Droplet control technologies for microfluidic high throughput screening (μHTS)

μREACT: A microfluidic system for rapid evaluation of trans-kingdom interactions

Trans-kingdom interactions between cells play pivotal roles in shaping intricate ecological and biological networks. However, our grasp of these interactions remains incomplete. Specifically, the vast phylogenetic spectrum of microorganisms capable of interacting with a given host cell type remains obscure, primarily due to the absence of efficient, high-throughput, single-cell resolution systems that can rapidly decipher these interactions. Here, we introduce μREACT (Microfluidic system for Rapid Evaluation of bacterial Adherence and Communication in Trans-kingdom interactions), a microfluidic system designed to analyze interkingdom interactions. μREACT not only unveiled both recognized and previously unknown interactions but also enabled their detailed characterization. The system features the use of microfluidic dielectrophoretic separation of bacteria that adhere to host cells at single-cell (digital) resolution, and enabled the sorting of 107 adherent microorganisms per hour, representing a comparable throughput to conventional flow cytometry systems, but without requiring any labeling. The analysis of soil microbial samples using μREACT revealed several bacterial species previously known to have high adherence to mammalian host cells, as well as new interactions involving strains that displayed hallmarks of emerging endosymbiosis. Taken together, μREACT serves as a formidable tool for identifying and characterizing webs of interkingdom interactions. Its implications extend beyond discovery of such interactions, where it has the potential to provide new insights into fundamental mechanisms driving ecosystem dynamics and biological processes.

Reshaping Capillary Electrophoresis With State-of-the-Art Sample Preparation Materials: Exploring New Horizons

Capillary electrophoresis (CE) is a powerful analysis technique with advantages such as high separation efficiency with resolution factors above 1.5, low sample consumption of less than 10 µL, cost-effectiveness, and eco-friendliness such as reduced solvent use and lower operational costs. However, CE also faces limitations, including limited detection sensitivity for low-concentration samples and interference from complex biological matrices. Prior to performing CE, it is common to utilize sample preparation procedures such as solid-phase microextraction (SPME) and liquid-phase microextraction (LPME) in order to improve the sensitivity and selectivity of the analysis. Recently, there have been advancements in the development of novel materials that have the potential to greatly enhance the performance of SPME and LPME. This review examines various materials and their uses in microextraction when combined with CE. These materials include carbon nanotubes, covalent organic frameworks, metal-organic frameworks, graphene and its derivatives, molecularly imprinted polymers, layered double hydroxides, ionic liquids, and deep eutectic solvents. The utilization of these innovative materials in extraction methods is being examined. Analyte recoveries and detection limits attained for a range of sample matrices are used to assess their effects on extraction selectivity, sensitivity, and efficiency. Exploring new materials for use in sample preparation techniques is important as it enables researchers to address current limitations of CE. The development of novel materials has the potential to greatly enhance extraction selectivity, sensitivity, and efficiency, thereby improving CE performance for complex biological analysis.

Droplet Microfluidic Devices: Working Principles, Fabrication Methods, and Scale-Up Applications

Compared with the conventional emulsification method, droplets generated within microfluidic devices exhibit distinct advantages such as precise control of fluids, exceptional monodispersity, uniform morphology, flexible manipulation, and narrow size distribution. These inherent benefits, including intrinsic safety, excellent heat and mass transfer capabilities, and large surface-to-volume ratio, have led to the widespread applications of droplet-based microfluidics across diverse fields, encompassing chemical engineering, particle synthesis, biological detection, diagnostics, emulsion preparation, and pharmaceuticals. However, despite its promising potential for versatile applications, the practical utilization of this technology in commercial and industrial is extremely limited to the inherently low production rates achievable within a single microchannel. Over the past two decades, droplet-based microfluidics has evolved significantly, considerably transitioning from a proof-of-concept stage to industrialization. And now there is a growing trend towards translating academic research into commercial and industrial applications, primarily driven by the burgeoning demands of various fields. This paper comprehensively reviews recent advancements in droplet-based microfluidics, covering the fundamental working principles and the critical aspect of scale-up integration from working principles to scale-up integration. Based on the existing scale-up strategies, the paper also outlines the future research directions, identifies the potential opportunities, and addresses the typical unsolved challenges.

Fabrication of Crescent Shaped Microparticles for Particle Templated Droplet Formation

Crescent-shaped hydrogel microparticles are shown to template uniform volume aqueous droplets upon simple mixing with aqueous and oil media for various bioassays. This emerging "lab on a particle" technique requires hydrogel particles with tunable material properties and dimensions. The crescent shape of the particles is attained by aqueous two-phase separation of polymers followed by photopolymerization of the curable precursor. In this work, the phase separation of poly(ethylene glycol) diacrylate (PEGDA, Mw 700) and dextran (Mw 40 000) for tunable manufacturing of crescent-shaped particles is investigated. The particles' morphology is precisely tuned by following a phase diagram, varying the UV intensity, and adjusting the flow rates of various streams. The fabricated particles with variable dimensions encapsulate uniform aqueous droplets upon mixing with an oil phase. The particles are fluorescently labeled with red and blue emitting dyes at variable concentrations to produce six color-coded particles. The blue fluorescent dye shows a moderate response to the pH change. The fluorescently labeled particles are able to tolerate an extremely acidic solution (pH 1) but disintegrate within an extremely basic solution (pH 14). The particle-templated droplets are able to effectively retain the disintegrating particle and the fluorescent signal at pH 14.

