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. 2021 Jan 9;10(1):112. doi: 10.3390/cells10010112

Metabolomics and DNA-Based Authentication of Two Traditional Asian Medicinal and Aromatic Species of Salvia subg. Perovskia

Monika Bielecka 1,*, Bartosz Pencakowski 1, Marta Stafiniak 1, Klemens Jakubowski 2, Mehdi Rahimmalek 2,3, Shima Gharibi 4, Adam Matkowski 2,5, Sylwester Ślusarczyk 5
PMCID: PMC7826587  PMID: 33435339

Abstract

Subgenus Perovskia of the extended genus of Salvia comprises several Central Asian medicinal and aromatic species, of which S. yangii and S. abrotanoides are the most widespread. These plants are cultivated in Europe as robust ornamentals, and several cultivars are available. However, their medicinal potential remains underutilized because of limited information about their phytochemical and genetic diversity. Thus, we combined an ultra-high performance liquid chromatography quadrupole time of flight mass spectrometry (UHPLC-QTOF-MS) based metabolomics with DNA barcoding approach based on trnH-psbA and ITS2 barcodes to clarify the relationships between these two taxa. Metabolomic analysis demonstrated that aerial parts are more similar than roots and none of the major compounds stand out as distinct. Sugiol in S. yangii leaves and carnosic acid quinone in S. abrotanoides were mostly responsible for their chemical differentiation, whereas in roots the distinction was supported by the presence of five norditerpenoids in S. yangii and two flavonoids and one norditerpenoid in S. abrotanoides. To verify the metabolomics-based differentiation, we performed DNA authentication that revealed S. yangii and S. abrotanoides to be very closely related but separate species. We demonstrated that DNA barcoding coupled with parallel LC-MS profiling constitutes a powerful tool in identification of taxonomically close Salvia species.

Keywords: phenolic compounds, diterpenoids, tanshinones, Salvia abrotanoides, Salvia yangii, subgenus Perovskia, DNA barcoding

1. Introduction

The subgenus Perovskia Kar. comprises several species with an ethnobotanical value and medicinal potential. These shrubby, aromatic plants are widespread throughout Central Asia, in an area that includes Iran, Pakistan, Afghanistan, Turkmenistan, Uzbekistan, and Tibet. The ranges of most of the accepted species are limited to the arid montane regions in Central Asia, but two of them, Salvia abrotanoides Karel. (previously known as Perovskia abrotanoides Kar.) and Salvia yangii B.T. Drew (formerly Perovskia atriplicifolia Benth.), are distributed over vast areas from Western Iran and Pakistan and as far as Tibet and Xinjiang, in China [1,2,3,4,5,6,7,8,9].

There are a lot of discrepancies regarding the taxonomy of the subgenus Perovskia. According to primary classification based on flower morphology, species belonging to Perovskia together with four other genera, Dorystaechas, Meriandra, Rosmarinus, and Zhumeria, have previously been considered closely related to Salvia and were treated together as part of the subtribe Salviinae in the most recent and comprehensive conspectus of Lamiaceae [10].

Later, the field of molecular phylogenetics fundamentally altered the basis of classification of organisms. In 2004, Walker et al., using the rbcL and trnL-F gene regions and broad sampling within Salvia, were the first to reveal that Salvia was non-monophyletic [11]. They found Perovskia, Dorystaechas, and Rosmarinus, as well as Mentha L., Origanum L., and Thymus L., and later also Meriandra and Zhumeria embedded within Salvia [11,12].

In 2017, a broad phylogenetic study was undertaken using nuclear markers such as the internal transcribed spacer from nuclear ribosomal DNA (nrITS) and plastid marker rpl32-trnL [13]. This study confirmed the polyphyletic character of Salvia but also showed the existence of four distinct, well supported evolutionary lineages (Clades I-–IV) within Salvia and the inclusion of five additional non-Salvia genera, namely, Dorystaechas, Meriandra, Perovskia, Rosmarinus, and Zhumeria. Based on the plastid data, Perovskia and Rosmarinus were found in a trichotomy with Clade I (Salvia s.s.). The authors reconstructed the evolution and biogeography of Salvia and found that the most recent common ancestor of Perovskia and Rosmarinus, which are sister to Salvia Clade I, diverged most likely during the early to middle Miocene. Based on current knowledge, Will and Claßen-Bockhoff propose to split the former large genus Salvia into six genera, each supported by geographical distribution, morphology, and karyology, and suggest that they could be elevated to generic rank after revision.

In a related study, low-copy nuclear markers (PPR-AT3G09060, GBSSI) were used to further assess relationships of Salvia and related genera within Salviinae [14]. Based upon these results, previous phylogenetic findings, taxonomic, morphological, and practical considerations, the authors concluded that the botanical community would be better served by keeping the genus Salvia as traditionally circumscribed, but with the inclusion of 15 species in the five small embedded genera: Perovskia, Dorystaechas, Meriandra, Rosmarinus, and Zhumeria. Subsequently, to implement this approach and unify all genera within Salvia, the authors provided an updated nomenclatural revision, according to which former Perovskia abrotanoides is now circumscribed as Salvia abrotanoides (Kar.) Sytsma and former Perovskia atriplicifolia as Salvia yangii B.T. Drew.

Salvia yangii B.T. Drew, commonly called Russian sage, is a silver-grey herbaceous perennial half-shrubby plant. All parts of S. yangii have silvery hairs, including the flower heads. This plant is native to Central Asia in an area that includes Afghanistan, Eastern Iran, Pakistan, and Tibet [1,15]. Successful over a wide range of climate and soil conditions, S. yangii has become popular and is widely planted. Several cultivars/varieties have been developed and cultivated worldwide for ornamental purposes, mainly due to the bountiful blue to violet blossoms arranged in branched panicles.

Salvia abrotanoides Kar., called Caspian Russian sage, is also an aromatic erect shrub that occurs in mountains at an elevation of 2200 to 4200 m above sea level from Central and Northeastern Iran across Northern Pakistan to Northwestern India [7].

Both species are closely related and may share very similar morphology, except the leaf shape, which is the main determinative feature, according to many identification keys [1,8,16]. Numerous publications also inform that the characters of the inflorescence, flower, and seeds are similar in both species and they only differ in leaf shape [17,18,19]. The leaf shape is not a reliable determination feature though, as it is very variable within the species, especially in S. yangii.

Species of subgenus Perovskia range from southwestern to central Asia, with S. abrotanoides being more distributed to the west and S. yangii to the east. The ranges of the two species overlap in Northeastern Iran, Afghanistan, Pakistan, and Nepal [20]. It is suggested that both species can hybridise in natural habitats [1]. Plants grown from seeds originating from botanical gardens or other plant collections where both species grow in short distance from each other also might be crossed. As both species are able to hybridise, it is not clear which cultivars are variants of S. yangii or hybrids between S. abrotanoides and S. yangii [18,19]. This makes the seemingly simple determination of Perovskia species unexpectedly complicated.

Both S. yangii and S. abrotanoides are used as a folk medicinal herb in the areas of natural occurrence. S. yangii is a folk medicinal plant used in Pakistan, Turkmenistan, and Afghanistan [21,22]. The plant has antibacterial activity and is also used as a cooling medicine in the treatment of fever [3,23]. It is known for its flavouring qualities and it is also smoked as a euphoriant and used as a decoction for chronic dysentery [21]. In Uzbekistan and Kyrgyzstan, the aboveground parts are used to heal wounds, and a decoction is used to treat scabies [17]. In traditional Tibetan and Chinese medicine, it has been claimed that S. yangii is a powerful analgesic and parasiticide agent [9,24].

