Comparative metabolomics of Tilia platyphyllos Scop. bracts during phenological development

Phytochemistry 167 (2019) 112084

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Comparative metabolomics of Tilia platyphyllos Scop. bracts during phenological development

T

Zsolt Szűcsa,1, Zoltán Cziákyb, Attila Kiss-Szikszaic, László Sinkab, Gábor Vasasa, Sándor Gondaa,* a

University of Debrecen, Department of Botany, Division of Pharmacognosy, H-4010 Debrecen, Egyetem tér 1, Hungary University of Nyíregyháza, Agricultural and Molecular Research and Service InstituteTab, Hungary c University of Debrecen, Department of Organic Chemistry; H-4010 Debrecen, Egyetem tér 1, Hungary b

A R T I C LE I N FO

A B S T R A C T

Keywords: Tilia platyphyllos Scop. (Malvaceae) Metabolomics Bract Phenological phases Seasonal variation LC-ESI-MS

The medicinal plant drug “Tiliae flos” consists of the botanical flowers and bracts of Tilia sp., gathered almost exclusively during flowering. In this study, we examined the changes in the metabolome of specialized products in the bracts of Tilia platyphyllos from the appearance of the organ till the onset of senescence by LC-ESI-MS and data mining. A set of 504 natural products were detected, 241 of which showed significant seasonal variation (p < 9.92E5). Seven compounds were quantified and an additional 45 were putatively identified. These included flavonoid glycosides, catechins, procyanidins, quinic acid derivatives (including chlorogenic acid) and coumarins. Compared to bracts during flowering, young tissues were characterized by a relatively high diversity of polyphenolic substances. Higher amounts of flavonol glycosides (quercetin, kaempferol), catechins and derivatives have been observed. Deoxyhexosides were almost exclusive to this phenological stage. Changes of about one order of magnitude were not uncommon. For some substances, 5-fold differences were observed (calibration with authentic standards). Some compounds (e.g. the coumarin fraxin) were more prominent at the late fruit growth stage. It was shown that bracts gathered before or after flowering could potentially be therapeutically useful. Changes are rapid during the early phase of bract development: three different groups of compounds presented their maxima during the first 32 days. Considering seasonal variation is of extreme importance during bioactivity tests and screening candidate sources for bioactive natural products. In the case of T. platyphyllos, young and old bracts can be of interest because of their high diversity of distinct specialized metabolites.

1. Introduction Lime flower is used worldwide as a delicious herbal tea. The herbal drug “Tiliae flos” consists of the inflorescences (flowers and bracts) of Tilia cordata Miller, Tilia platyphyllos Scop. and Tilia × vulgaris Heyne (Malvaceae). It has been used in traditional medicine to treat migraine, hysteria, feverish cold, arteriosclerotic hypertension and nervous tension for a long time. Tiliae flos is an official drug in the European Pharmacopoeia 9th edition. Herbal teas containing Tiliae flos are on the European market mainly for the relief of the common cold. It is listed by the Council of Europe as a natural source of food flavoring (category N2) (Barnes et al., 2007; Dénes et al., 2012; Sõukand et al., 2013). Tilia platyphyllos inflorescences contain high amounts of several flavonoids (quercetin-3,7-dirhamnoside, quercitrin, rutin, isoquercitrin, astragalin (Toker et al., 2001), catechins ((+)-catechin,

(−)-epicatechin, procyanidin dimers (B type) and trimers (C type)), cinnamic acid derivatives, coumarins, polysaccharides and essential oil (Karioti et al., 2014). The inflorescence is (traditionally) gathered almost exclusively during flowering. Up until now, organs of Tilia spp. have been studied in several papers. Our hypothesis was that T. platyphyllos bracts can be of therapeutic value outside the usual harvesting period, i.e., flowering. The inflorescence is the most frequently examined organ (Karioti et al., 2014), but only a few studies examine the bract specifically. One paper studied the bract separately, and compared the flavonoid content of different organs (Toker et al., 2001). The related species Tilia cordata Mill and Tilia americana var. mexicana (Schltdl) Hardin are examined in more detail. There are many articles about the chemical comparison of the inflorescences of different Tilia spp. or Tilia spp. with other species (Neirynck et al., 2000; Toker et al., 1999; Yıldırım et al., 2000).

*

Corresponding author. E-mail addresses: [email protected], [email protected] (S. Gonda). 1 Zsolt Szűcs worked on this research as the student of the University of Debrecen, Doctoral School of Pharmaceutical Sciences. https://doi.org/10.1016/j.phytochem.2019.112084 Received 23 November 2018; Received in revised form 24 June 2019; Accepted 4 August 2019 0031-9422/ © 2019 Published by Elsevier Ltd.

Phytochemistry 167 (2019) 112084

Z. Szűcs, et al.

of 15 metabolites (2.97%) showed significant differences (p < 9.92E5) between trees and sampling times as well. Studies dealing with the seasonal variability of specialized metabolites in plant organs usually have much lower resolution than the current study (Dai et al., 2015; Vagiri et al., 2015; Valares Masa et al., 2016; Yang et al., 2015; Zhang et al., 2016), which is not enough to adequately detect several trends. For example, in the case of Salminen et al. (2004) and Tuominen and Salminen (2017), phenomena would have been missed with a typical once-a-month sampling. Using the untargeted metabolomics approach complemented quantification of a set of compounds after calibration (Cosmulescu et al., 2014), giving much more insight (Dai et al., 2015). The metabolome of young tissues was also shown to be substantially different from that of the older organs in leaves of Quercus sp. (Salminen et al., 2004), in Geranium sylvaticum (Tuominen and Salminen, 2017) and in Cistus ladanifer (Valares Masa et al., 2016).

