Volatile fingerprinting of human respiratory viruses from cell culture
- 1 March 2018
- journal article
- research article
- Published by IOP Publishing in Journal of Breath Research
- Vol. 12 (2), 026015
- https://doi.org/10.1088/1752-7163/aa9eef
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
Funding Information
- Hitchcock Foundation
- Burroughs Wellcome Fund (Grant#1014106)
- Center for Scientific Review (Project # 1R21AI12107601)
This publication has 58 references indexed in Scilit:
- FilmArray, an Automated Nested Multiplex PCR System for Multi-Pathogen Detection: Development and Application to Respiratory Tract InfectionPLOS ONE, 2011
- Modulators for comprehensive two-dimensional gas chromatographyTrAC Trends in Analytical Chemistry, 2011
- Visualization and Recovery of the (Bio)chemical Interesting Variables in Data Analysis with Support Vector Machine ClassificationAnalytical Chemistry, 2010
- Effect of influenza vaccination on oxidative stress products in breathJournal of Breath Research, 2010
- Respiratory Syncytial Virus Induces Oxidative Stress by Modulating Antioxidant EnzymesAmerican Journal of Respiratory Cell and Molecular Biology, 2009
- Release of volatile organic compounds (VOCs) from the lung cancer cell line CALU-1 in vitroCancer Cell International, 2008
- Headspace sorptive extraction and GC-TOFMS for the identification of volatile fungal metabolitesJournal of Microbiological Methods, 2008
- Youden Index and Optimal Cut‐Point Estimated from Observations Affected by a Lower Limit of DetectionBiometrical Journal, 2008
- Immunité naturellemédecine/sciences, 2007
- Support-vector networksMachine Learning, 1995