Page 46 - Small Animal Clinical Nutrition 5th Edition

46 Small Animal Clinical Nutrition

moment, with expression levels that span many orders of Because these genomic technologies generate an avalanche
VetBooks.ir magnitude, there is no single technology platform that can of data, there is a need for continuing developments in bioin-
formatics. Bioinformatics refers to the computational tech-
measure all the protein in the cell. Therefore, proteomics and
nologies that support the processing, clustering, dynamics,
the corresponding proteomic technologies are not as widely
used or as standardized as the gene-based studies and tech- integration and storing of the enormously complex datasets
nologies described above. However, because protein expres- like those generated from “omics” research. The challenge is
sion is the functional outcome of gene transcription and to combine all these pieces of information to ensure all data
translation, it has long been a focus of extensive research. can be observed coherently. To gain full access to the poten-
Using proteomics tools (the analysis of the proteome), tial output of the new “omics” tools, it is imperative to
researchers can simultaneously display and determine thou- address the enormous challenge of unifying complex and dis-
sands of proteins in a study sample and identify their changes similar data. The goal is to turn all these data into knowl-
in response to nutritional inputs. Research methods in pro- edge.
teomics are progressing rapidly. Proteome analysis holds great Bioinformatics software packages can be obtained through
promise for discoveries in nutrition research (Afman and licensing arrangements with a variety of organizations, pur-
Muller, 2006). chased from specialty software companies or are available
One of the newest “omics” is metabolomics. Metabolomics from open sources. Open source software usually requires
technology measures the level of all substances, other than programming skills on the part of the user. Regardless of
DNA, RNA or protein, present in a sample. Metabolites source, these packages generally include programs for data
include such things as intermediates of metabolism and a vari- analysis and visualization. Visualization describes a way of
ety of low molecular weight molecules (e.g., lactic acid, carbon qualitatively “graphing” the results; it is an important step in
dioxide, ketones, ATP, ADP, prostaglandins, prostacyclins and extracting knowledge from data. Other software go beyond
thromboxanes). The metabolome represents the complete set data analysis and visualization to provide the means of over-
of metabolites synthesized by a biologic system. Studying laying the data generated from “omics” experiments onto
metabolites is important because of the simplistic, often incor- knowledge-based molecular pathways and networks and pro-
rect belief that one gene leads to the formation of one protein, vide an overview of the interactions of the genomic, pro-
which creates one metabolite (Munoz et al, 2004). The study teomic and metabolomic data together in the context of the
of a cell’s complete set of metabolites is much more complex whole cell.
than transcriptomics and proteomics. Besides the huge variety
and number of potential metabolites, many cellular metabo-
lites have a very rapid turnover. For example, ATP has a half- THE PROMISE OF NUTRITIONAL
life of less than 0.1 second. Also, metabolites need to be deter- GENOMICS: EXAMPLES OF PROGRESS
mined separately in the different compartments of a cell (e.g., AND POTENTIAL
cytoplasm, mitochondria, extracellular matrix) (van der Werf
et al, 2001). Until recently, it was thought that changes in gene expression
Unlike transcriptomics, proteomics and metabolomics are attributed to diet were mediated through endocrine or neural
not yet routinely performed, do not have standardized proce- pathways. However, research has shown that macronutrients,
dures and continue to face challenges such as sample prepara- micronutrients and their metabolites can directly regulate gene
tion, technological sensitivity and lack of standardized statisti- expression. For example, some of the earliest evidence demon-
cal methods (Mutch et al, 2005). However, the potential for strating direct effects of nutrients on gene expression came
nutritional applications of metabolomics is considerable and a from studies in zinc-deficient rats. In these models, researchers
number of research teams are addressing the current shortcom- found that almost 50 genes were either up- or down-regulated
ings (Afman and Muller, 2006). in the zinc-deficient group, suggesting new mechanisms for
“Systems biology” refers to a merging of the previously dis- some of the signs associated with zinc deficiency (Blanchard
cussed “omics” technologies. Together, transcriptomics, pro- and Cousins, 1996). Currently, many food components, includ-
teomics and metabolomics allow for nutrition studies to con- ing minerals besides zinc, vitamins, carotenoids, flavonoids,
currently observe and quantify a significant fraction of all reg- monoterpenes and phenolic acids are thought to act as tran-
ulated genes, gene expression products and metabolites. scriptional activator molecules affecting gene expression
Because these layers of “omics” technologies are related (e.g., (Milner, 2004).
genes encode RNA, which produces enzymes that catalyze The action mechanism of dietary carbohydrates in metabol-
the conversion of metabolites), this combination of datasets ic programming and its short- and long-term effects is a
paves the way to a complete description of how a cellular sys- macronutrients example. Studies showed that feeding rat pups
tem behaves in response to external stimuli (Corthesy- a high-carbohydrate milk formula resulted in hyperinsulinemia
Theulaz et al, 2005). Although the complexity of the systems that persisted throughout the period of dietary intervention.
biology approach exceeds the current bioinformatics tool’s There was increased hexokinase activity and increased gene
capabilities, its implications for nutrition research can be expression of preproinsulin and related transcription factors and
enormous. kinases in the pancreatic islets. In these experiments, the pre-