Seasonal variation of natural products originates from the needs of the plant during adaptation to its changing environment. Logically, the changes in the metabolome lead to different bioactivities of the plant during phenological development, as exemplified in several studies (ElReadi et al., 2013; Miller et al., 2009; Zhang et al., 2016). In the current study we aimed to examine seasonal variability of the specialized compounds of T. platyphyllos bracts and test the hypothesis that the bracts can be of therapeutic value before and after flowering as well. Therefore, we characterized the pharmaceutically relevant specialized products in the metabolome of the Tilia platyphyllos bract during different phenological stages using an LC-ESI-MS-based metabolomic approach. This methodology enables the gathering of lots of data without the need to purify natural products from the matrices of interest. The data are processed using data mining techniques to find correlations and general phenomena. 2. Results and discussion

2.3. Metabolome diversity 2.1. Identified specialized metabolites of Tilia platyphyllos bracts Metabolome diversity is usually not assessed in seasonal variation studies. In the current work, the Shannon index was used to measure metabolome diversity as in Peters et al. (2018), who used this index to describe metabolite diversity in the studied bryophytes. As seen in Fig. S5, the initial metabolome is highly diverse compared to that during growth: many compounds disappear within the first week of organ development. Thereafter, there is a slow increase as new compounds appear, but the level of the initial complexity is not reached until after fruit development takes place.

Bracts of various phenological stages were shown to contain various phenolic compounds, based on the identification of LC-ESI-MS spectra (Table 1). Several flavonoids, including kaempferol, quercetin and luteolin glycosides, as well as catechin derivatives, procyanidins, coumarin derivatives and quinic acid derivatives were identified according to reference spectra (see section 4.6.), along with some non-phenolic compounds. As specialized metabolites were only tentatively identified, description of novel compounds was not attempted. The compounds found were previously found in inflorescences of Tilia sp. consisting of the bract and the flowers. Procyanidin oligomers, catechin and epicatechin were found in Tiliae flos (Karioti et al., 2014), and flavonoid hexosides, deoxyhexosides were described from inflorescences of T. americana (Aguirre-Hernández et al., 2010; Pérez-Ortega et al., 2008). Specifically regarding T. platyphyllos, kaempferol and quercetin monoglycosides, diglycosides as well as catechin, epicatechin and procyanidin B2 have been described (Jabeur et al., 2017). However, it is unclear how much of these compounds come from the botanical flowers, as only Toker et al. (2001) specifically examined the bract, providing a comparison to flowers and leaves. They found that the bract has a similar composition to that of the leaves (Toker et al., 2001).

2.4. Metabolite clusters in seasonal variation Unsupervised clustering of the scaled and centered abundance data was done in R 3.5.0 to obtain groups of metabolites with similar time course concentration kinetics. The clustering is thus based on the similarity and dissimilarity of seasonal variation trends in the sample set. Four major trend types have been identified: (1) no significant trend can be observed; (2) low initial concentration that increases over time; (3) a high initial concentration followed by a decrease; and (4) a transient increase during the growth period. Most metabolites can be associated with these groups. Unsupervised hierarchical clustering of the dataset and cutting to clusters at equal height resulted in 6 clusters which can be more or less linked to one of the trend types recently mentioned. Some clusters could be divided further into subgroups (Fig. 2, Fig. 3). Several clusters contained compounds from different subclasses of phenolic compounds (flavonoids, quinic acid derivatives) (Fig. 4(a)-(b) Table 1). In concordance with Tuominen and Salminen (2017), we could conclude that different metabolite groups can exhibit different seasonal trends. However, it is necessary to add that compounds from a single metabolite class can show different seasonal trends, as is the case with the leaves of Quercus sp. (Salminen et al., 2004).

2.2. Seasonal variation of the Tilia platyphyllos bract metabolome The overall changes in the T. platyphyllos bract metabolome change are plotted as a PCA score plot (Fig. S1). PC1 and PC4 were chosen as they were most affected by time (p = 8.12E-24, p = 3.95E-4, ANOVA). It is obvious that severe changes occur in the metabolome between days 0–32, before flowering, especially during the major growth phase of the bract (days 0–21) (Fig. 1, Figs. S1–4). In the young organ (days 0–21), the metabolome is extremely different from the metabolome during the flowering and later developmental stages. Later on, a relative stability can be observed during flowering, followed by a slow characteristic change during fruit growth, and rapid changes from the onset of senescence (days 72–112). As Fig. S1 only covers a small proportion of variance of the whole change (9.68% and 5.85%, respectively), it is better to examine the change kinetics of the major groups, as detailed in 2.4. The significance of the effects of time and tree number was also studied using ANOVA models for each compound separately (Table S1). After Bonferroni correction (n = 504), 241 features turned out to be significantly (p < 9.92E-5) affected by time (47.82% of features). Of these, 202 (40.07%) were highly significant (p < 1.98E-6). The difference among trees was only significant for 6.34% of all metabolites studied (n = 32), while the interaction between the two experimental factors was only significant in the case of a single feature (0.19%). A set

2.4.1. Specialized compounds with no apparent or insignificant seasonal variation Several compounds did not show significant seasonal variability (p > 9.92E-5). Most of these belong to clusters 2, 4 and 5a. Cluster 2 was found to contain a compound (a dihexoside (1)), but no specialized metabolites were identified (Table 1, Fig. 4(a)). The concentrations of the compounds in this group showed a transient decrease during the expansion of the organ (in parallel with the decrease of diversity of the metabolome (Fig. S5)), but are generally present in the tissue at a constant level (Fig. 3). Therefore, we think that 1 also acts as a building block of other specialized products. Monosaccharides showed various kinetics in leaves of Betula pubescens subsp. czerepanovii (Riipi et al., 2002): each monosaccharide shows a maximum at a different phenological stage which is not similar to that of 1. 2

