24 results on '"van Wageningen S"'
Search Results
2. MR1 encompasses at least six allele groups with coding region alterations
- Author
-
Rozemuller, E, Eckle, SBG, McLaughlin, I, Penning, M, Mulder, W, de Bruin, H, van Wageningen, S, Rozemuller, E, Eckle, SBG, McLaughlin, I, Penning, M, Mulder, W, de Bruin, H, and van Wageningen, S
- Abstract
Unlike classical HLA class I genes, MR1 is assumed to have limited polymorphic positions. We developed a MR1 specific PCR assay and sequenced 56 DNA samples from cells with a diverse set of HLA genotypes. In this relatively small panel we found six allele groups encoding for different MR1 proteins. The two most frequent allele groups found in this panel had a frequency of 71% (MR1*01) and 25% (MR1*02), respectively. Moreover, the panel contained many intronic SNPs and silent variants, with individual samples containing up to 15 heterozygous positions. The data presented here is consistent with marked variation in MR1.
- Published
- 2021
3. P705 HLA loss detection by NGS using a multiplex of 16 markers within the MHC region
- Author
-
Geerligs, J., Rond, L., Dadkhodaie, F., van de Pasch, L.A., Penning, M., and van Wageningen, S.
- Published
- 2023
- Full Text
- View/download PDF
4. O33 HLA common null allele detection using a fast and easy CRISPR-Cas assay
- Author
-
van Wageningen, S., Stokman, S., Dadkhodaie, F., Penning, M., and Steens, J.
- Published
- 2023
- Full Text
- View/download PDF
5. ID1 and ID2 are retinoic acid responsive genes and induce a G0/G1 accumulation in acute promyelocytic leukemia cells
- Author
-
Nigten, J, Breems-de Ridder, M C, Erpelinck-Verschueren, C A J, Nikoloski, G, van der Reijden, B A, van Wageningen, S, van Hennik, P B, de Witte, T, Löwenberg, B, and Jansen, J H
- Published
- 2005
- Full Text
- View/download PDF
6. Large-scale genetic perturbations reveal regulatory networks and an abundance of gene-specific repressors
- Author
-
Kemmeren, P.P.C.W., Sameith, K., van de Pasch, L.A.L., Benschop, J.J., Lenstra, T.L., Margaritis, A., O'Duibhir, E., Apweiler, E., van Wageningen, S., Ko, C.W., van Heesch, S.A.A.C., Kashani, M.M., Ampatziadis-Michailidis, G., Brok, M.O., Brabers, N.A.C.H., Miles, A.J., Bouwmeester, D., van Hooff, S.R., van Bakel, H.H.M.J., Sluiters, E.C., Bakker, L.V., Snel, B., Lijnzaad, P., van Leenen, D., Groot Koerkamp, M.J.A., Holstege, F.C.P., Theoretical Biology and Bioinformatics, Sub Theoretical Biology & Bioinformatics, Theoretical Biology and Bioinformatics, and Sub Theoretical Biology & Bioinformatics
- Subjects
Genetics ,Regulation of gene expression ,biology ,Biochemistry, Genetics and Molecular Biology(all) ,Saccharomyces cerevisiae ,Gene regulatory network ,Computational biology ,biology.organism_classification ,Interactome ,General Biochemistry, Genetics and Molecular Biology ,Chromatin ,Gene Knockout Techniques ,Genetic Techniques ,Transcription (biology) ,Gene Expression Regulation, Fungal ,Gene Regulatory Networks ,Transcriptome ,Transcription factor ,Gene ,Gene Deletion - Abstract
SummaryTo understand regulatory systems, it would be useful to uniformly determine how different components contribute to the expression of all other genes. We therefore monitored mRNA expression genome-wide, for individual deletions of one-quarter of yeast genes, focusing on (putative) regulators. The resulting genetic perturbation signatures reflect many different properties. These include the architecture of protein complexes and pathways, identification of expression changes compatible with viability, and the varying responsiveness to genetic perturbation. The data are assembled into a genetic perturbation network that shows different connectivities for different classes of regulators. Four feed-forward loop (FFL) types are overrepresented, including incoherent type 2 FFLs that likely represent feedback. Systematic transcription factor classification shows a surprisingly high abundance of gene-specific repressors, suggesting that yeast chromatin is not as generally restrictive to transcription as is often assumed. The data set is useful for studying individual genes and for discovering properties of an entire regulatory system.
