Microfluidic Single-cell Cultivation Research Articles

Quantifying microbial robustness in dynamic environments using microfluidic single-cell cultivation

BackgroundMicroorganisms must respond to changes in their environment. Analysing the robustness of functions (i.e. performance stability) to such dynamic perturbations is of great interest in both laboratory and industrial settings. Recently, a quantification method capable of assessing the robustness of various functions, such as specific growth rate or product yield, across different conditions, time frames, and populations has been developed for microorganisms grown in a 96-well plate. In micro-titer-plates, environmental change is slow and undefined. Dynamic microfluidic single-cell cultivation (dMSCC) enables the precise maintenance and manipulation of microenvironments, while tracking single cells over time using live-cell imaging. Here, we combined dMSCC and a robustness quantification method to a pipeline for assessing performance stability to changes occurring within seconds or minutes.ResultsSaccharomyces cerevisiae CEN.PK113-7D, harbouring a biosensor for intracellular ATP levels, was exposed to glucose feast-starvation cycles, with each condition lasting from 1.5 to 48 min over a 20 h period. A semi-automated image and data analysis pipeline was developed and applied to assess the performance and robustness of various functions at population, subpopulation, and single-cell resolution. We observed a decrease in specific growth rate but an increase in intracellular ATP levels with longer oscillation intervals. Cells subjected to 48 min oscillations exhibited the highest average ATP content, but the lowest stability over time and the highest heterogeneity within the population.ConclusionThe proposed pipeline enabled the investigation of function stability in dynamic environments, both over time and within populations. The strategy allows for parallelisation and automation, and is easily adaptable to new organisms, biosensors, cultivation conditions, and oscillation frequencies. Insights on the microbial response to changing environments will guide strain development and bioprocess optimisation.Graphical

Experimental kS estimation: A comparison of methods for Corynebacterium glutamicum from lab to microfluidic scale.

Knowledge about the specific affinity of whole cells towarda substrate, commonly referred to as kS , is a crucial parameter for characterizing growth within bioreactors. State-of-the-art methodologies measure either uptake or consumption rates at different initial substrate concentrations. Alternatively, cell dry weight or respiratory data like online oxygen and carbon dioxide transfer rates can be used to estimate kS . In this work, a recently developed substrate-limited microfluidic single-cell cultivation (sl-MSCC)method is applied for the estimation of kS values under defined environmental conditions. This method is benchmarked with two alternative microtiter plate methods, namely high-frequency biomass measurement (HFB)and substrate-limited respiratory activity monitoring (sl-RA).As a model system, the substrate affinity kS of Corynebacterium glutamicum ATCC 13032 regarding glucose was investigated assuming a Monod-type growth response. A kS of <70.7 mg/L(with 95% probability) with HFB, 8.55 ± 1.38 mg/Lwith sl-RA, and 2.66 ± 0.99 mg/L with sl-MSCC was obtained. Whereas HFB and sl-RA are suitable for a fast initial kS estimation, sl-MSCC allows an affinity estimation by determining tD at concentrations less or equal to the kS value. Thus, sl-MSCC lays the foundation for strain-specific kS estimations under defined environmental conditions with additional insights into cell-to-cell heterogeneity.

Novel transfer learning schemes based on Siamese networks and synthetic data

Transfer learning schemes based on deep networks which have been trained on huge image corpora offer state-of-the-art technologies in computer vision. Here, supervised and semi-supervised approaches constitute efficient technologies which work well with comparably small data sets. Yet, such applications are currently restricted to application domains where suitable deep network models are readily available. In this contribution, we address an important application area in the domain of biotechnology, the automatic analysis of CHO-K1 suspension growth in microfluidic single-cell cultivation, where data characteristics are very dissimilar to existing domains and trained deep networks cannot easily be adapted by classical transfer learning. We propose a novel transfer learning scheme which expands a recently introduced Twin-VAE architecture, which is trained on realistic and synthetic data, and we modify its specialized training procedure to the transfer learning domain. In the specific domain, often only few to no labels exist and annotations are costly. We investigate a novel transfer learning strategy, which incorporates a simultaneous retraining on natural and synthetic data using an invariant shared representation as well as suitable target variables, while it learns to handle unseen data from a different microscopy technology. We show the superiority of the variation of our Twin-VAE architecture over the state-of-the-art transfer learning methodology in image processing as well as classical image processing technologies, which persists, even with strongly shortened training times and leads to satisfactory results in this domain. The source code is available at https://github.com/dstallmann/transfer_learning_twinvae, works cross-platform, is open-source and free (MIT licensed) software. We make the data sets available at https://pub.uni-bielefeld.de/record/2960030.

