| Title: | SPME-GCxGC-TOF MS fingerprint of virally-infected cell culture: Sample preparation optimization and data processing evaluation |
| Author(s): | Purcaro G; Stefanuto PH; Franchina FA; Beccaria M; Wieland-Alter WF; Wright PF; Hill JE; |
| Address: | "Thayer School of Engineering, Dartmouth College, Hanover, NH, 03755, United States. Electronic address: Giorgia.purcaro@dartmouth.edu. Thayer School of Engineering, Dartmouth College, Hanover, NH, 03755, United States. Geisel School of Medicine, Dartmouth College, Hanover, NH, 03755, United States. Geisel School of Medicine, Dartmouth College, Hanover, NH, 03755, United States; Dartmouth-Hitchcock Medical Center, Lebanon, NH, 03756, United States. Thayer School of Engineering, Dartmouth College, Hanover, NH, 03755, United States; Geisel School of Medicine, Dartmouth College, Hanover, NH, 03755, United States" |
| DOI: | 10.1016/j.aca.2018.03.037 |
| ISSN/ISBN: | 1873-4324 (Electronic) 0003-2670 (Print) 0003-2670 (Linking) |
| Abstract: | "Untargeted metabolomics study of volatile organic compounds produced by different cell cultures is a field that has gained increasing attention over the years. Solid-phase microextraction has been the sampling technique of choice for most of the applications mainly due to its simplicity to implement. However, a careful optimization of the analytical conditions is necessary to obtain the best performances, which are highly matrix-dependent. In this work, five different solid-phase microextraction fibers were compared for the analysis of the volatiles produced by cell culture infected with the human respiratory syncytial virus. A central composite design was applied to determine the best time-temperature combination to maximize the extraction efficiency and the salting-out effect was evaluated as well. The linearity of the optimized method, along with limits of detection and quantification and repeatability was assessed. Finally, the effect of i) different normalization techniques (i.e. z-score and probabilistic quotient normalization), ii) data transformation (i.e. in logarithmic scale), and iii) different feature selection algorithms (i.e. Fisher ratio and random forest) on the capability of discriminating between infected and not-infected cell culture was evaluated" |
| Keywords: | Analysis of Variance Biomarkers/analysis Gas Chromatography-Mass Spectrometry Hep G2 Cells Humans Limit of Detection Metabolomics/*methods Respiratory Syncytial Virus Infections/*diagnosis Respiratory Syncytial Viruses/*isolation & purification *Solid Pha; |
| Notes: | "MedlinePurcaro, Giorgia Stefanuto, Pierre-Hugues Franchina, Flavio A Beccaria, Marco Wieland-Alter, Wendy F Wright, Peter F Hill, Jane E eng R21 AI121076/AI/NIAID NIH HHS/ Evaluation Study Validation Study Netherlands 2018/06/06 Anal Chim Acta. 2018 Oct 16; 1027:158-167. doi: 10.1016/j.aca.2018.03.037. Epub 2018 Mar 30" |