S. abrotanoides, locally known as brazambol, is used to treat leishmaniasis in Iranian folk medicine. Villagers in the Isfahan Province apply a poultice, made of crushed roots of the plant, water, sesame oil, and wax, on lesions caused by cutaneous leishmaniasis [25,26]. The plant is also used locally for treatment of typhoid, fever, headache, gonorrhoea, vomiting, motion, toothache, cardiovascular diseases, liver fibrosis, painful urination, cough, and as a sedative, analgesic and antiseptic drug [21,27,28,29,30]. Also, the essential oil of S. abrotanoides is effective as an antimicrobial agent [31].

Species of subgenus Perovskia contain a wide array of natural compounds belonging to different classes [22]. Most of the published data refer to the composition and activities of essential oils from aerial parts [32,33,34,35,36,37,38,39,40,41], indicating a significant variability associated with geographic origin and environmental factors Aerial parts contain also lignans, triterpenes, steroids, and their glycosides, as well as phenolic compounds, including considerable amounts of rosmarinic acid, which is a typical product of the Nepetoideae subfamily of Lamiaceae, known for its numerous health-promoting properties [2,3,7,15,42,43].

Roots of species belonging to the subgenus Perovskia are abundant in red-colored quinoid norabietanoids called tanshinones and are considered an alternative source of these valuable pharmacologically active compounds [25,44]. Tanshinones are the main constituents of the well-known Traditional Chinese Medicine herbal drug ‘Danshen’ (Salvia miltiorrhiza rhizome et radix a pharmacopoeial drug of China and Europe) [45,46,47,48].

The research performed to date on plants of subgenus Perovskia concentrated on either roots [25,44] or aerial parts [7,49,50,51]. There are also reports on phytochemical analysis of the air-dried whole plants [2,3,4,9,24,52]. Plants were collected from their natural habitat or were cultivated. Various methods and solvents were used by researchers to extract natural products of interest which often makes the results hardly comparable. Therefore, we aimed at comprehensive analysis of phytochemical profiles of non-volatile compounds in both roots and leaves of S. yangii and S. abrotanoides cultivated in Europe under identical climatic and edaphic conditions (Wroclaw, Poland). The ethnopharmacological importance of S. yangii and S. abrotanoides has prompted us to reanalyse their chemical constituents with potential or proven bioactivity. Here, for the first time, we offer a detailed comparison of phytochemical non-volatile profile in roots and leaves of S. yangii and S. abrotanoides together with the analysis of a mutual genetic relationship between the two species. The proposed approach of a comparative analysis of closely related plants of a similar but not identical chemical profile may bring tangible results which might potentially pinpoint the outlook for follow-up work through genetic approaches, transcriptomics, proteomics, and other applications. Choosing non-model but potentially important medicinal plants allowed us to test this methodology and prove that the slight differences in morphological and metabolic phenotypes can be verified by molecular analyses, thus facilitating the proper material identification and accelerating the selection of desired traits, breeding, and herb quality control and improvement.

2. Materials and Methods

2.1. Plant Material

Salvia abrotanoides and S. yangii plants were grown at the experimental field in the Botanical Garden of Medicinal Plants at the Wroclaw Medical University (Poland). The geographical location of the Garden is as follows: latitude 51°07′03″ N, longitude 17°04′27″ E, altitude 117 m a.s.l. S. abrotanoides was introduced from its original habitat in Iranian Karkas Mountains (coordinates: 33°24′57.3″ N 51°46′45.4″ E). Seeds of S. yangii were obtained from the collection of the Botanical Garden in Essen (Germany). Cultivars “Lacey Blue” and “Blue Spire” are available commercially as ornamental plants. Plants analyzed in this study were cultivated clonally via vegetative propagation since introduced into the Botanical Garden of Medicinal Plants at the Wroclaw Medical University. Plant voucher specimens were deposited in the herbarium of the Botanical Garden of Medicinal Plants at the Wroclaw Medical University (reference numbers: S. abrotanoides: P-122; S. yangii: P-123; cultivar “Blue Spire”: P-124; cultivar “Lacey Blue”: P-125).

Leaves and roots of S. abrotanoides and wild type S. yangii (Appendix A, Figure A1) were collected for phytochemical analysis and were immediately frozen in liquid nitrogen. Harvested leaf samples were finely ground using a mortar and pestle with liquid nitrogen. Root samples were finely ground using an automatic/electric grinder Analysette 3 Spartan and Pulverisette 0 Cryo-Box (Fritsch GmbH, Idar-Oberstein, Germany) filled with liquid nitrogen.

Three accessions of S. yangii (including wild type and cultivars “Lacey Blue” and “Blue Spire”) and a single accession of vegetatively propagated S. abrotanoides were subject to the molecular study. For phylogenetic analysis, a single, fresh, mature leaf of each plant was harvested and ground to a fine powder in liquid nitrogen.

All samples were stored at −80 °C. The harvest of leaves and roots was done during the flowering season (August 2016).

2.2. Sample Preparation for Qualitative Analysis

For direct qualitative analysis, 100 mg of lyophilized plant material was extracted with 5 mL of MeOH: H2O (8:2 v/v) in an ultrasonic bath for 20 min at 25 °C. The supernatant was collected and evaporated to dryness. Extracts were suspended in 2 mL of 0.2% formic acid (FA) in H2O prior to preliminary purification and concentration using solid phase extraction (SPE). SPE was performed using an Oasis Max 1cc Vac Cartridge, 500 mg Sorbent per Cartridge, 30 µm Particle Size (Waters Corporation, Milford, MA, USA) conditioned with MeOH (4 mL) and H2O (4 mL). The sample was loaded and cartridges washed with 5 mL water in 0.1% FA. The phenolic compounds were eluted with 5 mL of 80% MeOH in 0.1% FA. Samples were re-evaporated to dryness and dissolved in 25% of MeOH to obtain 1 mg dry weight/mL baseline plant material concentration.

2.3. Liquid Chromatography–Mass Spectrometry Analysis

Ultra-high performance liquid chromatography quadrupole time of flight mass spectrometry (UHPLC-QTOF-MS) estimation of metabolite contents was carried out on a Thermo Ultimate 3000 RS (Thermo Fischer Scientific, Waltham, MA, USA) chromatographic system coupled to a Bruker Compact (Bruker, Billerica, MA, USA) quadrupole time of flight (QTOF) mass spectrometer, consisting of a binary pump, sample manager, column manager, and the PDA/diode array detector. Separations were performed on a Kinetex C18 column (2.1 × 100 mm, 2.6 μm, Phenomenex, Torrance, CA, USA), with mobile phase A consisting of 0.1% (v/v) FA in water and mobile phase B consisting of 0.1% (v/v) FA in acetonitrile. The samples (2 μL) were injected, and a linear gradient from 15% to 70% phase B in phase A was used for 27 min to separate all main compounds. The flow rate was 0.3 mL/min, and the column was held at 30 °C. Mass spectra were acquired in positive-ion mode over a mass range from m/z 100 to 1500 with 5 Hz frequency. Ultrapure nitrogen was used as drying and nebulizer gas and argon was used as collision gas. The collision energy was set automatically from 15 to 75 eV, depending on the m/z of the fragmented ion. Operating parameters of the ESI ion source were as follows: capillary voltage 3 kV, dry gas flow 6 L/min, dry gas temperature 200 °C, nebulizer pressure 0.7 bar, collision radio frequency 700.0 V, transfer time 100.0 μs, and pre pulse storage 7.0 μs. Acquired data were calibrated internally with sodium formate introduced to the ion source at the beginning and end of each separation via a 20 μL loop. Processing of spectra was performed with Bruker DataAnalysis 4.3 software. UV DAD data were collected at 190–450 nm, and chromatograms acquired at UV 280 nm were smoothed by use of the Savitzky−Golay algorithm (window width 5 points, one iteration). Then, the detected peaks at retention time and the corresponding MS/MS were integrated. All determinations were done in triplicate (biological replication meaning a different extract n = 3); each biological replication was measured at least twice as a technical replication.

