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17 Publications visible to you, out of a total of 25
Review of Key Elements in Developing a Common Data Model for Rare Diseases: Identifying Common Success Factors.

Abstract (Expand)

This paper explores key success factors for the development and implementation of a Common Data Model (CDM) for Rare Diseases (RDs) focusing on the European context. Several challenges hinder RD care … and research in diagnosis, treatment, and research, including data fragmentation, lack of standardisation, and Interoperability (IOP) issues within healthcare information systems. We identify key issues and recommendations for an RD-CDM, drawing on international guidelines and existing infrastructure, to address organisational, consensus, interoperability, usage, and secondary use challenges. Based on these, we analyse the importance of balancing the scope and IOP of a CDM to cater to the unique requirements of RDs while ensuring effective data exchange and usage across systems. In conclusion, a well-designed RD-CDM can bridge gaps in RD care and research, enhance patient care and facilitate international collaborations.

Authors: A. S. L. Graefe, F. Rehburg, M. Hubner, S. Thun, O. Beyan

Date Published: 22nd Aug 2024

Publication Type: Proceedings

Metabolome plasticity in 241 Arabidopsis thaliana accessions reveals evolutionary cold adaptation processes.

Abstract (Expand)

Acclimation and adaptation of metabolism to a changing environment are key processes for plant survival and reproductive success. In the present study, 241 natural accessions of Arabidopsis (Arabidopsis … thaliana) were grown under two different temperature regimes, 16 degrees C and 6 degrees C, and growth parameters were recorded, together with metabolite profiles, to investigate the natural genome x environment effects on metabolome variation. The plasticity of metabolism, which was captured by metabolic distance measures, varied considerably between accessions. Both relative growth rates and metabolic distances were predictable by the underlying natural genetic variation of accessions. Applying machine learning methods, climatic variables of the original growth habitats were tested for their predictive power of natural metabolic variation among accessions. We found specifically habitat temperature during the first quarter of the year to be the best predictor of the plasticity of primary metabolism, indicating habitat temperature as the causal driver of evolutionary cold adaptation processes. Analyses of epigenome- and genome-wide associations revealed accession-specific differential DNA-methylation levels as potentially linked to the metabolome and identified FUMARASE2 as strongly associated with cold adaptation in Arabidopsis accessions. These findings were supported by calculations of the biochemical Jacobian matrix based on variance and covariance of metabolomics data, which revealed that growth under low temperatures most substantially affects the accession-specific plasticity of fumarate and sugar metabolism. Our findings indicate that the plasticity of metabolic regulation is predictable from the genome and epigenome and driven evolutionarily by Arabidopsis growth habitats.

Authors: J. Weiszmann, D. Walther, P. Clauw, G. Back, J. Gunis, I. Reichardt, S. Koemeda, J. Jez, M. Nordborg, J. Schwarzerova, I. Pierides, T. Nagele, W. Weckwerth

Date Published: 22nd Sep 2023

Publication Type: Journal

EnzymeML: seamless data flow and modeling of enzymatic data.

Abstract (Expand)

The design of biocatalytic reaction systems is highly complex owing to the dependency of the estimated kinetic parameters on the enzyme, the reaction conditions, and the modeling method. Consequently, … reproducibility of enzymatic experiments and reusability of enzymatic data are challenging. We developed the XML-based markup language EnzymeML to enable storage and exchange of enzymatic data such as reaction conditions, the time course of the substrate and the product, kinetic parameters and the kinetic model, thus making enzymatic data findable, accessible, interoperable and reusable (FAIR). The feasibility and usefulness of the EnzymeML toolbox is demonstrated in six scenarios, for which data and metadata of different enzymatic reactions are collected and analyzed. EnzymeML serves as a seamless communication channel between experimental platforms, electronic lab notebooks, tools for modeling of enzyme kinetics, publication platforms and enzymatic reaction databases. EnzymeML is open and transparent, and invites the community to contribute. All documents and codes are freely available at https://enzymeml.org .

