Quantitative N-glycoproteomics characterization of differential N-glycosylation in Sorghum bicolor under salinity stress.

Salt stress is one of the significant environmental stresses that severely affect plant growth and development. Here, we report quantitative N-glycoproteomics characterization of differential N-glycosylation in Sorghum bicolor under low, median and high salinity stress. 21,621 intact N-glycopeptides coming from the combination of 127 N-glycan structures on 6574 N-glycosites from 5321 proteins were identified; differential N-glycosylation was observed for 682 N-glycoproteins which are mainly involved in the pathways of biosynthesis of secondary metabolites, biosynthesis of amino acids and several metabolic pathways. 41 N-glycan structures modifying on 338 N-glycopeptides from 122 glycoproteins were co-quantified and deregulated under at least one salt stress, including enzymes of energy production and carbohydrate metabolisms, cell wall organization related proteins, glycosyltransferases and so on. Intriguingly, with increasing salt concentration, there was an increase in the percentage of complex N-glycans on the altered N-glycopeptides. Furthermore, the observation of glycoproteins with distinct salt sensitivity is noteworthy, particularly the upregulated hyposensitive glycoproteins that predominantly undergo complex N-glycan modification. This is the first N-glycoproteome description of salt stress response at the intact N-glycopeptide level in sorghum and a further validation of data reported here would likely provide deeper insights into the stress physiology of this important crop plant.

Analysis of mutation-originated gain-of-glycosylation using mass spectrometry-based N-glycoproteomics.

RATIONALE: A general N-glycoproteomics analysis pipeline has been established for characterization of mutation-related gain-of-glycosylation (GoG) at intact N-glycopeptide molecular level, generating comprehensive site and structure information of N-glycosylation. METHODS: This study focused on mutation-originated GoG using a mass spectrometry-based N-glycoproteomics analysis workflow. In brief, GoG intact N-glycopeptide databases were built, consisting of 2701 proteins (potential GoG N-glycosites and amino acids derived from MUTAGEN, VARIANT and VAR_SEQ in UniProt) and 6709 human N-glycans (≤50 sequence isomers per monosaccharide composition). We employed the site- and structure-specific N-glycoproteomics workflow utilizing intact N-glycopeptides search engine GPSeeker to identify GoG intact N-glycopeptides from parental breast cancer stem cells (MCF-7 CSCs) and adriamycin-resistant breast cancer stem cells (MCF-7/ADR CSCs). RESULTS: With the criteria of spectrum-level false discovery rate control of ≤1%, we identified 87 and 94 GoG intact N-glycopeptides corresponding to 37 and 35 intact N-glycoproteins from MCF-7 CSCs and MCF-7/ADR CSCs, respectively. Micro-heterogeneity and macro-heterogeneity of N-glycosylation from GoG intact N-glycoproteins with VAR_SEQ and VARIANT were found in both MCF-7 CSCs and MCF-7/ADR CSCs systems. CONCLUSIONS: The integration of site- and structure-specific N-glycoproteomics approach, conjugating with GoG characterization, provides a universal workflow for revealing comprehensive N-glycosite and N-glycan structure information of GoG. The analysis of mutation-originated GoG can be extended to GoG characterization of other N-glycoproteome systems including complex clinical tissues and body fluids.

Deep structure-level N-glycan identification using feature-induced structure diagnosis integrated with a deep learning model.

Being a widely occurring protein post-translational modification, N-glycosylation features unique multi-dimensional structures including sequence and linkage isomers. There have been successful bioinformatics efforts in N-glycan structure identification using N-glycoproteomics data; however, symmetric "mirror" branch isomers and linkage isomers are largely unresolved. Here, we report deep structure-level N-glycan identification using feature-induced structure diagnosis (FISD) integrated with a deep learning model. A neural network model is integrated to conduct the identification of featured N-glycan motifs and boosts the process of structure diagnosis and distinction for linkage isomers. By adopting publicly available N-glycoproteomics datasets of five mouse tissues (17,136 intact N-glycopeptide spectrum matches) and a consideration of 23 motif features, a deep learning model integrated with a convolutional autoencoder and a multilayer perceptron was trained to be capable of predicting N-glycan featured motifs in the MS/MS spectra with previously identified compositions. In the test of the trained model, a prediction accuracy of 0.8 and AUC value of 0.95 were achieved; 5701 previously unresolved N-glycan structures were assigned by matched structure-diagnostic ions; and by using an explainable learning algorithm, two new fragmentation features of m/z = 674.25 and m/z = 835.28 were found to be significant to three N-glycan structure motifs with fucose, NeuAc, and NeuGc, proving the capability of FISD to discover new features in the MS/MS spectra.

