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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 (Hex 2 HexNAc 1 ) ion to m / z 366.14 (Hex 1 HexNAc 1 ) ion ( I m / z 528 / I m / z 366 ). The measure of [ I m / z 528 / I m / z 366 > 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.

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-CH 6 O 3 and HexNAc-2H 2 O) over GalNAc-specific fragment ions (HexNAc-C 2 H 6 O 3 and HexNAc-C 2 H 4 O 2 ) in the HCD spectrum. Furthermore, we classified the different mucin types of O -glycopeptides from characteristic B 2 (HexNAc 2 ) or Y 2α (PEP + HexNAc 2 ), 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.

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.

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.

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).

The goal of the Chromosome-Centric Human Proteome Project (C-HPP) is to fully provide proteomic information from each human chromosome, including novel proteoforms, such as novel protein-coding variants expressed from noncoding genomic regions, alternative splicing variants (ASVs), and single amino acid variants (SAAVs). In the 144 LC/MS/MS raw files from human hippocampal tissues of control, epilepsy, and Alzheimer's disease, we identified the novel proteoforms with a workflow including integrated proteomic pipeline using three different search engines, MASCOT, SEQUEST, and MS-GF+. With a <1% false discovery rate (FDR) at the protein level, the 11 detected peptides mapped to four translated long noncoding RNA variants against the customized databases of GENCODE lncRNA, which also mapped to coding-proteins at different chromosomal sites. We also identified four novel ASVs against the customized databases of GENCODE transcript. The target peptides from the variants were validated by tandem MS fragmentation pattern from their corresponding synthetic peptides. Additionally, a total of 128 SAAVs paired with their wild-type peptides were identified with FDR <1% at the peptide level using a customized database from neXtProt including nonsynonymous single nucleotide polymorphism (nsSNP) information. Among these results, several novel variants related in neuro-degenerative disease were identified using the workflow that could be applicable to C-HPP studies. All raw files used in this study were deposited in ProteomeXchange (PXD000395).

O-Glycans in saliva and tear isolated from patients suffering from ocular rosacea, a form of inflammatory ocular surface disease, were profiled, and their structures were elucidated using high resolution mass spectrometry. We have previously shown that certain structures, particularly sulfated oligosaccharides, increased in the tear and saliva of rosacea patients. In this study, the structures of these glycans were elucidated using primarily tandem mass spectrometry. There were important similarities in the glycan profiles of tears and saliva with the majority of the structures in common. The structures of the most abundant species common to both tear and saliva, which were also the most abundant species in both, were elucidated. For sulfated species, the positions of the sulfate groups were localized. The majority of the structures were new, with the sulfated glycans comprising mucin core 1- and core 2-type structures. As both saliva and tear are rich in mucins, it is suggested that the O-glycans are mainly components of mucins. The study further illustrates the strong correspondence between the glycans in the tear and saliva of ocular rosacea patients.

Human chromosome 11 is the third gene-rich chromosome having 1304 protein-coding genes. According to the GeneCards, this chromosome contains 240 genes related to diseases, as it is well known as a disease-rich chromosome. Although there are many protein-coding genes, the proteomic identification ratio is rather low. As a model study, human hippocampal tissues from patients suffering from Alzheimer's disease and epilepsy were prepared to evaluate the gene-centric statistics related to the gene expression and disorders of chromosome 11. A total of 8828 protein coding genes from brain tissues were extensively off-gel fractionated and profiled by a high resolution mass spectrometer with collision induced dissociation and electron transfer dissociation. Five-hundred twenty-three of the proteins from brain tissues were determined to belong to chromosome 11, representing 37% of the proteins reported in the Global Proteome Machine Database. We extracted gene clusters from a specific biological process or molecular function in gene ontology, among which the olfactory receptor genes showed the largest cluster on chromosome 11. Analysis of the proteome data set from the hippocampus provides a significant network associated with genes and proteins and leads to new insights into the biological and genetic mechanisms of chromosome 11-specific diseases such as Alzheimer's disease.

Acinetobacter baumannii is a Gram-negative, nonmotile aerobic bacterium that has emerged as an important nosocomial pathogen. Multidrug-resistant (MDR) A. baumannii is difficult to treat with antibiotics, and treatment failure in infected patients is of great concern in clinical settings. To investigate proteome regulation in A. baumannii under antibiotic stress conditions, quantitative membrane proteomic analyses of a clinical MDR A. baumannii strain cultured in subminimal inhibitory concentrations of tetracycline and imipenem were performed using a combination of label-free (one-dimensional electrophoresis-liquid chromatography-tandem mass spectrometry) and label (isobaric tag for relative and absolute quantitation) approaches. In total, 484 proteins were identified, and 302 were classified as outer membrane, periplasmic, or plasma membrane proteins. The clinical A. baumannii strain DU202 responded specifically and induced different cell wall and membrane protein sets that provided resistance to the antibiotics. The induction of resistance-nodulation-cell division transporters and protein kinases, and the repression of outer membrane proteins were common responses in the presence of tetracycline and imipenem. Induction of a tetracycline resistant pump, ribosomal proteins, and iron-uptake transporters appeared to be dependent on tetracycline conditions, whereas β-lactamase and penicillin-binding proteins appeared to be dependent on imipenem conditions. These results suggest that combined liquid chromatography-based proteomic approaches can be used to identify cell wall and membrane proteins involved in the antibiotic resistance of A. baumannii.

Microvesicles (MV) are membrane vesicles secreted from the plasma and endosomal membrane compartment by various cell types such as hematopoietic, epithelial, and tumor cells. Actively growing tumor cells shed MV, and the rate of shedding increases in malignant tumors. Although recent progress in this area has revealed that tumor-derived MV play multiple roles in tumor growth and metastasis via immune escape, tumor invasion, and angiogenesis, the mechanism of vesicle formation and the biological roles of tumor-derived MV are not understood. Here, we report the first global proteomic analysis of highly purified MV from human colorectal cancer cells. Using 1D SDS gel electrophoresis and nano-LC-MS/MS analyses, we identified a total of 547 microvesicular proteins from three independent experiments with high confidence; 416 proteins were identified at least in two trials, including 181 as yet unreported proteins. We identified 49 proteins involved in the biogenesis of MV, including annexins, ADP-ribosylation factors, and Rab proteins. We also identified 28 proteins that may function in tumorigenesis via promotion of migration, invasion, and growth of tumor cells, immune modulation, metastasis, and angiogenesis. Taken together with previously reported results, our observations suggest that tumor-derived MV may act as communicasomes, that is, extracellular organelles that play diverse roles in intercellular communication. This information will help elucidate the biogenesis and functions of tumor-derived MV, and aid in the development of effective vaccines for various cancers, including colorectal cancer.