Here, we describe in great detail an established and robust protocol for the extraction of glucosinolates from ground plant materials. After an on-column sulfatase treatment of the extracts, the desulfoglucosinolates are eluted and analyzed by high-pressure liquid chromatography.
Glucosinolates are a well-studied and highly diverse class of natural plant compounds. They play important roles in plant resistance, rapeseed oil quality, food flavoring, and human health. The biological activity of glucosinolates is released upon tissue damage, when they are mixed with the enzyme myrosinase. This results in the formation of pungent and toxic breakdown products, such as isothiocyanates and nitriles. Currently, more than 130 structurally different glucosinolates have been identified. The chemical structure of the glucosinolate is an important determinant of the product that is formed, which in turn determines its biological activity. The latter may range from detrimental (e.g., progoitrin) to beneficial (e.g., glucoraphanin). Each glucosinolate-containing plant species has its own specific glucosinolate profile. For this reason, it is important to correctly identify and reliably quantify the different glucosinolates present in brassicaceous leaf, seed, and root crops or, for ecological studies, in their wild relatives. Here, we present a well-validated, targeted, and robust method to analyze glucosinolate profiles in a wide range of plant species and plant organs. Intact glucosinolates are extracted from ground plant materials with a methanol-water mixture at high temperatures to disable myrosinase activity. Thereafter, the resulting extract is brought onto an ion-exchange column for purification. After sulfatase treatment, the desulfoglucosinolates are eluted with water and the eluate is freeze-dried. The residue is taken up in an exact volume of water, which is analyzed by high-pressure liquid chromatography (HPLC) with a photodiode array (PDA) or ultraviolet (UV) detector. Detection and quantification are achieved by conducting comparisons of the retention times and UV spectra of commercial reference standards. The concentrations are calculated based on a sinigrin reference curve and well-established response factors. The advantages and disadvantages of this straightforward method, when compared to faster and more technologically advanced methods, are discussed here.
It is estimated that plants produce over 200,000 different types of chemical compounds1. Only the minority of these compound seems to play a role in the plants' primary metabolism, which fuels growth and reproduction; the majority are so-called secondary metabolites. Despite their name, secondary metabolites are often critical for plant survival and reproduction, as they serve to attract pollinators or to defend the plant against pathogens and herbivores1.
Glucosinolates are a very diverse class of secondary metabolites that have been studied for over 150 years2. To date, more than 130 structurally different glucosinolates have been identified3. Broadly, glucosinolates can be subdivided into different classes based on the amino acid from which they are synthesized. Indole glucosinolates, for example, are synthesized from the amino acid tryptophan, whereas phenylalanine provides the base skeleton for the synthesis of aromatic glucosinolates4. Within classes, there is a high level of structural diversity, which is brought about by sequential chain elongation steps in the biosynthetic pathways, such as in the class of aliphatic glucosinolates, or by side chain modifications (e.g., hydroxylation)4,5. One glucosinolate plant species may contain up to 37 different glucosinolates belonging to different structural classes6. Even though plant species have typical glucosinolate profiles, intraspecific variation for the types of glucosinolates is frequently found among individuals and populations6,7. Intact glucosinolates are stored in the vacuoles of plant cells and can be found in any aboveground or belowground organ7,8,9. Upon cell rupture (e.g., by herbivory), glucosinolates are released and are mixed with the enzyme myrosinase, setting off a mustard oil bomb10. Due to the activity of myrosinase, and depending on the structure of the glucosinolate, the reaction conditions, and the presence of modifying enzymes, different pungent, toxic, or noxious compounds are formed, such as nitriles and (iso)thiocyanates11. The reaction products have high biological activities; for example, they serve as repellents of generalist insect herbivores12. The heritability and biosynthetic pathways of glucosinolates are well studied, mainly because of their importance for herbivore and pathogen resistance, their value as flavor components in mustards and cabbages, and their negative (progoitrin) and positive (glucoraphanin) effects on human health5,13,14.
