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Evaluation of PAC and FASP Performance: DIA-Based Quantitative Proteomic Analysis
Maria Stella Murfuni1, Licia E Prestagiacomo1, Annarita Giuliano1
1Research Centre for Advanced Biochemistry and Molecular Biology, Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, 88100 Catanzaro, Italy.
International Journal of Molecular Sciences
|May 25, 2024
Summary
Protein aggregation capture (PAC) identified more proteins than filter-aided sample preparation (FASP). Data analysis software varied in sensitivity, precision, and specificity, offering guidance for proteomics workflows.
Area of Science:
- Proteomics
- Biochemistry
- Analytical Chemistry
Background:
- Optimizing sample preparation and data analysis is crucial for maximizing protein identification in complex biological samples.
- Filter-aided sample preparation (FASP) and protein aggregation capture (PAC) are common techniques, but their comparative performance requires evaluation.
- Data-independent acquisition (DIA) coupled with various software tools presents challenges in selecting the optimal analysis pipeline.
Purpose of the Study:
- To compare the efficacy of FASP and PAC methods for protein identification using a three-species mix.
- To evaluate the performance of Spectronaut, MaxDIA, and DIA-NN software for processing DIA-generated proteomics data.
- To provide insights into selecting appropriate sample preparation and data analysis strategies for proteomics research.
Main Methods:
- Comparative analysis of Filter-Aided Sample Preparation (FASP) and Protein Aggregation Capture (PAC) techniques.
- Utilizing a defined protein mixture (Human, Soybean, Pisum sativum) at two concentrations (1 µg and 10 µg).
- Employing data-independent acquisition (DIA) for peptide mixture analysis and processing raw files with Spectronaut, MaxDIA, and DIA-NN.
Main Results:
- Protein Aggregation Capture (PAC) with 10 µg yielded the highest protein identification (5491 mean), while FASP with 1 µg showed the lowest (4855).
- FASP at 1 µg exhibited the poorest performance (specificity 0.73, precision 0.24), whereas other conditions achieved higher diagnostic accuracy (specificity 0.95-0.99, precision 0.61-0.86).
- Spectronaut demonstrated the highest sensitivity (median 0.67) for low-abundance proteins, MaxDIA offered the best precision (median 0.84), and all software showed comparable specificity (0.93-0.99).
Conclusions:
- Protein aggregation capture (PAC) is a more effective sample preparation method than FASP for comprehensive protein identification in complex mixtures.
- The choice of data analysis software significantly impacts proteomics results, with Spectronaut excelling in sensitivity and MaxDIA in precision.
- These findings offer valuable guidance for optimizing proteomics workflows, particularly in selecting appropriate sample preparation and data processing tools for enhanced protein discovery.
