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 T&#252;bingen, 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).

1. Preparation of Solutions Needed for the Glucosinolate Extraction
<ol>
	<li>Prepare 500 mL of 70% methanol (MeOH) in water (ultrapure) in a glass bottle. For 100 samples and 5 standards, 420 mL of 70% MeOH is needed.</li>
	<li>Prepare 20 mM sodium acetate (NaOAc) (pH = 5.5) by adding 0.82 g of NaOAc or 1.36 g of NaOAc x 3 H2O in 500 mL of water; adjust the pH with hydrogen chloride (HCl). Store the NaOAc in the refrigerator. For 100 samples and 5 standards, 370 mL of 20 mM NaOAc (pH = 5.5) in water is needed.</li>
	<li>To prepare the column material, mix 10 g of cross-linked dextran gel (type G-25) with 125 mL of ultrapure water. Store the resulting mixture in a refrigerator (4 &#176;C).</li>
	<li>Preparation of the sulfatase solution
	<ol>
		<li>Dissolve 10,000 units of aryl sulfatase (type H-1 from Helix pomatia) in 30 mL of ultrapure water and add 30 mL of absolute ethanol (EtOH). Mix the solution well and transfer it to one 250-mL centrifuge tube or multiple smaller tubes, depending on availability.</li>
		<li>Centrifuge the mixture at 2,650 x g for 20 min at room temperature (RT). Transfer the supernatant(s) to a beaker; add 90 mL of EtOH and mix it. Centrifuge the mixture in one or more centrifuge tubes at 1,030 x g for 15 min at RT.</li>
		<li>Discard the supernatants. Dissolve and combine the pellets in a total of 25 mL of ultrapure water. Vortex well, dispense in 1-mL tubes, and store in a freezer at -20 &#176;C; they will keep for at least one year.</li>
	</ol>
	</li>
	<li>Preparation of the sinigrin reference solution
	<ol>
		<li>Weigh in around 9 mg of sinigrin monohydrate with 1-&#181;g accuracy (e.g., 8.769 mg). Transfer it into a 10-mL volumetric flask and dissolve the sinigrin monohydrate in 10.0 mL of ultrapure water.</li>
		<li>Calculate the molarity of the stock solution and prepare five sinigrin references between 50-750 &#181;M by diluting of the stock solution. For a detailed example, see <a href="https://cloudfront-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55425/20160918GrosservanDamJoVEGlucosinolates_S1.docx" target="_blank">Supplementary File S1</a>.</li>
		<li>Dispense the different sinigrin references in 1.5-mL reaction tubes and freeze them at 20 &#176;C. Include a series of five sinigrin references in each extraction batch. Always use the correct molarity values for the currently used sinigrin references when calculating the concentrations.</li>
	</ol>
	</li>
</ol>
2. Preparation of the Extraction Setup
<ol>
	<li>Prepare a column rack for the Pasteur pipette columns (for the preparation of columns, see step 3.1). Label the rack or the columns to keep track of the sample numbers (see Figure 1).</li>
	<li>Prepare a block holding the same number of labelled 2-mL microcentrifuge tubes (see step 3.3 and Figure 1)</li>
</ol>
<img alt="Figure 1" src="/files/ftp_upload/55425/55425fig1.jpg" /> 
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). <a href="https://cloudfront-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55425/55425fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
3. Preparation of the Columns and Microcentrifuge Tubes
<ol>
	<li>Prepare one column per sample and five extra columns for the five sinigrin reference samples.
	<ol>
		<li>In each glass pipette, place a piece of glass wool approximately 1 cm x 1 cm. Use a wooden or glass stick to push the glass wool down to the point where the pipette narrows. The glass wool should prevent the column material from running out, but do not use too much, as it will slow the elution of the columns. Wear gloves when working with the glass wool.</li>
	</ol>
	</li>
	<li>Place the columns on the column rack (see Figure 1). Place the column rack in a lab tray (waste tray) to catch the eluents used for the consecutive column washes.</li>
	<li>Cut the first 5 mm off the tip of a plastic 1-mL pipette tip and pipette 0.5 mL of the prepared column material (G-25 gel in water, see step 1.3) into each column. Shake the bottle containing the column material well before pipetting. Discard leaking columns (G-25 material running out through the glass wool layer) and replace with new ones.
	<ol>
		<li>After pipetting the column material into the columns, add 1 mL of ultrapure water to flush down the material.</li>
	</ol>
	</li>
	<li>Prepare one 2-mL reaction tube per sample and five tubes for the five sinigrin reference samples; label them. Use a dissecting needle to make holes in the caps for later freeze-drying and place the prepared tubes into the tube block in the exact same pattern as the columns (step 2.2, see Figure 1).</li>
</ol>
4. Extraction of Glucosinolates
<ol>
	<li>Weigh freeze-dried and finely-ground plant material (usually 50.0-100.0 mg of dry weight; the final glucosinolate concentrations in the extract should be in the range of the reference curve) to the nearest 0.1 mg in 2-mL, labeled, round-bottom reaction tubes. Add two small metal balls (3 mm in diameter) as boiling retardants to each tube. 
	NOTE: The protocol can also be applied to fresh, flash-frozen materials, that have been ground under liquid nitrogen and kept frozen until extraction. Increase the amount of material weighed for extraction and the percentage of MeOH in the extraction liquid to 85% to compensate for dilution by the water in the materials19.</li>
	<li>Pipette 1 mL of 70% MeOH into each tube and vortex briefly. Close the tubes and seal them with safety caps before placing them as quickly as possible into a hot water bath (90-92 &#176;C) for a few minutes (~5 min), until the 70% MeOH just boils. Caution: Wear safety goggles during this step!</li>
	<li>Place the sample tubes in an ultrasonic bath for 15 min. Meanwhile, take the sulfatase and the five sinigrin reference samples out of the freezer to thaw them at RT.</li>
	<li>After ultra-sonication, centrifuge the sample tubes at 2,700 x g in a benchtop centrifuge for 10 min at RT; a pellet should form in each tube. Add the supernatants to the labelled columns and pipette the five reference samples onto separate columns.
	<ol>
		<li>While pipetting the supernatants, keep the tip well over the pellet to avoid pipetting plant materials. Note that when dried samples are used, the supernatant volume will be less than 1.0 mL.</li>
	</ol>
	</li>
	<li>Add 1 mL of 70% MeOH to the remaining pellets in the sample tubes and vortex the tubes before placing them in an ultrasonic bath for 15 min. Centrifuge the tubes again, as in step 4.4, and add the supernatants to the respective columns; due to the properties of the column material, the negatively charged sulfate group of the glucosinolates will be specifically retained on the column.</li>
	<li>Wash the columns with the extracts in three sequential steps.
	<ol>
		<li>Pipette 2 x 1 mL of 70% MeOH onto each column. Wait for the column to run dry before adding the next 1 mL; this will remove more apolar compounds from the extracts (e.g., chlorophyll).</li>