Phytochemistry 167 (2019) 112084

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Table 1 Identified and putatively identified natural products from Tilia platyphyllos bracts of various phenological stages. Identification is based on the listed references and comparison with authentic standards. Class abbreviations: Coum, coumarins; Flav, flavonoids (including catechins and procyanidins); Qui, quinic acid derivates; Sacch, saccharides. References: K, Karioti et al. (2014); M, Mulroney et al., 1995; MSA, Mohd Shukri and Alan, 2010; P, Parejo et al. (2004); SR, SR.; V, Vukics and Guttman (2010). ID

(Putative) identification

[M-H]-

Rt (min)

Class

MS2

Cl.

References

1 2

Dihexoside Quinic acid-derivate 1

341.1084 373.1238

1.006 1.02

Sacch Qui

2 1

M MSA, P, SR

3 4 5 6 7

Quinoyl-dihexoside derivate 1 Quinic acid Quinoyl-hexoside Quinoyl-hidroxyquinic acid Quinic acid-derivate 3

533.1714 191.055 353.1084 383.1190 406.0199

1.023 1.04 1.04 1.04 1.04

Qui Qui Qui Qui Qui

4c 6b 3 6b 3

MSA, MSA, MSA, MSA, MSA,

8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

Quinic acid-derivate 4 Quinic acid dimer Procyanidin dimer (B type) 1 Esculetin-derivate (+)-Catechin Catechin-derivate Chlorogenic acid Hidroxy-coniferyl alcohol-hexoside Fraxin Procyanidin dimer (B type) 2 (−)-Epicatechin Coumaroylquinic acid 1 Taxifolin-hidroxyquinoyl-hexoside Quercetin-hexoside-deoxihexoside Procyanidin trimer (C type) Quercetin-deoxyhexoside-derivate Quercetin-dihexoside Quercetin-deoxyhexoside-pentoside Quinic acid-derivate 6

421.096 365.1083 577.1352 385.0776 289.0717 335.0772 353.0877 357.1188 369.0823 577.1347 289.0716 337.0927 655.1515 609.1458 865.1984 615.1115 625.1407 579.1352 461.1664

1.04 1.057 8.239 8.421 8.712 8.712 8.8 8.962 9.269 9.377 9.625 9.64 9.838 9.856 9.856 9.944 9.944 9.961 9.97

Qui Qui Flav Coum Flav Flav Qui Qui Coum Flav Flav Qui Flav Flav Flav Flav Flav Flav Qui

3 6b 6a 4c 5b 5b 5b 1 1 1 6a 6b 6b 6b 6a 6b 6b 6b 1

MSA, P, SR MSA, P, SR K P Authentic standard K Authentic standard MSA, P, SR P K Authentic standard MSA, P, SR K, V K, V K K, V K, V K, V MSA, P, SR

27 28 29

Coumaroylquinic acid 2 Quercetin-deoxyhexoside derivate 1 Quercetin-dideoxyhexoside

337.0927 725.1932 593.1503

10.048 10.1 10.117

Qui Flav Flav

6b 4b 6b

MSA, P, SR K, V K, V

30

Quercetin-deoxyhexoside-pentoside derivate 2 Luteolin-deoxyhexoside-pentoside

661.1385

10.13

Flav

6b

K, V

563.1399

10.135

Flav

6b

K, V

629.1275

10.135

Flav

6b

K, V

33 34 35 36 37 38 39 40 41 42 43 44 45

Quercetin-deoxyhexoside-pentoside derivate 1 Taxifolin-quinoyl-hexoside Rutin Luteolin-deoxyhexoside-derivate 4 Kaempferol dideoxyhexoside-pentoside Kaempferol-deoxyhexoside-dihexoside Luteolin-deoxyhexoside-derivate 5 Kaepmferol-dideoxyhexoside Luteolin-deoxyhexoside-derivate 3 Luteolin-deoxyhexoside-derivate 1 Eriodictyol-hexoside Quercetin-hexoside Quercetin-pentoside Quercetin-derivate

639.1562 609.1458 679.1516 709.1982 755.204 613.1770 577.1553 613.1326 645.1428 449.1083 463.0880 433.0770 501.0646

10.135 10.14 10.328 10.346 10.346 10.364 10.398 10.398 10.398 10.432 10.467 10.679 10.679

Flav Flav Flav Flav Flav Flav Flav Flav Flav Flav Flav Flav Flav

6b 6b 6b 4b 4b 1 6b 6b 6b 4c 5a 5a 5a

Authentic standard K, V K, V K, V K, V K, V K, V K, V K, V K, V K, V K, V

46 47 48 49 50 51 52

Procyanidin A2 Quercitrin Tetrahydroxychalcone-hexoside Kaempferol-pentoside Isoramnetin-3-glucoside Luteolin-derivate Kaempferol-deoxyhexoside

