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Published on: January 20, 2022
Parallel Accumulation-Serial Fragmentation (PASEF): Multiplying Sequencing Speed and Sensitivity by Synchronized
Florian Meier1, Scarlet Beck1, Niklas Grassl1
1Proteomics and Signal Transduction, Max-Planck-Institute of Biochemistry , Am Klopferspitz 18, 82152 Martinsried, Germany.
Trapped ion mobility spectrometry (TIMS) coupled with synchronized quadrupole scans, termed parallel accumulation-serial fragmentation (PASEF), significantly enhances proteomics. This method allows for rapid, sensitive sequencing of multiple precursors simultaneously, boosting speed tenfold.
Area of Science:
- Proteomics
- Analytical Chemistry
- Mass Spectrometry
Background:
- Liquid chromatography-mass spectrometry (LC-MS) often faces limitations with simultaneous precursor elution.
- Data-dependent acquisition discards many potential precursors during analysis.
- Existing methods struggle to efficiently fragment co-eluting peptides.
Purpose of the Study:
- To overcome the limitations of discarding co-eluting precursors in LC-MS proteomics.
- To develop a method for serial selection and fragmentation of multiple precursors in a single scan.
- To increase the speed and efficiency of shotgun proteomics analyses.
Main Methods:
- Implementation of trapped ion mobility spectrometry (TIMS) on an orthogonal quadrupole time-of-flight (QTOF) mass spectrometer.
- Development of synchronized quadrupole scans with sub-millisecond switching times.
- Introduction of parallel accumulation-serial fragmentation (PASEF) for precursor selection and fragmentation.
Main Results:
- Demonstration of serial selection and fragmentation of multiple precursors within single 50 ms TIMS scans.
- Achieved hundreds of MS/MS events per second with full sensitivity using PASEF.
- Estimated a 10-fold gain in sequencing speed for shotgun proteomics without sensitivity loss.
Conclusions:
- PASEF overcomes the precursor limitation in LC-MS-based proteomics.
- The method enables high-throughput, sensitive analysis of complex proteomes.
- PASEF represents a significant advancement in mass spectrometry-based proteomics speed and efficiency.
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