Next Article in Journal
Spore-Trapping Device: An Efficient Tool to Manage Fungal Diseases in Winter Wheat Crops
Next Article in Special Issue
Phenolic Profile and Cholinesterase Inhibitory Properties of Three Chilean Altiplano Plants: Clinopodium gilliesii (Benth.) Kuntze [Lamiaceae], Mutisia acuminata Ruiz & Pav. var. hirsuta (Meyen) Cabrera, and Tagetes multiflora (Kunth) [Asteraceae]
Previous Article in Journal
Small Heat Shock Protein (sHSP) Gene Family from Sweet Pepper (Capsicum annuum L.) Fruits: Involvement in Ripening and Modulation by Nitric Oxide (NO)
Previous Article in Special Issue
NMR Metabolomics and Chemometrics of Lettuce, Lactuca sativa L., under Different Foliar Organic Fertilization Treatments
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Plants
Volume 12
Issue 2
10.3390/plants12020390
plants-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Chemophenetic Approach to Selected Senecioneae Species, Combining Morphometric and UHPLC-HRMS Analyses

by
Yulian Voynikov
1,*,†,
Vessela Balabanova
2,†,
Reneta Gevrenova
2 and
Dimitrina Zheleva-Dimitrova
2
1
Department of Chemistry, Faculty of Pharmacy, Medical University, 2 Dunav Str., 1000 Sofia, Bulgaria
2
Department of Pharmacognosy, Faculty of Pharmacy, Medical University, 2 Dunav Str., 1000 Sofia, Bulgaria
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Plants 2023, 12(2), 390; https://doi.org/10.3390/plants12020390
Submission received: 21 December 2022 / Revised: 4 January 2023 / Accepted: 11 January 2023 / Published: 14 January 2023
(This article belongs to the Special Issue Spectra Analysis and Plants Research 2.0)
Browse Figures
Review Reports Versions Notes

Abstract

:
Herein, a chemophenetic significance, based on the phenolic metabolite profiling of three Senecio (S. hercynicus, S. ovatus, and S. rupestris) and two Jacobaea species (J. pancicii and J. maritima), coupled to morphometric data, is presented. A set of twelve morphometric characters were recorded from each plant species and used as predictor variables in a linear discriminant analysis (LDA) model. From a total 75 observations (15 from each of the five species), the model correctly assumed their species’ membership, except for 2 observations. Among the studied species, S. hercynicus and S. ovatus presented the greatest morphological similarity. A phytochemical profiling of phenolic specialized metabolites by UHPLC-Orbitrap-MS revealed 46 hydroxybenzoic, hydroxycinnamic, and acylquinic acids and their derivatives, 1 coumarin and 21 flavonoids. Hierarchical and PCA clustering applied to the phytochemical data corroborated the similarity of S. hercynicus and S. ovatus, observed in the morphometric analysis. This study contributes to the phylogenetic relationships between the tribe Senecioneae taxa and highlights the chemophenetic similarity/dissimilarity of the studied species belonging to Senecio and Jacobaea genera.

1. Introduction

The tribe Senecioneae (Asteraceae) encompasses more than 150 genera and 3000 species; approximately half of its species belong to the genus Senecio L., considering it one of the largest genera of flowering plants [1]. Senecio species have a wide distribution and they occur in various habitats—from low altitudes to high mountain communities, and from Arctic regions to hot tropical areas [1]. Although phylogenetic studies have been carried out classifying the taxa, the intergeneric relations are still vague [1,2]; some Senecio species have been recently transferred to a separate genus, Jacobaea Mill. [3]. Within the genus Senecio, hybridization was observed, e.g., S. hercynicus × S. ovatus [4]. Most taxa in the tribe can be identified by the existence of capitula (flower heads) with a typically uniseriate involucre. However, some species are poorly differentiated morphologically, and there is still uncertainty about recognition of their taxa [2,5,6,7]. Senecio species are reported to accumulate sesquiterpenoids (eremophilanes, furanoeremophilanes, cacalols, eudesmanes, oplopanes, germacranes, etc.), pyrrolizidine alkaloids (PAs) [1,8,9], phenolic compounds [10,11,12,13,14,15], and various other secondary metabolites [4,9,16]. Senecio species have been described to possess analgesic [17] and hypoglycemic [18] activity, related to the typical for the genus sesquiterpene lactones, and insecticidal properties [19] related to the presence of PAs. Additionally, the taxa are reported to express strong antioxidant, cytotoxic, and antimicrobial activity attributed to the presence of phenolic compounds [11,12,13,15].
In the Bulgarian flora, Senecio hercynicus Herborg., S. ovatus (G. Gaertn. and Al.) Willd., S. rupestris Waldst. and Kit., and Jacobaea pancicii (Degen) Vladimirov and Raab-Straube are perennial plants distributed in the mountain regions, up to 1500 (2200) m a.s.l., while J. maritima (L.) Pelser and Meijden is a shrub spread on the Black Sea coast [20]. Presently, S. hercynicus and S. ovatus are included in the S. nemorensis group. Formerly, S. hercynicus was recognized as S. nemorensis L.; S. ovatus as Jacobaea ovata G. Gaertn.; J. maritima as Senecio maritima (L.) Rchb.; J. pancicii as Senecio pancicii Degen [20]. Phytochemical studies on some Senecio and Jacobaea species with Bulgarian origin were based on the characterization of PAs [19,21,22], phenolic, and flavonoid derivatives [14]. Although the studied species are distributed in other European floras, including the floras of neighboring countries [2,23], up until now there has been no study focused on morphometric and phytochemical data analysis.
Plant chemophenetics [24] is a term that was recently proposed for exploring characteristic arrangements of specialized plant taxon metabolites; this analysis contributes to the phenetic description of the taxa—similar to anatomical, morphological, and karyological approaches—and represents an opportunity to describe organisms classified with molecular methods. Thus, the specialized metabolism products could be treated as phenotypic characters that can be used as arguments, e.g., the existence of botanical varieties in the same way as, e.g., traditional morphological characters [25].
Hence, the present study aims to apply a chemophenetic [24] approach to three Senecio (S. hercynicus, S. ovatus, and S. rupestris) and two Jacobaea species (J. pancicii and J. maritima). The morphometric data and phytochemical profiling of phenolic specialized metabolites are combined to give insight into the similarity of species in the Senecio taxa.

2. Results and Discussion

2.1. Morphometric Analysis

Samples for each of the three Senecio species (S. hercynicus, S. ovatus, and S. rupestris) and two Jacobaea species (J. pancicii and J. maritima) were characterized by 12 independent variables, (X1–12) as follows: X1—root diameter [cm]; X2—stem height [cm]; X3—leaf length [cm]; X4—leaf width [cm]; X5—involucral bract length [cm]; X6—involucral bracts number per capitula; X7—ray flower length [cm]; X8—number of ray flowers per flower head; X9—disc flower length [cm]; X10—number of disc flowers per flower head; X11—flower head diameter [cm]; and X12—number of capitula per plant. These variables have been ordinarily applied to differentiate the studied taxa [20,26,27,28]. The raw morphometric data, together with the descriptive statistics, are presented in Table S1 and Table S2, respectively. A combination of parametric (MANOVA) and non-parametric (Kruskal–Wallis) tests, together with post-hoc Bonferroni tests, were used to derive relationships between the tested variables and the samples’ taxonomic membership. An α level of 0.05 was set as significant. Some notable relationships will be drawn. Root diameter (X1) was the only parameter by which a discrimination was evident between samples belonging to the different genera; however, without differentiation within species of the same genus, i.e., J. pancicii was not differentiated from J. maritia. Similarly, the three Senecio species showed a relative homogeneity on the X4 parameter, and were distinguished from the two Jacoboea species; X4 also differentiated J. pancicii from J. maritima. On the other hand, parameters the X2, X5–7 showed similarity between S. rupestris and J. maritima, and between S. ovatus, S. hercynicus, and J. pancicii. The other parameters showed quite different relationships to the species, and it is evident from the LDA analysis shown below that a combination of the parameters is needed for the confident differentiation of the discussed species.

