Ultra-deep proteomics by Thin-diaPASEF with a 60-cm long column system

Rapid and comprehensive analysis of complex proteomes across large sample sets is vital for unlocking the potential of systems biology. We present UFP-MS, an ultra-fast mass spectrometry (MS) proteomics method that integrates narrow-window data-independent acquisition (nDIA) with short-gradient micro-flow chromatography, enabling profiling of >240 samples per day. This optimized MS approach identifies 6,201 and 7,466 human proteins with 1- and 2-min gradients, respectively. Our streamlined sample preparation workflow features high-throughput homogenization, adaptive focused acoustics (AFA)-assisted proteolysis, and Evotip-accelerated desalting, allowing for the processing of up to 96 tissue samples in 5 h. As a practical application, we analyzed 507 samples from 13 mouse tissues treated with the enzyme-drug L-asparaginase (ASNase) or its glutaminase-free Q59L mutant, generating a quantitative profile of 11,472 proteins following drug treatment. The MS results confirmed the impact of ASNase on amino acid metabolism in solid tissues. Further analysis revealed broad suppression of anticoagulants and cholesterol metabolism and uncovered numerous tissue-specific dysregulated pathways. In summary, the UFP-MS method greatly accelerates the generation of biological insights and clinically actionable hypotheses into tissue-specific vulnerabilities targeted by ASNase.

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Differences in Uniquely Identified Peptides Between ddaPASEF and diaPASEF

Iwasaki,

Nishimura,

Yamakawa

et al. 2024

Cells

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Recent advancements in mass spectrometry-based proteomics have made it possible to conduct comprehensive protein analysis. In particular, the emergence of the data-independent acquisition (DIA) method powered by machine learning has significantly improved protein identification efficiency. However, compared with the conventional data-dependent acquisition (DDA) method, the degree to which peptides are uniquely identified by DIA and DDA has not been thoroughly examined. In this study, we identified over 10,000 proteins using the DDA and DIA methods and analyzed the characteristics of unique peptides identified by each method. Results showed that the number of peptides uniquely identified by DDA and DIA using the same column type was 19% and 32%, respectively, with shorter peptides preferentially detected by the DIA method. In addition, more DIA-specific peptides were identified, especially during the first 10% of elution time, and the overall 1/K0 and m/z shifted toward smaller values than in the DDA method. Furthermore, comparing the phosphorylation and ubiquitination proteome profiles with those of whole-cell lysates by DDA showed that the enrichment of post-translationally modified peptides resulted in wider m/z and 1/K0 ranges. Notably, the ubiquitin peptide-enriched samples displayed lower m/z values than the phospho-proteome. These findings suggest a bias in the types of peptides identified by the acquisition method and the importance of setting appropriate ranges for DIA based on the post-translational modification of peptide characteristics.

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Ultra-deep proteomics by Thin-diaPASEF with a 60-cm long column system

Cited by 3 publications

References 33 publications

Eleven shades of PASEF

Eleven shades of PASEF

Ultra-Fast Multi-Organ Proteomics Unveils Tissue-Specific Mechanisms of Drug Efficacy and Toxicity

Differences in Uniquely Identified Peptides Between ddaPASEF and diaPASEF

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