Volatile fingerprinting of human respiratory viruses from cell culture.
Volatile fingerprinting of human respiratory viruses from cell culture.
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DOI：
10.1088/1752-7163/aa9eef
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发表时间：
2018-03-01
影响因子：
3.8
通讯作者：
Hill JE
中科院分区：
文献类型：
--
作者：
Purcaro G;Rees CA;Wieland-Alter WF;Schneider MJ;Wang X;Stefanuto PH;Wright PF;Enelow RI;Hill JE
挥发性代谢物目前正在研究中，作为潜在的生物标志物，用于检测和鉴定病原微生物，包括细菌，真菌和病毒。与细菌和真菌不同，细菌和真菌产生与初级和次级代谢过程的先天差异相关的独特挥发性代谢特征，病毒完全依赖于受感染细胞的代谢机制进行复制和繁殖。在本研究中，挥发性代谢物的能力，区分呼吸道细胞感染和未感染病毒，在体外进行了研究。评价了两种重要的呼吸道病毒，即呼吸道合胞病毒（RSV）和甲型流感病毒（IAV）。使用三种不同的机器学习算法（随机森林（RF）、线性支持向量机（线性SVM）和偏最小二乘判别分析（PLS-DA））分析数据，从用于预测验证集中的样品分类的训练集中鉴定挥发性代谢物。RF、线性SVM和PLS-DA的区分性能对于IAV感染的细胞与未感染的细胞的比较是相当的，受试者工作特征曲线（AUROC）下的面积在0.78和0.82之间，而RF和线性SVM在RSV感染细胞与未感染细胞的分类中表现出上级性能（AUROC在0.80和0.84之间）相对于PLS-DA（0.61）。一个子集的歧视性特征被指定为推定的化合物鉴定，与过量的烃类观察在RSV和IAV感染的细胞培养物相对于未感染的控制。这一发现与氧化应激增加一致，这是一个与呼吸道细胞病毒感染相关的过程。
Volatile metabolites are currently under investigation as potential biomarkers for the detection and identification of pathogenic microorganisms, including bacteria, fungi, and viruses. Unlike bacteria and fungi, which produce distinct volatile metabolic signatures associated with innate differences in both primary and secondary metabolic processes, viruses are wholly reliant on the metabolic machinery of infected cells for replication and propagation. In the present study, the ability of volatile metabolites to discriminate between respiratory cells infected and uninfected with virus, in vitro, was investigated. Two important respiratory viruses, namely respiratory syncytial virus (RSV) and influenza A virus (IAV), were evaluated. Data were analyzed using three different machine learning algorithms (random forest (RF), linear support vector machines (linear SVM), and partial least squares-discriminant analysis (PLS-DA)), with volatile metabolites identified from a training set used to predict sample classifications in a validation set. The discriminatory performances of RF, linear SVM, and PLS-DA were comparable for the comparison of IAV-infected versus uninfected cells, with area under the receiver operating characteristic curves (AUROCs) between 0.78 and 0.82, while RF and linear SVM demonstrated superior performance in the classification of RSV-infected versus uninfected cells (AUROCs between 0.80 and 0.84) relative to PLS-DA (0.61). A subset of discriminatory features were assigned putative compound identifications, with an overabundance of hydrocarbons observed in both RSV- and IAV-infected cell cultures relative to uninfected controls. This finding is consistent with increased oxidative stress, a process associated with viral infection of respiratory cells.
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影响因子：
2.6
作者：
Mochalski, Pawel;Theurl, Markus;Sponring, Andreas;Unterkofler, Karl;Kirchmair, Rudolf;Amann, Anton
通讯作者：
Amann, Anton
影响因子：
8.8
作者：
Davies, M. P. A.;Barash, O.;Jeries, R.;Peled, N.;Ilouze, M.;Hyde, R.;Marcus, M. W.;Field, J. K.;Haick, H.
通讯作者：
Haick, H.
影响因子：
1.8
作者：
Abd El Qader, Amir;Lieberman, David;Zeiri, Yehuda
通讯作者：
Zeiri, Yehuda
影响因子：
2.4
作者：
Barker, M;Rayens, W
通讯作者：
Rayens, W
影响因子：
7.5
作者：
CORTES, C;VAPNIK, V
通讯作者：
VAPNIK, V