Uncovering the heterogeneity of cell populations is a long-standing goal in
fields ranging from antimicrobial resistance to cancer research. Emerging
technology platforms such as droplet microfluidics hold the promise to decipher
cellular heterogeneity at ultra-high-throughput. However, there is a lack of
methods able to rapidly identify and isolate single cells or 3D cell cultures.
Here we demonstrate that deep neural networks can accurately classify single
droplet images in real-time based on the presence and number of micro-objects
including single mammalian cells and multicellular spheroids. This approach
also enables the identification of specific objects within mixtures of objects
of different types and sizes. The training sets for the neural networks
consisted of several hundred images manually picked and augmented to up to
thousands of images per training class. Training required less than 10 minutes
using a single GPU, and yielded accuracies of over 90% for single mammalian
cell identification. Crucially, the same model could be used to classify
different types of objects such as polystyrene spheres, polyacrylamide beads
and MCF-7 cells. We applied the developed method to the selection of 3D cell
cultures generated with Hek293FT cells encapsulated in agarose gel beads,
highlighting the potential of the technology for the selection of objects with
high diversity of visual appearance. The real-time sorting of single droplets
was in-line with droplet generation and occurred at rates up to 40 per second
independently of image size up to 480 x 480 pixels. The presented microfluidic
device also enabled storage of sorted droplets to allow for downstream
analyses.

Functional annotation of novel proteins lags behind the number of sequences discovered by the next-generation sequencing. The throughput of conventional testing methods is far too low compared to sequencing; thus, experimental alternatives are needed. Microfluidics offer high throughput and reduced sample consumption as a tool to keep up with a sequence-based exploration of protein diversity. The most promising droplet-based systems have a significant limitation: leakage of hydrophobic compounds from water compartments to the carrier prevents their use with hydrophilic reagents. Here, we present a novel approach of substrate delivery into microfluidic droplets and apply it to high-throughput functional characterization of enzymes that convert hydrophobic substrates. Substrate delivery is based on the partitioning of hydrophobic chemicals between the oil and water phases. We applied a controlled distribution of 27 hydrophobic haloalkanes from oil to reaction water droplets to perform substrate specificity screening of eight model enzymes from the haloalkane dehalogenase family. This droplet-on-demand microfluidic system reduces the reaction volume 65 000-times and increases the analysis speed almost 100-fold compared to the classical test tube assay. Additionally, the microfluidic setup enables a convenient analysis of dependences of activity on the temperature in a range of 5 to 90 °C for a set of mesophilic and hyperstable enzyme variants. A high correlation between the microfluidic and test tube data supports the approach robustness. The precision is coupled to a considerable throughput of >20 000 reactions per day and will be especially useful for extending the scope of microfluidic applications for high-throughput analysis of reactions including compounds with limited water solubility.

Developmental cell biology requires technologies in which the fate of single cells is followed over extended time periods, to monitor and understand the processes of self-renewal, differentiation, and reprogramming. A workflow is presented, in which single cells are encapsulated into droplets (Ø: 80 µm, volume: ≈270 pL) and the droplet compartment is later converted to a hydrogel bead. After on-chip de-emulsification by electrocoalescence, these 3D scaffolds are subsequently arrayed on a chip for long-term perfusion culture to facilitate continuous cell imaging over 68 h. Here, the response of murine embryonic stem cells to different growth media, 2i and N2B27, is studied, showing that the exit from pluripotency can be monitored by fluorescence time-lapse microscopy, by immunostaining and by reverse-transcription and quantitative PCR (RT-qPCR). The defined 3D environment emulates the natural context of cell growth (e.g. in tissue) and enables the study of cell development in various matrices. The large scale of cell cultivation (in 2000 beads in parallel) may reveal infrequent events that remain undetected in lower throughput or ensemble studies. This platform will help to gain qualitative and quantitative mechanistic insight into the role of external factors on cell behavior.

The success of ultrahigh-throughput screening experiments in directed evolution or functional metagenomics strongly depends on the availability of efficient technologies for the quantitative testing of a large number of variants. With advanced robotics, libraries of up to 105 clones can be screened per day as colonies on agar plates or cell lysates in microwell plates, albeit at high cost of capital, manpower and consumables. These cost considerations and the general need for high-throughput make miniaturization of assay volumes attractive. To provide a general solution to maintain genotype-phenotype linkage, biochemical assays have been compartmentalized into water-in-oil droplets. This chapter presents a microfluidic workflow that translates a frequently used screening procedure consisting of cytoplasmic/periplasmic protein expression and cell lysis to the single cell level in water-in-oil droplet compartments. These droplets are sorted based on reaction progress by fluorescence measurements at the picoliter scale.

