Development of an adaptable headspace sampling method for metabolic profiling of the fungal volatome.

TitleDevelopment of an adaptable headspace sampling method for metabolic profiling of the fungal volatome.
Publication TypeJournal Article
Year of Publication2018
AuthorsAhmed, WM, Geranios, P, White, IR, Lawal, O, Nijsen, TM, Bromley, MJ, Goodacre, R, Read, ND, Fowler, SJ
JournalAnalyst
Volume143
Issue17
Pagination4155-4162
Date Published2018 Aug 20
ISSN1364-5528
Abstract

Pulmonary aspergillosis can cause serious complications in people with a suppressed immune system. Volatile metabolites emitted by Aspergillus spp. have shown promise for early detection of pathogenicity. However, volatile profiles require further research, as effective headspace analysis methods are required for extended chemical coverage of the volatome; in terms of both very volatile and semi-volatile compounds. In this study, we describe a novel adaptable sampling method in which fungal headspace samples can be sampled continuously throughout a defined time period using both active (pumped) and passive (diffusive) methods, with the capability for samples to be stored for later off-line analysis. For this method we utilise thermal desorption-gas chromatography-mass spectrometry to generate volatile metabolic profiles using Aspergillus fumigatus as the model organism. Several known fungal-specific volatiles associated with secondary metabolite biosynthesis (including α-pinene, camphene, limonene, and several sesquiterpenes) were identified. A comparison between the wild-type A. fumigatus with a phosphopantetheinyl transferase null mutant strain (ΔpptA) that is compromised in secondary metabolite synthesis, revealed reduced production of sesquiterpenes. We also showed the lack of terpene compounds production during the early growth phase, whilst pyrazines were identified in both early and late growth phases. We have demonstrated that the fungal volatome is dynamic and it is therefore critically necessary to sample the headspace across several time periods using a combination of active and passive sampling techniques to analyse and understand this dynamism.

DOI10.1039/c8an00841h
Alternate JournalAnalyst
PubMed ID30069568