High-throughput, quantitative enzyme kinetic analysis in microdroplets using stroboscopic epifluorescence imaging

Deep learning-assisted concentration gradient generation for the study of 3D cell cultures in hydrogel beads of varying stiffness

The study of dose-response relationships underpins analytical biosciences. Droplet microfluidics platforms can automate the generation of microreactors encapsulating varying concentrations of an assay component, providing datasets across a large chemical space in a single experiment. A classical method consists in varying the flow rate of multiple solutions co-flowing into a single microchannel (producing different volume fractions) before encapsulating the contents into water-in-oil droplets. This process can be automated through controlling the pumping elements but lacks the ability to adapt to unpredictable experimental scenarios, often requiring constant human supervision. In this paper, we introduce an image-based, closed-loop control system for assessing and adjusting volume fractions, thereby generating unsupervised, uniform concentration gradients. We trained a shallow convolutional neural network to assess the position of the laminar flow interface between two co-flowing fluids and used this model to adjust flow rates in real-time. We apply the method to generate alginate microbeads in which HEK293FT cells could grow in three dimensions. The stiffnesses ranged from 50 Pa to close to 1 kPa in Young modulus and were encoded with a fluorescent marker. We trained deep learning models based on the YOLOv4 object detector to efficiently detect both microbeads and multicellular spheroids from high-content screening images. This allowed us to map relationships between hydrogel stiffness and multicellular spheroid growth.

Ultrahigh-Throughput Enzyme Engineering and Discovery in In Vitro Compartments

Novel and improved biocatalysts are increasingly sourced from libraries via experimental screening. The success of such campaigns is crucially dependent on the number of candidates tested. Water-in-oil emulsion droplets can replace the classical test tube, to provide in vitro compartments as an alternative screening format, containing genotype and phenotype and enabling a readout of function. The scale-down to micrometer droplet diameters and picoliter volumes brings about a >107-fold volume reduction compared to 96-well-plate screening. Droplets made in automated microfluidic devices can be integrated into modular workflows to set up multistep screening protocols involving various detection modes to sort >107 variants a day with kHz frequencies. The repertoire of assays available for droplet screening covers all seven enzyme commission (EC) number classes, setting the stage for widespread use of droplet microfluidics in everyday biochemical experiments. We review the practicalities of adapting droplet screening for enzyme discovery and for detailed kinetic characterization. These new ways of working will not just accelerate discovery experiments currently limited by screening capacity but profoundly change the paradigms we can probe. By interfacing the results of ultrahigh-throughput droplet screening with next-generation sequencing and deep learning, strategies for directed evolution can be implemented, examined, and evaluated.

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.

Kinetic Profiling of Homogeneous and Heterogeneous Biocatalysts in Continuous Flow by Online Mass Spectrometry

Enzyme kinetics is normally assessed by performing individual kinetic measurements using batch-type reactors (test tubes, microtiter plates), in which enzymes are mixed with different substrates. Some drawbacks of conventional methods are the large amounts of experimental materials, long analysis times, and limitations of spectrophotometry. Therefore, we have developed a method for facile determination of enzyme kinetics using online flow-based mass spectrometry. A concentration ramp of substrate or product was created by dynamically adjusting flow rates of pumps delivering stock solution of substrate and diluent. Precise kinetic measurements were performed by reaction product quantification and initial rate calculation. In the presence of ascending substrate concentrations, the rate of a target enzyme (penicillinase)-catalyzed hydrolysis was varied. By measuring the reaction product continuously, Michaelis constants (K_M) could be calculated. The enzyme kinetic measurements for hydrolysis of penicillins were conducted based on this simple, rapid, and low sample consumption online flow device. In the homogeneous reaction, the K_M values for amoxicillin, ampicillin, penicillin G, and penicillin V were 254.9 ± 14.5, 29.2 ± 0.3, 2.6 ± 0.1, and 5.4 ± 0.1 μM, respectively. In the heterogeneous reaction, the K_M values for amoxicillin, ampicillin, penicillin G, and penicillin V were 408.9 ± 75.1, 114.4 ± 8.0, 21.8 ± 0.7, and 83.3 ± 4.8 μM, respectively. Apart from enzyme assay, the showcased method for the generation of temporal concentration ramps can be utilized to perform rapid quantity calibrations for mass spectrometric analyses.

