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Protocol: a fast, comprehensive and reproducible one-step extraction method for the rapid preparation of polar and semi-polar metabolites, lipids, proteins, starch and cell wall polymers from a single sample

Protocol: a fast, comprehensive and reproducible one-step extraction method for the rapid... Background: The elucidation of complex biological systems requires integration of multiple molecular parameters. Accordingly, high throughput methods like transcriptomics, proteomics, metabolomics and lipidomics have emerged to provide the tools for successful system-wide investigations. Unfortunately, optimized analysis of different compounds requires specific extraction procedures in combination with specific analytical instrumentation. However, the most efficient extraction protocols often only cover a restricted number of compounds due to the different physico-chemical properties of these biological compounds. Consequently, comprehensive analysis of several molecular components like polar primary metabolites next to lipids or proteins require multiple aliquots to enable the specific extraction procedures required to cover these diverse compound classes. This multi-parallel sample handling of different sample aliquots is therefore not only more sample intensive, it also requires more time and effort to obtain the required extracts. Results: To circumvent large sample amounts, distributed into several aliquots for the comprehensive extraction of most relevant biological compounds, we developed a simple, robust and reproducible two-phase liquid–liquid extraction protocol. This one-step extraction protocol allows for the analysis of polar-, semi-polar and hydrophobic metabolites, next to insoluble or precipitated compounds, including proteins, starch and plant cell wall components, from a single sample. The method is scalable regarding the used sample amounts but also the employed volumes and can be performed in microcentrifuge tubes, enabling high throughput analysis. The obtained fractions are fully compatible with common analytical methods, including spectroscopic, chromatographic and mass spectrometry- based techniques. To document the utility of the described protocol, we used 25 mg of Arabidopsis thaliana rosette leaves for the generation of multi-omics data sets, covering lipidomics, metabolomics and proteomics. The obtained data allowed us to measure and annotate more than 200 lipid compounds, 100 primary metabolites, 50 secondary metabolites and 2000 proteins. Conclusions: The described extraction protocol provides a simple and straightforward method for the efficient extraction of lipids, metabolites and proteins from minute amounts of a single sample, enabling the targeted but also untargeted high-throughput analyses of diverse biological tissues and samples. *Correspondence: Giavalisco@mpimp-golm.mpg.de Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany Full list of author information is available at the end of the article © The Author(s) 2016. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Salem et al. Plant Methods (2016) 12:45 Page 2 of 15 Keywords: Primary metabolites, Secondary metabolites, Lipids, MTBE, Starch, Cell wall, Proteins, Metabolomics, Lipidomics, Proteomics, Systems biology Background compounds possibly negatively interfering with down- Systems biology, the comprehensive study of several bio- stream analytical methods, leading to improved quality logical components and the analysis of their complex in the analysis of the compounds of interest. Only later, dependencies within a biological cell or tissue [1], is an with the onset of system-wide analysis strategies, these indispensable approach to understand complex cellular methods, especially the chloroform–methanol extrac- functions and processes. To obtain the analytical data tion protocol, were also projected to collect more than a for the diverse molecular constituents, ‘-omic’ platforms, single fraction of the two main phases [18–21]. Unfortu- including transcriptomics [2], metabolomics [3, 4], lipid- nately, the main problem associated with the reproduc- omics [5, 6] and proteomics [7, 8] have emerged to pro- ibility of the chloroform-based methods is derived from vide the ever growing tool-box for successful systems the fact that the solid components lie between the upper biology investigations [9]. Metabolomics and lipidomics organic (chloroform) and the lower methanol/water are aiming for the identification and quantification of phase after the phase separation. Accordingly, this diffuse the complement of all small molecules and lipids within and amorphous interphase hinders the quantitative col- a biological system, respectively [10]. In recent years, lection of this insoluble fraction, but also complicates the metabolomics and lipidomics have emerged as corner- maximal and contamination-free collection of the two stones in the field of systems biology [11]. main liquid phases. To overcome this problem, recent Owing, not only to the complexity, but also to the modifications of the chloroform–methanol method were diverse physico-chemical properties of the cellular con- introduced. Here the phase separation of the homoge- stituents, especially the different metabolite classes, neous, one phase chloroform–methanol mixture, was no single extraction solvent can extract all molecular achieved only after a centrifugation and the separation components from a complex biological sample [12, 13]. of the solid and the liquid phase in an independent step Accordingly, different classes of compounds require spe - [18–21]. This two-step approach partially overcomes the cific extraction methods to obtain adequate coverage of problem of the interphase between the two liquid phases the full diversity of cellular metabolism [14, 15]. but it is more time consuming, since the phase separation Because of the above-mentioned extraction specific - has to be achieved in an independent step [22]. Addition- ity, multiple aliquots of the same sample are required to ally, unwanted phase separation could occur if the water obtain sufficient material for the different extraction pro - content of the extracted samples are too high. cedures. Next to the increased effort due to multi-parallel To overcome these problems, we used a cleaner and sample handling, the required sample amounts for mul- safer alternative to chloroform, namely methyl tert-butyl tiple extractions are often not available for all tissues or ether (MTBE) for liquid–liquid extraction [23]. MTBE organisms. Consequently, a comprehensive extraction was initially used for the recovery of bacterial organic method providing the robust and reliable recovery of the acids [24] and lipids from different eukaryotic samples major molecular components from a single aliquot of a [25, 26]. The main advantage of using MTBE is the fact −3 single sample would be desirable. Such a method would that it has a severely decreased density (0.74  g  cm ) −3 decrease the sample handling time and therefore increase compared to chloroform (1.48  g  cm ), which not only the sample throughput. Since the compounds are derived leads to an inversion of the methanol and the MTBE from the same aliquot, it would also improve the data phases, but also to a stable and solid pellet at the bottom precision and its comparability. of the centrifugation tube. Based on these improved sep- To minimize the problem of multiple extractions from aration features, we were able to set up a MTBE-based several sample aliquots, multi-phase extraction proto- extraction method for the complete recovery of multiple cols, often relying on a two-phase separation system, compounds [23]. consisting of different mixtures of chloroform and meth - In this article, we now summarize and describe the anol, have been developed. These methods were initially complete single-step extraction protocol for rapid com- designed for the extraction and analysis of either pure prehensive and simultaneous analysis of lipids, metabo- lipids [16, 17] or polar metabolites [18]. Accordingly, the lites and proteins from a single aliquot of plant tissues. motivation to use the two-phase separation methods of This protocol also includes a reproducible recovery these initial studies was to reduce the compound com- of starch and cell wall (CW) polymers from the solid plexity in the extracted sample and clean them up from phase. Using Arabidopsis thaliana leaves as a model, Salem et al. Plant Methods (2016) 12:45 Page 3 of 15 we generated lipidomics, metabolomics and proteomics 15 min sonication step. For phase separation, a volume of datasets from 25  mg sample. We have successfully used 650 µl of solvent M2, was added to each vial/tube and the this method to annotate more than 200 lipid compounds, samples were again thoroughly vortexed for 1 min. After covering most of the classes involved in lipid metabolism. that, the samples are centrifuged at a speed of 20,000g for Additionally, we annotated more than 50 compounds 5 min at 4 °C. using LC–MS method covering most of phenylpropa- noids and glucosinolates and more than 90 covering the Analysis of lipids from the MTBE‑phase by UPLC‑MS classes involved in central metabolism from GC–MS A fixed volume (500  µl) of the solvent from the upper, method. Additionally, we obtained about 2000 protein lipid-containing phase, was transferred to a pre-labelled identifications but also the polysaccharide composition 1.5  ml microcentrifuge tube or glass vial and the sol- of the cell wall and the crystalline cellulose content. We vent was evaporated using either a SpeedVac concentra- therefore believe that this method could be used, with tor at RT or, preferably, a nitrogen flow evaporator. For minor adaptations, to analyze metabolites, lipids and the lipidomic analysis, we used our previously published proteins from most biological samples. Ultra Performance Liquid Chromatography Mass Spec- trometry (UPLC-MS) method [27]. Briefly, the dried pel - Methods lets from the 500  µl lipid fractions were re-suspended Plant material in 250  µl acetonitrile: 2-propanol (7:3, vol/vol) solution. Arabidopsis thaliana seeds (wild-type of ecotype Col- Once the samples are re-suspended in appropriate vol- 0) were stratified at 4  °C in dark for 3  days before sow - umes, 2  µl per sample was injected and the lipids were ing them on soil. The plants were grown in long day separated on a Reversed Phase (RP) Bridged Ethyl Hybrid (LD) phytotrons that were maintained at 16/8 light/ (BEH) C column (100 mm × 2.1 mm containing 1.7 μm dark cycle. The average light intensity was maintained at diameter particles, Waters), using a Waters Acquity −2 2 150  µmol  m /s . The day/night temperature and rela - UPLC system (Waters, Machester, UK). The mass spec - tive humidity were 20/16  °C and 60/75%, respectively. tra were acquired in positive and negative ionization Rosette leaves of 21-day-old plants were harvested and mode using a heated electrospray ionization (HESI) snap frozen in liquid nitrogen. The plant material was source in combination with an Exactive, Orbitrap-type, grounded into a homogeneous and fine powder using tis - MS (Exactive, Thermo-Fisher, Bremen, Germany). The sue homogenizer and then aliquoted (25  mg) into 2  ml mobile phases used for the chromatographic separation safe-lock microcentrifuge tubes. were water containing 1% 1  M ammonium acetate, 0.1% acetic acid (Buffer A) and acetonitrile: isopropanol (7:3, Reagent set‑up vol/vol) containing 1% 1 M ammonium acetate, 0.1% ace- For the preparation of 100 ml of extraction solvent mix- tic acid (Buffer B). The gradient separation was: 1  min ture 1 (M1), 75 ml of methyl tert-butyl ether were added 45% A, 3 min linear gradient from 45% A to 35% A, 8 min to 25 ml of methanol (3:1, vol/vol). Corticosterone (50 µl linear gradient from 25% A to 11% A, and 3  min linear of a 1  mg/ml stock solution in methanol) and ampicil- gradient from 11% A to 1% A. After washing the col- lin (25 µl of a 1 mg/ml stock solution in methanol) were umn for 3  min with 1% A, the buffer is set back to 45% used as internal standards for UPLC-MS analysis of A and the column is re-equilibrated for 4  min. The flow semi-polar metabolites. 