Advanced assessment through intact glycopeptide analysis of Infliximab’s biologics and biosimilar

Characterization of therapeutic monoclonal antibodies (mAbs) represents a major challenge for analytical sciences due to their heterogeneity associated with post-translational modifications (PTMs). The protein glycosylation requires comprehensive identification, which could influence on the mAbs’ structure and their function. Here, we demonstrated high-resolution tandem mass spectrometry with an ultra-high-performance liquid chromatography for characterization and comparison between biologics and biosimilar of infliximab at an advanced level. Comparing the N- and O-glycopeptides profiles, a total of 49 and 54 glycopeptides was identified for each product of the biologics and biosimilar, respectively. We also discovered one novel N-glycosylation site at the light chain from both biopharmaceuticals and one novel O-glycopeptide at the heavy chain from only biosimilar. Site-specific glycopeptide analysis process will be a robust and useful technique for evaluating therapeutic mAbs and complex glycoprotein products.

Defect in cytosolic Neu2 sialidase abrogates lipid metabolism and impairs muscle function in vivo

Sialic acid (SA) is present in glycoconjugates and important in cell–cell recognition, cell adhesion, and cell growth and as a receptor. Among the four mammalian sialidases, cytosolic NEU2 has a pivotal role in muscle and neuronal differentiation in vitro. However, its biological functions in vivo remain unclear due to its very low expression in humans. However, the presence of cytoplasmic glycoproteins, gangliosides, and lectins involved in cellular metabolism and glycan recognition has suggested the functional importance of cytosolic Neu2 sialidases. We generated a Neu2 knockout mouse model via CRISPR/Cas9-mediated genome engineering and analyzed the offspring littermates at different ages to investigate the in vivo function of cytosolic Neu2 sialidase. Surprisingly, knocking out the Neu2 gene in vivo abrogated overall lipid metabolism, impairing motor function and leading to diabetes. Consistent with these results, Neu2 knockout led to alterations in sialylated glycoproteins involved in lipid metabolism and muscle function, as shown by glycoproteomics analysis.

Flashlight into the Function of Unannotated C11orf52 using Affinity Purification Mass Spectrometry

For an enhanced understanding of the biological mechanisms of human disease, it is essential to investigate protein functions. In a previous study, we developed a prediction method of gene ontology (GO) terms by the I-TASSER/COFACTOR result, and we applied this to uPE1 in chromosome 11. Here, to validate the bioinformatics prediction of C11orf52, we utilized affinity purification and mass spectrometry to identify interacting partners of C11orf52. Using immunoprecipitation methods with three different peptide tags (Myc, Flag, and 2B8) in HEK 293T cell lines, we identified 79 candidate proteins that are expected to interact with C11orf52. The results of a pathway analysis of the GO and STRING database with candidate proteins showed that C11orf52 could be related to signaling receptor binding, cell-cell adhesion, and ribosome biogenesis. Then, we selected three partner candidates of DSG1, JUP, and PTPN11 for verification of the interaction with C11orf52 and confirmed them by colocalization at the cell-cell junctions by coimmunofluorescence experiments. On the basis of this study, we expect that C11orf52 is related to the Wnt signaling pathway via DSG1 from the protein-protein interactions, given the results of a comprehensive analysis of the bioinformatic predictions. The data set is available at the ProteomeXchange consortium via PRIDE repository (PXD026986).

Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.

Depletion of ST6GALNACIII retards A549 non-small cell lung cancer cell proliferation by downregulating transferrin receptor protein 1 expression

Alterations in sialylation of terminal residues of glycoproteins have been implicated in forming tumor-associated glycans. ST6GALNAC transfers sialyl moiety to N-acetylgalactosamine residue via α2,6 linkage. Although the oncogenic characteristics of ST6GALNACI or II have been demonstrated in various cancer cells, the impact of ST6GALNACIII on tumor progression remains undefined. In this study, we evaluated the effect of ST6GALNACIII knockdown on the growth of A549 non-small cell lung cancer cells. ST6GALNACIII depletion resulted in significant retardation in growth of A549 cells under various culture conditions, including collagen-supported 3D culture and anchorage-independent soft agar culture conditions. Liquid chromatography with tandem mass spectrometry revealed that two glycopeptides of transferrin receptor protein 1 (TFR1) containing N-acetylhexosamine-sialic acid were not detected in ST6GALNACIII-depleted A549 cells compared with control cells. Subsequent lectin binding assay, western blotting, and real-time RT-PCR indicated that TFR1 sialylation was not significantly changed, but TFR1 protein and mRNA expressions were decreased after ST6GALNACIII knockdown. However, cell growth retardation by ST6GALNACIII knockdown was partially rescued by TFR1 overexpression. Additionally, TFR1 mRNA degradation was accelerated following ST6GALNACIII knockdown with concomitant reduction in mRNA levels of iron regulatory protein 1 and 2, the upstream regulators of TFR1 mRNA stability. Therefore, our results indicated an important role of ST6GALNACIII in promoting A549 cell growth through quantitative regulation of TFR1 expression and provided therapeutic implications for ST6GALNACIII targeting in tumor growth suppression in vivo.

Measuring fucosylated alpha-fetoprotein in hepatocellular carcinoma: A comparison of μTAS and parallel reaction monitoring

PURPOSE

Fucosylation of alpha-fetoprotein (AFP) is closely correlated with the diagnosis of patients with hepatocellular carcinoma (HCC). In current, a micro-total analysis system (μTAS) using immunoassay has been developed for determining fucosylated AFP EXPERIMENTAL DESIGN: We compared two analytical methods, μTAS and liquid chromatography-parallel reaction monitoring mass spectrometry (LC-PRM MS), for the measurement of fucosylated AFP in serum to evaluate the usefulness of the results. For this purpose, serum samples were used (cirrhosis, n = 105; HCC, n = 105), and we have discussed the analytical performance of these two methods RESULTS: We observed a correlation (R²  = 0.84) between LC-PRM MS and μTAS using samples where fucosylated levels were measured by both methods. The fucosylated level of AFP by LC-PRM MS better differentiated between cirrhosis and HCC patients than those by μTAS (AUC = 0.910 vs. 0.861), particularly in subgroups with a level of total AFP < 20 ng/mL (0.973 vs. 0.874) and in early stage (I and II) patients (0.922 vs. 0.835) CONCLUSIONS AND CLINICAL RELEVANCE: From this comparative study we can suggest that the LC-PRM MS is applicable in the measurement of fucosylated AFP from human serum and is more useful for early diagnosis of HCC.

CLINICAL RELEVANCE

Fucosylation of AFP is used for the detection of HCC. A micro-total analysis system (μTAS) has been only developed for measuring fucosylation of AFP in clinical research. This study reports the fucosylation of AFP in human serum samples from cirrhosis and HCC patients using the μTAS and a LC-PRM MS to evaluate fucosylation of AFP from each method. As a result, LC-PRM MS is complementary to the conventional μTAS method. Furthermore, LC-PRM MS provides a higher diagnostic accuracy than the μTAS in patients with low AFP levels and an early stage.

