Human plasma proteomic and glycoproteomic analyses have emerged as an alternate avenue to identify disease biomarkers and therapeutic approaches. However, the vast number of high-abundance proteins in plasma can cause mass spectrometry (MS) suppression, which makes it challenging to detect low-abundance proteins (LAP). Currently, immunoaffinity-based depletion methods and strategies involving nanomaterial protein coronas have been developed to remove high-abundance proteins (HAP) and enhance the depth of plasma protein identification. Despite these advancements, there is a lack of systematic comparison and evaluation of the qualitative and quantitative effects of different strategies on the human plasma proteome and glycoproteome. In this study, we evaluated the performance of four depletion methods including combinatorial peptide ligand libraries (CPLL), Top 2, Top 14, and the nanomaterial protein corona formed by magnetic nanoparticles (MN) in both plasma proteomics and N-glycoproteomics. Compared to the CPLL, Top 2, and Top 14 strategies, the MN approach significantly increased the number of identified peptides and proteins. However, it demonstrated a relatively lower efficacy in identifying intact N-glycopeptides and N-glycoproteins. In contrast, the immunoaffinity-based depletion methods are better suited to glycoproteomics due to higher identification numbers. We believe that this work provides valuable insights and options for various research objectives, as well as clinical applications.
Keywords: N-glycoproteomics; enrichment; mass spectrometry; plasma; proteomics.