cryst. A. 39:876–881. 913 https://doi.org/10.1107/S0108767383001762

914 Freitag CM, Morrell JJ. 2001. Durability of a changing Western Redcedar resource. Wood Fiber 915 Sci. 33:69–75.

916 Fritsch C, Dumarçay S, Colin F, Gérardin P. 2022. Bark composition changes along the trunk 917 of three softwood species: *Picea abies*, *Abies alba* Mill. and *Pseudotsuga menziesii*. 918 *Scand. J. Forest Res.* 37:314–319. https://doi.org/10.1080/02827581.2022.2132283
919 Fu T, Houël E, Amusant N, Touboul D, Genta-Jouve G, Della-Negra S, Fischer GL, Brunelle
920 A, Duplais C. 2019. Biosynthetic investigation of γ-lactones in *Sextonia rubra* wood
921 using in situ TOF-SIMS MS/MS imaging to localize and characterise biosynthetic
922 intermediates. Sci. Rep. 9:1928. https://doi.org/10.1038/s41598-018-37577-5

923 Fu T, Touboul D, Della-Negra S, Houël E, Amusant N, Duplais C, Fischer GL, Brunelle A.
924 2018. Tandem mass spectrometry imaging and in situ characterisation of bioactive
925 wood metabolites in Amazonian tree species *Sextonia rubra*. Anal. Chem. 90:7535-
926 7543. https://doi.org/10.1021/acs.analchem.8b01157

927 Gale PJ, Duncan MW. 2020. Tools for quantitative analysis: The Al Yergey perspective. J.
928 Mass Spectrom. 55:e4524. https://doi.org/10.1002/jms.4524

929 Garcez F, Francisca da Silva A, Garcez W, Linck G, Matos MCF, Santos ECS, Queiroz LMM.
930 2011. Cytotoxic aporphine alkaloids from *Ocotea acutifolia*. Planta Med. 77:383-387.
931 https://doi.org/10.1055/s-0030-1250401

932 Gartner BL, Morrell JJ, Freitag CM, Spicer R. 1999. Heartwood decay resistance by vertical
933 and radial position in Douglas-fir trees from a young stand. Can. J. For Res. 29:1993-
934 1996.

935 Gérard J, Paradis S, Thibaut B. 2019. Survey on the chemical composition of several tropical
936 wood species. Bois et Forêts des Tropiques 342:79-91.
937 https://doi.org/10.19182/BFT2019.342.A31809

938 Gierlinger N, Wimmer R. 2004. Radial distribution of heartwood extractives and lignin in
939 mature European larch. Wood Fiber Sci. 36:387-394.

940 Godzien J, Gil De La Fuente A, Otero A, Barbas C. 2018. Metabolite annotation and
941 identification. In: Jaumot J, Bedia C, Tauler R, editors. Compr. Anal. Chem., Elsevier
942 82:415-445. https://doi.org/10.1016/bs.coac.2018.07.004
943 Gominho J, Figueira J, Rodrigues JC, Pereira H. 2001. Within-tree variation of heartwood, extractives and wood density in the eucalypt hybrid urograndis (Eucalyptus grandis x Europhylla). Wood Fiber Sci. 33: 3-8.

946 Gouveia FN, da Silveira MF, Garlet A. 2021. Natural durability and improved resistance of 20 Amazonian wood species after 30 years in ground contact. Holzforschung 75:892-899.
948 https://doi.org/10.1515/hf-2020-0192

949 Gullner G, Komives T, Király L, Schröder P. 2018. Glutathione S-Transferase enzymes in plant-pathogen interactions. Front. Plant Sci. 9:1836.
951 https://doi.org/10.3389/fpls.2018.01836

952 Guo M, Song W, Buhain J. 2015. Bioenergy and biofuels: History, status, and perspective. Renew. Sust. Energ. Rev. 42:712-725. https://doi.org/10.1016/j.rser.2014.10.013