1,2-diheptadecanoyl-sn-glycero- rate was set to 400  µl/min. Data analysis was performed 3-phosphocholine (50  µl of a 1  mg/ml stock solution in using the Progenesis QI software package (Progenesis QI chloroform) and C sorbitol (50  µl of a 1  mg/ml stock Version 2.2, Nonlinear Dynamics, Newcastle, UK) and as solution in water) were added as internal standards for described in Hummel et al. [27]. the UPLC-MS analysis of lipid and GC–MS analysis of polar metabolites, respectively. For extraction solvent Analysis of pigments from the MTBE‑phase mixture 2 (M2), phase separation-inducing solvent, 75 ml To measure chlorophylls, a volume of 100 µl of the upper of water were added to 25 ml of methanol (3:1, vol/vol). MTBE phase was mixed with 900  µl of methanol (1:9, vol/vol). The absorption UV–VIS spectra were measured Extraction and phase separation and the concentration of chlorophyll a (Chl ), chlorophyll A fixed volume (1 ml) of pre-cooled (−20 °C) extraction b (Chl ), total chlorophylls (Chl ), and total carotenoid b a+b solvent M1 was added to homogenized tissues. After contents was calculated as described previously [28–30]. adding the extraction solvent, the vials/tubes were thor- Additionally, a volume of 200  µl of the upper MTBE oughly vortexed for 1  min and then incubated on an phase was evaporated and used for HPLC-based analysis orbital shaker (100 rpm) for 45 min at 4 °C followed by a of carotenoids [31]. Salem et al. Plant Methods (2016) 12:45 Page 4 of 15 Analysis of primary metabolites from the methanol/water The sequential extraction of protein and starch from the phase by GC–MS insoluble pellet After having removed the remaining lipid phase from For the sequential protein and starch extraction, the the vials/tubes, 200  µl of the polar phase was trans- remainder of the aqueous phase was removed by pipet- ferred into pre-labelled 1.5  ml microcentrifuge tube and ting off the excess volume. The obtained pellet after the the samples were dried down in a SpeedVac concentra- metabolite and lipid extraction was washed by thor- tor without heating. For the analysis of the samples, the oughly adding 500  µl methanol and vortexing the sam- dried pellets were derivatized and analyzed using a pre- ples for 30 s. The samples were centrifuged at a speed of viously published GC-TOF–MS method [21, 32]. Briefly, 20,000g for 5 min at 4 °C. This washing step was repeated the dried 200 µl aliquots of the polar phase were re-sus- two more times. pended in methoxyamine-hydrochloride/pyridine solu- tion for methoxymization of carbonyl groups followed Extraction and analysis of proteins by LC–MS/MS by heating at 37 °C for 90 min. The samples were further For protein extraction, the washed pellet of a 25 mg leaf derivatized with N-methyl-N-trimethylsilyltrifloracet - material was re-suspended in 150  µl of protein extrac- amide (MSTFA) for 30  min at 37  °C. The MSTFA solu - tion buffer (6  M urea, 2  M thiourea, 15  mM DTT, 2% tion contained a mixture of 13 fatty acid methyl esters CHAPS and protease and phosphatase inhibitors). Once (FAMEs) with different chain length, which were used in the proteins were dissolved, the samples were sonicated the post-measurement as retention time standards. 1  µl for 10 min in a sonication bath, followed by an additional of the derivatized sample mixture was injected onto the 30  min incubation on an orbital shaker (100 r.p.m.) at GC-column and measured. Data analysis was performed room temperature. In the next step, the solubilized pro- using the TargetSearch package according to Cuadros- teins were centrifuged at 10,000g for 5 min and the pro- Inostroza et al. [33]. tein concentration was determined from the collected supernatant [34]. 50 µg of proteins extract were digested Analysis of secondary metabolites from the methanol/ in-solution using a Trypsin/Lys-C mixture (Mass Spec water phase by UPLC–MS Grade, Promega) according to the instruction manual. A fixed volume of 400  µl of the polar phase was trans - After the digestion, the samples were desalted using C ferred into a pre-labelled 1.5 ml microcentrifuge tube and stage tips as described in Rappsilber et al. [35]. After the the samples were dried down in a SpeedVac concentrator elution of the digested and desalted peptides from C - without heating. For the direct analysis, the samples were stage tips, the samples were concentrated to near dryness handled as described previously in Giavalisco et  al. [23]. in a SpeedVac and the peptide mixtures were analyzed by Briefly, the dried 400 µl aliquots of the polar phase were LC-MS/MS using a Q ExactivePlus high resolution mass re-suspended in 200  µl UPLC-grade methanol: water spectrometer connected to an EASY-nLC 1000 system (1:1, vol/vol) and transferred to the autosampler, 2 µl was (Thermo-Fisher, Bremen, Germany). Peptides were sep - injected and separated on RP High Strength Silica (HSS) arated using a binary buffer system of 0.1% formic acid T3 C column (100  mm  ×  2.1  mm containing 1.7  μm in water (Buffer A) and 60% acetonitrile containing 0.1% diameter particles, Waters), using a Waters Acquity formic (Buffer B). The flow rate was adjusted to 300  nl/ UPLC system. The mass spectra were acquired by full min. Peptides were eluted with using a linear gradient of scan MS in positive and negative ionization mode on an 0–40% buffer B for 50  min followed by a linear gradient Exactive high resolution Orbitrap-type MS (Thermo- between 40–80% buffer B for additional 30  min. Pep - Fisher, Bremen, Germany). The mobile phases used for tides were analyzed with one full scan (200–2000  m/z, chromatographic separation were water containing 0.1% R  =  70,000 at 200  m/z), followed by up to fifteen data- formic acid (Buffer A) and acetonitrile containing 0.1% dependent MS/MS scans (Top 15 approach) with higher- formic acid (Buffer B). The compounds were separated by energy collisional dissociation (HCD) at a resolution of a gradient: 1 min 99% A, 13 min linear gradient from 99% 17,500 at 200  m/z. Dynamic exclusion was set to 30  s. A to 65% A, 14.5 min linear gradient from 65% A to 30% Raw data were processed using the Progenesis QI for A, 15.5 min linear gradient from 30% A to 1% A, hold 1% proteomics (Progenesis QI for Proteomics Version 3.0, A until 17, 17.5 min linear gradient from1% A to 99% A, Nonlinear Dynamics, Newcastle, UK) software in combi- and re-equilibrate the column for 2.5  min. The flow rate nation with the Mascot (Version 2.5, MatrixScience, Bos- was adjusted to 400 µl/min. Data analysis was performed ton MS, USA) database search tool using the Arabidopsis by using the Progenesis QI software package (Progenesis TAIR database (Version 10, The Arabidopsis Information QI Version 2.2, Nonlinear Dynamics, Newcastle, UK). Resource, www.arabidopsis.org). Salem et al. Plant Methods (2016) 12:45 Page 5 of 15 Extraction and enzymatic determination of the starch nitric acid/water (8: 1: 2, vol/vol/vol). The samples were content quickly vortexed, heated at 100  °C for 30  min, cooled to For starch extraction, the remaining pellet after pro- room temperature and finally centrifuged at 10,000g for tein extraction was washed using 1  ml of 80% ethanol. 10 min at room temperature. After discarding the super- After that step, the samples were incubated for 3  min at natant, the pellet was washed tree times with 100  µl of 80 °C and finally centrifuged at 3000g for 10 min at room water and finally re-dissolved in 100  µl of 72% sulfu - temperature. The washed pellets were re-dissolved in ric acid. Crystalline cellulose content was determined 0.5  ml of water and the starch was gelatinized by heat- based on glucose standard curve using the colorimetric ing at 100  °C for 1.5  h. After allowing the samples to anthrone assay [39, 40]. cool, 0.5  ml of 200  mM sodium acetate was added and The lignin content and composition was determined the dissolved starch was digested into its glucose mono- using the thioglycolic acid (TGA) and the thioacidoly- mers with an enzyme mix of α-amyloglucosidase and sis quantification methods, respectively [41–44]. For α-amylase, according to manufacturer instructions [36, TGA quantification of lignin, 1  mg of the prepared cell 37]. The tubes were incubated overnight at 37  °C and wall material was re-suspended in 250 µl of 2 N HCl and finally centrifuged at 10,000g for 5  min at room tem - 25  µl of TGA and the samples were incubated at 100  °C perature. Glucose concentration was determined based for 3  h with regular shaking. The samples were allowed on an enzymatic assay through hexokinase and glucose to cool before centrifuging them at 10,000g for 5  min at 6-phosphate dehydrogenase and the assay was performed room temperature. The pellet was washed three times in a 96-well plate using a microtiter plate reader. Briefly, with 0.5  ml of water before re-dissolving in 0.5  ml of an appropriate volume (40  µl) of the digested samples 1  M NaOH followed by overnight incubation at room was mixed with 160  µl of glucose assay mix consists of temperature with gentle shaking. The sample were cen - 100  mM HEPES, pH 7.5, 4  mM MgCl , 0.5  mM adeno- trifuged at 12,000g for 10  min at room temperature and sine triphosphate (ATP) and 1 mM nicotinamide adenine the supernatant was acidified with 100 µl of concentrated dinucleotide (NAD ), hexokinase (6 U/ml). After moni- HCl before incubating them at 4  °C for 4  h with regular toring the initial absorption at 340 nm (OD ), 0.25 units shaking. The pellet remained after centrifugation was re- glucose 6-phosphate dehydrogenase were added to each dissolved in 1 ml of 1 M NaOH and then the absorbance well and the OD was recorded again. Starch concen- was measured spectrophotometrically at 280 nm [41, 42]. tration was determined based on a calibration curve of a For lignin composition, 1  mg of the prepared cell wall standard glucose [36, 37]. material was re-suspended in 100  µl of 2.5% boron trif- luoride etherate and 10% ethanethiol/dioxane solution. Analysis of cell wall composition The samples were heated at 100 °C for 4 h with shaking. For the analysis of the cell wall polymers, the remaining The samples were allowed to cool before adding 100  µl pellet, after protein and starch extraction, was washed of 0.4  M sodium bicarbonate followed by liquid–liquid three times by thoroughly vortexing the samples for 30 s separation using 0.5 ml of ethyl acetate and 1 ml of water. in 500 µl of water. After washing the pellets, the samples An appropriate aliquot (200 µl) of the ethyl acetate layer were air-dried in a container with silica beads and were was allowed to evaporate followed by derivatization and analyzed immediately or they can be stored in a desicca- GC–MS analysis [43, 44]. tor until further extraction. The detailed polysaccharide composition of cell walls Troubleshooting was determined after acid hydrolysis and GC derivati- During the development and validation of this protocol, zation [38, 39]. Briefly, 2  mg of the cell wall pellet was a number of issues arose, for which we developed a trou- hydrolyzed by dissolving in 200 µl of 2.5 M trifluoroacetic bleshooting guide, which is summarized in Additional acid (TFA) and heating at 121  °C for 1.5  h. The samples file 1: Table S1. were allowed to cool before centrifuging them at 10,000g for 5  min at room temperature. An appropriate volume Results (100 µl) of the acidic supernatant was transferred to new Development of a comprehensive extraction method glass screw-capped tubes and 10 µl of the internal stand- Based on the requirement to extract all relevant molecu- ard (10 mg/ml of myo-inositol) was added. Samples were lar features from a biological sample, ideally from a single evaporated to dryness, reduced, acetylated and finally sample aliquot, we decided to develop a comprehensive measured on GC–MS [38, 39]. The content of crystal - one-step extraction protocol for the analysis of plant line cellulose was determined by a spectrophotometric tissue. The developed liquid–liquid two-phase separa - method [39, 40]. Briefly, the pellet remained after hydrol - tion system, which is conceptual similar to the classical ysis with TFA was re-dissolved in 100  µl of acetic acid/ chloroform: methanol extraction methods [18–21], relies Salem et al. Plant Methods (2016) 12:45 Page 6 of 15 on a MTBE: methanol: water system. Based on the ini- and 0.65 ml of extraction buffer M2 (see “Methods ” sec- tially published version of the method, where we ana- tion). If larger amounts of tissue have to be extracted, the lyzed lipids, proteins and polar metabolites [23], we were extraction volume can be linearly scaled. Unfortunately, able to extend and improved our previously published larger extraction volumes cannot be handled any longer extraction protocol. The updated protocol allows for in microcentrifuge tubes, which decreases the through- the fast and reproducible extraction of lipids, pigments, put of the method. Thus far, we have not encountered polar to semi-polar primary and secondary metabolites biological material where the usage of larger amounts of but also proteins, starch and cell wall (CW) polymers. material for the comprehensive analysis of lipids, polar Figure  1 illustrates graphically the simple and straight- metabolites or secondary metabolites was required, actu- forward workflow of the described extraction proto - ally contrary we were able to extract a full lipid profile col, which is easily adjustable to the required amount from as little as 20 Arabidopsis thaliana seeds (data not of sample. Usually between 10 and 50  mg of tissue are shown). used. The employed sample amounts are depending on As indicated in Fig.  1, the whole procedure requires tissue availability but also the intended analysis. Tissue only few pipetting steps once the required sample are amounts within this scale are routinely extracted in 2 ml aliquoted in the microcentrifuge tubes. Due to this sim- microcentrifuge