Emerging platforms for high-throughput enzymatic bioassays

Enzymes have essential roles in catalyzing biological reactions and maintaining metabolic systems. Many in vitro enzymatic bioassays have been developed for use in industrial and research fields, such as cell biology, enzyme engineering, drug screening, and biofuel production. Of note, many of these require the use of high-throughput platforms. Although the microtiter plate remains the standard for high-throughput enzymatic bioassays, microfluidic arrays and droplet microfluidics represent emerging methods. Each has seen significant advances and offers distinct advantages; however, drawbacks in key performance metrics, including reagent consumption, reaction manipulation, reaction recovery, real-time measurement, concentration gradient range, and multiplexity, remain. Herein, we compare recent high-throughput platforms using the aforementioned metrics as criteria and provide insights into remaining challenges and future research trends.

Low-cost programable stroboscopic illumination with sub-microsecond pulses for high-throughput microfluidic applications

To visualize fast-moving objects in microfluidic applications, the image acquisition time must be on the order of a microsecond or less. Commercial imaging systems capable of such short exposure times may be too expensive for many research laboratories. We have therefore developed a low-cost stroboscopic illumination for transmitted-light microscopy based on a high-power LED that can be coupled to a standard industrial camera and provides exposure times on the order of 500 ns. The system is designed to be easily mounted on a standard condenser of an inverted microscope. The illumination is controlled by a fast Arduino-compatible Teensy® 4.0 development board, and the illumination parameters can be set from a PC via a graphical user interface written in Python. The system has been successfully used for high-throughput cell phenotyping using deformability cytometry on a Nikon TE2000 microscope, as well as for droplet microfluidic on an old Olympus inverted microscope.

Biochemical Reaction Acceleration by Electrokinetic Mixing in a Microfluidic Chip

In the past two decades, a large number of micromixers have been studied and reported to solve the low mass transfer in microchannels. However, there is still a lack of research on how much biochemical reaction efficiency or detection sensitivity can be improved by microfluidic rapid mixing. In this study, using our previously developed ultrafast microelectrokinetic turbulent (μEKT) mixing method, taking glucose oxidation reaction as the research object, we investigated the effect of increasing microfluidic mass transfer efficiency on the efficiency and sensitivity of biochemical reactions. The results showed that fast mixing could improve the enzymatic reaction efficiency by improving the mass transfer efficiency. Further detection of glucose in glucose solutions and blood samples showed that the fast mixing could significantly improve the sensitivity of detection. These results indicate that mixing enhancement can be a significant step of microfluidics-based applications such as POCT, liquid biopsy, food safety, and so on.

Coupling Droplet Microfluidics with Ion Mobility Spectrometry for Monitoring Chemical Conversions at Nanoliter Scale

We introduce the coupling of droplet microfluidics and ion mobility spectrometry (IMS) to address the challenges of label-free and chemical-specific detection of compounds in individual droplets. In analogy to the established use of mass spectrometry, droplet-IMS coupling can be also achieved via electrospray ionization but with significantly less instrumental effort. Because IMS instruments do not require high-vacuum systems, they are very compact, cost-effective, and robust, making them an ideal candidate as a chemical-specific end-of-line detector for segmented flow experiments. Herein, we demonstrate the successful coupling of droplet microfluidics with a custom-built high-resolution drift tube IMS system for monitoring chemical reactions in nL-sized droplets in an oil phase. The analytes contained in each droplet were assigned according to their characteristic ion mobility with limit of detections down to 200 nM to 1 μM and droplet frequencies ranging from 0.1 to 0.5 Hz. Using a custom sheath flow electrospray interface, we have further achieved the chemical-specific monitoring of a biochemical transformation catalyzed by a few hundred yeast cells, at single droplet level.

