Besides, the non-metric dimensional scoring (NMDS) plots showed that those changes were related to the initial microbiota composition. The results may offer useful information for the design of personalized food products and relevant therapies at least within Bacteroides-dominated enterotype.Sprouts harbor high populations of bacteria and cause numerous foodborne disease outbreaks, yet little is known about their microbial composition. The present study aimed to define the microbiological ecology of sprouts using 16S rRNA microbiome sequencing and culture-dependent methods. Different types (radish, alfalfa, and rapeseed), brands (A, B, and C), and distribution routes (online and offline) of sprouts (n = 70) were considered for microbiome analysis, as well as quantitative (aerobic plate count and coliforms) and qualitative analyses (Escherichia coli O157H7, Listeria monocytogenes, and Salmonella Typhimurium). The aerobic plate count ranged from 7 to 8 CFU/g, and the coliforms ranged from 6 to 7 log CFU/g. Microbiome analysis revealed that Proteobacteria was the dominant phylum, accounting for 79.0% in alfalfa sprouts, 68.5% in rapeseed sprouts, and 61.9% in radish sprouts. Enterobacteriaceae was the dominant family in alfalfa sprouts (33.9%) and rapeseed sprouts (14.6%), while Moraxellaceae (11.9%) were prevalent on radish sprouts. The majority of the dominant genera were common in the environment, such as soil or water. Alfalfa sprouts yielded the lowest aerobic plate count but the highest relative abundance of Enterobacteriaceae compared to the other sprouts. These results could explain why alfalfa sprouts are a leading cause of sprout-related foodborne disease outbreaks. Alpha-diversity results (Chao1 and Shannon indices) suggested that species richness was greater on radish sprouts than the other sprout types. Beta-diversity results showed samples were clustered by types, indicating dissimilarity in microbial communities. However, the distribution route had a limited influence on microbial composition. The present study provides a comparative examination of the microbial profiles of sprouts. Microbiome analyses contribute to an in-depth understanding of the microbial ecology of sprouts, leading to potential control measures for ensuring food safety.Xinjiang is a multiethnic region of China. Traditionally, most ethnic minorities are known to produce and consume cheese. Nomadic people have been reported to use lactic acid bacteria (LAB) for decades to produce fermented dairy products as part of a balanced diet. Non-starter LAB (NSLAB) contribute to different degrees of ripening, depending on the cheese variety. In the present study, we screened three types of NSLAB with good proteolysis and autolytic abilities from traditional Kazakh cheese Pediococcus acidilactici R3-5, Staphylococcus epidermidis R4-2, and Lactobacillus rhamnosus R9-6. A control (no NSLAB) was also included, resulting in four distinct types of cheese samples. We used gas chromatography-mass spectrometry and the electronic nose system to identify volatile compounds and analyze the effect of NSLAB on cheese flavor at the ripening stage. The physicochemical indicators changed significantly during the ripening of Kazakh cheese. Compared with the control, the protein content, free fatty acid content, pH, flavor compounds, and odor profiles of the test cheeses were significantly different. The major chemical differences among cheeses were the synthesis of some key volatile components (ethyl caprylate, ethyl caprate, myristyl carbonate, capric acid, caprylic acid, nonanal, and benzyl alcohol). NSLAB can be used as an adjunct starter to make Kazakh cheese and the use of NSLAB affected the cheese flavor quality positively.The previous research has indicated that Ganoderma atrum polysaccharide (PSG-1) indirectly affects the immune function of dendritic cells (DCs) in intestinal-like Caco-2/DCs co-culture model, in which NF-κB and MAPK pathway play an essential role. To explore the interaction of Caco-2 in the interaction between the intestinal epithelium and its internal immune cells, the intestinal-like Caco-2/DCs co-culture model was developed. All transcripts of Caco-2 treated with or without PSG-1 were globally screened by RNA-seq. The expression of 452 genes regulated by PSG-1 was statistically significant, the counts of up-regulated and down-regulated genes were 198 and 256, respectively. According to KEGG analysis, tumor necrosis factor (TNF)-α and NF-κB signaling pathways of Caco-2 were selected to elucidate the mechanism of interaction between Caco-2/DCs induced by PSG-1. After the addition of TNF-α inhibitor Apremilast and NF-κB inhibitor BAY11-70821 in Caco-2, expression of cytokines (TNF-α, IL-6, IL-1β, IL-10), chemokines (RANTES, MIP-1α, MCP-1), and the key proteins of MAPK and NF-κB pathways of DCs were all reduced. In summary, "dialogue" between Caco-2 and DCs was regulated by PSG-1 through TNF-α and NF-κB signaling pathways of Caco-2 in the model.Metagenomics is a powerful tool to study and understand the microbial dynamics that occur during food fermentation and allows to close the link between microbial diversity and final sensory characteristics. Each food matrix can be colonized by different microbes, but also by different strains of the same species. In this study, using an innovative integrated approach combining culture-dependent method with a shotgun sequencing, we were able to show how strain-level biodiversity could influence the quality characteristics of the final product. The attention was placed on a model food fermentation process Salame Piemonte, a Protected Geographical Indication (PGI) Italian fermented sausage. Three independent batches produced in February, March and May 2018 were analysed.  https://www.selleckchem.com/  The sausages were manufactured, following the production specification, in a local meat factory in the area of Turin (Italy) without the use of starter cultures. A pangenomic approach was applied in order to identify and evaluate the lactic acid bacteria (LAB) population driving the fermentation process. It was observed that all batches were characterized by the presence of few LAB species, namely Pediococcus pentosaceus, Latilactobacillus curvatus and Latilactobacillus sakei. Sausages from the different batches were different when the volatilome was taken into consideration, and a strong association between quality attributes and strains present was determined. In particular, different strains of L. sakei, showing heterogeneity at genomic level, colonized the meat at the beginning of each production and deeply influenced the fermentation process by distinctive metabolic pathways that affected the fermentation process and the final sensory aspects.