Semi-Automated High-Throughput Substrate Screening Assay for Nucleoside Kinases.

Nucleoside kinases (NKs) are key enzymes involved in the in vivo phosphorylation of nucleoside analogues used as drugs to treat cancer or viral infections. Having different specificities, the characterization of NKs is essential for drug design and nucleotide analogue production in an in vitro enzymatic process. Therefore, a fast and reliable substrate screening method for NKs is of great importance. Here, we report on the validation of a well-known luciferase-based assay for the detection of NK activity in a 96-well plate format. The assay was semi-automated using a liquid handling robot. Good linearity was demonstrated (r² > 0.98) in the range of 0-500 µM ATP, and it was shown that alternative phosphate donors like dATP or CTP were also accepted by the luciferase. The developed high-throughput assay revealed comparable results to HPLC analysis. The assay was exemplarily used for the comparison of the substrate spectra of four NKs using 20 (8 natural, 12 modified) substrates. The screening results correlated well with literature data, and additionally, previously unknown substrates were identified for three of the NKs studied. Our results demonstrate that the developed semi-automated high-throughput assay is suitable to identify best performing NKs for a wide range of substrates.

Automated Conditional Screening of Multiple Escherichia coli Strains in Parallel Adaptive Fed-Batch Cultivations.

In bioprocess development, the host and the genetic construct for a new biomanufacturing process are selected in the early developmental stages. This decision, made at the screening scale with very limited information about the performance in larger reactors, has a major influence on the efficiency of the final process. To overcome this, scale-down approaches during screenings that show the real cell factory performance at industrial-like conditions are essential. We present a fully automated robotic facility with 24 parallel mini-bioreactors that is operated by a model-based adaptive input design framework for the characterization of clone libraries under scale-down conditions. The cultivation operation strategies are computed and continuously refined based on a macro-kinetic growth model that is continuously re-fitted to the available experimental data. The added value of the approach is demonstrated with 24 parallel fed-batch cultivations in a mini-bioreactor system with eight different Escherichia coli strains in triplicate. The 24 fed-batch cultivations were run under the desired conditions, generating sufficient information to define the fastest-growing strain in an environment with oscillating glucose concentrations similar to industrial-scale bioreactors.

A model-based framework for parallel scale-down fed-batch cultivations in mini-bioreactors for accelerated phenotyping.

Concentration gradients that occur in large industrial-scale bioreactors due to mass transfer limitations have significant effects on process efficiency. Hence, it is desirable to investigate the response of strains to such heterogeneities to reduce the risk of failure during process scale-up. Although there are various scale-down techniques to study these effects, scale-down strategies are rarely applied in the early developmental phases of a bioprocess, as they have not yet been implemented on small-scale parallel cultivation devices. In this study, we combine mechanistic growth models with a parallel mini-bioreactor system to create a high-throughput platform for studying the response of Escherichia coli strains to concentration gradients. As a scaled-down approach, a model-based glucose pulse feeding scheme is applied and compared with a continuous feed profile to study the influence of glucose and dissolved oxygen gradients on both cell physiology and incorporation of noncanonical amino acids into recombinant proinsulin. The results show a significant increase in the incorporation of the noncanonical amino acid norvaline in the soluble intracellular extract and in the recombinant product in cultures with glucose/oxygen oscillations. Interestingly, the amount of norvaline depends on the pulse frequency and is negligible with continuous feeding, confirming observations from large-scale cultivations. Most importantly, the results also show that a larger number of the model parameters are significantly affected by the scale-down scheme, compared with the reference cultivations. In this example, it was possible to describe the effects of oscillations in a single parallel experiment. The platform offers the opportunity to combine strain screening with scale-down studies to select the most robust strains for bioprocess scale-up.

Integrated Robotic Mini Bioreactor Platform for Automated, Parallel Microbial Cultivation With Online Data Handling and Process Control.

During process development, the experimental search space is defined by the number of experiments that can be performed in specific time frames but also by its sophistication (e.g., inputs, sensors, sampling frequency, analytics). High-throughput liquid-handling stations can perform a large number of automated experiments in parallel. Nevertheless, the experimental data sets that are obtained are not always relevant for development of industrial bioprocesses, leading to a high rate of failure during scale-up. We present an automated mini bioreactor platform that enables parallel cultivations in the milliliter scale with online monitoring and control, well-controlled conditions, and advanced feeding strategies similar to industrial processes. The combination of two liquid handlers allows both automated mini bioreactor operation and at-line analysis in parallel. A central database enables end-to-end data exchange and fully integrated device and process control. A model-based operation algorithm allows for the accurate performance of complex cultivations for scale-down studies and strain characterization via optimal experimental redesign, significantly increasing the reliability and transferability of data throughout process development. The platform meets the tradeoff between experimental throughput and process control and monitoring comparable to laboratory-scale bioreactors.

Construction and characterization of broad-host-range reporter plasmid suitable for on-line analysis of bacterial host responses related to recombinant protein production.

