Droplet-based optofluidic systems for measuring enzyme kinetics

Integrated Droplet-Based Digital Loop-Mediated Isothermal Amplification Microfluidic Chip with Droplet Generation, Incubation, and Continuous Fluorescence Detection

This study integrated sample partition, incubation, and continuous fluorescence detection on a single microfluidic chip for droplet-based digital Loop-Mediated Isothermal Amplification (LAMP) of nucleic acids. This integration eliminated the need to transfer reactions between different platforms, avoiding sample contamination and loss. Prior to the reaction, filling the channels with an oil phase and adding a glass cover slip on top of the chip overcame the problem of bubble generation in the channels during the LAMP reaction due to heating. Additionally, using two fluorescence intensity thresholds enabled simultaneous detection and counting of positive and negative droplets within a single fluorescence detection channel. The chip can partition approximately 6000 droplets from a 5 µL sample within 10 min, with a droplet diameter of around 110 µm and a coefficient of variation (CV) value of 0.82%. Staphylococcus aureus was quantified via the proposed platform. The results demonstrated a highly accurate correlation coefficient (R = 0.9998), and the detection limit reached a concentration of 1.7 × 102 copies/µL. The entire process of the droplet digital LAMP reaction, from droplet generation to incubation to quantitative results, took a maximum of 70 min.

Droplet-Based Microfluidics Reveals Insights into Cross-Coupling Mechanisms over Single-Atom Heterogeneous Catalysts

Single-atom heterogeneous catalysts (SACs) hold promise as sustainable alternatives to metal complexes in organic transformations. However, their working structure and dynamics remain poorly understood, hindering advances in their design. Exploiting the unique features of droplet-based microfluidics, we present the first in-situ assessment of a palladium SAC based on exfoliated carbon nitride in Suzuki-Miyaura cross-coupling using X-ray absorption spectroscopy. Our results confirm a surface-catalyzed mechanism, revealing the distinct electronic structure of active Pd centers compared to homogeneous systems, and providing insights into the stabilizing role of ligands and bases. This study establishes a valuable framework for advancing mechanistic understanding of organic syntheses catalyzed by SACs.

Optofluidic Tweezers: Efficient and Versatile Micro/Nano-Manipulation Tools

Optical tweezers (OTs) can transfer light momentum to particles, achieving the precise manipulation of particles through optical forces. Due to the properties of non-contact and precise control, OTs have provided a gateway for exploring the mysteries behind nonlinear optics, soft-condensed-matter physics, molecular biology, and analytical chemistry. In recent years, OTs have been combined with microfluidic chips to overcome their limitations in, for instance, speed and efficiency, creating a technology known as "optofluidic tweezers." This paper describes static OTs briefly first. Next, we overview recent developments in optofluidic tweezers, summarizing advancements in capture, manipulation, sorting, and measurement based on different technologies. The focus is on various kinds of optofluidic tweezers, such as holographic optical tweezers, photonic-crystal optical tweezers, and waveguide optical tweezers. Moreover, there is a continuing trend of combining optofluidic tweezers with other techniques to achieve greater functionality, such as antigen-antibody interactions and Raman tweezers. We conclude by summarizing the main challenges and future directions in this research field.

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.

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.

Droplet Microfluidic Device for Chemoenzymatic Sensing

The rapid detection of pollutants in water can be performed with enzymatic probes, the catalytic light-emitting activity of which decreases in the presence of many types of pollutants. Herein, we present a microfluidic system for continuous chemoenzymatic biosensing that generates emulsion droplets containing two enzymes of the bacterial bioluminescent system (luciferase and NAD(P)H:FMN-oxidoreductase) with substrates required for the reaction. The developed chip generates "water-in-oil" emulsion droplets with a volume of 0.1 μL and a frequency of up to 12 drops per minute as well as provides the efficient mixing of reagents in droplets and their distancing. The bioluminescent signal from each individual droplet was measured by a photomultiplier tube with a signal-to-noise ratio of up to 3000/1. The intensity of the luminescence depended on the concentration of the copper sulfate with the limit of its detection of 5 μM. It was shown that bioluminescent enzymatic reactions could be carried out in droplet reactors in dispersed streams. The parameters and limitations required for the bioluminescent reaction to proceed were also studied. Hereby, chemoenzymatic sensing capabilities powered by a droplet microfluidics manipulation technique may serve as the basis for early-warning online water pollution systems.

