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1.
Methods Mol Biol ; 2511: 183-200, 2022.
Article in English | MEDLINE | ID: covidwho-1941376

ABSTRACT

Blood serum or plasma proteins are potentially useful in COVID-19 research as biomarkers for risk prediction, diagnosis, stratification, and treatment monitoring. However, serum protein-based biomarker identification and validation is complicated due to the wide concentration range of these proteins, which spans more than ten orders of magnitude. Here we present a combined affinity purification-liquid chromatography mass spectrometry approach which allows identification and quantitation of the most abundant serum proteins along with the nonspecifically bound and interaction proteins. This led to the reproducible identification of more than 100 proteins that were not specifically targeted by the affinity column. Many of these have already been implicated in COVID-19 disease.


Subject(s)
COVID-19 , Serum , Biomarkers , Blood Proteins/chemistry , COVID-19/diagnosis , Chromatography, Affinity/methods , Chromatography, Liquid/methods , Humans , Serum/chemistry , Tandem Mass Spectrometry/methods
2.
Nat Commun ; 12(1): 6073, 2021 10 18.
Article in English | MEDLINE | ID: covidwho-1860369

ABSTRACT

Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data independent acquisition (DIA) is an emerging technology with deep proteome coverage and accurate quantitative capability in proteomics studies, but is still in the early stage of development in the field of glycoproteomics. We propose GproDIA, a framework for the proteome-wide characterization of intact glycopeptides from DIA data with comprehensive statistical control by a 2-dimentional false discovery rate approach and a glycoform inference algorithm, enabling accurate identification of intact glycopeptides using wide isolation windows. We further utilize a semi-empirical spectrum prediction strategy to expand the coverage of spectral libraries of glycopeptides. We benchmark our method for N-glycopeptide profiling on DIA data of yeast and human serum samples, demonstrating that DIA with GproDIA outperforms the data-dependent acquisition-based methods for glycoproteomics in terms of capacity and data completeness of identification, as well as accuracy and precision of quantification. We expect that this work can provide a powerful tool for glycoproteomic studies.


Subject(s)
Glycopeptides/analysis , Proteome/analysis , Proteomics/methods , Algorithms , Blood Proteins/chemistry , Glycoproteins/chemistry , Humans , Mass Spectrometry , Polysaccharides/chemistry , Schizosaccharomyces pombe Proteins/chemistry , Workflow
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