BACKGROUND

Gene expression variation can often be linked to certain chromosomal regions and are tightly associated with phenotypic variation such as disease conditions. Inferring the causal genes for the expression variation is of great importance but rather challenging as the linked region generally contains multiple genes. Even when a single candidate gene is proposed, the underlying biological mechanism by which the regulation is enforced remains unknown. Novel approaches are needed to both infer the causal genes and generate hypothesis on the underlying regulatory mechanisms.

RESULTS

We propose a new approach which aims at achieving the above objectives by integrating genotype information, gene expression, protein-protein interaction, protein phosphorylation, and transcription factor (TF)-DNA binding information. A network based stochastic algorithm is designed to infer the causal genes and identify the underlying regulatory pathways. We first quantitatively verified our method by a test using data generated by yeast knock-out experiments. Over 40% of inferred causal genes are correct, which is significantly better than 10% by random guess. We then applied our method to a recent genome-wide expression variation study in yeast. We show that our method can correctly identify the causal genes and effectively output experimentally verified pathways. New potential gene regulatory pathways are generated and presented as a global network.

BACKGROUND

Source code is available upon request.

Drug carriers are generally introduced into the body intravenously and directly exposed to endothelial cells. Silica nanoparticles could be promising delivery vehicles for drug targeting or gene therapy. However, few studies have been undertaken to determine the biological behavior of silica nanoparticles on endothelial cells. Here we measured reactive oxygen species (ROS) generation, apoptosis and necrosis, proinflammatory and prothrombic properties and the levels of the apoptotic signaling proteins and the transcription factors in human umbilical vein endothelial cells (HUVECs) after exposure to silica nanoparticles of different concentrations (25, 50, 100, and 200 microg/mL) for 24h. The results showed that silica nanoparticles, ranging from 50 microg/mL to 200 microg/mL, markedly induced ROS production, mitochondrial depolarization and apoptosis in HUVECs. At the highest concentration, the necrotic rate, LDH leakage, the expression of CD54 and CD62E, and the release of TF, IL-6, IL-8 and MCP-1 were significantly increased. Silica nanoparticles also activated c-Jun N-terminal kinase (JNK), c-Jun, p53, caspase-3 and NF-kappaB, increased Bax expression and suppressed Bcl-2 protein. Moreover, inhibition of ROS attenuated silica nanoparticles-induced apoptosis and inflammation and the activation of JNK, c-Jun, p53 and NF-kappaB. In summary, our findings demonstrated that silica nanoparticles could induce dysfunction of endothelial cells through oxidative stress via JNK, p53 and NF-kappaB pathways, suggesting that exposure to silica nanoparticles may be a significant risk for the development of cardiovascular diseases such as atherosclerosis and thrombus.

In Saccharomyces cerevisiae, Maf1 is essential for mediating the repression of transcription by RNA polymerase (pol) III in response to diverse cellular conditions. These conditions activate distinct signaling pathways that converge at or above Maf1. Thus, Maf1-dependent repression is thought to involve a common set of downstream inhibitory effects on the pol III machinery. Here we provide support for this view and define two steps in Maf1-dependent transcriptional repression. We show that chlorpromazine (CPZ)-induced repression of pol III transcription is achieved by inhibiting de novo assembly of transcription factor (TF) IIIB onto DNA as well as the recruitment of pol III to preassembled TFIIIB.DNA complexes. Additionally Brf1 was identified as a target of repression in extracts of CPZ-treated cells. Maf1-Brf1 and Maf1-pol III interactions were implicated in the inhibition of TFIIIB.DNA complex assembly and polymerase recruitment by recombinant Maf1. Co-immunoprecipitation experiments confirmed these interactions in yeast extracts and demonstrated that Maf1 does not differentially sequester Brf1 or pol III under repressing conditions. The results suggest that Maf1 functions by a non-stoichiometric mechanism to repress pol III transcription.