954 Hassegawa M, Stevanovic T, Achim A. 2016. Relationship between ethanolic extracts of yellow birch and tree characteristics. Ind. Crops. Prod. 94:1-8.
956 https://doi.org/10.1016/j.indcrop.2016.08.038

957 Hooft RWW, Straver LH, Spek AL. 2008. Determination of absolute structure using Bayesian statistics on Bijvoet differences. J. Appl. Cryst. 41:96-103.
959 https://doi.org/10.1107/S0021889807059870

960 Houël E, Rodrigues AMS, Nicolini EA., Ngwete O, Duplais C, Stien D, Amusant N. 2017. Natural durability of *Sextonia rubra*, an Amazonian tree species: description and origin.
962 Proceedings IRG Annual Meeting, IRG/WP 17-10887.

963 Jacobs K, Plashkies K, Scheiding W, Weiß B, Melcher E, Conti E, Fojutowski A, Le Bayon I. 2019. Natural durability of important European wood species against wood decay fungi.
964 Part 2: Filed tests and fungal community. Int. Biodeterior. Biodegradation 137:118-126.
966 https://doi.org/10.1016/j.ibiod.2018.12.002
967 Jin L, Kamp BJVD, Wilson J, Swan EP. 1988. Biodegradation of thujaplicins in living western
968 red cedar. Can. J. For Res. 18:784–788. https://doi.org/10.1139/x88-119

969 Kampe A, Magel E. 2013. New insights into heartwood and heartwood formation. In: Fromm
970 J, editor. Cellular Aspects of Wood Formation, Plant Cell Monographs. Springer Berlin
971 Heidelberg, p. 71–95. https://doi.org/10.1007/978-3-642-36491-4_3

972 Kirker GT, Blodgett AB, Arango RA, Lebow PK, Clausen CA. 2013. The role of extractives in
973 naturally durable wood species. Int. Biodeterior. Biodegradation 82:53-58.
974 http://dx.doi.org/10.1016/j.ibiod.2013.03.007

975 Kessner D, Chambers M, Burke R, Agus D, Mallick P. 2008. ProteoWizard: open source
976 software for rapid proteomics tools development. Bioinformatics 24:2534–2536.
977 https://doi.org/10.1093/bioinformatics/btn323

978 Latorraca JVF, Dünisch O, Koch G. 2011. Chemical composition and natural durability of
979 juvenile and mature heartwood of Robinia pseudoacacia L. An. Acad. Bras. Ciênc.
980 83:1059–1068. https://doi.org/10.1590/S0001-37652011005000016

981 Lehnebach R, Bossu J, Va S., Amusant N, Nicolini E, Beauchêne J. 2019. Wood density
982 variations of legume trees in French Guiana along the shade tolerance continuum:
983 Heartwood effects on radial patterns and gradients. Forests 10:80.
984 https://doi.org/10.3390/f10020080

985 Lehnebach R, Morel H, Bossu J, Le Moguédec G, Amusant N, Beauchêne J, Nicolini E. 2017.
986 Heartwood/sapwood profile and the tradeoff between trunk and crown increment in a
987 natural forest: the case study of a tropical tree (Dicorynia guianensis Amsh., Fabaceae).
988 Trees 31: 199–214. https://doi.org/10.1007/s00468-016-1473-7

989 L'herbier IRD de Guyane. UMR AMAP. CIRAD, CNRS, INRAE, IRD, Univ. Montpellier
990 (France) [accessed 12/01/2021]. https://herbier-guyane.ird.fr/
991 Li M, Liu M, Wang B, Shi L. 2022. Metabonomics Analysis of stem extracts from *Dalbergia sissoo*. *Molecules* 27:1982. https://doi.org/10.3390/molecules27061982

993 Loehle C. 1988. Tree life history strategies: the role of defences. Can. J. For. Res. 18:209-222.
https://doi.org/10.1139/x88-032

