Leaf Proteome Analysis of Transgenic Plants Expressing Antiviral

Dec 19, 2008 - To whom correspondence should be addressed: Angiola Desiderio, Sezione Genetica e Genomica Vegetale, Dipartimento BAS-BIOTEC, ...
0 downloads 0 Views 5MB Size
Leaf Proteome Analysis of Transgenic Plants Expressing Antiviral Antibodies Mariasole Di Carli,† Maria Elena Villani,† Giovanni Renzone,‡ Luca Nardi,† Alessandra Pasquo,† Rosella Franconi,† Andrea Scaloni,‡ Eugenio Benvenuto,† and Angiola Desiderio*,† Sezione Genetica e Genomica Vegetale, Dipartimento BAS-BIOTEC, ENEA Casaccia, Rome, Italy, and Proteomics & Mass Spectrometry Laboratory, ISPAAM, National Research Council, Naples, Italy Received May 16, 2008

The expression of exogenous antibodies in plant is an effective strategy to confer protection against viral infection or to produce molecules with pharmaceutical interest. However, the acceptance of the transgenic technology to obtain self-protecting plants depends on the assessment of their substantial equivalence compared to non-modified crops with an established history of safe use. In fact, the possibility exists that the introduction of transgenes in plants may alter expression of endogenous genes and/or normal production of metabolites. In this study, we investigated whether the expression in plant of recombinant antibodies directed against viral proteins may influence the host leaf proteome. Two transgenic plant models, generated by Agrobacterium tumefaciens-mediated transformation, were analyzed for this purpose, namely, Lycopersicon esculentum cv. MicroTom and Nicotiana benthamiana, expressing recombinant antibodies against cucumber mosaic virus and tomato spotted wilt virus, respectively. To obtain a significant representation of plant proteomes, optimized extraction procedures have been devised for each plant species. The proteome repertoire of antibody-expressing and control plants was compared by 2-DE associated to DIGE technology. Among the 2000 spots detected within the gels, about 10 resulted differentially expressed in each transgenic model and were identified by MALDI-TOF PMF and µLC-ESI-IT-MS/MS procedures. Protein variations were restricted to a limited number of defined differences with an average ratio below 2.4. Most of the differentially expressed proteins were related to photosynthesis or defense function. The overall results suggest that the expression of recombinant antibodies in both systems does not significantly alter the leaf proteomic profile, contributing to assess the biosafety of resistant plants expressing antiviral antibodies. Keywords: recombinant antibody • transgenic plants • substantial equivalence • leaf protein extraction • plant proteomics • 2D-DIGE

1. Introduction Because of their high binding affinity and specificity, antibodies represent a useful tool to interfere with or define the function of several target molecules. Antibodies that specifically recognize soluble or membrane-associated receptors, enzymes or DNA-binding proteins may affect structure, function or misallocation of the target molecule, thus, interfering with the associated biological processes.1 Hence, antibody-mediated control of cell metabolism has been reported as an effective strategy for different applications, including human therapy2 and modulation of plant physiology or pathology.3-5 Antibodies or antibody fragments expressed in plant (“plantibodies”) have been used either to immunomodulate physiological or pathological function in planta or to synthesize large amounts of antibodies for diagnostic or therapeutic use.6 The effectiveness * To whom correspondence should be addressed: Angiola Desiderio, Sezione Genetica e Genomica Vegetale, Dipartimento BAS-BIOTEC, ENEA Casaccia, via Anguillarese 301, 00123 Rome, Italy. E-mail: desiderio@ casaccia.enea.it. Tel: ++39 06 30484176. Fax: + + 39 06 30484808. † Dipartimento BAS-BIOTEC, ENEA Casaccia. ‡ ISPAAM, National Research Council.

838 Journal of Proteome Research 2009, 8, 838–848 Published on Web 12/19/2008

of antibody-mediated resistance in plants has been widely demonstrated. Single chain variable fragment (scFv) recombinant antibodies directed against viral coat proteins, expressed in the appropriate cell compartment, were able to protect plants from virus infections.7-11 The possibility to obtain selfprotecting plants against viral attacks is crucial for agronomical applications, since viruses are not sensitive to common chemical treatments of crops. Considering the economic impact of virus diseases, transgenic plants may represent an interesting solution to this problem.12 However, acceptance of genetically modified organisms is strictly related to biosafety issues. Although the difference between a transgenic genotype and its unmodified background is generally restricted to one or two inserted genes, the risk of unintended biological modifications cannot be excluded a priori. In fact, acquisition of exogenous genes and/or the suppression of endogenous genes may underlie unexpected modifications in the host protein profile. These changes may, in turn, lead to accumulation of undesired compounds or biochemical modifications (i.e., different folding or post-translation modifications, complex formation, protein degradation) that could alter the plant-derived products. In the 10.1021/pr800359d CCC: $40.75

 2009 American Chemical Society

Leaf Proteome Analysis of Transgenic Plants last years, large-scale profiling methods have allowed to analyze entire sets of transcripts, proteins or metabolites, providing a comprehensive view of a biological sample. The comparative evaluation of transgenic tomato, potato, Arabidopsis thaliana, soybean and Zoysia grass with their wild-type counterparts has been accomplished using either proteomic or transcriptomic approaches, generally demonstrating that there are less qualitative or quantitative differences between genetically modified lines and their unmodified controls than those found between different plant varieties and landraces.13-18 However, we recently observed that the introduction of a foreign gene coding for a signaling molecule can highly affect the proteome repertoire of the transformed plant, indicating that the biological effect of a transgene should be determined on the caseby-case basis.19 The aim of the present work was to investigate on the “substantial equivalence” of transgenic plants expressing antiviral antibodies by analyzing their proteome repertoire with DIGE technology. To this purpose, two Solanaceae plant models expressing different recombinant antibodies were comparatively evaluated with their untransformed counterparts, namely, (i) tomato plants expressing in the cytoplasm an antibody directed against the cucumber mosaic virus (CMV) coat protein10 and (ii) Nicotiana benthamiana plants expressing in the apoplast an antibody against the tomato spotted wilt virus (TSWV) G1 envelope glycoprotein.20 Both CMV and TSWV present a broad host range among Solanaceae causing important crop loss.21,22 Here, we demonstrate by leaf proteome analysis that insertion of antibody transgenes in these plants did not cause pleiotropic effects, thus, validating antibodymediated engineered protection as a tool to generate organisms resistant to virus attack.

2. Material and Methods 2.1. Plant Materials. Two independent Agrobacteriumtransformed plants previously described and characterized were used: tomato (Lycopersycon esculentum cv. Micro-Tom) expressing the antibody scFv(G4) against the CMV coat protein10 and N. benthamiana expressing the antibody scFv(B9) against the TSWV G1 envelope glycoprotein.20 As a reference, the corresponding untransformed plants were used. All plant transformations were realized using an expression cassette, including the gene encoding for the scFv antibody under the control of the constitutive 35S promoter, cloned in the pBI vector for Agrobacterium-mediated transformation. Transgenic plants at T4 and T3 isogenic generation were used for tomato and N. benthamiana, respectively. All transgenic seeds were germinated on selective medium containing 1/2 Murashige and Skoog (MS) salts (Sigma M5524), 20 g/L sucrose, 100 mg/L kanamycin, 7 g/L Difco Bacto-agar (pH 5.8), and plants showing kanamycin resistance were then transferred to soil. All transgenic and untransformed plants were grown in containment greenhouse (biosafety level 2), under constant conditions: 24 °C, 16 h of light and 60% of humidity. Subapical leaves from 1 month old N. benthamiana and tomato plants were collected approximately at the same preflowering stage and stored at -80 °C prior to protein analysis. To reduce the biological variance, two “average” samples were prepared pooling green leaves derived from three to four randomly selected plants at the same preflowering stage. This experimental setup, adopted for both transgenic plant models and untransformed counterparts, was finalized to focus on the differences due to genetic background manipulation.

