Long-term cultured human myotubes decrease contractile gene expression and regulate apoptosis-related genes.

The present study examined time-dependent changes in the gene expression profile of long-term cultured human myotubes. Microarray transcriptional analysis was performed in a primary culture of differentiated myotubes from one subject over seven weeks. This analysis showed a main gradual fall in genes of the contractile apparatus, and a broad upregulation of genes involved in cell development and growth, followed by stress response and signal transduction. Glucose metabolism was also monitored, but no significant alterations in glucose uptake, oxidation or glycogen storage were observed. Mitochondrial membrane potential, or the amount of membrane lipid peroxides, remained similarly unchanged, nor was lactate dehydrogenase leakage observed. Time-dependent changes in eight genes were validated by real-time RT-PCR in primary cultured myotubes from four subjects, of similar age and isolated after equivalent replication cycles in vitro and differentiated over seven weeks. Insulin-like growth factor-binding protein 2 (IGFBP2), a modulator of the IGF signal, was upregulated. The antiapoptotic gene heat-shock 70-kd protein 2 (HSPA2) was induced, whereas the proapoptotic tumor necrosis factor receptor superfamily, member 25 (WSL-1) was suppressed. A decline in the muscle-specific gene M-cadherin and contraction genes, such as slow-twitch troponin I (TNNI1) and myosin heavy chain 2 (MYH2), myosin light chain 1 (MYL1) and myosin-binding protein H (MYBPH), which are expressed in adult fast-twitch muscle, was shown. In summary, these data demonstrate extensive downregulation of contractile genes and modulation of apoptosis-related genes, in favour of cell survival, during maintenance of cultured human myotubes.

Changes in the transcriptional profile of transporters in the intestine along the anterior-posterior and crypt-villus axes.

BACKGROUND: The purpose of this work was to characterize the expression of drug and nutrient carriers along the anterior-posterior and crypt-villus axes of the intestinal epithelium and to study the validity of utilizing whole gut tissue rather than purified epithelial cells to examine regional variations in gene expression. RESULTS: We have characterized the mRNA expression profiles of 76 % of all currently known transporters along the anterior-posterior axis of the gut. This is the first study to describe the expression profiles of the majority of all known transporters in the intestine. The expression profiles of transporters, as defined according to the Gene Ontology consortium, were measured in whole tissue of the murine duodenum, jejunum, ileum and colon using high-density microarrays. For nine transporters (Abca1, Abcc1, Abcc3, Abcg8, Slc10a2, Slc28a2, Slc2a1, Slc34a2 and Slc5a8), the mRNA profiles were further measured by RT-PCR in laser micro-dissected crypt and villus epithelial cells corresponding to the aforementioned intestinal regions. With respect to differentially regulated transporters, the colon had a distinct expression profile from small intestinal segments. The majority (59 % for p cutoff < or = 0.05) of transporter mRNA levels were constant across the intestinal sections studied. For the transporter subclass "carrier activity", which contains the majority of known carriers for biologically active compounds, a significant change (p < or = 0.05) along the anterior-posterior axis was observed. CONCLUSION: All nine transporters examined in laser-dissected material demonstrated good replication of the region-specific profiles revealed by microarray. Furthermore, we suggest that the distribution characteristics of Slc5a8 along the intestinal tract render it a suitable candidate carrier for monocarboxylate drugs in the posterior portion of the intestine. Our findings also predict that there is a significant difference in the absorption of carrier-mediated compounds in the different intestinal segments. The most pronounced differences can be expected between the adjoining segments ileum and colon, but the differences between the other adjoining segments are not negligible. Finally, for the examined genes, profiles measured in whole intestinal tissue extracts are representative of epithelial cell-only gene expression.

An integrative metabolism approach identifies stearoyl-CoA desaturase as a target for an arachidonate-enriched diet.

Epidemiological studies have correlated diets containing higher intakes of PUFA with lower rates of chronic metabolic diseases. The molecular mechanisms regulated by the consumption of PUFA were examined by using an integrative metabolism approach assaying the liver transcriptome and lipid-metabolome of mice fed a control diet, an arachidonate (AA)-enriched fungal oil, an eicosapentaenoic (EPA)/docosahexaenoic (DHA)-enriched fish oil, or a combination of the two oils. Hepatic gene transcription and fatty acid (FA) metabolism were significantly altered by diets enriched with AA, as revealed by global error assessment and singular value decomposition (SVD) analysis, respectively. SVD analysis of the lipid data, reinforced with transcriptomics, suggests that the chronic feeding of AA modulates molecular endpoints similar to those previously reported in the obesity-resistant SCD1-/- mouse, namely, genes involved in lipid oxidation/synthesis and the significant changes in FA metabolism stemming from a repressed SCD1 activity. Specifically, the total levels and FA composition of several phospholipid (PL) species were significantly changed, with phosphatidylcholine (PC) demonstrating the greatest alterations. Reduced PC levels were linked to decreased expression of enzymes in PC biosynthesis (choline kinase, -2.2-fold; glycerol-3-phosphate acyltransferase, -2.0-fold). Alterations in PL-FA composition were related to decreased expression of FA biosynthetic genes [fatty acid synthetase, -3.7-fold; stearoyl-CoA desaturase-1 (SCD1), -1.8-fold]. Lower hepatic SCD1 gene expression levels were reflected in various aspects of FA metabolism through increased concentrations of palmitic (fungal oil, +45%; combination, +106%) and stearic acids (fungal oil, +60%; combination, +63%) in PC. Importantly, an integrated approach showed that these effects were not attenuated by the addition of an EPA/DHA-enriched fish oil, thereby identifying a previously unrecognized and distinct role for AA in the regulation of hepatic lipid metabolism.

