Integrative analysis of chemo-transcriptomic profiles for drug-feature specific gene expression signatures

One of the major challenges in systems biology is to understand the complex responses of a biological system to external perturbations or internal signalling depending on its biological conditions. Genome-wide transcriptomic profiling of cellular systems under various chemical perturbations allows the manifestation of certain features of the chemicals through their transcriptomic expression profiles. The insights obtained may help to establish the connections between human diseases, associated genes and therapeutic drugs. The main objective of this study was to systematically analyse cellular gene expression data under various drug treatments to elucidate drug-feature specific transcriptomic signatures. We first extracted drug-related information (drug features) from the collected textual description of DrugBank entries using text-mining techniques. A novel statistical method employing orthogonal least square learning was proposed to obtain drug-feature-specific signatures by integrating gene expression with DrugBank data. To obtain robust signatures from noisy input datasets, a stringent ensemble approach was applied with the combination of three techniques: resampling, leave-one-out cross validation, and aggregation. The validation experiments showed that the proposed method has the capacity of extracting biologically meaningful drug-feature-specific gene expression signatures. It was also shown that most of signature genes are connected with common hub genes by regulatory network analysis. The common hub genes were further shown to be related to general drug metabolism by Gene Ontology analysis. Each set of genes has relatively few interactions with other sets, indicating the modular nature of each signature and its drug-feature-specificity. Based on Gene Ontology analysis, we also found that each set of drug feature (DF)-specific genes were indeed enriched in biological processes related to the drug feature. The results of these experiments demonstrated the pot- ntial of the method for predicting certain features of new drugs using their transcriptomic profiles, providing a useful methodological framework and a valuable resource for drug development and characterization.

HES6 drives a critical AR transcriptional programme to induce castration-resistant prostate cancer through activation of an E2F1-mediated cell cycle network

Castrate-resistant prostate cancer (CRPC) is poorly characterized and heterogeneous and while the androgen receptor (AR) is of singular importance, other factors such as c-Myc and the E2F family also play a role in later stage disease. HES6 is a transcription co-factor associated with stem cell characteristics in neural tissue. Here we show that HES6 is up-regulated in aggressive human prostate cancer and drives castration-resistant tumour growth in the absence of ligand binding by enhancing the transcriptional activity of the AR, which is preferentially directed to a regulatory network enriched for transcription factors such as E2F1. In the clinical setting, we have uncovered a HES6-associated signature that predicts poor outcome in prostate cancer, which can be pharmacologically targeted by inhibition of PLK1 with restoration of sensitivity to castration. We have therefore shown for the first time the critical role of HES6 in the development of CRPC and identified its potential in patient-specific therapeutic strategies.

Elevated NCOR1 disrupts a network of dietary-sensing nuclear receptors in bladder cancer cells

Increasingly invasive bladder cancer cells lines displayed insensitivity toward a panel of dietary-derived ligands for members of the nuclear receptor superfamily. Insensitivity was defined through altered gene regulatory actions and cell proliferation and reflected both reduced receptor expression and elevated nuclear receptor corepressor 1 (NCOR1) expression. Stable overexpression of NCOR1 in sensitive cells (RT4) resulted in a panel of clones that recapitulated the resistant phenotype in terms of gene regulatory actions and proliferative responses toward ligand. Similarly, silencing RNA approaches to NCOR1 in resistant cells (EJ28) enhanced ligand gene regulatory and proliferation responses, including those mediated by peroxisome proliferator-activated receptor (PPAR) gamma and vitamin D receptor (VDR) receptors. Elevated NCOR1 levels generate an epigenetic lesion to target in resistant cells using the histone deacetylase inhibitor vorinostat, in combination with nuclear receptor ligands. Such treatments revealed strong-additive interactions toward the PPARgamma, VDR and Farnesoid X-activated receptors. Genome-wide microarray and microfluidic quantitative real-time, reverse transcription-polymerase chain reaction approaches, following the targeting of NCOR1 activity and expression, revealed the selective capacity of this corepressor to govern common transcriptional events of underlying networks. Combined these findings suggest that NCOR1 is a selective regulator of nuclear receptors, notably PPARgamma and VDR, and contributes to their loss of sensitivity. Combinations of epigenetic therapies that target NCOR1 may prove effective, even when receptor expression is reduced.

