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Molecular & Cellular Proteomics 5:2044-2059, 2006.
© 2006 by The American Society for Biochemistry and Molecular Biology, Inc.
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From the Biochemistry Department, University of Missouri-Columbia, Columbia, Missouri 65211 and Research Laboratory for Agricultural Biotechnology and Biochemistry, P O. Box 8207, Kathmandu, Nepal
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ABSTRACT |
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 TOP ABSTRACT EXPERIMENTAL PROCEDURESRESULTSDISCUSSIONREFERENCES |
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300 phosphoprotein spots. Of these, quantitative expression profiles for 234 high quality spots were established, and hierarchical cluster analyses revealed the occurrence of six principal expression trends during seed filling. The identity of 103 spots was determined using LC-MS/MS. The identified spots represented 70 non-redundant phosphoproteins belonging to 10 major functional categories including energy, metabolism, protein destination, and signal transduction. Furthermore phosphorylation within 16 non-redundant phosphoproteins was verified by mapping the phosphorylation sites by LC-MS/MS. Although one of these sites was postulated previously, the remaining sites have not yet been reported in plants. Phosphoprotein data were assembled into a web database. Together this study provides evidence for the presence of a large number of functionally diverse phosphoproteins, including global regulatory factors like 14-3-3 proteins, within developing B. napus seed.
360 known Arabidopsis ecotypes revealed a range from 34 to 46% of seed dry weight (8). Extensive studies on seed development have firmly established that the components of storage reserve begin to accumulate and their relative levels are determined in the mature seed during a particular phase of seed development (for reviews, see Refs. 5, 9, and 10), referred to as seed filling (1, 4, 11, 12). The seed filling phase involves cell division, cell expansion, and the early maturation stage (1, 2). Numerous studies including two global approaches, transcriptomics and proteomics, conducted to date on seed filling, in particular oilseed plants such as oilseed rape (Brassica napus L.), soybean, and Arabidopsis, continue to produce new paradigms and refine our understanding of the existing biosynthetic pathways responsible for accumulation of seed storage reserves (5, 9, 10, 12, 13–20). A microarray of developing Arabidopsis seed provided insight into primary transcriptional networks that coordinate the metabolic responses to seed developmental programs and lead to the distribution of carbon among carbohydrate, oil, and protein reserves (12). Proteomics studies have also been performed in Medicago truncatula (18), pea (19), and soybean (20) using high resolution two-dimensional gel electrophoresis (2-DGE)1 in combination with either MALDI-TOF-MS or LC-MS/MS. Of these studies, the soybean investigation was the most systematic with respect to quantitative expression profiling and protein identification. In that study, 679 and 422 protein spots were profiled and identified, respectively, representing 216 non-redundant proteins and 14 functional classes (20). Despite these investigations, including the large data sets of genes and proteins, the specific underlying regulatory mechanisms that control the levels of storage reserves in the seed remain largely unknown.
Understanding the underlying regulatory mechanism(s) of the networks by identifying and characterizing their regulatory components will undoubtedly broaden our knowledge on how the levels of stored components in the seed are fine tuned. Reversible phosphorylation is a major post-translational mechanism by which cells transduce cellular, developmental, and environmental signals and thereby control a myriad of biological processes in diverse organisms including plants (for reviews, see Refs. 21–23). Previous studies have shown that several intermediary and primary metabolic enzymes are regulated by reversible phosphorylation in plants, including sucrose synthase (24), sucrose-phosphate synthase (Ref. 25; for a review, see Ref. 26), trehalose-6-phosphate synthase (27, 28), pyruvate kinase (29), acetyl-CoA carboxylase (30), phosphoenolpyruvate carboxylase (31), nitrate reductase (32), and the mitochondrial pyruvate dehydrogenase complex (33).
Hence understanding the dynamics of this post-translation modification in response to cellular as well as environmental cues can lead to the identification of candidate regulatory proteins (protein kinases) and their substrates and thereby can help in dissecting the signaling and metabolic networks. This emerging new area of systems biology is termed phosphoproteomics (34–36). Many advances in phosphoproteomics technologies, including enrichment, detection, phosphorylation site mapping, and quantification of phosphoproteins, have made the large scale study of phosphoproteins a feasible task (23, 34–39). One of the major developments in this area is the detection of phosphoproteins using a unique fluorescence dye, Pro-Q Diamond phosphoprotein stain (Pro-Q DPS; Ref. 40). Two major advantages of this stain are: 1) it can be used for global quantitative analysis of phosphoproteins as it binds directly to the phosphate moiety of phosphoproteins with high sensitivity and linearity regardless of phosphoamino acid and 2) the stain is fully compatible with other staining methods and modern MS. Despite these recent advancements, phosphoproteins in plants have been rarely studied on a large scale basis (for a review, see Ref. 41). One example of a large scale phosphoproteomics study is the identification of more than 300 phosphorylation sites from Arabidopsis plasma membrane proteins (42). To our knowledge, no large scale study of phosphoproteins has been carried out on developing plant seeds.
