apid turnover, some assumptions had to be made. Firstly, we assumed that replicate injections could be forgone if replicate extractions were performed for each sample. The experimental design employed replicate extractions to assess variation at the protein extraction level. Assuming that the variation at the extraction level was greater than the variation at the injection level (largely controlled for with AQUA™ peptides, and previously assessed at 3–5%), we were satisfied that we were accounting for the majority of experimental variation by comparing replicate extractions without replicate injections. Secondly, we assumed that single point quantification can accurately assess peptide abundance. For our quantification experiments, protein quantities were calculated based on a single simultaneous measurement of both AQUA™ and endogenous peptide intensities. Ideally, the analysis would be repeated for each sample using a dilution strategy, where the AQUA™ peptide or the endogenous matrix is diluted and subsequent measurements are made of these samples to assess the linearity of response. To avoid this necessity, we assessed the linearity of our endogenous peptides with a twofold dilution series from 2.0 to 0.0625 μg/injection (2.0 μg maximum capacity peptide traps) of a Williams 82 soybean protein sample using a constant amount of AQUA™ peptide for all dilutions. The ratio of endogenous: AQUA™ peak areas were used to assess linearity. The scatter plot of “measured fold change” versus “actual fold change” shows slopes that on average are within 5.70 ± 3.82% of the optimal value of 1, with an average R2 value of 0.9969 ± 0.0042 (Figure A1 in Appendix). With this information in mind, we decided to use 1 μg injections allowing for at least a twofold increase, and a 16-fold decrease in any of the endogenous peptides without extrapolating past the linear range (2.0–0.0625 μg). To maximize the efficacy of our internal standards, we calibrated the amount of each AQUA™ to approximately match the amount of the endogenous analyte. This relationship was not maintained for two of the peptide analytes (Glycinin 1 and Glycinin 2) which were present in such large quantities that matching the signal would require 3 and 2 pmol respectively per injection. For these peptides, a 10:1 (endogenous: AQUA™) ratio was attained, which was still within the pre-determined linear range.
Lastly, our strategy assumed that monitoring one proteotypic peptide is sufficient to represent the whole protein. This assumption is mostly an assumption of complete protein digestion. Although digestion conditions were monitored by Coomassie SDS-PAGE to ensure all proteins were digested to peptides, this approach is not as quantitative as MRM. Ideally, if a protein is subjected to proteolysis using trypsin, the entire protein will be reduced to peptides by cleavage at all Lys and Arg residues. However, this is not necessarily the case. Studies have shown that a number of exceptions exist, which prevent cleavage, or prevent complete cleavage. For example, trypsin was perceived to not cleave at a Lys or Arg when a Pro immediately follows it (Keil, 1992). This rule has been questioned recently. A group using peptide identification data from both low and high mass accuracy proteomics experiments have shown that the prevalence of cuts at the Lys or Arg residues preceding Pro indicates they are not preferred by trypsin but are in fact possible (Rodriguez et al., 2007). The presence of a double cleavage site can also cause issues. If two Lys or Arg residues are immediately adjacent or within a few residues, there is the possibility of incomplete cleavage at any one of the residues. Furthermore, accuracy of quantification is affected by chemistry. Depending on when the internal standards are added (e.g., immediately before, versus immediately after the digestion step), chemical modifications could alter the peptide pool, potentially altering the mass of the endogenous peptide and thereby preventing its measurement during MRM. In our experience, peptide loss due to breakdown 