Selective Enrichment of Phosphopeptides and Phospholipids from Biological Matrices on TiO2 Nanowire Arrays for Direct Molecular Characterization by Internal Extractive Electrospray Ionization Mass Spectrometry
作者单位：College of ChemistryJilin University Jiangxi Key Laboratory for Mass Spectrometry and InstrumentationEast ChinaUniversity of Technology Department of Obstetrics and GynecologyFirst Hospital of Jilin University
会议名称：《2018年中国质谱学术大会（CMSC2018）》
会议日期：2018年
学科分类：081704[工学-应用化学] 07[理学] 08[工学] 0817[工学-化学工程与技术] 1010[医学-医学技术（可授医学、理学学位）] 070302[理学-分析化学] 0703[理学-化学] 10[医学]
关 键 词：Mass spectrometry TiO2 nanowire arrays extractive electrospray ionization phospholipids biological samples
摘 要：Rapid analysis of phosphopeptides and phospholipids in biological matrices is of significant interest in multiple disciplines of life science. 1-2 Herein, trace phospholipids in human plasma, whole blood and undiluted human urine as well as phosphopeptides in protein digest were selectively captured on a homemade array of TiO2 nanowires for sensitive characterization by internal extractive electrospray ionization mass spectrometry(Ti O2-i EESI-MS).3-5 Sequential release of captured chemicals from TiO2 array was achieved by tuning pH of the extraction solvent. A single sample analysis, including sample loading, chemical extraction and MS detection, was accomplished within 3 min. For the detection of LysoPC(16:0) in raw urine samples, the limit-of-detection(LOD) of 0.005 μg L-1, the linear response range of 0.1-500 μg L-1(R2 = 0.9985), the recovery rates of 94.8-101.6%, and the relative standard deviation(RSD, n = 6) values below 8.9% were demonstrated. Based on the orthogonal partial least squares discriminant analysis(OPLS-DA), TiO2-i EESI-MS patterns from the blood of 46 patients with ovarian cancer were confidently discriminated from the MS patterns of 46 healthy volunteers. Our results indicate the strong potential of Ti O2-i EESI-MS approach for the selective detection of trace phosphopeptides and phospholipids in various biological matrices with high sensitivity, high specificity, low sample consumption, and high throughput.