tubes, using 1 ml of extraction buffer M1 plified workflow, a single person can handle 100 or more samples within half working day (4  h), enabling high throughput sample preparation as a pre-requirement for large-scale experiments. In the following sections we pro- vide an exemplary multi-omics analysis of a 25  mg leaf sample of Arabidopsis thaliana (Col-0), extracted with 1 ml of the MTBE: Methanol extraction solution. Figure 2 provides an overview of the analytical workflow applied to the different fractions of the tissue sample. Analysis of the lipid phase As indicated in the Fig.  2, the upper-organic (MTBE) phase obtained from the extraction contains most of the hydrophobic compounds. On the one hand, as indicated by the green color of the extract, this fraction contains the full inventory of pigments, including the major chlo- rophylls, but also several carotenoids. On the other hand, most lipids, namely the polar phospholipids and sphin- golipids, which are the constituents of the cellular mem- brane system, next to the neutral storage lipids and the free fatty acids were extracted in this phase. To validate this hydrophobic phase of the MTBE- extraction protocol, we initially tested the efficiency but also the reproducibility of this fraction compared to other commonly used protocols used for specific analy - sis of hydrophobic metabolites. For this purpose, we have performed parallel extractions of chlorophylls using the organic MTBE-fraction and compared the obtained results to chlorophyll extraction methods using acetone Fig. 1 Overview of the experimental workflow for the MTBE-based [28–30]. As indicated in Additional file  1: Figure S1 the extraction procedure. Plant material is harvested and snap-frozen analysis of chlorophyll a and b led to almost identical in liquid nitrogen. The harvested tissue is homogenized using a results between the commonly used 80% acetone method pre-cooled mortar and pestle or cooled tubes in a mixer mill. About 10–50 mg ±10% of the frozen powder is weighed in pre-labelled and an aliquot of 0.1  ml of the upper MTBE-fraction, 2 ml microcentrifuge tube. The weighed powder is extracted using indicating the suitability of this fraction for the analysis 1 ml of the first extraction solvent (M1, MTBE:MeOH 3:1, vol/vol) fol- of chlorophylls. Next to the analysis of chlorophylls using lowed by rigorous vortexing, agitated incubation and sonication of the spectroscopic method, we have also validated the the samples. A liquid/liquid phase separation is achieved by adding frequently used method of Fraser et  al., for the HPLC- 0.65 ml of the second extraction solvent (M2, H2O:MeOH 3:1, vol/vol) followed by vortexing and centrifugation based analysis of carotenoids. Here we observed that the Salem et al. Plant Methods (2016) 12:45 Page 7 of 15 Fig. 2 Schematic overview of the applied analytical methods. Following the two plus one phase extraction procedure, a phase separation of upper non-polar metabolites and a lower layer of polar to semi-polar metabolites next to a solid pellet (proteins, starch and cell wall) is obtained. A predefined volume (0.5 ml) of the upper lipid phase is aliquoted into three fractions (0.2, 0.2 and 0.1 ml), which are concentrated and analyzed by UPLC-MS, LC- photodiode array (PDA) or spectrometry for the lipid, pigment or chlorophyll composition, respectively. Two aliquots with predefined volume (0.2 and 0.4 ml) of the lower methanol: water phase are dried and the re-suspended compounds are analysed by GC- and UPLC-MS for analysis of primary and secondary metabolite composition, respectively. The starch/protein/cell wall pellet is washed followed by sequential protein and starch extraction. The de-proteinated and de-starched pellet, which contains the remaining cell wall material, can be used for determination of polysaccharide composition, cellulose and lignin Salem et al. Plant Methods (2016) 12:45 Page 8 of 15 hydrophobic MTBE fraction provided comparable results rosette leaf tissue using a high-throughput UPLC-MS for carotenoids to the results obtained using the extrac- analysis (Additional file  1: Table S4). Similar to the lipid- tion protocols described in the original paper [31] (Addi- omic analysis, the compounds were chromatographically tional file 1: Figure S2). separated and the molecular ions were detected in the There are several simple (e.g. thin layer chromatogra - mass spectrometer using the positive and negative ioni- phy or LC-Evaporative Light Scattering detector) and zation mode (Fig.  5). In sum, these two measurements advanced (UPLC-MS or Shotgun MS) methods available allowed us to detect, similarly to the UPLC-MS spectra to analyze or profile lipids in a targeted or untargeted from the lipidomic analysis, several thousand reproduc- way [5]. One of the well-established approaches relies ible peaks in positive and negative ionization mode. Still, on the mass spectrometric analysis in combination with even though several thousand chromatographic peaks reversed-phase chromatographic separation [27]. This can be detected from this fraction, thus far only few approach, especially, if fast UPLC is used, allows for the compounds could be reliably annotated. Nevertheless, detailed profiling of the main lipid classes. The obtained these annotated metabolites cover a wide range of the data (Additional file  1: Table S2) can provide an overview Arabidopsis thaliana secondary metabolism, providing a of changes in the composition of the plasma-, the endog- detailed insight into the regulation of the main classes of enous-, organelle- and the chloroplast membrane system, sinapates [45], glucosinolates [46], flavonoids and antho - next to the availability and composition of free fatty acids cyanins [47] (Fig.  5), which are known to be involved in and storage lipids. As described in detail in the method many biotic and abiotic stress responses. section, our UPLC-MS-based profiling approach enables the reliable and robust detection of more several thou- Analysis of the solid pellet sand chromatographic peaks, of which at least 200 lipid After removing the liquid-extracted metabolites (polar species (Additional file  1: Table S2) from an Arabidop- and hydrophobic), the remaining solid pellet can be used sis rosette leaf sample could be reliably annotated using for the extraction of proteins, starch and cell wall mate- the accurate mass and the obtained retention time [27]. rial (Fig.  2). The order of the extraction of the different These annotated lipid classes, obtained from the positive classes of compounds cannot be interchanged, since and negative ionization mode measurements of the same severe losses of proteins are observed if the extraction sample are displayed on a representative set of chroma- steps required for solubilization and hydrolysis of the tograms in Fig.  3. Because each optimized chromato- starch are applied before protein extraction (Additional graphic run takes only 24  min, the employed method is file  1: Figure S3). Accordingly, the first step of the three- highly compatible to high throughput analysis of large step extraction procedure of the solid pellet relies on the lipidomic data sets [27, 32]. efficient extraction of proteins from the obtained pellet. In addition to the reproducible results of protein concen- Analysis of the polar phase: primary and secondary trations obtained by our extraction method (Additional metabolites file  1: Figure S3), we were able to obtain high-quality As described in Fig.  2, two aliquots derived from the shotgun proteomics data from the generated protein polar (lower) fraction, were analyzed using two comple- extracts (Fig.  6). The results and the spectra from the mentary analytical methods. Polar primary metabolites proof of concept in-solution digestion and nanoLC-MS were measured routinely, after a trimethylsilyl (TMS) analysis of the extracted proteins allowed for the rou- derivatization, by a very well established GC–MS analysis tine identification of more than 2000 proteins from a method [21, 32], while the semi-polar secondary metabo- 25 mg sample of Arabidopsis thaliana rosette leaves. The lites could be directly analyzed using a robust reversed obtained identifications, using a single measurement, had phase UPLC-MS method [23]. at least two independent peptides and a false discovery As can be seen from Additional file  1: Table S3, the rate (FDR) below 1% (Additional file  1: Table S5). Inter- GC–MS analysis enables the reliable detection of several estingly, next to the large amount of soluble proteins, hundred peaks, of which more than 90 polar metabo- we also detected significant amounts of transmembrane lites, covering a wide range of metabolic classes from proteins, especially from the thylakoids, the nucleus, the the central primary metabolism, including the main sug- ER, and the plasma membrane. This increased quantity ars, amino acids and organic acids, could be annotated. of hydrophobic proteins is explained by the fact that the Figure  4 shows a representative GC–MS chromato- MTBE extraction method provides a clean and com- gram, where the identities of the major metabolites are pletely de-lipidation of membranes, namely membrane indicated. lipid are extracted in the upper MTBE phase, providing As mentioned above, next to the polar metabolites, we a high quantity of precipitated membrane proteins in the also annotated more than 50 secondary metabolites from solid pellet. Salem et al. Plant Methods (2016) 12:45 Page 9 of 15 Fig. 3 Base peak chromatograms of total lipids extracted from Arabidopsis rosette leaves. Relative abundances of eluted peaks versus retention time (min) are shown. The region of the different detected and annotated lipid classes is indicated according to its abundance either in positive or negative ion modes (for details see Additional file 1: Table S2). The number of detected lipid compounds for every class is indicated in brackets. Chl a chlorophyll a, Chl b chlorophyll b, DAG diacylglyceride, DGDG digalactosyldiacylglycerol, FA fatty acid, LysoPC lysophosphatidylcholine, MGDG monogalactosyldiacylglycerol, PC phosphatidylcholine, PE phosphatidylethanolamine, PG phosphatidylglycerol, PI phosphatidylinositol, PS phos- phatidylserine, SP sphingolipid, SQDG sulfoquinovosyldiacylglycerol, TAG triacylglyceride Fig. 4 GC–MS-based total ion chromatogram of derivatized primary metabolites from Arabidopsis rosette leaves. Intensity of eluted peaks versus retention time (seconds) are shown. Identities of the most abundant metabolites are indicated. More than 90 compounds from this GC-MS data were annotated (Additional file 1: Table S3). These compounds include amino acids and their derivatives, sugars, sugar acids, sugar alcohols, sugar derivatives, organic acids and their derivatives, fatty acids, sinapates, amines and others Salem et al. Plant Methods (2016) 12:45 Page 10 of 15 Fig. 5 UPLC-MS base peak chromatograms of polar to semi-polar metabolites extracted from Arabidopsis rosette leaves. Relative abundances of eluted peaks versus retention time (min) are shown. The region of each eluted compound class is indicated according to its elution window either in positive or negative ionization modes. The number of detected compounds for every class is indicated in brackets (for details see Additional file 1: Table S4) Once the proteins are extracted from the solid pellet, namely the insoluble cell wall material. This material can a quantitative extraction and analysis of cellular starch be used to determine the polysaccharide composition of content can be performed on the remaining pellet. Since cell walls, the crystalline cellulose content and lignin by starch analysis is a highly established and standardized GC–MS and spectroscopic methods (see “Methods” sec- method for photoautotrophic organisms, we aimed to tion). Additional file  1: Figure S5 summarizes the analysis compare the extracted amounts of starch derived from of this last fraction of the solid pellet and illustrated that the insoluble protein, starch, cell wall pellet obtained these compounds can be analyzed reproducibly from the from the MTBE extraction, to the values obtained from remaining pellet, providing an additional insight in an the commonly used standard extraction methods [32, often-neglected cellular compartment. 