Parallelized disruption of prokaryotic and eukaryotic cells via miniaturized and automated bead mill

The application of integrated microbioreactor systems is rapidly becoming of more interest to accelerate strain characterization and bioprocess development. However, available high‐throughput screening capabilities are often limited to target extracellular compounds only. Consequently, there is a great demand for automated technologies allowing for miniaturized and parallel cell disruption providing access to intracellular measurements. In this study, a fully automated bead mill workflow was developed and validated for four different industrial platform organisms: Escherichia coli, Corynebacterium glutamicum, Saccharomyces cerevisiae, and Aspergillus niger. The workflow enables up to 48 parallel cell disruptions in microtiter plates and is applicable at‐line to running lab‐scale cultivations. The resulting cell extracts form the basis for quantitative omics studies where no rapid metabolic quenching is required (e.g., genomics and proteomics).     

Cellular radiation effects and hyperthermia: Cytokinetic investigations with stationary phase yeast cells

Summary Wild type diploid yeast, Saccharomyces cerevisiae strain 211, was subjected to 250 kV X-rays or 50° C heat treatment for 30 min or to a combination of both. X-ray exposure took place either in air or in nitrogen. Cell number, percentage of budding cells and cell cycle progression was followed for up to 12 h post irradiation. The distribution of cell cycle stages was determined by flow cytofluorometry. All treatments cause a retardation of cell division rate. Hyperthermia leads mainly to a lengthening of G₁, whereas X-rays arrest the cells reversibly in G₂. The effect of the combined treatment appears to be merely additive. No selective action of hyperthermia on hypoxic cells was found.Dedicated to Prof. Dr. A. Schraub on the occasion of his 70th birthday     

Standard reporting requirements for biological samples in metabolomics experiments: microbial and in vitro biology experiments

With the increasing use of metabolomics as a means to study a large number of different biological research questions, there is a need for a minimal set of reporting standards that allow the scientific community to evaluate, understand, repeat, compare and re-investigate metabolomics studies. Here we propose, a first draft of minimal requirements to effectively describe the biological context of metabolomics studies that involve microbial or in vitro biological subjects. This recommendation has been produced by the microbiology and in vitro biology working subgroup of the Metabolomics Standards Initiative in collaboration with the yeast systems biology network as part of a wider standardization initiative led by the Metabolomics Society. Microbial and in vitro biology metabolomics is defined by this sub-working group as studies with any cell or organism that require a defined external medium to facilitate growth and propagation. Both a minimal set and a best practice set of reporting standards for metabolomics experiments have been defined. The minimal set of reporting standards for microbial or in vitro biology metabolomics experiments includes those factors that are specific for metabolomics experiments and that critically determine the outcome of the experiments. The best practice set of reporting standards contains both the factors that are specific for metabolomics experiments and general aspects that critically determine the outcome of any microbial or in vitro biological experiment.     

Carboxylic acid consumption and production by Corynebacterium glutamicum

Corynebacterium glutamicum is well-known as an industrial workhorse, most notably for its use in the bulk production of amino acids in the feed and food sector. Previous studies of the effect of gradients in scale-down reactors with complex media disclosed an accumulation of several carboxylic acids and a parallel decrease of growth and product accumulation. This study, therefore, addresses the impact of carboxylic acids, for example, acetate and l -lactate, on the cultivation of the cadaverine producing strain C. glutamicum DM1945Δact3:P_tuf-ldcC^opt and their potential role in scale up related performance losses. A fluctuating power input in shake flask and stirred tank cultivations with mineral salt was applied to mimic discontinuous oxygen availability. Results demonstrate, whenever sufficient oxygen was available, C. glutamicum recovered from previously occurring stressful conditions like an oxygen limiting phase. Reassimilation of acids was detected simultaneously. In cultures, which were supplemented with either acetate or l -lactate, a rapid cometabolization of both acids in presence of glucose was observed, showing conversion rates of 7.8 and 3.8 mmol g_{cell dry weight}⁻¹ hr⁻¹, respectively. Uptake of these acids was accompanied by increased oxygen consumption. Proteins related to oxidative stress response, glycogen synthesis, and the main carbon metabolism were found in altered concentrations under oscillatory cultivation conditions. (Proteomics data are available via ProteomeXchange with identifier PXD012760). Virtually no impact on growth or product formation was observed. We conclude that the reduced growth and product formation in scale-down cultivations when complex media was used is not caused by the accumulation of carboxylic acids.     