ProfileAnalysis software (version 2.1, Bruker Daltonik GmbH, Bremen, Germany) was used to preprocess the raw UHPLC-QTOF-MS data. ProfileAnalysis parameters were set as follows: advanced bucket generation with retention time range of 1.0–24.0 min, mass range of 100–800 m/z, normalization to sum of peaks, background subtraction, and time alignment; then, analyses were processed with the Find Molecular Futures (FMF) function to create compounds with a signal-to-noise threshold of 3 for peak detection. The generated bucket table consisting of m/z–retention time pairs and respective compound intensity was exported and uploaded to Metabolists 5.0 (http://www.MetaboAnalyst.ca/) for multivariate statistical analysis. The initial and final retention times were set for data collection. Data were imported into Metabolists 5.0 (http://www.MetaboAnalyst.ca/) online software to estimate missing values and to filter and normalize data (normalization by the median). No transformation was generalized, and the data matrix was mean-centered and divided by the square root of the standard deviation of each variable (Pareto scaling). The obtained data matrix was introduced into SIMCA-P+ 16.01 (Sartorius AG, Göttingen, Germany) software for in-review multivariate statistical analysis of principal component analysis (PCA). The PCA score plot was used to present a natural correlation between the observations. To identify differential compounds, the PLS-DA (Partial Least Squares Discriminant Analysis) model was used to explore differences in depth between the profile metabolome of Salvia yangii and S. abrotanoides The PLS-DA model with VIP values (VIP ≥ 1.0) and |p(corr)| ≥ 0.5 was used to select differential compounds (PLS-DA data not shown).

2.4. Genomic DNA Extraction

DNA was extracted with the modified Doyle & Doyle method [53]. Spectrometric DNA concentration measurements were conducted with a NanoDrop ND 2000C (Thermo Fisher Scientific, Waltham, MA, USA). If needed, DNA isolates were purified with the Syngen DNA clean-up Kit (Syngen Biotech, Wroclaw, Poland) and the DNA concentration was measured again.

2.5. DNA Barcoding

ITS rDNA regions were amplified using primers ITS1F [54] and ITS4 [55] while the trnH-psbA chloroplast intergenic spacer was amplified with trnHf_05 [56] and psbA3_f [57] primers (Table 1). PCR was performed in a T-100 thermal cycler (BIO-RAD Laboratories, Hercules, CA, USA) in 20 μL volumes containing template DNA and was set up according to the Q5™ High-Fidelity DNA Polymerase manufacturer’s protocol (Q5™ High-Fidelity DNA Polymerase, New England BioLabs Ltd., Hitchin, UK). Thermal cycling conditions were as follows: 95 °C for 30 s; 35 cycles of 95 °C for 10 s; 60 °C (for ITS1F&ITS4) or 62 °C (for trnHf_05&psbA3_f) for 30 s; 72 °C for 45 s and 72 °C for 2 min for final extension. PCR products were visualized by gel electrophoresis in 2% agarose gel in TEA buffer with 50 bp DNA Ladder (New England Biolabs Ltd., Hitchin, UK) and stained with SimplySafe (EURx, Gdansk, Poland). Amplified DNA products were purified with the Syngen Gel/PCR Mini Kit (Syngen Biotech, Wroclaw, Poland).

Table 1.

Primers used for amplification and Sanger sequencing of the ITS rDNA region and trnH-psbA intergenic spacer.

Primer Sequence (5′ to 3′) Reference
ITS1F CTTGGTCATTTAGAGGAAGTAA [54]
ITS4 TCCTCCGCTTATTGATATGC [55]
psbA3_f GTTATGCATGAACGTAATGCTC [57]
trnHf_05 CGCGCATGGTGGATTCACAATCC [56]

Sanger sequencing was carried out with the BrilliantDye™ Terminator v3.1 Kit (Nimagen B.V., Nijmegen, The Netherlands). Reactions were set with a fourfold dilution of the reaction premix and the addition BrilliantDye® Terminator 5X Sequencing Buffer (Nimagen B.V., Nijmegen, The Netherlands) according to the producer’s instructions. Sequencing products were precipitated with ethanol, dissolved in TSR (Hi-Di Formamide) (Thermo Fisher Scientific, Waltham, MA, USA) and then separated by capillary electrophoresis on an Applied Biosystems™ 310 Genetic Analyzer (Thermo Fisher Scientific, Waltham, MA, USA). Two reads were collected for each sample. Eight sequences were generated for molecular and phylogenetic analyses performed along with additional sequences obtained from NCBI (https://www.ncbi.nlm.nih.gov).

Sequence quality was checked with the Sanger Quality Check App (Thermo Fisher Scientific, Waltham, MA, USA). Forward and reverse sequencing reads for each marker region were assembled into a contig using the BioEdit Sequence Alignment Editor [58]. The identity of all obtained sequences was confirmed as ITS or trnH-psbA through similarity to published sequences using the BLAST algorithm. The ITS2 fragment was extracted with ITSx [59].

Alignments were assembled separately for each marker with the ClustalW algorithm under default conditions in MEGA 7 [60] and were then entered into the program Gblocks v.091b to objectively eliminate poorly aligned positions and divergent regions [61]. Then, a final alignment was assembled by a combination of both alignments calculated for individual markers. The relationship among the taxa was estimated using the Neighbor-Joining (NJ) method [62] and presented as an -rooted phylogram. Due to the large number of gaps in the dataset, a Pairwise deletion Gaps/Missing data treatment was applied. The evolutionary distances were computed using the Maximum Composite Likelihood method [63] according to the general recommendation. To estimate reliability of the tree bootstrap, a 1000-replication test was used [64]. The analysis involved 29 nucleotide sequence combinations including L. maculatum and L. amplexicaule as an outgroup.

3. Results

3.1. Metabolic Analysis

Using UHPLC-QTOF-MS analysis, thirty-eight different compounds were found in the methanolic extract of S. yangii leaves, while leaves of S. abrotanoides comprised thirty-six metabolites extracted with methanol (Table 2; Figure 1). The analysis showed the presence of 14 different phenylpropanoids (3–6, 8–11,14,15,17,18, 21, 27) in leaves of both S. yangii and S. abrotanoides, including rosmarinic acid (11), considered as one of the chemotaxonomic markers in the Nepetoideae subfamily [22]. In total, 13 diterpenoids were detected in S. yangii leaves (20, 22, 23, 28–30, 32, 34, 35, 37, 38, 40, 41) while leaves of S. abrotanoides contained 15 different diterpenoids, out of which carnosic acid quinone (31), isorosmanol (33), and trilobinol (39) were found in S. abrotanoides and not in S. yangii. On the other hand, rosmaridiphenol (35) and sugiol (38) were detected exclusively in S. yangii leaves. Among all detected diterpenoids, carnosol (30) turned out to be the most abundant in the leaves of both species as it yielded the highest peak (Figure 1). Both species were found to contain a phenantrene, methoxy-8,11,13-abietatrien-20,11-olide (36), in their leaves. Interestingly, three metabolites identified as triterpenoids (24–26) were detected exclusively in leaves of S. yangii. Seven compounds found in leaves of both species were not determined (1, 2, 7, 12, 13, 16, 19).

Table 2.

Characterization of identified compounds in leaves of S. yangii and S. abrotanoides, UHPLC–QTOF-MS in positive ion mode.