Correlation and Linear Discriminant Analysis (LDA)

The correlation matrix (Figure 1) revealed that stem height (X2) was positively correlated to leaf length (X3) and negatively correlated to the variables X6, X8, and X10. The number of ray flowers (X8) was positively associated to the involucral bracts number (X6) and number of disc flowers (X10). Additionally, the variables X6, X8, and X10 showed a high positive correlation between each other.
Next, a linear discriminant analysis (LDA) was performed on the X1-12 variables [29,30]. Based on several calculated parameters (Figure S1), including the residual sum of squares (RSS), adjusted R2, Mallow’s Cp, and Bayesian information criterion (BIC), a six variable model was selected, including the variables X1, X4, X7, X8, X9, and X11 (Table S3). Then, 80% of the data was used as a training set (n = 60) and 20%—as a test set (n = 15), on a random principle. The training set was used to derive a linear model for predicting the species of a plant, based on the selected set of six parameters. The linear model was able to correctly predict the species on the test set (n = 15), but one (Table S4). On the one-dimensional plot derived from the linear model (Figure 2A), S. ovatus and S. hercynicus were not well-distinguished, while on the two-dimensional plot, all species were separated, except S. ovatus and S. hercynicus with a partial overlap (Figure 2B).
Given these results, the morphological variability of the Senecio and Jacobaea species is not random and is long-established for the tribe Senecioneae taxa as prominent [31]. Although the Jacobaea is distinguished from Senecio sensu stricto, a clear morphological synapomorphies for Jacobaea have not yet been recognized [1]. The received data by the morphometrical study unequivocally confirm the taxonomical relationship of S. hercynicus and S. ovatus belonging to S. nemorensis group and the transfer of the last-mentioned species to the genus Senecio. Moreover, the results favor the delimitation of J. maritima and J. pancicii from the genus Senecio and the distinguishing of the other studied taxa [20].

2.2. UHPLC-HRMS Identification and Tentative Annotation of Specialized Natural Products

In order to establish a phenolic metabolite profiling, combined hydromethanolic plant extracts were prepared, i.e., LC-MS measurements on phenolic content were performed on the homogenized samples from the 15 collected plants from each species, as described in Section 3.4. Based on chromatographic retention times, MS and MS/MS accurate measurements, fragmentation patterns, and the comparison with reference standards and literature data, a total of 46 hydroxybenzoic, hydroxycinnamic, and acylquinic acids and their derivatives, 1 coumarin and 21 flavonoids, were annotated in the tested extracts. The LC-MS and MS/MS data of all 68 identified phenolic compounds are presented in Table 1 along with their distribution in the studied extracts.

2.2.1. Hydroxybenzoic, Hydroxycinnamic Acids, and Their Glycosides

Five hydroxybenzoic acids (compounds 3–5, 16 and 42) and four hydoxycinnamic acids (compounds 14, 26, 27, and 36) along with p-hydroxyphenylacetic acid (compound 24) were identified in the studied species by comparison with reference standards (Table 1).
Compounds 1, 2, 6–8, 10, 11, 15, 17, 19, 22, 25, and 28 presented similar fragmentation patterns indicating phenolic acid-hexosides. They gave indicative fragment ions at m/z 153.018 (compound 1), m/z 167.034 (compound 2), m/z 151.039 (compound 6), m/z 197.045 (compound 8), m/z 179.034 (compounds 10, 19, 22, 28), m/z 137.023 (compounds 11, 17), m/z 193.050 (compound 15), m/z 163.039 (compound 26), and fragmentation pathways consistent with protocatechuic, vanillic, p-hydroxyphenylacetic, syringic, caffeic, 4-hydroxybenzoic, ferulic, and p-coumaric acid, respectively (Table 1).
Compound 33 afforded a base peak at m/z 151.039 [(M−H)−162-42]−, and fragment ions at m/z 123.008 [(M−H)−162-60]− and 109.028 [(M−H)−162-2×42]−, suggesting two acetyl groups and a hexose unit. Thus, 33 was ascribed to acetoxy-hydroxyacetophenone-O-hexoside. MS/MS of 34 at m/z 595.131 [M−H]− was acquired; taraxafolin B residue was deduced from the abundant ions at m/z 341.0883 [M−H−C11H10O7]− (25.4%) and 253.035 [taraxafolin (TF)−H]−(23.5%), supported by m/z 209.045 [TF−H−CO2]−, 191.034 [TF−H−H2O−CO2]− and 165.055 [TF−H−2CO2]−. Accordingly, 34 was tentatively identified as taraxafolin B-(caffeoyl)-hexoside (Table 1).

2.2.2. Acylquinic Acids

Six mono-, nine di- and one triacylquinic acids (AQAs) were identified or annotated in the assayed species. Fragmentation behaviors were consistent with those reported [32,33]. Thus, 23, 29, and 35 were assigned to 4-caffeoyl-, 5-p-coumaroyl-, and 5-feruloylquinic acid, respectively. diAQA belongs to four widely spread in Asteraceae subclasses: dicaffeoylquinic acids (diCQA) (compounds 37–40), feruloyl-caffeoylquinic acids (FCQA) (compounds 45, 46), p-coumaroyl-caffeoylquinic acids (p-CoCQA) (compounds 43, 44), and 3-hydroxy-dihydroxy-5-caffeoylquinic acid (HC-CQA) (compound 30).
Compounds 43 and 45 gave abundant ions at m/z 337.093 (74%) and 367.104 (99%), respectively, indicating a loss of caffeoyl residue before the p-coumaroyl (compound 43) and feruloyl (compound 45) moiety. Moreover, both compounds gave base peaks at m/z 163.039 and 193.050, as observed in 3AQA, accompanied by m/z 119.049 [p-coumaric acid-H−CO2]− (34%) (compound 43) and 134.036 [ferulic acid−H−CH3−CO2]− (69%) (compound 45) (Table 1). Thus, 43 and 45 were assigned to 3-p-Co-5CQA and 3F-5CQA, respectively. In the same way, 44 and 46 were annotated as 3C-5-p-CoQA and 3C-5FQA, witnessed by the base peak at m/z 191.055 [quinic acid−H]− as was seen in 3CQA. Likewise, the base peak at m/z 191.055, together with the abundant ions at m/z 179.034 and 135.044 defined 3,5-diCQA, while 1,5-diCQA was deduced from the low abundant dehydrated ion at m/z 335.078. Vicinal diCQA 3,4-diCQA (compound 37) and 4,5-diCQA (compound 40) were witnessed by the distinctive dehydrated ion at m/z 173.045; this assumption is supported by the chromatographic behavior of both compounds on the reverse phase support being the most polar and lipophilic isomers among the diCQA [34]. It was noted that 3,4,5-triCQA (compound 47) was discernable by the prominent ions at m/z 179.034, 173.045, and 135.044, as was observed in the 3,4-disubstituted quinic acid skeleton.

2.2.3. Flavonoids

The flavonoid annotation was based on the fragmentation patterns for different flavonoid classes previously reported in a few Asteraceae species [32,33,34], or by using flavonoid standards. Retro-Diels-Alder (RDA) fragmentation allowed for the differentiation of flavon and flavonol derivatives. Thus, quercetin (compounds 51, 53, 54, 57, and 61), kaempferol (compounds 49, 56, and 58) and isorhamnetin (compounds 50, 52, 59, and 60) flavonols were identified from the RDA ions 1,3B−, 1,3A−, 0,4A−, 1,2A−, and 1,2B− (Table 1). Compounds 51, 53, 56, 58, 59, 61, and 62–66 were unambiguously identified by comparison with reference standards. Compound 48 ([M−H]− at m/z 595.168) showed a typical fragmentation of C-glycosylflavone, yielding a series of fragment ions at m/z 475.125 [M−H−120]−, 415.104 [M−H−120−60]−, 385.093 [M−H−120−90]−, 355.0822 [M−H−2×120]− [35]. The aglycone naringenin in 48 was evidenced by the RDA ions at m/z 119.049 (1,3B−), and 107.012 (0,4A−). Thus, 48 was annotated as 6,8-diC-hexosyl-naringenin. In 49 and 50, the consecutive loss of two hexose units (2×162 Da) is related to an O-dihexosyl linkage, while in 52 O-pentosylhexosyl linkage was suggested. Compounds 54, 55, and 60 presented similar fragmentation patterns yielding base peaks at m/z 301.036 (compound 54), 285.041 (compound 55), and 315.052 (compound 60) [M−H−HexA]−, respectively, indicating flavonoid hexuronides. In the case of 57, a loss of an acetyl moiety at m/z 463.089 allowed to annotate quercetin 3-O-acetylhexoside. Unlike the Asteraceae species, only two 6-methoxylated flavonoids, 67 and 68, were suggested on the base of the transitions: 329.067→314.044→299.020 (67) and 313.072→298.048→283.025 (68). Accordingly, 67 and 68 were ascribed to cirsiliol and cirsimaritin, respectively (Table 1).