With the goal of charting plant transcriptional regulatory maps (i.e. transcription factors (TFs), cis-elements and interactions between them), we have upgraded the TF-centred database PlantTFDB (http://planttfdb.cbi.pku.edu.cn/) to a plant regulatory data and analysis platform PlantRegMap (http://plantregmap.cbi.pku.edu.cn/) over the past three years. In this version, we updated the annotations for the previously collected TFs and set up a new section, 'extended TF repertoires' (TFext), to allow users prompt access to the TF repertoires of newly sequenced species. In addition to our regular TF updates, we are dedicated to updating the data on cis-elements and functional interactions between TFs and cis-elements. We established genome-wide conservation landscapes for 63 representative plants and then developed an algorithm, FunTFBS, to screen for functional regulatory elements and interactions by coupling the base-varied binding affinities of TFs with the evolutionary footprints on their binding sites. Using the FunTFBS algorithm and the conservation landscapes, we further identified over 20 million functional TF binding sites (TFBSs) and two million functional interactions for 21 346 TFs, charting the functional regulatory maps of these 63 plants. These resources are publicly available at PlantRegMap (http://plantregmap.cbi.pku.edu.cn/) and a cloud-based mirror (http://plantregmap.gao-lab.org/), providing the plant research community with valuable resources for decoding plant transcriptional regulatory systems.

Transcription factors (TFs) play important roles in plant development and its response to the environment. A variety of reverse genetics tools have been developed to study TF function, the two most commonly used ones being knockout and overexpression. Because of the unique characteristics and modes of action of TFs, the overexpression strategy has been particularly effective in revealing TF function. Thus, a number of overexpression-based methodologies - constitutive expression, tissue-specific expression, chemically inducible expression and overexpression of modified TFs - have been developed and are used in the analysis of TF function.

Many putative genetic factors that confer risk to neurodevelopmental disorders such as autism spectrum disorders (ASDs) and X-linked intellectual disability (XLID), and to neuropsychiatric disorders including attention deficit hyperactivity disorder (ADHD) and schizophrenia (SZ) have been identified in individuals from diverse human populations. Although there is significant aetiological heterogeneity within and between these conditions, recent data show that genetic factors contribute to their comorbidity. Many studies have identified candidate gene associations for these mental health disorders, albeit this is often done in a piecemeal fashion with little regard to the inherent molecular complexity. Here, we sought to abstract relationships from our knowledge of systems level biology to help understand the unique and common genetic drivers of these conditions. We undertook a global and systematic approach to build and integrate available data in gene networks associated with ASDs, XLID, ADHD and SZ. Complex network concepts and computational methods were used to investigate whether candidate genes associated with these conditions were related through mechanisms of gene regulation, functional protein-protein interactions, transcription factor (TF) and microRNA (miRNA) binding sites. Although our analyses show that genetic variations associated with the four disorders can occur in the same molecular pathways and functional domains, including synaptic transmission, there are patterns of variation that define significant differences between disorders. Of particular interest is DNA variations located in intergenic regions that comprise regulatory sites for TFs or miRNA. Our approach provides a hypothetical framework, which will help discovery and analysis of candidate genes associated with neurodevelopmental and neuropsychiatric disorders.

BACKGROUND

Apoptosis and other forms of cell death have been intensively investigated in the past years to explain the mode of action of synthetic anticancer drugs and natural products. Recently, a new form of cell death emerged, which was termed ferroptosis, because it depends on intracellular iron. Here, the role of genes involved in iron metabolism and homeostasis for the cytotoxicity of ten artemisinin derivatives have been systematically investigated.

METHODS

Log10IC50 values of 10 artemisinin derivatives (artesunate, artemether, arteether, artenimol, artemisitene, arteanuin B, another monomeric artemisinin derivative and three artemisinin dimer molecules) were correlated to the microarray-based mRNA expression of 30 iron-related genes in 60 cell lines of the National Cancer Institute (NCI, USA) as determined in 218 different microarray hybridization experiments. The effect of desferoxamine and ferrostatin-1 on the cytotoxicity of artenimol of CCRF-CEM cells was determined by resazurin assays. The mRNA expression of TFRC was exemplarily validated by immunohistochemical detection of transferrin receptor protein expression.

