Contacts
Jian Wang [jiw006 (at) ucsd.edu]Summary
The next big challenge in proteomics lies at qualitatively and quantitatively capturing the dynamics of proteins and their interactions inside the cell. This requires the consistent identification and quantification of peptides and proteins of interest across multiple sample conditions and/or time points. However the complexity of proteomics samples is very large and the widely used data dependent acquisition (DDA) strategies have limitations such as under-sampling, long analysis time and low reproducibility which are problematic for large-scale comparative analysis . Data independent acquisition (DIA) strategies have been proposed to address these issues, however computational tools to analyze the complex multiplexed MS/MS spectra from DIA data are lagging behind. Here we proposed MSPLIT-DIA, a new spectral-library search method that can identify multiplexed spectra with up to ten co-eluting peptides and improves the number of peptides identified across multiple experiments by up to 80% when compared to DDA, making it an ideal tool for comparative LC/MS/MS analysis. Integrating MSPLIT-DIA into a semi-quantitative pipeline, we show that it improves our ability to detect protein-protein interactions (PPIs) by reducing the instrument time required by half and improve the number of PPI detected by 40%.