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Simplifying the proteome: analytical strategies for improving peak capacity.
Lee A Gethings1, Joanne B Connolly
1Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow, SK9 4AX, Manchester, UK, lee_gethings@waters.com.
Advances in Experimental Medicine and Biology
|June 22, 2014
Summary
Maximizing peak capacity in analytical workflows, including liquid chromatography and mass spectrometry, enhances proteomic studies by extending dynamic range and improving analyte identification rates. This approach addresses challenges in analyzing diverse biological samples.
Area of Science:
- Analytical Chemistry
- Biochemistry
- Proteomics
Background:
- Biological sample analysis presents significant analytical challenges due to sample diversity and wide analyte dynamic ranges.
- Proteomic studies are particularly affected by these challenges, impacting analyte identification and quantification.
- Current workflows often struggle to achieve sufficient peak capacity for comprehensive analysis.
Purpose of the Study:
- To present methods for maximizing peak capacity in analytical workflows.
- To enhance dynamic range and identification rates in proteomic analyses.
- To address analytical challenges in diverse biological sample matrices.
Main Methods:
- Focus on optimizing liquid chromatography (LC) parameters.
- Integration of mass spectrometry (MS) techniques for enhanced detection.
- Application of ion mobility (IM) spectrometry to improve separation.
- Utilizing data-independent acquisition (DIA) strategies.
Main Results:
- Achieving maximized peak capacity extends the dynamic range of analytical measurements.
- Increased identification rates for a broader spectrum of analytes are observed.
- Data-independent acquisition strategies mitigate issues like chimericy in complex samples.
- Improved analytical performance for diverse biological samples.
Conclusions:
- Maximizing peak capacity is crucial for advancing proteomic analysis.
- Combining LC, MS, and IM offers a powerful strategy for complex sample analysis.
- Data-independent acquisition is effective for handling regions of high analyte density and reducing spectral interference.