- Published
- 2014
7. Large-scale genetic perturbations reveal regulatory networks and an abundance of gene-specific repressors
- Author
-
Theoretical Biology and Bioinformatics, Sub Theoretical Biology & Bioinformatics, Kemmeren, P.P.C.W., Sameith, K., van de Pasch, L.A.L., Benschop, J.J., Lenstra, T.L., Margaritis, A., O'Duibhir, E., Apweiler, E., van Wageningen, S., Ko, C.W., van Heesch, S.A.A.C., Kashani, M.M., Ampatziadis-Michailidis, G., Brok, M.O., Brabers, N.A.C.H., Miles, A.J., Bouwmeester, D., van Hooff, S.R., van Bakel, H.H.M.J., Sluiters, E.C., Bakker, L.V., Snel, B., Lijnzaad, P., van Leenen, D., Groot Koerkamp, M.J.A., Holstege, F.C.P., Theoretical Biology and Bioinformatics, Sub Theoretical Biology & Bioinformatics, Kemmeren, P.P.C.W., Sameith, K., van de Pasch, L.A.L., Benschop, J.J., Lenstra, T.L., Margaritis, A., O'Duibhir, E., Apweiler, E., van Wageningen, S., Ko, C.W., van Heesch, S.A.A.C., Kashani, M.M., Ampatziadis-Michailidis, G., Brok, M.O., Brabers, N.A.C.H., Miles, A.J., Bouwmeester, D., van Hooff, S.R., van Bakel, H.H.M.J., Sluiters, E.C., Bakker, L.V., Snel, B., Lijnzaad, P., van Leenen, D., Groot Koerkamp, M.J.A., and Holstege, F.C.P.
- Published
- 2014
8. 148 RAS synthetic lethal interactions from yeast to human cells
- Author
-
van Wageningen, S., primary, Prahallad, A., additional, Heynen, G., additional, Rothstein, R., additional, and Bernards, R., additional
- Published
- 2014
- Full Text
- View/download PDF
9. Unraveling signaling mysteries by expression profiling activated kinases
- Author
-
Waaijers, S., van Wageningen, S. (Thesis Advisor), Waaijers, S., and van Wageningen, S. (Thesis Advisor)
- Abstract
Signal transduction is indispensible for control of cell growth, differentiation, metabolism, and migration. Key regulators in signaling are protein kinases, a major superfamily of enzymes containing a kinase domain with a high degree of conservation across eukaryotes. Improper functioning of a protein kinase is commonly observed in diseases, especially cancer. Under normal conditions, they are capable of regulating the activity of proteins by attaching a phosphate group, mostly originating from adenosine triphosphate (ATP), to an amino acid with a free hydroxyl group; serine, threonine, or tyrosine. The simplest model organism to study eukaryotic protein kinases (ePKs) in is yeast, Saccharomyces cerevisiae (S. cerevisiae). It has a relatively small number of ePKs, namely 139, and is easy to manipulate and to keep under laboratory circumstances. Expression profiling by microarray can be used to study ePKs. This technique measures the relative abundance of mRNA. The method allows for clarification of the biological process in which an ePK is involved and of the mutual relationship among ePKs via clustering. A common strategy is to compare the transcriptome of a deletion mutant of a gene of interest with mRNA levels of wild type yeast. Expression profiling has been shown to be a useful tool when it comes to structure-function analysis of a large multisubunit complex, genetic epistasis with expression profiles as phenotype, and revealing the effects of regulatory kinase activity. Single deletions could not obtain an altered expression profile compared to wild type yeast for the majority of ePKs. Other attempts, like studying essential protein kinases with DAmP mutants, were also not sufficient to obtain specific expression signatures for all studied genes. A DAmP mutant has an antibiotics cassette in the 3 prime untranslated region of a specific gene, resulting in destabilization of its mRNA. Only two out of 20 DAmP mutants gave a specific expression signature. These m
- Published
- 2009
10. The transcription factor nuclear factor Y regulates the proliferation of myeloid progenitor cells
- Author
-
van Wageningen, S., primary, Nikoloski, G., additional, Vierwinden, G., additional, Knops, R., additional, van der Reijden, B. A., additional, and Jansen, J. H., additional
- Published
- 2008
- Full Text
- View/download PDF
11. Structure of the Schizosaccharomyces pombe Mediator subcomplex Med8C/18
- Author
-
Lariviere, L., primary, Seizl, M., additional, van Wageningen, S., additional, Rother, S., additional, van de Pasch, L., additional, Feldmann, H., additional, Strasser, K., additional, Hahn, S., additional, Holstege, F.C.P., additional, and Cramer, P., additional
