Robust computational reconstitution – a new method for the comparative analysis of gene expression in tissues and isolated cell fractions

BACKGROUND: Biological tissues consist of various cell types that differentially contribute to physiological and pathophysiological processes. Determining and analyzing cell type-specific gene expression under diverse conditions is therefore a central aim of biomedical research. The present study compares gene expression profiles in whole tissues and isolated cell fractions purified from these tissues in patients with rheumatoid arthritis and osteoarthritis. RESULTS: The expression profiles of the whole tissues were compared to computationally reconstituted expression profiles that combine the expression profiles of the isolated cell fractions (macrophages, fibroblasts, and non-adherent cells) according to their relative mRNA proportions in the tissue. The mRNA proportions were determined by trimmed robust regression using only the most robustly-expressed genes (1/3 to 1/2 of all measured genes), i.e. those showing the most similar expression in tissue and isolated cell fractions. The relative mRNA proportions were determined using several different chip evaluation methods, among which the MAS 5.0 signal algorithm appeared to be most robust. The computed mRNA proportions agreed well with the cell proportions determined by immunohistochemistry except for a minor number of outliers. Genes that were either regulated (i.e. differentially-expressed in tissue and isolated cell fractions) or robustly-expressed in all patients were identified using different test statistics. CONCLUSION: Robust Computational Reconstitution uses an intermediate number of robustly-expressed genes to estimate the relative mRNA proportions. This avoids both the exclusive dependence on the robust expression of individual, highly cell type-specific marker genes and the bias towards an equal distribution upon inclusion of all genes for computation

Long-Lived Plasma Cells and Memory B Cells Produce Pathogenic Anti-GAD65 Autoantibodies in Stiff Person Syndrome

Stiff person syndrome (SPS) is a rare, neurological disorder characterized by sudden cramps and spasms. High titers of enzyme-inhibiting IgG autoantibodies against the 65 kD isoform of glutamic acid decarboxylase (GAD65) are a hallmark of SPS, implicating an autoimmune component in the pathology of the syndrome. Studying the B cell compartment and the anti-GAD65 B cell response in two monozygotic twins suffering from SPS, who were treated with the B cell-depleting monoclonal anti-CD20 antibody rituximab, we found that the humoral autoimmune response in SPS is composed of a rituximab-sensitive part that is rapidly cleared after treatment, and a rituximab-resistant component, which persists and acts as a reservoir for autoantibodies inhibiting GAD65 enzyme activity. Our data show that these potentially pathogenic anti-GAD65 autoantibodies are secreted by long-lived plasma cells, which may either be persistent or develop from rituximab-resistant memory B lymphocytes. Both subsets represent only a fraction of anti-GAD65 autoantibody secreting cells. Therefore, the identification and targeting of this compartment is a key factor for successful treatment planning of SPS and of similar autoimmune diseases

Integrative modeling of transcriptional regulation in response to antirheumatic therapy

<p>Abstract</p> <p>Background</p> <p>The investigation of gene regulatory networks is an important issue in molecular systems biology and significant progress has been made by combining different types of biological data. The purpose of this study was to characterize the transcriptional program induced by etanercept therapy in patients with rheumatoid arthritis (RA). Etanercept is known to reduce disease symptoms and progression in RA, but the underlying molecular mechanisms have not been fully elucidated.</p> <p>Results</p> <p>Using a DNA microarray dataset providing genome-wide expression profiles of 19 RA patients within the first week of therapy we identified significant transcriptional changes in 83 genes. Most of these genes are known to control the human body's immune response. A novel algorithm called TILAR was then applied to construct a linear network model of the genes' regulatory interactions. The inference method derives a model from the data based on the Least Angle Regression while incorporating DNA-binding site information. As a result we obtained a scale-free network that exhibits a self-regulating and highly parallel architecture, and reflects the pleiotropic immunological role of the therapeutic target TNF-alpha. Moreover, we could show that our integrative modeling strategy performs much better than algorithms using gene expression data alone.</p> <p>Conclusion</p> <p>We present TILAR, a method to deduce gene regulatory interactions from gene expression data by integrating information on transcription factor binding sites. The inferred network uncovers gene regulatory effects in response to etanercept and thus provides useful hypotheses about the drug's mechanisms of action.</p

A New Cryogenic Test Facility for Large and Heavy Superconducting Magnets

CERN has recently designed and constructed a new cryogenic facility for testing large and heavy superconducting magnets at liquid helium temperatures. The facility, erected in a large assembly hall with cranes capable of up to 100 t, provides a cooling capacity of 1.2 kW at 4.5 K equivalent, 15-kW LN$_2$ cooling and warming capabilities for up to three magnets in parallel. The facility provides the required technical infrastructure for continuous and reliable operation. Test capabilities comprise electrical, cryogenics, vacuum and mechanical verification, and validation at ambient and liquid helium temperatures. A comprehensive survey and magnetic measurement system, comprising a hall-probe mapper, a rotating-coil magnetometer, a stretched wire, a translating fluxmeter, and a laser tracker, allows the detailed measurement of the magnetic field strength and quality on a large volume. The magnetic axes of the quadrupoles can be established within $\pm 0.2$ mm at $1 \sigma$ accuracy. The facility has been equipped with power supplies, three converters of $\pm 500$ A/120 V, and six converters of $\pm 600$ A/40 V, as well as the required energy extraction, quench protection, data acquisition, and interlocks for the testing of superconducting magnets for the FAIR project, currently under construction at the GSI Research Center, in Darmstadt, Germany. The versatile design of the facility, its layout, and testing capabilities complements CERN's other test infrastructures for large superconducting magnets. We report on the design, construction, and commissioning of the facility as well as the expected capabilities and performances for future tests of large and heavy superconducting magnets

Disruption of the Interaction between Transcriptional Intermediary Factor 1β and Heterochromatin Protein 1 Leads to a Switch from DNA Hyper- to Hypomethylation and H3K9 to H3K27 Trimethylation on the MEST Promoter Correlating with Gene Reactivation

Here, we identified the imprinted mesoderm-specific transcript (MEST) gene as an endogenous TIF1β primary target gene and demonstrated that transcriptional intermediary factor (TIF) 1β, through its interaction with heterochromatin protein (HP) 1, is essential in establishing and maintaining a local heterochromatin-like structure on MEST promoter region characterized by H3K9 trimethylation and hypoacetylation, H4K20 trimethylation, DNA hypermethylation, and enrichment in HP1 that correlates with preferential association to foci of pericentromeric heterochromatin and transcriptional repression. On disruption of the interaction between TIF1β and HP1, TIF1β is released from the promoter region, and there is a switch from DNA hypermethylation and histone H3K9 trimethylation to DNA hypomethylation and histone H3K27 trimethylation correlating with rapid reactivation of MEST expression. Interestingly, we provide evidence that the imprinted MEST allele DNA methylation is insensitive to TIF1β loss of function, whereas the nonimprinted allele is regulated through a distinct TIF1β–DNA methylation mechanism