Predicting Cell Cycle Regulated Genes by Causal Interactions

The fundamental difference between classic and modern biology is that technological innovations allow to generate high-throughput data to get insights into molecular interactions on a genomic scale. These high-throughput data can be used to infer gene networks, e. g., the transcriptional regulatory or signaling network, representing a blue print of the current dynamical state of the cellular system. However, gene networks do not provide direct answers to biological questions, instead, they need to be analyzed to reveal functional information of molecular working mechanisms. In this paper we propose a new approach to analyze the transcriptional regulatory network of yeast to predict cell cycle regulated genes. The novelty of our approach is that, in contrast to all other approaches aiming to predict cell cycle regulated genes, we do not use time series data but base our analysis on the prior information of causal interactions among genes. The major purpose of the present paper is to predict cell cycle regulated genes in S. cerevisiae. Our analysis is based on the transcriptional regulatory network, representing causal interactions between genes, and a list of known periodic genes. No further data are used. Our approach utilizes the causal membership of genes and the hierarchical organization of the transcriptional regulatory network leading to two groups of periodic genes with a well defined direction of information flow. We predict genes as periodic if they appear on unique shortest paths connecting two periodic genes from different hierarchy levels. Our results demonstrate that a classical problem as the prediction of cell cycle regulated genes can be seen in a new light if the concept of a causal membership of a gene is applied consequently. This also shows that there is a wealth of information buried in the transcriptional regulatory network whose unraveling may require more elaborate concepts than it might seem at first.

Harnessing naturally randomized transcription to infer regulatory relationships among genes

We develop an approach utilizing randomized genotypes to rigorously infer causal regulatory relationships among genes at the transcriptional level, based on experiments in which genotyping and expression profiling are performed. This approach can be used to build transcriptional regulatory networks and to identify putative regulators of genes. We apply the method to an experiment in yeast, in which genes known to be in the same processes and functions are recovered in the resulting transcriptional regulatory network.

Resolving candidate genes of mouse skeletal muscle QTL via RNA-Seq and expression network analyses

BACKGROUND:

We have recently identified a number of Quantitative Trait Loci (QTL) contributing to the 2-fold muscle weight difference between the LG/J and SM/J mouse strains and refined their confidence intervals. To facilitate nomination of the candidate genes responsible for these differences we examined the transcriptome of the tibialis anterior (TA) muscle of each strain by RNA-Seq.

13,726 genes were expressed in mouse skeletal muscle. Intersection of a set of 1061 differentially expressed transcripts with a mouse muscle Bayesian Network identified a coherent set of differentially expressed genes that we term the LG/J and SM/J Regulatory Network (LSRN). The integration of the QTL, transcriptome and the network analyses identified eight key drivers of the LSRN (Kdr, Plbd1, Mgp, Fah, Prss23, 2310014F06Rik, Grtp1, Stk10) residing within five QTL regions, which were either polymorphic or differentially expressed between the two strains and are strong candidates for quantitative trait genes (QTGs) underlying muscle mass. The insight gained from network analysis including the ability to make testable predictions is illustrated by annotating the LSRN with knowledge-based signatures and showing that the SM/J state of the network corresponds to a more oxidative state. We validated this prediction by NADH tetrazolium reductase staining in the TA muscle revealing higher oxidative potential of the SM/J compared to the LG/J strain (p<0.03).

Thus, integration of fine resolution QTL mapping, RNA-Seq transcriptome information and mouse muscle Bayesian Network analysis provides a novel and unbiased strategy for nomination of muscle QTGs.

miR-7 and miR-214 are specifically expressed during neuroblastoma differentiation, cortical development and embryonic stem cells differentiation, and control neurite outgrowth in vitro

The mammalian nervous system exerts essential control on many physiological processes in the organism and is itself controlled extensively by a variety of genetic regulatory mechanisms. microRNA (miR), an abundant class of small non-coding RNA, are emerging as important post-transcriptional regulators of gene expression in the brain. Increasing evidence indicates that miR regulate both the development and function of the nervous system. Moreover, deficiency in miR function has also been implicated in a number of neurological disorders. Expression profile analysis of miR is necessary to understand their complex role in the regulation of gene expression during the development and differentiation of cells. Here we present a comparative study of miR expression profiles in neuroblastoma, in cortical development, and in neuronal differentiation of embryonic stem (ES) cells. By microarray profiling in combination with real time PCR we show that miR-7 and miR-214 are modulated in neuronal differentiation (as compared to miR-1, -16 and -133a), and control neurite outgrowth in vitro. These findings provide an important step toward further elucidation of miR function and miR-related gene regulatory networks in the mammalian central nervous system. (C) 2010 Elsevier Inc. All rights reserved.