575.1061 447.0926 433.1135 417.0824 477.1034 499.0854 431.0979

10.702 10.817 10.904 10.938 11.18 11.186 11.717

Flav Flav Flav Flav Flav Flav Flav

179.0549; 161.04396; 101.02279; 89.02269; 71.01211; 59.01215 217.05157; 199.04143; 191.0551; 155.03372; 137.02316; 111.04359; 93.03294 191.05505 127.0386; 93.03295; 85.02786 191.05515; 173.0442 191.05507; 173.04434 315.98843; 285.97824; 244.97507; 225.95621; 201.95654; 191.05524; 171.94518; 104.92645; 96.95862; 87.92357 241.03227; 191.05518; 173.04437; 155.03339; 111.0437; 93.03301 191.05499; 173.04428 289.07199; 407.07693; 271.03961; 125.02278 177.01799; 220.9231; 112.98399 245.08211; 125.02283 289.07144; 245.08119; 125.02279 191.0551; 179.03409; 161.02296; 85.02779 177.05461; 195.06537; 162.03082; 71.01215 207.02896; 192.00543 289.07153; 407.07693; 245.08147; 125.02278 245.08125; 125.02277 191.05544; 163.03885; 173.04433; 112.98392; 93.03295 301.0351; 299.01941; 463.08878; 446.08496; 151.00218 301.035; 299.01932; 463.08798; 447.09158; 271.02475; 151.00217 289.07184; 407.07599; 125.02278 301.03513; 299.0195; 446.08496 301.03513; 299.01941; 446.08496; 271.0242; 151.00212 301.03503; 299.01938; 446.0851; 271.0246 191.05544; 149.04427; 131.03355; 101.0229; 89.0228; 71.0122; 59.01223 191.05507; 163.03888 301.03516; 299.01938; 446.08521; 151.00171 301.03503; 299.01941; 447.09247; 271.02469; 255.02997; 151.00212 593.15118; 446.08542; 447.09311; 431.0986; 430.09033; 301.0354; 299.01974; 285.04058; 283.02481; 151.00214 285.04022; 283.02457; 430.09003; 255.02946; 227.03389; 151.00209 285.04031; 283.02454; 301.03497; 299.01926; 446.08527; 430.09015; 255.02898; 151.00217 301.03513; 299.01941; 447.09262; 446.08508; 430.0896; 151.00212 285.04031; 283.0246; 430.09003; 417.08319 285.04034; 283.02469; 430.08997; 255.02943 285.04031; 431.09824 285.04025; 431.0976 285.04022; 430.09079; 153.01791; 135.00725; 109.02785; 71.01212 285.04025; 283.0246; 430.09; 255.02979; 151.00215 285.04025; 430.08994; 255.0179 285.04019; 430.09018; 307.02277 287.05585; 175.0025; 151.00226; 135.04372 301.03503; 300.02716; 271.02432; 255.02936; 151.00218 301.03503; 300.02722; 271.02454; 255.0294; 151.00218 301.03525; 300.02731; 433.07761; 271.02484; 255.02917; 178.9976; 151.0022 289.07257; 407.07791; 245.08211; 125.02318 301.03506; 300.02728; 271.02469; 255.02948; 151.00223 301.03513; 300.02734; 277.06104; 255.0291; 151.00217 285.04019; 284.03241; 255.02937; 227.03418; 151.00214 285.04022; 283.03247; 431.09818; 255.02948; 229.05002; 151.1371 285.04022; 255.0292; 229.04956 285.04025; 284.03235; 151.00224

– 5a 4c 5b 5b 5b 6b

Authentic standard Authentic standard K, V K, V Authentic standard K, V K, V

31 32

P, P, P, P, P,

SR SR SR SR SR

4-5a contain flavonoid glycosides, including kaempferol diglycosides (37, 36, 4), pentosides (a quercetin-pentoside (44, 5a), hexosides (a quercetin-hexoside (43, 5a) and deoxyhexosides (quercitrin (47, 5a), Fig. 5(d)), a chalcone hexoside (48, 4) and a coumarin derivative (esculetin derivative, 11, 4). Such constitutive presence of phenoloids was shown for individual quercetin glycosides in Quercus sp. leaves by Salminen et al. (2004), but this was unlike the trends shown by other flavonoid glycosides.

A similar group is clusters 4-5a, a loosely attached group with many putatively identified specialized phenoloids; the concentrations of its metabolites fall in the same range during most of the organ's lifetime (Figs. 3 and 5(d) and Table 1). These changes were not significant (p > 9.92E-5, Table S1). A subgroup (4b) shows low concentrations in young tissues, which increase to higher amounts within two weeks, and show a slow decrease during the remaining time period (Fig. 3, a kaempferol-deoxyhexoside-dihexoside (37, 4b, Fig. 5(a)). The clusters 3

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Fig. 1. Photos of Tilia platyphyllos bracts at various sampling time points and phenological stages. Photos were taken before drying. (a) day 0, (b) day 27, (c) day 42, (d) day 52, (e) day 88, (f) day 104.

The compounds in the group have very high initial concentration compared to later development stages. They show maximal concentration at day 0, followed by a rapid, statistically significant decrease within 7–14 days (p < 9.92E-5). For example, the concentration of (−)-epicatechin (18) was reduced by about an order of magnitude (Fig. 5(f)) during the first two weeks of phenological development. From the 14th day on, the concentrations of these compounds remained practically constant during most of the phenological development. This group was shown to contain several monoglycosides (Fig. 4(c)). Among flavonoids, flavonol-type aglyca were dominant (Fig. 4(a)–(b), Table 1): a kaempferol-pentoside (49, 5b)), and isorhamnetin-3-glucoside (50, 5b, Fig. 5(c))), Fig. 5(d)) were classified here. This group also contains several catechin derivatives ((+)-catechin, (12, 5b, Fig. 5(e)), (−)-epicatechin (18, 6a, Fig. 5(f))), a catechin derivative (13, 5b), a procyanidin dimer (B type) (10, 6a) and a procyanidin trimer (C type) (22, 6a) as well as the quinic acid derivative chlorogenic acid (14, 5b). The high amount of tannin-like substances, procyanidins and catechins was observed in young organs of different tree species. In a study on Quercus sp. (Salminen et al., 2004), the total amount of phenolics, as well as the amount of individual kaempferol glycosides and hydrolyzable tannins follow a trend similar to the compounds above: higher abundance in young tissues, and a subsequent decreasing trend. High amounts of catechins in young tissues and a subsequent decrease was also shown in different Juglans regia cultivars (Cosmulescu et al., 2014).