Highly sensitive absorbance measurement using droplet microfluidics integrated with an oil extraction and long pathlength detection flow cell

In droplet microfluidics, UV-Vis absorption spectroscopy along with colorimetric assays have been widely used for chemical and biochemical analysis. However, the sensitivity of the measurement can be limited by the short optical pathlength. Here we report a novel design to enhance the sensitivity by removing oil and converting the droplets into a single-phase aqueous flow, which can be measured within a U-shape channel with long optical pathlength. The flow cells were fabricated via 3D printing. The calibration results have demonstrated complete oil removal and effective optical pathlengths similar to the designed channel lengths (from 5 to 20 mm). The flow cell was further employed in a droplet microfluidic-based phosphate sensing system. The measured phosphate levels displayed excellent consistency with data obtained from traditional UV spectroscopy analysis. This flow cell design overcomes the limitations of short optical pathlengths in droplet microfluidics and has the potential to be used for in situ and continuous monitoring.

Cellular immunity analysis by a modular acoustofluidic platform: CIAMAP

The study of molecular mechanisms at the single-cell level holds immense potential for enhancing immunotherapy and understanding neuroinflammation and neurodegenerative diseases by identifying previously concealed pathways within a diverse range of paired cells. However, existing single-cell pairing platforms have limitations in low pairing efficiency, complex manual operation procedures, and single-use functionality. Here, we report a multiparametric cellular immunity analysis by a modular acoustofluidic platform: CIAMAP. This platform enables users to efficiently sort and collect effector-target (i.e., NK92-K562) cell pairs and monitor the real-time dynamics of immunological response formation. Furthermore, we conducted transcriptional and protein expression analyses to evaluate the pathways that mediate effector cytotoxicity toward target cells, as well as the synergistic effect of doxorubicin on the cellular immune response. Our CIAMAP can provide promising building blocks for high-throughput quantitative single-cell level coculture to understand intercellular communication while also empowering immunotherapy by precision analysis of immunological synapses.

Rapid microfluidics prototyping through variotherm desktop injection molding for multiplex diagnostics

In this work, we demonstrate an inexpensive method of prototyping microfluidics using a desktop injection molding machine. A centrifugal microfluidic device with a novel central filling mechanism was developed to demonstrate the technique. We overcame the limitations of desktop machines in replicating microfluidic features by variotherm heating and cooling the mold between 50 °C and 110 °C within two minutes. Variotherm heating enabled good replication of microfeatures, with a coefficient of variation averaging only 3.6% attained for the measured widths of 100 μm wide molded channels. Using this methodology, we produced functional polystyrene centrifugal microfluidic chips, capable of aliquoting fluids into 5.0 μL reaction chambers with 97.5% accuracy. We performed allele-specific loop-mediated isothermal amplification (AS-LAMP) reactions for genotyping CYP2C19 alleles on these chips. Readouts were generated using optical pH sensors integrated onto chips, by drop-casting sensor precursor solutions into reaction chambers before final chip assembly. Positive reactions could be discerned by decreases in pH sensor fluorescence, thresholded against negative control reactions lacking the primers for nucleic acid amplification and with time-to-results averaging 38 minutes. Variotherm desktop injection molding can enable researchers to prototype microfluidic devices more cost-effectively, in an iterative fashion, due to reduced costs of smaller, in-house molds. Designs prototyped this way can be directly translated to mass production, enhancing their commercialization potential and positive impacts.

Direct electrification of silicon microfluidics for electric field applications

Microfluidic systems are widely used in fundamental research and industrial applications due to their unique behavior, enhanced control, and manipulation opportunities of liquids in constrained geometries. In micrometer-sized channels, electric fields are efficient mechanisms for manipulating liquids, leading to deflection, injection, poration or electrochemical modification of cells and droplets. While PDMS-based microfluidic devices are used due to their inexpensive fabrication, they are limited in terms of electrode integration. Using silicon as the channel material, microfabrication techniques can be used to create nearby electrodes. Despite the advantages that silicon provides, its opacity has prevented its usage in most important microfluidic applications that need optical access. To overcome this barrier, silicon-on-insulator technology in microfluidics is introduced to create optical viewports and channel-interfacing electrodes. More specifically, the microfluidic channel walls are directly electrified via selective, nanoscale etching to introduce insulation segments inside the silicon device layer, thereby achieving the most homogeneous electric field distributions and lowest operation voltages feasible across microfluidic channels. These ideal electrostatic conditions enable a drastic energy reduction, as effectively shown via picoinjection and fluorescence-activated droplet sorting applications at voltages below 6 and 15 V, respectively, facilitating low-voltage electric field applications in next-generation microfluidics.

In-depth analysis of biocatalysts by microfluidics: An emerging source of data for machine learning

Nowadays, the vastly increasing demand for novel biotechnological products is supported by the continuous development of biocatalytic applications which provide sustainable green alternatives to chemical processes. The success of a biocatalytic application is critically dependent on how quickly we can identify and characterize enzyme variants fitting the conditions of industrial processes. While miniaturization and parallelization have dramatically increased the throughput of next-generation sequencing systems, the subsequent characterization of the obtained candidates is still a limiting process in identifying the desired biocatalysts. Only a few commercial microfluidic systems for enzyme analysis are currently available, and the transformation of numerous published prototypes into commercial platforms is still to be streamlined. This review presents the state-of-the-art, recent trends, and perspectives in applying microfluidic tools in the functional and structural analysis of biocatalysts. We discuss the advantages and disadvantages of available technologies, their reproducibility and robustness, and readiness for routine laboratory use. We also highlight the unexplored potential of microfluidics to leverage the power of machine learning for biocatalyst development.

