Microfluidic single-cell analysis in biotechnology: from monitoring towards understanding

Transcriptional biomarker discovery toward building a load stress reporting system for engineered Escherichia coli strains

Foreign proteins are produced by introducing synthetic constructs into host bacteria for biotechnology applications. This process can cause resource competition between synthetic circuits and host cells, placing a metabolic burden on the host cells which may result in load stress and detrimental physiological changes. Consequently, the host bacteria can experience slow growth, and the synthetic system may suffer from suboptimal function. To help in the detection of bacterial load stress, we developed machine-learning strategies to select a minimal number of genes that could serve as biomarkers for the design of load stress reporters. We identified pairs of biomarkers that showed discriminative capacity to detect the load stress states induced in 41 engineered Escherichia coli strains.

Recent developments in ionization techniques for single-cell mass spectrometry

The variation among individual cells plays a significant role in many biological functions. Single-cell analysis is advantageous for gaining insight into intricate biochemical mechanisms rarely accessible when studying tissues as a whole. However, measurement on a unicellular scale is still challenging due to unicellular complex composition, minute substance quantities, and considerable differences in compound concentrations. Mass spectrometry has recently gained extensive attention in unicellular analytical fields due to its exceptional sensitivity, throughput, and compound identification abilities. At present, single-cell mass spectrometry primarily concentrates on the enhancement of ionization methods. The principal ionization approaches encompass nanoelectrospray ionization (nano-ESI), laser desorption ionization (LDI), secondary ion mass spectrometry (SIMS), and inductively coupled plasma (ICP). This article summarizes the most recent advancements in ionization techniques and explores their potential directions within the field of single-cell mass spectrometry.

Microbial single-cell mass spectrometry: status, challenges, and prospects

Single-cell analysis uncovers phenotypic differences between cells in a population and dissects their individual physiological states and differences on all omics levels from genome to phenome. Spectrometric observation allows label-free analysis of the metabolome and proteome of individual cells, but is still mainly limited to the analysis of mammalian single cells. Recent progress in mass spectrometry approaches now enables the analysis of microbial single cells - mainly by miniaturizing cell handling, incubation, and improving chip-coupling concepts for analyte ionization by interfacing microfluidic chips and mass spectrometers. This review aims at distilling the enabling principles behind microbial single-cell mass spectrometry and puts them into perspective for the future of the field.

Rapid prototyping of microfluidic chips enabling controlled biotechnology applications in microspace

Rapid prototyping of microfluidic chips is a key enabler for controlled biotechnology applications in microspaces, as it allows for the efficient design and production of microfluidic systems. With rapid prototyping, researchers and engineers can quickly create and test new microfluidic chip designs, which can then be optimized for specific applications in biotechnology. One of the key advantages of microfluidic chips for biotechnology is the ability to manipulate and control biological samples in a microspace, which enables precise and controlled experiments under well-defined conditions. This is particularly useful for applications such as cell culture, drug discovery, and diagnostic assays, where precise control over the biological environment is crucial for obtaining accurate results. Established methods, for example, soft lithography, 3D printing, injection molding, as well as other recently highlighted innovative approaches, will be compared and challenges as well as limitations will be discussed. It will be shown that rapid prototyping of microfluidic chips enables the use of advanced materials and technologies, such as smart materials and digital sensors, which can further enhance the capabilities of microfluidic systems for biotechnology applications. Overall, rapid prototyping of microfluidic chips is an important enabling technology for controlled biotechnology applications in microspaces, as well as for upscaling it into macroscopic bioreactors, and its continued development and improvement will play a critical role in advancing the field. The review will highlight recent trends in terms of materials and competing approaches and shed light on current challenges on the way toward integrated microtechnologies. Also, the possibility to easy and direct implementation of novel functions (membranes, functionalization of interfaces, etc.) is discussed.