- Published
- 2008
- Full Text
- View/download PDF
12. MR1 encompasses at least six allele groups with coding region alterations.
- Author
-
Rozemuller E, Eckle SBG, McLaughlin I, Penning M, Mulder W, de Bruin H, and van Wageningen S
- Subjects
- Alleles, Base Sequence, Humans, Minor Histocompatibility Antigens genetics, Minor Histocompatibility Antigens metabolism, Open Reading Frames, Histocompatibility Antigens Class I genetics
- Abstract
Unlike classical HLA class I genes, MR1 is assumed to have limited polymorphic positions. We developed a MR1 specific PCR assay and sequenced 56 DNA samples from cells with a diverse set of HLA genotypes. In this relatively small panel we found six allele groups encoding for different MR1 proteins. The two most frequent allele groups found in this panel had a frequency of 71% (MR1*01) and 25% (MR1*02), respectively. Moreover, the panel contained many intronic SNPs and silent variants, with individual samples containing up to 15 heterozygous positions. The data presented here is consistent with marked variation in MR1., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)
- Published
- 2021
- Full Text
- View/download PDF
13. Correction to: A role for the unfolded protein response stress sensor ERN1 in regulating the response to MEK inhibitors in KRAS mutant colon cancers.
- Author
-
Šuštić T, van Wageningen S, Bosdriesz E, Reid RJD, Dittmar J, Lieftink C, Beijersbergen RL, Wessels LFA, Rothstein R, and Bernards R
- Published
- 2021
- Full Text
- View/download PDF
14. RUNX2/CBFB modulates the response to MEK inhibitors through activation of receptor tyrosine kinases in KRAS-mutant colorectal cancer.
- Author
-
Šuštić T, Bosdriesz E, van Wageningen S, Wessels LFA, and Bernards R
- Abstract
Intrinsic and acquired resistances are major hurdles preventing the effective use of MEK inhibitors for treatment of colorectal cancer (CRC). Some 35-45% of colorectal cancers are KRAS-mutant and their treatment remains challenging as these cancers are refractory to MEK inhibitor treatment, because of feedback activation of receptor tyrosine kinases (RTKs). We reported previously that loss of ERN1 sensitizes a subset of KRAS-mutant colon cancer cells to MEK inhibition. Here we show that the loss of RUNX2 or its cofactor CBFB can confer MEK inhibitor resistance in CRC cells. Mechanistically, we find that cells with genetically ablated RUNX2 or CBFB activate multiple RTKs, which coincides with high SHP2 phosphatase activity, a phosphatase that relays signals from the cell membrane to downstream pathways governing growth and proliferation. Moreover, we show that high activity of SHP2 is causal to loss of RUNX2-induced MEK inhibitor resistance, as a small molecule SHP2 inhibitor reinstates sensitivity to MEK inhibitor in RUNX2 knockout cells. Our results reveal an unexpected role for loss of RUNX2/CBFB in regulating RTK activity in colon cancer, resulting in reduced sensitivity to MEK inhibitors., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)
- Published
- 2020
- Full Text
- View/download PDF
15. A role for the unfolded protein response stress sensor ERN1 in regulating the response to MEK inhibitors in KRAS mutant colon cancers.