We have embarked on large scale phosphoproteomics study during seed filling in B. napus with the following objectives: (i) to obtain quantitative expression profiles of phosphoproteins through seed development, (ii) to generate a 2-DGE phosphoprotein reference map, (iii) to determine the phosphorylation sites of phosphoproteins, and (iv) to begin building resources for dissecting biological processes that might be regulated by reversible phosphorylation, including metabolism. A high throughput 2-DGE approach in combination with Pro-Q DPS and LC-MS/MS were applied on five sequential stages 2, 3, 4, 5, and 6 weeks after flowering (WAF), covering the majority of seed filling. This study reports major achievements toward fulfilling these objectives by the establishment of a high resolution 2-DGE phosphoprotein reference map comprising 234 quantitative expression profiles, 103 identified phosphoproteins, and a map of phosphorylation site in 16 non-redundant phosphoproteins. This study also extends the oilseed proteomics web-based database with a "Brassica phosphoproteomics" resource for the plant community.
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EXPERIMENTAL PROCEDURES |
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TOPABSTRACTEXPERIMENTAL PROCEDURESRESULTSDISCUSSIONREFERENCES |
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Plant Materials and Growth Conditions—
B. napus (var. Reston) seeds were grown in soil (Promix, Quakertown, PA) in a growth chamber (light/dark cycles of 16 h (23 °C)/8 h (20 °C), 48% humidity, and light intensity of 8000 lux). Plants were fertilized at 2-week intervals (all purpose fertilizer, 15:30:15, nitrogen-phosphorus-potassium). Flowers were tagged immediately after opening of buds (between 1 and 3 p.m.). Harvesting of developing seeds was also performed between 1 and 3 p.m. during the daytime at precisely 2, 3, 4, 5, and 6 WAF. At each developmental stage, the dry weight and total protein content of whole seeds were also measured. Total protein was quantified in triplicate using dye-binding protein assay kit (Bio-Rad) and chicken 
-globulin as standard.
Two-dimensional Gel Electrophoresis—
Total seed protein was prepared from each developmental stage according to a modified phenol-based procedure as described previously (20). The protein pellet, obtained from the above extraction procedure, was suspended in IEF extraction buffer (8 M urea, 2 M thiourea, 2% (w/v) CHAPS, 2% (v/v) Triton X-100, 50 mM DTT) and vortexed at low speed for 30 min at room temperature followed by centrifugation at 14,000 rpm for 15 min to remove insoluble material. Supernatant was used for measuring protein concentration and 2-DGE analysis. 2-DGE was carried out using IPG strips (pH 3–10 or 4–7, 24 cm; GE Healthcare) as described previously (20). One milligram of total protein was mixed with 2.25 µl of IPG buffer (pH 3–10 or 4–7; GE Healthcare) and IEF extraction buffer to bring up to 450 µl, vortexed for 30 s, and subjected to IEF followed by SDS-PAGE. A total of six to eight high resolution 2-D gels were run for each developmental stage using protein isolated from four independent biological samples to finally select four gels for further analysis. Additionally "reference gels" were also run for the purpose of spot matching and their downstream analysis (20) and for the development of a reference map of phosphoproteins. A reference gel is defined as 0.2 mg of total protein from each of the five developmental stages pooled and resolved by 2-DGE.
SDS-PAGE for Phosphorylation Site Mapping—
SDS-PAGE was performed by standard methods utilizing 4% T, 2.6% C stacking gels, pH 6.8, and 12% T, 2.6% C separating gels, pH 8.8 (43). The % T is the total monomer concentration expressed in grams/100 ml, and % C is the percentage of cross-linker. The stacking and separating gel buffer concentrations were 0.125 M Tris-HCl, pH 6.8, and 0.375 M Tris-HCl, pH 8.8, respectively. The reservoir buffer concentration was 0.025 M Tris, 0.192 M glycine, pH 8.3. All gel and reservoir buffers contained SDS to a final concentration of 0.1% (w/v). SigmaMarker or protein samples were heated for 5 min at 75 °C in SDS loading buffer (5% (v/v) glycerol, 60 mm SDS, 100 mm DTT, 0.03 mm bromphenol blue, and 60 mm Tris-HCl, pH 6.8) and were cooled to room temperature before loading to 10 and 15% gels. A total of 500 µg was loaded per lane, and electrophoresis was conducted overnight in a Hoefer vertical SE600 electrophoresis unit (GE Healthcare catalog number 80-6171-96) at room temperature until the dye reached the bottom of the gel. Gels were stained with colloidal Coomassie Brilliant Blue (CBB) to detect protein.
