Breaking through the Poisson Distribution: A compact high-efficiency droplet microfluidic system for single-bead encapsulation and digital immunoassay detection

Label-free active single-cell encapsulation enabled by microvalve-based on-demand droplet generation and real-time image processing

Droplet microfluidics-based single-cell encapsulation is a critical technology that enables large-scale parallel single-cell analysis by capturing and processing thousands of individual cells. As the efficiency of passive single-cell encapsulation is limited by Poisson distribution, active single-cell encapsulation has been developed to theoretically ensure that each droplet contains one cell. However, existing active single-cell encapsulation technologies still face issues related to fluorescence labeling and low throughput. Here, we present an active single-cell encapsulation technique by using microvalve-based drop-on-demand technology and real-time image processing to encapsulate single cells with high throughput in a label-free manner. Our experiments demonstrated that the single-cell encapsulation system can encapsulate individual polystyrene beads with 96.3 % efficiency and HeLa cells with 94.9 % efficiency. The flow speed of cells in this system can reach 150 mm/s, resulting in a corresponding theoretical encapsulation throughput of 150 Hz. This technology has significant potential in various biomedical applications, including single-cell omics, secretion detection, and drug screening.

Image-activated pico-injection for single-cell analysis

The addition of reagents into preformed droplets is a crucial yet intricate task in droplet-based applications where sequential reactions is required. Pico-injection offers high throughput and robustness in accomplishing this task, but the existing pico-injection techniques work in an indiscriminate manner, making it difficult to target particular groups of droplets. Here we report image-activated pico-injection (imgPico) for label-free, on-demand reagent supplementation into droplets. The imgPico detects the droplets of interest by real-time image analysis and makes decisions for the downstream pico-injection operation. We studied the performance of different algorithms for the image analysis and optimized the experimental settings of the imgPico. In the validation experiment, the imgPico successfully injected fluorescent dyes into droplets encapsulating one, two, and three cells, respectively, as expected. We further demonstrated the utility of imgPico by targeting droplets encapsulating single cells in droplet-based single-cell RNA sequencing (scRNA-seq) using exceedingly high cell density, and the results showed that the imgPico effectively reduced the presence of doublets in the scRNA-seq data. With the merits of being label-free and versatile, the imgPico represents a technical advance with potential applications in single-cell analysis.

Dynamic video recognition for cell-encapsulating microfluidic droplets

Droplet microfluidics is a highly sensitive and high-throughput technology extensively utilized in biomedical applications, such as single-cell sequencing and cell screening. However, its performance is highly influenced by the droplet size and single-cell encapsulation rate (following random distribution), thereby creating an urgent need for quality control. Machine learning has the potential to revolutionize droplet microfluidics, but it requires tedious pixel-level annotation for network training. This paper investigates the application software of the weakly supervised cell-counting network (WSCApp) for video recognition of microdroplets. We demonstrated its real-time performance in video processing of microfluidic droplets and further identified the locations of droplets and encapsulated cells. We verified our methods on droplets encapsulating six types of cells/beads, which were collected from various microfluidic structures. Quantitative experimental results showed that our approach can not only accurately distinguish droplet encapsulations (micro-F1 score > 0.94), but also locate each cell without any supervised location information. Furthermore, fine-tuning transfer learning on the pre-trained model also significantly reduced (>80%) annotation. This software provides a user-friendly and assistive annotation platform for the quantitative assessment of cell-encapsulating microfluidic droplets.

