The peptide library workflow (Fig.1A) - The initial DDA peptide library consists of peptides containing leucines within first/last five residues [7 (link)]. The library is refined by ranking the peptides based on their monoisotopic peak XIC intensities. The top-ranked peptides are then reanalyzed using PRM (R=17.5K) to classify peptides considering the quality and intensities of their leucine-containing fragment ions. The final candidate peptide library comprises the inclusion list for PRM at the higher resolutions settings (e.g. R=140K) in order to detect D3-Leu tracer.
Detection and quantification of light and heavy target ions (Fig. 1B) - XPI is an automated pipeline for, but not limited to, PRM-dependent D3-Leu tracer enrichment in clinically derived HDL apoA-I. From the peptide library, XPI generates all the possible leucine-containing fragment ions including light (M0) and heavy (2HM3) by considering the mass shift (3.01883025 Da) induced by D3-Leu labeling. XPI extracts data from mzML files and carries out pre-processing steps including intensity centroiding, background subtraction, and noise removal using Pymzml. With the collected data, XPI finds target fragment ions by matching the scan number, the Δmass window (=|theoretical mass – observed mass|) and the RT range. In order to accommodate the RT shift incurred by the deuterium, and to identify the low abundant 2HM3 peak efficiently, XPI performs RT refinement steps by reference to M0 ion detection since the M0 peaks are readily identified. This extra refinement step excludes non-specific peaks that appear in a larger RT window, and uses the LOWESS algorithm, the local maxima and minima method, to do so. XPI provides nine methods for the quantification: the sum, max, top3, median, average, qsum, qtop3, qmax and qaverage (Fig. 1B). The sum, max, top3, median and average options calculate a representative value from the whole set of collected PRM intensities, while the others, qsum, qtop3, qmax and qaverage, calculate the intensity from the second and third quartiles. XPI finally calculates ratios between M0 and 2HM3 ions in two ways: 1) heavy/light or light/heavy, or 2) enrichment (Heavy/(Heavy+Light)).
Validation and visualization (Fig. 1C) - Since XPI has nine options for quantification, XPI shows which method fits best to a given dataset by drawing box-plots based on the R2 between the intended and observed ratio (Fig. 1C). When possible, we recommend using standard mixtures to evaluate the best quantification method. The user can choose the best quantification method by comparing the average or median R2 of the standard data. XPI provides a standard curve plot with a regression line to check the linearity of the standard data (Fig. 1C). XPI also provides the summed M0 ion intensity versus accumulated ratio plots for filtering/excluding low and outlier enrichment PRM ions (Supplemental Information). XPI draws various plots at the protein and peptide level. Two- and three-dimensional mass profiles with a color scheme using the Δmass are supplied for visualization and validation of the target ion identification if needed. Since XPI uses Python scripts, it is executable regardless of the operating system as long as Python 3 and the required packages are installed. XPI can process 7 mzML files (~1.6 gigabytes) within 12 minutes with Intel Core i7 (2.6 GHz), 16Gb memory and OS X 10.11.2 environment. XPI is downloadable at http://cics.bwh.harvard.edu/software.