Detection of Phosphoproteins and Proteins—
For phosphoprotein detection, 2-D gels were stained with a modified protocol using Pro-Q DPS (44). Briefly all gels were treated with fixation solution (2 x 30 min), washed with deionized water (2 x 15 min), stained with 3-fold diluted Pro-Q DPS in deionized water (120 min), destained with destaining solution (4 x 30 min) to remove gel-bound nonspecific Pro-Q DPS, and washed again with deionized water (2 x 5 min). Following scanning of Pro-Q DPS-stained gels, the same gels were then overstained with colloidal CBB G-250 to detect proteins (45). All gels in the incubation solution were constantly shaken on an orbital shaker (GeneMate, ISC Bioexpress) at room temperature at speeds of 35 rpm.
Image Analysis of 2-D Gels—
Following the Pro-Q DPS procedure, gels were imaged using an FLA 5000 laser scanner (Fuji Medical Systems, Stamford, CT) with 532 nm excitation and 550-nm bandpass emission filter. Data were collected as 100-µm resolution, 16-bit TIFF files using the Image Gauge Analysis software (Fuji Medical Systems). With this software, fluorescent protein signals in 2-D gels were displayed as dark spots. To quantify phosphoprotein spots in profile mode, 2-D gels were analyzed using ImageMaster 2D Platinum software version 5 (hereafter called ImageMaster software; GE Healthcare) as described by Hajduch et al. (20). Under applied stringent criteria to select phosphoprotein spots for quantification and expression profiling, only those spots were analyzed that were present in all four gels derived from independent biological samples of one developmental stage and expressed at least in two of five developmental stages. The relative volumes of high quality phosphoprotein spots were determined followed by establishment of their expression profiles. To obtain the statistical significance of the variation of each expressed phosphoprotein spot volumes across all four selected replicates of each developmental stage, the coefficient of variation (CV) was calculated using the following formula,
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where 
is the average of relative volumes (x) of spots in biological quadruplicate analysis and n is the sample size (four in case of biological quadruplicate).
It is important to mention that we used two types of protein markers, PeppermintStick standards and SigmaMarker, in SDS-PAGE. The PeppermintStick standards carry two phosphorylated (ovalbumin and bovine ß-casein of 45.0 and 23.6 kDa, respectively) and four non-phosphorylated (ß-galactosidase, bovine serum albumin, avidin, and lysozyme of 116.25, 66.2, 18.0, and 14.4 kDa, respectively) proteins. SigmaMarker contains one phosphorylated protein (ovalbumin, 45.0 kDa) of 13 protein markers. Detected phosphoprotein spots on 2-D gel were normalized against positive and negative phosphoprotein markers to eliminate false positive spots. Colloidal CBB-stained gels were imaged using a Scan Maker 9800XL densitometer (Microtek, Carson, CA). Digitized 2-D gel images (300 dpi, 16-bit grayscale pixel depth) were analyzed using ImageMaster software as described previously (20).
Hierarchical Cluster Analysis of Expression Profiles—
The expression profiles of phosphoproteins established by ImageMaster software were subjected to hierarchical cluster analysis using SAS statistical software (SAS Institute Inc., Cary, NC). The program accomplishes the cluster analysis of expression profiles in two steps. The first step is to establish a number of classes that is best suited for a present data set. The "CLUSTER" keyword is used with options "STANDARD METHOD = AVERAGE CCC PSEUDO" as the command for step 1 in which "STANDARD" means to normalize the variables, "AVERAGE" means a certain clustering method in contrast to the other 10 methods which are included in SAS IDE, and "CCC" and "PSEUDO" are both options for calculating some statistical variables that are used to determine the class number. The second step is to cluster expression profiles into each of the established classes. Expression profile data are also normalized as follows: any zero between two non-zero points is replaced with the average of the values of two neighbors, and a linear transformation is used to normalize expression profiles of different spots to uniform scale. The SAS program used procedure "FASTCLUS" for the real clustering and the maximum number of clusters established earlier. SAS also generates the variable distance parameter for each spot.