Comprehensive characterization of differential glycation in hepatocellular carcinoma using tissue proteomics with stable isotopic labeling.

Glycation is a non-enzymatic posttranslational modification coming from the reaction between reducing sugars and free amino groups in proteins, where early glycation products (fructosyl-lysine, FL) and advanced glycation end products (AGEs) are formed. The occurrence of glycation and accumulation of AGEs have been closely associated with hepatocellular carcinoma (HCC). Here, we reported the characterization of differential glycation in HCC using tissue proteomics with stable isotopic labeling; early glycation-modified peptides were enriched with boronate affinity chromatography (BAC), and AGEs-modified peptides were fractionated with basic reversed-phase separation. By this integrated approach, 3717 and 1137 early and advanced glycated peptides corresponding to 4007 sites on 1484 proteins were identified with a false discovery rate (FDR) of no more than 1%. One hundred fifty-five sites were modified with both early and advanced end glycation products. Five early and 7 advanced glycated peptides were quantified to be differentially expressed in HCC tissues relative to paired adjacent tissues. Most (8 out of 10) of the proteins corresponding to the differential glycated peptides have previously been reported with dysregulation in HCC. The results together may deepen our knowledge of glycation as well as provide insights for therapeutics.

Mass spectrometry-based structure-specific N-glycoproteomics and biomedical applications.

N-linked glycosylation is a common posttranslational modification of proteins that results in macroheterogeneity of the modification site. However, unlike simpler modifications, N-glycosylation introduces an additional layer of complexity with tens of thousands of possible structures arising from various dimensions, including different monosaccharide compositions, sequence structures, linking structures, isomerism, and three-dimensional conformations. This results in additional microheterogeneity of the modification site of N-glycosylation, i.e., the same N-glycosylation site can be modified with different glycans with a certain stoichiometric ratio. N-glycosylation regulates the structure and function of N-glycoproteins in a site- and structure-specific manner, and differential expression of N-glycosylation under disease conditions needs to be characterized through site- and structure-specific quantitative analysis. Numerous advanced methods ranging from sample preparation to mass spectrum analysis have been developed to distinguish N-glycan structures. Chemical derivatization of monosaccharides, online liquid chromatography separation and ion mobility spectrometry enable the physical differentiation of samples. Tandem mass spectrometry further analyzes the macro/microheterogeneity of intact N-glycopeptides through the analysis of fragment ions. Moreover, the development of search engines and AI-based software has enhanced our understanding of the dissociation patterns of intact N-glycopeptides and the clinical significance of differentially expressed intact N-glycopeptides. With the help of these modern methods, structure-specific N-glycoproteomics has become an important tool with extensive applications in the biomedical field.

Structure-Specific N-Glycoproteomics Characterization of NIST Monoclonal Antibody Reference Material 8671.

The characteristics of monoclonal antibodies (mAbs) cohering various function effectors show great expectation in therapy. Glycosylation, one of the common post-translational modifications, deeply influences cohesion. It is necessary to grasp monosaccharide composition/sequence and glycan structures in mAbs. There has been comprehensive mass spectrometry characterization of N-glycosylation of mAbs, and monosaccharide compositions are deduced according to known biosynthetic rules. Our recently developed intact N-glycopeptide search engine GPSeeker has made structure-specific characterization of N-glycosylation possible with structure-diagnostic fragment ions from selective fragmentation of N-glycan moieties. Here, we report our structure-specific N-glycoproteomics characterization of NIST monoclonal antibody reference material 8671 using GPSeeker, and 59 N-glycan structures (including 16 pairs of isomers) are characterized.

Benchmark of site- and structure-specific quantitative tissue N-glycoproteomics for discovery of potential N-glycoprotein markers: a case study of pancreatic cancer.

