15 research outputs found
Kinetische und Mechanistische Charakterisierung eines Diels-Alderase-Ribozyms
Zusammenfassung Stefanie Kraut, Diplom-Lebensmittelchemikerin Kinetische und Mechanistische Charakterisierung eines Diels Alderase-Ribozyms 1. Gutachter: Prof. Dr. Andres JĂ€schke, 2. Gutachter: Prof. Dr. Stefan Wölfl Mit der Entdeckung der Ribozyme als katalytisch-aktive RNAs entstand mit der âRNA-Weltâ-Hypothese ein neues VerstĂ€ndnis ĂŒber die Entstehung des Lebens. RNA kann demnach genetische Information codieren und speichern, sowie katalytische Funktionen in Zellen ĂŒbernehmen. Die Entwicklung von in vitro-Selektionstechniken ermöglichte die Selektion synthetischer Ribozyme mit groĂem katalytischem Potential. Das in unserer Gruppe selektierte Diels-Alderase-Ribozym katalysiert stereoselektiv neue Kohlenstoff-Kohlenstoff-Bindungen zwischen einem Anthracen und einem Maleimid. In der vorliegenden Arbeit wurde das Diels-Alderase-Ribozym auf seine kinetische und mechanistische Funktionsweise untersucht. In der Kristallstruktur des Diels-Alderase-Ribozyms wurden divalente Ionen-bindungsstellen identifiziert. Im ersten Teil der Arbeit wurde der Einfluss divalenter Ionen auf die katalytische Ribozym-AktivitĂ€t mit einem UV/VIS-spektroskopischen Assay quantitativ untersucht. Dabei konnte gezeigt werden, dass fĂŒr die vollstĂ€ndige katalytische AktivitĂ€t eine gröĂere Anzahl an divalenten Ionen neben denen zur Besetzung der hochaffinen Bindungsstellen erforderlich sind. Mn2+-Ionen als Substitution von Mg2+-Ionen fĂŒhrten zur Reduktion der katalytischen Ribozym-AktivitĂ€t auf die HĂ€lfte. Obwohl Cd2+-Ionen die höchste BindungsaffinitĂ€t aufwiesen, trat keinerlei Ribozym-AktivitĂ€t auf. Die quantifizierende Analyse der Diels-Alder-Reaktionen mittels HPLC (Hochleistungs-FlĂŒssigkeits-Chromatographie) zeigte, dass etwa die HĂ€lfte des konsumierten Anthracen-Substrats nicht zu Diels-Alder-Produkt reagierte. Zur AufklĂ€rung möglicher Nebenreaktionen wurde die sensitive, hochauflösende MolekĂŒlmassen-Bestimmung mittels LC-MS (HPLC-Massenspektrometrie) fĂŒr die Diels-Alder-Reaktion etabliert. Sauerstoff-Addukte und Dimere der Anthracen-Komponente konnten identifiziert werden, die auch eine Bedeutung in Nebenreaktionen haben könnten. In weiterfĂŒhrenden Studien sollte dies noch genauer untersucht werden. Wasserstoff-BrĂŒcken-Bindungen (H BrĂŒcken) wurden aus der Kristallstruktur innerhalb der katalytischen Tasche des Ribozyms und zwischen der katalytischen Tasche und dem Diels-Alder-Produkt abgeleitet. Ein Teil dieser Arbeit umfasste die AufklĂ€rung der Bedeutung der H-BrĂŒcken zur StabilitĂ€t, katalytischen Ribozym-AktivitĂ€t und hohen Produkt-Inhibition. Durch atomare Mutagenese eingefĂŒhrte Nukleotid-Modifikationen im Ribozym wurden zur Störung der H-BrĂŒcken eingesetzt. Die Effekte dieser Störungen wurden mit dem chemischen Blei-Ionen Probing und einem radioaktiven gelelektrophoretischen Assay analysiert. Die strukturelle Analyse zwischen dem Wildtyp und einem modifizierten Ribozym mit gestörter H-BrĂŒcke, die die Verbindung zwischen âDachâ und âRĂŒckgratâ der katalytischen Tasche bildet, ergab eine Ă€hnliche Gesamtstruktur der Ribozyme. Das modifizierte Ribozym konnte jedoch in Anwesenheit von Diels-Alder-Produkt und Mg2+-Ionen keine Strukturstabilisierung ausbilden. Aus diesem Verhalten konnte die hohe Relevanz dieser einen H-BrĂŒcke und deren nötige prĂ€zise Positionierung zur Ausbildung der intakten katalytischen Tasche abgeleitet werden. Die Doppelmutanten wiesen nur 4-5% der Wildtyp-AktivitĂ€t auf, was die hohe Relevanz der H-BrĂŒcken zwischen Ribozym und Diels-Alder-Produkt fĂŒr die katalytische AktivitĂ€t indizierte. Aus dem Vergleich der Einzel- und Doppelmutanten wurde der additive Beitrag beider H-BrĂŒcken zur katalytischen AktivitĂ€t des Ribozyms abgeleitet. Die Ribozym - Produkt H-BrĂŒcken konnten mittels UV/VIS-Spektroskopie als Verursacher der hohen Produkt-Inhibition identifiziert werden. Diese Arbeit konnte das VerstĂ€ndnis der Funktionsweise des Diels-Alderase-Ribozyms in Bezug der H-BrĂŒcken und divalenten Ionen auf die StabilitĂ€t und die katalytische AktivitĂ€t vertiefen. Mit der Etablierung der LC-MS-Methode fĂŒr Diels-Alder-Reaktionen wurde die Grundlage zur hochauflösenden massenspektrometrischen Analyse der Reaktionen gelegt
Three critical hydrogen bonds determine the catalytic activity of the DielsâAlderase ribozyme