In-gel Trypsin Digestion—
Phosphoprotein spots were excised from a 2-D reference gel, transferred to polypropylene 96-well filter bottom plates, and digested with sequencing grade modified trypsin (Promega, Madison, WI) according to a previous procedure (20). In case of SDS-PAGE, the colloidal CBB-stained gel was cut into 54 bands per protein sample, diced into 1-mm cubes, and transferred into a sterile 1.5-ml microcentrifuge tubes. The gel pieces were washed with water, destained, and in-gel digested with sequencing grade modified trypsin as described previously (20).
Identification of Phosphoprotein 2-DGE Spots by LC-MS/MS—
Before MS analysis, 50 µl of 0.1% (v/v) FA in water (Milli-Q grade) was added to each sample well to reconstitute dried peptides. Ten microliters were used for mass spectral analysis using a configuration termed high throughput protein identification on an LTQ ProteomeX linear ion trap LC-MS/MS instrument. Briefly on-line capillary LC included two polymeric PSDVB-based peptide traps (2-µg capacity each; MicroBioresource) and a fast equilibrating C18 capillary column (Micro-Tech Scientific, Cousteau Ct. Vista, CA; packed with C18, 5 µm, 300 Å, 150-µm inner diameter x 10 cm). The method alternated between loading/equilibration and elution using the two peptide traps to reduce the time required for sample analysis on the LC-MS/MS instrument. Sample was loaded onto peptide traps for concentration and desalting prior to final separation by C18 column using an acetonitrile gradient (0–80% solvent B in solvent A for a duration of 20 min; solvent A = 0.1% (v/v) FA in water; solvent B = 100% acetonitrile containing 0.1% FA). The peptide trap and C18 column were then reset for 2 min and re-equilibrated for 10 min with 100% of solvent A before the sample already loaded onto the second trap was eluted. The m/z ratios of eluted peptides and fragmented ions from fused silica PicoTip emitter (12 cm, 360-µm outer diameter, 75-µm inner diameter, 30-µm tip; New Objective, Ringoes, NJ) were analyzed in the data-dependent positive acquisition mode on the LC-MS/MS instrument. Following each full scan (400–1600 m/z), a data-dependent triggered MS/MS scan for the most intense parent ion was acquired. The heated fused silica PicoTip emitter was held at ion sprays of 1.7 kV and a flow rate of 250 nl/min.
Phosphorylation Site Mapping—
To map phosphorylation site(s), 10 µl of the reconstituted tryptic peptides with 0.1% (v/v) FA in water was subjected to LC-MS/MS using the ProteomeX-based configuration, termed phosphorylation site mapping method. This configuration utilizes two Zorbax 300SB C18 traps (5 µm, 5 x 0.3 mm; Agilent) and one C18 PicoFrit capillary column (10 cm, 360-µm outer diameter, 75-µm inner diameter, 15-µm tip; packed with 5-µm Biobasic C18; Thermo-Finnigan). Peptides were loaded onto one of the peptide traps via autosampler, concentrated, desalted, and eluted into the C18 PicoFrit capillary column with an acetonitrile gradient (0–80% solvent B in solvent A for a duration of 72 min; solvent A = 0.1% (v/v) FA in water; solvent B = 100% acetonitrile containing 0.1% FA). The peptide trap and C18 PicoFrit capillary column were then reset for 2 min and re-equilibrated for 15 min with 100% of solvent A. Following re-equilibration, the sample already loaded onto the second trap was eluted and analyzed. The m/z ratios of eluted peptides and fragmented ions from the C18 PicoFrit capillary column were analyzed in the data-dependent neutral loss MS/MS/MS mode. In this mode, each full scan (400–1600 m/z) was followed by three data-dependent MS/MS scans (isolation width, 2 amu; normalized collision energy, 35%; minimum signal threshold, 500 counts; dynamic exclusion (repeat count, 2; repeat duration, 30 s; exclusion list size, 50; exclusion duration, 180 s)) on the top three intense ions from that scan. An MS/MS/MS scan was automatically performed when the most intense peak from the MS/MS spectrum corresponded to a neutral loss event of 98 (+1), 49 (+2), and 32.7 (+3) m/z ± 1.0 Da. The heated C18 PicoFrit tip was held at ion sprays of 1.7 kV and a flow rate of 250 nl/min. The total run time was 98 min per sample.