Activation of mitochondrial TUFM ameliorates metabolic dysregulation through coordinating autophagy induction

Disorders of autophagy, a key regulator of cellular homeostasis, cause a number of human diseases. Due to the role of autophagy in metabolic dysregulation, there is a need to identify autophagy regulators as therapeutic targets. To address this need, we conducted an autophagy phenotype-based screen and identified the natural compound kaempferide (Kaem) as an autophagy enhancer. Kaem promoted autophagy through translocation of transcription factor EB (TFEB) without MTOR perturbation, suggesting it is safe for administration. Moreover, Kaem accelerated lipid droplet degradation in a lysosomal activity-dependent manner in vitro and ameliorated metabolic dysregulation in a diet-induced obesity mouse model. To elucidate the mechanism underlying Kaem’s biological activity, the target protein was identified via combined drug affinity responsive target stability and LC–MS/MS analyses. Kaem directly interacted with the mitochondrial elongation factor TUFM, and TUFM absence reversed Kaem-induced autophagy and lipid degradation. Kaem also induced mitochondrial reactive oxygen species (mtROS) to sequentially promote lysosomal Ca²⁺ efflux, TFEB translocation and autophagy induction, suggesting a role of TUFM in mtROS regulation. Collectively, these results demonstrate that Kaem is a potential therapeutic candidate/chemical tool for treating metabolic dysregulation and reveal a role for TUFM in autophagy for metabolic regulation with lipid overload.

Kim, Hwang et al. use in vitro and in vivo models of autophagy disorder/metabolic dysfunction to show that in this context, the natural compound kaempferide is an autophagy enhancer and reveal that one of the underlying mechanisms governing this is mediated by the mitochondrial elongation factor TUFM. This insight may have therapeutic value in the treatment of metabolic disorders.

Computational classification of core and outer fucosylation of N-glycoproteins in human plasma using collision-induced dissociation in mass spectrometry

RATIONALE

Glycoprotein fucosylation, one of the major posttranslational modifications, is known to be highly involved in proteins related to various cancers. Fucosylation occurs in the core and/or outer sites of N-glycopeptides. Elucidation of the fucosylation type of N-glycoproteins is therefore important. However, it has remained a challenge to classify the fucosylation types of N-glycopeptides using collision-induced dissociation (CID) tandem mass (MS/MS) spectra.

METHODS

The relative intensities of the Y₁ F, Y₂ F, Y₃ F, and Y₄ F product ions in the CID-MS/MS spectra of the IgG N-glycopeptides were measured for core fucosylation. The Core Fucose Index (CFI) was then calculated by multiplication of the relative intensities with a weight factor from logistic regression to differentiate between the core and none fucosylation. From the relative intensities of the B₂ F and B₃ SF ions of the MS/MS spectra of the AGP N-glycopeptides for outer fucosylation, the Outer Fucose Index (OFI) was calculated to differentiate between the outer and none fucosylation.

RESULTS

In order to classify core and/or outer fucosylation of N-glycoproteins, we defined the fucosylation score (F-score) by a sigmoidal equation using a combination of the CFI and the OFI. For application, we classified the fucosylation types of N-glycoproteins in human plasma with 99.7% accuracy from the F-score. Human plasma samples showed 54.4%, 33.3%, 10.3%, and 1.6% for none, core, outer, and dual fucosylated N-glycopeptides, respectively. Core fucosylation was abundant at mono- and bi-antennary N-glycopeptides. Outer fucosylation was abundant at tri- and tetra-antennary N-glycopeptides. In total, 113 N-glycopeptides of 29 glycoproteins from 3365 glycopeptide spectral matches (GPSMs) were classified for different types of fucosylation.

CONCLUSIONS

We established an F-score to classify three different fucosylation types: core, outer, and dual types of N-glycopeptides. The fucosylation types of 20 new N-glycopeptides from 11 glycoproteins in human plasma were classified using the F-score. Therefore, the F-score can be useful for the automatic classification of different types of fucosylation in N-glycoproteins of biological fluids including plasma, serum, and urine.

Bioinformatic Prediction of Gene Ontology Terms of Uncharacterized Proteins from Chromosome 11

In chromosome 11, 71 out of its 1254 proteins remain functionally uncharacterized on the basis of their existence evidence (uPE1s) following the latest version of neXtProt (release 2020-01-17). Because in vivo and in vitro experimental strategies are often time-consuming and labor-intensive, there is a need for a bioinformatics tool to predict the function annotation. Here, we used I-TASSER/COFACTOR provided on the neXtProt web site, which predicts gene ontology (GO) terms based on the 3D structure of the protein. I-TASSER/COFACTOR predicted 2413 GO terms with a benchmark dataset of the 22 proteins belonging to PE1 of chromosome 11. In this study, we developed a filtering algorithm in order to select specific GO terms using the GO map generated by I-TASSER/COFACTOR. As a result, 187 specific GO terms showed a higher average precision-recall score at the least cellular component term compared to 2413 predicted GO terms. Next, we applied 65 proteins belonging to uPE1s of chromosome 11, and then 409 out of 6684 GO terms survived, where 103 and 142 GO terms of molecular function and biological process, respectively, were included. Representatively, the cellular component GO terms of CCDC90B, C11orf52, and the SMAP were predicted and validated using the overexpression system into 293T cells and immunofluorescence staining. We will further study their biological and molecular functions toward the goal of the neXt-CP50 project as a part of C-HPP. We shared all results and programs in Github (https://github.com/heeyounh/I-TASSER-COFACTOR-filtering.git).

Selective Identification of α-Galactosyl Epitopes in N-Glycoproteins Using Characteristic Fragment Ions from Higher-Energy Collisional Dissociation

The α-galactosyl epitope is a terminal N-glycan moiety of glycoproteins found in mammals except in humans, and thus, it is recognized as an antigen that provokes an immunogenic response in humans. Accordingly, it is necessary to analyze the α-galactosyl structure in biopharmaceuticals or organ transplants. Due to an identical glycan composition and molecular mass between α-galactosyl N-glycans and hybrid/high-mannose-type N-glycans, it is challenging to characterize α-galactosyl epitopes in N-glycoproteins using mass spectrometry. Here, we describe a method to identify α-galactosyl N-glycopeptides in mice glycoproteins using liquid chromatography with tandem mass spectrometry with higher-energy collisional dissociation (HCD). The first measure was an absence of [Y_HM] ion peaks in the HCD spectra, which was exclusively observed in hybrid and/or high-mannose-type N-glycopeptides. The second complementary criterion was the ratio of an m/z 528.19 (Hex₂HexNAc₁) ion to m/z 366.14 (Hex₁HexNAc₁) ion (I_m/z528/I_m/z366). The measure of [I_m/z528/I_m/z366 > 0.3] enabled a clear-cut determination of α-galactosyl N-glycopeptides with high accuracy. In Ggta1 knockout mice, we could not find any α-galactosyl N-glycoproteins identified in WT mice plasma. Using this method, we could screen for α-galactosyl N-glycoproteins from mice spleen, lungs, and plasma samples in a highly sensitive and specific manner. Conclusively, we suggest that this method will provide a robust analytical tool for determination of α-galactosyl epitopes in pharmaceuticals and complex biological samples.