2.3. Chemophenetic Significance

The chemophenetic significance of phenolic metabolite profiling coupled to morphometric data of the studied Senecioneae species is presented. The raw LC-MS data of annotated specialized compounds were converted and further manipulated with the R programming language, as detailed in Section 3.6. Integration of the Full-MS intensity signals corresponding to the identified compounds allowed the determination of their AUC values. These AUC values were used as a relative quantitative measure for a particular compound, between the studied species. In order to do so, the AUC values were normalized from 0 to 100. Thence, a similarity/dissimilarity clustering analysis of the species was conducted for those compounds found in at least two, out of all five, species (Table 2, Figure 3 and Figure 4).
Figure 3 depicts a heatmap of the AUC values from Table 2. The dendrograms separated the compounds (columns) into five clusters, and the species (rows) into two clusters (Figure 3).
The clustering, by rows, did not differentiate the two genera. The greatest resemblance was generated between S. ovatus and S. hercynicus; J. pancicii showed greater similarity to the last-mentioned two species compared to J. maritima; S. rupestris was cast as a separate node. Table S5 presents the grouped compounds from Figure 3, where it is notable which compounds were characteristic for a given species. Hence, the contribution of the annotated phenolic compounds to the phenetic description of the selected taxa was determined. For example, hydroxybenzoic (1, 4, 6, 11, 16, 17, and 42) and hydroxycinnamic (10, 15, 19, 22, 27, and 28), derivatives as well as the flavonol glucosides (57 and 58) were dominant in S. rupestris, while diAQAs (37, 38, 39, 40, 43, 44, and 46), triAQA (47) and the flavonols (53, 59, 63, and 65) were in the highest amount in J. maritima. The coumarin 12, acylquinic acids (35 and 45) and flavonoid hexuronides (54, 55, and 60) were characteristic for S. ovatus. J. pancicii, on the other hand, presented the highest amount of AQAs (9, 23, and 30), hydroxycinnamic (5 and 8), and flavonol (48, 51, and 56) derivatives. A heatmap of the Euclidean distance and a PCA plot (of the data in Table 2) are shown in Figure 4, where similar clustering is observed, compared to that in Figure 3.
As phenolic content varies between different plant parts, the %CV of the morphometric characteristics, recorded for each plant species, were typically below 20%CV, except for the number of capitula per plant (X12) reaching above 40%CV (Table S2). Noteworthy, for each of the plant species, the LC-MS measurements on the phenolic content were performed on homogenized samples from all 15 aerial plant samples, providing a representative phenolic profile. Overall, the morphometric data (Figure 2) corroborates the taxonomical relationship of S. hercynicus and S. ovatus to the S. nemorensis group. Moreover, a delimitation was observed between the two Jacoboea species (J. maritima and J. pancicii) from the genus Senecio and distinguishing of the other studied taxa [20], and similar findings were detected by to the unsupervised clustering methods applied on the phytochemical data (Figure 3 and Figure 4). In both morphometric characteristics and phenolics content, S. hercynicus and S. ovatus showed the highest similarity.

3. Materials and Methods

3.1. Plant Material

The herbal drugs (aerial parts) were collected during the full flowering stage in July 2021, with the location coordinates as follow: S. hercynicus at Vitosha Mt., “Zlatni mostove” locality at 1404 m a.s.l. (42.41° N 23.23° E); S. ovatus, S. rupestris, J. pancicii at Vitosha Mt., “Aleko hut” locality at 1855 m a.s.l. (42.58° N 23.29° E); J. maritima at the Black Sea coast, “Golden sand” resort at 24 m a.s.l. (43.28° N 28.04° E). The collected taxa at Vitosha Mt. inhabited one and the same plant community. The plant species were identified according to Vladimirov, 2012 [20]. A voucher specimen of S. hercynicus was deposited at Herbarium Academiae Scientiarum Bulgariae (SOM 177012). S. ovatus, S. rupestris, J. pancicii, and J. maritima specimens were given at Herbarium Facultatis Pharmaceuticae Sophiensis, Medical University-Sofia, Bulgaria (Voucher specimen № 11 631–11 634).

3.2. Morphometric Measurements

Morphometric measurements on the studied Senecio and Jacobaea species were performed on 15 randomly chosen plants, from each species, during the full flowering stage. The morphometric variability was determined using 12 quantitative characters (parameters) as follows: X1—root diameter [cm]; X2—stem height [cm]; X3—leaf length [cm]; X4—leaf width [cm]; X5—involucral bract length [cm]; X6—involucral bracts number per capitula; X7—ray flower length [cm]; X8—number of ray flowers per flower head; X9—disc flower length [cm]; X10—number of disc flowers per flower head; X11—flower head diameter [cm]; and X12—number of capitula per plant. The morphometric measurements are presented in Table S1. Descriptive statistics of the 12 characteristics was performed in the R programming language and presented in Table S2.

3.3. Chemicals and Reagents

Acetonitrile and formic acid for LC-MS, and methanol of analytical grade, were purchased from Merck (Merck, Bulgaria). The reference standards used for compound identification were bought from Phytolab (Vestenbergsgreuth, Germany).

3.4. Sample Extraction and Sample Preparation

Air-dried powdered aerial parts (5 g, combined plant material belonging to the same species) were extracted with 80% MeOH (1:20 w/v) by sonication (100 kHz) for 15 min (×2) at room temperature. Then, the extracts were concentrated in vacuo and lyophilized to yield crude extracts: S. hercynicus—0.74 g, S. ovatus—0.71 g, S. rupestris—1.02 g, J. pancicii—0.95 g, and J. maritima—0.96 g.

3.5. Ultra-High-Performance Liquid Chromatography—High Resolution Mass Spectrometry (UHPLC-HRMS)

Elution was achieved on a reversed phase column Kromasil EternityXT C18 (1.8 µm, 2.1 × 100 mm, AkzoNobel, Sweden) column maintained at 40 °C. The binary mobile phase consisted of A: 0.1% formic acid in water and B: 0.1% formic acid in acetonitrile. The run time was 24.5 min. Prior to injection, the mobile phase was held at 50% B for 4.5 min, and then gradually turned at 5% B in 0.5 min. After injection, the % B was gradually turned to 60% B over 15 min, and then held at 60% B for 3 min, increased gradually to 95% B over 3 min, held at 95% B over 2 min, then turned to 50% B in 0.5 min. The retention time of the identified compounds ranged between 1.74 and 9.60 min. The flow rate and the injection volume were set to 300 µL/min and 1 µL, respectively. The effluents were connected on-line with a Q Exactive Plus Orbitrap mass spectrometer (ThermoFisher Scientific) where the compounds were detected. Data were processed with Xcalibur software 4.2 (ThermoFisher Scientific, Waltham, MO, USA).
Mass spectrometric analyses were carried out on a Q Exactive Plus Mass Spectrometer (ThermoFisher Scientific) equipped with a heated electrospray ionization (HESI-II) probe (ThermoFisher Scientific). The tune parameters were as follows: spray voltage 3.5 kV; sheath gas flow rate 38; auxiliary gas flow rate 12; spare gas flow rate 0; capillary temperature 320 °C; probe heater temperature 320 °C, and S-lens RF level 50. Acquisition was acquired at Full-scan MS and Data Dependent-MS2 modes. Full-scan spectra over the m/z range 100 to 1000 were acquired in the negative ionization mode at a resolution of 70,000. Other instrument parameters for the Full MS mode were set as follows: AGC target 1e6, maximum ion time 80 ms, number of scan ranges 1. For DD-MS2 mode, instrument parameters were as follows: microscans 1, resolution 17,500, AGC target 1e5, maximum ion time 50ms, MSX count 1, isolation window 1.0 m/z, stepped collision energy (NCE) 10, 30, and 60. Data acquisition and processing were carried out with Xcalibur 4.2 software (ThermoFisher Scientific).

