Single-cell Cultivation Research Articles

Precision isolation and cultivation of single cells by vortex and flat-top laser ejection.

Single-cell isolation stands as a critical step in single-cell studies, and single-cell ejection technology based on laser induced forward transfer technology (LIFT) is considered one of the most promising methods in this regard for its ability of visible isolating single cell from complex samples. In this study, we improve the LIFT technology and introduce optical vortex laser-induced forward transfer (OV-LIFT) and flat-top laser-induced forward transfer (FT-LIFT) by utilizing spatial light modulator (SLM), aiming to enhance the precision of single-cell sorting and the cell's viability after ejection. Experimental results demonstrate that applying vortex and flat-top beams during the sorting and collection process enables precise retrieval of single cells within diameter ranges of 50 μm and 100 μm, respectively. The recovery rates of Saccharomyces cerevisiae and Escherichia coli DH5α single cell ejected by vortex beam are 89 and 78%, by flat-top beam are 85 and 57%. When employing Gaussian beam sorting, the receiving range extends to 400 μm, with cultivation success rates of S. cerevisiae and E. coli DH5α single cell are 48 and 19%, respectively. This marks the first application of different mode beams in the ejection and cultivation of single cells, providing a novel and effective approach for the precise isolation and improving the viability of single cells.

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

Optical-based microbubble for on-demand droplet release from static droplet array (SDA) for dispensing one droplet into one tube

Static droplet array (SDA) is a pivotal tool for high-capacity screening assays, yet extraction and collection the target droplets that contain unique analytes or cells from the SDA remains one major technical bottleneck that limits its broader application. Here we present an optical-based on-demand droplet release (OODR) system by incorporating a 1064 nm laser-responsive indium tin oxide (ITO) layer into a chamber array-based droplet microfluidic chip. By focusing the 1064 nm laser onto the ITO layer, microbubbles can be created via local heating to selectively push-out the droplets from the chamber. Then the released droplet is readily exported in a one-droplet-one-tube (ODOT) manner by the inherent capillary force into pipette tip. Releasing of the droplets containing fluorescein sodium demonstrated ∼100% successful rate (9 out of 6400 droplets were successfully released) and low residual (only ∼5% of the droplet volume remains in the chamber). White or fluorescence image-based releasing of single-cell-droplets directly after cell loading or multi-cells-droplets derived from on-chip single-cell cultivation for both E. coli and yeast cells further demonstrated the wide applicability of OODR. The present system is user-friendly and has the potential to be applied in various high-throughput screening assays, including single molecule/cell analysis, drug screening, and phenotype-based cell sorting.

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.

A novel high-throughput approach for transforming filamentous fungi employing a droplet-based microfluidic platform

Droplet-based microfluidic technology is a powerful tool for single-cell cultivation and rapid isolation of bacteria, yeasts and algae. However, it has been of limited use for studies of filamentous fungi due to the fast growth of their branched hyphae. The long regeneration time for fungal protoplasts and low-throughput screening methods are inherent problems for current genetic transformation techniques. Therefore, we have developed a novel droplet-based method for the filamentous fungus Trichoderma reesei expressing green fluorescent protein (GFP) as a marker. This approach presented several outstanding advantages over the traditional transformation method, including a 7-fold reduction in time for T. reesei protoplast regeneration, an 8-fold increase in regeneration frequency, and a screening speed of up to 8,000 droplets min−1. In this study, we encapsulated and incubated the gfp-transformed T. reesei protoplasts in droplets for 24 h, screened the droplets in a high-throughput assay, and eventually collected a transformant library with over 96 % of the candidates transformed with the marker gene. This versatile approach should make fungi more amenable to genetic manipulation and encourage strain improvements for industrial applications.

Single-Cell-Based High-Throughput Cultivation and Functional Characterization of Biosurfactant-Producing Bacteria from Soil and Oilfield-Produced Water.

