Wolfgang Wiechert

Wolfgang Wiechert
Forschungszentrum Jülich · Institute of Bio- and Geosciences (IBG)

Prof.

About

402
Publications
35,243
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9,569
Citations
Citations since 2017
120 Research Items
3766 Citations
20172018201920202021202220230100200300400500600
20172018201920202021202220230100200300400500600
20172018201920202021202220230100200300400500600
20172018201920202021202220230100200300400500600

Publications

Publications (402)
Article
Fostered by novel analytical techniques, digitalization, and automation, modern bioprocess development provides large amounts of heterogeneous experimental data, containing valuable process information. In this context, data-driven methods like machine learning (ML) approaches have great potential to rationally explore large design spaces while exp...
Preprint
Full-text available
Thinning is a sub-sampling technique to reduce the memory footprint of Markov chain Monte Carlo. Despite being commonly used, thinning is rarely considered efficient. For sampling convex polytopes uniformly, a highly relevant use-case in systems biology, we here demonstrate that thinning generally boosts computational and, thereby, sampling efficie...
Article
Full-text available
Autonomously operated parallelized mL-scale bioreactors are considered the key to reduce bioprocess development cost and time. However, their application is often limited to products with very simple analytics. In this study, we investigated enhanced protein expression conditions of a carboxyl reductase from Nocardia otitidiscaviarum in E. coli. Ce...
Article
Extracellular production of target proteins simplifies downstream processing due to obsolete cell disruption. However, optimal combinations of a heterologous protein, suitable signal peptide and secretion host can currently not be predicted, resulting in large strain libraries that need to be tested. On the experimental side, this challenge can be...
Preprint
Full-text available
Fostered by novel analytical techniques, digitalization and automation, modern bioprocess development provides high amounts of heterogeneous experimental data, containing valuable process information. In this context, data-driven methods like machine learning (ML) approaches have a high potential to rationally explore large design spaces while expl...
Preprint
Full-text available
We here propose an automated pipeline for the microscopy image-based characterization of catalytically active inclusion bodies (CatIBs), which includes a fully automatic experimental high-throughput workflow combined with a hybrid approach for multi-object microbial cell segmentation. For automated microscopy, a CatIB producer strain was cultivated...
Article
Full-text available
To train deep learning based segmentation models, large ground truth data sets are needed. To address this need in microfluidic live-cell imaging, we present CellSium, a flexibly configurable cell simulator built to synthesize realistic image sequences of bacterial microcolonies growing in monolayers. We illustrate that the simulated images are sui...
Preprint
Extracellular production of target proteins simplifies downstream processing due to obsolete cell disruption. However, optimal combinations of a heterologous protein, suitable signal peptide and secretion host can currently not be predicted, resulting in large strain libraries that need to be tested. On the experimental side, this challenge can be...
Conference Paper
We here propose an automated pipeline for the microscopy image-based characterization of catalytically active inclusion bodies (CatIBs), which includes a fully automatic experimental high-throughput workflow combined with a hybrid approach for multi-object microbial cell segmentation. For automated microscopy, a CatIB producer strain was cultivated...
Article
Full-text available
Background Catalytically active inclusion bodies (CatIBs) are known for their easy and cost efficient production, recyclability as well as high stability and provide an alternative purely biological technology for enzyme immobilization. Due to their ability to self-aggregate in a carrier-free, biodegradable form, no further laborious immobilization...
Article
Current bioprocesses for production of value-added compounds are mainly based on pure cultures that are composed of rationally engineered strains of model organisms with versatile metabolic capacities. However, in the comparably well-defined environment of a bioreactor, metabolic flexibility provided by various highly abundant biosynthetic enzymes...
Article
Full-text available
Secretion of bacterial proteins into the culture medium simplifies downstream processing by avoiding cell disruption for target protein purification. However, a suitable signal peptide for efficient secretion needs to be identified, and currently, there are no tools available to predict optimal combinations of signal peptides and target proteins. T...
Article
Full-text available
Background Currently, the generation of genetic diversity for microbial cell factories outpaces the screening of strain variants with omics-based phenotyping methods. Especially isotopic labeling experiments, which constitute techniques aimed at elucidating cellular phenotypes and supporting rational strain design by growing microorganisms on subst...