DNA Polymerase Alpha Subunit B Is a Binding Protein for Erlotinib Resistance in Non-Small Cell Lung Cancer

Simple Summary

Non-small-cell lung carcinoma (NSCLC) covers for almost 85% of all lung cancers and a major contributor to the overall cancer death rate. Erlotinib is used to treat NSCLC via inhibition of epithelial growth factor receptor (EGFR) kinase activity. Despite its high efficacy, recurrence can occur in patients who become resistant to the drug. We performed DARTS LC-MS/MS with SWATH of DIA analysis and identified a novel binding protein of Erlotinib that may underlie NSCLC resistance. Our study indicated that Erlotinib binds POLA2 in addition to EGFR. This was confirmed by DARTS and CETSA results. Importantly, POLA2 expression levels in four NSCLC cell lines were positively correlated with anti-proliferative Erlotinib efficacy (Pearson correlation coefficient, R = 0.9886). These results suggest that POLA2 is a novel complementary target protein of Erlotinib, and could clinically provide validity as a surrogate marker for drug resistance in patients with NSCLC.

Abstract

Erlotinib inhibits epithelial growth factor receptor (EGFR) kinase activity and is used to treat non-small cell lung cancer (NSCLC). Despite its high efficacy, recurrence can occur in patients who become resistant to the drug. To address the underlying mechanism of Erlotinib resistance, we investigated additional mechanisms related to mode-of-drug-action, by multiple protein-binding interactions, besides EGFR by using drug affinity responsive target stability (DARTS) and liquid chromatography-mass spectrometry (LC-MS/MS) methods with non-labeled Erlotinib. DNA polymerase alpha subunit B (POLA2) was identified as a new Erlotinib binding protein that was validated by the DARTS platform, complemented with cellular thermal shift assays. Genetic knock-down of POLA2 promoted the anti-proliferative effect of the drug in the Erlotinib-resistant cell line H1299 with high POLA2 expression, whereas the overexpression of POLA2 restored anti-proliferative effects in the Erlotinib-sensitive cell line HCC827 with low POLA2 expression. Importantly, POLA2 expression levels in four NSCLC cell lines were positively correlated with anti-proliferative Erlotinib efficacy (Pearson correlation coefficient, R = 0.9886). These results suggest that POLA2 is a novel complementary target protein of Erlotinib, and could clinically provide validity as a surrogate marker for drug resistance in patients with NSCLC.

BMDMS-NP: A comprehensive ESI-MS/MS spectral library of natural compounds

The Bioinformatics & Molecular Design Research Center Mass Spectral Library - Natural Products (BMDMS-NP) is a library containing the mass spectra of natural compounds, especially plant specialized metabolites. At present, the library contains the electrospray ionization tandem mass spectrometry (ESI-MS/MS) spectra of 2739 plant metabolites that are commercially available. The contents of the library were made comprehensive by incorporating data generated under various experimental conditions for compounds with diverse molecular structures. The structural diversity of the BMDMS-NP data was evaluated using molecular fingerprints, and it was sufficiently exhaustive enough to represent the structures of the natural products commercially available. The MS/MS spectra of each metabolite were obtained with different types/brands of ion traps (tandem-in-time) or combinations of mass analyzers (tandem-in-space) at multiple collision energies. All spectra were measured repeatedly in each environment because variations can occur in spectra, even under the same conditions. Moreover, the probability, separability of searching, and transferability of this spectral library were evaluated against those of MS/MS libraries, namely: NIST17 and MoNA.

Classification of Mucin-Type O-Glycopeptides Using Higher-Energy Collisional Dissociation in Mass Spectrometry

Changes in mucin-type O-glycosylation of human proteins affect protein function, immune response, and cancer progression. Since O-glycoproteins are characterized by the microheterogeneity of diverse O-glycans with no conserved sequence and the macroheterogeneity of multiple glycosylation sites on serine and/or threonine in human proteins, the assessment of different mucin types, such as Tn-antigen, core 1, and core 2, and their extended core types in O-glycopeptides, is extremely challenging. Here, we present an O-GlycoProteome Analyzer (O-GPA) that automatically classifies mucin-type O-glycosylation using higher-energy collisional dissociation (HCD) in mass spectrometry. First, we estimated the number of GlcNAc residues using the intensity ratio of GlcNAc-specific fragment ions (HexNAc-CH₆O₃ and HexNAc-2H₂O) over GalNAc-specific fragment ions (HexNAc-C₂H₆O₃ and HexNAc-C₂H₄O₂) in the HCD spectrum. Furthermore, we classified the different mucin types of O-glycopeptides from characteristic B₂ (HexNAc₂) or Y_2α (PEP + HexNAc₂), and Y_2β (PEP + HexNAcHex) fragment ions, along with the number of GlcNAc. Furthermore, O-GPA automatically determined single or multiple O-glycosylation, regardless of the mucin types. The mucin type of O-glycopeptides from human urine and plasma was confirmed with an overall accuracy of 96%. We found 97 core 1, 56 core 2, 13 extended core 1, and 12 extended core 2 glycopeptides from urine; and 22 core 1, 13 core 2, 7 extended core 1, 1 extended core 2, and 1 Tn-antigen from plasma. Our strategy can be used to successfully characterize specific mucin types of O-glycoproteins in human biological samples.

A Proteotranscriptomic-Based Computational Drug-Repositioning Method for Alzheimer's Disease

Numerous clinical trials of drug candidates for Alzheimer’s disease (AD) have failed, and computational drug repositioning approaches using omics data have been proposed as effective alternative approaches to the discovery of drug candidates. However, little multi-omics data is available for AD, due to limited availability of brain tissues. Even if omics data exist, systematic drug repurposing study for AD has suffered from lack of big data, insufficient clinical information, and difficulty in data integration on account of sample heterogeneity derived from poor diagnosis or shortage of qualified post-mortem tissue. In this study, we developed a proteotranscriptomic-based computational drug repositioning method named Drug Repositioning Perturbation Score/Class (DRPS/C) based on inverse associations between disease- and drug-induced gene and protein perturbation patterns, incorporating pharmacogenomic knowledge. We constructed a Drug-induced Gene Perturbation Signature Database (DGPSD) comprised of 61,019 gene signatures perturbed by 1,520 drugs from the Connectivity Map (CMap) and the L1000 CMap. Drugs were classified into three DRPCs (High, Intermediate, and Low) according to DRPSs that were calculated using drug- and disease-induced gene perturbation signatures from DGPSD and The Cancer Genome Atlas (TCGA), respectively. The DRPS/C method was evaluated using the area under the ROC curve, with a prescribed drug list from TCGA as the gold standard. Glioblastoma had the highest AUC. To predict anti-AD drugs, DRPS were calculated using DGPSD and AD-induced gene/protein perturbation signatures generated from RNA-seq, microarray and proteomic datasets in the Synapse database, and the drugs were classified into DRPCs. We predicted 31 potential anti-AD drug candidates commonly belonged to high DRPCs of transcriptomic and proteomic signatures. Of these, four drugs classified into the nervous system group of Anatomical Therapeutic Chemical (ATC) system are voltage-gated sodium channel blockers (bupivacaine, topiramate) and monamine oxidase inhibitors (selegiline, iproniazid), and their mechanism of action was inferred from a potential anti-AD drug perspective. Our approach suggests a shortcut to discover new efficacy of drugs for AD.