3.6. File Conversions and Data Analysis

After the .raw (ThermoFisher Scientific) mass spectrometric files were obtained, they were converted to .ms1 (MS1 data) and .mgf (MS2 data) files using MSConvertGUI 3.1 (ProteoWizard). Then, the .ms1 and .mgf files were imported to RStudio (2021, Build 382) and further manipulated under the R programming language (version 4.2.1, 23 June 2022, “Funny-Looking Kid”). The MS2 spectra were screened for the presence of the available target (hydroxybenzoic acid derivatives and flavonoids) standard compounds. The screening was achieved by selecting spectra based on the following criteria: m/z error of the molecular ion < 15 ppm (minimum 0.0010 Da), retention time error < 2% (minimum 0.05 min, maximum 0.15 min), number of fragment ions match > 2/3, and error of the percentage intensity of matched fragment ion < 15. Similar MS2 scans found in the same chromatographic peak were grouped, i.e., the spectra were summed, the m/z were adjusted by weight averaging:
( m / z ) a v g = ∑ i = 1 N i n t i × ( m / z ) i N  
where ( m / z ) a v g is the recalculated m/z value, ( m / z ) i and i n t i are the m/z and the intensity of the ith fragment ion, respectively. The areas under the curve (AUC) of the identified compounds were calculated and normalized from 0 to 100.
Data analysis was performed in the R programming language (R version 4.2.1., 23 June 2022, Funny-Looking Kid), operated under the RStudio environment (2022.07.2 Build 576). R packages used include: “MASS” [36], “klaR” [37], “caret” [38], “leaps” [39], “factoextra” [40], “cluster” [41], “lpSolve” [42], “DescTools” [43], “pheatmap” [44], and “arsenal” [45]. Distance matrices were generated using the “Euclidean” method, and hierarchical clustering was performed using the “ward.D2” method. The complete R code used for morphometric analysis is presented in the supplementary material.

4. Conclusions

Herein, a chemophenetic study of three Senecio (S. hercynicus, S. ovatus, and S. rupestris) and two Jacobaea species (J. pancicii and J. maritima) is presented. From the collected morphometric data, describing 12 parameters, a distinguishment of species by genera was performed using linear discriminant analysis (LDA). Among the studied species, S. hercynicus and S. ovatus presented the greatest similarity, and hence, their formed clusters were the closest. Even though no overlap in the LDA analysis was observed between the Jacoboea and Senecio species, J. pancicii and J. maritima did not demonstrate likeness. A phytochemical analysis by UHPLC-Orbitrap-HRMS revealed a total of 46 hydroxybenzoic, hydroxycinnamic, and acylquinic acids and their derivatives, 1 coumarin and 21 flavonoids. Hierarchical and PCA clustering was then applied to the phytochemical data on combined plant material from each species. The data corroborated the similarity of S. hercynicus and S. ovatus, established in the morphometric analysis. The study highlights the similarity/dissimilarity, both morphometric, and in a manner of specialized metabolites, of the selected species belonging to Senecio and Jacobaea genera (Senecioneae).

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants12020390/s1, Table S1: Scaled and unscaled raw morphometric data; Table S2: Descriptive statistics on the morphometric data; Table S3: Selection of a model with n variables; Table S4: Prediction of membership of the test set (n = 15); Table S5: The compounds presented in Figure 3 grouped by the hierarchical clustering; Figure S1: Residual sum of squares (RSS), adjusted R2, Mallow’s Cp, and Bayesian information criterion (BIC) for the standardized morphological data. R code: contains the code written in the R programming language for the analysis of the morphological data.

Author Contributions

Conceptualization: V.B., R.G. and D.Z.-D.; data curation: V.B., Y.V.; formal analysis: Y.V.; funding acquisition: D.Z.-D.; investigation: V.B., R.G. and D.Z.-D.; methodology: R.G., V.B. and Y.V.; project administration: D.Z.-D.; resources: V.B., D.Z.-D.; software: Y.V.; supervision: D.Z.-D.; visualization: Y.V.; writing—original draft preparation: V.B., R.G. and D.Z.-D.; writing—review and editing: Y.V. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Council of Medical Science at the Medical University of Sofia, Bulgaria, grant number 102/04.06.2021, project number 7845/18.11.2020.