High-throughput screening paradigms in ecotoxicity testing: Emerging prospects and ongoing challenges

The rapidly increasing number of new production chemicals coupled with stringent implementation of global chemical management programs necessities a paradigm shift towards boarder uses of low-cost and high-throughput ecotoxicity testing strategies as well as deeper understanding of cellular and sub-cellular mechanisms of ecotoxicity that can be used in effective risk assessment. The latter will require automated acquisition of biological data, new capabilities for big data analysis as well as computational simulations capable of translating new data into in vivo relevance. However, very few efforts have been so far devoted into the development of automated bioanalytical systems in ecotoxicology. This is in stark contrast to standardized and high-throughput chemical screening and prioritization routines found in modern drug discovery pipelines. As a result, the high-throughput and high-content data acquisition in ecotoxicology is still in its infancy with limited examples focused on cell-free and cell-based assays. In this work we outline recent developments and emerging prospects of high-throughput bioanalytical approaches in ecotoxicology that reach beyond in vitro biotests. We discuss future importance of automated quantitative data acquisition for cell-free, cell-based as well as developments in phytotoxicity and in vivo biotests utilizing small aquatic model organisms. We also discuss recent innovations such as organs-on-a-chip technologies and existing challenges for emerging high-throughput ecotoxicity testing strategies. Lastly, we provide seminal examples of the small number of successful high-throughput implementations that have been employed in prioritization of chemicals and accelerated environmental risk assessment.

From Microtiter Plates to Droplets—There and Back Again

Droplet-based microfluidic screening techniques can benefit from interfacing established microtiter plate-based screening and sample management workflows. Interfacing tools are required both for loading preconfigured microtiter-plate (MTP)-based sample collections into droplets and for dispensing the used droplets samples back into MTPs for subsequent storage or further processing. Here, we present a collection of Digital Microfluidic Pipetting Tips (DMPTs) with integrated facilities for droplet generation and manipulation together with a robotic system for its operation. This combination serves as a bidirectional sampling interface for sample transfer from wells into droplets (w2d) and vice versa droplets into wells (d2w). The DMPT were designed to fit into 96-deep-well MTPs and prepared from glass by means of microsystems technology. The aspirated samples are converted into the channel-confined droplets’ sequences separated by an immiscible carrier medium. To comply with the demands of dose-response assays, up to three additional assay compound solutions can be added to the sample droplets. To enable different procedural assay protocols, four different DMPT variants were made. In this way, droplet series with gradually changing composition can be generated for, e.g., 2D screening purposes. The developed DMPT and their common fluidic connector are described here. To handle the opposite transfer d2w, a robotic transfer system was set up and is described briefly.

Strain Development in Microalgal Biotechnology-Random Mutagenesis Techniques

Microalgal biomass and metabolites can be used as a renewable source of nutrition, pharmaceuticals and energy to maintain or improve the quality of human life. Microalgae’s high volumetric productivity and low impact on the environment make them a promising raw material in terms of both ecology and economics. To optimize biotechnological processes with microalgae, improving the productivity and robustness of the cell factories is a major step towards economically viable bioprocesses. This review provides an overview of random mutagenesis techniques that are applied to microalgal cell factories, with a particular focus on physical and chemical mutagens, mutagenesis conditions and mutant characteristics.

Application and prospects of high-throughput screening for in vitro neurogenesis

Over the past few decades, high-throughput screening (HTS) has made great contributions to new drug discovery. HTS technology is equipped with higher throughput, minimized platforms, more automated and computerized operating systems, more efficient and sensitive detection devices, and rapid data processing systems. At the same time, in vitro neurogenesis is gradually becoming important in establishing models to investigate the mechanisms of neural disease or developmental processes. However, challenges remain in generating more mature and functional neurons with specific subtypes and in establishing robust and standardized three-dimensional (3D) in vitro models with neural cells cultured in 3D matrices or organoids representing specific brain regions. Here, we review the applications of HTS technologies on in vitro neurogenesis, especially aiming at identifying the essential genes, chemical small molecules and adaptive microenvironments that hold great prospects for generating functional neurons or more reproductive and homogeneous 3D organoids. We also discuss the developmental tendency of HTS technology, e.g., so-called next-generation screening, which utilizes 3D organoid-based screening combined with microfluidic devices to narrow the gap between in vitro models and in vivo situations both physiologically and pathologically.

Artificial intelligence to bring nanomedicine to life

The technology of drug delivery systems (DDSs) has demonstrated an outstanding performance and effectiveness in production of pharmaceuticals, as it is proved by many FDA-approved nanomedicines that have an enhanced selectivity, manageable drug release kinetics and synergistic therapeutic actions. Nonetheless, to date, the rational design and high-throughput development of nanomaterial-based DDSs for specific purposes is far from a routine practice and is still in its infancy, mainly due to the limitations in scientists' capabilities to effectively acquire, analyze, manage, and comprehend complex and ever-growing sets of experimental data, which is vital to develop DDSs with a set of desired functionalities. At the same time, this task is feasible for the data-driven approaches, high throughput experimentation techniques, process automatization, artificial intelligence (AI) technology, and machine learning (ML) approaches, which is referred to as The Fourth Paradigm of scientific research. Therefore, an integration of these approaches with nanomedicine and nanotechnology can potentially accelerate the rational design and high-throughput development of highly efficient nanoformulated drugs and smart materials with pre-defined functionalities. In this Review, we survey the important results and milestones achieved to date in the application of data science, high throughput, as well as automatization approaches, combined with AI and ML to design and optimize DDSs and related nanomaterials. This manuscript mission is not only to reflect the state-of-art in data-driven nanomedicine, but also show how recent findings in the related fields can transform the nanomedicine's image. We discuss how all these results can be used to boost nanomedicine translation to the clinic, as well as highlight the future directions for the development, data-driven, high throughput experimentation-, and AI-assisted design, as well as the production of nanoformulated drugs and smart materials with pre-defined properties and behavior. This Review will be of high interest to the chemists involved in materials science, nanotechnology, and DDSs development for biomedical applications, although the general nature of the presented approaches enables knowledge translation to many other fields of science.