		<li>Flush out the MeOH by adding 1 mL of ultrapure water to each column.</li>
		<li>Pipette 2 x 1 mL of 20 mM NaOAc buffer to each column to create the optimal conditions for the sulfatase reaction.</li>
	</ol>
	</li>
	<li>Take the rack with the columns out of the waste tray and dry the feet of the rack with a tissue. Place the rack over the block with vials and labeled tubes. Make sure that each column tip is in the corresponding, labeled, 2-mL tube (see Figure 1).</li>
	<li>Add 20 &#181;L of sulfatase solution to the columns. Ensure that the sulfatase reaches the surface of the column material. Pipette 50 &#181;L of NaOAc buffer onto each column to flush down the sulfatase. Cover the columns with aluminum foil and let stand overnight. 
	NOTE: Due to the activities of the sulfatase, the sulfate group will be removed, releasing the desulfoglucosinolates from the column so that they can elute with the water. For a detailed description, see Crocoll et al.19.</li>
	<li>The next day, elute the desulfoglucosinolates by pipetting 2 x 0.75 mL of ultrapure water onto each column. When all columns have run dry, lift the column rack and remove it from the reaction tubes.
	<ol>
		<li>Cap the tubes (make sure that there are holes in the caps) and freeze them in liquid nitrogen or in a -80 &#176;C freezer for 30 min. Freeze-dry the samples for 12-24 h (depending on the number of samples and the capacity of the freeze-drier) to remove all water.</li>
	</ol>
	</li>
	<li>After freeze-drying, re-dissolve the residue in an exact volume (usually 1.0 mL) of ultrapure water. Transfer the samples and the five sinigrin references to labeled HPLC vials. Keep the samples in a refrigerator (4 &#176;C) for up to two weeks or a freezer (-20 &#176;C) for up to one year before analyzing them with HPLC.</li>
	<li>Let the glass columns dry under the hood overnight and dispose them when dry. Recover the metal balls from the sample tubes used in step 4.5 for reuse and put the tubes in the waste disposal bin.</li>
</ol>
5. HPLC Measurements of Extracted Samples
<ol>
	<li>Separate the glucosinolates on a reversed-phase C18 column (4.6 x 150 mm, 3 &#181;m, 300 &#197;) with an acetonitrile-water gradient (see Table 1) and a flow of 0.75 mL/min and a column temperature of 40 &#176;C. Perform detection and quantification at 229 nm.</li>
	<li>Measure the sinigrin references on the same column but with an adapted gradient method to reduce solvent use (see Table 2). Start with injecting the five sinigrin references, beginning with the reference with the lowest concentration. Then inject the samples, including a methanol injection (blank) after every tenth sample to clean the column and to prevent the carryover of peaks.</li>
</ol>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Time [min]</td>
			<td>Flow [mL/min]</td>
			<td>% A Water</td>
			<td>% B ACN</td>
		</tr>
		<tr>
			<td>1</td>
			<td>0.750</td>
			<td>98</td>
			<td>2</td>
		</tr>
		<tr>
			<td>35</td>
			<td>0.750</td>
			<td>65</td>
			<td>35</td>
		</tr>
		<tr>
			<td>40</td>
			<td>0.750</td>
			<td>98</td>
			<td>2</td>
		</tr>
		<tr>
			<td colspan="4">Column Temperature 40 &#176;C.</td>
		</tr>
	</tbody>
</table>
Table 1: Acetonitrile-water gradient for glucosinolate separation and analysis on reversed-phase HPLC.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Time [min]</td>
			<td>Flow [mL/min]</td>
			<td>% A Water</td>
			<td>% B ACN</td>
		</tr>
		<tr>
			<td>1</td>
			<td>0.750</td>
			<td>98</td>
			<td>2</td>
		</tr>
		<tr>
			<td>10</td>
			<td>0.750</td>
			<td>89.3</td>
			<td>10.7</td>
		</tr>
		<tr>
			<td>11</td>
			<td>0.750</td>
			<td>98</td>
			<td>2</td>
		</tr>
		<tr>
			<td colspan="4">Column Temperature 40 &#176;C.</td>
		</tr>
	</tbody>
</table>
Table 2: Shortened acetonitrile-water gradient for quantification of the five sinigrin references used for the quantification of glucosinolates.
6. Glucosinolate Identification and Quantification
<ol>
	<li>Identification
	<ol>
		<li>Compare the UV spectra and retention times of the peaks in the samples with commercially available, pure glucosinolate references. See Figure 2 for examples of UV spectra from the various glucosinolate classes.</li>
		<li>Identify unknown glucosinolates with reference standards or on LC-MS18,19, if possible.</li>
		<li>Identify unknown glucosinolates with nuclear magnetic resonance (NMR), if possible.</li>
		<li>Compare the UV spectra and retention times of the peaks with those in Figure 2 and Table 3, databases, or literature references.</li>
	</ol>
	</li>
</ol>
<img alt="Figure 2" src="/files/ftp_upload/55425/55425fig2.jpg" /> 
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. <a href="https://cloudfront-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55425/55425fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol start="2">
	<li>Quantification
	<ol>
		<li>Integrate the area under the peaks of the five sinigrin references and the samples.</li>
		<li>Calculate a calibration curve of the five measured sinigrin references based on the integrated area. Use the equation of the regression line (see Equation 1) to calculate the interpolated amount of glucosinolates (see Equation 2).</li>
		<li>To calculate the concentration of the different glucosinolates, multiply the interpolated amount (x) by the response factor (M) for detection at 229 nm from EC (1990)16, Buchner (1987)15, or Brown et al. (1993)17; the consensus response factors of the most commonly detected desulphoglucosinolates are given in Table 3. 
		NOTE: Response factors may vary between systems-this may be the reason that there are different values given by different references (see References 15-17). Nevertheless, the values are mostly quite close and in a similar range with structural classes. Following the convention, set the response factor of unidentified glucosinolates to 1, although for unknown indole glucosinolates with a UV spectrum similar to that of glucobrassicin and other indole glucosinolates (Figure 2), it would be advisable to use 0.25 as a response factor to obtain a realistic estimate of the concentration (Table 3).</li>
		<li>To calculate the final amount of glucosinolates (xt) in the sample, take the dilution factor (D) and the mass of sample (w) used for the analysis into account (see Equation 3). 
		<img alt="Equation" src="/files/ftp_upload/55425/55425eq1.jpg" /> (1) 
		<img alt="Equation" src="/files/ftp_upload/55425/55425eq2.jpg" /> (2) 
		<img alt="Equation" src="/files/ftp_upload/55425/55425eq3.jpg" /> (3) 
		y = Peak area 
		m = slope of the reference 5-point regression curve 
		c = the intercept of the regression line with the y-axis 
		x = amount of glucosinolates in the extract 
		xt = concentration of glucosinolates in the plant sample 
		D = dilution factor 
		M = response factor for the detection at 229 nm from Buchner (1987) or Brown et al. (1993) 
		w = mass of sample used for extraction</li>
	</ol>
	</li>
</ol>