RESULTS

The mRNA expression of 20 genes represented by 59 different cDNA clones significantly correlated to the log10IC50 values for the artemisinins, including genes encoding transferrin (TF), transferrin receptors 1 and 2 (TFRC, TFR2), cerulopasmin (CP), lactoferrin (LTF) and others. The ferroptosis inhibitor ferrostatin-1 and the iron chelator deferoxamine led to a significantly reduced cytotoxicity of artenimol, indicating ferroptosis as cell death mode.

CONCLUSIONS

The numerous iron-related genes, whose expression correlated with the response to artemisinin derivatives speak in factor for the relevance of iron for the cytotoxic activity of these compounds. Treatment with ferroptosis-inducing agents such as artemisinin derivatives represents an attractive strategy for cancer therapy. Pre-therapeutic determination of iron-related genes may indicate tumor sensitivity to artemisinins. Ferroptosis induced by artemisinin-type drugs deserve further investigation for individualized tumor therapy.

We describe PReMod, a new database of genome-wide cis-regulatory module (CRM) predictions for both the human and the mouse genomes. The prediction algorithm, described previously in Blanchette et al. (2006) Genome Res., 16, 656-668, exploits the fact that many known CRMs are made of clusters of phylogenetically conserved and repeated transcription factors (TF) binding sites. Contrary to other existing databases, PReMod is not restricted to modules located proximal to genes, but in fact mostly contains distal predicted CRMs (pCRMs). Through its web interface, PReMod allows users to (i) identify pCRMs around a gene of interest; (ii) identify pCRMs that have binding sites for a given TF (or a set of TFs) or (iii) download the entire dataset for local analyses. Queries can also be refined by filtering for specific chromosomal regions, for specific regions relative to genes or for the presence of CpG islands. The output includes information about the binding sites predicted within the selected pCRMs, and a graphical display of their distribution within the pCRMs. It also provides a visual depiction of the chromosomal context of the selected pCRMs in terms of neighboring pCRMs and genes, all of which are linked to the UCSC Genome Browser and the NCBI. PReMod: http://genomequebec.mcgill.ca/PReMod.

During cardiac hypertrophy, the chief myocardial energy source switches from fatty acid beta-oxidation (FAO) to glycolysis-a reversion to fetal metabolism. The expression of genes encoding myocardial FAO enzymes was delineated in a murine ventricular pressure overload preparation to characterize the molecular regulatory events involved in the alteration of energy substrate utilization during cardiac hypertrophy. Expression of genes involved in the thioesterification, mitochondrial import, and beta-oxidation of fatty acids was coordinately down-regulated after 7 days of right ventricular (RV) pressure overload. Results of RV pressure overload studies in mice transgenic for the promoter region of the gene encoding human medium-chain acyl-CoA dehydrogenase (MCAD, which catalyzes a rate-limiting step in the FAO cycle) fused to a chloramphenicol acetyltransferase reporter confirmed that repression of MCAD gene expression in the hypertrophied ventricle occurred at the transcriptional level. Electrophoretic mobility-shift assays performed with MCAD promoter fragments and nuclear protein extracts prepared from hypertrophied and control RV identified pressure overload-induced protein/DNA interactions at a regulatory unit shown previously to confer control of MCAD gene transcription during cardiac development. Antibody "supershift" studies demonstrated that members of the Sp (Sp1, Sp3) and nuclear hormone receptor [chicken ovalbumin upstream promoter transcription factor (COUP-TF)/erbA-related protein 3] families interact with the pressure overload-responsive unit. Cardiomyocyte transfection studies confirmed that COUP-TF repressed the transcriptional activity of the MCAD promoter. The DNA binding activities and nuclear expression of Sp1/3 and COUP-TF in normal fetal mouse heart were similar to those in the hypertrophied adult heart. These results identify a transcriptional regulatory mechanism involved in the reinduction of a fetal metabolic program during pressure overload-induced cardiac hypertrophy.