Microfluidic single-cell scale-down bioreactors: A proof-of-concept for the growth of Corynebacterium glutamicum at oscillating pH values.

In large-scale bioreactors, gradients in cultivation parameters such as oxygen, substrate, and pH result in fluctuating cell environments. pH fluctuations were identified as a critical parameter for bioprocess performance. Traditionally, scale-down systems at the laboratory scale are used to analyze the effects of fluctuating pH values on strains and thus process performance. Here, we demonstrate the application of dynamic microfluidic single-cell cultivation (dMSCC) as a novel scale-down system for the characterization of Corynebacterium glutamicum growth using oscillating pH conditions as a model stress factor. A detailed comparison between two-compartment reactor (two-CR) scale-down experiments and dMSCC was performed for one specific pH oscillation between reference pH 7 (~8 min) and disturbed pH 6 (~2 min). Similar reductions in growth rates were observed in both systems (dMSCC 21% and two-CR 27%) compared to undisturbed cultivation at pH 7. Afterward, systematic experiments at symmetric and asymmetric pH oscillations, between pH ranges of 4-6 and 8-11 and different intervals from 1to 20 min, were performed to demonstrate the unique application range and throughput of the dMSCC system. Finally, the strength of the dMSCC application was demonstrated by mimicking fluctuating environmental conditions of a putative large-scale bioprocess, which is difficult to conduct using two-CRs.

Microfluidic Reproduction of Dynamic Bioreactor Environment Based on Computational Lifelines

The biotechnological production of fine chemicals, proteins and pharmaceuticals is usually hampered by loss of microbial performance during scale-up. This challenge is mainly caused by discrepancies between homogeneous environmental conditions at laboratory scale, where bioprocesses are optimized, and inhomogeneous conditions in large-scale bioreactors, where production takes place. Therefore, to improve strain selection and process development, it is of great interest to characterize these fluctuating conditions at large-scale and to study their effects on microbial cells. In this paper, we demonstrate the potential of computational fluid dynamics (CFD) simulation of large-scale bioreactors combined with dynamic microfluidic single-cell cultivation (dMSCC). Environmental conditions in a 200 L bioreactor were characterized with CFD simulations. Computational lifelines were determined by combining simulated turbulent multiphase flow, mass transport and particle tracing. Glucose availability for Corynebacterium glutamicum cells was determined. The reactor was simulated with average glucose concentrations of 6 g m−3, 10 g m−3 and 16 g m−3. The resulting computational lifelines, discretized into starvation and abundance regimes, were used as feed profiles for the dMSCC to investigate how varying glucose concentration affects cell physiology and growth rate. In this study, each colony in the dMSCC device represents a single cell as it travels through the reactor. Under oscillating conditions reproduced in the dMSCC device, a decrease in growth rate of about 40% was observed compared to continuous supply with the same average glucose availability. The presented approach provides insights into environmental conditions observed by microorganisms in large-scale bioreactors. It also paves the way for an improved understanding of how inhomogeneous environmental conditions influence cellular physiology, growth and production.

Growth and eGFP Production of CHO-K1 Suspension Cells Cultivated From Single Cell to Laboratory Scale.