Direct Measurement of Initial Rate of Enzyme Reaction by Electrokinetic Filtration Using a Hydrogel-plugged Capillary Device

A novel electrokinetic filtration device using a plugged hydrogel was developed to directly measure the initial rate of enzyme reactions. In the proposed method, the enzyme reaction proceeded only for a short time when the substrate was passed through a thin layer of enzyme trapped by the hydrogel without any lag times for mixing and detection. In experimental conditions, alkaline phosphatase (enzyme) was filtrated at a cathodic-side interface of the plugged hydrogel by molecular sieving effect, providing the thin enzyme zone whose thickness was approximately 100 μm. When 4-methylumberiferyl phosphate (substrate) was electrokinetically introduced into the device after trapping the enzyme, 4-methylumberiferone (product) was generated by the enzyme reaction for only 1.26 s as the substrate passed through the trapped enzyme zone. As a result, the initial rate of the enzyme reaction could be directly calculated to 31.0 μM/s by simply dividing the concentration of the product by the tunable reaction time. Compared to the initial rate obtained by mixing the enzyme and substrate solutions, the value of the maximum velocity of the enzyme reaction was 30-fold larger than that in the mixing method due to the preconcentration of the enzyme by trapping. The Michaelis-Menten constant in the proposed method was 2.7-fold larger than that in the mixing method, suggesting the variation of changes in the equilibrium of complex formation under the experimental conditions.

In Situ X-ray Absorption Spectroscopy and Droplet-Based Microfluidics: An Analysis of Calcium Carbonate Precipitation

Droplet-based microfluidic systems are ideally suited for the investigation of nucleation and crystallization processes. To best leverage the features of such platforms (including exquisite time resolution and high-throughput operation), sensitive and in situ detection schemes are needed to extract real-time chemical information about all species of interest. In this regard, the extension of conventional (UV, visible, and infrared) optical detection schemes to the X-ray region of the electromagnetic spectrum is of high current interest, as techniques such as X-ray absorption spectroscopy (XAS) provide for the element-specific investigation of the local chemical environment. Accordingly, herein, we report for the first time the integration of millisecond droplet-based microfluidics with XAS. Such a platform allows for the sensitive acquisition of X-ray absorption data from picoliter-volume droplets moving at high linear velocities. Significantly, the high-temporal resolution of the droplet-based microfluidic platform enables unprecedented access to the early stages of the reaction. Using such an approach, we demonstrate in situ monitoring of calcium carbonate precipitation by extracting XAS spectra at the early time points of the reaction with a dead time as low as 10 ms. We obtain insights into the kinetics of the formation of amorphous calcium carbonate (ACC) as a first species during the crystallization process by monitoring the proportion of calcium ions converted into ACC. Within the confined and homogeneous environment of picoliter-volume droplets, the ACC content reaches 60% over the first 130 ms. More generally, the presented method offers new opportunities for the real-time monitoring of fast chemical and biological processes.

Broad-Band Spectrum, High-Sensitivity Absorbance Spectroscopy in Picoliter Volumes

