Relative Mass Defect Filtering of Mass Spectra: A Path to Discovery of Plant Specialized Metabolites^,

Metabolite masses measured using LC-MS can be sorted into structural classes using relative mass defect filtering to accelerate the annotation of novel metabolites.

Abstract

The rapid identification of novel plant metabolites and assignments of newly discovered substances to natural product classes present the main bottlenecks to defining plant specialized phenotypes. Although mass spectrometry provides powerful support for metabolite discovery by measuring molecular masses, ambiguities in elemental formulas often fail to reveal the biosynthetic origins of specialized metabolites detected using liquid chromatography-mass spectrometry. A promising approach for mining liquid chromatography-mass spectrometry metabolite profiling data for specific metabolite classes is achieved by calculating relative mass defects (RMDs) from molecular and fragment ions. This strategy enabled the rapid recognition of an extensive range of terpenoid metabolites in complex plant tissue extracts and is independent of retention time, abundance, and elemental formula. Using RMD filtering and tandem mass spectrometry data analysis, 24 novel elemental formulas corresponding to glycosylated sesquiterpenoid metabolites were identified in extracts of the wild tomato Solanum habrochaites LA1777 trichomes. Extensive isomerism was revealed by ultra-high-performance liquid chromatography, leading to evidence of more than 200 distinct sesquiterpenoid metabolites. RMD filtering led to the recognition of the presence of glycosides of two unusual sesquiterpenoid cores that bear limited similarity to known sesquiterpenes in the genus Solanum. In addition, RMD filtering is readily applied to existing metabolomics databases and correctly classified the annotated terpenoid metabolites in the public metabolome database for Catharanthus roseus.

Plant metabolic networks generate amazing chemical diversity, but our understanding of the genetic factors responsible for plant chemistry remains primitive. The discovery and identification of metabolites has posed the greatest bottleneck in recent efforts to exploit metabolomics to address questions about the basis for biosynthetic diversity in the plant kingdom (Ji et al., 2009; Zhou et al., 2012). Since the specialized metabolism of nonmodel plants is taxonomically restricted, metabolite databases offer a poor representation of plant chemical diversity, and de novo recognition and discovery of metabolite chemistry is necessary. A common strategy for metabolite discovery has often started with the generation of tandem mass spectrometry (MS/MS) spectra, usually beginning with the most abundant metabolites, and uses characteristic fragment ions to assign metabolites to a particular class of compounds. Flavonoid identification from MS/MS spectra is often successful because most flavonoids yield MS/MS fragment ions characteristic of their flavonoid cores (Ma et al., 1997; Li et al., 2013). However, when MS/MS spectra fail to display class-characteristic fragment ions, the recognition of a metabolite’s structural class is less obvious.

Specialized plant metabolites are often grouped as polyphenolic, terpenoid, alkaloid, polyketide, or fatty acid metabolites based upon the biosynthesis of their core scaffolds, which often undergo subsequent metabolic decoration such as glycosylation. Among phytochemicals, terpenoids offer perhaps the greatest structural diversity. This feature makes them useful as chemical defenses and as the foundation for candidate drugs (Ajikumar et al., 2008; Goodger and Woodrow, 2011), and the commercial importance of terpenes makes their discovery and synthesis an important research focus (Zwenger and Basu, 2008). Terpenoids exhibit remarkable structural diversity resulting from varied metabolic cyclizations, oxidations, rearrangements, and branching reactions (Chappell, 1995; Mizutani and Ohta, 2010) and from diversity in glycosylation (Dembitsky, 2006; Goodger and Woodrow, 2011). Such structural diversity challenges investigators to recognize novel terpenoids in a complex matrix (Pfander and Stoll, 1991; Fraga, 2012), because few features in the MS/MS spectra of nonvolatile terpenoids provide reliable keys for their annotation as terpenoids. As a result, nonvolatile terpenoids represent an underappreciated group of plant specialized metabolites.

Advances in chromatography and mass spectrometry (MS) have enabled the detection of a broad range of natural products, and characteristic ions in mass spectra have been useful for distinguishing compound classes. While gas chromatography-MS has enabled the identification of volatile and semivolatile terpenes for decades, it is not a suitable approach for nonvolatile conjugated terpenoids unless they are first cleaved to form volatile products or derivatized to increase volatility. Furthermore, MS/MS fragment ions characteristic of terpenoid glycosides have yet to be documented, and the characterization of conjugated terpenoids has been limited largely to saponins that share a common steroidal or triterpenoid core (Challinor and De Voss, 2013). In contrast with other specialized metabolite classes, the diversity of terpenoid cores dictates that fragment ions specific to terpenoids often fail to provide for the universal recognition of metabolites within this class, particularly for two situations: (1) when terpenoids are glycosylated and MS/MS spectra are dominated by fragment ions derived from the carbohydrate, and (2) when mass spectra are generated in negative ion mode, which often yields limited cleavage of carbon-carbon bonds in the terpenoid core that might serve as terpenoid indicators. The structural diversity of the terpenoid cores yields different fragments in MS/MS spectra of different nonvolatile terpenoids, as has been demonstrated for a series of saponins (Huhman and Sumner, 2002). Therefore, annotations of terpene glycosides in a metabolite profile have been driven by the absence of fragment ions in mass spectra that represent other classes of molecules (Ward et al., 2011).

Despite its limited capabilities in differentiating stereoisomers, MS plays important roles in the discovery of natural products and the elucidation of their structures (Lei et al., 2011). Modern medium- to high-resolution mass spectrometers have provided greater (low-ppm) mass measurement accuracy. Such mass measurement errors may be more pronounced than measurements for an individual sample when they represent an average mass extracted from large metabolomics data sets. For metabolites of relatively low molecular mass, such measurements provide sufficient information to assign molecular formulas, but for metabolites of higher (greater than 500 D) molecular masses, formula assignments often are ambiguous owing to the large number of formulas consistent with a molecular mass (Kind and Fiehn, 2007). Moreover, assignments of molecular formulas often fail to yield reliable assignments of metabolites to specific biosynthetic origins.