Pancreatic cancer is a highly malignant tumor of the digestive tract that is difficult to diagnose and treat. It is more common in developed countries and has become one of the main causes of death in some countries and regions. Currently, pancreatic cancer generally has a poor prognosis, partly due to the lack of symptoms in the early stages of pancreatic cancer. Therefore, most cases are diagnosed at advanced stage. With the continuous in-depth research of glycoproteomics in precision medical diagnosis, there have been some reports on quantitative analysis of cancer-related cells, plasma or tissues to find specific biomarkers for targeted therapy. This research is based on the developed complete N-linked glycopeptide database search engine GPSeeker, combined with liquid-mass spectrometry and stable diethyl isotope labeling, providing a benchmark of site- and structure-specific quantitative tissue N-glycoproteomics for discovery of potential N-glycoprotein markers. With spectrum-level FDR ≤1%, 20,038 intact N-Glycopeptides corresponding to 4518 peptide backbones, 228 N-glycan monosaccharide compositions 1026 N-glycan putative structures, 4460 N-glycosites and 3437 intact N-glycoproteins were identified. With the criteria of ≥1.5-fold change and p value<0.05, 52 differentially expressed intact N-glycopeptides (DEGPs) were found in pancreatic cancer tussues relative to control, where 38 up-regulated and 14 down-regulated, respectively.

Site- and structure-specific characterization of the human urinary N-glycoproteome with site-determining and structure-diagnostic product ions.

RATIONALE: N-glycosylation is one of the most common protein post-translational modifications; it is extremely complex with multiple glycoforms from different monosaccharide compositions, sequences, glycosidic linkages, and anomeric positions. Each glycoform functions with a particular site- and structure-specific N-glycan that can be fully characterized using state-of-the-art tandem mass spectrometry (MS/MS) and the intact N-glycopeptide database search engine GPSeeker that we recently developed. Urine has recently gained increasing attention as a non-invasive source for disease marker discovery. In this study, we report our structure-specific N-glycoproteomics study of human urine. METHODS: We performed trypsin digestion, Zwitterionic Hydrophilic Interaction chromatography (ZIC-HILIC) enrichment, C18-RPLC/nano-ESI-MS/MS using HCD with stepped normalized collisional energies, and GPSeeker database search for a comprehensive site- and structure-specific N-glycoproteomics characterization of the human urinary N-glycoproteome at the intact N-glycopeptide level. For this, we used b/y product ion pairs from the GlcNAc-containing site-determining peptide backbone and structure-diagnostic product ions from the N-glycan moieties, respectively. RESULTS: We identified 2986 intact N-glycopeptides with comprehensive site and structure information for the peptide backbones (amino acid sequences and N-glycosites) and the N-glycan moieties (monosaccharide compositions, sequences/linkages). The 2986 intact N-glycopeptide IDs corresponded to 754 putative N-glycan linkage structures on 419 N-glycosites of 450 peptide backbones from 327 intact N-glycoproteins. Next, 146 linkage structures and 200 N-glycosites were confirmed with structure-diagnostic and GlcNAc-containing site-determining product ions, respectively. CONCLUSIONS: We found 106 new N-glycosites not annotated in the current UniProt database. The elution-abundance patterns of urinary intact N-glycopeptide oxonium ions (m/z 138 and 204) of the same subject were temporally stable during the day and over 6 months. These patterns are rather different among different subjects. The results implied an interesting possibility that glycopeptide oxonium ion patterns could serve as distinguishing markers between individuals and/or between physiological and pathological states.

Genome­wide association study and genomic prediction for growth traits in yellow-plumage chicken using genotyping-by-sequencing.