No. Compound RT UV m/z[M + H]+ Formula MS2 Main-Ion (Relative Intensity %) MS2 Fragments (Relative Intensity %) Salvia yangii Salvia abrotanoides References
1 ND 0.9 - 365.1123 C13H16O10 169(100) 271(45), 211(23), 151(18) *** ***
2 ND 1.7 237, 285, 323 369.1184 C17H20O9 207(100) *** ***
3 Quercetin 3-rutinoside 2.7 282, 342 611.1609 C27H30O16 303(100) 465(4) *** *** HMDB0003249
4 Luteolin-O-Hex-Dhex 4.6 260, 343 595.1660 C27H30O15 287(100) 449(3) *** ** MetFrag
5 Luteolin-O-Pen-Glucuronide 5.1 260, 343 595.1660 C27H30O15 287(100) 395(5), 419(3) *** *** MetFrag
6 Quercetin 4′-glucoside 5.3 260, 348 465.1025 C21H20O12 303(100) *** * HMDB0037932
7 ND 6.1 279, 324 603.2056 C31H38O12 441(100) *** ***
8 Apigenin-O-Hex-Dhex 6.7 282, 323 579.1706 C27H31O14 271(100) 433(3) *** ** MetFrag
9 Hesperidin 6.9 284 611.1970 C27H30O16 303(100) 263(5), 449(2), 369(2) *** * HMDB0003265
10 Diosmetin-O-Hex-Dhex 7.2 285, 324 609.1815 C28H32O15 301(100) 463(3) *** *** HMDB0029548
11 Rosmarinic acid 7.4 289, 328 361.0927 C18H16O8 163(100) 181(42), 325(15), 283(10) *** ** Standard
12 ND 8.6 219, 279 503.1915 C26H30O10 279(100) 341(32), 311(14), 291(25) *** **
13 ND 8.8 219, 283, 323 435.1267 C21H22O10 391(100) 349(15) ** ***
14 Isomargaritene 9.2 - 593.1870 C28H32O14 285(100) 447(12), 429(10) *** * HMDB0037415
15 Poncirin (Isosakuranetin-7-O-beta-D-neohesperidoside) 9.2 - 595.2017 C28H34O14 287(100) 269(2) *** * HMDB0037487
16 ND 9.3 - 503.1920 C26H30O10 279(100) 311(90), 291(80), 251(70), 259(20) *** *
17 Dihydrokaempferide 7-rhamnoside 10.5 282, 320 449.1428 C22H24O10 285(100) ** *** HMDB0040561
18 Trihydroxy-dimethoxyflavone 11.4 334 331.0813 C17H14O7 270(100) 298(63), 286(4) *** *** HMDB0128752
19 ND 11.9 - 631.2018 C31H34O14 291(100) 323(65), 259(8) *** ***
20 Isorosmanol derivative 12.6 - 347.1849 C20H26O5 301(100) 273(15), 241(8), 231(7) * *** MetFrag
21 Dihydroxy-methoxymethylflavone 13.1 275, 333 315.0861 C17H14O6 254(100) 282(61), 300(13), 271(7), 285(2) *** * MetFrag
22 Rosmanol 13.4 288 347.1858 C20H26O5 301(100) 273(48), 241(27), 283(20) * *** MetFrag
23 Epi-rosmanol 14 - 347.1856 C20H26O6 229(100) 273(42), 283(25), 231(18), * *** HMDB0035812
24 2-Hydroxy-3-oxo-12-oleanen-28-oic acid 15.4 - 471.3471 C30H46O4 453(100) 425(42), 261(18), 201(12) *** HMDB0040494
25 3-Oxo-12,18-ursadien-28-oic acid 16 - 453.3377 C30H44O3 407(100) 201(42), 435(10), 205(10) *** HMDB0037065
26 Trihydroxy-12-ursen-28-oic acid 16.6 - 489.3579 C30H48O5 407(100) 471(25), 435(14) *** HMDB0036961
27 Hydroxy-trimethoxyflavone 16.8 331 329.1016 C18H16O6 296(100) 329(15), 284(4) ** *** HMDB0040719
28 11-Methylrosmanol 17 - 361.2020 C21H28O4 329(100) 301(48), 283(15) * *** MetFrag
29 7-Methylrosmanol 17.5 - 361.2045 C21H28O5 273(100) 245(90) 301(67), 237(50), 283(41) *** ** HMDB0035813
30 Carnosol 17.8 284 331.1903 C20H26O4 285(100) 215(45), 267(42), 243(21), 331(20) *** *** HMDB0002121
31 Carnosic acid quinone 18.2 284 331.1949 C20H26O5 285(100) 303(42), 267(25), 243(18), 225(11), 215(10), 192(8) *** MetFrag
32 12-Hydroxy-7-oxo-8,11,13-abietatrien-18-al 18.9 315.1938 C20H26O3 287(100) ** ** HMDB0040746
33 Isorosmanol 19.5 - 347.1858 C20H26O5 301(100) 231(91), 259(85), 283(45), 255(21) *** HMDB0036661
34 11,12-Dimethylrosmanol 19.9 - 375.2166 C22H30O5 287(100) 329(45), 269(22), 217(15), 191(8) *** *** HMDB0040525
35 Rosmaridiphenol 20.1 - 317.2104 C20H28O3 181(100) 299(15), 273(14), 261(8) *** HMDB0037233
36 Methoxy-8,11,13-abietatrien-20,11-olide 20.3 - 329.2112 C21H28O3 217(100) 191(42), 205(33), 231(17), 245(15) *** *** HMDB0038391
37 Sageone 20.4 - 301.1789 C19H24O3 259(100) 241(27), 272(20), 283(18), 303(13), (216(4) * *** HMDB0038684
38 Sugiol 21.1 205, 223, 282 301.2153 C20H28O2 272(100) 191(60), 217(51), 203(42), *** HMDB0036564
39 Trilobinol 21.2 205, 223, 282 301.2153 C20H28O2 272(100) 191(85), 217(31), 203(22), *** HMDB0038702
40 Carnosic acid 21.6 - 333.2056 C20H28O4 315(100) 287(65), 273(41), 259(12), 245(5), 233(2) *** * Standard
41 Miltirone 22.2 - 283.1678 C19H22O2 225(100) 268(40), 240(28), 253(20) ** *** [44]

ND: not determined, * ranges from 0.01–0.1 mg/g DM (Dry Mass), ** 0.1–1 mg/g DM and *** above 1 mg/g DM HMDB ID: The Human Metabolome Database MetFrag-MetFrag Online DataBase.

Figure 1.

Figure 1

BPC chromatogram of the main metabolites identified in the MeOH extract of leaves of S. yangii and S. abrotanoides, harvested in the middle of the season.

UHPLC-QTOF-MS analysis of methanolic extracts of S. yangii roots revealed the presence of thirty-five different compounds, while in roots of S. abrotanoides, only twenty-six metabolites were detected (Table 3; Figure 2). In roots of S. yangii, six phenylpropanoids were found (1, 3, 5, 9–11), out of which three, namely, methoxytaxifolin (1), 2-O-p-coumaroyltartronic acid (3), and melitric acid B (10), were found only in S. yangii and not in S. abrotanoides. Roots of S. abrotanoides contained four phenylpropanoids, one of which was found exclusively in this species: a flavonoid glucoside–hesperidin (7). Rosmarinic acid (9) and salviaflaside (5), a rosmarinic acid 3′ glucoside, were detected in both species as well as the 8-methylchromen-4-one (12), a phenolic compound belonging to benzopyrans, and salvianolic acid L (6), belonging to phenylnaphthalenes. Chrysoeriol 7-rutinoside (8), which belongs to fatty alcohols/aliphatic alcohols, was detected exclusively in the roots of S. abrotanoides. The most abundant group of non-volatile metabolites in roots was diterpenoids, represented by 18 compounds in S. yangii and by 13 metabolites in S. abrotanoides. Twelve diterpenoids (14, 15, 17–21, 31, 34, 35, 37, 38) were common to both species, including the most abundant, cryptotanshinone (31). Six diterpenoids were unique in the metabolite profile of S. yangii roots, namely: didehydrotanshinone IIa (25), acetyloxycryptotanshinone (26), isograndifoliol (27), grandifoliol (28), didehydroacetyloxycryptotanshinone (30), and ketoisogrndifoliol (32). An undetermined cryptotanshinone derivative (29) was found exclusively in S. abrotanoides roots. Nine compounds were not determined in methanolic extracts of roots (2, 4, 13, 16, 22, 23, 24, 33, 36) out of which three were detected only in S. yangii (2, 24, 36).

