Zhao Yan, Chang Cheng, Qin Peibin, Cao Qichen, Tian Fang, Jiang Jing, Li Xianyu, Yu Wenfeng, Zhu Yunping, He Fuchu, Ying Wantao, Qian Xiaohong
State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, No. 33 Life Science Park Road, Changping District, Beijing 102206, PR China.
State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, No. 33 Life Science Park Road, Changping District, Beijing 102206, PR China.
Anal Chim Acta. 2016 Jan 21;904:65-75. doi: 10.1016/j.aca.2015.11.001. Epub 2015 Nov 25.
Human plasma is a readily available clinical sample that reflects the status of the body in normal physiological and disease states. Although the wide dynamic range and immense complexity of plasma proteins are obstacles, comprehensive proteomic analysis of human plasma is necessary for biomarker discovery and further verification. Various methods such as immunodepletion, protein equalization and hyper fractionation have been applied to reduce the influence of high-abundance proteins (HAPs) and to reduce the high level of complexity. However, the depth at which the human plasma proteome has been explored in a relatively short time frame has been limited, which impedes the transfer of proteomic techniques to clinical research. Development of an optimal strategy is expected to improve the efficiency of human plasma proteome profiling. Here, five three-dimensional strategies combining HAP depletion (the 1st dimension) and protein fractionation (the 2nd dimension), followed by LC-MS/MS analysis (the 3rd dimension) were developed and compared for human plasma proteome profiling. Pros and cons of the five strategies are discussed for two issues: HAP depletion and complexity reduction. Strategies A and B used proteome equalization and tandem Seppro IgY14 immunodepletion, respectively, as the first dimension. Proteome equalization (strategy A) was biased toward the enrichment of basic and low-molecular weight proteins and had limited ability to enrich low-abundance proteins. By tandem removal of HAPs (strategy B), the efficiency of HAP depletion was significantly increased, whereas more off-target proteins were subtracted simultaneously. In the comparison of complexity reduction, strategy D involved a deglycosylation step before high-pH RPLC separation. However, the increase in sequence coverage did not increase the protein number as expected. Strategy E introduced SDS-PAGE separation of proteins, and the results showed oversampling of HAPs and identification of fewer proteins. Strategy C combined single Seppro IgY14 immunodepletion, high-pH RPLC fractionation and LC-MS/MS analysis. It generated the largest dataset, containing 1544 plasma protein groups and 258 newly identified proteins in a 30-h-machine-time analysis, making it the optimum three-dimensional strategy in our study. Further analysis of the integrated data from the five strategies showed identical distribution patterns in terms of sequence features and GO functional analysis with the 1929-plasma-protein dataset, further supporting the reliability of our plasma protein identifications. The characterization of 20 cytokines in the concentration range from sub-nanograms/milliliter to micrograms/milliliter demonstrated the sensitivity of the current strategies.
人血浆是一种易于获取的临床样本,能反映人体在正常生理状态和疾病状态下的状况。尽管血浆蛋白的动态范围广且极其复杂是障碍,但对人血浆进行全面的蛋白质组分析对于生物标志物的发现和进一步验证是必要的。免疫去除、蛋白质均衡化和超分级分离等各种方法已被应用于减少高丰度蛋白(HAPs)的影响并降低高度复杂性。然而,在相对较短的时间内对人血浆蛋白质组的探索深度有限,这阻碍了蛋白质组技术向临床研究的转化。预计开发一种最佳策略将提高人血浆蛋白质组分析的效率。在此,开发并比较了五种三维策略,这些策略将HAP去除(第一维)和蛋白质分级分离(第二维)相结合,随后进行液相色谱-串联质谱分析(第三维)以进行人血浆蛋白质组分析。针对HAP去除和复杂性降低这两个问题讨论了这五种策略的优缺点。策略A和策略B分别使用蛋白质组均衡化和串联Seppro IgY14免疫去除作为第一维。蛋白质组均衡化(策略A)偏向于富集碱性和低分子量蛋白质,富集低丰度蛋白质的能力有限。通过串联去除HAPs(策略B),HAP去除效率显著提高,而同时减去了更多的非靶向蛋白质。在复杂性降低的比较中,策略D在高pH反相液相色谱分离之前涉及去糖基化步骤。然而,序列覆盖率的增加并未如预期那样增加蛋白质数量。策略E引入了蛋白质的十二烷基硫酸钠-聚丙烯酰胺凝胶电泳分离,结果显示HAPs过度抽样且鉴定出的蛋白质较少。策略C结合了单次Seppro IgY14免疫去除、高pH反相液相色谱分级分离和液相色谱-串联质谱分析。在30小时的机器分析时间内,它生成了最大的数据集,包含1544个血浆蛋白组和258个新鉴定的蛋白质,使其成为我们研究中的最佳三维策略。对这五种策略的整合数据的进一步分析表明,在序列特征和基因本体功能分析方面,其分布模式与1929个血浆蛋白数据集相同,进一步支持了我们血浆蛋白鉴定的可靠性。对浓度范围从亚纳克/毫升到微克/毫升的20种细胞因子的表征证明了当前策略的灵敏度。