Nutrients can regulate metabolic and other biological processes by altering expression of genes. Transcriptomics analysis allows measurement of all genes in a given sample and is an important tool in studying the molecular mechanisms that underlie the interaction between nutrition and health.
The Nutrigenomics technology platform within the Nutrition, Metabolism and Genomics group of the Division of Human Nutrition provides a comprehensive approach for robust and reliable transcriptomics analysis. We use a high‑throughput microarray system (Affymetrix GeneTitan) for rapid and cost‑effective measurement of gene expression in a wide variety of cells and organisms. Complementing our laboratory facilities, we have an in‑house‑developed database and data-analysis pipeline, allowing in‑depth analysis of microarray and RNAseq data. One of the major bottlenecks of transcriptomics analysis is the biological interpretation of the data.
A major strength of the nutrigenomics platform is that we have extensive experience with the interpretation of transcriptomics data and with coupling transcriptomics data to other relevant biological parameters. Over the past 10 years we have become one of the leading research units in nutrigenomics, as exemplified by our collaborative research with numerous partners worldwide and by our contribution to over one-hundred published (nutri)genomic studies.
Development of databases and tools
In addition to performing microarray analysis for multiple internal and external partners, the group is involved in the development of improved methodology for data analysis. We have developed a database and analysis system for centralized storage and analysis of microarray data called Madmax, presently containing over 10000 microarrays. Our efforts are aligned with the development of The Phenotype Data Infrastructure (www.dbNP.org), an open source application suite to store biological studies. Currently, Madmax enables us to perform statistical analysis at both the gene and pathway level, and provides built-in Gene Set Enrichment Analysis, Gene Ontology analysis and secretome analysis.
The use of transcriptomics technology has yielded a vast amount of data, most of which is publicly available in special repositories. To tap into this rich source of information, we have developed tools to facilitate the mining of these existing datasets. We have also put a serious effort into the creation of special resources that can be made available to a wider audience, including a custom‑developed database tool allowing visualization of gene expression along the length of the small intestine.
Muscle Health and Function
Within the TI Food and Nutrition project on Muscle Health and Function we lead the workpackage Gene Expression Profiles in Muscle Biopsies. This project aims to establish the impact of nutrition and exercise on muscle growth and function. In our workpackage we aim to identify expression profiles that are associated with age and health status. In addition to collecting transcriptomics data, we collect metabolomics data in serum and in muscle tissue in collaboration with the Netherlands Metabolomics Centre. The combined transcriptomics and metabolomics analysis will allow us to study shifts in metabolism induced by training or immobilisation at different levels, thereby clarifying the mechanisms underlying the effects of training and nutrition on health.