Investigation of the Effects of a High Fibre Diet Challenge on Colonic Microbiota, Metabolic Profiles and Health Outcomes across Generations

Lead Research Organisation: Imperial College London
Department Name: Metabolism, Digestion and Reproduction

Abstract

Dietary fibres are polysaccharides present in fruit, vegetables, grains or legumes. Dietary fibres cannot be digested by human digestive enzymes and therefore they reach the large intestine intact where they are fermented into short-chain fatty acids and gases by the gut microbiota. Short-chain fatty acids are absorbed into the bloodstream, and have a range of effects, such as energy source for colonocytes or regulation of lipid levels among others. Their production is a proxy for how capable the gut microbiota is to ferment dietary fibres.
Dietary fibres are an important component of a healthy lifestyle as their increased intake is associated with good health such as lower risks of heart disease, type 2 diabetes or colorectal cancer. Despite their health benefits, the average daily intake of dietary fibres of most individuals is way below the recommended 30g a day. One reason behind this is the advent of Westernised dietary patterns characterised by increased intake of animal-derived proteins and fats, sugars and reduced consumption of dietary fibre-rich foods. Evidence suggests that these dietary habits have affected the gut microbiota composition and ability to ferment fibres. Indeed, a human study has indicated that migration from a society where intake of fibre-rich foods is common to a society where Westernised dietary patterns are common and adopting the latter dietary habits leads to rapid loss of gut microbiota diversity, especially species capable of fermenting complex fibres as well as increased body-mass index. In addition, a mice study has indicated that diets low in dietary fibres over 4 generations lead to extinction of 70% of gut microbiota species and that high fibre diets cannot replace the lost species. To our knowledge, there is little information on whether what has been observed in mice is valid to humans from different generations given the current dietary habits.
The aim of this project is to elucidate these unknowns by examining the gut microbiota composition and function and health outcomes of healthy individuals in direct link from 2 or 3 generations from the same family (mother and daughter or grandmother, mother and daughter) in response to a range of dietary fibres (inulin, pectin, beta-glucan and cellulose). Two projects will be carried out to achieve this study's aims: a batch fermentation study using human stool samples (non-NHS study) and a human double-blinded, randomised cross-over clinical trial (NHS study). The first project involved incubating stool samples with a range of dietary fibres over 24h in anaerobic conditions and examination of gut microbiota composition and metabolites production. The second project will involve human volunteers taking dietary fibres or placebo supplements daily over 4 weeks and examination of their impact on gut microbiota composition, function and health outcomes (glucose, insulin, gut hormone, lipid and inflammatory marker levels).
Skills already gained during this project are: writing the protocols and ethics for both projects, for the first project ethical approval has been obtained and samples collection has been finalised, project management, analysis of participants' food diaries, DNA extraction for gut microbiota sequencing, samples preparation and analysis using gas-chromatography coupled with mass-spectrometry (GC-MS) for metabolites analysis and data analysis. Future skills expected to be gained during this are project are: obtaining ethical approval for the clinical trial, its management, analysis of gut microbiome genetic data, utilization of nuclear magnetic resonance equipment and analysing the data generated by it, preparation and analysis of blood samples to measure glucose, insulin, gut hormone, lipid and inflammatory marker levels and improved competence in using GC-MS and statistical software (R and Matlab).

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