Salmonella is among the leading foodborne pathogens in the European Union, with Salmonella Enteritidis and Salmonella Typhimurium being the most frequently reported serovars. Traditional methods for Salmonella identification and serotyping, such as ISO standards, are time-consuming and labor-intensive. MALDI-TOF MS has emerged as a rapid and reliable tool for bacterial identification. This study evaluated the ability of MALDI-TOF MS in identifying Salmonella isolates collected from various stages of chicken and pork meat production. Eight pathogenic isolates (four S. Enteritidis and four S. Typhimurium) were analyzed using both direct colony transfer and protein extraction methods. Results showed that the direct transfer method yielded low-confidence or no identification for four isolates. However, all isolates were successfully identified with high-confidence scores (> 2.00) after protein extraction. Despite the good scores, all isolates were identified only at the genus level (Salmonella sp.), consistent with current limitations of the MALDI Biotyper database. Nevertheless, best database matches after protein extraction indicated potential for more detailed classification. This study confirms that MALDI-TOF MS, particularly when combined with protein extraction, is a valuable method for rapid screening and identification of Salmonella sp. in food production chain. However, its inability to perform accurate serotyping highlights the need for improved databases and computational approaches. Future integration of machine learning and expanded reference spectra may enhance the serotype-level resolution of MALDI-TOF MS.
Vidaković-Knežević et al. (Thu,) studied this question.