Tools for computational design and high-throughput screening of therapeutic enzymes

Therapeutic enzymes are valuable biopharmaceuticals in various biomedical applications. They have been successfully applied for fibrinolysis, cancer treatment, enzyme replacement therapies, and the treatment of rare diseases. Still, there is a permanent demand to find new or better therapeutic enzymes, which would be sufficiently soluble, stable, and active to meet specific medical needs. Here, we highlight the benefits of coupling computational approaches with high-throughput experimental technologies, which significantly accelerate the identification and engineering of catalytic therapeutic agents. New enzymes can be identified in genomic and metagenomic databases, which grow thanks to next-generation sequencing technologies exponentially. Computational design and machine learning methods are being developed to improve catalytically potent enzymes and predict their properties to guide the selection of target enzymes. High-throughput experimental pipelines, increasingly relying on microfluidics, ensure functional screening and biochemical characterization of target enzymes to reach efficient therapeutic enzymes.

Advantages of optical fibers for facile and enhanced detection in droplet microfluidics

Droplet microfluidics offers a unique opportunity for ultrahigh-throughput experimentation with minimal sample consumption and thus has obtained increasing attention, particularly for biological applications. Detection and measurements of analytes or biomarkers in tiny droplets are essential for proper analysis of biological and chemical assays like single-cell studies, cytometry, nucleic acid detection, protein quantification, environmental monitoring, drug discovery, and point-of-care diagnostics. Current detection setups widely use microscopes as a central device and other free-space optical components. However, microscopic setups are bulky, complicated, not flexible, and expensive. Furthermore, they require precise optical alignments, specialized optical and technical knowledge, and cumbersome maintenance. The establishment of efficient, simple, and cheap detection methods is one of the bottlenecks for adopting microfluidic strategies for diverse bioanalytical applications and widespread laboratory use. Together with great advances in optofluidic components, the integration of optical fibers as a light guiding medium into microfluidic chips has recently revolutionized analytical possibilities. Optical fibers embedded in a microfluidic platform provide a simpler, more flexible, lower-cost, and sensitive setup for the detection of several parameters from biological and chemical samples and enable widespread, hands-on application much beyond thriving point-of-care developments. In this review, we examine recent developments in droplet microfluidic systems using optical fiber as a light guiding medium, primarily focusing on different optical detection methods such as fluorescence, absorbance, light scattering, and Raman scattering and the potential applications in biochemistry and biotechnology that are and will be arising from this.

Digital Microfluidics Chips for the Execution and Real-Time Monitoring of Multiple Ribozymatic Cleavage Reactions

In this paper, we describe the design and performance of two digital microfluidics (DMF) chips capable of executing multiple ribozymatic reactions, with proper controls, in response to short single-stranded DNA inducers. Since the fluorescence output of a reaction is measurable directly from the chip, without the need for gel electrophoresis, a complete experiment involving up to eight reactions (per chip) can be carried out reliably, relatively quickly, and efficiently. The ribozymes can also be used as biosensors of the concentration of oligonucleotide inputs, with high sensitivity, low limits of quantification and of detection, and excellent signal-to-noise ratio. The presented chips are readily usable devices that can be used to automate, speed up, and reduce the costs of ribozymatic reaction experiments.

Effect of Surfactant Dynamics on Flow Patterns Inside Drops Moving in Rectangular Microfluidic Channels

Drops contained in an immiscible liquid phase are attractive as microreactors, enabling sound statistical analysis of reactions performed on ensembles of samples in a microfluidic device. Many applications have specific requirements for the values of local shear stress inside the drops and, thus, knowledge of the flow field is required. This is complicated in commonly used rectangular channels by the flow of the continuous phase in the corners, which also affects the flow inside the drops. In addition, a number of chemical species are present inside the drops, of which some may be surface-active. This work presents a novel experimental study of the flow fields of drops moving in a rectangular microfluidic channel when a surfactant is added to the dispersed phase. Four surfactants with different surface activities are used. Flow fields are measured using Ghost Particle Velocimetry, carried out at different channel depths to account for the 3-D flow structure. It is shown that the effect of the surfactant depends on the characteristic adsorption time. For fast-equilibrating surfactants with a characteristic time scale of adsorption that is much smaller than the characteristic time of surface deformation, this effect is related only to the decrease in interfacial tension, and can be accounted for by the change in capillary number. For slowly equilibrating surfactants, Marangoni stresses accelerate the corner flow, which changes the flow patterns inside the drop considerably.

Droplet Microfluidics for Food and Nutrition Applications

Droplet microfluidics revolutionizes the way experiments and analyses are conducted in many fields of science, based on decades of basic research. Applied sciences are also impacted, opening new perspectives on how we look at complex matter. In particular, food and nutritional sciences still have many research questions unsolved, and conventional laboratory methods are not always suitable to answer them. In this review, we present how microfluidics have been used in these fields to produce and investigate various droplet-based systems, namely simple and double emulsions, microgels, microparticles, and microcapsules with food-grade compositions. We show that droplet microfluidic devices enable unprecedented control over their production and properties, and can be integrated in lab-on-chip platforms for in situ and time-resolved analyses. This approach is illustrated for on-chip measurements of droplet interfacial properties, droplet-droplet coalescence, phase behavior of biopolymer mixtures, and reaction kinetics related to food digestion and nutrient absorption. As a perspective, we present promising developments in the adjacent fields of biochemistry and microbiology, as well as advanced microfluidics-analytical instrument coupling, all of which could be applied to solve research questions at the interface of food and nutritional sciences.

