Label-free single-cell analysis in microdroplets using a light-scattering-based optofluidic chip

Droplet-based single-cell analysis is a very powerful tool for studying phenotypic and genomic heterogeneity at single-cell resolution for a variety of biological problems. In conventional two-phase droplet microfluidics, due to the mismatch in optical properties between oil and aqueous phases, light scattering mainly happens at the oil/water interface that disables light-scattering-based cell analysis confined in microdroplets. Detection and analysis of cells in microdroplets thus mostly rely on the fluorescence labeling of cell samples, which may suffer from complex operation, cytotoxicity, and low fluorescence stability. In this work, we propose a novel light-scattering-based droplet screening (LSDS) that can effectively detect and characterize single cells confined in droplets by adjusting the optical properties of droplets in a multiangle optofluidic chip. Theoretical and simulated calculations suggest that refractive index (RI) matching in droplet two-phase materials can reduce or eliminate droplets' scattered signals (background signal), enabling the differentiation of scattered signals from single cells and particles within droplets. Furthermore, by using a set of multiangle (from -145° to 140°) optical fibers integrated into the optofluidic chip, the scattered light properties of droplets with the RI ranging from 1.334 to 1.429 are measured. We find that the smaller the RI and size of microparticles inside droplets are, the smaller the RI difference between two-phase materials Δn is required. Especially, when Δn is smaller than 0.02, single cells in droplets can be detected and analyzed solely based on light scattering. This capability allows to accurately detect droplets containing one single cell and one single gel bead, a typical droplet encapsulation for single-cell sequencing. Altogether, this work provides a powerful platform for high-throughput label-free single-cell analysis in microdroplets for diverse single-cell related biological assays.

A facile single-cell patterning strategy based on harbor-like microwell microfluidics

Single-cell analysis is an effective method for conducting comprehensive heterogeneity studies ranging from cell phenotype to gene expression. The ability to arrange different cells in a predetermined pattern at single-cell resolution has a wide range of applications in cell-based analysis and plays an important role in facilitating interdisciplinary research by researchers in various fields. Most existing microfluidic microwell chips is a simple and straightforward method, which typically use small-sized microwells to accommodate single cells. However, this method imposes certain limitations on cells of various sizes, and the single-cell capture efficiency is relatively low without the assistance of external forces. Moreover, the microwells limit the spatiotemporal resolution of reagent replacement, as well as cell-to-cell communication. In this study, we propose a new strategy to prepare a single-cell array on a planar microchannel based on microfluidic flip microwells chip platform with large apertures (50 μm), shallow channels (50 μm), and deep microwells (50 μm). The combination of three configuration characteristics contributes to multi-cell trapping and a single-cell array within microwells, while the subsequent chip flipping accomplishes the transfer of the single-cell array to the opposite planar microchannel for cells adherence and growth. Further assisted by protein coating of bovine serum albumin and fibronectin on different layers, the single-cell capture efficiency in microwells is achieved at 92.1% ± 1%, while ultimately 85% ± 3.4% on planar microchannel. To verify the microfluidic flip microwells chip platform, the real-time and heterogeneous study of calcium release and apoptosis behaviours of single cells is carried out. To our knowledge, this is the first time that high-efficiency single-cell acquisition has been accomplished using a circular-well chip design that combines shallow channel, large aperture and deep microwell together. The chip is effective in avoiding the shearing force of high flow rates on cells, and the large apertures better allows cells to sedimentation. Therefore, this strategy owns the advantages of easy preparation and user-friendliness, which is especially valuable for researchers from different fields.

Evaluation of Acoustophoretic and Dielectrophoretic Forces for Droplet Injection in Droplet-Based Microfluidic Devices