Picoliter-volume droplets within segmented flows can be probed in a rapid and efficient manner using optical detection methods. To date, however, most detection schemes for droplet content analysis have relied on the use of time-integrated fluorescence measurements. Despite its undoubted utility, the implementation of absorbance-based detectors is particularly challenging due to the reduced optical path lengths that are characteristic of microfluidic systems and deleterious scattering at droplet-oil interfaces. Unsurprisingly, efforts to develop sensitive absorbance-based detection schemes for the interrogation of rapidly moving droplets have primarily focused on ensuring adequate analytical sensitivity and, to date, have been exclusively limited to single-wavelength measurements. To address this limitation, and expand the information content associated with absorbance measurements on-chip, we herein describe a detection scheme for the extraction of broad-band absorbance spectra from pL-volume droplets with high sensitivity. The combination of a confocal optical system (that confines incident light to a reduced detection volume) and a postprocessing algorithm (that effectively removes the contribution of the carrier oil from the extracted spectra) engenders significant improvements in signal-to-noise ratios. Our system is initially calibrated by acquiring absorbance spectra from aqueous solutions of fluorescein isothiocyanate. These measurements confirm both excellent linearity over the studied range (from 0 to 100 μM) and a concentration limit of detection of 800 nM. The methodology is then used to monitor the salt-induced aggregation of gold nanoparticles with millisecond time resolution. This approach for small-volume absorbance spectroscopy allows for both high-throughput and high-information content measurements in subnanoliter volumes and will be highly desirable in a wide variety of bioanalytical applications where sensitivity and throughput are priorities.

Optical Detection Methods for High-Throughput Fluorescent Droplet Microflow Cytometry

High-throughput microflow cytometry has become a focal point of research in recent years. In particular, droplet microflow cytometry (DMFC) enables the analysis of cells reacting to different stimuli in chemical isolation due to each droplet acting as an isolated microreactor. Furthermore, at high flow rates, the droplets allow massive parallelization, further increasing the throughput of droplets. However, this novel methodology poses unique challenges related to commonly used fluorometry and fluorescent microscopy techniques. We review the optical sensor technology and light sources applicable to DMFC, as well as analyze the challenges and advantages of each option, primarily focusing on electronics. An analysis of low-cost and/or sufficiently compact systems that can be incorporated into portable devices is also presented.

Droplet-based optofluidic systems for measuring enzyme kinetics

The study of enzyme kinetics is of high significance in understanding metabolic networks in living cells and using enzymes in industrial applications. To gain insight into the catalytic mechanisms of enzymes, it is necessary to screen an enormous number of reaction conditions, a process that is typically laborious, time-consuming, and costly when using conventional measurement techniques. In recent times, droplet-based microfluidic systems have proved themselves to be of great utility in large-scale biological experimentation, since they consume a minimal sample, operate at high analytical throughput, are characterized by efficient mass and heat transfer, and offer high levels of integration and automation. The primary goal of this review is the introduction of novel microfluidic tools and detection methods for use in high-throughput and sensitive analysis of enzyme kinetics. The first part of this review focuses on introducing basic concepts of enzyme kinetics and describing most common microfluidic approaches, with a particular focus on segmented flow. Herein, the key advantages include accurate control over the flow behavior, efficient mass and heat transfer, multiplexing, and high-level integration with detection modalities. The second part describes the current state-of-the-art platforms for high-throughput and sensitive analysis of enzyme kinetics. In addition to our categorization of recent advances in measuring enzyme kinetics, we have endeavored to critically assess the limitations of each of these detection approaches and propose strategies to improve measurements in droplet-based microfluidics. Graphical abstract.

Droplet-Based Microfluidics Methods for Detecting Enzyme Inhibitors

Sub-nanoliter droplets produced in microfluidic devices have gained an enormous importance for performing all kinds of biochemical assays. One of the main reasons is that the amounts of reagents employed can be reduced in approximately five orders of magnitude compared to conventional microplate assays. In this chapter, we describe how to carry out the design, fabrication, and operation of a microfluidic device that allows performing enzyme kinetics and enzyme inhibition assays in droplets. This procedure can be used effectively to screen a small size library of compounds. Then, we describe how to use this droplet microfluidic setup to screen for potential inhibitor compounds eluted from a coupled high-performance liquid chromatography (HPLC) system that separates crude natural extracts.

