TcoF-DB: dragon database for human transcription co-factors and transcription factor interacting proteins

The initiation and regulation of transcription in eukaryotes is complex and involves a large number of transcription factors (TFs), which are known to bind to the regulatory regions of eukaryotic DNA. Apart from TF–DNA binding, protein–protein interaction involving TFs is an essential component of the machinery facilitating transcriptional regulation. Proteins that interact with TFs in the context of transcription regulation but do not bind to the DNA themselves, we consider transcription co-factors (TcoFs). The influence of TcoFs on transcriptional regulation and initiation, although indirect, has been shown to be significant with the functionality of TFs strongly influenced by the presence of TcoFs. While the role of TFs and their interaction with regulatory DNA regions has been well-studied, the association between TFs and TcoFs has so far been given less attention. Here, we present a resource that is comprised of a collection of human TFs and the TcoFs with which they interact. Other proteins that have a proven interaction with a TF, but are not considered TcoFs are also included. Our database contains 157 high-confidence TcoFs and additionally 379 hypothetical TcoFs. These have been identified and classified according to the type of available evidence for their involvement in transcriptional regulation and their presence in the cell nucleus. We have divided TcoFs into four groups, one of which contains high-confidence TcoFs and three others contain TcoFs which are hypothetical to different extents. We have developed the Dragon Database for Human Transcription Co-Factors and Transcription Factor Interacting Proteins (TcoF-DB). A web-based interface for this resource can be freely accessed at http://cbrc.kaust.edu.sa/tcof/ and http://apps.sanbi.ac.za/tcof/

Network analysis of microRNAs and their regulation in human ovarian cancer

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are small non-coding RNA molecules that repress the translation of messenger RNAs (mRNAs) or degrade mRNAs. These functions of miRNAs allow them to control key cellular processes such as development, differentiation and apoptosis, and they have also been implicated in several cancers such as leukaemia, lung, pancreatic and ovarian cancer (OC). Unfortunately, the specific machinery of miRNA regulation, involving transcription factors (TFs) and transcription co-factors (TcoFs), is not well understood. In the present study we focus on computationally deciphering the underlying network of miRNAs, their targets, and their control mechanisms that have an influence on OC development.</p> <p>Results</p> <p>We analysed experimentally verified data from multiple sources that describe miRNA influence on diseases, miRNA targeting of mRNAs, and on protein-protein interactions, and combined this data with <it>ab initio </it>transcription factor binding site predictions within miRNA promoter regions. From these analyses, we derived a network that describes the influence of miRNAs and their regulation in human OC. We developed a methodology to analyse the network in order to find the nodes that have the largest potential of influencing the network's behaviour (network hubs). We further show the potentially most influential miRNAs, TFs and TcoFs, showing subnetworks illustrating the involved mechanisms as well as regulatory miRNA network motifs in OC. We find an enrichment of miRNA targeted OC genes in the highly relevant pathways cell cycle regulation and apoptosis.</p> <p>Conclusions</p> <p>We combined several sources of interaction and association data to analyse and place miRNAs within regulatory pathways that influence human OC. These results represent the first comprehensive miRNA regulatory network analysis for human OC. This suggests that miRNAs and their regulation may play a major role in OC and that further directed research in this area is of utmost importance to enhance our understanding of the molecular mechanisms underlying human cancer development and OC in particular.</p

The Combined Effect of Hg(II) Speciation, Thiol Metabolism, and Cell Physiology on Methylmercury Formation by Geobacter sulfurreducens

