Investigation of MALDI-TOF Mass Spectrometry for Assessing the Molecular Diversity of Campylobacter jejuni and Comparison with MLST and cgMLST: A Luxembourg One-Health Study
There is a need for active molecular surveillance of human and veterinary Campylobacter
infections. However, sequencing of all isolates is associated with high costs and a considerable
workload. Thus, there is a need for a straightforward complementary tool to prioritize isolates to
sequence. In this study, we proposed to investigate the ability of MALDI-TOF MS to pre-screen C.
jejuni genetic diversity in comparison to MLST and cgMLST. A panel of 126 isolates, with 10 clonal
complexes (CC), 21 sequence types (ST) and 42 different complex types (CT) determined by the
SeqSphere+ cgMLST, were analysed by a MALDI Biotyper, resulting into one average spectra per
isolate. Concordance and discriminating ability were evaluated based on protein profiles and different
cut-offs. A random forest algorithm was trained to predict STs. With a 94% similarity cut-off, an
AWC of 1.000, 0.933 and 0.851 was obtained for MLSTCC, MLSTST and cgMLST profile, respectively.
The random forest classifier showed a sensitivity and specificity up to 97.5% to predict four different
STs. Protein profiles allowed to predict C. jejuni CCs, STs and CTs at 100%, 93% and 85%, respectively.
Machine learning and MALDI-TOF MS could be a fast and inexpensive complementary tool to give
an early signal of recurrent C. jejuni on a routine basis