995 Macrae CF, Edgington PR, McCabe P, Pidcock E, Shields GP, Taylor R, Towler M, van de  
996 Streek J. 2006. Mercury: visualization and analysis of crystal structures. J. Appl. Cryst.  
997 39:453-457. https://doi.org/10.1107/S002188980600731X

998 Martins GS, Yuliarto M, Antes R, Sabki, Prasetyo, A, Unda F, Mnasfield SD, Hodge GR,
999 Acosta JJ. 2020. Wood and pulping properties variation of *Acacia crassicarpa* A. Cunn.
1000 ex Benth. and sampling strategies for accurate phenotyping. *Forests* 11: 1043.
1001 https://doi.org/10.3390/f11101043

1002 Morais MC, Pereira H. 2012. Variation of extractives content in heartwood and sapwood of
1003 *Eucalyptus globulus* trees. Wood Sci. Technol. 46:709-719.
1004 https://doi.org/10.1007/s00226-011-0438-7

1005 Morris H, Brodersen C, Schwarze FWMR, Jansen S. 2016. The parenchyma of secondary
1006 xylem and its critical role in tree defence against fungal decay in relation to the CODIT
1007 model. Front. Plant Sci. 7:1665. https://doi.org/10.3389/fpls.2016.01665.

1008 Morris H, Hietala AM, Jansen S, Ribera J, Rosner S, Salmeia KA, Schwarze FWMR. 2020.
1009 Using the CODIT model to explain secondary metabolites of xylem in defence systems
1010 of temperate trees against decay fungi. *Annals of Botany* 125: 701-720.
1011 https://doi.org/10.1093/aob/mcz138.

1012 Moya R, Araya L, Vilchez B. 2008. Variation in the pith parameter of *Gmelina arborea* trees
1013 from fast growth plantations in Costa Rica. Ann. For Sci. 65:612-612.
1014 https://doi.org/10.1051/forest:2008045
1015 Moya R, Bond B, Quesada H. 2014. A review of heartwood properties of *Tectona grandis* trees
1016 from fast-growth plantations. Wood Sci. Technol. 48:411-433.
1017 https://doi.org/10.1007/s00226-014-0618-3

1018 Olivon F, Elie N, Grelier G, Roussi F, Litaudon M Touboul, D. 2018. MetGem software for the
generation of molecular networks based on the t-SNE algorithm. Anal. Chem.
1019
1020 90:13900-13908. https://doi.org/10.1021/acs.analchem.8b03099

1021 Palanti S, Alves A, Rodrigues J, Danti R. 2021. Determination of extractive content in
1022 Cupressus sempervirens wood through a NIRS-PLSR model and its correlation with
durability. Int. Biodeterior. Biodegradation 162:105247.
1023
1024 https://doi.org/10.1016/j.ibiod.2021.105247

1025 Pang Z, Chong J, Zhou G, Morais DAL, Chang L, Barrette M, Gauthier C, Jacques PE, Li
1026 Shuzao, Xia J. 2021. MetaboAnalyst 5.0: narrowing the gap between raw spectra and
functional insights. Nucleic Acids Res. 49: W388-W396.
1027
1028 https://doi.org/10.1093/nar/gkab382

1029 Patyra A, Dudek MK, Kiss AK. 2022. LC-DAD-ESI-MS/MS and NMR analysis of conifer
wood specialised metabolites. Cells 11:3332. https://doi.org/10.3390/cells11203332

1031 Perrot T, Salzet G, Amusant N, Beauchêne J, Gérardin P, Dumarçay S, Sormani R, Morel-
Rouhier M, Gelhaye E. 2020. A reverse chemical ecology approach to explore wood
natural durability. Microb. Biotechnol. 13:1673-1677. https://doi.org/10.1111/1751-
7915.13540

1035 Perrot T, Schwartz M, Saiag F, Salzet G, Dumarçay S, Favier F, Gérardin P, Girardet JM,
1036 Sormani R, Morel-Rouhier M, et al. 2018. Fungal glutathione transferases as tools to
explore the chemical diversity of Amazonian wood extractives. ACS Sustainable Chem.
1037
1038 Eng. 6:13078-13085. https://doi.org/10.1021/acssuschemeng.8b02636
1039 Petit RJ, Hampe A 2006. Some evolutionary consequences of being a tree. Annu. Rev. Ecol.