Screening of enzyme mutants in monodisperse picoliter compartments, generated at kilohertz speed in microfluidic devices, is coming of age. After a decade of proof-of-principle experiments, workflows have emerged that combine existing microfluidic modules to assay reaction progress quantitatively and yield improved enzymes. Recent examples of the screening of libraries of randomised proteins and from metagenomic sources suggest that this approach is not only faster and cheaper, but solves problems beyond the feasibility scope of current methodologies. The establishment of new assays in this format - so far covering hydrolases, aldolases, polymerases and dehydrogenases - will enable the exploration of sequence space for new catalysts of natural and non-natural chemical transformations.

Ultrahigh-throughput screening, in which members of enzyme libraries compartmentalized in water-in-oil emulsion droplets are assayed, has emerged as a powerful format for directed evolution and functional metagenomics but is currently limited to fluorescence readouts. Here we describe a highly efficient microfluidic absorbance-activated droplet sorter (AADS) that extends the range of assays amenable to this approach. Using this module, microdroplets can be sorted based on absorbance readout at rates of up to 300 droplets per second (i.e. >1 million droplets per hour). To validate this device, we implemented a miniaturized coupled assay for NAD+-dependent amino acid dehydrogenases. The detection limit (10 μM in a coupled assay producing a formazan dye) enables accurate kinetic readouts sensitive enough to detect a minimum of 1,300 turnovers per enzyme molecule, expressed in a single cell, and released by lysis within a droplet. Sorting experiments showed that the AADS successfully enriched active variants up to 2,800-fold from an overwhelming majority of inactive ones at ∼100 Hz. To demonstrate the utility of this module for protein engineering, two rounds of directed evolution were performed to improve the activity of phenylalanine dehydrogenase toward its native substrate. Fourteen hits showed increased activity (improved >4.5-fold in lysate; kcat increased >2.7-fold), soluble protein expression levels (up 60%), and thermostability (Tm, 12 °C higher). The AADS module makes the most widely used optical detection format amenable to screens of unprecedented size, paving the way for the implementation of chromogenic assays in droplet microfluidics workflows.

FRET is widely used for the study of protein-protein interactions in biological samples. However, it is difficult to quantify both the FRET efficiency (E) and the affinity (Kd) of the molecular interaction from intermolecular FRET signals in samples of unknown stoichiometry. Here, we present a method for the simultaneous quantification of the complete set of interaction parameters, including fractions of bound donors and acceptors, local protein concentrations, and dissociation constants, in each image pixel. The method makes use of fluorescence lifetime information from both donor and acceptor molecules and takes advantage of the linear properties of the phasor plot approach. We demonstrate the capability of our method in vitro in a microfluidic device and also in cells, via the determination of the binding affinity between tagged versions of glutathione and glutathione S-transferase, and via the determination of competitor concentration. The potential of the method is explored with simulations.

Analysis of concentration dependencies is key to the quantitative understanding of biological and chemical systems. In experimental tests involving concentration gradients such as inhibitor library screening, the number of data points and the ratio between the stock volume and the volume required in each test determine the quality and efficiency of the information gained. Titerplate assays are currently the most widely used format, even though they require microlitre volumes. Compartmentalization of reactions in pico- to nanoliter water-in-oil droplets in microfluidic devices provides a solution for massive volume reduction. This work addresses the challenge of producing microfluidic-based concentration gradients in a way that every droplet represents one unique reagent combination. We present a simple microcapillary technique able to generate such series of monodisperse water-in-oil droplets (with a frequency of up to 10 Hz) from a sample presented in an open well (e.g. a titerplate). Time-dependent variation of the well content results in microdroplets that represent time capsules of the composition of the source well. By preserving the spatial encoding of the droplets in tubing, each reactor is assigned an accurate concentration value. We used this approach to record kinetic time courses of the haloalkane dehalogenase DbjA and analyzed 150 combinations of enzyme/substrate/inhibitor in less than 5 min, resulting in conclusive Michaelis-Menten and inhibition curves. Avoiding chips and merely requiring two pumps, a magnetic plate with a stirrer, tubing, and a pipet tip, this easy-to-use device rivals the output of much more expensive liquid handling systems using a fraction (∼100-fold less) of the reagents consumed in microwell format.

Unculturable bacterial communities provide a rich source of biocatalysts, but their experimental discovery by functional metagenomics is difficult, because the odds are stacked against the experimentor. Here we demonstrate functional screening of a million-membered metagenomic library in microfluidic picolitre droplet compartments. Using bait substrates, new hydrolases for sulfate monoesters and phosphotriesters were identified, mostly based on promiscuous activities presumed not to be under selection pressure. Spanning three protein superfamilies, these break new ground in sequence space: promiscuity now connects enzymes with only distantly related sequences. Most hits could not have been predicted by sequence analysis, because the desired activities have never been ascribed to similar sequences, showing how this approach complements bioinformatic harvesting of metagenomic sequencing data. Functional screening of a library of unprecedented size with excellent assay sensitivity has been instrumental in identifying rare genes constituting catalytically versatile hubs in sequence space as potential starting points for the acquisition of new functions.

