An Optimized Miniaturized Filter-Aided Sample Preparation Method for Sensitive Cross-Linking Mass Spectrometry
1Institute of Drug Discovery Technology, Ningbo University, Ningbo, Zhejiang 315211, China.
Analytical Chemistry
|July 15, 2024
Summary
A new optimized miniaturized filter-aided sample preparation (O-MICROFASP) method enhances cross-linked mass spectrometry (XL-MS) sensitivity for low-abundance protein samples. This technique significantly increases the identification of cross-linked peptides, improving protein structure and interaction analysis.
Area of Science:
- Proteomics
- Biochemistry
- Analytical Chemistry
Background:
- Cross-linking mass spectrometry (XL-MS) is vital for mapping protein structures and interactions.
- Sensitive XL-MS analysis of limited samples is hindered by sample loss during preparation.
- Low-abundance cross-linked peptides are particularly challenging to detect.
Purpose of the Study:
- To develop a sensitive XL-MS method for microscale samples.
- To optimize sample preparation for improved identification of cross-linked peptides.
- To enhance the analysis of protein structures and protein-protein interactions (PPIs) from limited biological material.
Main Methods:
- Development and optimization of the miniaturized filter-aided sample preparation (O-MICROFASP) method.
- Systematic investigation of crucial experimental factors for XL-MS.
- Integration of O-MICROFASP with tip-based strong cation exchange (SCX) fractionation.
- Application of five different cross-linkers for comprehensive proteome coverage.
Main Results:
- O-MICROFASP significantly improved cross-linked peptide identification from microgram samples compared to conventional methods.
- Over 7.4 times more cross-linked peptides were identified from 1 μg of HeLa cell lysates using O-MICROFASP.
- Reduced filter surface area in a microreactor further increased identification rates for 0.5 μg samples.
- Analysis of 5 μg HeLa cell lysates identified 2741 unique cross-linked peptides, revealing 2579 K-K linkages in 1092 proteins.
- High confidence (≥0.9) was observed for 75% of identified PPIs, validating the method's reliability.
Conclusions:
- O-MICROFASP provides a highly sensitive and reliable method for proteome-wide XL-MS analysis of microscale samples.
- The optimized method overcomes sample loss issues, enabling deeper insights into protein structures and PPIs.
- This technique is a universal tool for advancing structural proteomics and interaction studies with limited sample amounts.
