Microbiology Service, Institute for Research INCLIVA, Hospital Clínico Universitario, Valencia, Spain.
Department of Microbiology, School of Medicine, University of Valencia, Av. Blasco Ibáñez 17, 46010, Valencia, Spain.
Eur J Clin Microbiol Infect Dis. 2018 Dec;37(12):2331-2339. doi: 10.1007/s10096-018-3380-x. Epub 2018 Sep 27.
The use of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for diagnosing viral infections by directly testing clinical specimens has not previously been explored. In this proof-of-principle study, we tested the hypothesis that proteomic profiling of cerebrospinal fluid (CSF) by mass spectrometry may be useful in the diagnosis of enteroviral (EV) meningitis. A total of 114 cryopreserved CSF samples were analyzed, of which 47 were positive for EV and 67 were negative. Total CSF proteins were precipitated and subjected to MALDI-TOF-MS analysis in a low (2-20 kDa) molecular weight range using a MicroFlex LT mass spectrometer. The whole data set was randomly split into a training set (n = 76 specimens) and a validation set (n = 38 samples). Backward/forward stepwise logistic regression analyses identified 30 peaks that were differentially present in EV-positive and EV-negative specimens. These were used to build a model which displayed an overall classification accuracy of 93%. The discriminative ability of the model was confirmed by using a validation sample set (overall accuracy 83%). In fact, the model was able to correctly classify 61 out of 67 EV-negative samples and 42 out of 47 EV-positive specimens. EV meningitis is associated with a distinctive protein profile that may be directly detectable in CSF specimens by MALDI-TOF-MS.
基质辅助激光解吸电离飞行时间质谱(MALDI-TOF-MS)用于通过直接检测临床标本来诊断病毒感染的用途尚未得到探索。在这项原理验证研究中,我们检验了这样一个假设,即通过质谱对脑脊液(CSF)进行蛋白质组学分析可能有助于诊断肠道病毒(EV)脑膜炎。共分析了 114 份冷冻 CSF 样本,其中 47 份为 EV 阳性,67 份为 EV 阴性。使用 MicroFlex LT 质谱仪在低分子量范围(2-20 kDa)沉淀总 CSF 蛋白,并进行 MALDI-TOF-MS 分析。整个数据集随机分为训练集(n = 76 个标本)和验证集(n = 38 个样本)。反向/正向逐步逻辑回归分析确定了 30 个在 EV 阳性和 EV 阴性标本中差异存在的峰。这些被用于构建一个模型,该模型显示出 93%的总体分类准确性。通过使用验证样本集(总准确率 83%)来确认该模型的判别能力。实际上,该模型能够正确分类 67 个 EV 阴性样本中的 61 个和 47 个 EV 阳性样本中的 42 个。EV 脑膜炎与独特的蛋白质谱相关,该蛋白质谱可能可通过 MALDI-TOF-MS 直接在 CSF 标本中检测到。