From Conventional to Microfluidic: Progress in Extracellular Vesicle Separation and Individual Characterization

Extracellular vesicles (EVs) are nanoscale membrane vesicles, which contain a wide variety of cargo such as proteins, miRNAs, and lipids. A growing body of evidence suggests that EVs are promising biomarkers for disease diagnosis and therapeutic strategies. Although the excellent clinical value, their use in personalized healthcare practice is not yet feasible due to their highly heterogeneous nature. Taking the difficulty of isolation and the small size of EVs into account, the characterization of EVs at a single-particle level is both imperative and challenging. In a bid to address this critical point, more research has been directed into a microfluidic platform because of its inherent advantages in sensitivity, specificity, and throughput. This review discusses the biogenesis and heterogeneity of EVs and takes a broad view of state-of-the-art advances in microfluidics-based EV research, including not only EV separation, but also the single EV characterization of biophysical detection and biochemical analysis. To highlight the advantages of microfluidic techniques, conventional technologies are included for comparison. The current status of artificial intelligence (AI) for single EV characterization is then presented. Furthermore, the challenges and prospects of microfluidics and its combination with AI applications in single EV characterization are also discussed. In the foreseeable future, recent breakthroughs in microfluidic platforms are expected to pave the way for single EV analysis and improve applications for precision medicine.

Advances in Microfluidics for Single Red Blood Cell Analysis

The utilizations of microfluidic chips for single RBC (red blood cell) studies have attracted great interests in recent years to filter, trap, analyze, and release single erythrocytes for various applications. Researchers in this field have highlighted the vast potential in developing micro devices for industrial and academia usages, including lab-on-a-chip and organ-on-a-chip systems. This article critically reviews the current state-of-the-art and recent advances of microfluidics for single RBC analyses, including integrated sensors and microfluidic platforms for microscopic/tomographic/spectroscopic single RBC analyses, trapping arrays (including bifurcating channels), dielectrophoretic and agglutination/aggregation studies, as well as clinical implications covering cancer, sepsis, prenatal, and Sickle Cell diseases. Microfluidics based RBC microarrays, sorting/counting and trapping techniques (including acoustic, dielectrophoretic, hydrodynamic, magnetic, and optical techniques) are also reviewed. Lastly, organs on chips, multi-organ chips, and drug discovery involving single RBC are described. The limitations and drawbacks of each technology are addressed and future prospects are discussed.

Microbial lifelines in bioprocesses: From concept to application

Bioprocesses are scaled up for the production of large product quantities. With larger fermenter volumes, mixing becomes increasingly inefficient and environmental gradients get more prominent than in smaller scales. Environmental gradients have an impact on the microorganism's metabolism, which makes the prediction of large-scale performance difficult and can lead to scale-up failure. A promising approach for improved understanding and estimation of dynamics of microbial populations in large-scale bioprocesses is the analysis of microbial lifelines. The lifeline of a microbe in a bioprocess is the experience of environmental gradients from a cell's perspective, which can be described as a time series of position, environment and intracellular condition. Currently, lifelines are predominantly determined using models with computational fluid dynamics, but new technical developments in flow-following sensor particles and microfluidic single-cell cultivation open the door to a more interdisciplinary concept. We critically review the current concepts and challenges in lifeline determination and application of lifeline analysis, as well as strategies for the integration of these techniques into bioprocess development. Lifelines can contribute to a successful scale-up by guiding scale-down experiments and identifying strain engineering targets or bioreactor optimisations.

A knowledge integration strategy for the selection of a robust multi-stress biomarkers panel for Bacillus subtilis

One challenge in the engineering of biological systems is to be able to recognise the cellular stress states of bacterial hosts, as these stress states can lead to suboptimal growth and lower yields of target products. To enable the design of genetic circuits for reporting or mitigating the stress states, it is important to identify a relatively reduced set of gene biomarkers that can reliably indicate relevant cellular growth states in bacteria. Recent advances in high-throughput omics technologies have enhanced the identification of molecular biomarkers specific states in bacteria, motivating computational methods that can identify robust biomarkers for experimental characterisation and verification. Focused on identifying gene expression biomarkers to sense various stress states in Bacillus subtilis, this study aimed to design a knowledge integration strategy for the selection of a robust biomarker panel that generalises on external datasets and experiments. We developed a recommendation system that ranks the candidate biomarker panels based on complementary information from machine learning model, gene regulatory network and co-expression network. We identified a recommended biomarker panel showing high stress sensing power for a variety of conditions both in the dataset used for biomarker identification (mean f1-score achieved at 0.99), as well as in a range of independent datasets (mean f1-score achieved at 0.98). We discovered a significant correlation between stress sensing power and evaluation metrics such as the number of associated regulators in a B. subtilis gene regulatory network (GRN) and the number of associated modules in a B. subtilis co-expression network (CEN). GRNs and CENs provide information relevant to the diversity of biological processes encoded by biomarker genes. We demonstrate that quantitatively relating meaningful evaluation metrics with stress sensing power has the potential for recognising biomarkers that show better sensitivity and robustness to an extended set of stress conditions and enable a more reliable biomarker panel selection.

