In the last decade, strains of the genera Franconibacter and Siccibacter have been misclassified as first Enterobacter and later Cronobacter Because Cronobacter is a serious foodborne pathogen that affects premature neonates and elderly individuals, such misidentification may not only falsify epidemiological statistics but also lead to tests of powdered infant formula or other foods giving false results. Currently, the main ways of identifying Franconibacter and Siccibacter strains are by biochemical testing or by sequencing of the fusA gene as part of Cronobacter multilocus sequence typing (MLST), but in relation to these strains the former is generally highly difficult and unreliable while the latter remains expensive. To address this, we developed a fast, simple, and most importantly, reliable method for Franconibacter and Siccibacter identification based on intact-cell matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Our method integrates the following steps: data preprocessing using mMass software; principal-component analysis (PCA) for the selection of mass spectrum fingerprints of Franconibacter and Siccibacter strains; optimization of the Biotyper database settings for the creation of main spectrum projections (MSPs). This methodology enabled us to create an in-house MALDI MS database that extends the current MALDI Biotyper database by including Franconibacter and Siccibacter strains. Finally, we verified our approach using seven previously unclassified strains, all of which were correctly identified, thereby validating our method.IMPORTANCE We show that the majority of methods currently used for the identification of Franconibacter and Siccibacter bacteria are not able to properly distinguish these strains from those of Cronobacter While sequencing of the fusA gene as part of Cronobacter MLST remains the most reliable such method, it is highly expensive and time-consuming. Here, we demonstrate a cost-effective and reliable alternative that correctly distinguishes between Franconibacter, Siccibacter, and Cronobacter bacteria and identifies Franconibacter and Siccibacter at the species level. Using intact-cell MALDI-TOF MS, we extend the current MALDI Biotyper database with 11 Franconibacter and Siccibacter MSPs. In addition, the use of our approach is likely to lead to a more reliable identification scheme for Franconibacter and Siccibacter strains and, consequently, a more trustworthy epidemiological picture of their involvement in disease.

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