Novel Method for Reliable Identification of Siccibacter and Franconibacter Strains: from "Pseudo-Cronobacter" to New Enterobacteriaceae Genera.

In the last decade, strains of the genera and have been misclassified as first and later Because 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 and strains are by biochemical testing or by sequencing of the gene as part of 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 and 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 and 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 and strains. Finally, we verified our approach using seven previously unclassified strains, all of which were correctly identified, thereby validating our method. We show that the majority of methods currently used for the identification of and bacteria are not able to properly distinguish these strains from those of While sequencing of the gene as part of 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 , , and bacteria and identifies and at the species level. Using intact-cell MALDI-TOF MS, we extend the current MALDI Biotyper database with 11 and MSPs. In addition, the use of our approach is likely to lead to a more reliable identification scheme for and strains and, consequently, a more trustworthy epidemiological picture of their involvement in disease.