Computer vision meets microfluidics: a label-free method for high-throughput cell analysis

Automated Uniform Spheroid Generation Platform for High Throughput Drug Screening Process

Three-dimensional (3D) spheroid models are crucial for cancer research, offering more accurate insights into tumour biology and drug responses than traditional 2D cell cultures. However, inconsistent and low-throughput spheroid production has hindered their application in drug screening. Here, we present an automated high-throughput platform for a spheroid selection, fabrication, and sorting system (SFSS) to produce uniform gelatine-encapsulated spheroids (GESs) with high efficiency. SFSS integrates advanced imaging, analysis, photo-triggered fabrication, and microfluidic sorting to precisely control spheroid size, shape, and viability. Our data demonstrate that our SFSS can produce over 50 GESs with consistent size and circularity in 30 min with over 97% sorting accuracy while maintaining cell viability and structural integrity. We demonstrated that the GESs can be used for drug screening and potentially for various assays. Thus, the SFSS could significantly enhance the efficiency of generating uniform spheroids, facilitating their application in drug development to investigate complex biological systems and drug responses in a more physiologically relevant context.

Continuous and autonomous-flow separation of laccase enzyme utilizing functionalized aqueous two-phase system with computer vision control

Downstream processing of biomolecules, particularly therapeutic proteins and enzymes, presents a formidable challenge due to intricate unit operations and high costs. This study introduces a novel cysteine (cys) functionalized aqueous two-phase system (ATPS) utilizing polyethylene glycol (PEG) and potassium phosphate, referred as PEG-K3PO4/cys, for selective extraction of laccase from complex protein mixtures. A 3D-baffle micro-mixer and phase separator was meticulously designed and equipped with computer vision controller, to enable precise mixing and continuous phase separation under automated-flow. Microfluidic-assisted ATPS exhibits substantial increase in partition coefficient (Kflow = 16.3) and extraction efficiency (EEflow = 88 %) for laccase compared to conventional batch process. Integrated and continuous-flow process efficiently partitioned laccase, even in low concentrations and complex crude extracts. Circular dichroism spectra of laccase confirm structural stability of enzyme throughout the purification process. Eventually, continuous-flow microfluidic bioseparation is highly useful for seamless downstream processing of target biopharmaceuticals in integrated and autonomous manner.

Vibrational imaging of metabolites for improved microbial cell strains

Significance

Biomanufacturing utilizes modified microbial systems to sustainably produce commercially important biomolecules for use in agricultural, energy, food, material, and pharmaceutical industries. However, technological challenges related to non-destructive and high-throughput metabolite screening need to be addressed to fully unlock the potential of synthetic biology and sustainable biomanufacturing.

Aim

This perspective outlines current analytical screening tools used in industrial cell strain development programs and introduces label-free vibrational spectro-microscopy as an alternative contrast mechanism.

Approach

We provide an overview of the analytical instrumentation currently used in the "test" portion of the design, build, test, and learn cycle of synthetic biology. We then highlight recent progress in Raman scattering and infrared absorption imaging techniques, which have enabled improved molecular specificity and sensitivity.

Results

Recent developments in high-resolution chemical imaging methods allow for greater throughput without compromising the image contrast. We provide a roadmap of future work needed to support integration with microfluidics for rapid screening at the single-cell level.

Conclusions

Quantifying the net expression of metabolites allows for the identification of cells with metabolic pathways that result in increased biomolecule production, which is essential for improving the yield and reducing the cost of industrial biomanufacturing. Technological advancements in vibrational microscopy instrumentation will greatly benefit biofoundries as a complementary approach for non-destructive cell screening.

Bone and Joint-on-Chip Platforms: Construction Strategies and Applications

Organ-on-a-chip, also known as "tissue chip," is an advanced platform based on microfluidic systems for constructing miniature organ models in vitro. They can replicate the complex physiological and pathological responses of human organs. In recent years, the development of bone and joint-on-chip platforms aims to simulate the complex physiological and pathological processes occurring in human bones and joints, including cell-cell interactions, the interplay of various biochemical factors, the effects of mechanical stimuli, and the intricate connections between multiple organs. In the future, bone and joint-on-chip platforms will integrate the advantages of multiple disciplines, bringing more possibilities for exploring disease mechanisms, drug screening, and personalized medicine. This review explores the construction and application of Organ-on-a-chip technology in bone and joint disease research, proposes a modular construction concept, and discusses the new opportunities and future challenges in the construction and application of bone and joint-on-chip platforms.

