258 research outputs found

    Regret Analysis for River Water Quality Management

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    The treatment of uncertainty inherent in water quality policy development and related modeling is a key issue. This is particularly true in the Central and Eastern European region which is characterized by high pollution levels, strong economic transition, lack of financial resources and scarce and imprecise data availability. Possibilities to account for uncertainties in policy development by a regret analysis approach were studied. The risks associated with regret in decision making were qualitatively and quantitatively defined. The design of a decision making procedure where these risks are accounted for was analyzed from a theoretical and practical viewpoint. A regret analysis procedure was implemented within an experimental decision support system (DSS) for water quality management of a river. This system was tested with a hypothetical situation where the best option of upgrading of a number of waste water treatment plants was to be selected from a small set of possible options. The main problem of analyses of this kind is the curse of dimensionality. The study shows that a modular approach, which uses already available software components and models, speeds up the building of a DSS

    A GO catalogue of human DNA-binding transcription factors

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    To control gene transcription, DNA-binding transcription factors recognise specific sequence motifs in gene regulatory regions. A complete and reliable GO annotation of all DNA-binding transcription factors is key to investigating the delicate balance of gene regulation in response to environmental and developmental stimuli. The need for such information is demonstrated by the many lists of transcription factors that have been produced over the past decade. The COST Action Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC) Consortium brought together experts in the field of transcription with the aim of providing high quality and interoperable gene regulatory data. The Gene Ontology (GO) Consortium provides strict definitions for gene product function, including factors that regulate transcription. The collaboration between the GREEKC and GO Consortia has enabled the application of those definitions to produce a new curated catalogue of over 1400 human DNA-binding transcription factors, that can be accessed at https://www.ebi.ac.uk/QuickGO/targetset/dbTF. This catalogue has facilitated an improvement in the GO annotation of human DNA-binding transcription factors and led to the GO annotation of almost sixty thousand DNA-binding transcription factors in over a hundred species. Thus, this work will aid researchers investigating the regulation of transcription in both biomedical and basic science

    A GO catalogue of human DNA-binding transcription factors

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    DNA-binding transcription factors recognise genomic addresses, specific sequence motifs in gene regulatory regions, to control gene transcription. A complete and reliable catalogue of all DNA-binding transcription factors is key to investigating the delicate balance of gene regulation in response to environmental and developmental stimuli. The need for such a catalogue of proteins is demonstrated by the many lists of DNA-binding transcription factors that have been produced over the past decade. The COST Action Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC) Consortium brought together experts in the field of transcription with the aim of providing high quality and interoperable gene regulatory data. The Gene Ontology (GO) Consortium provides strict definitions for gene product function, including factors that regulate transcription. The collaboration between the GREEKC and GO Consortia has enabled the application of those definitions to produce a new curated catalogue of human DNA-binding transcription factors, that can be accessed at https://www.ebi.ac.uk/QuickGO/targetset/dbTF. In addition, this curation effort has led to the GO annotation of almost sixty thousand DNA-binding transcription factors in over a hundred species. Thus, this work will aid researchers investigating the regulation of transcription in both biomedical and basic science

    Longitudinal Secretion of Paramyxovirus RNA in the Urine of Straw-Coloured Fruit Bats (Eidolon helvum).

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    The straw-coloured fruit bat (Eidolon helvum) is widespread in sub-Saharan Africa and is widely hunted for bushmeat. It is known to harbour a range of paramyxoviruses, including rubuloviruses and henipaviruses, but the zoonotic potential of these is unknown. We previously found a diversity of paramyxoviruses within a small, captive colony of E. helvum after it had been closed to contact with other bats for 5 years. In this study, we used under-roost urine collection to further investigate the paramyxovirus diversity and ecology in this colony, which had been closed to the outside for 10 years at the time of sampling. By sampling urine weekly throughout an entire year, we investigated possible seasonal patterns of shedding of virus or viral RNA. Using a generic paramyxovirus L-gene PCR, we detected eight distinct paramyxovirus RNA sequences. Six distinct sequences were detected using a Henipavirus-specific PCR that targeted a different region of the L-gene. Sequence detection had a bi-annual pattern, with the greatest peak in July, although different RNA sequences appeared to have different shedding patterns. No significant associations were detected between sequence detection and birthing season, environmental temperature or humidity, and no signs of illness were detected in any of the bats in the colony during the period of sample collection

