MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes - PubMed (original) (raw)

. 2014 Jul 15;86(14):7150-8.

doi: 10.1021/ac502040v. Epub 2014 Jul 3.

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MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes

Graeme C McAlister et al. Anal Chem. 2014.

Abstract

Multiplexed quantitation via isobaric chemical tags (e.g., tandem mass tags (TMT) and isobaric tags for relative and absolute quantitation (iTRAQ)) has the potential to revolutionize quantitative proteomics. However, until recently the utility of these tags was questionable due to reporter ion ratio distortion resulting from fragmentation of coisolated interfering species. These interfering signals can be negated through additional gas-phase manipulations (e.g., MS/MS/MS (MS3) and proton-transfer reactions (PTR)). These methods, however, have a significant sensitivity penalty. Using isolation waveforms with multiple frequency notches (i.e., synchronous precursor selection, SPS), we coisolated and cofragmented multiple MS2 fragment ions, thereby increasing the number of reporter ions in the MS3 spectrum 10-fold over the standard MS3 method (i.e., MultiNotch MS3). By increasing the reporter ion signals, this method improves the dynamic range of reporter ion quantitation, reduces reporter ion signal variance, and ultimately produces more high-quality quantitative measurements. To demonstrate utility, we analyzed biological triplicates of eight colon cancer cell lines using the MultiNotch MS3 method. Across all the replicates we quantified 8,378 proteins in union and 6,168 proteins in common. Taking into account that each of these quantified proteins contains eight distinct cell-line measurements, this data set encompasses 174,704 quantitative ratios each measured in triplicate across the biological replicates. Herein, we demonstrate that the MultiNotch MS3 method uniquely combines multiplexing capacity with quantitative sensitivity and accuracy, drastically increasing the informational value obtainable from proteomic experiments.

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Figures

Figure 1

Figure 1

(A) Yeast was digested with LysC and labeled with TMT (10:4:1:1:4:10). That sample was combined with a TMT labeled HeLa sample (1:1:1:0:0:0). (B) A TMT-labeled, yeast peptide (NAAWLVFANK) was interrogated in back-to-back scans using (left spectrum) MS2, where the MS1 precursor was fragmented using HCD. (Middle) MS3, where the MS1 precursor was fragmented with CID, and a single MS2 product ion was isolated and fragmented using HCD. And, (right) MultiNotch MS3, where multiple MS2 product ions were simultaneously isolated and fragmented. (C) The precursor populations of the standard and MultiNotch MS3 scans used to generate the reporters above (middle and bottom spectra, respectively). For reference, we also include the ITMS2 spectrum prior to MS3 precursor isolation (top).

Figure 2

Figure 2

(A) While infusing an ion with an m/z ratio of 989, we varied the isolation notch width and location. We recorded the isolation efficiency as a function of those parameters. This analysis was repeated for the series of ions, and the resulting data set was fitted using linear regression. (B) During a 90 min MultiNotch LC–MS2/MS3 analysis of the yeast/human two-proteome sample, we isolated the MS3 precursor population without any subsequent fragmentation. We then calculated the fraction of MS2 ions retained in the MS3 precursor population.

Figure 3

Figure 3

TMT-labeled, two-proteome mixture (yeast/human) was analyzed by LC–MS2, standard MS3, and MultiNotch MS3. (A) We distributed the quantitative spectra by the number of TMT reporter ions. (B) We also distributed the quantitative spectra using three select TMT ratios (channels 126:128, 127:128, and 128:129, i.e., 10:1, 4:1, and 1:1). The expected ratios are denoted using the dashed lines.

Figure 4

Figure 4

(A) Eight colorectal cancer cell lines were grown in biological triplicate. Each replicate was digested with LysC, labeled with TMT, fractionated, and analyzed using MultiNotch MS3 (3-h LC gradients). (B) All protein ratios from replicates 1 and 2 were plotted against each other. In total this represents 172 704 quantitative ratios. (C) Across the three replicate we performed a one way ANOVA with Welch’s correction. (D) We highlighted the protein expression profile for two commonly studied proteins, EGFR and MSH6, and (E) the WT and mutant (G13D) forms of KRAS.

Figure 5

Figure 5

(A) Number of members of the core pathways annotated by Vogelstein et al. showing significantly different expression. (B) The lists of proteins with altered expression were mapped on to the Reactome Pathway Database and clustered into graph modules. (C) Principal component analysis of the quantified proteome shows that PC1 distinguishes hypermutated from nonhypermutated cell lines. (D) The top contributors to PC1 among the Vogelstein gene set. SMAD4 and IDH2 are preferentially expressed in the hypermutated and nonhypermutated lines, respectively. (E,F) The Vogelstein gene set proteins with expression profiles most similar to SMAD4 (E) and IDH2 (F).

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