Deep Metaproteome Analysis using a Vanquish Neo UHPLC System Coupled to an Orbitrap Eclipse Tribrid Mass Spectrometer with FAIMS Pro Interface

Posters | 2021 | Thermo Fisher Scientific | ASMSInstrumentation
Ion Mobility, LC/HRMS, LC/MS, LC/MS/MS, LC/Orbitrap
Industries
Proteomics
Manufacturer
Thermo Fisher Scientific

Summary

Importance of the Topic


The characterization of complex microbial communities at the protein level (metaproteomics) is critical for understanding functional dynamics in health, environmental and industrial contexts. Deep profiling of these samples poses a challenge due to their high diversity and dynamic range, often requiring extensive fractionation.

Study Objectives and Overview


This work evaluates a high-performance liquid chromatography–mass spectrometry (LC-MS) workflow combining a Vanquish Neo UHPLC system with an Orbitrap Eclipse Tribrid mass spectrometer and FAIMS Pro Interface. Two standardized microbiome samples (ZymoBIOMICS Microbial Community and Gut Microbiome) were analyzed to assess improvements in protein identification, quantitation coverage and reproducibility.

Methodology and Instrumentation


  • Peptide Separation
    • Vanquish Neo UHPLC system
    • EASY-Spray PepMap Neo column (75 µm × 75 cm, 2 µm C18)
    • Gradient: 5–28% B over 105 min, then 28–40% B over 15 min; flow rate 250 nL/min; column at 50 °C
  • Mass Spectrometry
    • Orbitrap Eclipse Tribrid MS
    • FAIMS Pro Interface with compensation voltages at –35 V, –50 V, –65 V in a three-voltage cycle (3 s cycle time over 140 min)
    • No-FAIMS DDA: MS1 at 240 k resolution, AGC target 4 × 10^5; MS2 with 60 s dynamic exclusion
  • Sample Preparation
    • Lysis and bead beating
    • Protein reduction/alkylation
    • Lys-C and trypsin digestion
    • SPE cleanup and concentration measurement by UV
  • Data Processing
    • Proteome Discoverer 3.0 with SEQUEST HT and INFERYS rescoring
    • Minora Feature Detector, Feature Mapper, Precursor Ion Quantifier for label-free quantitation

Main Results and Discussion


  • Protein and Peptide Identification
    • No-FAIMS: ~10 000 proteins & 70 000 peptides (Community); ~11 000 proteins & 80 000 peptides (Gut)
    • With FAIMS: +19% protein identifications in Community (12 938); +17.5% in Gut (13 332)
    • Distinct peptide sets at each CV indicate effective gas-phase fractionation
  • Quantitative Performance
    • ~95% of identified proteins and peptides quantified across samples
    • Triplicate reproducibility: >93% proteins with CV <20%
  • Comparison to NGS
    • Species abundance from proteomics closely matches NGS profiles; NGS tends to overestimate low-abundance taxa

Benefits and Practical Applications of the Method


  • Achieves deep proteome coverage without laborious offline fractionation
  • Reliable label-free quantitation in complex microbial mixtures
  • Applicable to environmental studies, clinical metaproteomics, QA/QC and industrial analytics

Future Trends and Applications


  • Enhanced integration of FAIMS with other ion-mobility platforms for deeper coverage
  • Automated and high-throughput workflows leveraging advanced algorithms
  • Expansion into personalized medicine, ecosystem monitoring and bioprocess optimization

Conclusion


Coupling the Vanquish Neo UHPLC system with an Orbitrap Eclipse Tribrid mass spectrometer and FAIMS Pro Interface yields a ~20% gain in protein identifications and robust quantitation (>95% coverage, CV <20%), demonstrating a powerful platform for deep metaproteome analysis.

Instrumentation Used


  • Thermo Scientific Vanquish Neo UHPLC system
  • Thermo Scientific EASY-Spray PepMap Neo column
  • Thermo Scientific Orbitrap Eclipse Tribrid mass spectrometer
  • Thermo Scientific FAIMS Pro Interface
  • Proteome Discoverer 3.0 with SEQUEST HT and INFERYS rescoring

References


  1. Wilmes P, Bond PL. Metaproteomics: studying functional gene expression in microbial ecosystems. Trends Microbiol. 2006;14:92–97.
  2. Verberkmoes NC, et al. Shotgun metaproteomics of the human distal gut microbiota. ISME J. 2009;3:179–189.
  3. Zolg DP, et al. INFERYS rescoring: Boosting peptide identifications and scoring confidence of database search results. Rapid Commun Mass Spectrom. 2021;Special Issue May.

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