Differential gene expression by integrin β7(+ )and β7(- )memory T helper cells

BACKGROUND: The cell adhesion molecule integrin α4β7 helps direct the migration of blood lymphocytes to the intestine and associated lymphoid tissues. We hypothesized that β7(+ )and β7(- )blood memory T helper cells differ in their expression of genes that play a role in the adhesion or migration of T cells. RESULTS: RNA was prepared from β7(+ )and β7(- )CD4(+ )CD45RA(- )blood T cells from nine normal human subjects and analyzed using oligonucleotide microarrays. Of 21357 genes represented on the arrays, 16 were more highly expressed in β7(+ )cells and 18 were more highly expressed in β7(- )cells (≥1.5 fold difference and adjusted P < 0.05). Several of the differentially expressed transcripts encode proteins with established or putative roles in lymphocyte adhesion and chemotaxis, including the chemokine receptors CCR9 and CCR10, the integrin α4 subunit, L-selectin, KLRB1 (CD161), NT5E (CD73), LGALS1 and LGALS2 (galectin-1 and -2), and RGS1. Flow cytometry was used to determine whether differences in levels of transcripts encoding cell surface proteins were associated with differential expression of those proteins. Using this approach, we found that surface expression of KLRB1, LAIR1, and NT5E proteins was higher on β7(+ )memory/effector T cells than on β7(- )cells. CONCLUSIONS: Memory/effector T cells that express integrin β7 have a distinct pattern of expression of a set of gene transcripts. Several of these molecules can affect cell adhesion or chemotaxis and are therefore likely to modulate the complex multistep process that regulates trafficking of CD4(+ )memory T cell subsets with different homing behaviors

The transcriptional response to oxidative stress is part of, but not sufficient for, insulin resistance in adipocytes.

Insulin resistance is a major risk factor for metabolic diseases such as Type 2 diabetes. Although the underlying mechanisms of insulin resistance remain elusive, oxidative stress is a unifying driver by which numerous extrinsic signals and cellular stresses trigger insulin resistance. Consequently, we sought to understand the cellular response to oxidative stress and its role in insulin resistance. Using cultured 3T3-L1 adipocytes, we established a model of physiologically-derived oxidative stress by inhibiting the cycling of glutathione and thioredoxin, which induced insulin resistance as measured by impaired insulin-stimulated 2-deoxyglucose uptake. Using time-resolved transcriptomics, we found > 2000 genes differentially-expressed over 24 hours, with specific metabolic and signalling pathways enriched at different times. We explored this coordination using a knowledge-based hierarchical-clustering approach to generate a temporal transcriptional cascade and identify key transcription factors responding to oxidative stress. This response shared many similarities with changes observed in distinct insulin resistance models. However, an anti-oxidant reversed insulin resistance phenotypically but not transcriptionally, implying that the transcriptional response to oxidative stress is insufficient for insulin resistance. This suggests that the primary site by which oxidative stress impairs insulin action occurs post-transcriptionally, warranting a multi-level 'trans-omic' approach when studying time-resolved responses to cellular perturbations

Comparison study of microarray meta-analysis methods

<p>Abstract</p> <p>Background</p> <p>Meta-analysis methods exist for combining multiple microarray datasets. However, there are a wide range of issues associated with microarray meta-analysis and a limited ability to compare the performance of different meta-analysis methods.</p> <p>Results</p> <p>We compare eight meta-analysis methods, five existing methods, two naive methods and a novel approach (mDEDS). Comparisons are performed using simulated data and two biological case studies with varying degrees of meta-analysis complexity. The performance of meta-analysis methods is assessed via ROC curves and prediction accuracy where applicable.</p> <p>Conclusions</p> <p>Existing meta-analysis methods vary in their ability to perform successful meta-analysis. This success is very dependent on the complexity of the data and type of analysis. Our proposed method, mDEDS, performs competitively as a meta-analysis tool even as complexity increases. Because of the varying abilities of compared meta-analysis methods, care should be taken when considering the meta-analysis method used for particular research.</p

Discriminating lymphomas and reactive lymphadenopathy in lymph node biopsies by gene expression profiling

<p>Abstract</p> <p>Background</p> <p>Diagnostic accuracy of lymphoma, a heterogeneous cancer, is essential for patient management. Several ancillary tests including immunophenotyping, and sometimes cytogenetics and PCR are required to aid histological diagnosis. In this proof of principle study, gene expression microarray was evaluated as a single platform test in the differential diagnosis of common lymphoma subtypes and reactive lymphadenopathy (RL) in lymph node biopsies.</p> <p>Methods</p> <p>116 lymph node biopsies diagnosed as RL, classical Hodgkin lymphoma (cHL), diffuse large B cell lymphoma (DLBCL) or follicular lymphoma (FL) were assayed by mRNA microarray. Three supervised classification strategies (global multi-class, local binary-class and global binary-class classifications) using diagonal linear discriminant analysis was performed on training sets of array data and the classification error rates calculated by leave one out cross-validation. The independent error rate was then evaluated by testing the identified gene classifiers on an independent (test) set of array data.</p> <p>Results</p> <p>The binary classifications provided prediction accuracies, between a subtype of interest and the remaining samples, of 88.5%, 82.8%, 82.8% and 80.0% for FL, cHL, DLBCL, and RL respectively. Identified gene classifiers include LIM domain only-2 (<it>LMO2</it>), Chemokine (C-C motif) ligand 22 (<it>CCL22</it>) and Cyclin-dependent kinase inhibitor-3 (<it>CDK3</it>) specifically for FL, cHL and DLBCL subtypes respectively.</p> <p>Conclusions</p> <p>This study highlights the ability of gene expression profiling to distinguish lymphoma from reactive conditions and classify the major subtypes of lymphoma in a diagnostic setting. A cost-effective single platform "mini-chip" assay could, in principle, be developed to aid the quick diagnosis of lymph node biopsies with the potential to incorporate other pathological entities into such an assay.</p