Behind the relatively weak decreasing trends of total phenolics, a wide range of high-fold changes happened at the level of individual metabolites (Salminen et al., 2004). The sum of phenolics was also relatively stable in Betula sp. leaves (Riipi et al., 2002). In a study on Ribes leaves (Vagiri et al., 2015), several major individual flavonoids (quercetinrutinoside and quercetin-malonyl-glucoside) showed only weak trends. 2.4.2. Specialized compounds showing an increasing trend during development Most compounds of cluster 1 are present at low amounts in young tissues, but their concentrations rise significantly during the growth of the bract. Subsequently, concentrations either remain steady during later phases or increase further (Fig. 3). In the case of most metabolites, the change is statistically significant (p < 9.92E-5, Table S1). This biosynthetically mixed group was shown to include a quinic acid derivative (26), a coumarin (fraxin (16), Fig. 5(b)), and a phenylpropanoid (hydroxy-coniferyl alcohol-hexoside (15). The observed seasonal variation of fraxin is the opposite of what was observed for coumarin in Ficus carica leaves by Marrelli et al. (2014). 2.4.3. Specialized compounds showing a decreasing trend during development The clusters 5b-6a are responsible for a significant part of the rapid change of the metabolome in the first 14 days of bract development. 4

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Fig. 2. Pearson correlation heatmap of the filtered, scaled and centered dataset of 504 metabolites from Tilia platyphyllos bracts during the organ's lifetime. Numbering and letters in the colored rectangles show cluster numbers and subgroups, respectively.

32, 6b), a quercetin-deoxyhexoside derivative (23, 6b), as well as a quercetin-hexoside-deoxihexoside (21, 6b) and rutin (34, 6b, Fig. 5(h)). Kaempferol glycosides are represented by a kaempferol-deoxyhexoside (52, 6b, Fig. 5(j)). Quinic acid - phenylpropanoid conjugates also show this type of seasonal trend (two coumaroyl-quinic acid isomers (19, 27, 6b), a quinoyl-hidroxyquinic acid (6, 6b), Table 1), a quinoyl-hexoside (5, 3, Fig. 5(i)), and two quinic acid derivatives (7, 8, 3). Quinic acid is the intermediate metabolite of the phenylpropanoid pathway (Fraser and Chapple, 2011), and hence, flavonoid biosynthesis. Their accumulation before the opening of the flavonoid-rich flowers (Toker et al., 2001) suggests a reservoir-like role of the bract for these biosynthetic intermediates. For some compounds, the decrease is about 5-fold on average (see rutin (34, Fig. 5(h) as an example). Purification of such compounds would make an optimization of the sampling time inevitable, as a few days' time results in large differences in concentrations. The trends and the order of magnitude of change are very similar to the seasonal variation of p-coumaroyl-quinic acid derivatives and gallotannins in Betula sp. leaves (Riipi et al., 2002). Less pronounced temporary increases in concentration were observed in the same species for total flavonoid-glycosides and subsets of flavonoid glycosides (Riipi et al., 2002). In Juglans leaves, the rutin concent also showed a trend with a peak: it increased during the growth season, followed by a decline (Cosmulescu et al., 2014). The same phenomenon was found in leaves of different apple cultivars for rutin and quercitrin (Usenik et al., 2004).

The rationale behind the biosynthesis of high amounts of catechins might be to make the young, nutrient-rich tissue less attractive to herbivores and defend it against pathogenic microorganisms - until more complex biosynthetic pathways are turned on (Falasca et al., 2014).

2.4.4. Specialized compounds showing a transient increase during the growth of the bract Clusters 3 and 6b form this group, in which the compounds (cluster 6, Fig. 2) are present in low concentrations at day 0 (cluster 6b), or are absent (cluster 3). This is followed by a transient increase in concentration. From the beginning of flowering, these compounds show no apparent trend: they are present in relatively low concentrations (Fig. 3). A high proportion of these compounds shows significant seasonal variability (p < 9.92E-5, Table S1). This behavior is contrary to that found in Cluster 1 (very low amounts before flowering); hence, a strong negative correlation to that group can be observed (Fig. 2). The maximal concentrations of the compounds in subgroup 6b span the time range of days 7–21, while compounds in cluster 3 peak between 21 and 32 days (just before opening of the flowers). This group shows a high diversity of flavonoids and quinic acid derivatives. Flavones (luteolin), flavanolols (taxifolin) and flavonols (quercetin, kaempferol) are present mainly as glycosides: all diglycosidic flavonoids and almost all deoxyhexosides were classified in this group (Fig. 4(c)–(d), Table 1). Luteolin glycosides include luteolin-deoxyhexoside-derivatives (35, 41, 40, 6b) and a luteolin-deoxyhexosidepentoside (31, 6b). Quercetin derivatives are represented by a quercetin-dideoxyhexoside (29, 6b, Fig. 5(g)), a quercetin-dihexoside (24, 6b), several quercetin-deoxyhexoside-pentoside derivatives (25, 30,