36]. Much as we hoped for, we found that the starch con- centrations obtained from the de-proteinated pellet were Discussion highly similar to the concentrations measured by the The application of the here described protocol, allows for Smith and Zeeman protocol [36]. Next to the loss-free the independent and qualitative extraction and separa- fractionated extraction of protein and starch, our method tion of the major compound classes, from a single sam- also proved to be highly reproducible over a large range ple. In addition to the detailed extraction protocol (see of concentrations as indicated by the small error bars “Methods” section), we additionally provide exemplary (Additional file 1: Figure S4). analytical data, mainly using gas- (GC) and liquid-chro- Once we reached the de-proteinated and de-starched matography (LC) coupled to diverse mass spectrometers pellet at the end of the sequential extraction of the solid for the analysis of the three different phases (organic, pellet, there is still material for an additional analysis left, polar and solid). The precise conditions for analysis of Salem et al. Plant Methods (2016) 12:45 Page 11 of 15 11.1 22.9 16.2 20.1 29.2 40.6 24.6 31.0 43.4 33.2 83.0 46.9 52.3 60.1 66.5 55.8 70.4 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 Time (min) Storage proteins, 5 Kinases, 64 Isomerases, 96 Receptor proteins, 20 Proteases, 78 Cell junc‰on proteins, 1 Cytoskeletal proteins, 76 Chaperones, 68 Transporter proteins, 88 Transcrip‰on factors, 22 Phosphatases, 36 Transmembrane receptor regulatory/adaptor proteins, 2 Membrane traffic proteins , 25 Transfer/carrier proteins, 44 Transferases, 257 Hydrolases, 233 Defense/immunity proteins, 5 Calcium-binding proteins, 30 Oxidoreductases, 276 Enzyme modulators, 65 Lyases , 92 Signaling molecules, 26 Cell adhesion molecules , 2 Nucleic acid binding proteins, Ligases, 84 Fig. 6 UPLC-MS chromatogram of proteins from Arabidopsis rosette leaves and their classification according to protein identifications. a Total ion chromatogram of proteins extracted from Arabidopsis rosette leaves. Relative abundances of eluted peaks versus retention time (min) are shown. b Different protein classes and the number of proteins that contribute to each class from Arabidopsis rosette leaves (for details see Additional file 1: Table S5) different metabolites are based on the availability of spe - combination of these divers molecular entities, espe- cific instruments and can be easily extended beyond the cially the combination of metabolite data and the protein provided examples given in this article. data allows to draw causal conclusions of the functional As we have shown in this protocol, the analysis of a molecular machines (proteins) and their products single sample using the fractionated extraction method, (metabolites), from the exact same sample. The use of provides profound insight, not only into diverse molec- a single sample therefore allows minimizing the differ - ular compounds, but also provides a functional over- ence between the origin of measurement and therefore view of most cellular compartments and processes. The to maximize the accuracy of the analysis. Next to the Relative Abundance Salem et al. Plant Methods (2016) 12:45 Page 12 of 15 decrease in sample consumption, this strategy provides tissues. Amongst others, we studied Arabidopsis thaliana an ideal foundation for computational systems biological seedlings [32], roots and leaves [23], barley (Hordeum approaches. vulgare) [62], wild strawberry (Fragaria vesca) [63] straw- berry (Fragaria X ananassa) [64], the root tissue of maize Applications of the MTBE extraction protocol (Zea mays) [65], the green algae Chlamydomonas rein- for ‘omic’‑based analysis hardtii [66], the marine diatom Thalassiosira pseudonana As described in the result section the total amount of [61] and some low phosphate-tolerant proteaceae species 25  mg of leaf tissue allows for the complex analysis of [51]. several hundred molecular properties of a single sam- ple. Of course, the analysis and the annotation of further Future perspectives and challenges compounds are only limited by the biological question In this protocol, we  showed that our method could be and the analytical methods and the equipment employed used for a comprehensive “multi-omics” sample extrac- for the downstream analysis of the obtained extracts. tion, preparation and analysis. The analysis of multiple u Th s far we have not encountered analytical methods molecular entities, derived from several subcellular com- that were incompatible with the obtained fractions and partments and molecular processes provides a brought in most cases the obtained abundance and the quality overview of the status of the cell. Still compound anno- of the compounds from the MTBE-derived extracts was tation and/or identification are the major challenge in reaching sensitivities and quality to the more special- the metabolomics data analysis. Although we were able ized extraction methods. Beyond the optimal applicabil- to annotate many lipids, metabolites and proteins, more ity of our method for plant cells and tissues, it should be compounds are still to be uncovered and would, if possi- mentioned that we have not only applied this method ble allow to broaden our insight into the molecular inven- thus far for diverse plant samples [23, 27, 32, 48–54], but tory of the cell. For instance, even though we detected it was also successfully employed for metabolic and/or some sphingolipids or sterols in our lipid analysis, these proteomic studies of algae [55, 56], flies [57] and diverse lipid specific lipid classes are slightly underrepresented in mammalian cells and tissues [58–60]. our data set. This underrepresentation is not due to the In previous studies, we have analyzed the MTBE- extraction procedure, but it is explained by the complex- derived lipid phase for the identification and analysis ity of the sample, namely by ion suppression or matrix of lipid species from Arabidopsis thaliana dry seeds effects, and the measurement mode of our method. Still, [48, 53], seedlings [32, 49], leaves [23, 27, 50–54], roots it should be easily possible to modify our analytical work- [23] and flowers [54]. Additionally, we applied the same flow enabling the inclusion of the missed compounds. For method, with minor adaptations in the extraction pro- instance, it is possible to expand the number of detect- cess, to compare the lipid composition of mammalian tis- able sphingolipids by analyzing the MTBE but also the sues including brain, kidney and skeletal muscle of mice, methanol phase after mild base hydrolysis, which allows rhesus macaques, chimpanzees and humans [58–60]. depleting the highly abundant glycerolipids and therefore Moreover, the method allowed the detection and annota- improve the analysis of the slightly less abundant 100– tion of more than 180 lipid species from Chlamydomonas 150 species of the non-hydrolysable sphingolipids [67, reinhardtii [55]. Furthermore, we applied the described 68]. Next to the dedicated analysis of sphingolipids, the method to determine the lipid composition of the green uses of either atmospheric pressure chemical ionization algal species Scenedesmus (Acutodesmus) obliquus [56] (APCI) or improved direct infusion MS-based analysis and the model fly Drosophila melanogaster [57]. More - strategies can be used for the analysis of more than 100 over, the method has been proven useful also for lipid sterols and their derivatives [69, 70]. profiling of 124 lipid species from the marine diatom As already mentioned in the result section, we do rou- (Thalassiosira pseudonana) [53, 61] and the biddulphioid tinely annotate 50–60 secondary metabolites from Arabi- diatom (Biddulphia biddulphiana) [61]. dopsis thaliana by our UPLC–MS analysis. Although Next to the major lipid profiling approaches described these secondary metabolite classes include the main above, we also applied the extraction method for the secondary metabolites like the sinapates, glucosinolates, analysis of polar and semi-polar compounds in several flavonoids and anthocyanins, still we have to admit that plant species. These analyses provided a basic insight into the obtained spectra from these UPLC-MS measure- central carbon and nitrogen metabolism at the systems ments contain plenty of reproducible but unidentified level. Accordingly, we were able to apply the protocol for chromatographic peaks. Many of these will be true sec- the extraction, detection and identification of primary ondary metabolites derived from the plant. In a previous and/or secondary metabolites of several species and paper using the polar phase from the MTBE extraction Salem et al. Plant Methods (2016) 12:45 Page 13 of 15 method, we demonstrated by multiple isotope labelling Conclusion experiments that more than 1400 chromatographic peaks In this protocol, we describe a universal extraction of these spectra, obtained from the UPLC-MS analysis method that allows for the preparation and isolation of of the polar fraction, were of biological origin, indicating lipids, metabolites, proteins and other macromolecules the large pool of biologically-relevant information con- for high-throughput multi-omics analysis using a sin- tained and unexploited in these samples [23]. Unfortu- gle biological plant sample. We optimized and used this nately, metabolite annotation is still far from routine and approach to generate several analytical datasets from the high-throughput [71]. The main complication by using same sample. This allows for the brought insight into the this fraction for the analysis of secondary metabolites analyzed system and decreases the bias in systems biol- comes more from the high structural complexity of the ogy application. Accordingly, the described method does analyzed compounds and the difficulty to annotate them not only lead to significantly reduced sample consump - without authentic reference compounds. In the above- tion but also minimizes the time and effort needed to mentioned study, we were using stable isotope labeling perform separate extractions when many molecules are for the unambiguous annotation of the compounds, but to be studied in the same experiment. On the long run, of course it would be desirable to additionally use authen- we are planning to further improve the method, espe- tic standards and higher order MS-based fragmentation cially by expanding the repertoire of applicable analytical analysis for the proper structural elucidation of the thus methods and therefore further broadening the number far unknown compounds. and quality of the detectable components. Regarding proteomic analysis, we routinely identify Additional file 2000–3000 proteins from Arabidopsis covering sev- eral enzymes, signaling- and transmembrane proteins. Additional file 1. Supplemental Figures and Tables. The number of specific proteins can still be increased by either increasing the amount of starting material but also by sub fractionation of the obtained pellet. In the Author contributions current protocol, we re-suspended the protein pellet for MAS and JJ optimized the extraction protocol. KB performed protein extrac- tion, digestion and protein data analysis. MAS contributed to the develop- example initially in urea/thiourea buffer, which might not ment and validation of the methods and wrote the protocol. PG supervised fully solubilize the most hydrophobic membrane pro- the project, optimized GC- and LC-MS analytical methods for analysis and teins. Accordingly the protein extraction buffer, could be contributed to writing and improving the protocol. The work was performed at the Max-Planck Institute of Molecular Plant Physiology, Golm, Germany. All changed to a detergent-containing buffer (e.g. a 0.5–1% authors read and approved the final manuscript. sodium dodecyl sulphate-containg buffer) in combina - tion with a Filter Aided Sample Preparation (FASP) in Author details Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, solution digestion protocol [72]. 14476 Potsdam-Golm, Germany. Department of Pharmacognosy, Faculty It is also possible to maximize the number of extracta- of Pharmacy, Cairo University, Kasr El-Aini Street, Cairo 11562, Egypt. ble and identifiable proteins by using a sequential protein Acknowledgements extraction strategy [73]. So one can start extracting the We would like to thank Prof. Dr. Lothar Willmitzer, Dr. Alisdair Fernie and Dr. soluble proteins with a mild Tris buffered saline (TBS) Andrew Wiszniewski for proof reading and commenting on the manuscript. buffer, followed by the extraction of structure associated Special thanks to Andrea Leisse, Änne Michaelis and Gudrun Wolter for their excellent technical assistance. M.A.S. is a holder of a German-Egyptian proteins using a stronger chaotropic buffer (e.g. urea/ Research Long-Term Scholarship (GERLS-DAAD). thio urea) and finally, as mentioned above, a detergent- containing buffer for the extraction of transmembrane Competing interests The authors declare no competing interests. proteins. 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Toward the storage metabolome: profiling the barley vacuole. Plant Physiol. 2011;157(3):1469–82. Submit your next manuscript to BioMed Central and we will help you at every step: • We accept pre-submission inquiries • Our selector tool helps you to find the most relevant journal • We provide round the clock customer support • Convenient online submission • Thorough peer review • Inclusion in PubMed and all major indexing services • Maximum visibility for your research Submit your manuscript at www.biomedcentral.com/submit http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Plant Methods Springer Journals

Protocol: a fast, comprehensive and reproducible one-step extraction method for the rapid preparation of polar and semi-polar metabolites, lipids, proteins, starch and cell wall polymers from a single sample