Compared to protein enzymes, our knowledge about how RNA accelerates chemical reactions is rather limited. The crystal structures of a ribozyme that catalyzes DielsâAlder reactions suggest a rich tertiary architecture responsible for catalysis. In this study, we systematically probe the relevance of crystallographically observed ground-state interactions for catalytic function using atomic mutagenesis in combination with various analytical techniques. The largest energetic contribution apparently arises from the precise shape complementarity between transition state and catalytic pocket: A single point mutant that folds correctly into the tertiary structure but lacks one H-bond that normally stabilizes the pocket is completely inactive. In the rate-limiting chemical step, the dienophile is furthermore activated by two weak H-bonds that contribute âŒ7â8âkJ/mol to transition state stabilization, as indicated by the 25-fold slower reaction rates of deletion mutants. These H-bonds are also responsible for the tight binding of the DielsâAlder product by the ribozyme that causes product inhibition. For high catalytic activity, the ribozyme requires a fine-tuned balance between rigidity and flexibility that is determined by the combined action of one inter-strand H-bond and one magnesium ion. A sharp 360° turn reminiscent of the T-loop motif observed in tRNA is found to be important for catalytic function
Cellular Differentiation of Human Monocytes Is Regulated by Time-Dependent Interleukin-4 Signaling and the Transcriptional Regulator NCOR2.
Human in vitro generated monocyte-derived dendritic cells (moDCs) and macrophages are used clinically, e.g., to induce immunity against cancer. However, their physiological counterparts, ontogeny, transcriptional regulation, and heterogeneity remains largely unknown, hampering their clinical use. High-dimensional techniques were used to elucidate transcriptional, phenotypic, and functional differences between human in vivo and in vitro generated mononuclear phagocytes to facilitate their full potential in the clinic. We demonstrate that monocytes differentiated by macrophage colony-stimulating factor (M-CSF) or granulocyte macrophage colony-stimulating factor (GM-CSF) resembled in vivo inflammatory macrophages, while moDCs resembled in vivo inflammatory DCs. Moreover, differentiated monocytes presented with profound transcriptomic, phenotypic, and functional differences. Monocytes integrated GM-CSF and IL-4 stimulation combinatorically and temporally, resulting in a mode- and time-dependent differentiation relying on NCOR2. Finally, moDCs are phenotypically heterogeneous and therefore necessitate the use of high-dimensional phenotyping to open new possibilities for better clinical tailoring of these cellular therapies
Swarm Learning for decentralized and confidential clinical machine learning
Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes3. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation4,5. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learningâa decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine
Swarm Learning for decentralized and confidential clinical machine learning
Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learningâa decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine
Characterizing multiple metal ion binding sites within a ribozyme by cadmiumâinduced EPR silencing
The FAK inhibitor BI 853520 exerts anti-tumor effects in breast cancer.
Focal adhesion kinase (FAK) is a cytoplasmic tyrosine kinase that regulates a plethora of downstream signaling pathways essential for cell migration, proliferation and death, processes that are exploited by cancer cells during malignant progression. These well-established tumorigenic activities, together with its high expression and activity in different cancer types, highlight FAK as an attractive target for cancer therapy. We have assessed and characterized the therapeutic potential and the biological effects of BI 853520, a novel small chemical inhibitor of FAK, in several preclinical mouse models of breast cancer. Treatment with BI 853520 elicits a significant reduction in primary tumor growth caused by an anti-proliferative activity by BI 853520. In contrast, BI 853520 exerts effects with varying degrees of robustness on the different stages of the metastatic cascade. Together, the data demonstrate that the repression of FAK activity by the specific FAK inhibitor BI 853520 offers a promising anti-proliferative approach for cancer therapy
H Tumor cell-specific inhibition of MYC function using small molecule inhibitors of the HUWE1 ubiquitin ligase
Deregulated expression of MYC is a driver of colorectal carcinogenesis, necessitating novel strategies to inhibit MYC function. The ubiquitin ligase HUWE1 (HECTH9, ARF-BP1, MULE) associates with both MYC and the MYC-associated protein MIZ1. We show here that HUWE1 is required for growth of colorectal cancer cells in culture and in orthotopic xenograft models. Using high-throughput screening, we identify small molecule inhibitors of HUWE1, which inhibit MYC-dependent transactivation in colorectal cancer cells, but not in stem and normal colon epithelial cells. Inhibition of HUWE1 stabilizes MIZ1. MIZ1 globally accumulates on MYC target genes and contributes to repression of MYC-activated target genes upon HUWE1 inhibition. Our data show that transcriptional activation by MYC in colon cancer cells requires the continuous degradation of MIZ1 and identify a novel principle that allows for inhibition of MYC function in tumor cells