1040 Evol. Syst. 37:187-214. https://doi.org/10.1146/annurev.ecolsys.37.091305.110215

1041 Plomion C, Leprovost G, Stokes A. 2001. Wood formation in trees. Plant Physiol. 127:1513-
1042 1523. https://doi.org/10.1104/pp.010816

1043 Pluskal T, Castillo S, Villar-Briones A, Orešič M. 2010. MZmine 2: Modular framework for
1044 processing, visualizing, and analyzing mass spectrometry-based molecular profile data.

1045 BMC Bioinformatics 11:395. https://doi.org/10.1186/1471-2105-11-395

1046 Rodrigues AMS, Amusant N, Beauchêne J, Eparvier E, Leménager N, Baudassé C, Espindola

LS, Stien D. 2011. The termiticidal activity of *Sextonia rubra* (Mez) van der Werff

(Lauraceae) extract and its active constituent rubrynolide. Pest Manag. Sci. 67:1420-
1423. https://doi.org/10.1002/ps.2167

1050 Rodrigues AMS, Stien D, Eparvier V, Espindola LS, Beauchêne J, Amusant N, Leménager N,

1051 Baudassé C, Raguin L. 2012. The wood preservative potential of long-lasting
1052 Amazonian wood extracts. Int. Biodeterior. Biodegradation 75:146-149.

1053 https://doi.org/10.1016/j.ibiod.2012.03.014

1054 Rodrigues AMS, Theodoro PNET, Eparvier V, Basset C, Silva MRR, Beauchêne J, Espindola

LS, Stien D. 2010. Search for antifungal compounds from the wood of durable tropical
trees. J. Nat. Prod. 73:1706-1707. https://doi.org/10.1021/np1001412

1057 Royer M, Rodrigues AMS, Herbette G, Beauchêne J, Chevalier M, Hérault B, Thibaut B, Stien

D. 2012. Efficacy of *Bagassa guianensis* Aubl. extract against wood decay and human
pathogenic fungi. Int. Biodeterior. Biodegradation 70: 55-59.

1060 https://doi.org/10.1016/j.ibiod.2011.10.016

1061 Schmidt J, Raith K, Boettcher C, Zenk MH. 2005. Analysis of benzylisoquinoline-type

alkaloids by electrospray tandem mass spectrometry and atmospheric pressure
photoionization. Eur. J. Mass Spectrom. 11:325-333. https://doi.org/10.1255/ejms.745
Scotti I, Calvo-Vialettes L, Scotti-Saintagne C, Citterio M, Degen B, Bonal D, 2010. Genetic variation for growth, morphological, and physiological traits in a wild population of the Neotropical shade-tolerant rainforest tree *Sextonia rubra* (Mez) van der Werff (Lauraceae). Tree Genet. Genomes 6:319–329. https://doi.org/10.1007/s11295-009-0251-8

Sheldrick GM 2015a. SHELXT – Integrated space-group and crystal-structure determination. Acta Cryst. A 71:3–8. https://doi.org/10.1107/S2053273314026370

Sheldrick GM. 2015b. Crystal structure refinement with SHELXL. Acta Cryst. C 71:3–8. https://doi.org/10.1107/S2053229614024218

Silva Teles MMR, Vieira Pinheiro AA, Da Silva Dias C, Tavares JF, Filho JMB, Da Cunha EML. 2019. Alkaloids of the Lauraceae. In: Hans-Joachim Knölker, editor. The Alkaloids: Chemistry and Biology. Elsevier, p. 147–304. https://doi.org/10.1016/bs.alkal.2018.11.002