- Author
-
Šuštić T, van Wageningen S, Bosdriesz E, Reid RJD, Dittmar J, Lieftink C, Beijersbergen RL, Wessels LFA, Rothstein R, and Bernards R
- Subjects
- Benzimidazoles pharmacology, Cell Line, Tumor, Colonic Neoplasms drug therapy, Endoplasmic Reticulum Stress, HEK293 Cells, Humans, MAP Kinase Kinase Kinases genetics, Proto-Oncogene Proteins c-jun genetics, Pyridones pharmacology, Pyrimidinones pharmacology, Unfolded Protein Response, Yeasts genetics, Antineoplastic Agents pharmacology, Colonic Neoplasms genetics, Endoribonucleases genetics, MAP Kinase Kinase Kinases antagonists & inhibitors, Protein Kinase Inhibitors pharmacology, Protein Serine-Threonine Kinases genetics, Proto-Oncogene Proteins p21(ras) genetics
- Abstract
Background: Mutations in KRAS are frequent in human cancer, yet effective targeted therapeutics for these cancers are still lacking. Attempts to drug the MEK kinases downstream of KRAS have had limited success in clinical trials. Understanding the specific genomic vulnerabilities of KRAS-driven cancers may uncover novel patient-tailored treatment options., Methods: We first searched for synthetic lethal (SL) genetic interactions with mutant RAS in yeast with the ultimate aim to identify novel cancer-specific targets for therapy. Our method used selective ploidy ablation, which enables replication of cancer-specific gene expression changes in the yeast gene disruption library. Second, we used a genome-wide CRISPR/Cas9-based genetic screen in KRAS mutant human colon cancer cells to understand the mechanistic connection between the synthetic lethal interaction discovered in yeast and downstream RAS signaling in human cells., Results: We identify loss of the endoplasmic reticulum (ER) stress sensor IRE1 as synthetic lethal with activated RAS mutants in yeast. In KRAS mutant colorectal cancer cell lines, genetic ablation of the human ortholog of IRE1, ERN1, does not affect growth but sensitizes to MEK inhibition. However, an ERN1 kinase inhibitor failed to show synergy with MEK inhibition, suggesting that a non-kinase function of ERN1 confers MEK inhibitor resistance. To investigate how ERN1 modulates MEK inhibitor responses, we performed genetic screens in ERN1 knockout KRAS mutant colon cancer cells to identify genes whose inactivation confers resistance to MEK inhibition. This genetic screen identified multiple negative regulators of JUN N-terminal kinase (JNK) /JUN signaling. Consistently, compounds targeting JNK/MAPK8 or TAK1/MAP3K7, which relay signals from ERN1 to JUN, display synergy with MEK inhibition., Conclusions: We identify the ERN1-JNK-JUN pathway as a novel regulator of MEK inhibitor response in KRAS mutant colon cancer. The notion that multiple signaling pathways can activate JUN may explain why KRAS mutant tumor cells are traditionally seen as highly refractory to MEK inhibitor therapy. Our findings emphasize the need for the development of new therapeutics targeting JUN activating kinases, TAK1 and JNK, to sensitize KRAS mutant cancer cells to MEK inhibitors.
- Published
- 2018
- Full Text
- View/download PDF
16. MAP3K1 and MAP2K4 mutations are associated with sensitivity to MEK inhibitors in multiple cancer models.
- Author
-
Xue Z, Vis DJ, Bruna A, Sustic T, van Wageningen S, Batra AS, Rueda OM, Bosdriesz E, Caldas C, Wessels LFA, and Bernards R
- Subjects
- Animals, Benzimidazoles pharmacology, Benzimidazoles therapeutic use, Breast Neoplasms genetics, Cell Line, Tumor, Colonic Neoplasms genetics, Female, Heterografts, Humans, Loss of Function Mutation, MAP Kinase Kinase 4 antagonists & inhibitors, MAP Kinase Kinase Kinase 1 antagonists & inhibitors, MAP Kinase Signaling System drug effects, Male, Mice, Inbred BALB C, Mice, Nude, Mitogen-Activated Protein Kinase Kinases antagonists & inhibitors, Prostatic Neoplasms genetics, Protein Kinase Inhibitors pharmacology, Breast Neoplasms drug therapy, Colonic Neoplasms drug therapy, Drug Resistance, Neoplasm genetics, MAP Kinase Kinase 4 genetics, MAP Kinase Kinase Kinase 1 genetics, Prostatic Neoplasms drug therapy, Protein Kinase Inhibitors therapeutic use
- Abstract
Activation of the mitogen-activated protein kinase (MAPK) pathway is frequent in cancer. Drug development efforts have been focused on kinases in this pathway, most notably on RAF and MEK. We show here that MEK inhibition activates JNK-JUN signaling through suppression of DUSP4, leading to activation of HER Receptor Tyrosine Kinases. This stimulates the MAPK pathway in the presence of drug, thereby blunting the effect of MEK inhibition. Cancers that have lost MAP3K1 or MAP2K4 fail to activate JNK-JUN. Consequently, loss-of-function mutations in either MAP3K1 or MAP2K4 confer sensitivity to MEK inhibition by disabling JNK-JUN-mediated feedback loop upon MEK inhibition. In a panel of 168 Patient Derived Xenograft (PDX) tumors, MAP3K1 and MAP2K4 mutation status is a strong predictor of response to MEK inhibition. Our findings suggest that cancers having mutations in MAP3K1 or MAP2K4, which are frequent in tumors of breast, prostate and colon, may respond to MEK inhibitors. Our findings also suggest that MAP3K1 and MAP2K4 are potential drug targets in combination with MEK inhibitors, in spite of the fact that they are encoded by tumor suppressor genes.