BACKGROUND: Growth traits are of great importance for poultry breeding and production and have been the topic of extensive investigation, with many quantitative trait loci (QTL) detected. However, due to their complex genetic background, few causative genes have been confirmed and the underlying molecular mechanisms remain unclear, thus limiting our understanding of QTL and their potential use for the genetic improvement of poultry. Therefore, deciphering the genetic architecture is a promising avenue for optimising genomic prediction strategies and exploiting genomic information for commercial breeding. The objectives of this study were to: (1) conduct a genome-wide association study to identify key genetic factors and explore the polygenicity of chicken growth traits; (2) investigate the efficiency of genomic prediction in broilers; and (3) evaluate genomic predictions that harness genomic features. RESULTS: We identified five significant QTL, including one on chromosome 4 with major effects and four on chromosomes 1, 2, 17, and 27 with minor effects, accounting for 14.5 to 34.1% and 0.2 to 2.6% of the genomic additive genetic variance, respectively, and 23.3 to 46.7% and 0.6 to 4.5% of the observed predictive accuracy of breeding values, respectively. Further analysis showed that the QTL with minor effects collectively had a considerable influence, reflecting the polygenicity of the genetic background. The accuracy of genomic best linear unbiased predictions (BLUP) was improved by 22.0 to 70.3% compared to that of the conventional pedigree-based BLUP model. The genomic feature BLUP model further improved the observed prediction accuracy by 13.8 to 15.2% compared to the genomic BLUP model. CONCLUSIONS: A major QTL and four minor QTL were identified for growth traits; the remaining variance was due to QTL effects that were too small to be detected. The genomic BLUP and genomic feature BLUP models yielded considerably higher prediction accuracy compared to the pedigree-based BLUP model. This study revealed the polygenicity of growth traits in yellow-plumage chickens and demonstrated that the predictive ability can be greatly improved by using genomic information and related features.

Quantitative site- and structure-specific N-glycoproteomics characterization of differential N-glycosylation in MCF-7/ADR cancer stem cells.

BACKGROUND: Cancer stem cells (CSCs) are reported to be responsible for tumor initiation, progression, metastasis, and therapy resistance where P-glycoprotein (P-gp) as well as other glycoproteins are involved. Identification of these glycoprotein markers is critical for understanding the resistance mechanism and developing therapeutics. METHODS: In this study, we report our comparative and quantitative site- and structure-specific N-glycoproteomics study of MCF-7/ADR cancer stem cells (CSCs) vs. MCF-7/ADR cells. With zic-HILIC enrichment, isotopic diethyl labeling, RPLC-MS/MS (HCD) analysis and GPSeeker DB search, differentially expressed N-glycosylation was quantitatively characterized at the intact N-glycopeptide level. RESULTS: 4016 intact N-glycopeptides were identified with spectrum-level FDR ≤ 1%. With the criteria of ≥ 1.5 fold change and p value < 0.05, 247 intact N-glycopeptides were found differentially expressed in MCF-7/ADR CSCs as putative markers. Raw data are available via ProteomeXchange with identifier PXD013836. CONCLUSIONS: Quantitative site- and structure-specific N-glycoproteomics characterization may help illustrate the cell stemness property.

Separation and detection of minimal length glycopeptide neoantigen epitopes centering the GSTA region of MUC1 by liquid chromatography/mass spectrometry.

RATIONALE: We previously isolated antibodies binding to glycopeptide neoantigen epitopes centering the GSTA sequence of the highly glycosylated tandem repeat region of MUC1. Epitopes centering the GSTA sequence are also predicted by NetMHC programs to bind to MHC molecules. Detecting MUC1 glycopeptide epitopes remains a challenge since antigenic epitopes are often shorter than 10 amino acids. METHODS: In this study, we used pronase from Streptomyces griseus, which has no amino acid sequence preference for enzymatic cleavage sites, to digest synthetic glycopeptides RPAPGST (Tn)APPAHG and RPAPGS (Tn)TAPPAHG, and analyzed the digests by liquid chromatography/mass spectrometry (LC/MS) using electron transfer dissociation (ETD) and higher-energy collisional dissociation (HCD) methods with an Orbitrap Fusion Lumos Tribid mass spectrometer. RESULTS: We found that short glycopeptides containing 8 to 11 amino acids could be efficiently generated by pronase digestion. Such glycopeptides of minimal epitope lengths were clearly distinguished by characteristic MS/MS ion patterns and LC elution profiles. A glycopeptide library was generated which may serve as a standard for measuring neoantigen epitopes centering the GSTA sequence. CONCLUSIONS: Our data established the LC/MS/MS identities of a clinically relevant MUC1 glycopeptide neoantigen epitope centering the GSTA motif. A library of short MUC1 glycopeptides centered on the GSTA motif was created, which is a critical step for analysis of such antigen epitopes in real biological samples.

A quantitative N-glycoproteomics study of cell-surface N-glycoprotein markers of MCF-7/ADR cancer stem cells.