Siqueira CS, Dos Santos VS, Carollo CA, Damasceno-Junior GA. 2023. Unraveling the adaptive chemical traits of *Rhamnidium elaeocarpum* Reissek in response to fire in pantanal wetlands. Sci. Rep. 13:11860. https://doi.org/10.1038/s41598-023-38725-2

ter Steege H, Pitman NCA, Phillips OL, Chave J, Sabatier D, Duque A, Molino JF, Prévost MF, Spichiger R, Castellanos H, et al. 2006. Continental-scale patterns of canopy tree composition and function across Amazonia. Nature 443:444–447. https://doi.org/10.1038/nature05134

Tian XC, Guo JF, Yan XM, Shi TL, Nie S, Zhao SW, Bao YT, Li ZC, Kong L, Su GJ, et al. 2023. Unique gene duplications and conserved microsynteny potentially associated with resistance to wood decay in the Lauraceae. Front. Plant Sci. 14:1122549. https://doi.org/10.3389/fpls.2023.1122549
1088 Toledo-González KA, Riley-Saldaña CA, Salas-Lizana R, De-la-Cruz-Chacón I, González-Esquinca AR. 2023. Alkaloidal variation in seedlings of *Annona purpurea* Moc. & Sessé ex Dunal infected with *Colletotrichum gloeosporioides* (Penz.) Penz. and Sacc.
1089
1090
1091 Biochem. Syst. Ecol. 107:104611. https://doi.org/10.1016/j.bse.2023.104611

1092 Valette N, Perrot T, Sormani R, Gelhaye E, Morel-Rouhier M. 2017. Antifungal activities of wood extractives. Fungal Biol. Rev. 31:113-123.
1093
1094 https://doi.org/10.1016/j.fbr.2017.01.002

1095 van der Werff H. 1997. *Sextonia*, a new genus of Lauraceae from South America. Novon 7:436.
1096
1097

Verkasalo E, Möttönen V, Roitto M, Vepsäläinen J, Kumar A, Ilvesniemi H, Siwale W, Julkunen-Tiitto R, Raatikainen O, Sikanen L. 2021. Extractives of stemwood and sawmill residues of scots pine (*Pinus sylvestris* L.) for biorefining in four climatic regions in Finland—phenolic and resin acid compounds. Forests 12:192.
1098
1099
1100
1101 https://doi.org/10.3390/f12020192

1102 Wijayanto A, Dumarçay S, Gérardin-Charbonnier C, Sari RK, Syafii W, Gérardin P. 2015. Phenolic and lipophilic extractives in *Pinus merkusii* Jungh. et de Vries knots and stemwood. Ind. Crop Prod. 69:466-471. https://doi.org/10.1016/j.indcrop.2015.02.061

1103
1104
1105 Wolfender JL, Litaudon M, Touboul D, Queiroz EF. 2019. Innovative omics-based approaches for prioritisation and targeted isolation of natural products – new strategies for drug discovery. Nat. Prod. Rep. 36:855-868. https://doi.org/10.1039/C9NP00004F

1106
1107
1108 Yang G, Liang K, Zhou Z, Wang X, Huang G. 2020. UPLC-ESI-MS/MS-Based widely targeted metabolomics analysis of wood metabolites in teak (*Tectona grandis*). Molecules
1109
1110 25:2189. https://doi.org/10.3390/molecules25092189
1111 Yang H, An W, Gu Y, et al. 2022a. Integrative metabolomic and transcriptomic analysis reveals the mechanism of specific color formation in *Phoebe zhennan* heartwood. *IJMS* 23: 13569. https://doi.org/10.3390/ijms232113569

1114 Yang H, An W, Gu Y, Peng J, Jiang Y, Li J, Chen L, Zhu P, He F, Zhang F, et al. 2022b. Integrated transcriptomic, metabolomic, and physiological analyses reveal new insights into fragrance formation in the heartwood of *Phoebe hui*. *IJMS* 23:14044. https://doi.org/10.3390/ijms232214044