Table 3.

Characterization of identified compounds in roots of S. yangii and S. abrotanoides, UHPLC–QTOF-MS in positive ion mode.

No. Compound RT UV m/z[M + H]+ Formula MS2 Main-Ion (Relative Intensity %) MS2 Fragments (Relative Intensity %) Salvia yangii Salvia abrotanoides References
1 Methoxytaxifolin 1.3 283, 323 335.0763 C16H14O8 271(100) 253(23), 225(14), 197(8) * MetFrag
2 ND 1.8 217, 241, 292, 323 549.1594 C26H28O13 531(100) 313(8), 251(4), 295(3) *
3 2-O-p-Coumaroyltartronic acid 2.3 - 267.0483 C12H10O7 251(100) 223(23), 206(15) * MetFrag
4 ND 5.4 287, 319 511.2535 349(100) 331(47), 258(41), 245(25), 227(17), 211(10) *** ***
5 Salviaflaside 5.6 288, 319 523.1439 C24H26O13 163(100) 325(45), 287(22), 361(10) *** *** [65]
6 Salvianolic acid L 6.5 256, 285, 315, 350 719.1599 C36H30O16 521(100) 295(25), 493(18), 221(12), 249(10) *** *** [65]
7 Hesperidin 6.9 285 611.1982 C28H34O15 303(100) 449(10), 263(4) *** HMDB03265
8 Chrysoeriol 7-rutinoside 7.3 333 609.1812 C28H32O16 301(100) 463(10) *** HMDB37453
9 Rosmarinic acid 7.5 288, 319 361.0924 C18H16O8 163(100) 181(42), 325(15), 283(10) *** *** [44]
10 Melitric acid B 7.9 285, 329 521.1062 C27H20O11 295(100) 493(22), 457(14), 329(6) *** HMDB0040680
11 3-(3,4-dimethoxyphenyl)-5-hydroxy-7-methoxy-8-methyl-3,4-dihydro-2H-1-benzopyran-4-one 9.8 - 345.1334 C19H20O6 327(100) 283(45), 268(15), 255(8), 201(4) *** * HMDB0129573
12 3-(3,4-dimethoxyphenyl)-5-hydroxy-7-methoxy-8-methylchromen-4-one 11 - 343.1170 C19H18O6 325(100) 281(51), 266(18), 251(11), 238(10), 211(4) *** * HMDB0129572
13 ND 11.6 218, 339 315.0859 C17H14O6 267(100) 225(15) * **
14 Isograndifoliol derivative 11.8 - 303.1940 C19H26O3 272(100) 203(18), 256(14), 215(7) *** ** [66]
15 Tanshinone V 12.1 - 315.1210 C18H18O5 297(100) 264(84), 277(21), 236(18) *** ** [42]
16 ND 12.1 295.1317 267(100) 252(41), 237(28), 225(12) * ***
17 Dihydroxycryptotanshinon 12.3 - 329.1381 C19H20O5 265(100) 283(65), 250(18), 311(14), 237(8) *** * [44]
18 OH-Tanshindiol A 12.4 - 331.1540 C19H22O5 295(100) 277(42), 267(41), 249(32), 235(21), 225(10) *** * [65]
19 OH-cryptotanshinone 13.5 - 313.1435 C19H20O4 267(100) 295(81), 280(74), 249(41), 225(25), 197(20) *** * [44]
20 Oxocryptotanshinone 13.7 - 311.1279 C19H18O4 265(100) 283(74), 250(51), 295(14), 237(10), 197(8) *** * [44]
21 1-βOH-cryptotanshinone 13.8 220, 267 313.1427 C19H20O4 267(100) 295(81), 280(74), 249(41), 262(25), 197(20), 225(8) *** * [44]
22 ND 14.2 329.1388 C19H20O5 311(100) 285(24), 267(15), 252(8), 185(2) *** *
23 ND 14.4 - 331.1898 C19H20O4 311(100) 267(14), 283(10), 225(8), 185(5) *** *
24 ND 15.5 - 327.1228 C19H18O5 309(100) 265(15), 250(14), 223(11), 281(8) ***
25 Didehydrotanshinone IIa 16.1 222, 273 293.1163 C19H17O3 278(100) 263(45), 247(41), 232(38), 219(18), 204(5) *** [44]
26 Acetyloxy cryptotanshinone 16.3 - 355.1548 C21H22O5 295(100) 280(61), 277(48), 267(38), 262(32), 249(15), 247(8) *** [66]
27 Isograndifoliol 16.7 - 303.1956 C19H26O3 272(100) 203(41), 215(25), 257(21), 187(18), 229(15) *** [66]
28 Grandifoliol 16.8 - 289.1793 C18H24O3 271(100) 256(45), 241(18) ***
29 Cryptotanshinone derivative 16.9 - 297.1484 C19H20O3 269(100) 254(21), 239(25), 227(18), 209(3) *** [42]
30 Didehydro acetyloxy cryptotanshinone 18.6 - 353.1388 C21H20O5 315(100) 293(85), 275(45), 247(28) *** [65]
31 Cryptotanshinone 18.9 222, 264 297.1469 C19H20O3 269(100) 254(41), 251(38), 279(21), 282(18) *** * [44]
32 Ketoisograndifoliol 19.4 - 301.1796 C19H24O3 272(100) 203(45), 215(32), 229(18), 257(12) *** MetFrag
33 ND 20.4 - 287.1640 C18H23O3 269(100) 254(45), 213(22), 199(18) *** *
34 Tanshinone IIa 21.7 - 295.1326 C19H19O3 277(100) 249(71), 262(56), 252(41), 266(20) *** ** [44]
35 Miltiodiol (Arucadiol) 22 - 299.1636 C19H22O3 271(100) 203(41), 253(24), 183(7) *** ** [44]
36 ND 22.1 - 269.1520 C18H20O2 254(100) 239(14), 225(12), 215(6) ***
37 Miltirone 22.2 - 283.1689 C19H22O2 225(100) 268(41), 240(32),253(28) *** ** [44]
38 6,7-Didehydroferruginol 22.9 - 285.2197 C20H28O 271(100) 201(12), 272(8) *** **

ND: not determined, * ranges from 0.01–0.1 mg/g DM (Dry Mass), ** 0.1–1 mg/g DM and *** above 1 mg/g DM HMDB ID: The Human Metabolome Database MetFrag-MetFrag Online DataBase.

Figure 2.

Figure 2

BPC chromatogram of the main metabolites identified in the MeOH extract of roots of S. yangii and S. abrotanoides, harvested in the middle of the season.

3.2. Statistical Analysis of UHPLC-QTOF-MS Data

In order to reveal group patterns in non-volatile metabolic profiles of analyzed leaves and roots, an unsupervised PCA was applied. The PC loadings revealed a clear trend to form two clusters among all tested samples, either in leaves or roots, which represent the data in the space formed by the principal components (Figure 3 and Figure 4).

Figure 3.

Figure 3

Principal component analysis presenting the relationship between the chemical profile of the main compounds in the leaf and species annotation of the analyzed plants; S. yangii (blue) and S. abrotanoides (orange) (a), with corresponding loadings (PCA model: R2XCum = 0.767, Q2Cum = 0.45) (b). Each loading number corresponds to the peak number identified in the BPC chromatogram.