Importance of NADPH supply for improved L‐valine formation in Corynebacterium glutamicum

Cofactor recycling is known to be crucial for amino acid synthesis. Hence, cofactor supply was now analyzed for L ‐valine to identify new targets for an improvement of production. The central carbon metabolism was analyzed by stoichiometric modeling to estimate the influence of cofactors and to quantify the theoretical yield of L ‐valine on glucose. Three different optimal routes for L ‐valine biosynthesis were identified by elementary mode (EM) analysis. The modes differed mainly in the manner of NADPH regeneration, substantiating that the cofactor supply may be crucial for efficient L ‐valine production. Although the isocitrate dehydrogenase as an NADPH source within the tricarboxylic acid cycle only enables an L ‐valine yield of Y_Val/Glc = 0.5 mol L ‐valine/mol glucose (mol Val/mol Glc), the pentose phosphate pathway seems to be the most promising NADPH source. Based on the theoretical calculation of EMs, the gene encoding phosphoglucoisomerase (PGI) was deleted to achieve this EM with a theoretical yield Y_Val/Glc = 0.86 mol Val/mol Glc during the production phase. The intracellular NADPH concentration was significantly increased in the PGI‐deficient mutant. L ‐Valine yield increased from 0.49 ± 0.13 to 0.67 ± 0.03 mol Val/mol Glc, and, concomitantly, the formation of by‐products such as pyruvate was reduced. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

Bayesian calibration,process modeling and uncertainty quantification in biotechnology

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 quantified and accounted for. Accordingly calibration, i.e. the quantitative association between observed quantities and measurement responses, is a core element of many workflows in experimental sciences.Particularly in life sciences, univariate calibration, often involving non-linear saturation effects, must be performed to extract quantitative information from measured data. At the same time, the estimation of uncertainty is inseparably connected to quantitative experimentation. Adequate calibration models that describe not only the input/output relationship in a measurement system but also its inherent measurement noise are required. Due to its mathematical nature, statistically robust calibration modeling remains a challenge for many practitioners, at the same time being extremely beneficial for machine learning applications.In this work, we present a bottom-up conceptual and computational approach that solves many problems of understanding and implementing non-linear, empirical calibration modeling for quantification of analytes and process modeling. The methodology is first applied to the optical measurement of biomass concentrations in a high-throughput cultivation system, then to the quantification of glucose by an automated enzymatic assay. We implemented the conceptual framework in two Python packages, calibr8 and murefi, with which we demonstrate how to make uncertainty quantification for various calibration tasks more accessible. Our software packages enable more reproducible and automatable data analysis routines compared to commonly observed workflows in life sciences.Subsequently, we combine the previously established calibration models with a hierarchical Monod-like ordinary differential equation model of microbial growth to describe multiple replicates of Corynebacterium glutamicum batch cultures. Key process model parameters are learned by both maximum likelihood estimation and Bayesian inference, highlighting the flexibility of the statistical and computational framework.     

FeedER: a feedback-regulated enzyme-based slow-release system for fed-batch cultivation in microtiter plates

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 in industrial bioprocessing. In this study, a novel approach to realize a feedback-regulated enzyme-based slow-release system (FeedER), allowing exponential fed-batch for microscale cultivations, was realized by extending our existing Mini Pilot Plant technology with a customized process control system. By continuously comparing the experimental growth rates with predefined set points, the automated dosage of Amyloglucosidase enzyme for the cleavage of dextrin polymers into d-glucose monomers is triggered. As a prerequisite for stable fed-batch operation, a constant pH is maintained by automated addition of ammonium hydroxide. We show the successful application of FeedER to study fed-batch growth of different industrial model organisms including Corynebacterium glutamicum, Pichia pastoris, and Escherichia coli. Moreover, the comparative analysis of a C. glutamicum GFP producer strain, cultivated under microscale batch and fed-batch conditions, revealed two times higher product yields under slow growing fed-batch operation. In summary, FeedER enables to run 48 parallel fed-batch experiments in an automated and miniaturized manner, and thereby accelerates industrial bioprocess development at the screening stage.