Yanyan Qu

Boronic Acid Functionalized Core-Shell Polymer Nanoparticles Prepared by Distillation Precipitation Polymerization for Glycopeptide Enrichment

The boronic acid-functionalized core-shell polymer nanoparticles, poly(N,N-methylenebisacrylamide-co-methacrylic acid)@4-vinylphenylboronic acid (poly(MBA-co-MAA)@VPBA), were successfully synthesized for enriching glycosylated peptides. Such nanoparticles were composed of a hydrophilic polymer core prepared by distillation precipitation polymerization (DPP) and a boronic acid-functionalized shell designed for capturing glycopeptides. Owing to the relatively large amount of residual vinyl groups introduced by DPP on the core surface, the VPBA monomer was coated with high efficiency, working as the shell. Moreover, the overall polymerization route, especially the use of DPP, made the synthesis of nanoparticles facile and time-saving. With the poly(MBA-co-MAA)@VPBA nanoparticles, 18 glycopeptides from horseradish peroxidase (HRP) digest were captured and identified by MALDI-TOF mass spectrometric analysis, relative to eight glycopeptides enriched by using commercially available meta-aminophenylboronic acid agarose under the same conditions. When the concentration of the HRP digest was decreased to as low as 5 nmol, glycopeptides could still be selectively isolated by the prepared nanoparticles. Our results demonstrated that the synthetic poly(MBA-co-MAA)@VPBA nanoparticles might be a promising selective enrichment material for glycoproteome analysis.

Integrated Sample Pretreatment System for N-Linked Glycosylation Site Profiling with Combination of Hydrophilic Interaction Chromatography and PNGase F Immobilized Enzymatic Reactor via a Strong Cation Exchange Precolumn

An integrated sample pretreatment system, composed of a click maltose hydrophilic interaction chromatography (HILIC) column, a strong cation exchange (SCX) precolumn, and a PNGase F immobilized enzymatic reactor (IMER), was established for the simultaneous glycopeptide enrichment, sample buffer exchange, and online deglycosylation, by which the sample pretreatment for glycoproteome could be performed online automatically, beneficial to improve the efficiency and sensitivity of the N-linked glycosylation site identification. With such a system, the deglycosylated glycopeptide from the digests of avidin with the coexistence of 50 times (mass ratio) BSA could be selectively detected, and the detection limit as low as 5 fmol was achieved. Moreover, the sample pretreatment time was significantly shortened to ~1 h. Such a system was further successfully applied for analyzing the digest of the soluble fraction extracted from rat brain. A total of 120 unique glycoprotein groups and 196 N-linked glycosylation sites were identified by nanoreversed phase liquid chromatography-electrospray ionization-tandem mass spectrometry (nanoRPLC-ESI-MS/MS), with the injected digests amount as 6 μg. All these results demonstrate that the integrated system is of great promise for N-linked glycosylation site profiling and could be further online coupled with nanoHPLC-ESI-MS/MS to achieve high-throughput glycoproteome analysis.

Boronate Affinity Monolith with a Gold Nanoparticle-Modified Hydrophilic Polymer as a Matrix for the Highly Specific Capture of Glycoproteins

As low abundance is the great obstacle for glycoprotein analysis, the development of materials with high efficiency and selectivity for glycoprotein enrichment is a prerequisite in glycoproteome research. Herein, we report a new kind of hydrophilic boronate affinity monolith by attaching 4-mercaptophenylboronic acid (MPBA) with 2-mercaptoethylamine (MPA) on the gold nanoparticle-modified poly(glycidyl methacrylate-co-poly(ethylene glycol) diacrylate)) monolith for glycoprotein enrichment. With poly(ethylene glycol) diacrylate as the cross-linker and the further modification of gold nanoparticles, the matrix has advantages of good hydrophilicity and enhanced surface area, which are beneficial to improve the enrichment selectivity and efficiency for glycoproteins. The attachment of MPBA and MPA provide intramolecular BN coordination, which could further enhance the specificity of glycoprotein capture. Such a boronate affinity monolith was applied to enrich horseradish peroxidase (HRP) from the mixture of HRP and bovine serum albumin (BSA), and high selectivity was obtained even at a mass ratio of 1:1000. In addition, the binding capacity of ovalbumin on such monolith reached 390 μg g(-1) . Furthermore, the average recovery of HRP on the prepared affinity monoliths was (84.8±1.9) %, obtained in three times enrichment with the same column. Finally, the boronate affinity monolith was successfully applied for the human-plasma glycoproteome analysis. As a result, 160 glycoproteins were credibly identified from 9 μg of human plasma, demonstrating the great potential of such a monolith for large-scale glycoproteome research.

Boronic Acid-Functionalized Particles with Flexible Three-Dimensional Polymer Branch for Highly Specific Recognition of Glycoproteins

A novel organic-inorganic hybrid particle with high hydrophilicity three-dimensional boronic acid functional polymer branches was facilely synthesized through thiol-ene surface-initiated click reaction, by which the target glycoprotein could be captured selectively in the 5000-fold disrupting protein. This highest selectivity ever reported demonstrated that this boronic acid functionalized particle exhibited great potential in the recognition of cis-diol-containing biomolecules, including the glycoproteins.