Figure 4.

Figure 4

Principal component analysis presenting the relationship between the chemical profile of the main compounds in the root and species annotation of the analyzed plants; S. yangii (blue) and S. abrotanoides (orange) (a), with corresponding loadings (PCA model: R2XCum = 0.755, Q2Cum = 0.566) (b). Each loading number corresponds to the peak number identified in the BPC chromatogram.

In leaves, the first two principal components (PCs) explained 47.3% and 17.1% of the variation in the spectral data, respectively. On the right side of the score plots (green dots) a strong cluster of S. abrotanoides samples formed, while on the left side (blue dots) S. yangii samples were well separated (Figure 3a). According to the loadings plot (Figure 3b) these two groups were significantly positively correlated with particular compounds detected in leaves. The PC loadings analyses confirmed that the content of sugiol (38) in S. yangii leaves and of carnosic acid quinone (31) in leaves of S. abrotanoides were mostly responsible for their chemical differentiation and revealed a clear separation of samples derived from these two species.

In roots, the first principal component explained 65.3% of the variation in the spectral data and the second, 10.2%. Samples of S. yangii, represented by blue dots, were closely grouped on the right side of the plot, while on the left side (green dots), S. abrotanoides samples occurred (Figure 4a). The loadings plot revealed that these two groups were significantly positively correlated with particular compounds found in roots (Figure 4b). According to the PC loadings, the contents of isograndifoliol (27), acetyloxycryptotanshinone (26), ketoisograndofoliol (32), oxocryptotanshinone (20) and grandifoliol (28) in S. yangii roots and the presence of cryptotanshinone derivative (29), chrysoeriol 7-rutinoside (8), and hesperidin (7) in the roots of S. abrotanoides were mostly responsible for their chemical differentiation and allowed distinguishing the root samples from the two analyzed Salvia species.

3.3. Genetic Relationship Analysis

Sanger sequencing resulted in four rDNA ITS2 complete sequences (MT599312, MT599313, MT599314, MT599315) and four trnH-psbA intergenic spacer sequences (MT815871, MT815872, MT815873, MT815874) obtained for the cultivars S.OBRL.01, S.OBRL.03, S.OBRL.11 and S.OBRL.12, respectively (Table 4). All sequences were subject to BLAST analysis. Due to the lack of publicly available molecular data of the trnH-psbA barcode in subgenus Perovskia, BLAST analysis of the sequenced trnH-psbA region was not able to indicate similarity to any species from the Perovskia subgenus. Instead, the closest homolog of S.OBRL.01 and S.OBRL.11 trnH-psbA regions indicated by BLAST analysis was the trnH-psbA sequence of Salvia miltiorrhiza, while for S.OBRL.03 and S.OBRL.12, Salvia californica and Salvia chionopeplica were indicated as the closest homologs, respectively. BLAST analysis of the abundantly available data in the ITS2 region revealed high similarity between Salvia abrotanoides and Salvia yangii (Table 4).

Table 4.

Results of BLAST analysis.

Species (Voucher) DNA Region Accession Number (Query) BLAST Result Accession Number (Result) Identity
Salvia yangii “Lacey blue” (S.OBRL.01) ITS2 MT599312 Perovskia atriplicifolia
(Salvia yangii)
KJ584242.1 99.76%
Salvia yangii “Lacey blue” (S.OBRL.01) trnH-psbA MT815871 Salvia miltiorrhiza KC473184.1 95.51%
Salvia yangii “Blue spire” (S.OBRL.03) ITS2 MT599313 Perovskia atriplicifolia
(Salvia yangii)
KJ584242.1 99.63%
Salvia yangii “Blue spire” (S.OBRL.03) trnH-psbA MT815872 Salvia californica KP852621.1 96.61%
Salvia yangii (S.OBRL.11) ITS2 MT599314 Salvia yangii DQ667223.1 99.62%
Salvia yangii (S.OBRL.11) trnH-psbA MT815873 Salvia miltiorrhiza KC473184.1 96.83%
Salvia abrotanoides (S.OBRL.12) ITS2 MT599315 Salvia yangii DQ667223.1 99.64
Salvia abrotanoides (S.OBRL.12) trnH-psbA MT815874 Salvia chionopeplica KP852626.1 95.93%

NJ analysis was performed to estimate the relationship among the studied taxa (S. yangii, including wild type and cultivars “Lacey Blue” and “Blue Spire”, and S. abrotanoides) in comparison with 23 related Salvia species (Table 5). Lamium maculatum and Lamium amplexicaule were applied as an outgroup. Finally, 50 additional sequences used for the NJ analysis were downloaded from GenBank (25 sequences of ITS2 and 25 sequences of trnH-psbA). The manually adjusted alignment of 29 combined ITS2 and 29 trnH-psbA sequences was 540 characters long with 361/540 variable sites, 301/540 Parsimony-informative sites.

Table 5.

DNA sequences of the ITS2 and trnH-psbA regions of 23 Salvia species used for the NJ analysis. Sequences of Lamium maculatum and Lamium amplexicaule were used as an outgroup.

No. Species Specimen Voucher ITS2 trnH-psbA
1 Salvia aethiopis x142 * DQ667272.1 DQ667370.1
2 Salvia amplexicaulis C756 MG824168.1 MG823900.1
3 Salvia dorystaechas x108 * DQ667252.1 DQ667360.1
4 Salvia miltiorrhiza SMI4 JQ934135.1 JQ934199.1
5 Salvia nipponica Y. Ibaragi s. n AB295103.1 MG823977.1
6 Salvia nubicola FLPH 12-124 MG824236.1 MG823979.1
7 Salvia officinalis PS1700MT02 FJ883522.1 FJ513122.1
8 Salvia paramiltiorrhiza SPAR 3 JQ934142.1 JQ934206.1
9 Salvia przewalskii SPRZ 1 JQ934153.1 JQ934217.1
10 Salvia rosmarinus x074 * DQ667241.1 FJ493283.1
11 Salvia sclarea PS1701MT01 FJ883529.1 FJ513083.1
12 Salvia koyamae n/d MK425922.1 MG823960.1
13 Salvia campanulata PS1727MT01 FJ883500.1 FJ513135.1
14 Salvia bulleyana Yin et al. 1314 MG824179.1 FJ513128.1
15 Salvia taraxacifolia x001 * DQ667209.1 DQ667337.1
16 Salvia judaica C769 MG824218.1 MG823957.1
17 Salvia lyrata G.X. Hu QT011 MG824225.1 MG823966.1
18 Salvia disjuncta J. Walker 3018 (WIS) MF622126.1 MF623945.1
19 Salvia moniliformis Crone 15/9/00 (MJG) MF622160.1 MF623979.1
20 Salvia polystachya Mexico. Morelos F. Sazatornil 4 (MEXU) DQ667292.1 MF663893.1
21 Salvia patens x109 * DQ667253.1 DQ667361.1
22 Salvia funerea JBW 3131 KP852812.1 KP852638.1
23 Salvia aristata x170 * DQ667280.1 DQ667375.1
24 Lamium maculatum n/d KF055055.1 HE966679.1
25 Lamium amplexicaule n/d JX073976.1 HQ966679.1

n/d—not determined * isolate numbers retrieved from Walker and Sytsma, 2007 [12].

According to the phylogram reconstructed based on ITS2 and trnH-psbA regions, the subgenus Perovskia was separated from other sages, yet clearly embedded in Salvia, (Figure 5). The topology of the phylogram exhibiteds low interspecies genetic variation between subgenus Perovskia representatives indicated by short branches of the tree.

Figure 5.