BACKGROUND

MicroRNAs (miRNAs) are a novel class of non-coding small RNAs. In mammalian cells, miRNAs repress the translation of messenger RNAs (mRNAs) or degrade mRNAs. miRNAs play important roles in development and differentiation, and they are also implicated in aging, and oncogenesis. Predictions of targets of miRNAs suggest that they may regulate more than one-third of all genes. The overall functions of mammalian miRNAs remain unclear. Combinatorial regulation by transcription factors alone or miRNAs alone offers a wide range of regulatory programs. However, joining transcriptional and post-transcriptional regulatory mechanisms enables higher complexity regulatory programs that in turn could give cells evolutionary advantages. Investigating coordinated regulation of genes by miRNAs and transcription factors (TFs) from a statistical standpoint is a first step that may elucidate some of their roles in various biological processes.

RESULTS

Here, we studied the nature and scope of coordination among regulators from the transcriptional and miRNA regulatory layers in the human genome. Our findings are based on genome wide statistical assessment of regulatory associations ("interactions") among the sets of predicted targets of miRNAs and sets of putative targets of transcription factors. We found that combinatorial regulation by transcription factor pairs and miRNA pairs is much more abundant than the combinatorial regulation by TF-miRNA pairs. In addition, many of the strongly interacting TF-miRNA pairs involve a subset of master TF regulators that co-regulate genes in coordination with almost any miRNA. Application of standard measures for evaluating the degree of interaction between pairs of regulators show that strongly interacting TF-miRNA, TF-TF or miRNA-miRNA pairs tend to include TFs or miRNAs that regulate very large numbers of genes. To correct for this potential bias we introduced an additional Bayesian measure that incorporates not only how significant an interaction is but also how strong it is. Putative pairs of regulators selected by this procedure are more likely to have biological coordination. Importantly, we found that the probability of a TF-miRNA pair forming feed forward loops with its common target genes (where the miRNA simultaneously suppresses the TF and many of its targets) is increased for strongly interacting TF-miRNA pairs.

CONCLUSIONS

Genes are more likely to be co-regulated by pairs of TFs or pairs of miRNAs than by pairs of TF-miRNA, perhaps due to higher probability of evolutionary duplication events of shorter DNA sequences. Nevertheless, many gene sets are reciprocally regulated by strongly interacting pairs of TF-miRNA, which suggests an effective mechanism to suppress functionally related proteins. Moreover, the particular type of feed forward loop (with two opposing modes where the TF activates its target genes or the miRNA simultaneously suppresses this TF and the TF-miRNA joint target genes) is more prevalent among strongly interacting TF-miRNA pairs. This may be attributed to a process that prevents waste of cellular resources or a mechanism to accelerate mRNA degradation.

TFC5, the unique and essential gene encoding the B" component of the Saccharomyces cerevisiae RNA polymerase III transcription factor (TF)IIIB has been cloned. It encodes a 594-amino acid protein (67,688 Da). Escherichia coli-produced B" has been used to reconstitute entirely recombinant TFIIIB that is fully functional for TFIIIC-directed, as well as TATA box-dependent, DNA binding and transcription. The DNase I footprints of entirely recombinant TFIIIB, composed of B", the 67-kDa Brf, and TATA box-binding protein, and TFIIIB reconstituted with natural B" are indistinguishable. A truncated form of B" lacking 39 N-terminal and 107 C-terminal amino acids is also functional for transcription.