The Global Error Assessment (GEA) model for the selection of differentially expressed genes in microarray data.

MOTIVATION: Microarray technology has become a powerful research tool in many fields of study; however, the cost of microarrays often results in the use of a low number of replicates (k). Under circumstances where k is low, it becomes difficult to perform standard statistical tests to extract the most biologically significant experimental results. Other more advanced statistical tests have been developed; however, their use and interpretation often remain difficult to implement in routine biological research. The present work outlines a method that achieves sufficient statistical power for selecting differentially expressed genes under conditions of low k, while remaining as an intuitive and computationally efficient procedure. RESULTS: The present study describes a Global Error Assessment (GEA) methodology to select differentially expressed genes in microarray datasets, and was developed using an in vitro experiment that compared control and interferon-gamma treated skin cells. In this experiment, up to nine replicates were used to confidently estimate error, thereby enabling methods of different statistical power to be compared. Gene expression results of a similar absolute expression are binned, so as to enable a highly accurate local estimate of the mean squared error within conditions. The model then relates variability of gene expression in each bin to absolute expression levels and uses this in a test derived from the classical ANOVA. The GEA selection method is compared with both the classical and permutational ANOVA tests, and demonstrates an increased stability, robustness and confidence in gene selection. A subset of the selected genes were validated by real-time reverse transcription-polymerase chain reaction (RT-PCR). All these results suggest that GEA methodology is (i) suitable for selection of differentially expressed genes in microarray data, (ii) intuitive and computationally efficient and (iii) especially advantageous under conditions of low k. AVAILABILITY: The GEA code for R software is freely available upon request to authors.

Regional variations in ABC transporter expression along the mouse intestinal tract.

The ATP-binding cassette (ABC) family of proteins comprise a group of membrane transporters involved in the transport of a wide variety of compounds, such as xenobiotics, vitamins, lipids, amino acids, and carbohydrates. Determining their regional expression patterns along the intestinal tract will further characterize their transport functions in the gut. The mRNA expression levels of murine ABC transporters in the duodenum, jejunum, ileum, and colon were examined using the Affymetrix MuU74v2 GeneChip set. Eight ABC transporters (Abcb2, Abcb3, Abcb9, Abcc3, Abcc6, Abcd1, Abcg5, and Abcg8) displayed significant differential gene expression along the intestinal tract, as determined by two statistical models (a global error assessment model and a classic ANOVA, both with a P < 0.01). Concordance with semiquantitative real-time PCR was high. Analyzing the promoters of the differentially expressed ABC transporters did not identify common transcriptional motifs between family members or with other genes; however, the expression profile for Abcb9 was highly correlated with fibulin-1, and both genes share a common complex promoter model involving the NFkappaB, zinc binding protein factor (ZBPF), GC-box factors SP1/GC (SP1F), and early growth response factor (EGRF) transcription binding motifs. The cellular location of another of the differentially expressed ABC transporters, Abcc3, was examined by immunohistochemistry. Staining revealed that the protein is consistently expressed in the basolateral compartment of enterocytes along the anterior-posterior axis of the intestine. Furthermore, the intensity of the staining pattern is concordant with the expression profile. This agrees with previous findings in which the mRNA, protein, and transport function of Abcc3 were increased in the rat distal intestine. These data reveal regional differences in gene expression profiles along the intestinal tract and demonstrate that a complete understanding of intestinal ABC transporter function can only be achieved by examining the physiologically distinct regions of the gut.

Personal metabolomics as a next generation nutritional assessment.

