Rapid Identification of L. monocytogenes and L. innocua Based on MALDI-TOF MS
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Abstract:
To improve the discrimination ability of MALDI-TOF MS in identifying Listeria species, the objective of this work was to establish a rapid and accurate MS method to discriminate L. monocytogenes and L. innocua. Protein mass spectra of 79 verified L. monocytogenes and 57 L. innocua strains were generated using MALDI-TOF MS and subsequently analyzed with ClinPro tools software for specific biomarker identification and discrimination model establishment. The results of peak statistic showed that 16 specific peaks with significant difference were identified, including 6 L. monocytogenes and 10 L. innocua specific biomarker candidates, respectively. It was found that the mass peaks 3985/7970 u and 3972/7942 u in Listeria monocytogenes were independent and linked. Furthermore, the discrimination model based on genetic algorithm presented better cross validation (99.44%) and recognition capability (100.00%), and correct classified rate could reach above 96%, which can obtain the rapid and accurate identification for L. monocytogenes and L. innocua. Meanwhile, main spectra of a defined collection of these strains were compiled using Bruker Biotyper software and added to an in-house reference library. Evaluation of this library with 8 untested Listeria strains yielded improved score values, which were higher than that of commercial database. Application of the in-house database can improve the automatic identification capability of MALDI-TOF MS for Listeria species.