Automated detection of patterned single-cells within hydrogel using deep learning

Single-cell analysis has been widely used in various biomedical engineering applications, ranging from cancer diagnostics, and immune response monitoring to drug screening. Single-cell isolation is fundamental for observing single-cell activities and an automatic finding method of accurate and reliable cell detection with few possible human errors is also essential. This paper reports trapping single cells into photo patternable hydrogel microwell arrays and isolating them. Additionally, we present an object detection-based DL algorithm that detects single cells in microwell arrays and predicts the presence of cells in resource-limited environments at the highest possible mAP (mean average precision) of 0.989 with an average inference time of 0.06 s. This algorithm leads to the enhancement of the high-throughput single-cell analysis, establishing high detection precision and reduced experimentation time.

Glycolysis-Related SLC2A1 Is a Potential Pan-Cancer Biomarker for Prognosis and Immunotherapy

SLC2A1 plays a pivotal role in cancer glycometabolism. SLC2A1 has been proposed as a putative driver gene in various cancers. However, a pan-cancer analysis of SLC2A1 has not yet been performed. In this study, we explored the expression and prognosis of SLC2A1 in pan-cancer across multiple databases. We conducted genetic alteration, epigenetic, and functional enrichment analyses of SLC2A. We calculated the correlation between SLC2A1 and tumor microenvironment using the TCGA pan-cancer dataset. We observed high expression levels of SLC2A1 with poor prognosis in most cancers. The overall genetic alteration frequency of SLC2A1 was 1.8% in pan-cancer, and the SLC2A1 promoter was hypomethylation in several cancers. Most m6A-methylation-related genes positively correlated with the expression of SLC2A1 in 33 TCGA cancers. Moreover, SLC2A1 was mainly related to the functions including epithelial-mesenchymal transition, glycolysis, hypoxia, cell-cycle regulation, and DNA repair. Finally, SLC2A1 positively associated with neutrophils and cancer-associated fibroblasts in the tumor microenvironment of most cancers and significantly correlated with TMB and MSI in various cancers. Notably, SLC2A1 was remarkably positively correlated with PD-L1 and CTLA4 in most cancers. SLC2A1 might serve as an attractive pan-cancer biomarker for providing new insights into cancer therapeutics.

Microfluidics-Based Urine Biopsy for Cancer Diagnosis: Recent Advances and Future Trends

Urine biopsy, allowing for the detection, analysis and monitoring of numerous cancer-associated urinary biomarkers to provide insights into cancer occurrence, progression and metastasis, has emerged as an attractive liquid biopsy strategy with enormous advantages over traditional tissue biopsy, such as noninvasiveness, large sample volume, and simple sampling operation. Microfluidics enables precise manipulation of fluids in a tiny chip and exhibits outstanding performance in urine biopsy owing to its minimization, low cost, high integration, high throughput and low sample consumption. Herein, we review recent advances in microfluidic techniques employed in urine biopsy for cancer detection. After briefly summarizing the major urinary biomarkers used for cancer diagnosis, we provide an overview of the typical microfluidic techniques utilized to develop urine biopsy devices. Some prospects along with the major challenges to be addressed for the future of microfluidic-based urine biopsy are also discussed.

Digital models in biotechnology: Towards multi-scale integration and implementation

Industrial biotechnology encompasses a large area of multi-scale and multi-disciplinary research activities. With the recent megatrend of digitalization sweeping across all industries, there is an increased focus in the biotechnology industry on developing, integrating and applying digital models to improve all aspects of industrial biotechnology. Given the rapid development of this field, we systematically classify the state-of-art modelling concepts applied at different scales in industrial biotechnology and critically discuss their current usage, advantages and limitations. Further, we critically analyzed current strategies to couple cell models with computational fluid dynamics to study the performance of industrial microorganisms in large-scale bioprocesses, which is of crucial importance for the bio-based production industries. One of the most challenging aspects in this context is gathering intracellular data under industrially relevant conditions. Towards comprehensive models, we discuss how different scale-down concepts combined with appropriate analytical tools can capture intracellular states of single cells. We finally illustrated how the efforts could be used to develop digitals models suitable for both cell factory design and process optimization at industrial scales in the future.