research articles 2.2. Virus Resistance Analysis. The T4 generation of selfpollinated transgenic tomato plants expressing the scFv(G4) antibody derived from a line defined as resistant. These transgenic plants, used for the proteome analysis, were virus challenged in order to confirm the response to CMV infection, essentially as already described.10 Virus challenge experiment was performed on 10 transgenic and 10 control plants, in containment greenhouse (biosafety level 2), under constant conditions: 24 °C, 16 h of light and 60% of humidity. Virus inoculum was prepared by grinding young symptomatic leaves of N. benthamiana, infected with CMV-F100 strain, in freshly prepared ice-cold PBS (1:3 (w/v) ratio). The extract was then used to infect two leaves of transgenic and control tomato plants, at three to four leaves stage. Tissue penetration was facilitated by dusting leaves with abrasive powder (Carborundum, Sigma) and rubbing between gloved fingers dipped in virus containing extract. The infected plants were maintained in containment greenhouse at 24 °C for up to 8 weeks after inoculation. Typical infection symptoms, consisting in systemic mosaic, were detected in untransformed plants 10 days postinoculation. Prolonged infection time resulted in severe stunting and leaf deformation. 2.3. Immunoblotting of N. benthamiana and Tomato Leaves. The presence of the scFv antibodies in transgenic plants was assayed by Western blot analysis. Leaf extracts from untransformed N. benthamiana and tomato plants were used as negative controls. Leaf tissues (1 g) were finely ground in liquid N2 and 3 mL of ice-cold PBS (0.1 M, pH 7.0) containing Complete protease inhibitors (Roche) was added. After two centrifugation steps at 9000g for 30 min at 4 °C, the supernatant was recovered and quantified using the Bradford colorimetric assay (Bio-Rad). Leaf protein extracts (15 µg) from transgenic and control plants were solved in 80 mM Tris-HCl, pH 6.8, 10% (v/v) glycerol, 2% (w/v) SDS, 143 mM β-mercaptoethanol, containing traces of bromophenol blue, and heated for 5 min, at 100 °C. Proteins were then separated by 12% SDS-PAGE and electrotransferred to polyvinylidene difluoride (PVDF) membrane. Apparent molecular masses were estimated by comparison with the Rainbow prestained markers (GE Healthcare). Membrane was blocked overnight with 6% skimmed milk in PBS. ScFv antibodies were detected by ECL system (GE Healthcare). ScFv(B9) was revealed after incubation with biotinylated polyclonal antibody A318 (1 µg/mL) (obtained as described by Franconi et al.20) for 2 h at room temperature, followed by incubation with HRP-conjugated streptavidin, for 1 h. ScFv(G4) was revealed by incubation with HRP-anti-Flag M2 antibody (2 µg/mL) (Sigma) for 2 h, at room temperature. ScFv(G4) and scFv(B9) expression levels were estimated using 20 ng of purified scFv as band intensity reference. 2.4. Protein Extraction. Different protocols were tested to select the most effective protein extraction conditions for L. esculentum and N. benthamiana leaf material. Protocol A. The phenol extraction method was performed according to what had been previously reported.23 Leaf tissue (1 g) was finely powdered in liquid N2 and homogenized in 1 mL of 0.5 M Tris-HCl, pH 7.5, 1 M NaCl, 500 mM EDTA, 50 mM DTT, containing Complete protease inhibitors (Roche). An equal volume of phenol saturated solution in 0.5 M Tris-HCl, pH 8.0, was then added; this mixture was subjected to vortexing for 1 min, followed by cooling on ice. After centrifugation at 3500g for 10 min, the aqueous phase was removed without disrupting the liquid interface containing most of the proteins. This step was repeated, adding 2 vol of phenol saturated Journal of Proteome Research • Vol. 8, No. 2, 2009 839

research articles solution in 0.5 M Tris-HCl, pH 8.0. Proteins were precipitated with 5 vol of 0.1 M ammonium acetate in cold MeOH, at -20 °C, overnight. Supernatant was removed after centrifugation at 3500g for 10 min at 4 °C; the pellet was suspended in 0.1 M ammonium acetate and 80% (v/v) cold MeOH. The protein pellet obtained after a new centrifugation at 3500g for 10 min at 4 °C was rinsed with 80% (v/v) acetone and again subjected to centrifugation at 3500g for 10 min at 4 °C. The final pellet was dried to remove traces of acetone. Protocol B. Phenol extraction was carried out in presence of SDS according to Wang et al.24 Leaf tissue powder was dissolved in 8 vol of phenol saturated solution in 0.5 M TrisHCl, pH 8.0, and 8 vol of SDS buffer (30% sucrose, 2% SDS, 0.1 M Tris-HCl, pH 8.0, 5% DTT). After vortexing, the upper phenol phase was collected by centrifugation at 8000g for 5 min; this step was repeated twice. Proteins were precipitated adding 5 vol of 0.1 M ammonium acetate in cold MeOH at -20 °C for 30 min. The pellet was recovered by centrifugation at 8000g for 10 min, and then rinsed 3 times with 0.1 M ammonium acetate in cold MeOH and 3 times with 80% cold acetone. The final pellet was dried. Protocol C. Protein extraction by aqueous buffer associated to TCA-acetone precipitation was according to Saravanan and Rose, with minor modifications.25 Powdered leaves (5 g) were suspended in a 1% PVPP, 0.1 M KCl, 0.5 M Tris-HCl, pH 7.5, 500 mM EDTA, 2% DTT buffer, containing Complete protease inhibitor cocktail (Roche) (15 mL). The mixture was homogenized using an Ultraturrax homogenizer for 15 min at 4 °C; the insoluble material was removed by centrifugation at 6000g for 60 min at 4 °C. Proteins present in the supernatant were precipitated with 20 mL of cold acetone containing 10% TCA, 1% PVPP and 2% DTT, at -20 °C overnight. The protein pellet was recovered by centrifugation at 6000g for 60 min at 4 °C, rinsed once with cold MeOH, 3 times with cold acetone, and finally dried. Protocol D. TCA-acetone extraction was adapted from the method of Tsugita et al.,26 with some modifications. Leaf tissue (2 g) was ground to a fine powder in a mortar with liquid N2. The resulting powder was finely homogenized in cold acetone using an Ultraturrax homogenizer and recovered by centrifugation at 8000g for 30 min at 4 °C. The pellet was suspended in 8 mL of 10% TCA and 2% DTT, containing Complete protease inhibitor cocktail (Roche) in cold acetone. Proteins were precipitated at -20 °C overnight, and then were collected by centrifugation at 8000g for 1 h. The protein pellet was then mixed with 0.07% DTT containing protease inhibitor cocktail in cold acetone and placed at -20 °C for 1 h. The pellet was collected by centrifugation at 8000g for 1 h at 4 °C, washed at least 3 times with cold acetone until the supernatant was colorless, aliquoted, and lyophilized. Protocol E. Variation of the protocol D in which the DTT was replaced by 0.07% β-mercaptoethanol in all steps. Protocol F. Variation of the protocol D in which concentration of DTT in the TCA-acetone extraction buffer was reduced to 0.07%. Moreover, an additional precipitation step was performed. After TCA/acetone precipitation, the pellet was suspended in 5 M urea, 2 M thiourea, 30 mM Tris-HCl, pH 8.0, 2% CHAPS, 1% Triton X-100 and 50-60% ammonium sulfate was added to obtain a saturated solution. Proteins were precipitated overnight at 4 °C, and collected by centrifuging at 8000g for 1 h at 4 °C. Protocol G. Variation of protocol D in which 1% PVPP was added during leaf grinding. 840

