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Comprehensive Two-Dimensional Liquid Chromatography-High-Resolution Mass Spectrometry for Complex Protein Digest
Rick S van den Hurk1,2, Bart Lagerwaard1,2, Nathan J Terlouw1,2
1Analytical Chemistry Group, Van't Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam1098 XH,The Netherlands.
Analytical Chemistry
|May 17, 2024
Summary
This study introduces parallel gradients in comprehensive two-dimensional liquid chromatography with high-resolution mass spectrometry (LC × LC-HRMS) for protein digests. This method enhances sensitivity and peptide identification compared to shifted gradients and 1D-LC.
Area of Science:
- Proteomics
- Analytical Chemistry
- Chromatography
Background:
- Online comprehensive two-dimensional liquid chromatography coupled with high-resolution mass spectrometry (LC × LC-HRMS) offers high peak capacity for complex samples.
- However, reduced sensitivity due to high flow rates in the second dimension (2D) limits its application in protein digest analysis.
Purpose of the Study:
- To develop and evaluate a RPLC × RPLC-HRMS method using parallel gradients for enhanced sensitivity and peptide identification.
- To compare the performance of parallel gradients against shifted gradients and 1D-RPLC methods.
Main Methods:
- Development of a RPLC × RPLC-HRMS method with parallel gradients (0.7 mL min⁻¹ 2D flow rate).
- Comparison with shifted gradient methods (1.4 mL min⁻¹ 2D flow rate) and 1D-RPLC.
- Analysis of cell line digest samples using QExactive-Plus MS.
Main Results:
- Parallel gradients significantly increased MS intensity (3x) and peptide identifications (3900 vs 2600) compared to shifted gradients.
- Reduced modulation time to 10s increased MS/MS events.
- RPLC × RPLC-HRMS with parallel gradients improved separation performance and increased analyte identifications (7000 peptides, 1990 proteins) versus 1D-RPLC.
Conclusions:
- Parallel gradients in RPLC × RPLC-HRMS enhance sensitivity and analytical depth for complex protein digests.
- This approach offers superior separation performance over 1D-RPLC with manageable sensitivity trade-offs.
- The method holds promise for broader application in proteomics research.
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