Database Customization and Indexing—
The National Center for Biotechnology Information (NCBI; ftp.ncbi.nih.gov/blast/) non-redundant database (as of March 2005) was used for querying all data. The FASTA database utilities and indexer of the BioWorks 3.1SR1 software allowed us to create a plant database (keywords Arabidopsis, Oryza sativa, Zea mays, Medicago, Brassica, and Glycine) extracted from NCBI non-redundant database and to index it against trypsin enzyme and static and differential modifications, respectively. Two types of indexed databases were created using the plant database. The indexed database I carried cysteine (carboxyamidomethylation; +57 Da) and methionine (oxidation; +16 Da) as static and differential modifications, respectively. The indexed database II carried a static modification of +57 Da on cysteine and differential modifications of +16 Da on methionine and +80 Da on serine, threonine, and tyrosine residues.
Database Search—
For identification of phosphoprotein spots, LC-MS/MS (high throughput configuration) data were searched against the indexed database I using the SEQUEST algorithm (46, 47) as part of the BioWorks 3.1SR1 software suite. The search parameters for this database were set as follows: enzyme, trypsin; number of internal cleavage sites, 2; mass range, 400–4000 Da; threshold, 500; minimum ion count, 35; and peptide mass tolerance, 1.5 Da. Matching peptides were filtered for correlation scores (XCorr at least 1.5, 2.0, and 2.5 for +1, +2, and +3 charged ions, respectively). The XCorr value represents the overlap correlation between experimental and theoretical MS/MS spectra produced by candidate peptides in the database. For all protein assignments, a minimum of two unique peptides was required. Assignments annotated as "unknown" were BLASTP searched against the NCBI non-redundant database (as of March 2005) to further query their homology.
The indexed database II was used for analysis of raw data (MS/MS spectra) collected using the configuration "phosphorylation site mapping method." The search parameters for this database were the same except peptide mass tolerance was 2 Da as mentioned for the indexed database I. XCorr values of at least 1.9, 2.5, and 3.3 for +1, +2, and +3 charged ions, respectively, were applied for database matches. MS/MS/MS spectra were also searched against the database with a variable modification of –18 to serine and threonine residues (dehydroalanine). Resulting spectra were inspected manually to verify phosphorylation events.
Database Construction—
The annotated high resolution 2-DGE reference gel image and associated experimental, predicted, and other data presented in this study can be freely accessed via the oilseed proteomics server (oilseedproteomics.missouri.edu) under the links "Phosphoproteomics of B. napus seed filling." Data are viewable through 2-D gel reference map viewer and a protein identification table (Table I). The spots on the reference gel are hyperlinked to display expression profile and protein identification data.
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RESULTS |
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TOPABSTRACTEXPERIMENTAL PROCEDURESRESULTSDISCUSSIONREFERENCES |
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Seeds collected at different stages and embryos dissected from these seeds are shown in Fig. 1, top panel. A visual observation of seeds and embryos indicated that seeds at 2 WAF are largely occupied with liquid endosperm because the embryos occupied only a small portion of the total seed mass. As seed development progressed, the color of seeds turned green, and the embryo mass increased. The light pale green color of seeds changed to deep green and then part of the seed coat changed to dark red at 4 and 6 WAF, respectively. A dramatic expansion in embryo size occurred between 2 and 4 WAF and continued at a much slower rate until 6 WAF, indicating consumption of aqueous soluble constituents and sugars by the embryo. This is consistent with a previous finding where a shift from starch to oil accumulation during the early stages of cotyledon filling (i.e. embryo development) was shown (48); that is, embryo size increases with reserve deposition. Furthermore a decrease in deep green color followed by an increase in dark red color at 6 WAF indicates the initiation of maturation phase around 5 WAF. Another interesting observation was that embryos acquired a degree of photosynthetic capacity by 4 WAF as apparent by dark green embryos followed by a change to light green suggesting a decrease in photosynthesis (Fig. 1, Embryos). Two physiological parameters of seed, fresh seed and embryo mass and total protein contents in seed, were also measured at each seed developmental stage to support our above observations (Fig. 1, lower panel). The fresh seed weight reached a maximum at 5 WAF (6.1 mg/seed) followed by sudden decline at 6 WAF (3.6 mg/seed). A similar profile for embryo was also found except for only a slight increase in embryo mass at 3 WAF. The protein content increased gradually until 4 WAF and then sharply from 4 to 6 WAF. Therefore, to include most processes occurring during seed filling, seed materials at these studied stages were ideal for a systematic phosphoproteomics study.
