Background
Recent advances in mass spectrometry still faces a key challenge to maximize the complex proteome coverage. Although, data independent acquisition (DIA) is a very powerful tool to perform both protein identification and quantification of the complex samples still the ordinary approaches require more improvements to further extend the proteome in-depth analysis.
Cysteine is the second rarest amino acid but present in about 97% of the human proteome. By using a robust method for enrichment of cysteine-containing peptide in combination with DIA we should be able to increase the proteome coverage compared with normal DIA
In our study, we present Cysteine-DIA (Cys-DIA) approach that allows a successful and comprehensive characterization of the complex proteome with high dynamic range of protein abundances.
Methods
All experiments were performed on Q Exactive HF-X mass spectrometer using a high resolution MS1 based quantitation data-independent acquisition (HRMS1-DIA). Chromatographic separations were performed using EASY-nLC 1000 system (Thermo Fisher Scientific) and Evosep (Biosystems). HeLa and breast cancer cell line were used for analysis. Performed cysteine enrichment followed by high pH fractionation to generate sample specific spectral libraries. For quality control and retention times normalization, reference peptides were spiked into all samples. Spectral libraries generation and DIA data analysis were performed in Spectronaut PulsarX (Biognosis).
Preliminary Data
The Cys-DIA raw files were searched against the HeLa cysteine and total spectral library and we identified 5027 protein groups whereas for the total HeLa 3827 were identified. The cancer cell line 21 min of Cys-DIA search analysis resulted in the identification of about 2800 out of which about 2000 proteins were quantified across all replicates and all the three different cell line with average CV of 11%.
Novel Aspect
The cysteine-DIA approach reduces the proteome complexity and allows identification of a larger number of proteins in short time analyses.