Magic™ Anti-Salmonella Monoclonal antibody, Clone N0022334

Raw egg-based dishes present a safety risk when eggs of uncertain Salmonella status are used. Here, the inactivation of four Salmonella serovars at different combinations of acid, pH and temperature were investigated. Strains of egg or broiler-associated Salmonella serovars Enteritidis, Infantis, Typhimurium, and a heat resistant Senftenberg 775W were tested in broth and egg yolk. It was observed that although S. Senftenberg 775W survived better than its mutant lacking the loci of heat resistance, the wild type per se was not acid tolerant. For all strains, egg yolk acidification with vinegar to pH 3.9 and storage at 25 degrees C or 8 degrees C resulted in >4Log(cfu/mL) reductions within 2h or 24h, respectively. At pH 4.2, 2-3Log(cfu/mL) reductions were seen within 6h at 25 degrees C. In contrast, acidification with lemon juice to pH of 3.9 allowed for growth at 25 degrees C, while a pH of 2.9 ensured >4Log(cfu/mL) reductions within 24h. Egg yolk and acid form the basis for many recipes and with a ratio of 0.82 of vinegar (>= 5% acetic acid) to egg yolk or 1.23 of lemon juice to yolk and storage at 25 degrees C for 2h or 24h, respectively, a high degree of safety can be obtained, if properly chilled raw eggs are used.

Surface-enhanced Raman spectroscopy (SERS) with subsequent chemometric evaluation was performed for the rapid and non-destructive differentiation of seven important meat-associated microorganisms, namely Brochothrix thermosphacta DSM 20171(T), Pseudomonas fluorescens DSM 4358, Salmonella enterica subsp. enterica sv. Enteritidis DSM 14221, Listeria monocytogenes DSM 19094, Micrococcus luteus DSM 20030(T), Escherichia coli HB101 and Bacillus thuringiensis sv. israelensis DSM 5724. A simple method for collecting spectra from commercial paper-based SERS substrates without any laborious pre-treatments was used. In order to prepare the spectroscopic data for classification at genera level with a subsequent chemometric evaluation consisting of principal component analysis and discriminant analysis, a data pre-processing method with spike correction and sum normalisation was performed. Because of the spike correction rather than exclusion, and therefore the use of a balanced data set, the multivariate analysis of the data is significantly resilient and meaningful. The analysis showed that the differentiation of meat-associated microorganisms and thereby the detection of important meatrelated pathogenic bacteria was successful on genera level and a cross-validation as well as a classification of ungrouped data showed promising results, with 99.5% and 97.5%, respectively.