Listeria species
are characterized as gram-positive, non-spore forming, facultative anaerobes.
The pathogen Listeria monocytogenes
is most commonly known for causing the serious disease listeriosis.
Historically, this disease is associated with consumption of contaminated soft
cheeses, meat products and ready-to-eat foods. Current culture-based methods of
detection are time consuming, involving multiple enrichments followed by
biochemical and morphological confirmation. This work describes the use of gas
chromatography coupled to orthogonal acceleration time-of-flight mass spectrometry
(GC-oaToFMS) to detect low levels of Listeria
in both selective and non-selective liquid media. Utilizing chemometric
analysis, it was possible to identify metabolic differences between inoculated
and uninoculated samples based on how L.
monocytogenes metabolised the growth medium. In the untargeted analysis,
340 metabolites features were identified. Within those features, 11 potential
biomarkers (three sugars and several unknown compounds) for L. monocytogenes were identified with a
significance of p<0.05 and a fold-change of greater than or equal to 2. This
research demonstrates the potential of GC-MS metabolomics as a rapid method of
identifying food contamination.