In this report, we examine specialized metabolites of the wild tomato Solanum habrochaites LA1777, which has been studied extensively for its plant defense compounds, including volatile sesquiterpenoids and acyl sugars (Coates et al., 1988; Ghosh et al., 2014). Our recent discovery of a few glycosylated sesquiterpenoids in this accession suggested the metabolic capacity to form such metabolites in the genus (Ekanayaka et al., 2014). It is the intent of this report to present a framework for the accelerated discovery of terpenoid glycosides from mass spectra generated using common instruments such as time-of-flight mass spectrometers that provide intermediate mass resolution and low-ppm mass accuracy using S. habrochaites LA1777 as an example.

FOUNDATIONS OF RELATIVE MASS DEFECT FILTERING FOR MINING PLANT METABOLOMES FOR NOVEL TERPENOID GLYCOSIDES

The power of high-resolution or exact-mass MS for metabolite identification lies in the unique mass of each element and isotope. A common approach that reflects this derives from the idea of a mass defect, which is defined as the deviation of each atom’s mass from the integer-rounded mass (nominal mass). The absolute value of the mass defect of an ion reflects the ion’s elemental composition, because each element has a unique mass defect. A positive absolute mass defect usually reflects a large number of hydrogen atoms, because the atomic mass of hydrogen is slightly greater than the rounded-off integer (by +7.83 mD), and carbon (exactly 12 D) does not contribute to the mass defect. Oxygen has a smaller negative mass defect (−5.09 mD) and nitrogen has a small positive defect (+3.07 mD), and these elements often are fewer in number than hydrogen in specialized metabolites. The absolute mass defect of an ion represents the sum of the mass defects for all atoms in the molecule. Absolute mass defects serve as the basis for assigning elemental formulas from high-resolution mass spectra, but mass measurement accuracy often falls short of providing unambiguous formula assignments, particularly for higher M_r substances where the number of elemental formulas within mass measurement error can be large.

An alternative and promising strategy relies on normalizing the absolute mass defect to an ion’s mass, known as the relative mass defect (RMD). Since absolute mass defect largely reflects the total hydrogen content, RMD serves as a measure of fractional hydrogen content (Stagliano et al., 2010), which in turn reflects the reduced state of carbon that derives from the contributions of metabolic precursors. RMD is calculated in ppm as (mass defect/measured monoisotopic mass) × 10⁶. For the terpene building block isoprene, the RMD of 920 ppm reflects its high hydrogen content (11.8 weight percent hydrogen). This value remains constant for larger monoterpene, diterpene, and triterpene oligomers, which share the same fractional hydrogen content. This demonstrates how RMD values aid the grouping of metabolites based on common biosynthetic precursors, despite differences in molecular mass and absolute mass defect. Metabolic oxidations of a sesquiterpene decrease RMD values, as shown by the shift in RMD to 830, 752, and 692 ppm upon the addition of one- and two-oxygen atoms and subsequent oxidative dehydrogenation (e.g. C₁₅H₂₄O, C₁₅H₂₄O₂, and C₁₅H₂₂O₂). Terpenoid metabolites usually require one or more oxygen atoms in order to be detected by liquid chromatography (LC)-MS using electrospray ionization, and in many organisms, they are conjugated to more polar groups (e.g. glycosides or phosphates). Such conjugations decrease a terpenoid’s RMD value further: each glucosylation adds C₆H₁₀O₅, so glucosylation of a sesquiterpene alcohol (to form C₂₁H₃₄O₆) would decrease RMD to 616 ppm. Additional oxidation or conjugation by malonate (addition of C₃H₂O₃) would decrease the RMD value of terpenoid metabolites yet further, and acylation by aliphatic acids (e.g. acetylation) may increase RMD if the fractional hydrogen content of the acyl group is greater than that of the core molecule. Since conjugated terpenoids usually consist of a terpenoid core that is rich in reduced carbon and conjugate groups (carbohydrates, malonate esters) of low hydrogen content, RMD values of glycosylated sesquiterpenoids range from approximately 400 to 600 ppm. In contrast, polyphenolic metabolites have lower hydrogen content, and their RMD is usually less than 300 ppm (e.g. 230 ppm for salicylic acid and 167 ppm for kaempferol).

Terpenoid glycosides represent a diverse class of phytochemicals that have been understudied due to the challenges in their identification and structure elucidation (Pfander and Stoll, 1991; Sahu and Achari, 2001). While some of these compounds display biological activity (Chang et al., 2002; da Silva et al., 2008), much remains to be learned about their synthesis and functionality in plants (Maier et al., 1995). In this report, the application of RMD filtering is presented as a quickly calculated measure that can advance the annotation of novel plant metabolites from metabolite profiling analyses and databases.

RESULTS AND DISCUSSION

Recognition of Sesquiterpene Glycosides from Ion RMDs

Analysis of leaf extracts of S. habrochaites LA1777 using LC-multiplexed collision-induced dissociation (CID)-MS in negative ion mode yielded evidence of complex mixtures of metabolites, dominated by acylsucroses and flavonoid glycosides (Fig. 1). Automated peak detection, deisotoping, integration, and retention time alignment using Waters MarkerLynx XS software yielded a total of 3,280 mass-to-charge ratio (m/z)-retention time pairs, which are estimated to represent more than 1,000 distinct metabolites owing to the formation of multiple adduct ions, noncovalent dimer ions, and fragment ions.

Figure 1.

The complexity of a plant extract is evident from the number of peaks in an ultra-high-performance liquid chromatography (UHPLC)-MS base peak intensity chromatogram generated from a leaf dip extract of S. habrochaites LA1777. Automated peak detection yielded 3,280 retention time-mass pair features. Analysis was performed using a 110-min chromatographic gradient and detected in negative ion mode.

