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High-throughput Top-down FAIMS Data Analysis with ProSightPD Nodes in Proteome Discoverer Software

Posters | 2019 | Thermo Fisher Scientific | ASMSInstrumentation
Software, LC/HRMS, LC/MS, LC/MS/MS, LC/Orbitrap
Industries
Proteomics
Manufacturer
Thermo Fisher Scientific

Summary

Significance of the Topic


Top-down proteomics aims to characterize intact proteoforms but is challenged by structural similarity and wide dynamic range of proteins in complex samples. High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) offers gas-phase separation to enrich low-abundance species and reduce spectral complexity, enhancing depth and throughput of proteome analysis.

Objectives and Study Overview


The study evaluates Thermo Scientific™ ProSightPD™ nodes within Proteome Discoverer software for high-throughput top-down FAIMS data analysis. It compares proteomic metrics with and without a FAIMS Pro interface on Orbitrap Fusion Lumos instrumentation, aiming to demonstrate increased proteoform and protein identifications using multiple compensation voltages (CVs).

Methodology and Instrumentation


Samples were fractionated using GELFrEE or PLRP-S chromatography, then analyzed by reversed-phase liquid chromatography coupled to a FAIMS Pro interface and a Thermo Scientific™ Orbitrap Fusion™ Lumos™ Tribrid mass spectrometer in high-resolution MS1 and MS2 modes. RAW data were imported into Proteome Discoverer 2.3 and processed with ProSightPD nodes (version 2.0) and optimized cRAWler nodes (version ≥3.0) to deconvolute CV-resolved spectra. Key instrumentation:
  • GELFrEE system and PLRP-S monolithic columns for offline fractionation
  • Easy-nLC 1200 / EASY-Spray LC columns or custom nanospray sources
  • FAIMS Pro interface with stepwise CV switching
  • Orbitrap Fusion Lumos Tribrid mass spectrometer
  • Proteome Discoverer 2.3 with ProSightPD™ workflow nodes

Main Results and Discussion


Incorporation of FAIMS separation increased the number of detected monoisotopic precursors by 113% (S/N>3). Proteoform identifications rose by 17%, protein accession coverage by 43%, and highly characterized proteoforms (C-score>40) by 35%. FAIMS redistributed proteoform spectral matches (PrSMs) across more proteoforms per protein, reducing redundancy and revealing low-abundance species. Histograms of PrSM masses across nine CVs showed smaller proteins enriched at more negative CVs (-80 to -40) and larger proteins at mid-range CVs (-30 to -10), demonstrating FAIMS’s size-dependent separation.

Benefits and Practical Applications


FAIMS integration with ProSightPD nodes provides:
  • Enhanced detection of low-abundance proteoforms without additional sample depletion
  • Improved dynamic range and depth in top-down analyses
  • Streamlined bioinformatics via fully integrated Proteome Discoverer workflows
  • Visualization tools for CV-resolved proteoforms and PrSMs

These improvements support QA/QC, biomarker discovery, and detailed characterization of post-translational modifications in research and industrial laboratories.

Future Trends and Applications


Ongoing optimization of CV selection and switching times promises further gains in throughput and coverage. Integration with complementary separation techniques (e.g., capillary electrophoresis) and machine-learning-driven CV prediction could tailor FAIMS conditions for specific proteoform classes. Expanded applications may include clinical proteomics, structural biology studies, and real-time quality control in biopharmaceutical production.

Conclusion


The combination of FAIMS Pro interface and ProSightPD nodes within Proteome Discoverer significantly enhances top-down proteomic analyses by increasing proteoform and protein identifications, improving spectral distribution, and simplifying data processing. This integrated approach advances high-throughput, in-depth proteome characterization.

Reference


1. Lee JE, Kellie JF, Tran JC, et al. A robust two-dimensional separation for top-down tandem mass spectrometry of the low-mass proteome. J Am Soc Mass Spectrom. 2009;20(12):2183–2191. doi:10.1016/j.jasms.2009.08.001
2. Hebert AS, Prasad S, Belford MW, et al. Comprehensive Single-Shot Proteomics with FAIMS on a Hybrid Orbitrap Mass Spectrometer. Anal Chem. 2018;90(15):9529–9537. doi:10.1021/acs.analchem.8b02233

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