Microbial diversity of 3 raw milk samples after 72 h of storage at 4 °C in a bulk tank was analyzed by culture-dependent and -independent methods. The culture-dependent approach was based on the isolation of bacteria on complex and selective media, chemotaxonomic differentiation of isolates, and subsequent identification by 16S rRNA gene sequencing. The culture-independent approach included the treatment of raw milk with the dye propidium monoazide before direct DNA extraction by mechanic and enzymatic cell lysis approaches, and cloning and sequencing of the 16S rRNA genes. The selective detection of viable bacteria improved the comparability between bacterial compositions of raw milk based on culture-dependent and -independent methods, which was the major objective of this study. Several bacterial species of the phyla Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria were detected by the culture-dependent method, whereas mainly bacteria of the phylum Proteobacteria as well as low proportions of the phyla Bacteroidetes and Actinobacteria were detected by the culture-independent method. This led to the conclusion that the phylum Firmicutes was strongly discriminated by the culture-independent approach. Generally, species richness detected by the culture-dependent method was higher than that detected by the culture-independent method for all samples. However, few taxa could be detected solely by the direct DNA-based method. In conclusion, the combination of culture-dependent and -independent methods led to the detection of the highest bacterial diversity for the raw milk samples analyzed. It was shown that DNA extraction from raw milk as the essential step in culture-independent methods causes the discrimination of taxa by incomplete cell lysis. Treatment of raw milk with the viability dye propidium monoazide was optimized for the application in raw milk without former removal of milk ingredients and proved to be a suitable tool to ensure comparability of bacterial diversity depicted by both methods.

The complex interplay of a pathogen with the host immune response and the endogenous microbiome determines the course and outcome of gastrointestinal infection (GI). Expansion of a pathogen within the gastrointestinal tract implies an increased risk to develop systemic infection. Through computational modeling, we aimed to calculate bacterial population dynamics in GI in order to predict infection course and outcome. For the implementation and parameterization of the model, oral mouse infection experiments with Yersinia enterocolitica were used. Our model takes into account pathogen specific characteristics, such as virulence, as well as host properties, such as microbial colonization resistance or immune responses. We were able to confirm the model calculations in these scenarios by experimental mouse infections and show that it is possible to computationally predict the infection course. Far future clinical application of computational modeling of infections may pave the way for personalized treatment and prevention strategies of GI.

Despite the widespread use of antiseptics such as chlorhexidine digluconate (CHX) in dental practice and oral care, the risks of potential resistance toward these antimicrobial compounds in oral bacteria have only been highlighted very recently. Since the molecular mechanisms behind antiseptic resistance or adaptation are not entirely clear and the bacterial stress response has not been investigated systematically so far, the aim of the present study was to investigate the transcriptomic stress response in Streptococcus mutans after treatment with CHX using RNA sequencing (RNA-seq). Planktonic cultures of stationary-phase S. mutans were treated with a sublethal dose of CHX (125 µg/mL) for 5 min. After treatment, RNA was extracted, and RNA-seq was performed on an Illumina NextSeq 500. Differentially expressed genes were analyzed and validated by qRT-PCR. Analysis of differential gene expression following pathway analysis revealed a considerable number of genes and pathways significantly up- or downregulated in S. mutans after sublethal treatment with CHX. In summary, the expression of 404 genes was upregulated, and that of 271 genes was downregulated after sublethal CHX treatment. Analysis of differentially expressed genes and significantly regulated pathways showed regulation of genes involved in purine nucleotide synthesis, biofilm formation, transport systems and stress responses. In conclusion, the results show a transcriptomic stress response in S. mutans upon exposure to CHX and offer insight into potential mechanisms that may result in development of resistances.

The newborn's immune system is faced with the challenge of having to learn quickly to fight off infectious agents, but tolerating the colonization of the body surfaces with commensals without reacting with an excessive inflammatory response. Myeloid‐derived suppressor cells (MDSC) are innate immune cells with suppressive activity on other immune cells that regulate fetal‐maternal tolerance during pregnancy and control intestinal inflammation in neonates. Until now, nothing is known about the role of MDSC in microbiome establishment. One of the transcription factors regulating MDSC homeostasis is the hypoxia‐inducible factor 1α (HIF‐1α). We investigated the impact of HIF‐1α on MDSC accumulation and microbiome establishment during the neonatal period in a mouse model with targeted deletion of HIF‐1α in myeloid cells (Hif1a loxP/loxPLysMCre+). We show that in contrast to wildtype mice, where an extensive expansion of MDSC was observed, MDSC expansion in neonatal Hif1a loxP/loxPLysMCre+ mice was dramatically reduced both systemically and locally in the intestine. This was accompanied by an altered microbiome composition and intestinal T‐cell homeostasis. Our results point toward a role of MDSC in inflammation regulation in the context of microbiome establishment and thus reveal a new aspect of the biological role of MDSC during the neonatal period.

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