Location: Dairy and Functional Foods Research
Project Number: 8072-41000-108-000-D
Project Type: In-House Appropriated
Start Date: Sep 22, 2020
End Date: Sep 21, 2025
Objective 1: Determine the effects of dietary bovine milk, with and without lactose, on the gut microbiota. Determine changes to the gut microbiota in response to bovine milk, with and without lactose, in terms of population dynamics and metabolome shifts on the A) small intestine microbiota B) colon microbiota. C) Analyze changes to the microbial metabolomes of the small intestine and colon in response to bovine milk, with and without lactose, which may affect human cells by altering cellular morphology or signaling pathways, and evaluate the health impact of these changes through the detection of health associated biomarkers. Objective 2: Explicate the effect of food processing on the gut microbiota. Examine the inter-effects of cheese and the gut microbiota of the A) small intestine and B) colon by assessing changes to the community population dynamics and functionality and evaluating probiotic potential of the cheese bacterial components to colonize the mucosal surface. C) Investigate the effects of polyphenol and fiber combinations alone, and in the form of a food supplemental bar, on the gut microbial colon community composition and functionality.
This project focuses on the effects of diet and food processing on the dynamics of the gut microbial community (both small and large intestines) and metabolome, and consequently, the impact on health or disease. For small intestine fermentation, experiments will be conducted using a set of 5 bioreactors with 1 designated to simulate gastric digestion, followed by duodenal and jejunal digestion, and the other 4 for ileal gut microbiota growth. For colon fermentation, experiments will use the TWINSHIME apparatus, which simulates the physiological conditions of the colon. Inoculum obtained from ileostomy fluid and from fecal samples will be used for inoculation of the small and large intestines, respectively. Specimens will be taken from each bioreactor at designated time points, and separated into bacterial pellets (BP) and supernatant phases (SP). DNA will be extracted from the BP and quantified. The community composition will be determined using Next Generation 16 Small Ribosomal RNA sequencing of the V1V2 region. Shotgun sequencing may be applied to assess genetic capacity of the microbiota and this information may be used to relate community structure to the observed metabolic function. Reads will be clustered at 97% sequence identity to form Operational Taxonomic Units (OTUs). Communities will be compared globally using weighted and unweighted principal coordinating analysis (PCoA) based on the Jaccard index and Bray-Curtis distance, and alpha diversity metrics. Statistical analysis will be carried out in the R language and corrected for false discovery. The SP will be used for measuring metabolites and examining community functionalities at the molecular level. Gas-chromatography, liquid-chromatography, and mass spectrometry will be used for metabolomics, proteomics, and lipidomics research. UPLC-MS/MS will be used for the analysis of amino acid profiles and bile salt conversion and GC-MS will be used for SCFA analysis. Proteins and peptides may also be analyzed using a nano-LC connected to a Q-TOF MS using the ProteinLynx Global Server for a database search. The selection of statistical analysis and data interpretation, such as student t-test, ANOVA, PCA and/or PCoA, depends on the analytical technique, the nature of the data, and the purpose of the specific research. To evaluate the health impact of the intestinal microbial metabolomes, the changes in cell structure, cellular morphology, signaling pathways, and health associated biomarkers will be examined, using cell lines HT-29, CACO-2, LS-174 T, and HInEpC with multiple dilutions of SP. Changes to cell structure will be determined by analyzing intestinal barrier function through measuring cell viability, quantifying transepithelial electrical resistance, examining cell permeability, and the status of tight junction proteins. Changes to the signaling pathway of cells will be determined by comparing the production of pro-inflammatory cytokines, Interleukin (IL)-1alpha, IL-6, IL-8, IL-18, TNF-alpha, and anti-inflammatory cytokines, IL-4, IL-10, and transforming growth factor (TGF)- beta1, TGF-beta2, TGF-beta3,as well as the expression of the MUC-2 and MUC-5AC genes.