Isotopic-labeling quantitative N-glycoproteomics characterization of cell-surface differentially expressed N-glycosylation in MCF-7/ADR cancer stem cells (CSCs) relative to MCF-7/ADR cells was carried out at the intact N-glycopeptide level with trypsin digestion, ZIC-HILIC enrichment, isotopic diethyl labeling, RPLC-MS/MS analysis of the 1:1 mixture, and GPSeeker DB search. With a spectrum-level false discovery rate of ≤ 1%, 1,336 intact N-glycopeptides from the combination of 301 unique peptide backbones and 169 putative N-glycan linkages (52 monosaccharide compositions) were identified; the corresponding intact N-glycoproteins and N-glycosites were 289 and 305, respectively, among which 176 N-glycosites were confirmed with GlcNAc-containing site-determining b/y fragment ion pairs. The N-glycan moieties in 546 intact N-glycopeptide IDs were identified with more than one structure-diagnostic fragment ions where multiple linkage structures exist for each of the monosaccharide compositions. With the criteria of ≥ 1.5-fold change and p value < 0.05, 72 cell-surface differentially expressed intact N-glycopeptides (DEGPs) were found in MCF-7/ADR CSCs relative to MCF-7/ADR cells, where 8 and 64 were downregulated and upregulated, respectively. Graphical abstract.

GPSeeker Enables Quantitative Structural N-Glycoproteomics for Site- and Structure-Specific Characterization of Differentially Expressed N-Glycosylation in Hepatocellular Carcinoma.

N-Glycosylation, being one of the most common and complex protein post-translational modifications (PTMs), is known to have microheterogeneity with the presence of different N-glycan structures at a single specific glycosite. These different structures may have exactly the same monosaccharide composition but totally different differential expressions and pathological relevance. Mass spectrometry-based N-glycoproteomics has so far been successful in large-scale characterization of these N-glycans at the composition level, and structure-level identification and quantitation is urgently needed. Here we report our development of the intact N-glycopeptide search engine GPSeeker and the GPSeeker-centered quantitative structural N-glycoproteomics pipeline. In benchmark characterization of differentially expressed N-glycosylation in hepatocellular carcinoma HepG2 cells relative to LO2 cells, 5 405 and 1 081 intact N-glycopeptides with putative linkage structures were identified and quantified with isotopic dimethyl labeling and 2D liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Among the 5 405 IDs, 837 were identified with no less than one structure diagnostic fragment ion for the N-glycan moieties. Besides double isomers of sialic acid linkages and fucose sequences, quadruple isomers from combination of two linages and two sequences were chromatographically separated and confidently identified; microheterogeneity with different differentially expressions were observed on 183 out of the 231 quantified N-glycosites. This GPSeeker-centered quantitative structural N-glycoproteomics pipeline can be widely applied to precise qualitative and quantitative characterization of N-glycosylation with physiological and pathological relevance.

Comparative Glycomics Study of Cell-Surface N-Glycomes of HepG2 versus LO2 Cell Lines.

Cell-surface N-glycans play important roles in both inter- and intracellular processes, including cell adhesion and development, cell recognition, as well as cancer development and metastasis; detailed structural characterization of these N-glycans is thus paramount. Here we report our comparative N-glycomics study of cell-surface N-glycans of the hepatocellular carcinoma (HCC) HepG2 cells vs the normal liver LO2 cells. With sequential trypsin digestion of proteins, C18 depletion of peptides without glycosylation, PNGase F digestion of N-glycopeptides, PGC enrichment of N-glycans, CH3I permethylation of the enriched N-glycans, cell-surface N-glycomes of the HepG2 and LO2 cells were analyzed using C18-RPLC-MS/MS (HCD). With spectrum-level FDR no bigger than 1%, 351 and 310 N-glycans were identified for HepG2 and LO2, respectively, with comprehensive structural information (not only monosaccharide composition, but also sequence and linkage) by N-glycan database search engine GlySeeker. The percentage of hybrid N-glycans with tetra-antennary structures was substantially increased in the HepG2 cells. This comprehensive discovery study of differentially expressed cell-surface N-glycans in HepG2 vs LO2 serves as a solid reference for future validation study of glycosylation markers in HCC.

Selective fragmentation of the N-glycan moiety and protein backbone of ribonuclease B on an Orbitrap Fusion Lumos Tribrid mass spectrometer.

