Fast Quantitative Analysis of timsTOF PASEF Data with MSFragger and IonQuant

• Published in: Molecular & cellular proteomics Vol. 19; no. 9; pp. 1575 - 1585
• Main Authors: Yu, Fengchao, Haynes, Sarah E., Teo, Guo Ci, Avtonomov, Dmitry M., Polasky, Daniel A., Nesvizhskii, Alexey I.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.09.2020; American Society for Biochemistry and Molecular Biology
• Subjects: Algorithms; Bioinformatics; Chromatography, Liquid - methods; Databases, Protein; Escherichia coli - metabolism; HeLa Cells; Humans; ion mobility; Ion Mobility Spectrometry - methods; label-free quantification; PASEF; Peptides - analysis; Peptides - metabolism; Phylogeny; protein identification; Protein Processing, Post-Translational; Proteome - metabolism; Proteomics - methods; Saccharomyces cerevisiae - chemistry; Saccharomyces cerevisiae - metabolism; Sensitivity and Specificity; tandem mass spectrometry; Tandem Mass Spectrometry - methods; Technological Innovation and Resources; algorithms; tandem mass spectrometry; PASEF; label-free quantification; ion mobility; protein identification; Bioinformatics
• ISSN: 1535-9476; 1535-9484; 1535-9484
• DOI: 10.1074/mcp.TIR120.002048

Ion mobility helps resolve complex proteomics samples, but data structures can be unwieldy and lead to long post-acquisition analysis times. We adapted the fast search engine MSFragger for timsTOF data, and developed IonQuant for accurate quantification. These tools are part of a complete pipeline that is well suited for the analysis of timsTOF in terms of identification sensitivity, quantification accuracy, and runtimes. We additionally demonstrate complex analyses, including semi-enzymatic database search to monitor gas-phase fragmentation in early timsTOF data. [Display omitted] Highlights •MSFragger now supports raw timsTOF PASEF data.•IonQuant performs fast and accurate feature detection and quantification.•MSFragger and IonQuant provide excellent performance for timsTOF PASEF data.•Flexibility allows for complex analyses, such as semi-enzymatic and open search. 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.