Enhancing single-cell encapsulation in droplet microfluidics with fine-tunable on-chip sample enrichment

Single-cell encapsulation in droplet microfluidics is commonly hindered by the tradeoff between cell suspension density and on-chip focusing performance. In this study, we introduce a novel droplet microfluidic chip to overcome this challenge. The chip comprises a double spiral focusing unit, a flow resistance-based sample enrichment module with fine-tunable outlets, and a crossflow droplet generation unit. Utilizing a low-density cell/bead suspension (2 × 106 objects/mL), cells/beads are focused into a near-equidistant linear arrangement within the double spiral microchannel. The excess water phase is diverted while cells/beads remain focused and sequentially encapsulated in individual droplets. Focusing performance was assessed through numerical simulations and experiments at three flow rates (40, 60, 80 μL/min), demonstrating successful focusing at 40 and 80 μL/min for beads and cells, respectively. In addition, both simulation and experimental results revealed that the flow resistance at the sample enrichment module is adjustable by punching different outlets, allowing over 50% of the aqueous phase to be removed. YOLOv8n-based droplet detection algorithms realized the counting of cells/beads in droplets, statistically demonstrating single-cell and bead encapsulation rates of 72.2% and 79.2%, respectively. All the results indicate that this on-chip sample enrichment approach can be further developed and employed as a critical component in single-cell encapsulation in water-in-oil droplets.

Advanced design and applications of digital microfluidics in biomedical fields: An update of recent progress

Significant breakthroughs have been made in digital microfluidic (DMF)-based technologies over the past decades. DMF technology has attracted great interest in bioassays depending on automatic microscale liquid manipulations and complicated multi-step processing. In this review, the recent advances of DMF platforms in the biomedical field were summarized, focusing on the integrated design and applications of the DMF system. Firstly, the electrowetting-on-dielectric principle, fabrication of DMF chips, and commercialization of the DMF system were elaborated. Then, the updated droplets and magnetic beads manipulation strategies with DMF were explored. DMF-based biomedical applications were comprehensively discussed, including automated sample preparation strategies, immunoassays, molecular diagnosis, blood processing/testing, and microbe analysis. Emerging applications such as enzyme activity assessment and DNA storage were also explored. The performance of each bioassay was compared and discussed, providing insight into the novel design and applications of the DMF technology. Finally, the advantages, challenges, and future trends of DMF systems were systematically summarized, demonstrating new perspectives on the extensive applications of DMF in basic research and commercialization.

Digital droplet immunoassay based on a microfluidic chip with magnetic beads for the detection of prostate-specific antigen

Sensitive biomarker detection techniques are beneficial for both disease diagnosis and postoperative examinations. In this study, we report an integrated microfluidic chip designed for the immunodetection of prostate-specific antigens (PSAs). The microfluidic chip is based on the three-dimensional structure of quartz capillaries. The outlet channel extends to 1.8 cm, effectively facilitating the generation of uniform droplets ranging in size from 3 to 50 μm. Furthermore, we successfully immobilized the captured antibodies onto the surface of magnetic beads using an activator, and we constructed an immunosandwich complex by employing biotinylated antibodies. A key feature of this microfluidic chip is its integration of microfluidic droplet technology advantages, such as high-throughput parallelism, enzymatic signal amplification, and small droplet size. This integration results in an exceptionally sensitive PSA detection capability, with the detection limit reduced to 7.00 ± 0.62 pg/mL.

Multiplex fluorescence detection of single-cell droplet microfluidics and its application in quantifying protein expression levels

This study presented a platform of multiplex fluorescence detection of single-cell droplet microfluidics with demonstrative applications in quantifying protein expression levels. The platform of multiplex fluorescence detection mainly included optical paths adopted from conventional microscopy enabling the generation of three optical spots from three laser sources for multiple fluorescence excitation and capture of multiple fluorescence signals by four photomultiplier tubes. As to platform characterization, microscopic images of three optical spots were obtained where clear Gaussian distributions of intensities without skewness confirmed the functionality of the scanning lens, while the controllable distances among three optical spots validated the functionality of fiber collimators and the reflector lens. As to demonstration, this platform was used to quantify single-cell protein expression within droplets where four-type protein expression of α-tubulin, Ras, c-Myc, and β-tubulin of CAL 27 (Ncell = 1921) vs WSU-HN6 (Ncell = 1881) were quantitatively estimated, which were (2.85 ± 0.72) × 105 vs (4.83 ± 1.58) × 105, (3.69 ± 1.41) × 104 vs (5.07 ± 2.13) × 104, (5.90 ± 1.45) × 104 vs (9.57 ± 2.85) × 104, and (3.84 ± 1.28) × 105 vs (3.30 ± 1.10) × 105, respectively. Neural pattern recognition was utilized for the classification of cell types, achieving successful rates of 69.0% (α-tubulin), 75.4% (Ras), 89.1% (c-Myc), 65.8% (β-tubulin), and 99.1% in combination, validating the capability of this platform of multiplex fluorescence detection to quantify various types of single-cell proteins, which could provide comprehensive evaluations on cell status.