Journal of Proteome Research • Vol. 8, No. 2, 2009

Di Carli et al. 2.5. Electrophoretic Analysis. All applied procedures were optimized for DIGE (GE Healthcare) analysis. Protein pellets from each extraction method were air-dried under laminar flow. Different solubilization buffers (SB) were tested: SB1, 8 M urea, 2% ASB-14, 10 mM Tris-HCl, pH 8.0, 5 mM magnesium acetate; SB2, 8 M urea, 2% ASB-14, 10 mM Tris-HCl, pH 8.0, 5 mM magnesium acetate, 1% PVPP; SB3, 5 M urea, 2 M thiourea, 30 mM Tris-HCl, pH 8.0, 2% CHAPS, 1% Triton X-100; SB4, 5 M urea, 2 M thiourea, 30 mM Tris-HCl, pH 8.0, 2% CHAPS, 1% Triton X-100, 1% PVPP; SB5, 5 M urea, 2 M thiourea, 30 mM Tris-HCl, pH 8.0, 2% CHAPS, 1% Triton X-100, 1% celite; SB6, 8 M urea, 4% CHAPS, 10 mM Tris-HCl, pH 8.0, 5 mM magnesium acetate. No DTT and ampholytes were included in the solubilization buffer because they are known to react with the N-hydroxysuccinimide group of the cyanine dyes. After shaking at room temperature for 1 h, protein solution was sonicated on ice in an ultrasonic bath, for 1 h, and centrifuged at 14 000g for 40 min. The supernatant was immediately used for 1-DE and 2-DE, or purified using Clean-Up kit (GE Healthcare) prior to electrophoresis. Protein concentration was quantified using the DC Protein Assay (Bio-Rad) and BSA as standard. 1-DE was carried out using 12% polyacrylamide gels and the BioRad Mini Protean II System. Protein samples were solved in 62 mM Tris-HCl, pH 6.8, 20% (v/v) glycerol, 1.8% (w/v) SDS, 175 mM β-mercaptoethanol and heated at 100 °C for 5 min. Protein electrophoresis markers from GE Healthcare were used. Gels were silver stained according to Oakley et al.27 For 2-DE analysis, the amount of protein loaded onto an IPGstrip (GE Healthcare) was 100 and 600 µg for analytical and preparative runs, respectively. Solubilized protein samples were added with 350 µL of isoelectrofocusing (IEF) rehydration buffer, 7 M urea, 2 M thiourea, 13 mM DTT, 2% (w/v) ASB-14, 1% IPG buffer, and incubated with IPG-strips (4-7/18 cm or 3-10NL/18 cm), overnight at room temperature. IEF was performed on an IPGphor unit (GE Healthcare) at 20 °C, using a 50 µA current limit per strip and a program setting of 3 h at 300 V, 1 h at 500 V, 6 h at 1000 V, 5 h at 8000 V (analytical gels) or a 60 µA current limit per strip and a program setting of 10 h at 200 V, 3 h at 300 V, 1 h at 500 V, 6 h at 1000 V, 5 h at 8000 V (preparative gels). After focusing, proteins were reduced with 1% (w/v) DTT for 15 min, and alkylated with 2.5% (w/v) iodacetamide for 15 min, by independently incubating each strip in 10 mL of 50 mM Tris-HCl, pH 8.8, 6 M urea, 30% (v/v) glycerol, 2% (w/v) SDS, containing traces of bromophenol blue. Second dimension was run on 12.5% polyacrylamide gels (18 cm × 20 cm × 1 mm) in 250 mM Tris-HCl, pH 8.3, 1.92 M glycine, 1% (w/v) SDS, at 15 °C, applying 2 W/gel for 30 min and 20 W/gel for the remaining 4-5 h, using an Ettan DALTsix unit (GE Healthcare). Gels were silver stained according to Oakley et al. (analytical gels) or Shevchenko et al. (preparative gels).27,28 All protein extractions and solubilization procedures were carried out in triplicate, hence compared considering pattern quality, spot number and reproducibility. The number of spots was detected by ImageMaster Platinum 6.0 software (GE Healthcare). Automatic spot identification was performed followed by manual artifacts removal. 2.6. DIGE. Prior to electrophoresis, protein samples were labeled using the CyDyes DIGE Fluors (Cy2, Cy5 and Cy3) according to the manufacturer’s instructions.29 Each dye (1 mM stock) was freshly diluted with anhydrous dimethylformamide just prior to the labeling reaction. Protein extracts (50 µg) were

Leaf Proteome Analysis of Transgenic Plants

research articles

Figure 1. Comparison of the N. benthamiana leaf 2-DE proteomic maps obtained using different protocols from protein extraction. Protein samples (100 µg) were solubilized in SB1, purified by clean up method and analyzed in first dimension (pH 4-7 linear IPG, 18 cm). (A) phenol extraction (protocol A); (B) SDS/phenol extraction (protocol B); (C) aqueous buffer/TCA/acetone extraction (protocol C); (D) TCA/acetone extraction (protocol D). The second dimension was performed on a vertical slab 12.5% polyacrylamide gel. Protein spots were detected by silver staining.

mixed with Cy3, Cy5 and Cy2 (200 pmol) and incubated for 30 min in the dark.30 The Cy2-labeled sample was created by pooling an aliquot of all biological samples analyzed in the experiment. The reactions were then quenched by addition of 10 mM lysine, for 10 min in the dark. After a further addition of an equal volume of 7 M urea, 2 M thiourea, 130 mM DTT, 2% (w/v) ASB-14, and 2% IPG buffer, each sample was incubated for 15 min in the dark. The final volume of each sample mixture was adjusted to 350 µL with IEF rehydration buffer and 2-DE was performed on pH 3-10NL strips (GE Healthcare), as described above. To avoid artifacts due to preferential labeling, each biological sample was independently labeled with both Cy3 and Cy5 and was represented in the experiment three times as technical replicates. In this way, six replicate gels were run for each analysis either of N. benthamiana or tomato samples. 2.7. Gel Image and Statistical Analysis. After 2-DE, CyDyelabeled proteins were visualized by scanning using the Typhoon 9410 imager (GE Healthcare) set at the appropriate wavelengths for each dye. To ensure maximum pixel intensity between 40 000 and 60 000 pixels for the three dyes, all gels were scanned at a 100 µm resolution and the photo multiplier tube (PMT) voltage was set between 500 and 700 V. The scanned gel images were then directly transferred to the ImageQuant V5.2 software package (GE Healthcare). After cropping, the images were exported to the DeCyder Batch Processor and DIA (Differential-In gel Analysis) modules (GE Healthcare). To

compare protein spots across gels, a match set was created from the images of the six gels prepared for both tomato and N. benthamiana samples. The gel with the best resolution and the largest number of spots was chosen as the master gel. Landmark spots were manually defined to improve the automated matching results. Protein level changes between transformed and control samples was performed by the DeCyderBVA (Biological Variation Analysis, V5.02) module. Protein spots detected in at least 70% of all proteome maps were included, after normalization of the data, in PCA (Principal Component Analysis) analysis and nested ANOVA. For the PCA analysis, the DeCyder EDA (Extended Data Analysis, V6.5) module was used. To examine the effect of the transgene insertion in plant genetic background, a nested ANOVA was performed on the data sets, considering the hierarchical structure of the samples (transgene vs untransformed samples, biological replicates, technical replicates) with two nesting levels. The mean squares of the nested ANOVA were used to calculate the component of the total variance contributed by transgenes, biological replicates and technical replicates. This statistical analysis was performed using the JMP 7.0 software (SAS Institute, Inc., 2007: JMP Statistics and Graphics Guide, version 7. SAS Institute, Inc., Cary, NC). Protein spots showing a difference in volume over 1.5-fold and a statistically significant (p e 0.05) transgene effect with the relative variance component higher than 50% were selected Journal of Proteome Research • Vol. 8, No. 2, 2009 841

research articles

Di Carli et al.