- Published
- 2018
- Full Text
- View/download PDF
17. A high-resolution gene expression atlas of epistasis between gene-specific transcription factors exposes potential mechanisms for genetic interactions.
- Author
-
Sameith K, Amini S, Groot Koerkamp MJ, van Leenen D, Brok M, Brabers N, Lijnzaad P, van Hooff SR, Benschop JJ, Lenstra TL, Apweiler E, van Wageningen S, Snel B, Holstege FC, and Kemmeren P
- Subjects
- Gene Expression Profiling, Gene Library, Gene Ontology, Molecular Sequence Annotation, Mutation, Saccharomyces cerevisiae metabolism, Saccharomyces cerevisiae Proteins metabolism, Transcription Factors metabolism, Epigenesis, Genetic, Saccharomyces cerevisiae genetics, Saccharomyces cerevisiae Proteins genetics, Transcription Factors genetics
- Abstract
Background: Genetic interactions, or non-additive effects between genes, play a crucial role in many cellular processes and disease. Which mechanisms underlie these genetic interactions has hardly been characterized. Understanding the molecular basis of genetic interactions is crucial in deciphering pathway organization and understanding the relationship between genotype, phenotype and disease., Results: To investigate the nature of genetic interactions between gene-specific transcription factors (GSTFs) in Saccharomyces cerevisiae, we systematically analyzed 72 GSTF pairs by gene expression profiling double and single deletion mutants. These pairs were selected through previously published growth-based genetic interactions as well as through similarity in DNA binding properties. The result is a high-resolution atlas of gene expression-based genetic interactions that provides systems-level insight into GSTF epistasis. The atlas confirms known genetic interactions and exposes new ones. Importantly, the data can be used to investigate mechanisms that underlie individual genetic interactions. Two molecular mechanisms are proposed, "buffering by induced dependency" and "alleviation by derepression"., Conclusions: These mechanisms indicate how negative genetic interactions can occur between seemingly unrelated parallel pathways and how positive genetic interactions can indirectly expose parallel rather than same-pathway relationships. The focus on GSTFs is important for understanding the transcription regulatory network of yeast as it uncovers details behind many redundancy relationships, some of which are completely new. In addition, the study provides general insight into the complex nature of epistasis and proposes mechanistic models for genetic interactions, the majority of which do not fall into easily recognizable within- or between-pathway relationships.