High-throughput droplet-based microfluidics for directed evolution of enzymes

Natural enzymes have evolved over millions of years to allow for their effective operation within specific environments. However, it is significant to note that despite their wide structural and chemical diversity, relatively few natural enzymes have been successfully applied to industrial processes. To address this limitation, directed evolution (DE) (a method that mimics the process of natural selection to evolve proteins toward a user‐defined goal) coupled with droplet‐based microfluidics allows the detailed analysis of millions of enzyme variants on ultra‐short timescales, and thus the design of novel enzymes with bespoke properties. In this review, we aim at presenting the development of DE over the last years and highlighting the most important advancements in droplet‐based microfluidics, made in this context towards the high‐throughput demands of enzyme optimization. Specifically, an overview of the range of microfluidic unit operations available for the construction of DE platforms is provided, focusing on their suitability and benefits for cell‐based assays, as in the case of directed evolution experimentations.

A Facile Strategy for Visualizing and Modulating Droplet-Based Microfluidics

In droplet-based microfluidics, visualizing and modulating of droplets is often prerequisite. In this paper, we report a facile strategy for visualizing and modulating high-throughput droplets in microfluidics. In the strategy, by modulating the sampling frequency of a flash light with the droplet frequency, we are able to map a real high frequency signal to a low frequency signal, which facilitates visualizing and feedback controlling. Meanwhile, because of not needing synchronization signals, the strategy can be directly implemented on any droplet-based microfluidic chips. The only cost of the strategy is an additional signal generator. Moreover, the strategy can catch droplets with frequency up to several kilohertz, which covers the range of most high-throughput droplet-based microfluidics. In this paper, the principle, setup and procedure were introduced. Finally, as a demonstration, the strategy was also implemented in a miniaturized picoinjector in order to monitor and control the injection dosage to droplets. We expect that this facile strategy supplies a low-cost yet effective imaging system that can be easily implemented in miniaturized microfluidic systems or general laboratories.

Ultra-High-Throughput Multi-Parametric Imaging Flow Cytometry

I will present a microfluidic imaging flow cytometer incorporating stroboscopic illumination, for blur-free cellular analysis at throughputs exceeding 100,000 cells per second. By combining passive (inertial or viscoelastic) focusing of cells in parallel microchannels with stroboscopic illumination, such chip-based cytometers are able to extract multi-colour fluorescence and bright-field images of single cells moving at high linear velocities. This in turn allows accurate sizing of individual cells, intracellular localization and analysis of heterogeneous cell suspensions. The method is showcased through the rapid enumeration of apoptotic cells, high-throughput discrimination cell cycle phases and localization of p-bodies.

Continuous measurement of enzymatic kinetics in droplet flow for point-of-care monitoring

Droplet microfluidics is ideally suited to continuous biochemical analysis, requiring low sample volumes and offering high temporal resolution. Many biochemical assays are based on enzymatic reactions, the kinetics of which can be obtained by probing droplets at multiple points over time. Here we present a miniaturised multi-detector flow cell to analyse enzyme kinetics in droplets, with an example application of continuous glucose measurement. Reaction rates and Michaelis-Menten kinetics can be quantified for each individual droplet and unknown glucose concentrations can be accurately determined (errors <5%). Droplets can be probed continuously giving short sample-to-result time (∼30 s) measurement. In contrast to previous reports of multipoint droplet measurement (all of which used bulky microscope-based setups) the flow cell presented here has a small footprint and uses low-powered, low-cost components, making it ideally suited for use in field-deployable devices.

