Dataset Information

Proteomic Change Associated with Flooding Injury of Soybean

ABSTRACT: Flooding injury is one of the abiotic constraints on soybean growth. An experimental system established for evaluating flooding injury in soybean seedlings indicated that the degree of injury is dependent on seedling density in floodwater. To understand the molecular mechanism responsible for the injury, proteomic alterations in soybean seedlings that correlated with severity of stress were analyzed using label-free quantitative proteomics. Two-day-old soybeans, seedlings flooded for 2 days and hypocotyls of seedlings grown for 3 days after flooding were analyzed. The radicles of soybean seedlings were separated to root tips (RT), roots without tip (RwoT) and hypocotyls (Hypo). Protein was extracted from these organs by TCA/Acetone method. Protein samples were cleaned up with chloroform/methanol method and then subjected to in-solution digestion with trypsin. Resulting peptides were analyzed on a nanospray LTQ XL Orbitrap MS (Thermo Fisher Scientific) operated in data-dependent acquisition mode with the installed Xcalibur software (version 2.0.7, Thermo Fisher Scientific). Using an Ultimate 3,000 nanoLC system (Dionex), peptides in 0.1% formic acid were loaded onto a C18 PepMap trap column (300 µm ID × 5 mm, Dionex). The peptides were eluted from the trap column and their separation and spraying were done using 0.1% formic acid in acetonitrile at a flow rate of 200 nL/min on a C18 Tip column (75 µm 1D × 120 mm, nano HPLC capillary column, NTTC-360/75-3, Nikkyo Technos) with a spray voltage of 1.5 kV. The elution was done with a linear acetonitrile gradient 8-30% in 120 min for gel free proteomics in 0.1% formic acid. Full-scan mass spectra were acquired in the Orbitrap over a mass range of 400-1,500 m/z with a resolution of 30,000. A lock mass function was used to obtain high mass accuracy. The top 6 most intense precursor ions were selected for collision-induced fragmentation in the linear ion trap at normalized collision energy of 35%. Dynamic exclusion was employed within 90 sec to prevent repetitive selection of peptides.Identification of proteins were performed by Mascot search engine (version 2.3.0.2, Matrix Science) using soybean peptide database (55,787 sequences) obtained from the soybean genome database (Phytozome version 8.0)and a common contaminants database (262 sequences). Parameters used in Mascot searches were follows: Carbamidomethylation of cysteine was set as a fixed modification, and oxidation of methionine was set as a variable modification. Trypsin was specified as the proteolytic enzyme and one missed cleavage was allowed. Peptide mass tolerance was set at 5 ppm, fragment mass tolerance was set at 0.5 Da, and peptide charge was set at +2, +3, and +4. Automatic decoy database search was performed in the search. Mascot results were filtered with Mascot percolator to improve accuracy and sensitivity in the peptide identification. False discovery rates for peptide identification of all searches were less than 1.0%. The Mascot results were used for differential analysis using SIEVE software (version 1.3, Thermo Fisher Scientific)

INSTRUMENT(S): LTQ Orbitrap, instrument model

ORGANISM(S): Glycine Max

TISSUE(S): Plant Cell, Hypocotyl, Root, Root Tip

SUBMITTER: Yohei Nanjo

PROVIDER: PXD000201 | Pride | 2013-12-10

REPOSITORIES: Pride

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Publications

Identification of indicator proteins associated with flooding injury in soybean seedlings using label-free quantitative proteomics.

Nanjo Yohei Y Nakamura Takuji T Komatsu Setsuko S

Journal of proteome research 20130723 11

Flooding injury is one of the abiotic constraints on soybean growth. An experimental system established for evaluating flooding injury in soybean seedlings indicated that the degree of injury is dependent on seedling density in floodwater. Dissolved oxygen levels in the floodwater were decreased by the seedlings and correlated with the degree of injury. To understand the molecular mechanism responsible for the injury, proteomic alterations in soybean seedlings that correlated with severity of st ...[more]