Sorting of the RMD values for the entire automated peak-picking data set revealed that 3,199 (98%) of the ions had positive absolute mass defects, but 2% had negative absolute mass defects typical of inorganic salt cluster ions and instrument contaminants (e.g. trifluoroacetate, NaHPO₄⁻), and these were filtered from further consideration. The ions with positive mass defects were divided into bins, with 1,805 (55% of total) falling in the RMD range of 400 to 650 ppm and 1,177 (36% of total) with RMD from 200 to 400 ppm, the latter range being typical of polyphenols. Since the objective of this exercise was the annotation of sesquiterpene glycosides from this data set, three boundary conditions satisfied by sesquiterpenoid glycosides were proposed: (1) the maximum RMD for a sesquiterpene glycoside is estimated as 636 ppm based on the theoretical m/z of 383.2439 for [M-H]⁻ of farnesol monoglycoside (C₂₁H₃₅O₆⁻); (2) the minimum RMD that a sesquiterpene glycoside (maximum of four hexose moieties) can display is 463 ppm, calculated from the theoretical m/z of 869.4024 for [M-H]⁻ of farnesol tetraglycoside; and (3) the minimum nominal m/z of a sesquiterpenoid monoglycoside should be 383 based on farnesol monoglycoside. It is notable that some terpenoid compounds are esterified to malonate, as evidenced by the malonylated diterpene glycosides of Nicotiana attenuata and the malonylated sesquiterpenes of Panax ginseng (Guangzhi et al., 2005; Heiling et al., 2010; Ruan et al., 2010; Sun et al., 2011). To account for the acetate or malonate esters of sesquiterpenoid glycosides and to allow for experimental error in mass measurement, we propose that nearly all compounds in this class should fall in the RMD range of 440 to 640 ppm. The number of detected ions with RMD of 440 to 640 ppm detected was 1,280 (38% of total), and this number was reduced to 1,076 (33% of total) after application of the low-mass (m/z 383) cutoff. Next, this list of putative sesquiterpenoid glycosides was sorted by descending peak area, and the 200 most abundant ions were selected for further processing (Supplemental Table S1).

Distinguishing Terpenoid Glycosides from Other Compounds

Applying the RMD and molecular mass criteria described allows for the inclusion of nearly all sesquiterpene glycosides, but the final list also may include some nonterpenoids (Supplemental Table S1). To distinguish these, calculation of the RMD of fragment ions generated using either MS/MS or non-mass-selective CID can provide additional discriminating information. Fragment ion RMD values distinguish terpenoid glycosides from other compounds, since losses of all carbohydrate moieties will yield a fragment ion corresponding to a terpenoid core, yielding RMD values greater than 800 ppm. Furthermore, even if all sugars are not removed during fragmentation, the RMD values of fragment ions formed by terpenoid glycosides will be greater than that of the pseudomolecular ion, because RMDs are less than 350 ppm for the neutral hexose substructures and their fragments, values much less than for terpenoid cores (Table I). Therefore, terpenoid glycosides are characterized by fragment ions that display increasing RMD as their masses decrease from the removal of glycoside groups. This phenomenon is illustrated in Figure 2, which shows the MS/MS spectra of several abundant metabolites, with pseudomolecular ion RMD falling in the 440- to 636-ppm range. Among the fragment ions of these compounds, only the fragments m/z 199 (RMD of approximately 840 ppm; Fig. 2, A and 2B) display RMD close to that of isoprene or its oligomers (919 ppm), but m/z 199 has a mass too low to be an oxygenated sesquiterpenoid core (C₁₅H₂₄ would be 204 D). In addition, there is no systematic increase of RMD as fragment masses decrease among the fragment ions in any of these compounds, suggesting that the groups being lost have high hydrogen contents similar to, or greater than, the intact molecule. These findings suggest that the molecules are not terpenoid glycosides; in fact, the metabolites whose MS/MS spectra are depicted in Figure 2, A to C, are all acylsucroses. In contrast, the MS/MS spectra of glycosides of the sequiterpenoid campherenane diol (discussed below) shown in Figure 2, D and E, show a systematic increase in RMD as major fragment masses decrease, consistent with a hydrogen-rich terpenoid core and neutral mass losses of glycosides. Only the less-abundant carbohydrate-derived product ions of m/z 161 and 323 (Fig. 2D) and m/z 179 and 323 (Fig. 2E) deviate from this trend.

Table I. Characteristic fragment ions observed in negative ion mode MS/MS spectra for various sugar oligosaccharides and monosaccharides.

The masses shown correspond to [M-H]⁻ formed by each sugar group. The MS/MS spectra of candidate terpenoid compounds were examined for the presence of these fragment ions for identification of the presence of these oligosaccharides in the terpenoids.

Negative Ion Mode Fragment Ion (Theoretical Exact Mass)	RMD	Common Sugar Moiety
m/z	ppm
503.1618	321	Trihexoside (hexose-hexose-hexose; C18H31O16−)
485.1512	312	Trihexoside-water (C18H29O15−)
589.1622	275	Trihexoside malonate ester (C21H33O19−)
571.1516	265	Trihexoside malonate ester-water
341.1089	319	Dihexoside (hexose-hexose; C12H21O11−)
323.0984	304	Dihexoside-water (C12H19O10)
179.0561	313	Monohexoside (hexose; C6H11O6−)
221.0667	302	Monohexoside acetate ester (C8H13O7−)
161.0455	283	Monohexoside-water (C6H9O5−)
101.0232	230	Fragment ion from hexoses (C4H5O3−)
113.0228	202	Fragment ion from hexoses
125.0244	195	Fragment ion from hexoses

Figure 2.

Negative ion mode multiplexed CID mass spectra of S. habrochaites LA1777 metabolites. A, Acylsugar S4:22; RMD = 492 ppm for [M+formate]⁻. B, Acylsugar S4:23; RMD = 402 ppm for [M+formate]⁻. C, Acylsugar S4:17; RMD = 440 ppm for [M+formate]⁻. D, Negative ion mode MS/MS spectrum of products of m/z 609 [M+formate]⁻ of campherenane diol diglucoside. E, MS/MS spectrum of products of m/z 811 [M-H]⁻ from campherenane diol triglycoside malonate ester. F, Negative ion mode multiplexed CID mass spectrum of the triterpenoid glycoalkaloid tomatine from S. habrochaites LA1777. All chromatographically resolved isomers displayed fragments of the same m/z values. Values for RMD of the major fragment ions are presented. All displayed negative ion mode CID mass spectra were obtained using a collision potential of −60 V, and MS/MS spectra were obtained using a collision potential of −50 V. All chromatographically resolved isomers displayed fragments of the same m/z values.

Annotation of Sesquiterpene Diol Glycosides from S. habrochaites LA1777

An example workflow for metabolite annotation follows. In the list of the 200 S. habrochaites LA1777 metabolite ions with greatest peak areas within RMD 440 to 640 ppm (as discussed below), a metabolite m/z of 609 was ranked 17th in peak area (Supplemental Table S1). Negative ion mode multiplexed CID mass spectra of these compounds yielded fragment ions that displayed a systematic increase of RMD with decreasing mass, consistent with losses of neutral fragments lower in hydrogen content than the intact molecule. This observation flagged the metabolite as a potential terpenoid glycoside. In order to ensure that these fragment ions were derived from the proposed pseudomolecular ion, MS/MS spectra were generated.