Tissue factor (TF) expression by endothelial cells is implicated in thrombotic episodes in patients with a variety of clinical disorders. In a baboon model of lethal sepsis, TF is expressed by endothelial cells in the splenic microvasculature. In vitro, endothelial cells are induced to express TF in response to tumor necrosis factor-alpha (TNF-alpha), interleukin-1 beta (IL-1 beta), and bacterial endotoxin (lipopolysaccharide [LPS]). Here, we identified cis-acting regulatory elements that control TF gene transcription in primary human endothelial cells. Functional studies showed that the TF promoter contained a 56-bp enhancer (-227 to -172 bp), which included two activator protein-1 (AP-1) sites and a kappa B-like site, that mediated induction by TNF-alpha, IL-1 beta, and LPS. Electrophoretic mobility shift assays demonstrated that endothelial cells contained constitutive AP-1 binding activity, whereas the kappa B-like site, 5'-CGGAGTTTCC-3', bound an inducible nuclear complex composed of c-Rel-p65 heterodimers. Taken together, our data suggest that induction of TF gene transcription in endothelial cells is mediated by functional interactions between Fos-Jun and c-Rel-p65 heterodimers.

Comprehensive identification of DNA cis-regulatory elements is crucial for a predictive understanding of transcriptional network dynamics. Strong evidence suggests that these DNA sequence motifs are highly conserved between related species, reflecting strong selection on the network of regulatory interactions that underlie common cellular behavior. Here, we exploit a systems-level aspect of this conservation-the network-level topology of these interactions-to map transcription factor (TF) binding sites on a genomic scale. Using network-level conservation as a constraint, our algorithm finds 71% of known TF binding sites in the yeast Saccharomyces cerevisiae, using only 12% of the sequence of a phylogenetic neighbor. Most of the novel predicted motifs show strong features of known TF binding sites, such as functional category and/or expression profile coherence of their corresponding genes. Network-level conservation should provide a powerful constraint for the systematic mapping of TF binding sites in the larger genomes of higher eukaryotes.

The uptake of transferrin and iron by the brain, liver and femurs was investigated in rats using 125I-59Fe-transferrin (Tf), and 131I-albumin in order to measure the plasma content of the organs. Measurements in rats ranging in age from birth to 70 days revealed that the rate of iron uptake by the brain increased rapidly over the first 15 days of life, peaking at 15 days and thereafter declining. A similar pattern occurred in the uptake of 125I-Tf. These changes were accompanied by rapid growth of the brain up to 15 days and a decrease in the concentration of non-haem iron. The turnover of 59Fe and 125I-Tf in the brain was also determined by measuring radioactivity in the brain of 15-day rats at various times after injection from 15 min to 13 days. The amount of 59Fe in the brain increased over the first 4 h and thereafter remained constant. By contrast, the 125I-Tf values increased rapidly during the first 15 min to reach a relatively constant level which was maintained for at least 6 h after which it declined. The patterns of uptake by the brain were different from those found in the liver and femurs, indicating that the changes in the brain were specific for that organ.(ABSTRACT TRUNCATED AT 250 WORDS)

Numerous transcription factors (TFs) encode information about upstream signals in the dynamics of their activation, but how downstream genes decode these dynamics remains poorly understood. Using microfluidics to control the nucleocytoplasmic translocation dynamics of the budding yeast TF Msn2, we elucidate the principles that govern how different promoters convert dynamical Msn2 input into gene expression output in single cells. Combining modeling and experiments, we classify promoters according to their signal-processing behavior and reveal that multiple, distinct gene expression programs can be encoded in the dynamics of Msn2. We show that both oscillatory TF dynamics and slow promoter kinetics lead to higher noise in gene expression. Furthermore, we show that the promoter activation timescale is related to nucleosome remodeling. Our findings imply a fundamental trade-off: although the cell can exploit different promoter classes to differentially control gene expression using TF dynamics, gene expression noise fundamentally limits how much information can be encoded in the dynamics of a single TF and reliably decoded by promoters.

