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Updated: Mar 12, 2026
Quantitative Phosphoproteomics in Fatty Acid Stimulated Saccharomyces cerevisiae
Published on: October 12, 2009
Advanced Phosphoproteomics Depth and Quantitative Performance Using an Integrated noFAIMS-FAIMS Approach
Byoung-Kyu Cho1,2, Antonia Zamacona Calderon1, Young Ah Goo1,2,3
1Mass Spectrometry Technology Access Center at the McDonnell Genome Institute, Washington University School of Medicine, St. Louis, Missouri, USA.
Rationale:
Protein phosphorylation plays a central role in regulating cellular signaling, and its dysregulation is closely linked to diseases such as cancer and neurodegeneration. Mass spectrometry-based phosphoproteomics allows comprehensive mapping of phosphorylation; however, detecting low-abundance and poor ionization phosphopeptides remains a challenge. High-field asymmetric waveform ion mobility spectrometry (FAIMS) offers orthogonal gas-phase fractionation, enhancing phosphopeptide detection. However, FAIMS and conventional non-FAIMS (noFAIMS) analyses often identify partially overlapping yet complementary subsets of phosphopeptides. This suggests that integrating both approaches could significantly increase the depth of phosphoproteomic analysis.
Methods:
Phosphopeptide samples were analyzed using a Vanquish Neo UHPLC system coupled to an Orbitrap Eclipse Tribrid mass spectrometer. Using parallel reaction monitoring (PRM) on a panel of 200 synthetic phosphopeptides, we assessed ionization efficiencies under noFAIMS conditions and at six different FAIMS compensation voltages (CVs). The integrated noFAIMS and FAIMS approach was further evaluated using enriched phosphopeptide samples from HEK293 and HeLa cells, analyzed by data-dependent acquisition (DDA).
Results:
The integrated noFAIMS-FAIMS approach resulted in a substantial increase in phosphopeptide identifications (14.9%-46.5%) compared with either the noFAIMS or FAIMS method alone. This integrated approach also exhibited high reproducibility across technical and biological replicates. Importantly, the integrated approach expanded the coverage of key signaling pathways such as EGF/EGFR, VEGFA-VEGFR2, and PI3K-AKT, by capturing phosphoproteins identified exclusively in either dataset.
Conclusions:
This study demonstrates that an integrated noFAIMS-FAIMS approach significantly enhances phosphoproteomic depth and quantification by leveraging the complementary advantages of each method. By capturing unique phosphopeptides from each analysis, this strategy can be a practical and efficient phosphoproteomic approach, providing deeper insights into cellular signaling pathways.