Since multiplexed CID results can be complicated by the formation of fragments arising from other coeluting metabolites, the MS/MS spectrum of products of m/z 609 (Fig. 2D) was generated. A fragment ion at m/z 563 was observed, corresponding to the loss of HCOOH. Since formic acid was in the mobile phase, m/z 609 was annotated as [M+formate]⁻ of a metabolite of 564 D. Such ionization behavior is common for glycosides that lack acidic functional groups. The next most abundant fragment was m/z 401, corresponding to one less hexose moiety than m/z 563. RMD values of both of these fragments (539 and 631 ppm for m/z 563 and 401, respectively) increased as the m/z of the fragment decreased (Fig. 2D), consistent with annotation as a terpenoid glycoside. However, no prominent fragment ions with high RMD typical of terpenoid cores were observed with m/z < 401. The fragment ion mass of m/z 401.2532 suggested a formula of C₂₁H₃₇O₇⁻, which has six more than the 15 carbon atoms that are usually found in sesquiterpenes, suggesting the presence of an additional hexose not released during fragmentation. A fragment ion of m/z 323.098 (RMD = 303 ppm) was tentatively assigned as [dihexose-H-H₂O]⁻ (C₁₂H₁₉O₁₀⁻), suggesting a diglucoside where the two hexose groups are linked to one another. Additional evidence for a glycoside was provided by the fragment at m/z 161.04 (RMD = 271 ppm), corresponding to C₆H₉O₅⁻. Further characterization of this compound required purification and structure determination using one-dimensional and two-dimensional NMR, since further fragmentation of the core was not observed in negative ion mode and the mass spectra were not consistent with previously known metabolites. The NMR spectra confirmed the structure as the sesquiterpenoid glycoside campherenane diol diglucoside, as we reported earlier (Ekanayaka et al., 2014).

Another example of how RMD values guide the discovery of more complex terpenoid glycosides is presented in the form of a metabolite detected in negative ion profiling of S. habrochaites LA1777 leaf trichomes. The metabolite was detected as m/z 811.3587 (RMD = 442 ppm), perhaps higher in molecular mass and with lower RMD than expected for a sesquiterpenoid glycoside. Its MS/MS product ion spectrum (Fig. 2E) shows fragments formed by the loss of CO₂ to give m/z 767.3707 (RMD = 483 ppm) followed by the loss of C₂H₂O to give m/z 725.3587 (RMD = 495 ppm). Both fragments are characteristic of malonate esters. Further fragmentation generated ions of m/z 563.3057 (RMD = 543 ppm), m/z 401.2516 (RMD = 627 ppm), and m/z 239.2017 (RMD = 841 ppm). With the exception of common carbohydrate fragment ions, RMD values increased as fragment ion mass decreased, again consistent with a terpenoid glycoside. The fragment ion at m/z 239.2017 was annotated as a sesquiterpenoid core (C₁₅H₂₇O₂⁻), as it did not undergo further fragmentation. Based on these observed characteristics, this compound can be annotated as a sesquiterpenoid triglycoside malonate ester.

The application of RMD analysis is not limited to sesquiterpenoid metabolites but is readily extended to other related and unrelated substances. MS/MS spectra of the triterpenoid glycoalkaloid tomatine displayed similar behavior. The RMD of the [M-H]⁻ ion of tomatine (m/z 1032.5) is 520 ppm. The major fragments display an increasing RMD from 520 to 674 ppm with decreasing product ion mass and correspond to neutral losses of relatively hydrogen-deficient carbohydrate moieties (Fig. 2F). The relationship between fragment ion RMD value and ion mass (m/z) for a tetraacylsucrose, a sesquiterpenoid glycoside, and the triterpenoid glycoside tomatine shows how terpenoid glycosides can be distinguished from other compounds based on fragment ion RMD (Fig. 3). For the two glycosides that possess a terpenoid core, RMD values of fragment ions that contain the terpenoid core are greater than that for the precursor ion, whereas the reverse is true, with the exception of the fatty acyl anion at m/z 199, for the tetraacylsucrose.

Figure 3.

Relationships between negative ion mode MS/MS fragment ion masses (m/z values) and RMD values for a triterpenoid glycoalkaloid (tomatine; indicated by triangles), a sesquiterpene triglycoside malonate ester (sesquiterpene triglycoside-811; indicated by diamonds), and a tetraacylsucrose (AS2-765; indicated by circles) from S. habrochaites LA1777 leaf dip extract.

The utility of RMD filtering was then assessed by applying RMD-based filtering criteria for sesquiterpenoid glycosides, as described above, to the most abundant 200 metabolite ions in the list of S. habrochaites LA1777 metabolites detected by nontargeted LC-MS profiling. There were 224 peaks annotated as sesquiterpene glycosides, including multiple isomers for each elemental formula, as presented in Table II. Three different sesquiterpenoid core formulas were established from MS/MS spectra, including the campherenane diol core (C₁₅H₂₈O₂). The MS/MS data generated for each of these compounds and the RMD of each fragment ion are presented in Supplemental Figures S1 to S21.

Table II. Groups of metabolites identified as sesquiterpenoid glycosides from S. habrochaites LA1777 based on RMD filtering of molecular and fragment ions.

Δm, Difference between theoretical and measured m/z values, in parts per million.

