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4 Publications visible to you, out of a total of 4
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

EnzymeML-a data exchange format for biocatalysis and enzymology.

Abstract (Expand)

EnzymeML is an XML-based data exchange format that supports the comprehensive documentation of enzymatic data by describing reaction conditions, time courses of substrate and product concentrations, … the kinetic model, and the estimated kinetic constants. EnzymeML is based on the Systems Biology Markup Language, which was extended by implementing the STRENDA Guidelines. An EnzymeML document serves as a container to transfer data between experimental platforms, modeling tools, and databases. EnzymeML supports the scientific community by introducing a standardized data exchange format to make enzymatic data findable, accessible, interoperable, and reusable according to the FAIR data principles. An application programming interface in Python supports the integration of software tools for data acquisition, data analysis, and publication. The feasibility of a seamless data flow using EnzymeML is demonstrated by creating an EnzymeML document from a structured spreadsheet or from a STRENDA DB database entry, by kinetic modeling using the modeling platform COPASI, and by uploading to the enzymatic reaction kinetics database SABIO-RK.

Authors: J. Range, C. Halupczok, J. Lohmann, N. Swainston, C. Kettner, F. T. Bergmann, A. Weidemann, U. Wittig, S. Schnell, J. Pleiss

Date Published: 11th Dec 2021

Publication Type: Journal

Data management and data enrichment for systems biology projects.

Abstract (Expand)

Collecting, curating, interlinking, and sharing high quality data are central to de.NBI-SysBio, the systems biology data management service center within the de.NBI network (German Network for … Bioinformatics Infrastructure). The work of the center is guided by the FAIR principles for scientific data management and stewardship. FAIR stands for the four foundational principles Findability, Accessibility, Interoperability, and Reusability which were established to enhance the ability of machines to automatically find, access, exchange and use data. Within this overview paper we describe three tools (SABIO-RK, Excemplify, SEEK) that exemplify the contribution of de.NBI-SysBio services to FAIR data, models, and experimental methods storage and exchange. The interconnectivity of the tools and the data workflow within systems biology projects will be explained. For many years we are the German partner in the FAIRDOM initiative (http://fair-dom.org) to establish a European data and model management service facility for systems biology.

Authors: U. Wittig, M. Rey, A. Weidemann, W. Muller

Date Published: 10th Nov 2017

Publication Type: Journal

Genome reduction boosts heterologous gene expression in Pseudomonas putida.

Abstract (Expand)

BACKGROUND: The implementation of novel platform organisms to be used as microbial cell factories in industrial applications is currently the subject of intense research. Ongoing efforts include the … adoption of Pseudomonas putida KT2440 variants with a reduced genome as the functional chassis for biotechnological purposes. In these strains, dispensable functions removed include flagellar motility (1.1% of the genome) and a number of open reading frames expected to improve genotypic and phenotypic stability of the cells upon deletion (3.2% of the genome). RESULTS: In this study, two previously constructed multiple-deletion P. putida strains were systematically evaluated as microbial cell factories for heterologous protein production and compared to the parental bacterium (strain KT2440) with regards to several industrially-relevant physiological traits. Energetic parameters were quantified at different controlled growth rates in continuous cultivations and both strains had a higher adenosine triphosphate content, increased adenylate energy charges, and diminished maintenance demands than the wild-type strain. Under all the conditions tested the mutants also grew faster, had enhanced biomass yields and showed higher viability, and displayed increased plasmid stability than the parental strain. In addition to small-scale shaken-flask cultivations, the performance of the genome-streamlined strains was evaluated in larger scale bioreactor batch cultivations taking a step towards industrial growth conditions. When the production of the green fluorescent protein (used as a model heterologous protein) was assessed in these cultures, the mutants reached a recombinant protein yield with respect to biomass up to 40% higher than that of P. putida KT2440. CONCLUSIONS: The two streamlined-genome derivatives of P. putida KT2440 outcompeted the parental strain in every industrially-relevant trait assessed, particularly under the working conditions of a bioreactor. Our results demonstrate that these genome-streamlined bacteria are not only robust microbial cell factories on their own, but also a promising foundation for further biotechnological applications.

Authors: S. Lieder, P. I. Nikel, V. de Lorenzo, R. Takors

Date Published: 19th Apr 2015

Publication Type: Not specified

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