Research On Quantitative Proteomics Method For DIA Mass Spectrometry Data

As the direct biological functional molecule of organisms,protein is an important material basis for life activities.Quantitative proteomics aims to determine the amount of proteins in biological samples,and has important applications in biomarker discovery,protein-protein interaction and other fields.Mass spectrometry technology is widely used in quantitative proteomics,and a series of mass spectrometry acquisition strategies have been proposed.Mass spectrometry based on data-independent acquisition(DIA)strategy has broad application prospects in large-scale proteomics due to its reproducibility and comprehensiveness.Owing to the high complexity of DIA mass spectrometry data,the application of DIA in large-scale proteomics still faces many challenges,among which DIA spectral deconvolution,peptide quantification independent of retention time information and low-abundance protein determination are the key issues of current attention.In this paper,a bottom-up quantitative proteomics calculation method is designed to provide specific solutions to the above issues.The main tasks include:(1)For DIA spectral deconvolution,a new feature of reference spectra called featured ion is analyzed,and a method of spectral deconvolution based on featured ion is proposed.Compared with existing methods,this method significantly improved the accuracy and efficiency of spectral deconvolution.(2)For peptide quantification independent of retention time information,a peptide quantitative analysis process based on DIA spectral deconvolution is designed.The process is universal in conventional DIA and RTF-DIA mass spectrometry data,and can efficiently and accurately quantify peptides for both.(3)For low-abundance protein determination,a protein quantification method based on peptide abundances is proposed,which achieves comprehensive protein quantification by constructing a weighted non-negative least squares model.This method can effectively improve the throughput of protein quantification and the quantitative accuracy of proteins in various abundance ranges,and has more significant advantages for low-abundance proteins.