Authors: S. Lauterbach, H. Dienhart, J. Range, S. Malzacher, J. D. Sporing, D. Rother, M. F. Pinto, P. Martins, C. E. Lagerman, A. S. Bommarius, A. V. Host, J. M. Woodley, S. Ngubane, T. Kudanga, F. T. Bergmann, J. M. Rohwer, D. Iglezakis, A. Weidemann, U. Wittig, C. Kettner, N. Swainston, S. Schnell, J. Pleiss

Date Published: 10th Feb 2023

Publication Type: Journal

Making Sense of "Nonsense" and More: Challenges and Opportunities in the Genetic Code Expansion, in the World of tRNA Modifications.

Abstract (Expand)

The evolutional development of the RNA translation process that leads to protein synthesis based on naturally occurring amino acids has its continuation via synthetic biology, the so-called rational … bioengineering. Genetic code expansion (GCE) explores beyond the natural translational processes to further enhance the structural properties and augment the functionality of a wide range of proteins. Prokaryotic and eukaryotic ribosomal machinery have been proven to accept engineered tRNAs from orthogonal organisms to efficiently incorporate noncanonical amino acids (ncAAs) with rationally designed side chains. These side chains can be reactive or functional groups, which can be extensively utilized in biochemical, biophysical, and cellular studies. Genetic code extension offers the contingency of introducing more than one ncAA into protein through frameshift suppression, multi-site-specific incorporation of ncAAs, thereby increasing the vast number of possible applications. However, different mediating factors reduce the yield and efficiency of ncAA incorporation into synthetic proteins. In this review, we comment on the recent advancements in genetic code expansion to signify the relevance of systems biology in improving ncAA incorporation efficiency. We discuss the emerging impact of tRNA modifications and metabolism in protein design. We also provide examples of the latest successful accomplishments in synthetic protein therapeutics and show how codon expansion has been employed in various scientific and biotechnological applications.

Authors: O. M. Lateef, M. O. Akintubosun, O. T. Olaoba, S. O. Samson, M. Adamczyk

Date Published: 15th Jan 2022

Publication Type: Journal

Keratinases as Versatile Enzymatic Tools for Sustainable Development

Abstract (Expand)

To reduce anthropological pressure on the environment, the implementation of novel technologies in present and future economies is needed for sustainable development. The food industry, with dairy and …with dairy and meat production in particular, has a significant environmental impact. Global poultry production is one of the fastest-growing meat producing sectors and is connected with the generation of burdensome streams of manure, offal and feather waste. In 2020, the EU alone produced around 3.2 million tonnes of poultry feather waste composed primarily of keratin, a protein biopolymer resistant to conventional proteolytic enzymes. If not managed properly, keratin waste can significantly affect ecosystems, contributing to environmental pollution, and pose a serious hazard to human and livestock health. In this article, the application of keratinolytic enzymes and microorganisms for promising novel keratin waste management methods with generation of new value-added products, such as bioactive peptides, vitamins, prion decontamination agents and biomaterials were reviewed.

Authors: Marcin Sypka, Iga Jodłowska, Aneta M. Białkowska

Date Published: 1st Dec 2021

Publication Type: Journal

Prediction and analysis of redox-sensitive cysteines using machine learning and statistical methods.

Abstract (Expand)

Reactive oxygen species are produced by a number of stimuli and can lead both to irreversible intracellular damage and signaling through reversible post-translational modification. It is unclear which … factors contribute to the sensitivity of cysteines to redox modification. Here, we used statistical and machine learning methods to investigate the influence of different structural and sequence features on the modifiability of cysteines. We found several strong structural predictors for redox modification. Sensitive cysteines tend to be characterized by higher exposure, a lack of secondary structure elements, and a high number of positively charged amino acids in their close environment. Our results indicate that modified cysteines tend to occur close to other post-translational modifications, such as phosphorylated serines. We used these features to create models and predict the presence of redox-modifiable cysteines in human mitochondrial complex I as well as make novel predictions regarding redox-sensitive cysteines in proteins.

Authors: M. Kessler, I. Wittig, J. Ackermann, I. Koch

Date Published: 27th Jul 2021

Publication Type: Journal

Solvent Selection in Homogeneous Catalysis—Optimization of Kinetics and Reaction Performance

Abstract

Not specified

Authors: Fabian Huxoll, Froze Jameel, Jonas Bianga, Thomas Seidensticker, Matthias Stein, Gabriele Sadowski, Dieter Vogt

Date Published: 15th Jan 2021

Publication Type: Journal

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