The gut is the most extensively studied niche of the human microbiome. The aim of this study was to characterise the initial gut microbiota development of a cohort of breastfed infants (n = 192) from 1 to 24 weeks of age. V4-V5 region 16S rRNA amplicon Illumina sequencing and, in parallel, bacteriological culture. The metabolomic profile of infant urine at 4 weeks of age was also examined by LC-MS. Full-term (FT), spontaneous vaginally delivered (SVD) infants’ microbiota remained stable at both phylum and genus levels during the 24-week period examined. FT Caesarean section (CS) infants displayed an increased faecal abundance of Firmicutes (p < 0.01) and lower abundance of Actinobacteria (p < 0.001) after the first week of life compared to FT-SVD infants. FT-CS infants gradually progressed to harbouring a microbiota closely resembling FT-SVD (which remained stable) by week 8 of life, which was maintained at week 24. The gut microbiota of preterm (PT) infants displayed a significantly greater abundance of Proteobacteria compared to FT infants (p < 0.001) at week 1. Metabolomic analysis of urine at week 4 indicated PT-CS infants have a functionally different metabolite profile than FT (both CS and SVD) infants. Co-inertia analysis showed co-variation between the urine metabolome and the faecal microbiota of the infants. Tryptophan and tyrosine metabolic pathways, as well as fatty acid and bile acid metabolism, were found to be affected by delivery mode and gestational age. These findings confirm that mode of delivery and gestational age both have significant effects on early neonatal microbiota composition. There is also a significant difference between the metabolite profile of FT and PT infants. Prolonged breastfeeding was shown to have a significant effect on the microbiota composition of FT-CS infants at 24 weeks of age, but interestingly not on that of FT-SVD infants. Twins had more similar microbiota to one another than between two random infants, reflecting the influence of similarities in both host genetics and the environment on the microbiota.

The life sciences are currently being transformed by an unprecedented wave of developments in molecular analysis, which include important advances in instrumental analysis as well as biocomputing. In light of the central role played by metabolism in nutrition, metabolomics is rapidly being established as a key analytical tool in human nutritional studies. Consequently, an increasing number of nutritionists integrate metabolomics into their study designs. Within this dynamic landscape, the potential of nutritional metabolomics (nutrimetabolomics) to be translated into a science, which can impact on health policies, still needs to be realized.A key element to reach this goal is the ability of the research community to join, to collectively make the best use of the potential offered by nutritional metabolomics. This article, therefore, provides a methodological description of nutritional metabolomics that reflects on the state‐of‐the‐art techniques used in the laboratories of the Food Biomarker Alliance (funded by the European Joint Programming Initiative “A Healthy Diet for a Healthy Life” (JPI HDHL)) as well as points of reflections to harmonize this field. It is not intended to be exhaustive but rather to present a pragmatic guidance on metabolomic methodologies, providing readers with useful “tips and tricks” along the analytical workflow.

Apples are rich in bioactive polyphenols and fiber. Evidence suggests that consumption of apples or their bioactive components is associated with beneficial effects on lipid metabolism and other markers of cardiovascular disease (CVD). However, adequately powered randomized controlled trials are necessary to confirm these data and explore the mechanisms. We aimed to determine the effects of apple consumption on circulating lipids, vascular function, and other CVD risk markers. The trial was a randomized, controlled, crossover, intervention study. Healthy mildly hypercholesterolemic volunteers (23 women, 17 men), with a mean ± SD BMI 25.3 ± 3.7 kg/m² and age 51 ± 11 y, consumed 2 apples/d [Renetta Canada, rich in proanthocyanidins (PAs)] or a sugar- and energy-matched apple control beverage (CB) for 8 wk each, separated by a 4-wk washout period. Fasted blood was collected before and after each treatment. Serum lipids, glucose, insulin, bile acids, and endothelial and inflammation biomarkers were measured, in addition to microvascular reactivity, using laser Doppler imaging with iontophoresis, and arterial stiffness, using pulse wave analysis. Whole apple (WA) consumption decreased serum total (WA: 5.89 mmol/L; CB: 6.11 mmol/L; P = 0.006) and LDL cholesterol (WA: 3.72 mmol/L; CB: 3.86 mmol/L; P = 0.031), triacylglycerol (WA: 1.17 mmol/L; CB: 1.30 mmol/L; P = 0.021), and intercellular cell adhesion molecule-1 (WA: 153.9 ng/mL; CB: 159.4 ng/mL; P = 0.028), and increased serum uric acid (WA: 341.4 μmol/L; CB: 330 μmol/L; P = 0.020) compared with the CB. The response to endothelium-dependent microvascular vasodilation was greater after the apples [WA: 853 perfusion units (PU), CB: 760 PU; P = 0.037] than after the CB. Apples had no effect on blood pressure or other CVD markers. These data support beneficial hypocholesterolemic and vascular effects of the daily consumption of PA-rich apples by mildly hypercholesterolemic individuals. This trial was registered at clinicaltrials.gov as NCT01988389.

Fruit is a key component of a healthy diet. However, it is still not clear whether some classes of fruit may be more beneficial than others and whether all individuals whatever their age, gender, health status, genotype, or gut microbiota composition respond in the same way to fruit consumption. Such questions require further observational and intervention studies in which the intake of a specific fruit can be precisely assessed at the population and individual levels. Within the Food Biomarker Alliance Project (FoodBAll Project) under the Joint Programming Initiative “A Healthy Diet for a Healthy Life”, an ambitious action was undertaken aiming at reviewing existent literature in a systematic way to identify validated and promising biomarkers of intake for all major food groups, including fruits. This paper belongs to a series of reviews following the same BFIRev protocol and is focusing on biomarkers of pome and stone fruit intake. Selected candidate biomarkers extracted from the literature search went through a validation process specifically developed for food intake biomarkers.