Figure 5

Genetic relationship analysis by the Neighbor-Joining method based on the Maximum Composite Likelihood model and Bootstrap phylogeny test (1000 replicates). Support values are shown above nodes (values lower than 50 are not presented). The branch length is shown below branches. The analysis involved 29 nucleotide sequence combinations. Evolutionary analyses were conducted in MEGA7.

Despite the close genetic relationship, S. abrotanoides and S. yangii are suggested to be separate species. Moreover, intraspecies genetic variation within the S. yangii taxon, between “wild type” S. yangii and its cultivars (‘Lacey Blue’ and ‘Blue Spire’), was observed. Furthermore, the intermediate location of S. yangii ‘Blue Spire’ between the two Salvia species suggests that the ‘Blue Spire’ cultivar might have been created through hybridization between S. abrotanoides and S. yangii during the cultivation process.

4. Discussion

In this work, we have provided a comprehensive analysis of the phytochemical profile of non-volatile compounds separately for roots and leaves of S. yangii and S. abrotanoides cultivated in Europe (Wroclaw, Poland). A reliable comparison was possible due to ensuring the same cultivation conditions such as: latitude, weather conditions etc., the same sampling method (immediate freezing in liquid nitrogen), and time (middle of the growing season) as well as the same extraction procedure (MeOH: H2O; 8:2 v/v) and method for chemical analysis (UHPLC-QTOF-MS). Despite ensuring identical cultivation conditions and methodology, a detailed comparison of the phytochemical non-volatile profile in roots and leaves of S. yangii and S. abrotanoides resulted in detecting several metabolites present in one species and absent in the other. The PC loadings analyses showed that sugiol in S. yangii leaves and carnosic acid quinone in leaves of S. abrotanoides were mostly responsible for their chemical differentiation. In roots, isograndifoliol, acetyloxycryptotanshinone, ketoisograndofoliol, oxocryptotanshinone, and grandifoliol in S. yangii as well as chrysoeriol 7-rutinoside, hesperidin, and one unidentified cryptotanshinone derivative in S. abrotanoides allowed for chemical distinguishing of root samples from analyzed species.

As noticed before, most of the published data from aerial parts of species belonging to subgenus Perovskia refer to the composition and activities of essential oils, indicating a significant variation [67]. A thorough review of the chemical profile of essential oils from subgenus Perovskia is provided by Mohammadhosseini et al. [22]. There are very few reports, however, of non-volatile constituents from aerial parts of species belonging to subgenus Perovskia, as a vast majority of them present an analysis of a whole-plant material.

Moreover, the influence of geographic origin and environmental factors influenced the phytochemical profile in both the volatile and non-volatile subset. The extent of such influences in individual cases is hard to assess without extensive experimental research. For example, a light quality modified metabolic profile of cultivated S. abrotanoides [68].

Tarawneh et al. [51] isolated four flavoinoids from dried leaves of S. yangii, which were not present in our isolates, except for the hydroxy-trimethoxyflavone, detected in leaves of both S. yangii and S. abrotanoides. Additionally, we detected trihydroxy-dimethoxyflavone, not found by Tarawneh et al. [51].

Amongst ten compounds found in methanolic extracts of air-dried aerial parts of S. abrotanoides [7], we detected rosmarinic acid and hesperidin, both present in the leaves of S. yangii and S. abrotanoides. Interestingly, in our study, hesperidin was also found to be present in the roots of S. abrotanoides. Two new tertracyclic diterpens, abrotandiol and abrotanone, found by Khaliq et al. [7] were absent in our extracts. The dihydroxy-methoxymethylflavone, however, found in our leaf isolates, might be the same compound as cismaritin found by Khaliq et al. [7]. Confirming that would require additional NMR analysis.

Amongst diterpenoids found in n-hexane and ethyl acetate extracts of aerial parts of S. abrotanoides [69], carnosol, miltirone, rosmanol, and epi-rosmanol were found in methanol leaf extracts of both S. yangii and S. abrotanoides analyzed here. Miltiodiol, however, has been previously isolated from roots [25,44], which was confirmed by our study. Tabefam et al. [69] also detected ferruginol and dehydroferruginol, both belonging to abietane diterpenoids, which were absent in our isolates. Instead, we detected oxoferruginol (sugiol), present in leaves of S. yangii, while leaves of S. abrotanoides contained hydroxyferruginol (trilobinol).

Interestingly, our work has shown that the accumulation of triterpenoids, namely, 2-hydroxy-3-oxo-12-oleanen-28-oic acid, 3-oxo-12,18-ursadien-28-oic acid, and trihydroxy-12-ursen-28-oic acid, takes place exclusively in leaves of S. yangii and not in S. abrotanoides.

In a previous study of S. yangii roots (air-dried crude material, extraction with n-hexane), eight diterpenoids were detected [44]. Extraction with 80% methanol performed in this study allowed for the detection of 18 diterpenoids in S. yangii roots and 15 in roots of S. abrotanoides. 1βOH-cryptotanshinone, cryptotanshinone, tanshinone IIat, and arucadiol (a synonym of miltiodiol) found by Slusarczyk at al. [44] were also detected in our methanolic root extracts in both S. yangii and S.abrotanoides. Miltirone, however, was present only in the methanolic root extract of S. yangii and not in S. abrotanoides, which corroborates previous results [25,44]. Two dehydrogenation products, didehydrotanshinone and didehydromiltirone, which were previously detected in n-hexane root extract of S. yangii, were not present in our methanolic root extract, neither in S. yangii nor in S. abrotanoides. Interestingly, isograndifoliol, reported recently in n-hexane root extract of S. yangii [66] was also detected in the methanolic root extract of S. yangii and was proved to contribute most to chemical differentiation between S. yangii and S. abrotanoides.

Amongst diterpenoids detected in the EtOAc extracts of native dried roots of S. abrotanoides [25], cryptotanshinone, 1βOH-cryptotanshinone, and 1-oxocryptotanshinone were found in methanolic root extracts of both S. yangii and S. abrotanoides. 1-oxomiltirone, found in both previous studies [25,44], was not detected in this work.

The phytochemistry and chemotaxonomic significance of metabolites found in subgenus Perovskia representatives was reviewed by Mohammadhosseini et al. [22].

In this study, we also aimed at analysis of the mutual genetic relationship between S. abrotanoides and S. yangii rather than their taxonomical position within the Salvia subgenera. To our knowledge, no previous work has done that with using DNA barcoding. Usually, a single-entry representative of Perovskia subgenus was used for phylogenetic tree reconstructions of Salvia [11,12,13,14,70]. There are two reports of employing molecular markers (ISSR markers) to investigate genetic variability among populations from subgenus Perovskia growing wild in Iran [71,72]. Heshemifar and Rahimmalek [72] analysed 63 accessions of S. abrotanoides from 16 populations and four accessions of S. yangii. Thirteen ISSR markers were shown to have a relatively high efficiency in the assessment of population diversity, which was in most cases confirmed by morphological classifications. In the study of Pourhosseini at al. [71], twelve S. abrotanoides populations were analyzed and a cultivated population of S. yangii was used as an outgroup. The authors have shown that nine ISSR markers are able to genetically distinguish between all studied populations and that the S. yangii population was clearly separated from S. abrotanoides populations, proving the effectiveness of this DNA fingerprinting method in studying the genetic relationship within the Perovskia subgenus. Despite the suitability of the ISSR markers for studying genetic variation among species within subgenus Perovskia, we have chosen DNA barcoding as it is regarded as a more sophisticated, standardized, and worldwide acknowledged method, recommended for genetic relationship analysis of land plants [73,74,75].