A Machine Learning and Computer Vision Approach to Rapidly Optimize Multiscale Droplet Generation

Generating droplets from a continuous stream of fluid requires precise tuning of a device to find optimized control parameter conditions. It is analytically intractable to compute the necessary control parameter values of a droplet-generating device that produces optimized droplets. Furthermore, as the length scale of the fluid flow changes, the formation physics and optimized conditions that induce flow decomposition into droplets also change. Hence, a single proportional integral derivative controller is too inflexible to optimize devices of different length scales or different control parameters, while classification machine learning techniques take days to train and require millions of droplet images. Therefore, the question is posed, can a single method be created that universally optimizes multiple length-scale droplets using only a few data points and is faster than previous approaches? In this paper, a Bayesian optimization and computer vision feedback loop is designed to quickly and reliably discover the control parameter values that generate optimized droplets within different length-scale devices. This method is demonstrated to converge on optimum parameter values using 60 images in only 2.3 h, 30× faster than previous approaches. Model implementation is demonstrated for two different length-scale devices: a milliscale inkjet device and a microfluidics device.

An Overview of Organs-on-Chips Based on Deep Learning

Microfluidic-based organs-on-chips (OoCs) are a rapidly developing technology in biomedical and chemical research and have emerged as one of the most advanced and promising in vitro models. The miniaturization, stimulated tissue mechanical forces, and microenvironment of OoCs offer unique properties for biomedical applications. However, the large amount of data generated by the high parallelization of OoC systems has grown far beyond the scope of manual analysis by researchers with biomedical backgrounds. Deep learning, an emerging area of research in the field of machine learning, can automatically mine the inherent characteristics and laws of "big data" and has achieved remarkable applications in computer vision, speech recognition, and natural language processing. The integration of deep learning in OoCs is an emerging field that holds enormous potential for drug development, disease modeling, and personalized medicine. This review briefly describes the basic concepts and mechanisms of microfluidics and deep learning and summarizes their successful integration. We then analyze the combination of OoCs and deep learning for image digitization, data analysis, and automation. Finally, the problems faced in current applications are discussed, and future perspectives and suggestions are provided to further strengthen this integration.

Microfluidics as a Novel Technique for Tuberculosis: From Diagnostics to Drug Discovery

Tuberculosis (TB) remains a global healthcare crisis, with an estimated 5.8 million new cases and 1.5 million deaths in 2020. TB is caused by infection with the major human pathogen Mycobacterium tuberculosis, which is difficult to rapidly diagnose and treat. There is an urgent need for new methods of diagnosis, sufficient in vitro models that capably mimic all physiological conditions of the infection, and high-throughput drug screening platforms. Microfluidic-based techniques provide single-cell analysis which reduces experimental time and the cost of reagents, and have been extremely useful for gaining insight into monitoring microorganisms. This review outlines the field of microfluidics and discusses the use of this novel technique so far in M. tuberculosis diagnostics, research methods, and drug discovery platforms. The practices of microfluidics have promising future applications for diagnosing and treating TB.

Thermally-actuated microfluidic membrane valve for point-of-care applications

Microfluidics has enabled low volume biochemistry reactions to be carried out at the point-of-care. A key component in microfluidics is the microfluidic valve. Microfluidic valves are not only useful for directing flow at intersections but also allow mixtures/dilutions to be tuned real-time and even provide peristaltic pumping capabilities. In the transition from chip-in-a-lab to lab-on-a-chip, it is essential to ensure that microfluidic valves are designed to require less peripheral equipment and that they are transportable. In this paper, a thermally-actuated microfluidic valve is presented. The valve itself is fabricated with off-the-shelf components without the need for sophisticated cleanroom techniques. It is shown that multiple valves can be controlled and operated via a power supply and an Arduino microcontroller; an important step towards transportable microfluidic devices capable of carrying out analytical assays at the point-of-care. It is been calculated that a single actuator costs less than $1, this highlights the potential of the presented valve for scaling out. The valve operation is demonstrated by adjusting the ratio of a water/dye mixture in a continuous flow microfluidic chip with Y-junction channel geometry. The power required to operate one microfluidic valve has been characterised both theoretically and experimentally. Cyclical operation of the valve has been demonstrated for 65 h with 585 actuations. The presented valve is capable of actuating rectangular microfluidic channels of 500 μm × 50 μm with an expected temperature increase of up to 5 °C. The fastest actuation times achieved were 2 s for valve closing (heating) and 9 s for valve opening (cooling).

Cell Washing and Solution Exchange in Droplet Microfluidic Systems

Water-in-oil emulsion droplet microfluidic systems have been extensively developed, and currently, almost all cell handling steps can be conducted in this format. An exception is the cell washing and solution exchange step, which is commonly utilized in many conventional cell assays. This paper presents an in-droplet cell washing and solution exchange technology that utilizes dielectrophoretic (DEP) force to move all cells to one side of a droplet, followed by asymmetrical splitting of the droplet to obtain a small daughter droplet that contains all or most of the cells, and then finally merges this cell-concentrated droplet with a new droplet that contains the desired solution. These sequential droplet manipulation steps were integrated into a single platform, where up to 88% of the original solution in the droplet could be exchanged with the new solution while keeping cell loss to less than 5%. Two application examples were demonstrated using the developed technology. In the first example, green microalga Chlamydomonas reinhardtii cells were manipulated using negative DEP force to exchange the regular culture medium with a nitrogen-limited medium to induce lipid production. In the second example, Salmonella enterica cells were manipulated using positive DEP force to replace fluorescent dye that models fluorescent cell stains that contribute to high background noise in fluorescence-based droplet content detection with fresh buffer solution, significantly improving the droplet content detection sensitivity. Since the cell washing step is one of the most frequently utilized steps in many cell biology assays, we expect that the developed technology can significantly broaden the type of assay that can be conducted in droplet microfluidic format.