Data Availability Statement

The data presented in this study are available in the article or supplementary material. The raw MS files are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Pelser, P.B.; Nordenstam, B.; Kadereit, J.W.; Watson, L.E. An ITS phylogeny of tribe Senecioneae (Asteraceae) and a new delimitation of Senecio L. Taxon 2007, 56, 1077–1104. [Google Scholar] [CrossRef] [Green Version]
  2. Rola, K. Morphometry and distribution of Senecio nemorensis agg. species (Asteraceae) in Poland. Pol. Bot. J. 2014, 59, 37–54. [Google Scholar] [CrossRef] [Green Version]
  3. Galasso, G.; Bartolucci, F. Four new combinations in Jacobaea Mill.(Asteraceae, Senecioneae) for the European flora. Nat. Hist. Sci. 2015, 2, 95–96. [Google Scholar] [CrossRef]
  4. Bog, M.; Elmer, M.; Doppel, M.; Ehrnsberger, H.F.; Beuerle, T.; Heilmann, J.; Oberprieler, C. Phytochemical investigations and food-choice experiments with two mollusc species in three central European Senecio L.(Asteraceae, Senecioneae) species and their hybrids. Chemoecology 2017, 27, 155–169. [Google Scholar] [CrossRef]
  5. Hodalova, I.; Grulich, V.; Marhold, K. A multivariate morphometric study of Senecio paludosus L.(Asteraceae) in Central and Western Europe. Bot. Helv. 2002, 112, 137–152. [Google Scholar]
  6. Podsiedlik, M.; Nowinska, R.; Bednorz, L. A morphometric study on Senecio erucifolius (Asteraceae) from Poland and its taxonomic implications. Acta Soc. Bot. Pol. 2016, 85, 2305. [Google Scholar] [CrossRef]
  7. Abbott, R.; James, J.; Forbes, D.; Comes, H.-P. Hybrid origin of the Oxford Ragwort, Senecio squalidus L: Morphological and allozyme differences between S. squalidus and S. rupestris Waldst. and Kit. Watsonia 2002, 24, 17–30. [Google Scholar]
  8. Fei, D.-Q.; Zhang, Z.-X.; Chen, J.-J.; Gao, K. Eremophilane-type sesquiterpenes from Senecio nemorensis. Planta Med. 2007, 73, 1292–1297. [Google Scholar] [CrossRef]
  9. Yang, Y.; Zhao, L.; Wang, Y.F.; Chang, M.L.; Huo, C.H.; Gu, Y.C.; Shi, Q.W.; Kiyota, H. Chemical and pharmacological research on plants from the genus Senecio. Chem. Biodivers. 2011, 8, 13–72. [Google Scholar] [CrossRef]
  10. Mandić, B.M.; Gođevac, D.M.; Vujisić, L.V.; Trifunović, S.S.; Tesević, V.V.; Vajs, V.V.; Milosavljević, S.M. Semiquinol and phenol compounds from seven Senecio species. Chem. Pap. 2011, 65, 90–92. [Google Scholar] [CrossRef]
  11. Albayrak, S.; Aksoy, A.; Yurtseven, L.; Yaşar, A. A comparative study on phenolic components and biological activity of some Senecio species in Turkey. J. Pharm. Pharmacol. 2014, 66, 1631–1640. [Google Scholar] [CrossRef]
  12. Mohamed, S. Phytochemical and biological study of (Senecio glaucus subsp. coronopifolius)(Maire) c. alexander growing in Egypt. Al-Azhar J. Pharm. Sci. 2015, 52, 283–298. [Google Scholar] [CrossRef]
  13. Bousetla, A.; Keskinkaya, H.B.; Bensouici, C.; Lefahal, M.; Atalar, M.N.; Akkal, S. LC-ESI/MS-phytochemical profiling with antioxidant and antiacetylcholinesterase activities of Algerian Senecio angulatus Lf extracts. Nat. Prod. Res. 2021, 37, 123–129. [Google Scholar] [CrossRef] [PubMed]
  14. Balabanova, V.; Voynikov, Y.; Zengin, G.; Gevrenova, R.; Zheleva-Dimitrova, D. A view on antioxidant and enzyme inhibitory activity of senecio hercynicus herbal drugs. Comptes Rendus L Acad. Bulg. Des. Sci. 2020, 73, 1673–1680. [Google Scholar]
  15. Arab, Y.; SAHIN, B.; CEYLAN, O.; Zellagui, A.; OLMEZ, O.T.; Kucukaydin, S.; Tamfu, A.N.; Ozturk, M.; Gherraf, N. Assessment of in vitro activities and chemical profiling of Senecio hoggariensis growing in Algerian Sahara. Biodiversitas J. Biol. Divers. 2022, 23, 3498–3506. [Google Scholar] [CrossRef]
  16. Shi, B.-J.; Xiong, A.-Z.; Zheng, S.-S.; Chou, G.-X.; Wang, Z.-T. Two new pyrrolizidine alkaloids from Senecio nemorensis. Nat. Prod. Res. 2010, 24, 1897–1901. [Google Scholar] [CrossRef]
  17. Dekić, M.; Radulović, N.; Stojanović, N.; Mladenović, M. Analgesic activity of dehydrofukinone, sesquiterpene ketone from Senecio nemorensis L.(Asteraceae). Facta Univ. Ser. Phys. Chem. Technol. 2018, 16, 119. [Google Scholar]
  18. Tundis, R.; Loizzo, M.; Menichini, F.; Bonesi, M.; Conforti, F.; Statti, G.; Passalacqua, N.; Curini, M. In vitro hypoglycaemic activity of Senecio nemorensis subsp. stabianus Lacaita (Asteraceae). Planta Med. 2009, 75, PH20. [Google Scholar] [CrossRef]
  19. Christov, V.; Simeonov, M.; Velcheva, N.; Karadjova, O.; Atanassov, N.; Ivanova, I.; Evstatieva, L. Pyrrolizidine Alkaloids from Bulgarian Species—Genus Senecio and their Insecticidal Properties. Biotechnol. Biotechnol. Equip. 1997, 11, 53–59. [Google Scholar] [CrossRef] [Green Version]
  20. Vladimirov, V. Asteraceae. Senecio nemorensis L. group, Senecio hercynicus Herborg. In Flora Republicae Bulgaricae; Peev, D., Ed.; Marin Drinov: Sofia, Bulgaria, 2012; Volume XI, pp. 432–434. [Google Scholar]
  21. Christov, V.; Evstatieva, L. Alkaloid profile of Bulgarian species from genus Senecio L. Z. Für Nat. C 2003, 58, 300–302. [Google Scholar] [CrossRef]
  22. Christov, V.; Kostova, N.; Evstatieva, L. 6α-Angeloylplatynecine: A new alkaloid from Senecio nemorensis subsp. fuchsii (CC Gmelin) celak. Nat. Prod. Res. 2005, 19, 389–392. [Google Scholar] [CrossRef]
  23. Güner, A.; Akyıldırım, B.; Alkayış, M.; Çıngay, B.; Kanoğlu, S.; Özkan, A.; Öztekin, M.; Tuğ, G.; Güner, A.; Aslanl, S.; et al. Türkiye Bitkileri Listesi (Damarlı Bitkiler); Nezahat Gökyiğit Botanik Bahçesi ve Flora Araştırmaları Derneği Yayını: Istanbul, Turkey, 2012. [Google Scholar]
  24. Zidorn, C. Plant chemophenetics−A new term for plant chemosystematics/plant chemotaxonomy in the macro-molecular era. Phytochemistry 2019, 163, 147–148. [Google Scholar] [CrossRef] [PubMed]
  25. Dewick, P.M. Medicinal Natural Products: A Biosynthetic Approach; John Wiley & Sons: Hoboken, NJ, USA, 2002. [Google Scholar]
  26. Hodálová, I. Taxonomy of the Senecio nemorensis group (Compositae) in the Carpathians. Biologia 1999, 54, 395–404. [Google Scholar]
  27. Oberprieler, C.; Barth, A.; Schwarz, S.; Heilmann, J. Morphological and phytochemical variation, genetic structure and phenology in an introgressive hybrid swarm of Senecio hercynicus and S. ovatus (Compositae, Senecioneae). Plant Syst. Evol. 2010, 286, 153–166. [Google Scholar] [CrossRef]
  28. Oberprieler, C.; Hartl, S.; Schauer, K.; Meister, J.; Heilmann, J. Morphological, phytochemical and genetic variation in mixed stands and a hybrid swarm of Senecio germanicus and S. ovatus (Compositae, Senecioneae). Plant Syst. Evol. 2011, 293, 177–191. [Google Scholar] [CrossRef]
  29. Gareth, J.; Daniela, W.; Trevor, H.; Robert, T. An Introduction to Statistical Learning: With Applications in R; Spinger: Berlin/Heidelberg, Germany, 2013. [Google Scholar]