Scaling down bioproduction processes has become a major driving force for more accelerated and efficient process development over the last decades. Especially expensive and time-consuming processes like the production of biopharmaceuticals with mammalian cell lines benefit clearly from miniaturization, due to higher parallelization and increased insights while at the same time decreasing experimental time and costs. Lately, novel microfluidic methods have been developed, especially microfluidic single-cell cultivation (MSCC) devices have been proved to be valuable to miniaturize the cultivation of mammalian cells. So far, growth characteristics of microfluidic cultivated cell lines were not systematically compared to larger cultivation scales; however, validation of a miniaturization tool against initial cultivation scales is mandatory to prove its applicability for bioprocess development. Here, we systematically investigate growth, morphology, and eGFP production of CHO-K1 cells in different cultivation scales ranging from a microfluidic chip (230 nl) to a shake flask (125 ml) and laboratory-scale stirred tank bioreactor (2.0 L). Our study shows a high comparability regarding specific growth rates, cellular diameters, and eGFP production, which proves the feasibility of MSCC as a miniaturized cultivation tool for mammalian cell culture. In addition, we demonstrate that MSCC provides insights into cellular heterogeneity and single-cell dynamics concerning growth and production behavior which, when occurring in bioproduction processes, might severely affect process robustness.

Growth Response and Recovery of Corynebacterium glutamicum Colonies on Single-Cell Level Upon Defined pH Stress Pulses.

Bacteria respond to pH changes in their environment and use pH homeostasis to keep the intracellular pH as constant as possible and within a small range. A change in intracellular pH influences enzyme activity, protein stability, trace element solubilities and proton motive force. Here, the species Corynebacterium glutamicum was chosen as a neutralophilic and moderately alkali-tolerant bacterium capable of maintaining an internal pH of 7.5 ± 0.5 in environments with external pH values ranging between 5.5 and 9. In recent years, the phenotypic response of C. glutamicum to pH changes has been systematically investigated at the bulk population level. A detailed understanding of the C. glutamicum cell response to defined short-term pH perturbations/pulses is missing. In this study, dynamic microfluidic single-cell cultivation (dMSCC) was applied to analyze the physiological growth response of C. glutamicum to precise pH stress pulses at the single-cell level. Analysis by dMSCC of the growth behavior of colonies exposed to single pH stress pulses (pH = 4, 5, 10, 11) revealed a decrease in viability with increasing stress duration w. Colony regrowth was possible for all tested pH values after increasing lag phases for which stress durations w were increased from 5 min to 9 h. Furthermore, single-cell analyses revealed heterogeneous regrowth of cells after pH stress, which can be categorized into three physiological states. Cells in the first physiological state continued to grow without interruption after pH stress pulse. Cells in the second physiological state rested for several hours after pH stress pulse before they started to grow again after this lag phase, and cells in the third physiological state did not divide after the pH stress pulse. This study provides the first insights into single-cell responses to acidic and alkaline pH stress by C. glutamicum.

(Optochemical) Control of Synthetic Microbial Coculture Interactions on a Microcolony Level.

Synthetic microbial cocultures carry enormous potential for applied biotechnology and are increasingly the subject of fundamental research. So far, most cocultures have been designed and characterized based on bulk cultivations without considering the potentially highly heterogeneous and diverse single-cell behavior. However, an in-depth understanding of cocultures including their interacting single cells is indispensable for the development of novel cultivation approaches and control of cocultures. We present the development, validation, and experimental characterization of an optochemically controllable bacterial coculture on a microcolony level consisting of two Corynebacterium glutamicum strains. Our coculture combines an l-lysine auxotrophic strain together with a l-lysine-producing variant carrying the genetically IPTG-mediated induction of l-lysine production. We implemented two control approaches utilizing IPTG as inducer molecule. First, unmodified IPTG was supplemented to the culture enabling a medium-based control of the production of l-lysine, which serves as the main interacting component. Second, optochemical control was successfully performed by utilizing photocaged IPTG activated by appropriate illumination. Both control strategies were validated studying cellular growth on a microcolony level. The novel microfluidic single-cell cultivation strategies applied in this work can serve as a blueprint to validate cellular control strategies of synthetic mono- and cocultures with single-cell resolution at defined environmental conditions.

Towards an automatic analysis of CHO-K1 suspension growth in microfluidic single-cell cultivation.

Innovative microfluidic systems carry the promise to greatly facilitate spatio-temporal analysis of single cells under well-defined environmental conditions, allowing novel insights into population heterogeneity and opening new opportunities for fundamental and applied biotechnology. Microfluidics experiments, however, are accompanied by vast amounts of data, such as time series of microscopic images, for which manual evaluation is infeasible due to the sheer number of samples. While classical image processing technologies do not lead to satisfactory results in this domain, modern deep-learning technologies, such as convolutional networks can be sufficiently versatile for diverse tasks, including automatic cell counting as well as the extraction of critical parameters, such as growth rate. However, for successful training, current supervised deep learning requires label information, such as the number or positions of cells for each image in a series; obtaining these annotations is very costly in this setting. We propose a novel machine-learning architecture together with a specialized training procedure, which allows us to infuse a deep neural network with human-powered abstraction on the level of data, leading to a high-performing regression model that requires only a very small amount of labeled data. Specifically, we train a generative model simultaneously on natural and synthetic data, so that it learns a shared representation, from which a target variable, such as the cell count, can be reliably estimated. The project is cross-platform, open-source and free (MIT licensed) software. We make the source code available at https://github.com/dstallmann/cell_cultivation_analysis; the dataset is available at https://pub.uni-bielefeld.de/record/2945513.

Dynamic Environmental Control in Microfluidic Single-Cell Cultivations: From Concepts to Applications.

Microfluidic single-cell cultivation (MSCC) is an emerging field within fundamental as well as applied biology. During the last years, most MSCCs were performed at constant environmental conditions. Recently, MSCC at oscillating and dynamic environmental conditions has started to gain significant interest in the research community for the investigation of cellular behavior. Herein, an overview of this topic is given and microfluidic concepts that enable oscillating and dynamic control of environmental conditions with a focus on medium conditions are discussed, and their application in single-cell research for the cultivation of both mammalian and microbial cell systems is demonstrated. Furthermore, perspectives for performing MSCC at complex dynamic environmental profiles of single parameters and multiparameters (e.g., pH and O2 ) in amplitude and time are discussed. The technical progress in this field provides completely new experimental approaches and lays the foundation for systematic analysis of cellular metabolism at fluctuating environments.

DMSCC: a microfluidic platform for microbial single-cell cultivation of Corynebacterium glutamicum under dynamic environmental medium conditions.

In nature and in technical systems, microbial cells are often exposed to rapidly fluctuating environmental conditions. These conditions can vary in quality, e.g., the existence of a starvation zone, and quantity, e.g., the average residence time in this zone. For strain development and process design, cellular response to such fluctuations needs to be systematically analysed. However, the existing methods for physically imitating rapidly changing environmental conditions are limited in spatio-temporal resolution. Hence, we present a novel microfluidic system for cultivation of single cells and small cell clusters under dynamic environmental conditions (dynamic microfluidic single-cell cultivation (dMSCC)). This system enables the control of nutrient availability and composition between two media with second to minute resolution. We validate our technology using the industrially relevant model organism Corynebacterium glutamicum. The organism was exposed to different oscillation frequencies between nutrient excess (feasts) and scarcity (famine). The resulting changes in cellular physiology, such as the colony growth rate and cell morphology, were analysed and revealed significant differences in the growth rate and cell length between the different conditions. dMSCC also allows the application of defined but randomly changing nutrient conditions, which is important for reproducing more complex conditions from natural habitats and large-scale bioreactors. The presented system lays the foundation for the cultivation of cells under complex changing environmental conditions.