The chemical and biological factors controlling microbial formation of methylmercury (MeHg) are widely studied separately, but the combined effects of these factors are largely unknown. We examined how the chemical speciation of divalent, inorganic mercury (Hg(II)), as controlled by low-molecular-mass thiols, and cell physiology govern MeHg formation by Geobacter sulfurreducens. We compared MeHg formation with and without addition of exogenous cysteine (Cys) to experimental assays with varying nutrient and bacterial metabolite concentrations. Cysteine additions initially (0-2 h) enhanced MeHg formation by two mechanisms: (i) altering the Hg(II) partitioning from the cellular to the dissolved phase and/or (ii) shifting the chemical speciation of dissolved Hg(II) in favor of the Hg(Cys)2 complex. Nutrient additions increased MeHg formation by enhancing cell metabolism. These two effects were, however, not additive since cysteine was largely metabolized to penicillamine (PEN) over time at a rate that increased with nutrient addition. These processes shifted the speciation of dissolved Hg(II) from complexes with relatively high availability, Hg(Cys)2, to complexes with lower availability, Hg(PEN)2, for methylation. This thiol conversion by the cells thereby contributed to stalled MeHg formation after 2-6 h Hg(II) exposure. Overall, our results showed a complex influence of thiol metabolism on microbial MeHg formation and suggest that the conversion of cysteine to penicillamine may partly suppress MeHg formation in cysteine-rich environments like natural biofilms

DDESC: Dragon database for exploration of sodium channels in human

<p>Abstract</p> <p>Background</p> <p>Sodium channels are heteromultimeric, integral membrane proteins that belong to a superfamily of ion channels. The mutations in genes encoding for sodium channel proteins have been linked with several inherited genetic disorders such as febrile epilepsy, Brugada syndrome, ventricular fibrillation, long QT syndrome, or channelopathy associated insensitivity to pain. In spite of these significant effects that sodium channel proteins/genes could have on human health, there is no publicly available resource focused on sodium channels that would support exploration of the sodium channel related information.</p> <p>Results</p> <p>We report here Dragon Database for Exploration of Sodium Channels in Human (DDESC), which provides comprehensive information related to sodium channels regarding different entities, such as "genes and proteins", "metabolites and enzymes", "toxins", "chemicals with pharmacological effects", "disease concepts", "human anatomy", "pathways and pathway reactions" and their potential links. DDESC is compiled based on text- and data-mining. It allows users to explore potential associations between different entities related to sodium channels in human, as well as to automatically generate novel hypotheses.</p> <p>Conclusion</p> <p>DDESC is first publicly available resource where the information related to sodium channels in human can be explored at different levels. This database is freely accessible for academic and non-profit users via the worldwide web <url>http://apps.sanbi.ac.za/ddesc</url>.</p

DDEC: Dragon database of genes implicated in esophageal cancer

<p>Abstract</p> <p>Background</p> <p>Esophageal cancer ranks eighth in order of cancer occurrence. Its lethality primarily stems from inability to detect the disease during the early organ-confined stage and the lack of effective therapies for advanced-stage disease. Moreover, the understanding of molecular processes involved in esophageal cancer is not complete, hampering the development of efficient diagnostics and therapy. Efforts made by the scientific community to improve the survival rate of esophageal cancer have resulted in a wealth of scattered information that is difficult to find and not easily amendable to data-mining. To reduce this gap and to complement available cancer related bioinformatic resources, we have developed a comprehensive database (Dragon Database of Genes Implicated in Esophageal Cancer) with esophageal cancer related information, as an integrated knowledge database aimed at representing a gateway to esophageal cancer related data.</p> <p>Description</p> <p>Manually curated 529 genes differentially expressed in EC are contained in the database. We extracted and analyzed the promoter regions of these genes and complemented gene-related information with transcription factors that potentially control them. We further, precompiled text-mined and data-mined reports about each of these genes to allow for easy exploration of information about associations of EC-implicated genes with other human genes and proteins, metabolites and enzymes, toxins, chemicals with pharmacological effects, disease concepts and human anatomy. The resulting database, DDEC, has a useful feature to display potential associations that are rarely reported and thus difficult to identify. Moreover, DDEC enables inspection of potentially new 'association hypotheses' generated based on the precompiled reports.</p> <p>Conclusion</p> <p>We hope that this resource will serve as a useful complement to the existing public resources and as a good starting point for researchers and physicians interested in EC genetics. DDEC is freely accessible to academic and non-profit users at <url>http://apps.sanbi.ac.za/ddec/</url>. DDEC will be updated twice a year.</p