Nutrition research is in the process of addressing a series of questions related to the future of diet and health. Are all humans the same with respect to their response to diet? If not, humans must be fed differently according to the differences in their genetics and metabolic needs. Are those differences self-evident to the individual or their care-givers? If not, methods must be developed to measure the basis of differences between humans. Are the current sets of diagnostic biomarkers for disease appropriate and sufficient to distinguish the appropriate diets of humans for optimal metabolic health? If not, metabolites must be measured such that the differences in human metabolism are resolvable before they become diseased. Will a small subset of metabolic markers provide an indication of intended and unintended effects of diets that relate to overall metabolism? If not, comprehensive metabolic analyses (metabolomics) must be put in place to ensure that all aspects of health are accurately assessed. Inappropriate dietary choices are accelerating the development of chronic metabolic disease and threatening to overwhelm public health's ability to manage them. Nutrition and food sciences will need to collaborate with other scientific disciplines to develop and implement metabolic assessment technologies and to assemble annotated databases of metabolite profiles in humans, thus building the knowledge needed to link metabolism to diet and health. Biochemical and physiological research must be guided to define the mechanisms by which diet interacts with metabolism in different individuals. Integrating metabolism with the genetic and dietary variables that affect health is the role of nutrition sciences. Integrating personal nutritional value with food's other key values of safety, quality, comfort, delight, convenience and affordability is the role of food science. It is time for these two fields to address a common problem, metabolic health, with coordinated solutions.

Genomics and metabolomics as markers for the interaction of diet and health: lessons from lipids.

Foods are not purified compounds acting on single molecular targets, but complex mixtures of molecules that modulate many biochemical pathways simultaneously. Diet affects the probability of developing various diseases. Nevertheless, specific recommendations for individual diets are not simple. Recommending nutrient intakes above and beyond those needed to provide adequacy requires scientific knowledge and regulatory scrutiny to ensure the efficacy and safety even of essential nutrients. Designing a diet to improve metabolic health is a bold and ambitious goal. It is possible to design foods that will alter metabolism, but what change will make everyone who is otherwise healthy even healthier? Changing one aspect of metabolism to lower the risk of one disease does not improve overall health if it comes at the expense of disrupting another aspect of metabolism that increases the risk of another disease. This issue has: 1) frustrated nutritional recommendations that could provide benefits to the health of large subsets of the population, 2) caused the recall of drugs with many beneficial effects and 3) caused harm by implying that single nutrients/foods could be healthy for everyone. An individualized system for metabolic assessment would establish the efficacy and safety of nutrients such as amino acids or fatty acids when these are designed to be consumed at levels providing improved metabolic health. The need to document the lack of an adverse effect of a food or drug on physiology necessitates a global, i.e. metabolomic approach.

Gene expression databases and data mining.

The DNA microarray technology has arguably caught the attention of the worldwide life science community and is now systematically supporting major discoveries in many fields of study. The majority of the initial technical challenges of conducting experiments are being resolved, only to be replaced with new informatics hurdles, including statistical analysis, data visualization, interpretation, and storage. Two systems of databases, one containing expression data and one containing annotation data are quickly becoming essential knowledge repositories of the research community. This present paper surveys several databases, which are considered "pillars" of research and important nodes in the network. This paper focuses on a generalized workflow scheme typical for microarray experiments using two examples related to cancer research. The workflow is used to reference appropriate databases and tools for each step in the process of array experimentation. Additionally, benefits and drawbacks of current array databases are addressed, and suggestions are made for their improvement.

Unraveling lipid metabolism with microarrays: effects of arachidonate and docosahexaenoate acid on murine hepatic and hippocampal gene expression.

The functions, actions, and regulation of polyunsaturated fatty acids (PUFAs) are beginning to be unraveled. Mice were fed diets rich in either arachidonic acid, docosahexaenoic acid, or both. Liver and hippocampus tissue were then analyzed through a combined gene expression-, lipid-, and behavioral- profiling strategy. Novel hippocampal PUFA-molecular targets suggest that PUFA transcriptionally regulated genes with roles in appetite and learning.

The limit fold change model: a practical approach for selecting differentially expressed genes from microarray data.

BACKGROUND: The biomedical community is developing new methods of data analysis to more efficiently process the massive data sets produced by microarray experiments. Systematic and global mathematical approaches that can be readily applied to a large number of experimental designs become fundamental to correctly handle the otherwise overwhelming data sets. RESULTS: The gene selection model presented herein is based on the observation that: (1) variance of gene expression is a function of absolute expression; (2) one can model this relationship in order to set an appropriate lower fold change limit of significance; and (3) this relationship defines a function that can be used to select differentially expressed genes. The model first evaluates fold change (FC) across the entire range of absolute expression levels for any number of experimental conditions. Genes are systematically binned, and those genes within the top X% of highest FCs for each bin are evaluated both with and without the use of replicates. A function is fitted through the top X% of each bin, thereby defining a limit fold change. All genes selected by the 5% FC model lie above measurement variability using a within standard deviation (SDwithin) confidence level of 99.9%. Real time-PCR (RT-PCR) analysis demonstrated 85.7% concordance with microarray data selected by the limit function. CONCLUSION: The FC model can confidently select differentially expressed genes as corroborated by variance data and RT-PCR. The simplicity of the overall process permits selecting model limits that best describe experimental data by extracting information on gene expression patterns across the range of expression levels. Genes selected by this process can be consistently compared between experiments and enables the user to globally extract information with a high degree of confidence.