Recent advancements in single-cell metabolic analysis for pharmacological research

Cellular heterogeneity is crucial for understanding tissue biology and disease pathophysiology. Pharmacological research is being advanced by single-cell metabolic analysis, which offers a technique to identify variations in RNA, proteins, metabolites, and drug molecules in cells. In this review, the recent advancement of single-cell metabolic analysis techniques and their applications in drug metabolism and drug response are summarized. High-precision and controlled single-cell isolation and manipulation are provided by microfluidics-based methods, such as droplet microfluidics, microchamber, open microfluidic probe, and digital microfluidics. They are used in tandem with variety of detection techniques, including optical imaging, Raman spectroscopy, electrochemical detection, RNA sequencing, and mass spectrometry, to evaluate single-cell metabolic changes in response to drug administration. The advantages and disadvantages of different techniques are discussed along with the challenges and future directions for single-cell analysis. These techniques are employed in pharmaceutical analysis for studying drug response and resistance pathway, therapeutic targets discovery, and in vitro disease model evaluation.

Demand-driven active droplet generation and sorting based on positive pressure-controlled fluid wall

Droplet microfluidics is a rapidly advancing area of microfluidic technology, which offers numerous advantages for cell analysis, such as isolation and accumulation of signals, by confining cells within droplets. However, controlling cell numbers in droplets is challenging due to the uncertainty of random encapsulation which result in many empty droplets. Therefore, more precise control techniques are needed to achieve efficient encapsulation of cells within droplets. Here, an innovative microfluidic droplet manipulation platform had been developed, which employed positive pressure as a stable and controllable driving force for manipulating fluid within chips. The air cylinder, electro-pneumatics proportional valve, and the microfluidic chip were connected through a capillary, which enabled the formation of a fluid wall by creating a difference in hydrodynamic resistance between two fluid streams at the channel junction. Lowering the pressure of the driving oil phase eliminates hydrodynamic resistance and breaks the fluid wall. Regulating the duration of the fluid wall breakage controls the volume of the introduced fluid. Several important droplet microfluidic manipulations were demonstrated on this microfluidic platform, such as sorting of cells/droplets, sorting of droplets co-encapsulated cells and hydrogels, and active generation of droplets encapsulated with cells in a responsive manner. The simple, on-demand microfluidic platform was featured with high stability, good controllability, and compatibility with other droplet microfluidic technologies.

WSCNet: Biomedical Image Recognition for Cell Encapsulated Microfluidic Droplets

Microfluidic droplets accommodating a single cell as independent microreactors are frequently demanded for single-cell analysis of phenotype and genotype. However, challenges exist in identifying and reducing the covalence probability (following Poisson's distribution) of more than two cells encapsulated in one droplet. It is of great significance to monitor and control the quantity of encapsulated content inside each droplet. We demonstrated a microfluidic system embedded with a weakly supervised cell counting network (WSCNet) to generate microfluidic droplets, evaluate their quality, and further recognize the locations of encapsulated cells. Here, we systematically verified our approach using encapsulated droplets from three different microfluidic structures. Quantitative experimental results showed that our approach can not only distinguish droplet encapsulations (F1 score > 0.88) but also locate each cell without any supervised location information (accuracy > 89%). The probability of a "single cell in one droplet" encapsulation is systematically verified under different parameters, which shows good agreement with the distribution of the passive method (Residual Sum of Squares, RSS < 0.5). This study offers a comprehensive platform for the quantitative assessment of encapsulated microfluidic droplets.