Table 1. Comparison of the N. benthamiana and Tomato Leaf 2-DE Proteomic Maps Obtained Using Different Protocols for Protein Extraction and Solubilizationa extraction procedure

N. benthamiana (number of spots)

Phenol extraction (protocol A) SDS/phenol extraction (protocol B) Aqueous buffer/TCA/acetone extraction (protocol C) TCA/acetone extraction (protocol D) TCA/acetone/PVPP (protocol G) TCA/acetone/ammonium sulfate precipitation (protocol F) with no sample clean up TCA/acetone/ammonium sulfate precipitation (protocol F)

456 ( 10 397 ( 16 340 ( 20 450 ( 12

L. esculentum (number of spots)

410 ( 10 440 ( 12 300 ( 30 380 ( 36

solubilization procedure

N. benthamiana (number of spots)

L. esculentum (number of spots)

8 M urea, 2% ASB-14, 10 mM Tris-HCl, pH 8.0, 5 mM magnesium acetate (SB1) 5 M urea, 2 M thiourea, 30 mM Tris-HCl, pH 8.0, 2% CHAPS, 1% Triton X-100 (SB3) 8 M urea, 4% CHAPS, 10 mM Tris-HCl, pH 8.0, 5 mM magnesium acetate (SB6)

430 ( 18

420 ( 16

316 ( 25

340 ( 20

260 ( 28

288 ( 30

a To compare extraction procedures, protein samples (100 µg) from different extractions were solubilized in SB1, purified by clean up method and analyzed in first dimension (pH 4-7 linear IPG, 18 cm). To compare solubilization procedures, protein samples (100 µg) extracted from N. benthamiana with TCA/acetone-based protocol and from tomato with TCA/acetone/PVPP-based protocol were solubilized with different buffers and analyzed in first dimension (pH 3-10NL IPG, 18 cm). In all cases, second dimension was performed on a vertical slab 12.5% polyacrylamide gel. Protein spots were detected by silver staining.

as differentially expressed and further identified by different MS approaches (Table 2). 2.8. Protein Digestion and MS Analysis. Spots from 2-DE were excised from the gel, triturated, in-gel reduced, S-alkylated and digested with trypsin, as reported by Talamo et al.31 Gel particles were extracted with 25 mM NH4HCO3/acetonitrile (1:1 v/v) by sonication and peptide mixtures were concentrated. Samples were desalted using µZipTipC18 pipet tips (Millipore) before MALDI-TOF-MS analysis and/or directly analyzed by µLC-ESI-IT-MS/MS.32,33 Peptide mixtures from 2-DE spots were loaded on the MALDI target together with CHCA as matrix, using the dried droplet technique. Samples were analyzed with a Voyager-DE PRO spectrometer (Applera).33 Peptide mass spectra for PMF experiments were acquired in reflectron mode; internal mass calibration was performed with peptides derived from trypsin autoproteolysis. Data were elaborated using the DataExplorer 5.1 software (Applera). Peptide mixtures were also analyzed using a LCQ Deca Xp Plus mass spectrometer (ThermoFinnigan) equipped with an electrospray source connected to a Phoenix 40 pump (ThermoFinnigan).33 Peptide mixtures were separated on a capillary Hypersil-Keystone Aquasil C18 Kappa column (100 × 0.32 mm, 5 µm) using a linear gradient from 10% to 60% of acetonitrile in 0.1% formic acid, over 60 min, at flow rate of 5 µL/min. Spectra were acquired in the range 200-2000 m/z. Data were elaborated using the BioWorks 3.1 software provided by the manufacturer. 2.9. Protein Identification. ProFound software was used to identify spots from NCBI nonredundant database by PMF experiments.34 Candidates with ProFound’s Est’d Z-scores >2 were further evaluated by the comparison with Mr and pI experimental values obtained from 2-DE. SEQUEST software was used to identify proteins with data deriving from µLC-ESIIT-MS/MS experiments.35 Candidates from NCBI nonredundant databases with more than three identified CID spectra of peptides belonging to the same protein and SEQUEST Xcorr values >2.0 were further evaluated by comparison with experimental Mr and pI values obtained from 2-DE. Protein functional classification was done according to literature data. 842

Journal of Proteome Research • Vol. 8, No. 2, 2009

3. Results and Discussion 3.1. Optimization of the Proteomic Analysis of N. benthamiana and Tomato Leaves. Quality and yield of protein extraction from plant tissues are affected by the remarkable presence of nonprotein contaminants, such as pigments, secondary metabolites, polysaccharides and polyphenols, which also cause high background of gel staining, spot smearing and streaking during 2-DE.36-38 To reduce the presence of contaminants and to reach a good representation of tomato and N. benthamiana leaf proteomes, protocols based on the use of phenol24,25,39,40 or TCA/acetone26,41,42 extraction were comparatively evaluated for electrophoretic resolution and adapted to N. benthamiana leaf tissue. A better protein recovery and resolution during 2-DE was obtained when TCA/acetone-based protocol was used, associated with preliminary cold acetone washing steps during mechanical cell disruption and 2% DTT as a reducing agent (protocol D) (Figure 1 and Table 1). The extraction procedure optimized for N. benthamiana leaves was adapted to tomato sample, introducing some modifications for a thorough removal of potential contaminants (polyphenols and green pigments) present in this species in large amounts. We observed that addition of PVPP during leaf grinding (protocol G), described to remove phenolic compounds,43,44 resulted in higher amount of better resolved proteins in 2-DE gels (Table 1). Different cocktails of denaturing and detergent agents were evaluated to optimize protein solubilization after extraction. In both N. benthamiana and tomato samples, the optimal protein recovery was observed when thiourea/urea combination was used in the presence of sulfobetaine ASB14 (SB1) (Table 1).46,47 Addition of molecules able to capture contaminants, such as PVPP or celite,43,44,48 to denaturing buffers did not provide significant benefits. 3.2. Quantitative Proteome Analysis of N. benthamiana and Tomato Leaves. The DIGE technology was used to highlight quantitative differences during comparative proteomic analysis of transgenic and control plants. Six replicate 2-DE gels were prepared for each analysis. A mix of biological

Leaf Proteome Analysis of Transgenic Plants

Figure 2. Multicolor images from 2-D DIGE analysis. Equal amounts (50 µg) of wild-type sample, genetically modified sample, and the mixture (Cy2) of the samples included in N. benthamiana (A) and tomato (B) analysis were loaded on each gel. Proteins were visualized at the appropriate wavelengths for each individual cyanine dyes: Cy3, blue, for wild-type; Cy5, green, for transgenic sample; Cy2, red, for the standard mixture. Proteins were separated in the first-dimension IEF using nonlinear pH 3-10 IPG strip (18 cm) and second dimension was performed on a vertical slab 12.5% polyacrylamide gel. The arrows indicate differentially expressed proteins, identified by MS and listed in Table 2.