Compound No.	Experimental m/z	RMD	Proposed Elemental Formula of Neutral Molecule	∆m	Compound Type	Measured m/z of Terpenoid Core Fragment Ion	Elemental Formula of Terpenoid Core Fragment Ion	∆m	RMD of Terpenoid Core Fragment	No. of Isomers
		ppm		ppm					ppm
1	545.2932	538	C27H46O11	−1	Sesquiterpene II diglycoside	221.1527	C14H21O2−	−9	691	8
2	587.3049	519	C29H48O12	−3	Sesquiterpene II diglycoside acetate ester	221.1529	C14H21O2−	−8	692	1
3	631.2929	464	C37H44O13	3	Sesquiterpene II diglycoside malonate ester	221.1565	C14H21O2−	8	708	2
4	707.3112	440	C32H52O17	−3	Sesquiterpene II triglycoside	221.1539	C14H21O2−	−4	696	4
5	793.3474	438	C36H58O19	1	Sesquiterpene II diol triglycoside malonate ester	221.1527	C14H21O2−	−9	691	11
6	401.2520	628	C21H38O7	−6	Campherenane diol monoglycoside	239.1997	C15H27O2−	−8	836	6
7	443.2632	594	C23H40O8	−4	Campherenane diol monoglycoside acetate ester	239.1994	C15H27O2−	−9	834	14
8	445.2421	544	C22H38O9	−4	Campherenane diol monoglycoside derivative	239.1999	C15H27O2−	−7	836	5
9	487.2536	520	C24H40O10	−3	Campherenane diol monoglycoside malonate ester	239.1994	C15H27O2−	−9	834	9
10	563.3055	542	C27H48O12	−3	Campherenane diol diglycoside	239.2048	C15H27O2−	13	857	7
11	605.3152	521	C29H50O13	−4	Campherenane diol diglycoside acetate ester	239.1993	C15H27O2−	−10	834	9
12	649.3042	469	C30H50O15	−5	Campherenane diol diglycoside malonate ester	239.1993	C15H27O2−	−10	834	14
13	725.3607	497	C33H58O17	2	Campherenane diol triglycoside	239.2007	C15H27O2−	−4	840	6
14	811.3587	442	C36H60O20	−2	Campherenane diol triglycoside malonate ester	239.2006	C15H27O2−	−4	839	13
15	411.1986	483	C21H32O8	−9	Sesquiterpene III monoglycoside	249.1481	C15H21O3−	−4	595	13
16	453.2082	459	C23H34O9	−9	Sesquiterpene III monoglycoside acetate ester	249.1483	C15H21O3−	−3	596	14
17	497.2011	404	C24H34O11	−3	Sesquiterpene III monoglycoside malonate ester	249.1475	C15H21O3−	−6	592	11
18	413.2143	519	C21H34O8	−9	Sesquiterpene I monoglycoside	251.1634	C15H23O3−	−8	651	17
19	455.2270	499	C22H36O9	−4	Sesquiterpene I monoglycoside acetate ester	251.1638	C15H23O3−	−6	653	21
20	499.2162	433	C24H36O12	−5	Sesquiterpene I monoglycoside malonate ester	251.1643	C15H23O3−	−4	655	11
21	617.2795	453	C29H45O14	−2	Sesquiterpene I diglycoside acetate ester	251.1636	C15H23O3−	−7	652	4
22	661.2693	407	C30H46O16	−3	Sesquiterpene I diglycoside malonate ester	251.1639	C15H23O3−	−6	653	8
23	823.3245	394	C36H56O21	1	Sesquiterpene I triglycoside malonate ester	251.1640	C15H23O3−	−5	653	5
24	985.3742	380	C30H50O26	−3	Sesquiterpene I tetraglycoside malonate ester	251.1641	C15H23O3−	−5	654	11

Discovery of Conjugated Terpenoid Glycosides from S. habrochaites LA1777

RMD filtering of the list of m/z-retention time pairs extracted from nontargeted metabolite profiling of S. habrochaites LA1777 revealed numerous m/z values consistent with sesquiterpenoid glycosides. Among those giving the greatest integrated peak areas were three nominal masses (m/z 661, 633, and 591) that gave CID mass spectra suggestive of glycosides, yielded multiple chromatographic peaks consistent with several isomers (Fig. 4), and were judged to represent metabolites in sufficient abundance for their isolation and characterization by NMR spectroscopy.

Figure 4.

HPLC-MS extracted ion chromatogram profiles for masses of three compounds purified from S. habrochaites LA1777 showing evidence of 10 isomers of [M-H]⁻ (m/z 661) of sesquiterpene I diol diglucoside malonate ester (compound 22 formula from Table II; A), three isomers of [M+formate]⁻ (m/z 633) of sesquiterpene II alcohol diglucoside acetate ester (compound 2 formula from Table II; B), and eight isomers of [M+formate]⁻ (m/z 591) of sesquiterpene II alcohol diglucoside (compound 1 formula from Table II; C). Structures of compounds of Equations 1, 2, and 22 determined by NMR and MS/MS are presented. Carbon atoms are numbered in accordance with NMR assignments in Supplemental Table S2.

Three individual isomers designated with formulas 1, 2, and 22 (Table II) were selected based on RMD criteria and were purified using HPLC. Their NMR spectra (presented in Supplemental Table S2) revealed structures with methyl branching consistent with isoprenoid precursors, although the aglycone cores differed in structure from known volatile or nonvolatile sesquiterpene metabolites within the genus Solanum. The core for the isolated compound (Fig. 4A, peak 8a; detected as m/z 661 in negative ion mode) was consistent with an oxidized core of formula C₁₅H₂₄O₃, and this core formula was designated as sesquiterpene I. NMR spectra revealed the purified isomer to be an acyclic metabolite with a ketone group near the center of the carbon chain (Supplemental Fig. S22). NMR spectra of two additional metabolites (Fig. 4, B [peak 3b; m/z 663] and C [peak 6c; m/z 591]) suggested that both were glycosides of a common aglycone core of C₁₅H₂₆O, and this was designated sesquiterpene II. The two masses were consistent with the compounds differing by the attachment of one acetyl group. Structures of the three metabolites are presented in Figure 4.

Neither terpenoid core displays much structural similarity to volatile sesquiterpenes of S. habrochaites or other documented metabolites within the genus, nor do their structures suggest that they are formed by the action of common terpene synthase enzymatic transformations. RMD filtering accelerated the recognition of the presence of these unusual compounds, but it is clear that more investigation is needed to determine the biosynthetic origins and the biological functions of these metabolites.

