Miniaturization of the Whole Process of Protein Crystallographic Analysis by a Microfluidic Droplet Robot: From Nanoliter-Scale Purified Proteins to Diffraction-Quality Crystals

Optical-based microbubble for on-demand droplet release from static droplet array (SDA) for dispensing one droplet into one tube

Static droplet array (SDA) is a pivotal tool for high-capacity screening assays, yet extraction and collection the target droplets that contain unique analytes or cells from the SDA remains one major technical bottleneck that limits its broader application. Here we present an optical-based on-demand droplet release (OODR) system by incorporating a 1064 nm laser-responsive indium tin oxide (ITO) layer into a chamber array-based droplet microfluidic chip. By focusing the 1064 nm laser onto the ITO layer, microbubbles can be created via local heating to selectively push-out the droplets from the chamber. Then the released droplet is readily exported in a one-droplet-one-tube (ODOT) manner by the inherent capillary force into pipette tip. Releasing of the droplets containing fluorescein sodium demonstrated ∼100% successful rate (9 out of 6400 droplets were successfully released) and low residual (only ∼5% of the droplet volume remains in the chamber). White or fluorescence image-based releasing of single-cell-droplets directly after cell loading or multi-cells-droplets derived from on-chip single-cell cultivation for both E. coli and yeast cells further demonstrated the wide applicability of OODR. The present system is user-friendly and has the potential to be applied in various high-throughput screening assays, including single molecule/cell analysis, drug screening, and phenotype-based cell sorting.

Evaporation of Saline Droplets on a Superhydrophobic Substrate: Formation of Crystal Shell and "Legs"

We studied the evaporation-driven crystallization in the droplets of sodium acetate anhydrous (CH₃COONa) aqueous solution, which were deposited on superhydrophobic substrates. The results reveal distinct crystallization behaviors between saturated and unsaturated droplets under identical experimental conditions. Specifically, unsaturated droplets could form a quasi-spherical crystal shell on the superhydrophobic substrate, while saturated droplets could develop crystal legs between the droplet and substrate when the crystal shell formed. Subsequently, the saturated droplet was lifted off the substrate by the growing crystal legs. The formation of crystal shell was closely associated with the evaporation from the droplet surface and the internal convection inside the droplet. The formation of crystal legs was induced by the heterogeneous nucleation effect caused by the substrate of SiO₂ nanoparticles. These findings provide valuable insights into regulating the morphology of salt crystallization through adjustments in salt solution concentration and substrate surface structure.

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.

A 3D-printed robotic system for fully automated multiparameter analysis of drinkable water samples

This work describes a 3D-printed robotic system named RSAWA (robotic system for automatic water analysis) for fully automated water analysis. RSAWA consists of a robotic arm coupled to a syringe pump, temperature and conductivity sensors, a low-cost webcam as colorimetric detector, and a 96-well microplate placed on a 3D-printed platform. The robotic system is controlled by software and it performs all analytical procedures. RSAWA was applied to measure conductivity (CDT), pH, total alkalinity (TA), total hardness (TH), chloride (Cl^-), nitrite (NO₂^-), total dissolved phosphorus (TP), and total iron (TI) in drinkable water samples. A simple circuit was designed for conductivity determinations, while colorimetric pH determinations were carried out using Hue values extracted from digital images and a pH universal indicator. HSV histograms were used to calculate Pearson's correlation coefficients, allowing the construction of accurate titration curves. In addition to achieving sample throughputs of 112 h^-1 for TA and TH determinations and 92 h^-1 for Cl^- determinations, RSAWA produced 99.5% less waste than the corresponding reference methods during titrations. Colorimetric measurements were performed through RGB vector norms calculated from digital images were used as analytical signals. Limits of quantification (μg L^-1) were 6.83, 13.0 and 1.5 mg L^-1 for NO₂^-, TP, and TI determinations, respectively. Sample throughputs (samples h^-1) were 83 for NO₂^- and TP and 72 for TI with a 98.5% reduction in waste generation. Thus, RSAWA is a low-cost, feasible, and environmentally friendly alternative to quickly and accurately determine several chemical and physicochemical parameters in aqueous samples.

Room-temperature crystallography using a microfluidic protein crystal array device and its application to protein-ligand complex structure analysis

Room-temperature (RT) protein crystallography provides significant information to elucidate protein function under physiological conditions. In particular, contrary to typical binding assays, X-ray crystal structure analysis of a protein–ligand complex can determine the three-dimensional (3D) configuration of its binding site. This allows the development of effective drugs by structure-based and fragment-based (FBDD) drug design. However, RT crystallography and RT crystallography-based protein–ligand complex analyses require the preparation and measurement of numerous crystals to avoid the X-ray radiation damage. Thus, for the application of RT crystallography to protein–ligand complex analysis, the simultaneous preparation of protein–ligand complex crystals and sequential X-ray diffraction measurement remain challenging. Here, we report an RT crystallography technique using a microfluidic protein crystal array device for protein–ligand complex structure analysis. We demonstrate the microfluidic sorting of protein crystals into microwells without any complicated procedures and apparatus, whereby the sorted protein crystals are fixed into microwells and sequentially measured to collect X-ray diffraction data. This is followed by automatic data processing to calculate the 3D protein structure. The microfluidic device allows the high-throughput preparation of the protein–ligand complex solely by the replacement of the microchannel content with the required ligand solution. We determined eight trypsin–ligand complex structures for the proof of concept experiment and found differences in the ligand coordination of the corresponding RT and conventional cryogenic structures. This methodology can be applied to easily obtain more natural structures. Moreover, drug development by FBDD could be more effective using the proposed methodology.

Room temperature protein crystallography and its application to protein–ligand complex structure analysis was demonstrated using a microfluidic protein crystal array device.

Real-Time Measurement of Protein Crystal Growth Rates within the Microfluidic Device to Understand the Microspace Effect

Preparation of high-quality protein crystals is a major challenge in protein crystallography. Natural convection is considered to be an uncontrollable factor of the crystallization process at the ground level as it disturbs the concentration gradient around the growing crystal, resulting in lower-quality crystals. A microfluidic environment expects an imitated microgravity environment because of the small Gr number. However, the mechanism of protein crystal growth in the microfluidic device was not elucidated due to limitations in measuring the crystal growth process within the device. Here, we demonstrate the real-time measurement of protein crystal growth rates within the microfluidic devices by laser confocal microscopy with differential interference contrast microscopy (LCM-DIM) at the nanometer scale. We confirmed the normal growth rates in the 20 and 30 μm-deep microfluidic device to be 42.2 and 536 nm/min, respectively. In addition, the growth rate of crystals in the 20 μm-deep microfluidic device was almost the same as that reported in microgravity conditions. This phenomenon may enable the development of more accessible alternatives to the microgravity environment of the International Space Station.