The biological properties of dietary polyphenols are greatly dependent on their bioavailability that, in turn, is largely influenced by their degree of polymerization. The gut microbiota play a key role in modulating the production, bioavailability and, thus, the biological activities of phenolic metabolites, particularly after the intake of food containing high-molecular-weight polyphenols. In addition, evidence is emerging on the activity of dietary polyphenols on the modulation of the colonic microbial population composition or activity. However, although the great range of health-promoting activities of dietary polyphenols has been widely investigated, their effect on the modulation of the gut ecology and the two-way relationship "polyphenols ↔ microbiota" are still poorly understood. Only a few studies have examined the impact of dietary polyphenols on the human gut microbiota, and most were focused on single polyphenol molecules and selected bacterial populations. This review focuses on the reciprocal interactions between the gut microbiota and polyphenols, the mechanisms of action and the consequences of these interactions on human health.

Background: Few studies have investigated the effect of dietary polyphenols on the complex human gut microbiota, and they focused mainly on single polyphenol molecules and select bacterial populations.

Persons with high intake of polyunsaturated fatty acids (PUFAs) have lower cardiovascular morbidity and mortality. The protective effect of PUFAs is mediated by multiple mechanisms, including their antiinflammatory properties. The association of physiological PUFA levels with pro- and antiinflammatory markers has not been established. In 1123 persons (aged 20-98 yr), we examined the relationship between relative concentration of fatty acids in fasting plasma and level of inflammatory markers. Adjusting for age, sex, and major confounders, lower arachidonic and docosahexaenoic acids were associated with significantly higher IL-6 and IL-1ra and significantly lower TGFbeta. Lower alpha-linolenic acid was associated with higher C-reactive protein and IL-1ra, and lower eicosapentaenoic acid was associated with higher IL-6 and lower TGFbeta. Lower docosahexaenoic acid was strongly associated with lower IL-10. Total n-3 fatty acids were associated with lower IL-6 (P = 0.005), IL-1ra (P = 0.004), and TNFalpha (P = 0.040) and higher soluble IL-6r (P < 0.001), IL-10 (P = 0.024), and TGFbeta (P = 0.0012). Lower n-6 fatty acid levels were significantly associated with higher IL-1ra (P = 0.026) and lower TGFbeta (P = 0.014). The n-6 to n-3 ratio was a strong, negative correlate of IL-10. Findings were similar in participants free of cardiovascular diseases and after excluding lipids from covariates. In this community-based sample, PUFAs, and especially total n-3 fatty acids, were independently associated with lower levels of proinflammatory markers (IL-6, IL-1ra, TNFalpha, C-reactive protein) and higher levels of antiinflammatory markers (soluble IL-6r, IL-10, TGFbeta) independent of confounders. Our findings support the notion that n-3 fatty acids may be beneficial in patients affected by diseases characterized by active inflammation.

Flavan-3-ols, occurring in monomeric, as well as in oligomeric and polymeric forms (also known as condensed tannins or proanthocyanidins), are among the most abundant and bioactive dietary polyphenols, but their in vivo health effects in humans may be limited because of their recognition as xenobiotics. Bioavailability of flavan-3-ols is largely influenced by their degree of polymerization; while monomers are readily absorbed in the small intestine, oligomers and polymers need to be biotransformed by the colonic microbiota before absorption. Therefore, phenolic metabolites, rather than the original high molecular weight compounds found in foods, may be responsible for the health effects derived from flavan-3-ol consumption. Flavan-3-ol phenolic metabolites differ in structure, amount and excretion site. Phase II or tissular metabolites derived from the small intestine and hepatic metabolism are presented as conjugated derivatives (glucuronic acid or sulfate esters, methyl ether, or their combined forms) of monomeric flavan-3-ols and are preferentially eliminated in the bile, whereas microbial metabolites are rather simple conjugated lactones and phenolic acids that are largely excreted in urine. Although the colon is seen as an important organ for the metabolism of flavan-3-ols, the microbial catabolic pathways of these compounds are still under consideration, partly due to the lack of identification of bacteria with such capacity. Studies performed with synthesized or isolated phase II conjugated metabolites have revealed that they could have an effect beyond their antioxidant properties, by interacting with signalling pathways implicated in important processes involved in the development of diseases, among other bioactivities. However, the biological properties of microbe-derived metabolites in their actual conjugated forms remain largely unknown. Currently, there is an increasing interest in their effects on intestinal infections, inflammatory intestinal diseases and overall gut health. The present review will give an insight into the metabolism and microbial biotransformation of flavan-3-ols, including tentative catabolic pathways and aspects related to the identification of bacteria with the ability to catabolize these kinds of polyphenols. Also, the in vitro bioactivities of phase II and microbial phenolic metabolites will be covered in detail.

Bioinformatic tools for the enrichment of ‘omics’ datasets facilitate interpretation and understanding of data. To date few are suitable for metabolomics datasets. The main objective of this work is to give a critical overview, for the first time, of the performance of these tools. To that aim, datasets from metabolomic repositories were selected and enriched data were created. Both types of data were analysed with these tools and outputs were thoroughly examined. An exploratory multivariate analysis of the most used tools for the enrichment of metabolite sets, based on a non-metric multidimensional scaling (NMDS) of Jaccard’s distances, was performed and mirrored their diversity. Codes (identifiers) of the metabolites of the datasets were searched in different metabolite databases (HMDB, KEGG, PubChem, ChEBI, BioCyc/HumanCyc, LipidMAPS, ChemSpider, METLIN and Recon2). The databases that presented more identifiers of the metabolites of the dataset were PubChem, followed by METLIN and ChEBI. However, these databases had duplicated entries and might present false positives. The performance of over-representation analysis (ORA) tools, including BioCyc/HumanCyc, ConsensusPathDB, IMPaLA, MBRole, MetaboAnalyst, Metabox, MetExplore, MPEA, PathVisio and Reactome and the mapping tool KEGGREST, was examined. Results were mostly consistent among tools and between real and enriched data despite the variability of the tools. Nevertheless, a few controversial results such as differences in the total number of metabolites were also found. Disease-based enrichment analyses were also assessed, but they were not found to be accurate probably due to the fact that metabolite disease sets are not up-to-date and the difficulty of predicting diseases from a list of metabolites. We have extensively reviewed the state-of-the-art of the available range of tools for metabolomic datasets, the completeness of metabolite databases, the performance of ORA methods and disease-based analyses. Despite the variability of the tools, they provided consistent results independent of their analytic approach. However, more work on the completeness of metabolite and pathway databases is required, which strongly affects the accuracy of enrichment analyses. Improvements will be translated into more accurate and global insights of the metabolome.

The food metabolome is defined as the part of the human metabolome directly derived from the digestion and biotransformation of foods and their consti