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Accurate Identification of Deamidation and Citrullination from Global Shotgun Proteomics Data Using a Dual-Search Delta Score Strategy

机译:使用双重搜索三角洲评分策略准确地识别全球霰弹枪蛋白质组学数据的脱胺和柑橘

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摘要

Proteins with deamidated/citrullinated amino acids play critical roles in the pathogenesis of many human diseases; however, identifying these modifications in complex biological samples has been an ongoing challenge. Herein we present a method to accurately identify these modifications from shotgun proteomics data generated by a deep proteome profiling study of human pancreatic islets obtained by laser capture microdissection. All MS/MS spectra were searched twice using MSGF+ database matching, with and without a dynamic +0.9840 Da mass shift modification on amino acids asparagine, glutamine, and arginine (NQR). Consequently, each spectrum generates two peptide-to-spectrum matches (PSMs) with MSGF+ scores, which were used for the Delta Score calculation. It was observed that all PSMs with positive Delta Score values were clustered with mass errors around 0 ppm, while PSMs with negative Delta Score values were distributed nearly equally within the defined mass error range (20 ppm) for database searching. To estimate false discovery rate (FDR) of modified peptides, a "target-mock" strategy was applied in which data sets were searched against a concatenated database containing "real-modified" (+0.9840 Da) and "mock-modified" (+1.0227 Da) peptide masses. The FDR was controlled to similar to 2% using a Delta Score filter value greater than zero. Manual inspection of spectra showed that PSMs with positive Delta Score values contained deamidated/citrullinated fragments in their MS/MS spectra. Many citrullinated sites identified in this study were biochemically confirmed as autoimmunogenic epitopes of autoimmune diseases in literature. The results demonstrated that in situ deamidated/citrullinated peptides can be accurately identified from shotgun tissue proteomics data using this dual-search Delta Score strategy. Raw MS data is available at ProteomeXchange (PXDO10150).
机译:具有脱染/瓜氨酸的蛋白质在许多人类疾病的发病机制中起重要作用;然而,在复杂的生物样本中识别这些修改一直是持续的挑战。在此我们提出了一种方法,可以精确地识别来自通过激光捕获微散射获得的人胰岛的深蛋白质组织分析研究产生的霰弹枪蛋白质组学数据的这些修改。使用MSGF +数据库匹配搜索两次MS / MS光谱,在氨基酸天冬酰胺,谷氨酰胺和精氨酸(NQR)上没有动态+0.9840Da质量换档改性。因此,每个频谱产生具有MSGF +分数的两个肽 - 频谱匹配(PSM),其用于增量计数计算。观察到具有阳性Δ得分值的所有PSM与大约0ppm的质量误差聚集,而具有负Δ评分值的PSM几乎同样在规定的质量误差范围(20ppm)中分布,用于数据库搜索。为了估计修改肽的假发现率(FDR),应用了“目标模拟”策略,其中搜索了数据集,以抵御包含“实际修改”(+0.9840 da)和“模拟修改”(+ 1.0227DA)肽质量。使用大于零的增量滤波器值控制FDR与2%相似。 Spectra的手动检查表明,PSM具有正Δ评分值的PSM含有MS / MS光谱中的脱胺/瓜氨酸片段。本研究中鉴定的许多瓜氨酸位点被生物化学证实了文献中的自身免疫性疾病的自身免疫表位。结果表明,使用这种双搜索蛋白质组学数据可以准确地识别出原位脱胺/瓜氨酸肽。原始MS数据可在Proteomexchange(PXDO10150)上获得。

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