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.

One-step enzyme kinetics measurement in 3D printed microfluidics devices based on a high-performance single vibrating sharp-tip mixer

Measuring enzyme kinetics is of great importance to understand many biological processes and improve biosensing and industrial applications. Conventional methods of measuring enzyme kinetics require to prepare a series of solutions with different substrate concentrations and measure the signal response over time with these solutions, leading to tedious sample preparation steps, high reagents/sample consumption, and difficulties in studying fast enzyme kinetics. Here we report a one-step assay to measure enzyme kinetics using a 3D-printed microfluidic device, which eliminates the steps of preparing and handling multiple solutions thereby simplifying the whole workflow significantly. The assay is enabled by a highly efficient vibrating sharp-tip mixing method that can mix multiple streams of fluids with minimal mixing length (∼300 μm) and time (as low as 3 ms), and a wide range of working flow rates from 1.5 μL/min to 750 μL/min. Owing to the high performance of the mixer, a series of experiments with different substrate concentrations are performed by simply adjusting the flow rates of reagents loaded from three inlets in one experiment run. The Michaelis-Menten kinetics of the horseradish peroxidase (HRP)-catalyzed reaction between H₂O₂ and amplex red is measured in this system. The calculated Michaelis constant is consistent with the values from literature and conventional analysis methods. Due to the simplicity in fabrication and operation, rapid analysis, low power consumption (1.4-45.0 mW), and high temporal resolution, this method will significantly facilitate enzyme kinetics measurement, and offers great potential for optimizing enzyme based biosensing experiments and probing many biochemical processes.

Adaptation of a Microfluidic qPCR System for Enzyme Kinetic Studies

Microfluidic platforms offer a drastic increase in throughput while minimizing sample usage and hands-on time, which make them important tools for large-scale biological studies. A range of such systems have been developed for enzyme activity studies, although their complexity largely hinders their application to the wider scientific community. Here, we present adaptation of an easy-to-use commercial microfluidic qPCR system for performing enzyme kinetic studies. We demonstrate the functionality of the Fluidigm Biomark HD system (the Fluidigm system) by determining the kinetic properties of three oxidases in a resorufin-based fluorescence assay. The results obtained in the microfluidic system proved reproducible and comparable to the ones obtained in a standard microplate-based assay. With a wide range of easy-to-use, off-the-shelf components, the microfluidic system presents itself as a simple and customizable platform for high-throughput enzyme activity studies.

Photon-upconversion barcode for monitoring an enzymatic reaction with a fluorescence reporter in droplet microfluidics

We report luminescent photon-upconversion barcodes for indexing the chemical content of droplets. The barcode is compatible with the simultaneous detection of fluorescence. The encoding and decoding of the initial concentration of enzyme β-galactosidase and substrate 4-methylumbelliferyl β-d-galactopyranoside are described. The fluorescent product 4-methylumbelliferone is detected simultaneously with the barcode.

Mixing characterization of binary-coalesced droplets in microchannels using deep neural network

Real-time object identification and classification are essential in many microfluidic applications especially in the droplet microfluidics. This paper discusses the application of convolutional neural networks to detect the merged microdroplet in the flow field and classify them in an on-the-go manner based on the extent of mixing. The droplets are generated in PMMA microfluidic devices employing flow-focusing and cross-flow configurations. The visualization of binary coalescence of droplets is performed by a CCD camera attached to a microscope, and the sequence of images is recorded. Different real-time object localization and classification networks such as You Only Look Once and Singleshot Multibox Detector are deployed for droplet detection and characterization. A custom dataset to train these deep neural networks to detect and classify is created from the captured images and labeled manually. The merged droplets are segregated based on the degree of mixing into three categories: low mixing, intermediate mixing, and high mixing. The trained model is tested against images taken at different ambient conditions, droplet shapes, droplet sizes, and binary-fluid combinations, which indeed exhibited high accuracy and precision in predictions. In addition, it is demonstrated that these schemes are efficient in localization of coalesced binary droplets from the recorded video or image and classify them based on grade of mixing irrespective of experimental conditions in real time.

Step emulsification in microfluidic droplet generation: mechanisms and structures

Step emulsification for micro- and nano-droplet generation is reviewed in brief, including the emulsion mechanisms and microfluidic devices.