1118

1119

1120 **FIGURES LEGENDS**

<figure><img src="image_3.png" /></figure>

1121

1122 **FIG. 1.** Measurement of wood degradation of *S. rubra* tissues: distributions of mass losses of
1123 *S. rubra* sapwood (SW), heartwood (HW) and pith samples, and control (*V. surinamensis* HW)
1124 after exposure to forest soil over a 10-month period for all trunk heights sampled (total of 7 SW
1125 samples, 42 HW samples, from outer to inner HW, and 7 pith samples). Letters "a" and "b"
1126 denote significative differences of distributions between different tissues (Kruskal-Wallis:

1127 $p$-value < 1 × 10⁻²). M.L.: mass loss (%).

1128

<figure><img src="image_4.png" /></figure>

1129

1130 **FIG. 2.** Fragmentation pathway of protonated reticuline (A10), a benzylisoquinoline alkaloid.
<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /><figcaption>FIG. 3. Structures of annotated and identified (*) molecules.</figcaption></figure>
<figure><img src="image_8.png" /></figure>

1133

1134

FIG. 4. PLS-DA of ethyl acetate (EtOAc) crude extracts from samples analysed by RPLC-ESI(+)-HRMS.

1135

1136

<figure><img src="image_9.png" /></figure>

1137

1138

FIG. 5. Boxplots of the amounts of (A) alkaloids (A3 and A10) and (B) butyrolactones (B1 and B2) as a function of the heights analysed. Boxplots of (C) the amounts of alkaloids (A3 and

1139
1140 **A10**) and (D) butyrolactones (**B1** and **B2**) as a function of the depths analyzed. The color codes correspond to the quantified compounds. T0 corresponds to DBH. HW corresponds to heartwood samples and P corresponds to pith samples. HW1 corresponds to the outermost HW sample.

1144

<figure><img src="image_10.png" /></figure>

1145 **FIG. 6.** Correlogram showing mass losses, GST reactivity, amounts of **B1** (rubrynolide, butyrolactone), **B2** (rubrenolide, butyrolactone), **A3** (*N*-ethylcoclaurine, benzylisoquinoline alkaloid) and **A10** (reticuline, benzylisoquinoline alkaloid), and the ratio of butyrolactones to alkaloids.

1150
1151 TABLES

1152 **Table 1.** GST reactivity (thermal stability assay) obtained for the alkaloids **A3** (N-

1153 Methylcoclaurine) and **A10** (reticuline), and the butyrolactones **B1** (rubrynolide) and **B2**

1154 (rubrenolide).

<table><thead><tr><th rowspan="2">Compounds</th><th colspan="6">GSTs Omega from <i>Trametes versicolor</i> (ΔT<sub>m</sub> in °C)*</th></tr><tr><th>GST1</th><th>GST2</th><th>GST3</th><th>GST4</th><th>GST5</th><th>GST6</th></tr></thead><tbody><tr><td><b>A3</b></td><td>0 ±1</td><td>0 ±2</td><td>-16 ±4</td><td>1 ±0</td><td>0 ±1</td><td>-1 ±1</td></tr><tr><td><b>A10</b></td><td>0 ±1</td><td>0 ±1</td><td>-16 ±5</td><td>0 ±1</td><td>0 ±0</td><td>-1 ±1</td></tr><tr><td><b>B1</b></td><td>-1 ±1</td><td>-1 ±1</td><td>-1 ±1</td><td>0 ±0</td><td>-1 ±1</td><td>-1 ±1</td></tr><tr><td><b>B2</b></td><td>-2 ±1</td><td>-1 ±1</td><td>-1 ±1</td><td>-1 ±1</td><td>0 ±0</td><td>-1 ±1</td></tr></tbody></table>

1155

1156

1157

1158

<footnote>* ΔT<sub>m</sub>: Difference of melting temperature between the reference (reagents and DMSO) and the test conditions (reagents and compound)</footnote>