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90%) were concentrated in the region between pH 4 and 7, and many spots in this region overlapped with each other (data not shown). Overlapping spots cause problems in downstream analysis, such as precise volume quantification and identification by MS. In contrast, analysis of pH 4–7 showed distinct and defined spots; a slight spot overlap was noticed near the end of pH 4 and 7 and around the region of 84 kDa. Because quantitative expression profiling of phosphoproteins and establishment of a reference map were the main aims of this study, we decided to use pH 4–7 IPG strips exclusively. As mentioned under "Experimental Procedures," high resolution (24-cm) 2-D gels of 2, 3, 4, 5, and 6 WAF were developed along with their reference gel. In the reference gel, 300 phosphoprotein spot groups were assigned by ImageMaster software. The dynamic range of spot volume of all Pro-Q DPS-detected spots ranged from 1 to 3.2 x 104. Perfunctory analysis of 2-D gels revealed dynamic changes of phosphoprotein spots throughout seed filling (Fig. 2); gel sections presented are representative of four high quality 2-D gels obtained for each stage. The phosphoprotein spot numbers were assigned by ImageMaster software after image analysis of the gels (described below). For example, spot numbers 669 and 679 in area I were expressed at all the stages analyzed with maximum accumulation at 3 WAF, whereas spot numbers 792 and 868 in area II were initially detected at 5 WAF followed by a decrease in their expression levels. In area III, spot numbers 831 and 833 were also detected at 5 WAF, and their abundance increased dramatically at 6 WAF.
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Quantitative Analysis of Phosphoprotein Spots Established 234 Developmental Expression Profiles—
A strategy for analysis of acquired 2-D images is schematically presented in Fig. 3. Selection of spots and their matching were carried out using ImageMaster software as described under "Experimental Procedures." As shown at the left-hand side, four 2-D gels derived from biological quadruplicates were processed to select high quality spots. To generate high quality quantitative expression profiles, the following threshold criteria were applied: first, the spot should be present in all four biological replicate gels, and second, these spots should be detected in at least two developmental stages. Under these conditions, ImageMaster software established 234 developmental expression profiles (supplemental table); the matched spots and their volume were also manually validated. The variance of acquired quantification data on protein spots was calculated using two different statistical formulas, standard deviation (STDEV) and CV, and are presented in the supplemental table. The standard deviation represented the biological and technical variations arising from four independent sample harvesting events followed by four independent protein extractions. The CV values allowed direct spot-to-spot comparison of significance levels in acquired quantitative data; therefore, the statistical significance of differentially expressed phosphoprotein is inversely proportional to the CV value. The dynamic range in spot volume for these spots varied from 4.5 x 102 to 3.2 x 104. An example of quantitative expression profile for spot number 718 is shown (Fig. 3, upper panel).
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Database Construction and Establishment of High Resolution 2-DGE Phosphoprotein Reference Map—
The 2-D reference gel map, quantitative expression profiles, and assigned phosphoprotein spots by LC-MS/MS were assembled to develop the "B. napus phosphoproteomics" database (Fig. 3). An interactive high resolution 2-DGE phosphoprotein reference map serves as the portal for expression and identification data (Fig. 5). The presence of the cursor on any active spot automatically shows experimental molecular weight, pI, and phosphoprotein name (if identified by LC-MS/MS). Each of the active spots is hyperlinked to another web page displaying the expression profile.
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In-gel digested tryptic peptides of BSA and bovine ß-casein (derived from PeppermintStick standards) as non-phosphorylated and phosphorylated protein markers, respectively, were used to evaluate the above mentioned configuration and instrument method. As expected, no phosphopeptides were detected in the BSA trypsin-digested sample. In contrast, a monophosphorylated peptide (FQS*EEQQQTEDELQDK; the asterisk indicates phosphorylation at the serine residue) was detected in the bovine ß-casein sample with high confidence (Fig. 7A). The total ion chromatogram and acquired MS spectra, including the neutral loss-triggered MS/MS/MS spectrum, of the doubly charged FQS*EEQQQTEDELQDK monophosphopeptide at m/z 1031.81 (XCorr = 5.2) are shown. Peptides with phosphoserine and phosphothreonine are known to lose phosphoric acid (H3PO4 = 98.0 Da) with low collisional energy in MS/MS (52). In Fig. 7A, the MS/MS spectrum showed that the fragment ion from the neutral loss is notably abundant, whereas the informative fragment ions are suppressed. Because the parent ion was doubly charged, the theoretical difference between parent ion and the neutral loss fragment ion was 49.0 m/z. As the most abundant ion in the MS/MS spectrum was the neutral loss fragment ion at m/z 982.62, the MS/MS/MS spectrum of the neutral loss fragment ion was automatically acquired to more accurately determine the phosphopeptide sequence and the phosphorylation site. Abundance of the neutral loss fragment ion in the MS/MS spectrum and the acquired MS/MS/MS spectrum confidently determined the amino acid sequence of detected monophosphate peptide and mapped the phosphorylation site at the serine residue demonstrated previously for bovine ß-casein (53).
