Abstract
Ion mobility brings an additional dimension of separation to LC-MS, improving identification of peptides and proteins in complex mixtures. A recently introduced timsTOF mass spectrometer (Bruker) couples trapped ion mobility separation to TOF mass analysis. With the parallel accumulation serial fragmentation (PASEF) method, the timsTOF platform achieves promising results, yet analysis of the data generated on this platform represents a major bottleneck. Currently, MaxQuant and PEAKS are most used to analyze these data. However, because of the high complexity of timsTOF PASEF data, both require substantial time to perform even standard tryptic searches. Advanced searches (e.g. with many variable modifications, semi- or non-enzymatic searches, or open searches for post-translational modification discovery) are practically impossible. We have extended our fast peptide identification tool MSFragger to support timsTOF PASEF data, and developed a label-free quantification tool, IonQuant, for fast and accurate 4-D feature extraction and quantification. Using a HeLa data set published by Meier et al. (2018), we demonstrate that MSFragger identifies significantly (∼30%) more unique peptides than MaxQuant (1.6.10.43), and performs comparably or better than PEAKS X+ (∼10% more peptides). IonQuant outperforms both in terms of number of quantified proteins while maintaining good quantification precision and accuracy. Runtime tests show that MSFragger and IonQuant can fully process a typical two-hour PASEF run in under 70 min on a typical desktop (6 CPU cores, 32 GB RAM), significantly faster than other tools. Finally, through semi-enzymatic searching, we significantly increase the number of identified peptides. Within these semi-tryptic identifications, we report evidence of gas-phase fragmentation before MS/MS analysis.
Highlights
A major challenge to identification and quantification of proteins from tissue or cultured cells is the immense complexity of the peptide mixtures that result from enzymatic preparation of these samples for liquid chromatography-mass spectrometry (LC-MS) analysis
For typical data-dependent acquisition (DDA) measurements, a survey scan is performed, and the N-highest abundance precursor ions are targeted for tandem mass spectrometry (MS/MS) analysis based on their mass-to-charge ratio (m/z) and mobility
Using timsTOF parallel accumulationserial fragmentation (PASEF) HeLa data published by Meier et al [3] and multi-organism mixture data published by Prianichnikov et al [5], we show the application of MSFragger and IonQuant to measure the analysis speed and quantitative reproducibility across replicate injections, and compare these results to PEAKS and MaxQuant
Summary
A major challenge to identification and quantification of proteins from tissue or cultured cells is the immense complexity of the peptide mixtures that result from enzymatic preparation of these samples for liquid chromatography-mass spectrometry (LC-MS) analysis. Owing to the dual TIMS design of this instrument, where the first region is used for storing ions and the second for ion mobility separation, peptides can be continually selected for sequencing with minimal reduction in duty cycle This data acquisition method has been termed parallel accumulationserial fragmentation (PASEF) [2, 3]. We demonstrate that MSFragger can perform peptide identification from raw timsTOF PASEF data in a fraction of the time required by other tools. PEAKS [6] has extended its functionality to support quantification of timsTOF PASEF data, with analysis times similar to those of MaxQuant To address this challenge, we introduce IonQuant, a tool that takes Bruker's raw files and database search results as input to perform fast extracted ion chromatogram (XIC)-based quantification. We showcase a fast, flexible, and accurate computational platform for analyzing timsTOF PASEF proteomics data
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