A high-throughput qPCR system for simultaneous quantitative detection of dairy <em>Lactococcus lactis</em> and <em>Leuconostoc</em> bacteriophages

Simultaneous quantitative detection of Lactococcus (Lc.) lactis and Leuconostoc species bacteriophages (phages) has not been reported in dairies using undefined mixed-strain DL-starters, probably due to the lack of applicable methods. We optimized a high-throughput qPCR system that allows simultaneous quantitative detection of Lc. lactis 936 (now SK1virus), P335, c2 (now C2virus) and Leuconostoc phage groups. Component assays are designed to have high efficiencies and nearly the same dynamic detection ranges, i.e., from ~1.1 x 105 to ~1.1 x 101 phage genomes per reaction, which corresponds to ~9 x 107 to ~9 x 103 phage particles mL-1 without any additional up-concentrating steps. The amplification efficiencies of the corresponding assays were 100.1±2.6, 98.7±2.3, 101.0±2.3 and 96.2±6.2. The qPCR system was tested on samples obtained from a dairy plant that employed traditional mother-bulk-cheese vat system. High levels of 936 and P335 phages were detected in the mother culture and the bulk starter, but also in the whey samples. Low levels of phages were detected in the cheese milk samples

Impact of the gut microbiota on rodent models of human disease

Traditionally bacteria have been considered as either pathogens, commensals or symbionts. The mammal gut harbors 10(14) organisms dispersed on approximately 1000 different species. Today, diagnostics, in contrast to previous cultivation techniques, allow the identification of close to 100% of bacterial species. This has revealed that a range of animal models within different research areas, such as diabetes, obesity, cancer, allergy, behavior and colitis, are affected by their gut microbiota. Correlation studies may for some diseases show correlation between gut microbiota composition and disease parameters higher than 70%. Some disease phenotypes may be transferred when recolonizing germ free mice. The mechanistic aspects are not clear, but some examples on how gut bacteria stimulate receptors, metabolism, and immune responses are discussed. A more deeper understanding of the impact of microbiota has its origin in the overall composition of the microbiota and in some newly recognized species, such as Akkermansia muciniphila, Segmented filamentous bacteria and Faecalibacterium prausnitzii, which seem to have an impact on more or less severe disease in specific models. Thus, the impact of the microbiota on animal models is of a magnitude that cannot be ignored in future research. Therefore, either models with specific microbiota must be developed, or the microbiota must be characterized in individual studies and incorporated into data evaluation