Differential Mass Spectrometry:  A Label-Free LC−MS Method for Finding Significant Differences in Complex Peptide and Protein Mixtures

Abstract

Efficiently identifying and quantifying disease- or treatment-related changes in the abundance of proteins is an important area of research for the pharmaceutical industry. Here we describe an automated, label-free method for finding differences in complex mixtures using complete LC-MS data sets, rather than subsets of extracted peaks or features. The method selectively finds statistically significant differences in the intensity of both high-abundance and low-abundance ions, accounting for the variability of measured intensities and the fact that true differences will persist in time. The method was used to compare two complex peptide mixtures with known peptide differences. This controlled experiment allowed us to assess the validity of each difference found and so to analyze the method's sensitivity and specificity. The method detects both presence versus absence and a 2-fold change in peptide concentration near the limit of detection of the instrument used, where chromatographic peaks may not be sufficiently well defined to be detected in individual samples. The method is more sensitive and gives fewer false positives than subtractive methods that ignore signal variability. Differential mass spectrometry combined with targeted MS/MS analysis of only identified differences may save both computation time and human effort compared to shotgun proteomics approaches.

Quantitative strategies to fuel the merger of discovery and hypothesis-driven shotgun proteomics

“…In the first group, spectral features (typically isotopic clusters indicating a peptide) are detected first and then statistically compared [25][26][27][28][29]. Alternatively, the second group applies statistics first so that only differential features are detected from the extracted ion chromatograms [30][31][32][33]. Both computational methods rely on the ability to chromatographically align multiple LC-MS runs from different samples, identify differences between the samples and determine the magnitude of the change ( Figure 5).…”

Quantitative analysis of complex peptide mixtures using FTMS and differential mass spectrometry

“…Differential mass spectrometry was performed as previously© reported© [14].© Measured© (time,© m/z,© intensity) points were regularized onto a standard (time, m/z) grid,© with© spacing© of 3 s in time© and© 0.01© m/z units© [14]. A t-test was performed to produce a single p value describing the extent to which mean intensities differ between the two conditions at each elution time and m/z.…”

“…Had we compared data from an individual LC-MS acquisition for each condition (Mixture A and Mixture B) and used a subtraction method to look for differences in abundance, almost all of the observed ion species would have been found to have different abundances. The majority of these differences could be considered false positives because they arise due to variability in peak intensity measurements rather than from the differentially-spiked©peptides©in©this©experiment.©dMS© [14] minimizes these false positives because it considers only peptide changes that are statistically significant between two or more conditions. In other experiments, biological variability among different subjects as well as technical variability in sample preparation and MS measurement must be taken into consideration in the statistical analysis of the MS signals.…”

“…In 2004, we reported a method termed differential mass spectrometry (dMS) [14], which can identify statistically significant differences between two or more LC-MS datasets. This method was demonstrated using standard protein digests; a 2-fold change in peptide abundance was found in data collected by an ion trap instrument (LCQ) [14]. In this application note, we describe a well-controlled experiment to evaluate the ability of dMS to analyze Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS, or FTMS) datasets.…”

Proteomics in human cancer research

“…Also, it was shown that ICAT was an excellent tool for discovery of proteases making it useful in degradomic research [37]. Recently, a new version of the ICAT method was investigated [38]. The advantage of this new strategy is the use of 13 C as the heavy version and 12 C as the light version to eliminate the slight delay in retention time of peptides treated with the light tag that occurs with hydrogen and deuterium.…”