439138 Impact of Dietary Carbohydrate: Lipid Ratio on Metabolism in Murine Small Intestinal Epithelial Cells

Friday, September 18, 2015
Crowne Plaza Heidelberg City Centre
Neeraj Sinha, Nutrition, Metabolism & Genomics Group and Laboratory of Systems and Synthetic Biology, Wageningen University, Maria Suarez Diez, Laboratory of Systems and Synthetic Biology, Wageningen University, Evert Van Schothorst, Human and Animal Physiology, Wageningen University and Guido Hooiveld, Nutrition, Metabolism & Genomics Group, Wageningen University

We aim to study the effect of changes on mouse intestinal metabolism upon exposure to diets with different carbohydrate-lipid ratios. A metabolic model of small intestinal epithelial cells (sIEC) provides an optimal platform to study the induced metabolic changes on absorptive capacity by exposure to different diets. We integrated the metabolic model with genome-wide expression data from proximal, middle and distal parts of the small intestine of wild type C57BL/6J male mice that were fed 4 diets in which the amount of lipids were increased at the expense of carbohydrates (10, 20, 30, and 45 energy% percent of dietary fat). This allowed modeling of intestinal metabolism of lipid, carbohydrate, protein and vitamins to capture the essential changes in physiology and biochemistry of this intestinal cell type. This integration also allows  the validation of the sIECs model, through the comparison of  gene expression data and predicted flux values obtained through  FBA, a number of metabolic tasks can be studied with this approach by choosing the appropriate objective functions on selected metabolic reactions 

Our results show the profound impact of dietary changes on fatty acid and carbohydrate metabolism and on the ratios between the different types of secreted acyl glycerides. 

Keywords: Constrained based Metabolic modeling, Flux balance analysis, Microarray, Gene expression. 

References:

1)         Sahoo, S. and I. Thiele, Predicting the impact of diet and enzymopathies on human small intestinal epithelial cells. Human Molecular Genetics, 2013.

2)         Sigurdsson, M.I., et al., A detailed genome-wide reconstruction of mouse metabolism based on human Recon 1. BMC systems biology, 2010.

3)         Lewis, N.E., H. Nagarajan, and B.O. Palsson, Constraining the metabolic genotype-phenotype relationship using a phylogeny of in silico methods. Nature Reviews Microbiology, 2012.

4)         Covert, M.W., et al., Integrating high-throughput and computational data elucidates bacterial networks. Nature, 2004.


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