an Jose, CA, USA). Ion optics were tuned using Angiotensin at 500 fmol/μL [50% (v/v) methanol, 1.0% (v/v) formic acid], and capillary temperature step optimized for peptide desolvation under normal LC workflows with purified BSA peptides (Michrom Bioresources, Inc., Auburn, CA, USA) using the gradient described below. Sample handling and LC separations for LC-SRM analyses were all performed using an Eksigent nanoLC ultra 1D plus [0.1% (v/v) formic acid in MilliQ water (18.2 MΩ) as solvent A, and 99.9% (v/v) ACN, 0.1% (v/v) formic acid as solvent B]. Peptides were trapped and washed on a C8 Cap Trap (Michrom Bioresources, Inc., Auburn, CA, USA) using solvent A at 5 μL/min for 2 min. Peptide chromatography used a 25 min non-linear gradient from 2 to 60% over 12.5 min, a washing step, and a 9 min equilibration step at 2% solvent B all using a flow rate of 500 nL/min. AQUA™ peptides used were designed and described in Houston et al. (2010). All are listed in Table A1 in Appendix. Precursor and product ions, ion types, and charge states are also listed in Table A2 in Appendix. The development of an optimal LC-MRM analysis, including most abundant precursor and product ion selection and collision energy optimization, was aided by iterative analysis of soybean tryptic digests using Pinpoint 1.1 (Thermo Fisher Scientific, 2011). Peptide sequences were entered into Pinpoint manually and the recommended workflows for precursor/product ion selection were followed. When necessary, precursor and product ions were chosen manually by direct infusion of peptides at 500 fmol/μL in 50% (v/v) ACN, 1.0% (v/v) formic acid using product ion scans from the most intense precursor. At least five transitions were chosen for each peptide. Cycle times and chromatography were optimized to ensure 10 measurements for each transition across the chromatographic peak profile.
Selected Reaction Monitoring results were provided by LCQuan 2.6 (Thermo Fisher Scientific, 2009). Peak detection and integration were performed using the ICIS algorithm with five points of smoothing, and a baseline window of 20. All other values were left as default. Results were exported from LCQuan as tab delimited text files which were imported into MS-Excel (2007) for calculations. Response ratios (unlabeled peptide area/labeled peptide area) were multiplied by the mole amount of each AQUA™ present per microgram of sample to obtain endogenous mole quantities. Endogenous mole quantities were multiplied by the molecular weight of the protein (Table A1 in Appendix), and grams per microgram was converted to microgram protein per milligram of digest by dimensional analysis.
Linear ranges of detection for all unlabeled peptides of interest were determined with a twofold dilution series of soybean total protein digest using 0.5 M urea buffer (similar to final digest buffer) and AQUA™ internal standards at 100 fmol on column. Injection amounts for the dilution series were from 2 μg down to 125 ng on column. Using the peptide area ratios (unlabeled/labeled) attained from this initial standard curve, linear ranges were determined for each peptide by manually inspecting the response ratio changes between dilutions, using a twofold change in area ratio as an indicator of a perfect response between two dilutions. Slight deviations from this ideality were accounted for by ensuring the internal standard peptide was within 10-fold of the endogenous peptide signal (response of 10–0.1) for all peptides. Final quantitative analyses were performed with labeled standards at these concentrations. In most cases 100 fmol/μg of soy digest was appropriate. AQUA™ internal standard peptides were also analyzed for their linearity of response using a twofold dilution series from 2 pmol/injection down to 0.061 fmol/injection. This dilution was performed using total soy protein digest material at 200 ng/μL (typical endogenous peptide concentrations). All peptides, endogenous and AQUA™, were used within their linear ranges.
Technical variation was quantified by coefficient of variation (%CV). The %CV for a sin