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DISCUSSION |
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TOPABSTRACTEXPERIMENTAL PROCEDURESRESULTSDISCUSSIONREFERENCES |
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A phosphoprotein stain, Pro-Q DPS, was applied to detect and quantify phosphoproteins resolved by 2-DGE. As phosphorylation is a dynamic process, quantification of phosphoproteins is one major objective of this study in addition to the identification of phosphoproteins and their phosphorylation sites. To achieve this objective, we recently investigated some of the inherent limitations with Pro-Q DPS and established a modified protocol to reproducibly detect phosphoproteins on high resolution 2-D gels (44). Using this protocol, we detected 300 phosphoprotein spots on 2-D gels and provided quantitative expression profiles for 234 spots expressed in at least two seed developmental stages (Fig. 3 and supplemental table). Hierarchical clustering of expression profiles further revealed the occurrence of six major expression trends (Fig. 4). It appeared that phosphoproteins in each cluster are regulated in a stage-specific and coordinate manner; that is, abundance of phosphoproteins in clusters 1, 2, and 3 reached a maximum at 3, 4, and 5 WAF, respectively. Identification of 70 non-redundant phosphoproteins and their classification into 10 functional categories (energy and metabolism are the largest groups) suggested that protein phosphorylation might be involved in the regulation of storage reserve synthesis. As these phosphoproteins are of diverse functions ranging from signal transduction to protein synthesis and destination and are known to operate on different signaling and metabolic pathways, it is highly likely that phosphoproteins are linked to each other either through kinase function or common pathways.
The paucity of systematic studies on phosphoproteins in plants precludes us from discussing relational information about the phosphoproteins identified here, particularly because many of these phosphoproteins are novel. However, one can extract important information from the given inventory of phosphoproteins and their dynamic behavior. A few examples are as follows. Analyses of phosphoproteins belonging to different functional categories and their dynamic expressions revealed that the majority of phosphoproteins (75%) involved in signal transduction accumulated predominantly at 2 WAF followed by a sharp decrease in their abundance as shown for expression clusters 5 and 6 in Fig. 4. This is in contrast to expression profiles of 70% of phosphoproteins belonging to either the energy or metabolism category, which group with clusters 2 and 3 (Fig. 4 and Table I). Such opposite expression patterns of phosphoproteins suggest a tight coordination between the function of phosphoproteins associated with signal transduction and energy/metabolism. The 14-3-3 proteins have been shown previously to regulate both the signal transduction and metabolic pathways (for reviews, see Refs. 21 and 56–58). The 14-3-3 proteins typically contain two 14-3-3 protein family signature motifs, one each near the N- and C-terminal regions and one annexin binding motif (for reviews, see Refs. 56–58). 14-3-3 has been shown to interact with and be phosphorylated by multiple protein kinase C isoforms in platelet-derived growth factor-stimulated human vascular smooth muscle cells (59). However, there is no direct evidence for in vivo phosphorylation of 14-3-3 proteins in plants. This study identified two 14-3-3 phosphoproteins (Group IDs 720 and 867) and two annexin proteins (Group IDs 658 and 699) (Fig. 5 and Table I). In addition, among the known potent targets of 14-3-3 proteins, H+-ATPase and heat shock proteins were also found as phosphoproteins (Fig. 5 and Table I). A recent proteomics study of soybean has also identified four 14-3-3 isoforms highly expressed during seed development (20). These findings suggest that 14-3-3 proteins might be involved in signaling and metabolic pathways within developing seed. The overall inventory of phosphoproteins also indicated the presence of several phosphoproteins that have not yet been reported as a phosphoprotein, including stearoyl-acyl-carrier-protein desaturase (stearoyl-ACP desaturase) (Table I). Stearoyl-ACP desaturase is a key regulator of unsaturated fatty acids and has been implicated in the regulation of cell growth and development and the defense/stress responses (60, 61).