On-Chip Photonic Detection Techniques for Non-Invasive In Situ Characterizations at the Microfluidic Scale

Microfluidics has emerged as a robust technology for diverse applications, ranging from bio-medical diagnostics to chemical analysis. Among the different characterization techniques that can be used to analyze samples at the microfluidic scale, the coupling of photonic detection techniques and on-chip configurations is particularly advantageous due to its non-invasive nature, which permits sensitive, real-time, high throughput, and rapid analyses, taking advantage of the microfluidic special environments and reduced sample volumes. Putting a special emphasis on integrated detection schemes, this review article explores the most relevant advances in the on-chip implementation of UV-vis, near-infrared, terahertz, and X-ray-based techniques for different characterizations, ranging from punctual spectroscopic or scattering-based measurements to different types of mapping/imaging. The principles of the techniques and their interest are discussed through their application to different systems.

μMET: A Novel Reusable Microfluidic Chip for Precision Microbial Enumeration Tests

This work describes μMET, a novel microfluidic device for precise microbial enumeration tests (MET), essential in pharmaceutical, cosmetic, and food industries for ensuring microbiological safety standards. The μMET chip, comprising two hydrophobic glass plates, features a 15-μm deep μMET chamber enhanced by nanopillars and air supply units, facilitating both immediate and growth-dependent MET. Experimental results, with E. coli as a model bacterium, demonstrate that μMET provides counting linearity that outperforms traditional hemocytometers. The chip's design mitigates challenges like evaporation and ensures high-resolution imaging, making it a cost-effective and reusable alternative to conventional methods. Notably, bright-field μMET eliminates the need for fluorescent staining, streamlining operations with deep-learning algorithms for bacterial counts. Furthermore, we have developed a high-parallel μMET chip featuring 16 counting chambers, enhancing throughput and accommodating immediate and growth-dependent MET approaches. Its innovative design and adaptability render the μMET chip as a valuable tool for microbiology, medicine, and industry applications.

A perspective on computer vision in biosensing

Computer vision has become a powerful tool in the field of biosensing, aiding in the development of innovative and precise systems for the analysis and interpretation of biological data. This interdisciplinary approach harnesses the capabilities of computer vision algorithms and techniques to extract valuable information from various biosensing applications, including medical diagnostics, environmental monitoring, and food health. Despite years of development, there is still significant room for improvement in this area. In this perspective, we outline how computer vision is applied to raw sensor data in biosensors and its advantages to biosensing applications. We then discuss ongoing research and developments in the field and subsequently explore the challenges and opportunities that computer vision faces in biosensor applications. We also suggest directions for future work, ultimately underscoring the significant impact of computer vision on advancing biosensing technologies and their applications.

Particle Tracking and Micromixing Performance Characterization with a Mobile Device

Strategies to stir and mix reagents in microfluid devices have evolved concomitantly with advancements in manufacturing techniques and sensing. While there is a large array of reported designs to combine and homogenize liquids, most of the characterization has been focused on setups with two inlets and one outlet. While this configuration is helpful to directly evaluate the effects of features and parameters on the mixing degree, it does not portray the conditions for experiments that involve more than two substances required to be subsequently combined. In this work, we present a mixing characterization methodology based on particle tracking as an alternative to the most common approach to measure homogeneity using the standard deviation of pixel intensities from a grayscale image. The proposed algorithm is implemented on a free and open-source mobile application (MIQUOD) for Android devices, numerically tested on COMSOL Multiphysics, and experimentally tested on a bidimensional split and recombine micromixer and a three-dimensional micromixer with sinusoidal grooves for different Reynolds numbers and geometrical features for samples with fluids seeded with red, blue, and green microparticles. The application uses concentration field data and particle track data to evaluate up to eleven performance metrics. Furthermore, with the insights from the experimental and numerical data, a mixing index for particles (mp) is proposed to characterize mixing performance for scenarios with multiple input reagents.