Reinforcement Learning for Dynamic Microfluidic Control

Recent years have witnessed an explosion in the application of microfluidic techniques to a wide variety of problems in the chemical and biological sciences. Despite the many considerable advantages that microfluidic systems bring to experimental science, microfluidic platforms often exhibit inconsistent system performance when operated over extended timescales. Such variations in performance are because of a multiplicity of factors, including microchannel fouling, substrate deformation, temperature and pressure fluctuations, and inherent manufacturing irregularities. The introduction and integration of advanced control algorithms in microfluidic platforms can help mitigate such inconsistencies, paving the way for robust and repeatable long-term experiments. Herein, two state-of-the-art reinforcement learning algorithms, based on Deep Q-Networks and model-free episodic controllers, are applied to two experimental "challenges," involving both continuous-flow and segmented-flow microfluidic systems. The algorithms are able to attain superhuman performance in controlling and processing each experiment, highlighting the utility of novel control algorithms for automated high-throughput microfluidic experimentation.

Biocatalyst Screening with a Twist: Application of Oxygen Sensors Integrated in Microchannels for Screening Whole Cell Biocatalyst Variants

Selective oxidative functionalization of molecules is a highly relevant and often demanding reaction in organic chemistry. The use of biocatalysts allows the stereo- and regioselective introduction of oxygen molecules in organic compounds at milder conditions and avoids the use of complex group-protection schemes and toxic compounds usually applied in conventional organic chemistry. The identification of enzymes with the adequate properties for the target reaction and/or substrate requires better and faster screening strategies. In this manuscript, a microchannel with integrated oxygen sensors was applied to the screening of wild-type and site-directed mutated variants of naphthalene dioxygenase (NDO) from Pseudomonas sp. NICB 9816-4. The oxygen sensors were used to measure the oxygen consumption rate of several variants during the conversion of styrene to 1-phenylethanediol. The oxygen consumption rate allowed the distinguishing of endogenous respiration of the cell host from the oxygen consumed in the reaction. Furthermore, it was possible to identify the higher activity and different reaction rate of two variants, relative to the wild-type NDO. The meander microchannel with integrated oxygen sensors can therefore be used as a simple and fast screening platform for the selection of dioxygenase mutants, in terms of their ability to convert styrene, and potentially in terms of substrate specificity.

Impedance feedback control of microfluidic valves for reliable post processing combinatorial droplet injection

Droplet microfluidics has found use in many biological assay applications as a means of high-throughput sample processing. One of the challenges of the technology, however, is the ability to control and merge droplets on-demand as they flow through the microdevices. It is in the interest of developing lab-on-chip devices to be able to combinatorically program additive mixing steps for more complex multistep and multiplex assays. Existing technologies to merge droplets are either passive in nature or require highly predictable droplet movement for feedforward control, making them vulnerable to errors during high throughput operation. In this paper, we describe and demonstrate a microfluidic valve-based device for the purpose of combinatorial droplet injection at any stage in a multistep assay. Microfluidic valves are used to robustly control fluid flow, droplet generation, and droplet mixing in the device on-demand, while on-chip impedance measurements taken in real time are used as feedback to accurately time the droplet injections. The presented system is contrasted to attempts without feedback, and is shown to be 100% reliable over long durations. Additionally, content detection and discretionary injections are explored and successfully executed.

Chemical and Biological Dynamics Using Droplet-Based Microfluidics

Recent years have witnessed an increased use of droplet-based microfluidic techniques in a wide variety of chemical and biological assays. Nevertheless, obtaining dynamic data from these platforms has remained challenging, as this often requires reading the same droplets (possibly thousands of them) multiple times over a wide range of intervals (from milliseconds to hours). In this review, we introduce the elemental techniques for the formation and manipulation of microfluidic droplets, together with the most recent developments in these areas. We then discuss a wide range of analytical methods that have been successfully adapted for analyte detection in droplets. Finally, we highlight a diversity of studies where droplet-based microfluidic strategies have enabled the characterization of dynamic systems that would otherwise have remained unexplorable.