Mutations and Binding Sites of Human Transcription Factors

Mutations in any genome may lead to phenotype characteristics that determine ability of an individual to cope with adaptation to environmental challenges. In studies of human biology, among the most interesting ones are phenotype characteristics that determine responses to drug treatments, response to infections, or predisposition to specific inherited diseases. Most of the research in this field has been focused on the studies of mutation effects on the final gene products, peptides, and their alterations. Considerably less attention was given to the mutations that may affect regulatory mechanism(s) of gene expression, although these may also affect the phenotype characteristics. In this study we make a pilot analysis of mutations observed in the regulatory regions of 24,667 human RefSeq genes. Our study reveals that out of eight studied mutation types, “insertions” are the only one that in a statistically significant manner alters predicted transcription factor binding sites (TFBSs). We also find that 25 families of TFBSs have been altered by mutations in a statistically significant manner in the promoter regions we considered. Moreover, we find that the related transcription factors are, for example, prominent in processes related to intracellular signaling; cell fate; morphogenesis of organs and epithelium; development of urogenital system, epithelium, and tube; neuron fate commitment. Our study highlights the significance of studying mutations within the genes regulatory regions and opens way for further detailed investigations on this topic, particularly on the downstream affected pathways

Deciphering the transcriptional circuitry of microRNA genes expressed during human monocytic differentiation

<p>Abstract</p> <p>Background</p> <p>Macrophages are immune cells involved in various biological processes including host defence, homeostasis, differentiation, and organogenesis. Disruption of macrophage biology has been linked to increased pathogen infection, inflammation and malignant diseases. Differential gene expression observed in monocytic differentiation is primarily regulated by interacting transcription factors (TFs). Current research suggests that microRNAs (miRNAs) degrade and repress translation of mRNA, but also may target genes involved in differentiation. We focus on getting insights into the transcriptional circuitry regulating miRNA genes expressed during monocytic differentiation.</p> <p>Results</p> <p>We computationally analysed the transcriptional circuitry of miRNA genes during monocytic differentiation using <it>in vitro </it>time-course expression data for TFs and miRNAs. A set of TF→miRNA associations was derived from predicted TF binding sites in promoter regions of miRNA genes. Time-lagged expression correlation analysis was utilised to evaluate the TF→miRNA associations. Our analysis identified 12 TFs that potentially play a central role in regulating miRNAs throughout the differentiation process. Six of these 12 TFs (ATF2, E2F3, HOXA4, NFE2L1, SP3, and YY1) have not previously been described to be important for monocytic differentiation. The remaining six TFs are CEBPB, CREB1, ELK1, NFE2L2, RUNX1, and USF2. For several miRNAs (miR-21, miR-155, miR-424, and miR-17-92), we show how their inferred transcriptional regulation impacts monocytic differentiation.</p> <p>Conclusions</p> <p>The study demonstrates that miRNAs and their transcriptional regulatory control are integral molecular mechanisms during differentiation. Furthermore, it is the first study to decipher on a large-scale, how miRNAs are controlled by TFs during human monocytic differentiation. Subsequently, we have identified 12 candidate key controllers of miRNAs during this differentiation process.</p

DDPC: Dragon database of genes associated with prostate cancer

Prostate cancer (PC) is one of the most commonly diagnosed cancers in men. PC is relatively difficult to diagnose due to a lack of clear early symptoms. Extensive research of PC has led to the availability of a large amount of data on PC. Several hundred genes are implicated in different stages of PC, which may help in developing diagnostic methods or even cures. In spite of this accumulated information, effective diagnostics and treatments remain evasive. We have developed Dragon Database of Genes associated with Prostate Cancer (DDPC) as an integrated knowledgebase of genes experimentally verified as implicated in PC. DDPC is distinctive from other databases in that (i) it provides pre-compiled biomedical text-mining information on PC, which otherwise require tedious computational analyses, (ii) it integrates data on molecular interactions, pathways, gene ontologies, gene regulation at molecular level, predicted transcription factor binding sites on promoters of PC implicated genes and transcription factors that correspond to these binding sites and (iii) it contains DrugBank data on drugs associated with PC. We believe this resource will serve as a source of useful information for research on PC.DST/NRF Research Chair National Bioinformatics Network grants National Research Foundation of South Afric

