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dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts
Vadim Demichev1,2,3, Lukasz Szyrwiel4,5, Fengchao Yu6
1Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany. vadim.demichev@charite.de.
Nature Communications
|July 8, 2022
Summary
This study introduces a new computational platform for data-independent acquisition with parallel accumulation-спондent ion mobility separation (dia-PASEF) proteomics. The platform significantly enhances protein quantification depth, especially for rapid experiments and low sample amounts.
Area of Science:
- Proteomics
- Computational Biology
- Mass Spectrometry
Background:
- Data-independent acquisition with parallel accumulation-спондent ion mobility separation (dia-PASEF) is a sensitive technique for proteomic analysis.
- Improving proteomic depth and throughput remains a key challenge, particularly for fast experiments and limited sample quantities.
Purpose of the Study:
- To develop and validate a novel computational platform for enhanced analysis of dia-PASEF data.
- To increase proteomic depth and efficiency in quantitative proteomics experiments.
Main Methods:
- Development of a two-dimensional peak-picking algorithm.
- Generation of optimized spectral libraries.
- Application of neural network-based processing for dia-PASEF data.
- Integration of algorithms into DIA-NN software and FragPipe workflow.
Main Results:
- Achieved up to an 83% boost in proteomic depth compared to previous methods.
- Quantified over 5300 proteins in single injections at 200 samples per day throughput (Evosep One/timsTOF Pro).
- Quantified nearly 9000 proteins in single injections with a 93-min nanoflow gradient (timsTOF Pro 2) using 200 ng of HeLa peptides.
Conclusions:
- The developed computational platform significantly enhances proteomic depth and efficiency for dia-PASEF experiments.
- The platform is particularly beneficial for fast proteomic workflows and analyses involving low sample amounts.
- User-friendly implementation via DIA-NN and FragPipe facilitates broader adoption.