RATIONALE: The functional study and application of an intact glycoprotein require the structural characterization of both the protein backbone and the glycan moiety; the former has been successfully demonstrated with selective fragmentation of the protein backbone in CID and ExD; whether the latter can be achieved with selective fragmentation of the glycan moiety remains to be explored. METHODS: RNase B solution was electrosprayed and its intact glycoforms of GlcNAc2 Mann (n = 5-9) with the highest abundance (charge state z = 16) were isolated individually and fragmented using CID, ETD, HCD, ETciD, and EThcD on the Orbitrap Fusion Lumos Tribrid mass spectrometer; the dissociation parameters were optimized for selective fragmentation of the N-glycan moiety and protein backbone as well as high sequence coverage. The obtained spectra were interpreted using the protein and N-glycan database search engines ProteinGoggle and GlySeeker, respectively. RESULTS: With exploration of different dissociation parameters for all the five methods, selective fragmentation of the N-glycan moiety (the protein backbone staying intact) was observed in both HCD and EThcD at low collisional energies, but only a few matched product ions were observed; more comprehensive fragmentation was observed at high collisional energies (the protein backbone lost). Selective protein backbone fragmentation was observed in all the five dissociation methods. CONCLUSIONS: For comprehensive structural characterization of intact N-glycoproteins using tandem mass spectrometry, the composition and topology of the N-glycan moiety can be identified using HCD and EThcD complementarily at low and high energies; while the amino acid sequence and glycosite can be identified using CID, ETD, HCD, ETciD, and EThcD with their optimal dissociation parameters.

Large-scale identification and visualization of N-glycans with primary structures using GlySeeker.

RATIONALE: Most of the current popular tandem mass spectrometers have the capability of resolving the primary structures (monosaccharide composition, sequence and linkage) of N-glycans; however, compositions or putative structures have mostly been reported so far. Identification and visualization tools of N-glycans are needed. METHODS: The isotopic mass-to-charge ratio and envelope fingerprinting algorithm, which has been successfully used for intact protein database search and identification, was adapted for N-glycan database search, and a stand-alone N-glycan database search engine, GlySeeker, for automated N-glycan identification and visualization was developed and successfully benchmarked. Both pseudo 2D graph and one-line text formats with one-letter symbols for monosaccharides were proposed for representing N-glycans. N-glycans were identified with comprehensive interpretation of product ions and false discovery rate (FDR) control. RESULTS: In a database search of reversed-phase liquid chromatography/tandem mass spectrometry (RPLC/MS/MS) datasets of the N-glycome enriched from OVCAR-3 ovarian cancer cells, with FDR ≤1% and number of best hits (NoBHs) = 1-30, 1525 N-glycans with comprehensive primary structural information (composition, sequence and linkage) were identified and visualized; among these 1525 N-glycans, 559 had NoBHs = 1, i.e. their structures were uniquely identified. This represents a large-scale identification and visualization of N-glycans with primary structures from tandem mass spectra. CONCLUSIONS: A stand-alone N-glycan database search engine called GlySeeker has been developed for large-scale identification and visualization of N-glycans with comprehensive interpretation of tandem mass spectra and FDR control.

Large-scale identification and visualization of human liver N-glycome enriched from LO2 cells.

Aberrant glycosylation has been commonly observed in various physiological and pathological disorders (including cancers), and quite a few glycoproteins have been approved by the US Food and Drug Administration (FDA) as markers for early diagnosis. Each glycoprotein may have multiple glycoforms, and cancer-related ones can be only some specific glycoforms which have much higher sensitivity and specificity; for example, AFP glycoform AFP-L3 with N-glycan of 01Y(61F)41Y41M(31M41Y41L41S61M41Y41L41S is of bigger diagnostic value for hepatocellular carcinoma than total AFP (i.e., combination of all glycoforms). Mass spectrometry-based glycomics is currently the state-of-the-art instrumental analytical pipeline for high-throughput characterization of various glycoforms, where not only monosaccharide composition but also comprehensive structural information (sequence and linkage) of N-glycans are now reported thanks to our recently developed N-glycan database search engine GlySeeker. With this new capability, here, we report our large-scale characterization of human liver N-glycome with primary structures; 214 unique N-glycans with unique primary structures were identified and visualized with spectrum-level false discovery rate ≤ 1% and number of best hits of 1. The LO2 N-glycans reported here serve as a basic reference for future liver N-glycome study, and further quantitative analysis will enable characterization of differentially expressed N-glycans and discovery of more effective markers for liver and other diseases. Data are available via ProteomeXchange with identifier PXD008158.