Machine Learning Classifies Core and Outer Fucosylation of N-Glycoproteins Using Mass Spectrometry

Protein glycosylation is known to be involved in biological progresses such as cell recognition, growth, differentiation, and apoptosis. Fucosylation of glycoproteins plays an important role for structural stability and function of N-linked glycoproteins. Although many of biological and clinical studies of protein fucosylation by fucosyltransferases has been reported, structural classification of fucosylated N-glycoproteins such as core or outer isoforms remains a challenge. Here, we report for the first time the classification of N-glycopeptides as core- and outer-fucosylated types using tandem mass spectrometry (MS/MS) and machine learning algorithms such as the deep neural network (DNN) and support vector machine (SVM). Training and test sets of more than 800 MS/MS spectra of N-glycopeptides from the immunoglobulin gamma and alpha 1-acid-glycoprotein standards were selected for classification of the fucosylation types using supervised learning models. The best-performing model had an accuracy of more than 99% against manual characterization and area under the curve values greater than 0.99, which were calculated by probability scores from target and decoy datasets. Finally, this model was applied to classify fucosylated N-glycoproteins from human plasma. A total of 82N-glycopeptides, with 54 core-, 24 outer-, and 4 dual-fucosylation types derived from 54 glycoproteins, were commonly classified as the same type in both the DNN and SVM. Specifically, outer fucosylation was dominant in tri- and tetra-antennary N-glycopeptides, while core fucosylation was dominant in the mono-, bi-antennary and hybrid types of N-glycoproteins in human plasma. Thus, the machine learning methods can be combined with MS/MS to distinguish between different isoforms of fucosylated N-glycopeptides.

NIST Interlaboratory Study on Glycosylation Analysis of Monoclonal Antibodies: Comparison of Results from Diverse Analytical Methods

Glycosylation is a topic of intense current interest in the development of biopharmaceuticals because it is related to drug safety and efficacy. This work describes results of an interlaboratory study on the glycosylation of the Primary Sample (PS) of NISTmAb, a monoclonal antibody reference material. Seventy-six laboratories from industry, university, research, government, and hospital sectors in Europe, North America, Asia, and Australia submitted a total of 103 reports on glycan distributions. The principal objective of this study was to report and compare results for the full range of analytical methods presently used in the glycosylation analysis of mAbs. Therefore, participation was unrestricted, with laboratories choosing their own measurement techniques. Protein glycosylation was determined in various ways, including at the level of intact mAb, protein fragments, glycopeptides, or released glycans, using a wide variety of methods for derivatization, separation, identification, and quantification. Consequently, the diversity of results was enormous, with the number of glycan compositions identified by each laboratory ranging from 4 to 48. In total, one hundred sixteen glycan compositions were reported, of which 57 compositions could be assigned consensus abundance values. These consensus medians provide community-derived values for NISTmAb PS. Agreement with the consensus medians did not depend on the specific method or laboratory type. The study provides a view of the current state-of-the-art for biologic glycosylation measurement and suggests a clear need for harmonization of glycosylation analysis methods.

SAAVpedia: Identification, Functional Annotation, and Retrieval of Single Amino Acid Variants for Proteogenomic Interpretation

Next-generation genome sequencing has enabled the discovery of numerous disease- or drug-response-associated nonsynonymous single nucleotide variants (nsSNVs) that alter the amino acid sequences of a protein. Although several studies have attempted to characterize pathogenic nsSNVs, few have been confirmed as single amino acid variants (SAAVs) at the protein level. Here we developed the SAAVpedia platform to identify, annotate, and retrieve pathogenic SAAV candidates from proteomic and genomic data. The platform consists of four modules: SAAVidentifier, SAAVannotator, SNV/SAAVretriever, and SAAVvisualizer. The SAAVidentifier provides a reference database containing 18 206 090 SAAVs and performs the identification and quality assessment of SAAVs. The SAAVannotator provides functional annotation with biological, clinical, and pharmacological information for the interpretation of condition-specific SAAVs. The SNV/SAAVretriever module enables bidirectional navigation between relevant SAAVs and nsSNVs with diverse genomic and proteomic data. SAAVvisualizer provides various statistical plots based on functional annotations of detected SAAVs. To demonstrate the utility of SAAVpedia, the proteogenomic pipeline with protein-protein interaction network analysis was applied to proteomic data from breast cancer and glioblastoma patients. We identified 1326 and 12 breast-cancer- and glioblastoma-related genes that contained one or more SAAVs, including BRCA2 and FAM49B, respectively. SAAVpedia is a suitable platform for confirming whether a genomic variant is maintained in an amino acid sequence. Furthermore, as a result of the SAAV discovery of these positive controls, the SAAVpedia could play a key role in the protein functional study for the Human Proteome Project (HPP).

Isomer separation of sialylated O- and N-linked glycopeptides using reversed-phase LC-MS/MS at high temperature

Analyses of intact glycopeptides using mass spectrometry is challenging due to the numerous types of isomers of glycan moieties attached to the peptide backbone. Here, we demonstrate that high-temperature reversed-phase liquid chromatography (RPLC) can be used to separate isomeric O- and N-linked glycopeptides. In general, high column temperatures enhanced the resolution for separation of sialylated O- and N-linked glycopeptide isomers with decreased retention times. Using the high-temperature RPLC method, α2-6-linked sialylated N-glycopeptides were eluted first, followed by α2-3-linked isomers. However, highly sialylated N-glycopeptides containing hydrophobic amino acids exhibited increased retention times at high temperature. The separation of sialylated O- and N-glycopeptides with different glycan isoforms using a high-temperature RPLC method was demonstrated. This study indicates that reversed-phase chromatographic separation at high column temperatures is suitable for the separation of glycopeptide structural isomers.

Launching the C-HPP neXt-CP50 Pilot Project for Functional Characterization of Identified Proteins with No Known Function

An important goal of the Human Proteome Organization (HUPO) Chromosome-centric Human Proteome Project (C-HPP) is to correctly define the number of canonical proteins encoded by their cognate open reading frames on each chromosome in the human genome. When identified with high confidence of protein evidence (PE), such proteins are termed PE1 proteins in the online database resource, neXtProt. However, proteins that have not been identified unequivocally at the protein level but that have other evidence suggestive of their existence (PE2-4) are termed missing proteins (MPs). The number of MPs has been reduced from 5511 in 2012 to 2186 in 2018 (neXtProt 2018-01-17 release). Although the annotation of the human proteome has made significant progress, the "parts list" alone does not inform function. Indeed, 1937 proteins representing ∼10% of the human proteome have no function either annotated from experimental characterization or predicted by homology to other proteins. Specifically, these 1937 "dark proteins" of the so-called dark proteome are composed of 1260 functionally uncharacterized but identified PE1 proteins, designated as uPE1, plus 677 MPs from categories PE2-PE4, which also have no known or predicted function and are termed uMPs. At the HUPO-2017 Annual Meeting, the C-HPP officially adopted the uPE1 pilot initiative, with 14 participating international teams later committing to demonstrate the feasibility of the functional characterization of large numbers of dark proteins (CP), starting first with 50 uPE1 proteins, in a stepwise chromosome-centric organizational manner. The second aim of the feasibility phase to characterize protein (CP) functions of 50 uPE1 proteins, termed the neXt-CP50 initiative, is to utilize a variety of approaches and workflows according to individual team expertise, interest, and resources so as to enable the C-HPP to recommend experimentally proven workflows to the proteome community within 3 years. The results from this pilot will not only be the cornerstone of a larger characterization initiative but also enhance understanding of the human proteome and integrated cellular networks for the discovery of new mechanisms of pathology, mechanistically informative biomarkers, and rational drug targets.

