Using ion purity scores for enhancing quantitative accuracy and precision in complex proteomics samples

Abstract

To accurately determine the quantitative change of peptides and proteins in complex proteomics samples requires knowledge of how well each ion has been measured. The precision of each ions' calculated area is predicated on how uniquely it occupies its own space in m/z and elution time. Given an initial assumption that prior to the addition of the "heavy" label, all other ion detections are unique, which is arguably untrue, an initial attempt at quantifying the pervasiveness of ion interference events in a representative binary SILAC experiment was made by comparing the centered m/z and retention time of the ion detections from the "light" variant to its "heavy" companion. Ion interference rates were determined for LC-MS data acquired at mass resolving powers of 20 and 40 K with and without ion mobility separation activated. An ion interference event was recorded, if present in the companion dataset was an ion within ± its Δ mass at half-height, ±15 s of its apex retention time and if utilized by ±1 drift bin. Data are presented illustrating a definitive decrease in the frequency of ion interference events with each additional increase in selectivity of the analytical workflow. Regardless of whether the quantitative experiment is a composite of labeled samples or label free, how well each ion is measured can be determined given knowledge of the instruments mass resolving power across the entire m/z scale and the ion detection algorithm reporting both the centered m/z and Δ mass at half-height for each detected ion. Given these measurements, an effective resolution can be calculated and compared with the expected instrument performance value providing a purity score for the calculated ions' area based on mass resolution. Similarly, chromatographic and drift purity scores can be calculated. In these instances, the error associated to an ions' calculated peak area is estimated by examining the variation in each measured width to that of their respective experimental median. Detail will be disclosed as to how a final ion purity score was established, providing a first measure of how accurately each ions' area was determined as well as how precise the calculated quantitative change between labeled or unlabelled pairs were determined. Presented is how common ion interference events are in quantitative proteomics LC-MS experiments and how ion purity filters can be utilized to overcome and address them, providing ultimately more accurate and precise quantification results across a wider dynamic range.

The One Hour Yeast Proteome

“…low signal-to-noise, S/N), even fewer unique peptide identifications were achieved at higher MS 2 acquisition rates. Other studies using TOF technologies report similar results (27, 28). For maximal proteome depth, we conclude that increased scan speed must not come at the cost of reduced spectral quality.…”

Correlated S-palmitoylation profiling of Snail-induced epithelial to mesenchymal transition

“…With increased sampling, the data presented sufficient measurements to apply a statistical quartile test to eliminate outliers and overcome interference-dependent effects on SILAC accuracy. Nonetheless, the SILAC workflow doubles the ion complexity and reduces the total number of identifications 33 . Despite this loss, the overall quantitative accuracy provides low coefficients of variation (~20%) for precise quantitation.…”

Review on Ion Mobility Spectrometry. Part 2: hyphenated methods and effects of experimental parameters

“…LC-TWIMS-MS is being widely used for proteomic analysis 77 since Waters corp. launched the Synapt G2 instrument 26 series where TOF mass spectrometry is combined with TWIMS (travelling wave ion mobility separation) 78, 79 . An additional benefit of IMS is increased accuracy of quantitation for lower abundance peptides and a higher dynamic range for peptide detection 80–82 . Valentine et al .…”