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Analyzing the Photo-oxidation of 2-propanol at Indoor Air Level Concentrations Using Field Asymmetric Ion Mobility Spectrometry
Published on: June 14, 2018
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Characterization and Optimization of Multiplexed Quantitative Analyses Using High-Field Asymmetric-Waveform Ion
Devin K Schweppe1, Satendra Prasad2, Michael W Belford2
1Department of Cell Biology , Harvard Medical School , Cambridge , Massachusetts 02115 , United States.
Analytical Chemistry
|January 24, 2019
Summary
High-Field Asymmetric-waveform Ion Mobility Spectroscopy (FAIMS) improves quantitative accuracy in multiplexed proteomics by reducing peptide coisolation. This technique enhances data reliability without losing protein identifications.
Area of Science:
- Proteomics
- Analytical Chemistry
- Biotechnology
Background:
- Multiplexed, isobaric tagging is crucial for high-throughput quantitative proteomics.
- Peptide coisolation in these methods can limit dynamic range and accuracy.
- Current interference mitigation strategies may reduce protein identification rates.
Purpose of the Study:
- To evaluate High-Field Asymmetric-waveform Ion Mobility Spectroscopy (FAIMS) for improving quantitative accuracy in isobaric tagging proteomics.
- To assess FAIMS's impact on data quality and protein identification.
- To optimize FAIMS parameters for robust multiplex quantitation.
Main Methods:
- Utilized FAIMS coupled with mass spectrometry.
- Employed TMT-based interference standards (TKO and HYPER).
- Tested FAIMS with high-resolution MS2 (HRMS2) and synchronous precursor selection MS3 (SPS-MS3) methods.
Main Results:
- FAIMS significantly improved quantitative accuracy for both HRMS2 and SPS-MS3.
- No loss of protein identifications was observed when using FAIMS.
- Key factors for robust FAIMS implementation in multiplex quantitation were optimized and characterized.
Conclusions:
- FAIMS effectively reduces precursor coisolation, enhancing accuracy and dynamic range in multiplexed quantitative proteomics.
- FAIMS offers a valuable method to improve isobaric tagging quantitation without compromising proteome coverage.
- Method recommendations are provided for leveraging FAIMS in future quantitative proteomics studies.
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