Because of the great interest in glucosinolates as biologically active compounds, extraction and detection methods based on reversed-phase high-pressure liquid chromatography (HPLC) equipped with ultraviolet (UV) or photodiode array (PDA) detectors have been commonly used since the 1980s15. Based on this method, the European Communities issued a standard protocol that was tested and validated in several labs for the analysis of glucosinolates in oilseeds (Brassica napus, colza, Canola16). Others added to this method (e.g., by determining additional response factors for glucosinolates that are not present in oilseed rape)17. Despite the increasing availability of liquid chromatography-mass spectrometry (LC-MS) platforms and high-throughput protocols for glucosinolate analysis18,19, the original HPLC-UV/PDA method is still widely used by scientists. The main reasons are that this method is straightforward, cost-effective, and relatively accessible to labs without an extensive chemical-analytical knowledge infrastructure. To serve this community, we here detail the protocol for the extraction of glucosinolates from plant materials and the analysis of their desulfo-forms with HPLC-PDA.
1. Preparation of Solutions Needed for the Glucosinolate Extraction
2. Preparation of the Extraction Setup
Figure 1: Rack for glucosinolate extraction. Front view (left) and top view (right) of a self-made column rack and block for the glucosinolate extraction. Height: 100 mm, distance between shifted holes (to hold the Pasteur pipette columns): 30 mm (x-axis) x 15 mm (y-axis). Please click here to view a larger version of this figure.
3. Preparation of the Columns and Microcentrifuge Tubes
4. Extraction of Glucosinolates
5. HPLC Measurements of Extracted Samples
Time [min] | Flow [mL/min] | % A Water | % B ACN |
1 | 0.750 | 98 | 2 |
35 | 0.750 | 65 | 35 |
40 | 0.750 | 98 | 2 |
Column Temperature 40 °C. |
Table 1: Acetonitrile-water gradient for glucosinolate separation and analysis on reversed-phase HPLC.
Time [min] | Flow [mL/min] | % A Water | % B ACN |
1 | 0.750 | 98 | 2 |
10 | 0.750 | 89.3 | 10.7 |
11 | 0.750 | 98 | 2 |
Column Temperature 40 °C. |
Table 2: Shortened acetonitrile-water gradient for quantification of the five sinigrin references used for the quantification of glucosinolates.
6. Glucosinolate Identification and Quantification
Figure 2. UV spectra of the most common glucosinolate classes. UV absorption spectra (200-350 nm) of six desulfoglucosinolates (GSL), based on solutions made of commercially available reference compounds extracted as described here, representing the most common structural classes. The common name, structural name (between brackets), and structural class are given. (A) Sinigrin (2-propenyl GSL), alkenyl; (B) glucoerucin (4-methylthiobutyl GSL), thioalkenyl; (C) glucoraphanin (4-methylsulfinlybutyl GSL), sulfinyl; (D) glucobrassicin (indol-3-ylmethyl GSL), indole; (E) gluconasturtiin (2-phenylethyl GSL), aromatic; (F) sinalbin (4-hydroxybenzyl GSL), aromatic. Please click here to view a larger version of this figure.
This method enables the detection and separation of commonly found desulfoglucosinolates in all structural classes (Figure 3). The detrimental 2-hydroxyglucosinolate progoitrin comes relatively early in the chromatogram and is clearly separated from the beneficial glucosinolate glucoraphanin, the only methylsulfinylglucosinolate in this sample. Sinigrin, gluconapin, and glucobrassicanapin form an eluotropic series of alkenyl glucosinolates with increasing side-chain lengths (C3, C4, and C5, respectively). A similar logical series is visible for the two methylthioalkenyl glucosinolates, glucoiberverin (C3) and glucoerucin (C4). The peaks of the three indole glucosinolates, glucobrassicin and its derivatives 4-hydroxy and 1-methoxyglucobrassicin (neoglucobrassicin), are also clearly separated. It should be noted that the peaks of neoglucobrassicin and glucoerucin, as well as gluconasturtiin, the only aromatic glucosinolate in this sample, are particularly high in this Brassica extract due to the addition of root extracts to the mix9.
Figure 3: Chromatogram of a glucosinolate extract. Detail (1-32 min) of an HPLC chromatogram resulting from the analysis of combined root and shoot samples from Brassica nigra, B. rapa, and B. oleracea. The peak labels indicate the retention time and the abbreviations for identified desulfoglucosinolates (GSL). PRO = progoitrin (2-OH-3-butenyl GSL); RAPH = glucoraphanin (4-methylsulfinlybutyl GSL); SIN = sinigrin (2-propenyl GSL), GNA = gluconapin (3-butenyl GSL); 4OH = 4-hydroxyglucobrassicin; IBV = glucoiberverin (3-methylthiopropyl GSL); GBN = glucobrassicanapin (4-pentenyl GSL); ERU = glucoerucin (4-methylthiobutyl GSL); GBC = glucobrassicin (indol-3-ylmethyl GSL); NAS = gluconasturtiin (2-phenylethyl GSL); NEO = neoglucobrassicin (1-MeOH-glucobrassicin). Please click here to view a larger version of this figure.
