The biologically active form of vitamin D₃, 1α,25-dihydroxyvitamin D₃ (1,25(OH)₂D₃), modulates innate and adaptive immunity via genes regulated by the transcription factor vitamin D receptor (VDR). In order to identify the key vitamin D target genes involved in these processes, transcriptome-wide datasets were compared, which were obtained from a human monocytic cell line (THP-1) and peripheral blood mononuclear cells (PBMCs) treated in vitro by 1,25(OH)₂D₃, filtered using different approaches, as well as from PBMCs of individuals supplemented with a vitamin D₃ bolus. The led to the genes ACVRL1, CAMP, CD14, CD93, CEBPB, FN1, MAPK13, NINJ1, LILRB4, LRRC25, SEMA6B, SRGN, THBD, THEMIS2 and TREM1. Public epigenome- and transcriptome-wide data from THP-1 cells were used to characterize these genes based on the level of their VDR-driven enhancers as well as the level of the dynamics of their mRNA production. Both types of datasets allowed the categorization of the vitamin D target genes into three groups according to their role in (i) acute response to infection, (ii) infection in general and (iii) autoimmunity. In conclusion, 15 genes were identified as major mediators of the action of vitamin D in innate and adaptive immunity and their individual functions are explained based on different gene regulatory scenarios.

Background and objectives: Malting is a germination process that alters the composition of cereal grains and can impact the digestion of various nutrients included in whole-grain cereals. This can have a further impact on the composition of dietary fiber fractions fermented by the gut microbiota. We investigated the impact of malting with barley (Hordeum vulgare) and wheat (Triticum aestivum) grains on gut microbial metabolites during in vitro colonic fermentation in a model of human gut. Methods: Raw and malted barley and wheat grains went through in vitro gastric and intestinal digestions and a 24 h in vitro colonic fermentation mimicking human intestinal activities. Metabolite analysis was performed using nontargeted gas chromatography-mass spectrometry (GC-MS) optimized for the analysis of in vitro gut fermentation samples. Results: Multiple metabolites, including amino acids and their derivates (e.g., leucine and γ-aminobutyric acid), biogenic amines (e.g., tyramine, histamine, and putrescine), sugars and their derivates (e.g., fructose and galactinol), fatty acids and associated metabolites (e.g., glycerol and 2-aminoethanol), and energy metabolism-associated compounds (e.g., lactic acid) from raw and malted cereals were identified. The metabolite profiles differed significantly between cereal species and between raw and malted grains. Furthermore, the metabolite profiles changed during the fermentation. At 0 h, there was less variation between the metabolite profiles of raw cereals than malted cereals. At 24 h, the difference between malted barley and wheat was even more pronounced, but raw barley and wheat differed more from each other than at 0 h. Malting increased the initial sugar and sugar derivative levels in the cereals, as expected. However, levels of most amino acids and their derivates were significantly increased after the 24 h in vitro colonic fermentation. Discussion: The malting of cereal grains seems to influence the metabolites produced by the gut microbiota during colonic fermentation. Understanding how cereals and different processing methods affect gut microbial metabolism can help shed light on their microbial fermentation-mediated health impacts. The optimized GC-MS method used in this study was able to differentiate the different sample types and is thus an excellent tool for monitoring gut microbial metabolite profiles.