and technical replicates was obtained from pooled sample. To assess whether protein expression variation was due to transgene effect or to the natural variability among biological replicates, we performed a statistical test based on a nested analysis of variance (ANOVA).49 To evaluate the substantial equivalence between transformed plants and their unmodified counterparts, it is necessary considering the variance contribution inherent to sample manipulation (technical replicates) and the variance among individual plants (biological replicates). On the fluorescent-dye stained gels, 1818 ((2.3%) and 1989 ((4.5%) spots were detected in tomato and N. benthamiana, respectively. Figure 2 shows a representative multichannel image for each analysis. Quantitative comparisons of transgenic sample versus wild-type counterpart resulted in few differences with a low average ratio (e2.4) for both plant species. Table 2 reports the list of the proteins with difference in volume over 1.5-fold and a statistically significant (p e 0.05) transgene effect with the relative variance component higher than 50%. The nested ANOVA analysis allowed us to evaluate the contribution to the total variance of factors intrinsically related to the experimental design. In fact, even among the selected proteins we observed a non-negligible variance component due to technical (i.e., spot numbers 1 and 7 for tomato and spot numbers 2, 3 and 8 for N. benthamiana) and biological replicates (i.e., spot numbers 4, 5 and 7 for tomato and spot numbers 1, 4 and 7 for N. benthamiana).

research articles Our results indicated a limited number of differentially expressed proteins (10 for tomato and 8 for N. benthamiana), whose variation could be related to transformation events. Differential spots were visualized in preparative silver stained gels run in parallel experiments, excised and analyzed by MALDI-TOF PMF and µLC-ESI-IT-MS/MS procedures. All differentially expressed proteins were identified either in tomato or N. benthamiana leaf proteomes and classified in different groups according to their functional role (Table 2). Most proteins differentially expressed in transgenic tomato were involved in the photosynthetic function. We observed that three isoforms of ribulose bisphosphate carboxylase/oxygenase (RuBisCO) large subunit were overexpressed in transformed plants, whereas two isoforms were under-expressed. This abundant enzyme, consisting of 8 large (55 kDa) and 8 small subunits (14 kDa), is responsible for either CO2 fixation, through ribulose 1,5-bisphosphate carboxylation, or oxidative fragmentation of the pentose substrate in the chloroplast photorespiration process.50 Another protein implicated in electron transfer and water-splitting reactions essential for the production of molecular oxygen was up-regulated in transgenic samples, namely, photosystem II oxygen evolving complex protein 3.51,52 Two different isoforms of germin-like protein also resulted up-regulated in transgenic tomato. Germin-like proteins have been reported in literature and their diversity and ubiquity in the extracellular matrix has been recently demonstrated.53 Despite of a different function associated to these proteins (e.g., enzymatic, structural and receptor activity), they seem to play a general role in plant defense and development. An organelle protein essential in the last step of protein synthesis, namely, ribosome recycling factor, was also found as up-regulated in transgenic plants.54 Finally, a protein involved in ethylene signal pathway, namely, ethylene signaling protein, was up-regulated. The ethylene hormone plays a critical role in the regulation of developmental activity during the plant life cycle and serves as a major response mediator to various environmental signals.55 Similarly to what was observed in tomato, a majority of the proteins differentially expressed in transgenic N. benthamiana were also implicated in the photosynthesis and defense processes. In transformed plants, we detected a down-regulation of two different isoforms of carbonic anhydrase, an enzyme involved in the conversion of CO2 to HCO3- and H+ and photosynthetic bicarbonate assimilation.56 Moreover, an enzyme related to electron transport in energy production was identified as up-regulated, namely, oxygen evolving protein (16 kDa). Finally, five isoforms of germin-like proteins resulted upregulated in transformed N. benthamiana, paralleling what observed for tomato plants. The univariate nested ANOVA test allowed the statistical analysis of single protein spots according to a pairwise comparison without providing a general overview of the biological problem. A different perspective was provided by an explorative multivariate approach using the principal component analysis (PCA). In fact, the PCA consents to identify, from whole data sets, protein groups responsible for correlated variations. In this work, the PCA approach was adopted to investigate interand intra-group relationships between untransformed and transgenic plant data sets. This analysis is particularly indicated for this study since it allows to discriminate the transgene effects from the natural variability of the expression background. Figure 3 reports the PCA score plot of N. benthamiana (A) and tomato (B) plants. The variance of the first two principal Journal of Proteome Research • Vol. 8, No. 2, 2009 843

844

Journal of Proteome Research • Vol. 8, No. 2, 2009

RuBisCO large chain

RuBisCO large chain

RuBisCO large chain

RuBisCO large chain

Photosystem II oxygen-evolving complex

2

3

4

5

6

24K germin like protein

24K germin like protein

Etlylene signaling protein

Chloroplast oxygen-evolving protein

8

9

10

1

Carbonic anhydrase

Carbonic anhydrase

24 K germin-like protein

2

3

4

16 kDa subunit

Ribosome recycling factor

7

protein 3

RuBisCO large chain

protein name

1

spot

N. tabacum

N. benthamiana

N. benthamiana

N. benthamiana

S. lycopersicum

S. lycopersicum

S. lycopersicum

S. lycopersicum

S. lycopersicum

S. lycopersicum

S. lycopersicum

S. lycopersicum

S. lycopersicum

S. lycopersicum

organism

4/30

8/35

8/35

7/33

4/10

4/28

6/39

6/41

4/22

12/22

12/22

12/22

8/13

6/38

peptides/ coverage (%)

89258603

117710129

58253628

9291588/P82231

51457944/Q672Q6

92087012/P27065

92087012/P27065

92087012/P27065

92087012/P27065

89280643/P27065

code (gi/Swiss-Prot)

MALDI-PSD-MS

LC-MS-MS

LC-MS-MS

31711507/Q7XZV3

3061271/A4D0J9

3061271/A4D0J9

Nicotiana benthamiana MALDI-MS 58700507/Q5EFR5

LC-MS-MS

LC-MS-MS

LC-MS-MS

MALDI-MS

LC-MS-MS

MALDI-MS

MALDI-MS

MALDI-MS

MALDI-MS

MALDI-MS

identification method

Lycopersicon esculentum

a.0.0498 b.0.2782

a.0.0500 b.0.2056

a.0.0222 b.0.4113

a.0.0166 b.0.4007

a.0.0378 b.0.1553

a.0.0324 b.0.1246

a.0.0324 b.0.1246

a.0.0080 b.0.1660

a.0.0449 b.0.1994

a.0.0092 b.0.3080

a.0.0431 b.0.2544

a.0.0192 b.0.1036

a.0.0238 b.0.0893

a.0.0118 b.0.8390

nested Anova p-value(1)

a.57.09 b.0.60 c.42.13 a.59.28 b.9.72 c.31.00 a.59.08 b.25.94 c.14.98

a.68.13 b.28.76 c.3.11

a.54.58 b.20.71 c.24.71 a.67.01 b.19.67 c.13.32 a.67.01 b.19.67 c.13.32 a.86.67 b.4.18 c.9.15

a.71.03 b.0.00 c.28.97 a.77.43 b.15.30 c.7.27 a.74.45 b.19.16 c.6.39 a.71.43 b.26.88 c.1.69 a.54.64 b.36.79 c.8.56 a.83.13 b.4.17 c.12.70

variance component(2) (%)

