Targeted Data Acquisition for Improved Reproducibility and Robustness of Proteomic Mass Spectrometry Assays

Quantitative mass spectrometry-based proteomic assays often suffer from a lack of robustness and reproducibility. We here describe a targeted mass spectrometric data acquisition strategy for affinity enriched subproteomes—in our case the kinome—that enables a substantially improved reproducibility of detection, and improved quantification via isobaric tags. Inclusion mass lists containing m/z, charge state, and retention time were created based on a set of 80 shotgun-type experiments performed under identical experimental conditions. For each target protein, peptides were selected according to their frequency of observation and isobaric tag for relative and absolute quantitation (iTRAQ) reporter ion quality. Retention times of selected peptides were aligned using similarity driven pairwise alignment strategy yielding <1 min standard deviation for 4 h gradients. Multiple fragmentation of the same peptides resulted in better statistics and more precise reporter ion based quantification without any loss in coverage. Overall, 24% more target proteins were quantified using the targeted data acquisition approach, and precision of quantification improved by >1.5-fold. We also show that a combination of higher energy collisional dissociation (HCD) with collisional induced dissociation (CID) outperformed pulsed-Q-dissociation (PQD) on the OrbitrapXL. With the CID/HCD based targeted data acquisition approach 10% more quantifiable target proteins were identified and a 2-fold increase in quantification precision was achieved. We have observed excellent reproducibility between different instruments, underlining the robustness of the approach.

Graphical AbstractA targeted mass spectrometric data acquisition strategy is presented for affinity enriched subproteomes that enables a substantially improved reproducibility of detection, and improved quantification via isobaric tags.Figure optionsDownload high-quality image (151 K)Download as PowerPoint slide