The Effect of Dietary BIoactives on Gut Microbiome DivErsity (DIME) - A pilot study (Untargeted metabolomics)

ABSTRACT:

The gut microbiome refers to the complex community of microorganisms (bacteria, fungi, archaea and viruses) present within our gut. The composition and complexity of gut microbiota communities are crucial for maintaining human health. Humans depend on the gut microbiota to undertake essential metabolic functions and for effective immune system operations, such as protection against pathogens and maintaining gut integrity. Richer diversity in these microbiota communities has been associated with better health. A key modulator of intestinal microbial colonies is food. Dietary bioactives, also referred to as phytochemicals (non-nutrient food components) present in fruit and vegetables, can modulate metabolic processes, promoting better health; however, the interaction of bioactives with microbial communities is not yet fully understood. We have conducted a 2x2 randomised crossover study to estimate the effect of diets rich in dietary bioactives on gut microbial diversity and health markers in 20 healthy participants. Participants consumed a diet of high bioactive (HB) rich foods (containing polyphenols, Sulphur (S) metabolites and carotenoids) vs a low bioactive (LB) diet for 2 wk, with an in-between washout period of 4 wk. The primary aim was to examine the effect of a 2-wk diet high in bioactives rich foods on gut microbial diversity compared to a low bioactive diet. The secondary aim was to assess a high vs low bioactive diet on markers of cardiovascular health, inflammation and post-prandial glucose. We hypothesized that consuming a high bioactive diet would increase microbial diversity compared to a low bioactive diet.

METHODS: Each volunteer completed 4 study visit days, 1 at the start and 1 at the end of each intervention phase. Dietary intake, including bioactives, was recorded through the Libro app linked to Nutritics. We recorded diets during a 7-d period (baseline habitual diet) followed by a 14-d intervention period per arm. On each study day, volunteers provided a 24 h urine sample collected in the 24 h preceding their visit and a stool sample. Urine and stool samples were utilized for both untargeted and targeted metabolomics. Microbial composition was assessed through whole-genome shotgun sequencing carried out by GeneWiz, performed using Illumina HiSeq 2500 platform with paired-end read length 2 x 125 bp. For vascular health, total HDL/LDL cholesterol and triglycerides, along with inflammatory markers such as hs-CRP, were analyzed with an at-home finger-prick blood sample collection kit (Medichecks). Participants also carried out an oral glucose tolerance test; glucose measurements were provided through the Freestyle Libre continuous glucose monitor (Abbott Laboratories) over a 2 h period following ingestion of 113 mL of polycal (75 g anhydrous glucose).

Untargeted metabolomics is reported in the current study MTBLS8100.

Targeted metabolomics is reported in MTBLS7290.

Linked cross omic data sets:

Whole genome sequencing data associated with this study are available in the European Nucleotide Archive (ENA): accession number PRJEB55607.

Metagenomic data associated with this study are available from MGnify: accession number MGYS00006076.

INSTRUMENT(S): Liquid Chromatography MS - negative - reverse phase, Liquid Chromatography MS - positive - reverse phase

PROVIDER: MTBLS8100 | MetaboLights | 2025-10-10

REPOSITORIES: MetaboLights