Non-Newtonian Droplet Generation in a Cross-Junction Microfluidic Channel

A two-dimensional CFD model based on volume-of-fluid (VOF) is introduced to examine droplet generation in a cross-junction microfluidic using an open-source software, OpenFOAM together with an interFoam solver. Non-Newtonian power-law droplets in Newtonian liquid is numerically studied and its effect on droplet size and detachment time in three different regimes, i.e., squeezing, dripping and jetting, are investigated. To understand the droplet formation mechanism, the shear-thinning behaviour was enhanced by increasing the polymer concentrations in the dispersed phase. It is observed that by choosing a shear-dependent fluid, droplet size decreases compared to Newtonian fluids while detachment time increases due to higher apparent viscosity. Moreover, the rheological parameters-n and K in the power-law model-impose a considerable effect on the droplet size and detachment time, especially in the dripping and jetting regimes. Those parameters also have the potential to change the formation regime if the capillary number (Ca) is high enough. This work extends the understanding of non-Newtonian droplet formation in microfluidics to control the droplet characteristics in applications involving shear-thinning polymeric solutions.

Curvature in the reproductive tract alters sperm-surface interactions

The fallopian tube is lined with a highly complex folded epithelium surrounding a lumen that progressively narrows. To study the influence of this labyrinthine complexity on sperm behavior, we use droplet microfluidics to create soft curved interfaces over a range of curvatures corresponding to the in vivo environment. We reveal a dynamic response mechanism in sperm, switching from a progressive surface-aligned motility mode at low curvatures (larger droplets), to an aggressive surface-attacking mode at high curvatures (smaller droplets of <50 µm-radius). We show that sperm in the attacking mode swim ~33% slower, spend 1.66-fold longer at the interface and have a 66% lower beating amplitude than in the progressive mode. These findings demonstrate that surface curvature within the fallopian tube alters sperm motion from a faster surface aligned locomotion in distal regions to a prolonged physical contact with the epithelium near the site of fertilization, the latter being known to promote capacitation and fertilization competence.

Microfluidic technologies for drug discovery and development: friend or foe?

There is a point in the evolution of every new technology when questions need to be asked regarding its usefulness and impact. Although microfluidic technologies have drastically decreased the scales at which laboratory processes can be performed and have enabled scientific advances that would have otherwise not been possible, it is time to consider whether these technologies are more disruptive than enabling. Here, my aims are to introduce researchers in the broad fields of drug discovery and development to the advantages and disadvantages of microfluidic technologies, to highlight current work showing how microfluidic technologies can be used at different stages in the drug discovery and development process, to discuss how we can transfer academic breakthroughs in the field of microfluidic technologies to industrial environments, and to examine whether microfluidic technologies have the potential to cause a fundamental paradigm shift in the way that drug discovery and development occurs.

Molecular diffusion analysis of dynamic blood flow and plasma separation driven by self-powered microfluidic devices

Integration of microfluidic devices with pressure-driven, self-powered fluid flow propulsion methods has provided a very effective solution for on-chip, droplet blood testing applications. However, precise understanding of the physical process governing fluid dynamics in polydimethylsiloxane (PDMS)-based microfluidic devices remains unclear. Here, we propose a pressure-driven diffusion model using Fick's law and the ideal gas law, the results of which agree well with the experimental fluid dynamics observed in our vacuum pocket-assisted, self-powered microfluidic devices. Notably, this model enables us to precisely tune the flow rate by adjusting two geometrical parameters of the vacuum pocket. By linking the self-powered fluid flow propulsion method to the sedimentation, we also show that direct plasma separation from a drop of whole blood can be achieved using only a simple construction without the need for external power sources, connectors, or a complex operational procedure. Finally, the potential of the vacuum pocket, along with a removable vacuum battery to be integrated with non-PDMS microfluidic devices to drive and control the fluid flow, is demonstrated.

Recent advances in droplet microfluidics for enzyme and cell factory engineering

Enzymes and cell factories play essential roles in industrial biotechnology for the production of chemicals and fuels. The properties of natural enzymes and cells often cannot meet the requirements of different industrial processes in terms of cost-effectiveness and high durability. To rapidly improve their properties and performances, laboratory evolution equipped with high-throughput screening methods and facilities is commonly used to tailor the desired properties of enzymes and cell factories, addressing the challenges of achieving high titer and the yield of the target products at high/low temperatures or extreme pH, in unnatural environments or in the presence of unconventional media. Droplet microfluidic screening (DMFS) systems have demonstrated great potential for exploring vast genetic diversity in a high-throughput manner (>10⁶/h) for laboratory evolution and have been increasingly used in recent years, contributing to the identification of extraordinary mutants. This review highlights the recent advances in concepts and methods of DMFS for library screening, including the key factors in droplet generation and manipulation, signal sources for sensitive detection and sorting, and a comprehensive summary of success stories of DMFS implementation for engineering enzymes and cell factories during the past decade.

An ultra high-efficiency droplet microfluidics platform using automatically synchronized droplet pairing and merging

Droplet microfluidics systems hold great promise in their ability to conduct high-throughput assays for a broad range of life science applications. Despite their promise in the field and capability to conduct complex liquid handling steps, currently, most droplet microfluidic systems used for real assays utilize only a few droplet manipulation steps connected in series, and are often not integrated together on a single chip or platform. This is due to the fact that linking multiple sequential droplet functions within a single chip to operate at high efficiency over long periods of time remains technically challenging. Considering sequential manipulation is often required to conduct high-throughput screening assays on large cellular and molecular libraries, advancements in sequential operation and integration are required to advance the field. This current limitation greatly reduces the type of assays that can be realized in a high-throughput droplet format and becomes more prevalent in large library screening applications. Here we present an integrated multi-layer droplet microfluidic platform that can handle large numbers of droplets with high efficiency and minimum error. The platform combines two-photon photolithography-fabricated curved microstructures that allow high-efficiency (99.9%) re-flow of droplets and a unique droplet cleaving that automatically synchronizes paired droplets enabling high-efficiency (99.9%) downstream merging. We demonstrate that this method is applicable to a broad range of droplet sizes, including relatively large droplet sizes (hundreds of micrometers in diameter) that are typically more difficult to manipulate with high efficiency, yet are required in many cell assay applications requiring large organisms or multiple incubation steps. The utility of this highly efficient integrated droplet microfluidic platform was demonstrated by conducting a mock antibiotic screening assay against a bacterial pathogen. The approach and system presented here provides new avenues for the realization of ultra-high-efficiency multi-step droplet microfluidic systems with minimal error.