Nutrient ileal digestibility evaluation of dried mealworm (Tenebrio molitor) larvae compared to three animal protein by-products in growing pigs

Objective

This study was to investigate the nutrient ileal digestibility of dried mealworm (Tenebrio molitor) larvae and compare with those of three animal protein by-products in growing pigs.

Methods

A total of 12 crossbred ([Landrace×Yorkshire]×Duroc) growing pigs with average body weights of 24.12±0.68 kg were surgically equipped with simple T-cannulas after being deprived of feed for 24 h according to published surgical procedures. These pigs had a recovery period of two weeks. A total of 12 pigs were assigned to individual metabolic crates and allotted to one of four treatments with 3 replicates in a fully randomized design. Dietary treatments included the following: i) Fish meal, corn-vegetable by-product basal diet+9.95% fish meal; ii) Meat meal, corn-vegetable by-product basal diet+9.95% meat meal; iii) Poultry meal, corn-vegetable by-product basal diet+9.95% poultry meal; iv) Tenebrio molitor, corn-vegetable by-product basal diet+9.95% dried Tenebrio molitor larvae.

Results

Results showed that the apparent ileal digestibility (AID) of Lys was higher (p<0.05) in pigs fed Tenebrio molitor diet than that in pigs fed fish meal diet. Pigs fed Tenebrio molitor diet showed increased (p<0.05) AID of His and Arg compared to pigs fed Fish meal or Meat meal diet. The AID of Cys was increased (p<0.05) in pigs fed poultry meal and Tenebrio molitor diets compared to that in pigs fish meal diet. Pigs fed meat meal, poultry meal, and Tenebrio molitor diets showed higher (p<0.05) standardized ileal digestibility (SID) of total energy compared to pigs fed fish meal diet. The SID of Arg was higher (p<0.05) in pigs fed Tenebrio molitor diet than that in pigs fed fish meal or meat meal diet. Furthermore, pigs fed poultry meal or Tenebrio molitor diets showed increased (p<0.05) SID of Cys compared to pigs fed fish meal diet.

Conclusion

In conclusion, providing pigs with diets that contained Tenebrio molitor larvae meal improved AID and SID of nutrients as well as essential and non-essential amino acids. The digestibility of dried mealworm larvae protein and its utilization in vivo are also good. Therefore, dried mealworm larvae protein can be used as protein source at 10% level in growing pigs.

Identification of Missing Proteins in Human Olfactory Epithelial Tissue by Liquid Chromatography-Tandem Mass Spectrometry

We performed proteomic analyses of human olfactory epithelial tissue to identify missing proteins using liquid chromatography-tandem mass spectrometry. Using a next-generation proteomic pipeline with a < 1.0% false discovery rate at the peptide and protein levels, we identified 3731 proteins, among which five were missing proteins (P0C7M7, P46721, P59826, Q658L1, and Q8N434). We validated the identified missing proteins using the corresponding synthetic peptides. No olfactory receptor (OR) proteins were detected in olfactory tissue, suggesting that detection of ORs would be very difficult. We also identified 49 and 50 alternative splicing variants mapped at the neXtProt and GENCODE databases, respectively, and 2000 additional single amino acid variants. This data set is available at the ProteomeXchange consortium via PRIDE repository (PXD010025).

Direct Monitoring of Fucosylated Glycopeptides of Alpha-Fetoprotein in Human Serum for Early Hepatocellular Carcinoma by Liquid Chromatography-Tandem Mass Spectrometry with Immunoprecipitation

PURPOSE

Alpha-fetoprotein (AFP) is a widely used serological marker that is associated with hepatocellular carcinoma (HCC). Although the level of AFP is increased in HCC, its sensitivity for diagnosis is poor because AFP levels are also increased in liver diseases. Changes in glycoform, especially fucosylation, have been reported to be associated with the development of HCC.

EXPERIMENTAL DESIGN

The authors introduce the monitoring of fucosylated glycopeptides by liquid chromatography (LC)-mass spectrometry (MS) combined with immunoprecipitation, where glycan-cleaved fragments with an amino acid sequence are used as transitions. Furthermore, neuraminidase for desialylation is useful to improve the MS detection limit (limit of detection [LOD] <2 ng mL^-1 ) in 0.1 μL of serum.

RESULTS

The performance of the relative percentage of fucosylated AFP (AFP-fuc%) for differentiating between early HCC and cirrhosis is better than that of serum AFP levels as indicated by a greater area under the receiver operator characteristic curve (area under the curve = 0.962 vs. 0.628) and sensitivity (92.3% vs. 53.9%), respectively. Furthermore, the inter- and intraday repeatability of AFP-fuc% in serum is less than 2.1%.

CONCLUSIONS AND CLINICAL RELEVANCE

These findings suggest that glycopeptide-based LC-MS/MS is a promising method and that AFP-fuc% is a clinically useful parameter for differentiating between early HCC and liver cirrhosis.

Next Generation Proteomic Pipeline for Chromosome-Based Proteomic Research Using NeXtProt and GENCODE Databases

Human Proteome Project aims to map all human proteins including missing proteins as well as proteoforms with post translational modifications, alternative splicing variants (ASVs), and single amino acid variants (SAAVs). neXtProt and Ensemble databases are usually used to provide curated information on human coding genes. However, to find these proteoforms, we (Chr #11 team) first introduce a streamlined pipeline using customized and concatenated neXtProt and GENCODE originated from Ensemble, with controlled false discovery rate (FDR). Because of large sized databases used in this pipeline, we found more stringent FDR filtering (0.1% at the peptide level and 1% at the protein level) to claim novel findings, such as GENCODE ASVs and missing proteins, from human hippocampus data set (MSV000081385) and ProteomeXchange (PXD007166). Using our next generation proteomic pipeline (nextPP) with neXtProt and GENCODE databases, two missing proteins such as activity-regulated cytoskeleton-associated protein (ARC, Chr 8) and glutamate receptor ionotropic, kainite 5 (GRIK5, Chr 19) were additionally identified with two or more unique peptides from human brain tissues. Additionally, by applying the pipeline to human brain related data sets such as cortex (PXD000067 and PXD000561), spinal cord, and fetal brain (PXD000561), seven GENCODE ASVs such as ACTN4-012 (Chr.19), DPYSL2-005 (Chr.8), MPRIP-003 (Chr.17), NCAM1-013 (Chr.11), EPB41L1-017 (Chr.20), AGAP1-004 (Chr.2), and CPNE5-005 (Chr.6) were identified from two or more data sets. The identified peptides of GENCODE ASVs were mapped onto novel exon insertions, alternative translations at 5'-untranslated region, or novel protein coding sequence. Applying the pipeline to male reproductive organ related data sets, 52 GENCODE ASVs were identified from two testis (PXD000561 and PXD002179) and a spermatozoa (PXD003947) data sets. Four out of 52 GENCODE ASVs such as RAB11FIP5-008 (Chr. 2), RP13-347D8.7-001 (Chr. X), PRDX4-002 (Chr. X), and RP11-666A8.13-001 (Chr. 17) were identified in all of the three samples.