Longer chain methylsulfinyl glucosinolates, which are commonly found in the model plant Arabidopsis, also show an eluotropic series, as seen in a root extract of Rorippa austriaca. Glucohesperalin (C6), glucosiberin (C7), glucohirsutin (C8), and glucoarabin (C9) appear at regular intervals on the chromatogram (Figure 4). Together with the UV spectra of the peaks, such eluotropic logical series may be used to classify, and provisionally identify, unknown glucosinolates.
Figure 4: Chromatogram (frame 9-30 min) of the desulfoglucosinolates in a Rorippa austriaca root extract. The peak labels indicate the retention time and the abbreviations for identified desulfoglucosinolates (GSL). HES = glucohesperin (6-methylsulfinylhexyl GSL); SBE = glucosiberin (7-methylsulfinylheptyl GSL); GBC = glucobrassicin (indol-3-ylmethyl GSL); HIR = glucohirsutin (8-methylsulfinlyoctyl GSL); ARA = glucoarabin (9-methylsulfinylnonylglucosinolate); NEO = neoglucobrassicin (1-MeOH-glucobrassicin). Please click here to view a larger version of this figure.
Common name | Side chain structure | Rt (min)* | 229 nm | reference# |
aliphatic glucosinolates | ||||
Glucocapparin | methyl | 3.5 | 1 | Brown |
Sinigrin | 2-propenyl | 5.5 | 1 | Brown, EC |
Gluconapin | 3-butenyl | 9.5 | 1.11 | EC |
Glucobrassicanapin | 4-pentenyl | 13.5 | 1.15 | EC |
Glucoiberverin | 3-methylthiopropyl | 10.9 | 0.8 | Brown |
Glucoerucin | 4-methylthiobutyl | 14.0 | 0.9 | Brown |
Glucoiberin | 3-methylsulfinylpropyl | 3.7 | 1.2 | Brown |
Glucoraphanin | 4-methylsulfinylbutyl | 4.9 | 0.9 | Brown |
Glucoalyssin | 5-methylsulfinylpentyl | 7.6 | 0.9 | Brown |
Glucohesperin | 6-methylsulfinylhexyl | 10.5 | 1 | Brown |
Glucosiberin | 7-methylsulfinylheptyl | 13.5 | 1 | Brown |
Glucohirsutin | 8-methylsulfinyloctyl | 16.8 | 1.1 | Brown |
Glucoarabin | 9-methylsulfinylnonyl | 20.5 | 1 | |
Glucocheirolin | 3-methylsulfonylpropyl | 4.2 | 0.9 | Brown |
Progoitrin | 2(R)-OH-3-butenyl | 4.5 | 1.09 | Buchner, EC |
Gluconapoleiferin | 2-OH-5-pentenyl | 8.3 | 1 | EC |
indole glucosinolates | ||||
4-hydroxyglucobrassicin | 4-hydroxyindol-3-ylmethyl | 11.2 | 0.28 | Buchner, EC |
Glucobrassicin | indol-3-ylmethyl | 15.3 | 0.29 | Buchner, EC |
4-Methoxyglucobrassicin | 4-methoxyindol-3-ylmethyl | 18.2 | 0.25 | Buchner, EC |
Neoglucobrassicin | 1-methoxyindol-3-ylmethyl | 22.5 | 0.2 | Buchner, EC |
aromatic glucosinolates | ||||
Sinalbin | 4-hydroxybenzyl | 8.1 | 0.5 | Buchner |
Glucosibarin | 2(R)-OH-2-phenylethyl | 12.1 | 0.95 | see next |
Glucobarbarin | 2(S)-OH-2-phenylethyl | 12.7 | 0.95 | Buchner |
Glucotropaeolin | benzyl | 13.8 | 0.95 | Buchner, EC |
Gluconasturtiin | 2-phenylethyl | 18.0 | 0.95 | Buchner, EC |
unknown – aliphatic/aromatic like UV spectrum | 1 | EC | ||
unknown – indole like spectrum | 0.25 | EC | ||
* approximate retention time (Rt) rounded to nearest 0.1 min (± 0.3 min depending on the column, eluent quality). Retention times are determined on ThermoFisher/Dionex Ultimate HPLC platforms equipped with an C18 column (150 x 4.6 mm, 3 micrometer particle size) plus C18 precolumn (10 x 4.6 mm, 5 micrometer particle size) with a gradient program as in Table 1. | ||||
# References for response factors: Buchner, R. in Glucosinolates in rapeseed (ed J.P. Wathelet) 50-58 (Martinus Nijhoff Publishers, 1987); Brown, P. D., Tokuhisa, J. G., Reichelt, M. & Gershenzon, J. Variation of glucosinolate accumulation among different organs and developmental stages of Arabidopsis thaliana. Phytochemistry. 62 (3), 471-481, doi:10.1016/S0031-9422(02)00549-6, (2003); EC. Oil seeds – determination of glucosinolates High Performance Liquid Chromatography. Official Journal of the European Communities. L 170/28. Annex VIII 03.07.27-34 (1990). |
Table 3: Response factors of the most commonly found desulfo-glucosinolates in plant extracts and their approximate retention times on C18 columns. Eluents, gradient, column temperature, and flow rate as in Table 1.