Mood congruent psychotic symptoms and specific cognitive deficits in carriers of the novel schizophrenia risk variant at MIR-137

Objective: The Schizophrenia Psychiatric Genome-wide Association (GWAS) Consortium recently reported on five novel schizophrenia susceptibility loci. The most significant finding mapped to a micro-RNA, MIR-137, which may be involved in regulating the function of other schizophrenia and bipolar disorder susceptibility genes. Method: We genotyped 821 patients with confirmed DSM-IV diagnoses of schizophrenia, bipolar affective disorder I and schizoaffective disorder for the risk SNP (rs1625579) and investigated the clinical profiles of risk allele carriers using a within-case design. We also assessed neurocognitive performance in a subset of cases (n=399) and controls (n=171). Results: Carriers of the risk allele had lower scores for an OPCRIT-derived positive symptom factor (p=0.04) and lower scores on a lifetime measure of psychosis incongruity (p=0.017). Risk allele carriers also had more cognitive deficits involving episodic memory and attentional control. Conclusion: This is the first evidence that the MIR-137 risk variant may be associated with a specific subgroup of psychosis patients. Although the effect of this single SNP was not clinically relevant, investigation of the impact of carrying multiple risk SNPs in the MIR-137 regulatory network on diagnosis and illness profile may be warranted. © 2012 Elsevier Ireland Ltd.

Molecular basis of Yersinia enterocolitica temperature-dependent resistance to antimicrobial peptides

Antimicrobial peptides (APs) belong to the arsenal of weapons of the innate immune system against infections. In the case of gram-negative bacteria, APs interact with the anionic lipid A moiety of the lipopolysaccharide (LPS). In yersiniae most virulence factors are temperature regulated. Studies from our laboratory demonstrated that Yersinia enterocolitica is more susceptible to polymyxin B, a model AP, when grown at 37°C than at 22°C (J. A. Bengoechea, R. Díaz, and I. Moriyón, Infect. Immun. 64:4891-4899, 1996), and here we have extended this observation to other APs, not structurally related to polymyxin B. Mechanistically, we demonstrate that the lipid A modifications with aminoarabinose and palmitate are downregulated at 37°C and that they contribute to AP resistance together with the LPS O-polysaccharide. Bacterial loads of lipid A mutants in Peyer's patches, liver, and spleen of orogastrically infected mice were lower than those of the wild-type strain at 3 and 7 days postinfection. PhoPQ and PmrAB two-component systems govern the expression of the loci required to modify lipid A with aminoarabinose and palmitate, and their expressions are also temperature regulated. Our findings support the notion that the temperature-dependent regulation of loci controlling lipid A modifications could be explained by H-NS-dependent negative regulation alleviated by RovA. In turn, our data also demonstrate that PhoPQ and PmrAB regulate positively the expression of rovA, the effect of PhoPQ being more important. However, rovA expression reached wild-type levels in the phoPQ pmrAB mutant background, hence indicating the existence of an unknown regulatory network controlling rovA expression in this background.

Large-scale association analysis identifies new risk loci for coronary artery disease

Coronary artery disease (CAD) is the commonest cause of death. Here, we report an association analysis in 63,746 CAD cases and 130,681 controls identifying 15 loci reaching genome-wide significance, taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants (r(2)

Divergent androgen regulation of unfolded protein response pathways drives prostate cancer

The unfolded protein response (UPR) is a homeostatic mechanism to maintain endoplasmic reticulum (ER) function. The UPR is activated by various physiological conditions as well as in disease states, such as cancer. As androgens regulate secretion and development of the normal prostate and drive prostate cancer (PCa) growth, they may affect UPR pathways. Here, we show that the canonical UPR pathways are directly and divergently regulated by androgens in PCa cells, through the androgen receptor (AR), which is critical for PCa survival. AR bound to gene regulatory sites and activated the IRE1α branch, but simultaneously inhibited PERK signaling. Inhibition of the IRE1α arm profoundly reduced PCa cell growth in vitro as well as tumor formation in preclinical models of PCa in vivo. Consistently, AR and UPR gene expression were correlated in human PCa, and spliced XBP-1 expression was significantly upregulated in cancer compared with normal prostate. These data establish a genetic switch orchestrated by AR that divergently regulates the UPR pathways and suggest that targeting IRE1α signaling may have therapeutic utility in PCa.