Current cancer management strategies fail to adequately treat malignancies with multivariable dose-restricting factors such as systemic toxicity and multi-drug resistance limiting therapeutic benefit, quality of life and complete long-term remission rates. The targeted delivery of a therapeutic compound aims to enhance its circulation and cellular uptake, decrease systemic toxicity and improve therapeutic benefit with disease specificity. The transferrin peptide, its receptor and their biological significance, has been widely characterised and vastly relevant when applied to targeting strategies. Utilising knowledge about the physiological function of the transferrin-transferrin receptor complex and the efficiency of its receptor-mediated endocytosis provides rationale to continue the development of transferrin-targeted anticancer modalities. Furthermore, multiple studies report an upregulation in expression of the transferrin receptor on metastatic and drug resistant tumours, highlighting its selectivity to cancer. Due to the increased expression of the transferrin receptor in brain glioma, the successful delivery of anticancer compounds to the tumour site and the ability to cross the blood brain barrier has shown to be an important discovery. Its significance in the development of cancer-specific therapies is shown to be important by direct conjugation and immunotoxin studies which use transferrin and anti-transferrin receptor antibodies as the targeting moiety. Such conjugates have demonstrated enhanced cellular uptake via transferrin-mediated mechanisms and increased selective cytotoxicity in a number of cancer cell lines and tumour xenograft animal models. In addition, incubation of chemotherapy-insensitive cancer cells with transferrin-targeted conjugates in vitro has resulted in a reversal of their drug resistance. Transferrin immunotoxins have also shown similar promise, with a diphtheria toxin mutant covalently bound to transferrin (Tf-CRM107) currently involved in human clinical trials for the treatment of glioblastoma. Despite this, the inability to translate preliminary research into a clinical setting has compelled research into novel targeting strategies including the use of nanoparticulate theory in the design of drug delivery systems. The main objective of this review is to evaluate the importance of the transferrin-transferrin receptor complex as a target for cancer therapy through extensive knowledge of both the physiological and pathological interactions between the complex and different cell types. In addition, this review serves as a summary to date of direct conjugation and immunotoxin studies, with an emphasis on transferrin as an important targeting moiety in the directed delivery of anticancer therapeutic compounds.

The concept of non-transferrin bound iron (NTBI) was introduced 22 years ago by Hershko et al. (Brit. J. Haematol. 40 (1978) 255). It stemmed from a suspicion that, in iron overloaded patients, the large amounts of excess iron released into the circulation are likely to exceed the serum transferrin (Tf) iron-binding capacity (TIBC), leading to the appearance of various forms of iron not bound to Tf. In accordance with this assumption, NTBI was initially looked for and detected in patients with>> or = 100% Tf-saturation. As techniques for its detection became more sophisticated and sensitive, NTBI was also found in conditions where Tf was not fully saturated, leading to a revision of the original view of NTBI as a simple spillover phenomenon. In this review, we will discuss some of the properties of NTBI, methods for its detection, its significance and potential value as an indicator for therapeutic regimens of iron chelation and supplementation.

BACKGROUND

Transcription factors (TFs) play a central role in regulating gene expression by interacting with cis-regulatory DNA elements associated with their target genes. Recent surveys have examined the DNA binding specificities of most Saccharomyces cerevisiae TFs, but a comprehensive evaluation of their data has been lacking.

RESULTS

We analyzed in vitro and in vivo TF-DNA binding data reported in previous large-scale studies to generate a comprehensive, curated resource of DNA binding specificity data for all characterized S. cerevisiae TFs. Our collection comprises DNA binding site motifs and comprehensive in vitro DNA binding specificity data for all possible 8-bp sequences. Investigation of the DNA binding specificities within the basic leucine zipper (bZIP) and VHT1 regulator (VHR) TF families revealed unexpected plasticity in TF-DNA recognition: intriguingly, the VHR TFs, newly characterized by protein binding microarrays in this study, recognize bZIP-like DNA motifs, while the bZIP TF Hac1 recognizes a motif highly similar to the canonical E-box motif of basic helix-loop-helix (bHLH) TFs. We identified several TFs with distinct primary and secondary motifs, which might be associated with different regulatory functions. Finally, integrated analysis of in vivo TF binding data with protein binding microarray data lends further support for indirect DNA binding in vivo by sequence-specific TFs.

