Download The age of genomics, transcriptomics, and

Prof. Dr. Hannelore Daniel
Lehrstuhl für Ernährungsphysiologie
Technische Universität München
Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt
Nutritional systems biology - Systembiologie der Ernährung
Von der Grundlagenforschung zur personalisierten Ernährung
The age of Nutrigenomics is upon us. Numerous initiatives in Europe and the US
have launched new programs in molecular nutrition research. Nutrigenomics seeks to
provide a molecular understanding for how diets and common dietary constituents
affect mammalian metabolism and health by altering gene/protein expression on
basis of an individual’s genetic makeup.
Although Nutrigenomics represents in the first place just another “omic”, it clearly
induces a conceptual shift in nutritional sciences. Nutritional Sciences is functional
genomics “par excellence”. Like no other environmental factor do nutrients, nonnutrient components of foods or natural xenobiotics with a huge variability in dose
and time hit a rather static genome. Every nutritional process relies on the interplay
of a large number of proteins encoded by the respective mRNA molecules that are
expressed in a certain cell organ or organism. Alterations of mRNA levels and in turn
of the corresponding protein levels are critical parameters in controlling the flux of a
nutrient or metabolite through a biochemical pathway. Nutrients and non-nutrient
components of foods, diets and lifestyle can affect essentially every step in the flow
of genetic information from gene expression to protein synthesis and protein
degradation and thereby alter metabolic functions in the most complex ways.
Although a huge body of information on mammalian genes, their chromosomal
localization, their genomic structure and in part also on the functions of the encoded
proteins has been gathered, we are far from understanding the orchestrated way of
how they make metabolism to work.
Genomic data are in the first place compositional in nature and contain limited
information about the dynamic behaviour of integrated cellular processes.
Nevertheless, recent technological advancements have made it possible to analyze
the variability and dynamic changes in the genetic response of a cell or organisms by
determining the expression level of individual or huge sets of mRNA molecules.
Whereas genomics describes large scale DNA-sequencing that provides basic
genetic information and insights into sequence heterogeneity (i.e. SNP´s: single
nucleotide polymorphisms) in coding regions of genes as well as in control elements
(i.e. promotors), transcriptomics – also called mRNA expression profiling - assesses
in a biological sample the mRNA-levels of up to several thousand open reading
frames simultaneously and this is mainly done by DNA-hybridization arrays and/or by
quantitative PCR-techniques Proteomics allows the proteome - as the protein
complement of the genome that is expressed in a cell or an organ - to be identified
and changes in protein expression patterns and levels to be determined
simultaneously. Moreover, for individual proteins posttranslational modifications that
are crucial for functions or even amino acid substitutions (polymorphisms) can here
be detected. More recently, high-throughput applications of metabolomics (or
metabonomics) based on the combination of gas or liquid chromatography
separations with mass spectrometry or NMR techniques for detection of solutes allow
hundreds of nutrients/metabolites to be detected simultaneously. These functional
genomics tools in combination allow for the first time to assess all phenotypic
changes in a biological system to alterations in its nutritional environment.
Conceptually, functional genomics is either based on gene-driven or on phenotypedriven approaches. The gene-driven approaches use genomic information for
identifying, cloning, expressing and characterizing genes at the molecular level.
Phenotype-driven approaches characterize phenotypes from random mutation
screens or naturally occurring variants to identify and clone the gene(s) responsible
for the particular phenotype, without knowledge of the underlying molecular
mechanisms. Of course, the two strategies are highly complementary at virtually all
levels of analysis and lead collectively to the correlation of genotypes and
phenotypes. As far as nature has not provided inborn errors of metabolism that
demonstrate the phenotypical consequences of individual gene/protein malfunctions,
the role of single genes or groups of genes in the make up of metabolism can be
analyzed by gene inactivation (“knock-out”) or selective expression “knock-in” and
overexpression models employing experimental animals from fruit flies (Drosophila
melanogaster) to nematodes (Caenorhabditis elegans) to mice and rats or human
cell lines. These approaches have already produced a large number of animal lines
missing one or several genes or overexpressing others and have extended our
knowledge on gene/protein functions substantially. These approaches are embedded
into a rapidly evolving world of visual biology that allows the visualisation of the
dynamics of all the processes underlying biological adaptations (i.e. automated
image analysis of real-time laser confocal microscopic observations of GFP fusions,
BAC transgenics and others). Moreover, nano-technology will provide miniaturized
systems for on-line recording of metabolic and/or physiological processes in complex
biological systems in real-time. In this respect, nutritional processes may become
visible and the numerous “black-boxes” in human metabolism may see the first light.
Nutritional systems biology rephrases the conceptual shift in nutritional sciences as a
paradigm of the biology of genome-environment interactions. Nutritional systems
biology employs the “omics” and uses model systems for the most comprehensive
description of the interplay of genes and nutritional factors that make up metabolism
in health and disease. That nutritional systems biology in its application may lead to a
“new
age
of
human
nutrition”
with
genome-based
personalized
dietary
recommendations or even personalized foods can easily be envisioned. However, we
should not forget that eating foods is still more than applied nutritional systems
biology.