On-chip analysis of atmospheric ice-nucleating particles in continuous flow

Ice-nucleating particles (INPs) are of atmospheric importance because they catalyse the freezing of supercooled cloud droplets, strongly affecting the lifetime and radiative properties of clouds. There is a need to improve our knowledge of the global distribution of INPs, their seasonal cycles and long-term trends, but our capability to make these measurements is limited. Atmospheric INP concentrations are often determined using assays involving arrays of droplets on a cold stage, but such assays are frequently limited by the number of droplets that can be analysed per experiment, often involve manual processing (e.g. pipetting of droplets), and can be susceptible to contamination. Here, we present a microfluidic platform, the LOC-NIPI (Lab-on-a-Chip Nucleation by Immersed Particle Instrument), for the generation of water-in-oil droplets and their freezing in continuous flow as they pass over a cold plate for atmospheric INP analysis. LOC-NIPI allows the user to define the number of droplets analysed by simply running the platform for as long as required. The use of small (∼100 μm diameter) droplets minimises the probability of contamination in any one droplet and therefore allows supercooling all the way down to homogeneous freezing (around -36 °C), while a temperature probe in a proxy channel provides an accurate measure of temperature without the need for temperature modelling. The platform was validated using samples of pollen extract and Snomax®, with hundreds of droplets analysed per temperature step and thousands of droplets being measured per experiment. Homogeneous freezing of purified water was studied using >10 000 droplets with temperature increments of 0.1 °C. The results were reproducible, independent of flow rate in the ranges tested, and the data compared well to conventional instrumentation and literature data. The LOC-NIPI was further benchmarked in a field campaign in the Eastern Mediterranean against other well-characterised instrumentation. The continuous flow nature of the system provides a route, with future development, to the automated monitoring of atmospheric INP at field sites around the globe.

Creating and screening natural product libraries

Covering: up to 2020The National Cancer Institute of the United States (NCI) has initiated a Cancer Moonshot program entitled the NCI Program for Natural Product Discovery. As part of this effort, the NCI is producing a library of 1 000 000 partially purified natural product fractions which are being plated into 384-well plates and provided to the research community free of charge. As the first 326 000 of these fractions have now been made available, this review seeks to describe the general methods used to collect organisms, extract those organisms, and create a prefractionated library. Importantly, this review also details both cell-based and cell-free bioassay methods and the adaptations necessary to those methods to productively screen natural product libraries. Finally, this review briefly describes post-screen dereplication and compound purification and scale up procedures which can efficiently identify active compounds and produce sufficient quantities of natural products for further pre-clinical development.

A high-throughput system combining microfluidic hydrogel droplets with deep learning for screening the antisolvent-crystallization conditions of active pharmaceutical ingredients

Crystallization of active pharmaceutical ingredients (APIs) is a crucial process in the pharmaceutical industry due to its great impact in drug efficacy. However, conventional approaches for screening the optimal crystallization conditions of APIs are usually time-consuming, labor-intensive and expensive. Recently, droplet microfluidic technology has offered an alternative strategy for high-throughput screening of crystallization conditions. Despite its many advantages such as low sample consumption, reduced operation time, increased throughput, etc., some challenges remain to be solved, such as instability of droplets in the long-term and tedious efforts required for extracting useful information from massive data. To solve these problems, a high-throughput system that combined microfluidic hydrogel droplets with deep learning was proposed for the first time to screen the antisolvent-crystallization conditions of APIs. In this system, stable hydrogel droplets containing different concentrations of indomethacin, its solvent and antisolvent were generated on a chip. Crystals of indomethacin with different morphologies were formed in hydrogel droplets, and their optical images were captured by a camera. Then, deep learning was applied to identify the hundreds of indomethacin crystal images and successfully classify the crystal morphologies in a short time; a ternary phase diagram was drawn by combining the experimental results with the recognition results of crystal morphologies, and was used to guide the scale-up preparations of indomethacin crystals as desired. This system, which integrated high throughput preparation, characterization and data analysis, is also useful for screening the crystallization conditions and processes of semiconductors, catalysts, agrochemicals, proteins and other specialty chemicals.

Trapping and Coalescence of Diamagnetic Aqueous Droplets Using Negative Magnetophoresis

The manipulation of aqueous droplets has a profound significance in biochemical assays. Magnetic field-driven droplet manipulation, offering unique advantages, is consequently gaining attention. However, the phenomenon relating to diamagnetic droplets is not well understood. Here, we report the understanding of trapping and coalescence of flowing diamagnetic aqueous droplets in a paramagnetic (oil-based ferrofluid) medium using negative magnetophoresis. Our study revealed that the trapping phenomenon is underpinned by the interplay of magnetic energy (E_m) and frictional (viscous) energy (E_f), in terms of magnetophoretic stability number, S_m = (E_m/E_f). The trapping and nontrapping regimes are characterized based on the peak value of magnetophoretic stability number, S_mp, and droplet size, D*. The study of coalescence of a trapped droplet with a follower droplet (and a train of droplets) revealed that the film-drainage Reynolds number (Re_fd) representing the coalescence time depends on the magnetic Bond number, Bo_m. The coalesced droplet continues to remain trapped or gets self-released obeying the S_mp and D* criterion. Our study offers an understanding of the magnetic manipulation of diamagnetic aqueous droplets that can potentially be used for biochemical assays in microfluidics.