The greatest advantages of this established and widely used method are that it is robust, rather straightforward, and relatively low-cost per sample. Most of the equipment needed for the extraction and analysis should be available in a standard laboratory or can be self-built, with the exception of the HPLC-PDA. Another advantage is that desulfoglucosinolates dissolved in water are chemically quite stable when kept cool and in air-tight (HPLC) vials, so the extracts could easily be shipped for HPLC analysis elsewhere. In contrast to LC-MS platforms, which require specialized training and extensive hands-on experience for managing the software and analyzing the data, HPLC-UV/PDAs can be easily run after a short training period. This not only reduces the costs of the procedure, but also makes this method more accessible to a broad range of scientists, including students.
Generally, when the procedures described above are followed carefully, few problems should occur. In general, the glucosinolate peaks are very well separated in the chromatogram. If this is not the case, the gradient program could be adapted by decreasing the rate of increase of acetonitrile in the eluent. Alternatively, building in a new pre-column (200-500 injections) or column (1,500 -2,000 injections) may solve the issue. Occasionally, chromatograms of single samples in a batch may show very small or no peaks. This is usually due to pipetting errors when adding the sulfatase (e.g., a column has been skipped or the sulfatase was not properly washed down into the column). Alternatively, the glucosinolate concentration in the experimental materials may have been lower than expected and too little material was used for the extraction. If the latter is the case, the injection volume may be increased to 100 µL, or an exact aliquot (e.g., 800 µL) of the extract could be concentrated. The latter could be achieved by freeze-drying the extract, dissolving the residue in a smaller volume (e.g., 100 µL) of water, and reinjecting using the same reference curve. In the calculations for the original concentration of the extract, the numbers should be multiplied by the dilution factor. If this does not solve the issue, the materials should be extracted again using more starting material. If this is more than 100 mg, the volume of the extraction solvents and the size of the tubes should be adjusted proportionally to maintain the extraction efficiency.
An additional advantage is that this method has been well-validated. This is because it has been described as a standard method for the quantification of glucosinolates in rapeseed, for which the procedures and accuracy were confirmed in several laboratories16. In addition, the genetic background, biosynthesis, and biological functions of glucosinolates are subject to intense research efforts, in the model plant species Arabidopsis thaliana among others4,6,12. Therefore, many response factors for the exact quantification of desulfoglucosinolates in relation to sinigrin are well defined and publicly available15,17. Even though LS-MS-based protocols are more high-throughput, more sensitive, and are able to (tentatively) identify glucosinolates for which no standards are available18,19,20, the lack of universal response factors for LC-MS limits the exact quantification of glucosinolate concentrations18. Moreover, these methods usually do not include a freeze-drying step, and the amount of water in the fresh plant material is unaccounted for in the calculations, making exact quantification difficult. Lastly, because our extraction method involves a column-based purification and concentration step, it can also be applied to "dirty" samples with low concentrations of glucosinolates, such as soils21.
Compared to LC-MS-based methods that usually extract freshly frozen materials, use 96-well plates for extraction, and do not include a sulfatase step18,19, our method is relatively time-consuming and labor intense. With the column racks described in this paper, a single person can extract about 100-150 samples in one day. Elution (next day), freeze drying (overnight), and re-dissolving can take place within the following two days. With an automated HPLC injector, a run and equilibration time of 40-45 min per injection, and no unforeseen events, it would take 3-4 days to acquire the data for this sample set. When the HPLC software allows automatic quantification based on the sinigrin curve, a manual check of the chromatograms and peak assignments for 100 samples may only take another 1 or 2 h before the data can be used for statistical analyses.
