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.