Trace Sample Proteome Quantification by Data-Dependent Acquisition without Dynamic Exclusion.

ABSTRACT: Despite continuous technological improvements in sample preparation, mass-spectrometry-based proteomics for trace samples faces the challenges of sensitivity, quantification accuracy, and reproducibility. Herein, we explored the applicability of turboDDA (a method that uses data-dependent acquisition without dynamic exclusion) for quantitative proteomics of trace samples. After systematic optimization of acquisition parameters, we compared the performance of turboDDA with that of data-dependent acquisition with dynamic exclusion (DEDDA). By benchmarking the analysis of trace unlabeled human cell digests, turboDDA showed substantially better sensitivity in comparison with DEDDA, whether for unfractionated or high pH fractionated samples. Furthermore, through designing an iTRAQ-labeled three

SUBMITTER: Wu C 

PROVIDER: S-EPMC10719888 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature