03 Fakultät Chemie

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/4

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Institute: search.filters.UBSInstitut.Institut für Biochemie und Technische BiochemieSubject: search.filters.subject.660

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Now showing 1 - 7 of 7
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    Distinct specificities of the HEMK2 protein methyltransferase in methylation of glutamine and lysine residues
    (2024) Weirich, Sara; Ulu, Gizem T.; Chandrasekaran, Thyagarajan T.; Kehl, Jana; Schmid, Jasmin; Dorscht, Franziska; Kublanovsky, Margarita; Levy, Dan; Jeltsch, Albert
    The HEMK2 protein methyltransferase has been described as glutamine methyltransferase catalyzing ERF1-Q185me1 and lysine methyltransferase catalyzing H4K12me1. Methylation of two distinct target residues is unique for this class of enzymes. To understand the specific catalytic adaptations of HEMK2 allowing it to master this chemically challenging task, we conducted a detailed investigation of the substrate sequence specificities of HEMK2 for Q- and K-methylation. Our data show that HEMK2 prefers methylation of Q over K at peptide and protein level. Moreover, the ERF1 sequence is strongly preferred as substrate over the H4K12 sequence. With peptide SPOT array methylation experiments, we show that Q-methylation preferentially occurs in a G-Q-X3-R context, while K-methylation prefers S/T at the first position of the motif. Based on this, we identified novel HEMK2 K-methylation peptide substrates with sequences taken from human proteins which are methylated with high activity. Since H4K12 methylation by HEMK2 was very low, other protein lysine methyltransferases were examined for their ability to methylate the H4K12 site. We show that SETD6 has a high H4K12me1 methylation activity (about 1000-times stronger than HEMK2) and this enzyme is mainly responsible for H4K12me1 in DU145 prostate cancer cells.
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    Fluent integration of laboratory data into biocatalytic process simulation using EnzymeML, DWSIM, and ontologies
    (2024) Behr, Alexander S.; Surkamp, Julia; Abbaspour, Elnaz; Häußler, Max; Lütz, Stephan; Pleiss, Jürgen; Kockmann, Norbert; Rosenthal, Katrin
    The importance of biocatalysis for ecologically sustainable syntheses in the chemical industry and for applications in everyday life is increasing. To design efficient applications, it is important to know the related enzyme kinetics; however, the measurement is laborious and error-prone. Flow reactors are suitable for rapid reaction parameter screening; here, a novel workflow is proposed including digital image processing (DIP) for the quantification of product concentrations, and the use of structured data acquisition with EnzymeML spreadsheets combined with ontology-based semantic information, leading to rapid and smooth data integration into a simulation tool for kinetics evaluation. One of the major findings is that a flexibly adaptive ontology is essential for FAIR (findability, accessibility, interoperability, reusability) data handling. Further, Python interfaces enable consistent data transfer.
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    Semi‐rational engineering of toluene dioxygenase from Pseudomonas putida F1 towards oxyfunctionalization of bicyclic aromatics
    (2021) Wissner, Julian L.; Schelle, Jona T.; Escobedo‐Hinojosa, Wendy; Vogel, Andreas; Hauer, Bernhard
    Toluene dioxygenase (TDO) from Pseudomonas putida F1 was engineered towards the oxyfunctionalization of bicyclic substrates. Single and double mutant libraries addressing 27 different positions, located at the active site and entrance channel were generated. In total, 176 different variants were tested employing the substrates naphthalene, 1,2,3,4‐tetrahydroquinoline, and 2‐phenylpyridine. Introduced mutations in positions M220, A223 and F366, exhibited major influences in terms of product formation, chemo‐, regio‐ and enantioselectivity. By semi‐rational evolution, we lighted up the TDO capability to convert bulkier substrates than its natural substrate, at unprecedented reported conversions. Thus, the most active TDO variants were applied to biocatalytic oxyfunctionalizations of 1,2,3,4‐tetrahydroquinoline, and 2‐phenylpyridine, enabling the production of substantial amounts of (+)‐(R)‐1,2,3,4‐tetrahydroquinoline‐4‐ol (71% isolated yield, 94% ee) and (+)‐(1S,2R)‐3‐(pyridin‐2‐yl)cyclohexa‐3,5‐diene‐1,2‐diol (60% isolated yield, 98% ee), respectively. Here, we provide a set of novel TDO‐based biocatalysts useful for the preparation of oxyfunctionalized bicyclic scaffolds, which are valuable to perform downstream synthetic processes.
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    Inverting the stereoselectivity of an NADH‐dependent imine‐reductase variant
    (2021) Stockinger, Peter; Borlinghaus, Niels; Sharma, Mahima; Aberle, Benjamin; Grogan, Gideon; Pleiss, Jürgen; Nestl, Bettina M.
    Imine reductases (IREDs) offer biocatalytic routes to chiral amines and have a natural preference for the NADPH cofactor. In previous work, we reported enzyme engineering of the (R)‐selective IRED from Myxococcus stipitatus (NADH‐IRED‐Ms) yielding a NADH‐dependent variant with high catalytic efficiency. However, no IRED with NADH specificity and (S)‐selectivity in asymmetric reductions has yet been reported. Herein, we applied semi‐rational enzyme engineering to switch the selectivity of NADH‐IRED‐Ms. The quintuple variant A241V/H242Y/N243D/V244Y/A245L showed reverse stereopreference in the reduction of the cyclic imine 2‐methylpyrroline compared to the wild‐type and afforded the (S)‐amine product with >99 % conversion and 91 % enantiomeric excess. We also report the crystal‐structures of the NADPH‐dependent (R)‐IRED‐Ms wild‐type enzyme and the NADH‐dependent NADH‐IRED‐Ms variant and molecular dynamics (MD) simulations to rationalize the inverted stereoselectivity of the quintuple variant.
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    Standardized data, scalable documentation, sustainable storage : EnzymeML ss a basis for FAIR data management in biocatalysis
    (2021) Pleiss, Jürgen
    The often reported reproducibility crisis in the biomedical sciences also applies to enzymology and biocatalysis, and mainly results from incomplete reporting of reaction conditions. In this Concept article, an infrastructure based on EnzymeML is sketched, which enables reporting, exchange, and storage of enzymatic data according to the FAIR data principles. EnzymeML is a novel data exchange format for enzymology and biocatalysis, which facilitates the application of the STRENDA Guidelines and thus makes data on enzyme‐catalyzed reactions findable, accessible, interoperable, and reusable. EnzymeML enables the comprehensive documentation of metadata, thus fostering reproducibility and replicability in enzymology and biocatalysis. An EnzymeML Application Programming Interface integrates electronic lab notebooks with modelling platforms and databases on enzymatic reactions, and thus enables the seamless flow of enzymatic data from measurement to modelling to publication, without the need for manual intervention such as reformatting or editing. EnzymeML serves as a valuable tool for the design of biocatalytic experiments and contributes to the vision of a unified research data infrastructure for catalysis research.
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    Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes
    (2024) Cao, Xueqi; Huber, Sandra; Ahari, Ata Jadid; Traube, Franziska R.; Seifert, Marc; Oakes, Christopher C.; Secheyko, Polina; Vilov, Sergey; Scheller, Ines F.; Wagner, Nils; Yépez, Vicente A.; Blombery, Piers; Haferlach, Torsten; Heinig, Matthias; Wachutka, Leonhard; Hutter, Stephan; Gagneur, Julien
    Background. Rare oncogenic driver events, particularly affecting the expression or splicing of driver genes, are suspected to substantially contribute to the large heterogeneity of hematologic malignancies. However, their identification remains challenging. Methods. To address this issue, we generated the largest dataset to date of matched whole genome sequencing and total RNA sequencing of hematologic malignancies from 3760 patients spanning 24 disease entities. Taking advantage of our dataset size, we focused on discovering rare regulatory aberrations. Therefore, we called expression and splicing outliers using an extension of the workflow DROP (Detection of RNA Outliers Pipeline) and AbSplice, a variant effect predictor that identifies genetic variants causing aberrant splicing. We next trained a machine learning model integrating these results to prioritize new candidate disease-specific driver genes. Results. We found a median of seven expression outlier genes, two splicing outlier genes, and two rare splice-affecting variants per sample. Each category showed significant enrichment for already well-characterized driver genes, with odds ratios exceeding three among genes called in more than five samples. On held-out data, our integrative modeling significantly outperformed modeling based solely on genomic data and revealed promising novel candidate driver genes. Remarkably, we found a truncated form of the low density lipoprotein receptor LRP1B transcript to be aberrantly overexpressed in about half of hairy cell leukemia variant (HCL-V) samples and, to a lesser extent, in closely related B-cell neoplasms. This observation, which was confirmed in an independent cohort, suggests LRP1B as a novel marker for a HCL-V subclass and a yet unreported functional role of LRP1B within these rare entities. Conclusions. Altogether, our census of expression and splicing outliers for 24 hematologic malignancy entities and the companion computational workflow constitute unique resources to deepen our understanding of rare oncogenic events in hematologic cancers.
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    RepEnTools : an automated repeat enrichment analysis package for ChIP-seq data reveals hUHRF1 Tandem-Tudor domain enrichment in young repeats
    (2024) Choudalakis, Michel; Bashtrykov, Pavel; Jeltsch, Albert
    Background. Repeat elements (REs) play important roles for cell function in health and disease. However, RE enrichment analysis in short-read high-throughput sequencing (HTS) data, such as ChIP-seq, is a challenging task. Results. Here, we present RepEnTools , a software package for genome-wide RE enrichment analysis of ChIP-seq and similar chromatin pulldown experiments. Our analysis package bundles together various software with carefully chosen and validated settings to provide a complete solution for RE analysis, starting from raw input files to tabular and graphical outputs. RepEnTools implementations are easily accessible even with minimal IT skills (Galaxy/UNIX). To demonstrate the performance of RepEnTools , we analysed chromatin pulldown data by the human UHRF1 TTD protein domain and discovered enrichment of TTD binding on young primate and hominid specific polymorphic repeats (SVA, L1PA1/L1HS) overlapping known enhancers and decorated with H3K4me1-K9me2/3 modifications. We corroborated these new bioinformatic findings with experimental data by qPCR assays using newly developed primate and hominid specific qPCR assays which complement similar research tools. Finally, we analysed mouse UHRF1 ChIP-seq data with RepEnTools and showed that the endogenous mUHRF1 protein colocalizes with H3K4me1-H3K9me3 on promoters of REs which were silenced by UHRF1. These new data suggest a functional role for UHRF1 in silencing of REs that is mediated by TTD binding to the H3K4me1-K9me3 double mark and conserved in two mammalian species. Conclusions. RepEnTools improves the previously available programmes for RE enrichment analysis in chromatin pulldown studies by leveraging new tools, enhancing accessibility and adding some key functions. RepEnTools can analyse RE enrichment rapidly, efficiently, and accurately, providing the community with an up-to-date, reliable and accessible tool for this important type of analysis.