  30. Denis, D.J. Univariate, Bivariate, and Multivariate Statistics Using R: Quantitative Tools for Data Analysis and Data Science; John Wiley & Sons: Hoboken, NJ, USA, 2020. [Google Scholar]
  31. Barkley, T.M. Senecio. In North American Flora, Series II; AbeBooks: Victoria, BC, Canada, 1978; Volume 10, pp. 50–139. [Google Scholar]
  32. Gevrenova, R.; Zheleva-Dimitrova, D.; Balabanova, V.; Voynikov, Y.; Sinan, K.I.; Mahomoodally, M.F.; Zengin, G. Integrated phytochemistry, bio-functional potential and multivariate analysis of Tanacetum macrophyllum (Waldst. & Kit.) Sch. Bip. and Telekia speciosa (Schreb.) Baumg.(Asteraceae). Ind. Crop. Prod. 2020, 155, 112817. [Google Scholar]
  33. Gevrenova, R.; Zengin, G.; Sinan, K.I.; Yıldıztugay, E.; Zheleva-Dimitrova, D.; Picot-Allain, C.; Mahomoodally, M.F.; Imran, M.; Dall’Acqua, S. UHPLC-MS Characterization and biological insights of different solvent extracts of two Achillea species (A. aleppica and A. santolinoides) from Turkey. Antioxidants 2021, 10, 1180. [Google Scholar] [CrossRef]
  34. Clifford, M.N.; Knight, S.; Kuhnert, N. Discriminating between the six isomers of dicaffeoylquinic acid by LC-MS n. J. Agric. Food Chem. 2005, 53, 3821–3832. [Google Scholar] [CrossRef]
  35. Zheleva-Dimitrova, D.; Zengin, G.; Balabanova, V.; Voynikov, Y.; Lozanov, V.; Lazarova, I.; Gevrenova, R. Chemical characterization with in vitro biological activities of Gypsophila species. J. Pharm. Biomed. Anal. 2018, 155, 56–69. [Google Scholar] [CrossRef]
  36. Venables, W.; Ripley, B.D. Statistics Complements to Modern Applied Statistics with S, 4th ed.; Springer: Berlin/Heidelberg, Germany, 2002. [Google Scholar]
  37. Weihs, C.; Ligges, U.; Luebke, K.; Raabe, N. klaR analyzing German business cycles. In Data Analysis and Decision Support; Springer: Berlin/Heidelberg, Germany, 2005; pp. 335–343. [Google Scholar]
  38. Kuhn, M. Building predictive models in R using the caret package. J. Stat. Softw. 2008, 28, 1–26. [Google Scholar] [CrossRef]
  39. Lumley, T. Package ‘Leaps’. Regression Subset Selection Based on Fortran Code by Alan Miller. 2013. Available online: https://cran.microsoft.com/snapshot/2016-08-29/web/packages/leaps/leaps.pdf (accessed on 11 November 2022).
  40. Kassambara, A.; Mundt, F. Package ‘Factoextra’. Extract and Visualize the Results of Multivariate Data Analyses. 2017, 76. Available online: https://cran.microsoft.com/snapshot/2016-11-30/web/packages/factoextra/factoextra.pdf (accessed on 11 November 2022).
  41. Maechler, M.; Rousseeuw, P.; Struyf, A.; Hubert, M.; Hornik, K. Cluster: Cluster analysis basics and extensions. R Package Version 2012, 1, 56. [Google Scholar]
  42. Berkelaar, M. Package ‘lpSolve’. 2015. Available online: https://cran.uib.no/web/packages/lpSolve/lpSolve.pdf (accessed on 11 November 2022).
  43. Signorell, A.; Aho, K.; Alfons, A.; Anderegg, N.; Aragon, T.; Arppe, A.; Baddeley, A.; Barton, K.; Bolker, B.; Borchers, H. DescTools: Tools for descriptive statistics. R Package Version 0.99 2019, 28, 17. [Google Scholar]
  44. Kolde, R.; Kolde, M.R. Package ‘Pheatmap’. R Package. 2018. Available online: https://cran.microsoft.com/snapshot/2018-06-22/web/packages/pheatmap/pheatmap.pdf (accessed on 11 November 2022).
  45. Heinzen, E.; Sinnwell, J.; Atkinson, E.; Gunderson, T.; Votruba, P.; Dougherty, G.; Lennon, R.; Hanson, A.; Goergen, K.; Lundt, E. An Arsenal of “R” Functions for Large-Scale Statistical Summaries: R Package Arsenal Version 3.3.0; R Foundation for Statistical Computing: Vienna, Austria, 2019. [Google Scholar]
Plants 12 00390 g001 550
Figure 1. Correlogram of the 12 morphometric characters.
Figure 1. Correlogram of the 12 morphometric characters.
Plants 12 00390 g001
Plants 12 00390 g002a 550Plants 12 00390 g002b 550
Figure 2. Discriminatory power of LD1 and LD2 functions. (A)—one-dimensional (1D) and (B)—two-dimensional (2D) discrimination.
Figure 2. Discriminatory power of LD1 and LD2 functions. (A)—one-dimensional (1D) and (B)—two-dimensional (2D) discrimination.
Plants 12 00390 g002aPlants 12 00390 g002b
Plants 12 00390 g003 550
Figure 3. Heatmap of the normalized AUC values, from 0 (in case the compound was not detected) to 100, of the identified compounds (columns) by species (rows).
Figure 3. Heatmap of the normalized AUC values, from 0 (in case the compound was not detected) to 100, of the identified compounds (columns) by species (rows).
Plants 12 00390 g003
Plants 12 00390 g004 550
Figure 4. (A): Heatmap of the Euclidean distance using the normalized (0 to 100) AUC of identified compounds. In case a compound was not detected in an extract, the AUC for that compound was set to 0; (B): Principal component analysis (PCA) (cos2—quality of representation).
Figure 4. (A): Heatmap of the Euclidean distance using the normalized (0 to 100) AUC of identified compounds. In case a compound was not detected in an extract, the AUC for that compound was set to 0; (B): Principal component analysis (PCA) (cos2—quality of representation).
Plants 12 00390 g004
Table
Table 1. Specialized metabolites identified by UHPLC-HRMS. From a total of 68 annotated substances, 24 were identified by a reference standard (marked with *).
Table 1. Specialized metabolites identified by UHPLC-HRMS. From a total of 68 annotated substances, 24 were identified by a reference standard (marked with *).
№Annotated CompoundsMolecular FormulaExact Mass
[M−H]−		MS2tR
(Min)		Distribution
Hydroxybenzoic, Hydroxycinnamic and Acylquinic Acids, Their Derivatives and Coumarin
1protocatechuic acid-O-hexosideC13H16O9315.0722315.0726 (100), 153.0182 (29.5), 152.0104 (60.9), 109.0284 (10.1)1.74A, B, C, D, E
2vanillic acid 4-O-hexosideC14H18O9329.0878329.0885 (1.8), 167.034 (100), 152.0103 (23), 123.0438 (14.3), 108.0202 (37.8)1.81A, B, C, E
3syringic acid *C9H10O5197.0456197.0449 (16.5), 182.0211 (3.2), 153.0549 (8.9), 138.0314 (3.3), 123.0437 (58.3)1.76C
4vanillic acid *C8H8O4167.0350167.0339 (31.1), 152.0103 (100), 123.0438 (32.1), 108.0202 (52.9), 95.0486 (8)1.82A, B, C, D, E
5protocatechuic acid *C7H6O4153.0193153.0182 (15.2), 109.0281 (100), 91.0173 (1.2), 81.033 (1.4)2.04A, B, C, D, E
6p-hydroxyphenylacetic acid-O-hexosideC14H18O8313.0929313.0923 (13), 151.0389 (100), 133.0284 (0.2), 123.0075 (0.8), 109.0281 (4.2)3.00A, B, C
7gluconic acid-O-hexosideC15H18O10357.0827357.083 (100), 195.0293 (10.8), 177.0183 (8), 151.039 (71.8)2.25C
8syringic acid 4-O-hexosideC15H20O10359.0984359.0985 (8), 197.0448 (100), 182.0212 (21.7), 153.0546 (16.1), 138.031 (29.3), 123.0074 (33.1)2.27A, B, C, D, E
9neochlorogenic acid *C16H18O9353.0878353.0882 (46.1), 191.0553 (100), 179.0341 (68.1), 173.0444 (4.1), 161.0235 (5.9), 135.0439 (54.4), 127.0385 (0.9), 111.0438 (0.7), 93.0329 (3.7), 85.0279 (8.5)2.37A, B, C, D, E
10caffeic acid-O-hexosideC15H18O9341.0878341.0884 (2.2), 179.034 (2.9), 135.0438 (100), 107.0488 (0.7)2.54A, B, C, D, E
