Recognition of pathogens in food matrixes based on the untargeted in vivo microbial metabolite profiling via a novel SPME/GC × GC-QTOFMS approach.

Foodborne diseases incurred by pathogenic bacteria are one of the major threats in food safety, and thus it is important to develop facile and effective recognition methodology of pathogens in food. Herein, a new automatic approach for detection of in vivo volatile metabolites emitted from foodborne pathogens was proposed by coupling solid phase microextraction (SPME) technique with a comprehensive two-dimensional gas chromatography quadrupole time-of-flight mass spectrometry (GC × GC-QTOFMS). A novel polymer composite based SPME probe which possessed high-coverage of microbial metabolites was utilized in this contribution to realize the sensitive extraction of untargeted metabolites. As a result, a total of 126 in vivo metabolites generated by the investigated pathogens were detected and identified, with 33, 29, 25, 21 and 18 volatile metabolites belonging to Shigella sonnei, Escherichia coli, Salmonella typhimurium, Vibrio parahaemolyticus and Staphylococcus aureus, respectively. Multivariate statistical analyses were applied for further analysis of metabolic data and separation of responsive metabolic features among different microbial systems were found, which were also successfully verified in foodstuffs contaminated by microorganisms. The growth trend of the potential volatile markers of each pathogen in food samples kept consistent with that of the pure strain incubated in medium during the whole incubation time. This study promotes the application of SPME technology in microbial volatile metabolomics and contributes to the development of new approaches for foodborne pathogens recognition.