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Transected peripheral nerve injury (PNI) affects the quality of life of patients, which leads to socioeconomic burden. Despite the existence of autografts and commercially available nerve guidance conduits (NGCs), the complexity of peripheral nerve regeneration requires further research in bioengineered NGCs to improve surgical outcomes. In this work, we introduce multidomain peptide (MDP) hydrogels, as intraluminal fillers, into electrospun poly(ε-caprolactone) (PCL) conduits to bridge 10 mm rat sciatic nerve defects. The efficacy of treatment groups was evaluated by electromyography and gait analysis to determine their electrical and motor recovery. We then studied the samples' histomorphometry with immunofluorescence staining and automatic axon counting/measurement software. Comparison with negative control group shows that PCL conduits filled with an anionic MDP may improve functional recovery 16 weeks postoperation, displaying higher amplitude of compound muscle action potential, greater gastrocnemius muscle weight retention, and earlier occurrence of flexion contracture. In contrast, PCL conduits filled with a cationic MDP showed the least degree of myelination and poor functional recovery. This phenomenon may be attributed to MDPs' difference in degradation time. Electrospun PCL conduits filled with an anionic MDP may become an attractive tissue engineering strategy for treating transected PNI when supplemented with other bioactive modifications.

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 [YHM] 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 (Im/z528/Im/z366). The measure of [Im/z528/Im/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.

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 of1% 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).

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 Y2α (PEP + HexNAc2), and Y2β (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.

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