2.4.5. Comparison with kinetics of phenoloids in leaves of other tree species Though the above changes are not easy to summarize in a few 5

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Fig. 3. Heatmap of the relative abundance of 504 metabolites from Tilia platyphyllos bracts during the organ's lifetime, ordered by hierarchical clustering based on change kinetics. Metabolite-wise autoscaled data are shown: the quantitative change is presented as compared to the average value over time (shown as 0). Numbering and letters in the colored rectangles show cluster numbers and subgroups, respectively.

flowering (days 21–32). What is more, these dynamics can emerge as a relatively constant overall defensive compound concentration – typically examined by antioxidant or total polyphenolic assays. As Salminen et al. (2004) stated, rough quantifications of the total polyphenolic content tell nothing about the variance in individual compounds.

sentences, and there can be significant inter-species differences (Raal et al., 2015), some phenomena clearly show that the bract – despite being part of the generative shoot – shows change kinetics similar to that of leaves of various species. A direct comparison can be attempted as both organs photosynthesize, and the bract's polyphenolic composition is very similar to that of the leaves and distinct from that of the botanical flowers in T. platyphyllos, as shown in Toker et al. (2001). Firstly, the initial metabolome seems to be richer in metabolites regarding both diversity and quantity. Similar phenomena were found for catechins and procyanidins in leaves of Betula pendula (Raal et al., 2015) and various polyphenolics in Quercus sp. (Salminen et al., 2004). The most rapid changes take place during growth of the organ, as in Salminen et al. (2004). Therefore, tissue age during bioactivity screening can be of extreme importance during fast changes: recall that before flowering, three groups of compounds reach their concentration maxima: compounds highest at day 0, those presenting peak concentration during days 7–21, and compounds peaking just before

2.5. Implications for possible applications As the metabolome is different at different phenological stages, different bioactivities and absorption and distribution kinetics can be expected, as shown for Lippia thimoides (Silva et al., 2016). Bioactivities linked to coumarins, for example, are likely to be more pronounced during later phenological stages, while quinic acid derivatives are present at highest concentration before flowering. Flavonoids are always present in the bracts in some form, though there are significant variations in the concentrations of individual 6

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Fig. 4. Possible classifications and chemical characteristics of the identified and putatively identified natural products from Tilia platyphyllos bracts, along the clusters identified by comparing concentration change kinetics. Jittering along x-axes is arbitrary, it is to help evaluation of dense regions; y-axis coordinates match that on the hierarchical cluster tree. Numbering and letters in the colored rectangles show cluster numbers and subgroups, respectively. Subplots: (a) Metabolite class based on aglycone. Quinic acid – cinnamic acid conjugates are shown as quinic acid here; (b) Flavonoid aglyca. Non-flavonoid compounds were not plotted; (c) Total amount of sugar moieties attached, all putatively identified compounds shown; (d) Saccharide side-chain types, all putatively identified compounds shown.

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(caption on next page)

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Fig. 5. Boxplot of change of concentrations of selected natural products during the lifetime of Tilia platyphyllos bracts from four trees, measured by LC-ESI-MS. The yaxis is either concentration in DW (where authentic standards were available), or raw abundance data. Dotted vertical lines separate major phenological phases: early development, flowering, fruit development and senescence. Compounds for which authentic standards were available are marked with an asterisk '*'. Subplots: (a) kaempferol-deoxyhexoside-dihexoside (Cluster 4b, 37); (b) fraxin (Cluster 1, 16); (c) isorhamnetin-3-glucoside * (Cluster 5b, 50); (d) quercitrin * (Cluster 5a, 47); (e) (+)-catechin * (Cluster 5b, 12); (f) (−)-epicatechin * (Cluster 6a, 18); (g) quercetin-dideoxyhexoside (Cluster 6b, 29); (h) rutin * (Cluster 6b, 34); (i) quinoylhexoside (Cluster 3, 5); (j) kaempferol-deoxyhexoside (Cluster 6b, 52).

compound. In the herbal drug, the flavonoids are mainly present in glycosidic form (Karioti et al., 2014; Toker et al., 2001), which are deglycosylated in the human gastrointestinal tract by intestinal bacteria (Kim et al., 1998; Macdonald et al., 1983) and the β-glycosidase enzymes from the human small intestine (Németh et al., 2003). Flavonoids are generally thought to be absorbed as aglyca, as shown for quercetin (Crespy et al., 2002); in human plasma, they are present as conjugated metabolites (Graefe et al., 2001). The latter forms are thought to be responsible for the pharmacological effects. Pharmacokinetics of the pure flavonoid aglyca do not always match those in a plant extract (Wang et al., 2011), not to mention different glycosides (e.g. rhamnosides vs beta-glucosides) of the same aglycone (Gonzales, 2017). Young bracts are rich in flavonoid diglycosides and other flavonoids which become less significant over time, while the concentrations of monoglycosides remain relatively constant. Shortly before and after flowering, the bract metabolome seems to be extremely similar to that during the flowering phase – the main harvest period. Therefore, development stages usually not considered to be of interest can be good candidates for investigation for bioactivity. The presented data support our hypothesis: bracts are likely highly bioactive outside the time of the blooming of the flowers, and are likely to show altered bioactivity compared to other phenological stages. Of course, it is important to mention that (a) the bioactivity of the unidentified compounds is not taken into account; (b) the estimation of the amount from raw abundance is prone to errors because of the different detection sensitivities; and (c) synergy is not accounted for.

