Title: | Volatile fingerprinting of human respiratory viruses from cell culture |
Author(s): | Purcaro G; Rees CA; Wieland-Alter WF; Schneider MJ; Wang X; Stefanuto PH; Wright PF; Enelow RI; Hill JE; |
Address: | "Thayer School of Engineering, Dartmouth College, Hanover, NH, 03755, United States of America" |
ISSN/ISBN: | 1752-7163 (Electronic) 1752-7155 (Print) 1752-7155 (Linking) |
Abstract: | "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" |
Keywords: | Animals *Cell Culture Techniques Cell Line Discriminant Analysis Humans Influenza A virus/physiology Least-Squares Analysis Metabolome Metabolomics/*methods Mice Respiratory Syncytial Virus Infections/metabolism Respiratory Syncytial Viruses/*metabolism V; |
Notes: | "MedlinePurcaro, Giorgia Rees, Christiaan A Wieland-Alter, Wendy F Schneider, Mark J Wang, Xi Stefanuto, Pierre-Hugues Wright, Peter F Enelow, Richard I Hill, Jane E eng R21 AI121076/AI/NIAID NIH HHS/ T32 LM012204/LM/NLM NIH HHS/ Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't England 2017/12/05 J Breath Res. 2018 Mar 1; 12(2):026015. doi: 10.1088/1752-7163/aa9eef" |