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M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Isolation+and+identification+of+4-&#945;-rhamnosyloxy+benzyl+glucosinolate+in+Noccaea+caerulescens+showing+intraspecific+variation.">Isolation and identification of 4-&#945;-rhamnosyloxy benzyl glucosinolate in Noccaea caerulescens showing intraspecific variation.</a> Phytochemistry. 110, 166-171 (2015).</li><li>van Dam, N. M., Raaijmakers, C. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Local+and+systemic+induced+responses+to+cabbage+root+fly+larvae+(Delia+radicum)+in+Brassica+nigra+and+B.+oleracea.">Local and systemic induced responses to cabbage root fly larvae (Delia radicum) in Brassica nigra and B. oleracea.</a> Chemoecology. 16 (1), 17-24 (2006).</li><li>Gols, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Temporal+changes+affect+plant+chemistry+and+tritrophic+interactions.">Temporal changes affect plant chemistry and tritrophic interactions.</a> Bas Appl Ecol. 8 (5), 421-433 (2007).</li></ol>

The authors have nothing to disclose.

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 &#181;L, or an exact aliquot (e.g., 800 &#181;L) 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 &#181;L) 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 &#34;dirty&#34; 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.

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&#39; 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.

<table><tbody><tr><td>Methanol HiPerSolv CHROMANORM&amp;reg; gradient grade for HPLC grade</td><td>VWR</td><td>20864.320</td><td></td></tr><tr><td>Sodium acetate (NaOAc)</td><td>Sigma-Aldrich</td><td>W302406-1KG-K</td><td></td></tr><tr><td>HCl</td><td>VWR</td><td>1.09057.1000</td><td></td></tr><tr><td>Sephadex</td><td>Sigma-Aldrich</td><td>A25120-10G</td><td></td></tr><tr><td>(&amp;minus;)-Sinigrin hydrate&lt;br/&gt; from horseradish&amp;nbsp;</td><td>Sigma-Aldrich</td><td>S1647-500MG</td><td></td></tr><tr><td>Aryl Sulfatase</td><td>Sigma-Aldrich</td><td>S9626-10KU</td><td></td></tr><tr><td>Ethanol</td><td>VWR</td><td>20816.298</td><td></td></tr><tr><td>Pasteur Pipette</td><td>Carl Roth</td><td>4518.1</td><td></td></tr><tr><td>Glass Wool</td><td>Carl Roth</td><td>7377.1</td><td></td></tr><tr><td>Glass/wooden stick</td><td>VWR</td><td>HERE1080766</td><td></td></tr><tr><td>2 mL reaction tubes</td><td>VWR</td><td>211-2120</td><td></td></tr><tr><td>Dissecting needle</td><td>Carl Roth</td><td>KX93.1</td><td></td></tr><tr><td>Rotilabo-lab dishes</td><td>Carl Roth</td><td>0772.1</td><td>Waste tray</td></tr><tr><td>Rotilabo-sealing clips</td><td>Carl Roth</td><td>N217.1</td><td></td></tr><tr><td>Freeze Dryer Freezone 12 L</td><td>Labconco</td><td>7960030</td><td></td></tr><tr><td>Acetonitril super gradient grade</td><td>VWR</td><td>83639.320</td><td></td></tr><tr><td>Water bath</td><td>VWR</td><td>462-5112</td><td></td></tr><tr><td>Ultrasonic bath</td><td>Fisher Scientific</td><td>FB 15061</td><td></td></tr><tr><td>PH Electrode</td><td>Thermo Fisher Scientific</td><td>STARA2115</td><td></td></tr><tr><td>Centrifuge Heraeus Multifuge X1</td><td>Thermo Fisher Scientific</td><td>75004210</td><td></td></tr><tr><td>Pre-Column</td><td>Thermo Fisher Scientific</td><td>69697</td><td>C&lt;sub&gt;18&lt;/sub&gt; column (4.6 x 10 mm, 5 &amp;micro;m, 300 &amp;Aring;)&amp;nbsp;</td></tr><tr><td>Column Acclaim 300</td><td>Thermo Fisher Scientific</td><td>60266</td><td>C&lt;sub&gt;18&lt;/sub&gt; column (4.6 x 150 mm, 3 &amp;micro;m, 300 &amp;Aring;)&amp;nbsp;</td></tr><tr><td>HPLC Ultimate 3000</td><td>Thermo Fisher Scientific</td><td></td><td>with column oven and UV or PDA detector</td></tr><tr><td>Flask 1,000 mL</td><td>VWR</td><td>215-1595</td><td></td></tr><tr><td>Glucosinolate reference compounds</td><td>Phytoplan</td><td>various</td><td>http://www.phytoplan.de/</td></tr></tbody></table>

a straightforward method for glucosinolate extraction and analysis with high-pressure liquid chromatography (hplc)

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.

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.
<img alt="Figure 3" src="/files/ftp_upload/55425/55425fig3.jpg" /> 
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). <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55425/55425fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