A microfluidic photobioreactor for simultaneous observation and cultivation of single microalgal cells or cell aggregates

Microalgae are an ubiquitous and powerful driver of geochemical cycles which have formed Earth’s biosphere since early in the evolution. Lately, microalgal research has been strongly stimulated by economic potential expected in biofuels, wastewater treatment, and high-value products. Similar to bacteria and other microorganisms, most work so far has been performed on the level of suspensions which typically contain millions of algal cells per millilitre. The thus obtained macroscopic parameters average cells, which may be in various phases of their cell cycle or even, in the case of microbial consortia, cells of different species. This averaging may obscure essential features which may be needed for the correct understanding and interpretation of investigated processes. In contrast to these conventional macroscopic cultivation and measuring tools, microfluidic single-cell cultivation systems represent an excellent alternative to study individual cells or a small number of mutually interacting cells in a well-defined environment. A novel microfluidic photobioreactor was developed and successfully tested by the photoautotrophic cultivation of Chlorella sorokiniana. The reported microbioreactor facilitates automated long-term cultivation of algae with controlled temperature and with an illumination adjustable over a wide range of photon flux densities. Chemical composition of the medium in the microbioreactor can be stabilised or modulated rapidly to study the response of individual cells. Furthermore, the algae are cultivated in one focal plane and separate chambers, enabling single-cell level investigation of over 100 microcolonies in parallel. The developed platform can be used for systematic growth studies, medium screening, species interaction studies, and the thorough investigation of light-dependent growth kinetics.

Microbial single-cell growth response at defined carbon limiting conditions.

Growth is one of the most fundamental characteristics of life, but detailed knowledge regarding growth at nutrient limiting conditions remains scarce. In recent years progress in microfluidic single-cell analysis and cultivation techniques has given insights into many fundamental growth characteristics such as growth homeostasis, aging and cell division of microbial cells. Using microfluidic single-cell cultivation technologies we examined how single-cell growth at defined carbon conditions, ranging from strongly limiting conditions (0.01 mmol L−1) to a carbon surplus (100 mmol L−1), influenced cell-to-cell variability. The experiments showed robust growth of populations at intermediate concentrations and cell-to-cell variability was higher at low and high carbon concentrations, among an isogenic population. Single-cell growth at extremely limiting conditions led not only to significant variability of division times, but also to an increased number of cells that did not pursue growth. Overall, the results demonstrate that cellular behaviour shows robust, Monod-like growth, with significant cell-to-cell heterogeneity at extreme limiting conditions, resembling natural habitats. Due to this significant influence of the environment on cellular physiology, more carefulness needs to be given future microfluidic single-cell experiments. Consequently, our results lay the foundation for the re-interpretation and design of workflows for future experiments aiming at an improved understanding of cell growth mechanisms.

Germination and Growth Analysis of Streptomyces lividans at the Single-Cell Level Under Varying Medium Compositions.

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 variations and unexpected growth and production differences. Population heterogeneity is suspected to be one responsible factor, which is so far not systematically investigated at the single-cell level. Novel microfluidic single-cell cultivation devices offer promising solutions to investigate these phenomena. In this study, we investigated the germination and growth behavior of Streptomyces lividans TK24 under varying medium compositions on different complexity levels (i.e., mycelial growth, hyphal growth and tip elongation) on single-cell level. Our analysis reveals a remarkable stability within growth and germination of spores and early mycelium development when exposed to constant and defined environments. We show that spores undergo long metabolic adaptation processes of up to > 30 h to adjust to new medium conditions, rather than using a “persister” strategy as a possibility to cope with rapidly changing environments. Due to this uniform behavior, we conclude that S. lividans can be cultivated quite robustly under constant environmental conditions as provided by microfluidic cultivation approaches. Failure and non-reproducible cultivations are thus most likely to be found in less controllable larger-scale cultivation workflows and as a result of environmental gradients within large-scale cultivations.