BACKGROUND: Bacteria are widely used as hosts for recombinant protein production due to their rapid growth, simple media requirement and ability to produce high yields of correctly folded proteins. Overproduction of recombinant proteins may impose metabolic burden to host cells, triggering various stress responses, and the ability of the cells to cope with such stresses is an important factor affecting both cell growth and product yield. RESULTS: Here, we present a versatile plasmid-based reporter system for efficient analysis of metabolic responses associated with availability of cellular resources utilized for recombinant protein production and host capacity to synthesize correctly folded proteins. The reporter plasmid is based on the broad-host range RK2 minimal replicon and harbors the strong and inducible XylS/Pm regulator/promoter system, the ppGpp-regulated ribosomal protein promoter PrpsJ, and the σ32-dependent synthetic tandem promoter Pibpfxs, each controlling expression of one distinguishable fluorescent protein. We characterized the responsiveness of all three reporters in Escherichia coli by quantitative fluorescence measurements in cell cultures cultivated under different growth and stress conditions. We also validated the broad-host range application potential of the reporter plasmid by using Pseudomonas putida and Azotobacter vinelandii as hosts. CONCLUSIONS: The plasmid-based reporter system can be used for analysis of the total inducible recombinant protein production, the translational capacity measured as transcription level of ribosomal protein genes and the heat shock-like response revealing aberrant protein folding in all studied Gram-negative bacterial strains.

Accelerated Bioprocess Development of Endopolygalacturonase-Production with Saccharomyces cerevisiae Using Multivariate Prediction in a 48 Mini-Bioreactor Automated Platform.

Mini-bioreactor systems enabling automatized operation of numerous parallel cultivations are a promising alternative to accelerate and optimize bioprocess development allowing for sophisticated cultivation experiments in high throughput. These include fed-batch and continuous cultivations with multiple options of process control and sample analysis which deliver valuable screening tools for industrial production. However, the model-based methods needed to operate these robotic facilities efficiently considering the complexity of biological processes are missing. We present an automated experiment facility that integrates online data handling, visualization and treatment using multivariate analysis approaches to design and operate dynamical experimental campaigns in up to 48 mini-bioreactors (8⁻12 mL) in parallel. In this study, the characterization of Saccharomyces cerevisiae AH22 secreting recombinant endopolygalacturonase is performed, running and comparing 16 experimental conditions in triplicate. Data-driven multivariate methods were developed to allow for fast, automated decision making as well as online predictive data analysis regarding endopolygalacturonase production. Using dynamic process information, a cultivation with abnormal behavior could be detected by principal component analysis as well as two clusters of similarly behaving cultivations, later classified according to the feeding rate. By decision tree analysis, cultivation conditions leading to an optimal recombinant product formation could be identified automatically. The developed method is easily adaptable to different strains and cultivation strategies, and suitable for automatized process development reducing the experimental times and costs.

Automated Cell Treatment for Competence and Transformation of Escherichia coli in a High-Throughput Quasi-Turbidostat Using Microtiter Plates.

Metabolic engineering and genome editing strategies often lead to large strain libraries of a bacterial host. Nevertheless, the generation of competent cells is the basis for transformation and subsequent screening of these strains. While preparation of competent cells is a standard procedure in flask cultivations, parallelization becomes a challenging task when working with larger libraries and liquid handling stations as transformation efficiency depends on a distinct physiological state of the cells. We present a robust method for the preparation of competent cells and their transformation. The strength of the method is that all cells on the plate can be maintained at a high growth rate until all cultures have reached a defined cell density regardless of growth rate and lag phase variabilities. This allows sufficient transformation in automated high throughput facilities and solves important scheduling issues in wet-lab library screenings. We address the problem of different growth rates, lag phases, and initial cell densities inspired by the characteristics of continuous cultures. The method functions on a fully automated liquid handling platform including all steps from the inoculation of the liquid cultures to plating and incubation on agar plates. The key advantage of the developed method is that it enables cell harvest in 96 well plates at a predefined time by keeping fast growing cells in the exponential phase as in turbidostat cultivations. This is done by a periodic monitoring of cell growth and a controlled dilution specific for each well. With the described methodology, we were able to transform different strains in parallel. The transformants produced can be picked and used in further automated screening experiments. This method offers the possibility to transform any combination of strain- and plasmid library in an automated high-throughput system, overcoming an important bottleneck in the high-throughput screening and the overall chain of bioprocess development.

[Resource utilisation and cost of amblyopia treatment]. / Ressourcenverbrauch und Kosten der Amblyopiebehandlung.

BACKGROUND: The cost-effectiveness of screening for amblyopia is a controversial issue of international debate. The purpose of this study was to estimate the cost of amblyopia treatment to be used as a component for modelling the cost-effectiveness of prevention programmes. Cost was calculated from the perspective of the German social health insurance in the year 2002. MATERIALS AND METHODS: A standardised detailed survey was conducted in writing among 13 experienced experts in amblyopia treatment from various offices and strabismological units in Germany. Average volumes of treatment items were estimated for a maximum treatment period of nine years. Cost was calculated using administrative prices (based on the social health insurance's uniform fee schedule for physician services and reference prices for therapeutic aids) and market prices. RESULTS: The questionnaires were fully completed by 12 of the 13 experts. The mean total cost of treatment was estimated at 2.472 Euro (95 %-CI: 1.171 - 3.774) for strabismic amblyopia and 2.051 Euro (95 %-CI: 426 - 3.675) for amblyopia of refractive origin. About 70 % of the total cost was caused by the therapeutic aids (e. g. glasses, patches). The price of the patches had a marked impact on the total treatment cost. CONCLUSIONS: The results may be used for modelling the cost-effectiveness of screening programmes for the prevention of amblyopia.