Photosynthesis

Photosynthesis

Defense response

-1.61

-1.64

+2.40

Photosynthesis

Signal transduction

+1.69

+1.62

Defense response

Photosynthesis

+1.77

+1.62

Photosynthesis

-1.83

Defense response

Photosynthesis

+2.29

+1.55

Photosynthesis

+1.63

Protein synthesis

Photosynthesis

+1.82

+1.52

Photosynthesis

functional category

-1.84

average ratio(3) T/WT

Table 2. Identification of Tomato and N. benthamiana Differentially Expressed Proteins by MALDI-TOF Peptide Mass Fingerprint (PMF), MALDI-TOF PSD or µLC-ESI-IT-MS/MS (MS/MS) Analysisa

research articles Di Carli et al.

research articles

Defense response

Defense response

Defense response

+1.94

+1.50

+1.94 a.0.0088 b.0.4922 48754180/Q0PWM4 MALDI-PSD-MS 3/24 Germin-like protein 8

N. sylvestris

a.0.0009 b.0.2955 48754180/Q0PWM4 MALDI-PSD-MS 3/24 Germin-like protein 7

N. sylvestris

a.0.0079 b.0.5854 31711507/Q7XZV3 MALDI-PSD-MS 4/30 N. tabacum 24 K germin-like protein 6

a (1) Nested ANOVA p-value: (a) comparison between transgenic and untransformed samples (transgene effect); (b) biological replicates nested within (a). (2) Proportion (%) of variance components: (a) transgene effect; (b) biological replicates nested within (a); (c) technical replicates. (3) Relative fold change was calculated with respect to the relative WT control group spot intensities.

Defense response +1.83 a.0.0013 b.0.6090 31711507/Q7XZV3 MALDI-PSD-MS 4/30 N. tabacum 24 K germin-like protein 5

organism protein name spot

Table 2. Continued

a.96.69 b.0.00 c.3.31 a.82.11 b.0.00 c.17.89 a.59.48 b.30.48 c.10.03 a.72.81 b.0.00 c.27.19

functional category code (gi/Swiss-Prot) identification method peptides/ coverage (%)

Nicotiana benthamiana

nested Anova p-value(1)

variance component(2) (%)

average ratio(3) T/WT

Leaf Proteome Analysis of Transgenic Plants

components in PCA was 26.6% for N. benthamiana analysis and 23.9% for tomato analysis. Protein samples belonging to untransformed and transgenic groups, in both analyses, appeared to be partially overlapped, indicating an undefined separation between the two groups. On the contrary, biological replicates of the same group were clearly distinct (Figure 3). The correlation between protein spots and class membership (transgenic or untransformed plant) was visualized by loading plot (Figure 3). Not significant discrimination and clustering of transgenic versus untransformed data sets were observed. Moreover, differentially expressed proteins, identified by univariate analysis (Table 2), are not significantly outlying and their distribution can not be correlated to classes. The results obtained by the explorative multivariate analysis combined with the univariate statistical test for these two transgenic plant models indicated that events associated to introduction of exogenous antibody genes did not imply significant proteomic modifications. This consideration is supported by the limited quantitative variations, within an average ratio below 2.4, observed for all differential protein spots. It has already demonstrated that the expression levels of many proteins in transgenic plants may fluctuate.14 In this work, we found that these variations were limited to single expression products rather than to entire metabolic pathways. Moreover, the proteins found as differentially expressed between transgenic plants and their untransformed counterparts are mainly involved in processes highly influenced by the environment, such as photosynthesis and defense response. Consequently, minimal environmental stimuli may cause the independent expression of these proteins.57,58 Thus, we can conclude that the proteomic differences observed between transgenic and control plants are negligible, defined and more likely due to physiological variations. Our results are consistent with data already published for genome transformation performed through Agrobacterium infection. In fact, with the exception of transgenic plants expressing molecules interfering with regulative processes, such as signaling molecules,19 unintended variation most often falls in the range of natural differences between landraces or varieties.13-17,59-61 In contrast, recent differential studies on transgenic plants obtained by particle bombardment procedures and their isogenic controls have evidenced that this gene manipulation approach determines more pronounced effects on the proteomic repertoire of the transformed species.62 We also demonstrated that the expression of the analyzed transgenes was below the detection sensitivity of the 2-DE system. In fact, none of the scFv antibodies was directly detected in N. benthamiana and tomato leaf proteomes. A weak signal indicative of their presence was measured in N. benthamiana and tomato extracts only by Western blotting (Figure 4). Southern blot analysis revealed a single copy of transgene for both plant models (data not shown). Moreover, the use of selfed generations (T4 and T3 for tomato and N. benthamiana, respectively), associated with seedling development on selective medium at each generation, assured the near-isogenicity of the transgenic lines used for the analysis. Despite the low expression levels observed (below 0.005% of total soluble protein), the amount of scFv(G4) antibody present in tomato leaves was sufficient to confer resistance to CMV (Figure 5A). Symptom development was followed daily. Ten days postinoculation (d.p.i.), first symptoms, consisting in mild systemic mosaic, appeared on untransformed tomato plants, and 18 dpi, all untransformed plants showed severe Journal of Proteome Research • Vol. 8, No. 2, 2009 845

research articles

Di Carli et al.

Figure 3. Principal component analysis. Proteins present in 70% of spot maps were visualized using the principal component score and loading plots. Left panels show the principal component scores, for the transgenic plants (light and dark green) and controls (orange and red) of N. benthamiana (A) and tomato (B), PC1 and PC2 explaining a cumulated 26.6% and 23.9% of all variation for N. benthamiana and tomato, respectively. The right panels show the correlation loading plots. Protein spots identified by univariate analysis (Table 2) are highlighted.

symptoms, consisting in strong systemic mosaic, stunting and leaf deformation. In parallel, eight transgenic plants remained symptomless even after a prolonged period of observation (60 d.p.i.), while only two showed a mild systemic mosaic 20 d.p.i. without developing worst symptomatology also at 60 d.p.i. (Figure 5B). These observations substantiate the effectiveness of plant protection strategy based on antibody. In fact, low amounts of this molecule in a plant tissue were sufficient to contrast viral replication and diffusion, without significant interference with general homeostasis, as revealed by proteome analysis. More generally, we can argue that for transgenic applications aimed to plant protection low expression levels represent an advantage. Ideally, one should be able to stably express in plant 846

Journal of Proteome Research • Vol. 8, No. 2, 2009

the minimum amount of antibody to obtain the protection effect, limiting in this way a possible perturbation of the natural expression pattern of the plant. Similar considerations can be done for the gene encoding kanamycin resistance (neomycin phosphotransferase II, NPTII). In our engineered plants, NPTII expression level was below the 2-DE detection sensitivity, although the presence of functional enzyme was evident as demonstrated by the seedling selection on kanamycin. Even in this case, low expression of reporter gene was sufficient to confer effective resistance and significant proteome alteration was not observed. We cannot a priori exclude effects on proteome when antibody and reporter gene product are highly accumulated in plant cells, for example, when plants are destined to be used

research articles

Leaf Proteome Analysis of Transgenic Plants

Figure 4. Western blot analysis of the transgenic plant extracts (T-1, T-2) used as biological replicates for DIGE analysis. Total proteins (15 µg) from each plant species were loaded onto the gels. Twenty nanograms of purified scFv was used as a reference (C+). (A) Expression of the scFv(G4) in tomato detected by an anti-FLAG antibody. (B) Expression of the scFv(B9) in N. benthamiana detected by the polyclonal antibody A318. Untransformed plant extracts (WT) used as negative control. The extimated expression levels of both scFv(G4) and scFv(B9) were in the range of 0.001-0.005% of total proteins.

