Soybean root tip proteins under flooding with ABA

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).