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.
<img alt="Figure 4" src="/files/ftp_upload/55425/55425fig4.jpg" /> 
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). <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55425/55425fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Common name</td>
			<td>Side chain structure</td>
			<td>Rt (min)*</td>
			<td>229 nm</td>
			<td>reference#</td>
		</tr>
		<tr>
			<td>aliphatic glucosinolates</td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Glucocapparin</td>
			<td>methyl</td>
			<td>3.5</td>
			<td>1</td>
			<td>Brown</td>
		</tr>
		<tr>
			<td>Sinigrin</td>
			<td>2-propenyl</td>
			<td>5.5</td>
			<td>1</td>
			<td>Brown, EC</td>
		</tr>
		<tr>
			<td>Gluconapin</td>
			<td>3-butenyl</td>
			<td>9.5</td>
			<td>1.11</td>
			<td>EC</td>
		</tr>
		<tr>
			<td>Glucobrassicanapin</td>
			<td>4-pentenyl</td>
			<td>13.5</td>
			<td>1.15</td>
			<td>EC</td>
		</tr>
		<tr>
			<td>Glucoiberverin</td>
			<td>3-methylthiopropyl</td>
			<td>10.9</td>
			<td>0.8</td>
			<td>Brown</td>
		</tr>
		<tr>
			<td>Glucoerucin</td>
			<td>4-methylthiobutyl</td>
			<td>14.0</td>
			<td>0.9</td>
			<td>Brown</td>
		</tr>
		<tr>
			<td>Glucoiberin</td>
			<td>3-methylsulfinylpropyl</td>
			<td>3.7</td>
			<td>1.2</td>
			<td>Brown</td>
		</tr>
		<tr>
			<td>Glucoraphanin</td>
			<td>4-methylsulfinylbutyl</td>
			<td>4.9</td>
			<td>0.9</td>
			<td>Brown</td>
		</tr>
		<tr>
			<td>Glucoalyssin</td>
			<td>5-methylsulfinylpentyl</td>
			<td>7.6</td>
			<td>0.9</td>
			<td>Brown</td>
		</tr>
		<tr>
			<td>Glucohesperin</td>
			<td>6-methylsulfinylhexyl</td>
			<td>10.5</td>
			<td>1</td>
			<td>Brown</td>
		</tr>
		<tr>
			<td>Glucosiberin</td>
			<td>7-methylsulfinylheptyl</td>
			<td>13.5</td>
			<td>1</td>
			<td>Brown</td>
		</tr>
		<tr>
			<td>Glucohirsutin</td>
			<td>8-methylsulfinyloctyl</td>
			<td>16.8</td>
			<td>1.1</td>
			<td>Brown</td>
		</tr>
		<tr>
			<td>Glucoarabin</td>
			<td>9-methylsulfinylnonyl</td>
			<td>20.5</td>
			<td>1</td>
			<td></td>
		</tr>
		<tr>
			<td>Glucocheirolin</td>
			<td>3-methylsulfonylpropyl</td>
			<td>4.2</td>
			<td>0.9</td>
			<td>Brown</td>
		</tr>
		<tr>
			<td>Progoitrin</td>
			<td>2(R)-OH-3-butenyl</td>
			<td>4.5</td>
			<td>1.09</td>
			<td>Buchner, EC</td>
		</tr>
		<tr>
			<td>Gluconapoleiferin</td>
			<td>2-OH-5-pentenyl</td>
			<td>8.3</td>
			<td>1</td>
			<td>EC</td>
		</tr>
		<tr>
			<td>indole glucosinolates</td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>4-hydroxyglucobrassicin</td>
			<td>4-hydroxyindol-3-ylmethyl</td>
			<td>11.2</td>
			<td>0.28</td>
			<td>Buchner, EC</td>
		</tr>
		<tr>
			<td>Glucobrassicin</td>
			<td>indol-3-ylmethyl</td>
			<td>15.3</td>
			<td>0.29</td>
			<td>Buchner, EC</td>
		</tr>
		<tr>
			<td>4-Methoxyglucobrassicin</td>
			<td>4-methoxyindol-3-ylmethyl</td>
			<td>18.2</td>
			<td>0.25</td>
			<td>Buchner, EC</td>
		</tr>
		<tr>
			<td>Neoglucobrassicin</td>
			<td>1-methoxyindol-3-ylmethyl</td>
			<td>22.5</td>
			<td>0.2</td>
			<td>Buchner, EC</td>
		</tr>
		<tr>
			<td>aromatic glucosinolates</td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Sinalbin</td>
			<td>4-hydroxybenzyl</td>
			<td>8.1</td>
			<td>0.5</td>
			<td>Buchner</td>
		</tr>
		<tr>
			<td>Glucosibarin</td>
			<td>2(R)-OH-2-phenylethyl</td>
			<td>12.1</td>
			<td>0.95</td>
			<td>see next</td>
		</tr>
		<tr>
			<td>Glucobarbarin</td>
			<td>2(S)-OH-2-phenylethyl</td>
			<td>12.7</td>
			<td>0.95</td>
			<td>Buchner</td>
		</tr>
		<tr>
			<td>Glucotropaeolin</td>
			<td>benzyl</td>
			<td>13.8</td>
			<td>0.95</td>
			<td>Buchner, EC</td>
		</tr>
		<tr>
			<td>Gluconasturtiin</td>
			<td>2-phenylethyl</td>
			<td>18.0</td>
			<td>0.95</td>
			<td>Buchner, EC</td>
		</tr>
		<tr>
			<td>unknown - aliphatic/aromatic like UV spectrum</td>
			<td></td>
			<td></td>
			<td>1</td>
			<td>EC</td>
		</tr>
		<tr>
			<td>unknown - indole like spectrum</td>
			<td></td>
			<td></td>
			<td>0.25</td>
			<td>EC</td>
		</tr>
		<tr>
			<td colspan="5">* approximate retention time (Rt) rounded to nearest 0.1 min (&#177; 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.</td>
		</tr>
		<tr>
			<td colspan="5"># 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. &#38; 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).</td>
		</tr>
	</tbody>
</table>
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.