Clinical Application of Small Extracellular Vesicles in Gynecologic Malignancy Treatments

Small extracellular vesicles (sEVs) are the key mediators of intercellular communication. They have the potential for clinical use as diagnostic or therapeutic biomarkers and have been explored as vectors for drug delivery. Identification of reliable and noninvasive biomarkers, such as sEVs, is important for early diagnosis and precise treatment of gynecologic diseases to improve patient prognosis. Previous reviews have summarized routine sEVs isolation and identification methods; however, novel and unconventional methods have not been comprehensively described. This review summarizes a convenient method of isolating sEVs from body fluids and liquid biopsy-related sEV markers for early, minimally invasive diagnosis of gynecologic diseases. In addition, the characteristics of sEVs as drug carriers and in precision treatment and drug resistance are introduced, providing a strong foundation for identifying novel and potential therapeutic targets for sEV therapy. We propose potential directions for further research on the applications of sEVs in the diagnosis and treatment of gynecologic diseases.

Digital detection of proteins

This paper reviews methods for detecting proteins based on molecular digitization, i.e., the isolation and detection of single protein molecules or singulated ensembles of protein molecules. The single molecule resolution of these methods has resulted in significant improvements in the sensitivity of immunoassays beyond what was possible using traditional "analog" methods: the sensitivity of some digital immunoassays approach those of methods for measuring nucleic acids, such as the polymerase chain reaction (PCR). The greater sensitivity of digital protein detection has resulted in immuno-diagnostics with high potential societal impact, e.g., the early diagnosis and therapeutic intervention of Alzheimer's Disease. In this review, we will first provide the motivation for developing digital protein detection methods given the limitations in the sensitivity of analog methods. We will describe the paradigm shift catalyzed by single molecule detection, and will describe in detail one digital approach - which we call digital bead assays (DBA) - based on the capture and labeling of proteins on beads, identifying "on" and "off" beads, and quantification using Poisson statistics. DBA based on the single molecule array (Simoa) technology have sensitivities down to attomolar concentrations, equating to ∼10 proteins in a 200 μL sample. We will describe the concept behind DBA, the different single molecule labels used, the ways of analyzing beads (imaging of arrays and flow), the binding reagents and substrates used, and integration of these technologies into fully automated and miniaturized systems. We provide an overview of emerging approaches to digital protein detection, including those based on digital detection of nucleic acids labels, single nanoparticle detection, measurements using nanopores, and methods that exploit the kinetics of single molecule binding. We outline the initial impact of digital protein detection on clinical measurements, highlighting the importance of customized assay development and translational clinical research. We highlight the use of DBA in the measurement of neurological protein biomarkers in blood, and how these higher sensitivity methods are changing the diagnosis and treatment of neurological diseases. We conclude by summarizing the status of digital protein detection and suggest how the lab-on-a-chip community might drive future innovations in this field.

Viscoelastic Particle Encapsulation Using a Hyaluronic Acid Solution in a T-Junction Microfluidic Device

The encapsulation of particles and cells in droplets is highly relevant in biomedical engineering as well as in material science. So far, however, the majority of the studies in this area have focused on the encapsulation of particles or cells suspended in Newtonian liquids. We here studied the particle encapsulation phenomenon in a T-junction microfluidic device, using a non-Newtonian viscoelastic hyaluronic acid solution in phosphate buffer saline as suspending liquid for the particles. We first studied the non-Newtonian droplet formation mechanism, finding that the data for the normalised droplet length scaled as the Newtonian ones. We then performed viscoelastic encapsulation experiments, where we exploited the fact that particles self-assembled in equally-spaced structures before approaching the encapsulation area, to then identify some experimental conditions for which the single encapsulation efficiency was larger than the stochastic limit predicted by the Poisson statistics.