Assessing the growth kinetics and stoichiometry of Escherichia coli at the single-cell level

Microfluidic cultivation and single-cell analysis are inherent parts of modern microbial biotechnology and microbiology. However, implementing biochemical engineering principles based on the kinetics and stoichiometry of growth in microscopic spaces remained unattained. We here present a novel integrated framework that utilizes distinct microfluidic cultivation technologies and single-cell analytics to make the fundamental math of process-oriented biochemical engineering applicable at the single-cell level. A combination of non-invasive optical cell mass determination with sub-pg sensitivity, microfluidic perfusion cultivations for establishing physiological steady-states, and picoliter batch reactors, enabled the quantification of all physiological parameters relevant to approximate a material balance in microfluidic reaction environments. We determined state variables (biomass concentration based on single-cell dry weight and mass density), biomass synthesis rates, and substrate affinities of cells grown in microfluidic environments. Based on this data, we mathematically derived the specific kinetics of substrate uptake and growth stoichiometry in glucose-grown Escherichia coli with single-cell resolution. This framework may initiate microscale material balancing beyond the averaged values obtained from populations as a basis for integrating heterogeneous kinetic and stoichiometric single-cell data into generalized bioprocess models and descriptions.

Combining microscopy assays of bacteria-surface interactions to better evaluate antimicrobial polymer coatings

Validation of the antimicrobial performance of contact-killing polymer surfaces through experimental determination of bacterial adhesion or viability is essential for their targeted development and application. However, there is not yet a consensus on a single most appropriate evaluation method or procedure. Combining and benchmarking previously reported assays could reduce the significant variation and misinterpretation of efficacy data obtained from different methods. In this work, we systematically investigated the response of bacteria cells to anti-adhesive and antiseptic polymer coatings by combining (i) bulk solution-based, (ii) thin-film spacer-based and (iii) direct contact assays. In addition, we evaluated the studied assays using a five-point scoring framework that highlights key areas for improvement. Our data suggest that combined microscopy assays provide a more comprehensive representation of antimicrobial performance, thereby helping to identify effective types of antibacterial polymer coatings. Importance We present and evaluate a combination of methods for validating the efficacy of antimicrobial surfaces. Antimicrobial surfaces/coatings based on contact-killing components can be instrumental to functionalise a wide range of products. However, there is not yet a consensus on a single, most appropriate method to evaluate their performance. By combining three microscopy methods, we were able to discern contact killing effects at the single cell level that were not detectable by conventional bulk microbiological analyses. The developed approach is considered advantageous for the future targeted development of robust and sustainable antimicrobial surfaces.

Establishment of a simple method to evaluate mixing times in a plastic bag photobioreactor using image processing based on freeware tools

Objective

Accurate determination of the mixing time in bioreactors is essential for the optimization of the productivity of bioprocesses. The aim of this work was to develop a simple optical method to determine the mixing time in a photobioreactor. The image processing method should be based on freeware tools, should not require programming skills, and thus could be used in education within high schools and in early stages of undergraduate programs.

Results

An optical method has been established to analyze images from recorded videos of mixing experiments. The steps are: 1. Extraction of a sequence of images from the video file; 2. Cropping of the pictures; 3. Background removal; and 4. Image analysis and mixing time evaluation based on quantification of pixel-to-pixel heterogeneity within a given area of interest. The novel method was generally able to track the dependency between aeration rate and mixing time within the investigated photobioreactor. In direct comparison, a pearson correlation coefficient of rho = 0.99 was obtained. Gas flow rates between 10 L h⁻¹, and 300 L h⁻¹ resulted from mixing times of between 48 and 14 s, respectively. This technique is applicable without programming skills and can be used in education with inexperienced user groups.