Watch this Scientific Journal Video about A Straightforward Method for Glucosinolate Extraction and Analysis with High-pressure Liquid Chromatography HPLC at JoVE.com

A Straightforward Method for Glucosinolate Extraction and Analysis with High-pressure Liquid Chromatography HPLC

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.

A Straightforward Method for Glucosinolate Extraction and Analysis with High-pressure Liquid Chromatography (HPLC)

Glucosinolates are a well-studied and highly diverse class of natural plant compounds. They play important roles in plant resistance, rapeseed oil ...

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Chemistry

25.1K Views.  German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. 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. 

Video: A Straightforward Method for Glucosinolate Extraction and Analysis with High-pressure Liquid Chromatography HPLC

A Simple Fractionated Extraction Method for the Comprehensive Analysis of Metabolites, Lipids, and Proteins from a Single Sample

Understanding of complex biological systems requires the measurement, analysis and integration of multiple compound classes of the living cell, usually determined by transcriptomic, proteomic, metabolomics and lipidomic measurements. In this protocol, we introduce a simple method for the reproducible extraction of metabolites, lipids and proteins from biological tissues using a single aliquot per sample. The extraction method is based on a methyl tert-butyl ether: methanol: water system for liquid: liquid partitioning of hydrophobic and polar metabolites into two immiscible phases along with the precipitation of proteins and other macromolecules as a solid pellet. This method, therefore, provides three different fractions of specific molecular composition, which are fully compatible with common high throughput 'omics' technologies such as liquid chromatography (LC) or gas chromatography (GC) coupled to mass spectrometers. Even though the method was initially developed for the analysis of different plant tissue samples, it has proved to be fully compatible for the extraction and analysis of biological samples from systems as diverse as algae, insects, and mammalian tissues and cell cultures.

A protocol for comprehensive extraction of lipids, metabolites and proteins from biological tissues using one sample is presented.

Understanding of complex biological systems requires the measurement, analysis and integration of multiple compound classes of the living cell, usually ...

Biochemistry

Fizzy Extraction of Volatile Organic Compounds Combined with Atmospheric Pressure Chemical Ionization Quadrupole Mass Spectrometry

Chemical analysis of volatile and semivolatile compounds dissolved in liquid samples can be challenging. The dissolved components need to be brought to the gas phase, and efficiently transferred to a detection system. Fizzy extraction takes advantage of the effervescence phenomenon. First, a carrier gas (here, carbon dioxide) is dissolved in the sample by applying overpressure and stirring the sample. Second, the sample chamber is decompressed abruptly. Decompression leads to the formation of numerous carrier gas bubbles in the sample liquid. These bubbles assist the release of the dissolved analyte species from the liquid to the gas phase. The released analytes are immediately transferred to the atmospheric pressure chemical ionization interface of a triple quadrupole mass spectrometer. The ionizable analyte species give rise to mass spectrometric signals in the time domain. Because the release of the analyte species occurs over short periods of time (a few seconds), the temporal signals have high amplitudes and high signal-to-noise ratios. The amplitudes and areas of the temporal peaks can then be correlated with concentrations of the analytes in the liquid samples subjected to fizzy extraction, which enables quantitative analysis. The advantages of fizzy extraction include: simplicity, speed, and limited use of chemicals (solvents).