CONCLUSIONS

The comprehensive data in this curated collection allow for more accurate analyses of regulatory TF-DNA interactions, in-depth structural studies of TF-DNA specificity determinants, and future experimental investigations of the TFs' predicted target genes and regulatory roles.

The initiator of coagulation, full-length tissue factor (flTF), in complex with factor VIIa, influences angiogenesis through PAR-2. Recently, an alternatively spliced variant of TF (asTF) was discovered, in which part of the TF extracellular domain, the transmembrane, and cytoplasmic domains are replaced by a unique C terminus. Subcutaneous tumors produced by asTF-secreting cells revealed increased angiogenesis, but it remained unclear if and how angiogenesis is regulated by asTF. Here, we show that asTF enhances angiogenesis in matrigel plugs in mice, whereas a soluble form of flTF only modestly enhances angiogenesis. asTF dose-dependently upregulates angiogenesis ex vivo independent of either PAR-2 or VIIa. Rather, asTF was found to ligate integrins, resulting in downstream signaling. asTF-alphaVbeta3 integrin interaction induces endothelial cell migration, whereas asTF-dependent formation of capillaries in vitro is dependent on alpha6beta1 integrin. Finally, asTF-dependent aortic sprouting is sensitive to beta1 and beta3 integrin blockade and a TF-antibody that disrupts asTF-integrin interaction. We conclude that asTF, unlike flTF, does not affect angiogenesis via PAR-dependent pathways but relies on integrin ligation. These findings indicate that asTF may serve as a target to prevent pathological angiogenesis.

MAGIA(2) (http://gencomp.bio.unipd.it/magia2) is an update, extension and evolution of the MAGIA web tool. It is dedicated to the integrated analysis of in silico target prediction, microRNA (miRNA) and gene expression data for the reconstruction of post-transcriptional regulatory networks. miRNAs are fundamental post-transcriptional regulators of several key biological and pathological processes. As miRNAs act prevalently through target degradation, their expression profiles are expected to be inversely correlated to those of the target genes. Low specificity of target prediction algorithms makes integration approaches an interesting solution for target prediction refinement. MAGIA(2) performs this integrative approach supporting different association measures, multiple organisms and almost all target predictions algorithms. Nevertheless, miRNAs activity should be viewed as part of a more complex scenario where regulatory elements and their interactors generate a highly connected network and where gene expression profiles are the result of different levels of regulation. The updated MAGIA(2) tries to dissect this complexity by reconstructing mixed regulatory circuits involving either miRNA or transcription factor (TF) as regulators. Two types of circuits are identified: (i) a TF that regulates both a miRNA and its target and (ii) a miRNA that regulates both a TF and its target.

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy. The understanding of its gene expression regulation and molecular mechanisms still remains elusive. Started from experimentally verified T-ALL-related miRNAs and genes, we obtained 120 feed-forward loops (FFLs) among T-ALL-related genes, miRNAs and TFs through combining target prediction. Afterwards, a T-ALL miRNA and TF co-regulatory network was constructed, and its significance was tested by statistical methods. Four miRNAs in the miR-17-92 cluster and four important genes (CYLD, HOXA9, BCL2L11 and RUNX1) were found as hubs in the network. Particularly, we found that miR-19 was highly expressed in T-ALL patients and cell lines. Ectopic expression of miR-19 represses CYLD expression, while miR-19 inhibitor treatment induces CYLD protein expression and decreases NF-κB expression in the downstream signaling pathway. Thus, miR-19, CYLD and NF-κB form a regulatory FFL, which provides new clues for sustained activation of NF-κB in T-ALL. Taken together, we provided the first miRNA-TF co-regulatory network in T-ALL and proposed a model to demonstrate the roles of miR-19 and CYLD in the T-cell leukemogenesis. This study may provide potential therapeutic targets for T-ALL and shed light on combining bioinformatics with experiments in the research of complex diseases.