- Published
- 2015
- Full Text
- View/download PDF
18. Large-scale genetic perturbations reveal regulatory networks and an abundance of gene-specific repressors.
- Author
-
Kemmeren P, Sameith K, van de Pasch LA, Benschop JJ, Lenstra TL, Margaritis T, O'Duibhir E, Apweiler E, van Wageningen S, Ko CW, van Heesch S, Kashani MM, Ampatziadis-Michailidis G, Brok MO, Brabers NA, Miles AJ, Bouwmeester D, van Hooff SR, van Bakel H, Sluiters E, Bakker LV, Snel B, Lijnzaad P, van Leenen D, Groot Koerkamp MJ, and Holstege FC
- Subjects
- Gene Deletion, Gene Knockout Techniques, Gene Expression Regulation, Fungal, Gene Regulatory Networks, Genetic Techniques, Saccharomyces cerevisiae genetics, Transcriptome
- Abstract
To understand regulatory systems, it would be useful to uniformly determine how different components contribute to the expression of all other genes. We therefore monitored mRNA expression genome-wide, for individual deletions of one-quarter of yeast genes, focusing on (putative) regulators. The resulting genetic perturbation signatures reflect many different properties. These include the architecture of protein complexes and pathways, identification of expression changes compatible with viability, and the varying responsiveness to genetic perturbation. The data are assembled into a genetic perturbation network that shows different connectivities for different classes of regulators. Four feed-forward loop (FFL) types are overrepresented, including incoherent type 2 FFLs that likely represent feedback. Systematic transcription factor classification shows a surprisingly high abundance of gene-specific repressors, suggesting that yeast chromatin is not as generally restrictive to transcription as is often assumed. The data set is useful for studying individual genes and for discovering properties of an entire regulatory system., (Copyright © 2014 Elsevier Inc. All rights reserved.)
- Published
- 2014
- Full Text
- View/download PDF
19. Functional overlap and regulatory links shape genetic interactions between signaling pathways.
- Author
-
van Wageningen S, Kemmeren P, Lijnzaad P, Margaritis T, Benschop JJ, de Castro IJ, van Leenen D, Groot Koerkamp MJ, Ko CW, Miles AJ, Brabers N, Brok MO, Lenstra TL, Fiedler D, Fokkens L, Aldecoa R, Apweiler E, Taliadouros V, Sameith K, van de Pasch LA, van Hooff SR, Bakker LV, Krogan NJ, Snel B, and Holstege FC
- Subjects
- Epistasis, Genetic, Gene Expression Profiling, Phosphoric Monoester Hydrolases genetics, Phosphoric Monoester Hydrolases metabolism, Phosphorylation, Phosphotransferases genetics, Phosphotransferases metabolism, Saccharomyces cerevisiae genetics, Saccharomyces cerevisiae metabolism, Signal Transduction
- Abstract
To understand relationships between phosphorylation-based signaling pathways, we analyzed 150 deletion mutants of protein kinases and phosphatases in S. cerevisiae using DNA microarrays. Downstream changes in gene expression were treated as a phenotypic readout. Double mutants with synthetic genetic interactions were included to investigate genetic buffering relationships such as redundancy. Three types of genetic buffering relationships are identified: mixed epistasis, complete redundancy, and quantitative redundancy. In mixed epistasis, the most common buffering relationship, different gene sets respond in different epistatic ways. Mixed epistasis arises from pairs of regulators that have only partial overlap in function and that are coupled by additional regulatory links such as repression of one by the other. Such regulatory modules confer the ability to control different combinations of processes depending on condition or context. These properties likely contribute to the evolutionary maintenance of paralogs and indicate a way in which signaling pathways connect for multiprocess control., (Copyright © 2010 Elsevier Inc. All rights reserved.)
- Published
- 2010
- Full Text
- View/download PDF
20. Functional organization of the S. cerevisiae phosphorylation network.
- Author
-
Fiedler D, Braberg H, Mehta M, Chechik G, Cagney G, Mukherjee P, Silva AC, Shales M, Collins SR, van Wageningen S, Kemmeren P, Holstege FC, Weissman JS, Keogh MC, Koller D, Shokat KM, and Krogan NJ
- Subjects
- Acetylation, Histones metabolism, Protein Kinases metabolism, Phosphorylation, Saccharomyces cerevisiae metabolism, Saccharomyces cerevisiae Proteins metabolism, Signal Transduction
- Abstract
Reversible protein phosphorylation is a signaling mechanism involved in all cellular processes. To create a systems view of the signaling apparatus in budding yeast, we generated an epistatic miniarray profile (E-MAP) comprised of 100,000 pairwise, quantitative genetic interactions, including virtually all protein and small-molecule kinases and phosphatases as well as key cellular regulators. Quantitative genetic interaction mapping reveals factors working in compensatory pathways (negative genetic interactions) or those operating in linear pathways (positive genetic interactions). We found an enrichment of positive genetic interactions between kinases, phosphatases, and their substrates. In addition, we assembled a higher-order map from sets of three genes that display strong interactions with one another: triplets enriched for functional connectivity. The resulting network view provides insights into signaling pathway regulation and reveals a link between the cell-cycle kinase, Cak1, the Fus3 MAP kinase, and a pathway that regulates chromatin integrity during transcription by RNA polymerase II.