Acoustophoretic forces have been successfully implemented into droplet-based microfluidic devices to manipulate droplets. These acoustophoretic forces in droplet microfluidic devices are typically generated as in acoustofluidic devices through transducer actuation of a piezoelectric substrate such as lithium niobate (LiNbO3), which is inherently accompanied by the emergence of electrical fields. Understanding acoustophoretic versus dielectrophoretic forces produced by electrodes and transducers within active microfluidic devices is important for the optimization of device performance during design iterations. In this case study, we design microfluidic devices with a droplet injection module and report an experimental strategy to deduce the respective contribution of the acoustophoretic versus dielectrophoretic forces for the observed droplet injection. Our PDMS-based devices comprise a standard oil-in-water droplet-generating module connected to a T-junction injection module featuring actuating electrodes. We use two different electrode geometries produced within the same PDMS slab as the droplet production/injection channels by filling low-melting-point metal alloy into channels that template the electrode geometries. When these electrodes are constructed on LiNbO3 as the substrate, they have a dual function as a piezoelectric transducer, which we call embedded liquid metal interdigitated transducers (elmIDTs). To decipher the contribution of acoustophoretic versus dielectrophoretic forces, we build the same devices on either piezoelectric LiNbO3 or nonpiezo active glass substrates with different combinations of physical device characteristics (i.e., elmIDT geometry and alignment) and operate in a range of phase spaces (i.e., frequency, voltage, and transducer polarity). We characterize devices using techniques such as laser Doppler vibrometry (LDV) and infrared imaging, along with evaluating droplet injection for our series of device designs, constructions, and operating parameters. Although we find that LiNbO3 device designs generate acoustic fields, we demonstrate that droplet injection occurs only due to dielectrophoretic forces. We deduce that droplet injection is caused by the coupled dielectrophoretic forces arising from the operation of elmIDTs rather than by acoustophoretic forces for this specific device design. We arrive at this conclusion because equivalent droplet injection occurs without the presence of an acoustic field using the same electrode designs on nonpiezo active glass substrate devices. This work establishes a methodology to pinpoint the major contributing force of droplet manipulation in droplet-based acoustomicrofluidics.

Microfluidics Coupled Mass Spectrometry for Single Cell Multi-Omics

Population-level analysis masks significant heterogeneity between individual cells, making it difficult to accurately reflect the true intricacies of life activities. Microfluidics is a technique that can manipulate individual cells effectively and is commonly coupled with a variety of analytical methods for single-cell analysis. Single-cell omics provides abundant molecular information at the single-cell level, fundamentally revealing differences in cell types and biological states among cell individuals, leading to a deeper understanding of cellular phenotypes and life activities. Herein, this work summarizes the microfluidic chips designed for single-cell isolation, manipulation, trapping, screening, and sorting, including droplet microfluidic chips, microwell arrays, hydrodynamic microfluidic chips, and microchips with microvalves. This work further reviews the studies on single-cell proteomics, metabolomics, lipidomics, and multi-omics based on microfluidics and mass spectrometry. Finally, the challenges and future application of single-cell multi-omics are discussed.

Micro-Droplets Parameters Monitoring in a Microfluidic Chip via Liquid-Solid Triboelectric Nanogenerator

The monitoring of micro-droplets parameters is significant to the development of droplet microfluidics. However, existing monitoring methods have drawbacks such as high cost, interference with droplet movement, and even the potential for cross-contamination. Herein, a micro-droplets monitoring method (MDMM) based on liquid-solid triboelectric nanogenerator (LS-TENG) is proposed, which can realize non-invasive and self-powered monitoring of micro-droplets in a microfluidic chip. The droplet frequency is monitored by voltage pulse frequency and a mathematical model is established to monitor the droplet length and velocity. Furthermore, this work constructs micro-droplets sensor (MDS) based on the MDMM to carry out the experiment. The coefficients of determination (R2 ) of the fitting curves of the micro-droplets frequency, length, and velocity monitoring are 0.998, 0.997, and 0.995, respectively. To prove the universal applicability of the MDMM, the micro-droplets generated by different liquid media and channel structures are monitored. Eventually, a micro-droplet monitoring system is built, which can realize the counting of micro-droplets and the monitoring of droplet frequency and length. This work provides a novel approach for monitoring micro-droplets parameters, which holds the potential to advance developments in the field of microfluidics.

Water promoted 9-fluorenylmethyloxycarbonyl detachment from amino acids in charged microdroplets

Aqueous microdroplets exhibit unique properties and can trigger reactions that do not occur in bulk solution. Herein, we have demonstrated that water, in microdroplets, can reduce the energy barrier for the lone H transfer of 9-fluorenylmethyloxycarbonyl and promote its detachment from the amino group. This strategy works on various amino acids and opens opportunities of aqueous microdroplets in triggering organic reactions.

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.

Investigation of Experimental Endovascular Air Embolisms Using a New Model for the Generation and Detection of Highly Calibrated Micro Air Bubbles

BACKGROUND

Air embolism (AE), especially when affecting the brain, is an underrated and potentially life-threatening complication in various endovascular interventions. This study aims to investigate experimental AEs using a new model to generate micro air bubbles (MAB), to assess the impact of a catheter on these MAB, and to demonstrate the applicability of this model in vivo.

MATERIALS AND METHODS

Micro air bubbles were created using a system based on microfluidic channels. The MAB were detected and analyzed automatically. Micro air bubbles, with a target size of 85 µm, were generated and injected through a microcatheter. The MAB diameters proximal and distal to the catheter were assessed and compared. In a subsequent in vivo application, 2000 MAB were injected into the aorta (at the aortic valve) and into the common carotid artery (CCA) of a rat, respectively, using a microcatheter, resembling AE occurring during cardiovascular interventions.