Microgel Single-Cell Culture Arrays on a Microfluidic Chip for Selective Expansion and Recovery of Colorectal Cancer Stem Cells

Cancer stem cells (CSCs) are rare and lack definite biomarkers, necessitating new methods for a robust expansion. Here, we developed a microfluidic single-cell culture (SCC) approach for expanding and recovering colorectal CSCs from both cell lines and tumor tissues. By incorporating alginate hydrogels with droplet microfluidics, a high-density microgel array can be formed on a microfluidic chip that allows for single-cell encapsulation and nonadhesive culture. The SCC approach takes advantage of the self-renewal property of stem cells, as only the CSCs can survive in the SCC and form tumorspheres. Consecutive imaging confirmed the formation of single-cell-derived tumorspheres, mainly from a population of small-sized cells. Through on-chip decapsulation of the alginate microgel, ∼6000 live cells can be recovered in a single run, which is sufficient for most biological assays. The recovered cells were verified to have the genetic and phenotypic characteristics of CSCs. Furthermore, multiple CSC-specific targets were identified by comparing the transcriptomics of the CSCs with the primary cancer cells. To summarize, the microgel SCC array offers a label-free approach to obtain sufficient quantities of CSCs and thus is potentially useful for understanding cancer biology and developing personalized CSC-targeting therapies.

Recent advances in single-cell analysis: Encapsulation materials, analysis methods and integrative platform for microfluidic technology

Traditional cell biology researches on cell populations by their origin, tissue, morphology, and secretions. Because of the heterogeneity of cells, research at the single-cell level can obtain more accurate and comprehensive information that reflects the physiological state and process of the cell, increasing the significance of single-cell analysis. The application of single-cell analysis is faced with the problem of contaminated or damaged cells caused by cell sample transportation. Reversible encapsulation of a single cell can protect cells from the external environment and open the encapsulation shell to release cells, thus preserving cell integrity and improving extraction efficiency of analytes. Meanwhile, microfluidic single cell analysis (MSCA) exhibits integration, miniaturization, and high throughput, which can considerably improve the efficiency of single-cell analysis. The researches on single-cell reversible encapsulation materials, single-cell analysis methods, and the MSCA integration platform are analyzed and summarized in this review. The problems of single-cell viability, network of single-cell signal, and simultaneous detection of multiple biotoxins in food based on single-cell are proposed for future research.

Numerical simulation of critical particle size in asymmetrical deterministic lateral displacement

Microfluidics devices are widely used for particle separation. Deterministic Lateral Displacement (DLD) is a passive method for particle separation. DLD devices mainly separate particles based on their sizes. There are two main modes of movement in DLD arrays; the small particles move in a zigzag path, and the larger particles separate in the displacement mode. It is therefore important to estimate the critical particle size for the transition of modes before the fabrication of DLD devices. Asymmetry in the design of the arrays can affect the fluid behavior and the critical particle size. In this study, we investigate the effects of the asymmetry caused by changing the downstream gap size to the lateral gap size ratio on the fluid behavior and particle trajectories in DLD devices. We used two dimensional (2D) Finite Element Method (FEM) to study the variations in the flow lane's widths and combined the fluid analysis with structural mechanics to model the contact between the particles and the posts in DLD arrays. We simulated the spherical particles' trajectories with diameters ranging from 1.4 to 19.2 μm in circular post DLD arrays with a lateral gap size of 20μm. In contrast to the previous works, in these simulations, the effect of particle movement on the fluid flow profiles was considered. We evaluated the particle movement mode in seven different values of the downstream gap size to the lateral gap size ratio (ranging from 0.5 to 2) and eight different row shift fraction (ranging from 0.025 to 0.3). Our simulations showed that increasing the value of the downstream gap while the lateral gap is fixed increases the veering flow rate and width. By finding the particle with the largest diameter in the zigzag mode and the particle with the smallest diameter in the displacement mode, we estimated the critical particle diameter for each value of shift fraction in different values of the downstream gap to the lateral gap size ratio. Using these data, a curve was fitted for predicting the critical particle diameter in each ratio. Finally, a more general form of the formula for the critical particle diameter was proposed, which considers an extra parameter compared to the previous ones. The results of this study can lead to a better understanding of DLD devices' functions and, thus, save time and costs for better designs and experiments.