4. Experimental 4.1. Plant material Bract samples from four adjacent Tilia platyphyllos Scop. (Malvaceae) trees were collected from the campus of the University of Debrecen (47.5556 N, 21.6215 E), from the appearance of the organ until senescence (112 days). The first day of collection was 20th April 2015. Bracts were always collected at around 11:00 a.m., to ensure the drying of dew. Typically ~150–200 mg DW of bracts were collected (about n = 40–50 in the beginning, while n = 8–10 in the later period (Fig. 1)). During sampling, representative samples were collected from several points of the trees. This was necessary because the position on the plant can have significant impact on the metabolome, as exemplified by Vagiri et al. (2015) in Ribes leaves. The samples were subjected to drying in warm flowing air (temperature not exceeding 40 °C) within an hour after collection, for 4 h. Residual moisture was removed by overnight lyophilization in a Christ Alpha 1–2 LD apparatus. Samples were stored in sealed vials, in darkness, at room temperature until further processing. 4.2. Phenological stage scale The phenological status of the bract was divided into stages according to an arbitrary scale. The different points of the phenophase scale occurred at almost the same time in all examined trees (Fig. S3). The first phase (0–1) is the growth of the bract and the development of the flower bud, which lasted from day 0 to day 32 (Fig. 1(a)–(b)). A rapid initial increase in size, i.e. an early growth was observed, which took place between days 0–15 (Fig. S3). The second phase is the flowering phase (1–2, Fig. 1(c)–(d)), which lasted from day 32 (opening of the first flowers) to day 49 (the majority of petals have fallen, end of flowering, fruits set). The third phase (2–3) is the fruit development phase, which lasted from day 49 to day 104 (Fig. 1(e)). The fourth phase (3–4) begins after the full development of the fruits, when senescence of the bract starts, which is characterized by the browning of the whole organ (Fig. 1(f)), followed by its subsequent falling off the tree.

3. Conclusion The untargeted metabolomic approach was found to be useful for monitoring the chemical pattern changes in Tilia platyphyllos bracts over the organ's lifetime from appearance to senescence. The bract, which is part of the herbal drug “Tilia flos,” is almost exclusively gathered during flowering. In the current study, we have shown that the bract is a rich source of bioactive phenolic compounds before as well as after the flowering period, though metabolite patterns significantly differ. In particular, the metabolome of the bract in its early development phase is characterized by a higher diversity of polyphenolic compounds than later phenological stages: tissues in the early development phase contain high amounts of catechin derivatives and flavonoid glycosides, while the late stages of fruit growth have higher concentrations of fraxin, and some derivatives of quinic acid derivatives. Hence, the bract can have potential therapeutic value not only during flowering, but also during development and fruit growth. High-resolution sampling was necessary to make the phenomena visible during the growth period (0–32 days). As the pattern of the compounds is different at different times, the biological effects on consumers may vary depending on the phenological stage, but this can be masked by a relatively stable overall concentration of compounds. In particular, the amounts of quercetin and luteolin glycosides, catechin derivatives and deoxyglycosides are much higher during development than during flowering. The study highlights the need for the optimization of the harvesting time of plant materials when used for their bioactive constituents, especially for reproducible pharmacological studies. Even a week's time can severely impact the plant specialized metabolome as exemplified by several compounds detected and putatively identified in this study.

4.3. Sample preparation The dried samples were homogenized using a mortar and pestle using liquid N2. Thereafter, an amount of material weighing exactly 25 mg was thoroughly mixed with 1 ml MeOH, maintained at room temperature for 10 min and extracted for 30 min at 75 °C. The mixture was centrifuged at 13,000 rpm for 3 min and the obtained supernatant was stored at −24 °C. For the LC-ESI-MS measurement, the samples were diluted 100-fold with MeOH, and filtered through a 0.22 μm PTFE syringe filter prior to LC/MS analysis. Quality control samples were prepared by pooling 10 μL aliquots of all measured samples together. Seven injections were carried out from the 100-fold diluted QC samples during the measurement, equally spaced in time along the injection sequence. 4.4. Chemicals The standards ((+)-Catechin, Sigma-Aldrich Chemie Gmbh., Germany; Chlorogenic acid, Sigma-Aldrich Chemie Gmbh.; 9

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that showed a mixtures of zeroes and detected peaks for the four trees were discarded; (2) signal-to-noise ratio: maximum abundance had to be over 1E5; and (3) blank control: maximum abundance had to be 100fold higher than the corresponding value of the feature (if found) in blank (MeOH). Semi-automatic identification of isotopes and adducts was done at this point, in R 3.5.0: peaks were grouped into a list of multi-correlated peaks (> 0.9, Pearson) with the same retention time ( ± 0.03 min) and typical mass differences and adducts (13C, +HCOOH, [2M–H]-), and manually checked. A total of 182 features turned out to be isotopes or adducts; these were discarded prior to analysis. The raw dataset was scaled and centered (van den Berg et al., 2006) metabolite-wise: from each metabolite's abundance data, the average was subtracted, and it was divided by its variance. Thereafter, the scaled dataset was subjected to hierarchical clustering in R 3.5.0 (hclust, distance method “minkowski,” clusterind method “Ward.D″) to obtain a hierarchical cluster and an order of compounds along with it. For each metabolite, effects of time and trees were tested in ANOVA models for each metabolite separately, in R (aov). Shannon index was calculated in R (vegan).

