Identification of potential urine proteins and microRNA biomarkers for the diagnosis of pulmonary tuberculosis patients

生物标志物 尿 肺结核 医学 蛋白质组学 甘露聚糖结合凝集素 结核分枝杆菌 生物标志物发现 小RNA 免疫学 分子生物学 凝集素 生物 内科学 病理 基因 生物化学
作者
Jieru Wang,Xiaojie Zhu,Xuekai Xiong,Pan Ge,Han Liu,Ningning Ren,Farhan Anwar Khan,Xia Zhou,Li Zhang,Yangsheng Xu,Xi Chen,Yingyu Chen,Changmin Hu,Ian Robertson,Huanchun Chen,Aizhen Guo
出处
期刊:Emerging microbes & infections [Taylor & Francis]
卷期号:7 (1): 1-13 被引量:32
标识
DOI:10.1038/s41426-018-0066-5
摘要

This study identified urinary biomarkers for tuberculosis (TB) diagnosis. The urine proteomic profiles of 45 pulmonary tuberculosis patients prior to anti-TB treatment and 45 healthy controls were analyzed and compared using two-dimensional electrophoresis with matrix-assisted laser desorption/ionization time of flight mass spectrometry. Nineteen differentially expressed proteins were identified preliminarily, and western blotting and qRT-PCR were performed to confirm these changes at the translational and transcriptional levels, respectively, using samples from 122 additional pulmonary tuberculosis patients and 73 additional healthy controls. Two proteins, mannose-binding lectin 2 and a 35-kDa fragment of inter-α-trypsin inhibitor H4, exhibited the highest differential expression. We constructed a protein-microRNA interaction network that primarily involved complement and inflammatory responses. Eleven microRNAs from microRNA-target protein interactions were screened and validated using qRT-PCR with some of the above samples, including 97 pulmonary tuberculosis patients and 48 healthy controls. Only miR-625-3p exhibited significant differential expression (p < 0.05). miR-625-3p was increased to a greater extent in samples of smear-positive than smear-negative patients. miR-625-3p was predicted to target mannose-binding lectin 2 protein. A binary logistic regression model based on miR-625-3p, mannose-binding lectin 2, and inter-α-trypsin inhibitor H4 was further established. This three-biomarker combination exhibited better performance for tuberculosis diagnosis than individual biomarkers or any two-biomarker combination and generated a diagnostic sensitivity of 85.87% and a specificity of 87.50%. These novel urine biomarkers may significantly improve tuberculosis diagnosis.

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