Plasmonic Optical Tweezers for Particle Manipulation: Principles, Methods, and Applications

Inspired by the idea of combining conventional optical tweezers with plasmonic nanostructures, a technique named plasmonic optical tweezers (POT) has been widely explored from fundamental principles to applications. With the ability to break the diffraction barrier and enhance the localized electromagnetic field, POT techniques are especially effective for high spatial-resolution manipulation of nanoscale or even subnanoscale objects, from small bioparticles to atoms. In addition, POT can be easily integrated with other techniques such as lab-on-chip devices, which results in a very promising alternative technique for high-throughput single-bioparticle sensing or imaging. Despite its label-free, high-precision, and high-spatial-resolution nature, it also suffers from some limitations. One of the main obstacles is that the plasmonic nanostructures are located over the surfaces of a substrate, which makes the manipulation of bioparticles turn from a three-dimensional problem to a nearly two-dimensional problem. Meanwhile, the operation zone is limited to a predefined area. Therefore, the target objects must be delivered to the operation zone near the plasmonic structures. This review summarizes the state-of-the-art target delivery methods for the POT-based particle manipulating technique, along with its applications in single-bioparticle analysis/imaging, high-throughput bioparticle purifying, and single-atom manipulation. Future developmental perspectives of POT techniques are also discussed.

Microfluidics-Based Sensing of Biospecies

Over the past decades, microfluidic devices based on many advanced techniques have aroused widespread attention in the fields of chemical, biological, and analytical applications. Integration of microdevices with a variety of chip designs will facilitate promising functionality. Notably, the combination of microfluidics with functional nanomaterials may provide creative ideas to achieve rapid and sensitive detection of various biospecies. In this review, focused on the microfluids and microdevices in terms of their fabrication, integration, and functions, we summarize the up-to-date developments in microfluidics-based analysis of biospecies, where biomarkers, small molecules, cells, and pathogens as representative biospecies have been explored in-depth. The promising applications of microfluidic biosensors including clinical diagnosis, food safety control, and environmental monitoring are also discussed. This review aims to highlight the importance of microfluidics-based biosensors in achieving high throughput, highly sensitive, and low-cost analysis and to promote microfluidics toward a wider range of applications.

Microfluidics in Biotechnology: Quo Vadis

The emerging technique of microfluidics offers new approaches for precisely controlling fluidic conditions on a small scale, while simultaneously facilitating data collection in both high-throughput and quantitative manners. As such, the so-called lab-on-a-chip (LOC) systems have the potential to revolutionize the field of biotechnology. But what needs to happen in order to truly integrate them into routine biotechnological applications? In this chapter, some of the most promising applications of microfluidic technology within the field of biotechnology are surveyed, and a few strategies for overcoming current challenges posed by microfluidic LOC systems are examined. In addition, we also discuss the intensifying trend (across all biotechnology fields) of using point-of-use applications which is being facilitated by new technological achievements.

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.

Microfluidics for Biotechnology: Bridging Gaps to Foster Microfluidic Applications

Microfluidics and novel lab-on-a-chip applications have the potential to boost biotechnological research in ways that are not possible using traditional methods. Although microfluidic tools were increasingly used for different applications within biotechnology in recent years, a systematic and routine use in academic and industrial labs is still not established. For many years, absent innovative, ground-breaking and “out-of-the-box” applications have been made responsible for the missing drive to integrate microfluidic technologies into fundamental and applied biotechnological research. In this review, we highlight microfluidics’ offers and compare them to the most important demands of the biotechnologists. Furthermore, a detailed analysis in the state-of-the-art use of microfluidics within biotechnology was conducted exemplarily for four emerging biotechnological fields that can substantially benefit from the application of microfluidic systems, namely the phenotypic screening of cells, the analysis of microbial population heterogeneity, organ-on-a-chip approaches and the characterisation of synthetic co-cultures. The analysis resulted in a discussion of potential “gaps” that can be responsible for the rare integration of microfluidics into biotechnological studies. Our analysis revealed six major gaps, concerning the lack of interdisciplinary communication, mutual knowledge and motivation, methodological compatibility, technological readiness and missing commercialisation, which need to be bridged in the future. We conclude that connecting microfluidics and biotechnology is not an impossible challenge and made seven suggestions to bridge the gaps between those disciplines. This lays the foundation for routine integration of microfluidic systems into biotechnology research procedures.

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.