Genes Influencing Circadian Differences in Blood Pressure in Hypertensive Mice

Essential hypertension is a common multifactorial heritable condition in which increased sympathetic outflow from the central nervous system is involved in the elevation in blood pressure (BP), as well as the exaggerated morning surge in BP that is a risk factor for myocardial infarction and stroke in hypertensive patients. The Schlager BPH/2J mouse is a genetic model of hypertension in which increased sympathetic outflow from the hypothalamus has an important etiological role in the elevation of BP. Schlager hypertensive mice exhibit a large variation in BP between the active and inactive periods of the day, and also show a morning surge in BP. To investigate the genes responsible for the circadian variation in BP in hypertension, hypothalamic tissue was collected from BPH/2J and normotensive BPN/3J mice at the ‘peak’ (n = 12) and ‘trough’ (n = 6) of diurnal BP. Using Affymetrix GeneChip® Mouse Gene 1.0 ST Arrays, validation by quantitative real-time PCR and a statistical method that adjusted for clock genes, we identified 212 hypothalamic genes whose expression differed between ‘peak’ and ‘trough’ BP in the hypertensive strain. These included genes with known roles in BP regulation, such as vasopressin, oxytocin and thyrotropin releasing hormone, as well as genes not recognized previously as regulators of BP, including chemokine (C-C motif) ligand 19, hypocretin and zinc finger and BTB domain containing 16. Gene ontology analysis showed an enrichment of terms for inflammatory response, mitochondrial proton-transporting ATP synthase complex, structural constituent of ribosome, amongst others. In conclusion, we have identified genes whose expression differs between the peak and trough of 24-hour circadian BP in BPH/2J mice, pointing to mechanisms responsible for diurnal variation in BP. The findings may assist in the elucidation of the mechanism for the morning surge in BP in essential hypertension

Measures of Association for Identifying MicroRNA-mRNA Pairs of Biological Interest

MicroRNAs are a class of small non-protein coding RNAs that play an important role in the regulation of gene expression. Most studies on the identification of microRNA-mRNA pairs utilize the correlation coefficient as a measure of association. The use of correlation coefficient is appropriate if the expression data are available for several conditions and, for a given condition, both microRNA and mRNA expression profiles are obtained from the same set of individuals. However, there are many instances where one of the requirements is not satisfied. Therefore, there is a need for new measures of association to identify the microRNA-mRNA pairs of interest and we present two such measures. The first measure requires expression data for multiple conditions but, for a given condition, the microRNA and mRNA expression may be obtained from different individuals. The new measure, unlike the correlation coefficient, is suitable for analyzing large data sets which are obtained by combining several independent studies on microRNAs and mRNAs. Our second measure is able to handle expression data that correspond to just two conditions but, for a given condition, the microRNA and mRNA expression must be obtained from the same set of individuals. This measure, unlike the correlation coefficient, is appropriate for analyzing data sets with a small number of conditions. We apply our new measures of association to multiple myeloma data sets, which cannot be analyzed using the correlation coefficient, and identify several microRNA-mRNA pairs involved in apoptosis and cell proliferation

Epigenetic Analysis of KSHV Latent and Lytic Genomes

Epigenetic modifications of the herpesviral genome play a key role in the transcriptional control of latent and lytic genes during a productive viral lifecycle. In this study, we describe for the first time a comprehensive genome-wide ChIP-on-Chip analysis of the chromatin associated with the Kaposi's sarcoma-associated herpesvirus (KSHV) genome during latency and lytic reactivation. Depending on the gene expression class, different combinations of activating [acetylated H3 (AcH3) and H3K4me3] and repressive [H3K9me3 and H3K27me3] histone modifications are associated with the viral latent genome, which changes upon reactivation in a manner that is correlated with their expression. Specifically, both the activating marks co-localize on the KSHV latent genome, as do the repressive marks. However, the activating and repressive histone modifications are mutually exclusive of each other on the bulk of the latent KSHV genome. The genomic region encoding the IE genes ORF50 and ORF48 possesses the features of a bivalent chromatin structure characterized by the concomitant presence of the activating H3K4me3 and the repressive H3K27me3 marks during latency, which rapidly changes upon reactivation with increasing AcH3 and H3K4me3 marks and decreasing H3K27me3. Furthermore, EZH2, the H3K27me3 histone methyltransferase of the Polycomb group proteins (PcG), colocalizes with the H3K27me3 mark on the entire KSHV genome during latency, whereas RTA-mediated reactivation induces EZH2 dissociation from the genomic regions encoding IE and E genes concurrent with decreasing H3K27me3 level and increasing IE/E lytic gene expression. Moreover, either the inhibition of EZH2 expression by a small molecule inhibitor DZNep and RNAi knockdown, or the expression of H3K27me3-specific histone demethylases apparently induced the KSHV lytic gene expression cascade. These data indicate that histone modifications associated with the KSHV latent genome are involved in the regulation of latency and ultimately in the control of the temporal and sequential expression of the lytic gene cascade. In addition, the PcG proteins play a critical role in the control of KSHV latency by maintaining a reversible heterochromatin on the KSHV lytic genes. Thus, the regulation of the spatial and temporal association of the PcG proteins with the KSHV genome may be crucial for propagating the KSHV lifecycle