Chromatographic alignment of ESI-LC-MS proteomics data sets by ordered bijective interpolated warping

Area of Science:

• Proteomics
• Analytical Chemistry
• Computational Biology

Background:

• Mass spectrometry proteomics typically analyzes single experiments, limiting comprehensive data comparison.
• Comparing raw data across multiple experiments is crucial for enhancing peptide/protein identification and quantitation.
• Chromatographic alignment of mass spectrometry (MS) signals is necessary for comparing peptide quantities between experiments when tandem MS identifications are insufficient.

Purpose of the Study:

• To present an extension of dynamic time warping (DTW), named ordered bijective interpolated warping (OBI-Warp), for aligning electrospray ionization liquid chromatography mass spectrometry (ESI-LC-MS) proteomics data.
• To optimize and compare alignment parameters using high-confidence, overlapping tandem mass spectra as standards.
• To demonstrate the effectiveness of OBI-Warp in aligning diverse ESI-LC-MS datasets.

Main Methods:

• Developed OBI-Warp, an algorithm combining a bijective function from DTW output with piecewise cubic hermite interpolation for smooth signal alignment.
• Utilized a variety of ESI-LC-MS proteomics datasets representing diverse alignment scenarios.
• Evaluated spectral similarity measures, determining Pearson's correlation coefficient to be superior for alignment accuracy.

Main Results:

• OBI-Warp successfully aligned various ESI-LC-MS proteomics datasets.
• Pearson's correlation coefficient proved more effective than covariance, dot product, and Euclidean distance for accurate spectral alignment.
• Penalizing gaps was identified as important for achieving optimal alignments.

Conclusions:

• OBI-Warp provides consistent alignments across diverse ESI-LC-MS datasets when using optimized parameters.
• The OBI-Warp algorithm enhances the ability to compare raw proteomics data across experiments.
• This method improves peptide and protein identification and quantitation in mass spectrometry-based proteomics.