(−)-Epicatechin, Sigma-Aldrich Chemie Gmbh., Germany; Rutin trihydrate, Sigma-Aldrich Chemie Gmbh., Germany; Isorhamnetin-3-glucoside, Carl Roth Gmbh., Germany and Quercitrin, Carl Roth Gmbh., Germany; procyanidin A2, Sigma-Aldrich Chemie Gmbh., Germany) were dissolved separately in HPLC-MS grade acetonitrile (Fisher Scientific, USA), and a standard mix stock solution (1 mg/mL each) was prepared. The solution was filtered through a 0.22 μm PTFE syringe filter and the diluted calibration mix standards were prepared with water/acetonitrile (80/20, v/v). All solvents used for HPLC analysis were HPLC grade. MeOH for HPLC and extraction were purchased from Sigma-Aldrich. HPLC-MS grade acetonitrile, water and formic acid were purchased from Fisher Scientific (Geel, Belgium). 4.5. LC-ESI-MS The UHPLC system (Dionex Ultimate 3000RS) was coupled with a Thermo Q Exactive Orbitrap mass spectrometer (Thermo Fisher Scientific Inc., Waltham, USA) equipped with an electrospray ionization source (ESI). The HPLC separation was achieved on a Phenomenex Kinetex XB-C18 column (100 mm × 2.1 mm × 2.6 μm), oven temperature was maintained at 30 °C, and flow rate was 250 μL min−1. Eluent A was water containing 0.1% formic acid and eluent B was acetonitrile (Fisher Scientific, USA) containing 0.1% formic acid. The following gradient elution program was used: 0 min, 95% A; 0–3 min, 95% A; 3–15 min, 0% A; 15–20 min, 0% A; 20–21 min, 95% A; 21–29 min, 95% A. 1 μl of the samples was injected in every run. The Q Exactive hybrid quadrupole-orbitrap mass spectrometer was operated in negative ion mode with the following parameters: capillary temperature 320 °C, spray voltage 4.0 kV, and the resolution was set to 70000. The mass range scanned was 150–1500 m/z. The maximum injection time was 100 ms. The resolution was set to 35000 in the cases of MS2 scans. The collision energy was 40 NCE. Sheath gas and aux gas flow rates were 32 and 7 arb, respectively.

4.8. Quantification by LC-ESI-MS Calibration curves were constructed for (+)-catechin, (−)-epicatechin, rutin trihydrate, isorhamnetin-3-Glucoside, quercitrin and chlorogenic acid. From these stock solutions, we prepared seven-point serial dilutions: 3 μg/L, 10 μg/L, 30 μg/L, 100 μg/L, 300 μg/L, 1000 μg/ L, and 3000 μg/L (equally spaced along the log10(concentration) range), which were measured according to the above method. The R2 values were calculated from log10-transformed concentration and abundance data. R2 values were as follows: (+)-catechin, 0.9995; (−)-epicatechin, 0.9993; rutin trihydrate, 0.9993; isorhamnetin-3-glucoside, 0.9995; quercitrin, 0.9998; chlorogenic acid, 0.9930; procyanidin A2, 0.9940.

4.6. Peak detection and identification

Acknowledgement

Automatic feature detection was then performed on the dataset with the XCMS online (Tautenhahn et al., 2012) software (https:// xcmsonline.scripps.edu/) using the following parameters: (I) Feature detection: centWave method, min. and max. peak width = 5 and 20, respectively, S/N threshold = 10, mzdiff = 0.01, integration method = 1, prefilter peaks = 3, prefilter intensity = 5000, Noise filter = 1000; (II) Retention time correction: Obiwarp method, profStep = 1; (III) Alignment:mzwid = 0.015, minfrac = 0.5, bw = 5, max = 100, minsamp = 1; (IV) Statistical test: ANOVA parametric. Putative identification of all constituents was performed by LC-ESI-MS/ MS. Identification of phenolics using MS/MS spectra is based on the fragmentation pattern from the database (https://metlin.scripps.edu/), references from the literature and comparison with the fragments of the available authentic standards. Putative identification of flavonoids by MS/MS was carried out by identification of the aglycone and ring A characteristic fragments on the basis of Karioti et al. (2014); Parejo et al. (2004) and Vukics and Guttman (2010). A similar approach was applied to catechins (Karioti et al., 2014). Cinnamic acid derivatives were putatively identified using the available literature data in Mohd Shukri and Alan (2010), Parejo et al. (2004) and Sánchez-Rodríguez et al. (2012). The identification of the type of phenylpropanoid unit(s) was the main objective. For identification of coumarins, the article of Parejo et al. (2004) was used.

The following financial support is greatly acknowledged: this research was supported by the EU and co-financed by the European Regional Development Fund under the projects EFOP-3.6.1-16-201600022, GINOP-2.3.3-15-2016-00021, GINOP-2.3.2-15-2016-00008 and 20428-3/2018/FEKUTSTRAT. The research was also financed by the Higher Education Institutional Excellence Programme of the Ministry of Human Capacities in Hungary, within the framework of the Research and Development on Therapeutic purposes thematic programme of the University of Debrecen. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.phytochem.2019.112084. Author roles Conception and design of the study: Sándor Gonda; acquisition of data: Zsolt Szűcs (all methods), Zoltán Cziáky (LC-MS measurement), László Sinka (LC-MS measurement), Attila Kiss-Szikszai (LC-MS measurement and development); analysis and interpretation of data: Sándor Gonda (visualization, data mining), Zsolt Szűcs (MS/MS fragmentations); drafting the article: Sándor Gonda, Zsolt Szűcs; critical revision: Gábor Vasas. All authors have read and approved the uploaded version of the manuscript.

4.7. Data mining The raw XCMS dataset was filtered according to the following criteria, in R 3.5.0: (1) cleanness: only the features that were found in all four samples from the same time point were considered - compounds

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