Application of RMD Filtering for the Mining of Intermediates in Terpene Indole Alkaloid Biosynthesis in Catharanthus roseus

The original metabolome data set from the Medicinal Plants Consortium database has 3,229 m/z-retention time pairs derived from nontargeted LC-MS analysis of C. roseus tissue extracts. The distribution of RMD values for all detected ions is presented in Figure 5. Applying the boundary conditions discussed below resulted in 2,109 m/z-retention time pairs (65%) that satisfy the criteria as potential terpene alkaloid pathway intermediates, and this finding suggests that a large fraction of the specialized metabolome may be derived from common or similar precursors (Supplemental Table S3). All 12 monoterpene indole alkaloids annotated in the Medicinal Plants Consortium database were correctly assigned as lying within the RMD search criteria. The only annotated metabolite falling outside this range was Suc, reflecting the success of the filtering in excluding metabolites from different structural classes. For distinguishing potential terpene indole alkaloids from the nonterpenoid compounds, RMD of fragment ions can be used. Fragment ions of terpene indole alkaloids that possess the terpenoid component in it display a characteristic increase of RMD compared with the parent ion as the fragment ion m/z values decrease. This can be inferred based on the relationship between RMD and fragment ion masses reported for vinblastine, vindoline, and catharanthine (Fig. 6). Furthermore, terpene indole alkaloids display the presence of a number of even-mass-fragment ions as observed in their CID mass spectra (Supplemental Figs. S23–S25) that are characteristic of fragment ions containing an odd number of nitrogen atoms.

Figure 5.

Histogram of RMD values for C. roseus metabolites extracted from the Medicinal Plants Consortium metabolite database (available at http://metnetdb.org/PMR). The highlighted region corresponds to the range of RMD values anticipated for monoterpene indole alkaloid pathway intermediates. Data were generated by UHPLC-time-of-flight MS in positive ion mode.

Figure 6.

RMD filtering relationships between pseudomolecular and fragment ion masses for the terpene indole alkaloids vinblastine (A), vindoline (B), and catharanthine (C) from C. roseus. A slight increase of RMD of fragment ions is observed as their m/z decreases, consistent with a relatively hydrogen-rich terpenoid core.

The applications discussed in this report demonstrate the applicability of RMD filtering for discovering terpenoid compounds even when the terpenoid component represents only a minority fraction of the mass of the molecules of interest and has been subjected to a number of biotransformations, as in the case of vinblastine. However, RMD filtering still allows for distinguishing vinblastine among other compounds, and the gradual increase of the RMD of fragment ions with decreasing ion mass suggests the presence of a terpenoid core. Similar to the case with sesquiterpene triglycoside malonate esters in S. habrochaites, the sesquiterpene component was a minor fraction of metabolite mass.

CONCLUSION

The range of specialized metabolites in the plant kingdom is astounding, yet deep explorations into the metabolomes of nonmodel plants face enormous data sets and would benefit from tools that guide a focus on specific biosynthetic classes. Analyses using LC-MS with multiplexed CID generate molecular and fragment mass information for all ionized metabolites, providing that the ion signal is sufficient. When coupled with medium- to high-resolution mass measurements, this approach reduces the need for separate MS/MS analyses for all metabolites and generates information about molecular and fragment masses with sufficient accuracy to allow for useful RMD measurements. Analysis of the RMD variation among precursor ions and product/fragment ions accelerates metabolite discovery by eliminating signals with RMD values that are inconsistent with a target class of metabolites. For this investigation, while we cannot exclude the possibility that the RMD values consistent with terpenoid conjugates may include nonterpenoids, this sorting removes many nonterpenoid metabolites and guides a focus on candidate terpenoid conjugates. This strategy enabled the annotation of more than 200 novel sesquiterpene glycosides from a plant system that has been studied for several decades. We anticipate that RMD filtering of nontargeted metabolite profiles will propel the annotation and identification of terpenoid glycosides that have been underappreciated owing to the lack of a systematic method for the recognition of their presence.

The research discussed here used negative ion mode MS/MS for the annotation of terpene glycosides from complex matrices and provides, to our knowledge, the first evidence for a remarkably extensive and diverse group of sesquiterpenoid glycosides in S. habrochaites LA1777. We recognize that RMD values for molecular mass alone yield limited resolution of compound classes, and many metabolites are derived from multiple precursors (e.g. prenylated polyphenols and terpenoid glycosides). For more refined annotations, examinations of RMD values of molecular and fragment ions as well as neutral mass losses provide evidence of multiple biosynthetic precursors, as was demonstrated for the terpenoid glycosides described in this report. In addition, RMD filtering is equally applicable to positive ion mode data sets, as demonstrated by its application in the correct annotation of known terpene indole alkaloids and the assignment of more than 1,000 ions as candidate terpenoid intermediates from C. roseus. We envision that the development of algorithms that provide automated classification of metabolites based on molecular and fragment RMD values will accelerate discoveries of gene functions that regulate plant chemistry.

MATERIALS AND METHODS

Plant Material

Solanum habrochaites LA1777 plants were grown in Michigan State University plant growth chambers (28°C, 16 h of light/8 h of dark day/night cycle, 150 µmol m⁻² s⁻¹, 96% humidity) for 6 weeks from seeds obtained from the C.M. Rick Tomato Genetics Resource Center (University of California, Davis). Ten leaflets harvested from each plant (6 weeks postgermination) were extracted by dipping in 5 mL of methanol:water (80:20, v/v) for about 30 s. Three biological replicates were used for profiling. Extracts were concentrated by drying under a stream of N₂ gas at room temperature, and the residues were redissolved in 0.5 mL of methanol:water (80:20, v/v). The extract was centrifuged (10,000g for 10 min at 25°C) to remove debris; the supernatant was transferred to an autosampler vial for LC-MS and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses.

LC-MS and MS/MS Analyses

Initial exploration of the complexity of S. habrochaites LA1777 extracts was performed using a Waters LCT Premier time-of-flight mass spectrometer coupled to Shimadzu LC-20AD pumps. Separations were performed using an Ascentis Express C18 UHPLC column (2.1 × 100 mm, 2.7 µm; Supelco), and metabolites were detected using electrospray ionization in negative ion mode. Solvents used were 0.15% (v/v) aqueous formic acid, pH 2.85 (A), and methanol (B). The LC gradient was as follows: 0 to 1 min (99:1), 1.01 to 100 min (linear ramp to 20:80), 100.01 to 101 min (linear ramp to 1:99), 101 to 105 min (hold at 1:99), 105 to 106 min (linear ramp to 99:1), and hold at 99:1 over 106 to 110 min. The flow rate was 0.3 mL min⁻¹, and column temperature was held at 35°C. Sample volume injected to the column was 10 µL. Mass spectra were acquired over m/z 50 to 1,500 using dynamic range extension. Mass resolution (mass divided by mass peak width [M/ΔM] measured as the full width-half maximum) was approximately 10,000. Five parallel collision energy functions were used by switching the aperture 1 voltage between 5, 20, 40, 60, and 80 V with 0.1 s per function. Other parameters include capillary voltage of 2.50 kV, desolvation temperature of 350°C, source temperature of 100°C, cone gas (N₂) at 40 L h⁻¹, and desolvation gas (N₂) at 350 L h⁻¹.