    A modified bacterial one-hybrid system yields improved quantitative models of transcription factor specificity

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    We examine the use of high-throughput sequencing on binding sites recovered using a bacterial one-hybrid (B1H) system and find that improved models of transcription factor (TF) binding specificity can be obtained compared to standard methods of sequencing a small subset of the selected clones. We can obtain even more accurate binding models using a modified version of B1H selection method with constrained variation (CV-B1H). However, achieving these improved models using CV-B1H data required the development of a new method of analysis—GRaMS (Growth Rate Modeling of Specificity)—that estimates bacterial growth rates as a function of the quality of the recognition sequence. We benchmark these different methods of motif discovery using Zif268, a well-characterized C2H2 zinc-finger TF on both a 28 bp randomized library for the standard B1H method and on 6 bp randomized library for the CV-B1H method for which 45 different experimental conditions were tested: five time points and three different IPTG and 3-AT concentrations. We find that GRaMS analysis is robust to the different experimental parameters whereas other analysis methods give widely varying results depending on the conditions of the experiment. Finally, we demonstrate that the CV-B1H assay can be performed in liquid media, which produces recognition models that are similar in quality to sequences recovered from selection on solid media

    A Reporter Screen in a Human Haploid Cell Line Identifies CYLD as a Constitutive Inhibitor of NF-κB

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    The development of forward genetic screens in human haploid cells has the potential to transform our understanding of the genetic basis of cellular processes unique to man. So far, this approach has been limited mostly to the identification of genes that mediate cell death in response to a lethal agent, likely due to the ease with which this phenotype can be observed. Here, we perform the first reporter screen in the near-haploid KBM7 cell line to identify constitutive inhibitors of NF-κB. CYLD was the only currently known negative regulator of NF-κB to be identified, thus uniquely distinguishing this gene. Also identified were three genes with no previous known connection to NF-κB. Our results demonstrate that reporter screens in haploid human cells can be applied to investigate the many complex signaling pathways that converge upon transcription factors

    Probing the SELEX Process with Next-Generation Sequencing

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    Background SELEX is an iterative process in which highly diverse synthetic nucleic acid libraries are selected over many rounds to finally identify aptamers with desired properties. However, little is understood as how binders are enriched during the selection course. Next-generation sequencing offers the opportunity to open the black box and observe a large part of the population dynamics during the selection process. Methodology We have performed a semi-automated SELEX procedure on the model target streptavidin starting with a synthetic DNA oligonucleotide library and compared results obtained by the conventional analysis via cloning and Sanger sequencing with next-generation sequencing. In order to follow the population dynamics during the selection, pools from all selection rounds were barcoded and sequenced in parallel. Conclusions High affinity aptamers can be readily identified simply by copy number enrichment in the first selection rounds. Based on our results, we suggest a new selection scheme that avoids a high number of iterative selection rounds while reducing time, PCR bias, and artifacts

    Fibroid explants reveal a higher sensitivity against MDM2-inhibitor nutlin-3 than matching myometrium

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    <p>Abstract</p> <p>Background</p> <p>Spontaneous cessation of growth is a frequent finding in uterine fibroids. Increasing evidence suggests an important role of cellular senescence in this growth control. Deciphering the underlying mechanisms of growth control that can be expected not only to shed light on the biology of the tumors but also to identify novel therapeutic targets.</p> <p>Methods</p> <p>We have analyzed uterine leiomyomas and matching normal tissue for the expression of p14<sup>Arf </sup>and used explants to see if reducing the MDM2 activity using the small-molecule inhibitor nutlin-3 can induce p53 and activate genes involved in senescence and/or apoptosis. For these studies quantitative real-time RT-PCR, Western blots, and immunohistochemistry were used. Statistical analyses were performed using the student's <it>t </it>test.</p> <p>Results</p> <p>An in depth analysis of 52 fibroids along with matching myometrium from 31 patients revealed in almost all cases a higher expression of p14<sup>Arf </sup>in the tumors than in the matching normal tissue. In tissue explants, treatment with the MDM2 inhibitor nutlin-3 induced apoptosis as well as senescence as revealed by a dose-dependent increase of the expression of <it>BAX </it>as well as of <it>p21</it>, respectively. Simultaneously, the expression of the proliferation marker Ki-67 drastically decreased. Western-blot analysis identified an increase of the p53 level as the most likely reason for the increased activity of its downstream markers <it>BAX </it>and <it>p21</it>. Because as a rule fibroids express much higher levels of p14<sup>Arf</sup>, a major negative regulator of MDM2, than matching myometrium it was then analyzed if fibroids are more sensitive against nutlin-3 treatment than matching myometrium. We were able to show that in most fibroids analyzed a higher sensibility than that of matching myometrium was noted with a corresponding increase of the p53 immunopositivity of the fibroid samples compared to those from myometrium.</p> <p>Conclusions</p> <p>The results show that uterine fibroids represent a cell population of advanced cellular age compared to matching myometrium. Moreover, the data point to members of the p53-network as to potential novel therapeutic targets for the treatment of uterine fibroids.</p

    FOXM1 binds directly to non-consensus sequences in the human genome.

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    BACKGROUND: The Forkhead (FKH) transcription factor FOXM1 is a key regulator of the cell cycle and is overexpressed in most types of cancer. FOXM1, similar to other FKH factors, binds to a canonical FKH motif in vitro. However, genome-wide mapping studies in different cell lines have shown a lack of enrichment of the FKH motif, suggesting an alternative mode of chromatin recruitment. We have investigated the role of direct versus indirect DNA binding in FOXM1 recruitment by performing ChIP-seq with wild-type and DNA binding deficient FOXM1. RESULTS: An in vitro fluorescence polarization assay identified point mutations in the DNA binding domain of FOXM1 that inhibit binding to a FKH consensus sequence. Cell lines expressing either wild-type or DNA binding deficient GFP-tagged FOXM1 were used for genome-wide mapping studies comparing the distribution of the DNA binding deficient protein to the wild-type. This shows that interaction of the FOXM1 DNA binding domain with target DNA is essential for recruitment. Moreover, analysis of the protein interactome of wild-type versus DNA binding deficient FOXM1 shows that the reduced recruitment is not due to inhibition of protein-protein interactions. CONCLUSIONS: A functional DNA binding domain is essential for FOXM1 chromatin recruitment. Even in FOXM1 mutants with almost complete loss of binding, the protein-protein interactions and pattern of phosphorylation are largely unaffected. These results strongly support a model whereby FOXM1 is specifically recruited to chromatin through co-factor interactions by binding directly to non-canonical DNA sequences.We would like to acknowledge the Genomics and bioinformatics core at the CRUK Research Institute for the Illumina sequencing and the Proteomics core for the LC/MS-MS protein analysis for the RIME experiments. We acknowledge the support from The University of Cambridge and Cancer Research UK. The Balasubramanian Laboratory is supported by core funding from Cancer Research UK (C14303/A17197). SB is a Wellcome Trust Principle Investigator.This is the final version of the article. It first appeared from BioMed Central via http://dx.doi.org/10.1186/s13059-015-0696-

    An improved predictive recognition model for Cys2-His2 zinc finger proteins

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    Cys2-His2 zinc finger proteins (ZFPs) are the largest family of transcription factors in higher metazoans. They also represent the most diverse family with regards to the composition of their recognition sequences. Although there are a number of ZFPs with characterized DNA-binding preferences, the specificity of the vast majority of ZFPs is unknown and cannot be directly inferred by homology due to the diversity of recognition residues present within individual fingers. Given the large number of unique zinc fingers and assemblies present across eukaryotes, a comprehensive predictive recognition model that could accurately estimate the DNA-binding specificity of any ZFP based on its amino acid sequence would have great utility. Toward this goal, we have used the DNA-binding specificities of 678 two-finger modules from both natural and artificial sources to construct a random forest-based predictive model for ZFP recognition. We find that our recognition model outperforms previously described determinant-based recognition models for ZFPs, and can successfully estimate the specificity of naturally occurring ZFPs with previously defined specificities
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