- Published
- 2009
- Full Text
- View/download PDF
21. Structure-system correlation identifies a gene regulatory Mediator submodule.
- Author
-
Larivière L, Seizl M, van Wageningen S, Röther S, van de Pasch L, Feldmann H, Strässer K, Hahn S, Holstege FC, and Cramer P
- Subjects
- Electrophoresis, Polyacrylamide Gel, Gene Expression Profiling, Gene Expression Regulation, Fungal, Mass Spectrometry, Mediator Complex, Models, Biological, Models, Molecular, Protein Structure, Tertiary, Saccharomyces cerevisiae genetics, Saccharomyces cerevisiae metabolism, Saccharomyces cerevisiae Proteins metabolism, Structure-Activity Relationship, Transcription Factors metabolism, Transcription, Genetic, Gene Deletion, Saccharomyces cerevisiae Proteins chemistry, Saccharomyces cerevisiae Proteins genetics, Transcription Factors chemistry, Transcription Factors genetics
- Abstract
A combination of crystallography, biochemistry, and gene expression analysis identifies the coactivator subcomplex Med8C/18/20 as a functionally distinct submodule of the Mediator head module. Med8C forms a conserved alpha-helix that tethers Med18/20 to the Mediator. Deletion of Med8C in vivo results in dissociation of Med18/20 from Mediator and in loss of transcription activity of extracts. Deletion of med8C, med18, or med20 causes similar changes in the yeast transcriptome, establishing Med8C/18/20 as a predominantly positive, gene-specific submodule required for low transcription levels of nonactivated genes, including conjugation genes. The presented structure-based system perturbation is superior to gene deletion analysis of gene regulation.
- Published
- 2008
- Full Text
- View/download PDF
22. Gene transactivation without direct DNA binding defines a novel gain-of-function for PML-RARalpha.
- Author
-
van Wageningen S, Breems-de Ridder MC, Nigten J, Nikoloski G, Erpelinck-Verschueren CA, Löwenberg B, de Witte T, Tenen DG, van der Reijden BA, and Jansen JH
- Subjects
- CCAAT-Binding Factor genetics, CCAAT-Binding Factor metabolism, Cell Line, Tumor, DNA metabolism, Humans, Inhibitor of Differentiation Protein 1 genetics, Inhibitor of Differentiation Protein 1 metabolism, Leukemia, Promyelocytic, Acute genetics, Leukemia, Promyelocytic, Acute pathology, Molecular Sequence Data, Promoter Regions, Genetic genetics, Protein Binding, Receptors, Retinoic Acid genetics, Receptors, Retinoic Acid metabolism, Retinoic Acid Receptor alpha, Retinoid X Receptors genetics, Retinoid X Receptors metabolism, Sp1 Transcription Factor genetics, Sp1 Transcription Factor metabolism, Transcriptional Activation drug effects, Tretinoin pharmacology, Up-Regulation, DNA genetics, Oncogene Proteins, Fusion genetics, Oncogene Proteins, Fusion metabolism, Transcriptional Activation genetics
- Abstract
PML-RARalpha is the causative oncogene in 5% to 10% of the cases of acute myeloid leukemia. At physiological concentrations of retinoic acid, PML-RARalpha silences RARalpha target genes, blocking differentiation of the cells. At high concentrations of ligand, it (re)activates the transcription of target genes, forcing terminal differentiation. The study of RARalpha target genes that mediate this differentiation has identified several genes that are important for proliferation and differentiation control in normal and malignant hematopoietic cells. In this paper, we show that the PML-RARalpha fusion protein not only interferes with the transcription of regular RARalpha target genes. We show that the ID1 and ID2 promoters are activated by PML-RARalpha but, unexpectedly, not by wild-type RARalpha/RXR. Our data support a model in which the PML-RARalpha fusion protein regulates a novel class of target genes by interaction with the Sp1 and NF-Y transcription factors, without directly binding to the DNA, defining a gain-of-function for the oncoprotein.