FK506, an Immunosuppressive Drug, Induces Autophagy by Binding to the V-ATPase Catalytic Subunit A in Neuronal Cells

The drug FK506 (tacrolimus, fujimycin) exerts its immunosuppressive effects by regulating the nuclear factor of the activated T-cell (NFAT) family of transcription factors. However, FK506 also exhibits neuroprotective effects, but its direct target proteins that mediate these effects have not been determined. To identify the target proteins responsible for FK506's neuroprotective effects, the drug affinity responsive target stability (DARTS) method was performed using label-free FK506, and LC-MS/MS analysis of the FK506-treated proteome was also performed. Using DARTS and LC-MS/MS analyses in combination with reference studies, V-ATPase catalytic subunit A (ATP6V1A) was identified as a new target protein of FK506. The biological relevance of ATP6V1A in mediating the neuroprotective effects of FK506 was validated by analyzing FK506 activity with respect to autophagy via acridine orange staining and transcription factor EB (TFEB) translocation assay. These analyses demonstrated that the binding of FK506 with ATP6V1A induces autophagy by activating the translocation of TFEB from the cytosol into the nucleus. Because autophagy has been identified as a mechanism for treating neurodegenerative diseases and because we have demonstrated that FK506 induces autophagy, this study demonstrates that FK506 is a possible new therapy for treating neurodegenerative diseases.

Characterization of Site-Specific N-Glycopeptide Isoforms of α-1-Acid Glycoprotein from an Interlaboratory Study Using LC-MS/MS

Glycoprotein conformations are complex and heterogeneous. Currently, site-specific characterization of glycopeptides is a challenge. We sought to establish an efficient method of N-glycoprotein characterization using mass spectrometry (MS). Using alpha-1-acid glycoprotein (AGP) as a model N-glycoprotein, we identified its tryptic N-glycopeptides and examined the data reproducibility in seven laboratories running different LC-MS/MS platforms. We used three test samples and one blind sample to evaluate instrument performance with entire sample preparation workflow. 165 site-specific N-glycopeptides representative of all N-glycosylation sites were identified from AGP 1 and AGP 2 isoforms. The glycopeptide fragmentations by collision-induced dissociation or higher-energy collisional dissociation (HCD) varied based on the MS analyzer. Orbitrap Elite identified the greatest number of AGP N-glycopeptides, followed by Triple TOF and Q-Exactive Plus. Reproducible generation of oxonium ions, glycan-cleaved glycopeptide fragment ions, and peptide backbone fragment ions was essential for successful identification. Laboratory proficiency affected the number of identified N-glycopeptides. The relative quantities of the 10 major N-glycopeptide isoforms of AGP detected in four laboratories were compared to assess reproducibility. Quantitative analysis showed that the coefficient of variation was <25% for all test samples. Our analytical protocol yielded identification and quantification of site-specific N-glycopeptide isoforms of AGP from control and disease plasma sample.

gFinder: A Web-Based Bioinformatics Tool for the Analysis of N-Glycopeptides

Glycoproteins influence numerous indispensable biological functions, and changes in protein glycosylation have been observed in various diseases. The identification and characterization of glycoprotein and glycosylation sites by mass spectrometry (MS) remain challenging tasks, and great efforts have been devoted to the development of proteome informatics tools that facilitate the MS analysis of glycans and glycopeptides. Here we report on the development of gFinder, a web-based bioinformatics tool that analyzes mixtures of native N-glycopeptides that have been profiled by tandem MS. gFinder not only enables the simultaneous integration of collision-induced dissociation (CID) and high-energy collisional dissociation (HCD) fragmentation but also merges the spectra for high-throughput analysis. These merged spectra expedite the identification of both glycans and N-glycopeptide backbones in tandem MS data using the glycan database and a proteomic search tool (e.g., Mascot). These data can be used to simultaneously characterize peptide backbone sequences and possible N-glycan structures using assigned scores. gFinder also provides many convenient functions that make it easy to perform manual calculations while viewing the spectrum on-screen. We used gFinder to detect an additional protein (Q8N9B8) that was missed from the previously published data set containing N-linked glycosylation. For N-glycan analysis, we used the GlycomeDB glycan structure database, which integrates the structural and taxonomic data from all of the major carbohydrate databases available in the public domain. Thus, gFinder is a convenient, high-throughput analytical tool for interpreting the tandem mass spectra of N-glycopeptides, which can then be used for identification of potential missing proteins having glycans. gFinder is available publicly at http://gFinder.proteomix.org/ .

Integrated Proteomic Pipeline Using Multiple Search Engines for a Proteogenomic Study with a Controlled Protein False Discovery Rate

In the Chromosome-Centric Human Proteome Project (C-HPP), false-positive identification by peptide spectrum matches (PSMs) after database searches is a major issue for proteogenomic studies using liquid-chromatography and mass-spectrometry-based large proteomic profiling. Here we developed a simple strategy for protein identification, with a controlled false discovery rate (FDR) at the protein level, using an integrated proteomic pipeline (IPP) that consists of four engrailed steps as follows. First, using three different search engines, SEQUEST, MASCOT, and MS-GF+, individual proteomic searches were performed against the neXtProt database. Second, the search results from the PSMs were combined using statistical evaluation tools including DTASelect and Percolator. Third, the peptide search scores were converted into E-scores normalized using an in-house program. Last, ProteinInferencer was used to filter the proteins containing two or more peptides with a controlled FDR of 1.0% at the protein level. Finally, we compared the performance of the IPP to a conventional proteomic pipeline (CPP) for protein identification using a controlled FDR of <1% at the protein level. Using the IPP, a total of 5756 proteins (vs 4453 using the CPP) including 477 alternative splicing variants (vs 182 using the CPP) were identified from human hippocampal tissue. In addition, a total of 10 missing proteins (vs 7 using the CPP) were identified with two or more unique peptides, and their tryptic peptides were validated using MS/MS spectral pattern from a repository database or their corresponding synthetic peptides. This study shows that the IPP effectively improved the identification of proteins, including alternative splicing variants and missing proteins, in human hippocampal tissues for the C-HPP. All RAW files used in this study were deposited in ProteomeXchange (PXD000395).

