Identification of Pseudomonas aeruginosa and Aspergillus fumigatus mono- and co-cultures based on volatile biomarker combinations. (29th January 2016)

• Record Type: Journal Article
• Authors: Neerincx, A H; Geurts, B P; Habets, M F J; Booij, J A; van Loon, J; Jansen, J J; Buydens, L M C; van Ingen, J; Mouton, J W; Harren, F J M; Wevers, R A; Merkus, P J F M; Cristescu, S M; Kluijtmans, L A J
• Is Part Of: Journal of breath research. Volume 10:Number 1(2016:Mar.)
• Publication Date: 2016-01-29
• Subjects: Pseudomonas aeruginosa -- Aspergillus fumigatus -- co-culture -- volatile biomarker combination -- GC-MS -- partial least squares discriminant analysis -- cystic fibrosis; Volatile organic compounds -- Analysis -- Periodicals; Clinical chemistry -- Periodicals; Bad breath -- Periodicals; Bad breath -- Treatment -- Periodicals; Bad breath -- Diagnosis -- Periodicals; 616.0756
• DOI: 10.1088/1752-7155/10/1/016002
• Languages: English
• ISSNs: 1752-7155

Abstract

Abstract: Volatile organic compound (VOC) analysis in exhaled breath is proposed as a non-invasive method to detect respiratory infections in cystic fibrosis patients. Since polymicrobial infections are common, we assessed whether we could distinguish Pseudomonas aeruginosa and Aspergillus fumigatus mono- and co-cultures using the VOC emissions. We took headspace samples of P. aeruginosa, A. fumigatus and co-cultures at 16, 24 and 48 h after inoculation, in which VOCs were identified by thermal desorption combined with gas chromatography – mass spectrometry. Using multivariate analysis by Partial Least Squares Discriminant Analysis we found distinct VOC biomarker combinations for mono- and co-cultures at each sampling time point, showing that there is an interaction between the two pathogens, with P. aeruginosa dominating the co-culture at 48 h. Furthermore, time-independent VOC biomarker combinations were also obtained to predict correct identification of P. aeruginosa and A. fumigatus in mono-culture and in co-culture. This study shows that the VOC combinations in P. aeruginosa and A. fumigatus co-microbial environment are different from those released by these pathogens in mono-culture. Using advanced data analysis techniques such as PLS-DA, time-independent pathogen specific biomarker combinations can be generated that may help to detect mixed respiratory infections in exhaled breath of cystic fibrosis patients.