Benchmarking commonly used software suites and analysis workflows for DIA proteomics and phosphoproteomics.

Area of Science:

• Proteomics and Phosphoproteomics
• Mass Spectrometry Data Analysis
• Computational Biology

Background:

• Numerous software suites and spectral libraries exist for data-independent acquisition (DIA) proteomics.
• The impact of combining specific DIA software with spectral libraries on data analysis outcomes, especially in complex biological contexts, remains under-investigated.
• Robust DIA data processing is essential for accurate proteome and phosphoproteome profiling.

Purpose of the Study:

• To evaluate the performance of commonly used DIA software suites when paired with various spectral libraries.
• To assess the impact of these combinations on both global proteome and phosphoproteome analysis.
• To provide practical guidance for selecting optimal DIA data analysis pipelines.

Main Methods:

• Creation of DIA benchmark datasets simulating complex biological regulation on Orbitrap and timsTOF instruments.
• Evaluation of four DIA software suites (DIA-NN, Spectronaut, MaxDIA, Skyline) against seven spectral libraries.
• Assessment of performance on phosphopeptide standards and TNF-α-induced phosphoproteome regulation.

Main Results:

• Performance variations were observed between different software-library combinations in DIA proteomics and phosphoproteomics.
• The choice of software and spectral library significantly influences the depth and accuracy of proteomic and phosphoproteomic profiling.
• Specific combinations demonstrated superior performance for certain aspects of DIA data analysis.

Conclusions:

• The study offers a practical framework for constructing robust DIA data analysis pipelines.
• Selecting appropriate software-library combinations is critical for reliable results in DIA-based proteomics and phosphoproteomics.
• This research aids scientists in optimizing their DIA data processing strategies for complex biological studies.