Concomitant statin use does not impair the clinical outcome of patients with diffuse large B cell lymphoma treated with rituximab-CHOP

Preclinical data indicated a detrimental effect of statins on the anti-lymphoma activity of rituximab. We evaluated the impact of concomitant statin medication on the response and survival of patients with diffuse large B cell lymphoma (DLBCL) receiving rituximab-cyclophosphamide, doxorubicin, vincristine, prednisone (R-CHOP) as first-line therapy. Medical histories of patients with DLBCL who were treated with R-CHOP as first-line therapy were assessed for concomitant statin use, response after completion of chemotherapy, event-free survival (EFS), and overall survival (OS). Furthermore, 2-[18F]fluor-2-deoxyglucose (FDG)-PET/CT results after completion of first-line therapy were compared between the groups. Overall, 145 patients with DLBCL treated with R-CHOP from January 2001 to December 2009 were analyzed. Twenty-one (15%) patients received statins throughout therapy. Five-year EFS was 67.3% in patients without statins compared with 79% in patients receiving statins during R-CHOP (HR, 0.47; 95% CI, 0.15-1.54, p = 0.2). Five-year OS was 81.4% for patients without statins compared with 93.3% for patients taking statins (HR, 0.58; 95% CI 0.07-4.55, p = 0.6). There were no statistically significant differences in the rates of complete remissions between the two groups (75% in the non-statin group versus 86% in the statin group, p = 0.45). A trend toward a lower rate of complete metabolic responses in FDG-PET/CT after chemotherapy was seen in patients without statin medication compared with the patients taking statins (84% versus 92%, p = 0.068). Concomitant statin use had no adverse impact on response to chemotherapy, EFS, and OS in patients treated with R-CHOP for DLBC

Risk of symptomatic COVID-19 due to aircraft transmission: a retrospective cohort study of contact-traced flights during England's containment phase.

BACKGROUND: Knowledge gaps remain regarding SARS-CoV-2 transmission on flights. We conducted a retrospective cohort study to estimate risk of acquiring symptomatic SARS-CoV-2 on aircraft, to inform contact tracing and infection control efforts. METHODS: We identified co-passengers of infectious passengers on 18 England-bound flights from European cities up to 12/03/2020, using manifests received for contact tracing. Infectious passengers were laboratory-confirmed cases with symptom onset from 7 days before to 2 days after the flight. Possible aircraft-acquired cases were laboratory-confirmed with onset 3-14 days post-flight with no known non-flight exposure. Manifests was merged with the national case management dataset (identifying cases, onset dates, contact tracing status) and the national COVID-19 linelist. Contact tracing notes were reviewed to identify non-flight exposures. We calculated attack rates (ARs) among all co-passengers and within subgroups, including by distance from infectious cases and number of infectious cases on-board. RESULTS: There were 55 infectious passengers and 2313 co-passengers, including 2221 flight-only contacts. Five possible aircraft-acquired cases were identified; ARs of 0.2% (95%CI 0.1-0.5) among all flight-only contacts and 3.8% (95%CI 1.3-10.6) among contact-traced flight-only contacts sat within a two-seat radius. The AR among 92 co-travellers with known non-flight exposure to infectious cases was 13.0% (95%CI 7.6%-21.4%). There were insufficient numbers to assess differences between subgroups. CONCLUSION: We conclude that risk of symptomatic COVID-19 due to transmission on short to medium-haul flights is low, and recommend prioritising contact-tracing of close contacts and co-travellers where resources are limited. Further research on risk on aircraft is encouraged