Although the DNA barcoding has been endorsed as the method of choice for land plant species identification, no consensus has been reached on which plant DNA sequences should be regarded as barcodes. The generally low rate of nucleotide substitution in plant mitochondrial genomes precludes the use of cytochrome oxidase 1 (CO1), a potential equivalent for the standard animal barcode, as a universal plant barcode [76,77]. Instead, the search for a plant barcode has involved looking outside the mitochondrial genome and from the outset, many researchers have accepted that multiple markers will be required to obtain adequate species discrimination [78]. Consequently, the Consortium for the Barcode of Life (CBOL) Plant Working Group has recommended a core-barcode consisting of portions of two plastid-coding regions, rbcL+matK, to be supplemented with additional markers as required [75]. Limitations of the rbcL+matK barcodes and idiosyncratic performance of different markers in different taxonomic groups were well discussed by Fazekas et al. [77]. Using additional markers was also strongly suggested by these authors. Beyond the core rbcL+matK barcode, the most widely used plastid barcoding marker is the intergenic spacer trnH-psbA. This region is straightforward to amplify across land plants, and is one of the more variable intergenic spacers in plants [79]. Another suggestion is supplementing the phylogenetic analysis of plants with the internal transcribed spacer from nuclear ribosomal DNA (nrITS) [80,81]. A 20% gain in discriminatory power for full ITS and 10–15% gain even when just the ITS2 region is used is an observed and appreciable benefit [82].

Following these recommendations, we have chosen four most widely used and routinely included plant DNA barcodes out of seven leading and 15 known plant sequences considered as barcodes [78]. These were as follows: two plastid coding regions rbcL and matK, plastid intergenic spacer trnH-psbA, and nuclear internal transcribed spacer ITS2.

We have amplified, sequenced, and uploaded to GeneBank four matK (MT663156, MT663157, MT663158, MT663159) and four rbcL (MT663160, MT663161, MT663162, MT663163) fragments obtained for cultivars: S.OBRL.01, S.OBRL.03, S.OBRL.11, and S.OBRL.12, respectively. However, they were not used for phylogenetic analysis as they possessed little (about 1%) genetic diversity within the Salvia genus. We have also obtained novel DNA sequences for trnH-psbA and ITS2 barcodes for our cultivars: S.OBRL.01, S.OBRL.03, S.OBRL.11 and S.OBRL.12, which ensured significantly higher species discrimination success in our study.

In our approach of an extended marker framework for DNA barcodes, a combination of trnH-psbA and ITS2 barcodes showed sufficient discriminatory power to identify analysed plant organisms to the species level. The phylogram tree constructed with trnH-psbA and ITS2 barcodes has shown the existence of a separate Perovskia clade, which is clearly embedded within Salvia, which corroborates the findings of Drew et al. [14], who formally transferred former non-Salvia genera, such as Perovskia, to Salvia and created a subgeneric designation within Salvia for each of these former genera.

In the present form, our molecular analysis may suggest that S. abrotanoides and S. yangii are very closely related but regarded as two separate species. To make this conclusion fully justified, multiple accessions of S. abrotanoides would have to be included into the analysis. Unfortunately, at present, we do not have access to other taxonomically undoubtful accessions of S. abrotanoides; thus, we decided to rely on what is available. Despite a suggested close genetic relationship, S. abrotanoides and S. yangii possess distinct phytochemical profiles including qualitative differences within the non-volatile chemicals, which make them a potentially useful model for further analysis. Interestingly, the LC-MS profiles of aerial parts are apparently more similar, and none of the major compounds stand out as distinct, but the PCA processing revealed an obvious separation between the species. Hence, presence or absence of the minor compounds or their varied proportions is also important with such examples as the abovementioned sugiol/trilobinol pair. In contrast, the roots of both species are phytochemically distinct at first sight, and chemometric analysis has verified this fact. Isograndifoliol (Figure 2, peak 27), a hydroxylated norditerpenoid present only in S. yangii, is a rarely detected compound that has a high pharmacological potential [66], and its presence in a relatively high amount points out S. yangii as an especially valuable medicinal plant. Sugiol, even if a minor compound only, also has significant pharmacological potential, reviewed recently by Bajpai et al. 2020 [83], that can, for example, attenuate STAT3-dependent proliferation and unlocks apoptosis pathways in cancer cells and can block virus entry to cells. Whether or not this compound can contribute to the overall activity of S. yangii leaf as a drug has not been explored so far. On the other hand, carnosic acid quinone, a phytochemical marker of S. abrotanoides leaves, was reported as a highly potent factor in antioxidant reactions in S. rosmarinus and S. officinalis [84].

Yet, the phytochemical profiling alone is not sufficient to prove the taxonomic differentiation, especially if easily accessible organs (leaves) would be used for sampling. On the other hand, the results from molecular studies are independent from the sample type and coupled with parallel LC-MS profiling constitute a powerful tool in monitoring of taxonomically close and probably easily crossing species.

Qualitative chemical differences between closely related plant species might be of a different etiology. They might result directly from genetic (and/or epigenetic) differences between species or be an outcome of various processes occurring at the transcriptional and post-transcriptional levels. Comparative analysis of S. abrotanoides and S. yangii transcriptomes might help discover particular transcripts responsible for detected chemical differences. Performing genetic crosses between S. abrotanoides and S. yangii would create a segregating population which, through parallel phenotyping and genotyping, might serve for tracing genetic loci potentially responsible for the observed chemical profiles. A similar approach in Papaver somniferum allowed for discovering that ten genes from the noscapine biosynthesis pathway are clustered in the poppy genome [85]. In fact, there are numerous reports published to date proving that many secondary metabolites are a product of gene-clusters [86]. Once a certain target genetic locus is found, it could be subject to different biotechnological approaches, such as gene cloning, gene silencing or heterologous expression of proteins, in order to perform a functional analysis of target genes. In the long run, this may lead to developing applied research aiming at optimization of the chemical profile of Salvia, which may in turn become an alternative source of bioactive chemicals such as tanshinones.

Acknowledgments

The authors thank Agata Biernat for cultivating the plants in the Botanical Garden of Medicinal Plants. We would like to thank Hanna Czapor-Irzabek for technical assistance in UHPLC-QTOF-MS data analysis. Measurements were carried out in the Laboratory of Elemental Analysis and Structural Research at Wroclaw Medical University.

Appendix A

Figure A1.

Figure A1

Plants growing at the site of the experiment: Salvia yangii (a), Salvia abrotanoides (b) and mature leaves with fragments of inflorescence of Salvia yangii (c), Salvia abrotanoides (d); all photographs are from the collection of the Botanical Garden of Medicinal Plants, Wroclaw.

Author Contributions

Conceptualization, M.B.; methodology, M.B.; validation, M.B.; formal analysis, B.P. and S.Ś.; investigation, M.B., B.P., M.S. and S.Ś.; resources, K.J., M.R., S.G. and A.M.; data curation, M.B.; writing—original draft preparation, M.B.; writing—review and editing, A.M.; visualization, M.B.; supervision, A.M.; project administration, M.B.; funding acquisition, M.R., A.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Wroclaw Medical University, grant number, SUB.D033.19.009, and by the Ministry of Science and Higher Education grant-in-aid for Special Research Facility, grant number SPUBD.033.19.002.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

DNA sequence data generated in this study has been deposited in GeneBank at accession numbers: MT599312, MT599313, MT599314, MT599315, MT815871, MT815872, MT815873, MT815874. The UHPLC-QTOF-MS raw data presented in this study are available on request from the corresponding author. The data are not publicly available due to the institutional policy of the authors’ employer.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

DNA sequence data generated in this study has been deposited in GeneBank at accession numbers: MT599312, MT599313, MT599314, MT599315, MT815871, MT815872, MT815873, MT815874. The UHPLC-QTOF-MS raw data presented in this study are available on request from the corresponding author. The data are not publicly available due to the institutional policy of the authors’ employer.


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