Uncovering mechanisms of transcriptional regulations by systematic mining of cis regulatory elements with gene expression profiles

<p>Abstract</p> <p>Background</p> <p>Contrary to the traditional biology approach, where the expression patterns of a handful of genes are studied at a time, microarray experiments enable biologists to study the expression patterns of many genes simultaneously from gene expression profile data and decipher the underlying hidden biological mechanism from the observed gene expression changes. While the statistical significance of the gene expression data can be deduced by various methods, the biological interpretation of the data presents a challenge.</p> <p>Results</p> <p>A method, called CisTransMine, is proposed to help infer the underlying biological mechanisms for the observed gene expression changes in microarray experiments. Specifically, this method will predict potential cis-regulatory elements in promoter regions which could regulate gene expression changes. This approach builds on the MotifADE method published in 2004 and extends it with two modifications: up-regulated genes and down-regulated genes are tested separately and in addition, tests have been implemented to identify combinations of transcription factors that work synergistically. The method has been applied to a genome wide expression dataset intended to study myogenesis in a mouse C2C12 cell differentiation model. The results shown here both confirm the prior biological knowledge and facilitate the discovery of new biological insights.</p> <p>Conclusion</p> <p>The results validate that the CisTransMine approach is a robust method to uncover the hidden transcriptional regulatory mechanisms that can facilitate the discovery of mechanisms of transcriptional regulation.</p

Pituitary and systemic autoimmunity in a case of intrasellar germinoma

Germinomas arising in the sella turcica are difficult to differentiate from autoimmune hypophysitis because of similar clinical and pathological features. This differentiation, nevertheless, is critical for patient care due to different treatments of the two diseases. We report the case of an 11-year-old girl who presented with diabetes insipidus and growth retardation, and was found to have an intra- and supra-sellar mass. Initial examination of the pituitary biopsy showed diffuse lymphocytic infiltration of the adenohypophysis and absent placental alkaline phosphatase expression, leading to a diagnosis of hypophysitis and glucocorticoid treatment. Because of the lack of clinical and radiological response, the pituitary specimen was re-examined, revealing this time the presence of scattered c-kit and Oct4 positive germinoma cells. The revised diagnosis prompted the initiation of radiotherapy, which induced disappearance of the pituitary mass. Immunological studies showed that the patient’s serum recognized antigens expressed by the patient’s own germinoma cells, as well as pituitary antigens like growth hormone and systemic antigens like the Sjögren syndrome antigen B and alpha-enolase. The study first reports the presence of pituitary and systemic antibodies in a patient with intrasellar germinoma, and reminds us that diffuse lymphocytic infiltration of the pituitary gland and pituitary antibodies does not always indicate a diagnosis of autoimmune hypophysitis

Alteration of gene expression by alcohol exposure at early neurulation

<p>Abstract</p> <p>Background</p> <p>We have previously demonstrated that alcohol exposure at early neurulation induces growth retardation, neural tube abnormalities, and alteration of DNA methylation. To explore the global gene expression changes which may underline these developmental defects, microarray analyses were performed in a whole embryo mouse culture model that allows control over alcohol and embryonic variables.</p> <p>Result</p> <p>Alcohol caused teratogenesis in brain, heart, forelimb, and optic vesicle; a subset of the embryos also showed cranial neural tube defects. In microarray analysis (accession number GSM9545), adopting hypothesis-driven Gene Set Enrichment Analysis (GSEA) informatics and intersection analysis of two independent experiments, we found that there was a collective reduction in expression of neural specification genes (neurogenin, <it>Sox5, Bhlhe22</it>), neural growth factor genes [<it>Igf1, Efemp1</it>, <it>Klf10 </it>(<it>Tieg), and Edil3</it>], and alteration of genes involved in cell growth, apoptosis, histone variants, eye and heart development. There was also a reduction of retinol binding protein 1 (<it>Rbp1</it>), and <it>de novo </it>expression of aldehyde dehydrogenase 1B1 (<it>Aldh1B1</it>). Remarkably, four key hematopoiesis genes (glycophorin A, adducin 2, beta-2 microglobulin, and ceruloplasmin) were absent after alcohol treatment, and histone variant genes were reduced. The down-regulation of the neurospecification and the neurotrophic genes were further confirmed by quantitative RT-PCR. Furthermore, the gene expression profile demonstrated distinct subgroups which corresponded with two distinct alcohol-related neural tube phenotypes: an open (ALC-NTO) and a closed neural tube (ALC-NTC). Further, the epidermal growth factor signaling pathway and histone variants were specifically altered in ALC-NTO, and a greater number of neurotrophic/growth factor genes were down-regulated in the ALC-NTO than in the ALC-NTC embryos.</p> <p>Conclusion</p> <p>This study revealed a set of genes vulnerable to alcohol exposure and genes that were associated with neural tube defects during early neurulation.</p

Distinct Early Molecular Responses to Mutations Causing vLINCL and JNCL Presage ATP Synthase Subunit C Accumulation in Cerebellar Cells