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Springer Journals
Copyright
Copyright © 2016 by The Author(s)
Subject
Life Sciences; Plant Sciences; Biological Techniques
eISSN
1746-4811
DOI
10.1186/s13007-016-0146-2
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Abstract

Background: The elucidation of complex biological systems requires integration of multiple molecular parameters. Accordingly, high throughput methods like transcriptomics, proteomics, metabolomics and lipidomics have emerged to provide the tools for successful system-wide investigations. Unfortunately, optimized analysis of different compounds requires specific extraction procedures in combination with specific analytical instrumentation. However, the most efficient extraction protocols often only cover a restricted number of compounds due to the different physico-chemical properties of these biological compounds. Consequently, comprehensive analysis of several molecular components like polar primary metabolites next to lipids or proteins require multiple aliquots to enable the specific extraction procedures required to cover these diverse compound classes. This multi-parallel sample handling of different sample aliquots is therefore not only more sample intensive, it also requires more time and effort to obtain the required extracts. Results: To circumvent large sample amounts, distributed into several aliquots for the comprehensive extraction of most relevant biological compounds, we developed a simple, robust and reproducible two-phase liquid–liquid extraction protocol. This one-step extraction protocol allows for the analysis of polar-, semi-polar and hydrophobic metabolites, next to insoluble or precipitated compounds, including proteins, starch and plant cell wall components, from a single sample. The method is scalable regarding the used sample amounts but also the employed volumes and can be performed in microcentrifuge tubes, enabling high throughput analysis. The obtained fractions are fully compatible with common analytical methods, including spectroscopic, chromatographic and mass spectrometry- based techniques. To document the utility of the described protocol, we used 25 mg of Arabidopsis thaliana rosette leaves for the generation of multi-omics data sets, covering lipidomics, metabolomics and proteomics. The obtained data allowed us to measure and annotate more than 200 lipid compounds, 100 primary metabolites, 50 secondary metabolites and 2000 proteins. Conclusions: The described extraction protocol provides a simple and straightforward method for the efficient extraction of lipids, metabolites and proteins from minute amounts of a single sample, enabling the targeted but also untargeted high-throughput analyses of diverse biological tissues and samples. *Correspondence: Giavalisco@mpimp-golm.mpg.de Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany Full list of author information is available at the end of the article © The Author(s) 2016. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Salem et al. Plant Methods (2016) 12:45 Page 2 of 15 Keywords: Primary metabolites, Secondary metabolites, Lipids, MTBE, Starch, Cell wall, Proteins, Metabolomics, Lipidomics, Proteomics, Systems biology Background compounds possibly negatively interfering with down- Systems biology, the comprehensive study of several bio- stream analytical methods, leading to improved quality logical components and the analysis of their complex in the analysis of the compounds of interest. Only later, dependencies within a biological cell or tissue [1], is an with the onset of system-wide analysis strategies, these indispensable approach to understand complex cellular methods, especially the chloroform–methanol extrac- functions and processes. To obtain the analytical data tion protocol, were also projected to collect more than a for the diverse molecular constituents, ‘-omic’ platforms, single fraction of the two main phases [18–21]. Unfortu- including transcriptomics [2], metabolomics [3, 4], lipid- nately, the main problem associated with the reproduc- omics [5, 6] and proteomics [7, 8] have emerged to pro- ibility of the chloroform-based methods is derived from vide the ever growing tool-box for successful systems the fact that the solid components lie between the upper biology investigations [9]. Metabolomics and lipidomics organic (chloroform) and the lower methanol/water are aiming for the identification and quantification of phase after the phase separation. Accordingly, this diffuse the complement of all small molecules and lipids within and amorphous interphase hinders the quantitative col- a biological system, respectively [10]. In recent years, lection of this insoluble fraction, but also complicates the metabolomics and lipidomics have emerged as corner- maximal and contamination-free collection of the two stones in the field of systems biology [11]. main liquid phases. To overcome this problem, recent Owing, not only to the complexity, but also to the modifications of the chloroform–methanol method were diverse physico-chemical properties of the cellular con- introduced. Here the phase separation of the homoge- stituents, especially the different metabolite classes, neous, one phase chloroform–methanol mixture, was no single extraction solvent can extract all molecular achieved only after a centrifugation and the separation components from a complex biological sample [12, 13]. of the solid and the liquid phase in an independent step Accordingly, different classes of compounds require spe - [18–21]. This two-step approach partially overcomes the cific extraction methods to obtain adequate coverage of problem of the interphase between the two liquid phases the full diversity of cellular metabolism [14, 15]. but it is more time consuming, since the phase separation Because of the above-mentioned extraction specific - has to be achieved in an independent step [22]. Addition- ity, multiple aliquots of the same sample are required to ally, unwanted phase separation could occur if the water obtain sufficient material for the different extraction pro - content of the extracted samples are too high. cedures. Next to the increased effort due to multi-parallel To overcome these problems, we used a cleaner and sample handling, the required sample amounts for mul- safer alternative to chloroform, namely methyl tert-butyl tiple extractions are often not available for all tissues or ether (MTBE) for liquid–liquid extraction [23]. MTBE organisms. Consequently, a comprehensive extraction was initially used for the recovery of bacterial organic method providing the robust and reliable recovery of the acids [24] and lipids from different eukaryotic samples major molecular components from a single aliquot of a [25, 26]. The main advantage of using MTBE is the fact −3 single sample would be desirable. Such a method would that it has a severely decreased density (0.74  g  cm ) −3 decrease the sample handling time and therefore increase compared to chloroform (1.48  g  cm ), which not only the sample throughput. Since the compounds are derived leads to an inversion of the methanol and the MTBE from the same aliquot, it would also improve the data phases, but also to a stable and solid pellet at the bottom precision and its comparability. of the centrifugation tube. Based on these improved sep- To minimize the problem of multiple extractions from aration features, we were able to set up a MTBE-based several sample aliquots, multi-phase extraction proto- extraction method for the complete recovery of multiple cols, often relying on a two-phase separation system, compounds [23]. consisting of different mixtures of chloroform and meth - In this article, we now summarize and describe the anol, have been developed. These methods were initially complete single-step extraction protocol for rapid com- designed for the extraction and analysis of either pure prehensive and simultaneous analysis of lipids, metabo- lipids [16, 17] or polar metabolites [18]. Accordingly, the lites and proteins from a single aliquot of plant tissues. motivation to use the two-phase separation methods of This protocol also includes a reproducible recovery these initial studies was to reduce the compound com- of starch and cell wall (CW) polymers from the solid plexity in the extracted sample and clean them up from phase. Using Arabidopsis thaliana leaves as a model, Salem et al. Plant Methods (2016) 12:45 Page 3 of 15 we generated lipidomics, metabolomics and proteomics 15 min sonication step. For phase separation, a volume of datasets from 25  mg sample. We have successfully used 650 µl of solvent M2, was added to each vial/tube and the this method to annotate more than 200 lipid compounds, samples were again thoroughly vortexed for 1 min. After covering most of the classes involved in lipid metabolism. that, the samples are centrifuged at a speed of 20,000g for Additionally, we annotated more than 50 compounds 5 min at 4 °C. using LC–MS method covering most of phenylpropa- noids and glucosinolates and more than 90 covering the Analysis of lipids from the MTBE‑phase by UPLC‑MS classes involved in central metabolism from GC–MS A fixed volume (500  µl) of the solvent from the upper, method. Additionally, we obtained about 2000 protein lipid-containing phase, was transferred to a pre-labelled identifications but also the polysaccharide composition 1.5  ml microcentrifuge tube or glass vial and the sol- of the cell wall and the crystalline cellulose content. We vent was evaporated using either a SpeedVac concentra- therefore believe that this method could be used, with tor at RT or, preferably, a nitrogen flow evaporator. For minor adaptations, to analyze metabolites, lipids and the lipidomic analysis, we used our previously published proteins from most biological samples. Ultra Performance Liquid Chromatography Mass Spec- trometry (UPLC-MS) method [27]. Briefly, the dried pel - Methods lets from the 500  µl lipid fractions were re-suspended Plant material in 250  µl acetonitrile: 2-propanol (7:3, vol/vol) solution. Arabidopsis thaliana seeds (wild-type of ecotype Col- Once the samples are re-suspended in appropriate vol- 0) were stratified at 4  °C in dark for 3  days before sow - umes, 2  µl per sample was injected and the lipids were ing them on soil. The plants were grown in long day separated on a Reversed Phase (RP) Bridged Ethyl Hybrid (LD) phytotrons that were maintained at 16/8 light/ (BEH) C column (100 mm × 2.1 mm containing 1.7 μm dark cycle. The average light intensity was maintained at diameter particles, Waters), using a Waters Acquity −2 2 150  µmol  m /s . The day/night temperature and rela - UPLC system (Waters, Machester, UK). The mass spec - tive humidity were 20/16  °C and 60/75%, respectively. tra were acquired in positive and negative ionization Rosette leaves of 21-day-old plants were harvested and mode using a heated electrospray ionization (HESI) snap frozen in liquid nitrogen. The plant material was source in combination with an Exactive, Orbitrap-type, grounded into a homogeneous and fine powder using tis - MS (Exactive, Thermo-Fisher, Bremen, Germany). The sue homogenizer and then aliquoted (25  mg) into 2  ml mobile phases used for the chromatographic separation safe-lock microcentrifuge tubes. were water containing 1% 1  M ammonium acetate, 0.1% acetic acid (Buffer A) and acetonitrile: isopropanol (7:3, Reagent set‑up vol/vol) containing 1% 1 M ammonium acetate, 0.1% ace- For the preparation of 100 ml of extraction solvent mix- tic acid (Buffer B). The gradient separation was: 1  min ture 1 (M1), 75 ml of methyl tert-butyl ether were added 45% A, 3 min linear gradient from 45% A to 35% A, 8 min to 25 ml of methanol (3:1, vol/vol). Corticosterone (50 µl linear gradient from 25% A to 11% A, and 3  min linear of a 1  mg/ml stock solution in methanol) and ampicil- gradient from 11% A to 1% A. After washing the col- lin (25 µl of a 1 mg/ml stock solution in methanol) were umn for 3  min with 1% A, the buffer is set back to 45% used as internal standards for UPLC-MS analysis of A and the column is re-equilibrated for 4  min. The flow semi-polar metabolites. 