Preprint
Full-text available
To address the need for ground truth data for deep learning based segmentation algorithms in microfluidic live-cell imaging, we present CellSium , a cell simulator primarily aimed at synthesizing realistic image sequences of bacterial microcolonies suitable for training neural networks. Availability and Implementation CellSium is free and open sou...
Article
Full-text available
Metabolic footprinting represents a holistic approach to gathering large-scale metabolomic information of a given biological system and is, therefore, a driving force for systems biology and bioprocess development. The ongoing development of automated cultivation platforms increases the need for a comprehensive and rapid profiling tool to cope with...
Article
Full-text available
High-throughput experimentation has revolutionized data-driven experimental sciences and opened the door to the application of machine learning techniques. Nevertheless, the quality of any data analysis strongly depends on the quality of the data and specifically the degree to which random effects in the experimental data-generating process are qua...
Article
Full-text available
Microbioreactor (MBR) devices have emerged as powerful cultivation tools for tasks of microbial phenotyping and bioprocess characterization and provide a wealth of online process data in a highly parallelized manner. Such datasets are difficult to interpret in short time by manual workflows. In this study, we present the Python package bletl and sh...
Article
Full-text available
Background The split GFP assay is a well-known technology for activity-independent screening of target proteins. A superfolder GFP is split into two non-fluorescent parts, GFP11 which is fused to the target protein and GFP1-10. In the presence of both, GFP1-10 and the GFP11-tag are self-assembled and a functional chromophore is formed. However, it...
Article
Full-text available
Corynebacterium glutamicum belongs to the microbes of enormous biotechnological relevance. In particular, its strain ATCC 13032 is a widely used producer of L-amino acids at an industrial scale. Its apparent robustness also turns it into a favorable platform host for a wide range of further compounds, mainly because of emerging bio-based economies....
Preprint
Full-text available
Microbioreactor (MBR) devices have emerged as powerful cultivation tools for tasks of microbial phenotyping and bioprocess characterization and provide a wealth of online process data in a highly parallelized manner. Such datasets are difficult to interpret in short time by manual workflows. In this study, we present the Python package bletl and sh...
Preprint
Full-text available
High-throughput experimentation has revolutionized data-driven experimental sciences and opened the door to the application of machine learning techniques. Nevertheless, the quality of any data analysis strongly depends on the quality of the data and specifically the degree to which random effects in the experimental data-generating process are qua...
Chapter
The aim of Metabolic Flux Analysis (MFA) is to find out as much as possible about the actual intracellular reaction rates in living microorganisms from experimental data. To this end, MFA uses mathematical models to infer the metabolic fluxes quantitatively from measurements in multistep experimental-computational protocols. Over the recent decades...
Article
Full-text available
Background Lignocellulosic biomass is the most abundant raw material on earth. Its efficient use for novel bio-based materials is essential for an emerging bioeconomy. Possible building blocks for such materials are the key TCA-cycle intermediates α-ketoglutarate and succinate. These organic acids have a wide range of potential applications, partic...
Article
Full-text available
Given its geometric similarity to large‐scale production plants and the excellent possibilities for precise process control and monitoring, the classic stirred tank bioreactor still represents the gold standard for bioprocess development at a laboratory scale. However, compared to microbioreactor technologies bioreactors often suffer from a low deg...
Article
Full-text available
With the utilization of small-scale and highly parallelized cultivation platforms embedded in laboratory robotics, microbial phenotyping and bioprocess development have been substantially accelerated, thus generating a bottleneck in bioanalytical bioprocess sample analytics. While microscale cultivation platforms allow the monitoring of typical pro...
Article
In recent years, many fungal genomes have become publicly available. In combination with novel gene editing tools, this allows for accelerated strain construction, making filamentous fungi even more interesting for the production of valuable products. However, besides their extraordinary production and secretion capacities, fungi most often exhibit...
Article
Full-text available
Background Morphology, being one of the key factors influencing productivity of filamentous fungi, is of great interest during bioprocess development. With increasing demand of high-throughput phenotyping technologies for fungi due to the emergence of novel time-efficient genetic engineering technologies, workflows for automated liquid handling com...
Article
Full-text available
DOI: 10.1002/elsc.202000088 The cover illustrates the close integration of experimental work and in silico analyses to study and optimize bioprocesses. In pages 242–257 of this issue, Hemmerich et al. introduce the tool pyFOOMB that enables a guided and flexible implementation of bioprocess models in the form of ordinary differential equation syste...
Article
Full-text available
Background In recent years, the production of inclusion bodies that retained substantial catalytic activity was demonstrated. These catalytically active inclusion bodies (CatIBs) were formed by genetic fusion of an aggregation inducing tag to a gene of interest via short linker polypeptides and overproduction of the resulting gene fusion in Escheri...
Article
Full-text available
Wild-type C. glutamicum ATCC 13032 is known to possess two enzymes with anaplerotic (C4-directed) carboxylation activity, namely phosphoenolpyruvate carboxylase (PEPCx) and pyruvate carboxylase (PCx). On the other hand, C3-directed decarboxylation can be catalyzed by the three enzymes phosphoenolpyruvate carboxykinase (PEPCk), oxaloacetate decarbox...
Article
Full-text available
Quantitative characterization of biotechnological production processes requires the determination of different key performance indicators (KPIs) such as titer, rate and yield. Classically, these KPIs can be derived by combining black‐box bioprocess modeling with non‐linear regression for model parameter estimation. The presented pyFOOMB package ena...
Preprint
Full-text available
Quantitative characterization of biotechnological production processes requires the determination of different key performance indicators (KPIs) such as titer, rate and yield. Classically, these KPIs can be derived by combining black-box bioprocess modelling with non-linear regression for model parameter estimation. The presented pyFOOMB package en...
Article
Full-text available
Increasing the growth rate of the industrial host Corynebacterium glutamicum is a promising target to rise productivities of growth coupled product formation. As a prerequisite, detailed knowledge about the tight regulation network is necessary for identifying promising metabolic engineering goals. Here, we present comprehensive metabolic and trans...
Article
Full-text available
The construction of microbial platform organisms by means of genome reduction is an ongoing topic in biotechnology. In this study, we investigated whether the deletion of single or multiple gene clusters has a positive effect on the secretion of cutinase from Fusarium solani pisi in the industrial workhorse Corynebacterium glutamicum. A total of 22...
Article
Optimization‐constrained differential equations (OCDE) are a class of mathematical problems where differential equations are constrained by an embedded algebraic optimization problem. We analyze the well‐posedness of the local solutions of OCDE based on local optimality. By assuming linear independence constraint qualification and applying the Karu...
Article
Differential-algebraic equations with embedded optimization criteria (DAEO) are a class of mathematical models for underdetermined differential-algebraic equation (DAE) systems with less algebraic equations than algebraic variables. The algebraic variables may be calculated as the solution of an embedded (non)linear program, yielding a DAEO system....
Article
Full-text available
With the advent of modern genetic engineering methods, microcultivation systems have become increasingly important tools for accelerated strain phenotyping and bioprocess engineering. While these systems offer sophisticated capabilities to screen batch processes, they lack the ability to realize fed-batch processes, which are used more frequently i...
Article
Nowadays, chemical production of 1,4‐butanediol is supplemented by biotechnological processes using a genetically modified E. coli strain, which is an industrial showcase of successful application of metabolic engineering. However, large scale bioprocess performance can be affected by presence of physical and chemical gradients in bioreactors which...
Article
Full-text available
Limited throughput represents a substantial drawback during bioprocess development. In recent years, several commercial microbioreactor systems have emerged featuring parallelized experimentation with optical monitoring. However, many devices remain limited to batch mode and do not represent the fed-batch strategy typically applied on an industrial...
Article
Full-text available
Background: Streptomycetes are filamentous microorganisms of high biotechnological relevance, especially for the production of antibiotics. In submerged cultures, the productivity of these microorganisms is closely linked to their growth morphology. Microfluidic lab-on-a-chip cultivation systems, coupled with automated time-lapse imaging, generate...