Biosurfactants are a group of surface-active compounds that can be produced by diverse microorganisms. They have been widely used in various industrial fields. Reducing production costs, improving efficiency, and collecting more diverse producing strains have become major challenges in the biosurfactant industry. These challenges could be overcome by screening for more diverse and efficient biosurfactant-producing strains. The conventional methods for the isolation and functional characterization of microorganisms are laborious and biased toward fast-growing or strongly competitive microorganisms. Here, we established a high-throughput approach of single-cell-based cultivation and functional characterization of biosurfactant-producing bacteria (SCCBB). This approach combines single-cell cultivation with the detection of optical distortions. Using this approach, we isolated 431 strains with biosurfactant production potential from petroleum-contaminated soil and oilfield-produced water. The surfactant production capabilities of the strains were subsequently validated using surface tension measurements, TLC, and CMC measurements. To investigate the industrial production potential, we optimized the production conditions of a representative glycolipids-producing strain, Pseudomonas sp. L01, using response surface methodology (RSM). Optimal conditions yielded a crude biosurfactant yield of 8.43 g/L in a flask. Our work provides a high-throughput approach to the isolation and screening of biosurfactant-producing bacteria, as well as other functional bacteria in a wide range of fields.

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.

Single-Cell Analysis of CHO Cells Reveals Clonal Heterogeneity in Hyperosmolality-Induced Stress Response.

Hyperosmolality can occur during industrial fed-batch cultivation processes of Chinese hamster ovary (CHO) cells as highly concentrated feed and base solutions are added to replenish nutrients and regulate pH values. Some effects of hyperosmolality, such as increased cell size and growth inhibition, have been elucidated by previous research, but the impact of hyperosmolality and the specific effects of the added osmotic-active reagents have rarely been disentangled. In this study, CHO cells were exposed to four osmotic conditions between 300 mOsm/kg (physiologic condition) and 530 mOsm/kg (extreme hyperosmolality) caused by the addition of either high-glucose-supplemented industrial feed or mannitol as an osmotic control. We present novel single-cell cultivation data revealing heterogeneity in mass gain and cell division in response to these treatments. Exposure to extreme mannitol-induced hyperosmolality and to high-glucose-oversupplemented feed causes cell cycle termination, mtDNA damage, and mitochondrial membrane depolarization, which hints at the onset of premature stress-induced senescence. Thus, this study shows that both mannitol-induced hyperosmolality (530 mOsm/kg) and glucose overfeeding induce severe negative effects on cell growth and mitochondrial activity; therefore, they need to be considered during process development for commercial production.

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.

Recent advances in microfluidic devices for single-cell cultivation: methods and applications.

Single-cell analysis is essential to improve our understanding of cell functionality from cellular and subcellular aspects for diagnosis and therapy. Single-cell cultivation is one of the most important processes in single-cell analysis, which allows the monitoring of actual information of individual cells and provides sufficient single-cell clones and cell-derived products for further analysis. The microfluidic device is a fast-rising system that offers efficient, effective, and sensitive single-cell cultivation and real-time single-cell analysis conducted either on-chip or off-chip. Here, we introduce the importance of single-cell cultivation from the aspects of cellular and subcellular studies. We highlight the materials and structures utilized in microfluidic devices for single-cell cultivation. We further discuss biological applications utilizing single-cell cultivation-based microfluidics, such as cellular phenotyping, cell-cell interactions, and omics profiling. Finally, present limitations and future prospects of microfluidics for single-cell cultivation are also discussed.

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.

The G4 Resolvase DHX36 Possesses a Prognosis Significance and Exerts Tumour Suppressing Function Through Multiple Causal Regulations in Non-Small Cell Lung Cancer.

Lung cancer is one of the most prevalent cancers in both men and women worldwide. The nucleic acid G4 structures have been implicated in the transcriptional programmes of cancer-related genes in some cancers such as lung cancer. However, the role of the dominant G4 resolvase DHX36 in the progression of lung cancer remains unknown. In this study, by bioinformatic analysis of public datasets (TCGA and GEO), we find DHX36 is an independent prognosis indicator in non-small-cell lung carcinoma (NSCLC) with subtype dependence. The stable lentiviral knockdown of the DHX36 results in accelerated migration and aggregation of the S-phase subpopulation in lung cancer cells. The reduction of DHX36 level de-sensitises the proliferation response of lung cancer cells to chemotherapeutic drugs such as paclitaxel with cell dependence. The knockdown of this helicase leads to promoted tumour growth, demonstrated by a 3D fluorescence spheroid lung cancer model, and the stimulation of cell colony formation as shown by single-cell cultivation. High throughput proteomic array indicates that DHX36 functions in lung cancer cells through regulating multiple signalling pathways including activation of protein activity, protein autophosphorylation, Fc-receptor signalling pathway, response to peptide hormone and stress-activated protein kinase signalling cascade. A causal transcriptomic analysis suggests that DHX36 is significantly associated with mRNA surveillance, RNA degradation, DNA replication and Myc targets. Therefore, we unveil that DHX36 presents clinical significance and plays a role in tumour suppression in lung cancer, and propose a potentially new concept for an anti-cancer therapy based on helicase-specific targeting.