1,2-diheptadecanoyl-sn-glycero- rate was set to 400  µl/min. Data analysis was performed 3-phosphocholine (50  µl of a 1  mg/ml stock solution in using the Progenesis QI software package (Progenesis QI chloroform) and C sorbitol (50  µl of a 1  mg/ml stock Version 2.2, Nonlinear Dynamics, Newcastle, UK) and as solution in water) were added as internal standards for described in Hummel et al. [27]. the UPLC-MS analysis of lipid and GC–MS analysis of polar metabolites, respectively. For extraction solvent Analysis of pigments from the MTBE‑phase mixture 2 (M2), phase separation-inducing solvent, 75 ml To measure chlorophylls, a volume of 100 µl of the upper of water were added to 25 ml of methanol (3:1, vol/vol). MTBE phase was mixed with 900  µl of methanol (1:9, vol/vol). The absorption UV–VIS spectra were measured Extraction and phase separation and the concentration of chlorophyll a (Chl ), chlorophyll A fixed volume (1 ml) of pre-cooled (−20 °C) extraction b (Chl ), total chlorophylls (Chl ), and total carotenoid b a+b solvent M1 was added to homogenized tissues. After contents was calculated as described previously [28–30]. adding the extraction solvent, the vials/tubes were thor- Additionally, a volume of 200  µl of the upper MTBE oughly vortexed for 1  min and then incubated on an phase was evaporated and used for HPLC-based analysis orbital shaker (100 rpm) for 45 min at 4 °C followed by a of carotenoids [31]. Salem et al. Plant Methods (2016) 12:45 Page 4 of 15 Analysis of primary metabolites from the methanol/water The sequential extraction of protein and starch from the phase by GC–MS insoluble pellet After having removed the remaining lipid phase from For the sequential protein and starch extraction, the the vials/tubes, 200  µl of the polar phase was trans- remainder of the aqueous phase was removed by pipet- ferred into pre-labelled 1.5  ml microcentrifuge tube and ting off the excess volume. The obtained pellet after the the samples were dried down in a SpeedVac concentra- metabolite and lipid extraction was washed by thor- tor without heating. For the analysis of the samples, the oughly adding 500  µl methanol and vortexing the sam- dried pellets were derivatized and analyzed using a pre- ples for 30 s. The samples were centrifuged at a speed of viously published GC-TOF–MS method [21, 32]. Briefly, 20,000g for 5 min at 4 °C. This washing step was repeated the dried 200 µl aliquots of the polar phase were re-sus- two more times. pended in methoxyamine-hydrochloride/pyridine solu- tion for methoxymization of carbonyl groups followed Extraction and analysis of proteins by LC–MS/MS by heating at 37 °C for 90 min. The samples were further For protein extraction, the washed pellet of a 25 mg leaf derivatized with N-methyl-N-trimethylsilyltrifloracet - material was re-suspended in 150  µl of protein extrac- amide (MSTFA) for 30  min at 37  °C. The MSTFA solu - tion buffer (6  M urea, 2  M thiourea, 15  mM DTT, 2% tion contained a mixture of 13 fatty acid methyl esters CHAPS and protease and phosphatase inhibitors). Once (FAMEs) with different chain length, which were used in the proteins were dissolved, the samples were sonicated the post-measurement as retention time standards. 1  µl for 10 min in a sonication bath, followed by an additional of the derivatized sample mixture was injected onto the 30  min incubation on an orbital shaker (100 r.p.m.) at GC-column and measured. Data analysis was performed room temperature. In the next step, the solubilized pro- using the TargetSearch package according to Cuadros- teins were centrifuged at 10,000g for 5 min and the pro- Inostroza et al. [33]. tein concentration was determined from the collected supernatant [34]. 50 µg of proteins extract were digested Analysis of secondary metabolites from the methanol/ in-solution using a Trypsin/Lys-C mixture (Mass Spec water phase by UPLC–MS Grade, Promega) according to the instruction manual. A fixed volume of 400  µl of the polar phase was trans - After the digestion, the samples were desalted using C ferred into a pre-labelled 1.5 ml microcentrifuge tube and stage tips as described in Rappsilber et al. [35]. After the the samples were dried down in a SpeedVac concentrator elution of the digested and desalted peptides from C - without heating. For the direct analysis, the samples were stage tips, the samples were concentrated to near dryness handled as described previously in Giavalisco et  al. [23]. in a SpeedVac and the peptide mixtures were analyzed by Briefly, the dried 400 µl aliquots of the polar phase were LC-MS/MS using a Q ExactivePlus high resolution mass re-suspended in 200  µl UPLC-grade methanol: water spectrometer connected to an EASY-nLC 1000 system (1:1, vol/vol) and transferred to the autosampler, 2 µl was (Thermo-Fisher, Bremen, Germany). Peptides were sep - injected and separated on RP High Strength Silica (HSS) arated using a binary buffer system of 0.1% formic acid T3 C column (100  mm  ×  2.1  mm containing 1.7  μm in water (Buffer A) and 60% acetonitrile containing 0.1% diameter particles, Waters), using a Waters Acquity formic (Buffer B). The flow rate was adjusted to 300  nl/ UPLC system. The mass spectra were acquired by full min. Peptides were eluted with using a linear gradient of scan MS in positive and negative ionization mode on an 0–40% buffer B for 50  min followed by a linear gradient Exactive high resolution Orbitrap-type MS (Thermo- between 40–80% buffer B for additional 30  min. Pep - Fisher, Bremen, Germany). The mobile phases used for tides were analyzed with one full scan (200–2000  m/z, chromatographic separation were water containing 0.1% R  =  70,000 at 200  m/z), followed by up to fifteen data- formic acid (Buffer A) and acetonitrile containing 0.1% dependent MS/MS scans (Top 15 approach) with higher- formic acid (Buffer B). The compounds were separated by energy collisional dissociation (HCD) at a resolution of a gradient: 1 min 99% A, 13 min linear gradient from 99% 17,500 at 200  m/z. Dynamic exclusion was set to 30  s. A to 65% A, 14.5 min linear gradient from 65% A to 30% Raw data were processed using the Progenesis QI for A, 15.5 min linear gradient from 30% A to 1% A, hold 1% proteomics (Progenesis QI for Proteomics Version 3.0, A until 17, 17.5 min linear gradient from1% A to 99% A, Nonlinear Dynamics, Newcastle, UK) software in combi- and re-equilibrate the column for 2.5  min. The flow rate nation with the Mascot (Version 2.5, MatrixScience, Bos- was adjusted to 400 µl/min. Data analysis was performed ton MS, USA) database search tool using the Arabidopsis by using the Progenesis QI software package (Progenesis TAIR database (Version 10, The Arabidopsis Information QI Version 2.2, Nonlinear Dynamics, Newcastle, UK). Resource, www.arabidopsis.org). Salem et al. Plant Methods (2016) 12:45 Page 5 of 15 Extraction and enzymatic determination of the starch nitric acid/water (8: 1: 2, vol/vol/vol). The samples were content quickly vortexed, heated at 100  °C for 30  min, cooled to For starch extraction, the remaining pellet after pro- room temperature and finally centrifuged at 10,000g for tein extraction was washed using 1  ml of 80% ethanol. 10 min at room temperature. After discarding the super- After that step, the samples were incubated for 3  min at natant, the pellet was washed tree times with 100  µl of 80 °C and finally centrifuged at 3000g for 10 min at room water and finally re-dissolved in 100  µl of 72% sulfu - temperature. The washed pellets were re-dissolved in ric acid. Crystalline cellulose content was determined 0.5  ml of water and the starch was gelatinized by heat- based on glucose standard curve using the colorimetric ing at 100  °C for 1.5  h. After allowing the samples to anthrone assay [39, 40]. cool, 0.5  ml of 200  mM sodium acetate was added and The lignin content and composition was determined the dissolved starch was digested into its glucose mono- using the thioglycolic acid (TGA) and the thioacidoly- mers with an enzyme mix of α-amyloglucosidase and sis quantification methods, respectively [41–44]. For α-amylase, according to manufacturer instructions [36, TGA quantification of lignin, 1  mg of the prepared cell 37]. The tubes were incubated overnight at 37  °C and wall material was re-suspended in 250 µl of 2 N HCl and finally centrifuged at 10,000g for 5  min at room tem - 25  µl of TGA and the samples were incubated at 100  °C perature. Glucose concentration was determined based for 3  h with regular shaking. The samples were allowed on an enzymatic assay through hexokinase and glucose to cool before centrifuging them at 10,000g for 5  min at 6-phosphate dehydrogenase and the assay was performed room temperature. The pellet was washed three times in a 96-well plate using a microtiter plate reader. Briefly, with 0.5  ml of water before re-dissolving in 0.5  ml of an appropriate volume (40  µl) of the digested samples 1  M NaOH followed by overnight incubation at room was mixed with 160  µl of glucose assay mix consists of temperature with gentle shaking. The sample were cen - 100  mM HEPES, pH 7.5, 4  mM MgCl , 0.5  mM adeno- trifuged at 12,000g for 10  min at room temperature and sine triphosphate (ATP) and 1 mM nicotinamide adenine the supernatant was acidified with 100 µl of concentrated dinucleotide (NAD ), hexokinase (6 U/ml). After moni- HCl before incubating them at 4  °C for 4  h with regular toring the initial absorption at 340 nm (OD ), 0.25 units shaking. The pellet remained after centrifugation was re- glucose 6-phosphate dehydrogenase were added to each dissolved in 1 ml of 1 M NaOH and then the absorbance well and the OD was recorded again. Starch concen- was measured spectrophotometrically at 280 nm [41, 42]. tration was determined based on a calibration curve of a For lignin composition, 1  mg of the prepared cell wall standard glucose [36, 37]. material was re-suspended in 100  µl of 2.5% boron trif- luoride etherate and 10% ethanethiol/dioxane solution. Analysis of cell wall composition The samples were heated at 100 °C for 4 h with shaking. For the analysis of the cell wall polymers, the remaining The samples were allowed to cool before adding 100  µl pellet, after protein and starch extraction, was washed of 0.4  M sodium bicarbonate followed by liquid–liquid three times by thoroughly vortexing the samples for 30 s separation using 0.5 ml of ethyl acetate and 1 ml of water. in 500 µl of water. After washing the pellets, the samples An appropriate aliquot (200 µl) of the ethyl acetate layer were air-dried in a container with silica beads and were was allowed to evaporate followed by derivatization and analyzed immediately or they can be stored in a desicca- GC–MS analysis [43, 44]. tor until further extraction. The detailed polysaccharide composition of cell walls Troubleshooting was determined after acid hydrolysis and GC derivati- During the development and validation of this protocol, zation [38, 39]. Briefly, 2  mg of the cell wall pellet was a number of issues arose, for which we developed a trou- hydrolyzed by dissolving in 200 µl of 2.5 M trifluoroacetic bleshooting guide, which is summarized in Additional acid (TFA) and heating at 121  °C for 1.5  h. The samples file 1: Table S1. were allowed to cool before centrifuging them at 10,000g for 5  min at room temperature. An appropriate volume Results (100 µl) of the acidic supernatant was transferred to new Development of a comprehensive extraction method glass screw-capped tubes and 10 µl of the internal stand- Based on the requirement to extract all relevant molecu- ard (10 mg/ml of myo-inositol) was added. Samples were lar features from a biological sample, ideally from a single evaporated to dryness, reduced, acetylated and finally sample aliquot, we decided to develop a comprehensive measured on GC–MS [38, 39]. The content of crystal - one-step extraction protocol for the analysis of plant line cellulose was determined by a spectrophotometric tissue. The developed liquid–liquid two-phase separa - method [39, 40]. Briefly, the pellet remained after hydrol - tion system, which is conceptual similar to the classical ysis with TFA was re-dissolved in 100  µl of acetic acid/ chloroform: methanol extraction methods [18–21], relies Salem et al. Plant Methods (2016) 12:45 Page 6 of 15 on a MTBE: methanol: water system. Based on the ini- and 0.65 ml of extraction buffer M2 (see “Methods ” sec- tially published version of the method, where we ana- tion). If larger amounts of tissue have to be extracted, the lyzed lipids, proteins and polar metabolites [23], we were extraction volume can be linearly scaled. Unfortunately, able to extend and improved our previously published larger extraction volumes cannot be handled any longer extraction protocol. The updated protocol allows for in microcentrifuge tubes, which decreases the through- the fast and reproducible extraction of lipids, pigments, put of the method. Thus far, we have not encountered polar to semi-polar primary and secondary metabolites biological material where the usage of larger amounts of but also proteins, starch and cell wall (CW) polymers. material for the comprehensive analysis of lipids, polar Figure  1 illustrates graphically the simple and straight- metabolites or secondary metabolites was required, actu- forward workflow of the described extraction proto - ally contrary we were able to extract a full lipid profile col, which is easily adjustable to the required amount from as little as 20 Arabidopsis thaliana seeds (data not of sample. Usually between 10 and 50  mg of tissue are shown). used. The employed sample amounts are depending on As indicated in Fig.  1, the whole procedure requires tissue availability but also the intended analysis. Tissue only few pipetting steps once the required sample are amounts within this scale are routinely extracted in 2 ml aliquoted in the microcentrifuge