The ability to miniaturize biochemical assays in water-in-oil emulsion droplets allows a massive scale-down of reaction volumes, so that high-throughput experimentation can be performed more economically and more efficiently. Generating such droplets in compartment-on-demand (COD) platforms is the basis for rapid, automated screening of chemical and biological libraries with minimal volume consumption. Herein, we describe the implementation of such a COD platform to perform high precision nanoliter assays. The coupling of a COD platform to a droplet absorbance detection set-up results in a fully automated analytical system. Michaelis-Menten parameters of 4-nitrophenyl glucopyranoside hydrolysis by sweet almond β-glucosidase can be generated based on 24 time-courses taken at different substrate concentrations with a total volume consumption of only 1.4 μL. Importantly, kinetic parameters can be derived in a fully unsupervised manner within 20 min: droplet production (5 min), initial reading of the droplet sequence (5 min), and droplet fusion to initiate the reaction and read-out over time (10 min). Similarly, the inhibition of the enzymatic reaction by conduritol B epoxide and 1-deoxynojirimycin was measured, and Ki values were determined. In both cases, the kinetic parameters obtained in droplets were identical within error to values obtained in titer plates, despite a >10(4)-fold volume reduction, from micro- to nanoliters.

The Belousov-Zhabotinsky reaction was performed in microdroplets confined in rectangular microchannels. In addition to producing one-dimensional waves, the reaction showed an increase in oscillation frequency thought to be mainly due to bromine diffusion out of the microdroplets. We found that surfactant loaded mineral oil can be used as an encapsulation agent to not only extend the stable reaction time from 200 s to approximately 800 s, but more importantly to further extend the one-dimensional wave formation from ∼15 s to 800 s. © 2012 the Royal Society of Chemistry.

We present a novel method for the identification of live and dead T-cells, dynamically flowing within highly conductive buffers. This technique discriminates between live and dead (heat treated) cells on the basis of dielectric properties variations. The key advantage of this technique lies in its operational simplicity, since cells do not have to be resuspended in isotonic low conductivity media. Herein, we demonstrate that at 40 MHz, we are able to statistically distinguish between live and dead cell populations.

Pipetting and dilution are universal processes used in chemical and biological laboratories to assay and experiment. In microfluidics such operations are equally in demand, but difficult to implement. Recently, droplet-based microfluidics has emerged as an exciting new platform for high-throughput experimentation. However, it is challenging to vary the concentration of droplets rapidly and controllably. To this end, we developed a dilution module for high-throughput screening using droplet-based microfluidics. Briefly, a nanolitre-sized sample droplet of defined concentration is trapped within a microfluidic chamber. Through a process of droplet merging, mixing and re-splitting, this droplet is combined with a series of smaller buffer droplets to generate a sequence of output droplets that define a digital concentration gradient. Importantly, the formed droplets can be merged with other reagent droplets to enable rapid chemical and biological screens. As a proof of concept, we used the dilutor to perform a high-throughput homogeneous DNA-binding assay using only nanolitres of sample.

The use of dielectrophoretic forces is crucially tied to the knowledge of Joule heating within a fluid, since the use of planar microelectrodes creates a temperature gradient within which the particle of interest is manipulated. Mapping temperature with sufficient spatial resolution within a dielectrophoretic trap is recognized to be of high importance. Herein, we demonstrate local temperature measurements in the vicinity of a trapped micrometer-size particle using confocal fluorescence spectroscopy. Such measurements are shown to provide a novel calibration tool for screening temperature-mediated processes with high resolution.

In this paper we describe a universal mechanism for merging multiple aqueous microdroplets within a flowing stream consisting of an oil carrier phase. Our approach involves the use of both a pillar array acting as a passive merging element, as well as built-in electrodes acting as an active merging element. The pillar array enables slowing down and trapping of the droplets via the drainage of the oil phase. This brings adjacent droplets into close proximity. At this point, an electric field applied to the electrodes breaks up the thin oil film surrounding the droplets resulting in merging.

We present a novel planar electrode geometry in which particles (typically 10 microm in diameter) are focused near a defined surface before being trapped using negative dielectrophoresis. The focusing element can deflect particles having speeds up to hundreds of micrometers per second. This trapping configuration results in improved trapping yields and a decrease in overall reagent consumption. Particles are trapped dynamically while flowing in a microfluidic channel.