State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Radiation Medicine, Beijing 102206, China.
Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China.
J Proteomics. 2018 Jan 6;170:14-27. doi: 10.1016/j.jprot.2017.09.014. Epub 2017 Sep 29.
UNLABELLED: Human serum has been intensively studied to identify biomarkers via global proteomic analysis. The altered O-glycoproteome is associated with human pathological state including cancer, inflammatory and degenerative diseases and is an attractive source of disease biomarkers. Because of the microheterogeneity and macroheterogeneity of O-glycosylation, site-specific O-glycosylation analysis in human serum is still challenging. Here, we developed a systematic strategy that combined multiple enzyme digestion, multidimensional separation for sample preparation and high-resolution tandem MS with Byonic software for intact O-glycopeptide characterization. We demonstrated that multiple enzyme digestion or multidimensional separation can make sample preparation more efficient and that EThcD is not only suitable for the identification of singly O-glycosylated peptides (50.3%) but also doubly (21.2%) and triply (28.5%) O-glycosylated peptides. Totally, with the strict scoring criteria, 499 non-redundant intact O-glycopeptides, 173 O-glycosylation sites and 6 types of O-glycans originating from 49 O-glycoprotein groups were identified in human serum, including 121 novel O-glycosylation sites. Currently, this is the largest data set of site-specific native O-glycoproteome from human serum samples. We expect that the strategies developed by this study will facilitate in-depth analyses of native O-glycoproteomes in human serum and provide opportunities to understand the functional roles of protein O-glycosylation in human health and diseases. BIOLOGICAL SIGNIFICANCE: The altered O-glycoproteome is associated with human pathological state and is an attractive source of disease biomarkers. However, site-specific O-glycosylation analysis is challenging because of the microheterogeneity (different glycoforms attached to one glycosylation site) and macroheterogeneity (site occupancy) of O-glycosylation. In this work, we developed a systematic strategy for intact O-glycopeptide characterization. This study took advantage of the inherent properties of the new fragmentation method called EThcD, which provides more complete fragmentation information about O-glycosylated peptides and a more confident site localization of O-glycans than collision-induced dissociation (HCD). We demonstrated that multiple enzyme digestion or multidimensional separation can make sample preparation more efficient and that EThcD was not only suitable for the identification of singly O-glycosylated peptides (50.3%) but also doubly (21.2%) and triply (28.5%) O-glycosylated peptides. Finally, we got a largest data set of site-specific native O-glycoproteome from human serum samples. Furthermore, quantitative analysis of intact O-glycopeptides from the serum samples of IgA nephropathy (IgAN) patients and healthy donors was performed, and the results showed the potential of the strategy to discover O-glycosylation biomarkers. We expect that the strategies developed by this study will facilitate in-depth analyses of native O-glycoproteomes in human serum and lead to exciting opportunities to understand the functional roles of protein O-glycosylation in human health and diseases.
未加说明:人们曾深入研究人血清,试图通过整体蛋白质组分析来鉴定生物标志物。糖蛋白组的改变与包括癌症、炎症和退行性疾病在内的人类病理状态有关,是疾病生物标志物的一个有吸引力的来源。由于 O-糖基化的微观异质性和宏观异质性,人血清中特定位置的 O-糖基化分析仍然具有挑战性。在这里,我们开发了一种系统策略,该策略结合了多种酶消化、多维分离用于样品制备以及高分辨率串联 MS 和 Byonic 软件用于完整 O-糖肽的特征描述。我们证明了多种酶消化或多维分离可以使样品制备更有效,并且 EThcD 不仅适用于鉴定单-O-糖基化肽(50.3%),也适用于鉴定二-O-糖基化肽(21.2%)和三-O-糖基化肽(28.5%)。通过严格的评分标准,在人血清中鉴定到了 499 个非冗余的完整 O-糖肽、173 个 O-糖基化位点和 6 种来源于 49 个 O-糖蛋白组的 O-聚糖,包括 121 个新的 O-糖基化位点。目前,这是来自人血清样本的特定位置天然 O-糖蛋白组的最大数据集。我们希望本研究中开发的策略将有助于深入分析人血清中的天然 O-糖蛋白组,并为了解蛋白质 O-糖基化在人类健康和疾病中的功能作用提供机会。
生物学意义:改变的 O-糖蛋白组与人类病理状态有关,是疾病生物标志物的一个有吸引力的来源。然而,由于 O-糖基化的微观异质性(连接到一个糖基化位点的不同糖型)和宏观异质性(糖基化位点占有率),特定位置的 O-糖基化分析具有挑战性。在这项工作中,我们开发了一种用于完整 O-糖肽特征描述的系统策略。本研究利用了一种新的碎片化方法 EThcD 的固有特性,与碰撞诱导解离(HCD)相比,EThcD 提供了更完整的 O-糖基化肽的碎片化信息,并能更有把握地确定 O-聚糖的位置。我们证明了多种酶消化或多维分离可以使样品制备更有效,并且 EThcD 不仅适用于鉴定单-O-糖基化肽(50.3%),也适用于鉴定二-O-糖基化肽(21.2%)和三-O-糖基化肽(28.5%)。最后,我们从人血清样本中获得了最大的特定位置天然 O-糖蛋白组数据集。此外,对 IgA 肾病(IgAN)患者和健康供体的血清样本中的完整 O-糖肽进行了定量分析,结果表明该策略具有发现 O-糖基化生物标志物的潜力。我们希望本研究中开发的策略将有助于深入分析人血清中的天然 O-糖蛋白组,并为了解蛋白质 O-糖基化在人类健康和疾病中的功能作用提供机会。
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