tubes. Due to this sim- microcentrifuge tubes, using 1 ml of extraction buffer M1 plified workflow, a single person can handle 100 or more samples within half working day (4  h), enabling high throughput sample preparation as a pre-requirement for large-scale experiments. In the following sections we pro- vide an exemplary multi-omics analysis of a 25  mg leaf sample of Arabidopsis thaliana (Col-0), extracted with 1 ml of the MTBE: Methanol extraction solution. Figure 2 provides an overview of the analytical workflow applied to the different fractions of the tissue sample. Analysis of the lipid phase As indicated in the Fig.  2, the upper-organic (MTBE) phase obtained from the extraction contains most of the hydrophobic compounds. On the one hand, as indicated by the green color of the extract, this fraction contains the full inventory of pigments, including the major chlo- rophylls, but also several carotenoids. On the other hand, most lipids, namely the polar phospholipids and sphin- golipids, which are the constituents of the cellular mem- brane system, next to the neutral storage lipids and the free fatty acids were extracted in this phase. To validate this hydrophobic phase of the MTBE- extraction protocol, we initially tested the efficiency but also the reproducibility of this fraction compared to other commonly used protocols used for specific analy - sis of hydrophobic metabolites. For this purpose, we have performed parallel extractions of chlorophylls using the organic MTBE-fraction and compared the obtained results to chlorophyll extraction methods using acetone Fig. 1 Overview of the experimental workflow for the MTBE-based [28–30]. As indicated in Additional file  1: Figure S1 the extraction procedure. Plant material is harvested and snap-frozen analysis of chlorophyll a and b led to almost identical in liquid nitrogen. The harvested tissue is homogenized using a results between the commonly used 80% acetone method pre-cooled mortar and pestle or cooled tubes in a mixer mill. About 10–50 mg ±10% of the frozen powder is weighed in pre-labelled and an aliquot of 0.1  ml of the upper MTBE-fraction, 2 ml microcentrifuge tube. The weighed powder is extracted using indicating the suitability of this fraction for the analysis 1 ml of the first extraction solvent (M1, MTBE:MeOH 3:1, vol/vol) fol- of chlorophylls. Next to the analysis of chlorophylls using lowed by rigorous vortexing, agitated incubation and sonication of the spectroscopic method, we have also validated the the samples. A liquid/liquid phase separation is achieved by adding frequently used method of Fraser et  al., for the HPLC- 0.65 ml of the second extraction solvent (M2, H2O:MeOH 3:1, vol/vol) followed by vortexing and centrifugation based analysis of carotenoids. Here we observed that the Salem et al. Plant Methods (2016) 12:45 Page 7 of 15 Fig. 2 Schematic overview of the applied analytical methods. Following the two plus one phase extraction procedure, a phase separation of upper non-polar metabolites and a lower layer of polar to semi-polar metabolites next to a solid pellet (proteins, starch and cell wall) is obtained. A predefined volume (0.5 ml) of the upper lipid phase is aliquoted into three fractions (0.2, 0.2 and 0.1 ml), which are concentrated and analyzed by UPLC-MS, LC- photodiode array (PDA) or spectrometry for the lipid, pigment or chlorophyll composition, respectively. Two aliquots with predefined volume (0.2 and 0.4 ml) of the lower methanol: water phase are dried and the re-suspended compounds are analysed by GC- and UPLC-MS for analysis of primary and secondary metabolite composition, respectively. The starch/protein/cell wall pellet is washed followed by sequential protein and starch extraction. The de-proteinated and de-starched pellet, which contains the remaining cell wall material, can be used for determination of polysaccharide composition, cellulose and lignin Salem et al. Plant Methods (2016) 12:45 Page 8 of 15 hydrophobic MTBE fraction provided comparable results rosette leaf tissue using a high-throughput UPLC-MS for carotenoids to the results obtained using the extrac- analysis (Additional file  1: Table S4). Similar to the lipid- tion protocols described in the original paper [31] (Addi- omic analysis, the compounds were chromatographically tional file 1: Figure S2). separated and the molecular ions were detected in the There are several simple (e.g. thin layer chromatogra - mass spectrometer using the positive and negative ioni- phy or LC-Evaporative Light Scattering detector) and zation mode (Fig.  5). In sum, these two measurements advanced (UPLC-MS or Shotgun MS) methods available allowed us to detect, similarly to the UPLC-MS spectra to analyze or profile lipids in a targeted or untargeted from the lipidomic analysis, several thousand reproduc- way [5]. One of the well-established approaches relies ible peaks in positive and negative ionization mode. Still, on the mass spectrometric analysis in combination with even though several thousand chromatographic peaks reversed-phase chromatographic separation [27]. This can be detected from this fraction, thus far only few approach, especially, if fast UPLC is used, allows for the compounds could be reliably annotated. Nevertheless, detailed profiling of the main lipid classes. The obtained these annotated metabolites cover a wide range of the data (Additional file  1: Table S2) can provide an overview Arabidopsis thaliana secondary metabolism, providing a of changes in the composition of the plasma-, the endog- detailed insight into the regulation of the main classes of enous-, organelle- and the chloroplast membrane system, sinapates [45], glucosinolates [46], flavonoids and antho - next to the availability and composition of free fatty acids cyanins [47] (Fig.  5), which are known to be involved in and storage lipids. As described in detail in the method many biotic and abiotic stress responses. section, our UPLC-MS-based profiling approach enables the reliable and robust detection of more several thou- Analysis of the solid pellet sand chromatographic peaks, of which at least 200 lipid After removing the liquid-extracted metabolites (polar species (Additional file  1: Table S2) from an Arabidop- and hydrophobic), the remaining solid pellet can be used sis rosette leaf sample could be reliably annotated using for the extraction of proteins, starch and cell wall mate- the accurate mass and the obtained retention time [27]. rial (Fig.  2). The order of the extraction of the different These annotated lipid classes, obtained from the positive classes of compounds cannot be interchanged, since and negative ionization mode measurements of the same severe losses of proteins are observed if the extraction sample are displayed on a representative set of chroma- steps required for solubilization and hydrolysis of the tograms in Fig.  3. Because each optimized chromato- starch are applied before protein extraction (Additional graphic run takes only 24  min, the employed method is file  1: Figure S3). Accordingly, the first step of the three- highly compatible to high throughput analysis of large step extraction procedure of the solid pellet relies on the lipidomic data sets [27, 32]. efficient extraction of proteins from the obtained pellet. In addition to the reproducible results of protein concen- Analysis of the polar phase: primary and secondary trations obtained by our extraction method (Additional metabolites file  1: Figure S3), we were able to obtain high-quality As described in Fig.  2, two aliquots derived from the shotgun proteomics data from the generated protein polar (lower) fraction, were analyzed using two comple- extracts (Fig.  6). The results and the spectra from the mentary analytical methods. Polar primary metabolites proof of concept in-solution digestion and nanoLC-MS were measured routinely, after a trimethylsilyl (TMS) analysis of the extracted proteins allowed for the rou- derivatization, by a very well established GC–MS analysis tine identification of more than 2000 proteins from a method [21, 32], while the semi-polar secondary metabo- 25 mg sample of Arabidopsis thaliana rosette leaves. The lites could be directly analyzed using a robust reversed obtained identifications, using a single measurement, had phase UPLC-MS method [23]. at least two independent peptides and a false discovery As can be seen from Additional file  1: Table S3, the rate (FDR) below 1% (Additional file  1: Table S5). Inter- GC–MS analysis enables the reliable detection of several estingly, next to the large amount of soluble proteins, hundred peaks, of which more than 90 polar metabo- we also detected significant amounts of transmembrane lites, covering a wide range of metabolic classes from proteins, especially from the thylakoids, the nucleus, the the central primary metabolism, including the main sug- ER, and the plasma membrane. This increased quantity ars, amino acids and organic acids, could be annotated. of hydrophobic proteins is explained by the fact that the Figure  4 shows a representative GC–MS chromato- MTBE extraction method provides a clean and com- gram, where the identities of the major metabolites are pletely de-lipidation of membranes, namely membrane indicated. lipid are extracted in the upper MTBE phase, providing As mentioned above, next to the polar metabolites, we a high quantity of precipitated membrane proteins in the also annotated more than 50 secondary metabolites from solid pellet. Salem et al. Plant Methods (2016) 12:45 Page 9 of 15 Fig. 3 Base peak chromatograms of total lipids extracted from Arabidopsis rosette leaves. Relative abundances of eluted peaks versus retention time (min) are shown. The region of the different detected and annotated lipid classes is indicated according to its abundance either in positive or negative ion modes (for details see Additional file 1: Table S2). The number of detected lipid compounds for every class is indicated in brackets. Chl a chlorophyll a, Chl b chlorophyll b, DAG diacylglyceride, DGDG digalactosyldiacylglycerol, FA fatty acid, LysoPC lysophosphatidylcholine, MGDG monogalactosyldiacylglycerol, PC phosphatidylcholine, PE phosphatidylethanolamine, PG phosphatidylglycerol, PI phosphatidylinositol, PS phos- phatidylserine, SP sphingolipid, SQDG sulfoquinovosyldiacylglycerol, TAG triacylglyceride Fig. 4 GC–MS-based total ion chromatogram of derivatized primary metabolites from Arabidopsis rosette leaves. Intensity of eluted peaks versus retention time (seconds) are shown. Identities of the most abundant metabolites are indicated. More than 90 compounds from this GC-MS data were annotated (Additional file 1: Table S3). These compounds include amino acids and their derivatives, sugars, sugar acids, sugar alcohols, sugar derivatives, organic acids and their derivatives, fatty acids, sinapates, amines and others Salem et al. Plant Methods (2016) 12:45 Page 10 of 15 Fig. 5 UPLC-MS base peak chromatograms of polar to semi-polar metabolites extracted from Arabidopsis rosette leaves. Relative abundances of eluted peaks versus retention time (min) are shown. The region of each eluted compound class is indicated according to its elution window either in positive or negative ionization modes. The number of detected compounds for every class is indicated in brackets (for details see Additional file 1: Table S4) Once the proteins are extracted from the solid pellet, namely the insoluble cell wall material. This material can a quantitative extraction and analysis of cellular starch be used to determine the polysaccharide composition of content can be performed on the remaining pellet. Since cell walls, the crystalline cellulose content and lignin by starch analysis is a highly established and standardized GC–MS and spectroscopic methods (see “Methods” sec- method for photoautotrophic organisms, we aimed to tion). Additional file  1: Figure S5 summarizes the analysis compare the extracted amounts of starch derived from of this last fraction of the solid pellet and illustrated that the insoluble protein, starch, cell wall pellet obtained these compounds can be analyzed reproducibly from the from the MTBE extraction, to the values obtained from remaining pellet, providing an additional insight in an the commonly used standard extraction methods [32, often-neglected cellular compartment. 