Continuous electrical lysis of cancer cells in a microfluidic device with passivated interdigitated electrodes

Cell lysis is a critical step in genomics for the extraction of cellular components of downstream assays. Electrical lysis (EL) offers key advantages in terms of speed and non-interference. Here, we report a simple, chemical-free, and automated technique based on a microfluidic device with passivated interdigitated electrodes with DC fields for continuous EL of cancer cells. We show that the critical problems in EL, bubble formation and electrode erosion that occur at high electric fields, can be circumvented by passivating the electrodes with a thin layer (∼18 μm) of polydimethylsiloxane. We present a numerical model for the prediction of the transmembrane potential (TMP) at different coating thicknesses and voltages to verify the critical TMP criterion for EL. Our simulations showed that the passivation layer results in a uniform electric field in the electrode region and offers a TMP in the range of 5-7 V at an applied voltage of 800 V, which is well above the critical TMP (∼1 V) required for EL. Experiments revealed that lysis efficiency increases with an increase in the electric field (E) and residence time (tr): a minimum E ∼ 105 V/m and tr ∼ 1.0 s are required for efficient lysis. EL of cancer cells is demonstrated and characterized using immunochemical staining and compared with chemical lysis. The lysis efficiency is found to be ∼98% at E = 4 × 105 V/m and tr = 0.72 s. The efficient recovery of genomic DNA via EL is demonstrated using agarose gel electrophoresis, proving the suitability of our method for integration with downstream on-chip assays.

A High-Throughput Screening System Based on Droplet Microfluidics for Glucose Oxidase Gene Libraries

Glucose oxidase (GOx) is an important industrial enzyme that can be optimized for specific applications by mutagenesis and activity-based screening. To increase the efficiency of this approach, we have developed a new ultrahigh-throughput screening platform based on a microfluidic lab-on-chip device that allows the sorting of GOx mutants from a saturation mutagenesis library expressed on the surface of yeast cells. GOx activity was measured by monitoring the fluorescence of water microdroplets dispersed in perfluorinated oil. The signal was generated via a series of coupled enzyme reactions leading to the formation of fluorescein. Using this new method, we were able to enrich the yeast cell population by more than 35-fold for GOx mutants with higher than wild-type activity after two rounds of sorting, almost double the efficiency of our previously described flow cytometry platform. We identified and characterized novel GOx mutants, the most promising of which (M6) contained a combination of six point mutations that increased the catalytic constant kcat by 2.1-fold compared to wild-type GOx and by 1.4-fold compared to a parental GOx variant. The new microfluidic platform for GOx was therefore more sensitive than flow cytometry and supports comprehensive screens of gene libraries containing multiple mutations per gene.

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.

Single-Cell Analysis of Foot-and-Mouth Disease Virus

With the rapid development of single-cell technologies, the mechanisms underlying viral infections and the interactions between hosts and viruses are starting to be explored at the single-cell level. The foot-and-mouth-disease (FMD) virus (FMDV) causes an acute and persistent infection that can result in the break-out of FMD, which can have serious effects on animal husbandry. Single-cell techniques have emerged as powerful approaches to analyze virus infection at the resolution of individual cells. In this review, the existing single-cell studies examining FMDV will be systematically summarized, and the central themes of these studies will be presented.

Microfluidic Single-Cell Analytics

What is the impact of cellular heterogeneity on process performance? How do individual cells contribute to averaged process productivity? Single-cell analysis is a key technology for answering such key questions of biotechnology, beyond bulky measurements with populations. The analysis of cellular individuality, its origins, and the dependency of process performance on cellular heterogeneity has tremendous potential for optimizing biotechnological processes in terms of metabolic, reaction, and process engineering. Microfluidics offer unmatched environmental control of the cellular environment and allow massively parallelized cultivation of single cells. However, the analytical accessibility to a cell's physiology is of crucial importance for obtaining the desired information on the single-cell production phenotype. Highly sensitive analytics are required to detect and quantify the minute amounts of target analytes and small physiological changes in a single cell. For their application to biotechnological questions, single-cell analytics must evolve toward the measurement of kinetics and specific rates of the smallest catalytic unit, the single cell. In this chapter, we focus on an introduction to the latest single-cell analytics and their application for obtaining physiological parameters in a biotechnological context from single cells. We present and discuss recent advancements in single-cell analytics that enable the analysis of cell-specific growth, uptake, and production kinetics, as well as the gene expression and regulatory mechanisms at a single-cell level.