Analysis of fucosylation in liver-secreted N-glycoproteins from human hepatocellular carcinoma plasma using liquid chromatography with tandem mass spectrometry

Fucosylation of N-glycoproteins has been implicated in various diseases, such as hepatocellular carcinoma (HCC). However, few studies have performed site-specific analysis of fucosylation in liver-secreted proteins. In this study, we characterized the fucosylation patterns of liver-secreted proteins in HCC plasma using a workflow to identify site-specific N-glycoproteins, where characteristic B- and/or Y-ion series with and without fucose in collision-induced dissociation were used in tandem mass spectrometry. In total, 71 fucosylated N-glycopeptides from 13 major liver-secreted proteins in human plasma were globally identified by LC-MS/MS. Additionally, 37 fucosylated N-glycopeptides were newly identified from nine liver-secreted proteins, including alpha-1-antichymotrypsin, alpha-1-antitrypsin, alpha-2-HS-glycoprotein, ceruloplasmin, alpha-1-acid glycoprotein 1/2, alpha-2-macroglobulin, serotransferrin, and beta-2-glycoprotein 1. Of the fucosylated N-glycopeptides, bi- and tri-antennary glycoforms were the most common ones identified in liver-secreted proteins from HCC plasma. Therefore, we suggest that this analytical method is effective for characterizing fucosylation in liver-secreted proteins. Graphical abstract A global map of fucosylated and non-fucosylated glycopeptides from 13 liver-secreted glycoproteins in hepatocellular carcinoma plasma.

Variations in fat mass contribution to bone mineral density by gender, age, and body mass index: the Korea National Health and Nutrition Examination Survey (KNHANES) 2008-2011

The relationship of body composition and bone mineral density is complex and controversial. When classifying Korean population based on gender, age, and body mass index, fat mass had varying contributions to bone mineral density.

INTRODUCTION

The relationship between body composition and bone mineral density (BMD) is complex, and it is uncertain how components of body mass variably affect BMD.

METHODS

This cross-sectional observational study was performed in subjects ≥20 years based on the Korea National Health and Nutrition Examination Survey (KNHANES) 2008 to 2011. Among 17,583 subjects, the mean ages were 49.1 ± 16.0 years (M, n = 7495) and 49.3 ± 16.3 years (F, n = 10,088). Subjects were divided into age groups, either <50 or ≥50 years for males, or menopausal state, either premenopausal or postmenopausal, for females. A further classification used BMI, either <25 or ≥25 kg/m(2). Anthropometric and body composition parameters were compared and evaluated to look for correlations with BMD. Further, appendicular lean mass (ALM), fat mass (FM), fat percentage (FP), and waist circumference (WC) were included for multivariate analysis with BMD, controlling for covariates in each age group and BMI subgroup.

RESULTS

Anthropometric and body composition parameters significantly correlated with BMD in all age groups for both genders. After adjusting for covariates, ALM strongly affected BMD in all age groups for both genders. FM, FP, and WC significantly affected BMD in both age groups of women and in older men, but they did not affect BMD in younger men. Fat indices positively affected BMD of all sites in all non-obese women and in non-obese older men. However, little contribution was found in obese subgroups of both genders and in non-obese younger men.

CONCLUSION

Considering different weights of covariates, ALM strongly contributed to BMD in all gender, age, and BMI groups. On the other hand, fat indices positively affected BMD of both age groups in women and older men with normal BMI, but they showed little contribution to BMD within the same age groups with high BMI or any BMI subgroups of younger men.

Measurements of Elliptic and Triangular Flow in High-Multiplicity 3He+Au Collisions at √(s(NN))=200 GeV

We present the first measurement of elliptic (v(2)) and triangular (v(3)) flow in high-multiplicity (3)He+Au collisions at √(s(NN))=200  GeV. Two-particle correlations, where the particles have a large separation in pseudorapidity, are compared in (3)He+Au and in p+p collisions and indicate that collective effects dominate the second and third Fourier components for the correlations observed in the (3)He+Au system. The collective behavior is quantified in terms of elliptic v(2) and triangular v(3) anisotropy coefficients measured with respect to their corresponding event planes. The v(2) values are comparable to those previously measured in d+Au collisions at the same nucleon-nucleon center-of-mass energy. Comparisons with various theoretical predictions are made, including to models where the hot spots created by the impact of the three (3)He nucleons on the Au nucleus expand hydrodynamically to generate the triangular flow. The agreement of these models with data may indicate the formation of low-viscosity quark-gluon plasma even in these small collision systems.

Measurement of Long-Range Angular Correlation and Quadrupole Anisotropy of Pions and (Anti)Protons in Central d+Au Collisions at sqrt[s_{NN}]=200 GeV

We present azimuthal angular correlations between charged hadrons and energy deposited in calorimeter towers in central d+Au and minimum bias p+p collisions at sqrt[s_{NN}]=200 GeV. The charged hadron is measured at midrapidity |η|<0.35, and the energy is measured at large rapidity (-3.7<η<-3.1, Au-going direction). An enhanced near-side angular correlation across |Δη|>2.75 is observed in d+Au collisions. Using the event plane method applied to the Au-going energy distribution, we extract the anisotropy strength v_{2} for inclusive charged hadrons at midrapidity up to p_{T}=4.5 GeV/c. We also present the measurement of v_{2} for identified π^{±} and (anti)protons in central d+Au collisions, and observe a mass-ordering pattern similar to that seen in heavy-ion collisions. These results are compared with viscous hydrodynamic calculations and measurements from p+Pb at sqrt[s_{NN}]=5.02 TeV. The magnitude of the mass ordering in d+Au is found to be smaller than that in p+Pb collisions, which may indicate smaller radial flow in lower energy d+Au collisions.

Quantitative mass spectrometric analysis of glycoproteins combined with enrichment methods

Mass spectrometry (MS) has been a core technology for high sensitive and high-throughput analysis of the enriched glycoproteome in aspects of quantitative assays as well as qualitative profiling of glycoproteins. Because it has been widely recognized that aberrant glycosylation in a glycoprotein may involve in progression of a certain disease, the development of efficient analysis tool for the aberrant glycoproteins is very important for deep understanding about pathological function of the glycoprotein and new biomarker development. This review first describes the protein glycosylation-targeting enrichment technologies mainly employing solid-phase extraction methods such as hydrizide-capturing, lectin-specific capturing, and affinity separation techniques based on porous graphitized carbon, hydrophilic interaction chromatography, or immobilized boronic acid. Second, MS-based quantitative analysis strategies coupled with the protein glycosylation-targeting enrichment technologies, by using a label-free MS, stable isotope-labeling, or targeted multiple reaction monitoring (MRM) MS, are summarized with recent published studies.

Semi-quantitative measurement of a specific glycoform using a DNA-tagged antibody and lectin affinity chromatography for glyco-biomarker development

Aberrant glycosylation-targeted disease biomarker development is based on cumulative evidence that certain glycoforms are mass-produced in a disease-specific manner. However, the development process has been hampered by the absence of an efficient validation method based on a sensitive and multiplexed platform. In particular, ELISA-based analytical tools are not adequate for this purpose, mainly because of the presence of a pair of N-glycans of IgG-type antibodies. To overcome the associated hurdles in this study, antibodies were tagged with oligonucleotides with T7 promoter and then allowed to form a complex with corresponding antigens. An antibody-bound specific glycoform was isolated by lectin chromatography and quantitatively measured on a DNA microarray chip following production of fluorescent RNA by T7-trascription. This tool ensured measurement of targeted glycoforms of multiple biomarkers with high sensitivity and multiplexity. This analytical method was applied to an in vitro diagnostic multivariate index assay where a panel of hepatocellular carcinoma (HCC) biomarkers comprising alpha-fetoprotein, hemopexin, and alpha-2-macroglobulin (A2M) was examined in terms of the serum level and their fuco-fractions. The results indicated that the tests using the multiplexed fuco-biomarkers provided improved discriminatory power between non- hepatocellular carcinoma and hepatocellular carcinoma subjects compared with the alpha-fetoprotein level or fuco-alpha-fetoprotein test alone. The developed method is expected to facilitate the validation of disease-specific glycan biomarker candidates.