Ultrahigh-Throughput Improvement and Discovery of Enzymes Using Droplet-Based Microfluidic Screening

Enzymes are extremely valuable tools for industrial, environmental, and biotechnological applications and there is a constant need for improving existing biological catalysts and for discovering new ones. Screening microbe or gene libraries is an efficient way of identifying new enzymes. In this view, droplet-based microfluidics appears to be one of the most powerful approaches as it allows inexpensive screenings in well-controlled conditions and an ultrahigh-throughput regime. This review aims to introduce the main microfluidic devices and concepts to be considered for such screening before presenting and discussing the latest successful applications of the technology for enzyme discovery.

K-Channel: A Multifunctional Architecture for Dynamically Reconfigurable Sample Processing in Droplet Microfluidics

By rapidly creating libraries of thousands of unique, miniaturized reactors, droplet microfluidics provides a powerful method for automating high-throughput chemical analysis. In order to engineer in-droplet assays, microfluidic devices must add reagents into droplets, remove fluid from droplets, and perform other necessary operations, each typically provided by a unique, specialized geometry. Unfortunately, modifying device performance or changing operations usually requires re-engineering the device among these specialized geometries, a time-consuming and costly process when optimizing in-droplet assays. To address this challenge in implementing droplet chemistry, we have developed the "K-channel," which couples a cross-channel flow to the segmented droplet flow to enable a range of operations on passing droplets. K-channels perform reagent injection (0-100% of droplet volume), fluid extraction (0-50% of droplet volume), and droplet splitting (1:1-1:5 daughter droplet ratio). Instead of modifying device dimensions or channel configuration, adjusting external conditions, such as applied pressure and electric field, selects the K-channel process and tunes its magnitude. Finally, interfacing a device-embedded magnet allows selective capture of 96% of droplet-encapsulated superparamagnetic beads during 1:1 droplet splitting events at ∼400 Hz. Addition of a second K-channel for injection (after the droplet splitting K-channel) enables integrated washing of magnetic beads within rapidly moving droplets. Ultimately, the K-channel provides an exciting opportunity to perform many useful droplet operations across a range of magnitudes without requiring architectural modifications. Therefore, we envision the K-channel as a versatile, easy to use microfluidic component enabling diverse, in-droplet (bio)chemical manipulations.

Suzuki-Miyaura cross-coupling optimization enabled by automated feedback

An automated, droplet-flow microfluidic system explores and optimizes Pd-catalyzed Suzuki-Miyaura cross-coupling reactions. A smart optimal DoE-based algorithm is implemented to increase the turnover number and yield of the catalytic system considering both discrete variables-palladacycle and ligand-and continuous variables-temperature, time, and loading-simultaneously. The use of feedback allows for experiments to be run with catalysts and under conditions more likely to produce an optimum; consequently complex reaction optimizations are completed within 96 experiments. Response surfaces predicting reaction performance near the optima are generated and validated. From the screening results, shared attributes of successful precatalysts are identified, leading to improved understanding of the influence of ligand selection upon transmetalation and oxidative addition in the reaction mechanism. Dialkylbiarylphosphine, trialkylphosphine, and bidentate ligands are assessed.

Dodecylresorufin (C12R) Outperforms Resorufin in Microdroplet Bacterial Assays

This paper proves that dodecylresorufin (C12R) outperforms resorufin (the conventional form of this dye) in droplet microfluidic bacterial assays. Resorufin is a marker dye that is widely used in different fields of microbiology and has increasingly been applied in droplet microfluidic assays and experiments. The main concern associated with resorufin in droplet-based systems is dye leakage into the oil phase and neighboring droplets. The leakage decreases the performance of assays because it causes averaging of the signal between the positive (bacteria-containing) and negative (empty) droplets. Here we show that C12R is a promising alternative to conventional resorufin because it maintains higher sensitivity, specificity, and signal-to-noise ratio over time. These characteristics make C12R a suitable reagent for droplet digital assays and for monitoring of microbial growth in droplets.

Kinetics of nanocrystal synthesis in a microfluidic reactor: theory and experiment

A two-stage microreactor enables the quantitative evaluation of a kinetic model of nanocrystal nucleation and growth.