All LC-MS/MS experiments used for the characterization of novel terpenoid metabolites from S. habrochaites LA1777 were performed using a Waters Xevo G2-S QToF mass spectrometer coupled to a Waters Acquity ultra-high pressure LC system. The same chromatographic column and solvents used in experiments performed on the LCT Premier were used here. The solvent gradient (A:B) was as follows: 0 to 1 min (99:1), 1.01 to 4 min (linear ramp to 55:45), 4.01 to 9 min, (hold at 55:45), step to 50:50 and hold at 50:50 over 9.01 to 14 min, step to 1:99 and hold at this ratio over 14.01 to 17 min, and step to 99:1 and hold at this composition over 17.01 to 20 min. The flow rate was 0.3 mL min⁻¹, and column temperature was held at 35°C. Mass spectra were acquired using negative ion mode electrospray ionization and dynamic range extension over m/z 50 to 1,500, with mass resolution (M/ΔM, full width-half maximum) of approximately 20,000. Five parallel collision energy functions were used, with 0.1 s per function. Collision cell potentials used for negative ion mode fragmentation for each function were 5, 15, 25, 35, and 60 V. Other parameters include capillary voltage of 2.14 kV, desolvation temperature of 280°C, source temperature of 90°C, cone gas (N₂) at 0 L h⁻¹, and desolvation gas (N₂) at 800 L h⁻¹.

Data Processing

Automated peak detection, integration, and retention time alignment were performed using Waters MarkerLynx XS software, and lists of m/z values, retention times, and extracted ion chromatogram peak areas were exported as text files and processed further using Microsoft Excel software. The lowest collision energy function (function 1) was used for peak detection, integration, retention time alignment, and deisotoping. The parameters used with MarkerLynx processing were as follows: marker intensity threshold, 800 counts; mass window, 0.05 D; retention time window, 0.25 min; m/z range, 100 to 1,500; and retention time range, 0.5 to 20 min. Peak smoothing was not applied.

Structure Elucidation of Candidate Sequiterpenoid Glycosides from S. habrochaites LA1777

Details of the experimental procedures used to isolate sesquiterpenoid glycoside metabolites and determine their structures using LC-MS/MS and NMR spectroscopy are presented in the Supplemental Text S1. Metabolite structures, NMR chemical shifts (Supplemental Table S1), accurate mass measurements, and MS/MS data are included. NMR assignments were made based on one-dimensional ¹H and ¹³C spectra and two-dimensional ¹H-¹H correlation spectroscopy and Nuclear Overhauser Effect spectroscopy or ¹H-¹³C Heteronuclear Single Quantum Coherence, Heteronuclear Multiple Bond Correlation, and Total Correlation Spectroscopy spectra. Since none of the metabolite identities have been confirmed by synthesis, structures should be considered putatively annotated compounds or level 2 based on the Metabolomics Standards Initiative guidelines (Sumner et al., 2007).

LC-MS Analysis of Catharanthus roseus Metabolites

C. roseus tissue extracts were analyzed by LC-MS, and the data are available to the public at the Medicinal Plants Consortium Metabolome database (http://metnetdb.org/PMR/; Wurtele et al., 2012). Analyses were performed using a Waters LCT Premier time-of-flight mass spectrometer coupled to Shimadzu LC-20AD pumps. Separations were performed using an Ascentis Express C18 UHPLC column (2.1 × 50 mm, 2.7 µm; Supelco), and the ionized compounds were detected in positive ion mode electrospray ionization. Solvents used were 10 mm aqueous ammonium formate, pH 2.85 (A), and a 1:1 mixture of methanol and acetonitrile (B). The solvent gradient (A:B) was as follows: 0 to 1 min (90:10), 1.01 to 23 min (linear ramp to 10:90), 23.01 to 27 min (hold at 10:90), linear ramp to 90:10 by 28 min, and hold at 90:10 over 28 to 32 min. The flow rate was 0.3 mL min⁻¹, and column temperature was held at 40°C. Mass spectra were acquired using positive ion mode electrospray ionization and dynamic range extension over m/z 50 to 1,500, with mass resolution (M/ΔM, full width-half maximum) of approximately 8,500. Four parallel collision energy functions were used, with 0.15 s per function. Collision cell potentials used for positive ion mode fragmentation for each function were 20, 40, 60, and 80 V. Other parameters include capillary voltage of 3 kV, desolvation temperature of 350°C, source temperature of 100°C, cone gas (N₂) at 40 L h⁻¹, and desolvation gas (N₂) at 350 L h⁻¹.

Annotation of C. roseus Metabolomes

The performance of the RMD filtering approach was evaluated by applying it to annotate metabolites from C. roseus, which accumulates monoterpene indole alkaloids (Svoboda et al., 1959; O’Connor and Maresh, 2006). This was performed by establishing appropriate boundary conditions for monoterpene metabolites and assessing whether the proposed monoterpene-derived intermediates from C. roseus documented in the Medicinal Plants Consortium Metabolome database were correctly classified. The precursors of monoterpene indole alkaloids are tryptamine {theoretical m/z of 161.1073 ([M+H]⁺); RMD = 666 ppm} and the iridoid glycoside secologanin {theoretical m/z of 389.1442 ([M+H]⁺); RMD = 371 ppm}. One proposed precursor of secologanin is iridotrial {theoretical m/z of 183.1016 ([M+H]⁺); RMD = 555 ppm; Miettinen et al., 2014}. The biosynthetic pathway dictates that the indole component of these compounds originated from the tryptamine group, while the iridotrial acts as a precursor of the monoterpene component (El-Sayed and Verpoorte, 2007). Direct condensation of iridotrial with tryptamine would generate the simplest form of terpene indole alkaloid with elemental formula C₂₀H₂₅N₂O₂⁺ {theoretical m/z of 325.1911 ([M+H]⁺); RMD = 588 ppm}. Strictosidine {theoretical m/z of 531.2337 ([M+H]⁺); RMD = 440 ppm} is formed by condensation of the monoterpenoid glycoside secologanin with tryptamine (El-Sayed and Verpoorte, 2007). Additional biosynthetic steps result in the formation of more complicated terpene indole alkaloids, including vinblastine, which is consistent with the formation of a strictosidine dimer {theoretical m/z of 1,061.46 ([M+H]⁺); RMD = 434 ppm}. Based on this information, the minimum RMD for mining for terpene indole alkaloids can be proposed as about 420 ppm, and the maximum RMD can be estimated as about 588 ppm. To account for errors in mass measurements, the RMD range of 350 to 600 ppm was employed, and the mass range was estimated to span from about m/z 325 to 1,061 for [M+H]⁺ ions. Therefore, compounds with RMDs ranging from 350 to 600 ppm and m/z ranging from 320 to 1,100 were selected as representing potential pathway intermediates involved in monoterpene indole alkaloid biosynthesis in C. roseus.