- Published
- 2008
- Full Text
- View/download PDF
23. Isolation of FRET-positive cells using single 408-nm laser flow cytometry.
- Author
-
van Wageningen S, Pennings AH, van der Reijden BA, Boezeman JB, de Lange F, and Jansen JH
- Subjects
- Bacterial Proteins metabolism, Cell Line, Tumor, Cell Separation instrumentation, Flow Cytometry instrumentation, Fluorescence Resonance Energy Transfer instrumentation, Green Fluorescent Proteins metabolism, Humans, Luminescent Proteins metabolism, Microscopy, Confocal, Bacterial Proteins chemistry, Cell Separation methods, Flow Cytometry methods, Fluorescence Resonance Energy Transfer methods, Green Fluorescent Proteins chemistry, Luminescent Proteins chemistry
- Abstract
Background: Flow cytometry may be used to isolate large amounts of living, fluorescently labeled cells. Certain fluorescent labels, like enhanced cyan fluorescent protein (ECFP) and enhanced yellow fluorescent protein (EYFP), allow the assessment of direct protein-protein interaction in situ, by fluorescence resonance energy transfer (FRET). However, current flow cytometric methods either require elaborate technical adaptations or, using a single laser protocol, are hampered by background signal. We optimized a single 408-nm laser protocol to detect FRET between ECFP/EYFP-tagged proteins., Methods: Cell lines stably expressing ECFP and/or EYFP or an EYFP-ECFP fusion protein were used to design the settings for the flow cytometer to detect FRET-positive cells using a single 408-nm laser. Using these settings, interactions between the subunits of the transcription factor NF-Y were studied., Results: Flow cytometric analysis of the cells expressing an EYFP-ECFP fusion protein yielded a discrete FRET-positive population. Using the same settings, in cells expressing NF-YB-CFP and NF-YC-YFP fusion proteins, FRET could also be detected. These cells were sorted and FRET was confirmed by confocal microscopy., Conclusion: FRET-positive cells, expressing ECFP- and EYFP-tagged proteins, can be detected using single 408-nm laser excitation, with low background signal. This allows high-throughput analysis and isolation of viable FRET-positive and -negative cells for subsequent biological experiments.
- Published
- 2006
- Full Text
- View/download PDF
24. A lophotrochozoan twist gene is expressed in the ectomesoderm of the gastropod mollusk Patella vulgata.
- Author
-
Nederbragt AJ, Lespinet O, van Wageningen S, van Loon AE, Adoutte A, and Dictus WJ
- Subjects
- Amino Acid Sequence, Animals, Base Sequence, Blotting, Southern, DNA genetics, In Situ Hybridization, Molecular Sequence Data, Mollusca embryology, Phylogeny, Reverse Transcriptase Polymerase Chain Reaction, Sequence Homology, Amino Acid, Twist-Related Protein 1, Ectoderm metabolism, Gene Expression Regulation, Developmental, Mesoderm metabolism, Mollusca genetics, Nuclear Proteins genetics, Transcription Factors
- Abstract
The twist gene is known to be involved in mesoderm formation in two of the three clades of bilaterally symmetrical animals: viz. deuterostomes (such as vertebrates) and ecdysozoans (such as arthropods and nematodes). There are currently no data on the spatiotemporal expression of this gene in the third clade, the lophotrochozoans (such as mollusks and annelids). To approach the question of mesoderm homology across bilaterians, we decided to analyze orthologs of this gene in the gastropod mollusk Patella vulgata that belongs to the lophotrochozoans. We present here the cloning, characterization, and phylogenetic analysis of a Patella twist ortholog, Pv-twi, and determine the early spatiotemporal expression pattern of this gene. Pv-twi expression was found in the trochophore larva in a subset of the ectomesoderm, one of the two sources of mesoderm in Patella. These data support the idea that twist genes were ancestrally involved in mesoderm differentiation. The absence of Pv-twi in the second mesodermal source, the endomesoderm, suggests that also other genes must be involved in lophotrochozoan mesoderm differentiation. It therefore remains a question if the mesoderm of all bilaterians is homologous.
- Published
- 2002
- Full Text
- View/download PDF
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.