The clinical and environmental determinants of airway transcriptional profiles in allergic asthma.

RATIONALE: Gene expression profiling of airway epithelial and inflammatory cells can be used to identify genes involved in environmental asthma. METHODS: Airway epithelia and inflammatory cells were obtained via bronchial brush and bronchoalveolar lavage (BAL) from 39 subjects comprising three phenotypic groups (nonatopic nonasthmatic, atopic nonasthmatic, and atopic asthmatic) 4 hours after instillation of LPS, house dust mite antigen, and saline in three distinct subsegmental bronchi. RNA transcript levels were assessed using whole genome microarrays. MEASUREMENTS AND MAIN RESULTS: Baseline (saline exposure) differences in gene expression were related to airflow obstruction in epithelial cells (C3, ALOX5AP, CCL18, and others), and to serum IgE (innate immune genes and focal adhesion pathway) and allergic-asthmatic phenotype (complement genes, histone deacetylases, and GATA1 transcription factor) in inflammatory cells. LPS stimulation resulted in pronounced transcriptional response across all subjects in both airway epithelia and BAL cells, with strong association to nuclear factor-κB and IFN-inducible genes as well as signatures of other transcription factors (NRF2, C/EBP, and E2F1) and histone proteins. No distinct transcriptional profile to LPS was observed in the asthma and atopy phenotype. Finally, although no consistent expression changes were observed across all subjects in response to house dust mite antigen stimulation, we observed subtle differences in gene expression (e.g., GATA1 and GATA2) in BAL cells related to the asthma and atopy phenotype. CONCLUSIONS: Our results indicate that among individuals with allergic asthma, transcriptional changes in airway epithelia and inflammatory cells are influenced by phenotype as well as environmental exposures.

Evaluating genome-wide DNA methylation changes in mice by Methylation Specific Digital Karyotyping.

BACKGROUND: The study of genome-wide DNA methylation changes has become more accessible with the development of various array-based technologies though when studying species other than human the choice of applications are limited and not always within reach. In this study, we adapted and tested the applicability of Methylation Specific Digital Karyotyping (MSDK), a non-array based method, for the prospective analysis of epigenetic changes after perinatal nutritional modifications in a mouse model of allergic airway disease. MSDK is a sequenced based method that allows a comprehensive and unbiased methylation profiling. The method generates 21 base pairs long sequence tags derived from specific locations in the genome. The resulting tag frequencies determine in a quantitative manner the methylation level of the corresponding loci. RESULTS: Genomic DNA from whole lung was isolated and subjected to MSDK analysis using the methylation-sensitive enzyme Not I as the mapping enzyme and Nla III as the fragmenting enzyme. In a pair wise comparison of the generated mouse MSDK libraries we identified 158 loci that are significantly differentially methylated (P-value = 0.05) after perinatal dietary changes in our mouse model. Quantitative methylation specific PCR and sequence analysis of bisulfate modified genomic DNA confirmed changes in methylation at specific loci. Differences in genomic MSDK tag counts for a selected set of genes, correlated well with changes in transcription levels as measured by real-time PCR. Furthermore serial analysis of gene expression profiling demonstrated a dramatic difference in expressed transcripts in mice exposed to perinatal nutritional changes. CONCLUSION: The genome-wide methylation survey applied in this study allowed for an unbiased methylation profiling revealing subtle changes in DNA methylation in mice maternally exposed to dietary changes in methyl-donor content. The MSDK method is applicable for mouse models of complex human diseases in a mixed cell population and might be a valuable technology to determine whether environmental exposures can lead to epigenetic changes.

In utero supplementation with methyl donors enhances allergic airway disease in mice.

Asthma is a complex heritable disease that is increasing in prevalence and severity, particularly in developed countries such as the United States, where 11% of the population is affected. The contribution of environmental and genetic factors to this growing epidemic is currently not well understood. We developed the hypothesis, based on previous literature, that changes in DNA methylation resulting in aberrant gene transcription may enhance the risk of developing allergic airway disease. Our findings indicate that in mice, a maternal diet supplemented with methyl donors enhanced the severity of allergic airway disease that was inherited transgenerationally. Using a genomic approach, we discovered 82 gene-associated loci that were differentially methylated after in utero supplementation with a methyl-rich diet. These methylation changes were associated with decreased transcriptional activity and increased disease severity. Runt-related transcription factor 3 (Runx3), a gene known to negatively regulate allergic airway disease, was found to be excessively methylated, and Runx3 mRNA and protein levels were suppressed in progeny exposed in utero to a high-methylation diet. Moreover, treatment with a demethylating agent increased Runx3 gene transcription, further supporting our claim that a methyl-rich diet can affect methylation status and consequent transcriptional regulation. Our findings indicate that dietary factors can modify the heritable risk of allergic airway disease through epigenetic mechanisms during a vulnerable period of fetal development in mice.

Using mouse genomics to understand idiopathic interstitial fibrosis.

Idiopathic interstitial pneumonia represents a broad category of lung disorders characterized by scarring or fibrosis of the lung accompanied by varying degrees of inflammation. A number of important hypotheses based on clinical observations have substantially contributed to our understanding of the pathogenesis of the most insidious and devastating of the idiopathic interstitial pneumonias, idiopathic interstitial fibrosis (IIF). Patients with IIF usually present late in the course of their illness; thus, animal models of the early, preclinical stage of these diseases are needed. Although no model faithfully recapitulates the clinical course of disease or the histopathology observed in humans, all result in scarring of the lung and may therefore be used to understand the biological processes that contribute to this scarring. The purpose of this article is to summarize the application of mouse genetic and genomic tools to these models to advance our understanding of IIF and to describe emerging agnostic approaches to identifying genes important to the fibroproliferative component of IIF.