Supplemental Data

The following supplemental materials are available.

• Supplemental Figure S1. Negative ion mode product ion MS/MS spectrum of products from [M-H]⁻ (m/z 649) for campherenan-2,12-diol diglucoside malonate ester.

• Supplemental Figure S2. Negative ion mode product ion MS/MS spectrum of products from [M-H]⁻ (m/z 487) for campherenan-2,12-diol monoglucoside malonate ester.

• Supplemental Figure S3. Negative ion mode product ion MS/MS spectrum of products from [M+formate]⁻ (m/z 609) for campherenan-2,12-diol diglucoside.

• Supplemental Figure S4. Negative ion mode product ion MS/MS spectrum of products from [M+formate]⁻ (m/z 651) for campherenan-2,12-diol diglucoside acetate ester.

• Supplemental Figure S5. Negative ion mode product ion MS/MS spectrum of products from [M+formate]⁻ (m/z 771) for a campherenane-2,12-diol triglycoside.

• Supplemental Figure S6. Negative ion mode product ion MS/MS spectrum of products from [M+formate]⁻ (m/z 591) for a sesquiterpene II dihexoside.

• Supplemental Figure S7. Negative ion mode product ion MS/MS spectrum of products from [M-H]⁻ (m/z 631) for a sesquiterpene II dihexoside malonate ester.

• Supplemental Figure S8. Negative ion mode product ion MS/MS spectrum of products from [M-H]⁻ (m/z 793) for a sesquiterpene II trihexoside malonate ester.

• Supplemental Figure S9. Negative ion mode product ion MS/MS spectrum of products from [M+HCOO]⁻ (m/z 633) for a sesquiterpene II dihexoside acetate ester.

• Supplemental Figure S10. Negative ion mode product ion MS/MS spectrum of products from [M-H]⁻ (m/z 661) for a sesquiterpene I diglycoside malonate ester.

• Supplemental Figure S11. Negative ion mode product ion MS/MS spectrum of products from [M-H]⁻ (m/z 499) sesquiterpene I monoglycoside malonate ester.

• Supplemental Figure S12. Negative ion mode product ion MS/MS spectrum of [M-H]⁻ (m/z 455) for sesquiterpene I monoglycoside acetate ester.

• Supplemental Figure S13. Negative ion mode product ion MS/MS spectrum of [M-H]⁻ (m/z 413) of sesquiterpene I monoglycoside.

• Supplemental Figure S14. Negative ion mode product ion MS/MS spectrum of [M+HCOO]⁻ (m/z 499) for sesquiterpene I monoglycoside malonate ester.

• Supplemental Figure S15. Negative ion mode product ion MS/MS spectrum of [M-H]⁻ (m/z 497) of sesquiterpene III monoglycoside malonate ester.

• Supplemental Figure S16. Negative ion mode product ion MS/MS spectrum of products of [M-H]⁻ (m/z 411) of sesquiterpene III monoglycoside.

• Supplemental Figure S17. Negative ion mode product ion MS/MS spectrum of products from [M-H]⁻ (m/z 617) for sesquiterpene I diglycoside acetate ester.

• Supplemental Figure S18. Negative ion mode product ion MS/MS spectrum of products from [M-H]⁻ (m/z 823) for sesquiterpene I triglycoside malonate ester.

• Supplemental Figure S19. Negative ion mode product ion MS/MS spectrum of products from [M-H]⁻ (m/z 985) for sesquiterpene I tetraglycoside malonate ester.

• Supplemental Figure S20. Negative ion mode product ion MS/MS spectrum of products from [M+HCOO]⁻ (m/z 489) for campherenane diol monoglycoside acetate ester.

• Supplemental Figure S21. Negative ion mode product ion MS/MS spectrum of products from [M+HCOO]⁻ (m/z 753) sesquiterpene II triglycoside.

• Supplemental Figure S22. Proposed structures of sesquiterpene I diol diglucoside malonate ester, sesquiterpene II alcohol diglucoside acetate ester, and sesquiterpene II alcohol diglucoside.

• Supplemental Figure S23. Positive ion mode multiplexed CID mass spectrum of vinblastine (m/z 811.4 is [M+H]⁺) from C. roseus.

• Supplemental Figure S24. Positive ion mode multiplexed CID mass spectrum of vindoline (m/z 457.2 is [M+H]⁺) from C. roseus.

• Supplemental Figure S25. Positive ion mode multiplexed CID mass spectrum of catharanthine (m/z 337.2 is [M+H]⁺) from C. roseus.

• Supplemental Table S1. Extracted ion chromatogram peak areas for S. habrochaites LA1777 leaf dip extracts satisfying the mass and relative mass defect criteria consistent with sesquiterpenoid glycosides.

• Supplemental Table S2. ¹H and ¹³C NMR chemical shifts for sesquiterpene glycoside compound formulas 1, 2, and 22 listed in Table 2.

• Supplemental Table S3. List of metabolite ions from C. roseus mined from the Medicinal Plants Consortium database (http://metnetdb.org/PMR) that satisfy proposed mass and relative mass defect criteria for monoterpene indole alkaloids and their pathway intermediates.

• Supplemental Text S1. Supplemental information.

Glossary

MS/MS

tandem mass spectrometry

RMD

relative mass defect

LC-MS

liquid chromatography-mass spectrometry

m/z

mass-to-charge ratio

UHPLC

ultra-high-performance liquid chromatography