PMID: 23659366

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Project description:Flooding is a serious problem for soybean cultivation because it markedly reduces growth. We found that treatment with ABA enhances survival ratio of soybean under flooding stress. To investigate the role of ABA in soybean under flooding stress, proteomic changes were analyzed. Total protein and nuclear protein fractions from root tips of soybean seedlings that treated with flooding or flooding with ABA were analyzed. Protein samples were cleaned up with chloroform/methanol method and then subjected to in-solution digestion with trypsin and lysyl endopeptidase. Resulting peptides were analyzed on a nanospray LTQ XL Orbitrap MS (Thermo Fisher Scientific) operated in data-dependent acquisition mode with the installed Xcalibur software (version 2.0.7, Thermo Fisher Scientific). Using an Ultimate 3,000 nanoLC system (Dionex), peptides in 0.1% formic acid were loaded onto a C18 PepMap trap column (300 µm ID × 5 mm, Dionex). The peptides were eluted from the trap column and their separation and spraying were done using 0.1% formic acid in acetonitrile at a flow rate of 200 nL/min on a C18 Tip column (75 µm 1D × 120 mm, nano HPLC capillary column, NTTC-360/75-3, Nikkyo Technos) with a spray voltage of 1.5 kV. The elution was done with a linear acetonitrile gradient 8-30% in 120 min for gel free proteomics in 0.1% formic acid. Full-scan mass spectra were acquired in the Orbitrap over a mass range of 400-1,500 m/z with a resolution of 30,000. A lock mass function was used to obtain high mass accuracy. The top 10 most intense precursor ions were selected for collision-induced fragmentation in the linear ion trap at normalized collision energy of 35%. Dynamic exclusion was employed within 90 sec to prevent repetitive selection of peptides.Identification of proteins were performed by Mascot search engine (version 2.3.0.2, Matrix Science) using soybean peptide database (55,787 sequences) obtained from the soybean genome database (Phytozome version 8.0)and a common contaminants database (262 sequences). Parameters used in Mascot searches were follows: Carbamidomethylation of cysteine was set as a fixed modification, and oxidation of methionine was set as a variable modification. Trypsin was specified as the proteolytic enzyme and one missed cleavage was allowed. Peptide mass tolerance was set at 5 ppm, fragment mass tolerance was set at 0.5 Da, and peptide charge was set at +2, +3, and +4. Automatic decoy database search was performed in the search. Mascot results were filtered with Mascot percolator to improve accuracy and sensitivity in the peptide identification. False discovery rates for peptide identification of all searches were less than 1.0%. The Mascot results were used for differential analysis using SIEVE software (version 2.0, Thermo Fisher Scientific).

Project description:Abstract still has to be written. The obtained peptide mixtures were introduced into an LC-MS/MS system, the Ultimate 3000 (Dionex, Amsterdam, The Netherlands) in-line connected to an LTQ Orbitrap XL mass spectrometer (Thermo Fisher Scientific, Bremen, Germany). Samples were first loaded on a trapping column (made in-house, 100 um internal diameter (I.D.) x 20 mm, 5 um beads C18 Reprosil-HD, Dr. Maisch). After back-flushing from the trapping column, the sample was loaded on a reverse-phase column (made in-house, 75 um I.D. x 150 mm, 5 um beads C18 Reprosil-HD, Dr. Maisch). Peptides were loaded with solvent A (0.1% trifluoroacetic acid, 2% acetonitrile), and were separated with a linear gradient from 2% solvent A' (0.05% formic acid) to 55% solvent B' (0.05% formic acid and 80% acetonitrile) at a flow rate of 300 nL/min followed by a wash reaching 100% solvent B'. The mass spectrometer was operated in data-dependent mode, automatically switching between MS and MS/MS acquisition for the six most abundant peaks in a given MS spectrum. Full scan MS spectra were acquired in the Orbitrap at a target value of 1E6 with a resolution of 60,000. The six most intense ions were then isolated for fragmentation in the linear ion trap, with a dynamic exclusion of 60 s. Peptides were fragmented after filling the ion trap at a target value of 1E4 ion counts. From the MS/MS data in each LC run, Mascot Generic Files were created using the Mascot Distiller software (version 2.3.01, Matrix Science). While generating these peak lists, grouping of spectra was allowed with a maximum intermediate retention time of 30 s and a maximum intermediate scan count of 5 was used where possible. Grouping was done with 0.005 Da precursor tolerance. A peak list was only generated when the MS/MS spectrum contained more than 10 peaks. There was no de-isotoping and the relative signal to noise limit was set at 2. These peak lists were then searched with the Mascot search engine (Matrix Science) using the Mascot Daemon interface (version 2.3, Matrix Science). Spectra were searched against the human (H. sapiens) Swiss-Prot database. 13C2D3-acetylation of lysine side-chains, carbamidomethylation of cysteine and methionine oxidation to methionine-sulfoxide were set as fixed modifications for the N-terminal COFRADIC analyses. Variable modifications were 13C2D3-acetylation and acetylation of protein N-termini. Pyroglutamate formation of N-terminal glutamine was additionally set as a variable modification. Mass tolerance on precursor ions was set to 10 ppm (with Mascot's C13 option set to 1) and on fragment ions to 0.5 Da. Endoproteinase semi-Arg-C/P (Arg-C specificity with arginine-proline cleavage allowed) was set as enzyme allowing no missed cleavages. The peptide charge was set to 1+, 2+, 3+ and instrument setting was put to ESI-TRAP. Only peptides that were ranked one and scored above the threshold score, set at 99% confidence, were withheld. Quantification of the degree of Nt-Acetylation was performed as described previously (1). All data management was done in ms_lims (2).

Dataset Information

Proteomic Change Associated with Flooding Injury of Soybean

Publications

Identification of indicator proteins associated with flooding injury in soybean seedlings using label-free quantitative proteomics.

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