Fizzy extraction is a new laboratory technique for analysis of volatile and semivolatile compounds. A carrier gas is dissolved in the liquid sample by applying overpressure and stirring the sample. The sample chamber is then decompressed. The analyte species are liberated to the gas phase due to effervescence.

Chemical analysis of volatile and semivolatile compounds dissolved in liquid samples can be challenging. The dissolved components need to be brought to ...

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures

Natural organic matter (NOM) is composed of a highly complex mixture of thousands of organic compounds which, historically, proved difficult to characterize. However, to understand the thermodynamic and kinetic controls on greenhouse gas (carbon dioxide [CO2] and methane [CH4]) production resulting from the decomposition of NOM, a molecular-level characterization coupled with microbial proteome analyses is necessary. Further, climate and environmental changes are expected to perturb natural ecosystems, potentially upsetting complex interactions that influence both the supply of organic matter substrates and the microorganisms performing the transformations. A detailed molecular characterization of the organic matter, microbial proteomics, and the pathways and transformations by which organic matter is decomposed will be necessary to predict the direction and magnitude of the effects of environmental changes. This article describes a methodological throughput for comprehensive metabolite characterization in a single sample by direct injection Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), gas chromatography mass spectrometry (GC-MS), nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography mass spectrometry (LC-MS), and proteomics analysis. This approach results in a fully-paired dataset which improves statistical confidence for inferring pathways of organic matter decomposition, the resulting CO2 and CH4 production rates, and their responses to environmental perturbation. Herein we present results of applying this method to NOM samples collected from peatlands; however, the protocol is applicable to any NOM sample (e.g., peat, forested soils, marine sediments, etc.).

This protocol describes a single throughput for complementary analytical and omics techniques culminating in a fully-paired characterization of natural organic matter and microbial proteomics in different ecosystems. This approach permits robust comparisons for identifying metabolic pathways and transformations important for describing greenhouse gas production and predicting responses to environmental change.

Natural organic matter (NOM) is composed of a highly complex mixture of thousands of organic compounds which, historically, proved difficult to ...

Environment

A Convenient Method for Extraction and Analysis with High-Pressure Liquid Chromatography of Catecholamine Neurotransmitters and Their Metabolites

The extraction and analysis of catecholamine neurotransmitters in biological fluids is of great importance in assessing nervous system function and related diseases, but their precise measurement is still a challenge. Many protocols have been described for neurotransmitter measurement by a variety of instruments, including high-pressure liquid chromatography (HPLC). However, there are shortcomings, such as complicated operation or hard-to-detect multiple targets, which cannot be avoided, and presently, the dominant analysis technique is still HPLC coupled with sensitive electrochemical or fluorimetric detection, due to its high sensitivity and good selectivity. Here, a detailed protocol is described for the pretreatment and detection of catecholamines with high pressure liquid chromatography with electrochemical detection (HPLC-ECD) in real urine samples of infants, using electrospun composite nanofibers composed of polymeric crown ether with polystyrene as adsorbent, also known as the packed-fiber solid phase extraction (PFSPE) method. We show how urine samples can be easily precleaned by a nanofiber-packed solid phase column, and how the analytes in the sample can be rapidly enriched, desorbed, and detected on an ECD system. PFSPE greatly simplifies the pretreatment procedures for biological samples, allowing for decreased time, expense, and reduction of the loss of targets. 
Overall, this work illustrates a simple and convenient protocol for solid-phase extraction coupled to an HPLC-ECD system for simultaneous determination of three monoamine neurotransmitters (norepinephrine (NE), epinephrine (E), dopamine (DA)) and two of their metabolites (3-methoxy-4-hydroxyphenylglycol (MHPG) and 3,4-dihydroxy-phenylacetic acid (DOPAC)) in infants' urine. The established protocol was applied to assess the differences of urinary catecholamines and their metabolites between high-risk infants with perinatal brain damage and healthy controls. Comparative analysis revealed a significant difference in urinary MHPG between the two groups, indicating that the catecholamine metabolites may be an important candidate marker for early diagnosis of cases at risk for brain damage in infants.

We present a convenient solid-phase extraction coupled to high-pressure liquid chromatography (HPLC) with electrochemical detection (ECD) for simultaneous determination of three monoamine neurotransmitters and two of their metabolites in infants' urine. We also identify the metabolite MHPG as a potential biomarker for the early diagnosis of brain damage for infants.

The extraction and analysis of catecholamine neurotransmitters in biological fluids is of great importance in assessing nervous system function and ...

The MPLEx Protocol for Multi-omic Analyses of Soil Samples

Mass spectrometry (MS)-based integrated metaproteomic, metabolomic, and lipidomic (multi-omic) studies are transforming our ability to understand and characterize microbial communities in environmental and biological systems. These measurements are even enabling enhanced analyses of complex soil microbial communities, which are the most complex microbial systems known to date. Multi-omic analyses, however, do have sample preparation challenges, since separate extractions are typically needed for each omic study, thereby greatly amplifying the preparation time and amount of sample required. To address this limitation, a 3-in-1 method for the simultaneous extraction of metabolites, proteins, and lipids (MPLEx) from the same soil sample was created by adapting a solvent-based approach. This MPLEx protocol has proven to be both simple and robust for many sample types, even when utilized for limited quantities of complex soil samples. The MPLEx method also greatly enabled the rapid multi-omic measurements needed to gain a better understanding of the members of each microbial community, while evaluating the changes taking place upon biological and environmental perturbations.

A protocol is presented for simultaneously extracting metabolites, proteins, and lipids from a single soil sample, allowing reduced sample preparation times and enabling multi-omic mass spectrometry analyses of samples with limited quantities.

