Mining of serum glycoproteins by an indirect approach using cell line secretome.
ABSTRACT Glycosylation is the most important and abundant post-translational modification in serum proteome. Several specific types of glycan epitopes have been shown to be associated with various types of disease. Direct analysis of serum glycoproteins is challenging due to its wide dynamic range. Alternatively, glycoproteins can be discovered in the secretome of model cell lines and then confirmed in blood. However, there has been little experimental evidence showing cell line secretome as a tractable target for the study of serum glycoproteins. We used a hydrazine-based glycocapture method to selectively enrich glycoproteins from the secretome of the breast cancer cell line Hs578T. A total of 132 glycoproteins were identified by nanoLC-MS/MS analysis. Among the identified proteins, we selected 13 proteins that had one or more N-glycosylation motifs in the matched peptides, which were included in the Secreted Protein Database but not yet in the Plasma Proteome Database (PPD), and whose antibodies were commercially available. Nine out of the 13 selected proteins were detected from human blood plasma by western analysis. Furthermore, eight proteins were also detected from the plasma by targeted LC-MS/MS, which had never been previously identified by data-dependent LC-MS/MS. Our results provide novel proteins that should be enrolled in PPD and suggest that analysis of cell line secretome with subfractionation is an efficient strategy for discovering disease-relevant serum proteins.
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ABSTRACT: Mass spectrometric (MS) data of human cell secretomes are usually run through the conventional human database for identification. However, the search may result in false identifications due to contamination of the secretome with fetal bovine serum (FBS) proteins. To overcome this challenge, here we provide a composite protein database including human as well as 199 FBS protein sequences for MS data search of human cell secretomes. Searching against the human-FBS database returned more reliable results with fewer false-positive and false-negative identifications compared to using either a human only database or a human-bovine database. Furthermore, the improved results validated our strategy without complex experiments like SILAC. We expect our strategy to improve the accuracy of human secreted protein identification and to also add value for general use.PLoS ONE 03/2015; 10(3):e0121692. DOI:10.1371/journal.pone.0121692 · 3.53 Impact Factor
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ABSTRACT: Carbohydrate antigens expressed on pig cells are considered to be major barriers in pig-to-human xenotransplantation. Even after α1,3-galactosyltransferase gene knock-out (GalT-KO) pigs are generated, potential non-Gal antigens are still existed. However, to the best of our knowledge there is no extensive study analyzing N-glycans expressed on the GalT-KO pig tissues or cells. Here, we identified and quantified totally 47 N-glycans from wild-type (WT) and GalT-KO pig fibroblasts using mass spectrometry. First, our results confirmed the absence of galactose-alpha-1,3-galactose (α-Gal) residue in the GalT-KO pig cells. Interestingly, we showed that the level of overall fucosylated Nglycans from GalT-KO pig fibroblasts is much higher than from WT pig fibroblasts. Moreover, the relative quantity of the N-glycolylneuraminic acid (NeuGc) antigen is slightly higher in the GalT-KO pigs. Thus, this study will contribute to a better understanding of cellular glycan alterations on GalT-KO pigs for successful xenotransplantation.
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ABSTRACT: Lung cancer-related transcription factors (TFs) were identified by integrating previously reported genomic, transcriptomic and proteomic data, and were quantified by multiple reaction monitoring (MRM) in various cell lines. All experiments were performed without affinity depletion or subfractionation of cell lysates. Since the target proteins were expected to be present in low abundance, we experimentally optimized MRM transition parameters with chemically synthesized peptides. Quantitation was based on stable isotope labeled standard peptides (SIS peptides). Out of 288 MRM measurements (=36 peptides representing 28 TFs × 8 cell lines), 241 were successfully obtained within a quantitation limit of 15 amol, 221 measurements (91.7%) showed coefficients of variation (CVs) of ≤ 20%, and 149 (61.8%) showed CVs of ≤ 10%, quantifying as low as 19.4 amol/µg protein for STAT2 with a CV of 6.3% in an A549 cell. Comparisons between MRM measurements and levels of the corresponding mRNAs revealed linear, non-linear, or no relationship between protein and mRNA levels, indicating the need for an MRM assay. An integrative analysis of MRM and gene expression profiles from doxorubicin-resistant H69AR and sensitive H69 cells further showed that fourteen differentially-expressed TFs, such as STAT1 and SMAD4, regulated genes associated with drug-resistance and cell differentiation-related processes. Thus, the analytical performance of MRM for the quantitation of low abundance TFs suggests its usefulness for biological application.Journal of Proteome Research 04/2013; 12(6). DOI:10.1021/pr3011414 · 5.00 Impact Factor