Large-scale N-glycoproteome map of rat brain tissue: Simultaneous characterization of insoluble and soluble protein fractions

The large‐scale N‐glycosylation analysis is critical for biomedical research, since a variety of diseases are found to be associated with glycoproteins. By a combination of glycoprotein analysis in insoluble protein fraction solubilized with 1% v/v 1‐butyl‐3‐methylimidazolium tetrafluoroborate (BMIM BF4) and those in soluble fraction, a total number of 462 non‐redundant N‐glycoprotein groups, including 316 transmembrane glycoproteins, were successfully identified. Correspondingly, 849 unique N‐glycosites were confidently recognized. The data set could provide a support for the further in‐depth research of brain N‐glycosylation, such as for the discovery of candidate drug targets and biomarkers.

An integrated sample pretreatment platform for quantitative N-glycoproteome analysis with combination of on-line glycopeptide enrichment, deglycosylation and dimethyl labeling

Relative quantification of N-glycoproteomes shows great promise for the discovery of candidate biomarkers and therapeutic targets. The traditional protocol for quantitative analysis of glycoproteomes is usually off-line performed, and suffers from long sample preparation time, and the risk of sample loss or contamination due to manual manipulation. In this study, a novel integrated sample preparation platform for quantitative N-glycoproteome analysis was established, with combination of online N-glycopeptide capture by a HILIC column, sample buffer exchange by a N2-assisted HILIC-RPLC interface, deglycosylation by a hydrophilic PNGase F immobilized enzymatic reactor (hIMER) and solid dimethyl labeling on a C18 precolumn. To evaluate the performance of such a platform, two equal aliquots of immunoglobulin G (IgG) digests were sequentially pretreated, followed by MALDI-TOF MS analysis. The signal intensity ratio of heavy/light (H/L) labeled deglycosylated peptides with the equal aliquots was 1.00 (RSD=6.2%, n=3), much better than those obtained by the offline protocol, with H/L ratio as 0.76 (RSD=11.6%, n=3). Additionally, the total on-line sample preparation time was greatly shortened to 160 min, much faster than that of offline approach (24h). Furthermore, such an integrated pretreatment platform was successfully applied to analyze the two kinds of hepatocarcinoma ascites syngeneic cell lines with high (Hca-F) and low (Hca-P) lymph node metastasis rates. For H/L labeled Hca-P lysates with the equal aliquots, 99.6% of log2 ratios (H/L) of quantified glycopeptides ranged from -1 to 1, demonstrating high accuracy of the developed sample preparation strategy. By triplicated analysis of glycopeptides and non-glycopeptides of Hca-F and Hca-P lysates, 43 up-regulated and 30 down-regulated (Hca-F/P) N-glycosylation sites, and 11 significantly changed N-glycoproteins were successfully quantified, and most of them were related to tumorigenesis and tumor metastasis. All these results demonstrate the developed integrated N-glycoprotein pretreatment platform is of great power for the accurate, precise and high-throughput analysis of N-glycoproteomes.

NSI and NSMT: usages of MS/MS fragment ion intensity for sensitive differential proteome detection and accurate protein fold change calculation in relative label-free proteome quantification.

Although widely applied in the label-free quantification of proteomics, spectral count (SC)-based abundance measurements suffer from the narrow dynamic range of attainable ratios, leading to the serious underestimation of true protein abundance fold changes, especially when studying biological samples that exhibit very large fold changes in protein expression. MS/MS fragment ion intensity, as an alternative to SC, has recently gained acceptance as the abundance feature of protein in label-free proteomic studies. Herein, we implemented two formats of MS/MS fragment ion intensity, Spectral Index (SI) and Summed MS/MS TIC (SMT), to alleviate this particular deficiency arising from SC. Both were in forms of replacing SC in the Normalized Spectral Abundance Factor (NSAF) formula, resulting in two algorithms, abbreviated as NSI and NSMT, respectively. The necessity of the normalization process was validated using a publicly available dataset. Furthermore, when applied to another well characterized benchmark dataset, both NSI and NSMT showed improved overall accuracy over NSAF for the relative quantification of proteomes. Hereinto, NSI enabled the sensitive detection of differentially expressed proteins, while NSMT ensured accurate calculation for protein abundance fold change. Therefore, the selective use of both algorithms might facilitate the screening and quantification of potential biomarkers on the proteome scale.

Glycoprotein recognition by water-compatible core–shell polymeric submicron particles

Biocompatible boronate core-shell polymeric particles were grown in a unique polymerization system via a one-pot strategy making full use of the residual soluble boronate oligomer to in situ build the core-shell structure. The obtained submicron particles were shown to exhibit excellent recognition affinity toward glycoproteins with high binding capacity and specificity.