Robotic Platform for Parallelized Cultivation and Monitoring of Microbial Growth Parameters in Microwell Plates

Knepper, Andreas; Heiser, Michael; Glauche, Florian; Neubauer, Peter

doi:10.1177/2211068214547231

Cited by 37 publications

(42 citation statements)

References 27 publications

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“…In addition, substrate consumption or product formation can be efficiently determined using spectrophotometric MTP‐based assays . Here, the integration of MBR systems with liquid handling robots provides the possibility to sample microbial cultivations in an automated way …”

Section: Introductionmentioning

confidence: 99%

Less Sacrifice, More Insight: Repeated Low‐Volume Sampling of Microbioreactor Cultivations Enables Accelerated Deep Phenotyping of Microbial Strain Libraries

Hemmerich

Tenhaef

Steffens

et al. 2018

Biotechnology Journal

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With modern genetic engineering tools, high number of potentially improved production strains can be created in a short time. This results in a bottleneck in the succeeding step of bioprocess development, which can be handled by accelerating quantitative microbial phenotyping. Miniaturization and automation are key technologies to achieve this goal. In this study, a novel workflow for repeated low‐volume sampling of BioLector‐based cultivation setups is presented. Six samples of 20 μL each can be taken automatically from shaken 48‐well microtiter plates without disturbing cell population growth. The volume is sufficient for quantification of substrate and product concentrations by spectrophotometric‐based enzyme assays. From transient concentration data and replicate cultures, valid performance indicators (titers, rates, yields) are determined through process modeling and random error propagation analysis. Practical relevance of the workflow is demonstrated with a set of five genome‐reduced Corynebacterium glutamicum strains that are engineered for Sec‐mediated heterologous cutinase secretion. Quantitative phenotyping of this strain library led to the identification of a strain with a 1.6‐fold increase in cutinase yield. The prophage‐free strain carries combinatorial deletions of three gene clusters (Δ3102‐3111, Δ3263‐3301, and Δ3324‐3345) of which the last two likely contain novel target genes to foster rational engineering of heterologous cutinase secretion in C. glutamicum.

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Section: Introductionmentioning

confidence: 99%

Less Sacrifice, More Insight: Repeated Low‐Volume Sampling of Microbioreactor Cultivations Enables Accelerated Deep Phenotyping of Microbial Strain Libraries

Hemmerich

Tenhaef

Steffens

et al. 2018

Biotechnology Journal

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“…Recently, Knepper et al reported on robotic workflows for intermittent measurement of OD, pH and metabolites from cultures in 96-well plates in seven cycles at fixed times during 48 h cultivations [18]. Their successive sampling from plates incubated without humidity control led to a total volume reduction of 47% per well over 48 hours.…”

Section: Discussionmentioning

confidence: 99%

Bioprocess automation on a Mini Pilot Plant enables fast quantitative microbial phenotyping

Unthan¹,

Radek²,

Wiechert³

et al. 2015

Microb Cell Fact

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BackgroundThe throughput of cultivation experiments in bioprocess development has drastically increased in recent years due to the availability of sophisticated microliter scale cultivation devices. However, as these devices still require time-consuming manual work, the bottleneck was merely shifted to media preparation, inoculation and finally the analyses of cultivation samples. A first step towards solving these issues was undertaken in our former study by embedding a BioLector in a robotic workstation. This workstation already allowed for the optimization of heterologous protein production processes, but remained limited when aiming for the characterization of small molecule producer strains. In this work, we extended our workstation to a versatile Mini Pilot Plant (MPP) by integrating further robotic workflows and microtiter plate assays that now enable a fast and accurate phenotyping of a broad range of microbial production hosts.ResultsA fully automated harvest procedure was established, which repeatedly samples up to 48 wells from BioLector cultivations in response to individually defined trigger conditions. The samples are automatically clarified by centrifugation and finally frozen for subsequent analyses. Sensitive metabolite assays in 384-well plate scale were integrated on the MPP for the direct determination of substrate uptake (specifically D-glucose and D-xylose) and product formation (specifically amino acids). In a first application, we characterized a set of Corynebacterium glutamicum L-lysine producer strains and could rapidly identify a unique strain showing increased L-lysine titers, which was subsequently confirmed in lab-scale bioreactor experiments. In a second study, we analyzed the substrate uptake kinetics of a previously constructed D-xylose-converting C. glutamicum strain during cultivation on mixed carbon sources in a fully automated experiment.ConclusionsThe presented MPP is designed to face the challenges typically encountered during early-stage bioprocess development. Especially the bottleneck of sample analyses from fast and parallelized microtiter plate cultivations can be solved using cutting-edge robotic automation. As robotic workstations become increasingly attractive for biotechnological research, we expect our setup to become a template for future bioprocess development.

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“…Glucose release experiments from polysaccharides are based on an EnPresso Y defined medium (from BioSilta, Cambridge, UK) (see ). The computerized platform with a Hamilton robot is introduced in .…”

Section: Methodsmentioning

confidence: 99%

Rapid process synthesis supported by a unified modular software framework

Herold

Krämer

Violet

et al. 2017

Engineering in Life Sciences

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Rapid process synthesis supported by a unified modular software frameworkAlthough known to be very powerful, the widespread application of model-based techniques is still significantly hampered in the area of bio-processes. Reasons for this situation can be found along the whole chain to set up and implement such approaches. In a time-consuming step, models are typically hand-crafted. Whether alternatives of better models exist to actually fulfill the final goals is undocumented, most often even unknown. In a next step, model-based process control methods are hand-coded in an error-prone procedure. For many of these methods given in the literature, only simulation studies are shown, leaving the interested reader with the unanswered question whether the implementation of a specific method in a real process is viable. As the potentially time-consuming implementation of such a method presents a risk for a rapid process development, promising candidates may be overlooked. To remediate this unsatisfactory situation, a combination of theoretical methods and information technology is proposed here. By an exemplarily realized software tool, it is shown how such an environment helps to promote model-based optimization, supervision, and control of bio-processes and allows for an inexpensive test of new ideas as well in real-life experiments. The contribution concentrates on an overview of a possible software architecture with respect to necessary methods and a meaningful information strategy, highlighting some of the more crucial building blocks. Experimental results exploiting parts of the proposed methods are given for a yeast strain synthesizing a product of industrial interest.

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Robotic Platform for Parallelized Cultivation and Monitoring of Microbial Growth Parameters in Microwell Plates

Cited by 37 publications

References 27 publications

Less Sacrifice, More Insight: Repeated Low‐Volume Sampling of Microbioreactor Cultivations Enables Accelerated Deep Phenotyping of Microbial Strain Libraries

Less Sacrifice, More Insight: Repeated Low‐Volume Sampling of Microbioreactor Cultivations Enables Accelerated Deep Phenotyping of Microbial Strain Libraries

Bioprocess automation on a Mini Pilot Plant enables fast quantitative microbial phenotyping

Rapid process synthesis supported by a unified modular software framework

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