The ETS family member GABPα modulates androgen receptor signalling and mediates an aggressive phenotype in prostate cancer

In prostate cancer (PC), the androgen receptor (AR) is a key transcription factor at all disease stages, including the advanced stage of castrate-resistant prostate cancer (CRPC). In the present study, we show that GABPα, an ETS factor that is up-regulated in PC, is an AR-interacting transcription factor. Expression of GABPα enables PC cell lines to acquire some of the molecular and cellular characteristics of CRPC tissues as well as more aggressive growth phenotypes. GABPα has a transcriptional role that dissects the overlapping cistromes of the two most common ETS gene fusions in PC: overlapping significantly with ETV1 but not with ERG target genes. GABPα bound predominantly to gene promoters, regulated the expression of one-third of AR target genes and modulated sensitivity to AR antagonists in hormone responsive and castrate resistant PC models. This study supports a critical role for GABPα in CRPC and reveals potential targets for therapeutic intervention.

Changes of 5-hydroxymethylcytosine distribution during myeloid and lymphoid differentiation of CD34+ cells

BACKGROUND: Hematopoietic stem cell renewal and differentiation are regulated through epigenetic processes. The conversion of 5-methylcytosine into 5-hydroxymethylcytosine (5hmC) by ten-eleven-translocation enzymes provides new insights into the epigenetic regulation of gene expression during development. Here, we studied the potential gene regulatory role of 5hmC during human hematopoiesis.

RESULTS: We used reduced representation of 5-hydroxymethylcytosine profiling (RRHP) to characterize 5hmC distribution in CD34+ cells, CD4+ T cells, CD19+ B cells, CD14+ monocytes and granulocytes. In all analyzed blood cell types, the presence of 5hmC at gene bodies correlates positively with gene expression, and highest 5hmC levels are found around transcription start sites of highly expressed genes. In CD34+ cells, 5hmC primes for the expression of genes regulating myeloid and lymphoid lineage commitment. Throughout blood cell differentiation, intragenic 5hmC is maintained at genes that are highly expressed and required for acquisition of the mature blood cell phenotype. Moreover, in CD34+ cells, the presence of 5hmC at enhancers associates with increased binding of RUNX1 and FLI1, transcription factors essential for hematopoiesis.

CONCLUSIONS: Our study provides a comprehensive genome-wide overview of 5hmC distribution in human hematopoietic cells and new insights into the epigenetic regulation of gene expression during human hematopoiesis.

Comprehensive Transcriptome Analysis of Sex-Biased Expressed Genes Reveals Discrete Biological and Physiological Features of Male and Female Schistosoma japonicum

Schistosomiasis is a chronic and debilitating disease caused by blood flukes (digenetic trematodes) of the genus Schistosoma. Schistosomes are sexually dimorphic and exhibit dramatic morphological changes during a complex lifecycle which requires subtle gene regulatory mechanisms to fulfil these complex biological processes. In the current study, a 41,982 features custom DNA microarray, which represents the most comprehensive probe coverage for any schistosome transcriptome study, was designed based on public domain and local databases to explore differential gene expression in S. japonicum. We found that approximately 1/10 of the total annotated genes in the S. japonicum genome are differentially expressed between adult males and females. In general, genes associated with the cytoskeleton, and motor and neuronal activities were readily expressed in male adult worms, whereas genes involved in amino acid metabolism, nucleotide biosynthesis, gluconeogenesis, glycosylation, cell cycle processes, DNA synthesis and genome fidelity and stability were enriched in females. Further, miRNAs target sites within these gene sets were predicted, which provides a scenario whereby the miRNAs potentially regulate these sex-biased expressed genes. The study significantly expands the expressional and regulatory characteristics of gender-biased expressed genes in schistosomes with high accuracy. The data provide a better appreciation of the biological and physiological features of male and female schistosome parasites, which may lead to novel vaccine targets and the development of new therapeutic interventions.

Gaining biological perspectives from schistosome genomes

Characterization of the genomic basis underlying schistosome biology is an important strategy for the development of future treatments and interventions. Genomic sequence is now available for the three major clinically relevant schistosome species, Schistosoma mansoni, S. japonicum and S. haematobium, and this information represents an invaluable resource for the future control of human schistosomiasis. The identification of a biologically important, but distinct from the host, schistosome gene product is the ultimate goal for many research groups. While the initial elucidation of the genome of an organism is critical for most biological research, continued improvement or curation of the genome construction should be an ongoing priority. In this review we will discuss prominent recent findings utilizing a systems approach to schistosome biology, as well as the increased use of interference RNA (RNAi). Both of these research strategies are aiming to place parasite genes into a more meaningful biological perspective.