gene transfer may induce unattended modifications in the expression pattern of transgenic plants. The elucidation of this point not only has a scientific relevance, but could also determine the acceptance of the biotechnological approach to the breeding of crops, influencing the policy that regulates plant cultivation and commercialization. The resolution of these problems is particularly relevant when transgenic technology represents by far the best solution. The effectiveness of antibody-mediated plant protection has been clearly demonstrated, but the “biosafety” of the resulting transgenic plants remains to be established.7-11 In such perspective, proteomic techniques represent a powerful tool not only to evaluate the differential expression between samples, but also to detect unpredictable post-translational modifications potentially occurring in transgenic plants.67 The expression at low levels of antiviral antibody in plant may represent a valid strategy to obtain self-protecting plants with due regard for human and environment safety. Moreover, the absence of significant perturbations in the expression pattern put forward antibody-expressing plants as a tool to investigate molecular mechanisms controlling plant-pathogen interactions. Abbreviations: Phe, phenol; TCA, trichloroacetic acid; ASB14, 3-[N,N-dimethyl(3-myristoylaminopropyl)ammonio]-propanesulfonate; 2D-DIGE, two-dimensional differential in gel electrophoresis; MS, mass spectrometry; PMF, peptide mass fingerprinting; scFv, single chain variable fragment; PVPP, polyvinilpolypirrolidone; NHS, N-hydroxysuccinimide; CMV, cucumber mosaic virus; TSWV, tomato spotted wilt virus.

Acknowledgment. We thank Dr. Gaetano Perrotta and Dr. Linda Bianco (ENEA Trisaia, Matera, Italy) for their support in protein identification, Dr. Marcello Donini (ENEA-Casaccia, Rome, Italy) for helpful comments on the manuscript and Dr. Bruno Bacher (GE Healthcare, Ravensburg) for his excellent support and effective troubleshooting of our DIGE system. This research was partially supported by grants from Italian National Research Council (AG.P04.015 and RSTL 862) to A.S. Supporting Information Available: Analysis of copy number of scFv(G4) and scFv(B9) transgenes in tomato and N. benthamiana genomes by Southern blotting. This material is available free of charge via the internet at http://pubs.acs.org. Figure 5. CMV resistance analysis of T4 transgenic tomato plants. (A) Phenotype observed in transgenic (T) and untransformed (WT) plants 2 months after CMV infection. (B) Number of untransformed and T4 transgenic plants showing typical systemic symptoms at successive days postinoculation (d.p.i.).

in molecular farming. Unfortunately, data on proteomic analysis of plant expressing high levels of antibodies are not available yet. Our work represents the first demonstration, based on proteome analysis, that engineered plant expressing low levels of antibodies can be safely and effectively used to obtain protection against viruses. Nevertheless, in light of wide difference of literature data,63-66 every new genetically modified plant has to be considered as unique and, therefore, analyzed as a result of an independent DNA integration event.

Concluding Remarks The concept of “substantial equivalence” has been widely discussed and analyzed to understand if current practices of

References (1) Jobling, S. A.; Jarman, C.; The, M. M.; Holmberg, N.; Blake, C.; Verhoeyen, M. E. Nat. Biotechnol. 2003, 21, 77–80. (2) Lobato, M. N.; Rabbits, T. H. Curr. Mol. Med. 2004, 4, 519–528. (3) Eeckhout, D.; De Clercq, A.; Van De Slijke, E.; Van Leene, J.; Stals, H.; Casteels, P.; Persiau, G.; Vercammen, D.; Van Breusegem, F.; Zabeau, M.; Inze´, D.; Jespers, L.; Depicker, A.; De Jaeger, G. A. J. Immunol. Methods 2004, 294, 181–187. (4) Conrad, U.; Manteuffel, R. Trends Plant Sci. 2001, 6, 399–402. (5) Boonrod, K.; Galetzka, D. D; Nagy, P.; Conrad, U.; Krczal, G. Nat. Biotechnol. 2004, 22, 856–862. (6) De Jaeger, G.; de Wilde, C.; Eeckhout, D.; Fiers, E.; Depicker, A. Plant Mol. Biol. 2000, 43, 419–428. (7) Tavladoraki, P.; Benvenuto, E.; Trinca, S.; De Martinis, D.; Cattaneo, A.; Galeffi, P. Nature 1993, 366, 469–472. (8) Voss, A.; Niersbach, M; Hain, R.; Hirsch, R.; Liao, Y. C.; Kreuzaler, F.; Fischer, R. Mol. Breeding 1995, 1, 39–50. (9) Prins, M.; Lohuis, D.; Schots, A.; Goldbach, R. J. Gen. Virol. 2005, 86, 2107–2113. (10) Villani, M. E.; Roggero, P.; Bitti, O.; Benvenuto, E.; Franconi, R. Plant Mol. Biol. 2005, 58, 305–316. (11) Nickel, H.; Kawchuk, L.; Twyman, R. M.; Zimmermann, S.; Junghans, H.; Winter, S.; Fischer, R.; Pru ¨ fer, D. Virus Res. 2008, 136, 140–145.

