Soya–dairy protein blends can extend post-exercise muscle synthesis in young people more than whey protein control. Older adults differ metabolically from young people, and their ability to absorb amino acids from dietary protein is important for muscle function. The objective was to determine how protein source affects postprandial plasma amino acid response and/or metabolomic profile in older adults via a single-blind randomised crossover trial (n 16, males 50–70 years), using three nutritionally equivalent meal replacement drinks containing 30 g protein, from a 1:1 (mass ratio) soya:dairy blend, a 1:2 soya:dairy blend or whey protein. The outcome measures were plasma amino acid concentrations at 0–300 min postprandially and urine metabolomic fingerprint. Soya:dairy drinks gave similar amino acid response in plasma over time and similar urinary metabolite fingerprints. However, there were significant differences in plasma amino acid concentrations and AUC values for the soya:dairy drinks v. the whey protein drink. AUC for Leu, Trp and Lys was lower and AUC for Phe and Pro was higher for the soya:dairy drinks. Differences partly reflected the amino acid profiles of the drinks, but overall plasma amino acid response patterns were qualitatively unchanged. Plasma amino acid differences between the whey protein drink and the soya:dairy blends were reflected in urine metabolite patterns. In conclusion, postprandial plasma amino acid responses were broadly similar, irrespective of protein source (and soya:dairy ratio). There were significant differences for some plasma amino acid concentrations, reflecting different amino acid profiles of the protein source and influencing urine metabolite fingerprints.

Host–microbial co-metabolism products are being increasingly recognised to play important roles in physiological processes. However, studies undertaking a comprehensive approach to consider host–microbial metabolic relationships remain scarce. Metabolomic analysis yielding detailed information regarding metabolites found in a given biological compartment holds promise for such an approach. This work aimed to explore the associations between host plasma metabolomic signatures and gut microbiota composition in healthy adults of the Milieu Intérieur study. For 846 subjects, gut microbiota composition was profiled through sequencing of the 16S rRNA gene in stools. Metabolomic signatures were generated through proton NMR analysis of plasma. The associations between metabolomic variables and α- and β-diversity indexes and relative taxa abundances were tested using multi-adjusted partial Spearman correlations, permutational ANOVA and multivariate associations with linear models, respectively. A multiple testing correction was applied (Benjamini–Hochberg, 10 % false discovery rate). Microbial richness was negatively associated with lipid-related signals and positively associated with amino acids, choline, creatinine, glucose and citrate (−0·133 ≤ Spearman’s ρ ≤ 0·126). Specific associations between metabolomic signals and abundances of taxa were detected (twenty-five at the genus level and nineteen at the species level): notably, numerous associations were observed for creatinine (positively associated with eleven species and negatively associated with Faecalibacterium prausnitzii). This large-scale population-based study highlights metabolites associated with gut microbial features and provides new insights into the understanding of complex host–gut microbiota metabolic relationships. In particular, our results support the implication of a ‘gut–kidney axis’. More studies providing a detailed exploration of these complex interactions and their implications for host health are needed.