Pathway level analysis of gene expression using singular value decomposition.

BACKGROUND: A promising direction in the analysis of gene expression focuses on the changes in expression of specific predefined sets of genes that are known in advance to be related (e.g., genes coding for proteins involved in cellular pathways or complexes). Such an analysis can reveal features that are not easily visible from the variations in the individual genes and can lead to a picture of expression that is more biologically transparent and accessible to interpretation. In this article, we present a new method of this kind that operates by quantifying the level of 'activity' of each pathway in different samples. The activity levels, which are derived from singular value decompositions, form the basis for statistical comparisons and other applications. RESULTS: We demonstrate our approach using expression data from a study of type 2 diabetes and another of the influence of cigarette smoke on gene expression in airway epithelia. A number of interesting pathways are identified in comparisons between smokers and non-smokers including ones related to nicotine metabolism, mucus production, and glutathione metabolism. A comparison with results from the related approach, 'gene-set enrichment analysis', is also provided. CONCLUSION: Our method offers a flexible basis for identifying differentially expressed pathways from gene expression data. The results of a pathway-based analysis can be complementary to those obtained from one more focused on individual genes. A web program PLAGE (Pathway Level Analysis of Gene Expression) for performing the kinds of analyses described here is accessible at http://dulci.biostat.edu/pathways.

SpA: web-accessible spectratype analysis: data management, statistical analysis and visualization.

SUMMARY: SpA is a web-accessible system for the management, visualization and statistical analysis of T-cell receptor spectratype data. Users upload data from their spectratype analyzers to SpA, which saves the raw data and user-defined supplementary covariates to a secure database. The statistical engine performs several data analyses and statistical summaries. The visualization engine displays spectratype histograms in a Java applet and in an image file suitable for download. All of these results are also saved to the database and remain accessible to the user. Additional statistical tools specific to the analysis of multiple spectratypes are also available through the SpA interface. AVAILABILITY: The service is freely accessible via the web at http://www.duke.edu/~kepler/spa.html. Additional technical support and specialized statistical analysis and consultation are available by arrangement with the authors and, depending on the service requested, may be subject to fee.

Identifying differential expression in multiple SAGE libraries: an overdispersed log-linear model approach.

BACKGROUND: In testing for differential gene expression involving multiple serial analysis of gene expression (SAGE) libraries, it is critical to account for both between and within library variation. Several methods have been proposed, including the t test, tw test, and an overdispersed logistic regression approach. The merits of these tests, however, have not been fully evaluated. Questions still remain on whether further improvements can be made. RESULTS: In this article, we introduce an overdispersed log-linear model approach to analyzing SAGE; we evaluate and compare its performance with three other tests: the two-sample t test, tw test and another based on overdispersed logistic linear regression. Analysis of simulated and real datasets show that both the log-linear and logistic overdispersion methods generally perform better than the t and tw tests; the log-linear method is further found to have better performance than the logistic method, showing equal or higher statistical power over a range of parameter values and with different data distributions. CONCLUSION: Overdispersed log-linear models provide an attractive and reliable framework for analyzing SAGE experiments involving multiple libraries. For convenience, the implementation of this method is available through a user-friendly web-interface available at http://www.cbcb.duke.edu/sage.

Statistical analysis of antigen receptor spectratype data.

MOTIVATION: The effectiveness of vertebrate adaptive immunity depends crucially on the establishment and maintenance of extreme diversity in the antigen receptor repertoire. Spectratype analysis is a method used in clinical and basic immunological settings in which antigen receptor length diversity is assessed as a surrogate for functional diversity. The purpose of this paper is to describe the systematic derivation and application of statistical methods for the analysis of spectratype data. RESULTS: The basic probability model used for spectratype analysis is the multinomial model with n, the total number of counts, indeterminate. We derive the appropriate statistics and statistical procedures for testing hypotheses regarding differences in antigen receptor distributions and variable repertoire diversity in different treatment groups. We then apply these methods to spectratype data obtained from several healthy donors to examine the differences between normal CD4+ and CD8+ T cell repertoires, and to data from a thymus transplant patient to examine the development of repertoire diversity following the transplant.

Measurement of cell migration on surface-bound fibronectin gradients.

A novel technique for the quantitative observation of cell migration along linear gradient substrates functionalized with adhesive proteins is presented. Gradients of the cell adhesion molecule fibronectin are generated by the cross diffusion of functionalizable alkanethiols on gold and characterized by X-ray photoelectron spectroscopy and surface plasmon resonance. Two distinct migration assays are described that characterize the movement of either sparsely populated noncontacting cells or a confluent monolayer of cells into free space. The drift speed of bovine aortic endothelial cells is measured and shown to increase along a fibronectin gradient when compared to a uniform control substrate using both assays. The results of these experiments establish reproducible conditions for studies of cell migration on gradients of surface-bound ligands.

Theoretical analysis of electron transport through organic molecules.

We present a theoretical study of electron transport through a variety of organic molecules. The analysis uses the Landauer formalism in combination with complex bandstructure and projected densities of states calculations to reveal the main aspects of coherent electronic transport through alkanes, benzene-dithiol, and phenylene-ethynylene oligomers. We examine the dependence of the current on molecule length, the effects of molecule-molecule interactions from film packing, differences in contact geometry, and the influence of phenyl ring rotation on the conductances of phenylene-ethynylene oligomers such as 1,4-bis-phenylethynyl-benzene.