36]. Much as we hoped for, we found that the starch con- centrations obtained from the de-proteinated pellet were Discussion highly similar to the concentrations measured by the The application of the here described protocol, allows for Smith and Zeeman protocol [36]. Next to the loss-free the independent and qualitative extraction and separa- fractionated extraction of protein and starch, our method tion of the major compound classes, from a single sam- also proved to be highly reproducible over a large range ple. In addition to the detailed extraction protocol (see of concentrations as indicated by the small error bars “Methods” section), we additionally provide exemplary (Additional file 1: Figure S4). analytical data, mainly using gas- (GC) and liquid-chro- Once we reached the de-proteinated and de-starched matography (LC) coupled to diverse mass spectrometers pellet at the end of the sequential extraction of the solid for the analysis of the three different phases (organic, pellet, there is still material for an additional analysis left, polar and solid). The precise conditions for analysis of Salem et al. Plant Methods (2016) 12:45 Page 11 of 15 11.1 22.9 16.2 20.1 29.2 40.6 24.6 31.0 43.4 33.2 83.0 46.9 52.3 60.1 66.5 55.8 70.4 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 Time (min) Storage proteins, 5 Kinases, 64 Isomerases, 96 Receptor proteins, 20 Proteases, 78 Cell junc‰on proteins, 1 Cytoskeletal proteins, 76 Chaperones, 68 Transporter proteins, 88 Transcrip‰on factors, 22 Phosphatases, 36 Transmembrane receptor regulatory/adaptor proteins, 2 Membrane traffic proteins , 25 Transfer/carrier proteins, 44 Transferases, 257 Hydrolases, 233 Defense/immunity proteins, 5 Calcium-binding proteins, 30 Oxidoreductases, 276 Enzyme modulators, 65 Lyases , 92 Signaling molecules, 26 Cell adhesion molecules , 2 Nucleic acid binding proteins, Ligases, 84 Fig. 6 UPLC-MS chromatogram of proteins from Arabidopsis rosette leaves and their classification according to protein identifications. a Total ion chromatogram of proteins extracted from Arabidopsis rosette leaves. Relative abundances of eluted peaks versus retention time (min) are shown. b Different protein classes and the number of proteins that contribute to each class from Arabidopsis rosette leaves (for details see Additional file 1: Table S5) different metabolites are based on the availability of spe - combination of these divers molecular entities, espe- cific instruments and can be easily extended beyond the cially the combination of metabolite data and the protein provided examples given in this article. data allows to draw causal conclusions of the functional As we have shown in this protocol, the analysis of a molecular machines (proteins) and their products single sample using the fractionated extraction method, (metabolites), from the exact same sample. The use of provides profound insight, not only into diverse molec- a single sample therefore allows minimizing the differ - ular compounds, but also provides a functional over- ence between the origin of measurement and therefore view of most cellular compartments and processes. The to maximize the accuracy of the analysis. Next to the Relative Abundance Salem et al. Plant Methods (2016) 12:45 Page 12 of 15 decrease in sample consumption, this strategy provides tissues. Amongst others, we studied Arabidopsis thaliana an ideal foundation for computational systems biological seedlings [32], roots and leaves [23], barley (Hordeum approaches. vulgare) [62], wild strawberry (Fragaria vesca) [63] straw- berry (Fragaria X ananassa) [64], the root tissue of maize Applications of the MTBE extraction protocol (Zea mays) [65], the green algae Chlamydomonas rein- for ‘omic’‑based analysis hardtii [66], the marine diatom Thalassiosira pseudonana As described in the result section the total amount of [61] and some low phosphate-tolerant proteaceae species 25  mg of leaf tissue allows for the complex analysis of [51]. several hundred molecular properties of a single sam- ple. Of course, the analysis and the annotation of further Future perspectives and challenges compounds are only limited by the biological question In this protocol, we  showed that our method could be and the analytical methods and the equipment employed used for a comprehensive “multi-omics” sample extrac- for the downstream analysis of the obtained extracts. tion, preparation and analysis. The analysis of multiple u Th s far we have not encountered analytical methods molecular entities, derived from several subcellular com- that were incompatible with the obtained fractions and partments and molecular processes provides a brought in most cases the obtained abundance and the quality overview of the status of the cell. Still compound anno- of the compounds from the MTBE-derived extracts was tation and/or identification are the major challenge in reaching sensitivities and quality to the more special- the metabolomics data analysis. Although we were able ized extraction methods. Beyond the optimal applicabil- to annotate many lipids, metabolites and proteins, more ity of our method for plant cells and tissues, it should be compounds are still to be uncovered and would, if possi- mentioned that we have not only applied this method ble allow to broaden our insight into the molecular inven- thus far for diverse plant samples [23, 27, 32, 48–54], but tory of the cell. For instance, even though we detected it was also successfully employed for metabolic and/or some sphingolipids or sterols in our lipid analysis, these proteomic studies of algae [55, 56], flies [57] and diverse lipid specific lipid classes are slightly underrepresented in mammalian cells and tissues [58–60]. our data set. This underrepresentation is not due to the In previous studies, we have analyzed the MTBE- extraction procedure, but it is explained by the complex- derived lipid phase for the identification and analysis ity of the sample, namely by ion suppression or matrix of lipid species from Arabidopsis thaliana dry seeds effects, and the measurement mode of our method. Still, [48, 53], seedlings [32, 49], leaves [23, 27, 50–54], roots it should be easily possible to modify our analytical work- [23] and flowers [54]. Additionally, we applied the same flow enabling the inclusion of the missed compounds. For method, with minor adaptations in the extraction pro- instance, it is possible to expand the number of detect- cess, to compare the lipid composition of mammalian tis- able sphingolipids by analyzing the MTBE but also the sues including brain, kidney and skeletal muscle of mice, methanol phase after mild base hydrolysis, which allows rhesus macaques, chimpanzees and humans [58–60]. depleting the highly abundant glycerolipids and therefore Moreover, the method allowed the detection and annota- improve the analysis of the slightly less abundant 100– tion of more than 180 lipid species from Chlamydomonas 150 species of the non-hydrolysable sphingolipids [67, reinhardtii [55]. Furthermore, we applied the described 68]. Next to the dedicated analysis of sphingolipids, the method to determine the lipid composition of the green uses of either atmospheric pressure chemical ionization algal species Scenedesmus (Acutodesmus) obliquus [56] (APCI) or improved direct infusion MS-based analysis and the model fly Drosophila melanogaster [57]. More - strategies can be used for the analysis of more than 100 over, the method has been proven useful also for lipid sterols and their derivatives [69, 70]. profiling of 124 lipid species from the marine diatom As already mentioned in the result section, we do rou- (Thalassiosira pseudonana) [53, 61] and the biddulphioid tinely annotate 50–60 secondary metabolites from Arabi- diatom (Biddulphia biddulphiana) [61]. dopsis thaliana by our UPLC–MS analysis. Although Next to the major lipid profiling approaches described these secondary metabolite classes include the main above, we also applied the extraction method for the secondary metabolites like the sinapates, glucosinolates, analysis of polar and semi-polar compounds in several flavonoids and anthocyanins, still we have to admit that plant species. These analyses provided a basic insight into the obtained spectra from these UPLC-MS measure- central carbon and nitrogen metabolism at the systems ments contain plenty of reproducible but unidentified level. Accordingly, we were able to apply the protocol for chromatographic peaks. Many of these will be true sec- the extraction, detection and identification of primary ondary metabolites derived from the plant. In a previous and/or secondary metabolites of several species and paper using the polar phase from the MTBE extraction Salem et al. Plant Methods (2016) 12:45 Page 13 of 15 method, we demonstrated by multiple isotope labelling Conclusion experiments that more than 1400 chromatographic peaks In this protocol, we describe a universal extraction of these spectra, obtained from the UPLC-MS analysis method that allows for the preparation and isolation of of the polar fraction, were of biological origin, indicating lipids, metabolites, proteins and other macromolecules the large pool of biologically-relevant information con- for high-throughput multi-omics analysis using a sin- tained and unexploited in these samples [23]. Unfortu- gle biological plant sample. We optimized and used this nately, metabolite annotation is still far from routine and approach to generate several analytical datasets from the high-throughput [71]. The main complication by using same sample. This allows for the brought insight into the this fraction for the analysis of secondary metabolites analyzed system and decreases the bias in systems biol- comes more from the high structural complexity of the ogy application. Accordingly, the described method does analyzed compounds and the difficulty to annotate them not only lead to significantly reduced sample consump - without authentic reference compounds. In the above- tion but also minimizes the time and effort needed to mentioned study, we were using stable isotope labeling perform separate extractions when many molecules are for the unambiguous annotation of the compounds, but to be studied in the same experiment. On the long run, of course it would be desirable to additionally use authen- we are planning to further improve the method, espe- tic standards and higher order MS-based fragmentation cially by expanding the repertoire of applicable analytical analysis for the proper structural elucidation of the thus methods and therefore further broadening the number far unknown compounds. and quality of the detectable components. Regarding proteomic analysis, we routinely identify Additional file 2000–3000 proteins from Arabidopsis covering sev- eral enzymes, signaling- and transmembrane proteins. Additional file 1. Supplemental Figures and Tables. The number of specific proteins can still be increased by either increasing the amount of starting material but also by sub fractionation of the obtained pellet. In the Author contributions current protocol, we re-suspended the protein pellet for MAS and JJ optimized the extraction protocol. KB performed protein extrac- tion, digestion and protein data analysis. MAS contributed to the develop- example initially in urea/thiourea buffer, which might not ment and validation of the methods and wrote the protocol. PG supervised fully solubilize the most hydrophobic membrane pro- the project, optimized GC- and LC-MS analytical methods for analysis and teins. Accordingly the protein extraction buffer, could be contributed to writing and improving the protocol. The work was performed at the Max-Planck Institute of Molecular Plant Physiology, Golm, Germany. All changed to a detergent-containing buffer (e.g. a 0.5–1% authors read and approved the final manuscript. sodium dodecyl sulphate-containg buffer) in combina - tion with a Filter Aided Sample Preparation (FASP) in Author details Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, solution digestion protocol [72]. 14476 Potsdam-Golm, Germany. Department of Pharmacognosy, Faculty It is also possible to maximize the number of extracta- of Pharmacy, Cairo University, Kasr El-Aini Street, Cairo 11562, Egypt. ble and identifiable proteins by using a sequential protein Acknowledgements extraction strategy [73]. So one can start extracting the We would like to thank Prof. Dr. Lothar Willmitzer, Dr. Alisdair Fernie and Dr. soluble proteins with a mild Tris buffered saline (TBS) Andrew Wiszniewski for proof reading and commenting on the manuscript. buffer, followed by the extraction of structure associated Special thanks to Andrea Leisse, Änne Michaelis and Gudrun Wolter for their excellent technical assistance. M.A.S. is a holder of a German-Egyptian proteins using a stronger chaotropic buffer (e.g. urea/ Research Long-Term Scholarship (GERLS-DAAD). thio urea) and finally, as mentioned above, a detergent- containing buffer for the extraction of transmembrane Competing interests The authors declare no competing interests. proteins. 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Toward the storage metabolome: profiling the barley vacuole. Plant Physiol. 2011;157(3):1469–82. Submit your next manuscript to BioMed Central and we will help you at every step: • We accept pre-submission inquiries • Our selector tool helps you to find the most relevant journal • We provide round the clock customer support • Convenient online submission • Thorough peer review • Inclusion in PubMed and all major indexing services • Maximum visibility for your research Submit your manuscript at www.biomedcentral.com/submit

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Plant MethodsSpringer Journals

Published: Nov 10, 2016

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