Gut microbiota-mediated biotransformation of dietary bioactive compounds: inter-individual variability, determinants, and implications for personalised nutrition

Abstract

Dietary bioactive compounds, particularly polyphenols and glucosinolates, are widely associated with reduced risk of chronic disease, yet fewer than 10% of most ingested polyphenols reach systemic circulation in their active form, a figure that varies markedly by compound class; resveratrol bioavailability is below 1%, whereas some simple phenolic acids may reach 30%–50%. The gut microbiota is the primary site where these compounds are chemically transformed into absorbable metabolites, but individuals vary enormously in their capacity to carry out this transformation. This review examines how gut microbiota-mediated biotransformation of dietary bioactive compounds is determined by three interacting factors: baseline microbiota composition, fermented food consumption, and probiotic or prebiotic supplementation. The review covers polyphenols, isoflavones, ellagitannins, glucosinolates, and alkaloids. Synthetic drugs and non-dietary administration routes are excluded. The three-factor framework collectively determines an individual’s biotransformation phenotype, which governs how much of a given dietary bioactive reaches the bloodstream as an active metabolite. Documented examples include equol production from daidzein (present in only around 30% of Western adults), urolithin generation from ellagitannins (three distinct metabotypes in the population), and dihydroberberine production from berberine. Each of these variations produces measurable differences in health outcomes, including cardiovascular markers, glycaemic control, and muscle function. Biotransformation phenotyping is technically feasible through urine metabolomics and faecal enzyme assays. Personalised dietary guidance that accounts for an individual’s biotransformation capacity has the potential to resolve the inconsistency that has characterised polyphenol intervention trials. Standardised phenotyping protocols, re-analysis of existing trial datasets, and updated regulatory frameworks represent the most urgent research priorities.