Affiliation:
1. Department of Clinical Biochemistry Odense University Hospital Odense Denmark
2. Computational and Experimental Biology Group, CEDOC, Chronic Diseases Research Centre, NOVA Medical School, Faculdade de Ciências Médicas Universidade NOVA de Lisboa Lisbon Portugal
Abstract
AbstractClinical biomarker discovery is often based on the analysis of human plasma samples. However, the high dynamic range and complexity of plasma pose significant challenges to mass spectrometry‐based proteomics. Current methods for improving protein identifications require laborious pre‐analytical sample preparation. In this study, we developed and evaluated a TMTpro‐specific spectral library for improved protein identification in human plasma proteomics. The library was constructed by LC‐MS/MS analysis of highly fractionated TMTpro‐tagged human plasma, human cell lysates, and relevant arterial tissues. The library was curated using several quality filters to ensure reliable peptide identifications. Our results show that spectral library searching using the TMTpro spectral library improves the identification of proteins in plasma samples compared to conventional sequence database searching. Protein identifications made by the spectral library search engine demonstrated a high degree of complementarity with the sequence database search engine, indicating the feasibility of increasing the number of protein identifications without additional pre‐analytical sample preparation. The TMTpro‐specific spectral library provides a resource for future plasma proteomics research and optimization of search algorithms for greater accuracy and speed in protein identifications in human plasma proteomics, and is made publicly available to the research community via ProteomeXchange with identifier PXD042546.
Subject
Molecular Biology,Biochemistry
Cited by
1 articles.
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