RESULTS

Micro air bubbles with a highly calibrated size could be successfully generated (median: 85.5 µm, SD 1.9 µm). After passage of the microcatheter, the MAB were similar in diameter (median: 86.6 µm) but at a lower number (60.1% of the injected MAB) and a substantially higher scattering of diameters (SD 29.6 µm). In vivo injection of MAB into the aorta resulted in cerebral microinfarctions in both hemispheres, whereas injection into the CCA caused exclusively ipsilateral microinfarctions.

CONCLUSION

Using this new AE model, MAB can be generated precisely and reproducibly, resulting in cerebral microinfarctions. This model is feasible for further studies on the pathophysiology and prevention of AE in cardiovascular procedures.

Automation and Standardization-A Coupled Approach towards Reproducible Sample Preparation Protocols for Nanomaterial Analysis

Whereas the characterization of nanomaterials using different analytical techniques is often highly automated and standardized, the sample preparation that precedes it causes a bottleneck in nanomaterial analysis as it is performed manually. Usually, this pretreatment depends on the skills and experience of the analysts. Furthermore, adequate reporting of the sample preparation is often missing. In this overview, some solutions for techniques widely used in nano-analytics to overcome this problem are discussed. Two examples of sample preparation optimization by automation are presented, which demonstrate that this approach is leading to increased analytical confidence. Our first example is motivated by the need to exclude human bias and focuses on the development of automation in sample introduction. To this end, a robotic system has been developed, which can prepare stable and homogeneous nanomaterial suspensions amenable to a variety of well-established analytical methods, such as dynamic light scattering (DLS), small-angle X-ray scattering (SAXS), field-flow fractionation (FFF) or single-particle inductively coupled mass spectrometry (sp-ICP-MS). Our second example addresses biological samples, such as cells exposed to nanomaterials, which are still challenging for reliable analysis. An air-liquid interface has been developed for the exposure of biological samples to nanomaterial-containing aerosols. The system exposes transmission electron microscopy (TEM) grids under reproducible conditions, whilst also allowing characterization of aerosol composition with mass spectrometry. Such an approach enables correlative measurements combining biological with physicochemical analysis. These case studies demonstrate that standardization and automation of sample preparation setups, combined with appropriate measurement processes and data reduction are crucial steps towards more reliable and reproducible data.

Synthesis and Spectrophotometric Analysis of Microcapsules Containing Immortelle Essential Oil

In this study, microcapsules were prepared by solvent evaporation technique using ethyl cellulose component as wall and essential oil as core material. The synthesis of microcapsules was carried out using different oil masses. The analysis of the microcapsules was carried out using field emission scanning electron microscope (FE-SEM) and UV spectrophotometric analysis using absorption spectrophotometer. The obtained results confirm the regular spherical shape and size of the synthesized microcapsules. The qualitative and quantitative spectrophotometric analysis of the microencapsulated immortelle oil was measured at the wavelength of 265 nm. The calibration diagram was used to calculate the unknown concentrations of the microencapsulated oil. The obtained results confirm the application of the presented method as relevant for the possible determination of microencapsulated oil on textile materials.

The Role of Dendritic Mesoporous Silica Nanoparticles' Size for Quantum Dots Enrichment and Lateral Flow Immunoassay Performance

Using dendritic mesoporous silica nanoparticles (DMSNs) for quantum dots (QDs) enrichment and signal amplification is an emerging strategy for improving the detection sensitivity of lateral flow immunoassay (LFIA). In this study, a new and convenient approach is developed to prepare water-dispersible DMSNs-QDs. A series of DMSNs with various diameters (138, 251, 368, and 471 nm) are studied for loading QDs and LFIA applications. The resultant water-dispersible DMSNs-QDs exhibit a high fluorescence retention of 81.8%. The increase in particle size from 138 to 471 nm results in an increase in loading capacity of QDs and a decrease in binding quantity of the DMSNs-QDs in the test line of LFIA. This trade-off leads to an optimal DMSNs-QDs size of 368 nm with a limit of detection reaching 10 pg mL^-1 (equivalent to 9.0 × 10^-14 m) for the detection of C-reactive protein, which is nearly an order of magnitude more sensitive than the literature. To the best of the authors' knowledge, this study is the first to demonstrate the distinctive role of DMSN's size for QDs enrichment and LFIA. The strategy developed from this work is useful for the rational design of high-quality QDs-based nanoparticles for ultrasensitive detection.