To further improve peptide mapping results, the 11-14 trendline was applied to the previously obtained XylE, SMO, MsbA and SecYEG multi-pass peptide mapping data and compared to auto-calculated trendlines (Figure ). Application of 11-14 trendline increased the number of peptide identifications by 42, 17, 33, and 28% for SMO, XylE, MsbA and SecYEG, respectively, thereby including a total of 170 peptides which would otherwise have been omitted using auto-calculated trendlines. Thus, these results demonstrate the potential for manually specified drift FWHM trendlines to improve cIM multi-pass peptide mapping results. Whilst MsbA and SecYEG peptide identifications were still lower relative to cIM 1-pass, SMO and XylE exhibited peptide identification numbers comparable to cyclic 1-pass. This increase in peptide identification also translated into an increase in coverage and redundancy for all assessed targets (Table ); apart from MsbA which only saw increase in redundancy.