Song Lusheng, Wallstrom Garrick, Yu Xiaobo, Hopper Marika, Van Duine Jennifer, Steel Jason, Park Jin, Wiktor Peter, Kahn Peter, Brunner Al, Wilson Douglas, Jenny-Avital Elizabeth R, Qiu Ji, Labaer Joshua, Magee D Mitchell, Achkar Jacqueline M
From the ‡The Virginia G Piper Center for Personalized Diagnostics, The Biodesign Institute, Arizona State University, Tempe, Arizona, 85287.
§State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Radiation Medicine, Beijing, 102206, China.
Mol Cell Proteomics. 2017 Apr;16(4 suppl 1):S277-S289. doi: 10.1074/mcp.M116.065953. Epub 2017 Feb 21.
Better and more diverse biomarkers for the development of simple point-of-care tests for active tuberculosis (TB), a clinically heterogeneous disease, are urgently needed. We generated a proteomic () High-Density Nucleic Acid Programmable Protein Array (HD-NAPPA) that used a novel multiplexed strategy for expedited high-throughput screening for antibody responses to the proteome. We screened sera from HIV uninfected and coinfected TB patients and controls ( = 120) from the US and South Africa (SA) using the multiplex HD-NAPPA for discovery, followed by deconvolution and validation through single protein HD-NAPPA with biologically independent samples ( = 124). We verified the top proteins with enzyme-linked immunosorbent assays (ELISA) using the original screening and validation samples ( = 244) and heretofore untested samples ( = 41). We identified 8 proteins with TB biomarker value; four (Rv0054, Rv0831c, Rv2031c and Rv0222) of these were previously identified in serology studies, and four (Rv0948c, Rv2853, Rv3405c, Rv3544c) were not known to elicit antibody responses. Using ELISA data, we created classifiers that could discriminate patients' TB status according to geography (US or SA) and HIV (HIV- or HIV+) status. With ROC curve analysis under cross validation, the classifiers performed with an AUC for US/HIV- at 0.807; US/HIV+ at 0.782; SA/HIV- at 0.868; and SA/HIV+ at 0.723. With this study we demonstrate a new platform for biomarker/antibody screening and delineate its utility to identify previously unknown immunoreactive proteins.
迫切需要更好、更多样化的生物标志物,以开发用于活动性肺结核(TB)的简单即时检测,肺结核是一种临床异质性疾病。我们构建了一个蛋白质组学高密度核酸可编程蛋白阵列(HD-NAPPA),该阵列采用一种新型多重策略,用于快速高通量筛选针对结核分枝杆菌蛋白质组的抗体反应。我们使用多重HD-NAPPA对来自美国和南非(SA)的未感染HIV和合并感染TB的患者及对照(n = 120)的血清进行筛选以发现生物标志物,随后通过单蛋白HD-NAPPA对生物学独立样本(n = 124)进行反卷积和验证。我们使用原始筛选和验证样本(n = 244)以及此前未检测的样本(n = 41),通过酶联免疫吸附测定(ELISA)对筛选出的顶级蛋白质进行验证。我们鉴定出8种具有结核病生物标志物价值的蛋白质;其中4种(Rv0054、Rv0831c、Rv2031c和Rv0222)先前已在血清学研究中鉴定出来,另外4种(Rv0948c、Rv2853、Rv3405c、Rv3544c)此前未知可引发抗体反应。利用ELISA数据,我们创建了能够根据地理位置(美国或南非)和HIV(HIV阴性或HIV阳性)状态区分患者结核病状态的分类器。在交叉验证下进行ROC曲线分析时,这些分类器在美国/HIV阴性组的曲线下面积(AUC)为0.807;美国/HIV阳性组为0.782;南非/HIV阴性组为0.868;南非/HIV阳性组为0.723。通过这项研究,我们展示了一个用于生物标志物/抗体筛选的新平台,并描述了其在鉴定先前未知的免疫反应性蛋白质方面的效用。