A Microarray Screening Platform with an Experimental Conditions Gradient Generator for the High-Throughput Synthesis of Micro/Nanosized Calcium Phosphates

Calcium phosphates (CaP) represent an impressive kind of biomedical material due to their excellent biocompatibility, bioactivity, and biodegradability. Their morphology and structure highly influence their properties and applications. Whilst great progress has been made in research on biomedical materials, there is still a need to develop a method that can rapidly synthesize and screen micro/nanosized biomedical materials. Here, we utilized a microarray screening platform that could provide the high-throughput synthesis of biomedical materials and screen the vital reaction conditions. With this screening platform, 9 × 9 sets of parallel experiments could be conducted simultaneously with one- or two-dimensions of key reaction condition gradients. We used this platform to establish a one-dimensional gradient of the pH and citrate concentration and a two-dimensional gradient of both the Ca/P ratio and pH to synthesize CaP particles with various morphologies. This screening platform also shows the potential to be extended to other reaction systems for rapid high-throughput screening.

Image-Based Single Cell Sorting Automation in Droplet Microfluidics

The recent boom in single-cell omics has brought researchers one step closer to understanding the biological mechanisms associated with cell heterogeneity. Rare cells that have historically been obscured by bulk measurement techniques are being studied by single cell analysis and providing valuable insight into cell function. To support this progress, novel upstream capabilities are required for single cell preparation for analysis. Presented here is a droplet microfluidic, image-based single-cell sorting technique that is flexible and programmable. The automated system performs real-time dual-camera imaging (brightfield & fluorescent), processing, decision making and sorting verification. To demonstrate capabilities, the system was used to overcome the Poisson loading problem by sorting for droplets containing a single red blood cell with 85% purity. Furthermore, fluorescent imaging and machine learning was used to load single K562 cells amongst clusters based on their instantaneous size and circularity. The presented system aspires to replace manual cell handling techniques by translating expert knowledge into cell sorting automation via machine learning algorithms. This powerful technique finds application in the enrichment of single cells based on their micrographs for further downstream processing and analysis.

Scalable microfluidic droplet on-demand generator for non-steady operation of droplet-based assays

We developed a microfluidic droplet on-demand (DoD) generator that enables the production of droplets with a volume solely governed by the geometry of the generator for a range of operating conditions. The prime reason to develop this novel type of DoD generator is that its robustness in operation enables scale out and operation under non-steady conditions, which are both essential features for the further advancement of droplet-based assays. We first detail the working principle of the DoD generator and study the sensitivity of the volume of the generated droplets with respect to the used fluids and control parameters. We next compare the performance of our DoD generator when scaled out to 8 parallel generators to the performance of a conventional DoD generator in which the droplet volume is not geometry-controlled, showing its superior performance. Further scale out to 64 parallel DoD generators shows that all generators produce droplets with a volume between 91% and 105% of the predesigned volume. We conclude the paper by presenting a simple droplet-based assay in which the DoD generator enables sequential supply of reagent droplets to a droplet stored in the device, illustrating its potential to be used in droplet-based assays for biochemical studies under non-steady operation conditions.

Reaction Cycling for Kinetic Analysis in Flow

A reactor capable of efficiently collecting kinetic data in flow is presented. Conversion over time data is obtained by cycling a discrete reaction slug back and forth between two residence coils, with analysis performed each time the solution is passed between the two. In contrast to a traditional steady-state continuous flow system, which requires upward of 5× the total reaction time to obtain reaction progress data, this design achieves much higher efficiency by collecting all data during a single reaction. In combination with minimal material consumption (reactions performed in 300 μL slugs), this represents an improvement in efficiency for typical kinetic experimentation in batch as well. Application to kinetic analysis of a wide variety of transformations (acylation, S_NAr, silylation, solvolysis, Pd catalyzed C-S cross-coupling and cycloadditions) is demonstrated, highlighting both the versatility of the reactor and the benefits of performing kinetic analysis as a routine part of reaction optimization/development. Extension to the monitoring of multiple reactions simultaneously is also realized by operating the reactor with multiple reaction slugs at the same time.

Microfluidic Study of the Electrocoalescence of Aqueous Droplets in Crude Oil

In electrocoalescence, an electric field is applied to a dispersion of conducting water droplets in a poorly conducting oil to force the droplets to merge in the direction of the field. Electrocoalescence is used in petroleum refining to separate water from crude oil and in droplet-based microfluidics to combine droplets of water in oil and to break emulsions. Using a microfluidic design to generate a two-dimensional (2D) emulsion, we demonstrate that electrocoalescence in an opaque crude oil can be visualized with optical microscopy and studied on an individual droplet basis in a chamber whose height is small enough to make the dispersions two dimensional and transparent. From reconstructions of images of the 2D electrocoalescence, the electrostatic forces driving the droplet merging are calculated in a numerically exact manner and used to predict observed coalescence events. Hence, the direct simulation of the electrocoalescence-driven breakdown of 2D emulsions in microfluidic devices can be envisioned.

High-Throughput Screening Technology in Industrial Biotechnology

Based on the development of automatic devices and rapid assay methods, various high-throughput screening (HTS) strategies have been established for improving the performance of industrial microorganisms. We discuss the most significant factors that can improve HTS efficiency, including the construction of screening libraries with high diversity and the use of new detection methods to expand the search range and highlight target compounds. We also summarize applications of HTS for enhancing the performance of industrial microorganisms. Current challenges and potential improvements to HTS in industrial biotechnology are discussed in the context of rapid developments in synthetic biology, nanotechnology, and artificial intelligence. Rational integration will be an important driving force for constructing more efficient industrial microorganisms with wider applications in biotechnology.