One cell at a time: droplet-based microbial cultivation, screening and sequencing.

Microbes thrive and, in turn, influence the earth's environment, but most are poorly understood because of our limited capacity to reveal their natural diversity and function. Developing novel tools and effective strategies are critical to ease this dilemma and will help to understand their roles in ecology and human health. Recently, droplet microfluidics is emerging as a promising technology for microbial studies with value in microbial cultivating, screening, and sequencing. This review aims to provide an overview of droplet microfluidics techniques for microbial research. First, some critical points or steps in the microfluidic system are introduced, such as droplet stabilization, manipulation, and detection. We then highlight the recent progress of droplet-based methods for microbiological applications, from high-throughput single-cell cultivation, screening to the targeted or whole-genome sequencing of single cells.

Development of a microbe domestication pod (MD Pod) for in situ cultivation of micro-encapsulated marine bacteria.

Microbial marine natural products hold significant potential for the discovery of new bioactive therapeutics such as antibiotics. Unfortunately, this discovery is hindered by the inability to culture the majority of microbes using traditional laboratory approaches. While many new methods have been developed to increase cultivability, a high-throughput in situ incubation chamber capable of simultaneously isolating individual microbes while allowing cellular communication has not previously been reported. Development of such a device would expedite the discovery of new microbial taxa and, thus, facilitate access to their associated natural products. In this study, this concept is achieved by the development of a new device termed by the authors as the microbe domestication (MD) Pod. The MD Pod enables single-cell cultivation by isolating marine bacterial cells in agarose microbeads produced using microfluidics, while allowing potential transmission of chemical signals between cells during in situ incubation in a chamber, or "Pod," that is deployed in the environment. The design of the MD Pod was optimized to ensure the use of biocompatible materials, allow for simple assembly in a field setting, and maintain sterility throughout incubation. The encapsulation process was designed to ensure that the viability of marine sediment bacteria was not adversely impacted by the encapsulation process. The process was validated using representative bacteria isolated from temperate marine sediment samples: Marinomonas polaris, Psychrobacter aquimaris, and Bacillus licheniformis. The overall process appeared to promote metabolic activity of most representative species. Thus, microfluidic encapsulation of marine bacteria and subsequent in situ incubation in the MD Pod is expected to accelerate marine natural products discovery by increasing the cultivability of marine bacteria.

Development and application of a cultivation platform for mammalian suspension cell lines with single-cell resolution.

In bioproduction processes, cellular heterogeneity can cause unpredictable process outcomes or even provoke process failure. Still, cellular heterogeneity is not examined systematically in bioprocess research and development. One reason for this shortcoming is the applied average bulk analyses, which are not able to detect cell-to-cell differences. In this study, we present a microfluidic tool for mammalian single-cell cultivation (MaSC) of suspension cells. The design of our platform allows cultivation in highly controllable environments. As a model system, Chinese hamster ovary cells (CHO-K1) were cultivated over 150 h. Growth behavior was analyzed on a single-cell level and resulted in growth rates between 0.85 and 1.16 day-1 . At the same time, heterogeneous growth and division behavior, for example, unequal division time, as well as rare cellular events like polynucleation or reversed mitosis were observed, which would have remained undetected in a standard population analysis based on average measurements. Therefore, MaSC will open the door for systematic single-cell analysis of mammalian suspension cells. Possible fields of application represent basic research topics like cell-to-cell heterogeneity, clonal stability, pharmaceutical drug screening, and stem cell research, as well as bioprocess related topics such as media development and novel scale-down approaches.

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.