Data-Independent Acquisition and Label-Free Quantification for Quantitative Proteomics Analysis of Human...

Area of Science:

• Proteomics
• Neuroscience
• Analytical Chemistry

Background:

• Cerebrospinal fluid (CSF) is crucial for understanding central nervous system (CNS) function and disease.
• Comprehensive proteomic analysis of CSF is challenging but vital for biomarker discovery.
• Existing methods may lack the scalability and robustness needed for deep proteomic profiling.

Purpose of the Study:

• To provide a practical, step-by-step protocol for CSF proteomics using mass spectrometry.
• To establish a robust and scalable workflow for label-free quantification via data-independent acquisition.
• To enable deeper insights into the CNS proteomic landscape.

Main Methods:

• Detailed protocols for CSF sample collection and preparation for mass spectrometry.
• Implementation of data-independent acquisition (DIA) for comprehensive peptide and protein profiling.
• Label-free quantification strategies for accurate abundance measurements.
• Methods for mass spectrometry data analysis and interpretation.

Main Results:

• A validated workflow for reproducible CSF proteomics analysis.
• Demonstration of robust protein identification and quantification across samples.
• Establishment of a scalable approach applicable to large cohorts.

Conclusions:

• The presented DIA-based, label-free quantitative proteomics workflow offers a powerful tool for CNS research.
• This method facilitates comprehensive proteomic profiling of CSF, aiding in biomarker discovery and understanding neurological disorders.
• The protocol provides a scalable and robust foundation for future proteomic investigations of the central nervous system.