Benchmarking turboDDA for Trace Sample Proteomics and Phosphoproteomics Analysis

ABSTRACT: In our previous work, a simple and robust approach termed turboDDA was reported to improve proteomics analysis in data-dependent acquisition (DDA) by eliminating the dynamic exclusion (DE) step on fast scanning time of flight (TOF) mass spectrometry (MS). However, its compatibility and potential on slow scanning Orbitrap mass spectrometry has not been explored. Here, we firstly optimized DEDDA, turboDDA and DIA methods on the analysis of trace proteome sample on a Thermo Orbitrap Tribrid Eclipse instrument, then benchmarked the turboDDA approach against another two data acquisition approaches on trace proteome and phsophoproteome sample analysis. The results indicated significant improved identification and quantification could be achieved by turboDDA not only for trace proteome samples, but also for low input phosphoproteome samples. Furthermore, the turboDDA strategy was integrated with our recently developed “All-in-one” single cell proteomics workflow and an ultrasensitive on-Tip IMAC phosphopeptide enrichment platform to analyze the proteome and phosphoproteome of single human oocytes at different developmental stages, as well as clinical oocytes arrested at metaphase I (MI) with specific gene mutations, demonstrating its capability not only in mapping of the changes of protein expression and phosphorylation state during physiological development, but also in the profiling of these alterations in single human oocytes from clinical patients. This approach provides a powerful and versatile tool for high-sensitivity MS analysis at the single cell level, offering new insights into both normal development and disease associated molecular alterations in clinically relevant specimens.

ORGANISM(S): Homo Sapiens

SUBMITTER: Shen Zhang  

PROVIDER: PXD073755 | iProX | Thu Oct 08 00:00:00 BST 2026

REPOSITORIES: iProX