By mapping the phosphorylation sites in at least 16 non-redundant phosphoproteins, including the 14-3-3 and annexin, this study provided a further level of confidence in the identified phosphoproteins (Table II). The criteria applied for selection of these phosphopeptides are based on the seminal large scale phosphoproteomics studies of the developing mouse brain and HeLa cell nuclear phosphoproteins (51, 55). A survey of the published literature on phosphoproteomics showed that the criteria for assignment of phosphorylation sites and selection of phosphopeptides are still evolving (42, 51, 54, 55). Nevertheless among the applied criteria, the XCorr value of at least 1.9, 2.5, and 3.3 for +1, +2, and +3 charged ions, respectively, appears to be widely accepted. The given XCorr value has been applied along with the concept of data-dependent MS/MS/MS strategy to accurately assign the phosphorylation sites in this study. However, in our experience and as discussed by Beausoleil et al. (51), data-dependent MS/MS/MS strategy may be unnecessary for large scale phosphoprotein analyses. It was previously noted that only 96 of 2002 phosphorylation sites were determined from an MS/MS/MS spectrum (51). Of the mapped phosphorylation sites in this study, one site at the serine residue of 14-3-3 phosphoprotein was previously postulated based on phosphorylation of human 14-3-3 and on the presence of serine in all species (59, 62). Two serine, including one previously speculated, and threonine residues were identified as potential candidate sites for phosphorylation (Table II). Considering 14-3-3 proteins as ubiquitous regulatory factors, the 14-3-3 proteins were selected from diverse organisms, and their amino acid sequences were aligned together to determine the functional signification of the mapped phosphorylation sites (Fig. 8). For this purpose, Homo sapiens 14-3-3 protein 
isoform sequence was used as reference because the crystal structure of this isoform has been determined (62). As highlighted with a gray color in Fig. 8B, each putative phosphorylation site is conserved from plants to mammals and is located within the signature motif 2. The helix 9 of the C-terminal tail is within the signature motif 2, and this helix contains seven residues, which are directly involved in peptide binding (62, 63). Therefore, it is likely that phosphorylation at identified phosphorylation sites affects ligand bindings or induces conformational changes, which eventually might be important for specificity and selectivity of binding partners. This idea is consistent with increasing evidence that 14-3-3 post-translational modifications act as mechanisms for regulating interactions (64). In particular, the direct phosphorylation of 14-3-3 proteins, mediated by a variety of protein kinases, alters the binding affinity and dimerization properties of different 14-3-3 isoforms (64).
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In conclusion, we present the first quantitative global analysis of phosphoproteins during seed filling in B. napus. Phosphoprotein-specific Pro-Q DPS coupled to a 2-DGE and LC-MS/MS strategy led to the generation of 234 quantitative expression profiles of phosphoproteins and to the identification of 70 non-redundant phosphoproteins. Equally important was the establishment of a high resolution 2-D gel phosphoprotein reference map, which could be used for comparative functional proteomics. Identification of in vivo 14-3-3 phosphoproteins and their potential phosphorylation sites implied a potential role for 14-3-3 also in seed development. This collective data set is a step forward in the analysis of the seed filling phosphoproteome in B. napus and toward an understanding of the regulatory mechanisms behind embryo development and seed reserve deposition. Future studies will be directed toward investigating the function of phosphoproteins involved in mediating multiple signaling and metabolic pathway such as 14-3-3 phosphoproteins and developing a suitable and high throughput system to map phosphorylation sites in Pro-Q DPS-detected phosphoprotein spots on 2-D gels. The latter part will help determine whether the changes in expression of phosphoproteins are due to total phosphoprotein expression or phosphorylation status (i.e. phosphorylation stoichiometry).
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Published, MCP Papers in Press, July 6, 2006, DOI 10.1074/mcp.M600084-MCP200
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
1 The abbreviations used are: 2-DGE, two-dimensional gel electrophoresis; CBB, Coomassie Brilliant Blue; CV, coefficient of variation; FA, formic acid; PGK, phosphoglycerate kinase; Pro-Q DPS, Pro-Q Diamond phosphoprotein stain; WAF, weeks after flowering; TEMED, N,N,N',N'-tetramethylethylenediamine; 2-D, two-dimensional; ACP, acyl-carrier-protein. 
* This work was supported by National Science Foundation Plant Genome Research Grants DBI-0332418 and DBI-0445287 (to J J T.).
S The on-line version of this article (available at http://www.mcponline.org) contains supplemental material.
¶ To whom correspondence should be addressed: Biochemistry Dept., University of Missouri-Columbia, 109 Life Sciences Center, Columbia, MO 65211. Tel.: 573-884-5979; Fax: 573-884-9676; E-mail: agrawalg{at}missouri.edu
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TOPABSTRACTEXPERIMENTAL PROCEDURESRESULTSDISCUSSIONREFERENCES |
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Cn. At, A. thaliana; Bo, Brassica oleracea; Os, O. sativa. The hyphens and periods of the peptides indicate the N and C termini of their amino acid sequences and the digestion sites of the trypsin enzyme, respectively.