114-hydroxybenzoic acid-O-hexosideC13H16O8299.0773299.0775 (13.7), 137.0231 (100), 93.033 (0.2)2.46A, B, C, E
12esculetin-O-hexosideC15H16O9339.0722339.0721 (10.6), 177.0184 (100), 149.0233 (0.9), 133.0282 (8), 105.0331 (3.3), 89.0381 (2.4)2.72A, B, C, D, E
134-hydroxybenzoic acidC7H6O3137.0244137.0232 (100), 108.0203 (11.2), 93.0333 (3.3)2.84A, B, C, D, E
14ferulic acid *C10H10O4193.0506193.05 (100), 178.0264 (74.8), 163.0391 (34.4), 149.0598 (38), 134.036 (82.5)2.96A, B, C
15ferulic acid-O-hexosideC16H20O9355.1035355.1048 (1), 193.0499 (100), 178.0263 (10.9), 149.0596 (21.4), 134.036 (62.1)2.96A, B, C
16gentisic acid *C7H6O4153.0193153.0182 (46.7), 123.0074 (20.8), 109.0283 (40.6), 81.0331 (5.4)2.98A, B, C, D
174-hydroxybenzoic acid-O-hexoside isomerC13H16O8299.0773299.0783 (1.3), 137.0231 (100), 93.033 (50.8)3.00A, B, C
183-p-coumaroylquinic acidC16H18O8337.1500191.0554 (19.6), 163.039 (100), 161.0443 (4.2), 119.0488 (23.7)3.04C
19caffeic acid-O-hexosideC15H18O9341.0878341.088 (26.8), 179.034 (100), 135.0438 (77), 107.0486 (0.8)3.07A, B, C, D, E
20quinic acidC7H12O6191.0561191.0553 (100), 173.0446 (2), 155.0338 (0.2), 127.0388 (4.3), 111.0437 (1.9), 93.0331 (6.4), 85.0279 (18.1)3.19A, B, C, D, E
21chlorogenic acidC16H18O9353.0878353.0881 (3.9), 191.0553 (100), 179.0343 (1.1), 173.0449 (0.4), 161.0232 (1.6), 135.0439 (0.5), 127.0386 (1.3), 111.0433 (0.3), 93.033 (2.2), 85.0279 (7.2)3.19A, B, C, D, E
22caffeic acid-O-hexoside isomer IC15H18O9341.0878341.0881 (9.5), 179.034 (100), 135.0438 (60.8), 107.049 (0.6)3.27A, B, C, D, E
234-caffeoylquinic acidC16H18O9353.0878353.0882 (32.1), 191.0554 (97.5), 179.0341 (72.6), 173.0446 (100), 135.0439 (56.3), 127.0387 (1.8), 111.0435 (3.3), 93.0331 (22), 85.028 (11.3)3.37A, B, C, D, E
24p-hydroxyphenylacetic acidC8H8O3151.0401151.0389 (100), 136.0154 (2), 123.0074 (4.2), 109.028 (15)3.47C, E
25coumaric acid-O-hexosideC15H18O8325.0929325.0923 (1.7), 163.039 (100), 145.0284 (3.5), 119.0488 (92.1), 93.0333 (0.8)3.33A, B, C, D, E
26p-coumaric acid *C9H8O3163.0401163.0389 (6.7), 135.0438 (0.7), 119.0488 (100)3.33A, B, C, D, E
27caffeic acid *C9H8O4179.0350179.0341 (20.5), 135.0438 (100), 117.0332 (0.7), 107.0489 (1.4)3.53A, B, C, D, E
28caffeic acid-O-hexoside isomer IIC15H18O9341.0878341.088 (24.5), 179.0341 (100), 135.0439 (85.6), 107.0489 (0.5)3.79B, C, D, E
295-p-coumaroylquinic acidC16H18O8337.0929337.0933 (8.7), 191.0554 (100), 173.0449 (6), 163.0389 (5.7), 127.0391 (1), 119.0489 (4.8), 111.0437 (1.9), 93.033 (17.2), 85.028 (4.9)3.95A, B, C, D, E
303-hydroxy-dihydrocaffeoyl-5-caffeoylquinic acidC25H26O13533.1301533.1306 (100), 191.0554 (83.4), 173.0447 (10.1), 161.0596 (3.2), 127.0387 (3.3), 93.033 (17.8), 85.028 (11.8)3.09A, B, C, D, E
31isoferulic acidC10H10O4193.0506193.0499 (100), 178.0265 (0.8), 163.0391 (41.6), 149.0597 (18.8), 135.0439 (38.8)4.10C
32syiringaldehideC9H10O4181.0506181.0497 (15.2), 166.0261 (100), 151.0025 (58.4), 123.0074 (15.7)4.22C
33acetoxy-hydroxyacetophenone-O-hexosideC16H20O9355.1035355.1039 (13.7), 193.0494 (1.2), 151.0389 (100), 123.0076 (0.9), 109.0281 (4.4)4.27C
34taraxafolin B-(caffeoyl)-hexosideC26H28O16595.1305595.1308 (100), 341.0883 (25.4), 253.0353 (23.5), 235.0245 (3.5), 209.0446 (1.4), 191.0341 (31.1), 179.0341 (93.7), 165.0545 (16.4), 135.0438 (56)4.41C
355-feruoylquinic acidC17H20O9367.1035367.1038 (15.4), 191.0554 (100), 173.0445 (10.5), 134.0359 (13.1), 111.0437 (3.8), 93.0331 (25.5), 85.028 (5.1)4.42A, B, C, E
36m-coumaric acid *C9H8O3163.0401163.039 (7.6), 135.0439 (0.5), 119.0489 (100)4.56A, B, C, E
373,4-dicaffeoylquinic acid *C25H24O12515.1195515.1198 (100), 353.0881 (15), 335.0773 (5.3), 203.0344 (0.5), 191.0555 (29.1), 179.0341 (53), 173.0446 (58.7), 161.0233 (17), 135.0439 (53.1), 127.0386 (2.2), 111.0437 (3.6), 93.0331 (16.8), 85.028 (3.7)5.69A, B, C, D, E
383,5-dicaffeoylquinic acid *C25H24O12515.1195515.1202 (13.5), 353.0881 (100), 191.0554 (91.3), 179.0341 (49.4), 173.0443 (3.7), 161.0234 (4.2), 135.0439 (55.8), 111.0437 (1.3), 93.0332 (4.2), 85.028 (9.8)5.86A, B, C, D, E
391,5-dicaffeoylquinic acid *C25H24O12515.1195515.1199 (25.5), 353.088 (92.4), 335.0777 (1.9), 191.0554 (100), 179.0341 (53.3), 173.0446 (8.7), 135.0439 (65), 127.0387 (4.2), 111.0437 (2.1), 93.0332 (6.5), 85.028 (10.2)6.02A, B, C, D, E
404,5-dicaffeoylquinic acid *C25H24O12515.1195515.1197 (100), 353.0883 (72.3), 203.0341 (1.5), 191.0553 (38.9), 179.0341 (66.6), 173.0446 (98.1), 135.0439 (69.5), 111.0435 (5.2), 93.033 (30.8), 85.0279 (8.3)6.22A, B, C, D, E
41shikimic acidC7H10O5173.0456173.0444 (100), 111.0437 (10), 93.033 (68.4)6.22E
42salicilic acid *C7H6O3137.0244137.023 (8.7), 93.0331 (100)6.29A, C
433-p-coumaroyl-5-caffeoylquinic acidC25H24O11499.1246499.1238 (16.4), 353.0901 (1.5), 337.0933 (73.9), 335.0797 (1.7), 191.0553 (12.4), 173.0449 (7.9), 163.039 (100), 135.0441 (4.2), 119.0489 (34.4), 93.0334 (4.4)6.51B, C, E
443-caffeoyl-5-p-coumaroylquinic acidC25H24O11499.1246499.125 (26.1), 353.0882 (64.8), 337.0938 (17.5), 191.0554 (100), 179.0341 (34.5), 173.0446 (6.9), 163.0389 (2.9), 161.0231 (5.5), 135.0439 (36.8), 119.0488 (2.8), 111.0436 (1.4), 93.0331 (10.5), 85.0279 (7.1)6.57B, E
453-feruoyl-5-caffeoylquinic acidC26H26O12529.1352529.1296 (2.3), 367.1036 (99.2), 335.078 (1.1), 193.0499 (100), 191.0557 (3), 173.0443 (6.9), 161.0235 (2), 134.036 (68.5), 93.0331 (3.2)6.82A, B, C, E
463-caffeoyl-5-feruoylquinic acidC26H26O12529.1352529.1353 (41.1), 367.1037 (0.7), 353.0882 (43.5), 335.0794 (0.8), 191.0555 (100), 179.0342 (40.7), 173.0446 (11.5), 161.0238 (5.4), 135.0439 (37.7), 134.0361 (12.9), 127.0383 (1.3), 111.0437 (1.3), 93.0331 (15.5), 85.028 (7.5)6.89A, B, C, E
473,4,5-tricaffeoylquinic acidC34H30O15677.1512677.1517 (100), 515.1202 (46.2), 353.0883 (47.1), 335.0783 (13.9), 191.0554 (45.2), 179.0342 (65.2), 173.0446 (90.2), 161.0234 (24.1), 135.0439 (72.1), 111.0436 (5.6), 93.0331 (21.7)7.77B, C, E
Flavonoids
486,8-di-C-hexosyl-naringeninC27H32O15595.1669595.1677 (100), 475.1247 (3.8), 457.1138 (1.3), 427.1055 (1.2), 415.1037 (11.6), 385.0933 (36.1), 355.0822 (38.9), 343.0825 (3.9), 313.0722 (6.1), 119.0489 (15.5), 107.0123 (3.5), 3.63D, E
49kaempferol-O-dihexosideC27H30O16609.1461609.1462 (100), 447.0931 (24.7), 285.0405 (50.3), 284.0325 (7.6), 255.0300 (33.4), 227.0347 (5.7), 211.0391 (2.2)3.81C
50isorhamnetin-O-dihexosideC28H32O17639.1567639.1575 (100), 477.1039 (34.6), 315.0514 (56.7), 300.0275 (11.8), 314.0429 (12.6), 285.0408 (6.4), 270.0172 (20.8), 242.0218 (14.0), 227.0344 (0.7), 151.0027 (5.5), 107.0124 (1.3)4.04C
51rutin *C27H30O16609.1461609.1469 (100), 301.0352 (39.6), 300.0279 (64.0), 271.0249 (29.6), 255.0298 (14.6), 243.0296 (6.4), 227.0345 (2.2), 178.9975 (3.4), 163.0015 (0.8), 151.0025 (5.6), 121.0286 (0.9), 107.0125 (1.0)5.07A, B, C, D, E
52isorhamnetin-O-pentosylhexosideC27H30O16609.1461609.1464 (100), 315.0504 (19.9), 314.0436 (85.1), 299.0196 (18.4), 271.0252 (22.0), 243.0297 (20.1), 227.0350 (5.1), 178.9978 (1.3), 151.0023 (34.0)5.16A, B, C, D, E