Demands and technical developments of clinical flow cytometry with emphasis in quantitative, spectral, and imaging capabilities

As the gold-standard method for single-cell analysis, flow cytometry enables high-throughput and multiple-parameter characterization of individual biological cells. This review highlights the demands for clinical flow cytometry in laboratory hematology (e.g., diagnoses of minimal residual disease and various types of leukemia), summarizes state-of-the-art clinical flow cytometers (e.g., FACSLyricTM by Becton Dickinson, DxFLEX by Beckman Coulter), then considers innovative technical improvements in flow cytometry (including quantitative, spectral, and imaging approaches) to address the limitations of clinical flow cytometry in hematology diagnosis. Finally, driven by these clinical demands, future developments in clinical flow cytometry are suggested.

Quantitative flow cytometry leveraging droplet‐based constriction microchannels with high reliability and high sensitivity

This study presented a quantitative flow cytometry leveraging droplet-based constriction microchannels with high reliability and high sensitivity. Droplets encapsulating single cells and even distribution of fluorescein labeled antibodies removed from targeted cells deformed through the constriction microchannel where the excited fluorescent signals were sampled and interpreted into numbers of proteins based on volume equivalence in measurement of droplets and calibration of fluorescence. To improve the detection reliability, a comprehensive analysis and comparison of multiple stripping agents such as proteinase K, guanidine hydrochloride, and urea was conducted. To improve the detection sensitivity, light modulation was used to address electrical noises and quartz microchannels were fabricated to address optical noises. As a demonstration, based on this quantitative flow cytometry of droplet microfluidics, (1) mutant p53 expressions of single cells were quantified as 1.95 ± 0.60 × 10⁵ (n_cell  = 2918 of A431) and 1.30 ± 0.70 × 10⁵ (n_cell  = 3954 of T47D); (2) single-cell expressions of Ras, c-Myc, and β-tubulin were quantified as 1.90 ± 0.59 × 10⁵ , 4.39 ± 1.44 × 10⁵ , and 2.97 ± 0.81 × 10⁵ (n_cell  = 3298 of CAL 27), 1.83 ± 0.58 × 10⁵ , 2.08 ± 0.13 × 10⁶ , and 1.96 ± 0.74 × 10⁵ (n_cell  = 5459 of WSU-HN6). As a microfluidic tool capable of quantitatively estimating single-cell protein expressions, this methodology may provide a new quantitative perspective for the field of flow cytometry.

Selective single-bacteria extraction based on capture and release of microemulsion droplets

Human host-associated microbial communities in body sites can reflect health status based on the population distribution and specific microbial properties in the heterogeneous community. Bacteria identification at the single-cell level provides a reliable biomarker and pathological information for clinical diagnosis. Nevertheless, biosamples obtained from some body sites cannot offer sufficient sample volume and number of target cells as required by most of the existing single-cell isolation methods such as flow cytometry. Herein we report a novel integrated microfluidic system, which consists of a microemulsion module for single-bacteria encapsulation and a sequential microdroplet capture and release module for selectively extracting only the single-bacteria encapsulated in microdroplets. We optimize the system for a success rate of the single-cell extraction to be > 38%. We further verify applicability of the system with prepared cell mixtures (Methylorubrum extorquens AM1 and Methylomicrobium album BG8) and biosamples collected from human skin, to quantify the population distribution of multiple key species in a heterogeneous microbial community. Results indicate perfect viability of the single-cell extracts and compatibility with downstream analyses such as PCR. Together, this research demonstrates that the reported single-bacteria extraction system can be applied in microbiome and pathology research and clinical diagnosis as a clinical or point-of-care device.

Recent Advances in Digital Biosensing Technology

Digital biosensing assays demonstrate remarkable advantages over conventional biosensing systems because of their ability to achieve single-molecule detection and absolute quantification. Unlike traditional low-abundance biomarking screening, digital-based biosensing systems reduce sample volumes significantly to the fL-nL level, which vastly reduces overall reagent consumption, improves reaction time and throughput, and enables high sensitivity and single target detection. This review presents the current technology for compartmentalizing reactions and their applications in detecting proteins and nucleic acids. We also analyze existing challenges and future opportunities associated with digital biosensing and research opportunities for developing integrated digital biosensing systems.