Article
Full-text available
Due to their high triacylglyceride content, microalgae are intensively investigated for bioeconomy and food applications. However, lipid analysis is laborious incorporating extraction, transesterification and typically gas chromatographic measurement. Co-elution induces a significant risk of fatty acid misidentification and thus, additional purific...
Article
Miniaturization and automation are key technologies to cope with the high number of potentially improved production strains produced by modern genetic engineering tools. In article 1800428, Hemmerich et al. present a novel workflow for automated, repeated low‐volume sampling of microtiter plate cultivations. The high degree of parallelization witho...
Article
Full-text available
Background: In most microbial cultivations D-glucose is the main carbon and energy source. However, quantification of D-glucose especially in small scale is still challenging. Therefore, we developed a FRET-based glucose biosensor, which can be applied in microbioreactor-based cultivations. This sensor consists of a glucose binding protein sandwic...
Article
Full-text available
Background: Filamentously growing microorganisms offer unique advantages for biotechnological processes, such as extraordinary secretion capacities, going along with multiple obstacles due to their complex morphology. However, limited experimental throughput in bioprocess development still hampers taking advantage of their full potential. Miniaturi...
Article
Full-text available
A biorefinery comprises a variety of process steps to synthesize products from sustainable natural resources. Dynamic plant‐wide simulation enhances the process understanding, leads to improved cost efficiency and enables model‐based operation and control. It is thereby important for an increased competitiveness to conventional processes. To this e...
Article
Full-text available
13C metabolic flux analysis (MFA) is the method of choice when a detailed inference of intracellular metabolic fluxes in living organisms under metabolic quasi-steady state conditions is desired. Being continuously developed since two decades, the technology made major contributions to the quantitative characterization of organisms in all fields of...
Article
Optimal performance of multi‐step enzymatic one‐pot cascades requires a facile balance between enzymatic activity and stability of multiple enzymes under the employed reaction conditions. We here describe the optimization of an exemplary two‐step one‐pot recycling cascade utilizing the thiamine diphosphate (ThDP)‐dependent benzaldehyde lyase from P...
Article
Full-text available
Alcohol dehydrogenases are of high interest for stereoselective syntheses of chiral building blocks such as 1,2‐diols. As this class of enzymes requires nicotinamide cofactors, their application in biotechnological synthesis reactions is economically only feasible with appropriate cofactor regeneration. Therefore, a co‐substrate is oxidized to the...
Article
Recent research on population heterogeneity revealed fascinating insights into microbial behavior. In particular emerging single-cell technologies, image-based microfluidics lab-on-chip systems generate insights with spatio-temporal resolution, which are inaccessible with conventional tools. This review reports recent developments and applications...
Article
The impact of Sec signal peptides (SPs) from Bacillus subtilis in combination with IPTG concentration and feeding profile was investigated for heterologous protein secretion performance by Corynebacterium glutamicum using cutinase as model enzyme. Based on a comprehensive data set of about 150 bench‐scale bioreactor cultivations in fed‐batch mode a...
Article
Full-text available
Alternative sigma factors control numerous aspects of bacterial life, including adaptation to physiological stresses, morphological development, persistence states and virulence. This is especially true for the physiologically complex actinobacteria. Here we report the development of a robust gene deletions system for Streptomyces lividans TK24 bas...
Article
Full-text available
Quantitative single-cell cultivation has provided fundamental contributions to our understanding of heterogeneity among industrially used microorganisms. Filamentous growing Streptomyces species are emerging platform organisms for industrial production processes, but their exploitation is still limited due to often reported high batch-to-batch vari...
Article
Full-text available
Science revolves around the best way of conducting an experiment to obtain insightful results. Experiments with maximal information content can be found by computational experimental design (ED) strategies that identify optimal conditions under which to perform the experiment. Several criteria have been proposed to measure the information content,...
Data
Multi-objective experimental design: Results for the 5D scenario. Documentation of results for the analytical platforms GC-MS, LC-MS, LC-MS/MS, 13C-NMR. (PDF)
Data
Measurement models. Details on the derivation of measurement error models for the analytical platforms GC-MS, LC-MS, LC-MS/MS, 13C-NMR, 1H-NMR, and GC-C-IRMS. (PDF)