Facile synthesis of titanium(IV) ion-immobilized poly-glycidyl methacrylate microparticles functionalized with polyethylenimine and adenosine triphosphate for highly specific enrichment of intact phosphoproteins.

In this study, a facile synthesis of the titanium(IV) ion-immobilized poly-glycidyl methacrylate microparticles functionalized with polyethylenimine and adenosine triphosphate was developed for efficient enrichment of intact phosphoproteins. The titanium(IV) ion-immobilized microparticles had higher saturated adsorption capacity for phosphoproteins (1217.6 mg/g for ß-casein) than nonphosphoproteins (97.1 mg/g for bovine serum albumin) and the average particle diameter was about 1.4 µm with good dispersibility. In application, as demonstrated by SDS-PAGE, titanium(IV) ion-immobilized microparticles exhibited good performance in enriching intact phosphoproteins from standard protein mixtures of ß-casein and bovine serum albumin with high specificity and selectivity. In addition, titanium(IV) ion-immobilized microparticles were also successfully applied in intact phosphoprotein enrichment from complex biological samples including nonfat milk, chicken egg white, and mouse heart tissue extract.

Intact Protein Quantitation Using Pseudoisobaric Dimethyl Labeling.

Protein structural and functional studies rely on complete qualitative and quantitative information on protein species (proteoforms); thus, it is important to quantify differentially expressed proteins at their molecular level. Here we report our development of universal pseudoisobaric dimethyl labeling (pIDL) of amino groups at both the N-terminal and lysine residues for relative quantitation of intact proteins. Initial proof-of-principle study was conducted on standard protein myoglobin and hepatocellular proteomes (HepG2 vs LO2). The amino groups from both the N-terminal and lysine were dimethylated with HXHO (X = (13)C or C) and NaBY3CN (Y = H or D). At the standard protein level, labeling efficiency, effect of product ion size, and mass resolution on quantitation accuracy were explored; and a good linear quantitation dynamic range up to 50-fold was obtained. For the hepatocellular proteome samples, 33 proteins were quantified with RSD ≤ 10% from one-dimensional reversed phase liquid chromatography-tandem mass spectrometry (RPLC-MS/MS) analysis of the 1:1 mixed samples. The method in this study can be extended to quantitation of other intact proteome systems. The universal "one-pot" dimethyl labeling of all the amino groups in a protein without the need of preblocking of those on the lysine residues is made possible by protein identification and quantitation analysis using ProteinGoggle 2.0 with customized databases of both precursor and product ions containing heavy isotopes.

Mass measurement accuracy of the Orbitrap in intact proteome analysis.

RATIONALE: The mass measurement accuracy (MMA) of Orbitrap mass spectrometers is 1-5 ppm according to the manufacturer's specification; yet, up to 50 ppm has been used as mass tolerance to interpret Orbitrap data in the literature. A systematic evaluation of MMA is thus necessary to find the optimal mass tolerance to be used. METHODS: Reversed-phase liquid chromatography/tandem mass spectrometry (RPLC/MS/MS) analyses of the intact E. coli proteome were carried out on a Q Exactive Orbitrap mass spectrometer coupled to a Dionex UltiMate 3000 RSLCnano system. The analysis included three technical replicates each day and was repeated for six continuous days right after a mass calibration. The obtained raw datasets were searched using ProteinGoggle 2.0 under four different mass tolerances of 5, 10, 15, and 20 ppm. RESULTS: With both forward and random database searches and FDR ≤1% at the spectrum level, the most protein spectrum matches and protein IDs were obtained at a mass tolerance of 15 ppm. The average mass accuracy of both precursor and product ions from three representative high, medium, and low abundance proteins as well as the common proteins identified in all the 18 replicate runs was found to be 0-4 ppm; and no significant drift of measured mass accuracy was observed within the calibration period of 1 week. CONCLUSIONS: Despite the mass measurement accuracy of 1-5 ppm of the Orbitrap stated by the manufacturer, the optimal mass tolerance for protein identification was found to be 15 ppm for both the precursor and product ions. Weekly mass calibration is appropriate because no significant drift in MMA was found within the 6-day period. Copyright © 2016 John Wiley & Sons, Ltd.