A micrometer head integrated microfluidic device for facile droplet size control and automatic measurement of a droplet size

A novel microfluidic droplet generator is proposed, which can control the droplet size through turning an integrated micrometer head with ease, and the size of the produced micro-droplet can be automatically and real-time monitored by an open-sourced software and off-the-shelf hardware.

A Droplet Microfluidic-Based Sensor for Simultaneous in Situ Monitoring of Nitrate and Nitrite in Natural Waters

Microfluidic-based chemical sensors take laboratory analytical protocols and miniaturize them into field-deployable systems for in situ monitoring of water chemistry. Here, we present a prototype nitrate/nitrite sensor based on droplet microfluidics that in contrast to standard (continuous phase) microfluidic sensors, treats water samples as discrete droplets contained within a flow of oil. The new sensor device can quantify the concentrations of nitrate and nitrite within each droplet and provides high measurement frequency and low fluid consumption. Reagent consumption is at a rate of 2.8 mL/day when measuring every ten seconds, orders of magnitude more efficient than those of the current state-of-the-art sensors. The sensor's capabilities were demonstrated during a three-week deployment in a tidal river. The accurate and high frequency data (6% error relative to spot samples, measuring at 0.1 Hz) elucidated the influence of tidal variation, rain events, diurnal effects, and anthropogenic input on concentrations at the deployment site. This droplet microfluidic-based sensor is suitable for a wide range of applications such as monitoring of rivers, lakes, coastal waters, and industrial effluents.

Accurate high-throughput screening based on digital protein synthesis in a massively parallel femtoliter droplet array

We report a general strategy based on digital counting principle that enables an efficient acquisition of enzyme mutants with desired activities from just a few clones within a day. We prepared a high-density femtoliter droplet array, consisting of 1 million uniform droplets per 1 cm² to carry out high-throughput protein synthesis and screening. Single DNA molecules were randomly distributed into each droplet following a Poisson process to initiate the protein synthesis with coupled cell-free transcription and translation reactions and then recovered by a microcapillary. The protein yield in each droplet was proportional to the number of DNA molecules, meaning that droplets with apparent intensities higher than the Poisson distribution-predicted maximum can be readily identified as the exact hits exhibiting the desired increased activity. We improved the activity of an alkaline phosphatase up to near 20-fold by using less than 10 nl of reagents.

Single-cell RT-LAMP mRNA detection by integrated droplet sorting and merging

Recent advances in transcriptomic analysis at single-cell resolution reveal cell-to-cell heterogeneity in a biological sample with unprecedented resolution. Partitioning single cells in individual micro-droplets and harvesting each cell's mRNA molecules for next-generation sequencing has proven to be an effective method for profiling transcriptomes from a large number of cells at high throughput. However, the assays to recover the full transcriptomes are time-consuming in sample preparation and require expensive reagents and sequencing cost. Many biomedical applications, such as pathogen detection, prefer highly sensitive, reliable and low-cost detection of selected genes. Here, we present a droplet-based microfluidic platform that permits seamless on-chip droplet sorting and merging, which enables completing multi-step reaction assays within a short time. By sequentially adding lysis buffers and reactant mixtures to micro-droplet reactors, we developed a novel workflow of single-cell reverse transcription loop-mediated-isothermal amplification (scRT-LAMP) to quantify specific mRNA expression levels in different cell types within one hour. Including single cell encapsulation, sorting, lysing, reactant addition, and quantitative mRNA detection, the fully on-chip workflow provides a rapid, robust, and high-throughput experimental approach for a wide variety of biomedical studies.

Droplet-based single cell RNAseq tools: a practical guide

Droplet based scRNA-seq systems such as Drop-seq, inDrop and Chromium 10X have been the catalyst for the wide adoption of high-throughput scRNA-seq technologies in the research laboratory. In order to understand the capabilities of these systems to deeply interrogate biology; here we provide a practical guide through all the steps involved in a typical scRNA-seq experiment. Through comparing and contrasting these three main droplet based systems (and their derivatives), we provide an overview of all critical considerations in obtaining high quality and biologically relevant data. We also discuss the limitations of these systems and how they fit into the emerging field of Genomic Cytometry.

Fluorescent nucleic acid probe in droplets for bacterial sorting (FNAP-sort) as a high-throughput screening method for environmental bacteria with various growth rates

We have developed a new method for selectively sorting droplets containing growing bacteria using a fluorescence resonance energy transfer (FRET)-based RNA probe. Bacteria and the FRET-based RNA probe are encapsulated into nanoliter-scale droplets, which are incubated to allow for cell growth. The FRET-based RNA probe is cleaved by RNase derived from the bacteria propagated in the droplets, resulting in an increase in fluorescence intensity. The fluorescent droplets containing growing bacteria are distinguishable from quenching droplets, which contain no cells. We named this method FNAP-sort based on the use of a fluorescent nucleic acid probe in droplets for bacterial sorting. Droplets containing the FRET-based RNA probe and four species of pure cultures, which grew in the droplets, were selectively enriched on the basis of fluorescence emission. Furthermore, fluorescent droplets were sorted from more than 500,000 droplets generated using environmental soil bacteria and the FRET-based RNA probe on days 1, 3, and 7 with repeated incubation and sorting. The bacterial compositions of sorted droplets differed on days 1, 3, and 7; moreover, on day 7, the bacterial composition of the fluorescent droplets was drastically different from that of the quenching droplets. We believe that FNAP-sort is useful for high-throughput cultivation and sorting of environmental samples containing bacteria with various growth rates, including slow-growing microbes that require long incubation times.