Quantitative analysis of aberrant protein glycosylation in liver cancer plasma by AAL-enrichment and MRM mass spectrometry

A lectin-coupled mass spectrometry (MS) approach was employed to quantitatively monitor aberrant protein glycosylation in liver cancer plasma. To do this, we compared the difference in the total protein abundance of a target glycoprotein between hepatocellular carcinoma (HCC) plasmas and hepatitis B virus (HBV) plasmas, as well as the difference in lectin-specific protein glycoform abundance of the target glycoprotein. Capturing the lectin-specific protein glycoforms from a plasma sample was accomplished by using a fucose-specific aleuria aurantia lectin (AAL) immobilized onto magnetic beads via a biotin-streptavidin conjugate. Following tryptic digestion of both the total plasma and its AAL-captured fraction of each HCC and HBV sample, targeted proteomic mass spectrometry was conducted quantitatively by a multiple reaction monitoring (MRM) technique. From the MRM-based analysis of the total plasmas and AAL-captured fractions, differences between HCC and HBV plasma groups in fucosylated glycoform levels of target glycoproteins were confirmed to arise from both the change in the total protein abundance of the target proteins and the change incurred by aberrant fucosylation on target glycoproteins in HCC plasma, even when no significant change occurs in the total protein abundance level. Combining the MRM-based analysis method with the lectin-capturing technique proved to be a successful means of quantitatively investigating aberrant protein glycosylation in cancer plasma samples. Additionally, it was elucidated that the differences between HCC and control groups in fucosylated biomarker candidates A1AT and FETUA mainly originated from an increase in fucosylation levels on these target glycoproteins, rather than an increase in the total protein abundance of the target glycoproteins.

Cold-nuclear-matter effects on heavy-quark production at forward and backward rapidity in d + Au collisions at √sNN = 200 GeV

The PHENIX experiment has measured open heavy-flavor production via semileptonic decay over the transverse momentum range 1 < p(T) < 6  GeV/c at forward and backward rapidity (1.4 < |y| < 2.0) in d+Au and p + p collisions at √sNN = 200  GeV. In central d+Au collisions, relative to the yield in p + p collisions scaled by the number of binary nucleon-nucleon collisions, a suppression is observed at forward rapidity (in the d-going direction) and an enhancement at backward rapidity (in the Au-going direction). Predictions using nuclear-modified-parton-distribution functions, even with additional nuclear-p(T) broadening, cannot simultaneously reproduce the data at both rapidity ranges, which implies that these models are incomplete and suggests the possible importance of final-state interactions in the asymmetric d + Au collision system. These results can be used to probe cold-nuclear-matter effects, which may significantly affect heavy-quark production, in addition to helping constrain the magnitude of charmonia-breakup effects in nuclear matter.

Differential proteomic approach for identification and verification of aberrantly glycosylated proteins in adenocarcinoma lung cancer (ADLC) plasmas by lectin-capturing and targeted mass spectrometry

To investigate quantitative differences in aberrant glycosylation of target glycoproteins between noncancerous group and patient group with adenocarcinoma lung cancer (ADLC), differential proteomic approach was developed by cooperatively using comparative lectin-capturing, targeted mass spectrometry (MRM MS), and antibody/lectin sandwich ELISA. Plasma samples comparatively prepared from 3 ADLC patients and 3 controls, with and without lectin-fractionation using fucose-specific Aleuria aurantia lectin (AAL), were trypsin-digested and analyzed for target glycoproteins, alpha-1-acid glycoprotein (AGP) and ceruloplasmin (CP), by MRM MS. From the MRM MS data the abundance levels of AAL-captured glycoforms of both targets were significantly higher in ADLC cases compared to controls, although the levels in total protein abundance were comparable between ADLC and control groups. This difference between ADLC and control groups in the fucosylated glycoform levels was originated mainly from aberrant fucosylation on the targets in ADLC plasmas rather than change in total protein abundance of the targets, and also confirmed by sandwich ELISA. AGP and CP were further verified to be biomarker candidates by MRM-based analysis of AAL-captured plasmas (30 ADLC cases, 30 controls), with AUROC 0.758 and 0.847 respectively. This differential proteomic approach can be useful for identifying and verifying biomarker candidate involved in aberrant protein glycosylation.

BIOLOGICAL SIGNIFICANCE

The present paper introduces an efficient differential proteomic method to investigate quantitative differences in aberrant protein glycosylation of serological glycoproteins between noncancerous group and lung cancer patient group. This differential proteomic approach consisting of the targeted MRM MS of comparatively lectin-captured plasma fractions and the antibody/lectin sandwich ELISA-based assay was evaluated to be useful for identification of aberrantly fucosylated glycoproteins AGP and CP in lung cancer plasmas. In addition, we have demonstrated that the MRM MS-based differential proteomic approach is also useful for high-throughput verification of the aberrantly fucosylated glycoproteins AGP and CP using the large number of individual plasmas. Therefore, the present MRM MS-based differential proteomic strategy with lectin-capturing can be a powerful tool for high-throughput verification of aberrantly glycosylated biomarker candidates, identified preliminary by mass profiling experiments in proteomic fields but requiring further validation using a large number of cohorts.

Abundance-ratio-based semiquantitative analysis of site-specific N-linked glycopeptides present in the plasma of hepatocellular carcinoma patients

Aberrant structures of site-specific N-linked glycans are closely associated with the tumorigenesis of hepatocellular carcinoma (HCC), one of the most common fatal cancers worldwide. Vitronectin (VTN) is considered a candidate glycobiomarker of HCC. In this study, we describe a reliable and simple quantification strategy based on abundance ratios of site-specific N-linked glycopeptides of VTN to screen for potential biomarkers. A total of 14 unique N-linked glycans corresponding to 27 unique N-linked glycopeptides were characterized at three N-linked sites (Asn-86, -169, and -242) present in VTN. These glycans could be good candidate markers for HCC. Among these glycans, the abundance ratio of two representative glycoforms (fucosyl vs non-fucosyl) was significantly increased in HCC plasma relative to normal plasma. This strategy was also successfully applied to another potential HCC biomarker, haptoglobin. Furthermore, we demonstrate that our approach employing tandem mass tag (TMT) and target N-linked glycopeptides of VTN is a useful tool for quantifying specific glycans in HCC plasma relative to normal plasma. Our strategy represents a simple and potentially useful screening platform for the discovery of cancer-specific glycobiomarkers.