Gut enterotype-dependent modulation of gut microbiota and their metabolism in response to xanthohumol supplementation in healthy adults.

Xanthohumol (XN), a polyphenol found in the hop plant (Humulus lupulus), has antioxidant, anti-inflammatory, prebiotic, and anti-hyperlipidemic activity. Preclinical evidence suggests the gut microbiome is essential in mediating these bioactivities; however, relatively little is known about XN's impact on human gut microbiota in vivo. We conducted a randomized, triple-blinded, placebo-controlled clinical trial (ClinicalTrials.gov NCT03735420) to determine safety and tolerability of XN in healthy adults. Thirty healthy participants were randomized to 24 mg/day XN or placebo for 8 weeks. As secondary outcomes, quantification of bacterial metabolites and 16S rRNA gene sequencing were utilized to explore the relationships between XN supplementation, gut microbiota, and biomarkers of gut health. Although XN did not significantly change gut microbiota composition, it did re-shape individual taxa in an enterotype-dependent manner. High levels of inter-individual variation in metabolic profiles and bioavailability of XN metabolites were observed. Moreover, reductions in microbiota-derived bile acid metabolism were observed, which were specific to Prevotella and Ruminococcus enterotypes. These results suggest interactions between XN and gut microbiota in healthy adults are highly inter-individualized and potentially indicate that XN elicits effects on gut health in an enterotype-dependent manner.

Dietary (poly)phenols mitigate inflammatory bowel disease: Therapeutic targets, mechanisms of action, and clinical observations.

Inflammatory bowel diseases (IBD), which include Crohn's disease and ulcerative colitis, are a rapidly growing public health concern worldwide. These diseases are heterogeneous at the clinical, immunological, molecular, genetic, and microbial level, but characteristically involve a disrupted immune-microbiome axis. Shortcomings in conventional treatment options warrant the need for novel therapeutic strategies to mitigate these life-long and relapsing disorders of the gastrointestinal tract. Polyphenols, a diverse group of phytochemicals, have gained attention as candidate treatments due to their array of biological effects. Polyphenols exert broad anti-inflammatory and antioxidant effects through the modulation of cellular signaling pathways and transcription factors important in IBD progression. Polyphenols also bidirectionally modulate the gut microbiome, supporting commensals and inhibiting pathogens. One of the primary means by which gut microbiota interface with the host is through the production of metabolites, which are small molecules produced as intermediate or end products of metabolism. There is growing evidence to support that modulation of the gut microbiome by polyphenols restores microbially derived metabolites critical to the maintenance of intestinal homeostasis that are adversely disrupted in IBD. This review aims to define the therapeutic targets of polyphenols that may be important for mitigation of IBD symptoms, as well as to collate evidence for their clinical use from randomized clinical trials.

Computation-Assisted Identification of Bioactive Compounds in Botanical Extracts: A Case Study of Anti-Inflammatory Natural Products from Hops.

The slow pace of discovery of bioactive natural products can be attributed to the difficulty in rapidly identifying them in complex mixtures such as plant extracts. To overcome these hurdles, we explored the utility of two machine learning techniques, i.e., Elastic Net and Random Forests, for identifying the individual anti-inflammatory principle(s) of an extract of the inflorescences of the hops (Humulus lupulus) containing hundreds of natural products. We fractionated a hop extract by column chromatography to obtain 40 impure fractions, determined their anti-inflammatory activity using a macrophage-based bioassay that measures inhibition of iNOS-mediated formation of nitric oxide, and characterized the chemical composition of the fractions by flow-injection HRAM mass spectrometry and LC-MS/MS. Among the top 10 predictors of bioactivity were prenylated flavonoids and humulones. The top Random Forests predictor of bioactivity, xanthohumol, was tested in pure form in the same bioassay to validate the predicted result (IC50 7 µM). Other predictors of bioactivity were identified by spectral similarity with known hop natural products using the Global Natural Products Social Networking (GNPS) algorithm. Our machine learning approach demonstrated that individual bioactive natural products can be identified without the need for extensive and repetitive bioassay-guided fractionation of a plant extract.