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Automated single cell microbioreactor for monitoring intracellular dynamics and cell growth in free solution.

ABSTRACT: We report an automated microfluidic-based platform for single cell analysis that allows for cell culture in free solution with the ability to control the cell growth environment. Using this approach, cells are confined by the sole action of gentle fluid flow, thereby enabling non-perturbative analysis of cell growth away from solid boundaries. In addition, the single cell microbioreactor allows for precise and time-dependent control over cell culture media, with the combined ability to observe the dynamics of non-adherent cells over long time scales. As a proof-of-principle demonstration, we used the platform to observe dynamic cell growth, gene expression, and intracellular diffusion of repressor proteins while precisely tuning the cell growth environment. Overall, this microfluidic approach enables the direct observation of cellular dynamics with exquisite control over environmental conditions, which will be useful for quantifying the behaviour of single cells in well-defined media.

SUBMITTER: Johnson-Chavarria EM

PROVIDER: S-EPMC4112730 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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Automated single cell microbioreactor for monitoring intracellular dynamics and cell growth in free solution.

Johnson-Chavarria Eric M EM Agrawal Utsav U Tanyeri Melikhan M Kuhlman Thomas E TE Schroeder Charles M CM

Lab on a chip 20140519 15

We report an automated microfluidic-based platform for single cell analysis that allows for cell culture in free solution with the ability to control the cell growth environment. Using this approach, cells are confined by the sole action of gentle fluid flow, thereby enabling non-perturbative analysis of cell growth away from solid boundaries. In addition, the single cell microbioreactor allows for precise and time-dependent control over cell culture media, with the combined ability to observe t ...[more]

PMID: 24836754

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Project description:Microbioreactors play a critical role in process development as they reduce reagent requirements and can facilitate high-throughput screening of process parameters and culture conditions. Here, we have demonstrated and explained in detail, for the first time, the amenability of the automated ambr15 cell culture microbioreactor system for the development of scalable adherent human mesenchymal multipotent stromal/stem cell (hMSC) microcarrier culture processes. This was achieved by first improving suspension and mixing of the microcarriers and then improving cell attachment thereby reducing the initial growth lag phase. The latter was achieved by using only 50% of the final working volume of medium for the first 24?h and using an intermittent agitation strategy. These changes resulted in >150% increase in viable cell density after 24?h compared to the original process (no agitation for 24?h and 100% working volume). Using the same methodology as in the ambr15, similar improvements were obtained with larger scale spinner flask studies. Finally, this improved bioprocess methodology based on a serum-based medium was applied to a serum-free process in the ambr15, resulting in >250% increase in yield compared to the serum-based process. At both scales, the agitation used during culture was the minimum required for microcarrier suspension, NJS . The use of the ambr15, with its improved control compared to the spinner flask, reduced the coefficient of variation on viable cell density in the serum containing medium from 7.65% to 4.08%, and the switch to serum free further reduced these to 1.06-0.54%, respectively. The combination of both serum-free and automated processing improved the reproducibility more than 10-fold compared to the serum-based, manual spinner flask process. The findings of this study demonstrate that the ambr15 microbioreactor is an effective tool for bioprocess development of hMSC microcarrier cultures and that a combination of serum-free medium, control, and automation improves both process yield and consistency. Biotechnol. Bioeng. 2017;114: 2253-2266. © 2017 Wiley Periodicals, Inc.

Project description:BackgroundHigh-throughput methods are widely-used for strain screening effectively resulting in binary information regarding high or low productivity. Nevertheless achieving quantitative and scalable parameters for fast bioprocess development is much more challenging, especially for heterologous protein production. Here, the nature of the foreign protein makes it impossible to predict the, e.g. best expression construct, secretion signal peptide, inductor concentration, induction time, temperature and substrate feed rate in fed-batch operation to name only a few. Therefore, a high number of systematic experiments are necessary to elucidate the best conditions for heterologous expression of each new protein of interest.ResultsTo increase the throughput in bioprocess development, we used a microtiter plate based cultivation system (Biolector) which was fully integrated into a liquid-handling platform enclosed in laminar airflow housing. This automated cultivation platform was used for optimization of the secretory production of a cutinase from Fusarium solani pisi with Corynebacterium glutamicum. The online monitoring of biomass, dissolved oxygen and pH in each of the microtiter plate wells enables to trigger sampling or dosing events with the pipetting robot used for a reliable selection of best performing cutinase producers. In addition to this, further automated methods like media optimization and induction profiling were developed and validated. All biological and bioprocess parameters were exclusively optimized at microtiter plate scale and showed perfect scalable results to 1 L and 20 L stirred tank bioreactor scale.ConclusionsThe optimization of heterologous protein expression in microbial systems currently requires extensive testing of biological and bioprocess engineering parameters. This can be efficiently boosted by using a microtiter plate cultivation setup embedded into a liquid-handling system, providing more throughput by parallelization and automation. Due to improved statistics by replicate cultivations, automated downstream analysis, and scalable process information, this setup has superior performance compared to standard microtiter plate cultivation.

Project description:A few bacterial cells may be sufficient to produce a food-borne illness outbreak, provided that they are capable of adapting and proliferating on a food matrix. This is why any quantitative health risk assessment policy must incorporate methods to accurately predict the growth of bacterial populations from a small number of pathogens. In this aim, mathematical models have become a powerful tool. Unfortunately, at low cell concentrations, standard deterministic models fail to predict the fate of the population, essentially because the heterogeneity between individuals becomes relevant. In this work, a stochastic differential equation (SDE) model is proposed to describe variability within single-cell growth and division and to simulate population growth from a given initial number of individuals. We provide evidence of the model ability to explain the observed distributions of times to division, including the lag time produced by the adaptation to the environment, by comparing model predictions with experiments from the literature for Escherichia coli, Listeria innocua, and Salmonella enterica. The model is shown to accurately predict experimental growth population dynamics for both small and large microbial populations. The use of stochastic models for the estimation of parameters to successfully fit experimental data is a particularly challenging problem. For instance, if Monte Carlo methods are employed to model the required distributions of times to division, the parameter estimation problem can become numerically intractable. We overcame this limitation by converting the stochastic description to a partial differential equation (backward Kolmogorov) instead, which relates to the distribution of division times. Contrary to previous stochastic formulations based on random parameters, the present model is capable of explaining the variability observed in populations that result from the growth of a small number of initial cells as well as the lack of it compared to populations initiated by a larger number of individuals, where the random effects become negligible.

Dataset Information

Automated single cell microbioreactor for monitoring intracellular dynamics and cell growth in free solution.

Publications

Automated single cell microbioreactor for monitoring intracellular dynamics and cell growth in free solution.

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