Glucocorticoids are extensively used in combination chemotherapy of advanced prostate cancer (PC). Little is known, however, about the status of the glucocorticoid receptor (GR) in PC. We evaluated over 200 prostate samples and determined that GR expression was strongly decreased or absent in 70-85% of PC. Similar to PC tumors, some PC cell lines, including LNCaP, also lack GR. To understand the role of GR, we reconstituted its expression in LNCaP cells using lentiviral approach. Treatment of LNCaP-GR cells with the glucocorticoids strongly inhibited proliferation in the monolayer cultures and blocked anchorage-independent growth. This was accompanied by upregulation of p21 and p27, down-regulation of cyclin D1 expression and c-Myc phosphorylation. Importantly, the activation of GR resulted in normalized expression of PC markers hepsin, AMACR, and maspin. On the signaling level, GR decreased expression and inhibited activity of the MAP-kinases (MAPKs) including p38, JNK/SAPK, Mek1/2 and Erk1/2. We also found that activation of GR inhibited activity of numerous transcription factors (TF) including AP-1, SRF, NF-kappaB, p53, ATF-2, CEBPalpha, Ets-1, Elk-1, STAT1 and others, many of which are regulated via MAPK cascade. The structural analysis of hepsin and AMACR promoters provided the mechanistic rationale for PC marker downregulation by glucocorticoids via inhibition of specific TFs. Our data suggest that GR functions as a tumor suppressor in prostate, and inhibits multiple signaling pathways and transcriptional factors involved in proliferation and transformation.

The genomic era has revealed that the large repertoire of observed animal phenotypes is dependent on changes in the expression patterns of a finite number of genes, which are mediated by a plethora of transcription factors (TFs) with distinct specificities. The dimerization of TFs can also increase the complexity of a genetic regulatory network manifold, by combining a small number of monomers into dimers with distinct functions. Therefore, studying the evolution of these dimerizing TFs is vital for understanding how complexity increased during animal evolution. We focus on the second largest family of dimerizing TFs, the basic-region leucine zipper (bZIP), and infer when it expanded and how bZIP DNA-binding and dimerization functions evolved during the major phases of animal evolution. Specifically, we classify the metazoan bZIPs into 19 families and confirm the ancient nature of at least 13 of these families, predating the split of the cnidaria. We observe fixation of a core dimerization network in the last common ancestor of protostomes-deuterostomes. This was followed by an expansion of the number of proteins in the network, but no major dimerization changes in interaction partners, during the emergence of vertebrates. In conclusion, the bZIPs are an excellent model with which to understand how DNA binding and protein interactions of TFs evolved during animal evolution.

Thrombosis is initiated by tissue factor (TF), a coagulation cofactor/receptor expressed in the vessel wall, on myeloid cells, and on microparticles (MPs) with variable procoagulant activity. However, the molecular pathways that generate prothrombotic TF in vivo are poorly defined. The oxidoreductase protein disulfide isomerase (PDI) is thought to be involved in the activation of TF. Here, we found that in mouse myeloid cells, ATP-triggered signaling through purinergic receptor P2X, ligand-gated ion channel, 7 (P2X7 receptor; encoded by P2rx7) induced activation (decryption) of TF procoagulant activity and promoted release of TF+ MPs from macrophages and SMCs. The generation of prothrombotic MPs required P2X7 receptor-dependent production of ROS leading to increased availability of solvent-accessible extracellular thiols. An antibody to PDI with antithrombotic activity in vivo attenuated the release of procoagulant MPs. In addition, P2rx7-/- mice were protected from TF-dependent FeCl3-induced carotid artery thrombosis. BM chimeras revealed that P2X7 receptor prothrombotic function was present in both hematopoietic and vessel wall compartments. In contrast, an alternative anti-PDI antibody showed activities consistent with cellular activation typically induced by P2X7 receptor signaling. This anti-PDI antibody restored TF-dependent thrombosis in P2rx7-/- mice. These data suggest that PDI regulates a critical P2X7 receptor-dependent signaling pathway that generates prothrombotic TF, defining a link between inflammation and thrombosis with potential implications for antithrombotic therapy.