Mass spectrometry (MS)-based integrated metaproteomic, metabolomic, and lipidomic (multi-omic) studies are transforming our ability to understand and ...

Primary Organ Identification in Medicinal Plants Using 13C6&#45;Glucose Labeling

13C6&#45;Glucose Labeling Associated with LC&#45;MS&#58; Identification of Plant Primary Organs in Secondary Metabolite Synthesis

This paper presents a novel and efficient method for certifying primary organs involved in secondary metabolite synthesis. As the most important secondary metabolite in Parispolyphylla var. yunnanensis (Franch.) Hand. -Mzt. (PPY), Paris saponin (PS) has a variety of pharmacological activities and PPY is in increasing demand. This study established leaf, rhizome, and stem-vascular-bundle 13C6-Glucose feeding and non-feeding four treatments to precisely certify the primary organs involved in Paris saponins VII (PS VII) synthesis. By combining liquid chromatography-mass spectrometry (LC-MS), the 13C/12C ratios of leaf, rhizome, stem, and root in different treatments were quickly and accurately calculated, and four types of PS isotopic ion peak(M&#8722;) ratios were found: (M+1) &#8722;/M&#8722;, (M+2) &#8722;/M&#8722;, (M+3) &#8722;/M&#8722; and (M+4) &#8722;/M&#8722;. The results showed that the ratio of 13C/12C in the rhizomes of the stem-vascular-bundle and rhizome feeding treatments was significantly higher than that in the non-feeding treatment. Compared to the non-feeding treatment, the ratio of PS VII molecules (M+2) &#8722;/M&#8722; in the leaves increased significantly under leaf and stem-vascular-bundle feeding treatments. Simultaneously, compared to the non-feeding treatment, the ratio of PS VII molecules (M+2) &#8722;/M&#8722; in the leaves under rhizome treatment showed no significant difference. Furthermore, the ratio of PS VII molecules (M+2) &#8722;/M&#8722; in the stem, root, and rhizome showed no differences among the four treatments. Compared to the non-feeding treatment, the ratio of the Paris saponin II (PS II) molecule (M+2) &#8722;/M&#8722; in leaves under leaf feeding treatment showed no significant difference, and the (M+3) &#8722;/M&#8722; ratio of PS II molecules in leaves under leaf feeding treatment were lower. The data confirmed that the primary organ for the synthesizing of PS VII is the leaves. It lays the foundation for future identification of the primary organs and pathways involved in the synthesis of secondary metabolites in medicinal plants.

Author Spotlight: Plant Primary Organs Profiling Using 13C6&#45;Glucose Labeling and LC&#45;MS

The developed method of 13C6-Glucose labeling combined with liquid chromatography high-resolution mass spectrometry is versatile and lays the foundation for future studies on the primary organs and pathways involved in the synthesis of secondary metabolites in medicinal plants, as well as the comprehensive utilization of these secondary metabolites.

This paper presents a novel and efficient method for certifying primary organs involved in secondary metabolite synthesis. As the most important secondary ...

Arabidopsis thaliana Polar Glycerolipid Profiling by Thin Layer Chromatography (TLC) Coupled with Gas-Liquid Chromatography (GLC)

Biological membranes separate cells from the environment. From a single cell to multicellular plants and animals, glycerolipids, such as phosphatidylcholine or phosphatidylethanolamine, form bilayer membranes which act as both boundaries and interfaces for chemical exchange between cells and their surroundings. Unlike animals, plant cells have a special organelle for photosynthesis, the chloroplast. The intricate membrane system of the chloroplast contains unique glycerolipids, namely glycolipids lacking phosphorus: monogalactosyldiacylglycerol (MGDG), digalactosyldiacylglycerol (DGDG), sulfoquinovosyldiacylglycerol (SQDG)4. The roles of these lipids are beyond simply structural. These glycolipids and other glycerolipids were found in the crystal structures of photosystem I and II indicating the involvement of glycerolipids in photosynthesis8,11. During phosphate starvation, DGDG is transferred to extraplastidic membranes to compensate the loss of phospholipids9,12.
Much of our knowledge of the biosynthesis and function of these lipids has been derived from a combination of genetic and biochemical studies with Arabidopsis thaliana14. During these studies, a simple procedure for the analysis of polar lipids has been essential for the screening and analysis of lipid mutants and will be outlined in detail. A leaf lipid extract is first separated by thin layer chromatography (TLC) and glycerolipids are stained reversibly with iodine vapor. The individual lipids are scraped from the TLC plate and converted to fatty acyl methylesters (FAMEs), which are analyzed by gas-liquid chromatography coupled with flame ionization detection (FID-GLC) (Figure 1). This method has been proven to be a reliable tool for mutant screening. For example, the tgd1,2,3,4 endoplasmic reticulum-to-plastid lipid trafficking mutants were discovered based on the accumulation of an abnormal galactoglycerolipid: trigalactosyldiacylglycerol (TGDG) and a decrease in the relative amount of 18:3 (carbons : double bonds) fatty acyl groups in membrane lipids 3,13,18,20. This method is also applicable for determining enzymatic activities of proteins using lipids as substrate6.

Arabidopsis thaliana Polar Glycerolipid Profiling by Thin Layer Chromatography TLC Coupled with Gas-Liquid Chromatography GLC

Composition of polar lipid extracts and the fatty acid composition of individual glycerolipids are determined in a simple and robust lipid profiling experiment. For this purpose, glycerolipids are isolated by thin layer chromatography and subjected to transmethylation of their acyl groups. Fatty acyl methylesters are quantified by gas-liquid chromatography.