Journal of Proteome Research • Vol. 8, No. 2, 2009 847

research articles (12) Strange, R. N.; Scott, P. R. Annu. Rev. Phytopathol. 2005, 43, 83– 116. (13) Corpillo, D.; Gardini, G.; Vaira, A. M.; Basso, M.; Aime, S.; Accotto, G. P.; Fasano, M. Proteomics 2004, 4, 193–200. (14) Lehesranta, S. J; Davies, H. V.; Shepherd, V. T.; Nunan, N.; Mc Nicol, J. W.; Auriola, S.; Koistinen, K. M.; Suomalainen, S.; Kokko, H. I.; Karenlampi, S. O. Plant Physiol. 2005, 138, 1690–1699. (15) Ruebelt, M. C.; Leimgruber, N. K.; Lipp, M.; Reynolds, T. L.; Nemeth, M. A.; Astwood, J. D.; Engel, K. H.; Jany, K. D. J. Agric. Food Chem. 2006, 54, 2154–2161. (16) Batista, R.; Martins, I.; Jeno, P.; Ricardo, C. P.; Oliveira, M. M. Int. Arch. Allergy Immunol. 2007, 144, 29–38. (17) Bae, T. W.; Vanjildorj, E.; Song, S. Y.; Nishiguchi, S.; Yang, S. S.; Song, I. J; Chandrasekhar, T.; Kang, T. W.; Kim, J. I.; Koh, Y. J.; Park, S. Y.; Lee, J.; Lee, Y. E.; Ryu, K. H.; Riu, K. Z.; Song, P. S.; Lee, H. Y. J. Environ. Qual. 2008, 37, 207–218. (18) El Ouakfaoui, S.; Miki, B. Plant J. 2005, 41, 791–800. (19) Rocco, M.; Corrado, G.; Arena, S.; D’Ambrosio, C.; Tortiglione, C.; Sellaroli, S.; Marra, M.; Rao, R.; Scaloni, A. J. Proteomics 2008, 71, 176–185. (20) Franconi, R.; Roggero, P.; Pirazzi, P.; Arias, F. J.; Desiderio, A.; Bitti, O.; Pashkoulov, D.; Mattei, B.; Bracci, L.; Masenga, V.; Milne, R. G.; Benvenuto, E. Immunotechnology 1999, 4, 189–201. (21) Palukaitis, P.; Roossinck, M. J.; Dietzgen, R. G.; Francki, R. I. Adv. Virus Res. 1992, 41, 281–348. (22) Prins, M.; Goldbach, R. Trends Microbiol. 1998, 6, 31–35. (23) Hurkman, W. J.; Tanaka, C. K. Plant Physiol. 1986, 81, 802–806. (24) Wang, W.; Scali, M.; Vignani, R.; Spadafora, A.; Sensi, E.; Mazzuca, S.; Cresti, M. Electrophoresis 2003, 24, 2369–2375. (25) Saravanan, R. S.; Rose, J. K. C. Proteomics 2004, 4, 2522–2532. (26) Tsugita, A.; Kamo, M. Methods Mol. Biol. 1999, 112, 95–97. (27) Oakley, B. R.; Kirsch, D. R.; Morris, N. R. Anal. Biochem. 1980, 105, 361–363. (28) Shevchenko, A.; Wilm, M.; Vorm, O.; Mann, M. Anal. Chem. 1996, 68, 850–858. (29) Unlu ¨ , M.; Morgan, M. E.; Minden, J. S. Electrophoresis 1999, 18, 2071–2077. (30) Karp, N. A.; Lilley, K. S. Proteomics 2005, 5, 3105–3115. (31) Talamo, F.; D’Ambrosio, C.; Arena, S.; Del Vecchio, P.; Ledda, L.; Zehender, G.; Ferrara, L.; Scaloni, A. Proteomics 2003, 3, 440–460. (32) Arena, S.; D’Ambrosio, C.; Renzone, G.; Rullo, R.; Ledda, L.; Vitale, F.; Maglione, G.; Varcamonti, M.; Ferrara, L.; Scaloni, A. Proteomics 2006, 6, 181–192. (33) Rocco, M.; D’Ambrosio, C.; Arena, S.; Faurobert, M.; Scaloni, A.; Marra, M. Proteomics 2006, 6, 3781–3791. (34) Zhang, W. Z.; Chait, B. T. Anal. Chem. 2000, 72, 2482–2489. (35) Qian, W. J.; Liu, T.; Monroe, M. E.; Strittmatter, E. F.; Jacobs, J. M.; Kangas, L. J.; Petritis, K., II; Smith, R. D. J. Proteome Res. 2005, 4, 53–62. (36) Maserti, B. E.; Della Croce, C. M.; Luro, F.; Morillon, R.; Cini, M.; Caltavuturo, L. J. Chromatogr., B: Anal. Technol. Biomed. Life Sci. 2007, 849, 351–356. (37) Vaˆlcu, C. M.; Schlink, K. Proteomics 2006, 6, 4166–4175. (38) Song, J.; Braun, G.; Bevis, E.; Doncaster, K. Electrophoresis 2006, 27, 3144–3151.

848

Journal of Proteome Research • Vol. 8, No. 2, 2009

Di Carli et al. (39) Carpentier, S. C.; Witters, E.; Laukens, K.; Deckers, P.; Swennen, R.; Panis, B. Proteomics 2005, 5, 2497–2507. (40) Vincent, D.; Wheatley, M. D.; Cramer, G. R. Electrophoresis 2006, 27, 1853–1865. (41) Go´mez-Vidal, S.; Tena, M.; Lopez-Llorca, L. V.; Salinas, J. Electrophoresis 2008, 29, 448–456. (42) Gil-Agusti, M. T.; Campostrini, N.; Zolla, L.; Ciambella, C.; Invernizzi, C.; Righetti, P. G. Proteomics 2005, 5, 710–718. (43) Flengsrud, R.; Kobro, G. A. Anal. Biochem. 1989, 177, 33–36. (44) Laborde, B.; Moine-Ledoux, V.; Richard, T.; Saucier, C.; Dubourdieu, D.; Monti, J. P. J. Agric. Food Chem. 2006, 54, 4383–4389. (45) Rabilloud, T. Electrophoresis 1998, 19, 758–760. (46) Luche, S.; Santoni, V.; Rabilloud, T. Proteomics 2003, 3, 249–253. (47) Twine, S. M.; Mykytczuk, N. C.; Petit, M.; Tremblay, T. L.; Lanthier, P.; Conlan, J. W.; Kelly, J. F. J. Proteome Res. 2005, 4, 1848–1854. (48) Teixeira, D. M.; Pata˜o, R. F.; Coelho, A. V.; da Costa, C. T. J. Chromatogr., A 2006, 1103, 22–28. (49) Karp, N. A.; Spencer, M.; Lindsay, H.; O’Dell, K.; Lilley, K. S. J. Proteome Res. 2005, 4, 1867–1871. (50) Nelson, D. L.; Cox, M. M. Carbohydrate biosynthesis in plant and bacteria. In Lehninger Principles of Biochemistry, 4th ed.; W. H. Freeman and Company: New York, 2005, 751-786. (51) Nelson, D. L.; Cox, M. M. Oxidative phosphorylation and photophosphorylation In Lehninger Principles of Biochemistry, 4th ed.; W. H. Freeman and Company: New York, 2005; 690-750. (52) Kamiya, N.; Shen, J. R. Biochemistry 2000, 39, 14739–14744. (53) Schlesier, B.; Berna, A.; Bernier, F.; Mock, H. P. Phytochemistry 2004, 65, 1565–1574. (54) Rolland, N.; Janosi, L.; Block, M. A.; Shuda, M.; Teyssier, E.; Mie`ge, C.; Che´niclet, C.; Carde, J. P.; Kaji, A.; Joyard, J. Proc. Natl. Acad. Sci. U.S.A. 1999, 96, 5464–5469. (55) Johnson, P. R.; Ecker, J. R. Annu. Rev Genet. 1998, 32, 227–254. (56) Badger, M. R.; Price, G. D. Annu. Rev. Plant Physiol. Plant Mol. Biol. 1994, 45, 369–392. (57) Parry, M. A.; Keys, A. J.; Madgwick, P. J.; Carmo-Silva, A. E.; Andralojc, P. J. Exp. Bot. 2008, 59, 1569–1580. (58) Ichikawa, K.; Miyake, C.; Iwano, M.; Sekine, M.; Shinmyo, A.; Kato, K. Plant Cell Physiol. 2008, 49, 214–225. (59) Filipecki, M.; Malepszy, S. J. Appl. Genet. 2006, 47, 277–286. (60) Latham, J. R.; Wilson, A. K.; Steinbrecher, R. A. J. Biomed. Biotechnol. 2006, 2006, 1–7. (61) Ruebelt, M. C.; Lipp, M.; Reynolds, T. L.; Astwood, J. D.; Engel, K. H.; Jany, K. D. J. Agric. Food Chem. 2006, 54, 2162–2168. (62) Zolla, L.; Rinalducci, S.; Antonioli, P.; Righetti, P. G. J. Proteome Res. 2008, 7, 1850–1861. (63) Gelvin, S. B.; Kim, S. I. Biochim. Biophys. Acta 2007, 1769, 410– 421. (64) Filipecki, M.; Malepszy, S. Appl. Genet. 2006, 47, 277–286. (65) Lorence, A.; Verpoorte, R. Methods Mol. Biol. 2004, 267, 329–350. (66) Kohli, A.; Twyman, R. M.; Abranches, R.; Wegel, E.; Stoger, E.; Christou, P. Plant Mol. Biol. 2003, 52, 247–258. (67) Cellini, F.; Chesson, A.; Colquhoun, I.; Constable, A.; Davies, H. V.; Engel, K. H.; Gatehouse, A. M.; Ka¨renlampi, S.; Kok, E. J.; Leguay, J. J.; Lehesranta, S.; Noteborn, H. P.; Pedersen, J.; Smith, M. Food Chem. Toxicol. 2004, 42, 1089–1125.

PR800359D