Despite the increasing availability of glucosinolate standards, only a small fraction of the more than 130 candidates can currently be commercially bought. However, with a few references for each of the biosynthetic classes; access to literature databases specifying the compounds previously found in the plant species (e.g., Fahey et al.22); basic knowledge of chromatographic principles, such as the logic of eluotropic series (e.g., for increasing numbers of Cs on the side chain in aliphatic compounds, Figures 3 and 4); and the validation of single samples on LC-MS19 or isolated glucosinolates on NMR23, one may easily overcome this limitation. Most protocols for glucosinolate analyses use internal reference curves (i.e., a certain concentration for the extraction of sinigrin or sinalbin to the extraction solvent16,17,19). Principally, internal reference curves are more appropriate to correct for individual sample processing errors and thus theoretically yield a higher precision. Despite this advantage, we prefer to use a five-point external reference curve, as we often analyze different wild species, some of which contain high levels of sinigrin (e.g., Brassica nigra24) or sinalbin (e.g., Sinapis alba25), the two glucosinolate references for which response factors are available. Moreover, adding internal standards to each sample increases the cost of the analyses, as high-grade glucosinolate reference standards are usually quite expensive.
In conclusion, despite the time-consuming steps, this protocol provides a straightforward and accessible method to extract and quantify glucosinolates in plant samples. However, it is important to consider that the glucosinolate levels themselves are only an indication of the potential biological activity, seen as the necessity to react with myrosinase, and variation in the reaction products may arise from a single glucosinolate11. Validation assays must be performed to confirm the biological relevance.
The authors have nothing to disclose.
NMvD thanks Dr. Michael Reichelt (Max-Planck-Institute for chemical Ecology, Jena, Germany) for providing the first reference samples when she started using this method 16 years ago. Ciska Raaijmakers (NIOO-KNAW, Wageningen, the Netherlands), Sebastian Krosse (B-Ware, Nijmegen, the Netherlands), and Christian Ristok (iDiv, Leipzig) are acknowledged for improving the protocol over the course of the years. Mirka Macel and Martine Huberty (University Tübingen, Germany) are acknowledged for their permission to use the Rorippa chromatogram. The authors gratefully acknowledge the support of the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, funded by the German Research Foundation (FZT 118).
Methanol HiPerSolv CHROMANORM® gradient grade for HPLC grade | VWR | 20,864,320 | |
Sodium acetate (NaOAc) | Sigma-Aldrich | W302406-1KG-K | |
HCL | VWR | 1,090,571,000 | |
Sephadex | Sigma-Aldrich | A25120-10G | |
(−)-Sinigrin hydrate from horseradish |
Sigma-Aldrich | S1647-500MG | |
Aryl Sulfatase | Sigma-Aldrich | S9626-10KU | |
Ethanol | VWR | 20,816,298 | |
Pasteur Pipette | Carl Roth | 4518.1 | |
Glass Wool | Carl Roth | 7377.1 | |
Glass /wooden stick | VWR | HERE1080766 | |
2 mL reaction tubes | VWR | 211-2606 | |
Dissecting needle | Carl Roth | KX93.1 | |
Rotilabo-lab dishes | Carl Roth | 0772.1 | Waste tray |
Freeze Dryer Freezone 12 L | Labconco | 7960030 | |
Acetonitril super gradient grade | VWR | 83,639,320 | |
Water bath | VWR | 462-5112 | |
Ultrasonic bath | Fisher Scientific | FB 15061 | |
PH Electrode | Thermo Fisher Scientific | STARA2115 | |
Centrifuge Heraeus Multifuge X1 | Thermo Fisher Scientific | 75004210 | |
Pre-Column | Thermo Fisher Scientific | 69697 | C18 column (4.6 x 10 mm, 5 µm, 300 Å) |
Column Acclaim 300 | Thermo Fisher Scientific | 60266 | C18 column (4.6 x 150 mm, 3 µm, 300 Å) |
HPLC Ultimate 3000 | Thermo Fisher Scientific | with column oven and UV or PDA detector | |
Flask 1000 mL | VWR | 215-1595 | |
Glucosinolate reference compounds | Phytoplan | various | http://www.phytoplan.de/ |