Biological membranes separate cells from the environment. From a single cell to multicellular plants and animals, glycerolipids, such as ...

Biology

Liquid Chromatography Coupled to Refractive Index or Mass Spectrometric Detection for Metabolite Profiling in Lysate-based Cell-free Systems

Engineering cellular metabolism for targeted biosynthesis can require extensive design-build-test-learn (DBTL) cycles as the engineer works around the cell&#39;s survival requirements. Alternatively, carrying out DBTL cycles in cell-free environments can accelerate this process and alleviate concerns with host compatibility. A promising approach to cell-free metabolic engineering (CFME) leverages metabolically active crude cell extracts as platforms for biomanufacturing and for rapidly discovering and prototyping modified proteins and pathways. Realizing these capabilities and optimizing CFME performance requires methods to characterize the metabolome of lysate-based cell-free platforms. That is, analytical tools are necessary for monitoring improvements in targeted metabolite conversions and in elucidating alterations to metabolite flux when manipulating lysate metabolism. Here, metabolite analyses using high-performance liquid chromatography (HPLC) coupled with either optical or mass spectrometric detection were applied to characterize metabolite production and flux in E. coli S30 lysates. Specifically, this report describes the preparation of samples from CFME lysates for HPLC analyses using refractive index detection (RID) to quantify the generation of central metabolic intermediates and by-products in the conversion of low-cost substrates (i.e., glucose) to various high-value products. The analysis of metabolite conversion in CFME reactions fed with 13C-labeled glucose through reversed-phase liquid chromatography coupled to tandem mass spectrometry (MS/MS), a powerful tool for characterizing specific metabolite yields and lysate metabolic flux from starting materials, is also presented. Altogether, applying these analytical methods to CFME lysate metabolism enables the advancement of these systems as alternative platforms for executing faster or novel metabolic engineering tasks.

The protocols describe high-performance liquid chromatography methods coupled to refractive index or mass spectrometric detection for studying metabolic reactions in complex lysate-based cell-free systems.

Engineering cellular metabolism for targeted biosynthesis can require extensive design-build-test-learn (DBTL) cycles as the engineer works around the ...

Bioengineering

The Infiltration-centrifugation Technique for Extraction of Apoplastic Fluid from Plant Leaves Using Phaseolus vulgaris as an Example

The apoplast is a distinct extracellular compartment in plant tissues that lies outside the plasma membrane and includes the cell wall. The apoplastic compartment of plant leaves is the site of several important biological processes, including cell wall formation, cellular nutrient and water uptake and export, plant-endophyte interactions and defence responses to pathogens. The infiltration-centrifugation method is well established as a robust technique for the analysis of the soluble apoplast composition of various plant species. The fluid obtained by this method is commonly known as apoplast washing fluid (AWF). The following protocol describes an optimized vacuum infiltration and centrifugation method for AWF extraction from Phaseolus vulgaris (French bean) cv. Tendergreen leaves. The limitations of this method and the optimization of the protocol for other plant species are discussed. Recovered AWF can be used in a wide range of downstream experiments that seek to characterize the composition of the apoplast and how it varies in response to plant species and genotype, plant development and environmental conditions, or to determine how microorganisms grow in apoplast fluid and respond to changes in its composition.

The Infiltration-centrifugation Technique for Extraction of Apoplastic Fluid from Plant Leaves Using Phaseolus vulgaris as an Example

This protocol details the optimized extraction of apoplast washing fluid from plant leaves, using French bean plants (Phaseolus vulgaris) as a model example.

The apoplast is a distinct extracellular compartment in plant tissues that lies outside the plasma membrane and includes the cell wall. The apoplastic ...

Solid Phase Microextraction Sampling: A Probe-based Technique for Sample Extraction from Graft Tissues

Source: Stryjak, I. et al. <a href="https://www-jove-com.bdigitaluss.remotexs.co/video/60946" target="_blank">Using a Chemical Biopsy for Graft Quality Assessment.</a> J. Vis. Exp. (2020)
In this video, we demonstrate SPME-probe-based extraction of metabolites from a pre-harvested donor kidney. The extracted metabolites can be used to perform metabolomic and lipidomic analysis in order to assess the organ quality for transplantation.

Source: Stryjak, I. et al. Using a Chemical Biopsy for Graft Quality Assessment. J. Vis. Exp. (2020)
In this video, we demonstrate SPME-probe-based ...

A Straightforward Method for Glucosinolate Extraction and Analysis with High-pressure Liquid Chromatography (HPLC)

Summary

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Chapters in this video

A Simple Fractionated Extraction Method for the Comprehensive Analysis of Metabolites, Lipids, and Proteins from a Single Sample

Fizzy Extraction of Volatile Organic Compounds Combined with Atmospheric Pressure Chemical Ionization Quadrupole Mass Spectrometry

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures

A Convenient Method for Extraction and Analysis with High-Pressure Liquid Chromatography of Catecholamine Neurotransmitters and Their Metabolites

The MPLEx Protocol for Multi-omic Analyses of Soil Samples

¹³C₆-Glucose Labeling Associated with LC-MS: Identification of Plant Primary Organs in Secondary Metabolite Synthesis

Arabidopsis thaliana Polar Glycerolipid Profiling by Thin Layer Chromatography (TLC) Coupled with Gas-Liquid Chromatography (GLC)

Liquid Chromatography Coupled to Refractive Index or Mass Spectrometric Detection for Metabolite Profiling in Lysate-based Cell-free Systems

The Infiltration-centrifugation Technique for Extraction of Apoplastic Fluid from Plant Leaves Using Phaseolus vulgaris as an Example

Solid Phase Microextraction Sampling: A Probe-based Technique for Sample Extraction from Graft Tissues