Coarse‐grained simulation for the analysis of microfluidic single‐cell cultivation

Coarse‐grained simulation for the analysis of microfluidic single‐cell cultivation

Visualization of tandem repeat mutagenesis in Bacillus subtilis

Mutations are crucial for the emergence and evolution of proteins with novel functions, and thus for the diversity of life. Tandem repeats (TRs) are mutational hot spots that are present in the genomes of all organisms. Understanding the molecular mechanism underlying TR mutagenesis at the level of single cells requires the development of mutation reporter systems. Here, we present a mutation reporter system that is suitable to visualize mutagenesis of TRs occurring in single cells of the Gram-positive model bacterium Bacillus subtilis using microfluidic single-cell cultivation. The system allows measuring the elimination of TR units due to growth rate recovery. The cultivation of bacteria carrying the mutation reporter system in microfluidic chambers allowed us for the first time to visualize the emergence of a specific mutation at the level of single cells. The application of the mutation reporter system in combination with microfluidics might be helpful to elucidate the molecular mechanism underlying TR (in)stability in bacteria. Moreover, the mutation reporter system might be useful to assess whether mutations occur in response to nutrient starvation.

Spatiotemporal microbial single-cell analysis using a high-throughput microfluidics cultivation platform.

Cell-to-cell heterogeneity typically evolves due to a manifold of biological and environmental factors and special phenotypes are often relevant for the fate of the whole population but challenging to detect during conventional analysis. We demonstrate a microfluidic single-cell cultivation platform that incorporates several hundred growth chambers, in which isogenic bacteria microcolonies growing in cell monolayers are tracked by automated time-lapse microscopy with spatiotemporal resolution. The device was not explicitly developed for a specific organism, but has a very generic configuration suitable for various different microbial organisms. In the present study, we analyzed Corynebacterium glutamicum microcolonies, thereby generating complete lineage trees and detailed single-cell data on division behavior and morphology in order to demonstrate the platform's overall capabilities. Furthermore, the occurrence of spontaneously induced stress in individual C. glutamicum cells was investigated by analyzing strains with genetically encoded reporter systems and optically visualizing SOS response. The experiments revealed spontaneous SOS induction in the absence of any external trigger comparable to results obtained by flow cytometry (FC) analyzing cell samples from conventional shake flask cultivation. Our microfluidic setup delivers detailed single-cell data with spatial and temporal resolution; complementary information to conventional FC results.

Microfluidic single-cell analysis links boundary environments and individual microbial phenotypes.

Life is based on the cell as the elementary replicative and self-sustaining biological unit. Each single cell constitutes an independent and highly dynamic system with a remarkable individuality in a multitude of physiological traits and responses to environmental fluctuations. However, with traditional population-based cultivation set-ups, it is not possible to decouple inherent stochastic processes and extracellular contributions to phenotypic individuality for two central reasons: the lack of environmental control and the occlusion of single-cell dynamics by the population average. With microfluidic single-cell analysis as a new cell assay format, these issues can now be addressed, enabling cultivation and time-resolved analysis of single cells in precisely manipulable extracellular environments beyond the bulk. In this article, we explore the interplay of cellular physiology and environment at a single-cell level. We review biological basics that govern the functional state of the cell and put them in context with physical fundamentals that shape the extracellular environment. Furthermore, the significance of single-cell growth rates as pivotal descriptors for global cellular physiology is discussed and highlighted by selected studies. These examples illustrate the unique opportunities of microfluidic single-cell cultivation in combination with growth rate analysis, addressing questions of fundamental bio(techno)logical interest.

Microfluidic single-cell cultivation chip with controllable immobilization and selective release of yeast cells

We present a microfluidic cell-culture chip that enables trapping, cultivation and release of selected individual cells. The chip is fabricated by a simple hybrid glass-SU-8-PDMS approach, which produces a completely transparent microfluidic system amenable to optical inspection. Single cells are trapped in a microfluidic channel using mild suction at defined cell immobilization orifices, where they are cultivated under controlled environmental conditions. Cells of interest can be individually and independently released for further downstream analysis by applying a negative dielectrophoretic force via the respective electrodes located at each immobilization site. The combination of hydrodynamic cell-trapping and dielectrophoretic methods for cell releasing enables highly versatile single-cell manipulation in an array-based format. Computational fluid dynamics simulations were performed to estimate the properties of the system during cell trapping and releasing. Polystyrene beads and yeast cells have been used to investigate and characterize the different functions and to demonstrate biological compatibility and viability of the platform for single-cell applications in research areas such as systems biology.