Variant late-infantile neuronal ceroid lipofuscinosis (vLINCL), caused by CLN6 mutation, and juvenile neuronal ceroid lipofuscinosis (JNCL), caused by CLN3 mutation, share clinical and pathological features, including lysosomal accumulation of mitochondrial ATP synthase subunit c, but the unrelated CLN6 and CLN3 genes may initiate disease via similar or distinct cellular processes. To gain insight into the NCL pathways, we established murine wild-type and CbCln6nclf/nclf cerebellar cells and compared them to wild-type and CbCln3Δex7/8/Δex7/8 cerebellar cells. CbCln6nclf/nclf cells and CbCln3Δex7/8/Δex7/8 cells both displayed abnormally elongated mitochondria and reduced cellular ATP levels and, as cells aged to confluence, exhibited accumulation of subunit c protein in Lamp 1-positive organelles. However, at sub-confluence, endoplasmic reticulum PDI immunostain was decreased only in CbCln6nclf/nclf cells, while fluid-phase endocytosis and LysoTracker® labeled vesicles were decreased in both CbCln6nclf/nclf and CbCln3Δex7/8/Δex7/8 cells, though only the latter cells exhibited abnormal vesicle subcellular distribution. Furthermore, unbiased gene expression analyses revealed only partial overlap in the cerebellar cell genes and pathways that were altered by the Cln3Δex7/8 and Cln6nclf mutations. Thus, these data support the hypothesis that CLN6 and CLN3 mutations trigger distinct processes that converge on a shared pathway, which is responsible for proper subunit c protein turnover and neuronal cell survival

Acetaminophen Modulates the Transcriptional Response to Recombinant Interferon-β

BACKGROUND: Recombinant interferon treatment can result in several common side effects including fever and injection-site pain. Patients are often advised to use acetaminophen or other over-the-counter pain medications as needed. Little is known regarding the transcriptional changes induced by such co-administration. METHODOLOGY/PRINCIPAL FINDINGS: We tested whether the administration of acetaminophen causes a change in the response normally induced by interferon-beta treatment. CD-1 mice were administered acetaminophen (APAP), interferon-beta (IFN-beta) or a combination of IFN-beta+APAP and liver and serum samples were collected for analysis. Differential gene expression was determined using an Agilent 22 k whole mouse genome microarray. Data were analyzed by several methods including Gene Ontology term clustering and Gene Set Enrichment Analysis. We observed a significant change in the transcription profile of hepatic cells when APAP was co-administered with IFN-beta. These transcriptional changes included a marked up-regulation of genes involved in signal transduction and cell differentiation and down-regulation of genes involved in cellular metabolism, trafficking and the IkappaBK/NF-kappaB cascade. Additionally, we observed a large decrease in the expression of several IFN-induced genes including Ifit-3, Isg-15, Oasl1, Zbp1 and predicted gene EG634650 at both early and late time points. CONCLUSIONS/SIGNIFICANCE: A significant change in the transcriptional response was observed following co-administration of IFN-beta+APAP relative to IFN-beta treatment alone. These results suggest that administration of acetaminophen has the potential to modify the efficacy of IFN-beta treatment

Improving stability of prediction models based on correlated omics data by using network approaches

Building prediction models based on complex omics datasets such as transcriptomics, proteomics, metabolomics remains a challenge in bioinformatics and biostatistics. Regularized regression techniques are typically used to deal with the high dimensionality of these datasets. However, due to the presence of correlation in the datasets, it is difficult to select the best model and application of these methods yields unstable results. We propose a novel strategy for model selection where the obtained models also perform well in terms of overall predictability. Several three step approaches are considered, where the steps are 1) network construction, 2) clustering to empirically derive modules or pathways, and 3) building a prediction model incorporating the information on the modules. For the first step, we use weighted correlation networks and Gaussian graphical modelling. Identification of groups of features is performed by hierarchical clustering. The grouping information is included in the prediction model by using group-based variable selection or group-specific penalization. We compare the performance of our new approaches with standard regularized regression via simulations. Based on these results we provide recommendations for selecting a strategy for building a prediction model given the specific goal of the analysis and the sizes of the datasets. Finally we illustrate the advantages of our approach by application of the methodology to two problems, namely prediction of body mass index in the DIetary, Lifestyle, and Genetic determinants of Obesity and Metabolic syndrome study (DILGOM) and prediction of response of each breast cancer cell line to treatment with specific drugs using a breast cancer cell lines pharmacogenomics dataset

The Corepressor NCoR1 Antagonizes PGC-1α and Estrogen-Related Receptor α in the Regulation of Skeletal Muscle Function and Oxidative Metabolism

Skeletal muscle exhibits a high plasticity and accordingly can quickly adapt to different physiological and pathological stimuli by changing its phenotype largely through diverse epigenetic mechanisms. The nuclear receptor corepressor 1 (NCoR1) has the ability to mediate gene repression; however, its role in regulating biological programs in skeletal muscle is still poorly understood. We therefore studied the mechanistic and functional aspects of NCoR1 function in this tissue. NCoR1 muscle-specific knockout mice exhibited a 7.2% higher peak oxygen consumption (VO(2peak)), a 11% reduction in maximal isometric force, and increased ex vivo fatigue resistance during maximal stimulation. Interestingly, global gene expression analysis revealed a high overlap between the effects of NCoR1 deletion and peroxisome proliferator-activated receptor gamma (PPARγ) coactivator 1α (PGC-1α) overexpression on oxidative metabolism in muscle. Importantly, PPARβ/δ and estrogen-related receptor α (ERRα) were identified as common targets of NCoR1 and PGC-1α with opposing effects on the transcriptional activity of these nuclear receptors. In fact, the repressive effect of NCoR1 on oxidative phosphorylation gene expression specifically antagonizes PGC-1α-mediated coactivation of ERRα. We therefore delineated the molecular mechanism by which a transcriptional network controlled by corepressor and coactivator proteins determines the metabolic properties of skeletal muscle, thus representing a potential therapeutic target for metabolic diseases