Assessing the gain of biological data integration in gene networks inference

Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.

Divergent Roles of the CRH Receptors in the Control of Gonadotropin Secretion Induced by Acute Restraint Stress at Proestrus

CRH has been implicated as a mediator of stress-induced effects on the hypothalamus-pituitary-gonad axis, acting via CRH receptors in various brain regions. We investigated whether the effects of restraint stress on the secretion of gonadotropins on the morning of proestrus are mediated by the CRH-R1 or CRH-R2 receptors in the oval subdivision of the anterolateral BST, the central amygdala, the locus coeruleus (LC), or the A1 and A2 neuron groups in the medulla. At proestrus morning, rats were injected with antalarmin (a CRH-R1 antagonist), asstressin2-B (a CRH-R2 antagonist) or vehicles. Thirty minutes after the injection, the animals were placed into restraints for 30 min, and blood was sampled for 2 h. At the end of the experiment, the brains were removed for immunofluorescence analyses. Restraint stress increased the levels of FSH and LH. Antalarmin blocked the stress-induced increases in FSH and LH secretion, but astressin2-B only blocked the increase in FSH secretion. LC showed intense stress-induced neuronal activity. FOS/tyrosine-hydroxylase coexpression in LC was reduced by antalarmin, but not astressin2-B. The CRH-R1 receptor, more than CRH-R2 receptor, appears to be essential for the stimulation of the hypothalamus-pituitary-gonad axis by acute stress; this response is likely mediated in part by noradrenergic neurons in the LC. We postulate that the stress-induced facilitation of reproductive function is mediated, at least in part, by CRH action through CRH-R1 on noradrenaline neurons residing in the LC that trigger GnRH discharge and gonadotropin secretion. (Endocrinology 153: 4838-4848, 2012)

Using gene-network landscape to dissect genotype effects of TCF7L2 genetic variant on diabetes and cardiovascular risk

Vaquero AR, Ferreira NE, Omae SV, Rodrigues MV, Teixeira SK, Krieger JE, Pereira AC. Using gene-network landscape to dissect genotype effects of TCF7L2 genetic variant on diabetes and cardiovascular risk. Physiol Genomics 44: 903-914, 2012. First published August 7, 2012; doi:10.1152/physiolgenomics.00030.2012.-The single nucleotide polymorphism (SNP) within the TCF7L2 gene, rs7903146, is, to date, the most significant genetic marker associated with Type 2 diabetes mellitus (T2DM) risk. Nonetheless, its functional role in disease pathology is poorly understood. The aim of the present study was to investigate, in vascular smooth muscle cells from 92 patients undergoing aortocoronary bypass surgery, the contribution of this SNP in T2DM using expression levels and expression correlation comparison approaches, which were visually represented as gene interaction networks. Initially, the expression levels of 41 genes (seven TCF7L2 splice forms and 40 other T2DM relevant genes) were compared between rs7903146 wild-type (CC) and T2DM-risk (CT + TT) genotype groups. Next, we compared the expression correlation patterns of these 41 genes between groups to observe if the relationships between genes were different. Five TCF7L2 splice forms and nine genes showed significant expression differences between groups. RXR alpha gene was pinpointed as showing the most different expression correlation pattern with other genes. Therefore, T2DM risk alleles appear to be influencing TCF7L2 splice form's expression in vascular smooth muscle cells, and RXR alpha gene is pointed out as a treatment target candidate for risk reduction in individuals with high risk of developing T2DM, especially individuals harboring TCF7L2 risk genotypes.

Gene Expression Profile in Response to Doxorubicin-Rapamycin Combined Treatment of HER-2-Overexpressing Human Mammary Epithelial Cell Lines

HER-2-positive breast cancers frequently sustain elevated AKT/mTOR signaling, which has been associated with resistance to doxorubicin treatment. Here, we investigated whether rapamycin, an mTOR inhibitor, increased the sensitivity to doxorubicin therapy in two HER-2-overexpressing cell lines: C5.2, which was derived from the parental HB4a by transfection with HER-2 and SKBR3, which exhibits HER-2 amplification. The epithelial mammary cell line HB4a was also analyzed. The combined treatment using 20 nmol/L of rapamycin and 30 nmol/L of doxorubicin arrested HB4a and C5.2 cells in S to G(2)-M, whereas SKBR3 cells showed an increase in the G(0)-G(1) phase. Rapamycin increased the sensitivity to doxorubicin in HER-2-overexpressing cells by approximately 2-fold, suggesting that the combination displayed a more effective antiproliferative action. Gene expression profiling showed that these results might reflect alterations in genes involved in canonical pathways related to purine metabolism, oxidative phosphorylation, protein ubiquitination, and mitochondrial dysfunction. A set of 122 genes modulated by the combined treatment and specifically related to HER-2 overexpression was determined by finding genes commonly regulated in both C5.2 and SKBR3 that were not affected in HB4a cells. Network analysis of this particular set showed a smaller subgroup of genes in which coexpression pattern in HB4a cells was disrupted in C5.2 and SKBR3. Altogether, our data showed a subset of genes that might be more robust than individual markers in predicting the response of HER-2-overexpressing breast cancers to doxorubicin and rapamycin combination. Mol Cancer Ther; 11(2); 464-74. (C) 2011 AACR.

Leptin signaling in Kiss1 neurons arises after pubertal development

The adipocyte-derived hormone leptin is required for normal pubertal maturation in mice and humans and, therefore, leptin has been recognized as a crucial metabolic cue linking energy stores and the onset of puberty. Several lines of evidence have suggested that leptin acts via kisspeptin expressing neurons of the arcuate nucleus to exert its effects. Using conditional knockout mice, we have previously demonstrated that deletion of leptin receptors (LepR) from kisspeptin cells cause no puberty or fertility deficits. However, developmental adaptations and system redundancies may have obscured the physiologic relevance of direct leptin signaling in kisspeptin neurons. To overcome these putative effects, we re-expressed endogenous LepR selectively in kisspeptin cells of mice otherwise null for LepR, using the Cre-loxP system. Kiss1-Cre LepR null mice showed no pubertal development and no improvement of the metabolic phenotype, remaining obese, diabetic and infertile. These mice displayed decreased numbers of neurons expressing Kiss1 gene, similar to prepubertal control mice, and an unexpected lack of re-expression of functional LepR. To further assess the temporal coexpression of Kiss1 and Lepr genes, we generated mice with the human renilla green fluorescent protein (hrGFP) driven by Kiss1 regulatory elements and crossed them with mice that express Cre recombinase from the Lepr locus and the R26-tdTomato reporter gene. No coexpression of Kiss1 and LepR was observed in prepubertal mice. Our findings unequivocally demonstrate that kisspeptin neurons are not the direct target of leptin in the onset of puberty. Leptin signaling in kisspeptin neurons arises only after completion of sexual maturation.