53isoquercitrin *C21H20O12463.0882463.0887 (100), 301.0352 (44.4), 300.0278 (69.8), 271.0250 (46.2), 255.0300 (20.0), 243.0298 (11.0), 227.0346 (4.6), 211.0389 (1.4), 178.9976 (4.4), 151.0026 (7.8), 121.0280 (1.5), 107.0123 (2.8)5.27A, B, C, D, E
54quercetin 7-O-hexuronideC21H18O13477.0675477.0671 (47.4), 301.0356 (100), 283.0245 (2.1), 255.0302 (3.1), 227.0343 (2.0), 211.0396 (1.8), 178.9976 (9.9), 163.0028 (2.4), 151.0025 (20.2), 121.0281 (6.3), 107.0124 (8.9)5.22A, B, C, D
55luteolin-O-hexuronideC21H18O12461.0726461.0730 (39.5), 285.0406 (100), 257.0457 (4.6), 229.0505 (6.0), 213.0544 (2.0), 175.0242 (5.8), 151.0023 (0.9), 107.0125 (2.5)5.84A, B
56kaempferol 7-O-rutinoside *C27H30O15593.1512593.1516 (100), 285.0405 (90.5), 255.0298 (42.9), 227.0346 (31.3), 163.0025 (1.1)5.62A, B, D, E
57quercetin 3-O-acetylhexosideC23H22O13505.0988505.0996 (100), 463.0891 (0.8), 301.0351 (34.1), 300.0278 (88.9), 271.0251 (42.8), 255.0299 (21.5), 243.0297 (11.7), 227.0343 (3.1), 178.9976 (2.5), 163.0027 (2.8), 151.0024 (7.8), 121.0283 (1.1), 107.0124 (2.4)5.61A, B, C, D
58kaempferol-3-O-glucoside *C21H20O11447.0933447.0938 (100), 285.0401 (21.4), 284.0329 (51.3), 255.0300(38.4), 227.0347 (40.6), 151.0024 (2.7), 5.87B, C
59isorhamnetin 3-O-glucoside *C22H22O12477.1039477.1041 (100), 315.0495 (9.7), 314.0437 (51.2), 299.0213 (3.2), 271.0251 (18.8), 257.0460 (3.9), 243.0299 (22.3), 227.0341 (2.9), 215.0340 (3.7), 178.9972 (0.6), 151.0021 (1.7)6.02A, B, C, D, E
60isorhamnetin-O-hexuronideC22H20O13491.0831491.0836 (48.3), 315.0515 (100), 300.0278 (29.1), 271.0251 24.7), 255.0299 (10.7), 227.0347 (1.8), 175.0238 (5.7), 151.0029 (2.6), 107.0122 (0.8)6.09A, B
61quercetin-3-O-rhamnoside (quercitrin) *C21H20O11447.0933447.0936 (100), 301.0355 (81.9), 300.0278 (22.24), 271.0248 (1.7), 255.0298 (2.0), 227.0352 (1.6), 178.9974 (2.6), 151.0025 (40.6), 121.0281 (8.9), 107.0124 (15.2)6.76B
62luteolin *C15H10O6285.0405285.0406 (100), 175.0392 (3.0), 151.0024 (4.7), 133.0282 (22.8), 107.0124 (3.7)7.56C
63Quercetin *C15H10O7301.0354301.0356 (100), 273.0411 (3.3), 257.0469 (1.8), 245.0444 (0.8), 229.0500 (0.6), 215.1699 (0.3), 178.9977 (21.3), 151.0024 (49.4), 121.0281 (14.2), 107.0123 (12.9)7.61B, C, D, E
64apigenin *C15H10O5269.0456269.0458 (100), 225.0549(1.9), 201.0550 (0.9), 151.0025 (5.7), 121.0282 (1.3), 117.0332 (18.4), 107.0124 (5.3)8.62C
65kaempferol *C15H10O6285.0405285.0406 (100), 257.0465 (0.8), 243.0298 (0.2), 227.0353 (0.9), 211.0397 (1.3), 151.0025 (1.3), 107.0123 (1.2)8.85C, E
66chrysoeriol *C16H12O6299.0561299.0564 (63.8), 284.0329 (100), 255.0300 (46.5), 227.0344 (38.2), 211.0394 (1.5), 151.0024 (0.3)9.32C
67cirsiliolC17H14O7329.0667329.0672 (100), 314.0441 (43.6), 299.0199(89.6), 271.0248 (55.9), 243.0296 (6.5), 227.0345 (3.4), 211.1333 (6.8) 9.60C
68cirsimaritinC17H14O6313.0718313.0721 (100), 298.0483 (65.2), 283.0251 (52.5), 255.0298 (64.1), 227.0341 (4.4), 211.0396 (5.7)12.27C
* identified by reference standards. A—S. hercynicus; B—S. ovatus; C—S. rupestris; D—J. pancicii, E—J. maritima.
Table
Table 2. Normalized (by rows) AUC values of the identified specialized natural compounds found in at least two, out of all five, studied species. The cells show the normalized AUC, from 0 (in case the compound was not detected in the extract) to 100, by rows.
Table 2. Normalized (by rows) AUC values of the identified specialized natural compounds found in at least two, out of all five, studied species. The cells show the normalized AUC, from 0 (in case the compound was not detected in the extract) to 100, by rows.
№CompoundsSpecies
J.maritimaJ.panciciS.hercynicusS.ovatusS.rupestris
1protocatechuic acid-O-hexoside12.6415.2755.3238.45100
2vanillic acid 4-O-hexoside100056.87052.35
4vanillic acid0066.4784.99100
5protocatechuic acid68.0310043.9351.548.22
6p-hydroxyphenylacetic acid-O-hexoside0036.0568.05100
8syringic acid 4-O-hexoside24.1410017.3251.6933.42
9neochlorogenic acid28.061001.423.216.19
10caffeic acid-O-hexoside1.869.8234.2423.69100
114-hydroxybenzoic acid-O-hexoside15.24032.150.1100
12esculetin-O-hexoside1219.4445.4810024.71
134-hydroxybenzoic acid71.0242.460.2546.55100
15ferulic acid-O-hexoside0018.0370.66100
16gentisic acid017.775.993.02100
174-hydroxybenzoic acid-O-hexoside isomer0025.9778.36100
19caffeic acid-O-hexoside13.081.244.6114.54100
20quinic acid10093.5324.2475.970.84
21chlorogenic acida10094.4728.4777.3271.97
22caffeic acid-O-hexoside isomer I18.6238.5348.9244.77100
234-caffeoylquinic acid85.41001.784.37.54
24p-hydroxyphenylacetic acid10000023.6
25coumaric acid-O-hexoside24.0870.7981.3110012.01
26p-coumaric acid25.0873.4983.3810012.42
27caffeic acid17.1612.3833.5537.96100
28caffeic acid-O-hexoside isomer II4.283.58012.49100
295-p-coumaroylquinic acid10031.126.1363.1218.11
303-hydroxy-dihydroxy-5-caffeoylquinic acid010040.0586.5831.91
355-feruoylquinic acid3.74040.781008.11
36m-coumaric acid 68.8049.9241.24100
373,4-dicaffeoylquinic acid1001.723.321.573.38
383,5-dicaffeoylquinic acid10051.549.2159.8295.36
391,5-dicaffeoylquinic acid10021.849.5327.3445.34
404,5-dicaffeoylquinic acid10031.874.1414.5833.42
42salicilic acid16.54042.1140.7100
433-p-coumaroyl-5-caffeoylquinic acid1000080.5359.01
443-caffeoyl-5-p-coumaroylquinic acid1002.3305.894.4
453-feruoyl-5-caffeoylquinic acid17.99016.9910013.26
463-caffeoyl-5-feruoylquinic acid100014.9275.240
473,4,5-tricaffeoylquinic acid100003.957.03
486, 8-di-C-hexosyl-naringenin37.7100000
51rutin40.391001.6247.20.13
52isorhamnetin-O-pentosylhexoside12.0365.5401000.64
53isoquercitrin10022.061.1981.8729.95
54quercetin 7-O-hexuronide06.9146.71000.98
55luteolin-O-hexuronide0035.071000
56kaempferol 7-O-rutinoside39.271001.8958.250
57quercetin 3-O-acetylhexoside01.071.6685.28100
58kaempferol-3-O-glucoside00063.53100
59isorhamnetin 3-O-glucoside1007.50.736.2840.77
60isorhamnetin-O-hexuronide0034.341000
63quercetin10025.2027.1917.63
65kaempferol10000083.75
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Voynikov, Y.; Balabanova, V.; Gevrenova, R.; Zheleva-Dimitrova, D. Chemophenetic Approach to Selected Senecioneae Species, Combining Morphometric and UHPLC-HRMS Analyses. Plants 2023, 12, 390. https://doi.org/10.3390/plants12020390

AMA Style

Voynikov Y, Balabanova V, Gevrenova R, Zheleva-Dimitrova D. Chemophenetic Approach to Selected Senecioneae Species, Combining Morphometric and UHPLC-HRMS Analyses. Plants. 2023; 12(2):390. https://doi.org/10.3390/plants12020390

Chicago/Turabian Style

Voynikov, Yulian, Vessela Balabanova, Reneta Gevrenova, and Dimitrina Zheleva-Dimitrova. 2023. "Chemophenetic Approach to Selected Senecioneae Species, Combining Morphometric and UHPLC-HRMS Analyses" Plants 12, no. 2: 390. https://doi.org/10.3390/plants12020390

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop