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Search Results: 1 - 10 of 129438 matches for " Christopher T Workman "
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Synthetic Promoter Library for Modulation of Actinorhodin Production in Streptomyces coelicolor A3(2)
Sujata Vijay Sohoni, Alessandro Fazio, Christopher T. Workman, Ivan Mijakovic, Anna Eliasson Lantz
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0099701
Abstract: The objective of this study was the application of the synthetic promoter library (SPL) technology for modulation of actinorhodin production in Streptomyces coelicolor A3(2). The SPL technology was used to optimize the expression of a pathway specific positive transcriptional regulator ActII orf4, which activates the transcription of the S. coelicolor actinorhodin biosynthetic gene cluster. The native actII orf4 promoter was replaced with synthetic promoters, generating a S. coelicolor library with a broad range of expression levels of actII orf4. The resulting library was screened based on the yield of actinorhodin. Selected strains were further physiologically characterized. One of the strains from the library, ScoSPL20, showed considerably higher yield of actinorhodin and final actinorhodin titer, compared to S. coelicolor wild type and S. coelicolor with actII orf4 expressed from a strong constitutive promoter. ScoSPL20 demonstrated exceptional productivity despite having a comparatively weak expression from the promoter. Interestingly, the ScoSPL20 promoter was activated at a much earlier stage of growth compared to the wild type, demonstrating the advantage of fine-tuning and temporal tuning of gene expression in metabolic engineering. Transcriptome studies were performed in exponential and actinorhodin-producing phase of growth to compare gene expression between ScoSPL20 and the wild type. To our knowledge, this is the first successful application of the SPL technology for secondary metabolite production in filamentous bacteria.
Transcription factor control of growth rate dependent genes in Saccharomyces cerevisiae: A three factor design
Alessandro Fazio, Michael C Jewett, Pascale Daran-Lapujade, Roberta Mustacchi, Renata Usaite, Jack T Pronk, Christopher T Workman, Jens Nielsen
BMC Genomics , 2008, DOI: 10.1186/1471-2164-9-341
Abstract: We identified 268 growth rate dependent genes, independent of nutrient limitation and oxygen availability. The transcriptional response was used to identify key areas in metabolism around which mRNA expression changes are significantly associated. Among key metabolic pathways, this analysis revealed de novo synthesis of pyrimidine ribonucleotides and ATP producing and consuming reactions at fast cellular growth. By scoring the significance of overlap between growth rate dependent genes and known transcription factor target sets, transcription factors that coordinate balanced growth were also identified. Our analysis shows that Fhl1, Rap1, and Sfp1, regulating protein biosynthesis, have significantly enriched target sets for genes up-regulated with increasing growth rate. Cell cycle regulators, such as Ace2 and Swi6, and stress response regulators, such as Yap1, were also shown to have significantly enriched target sets.Our work, which is the first genome-wide gene expression study to investigate specific growth rate and consider the impact of oxygen availability, provides a more conservative estimate of growth rate dependent genes than previously reported. We also provide a global view of how a small set of transcription factors, 13 in total, contribute to control of cellular growth rate. We anticipate that multi-factorial designs will play an increasing role in elucidating cellular regulation.Regulation of cell growth is of crucial importance for the survival of all living cells. Much effort, therefore, has focused on understanding the mechanisms that control how cells achieve balanced growth, e.g. control of the cell cycle and biosynthesis of cellular building blocks. To date, DNA microarray technology [1,2] has had a considerable impact in defining causal relationships between different growth conditions and the transcriptional response of cells. A number of previous studies in S. cerevisiae have focused on the genome-wide transcriptional response of cells to nut
End-point Estimates and Multi-parameter Paraproducts on Higher Dimensional Tori
John T. Workman
Mathematics , 2008,
Abstract: Analogues of multi-paramter multiplier operators on R^d are defined on the torus T^d. It is shown that these operators satisfy the classical Coifman-Meyer theorem. In addition, L log L and L (log L)^n end-point estimates are proved.
Bourgain's Entropy Estimates Revisited
John T. Workman
Mathematics , 2006,
Abstract: The following is a near complete set of notes of Bourgain's 1988 paper "Almost Sure Convergence and Bounded Entropy." Both entropy results are treated, as is one application. The proofs here are essentially those of Bourgain's.
Equitoxic Doses of 5-Azacytidine and 5-Aza-2′Deoxycytidine Induce Diverse Immediate and Overlapping Heritable Changes in the Transcriptome
Xiangning Qiu,Christoffer Hother,Ulrik M. Ralfki?r,Alexandra S?gaard,Qianjin Lu,Christopher T. Workman,Gangning Liang,Peter A. Jones,Kirsten Gr?nb?k
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0012994
Abstract: The hypomethylating agent 5-Azacytidine (5-Aza-CR) is the first drug to prolong overall survival in patients with myelodysplastic syndrome (MDS). Surprisingly, the deoxyribonucleoside analog 5-Aza-2′deoxycytidine (5-Aza-CdR) did not have a similar effect on survival in a large clinical trial. Both drugs are thought to exert their effects after incorporation into DNA by covalent binding of DNA methyltransferase (DNMT). While 5-Aza-CdR is incorporated into only DNA, 5-Aza-CR is also incorporated into RNA. Here, we have analyzed whether this difference in nucleic acid incorporation may influence the capacities of these drugs to regulate the expression of mRNA and microRNAs (miRNA), which may potentially affect the activities of the drugs in patients.
Minimising Immunohistochemical False Negative ER Classification Using a Complementary 23 Gene Expression Signature of ER Status
Qiyuan Li,Aron C. Eklund,Nicolai Juul,Benjamin Haibe-Kains,Christopher T. Workman,Andrea L. Richardson,Zoltan Szallasi,Charles Swanton
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0015031
Abstract: Expression of the oestrogen receptor (ER) in breast cancer predicts benefit from endocrine therapy. Minimising the frequency of false negative ER status classification is essential to identify all patients with ER positive breast cancers who should be offered endocrine therapies in order to improve clinical outcome. In routine oncological practice ER status is determined by semi-quantitative methods such as immunohistochemistry (IHC) or other immunoassays in which the ER expression level is compared to an empirical threshold[1], [2]. The clinical relevance of gene expression-based ER subtypes as compared to IHC-based determination has not been systematically evaluated. Here we attempt to reduce the frequency of false negative ER status classification using two gene expression approaches and compare these methods to IHC based ER status in terms of predictive and prognostic concordance with clinical outcome.
Integrative analysis for finding genes and networks involved in diabetes and other complex diseases
Regine Bergholdt, Zenia M St?rling, Kasper Lage, E Olof Karlberg, Páll í ólason, Mogens Aalund, J?rn Nerup, S?ren Brunak, Christopher T Workman, Flemming Pociot
Genome Biology , 2007, DOI: 10.1186/gb-2007-8-11-r253
Abstract: Complex traits like type 1 diabetes (T1D) are generally believed to be under the influence of multiple genes interacting with each other to confer disease susceptibility and/or protection. Identification of susceptibility genes in complex genetic diseases, however, poses many challenging problems. The contribution from single genes is often limited and genetic studies generally do not offer clues about the functional context of a gene associated with a complex disorder. A recent report demonstrated the feasibility of constructing functional human gene networks (using, for example, expression and Gene Ontology (GO) data [1]), and using these in prioritizing positional candidate genes from non-interacting susceptibility loci for various heritable disorders [2]. It was shown that the obvious candidate genes were not always involved, and that taking an unbiased approach in assessing candidate genes using functional networks may result in new, non-obvious hypotheses that are statistically significant.One of the strongest indications of functional association is the presence of a physical interaction between proteins [3] and several reports have shown that proteins involved in the same phenotype are likely to be part of the same functional module (that is, protein sub-network) [4-6]. With this in mind, it seems reasonable to expect that, in many cases, components contributing to the same complex diseases will be members of the same functional modules, especially if the disease is associated with multiple genetic loci that show statistical indication for epistasis. This indicates that in the case of complex disorders a feasible strategy would be to search for groups of interacting proteins that together lead to significant association with the disease in question. However, a strategy searching for loci showing genetic interaction (epistasis) integrated with a search for protein networks spanning the epistatic regions and subsequent significance ranking of these networks ha
Dynamic summarization of bibliographic-based data
T Workman, John F Hurdle
BMC Medical Informatics and Decision Making , 2011, DOI: 10.1186/1472-6947-11-6
Abstract: We developed a flexible algorithm named Combo that combines three statistical metrics, the Kullback-Leibler Divergence (KLD), Riloff's RlogF metric (RlogF), and a new metric called PredScal, to automatically identify salient data in bibliographic text. We downloaded citations from a PubMed search query addressing the genetic etiology of bladder cancer. The citations were processed with SemRep, an NLM rule-based application that produces semantic predications. SemRep output was processed by Combo, in addition to the standard Semantic MEDLINE genetics schema and independently by the two individual KLD and RlogF metrics. We evaluated each summarization method using an existing reference standard within the task-based context of genetic database curation.Combo asserted 74 genetic entities implicated in bladder cancer development, whereas the traditional schema asserted 10 genetic entities; the KLD and RlogF metrics individually asserted 77 and 69 genetic entities, respectively. Combo achieved 61% recall and 81% precision, with an F-score of 0.69. The traditional schema achieved 23% recall and 100% precision, with an F-score of 0.37. The KLD metric achieved 61% recall, 70% precision, with an F-score of 0.65. The RlogF metric achieved 61% recall, 72% precision, with an F-score of 0.66.Semantic MEDLINE summarization using the new Combo algorithm outperformed a conventional summarization schema in a genetic database curation task. It potentially could streamline information acquisition for other needs without having to hand-build multiple saliency schemas.The continued growth of bibliographic databases creates challenges to users practicing traditional information retrieval (IR) techniques. Standard search techniques, when applied to large databases such as PubMed, often return large, unmanageable lists of citations that do not fulfill the searcher's information needs [1,2]. This problematic issue impedes many tasks, including secondary genetic database development. Databas
Chromatin Proteins: Key Responders to Stress
Karen T. Smith,Jerry L. Workman
PLOS Biology , 2012, DOI: 10.1371/journal.pbio.1001371
Abstract: Environments can be ever-changing and stresses are commonplace. In order for organisms to survive, they need to be able to respond to change and adapt to new conditions. Fortunately, many organisms have systems in place that enable dynamic adaptation to immediate stresses and changes within the environment. Much of this cellular response is coordinated by modulating the structure and accessibility of the genome. In eukaryotic cells, the genome is packaged and rolled up by histone proteins to create a series of DNA/histone core structures known as nucleosomes; these are further condensed into chromatin. The degree and nature of the condensation can in turn determine which genes are transcribed. Histones can be modified chemically by a large number of proteins that are thereby responsible for dynamic changes in gene expression. In this Primer we discuss findings from a study published in this issue of PLoS Biology by Weiner et al. that highlight how chromatin structure and chromatin binding proteins alter transcription in response to environmental changes and stresses. Their study reveals the importance of chromatin in mediating the speed and amplitude of stress responses in cells and suggests that chromatin is a critically important component of the cellular response to stress.
Chromatin Proteins: Key Responders to Stress
Karen T. Smith,Jerry L. Workman
PLOS Biology , 2012, DOI: 10.1371/journal.pbio.1001371
Abstract: Environments can be ever-changing and stresses are commonplace. In order for organisms to survive, they need to be able to respond to change and adapt to new conditions. Fortunately, many organisms have systems in place that enable dynamic adaptation to immediate stresses and changes within the environment. Much of this cellular response is coordinated by modulating the structure and accessibility of the genome. In eukaryotic cells, the genome is packaged and rolled up by histone proteins to create a series of DNA/histone core structures known as nucleosomes; these are further condensed into chromatin. The degree and nature of the condensation can in turn determine which genes are transcribed. Histones can be modified chemically by a large number of proteins that are thereby responsible for dynamic changes in gene expression. In this Primer we discuss findings from a study published in this issue of PLoS Biology by Weiner et al. that highlight how chromatin structure and chromatin binding proteins alter transcription in response to environmental changes and stresses. Their study reveals the importance of chromatin in mediating the speed and amplitude of stress responses in cells and suggests that chromatin is a critically important component of the cellular response to stress.
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