Broad-Band Spectrum, High-Sensitivity Absorbance Spectroscopy in Picoliter Volumes

High-Throughput Absorbance-Activated Droplet Sorting for Engineering Aldehyde Dehydrogenases

Recent decades have seen a dramatic increase in the commercial use of biocatalysts, transitioning from energy-intensive traditional chemistries to more sustainable methods. Current enzyme engineering techniques, such as directed evolution, require the generation and testing of large mutant libraries to identify optimized variants. Unfortunately, conventional screening methods are unable to screen such large libraries in a robust and timely manner. Droplet-based microfluidic systems have emerged as a powerful high-throughput tool for library screening at kilohertz rates. Unfortunately, almost all reported systems are based on fluorescence detection, restricting their use to a limited number of enzyme types that naturally convert fluorogenic substrates or require the use of surrogate substrates. To expand the range of enzymes amenable to evolution using droplet-based microfluidic systems, we present an absorbance-activated droplet sorter that allows droplet sorting at kilohertz rates without the need for optical monitoring of the microfluidic system. To demonstrate the utility of the sorter, we rapidly screen a 105-member aldehyde dehydrogenase library towards D-glyceraldehyde using a NADH mediated coupled assay that generates WST-1 formazan as the colorimetric product. We successfully identify a variant with a 51 % improvement in catalytic efficiency and a significant increase in overall activity across a broad substrate spectrum.

Droplet-based microfluidics and enzyme evolution

Enzymes are widely used as catalysts in the chemical and pharmaceutical industries. While successful in many situations, they must usually be adapted to operate efficiently under nonnatural conditions. Enzyme engineering allows the creation of novel enzymes that are stable at elevated temperatures or have higher activities and selectivities. Current enzyme engineering techniques require the production and testing of enzyme variant libraries to identify members with desired attributes. Unfortunately, traditional screening methods cannot screen such large mutagenesis libraries in a robust and timely manner. Droplet-based microfluidic systems can produce, process, and sort picoliter droplets at kilohertz rates and have emerged as powerful tools for library screening and thus enzyme engineering. We describe how droplet-based microfluidics has been used to advance directed evolution.

Recent advances in droplet sequential monitoring methods for droplet sorting

Droplet microfluidics is an attractive technology to run parallel experiments with high throughput and scalability while maintaining the heterogeneous features of individual samples or reactions. Droplet sorting is utilized to collect the desired droplets based on droplet characterization and in-droplet content evaluation. A proper monitoring method is critical in this process, which governs the accuracy and maximum frequency of droplet handling. Until now, numerous monitoring methods have been integrated in the microfluidic devices for identifying droplets, such as optical spectroscopy, mass spectroscopy, electrochemical monitoring, and nuclear magnetic resonance spectroscopy. In this review, we summarize the features of various monitoring methods integrated into droplet sorting workflow and discuss their suitable condition and potential obstacles in use. We aim to provide a systematic introduction and an application guide for choosing and building a droplet monitoring platform.

Droplet-based μChopper device with a 3D-printed pneumatic valving layer and a simple photometer for absorbance based fructosamine quantification in human serum

The development of microfluidic systems for biological assays presents challenges, particularly in adapting traditional optical absorbance assays to smaller volumes or to microfluidic formats. This often requires assay modification or translation to a fluorescence version, which can be impractical. To address this issue, our group has developed the μChopper device, which uses microfluidic droplet formation as a surrogate for an optical beam chopper, allowing for lock-in analysis and improved limits of detection with both absorbance and fluorescence optics without modifying the optical path length. Here, we have adapted the μChopper to low-cost optics using a light-emitting diode (LED) source and photodiode detector, and we have fabricated the pnuematically valved devices entirely by 3D printing instead of traditional photolithography. Using a hybrid device structure, fluidic channels were made in polydimethylsiloxane (PDMS) by moulding onto a 3D-printed master then bonding to a prefabricated thin layer, and the pneumatic layer was directly made of 3D-printed resin. This hybrid structure allowed an optical slit to be fabricated directly under fluidic channels, with the LED interfaced closely above the channel. Vacuum-operated, normally closed valves provided precise temporal control of droplet formation from 0.6 to 2.0 Hz. The system was validated against the standard plate reader format using a colorimetric fructosamine assay and by quantifying fructosamine in human serum from normal and diabetic patients, where strong correlation was shown. Showing a standard benefit of microfluidics in analysis, the device required 6.4-fold less serum volume for each assay. This μChopper device and lower cost optical system should be applicable to various absorbance based assays in low volumes, and the reliance on inexpensive 3D printers makes it more accessible to users without cleanroom facilities.

Particle Counting Methods Based on Microfluidic Devices

Particle counting serves as a pivotal constituent in diverse analytical domains, encompassing a broad spectrum of entities, ranging from blood cells and bacteria to viruses, droplets, bubbles, wear debris, and magnetic beads. Recent epochs have witnessed remarkable progressions in microfluidic chip technology, culminating in the proliferation and maturation of microfluidic chip-based particle counting methodologies. This paper undertakes a taxonomical elucidation of microfluidic chip-based particle counters based on the physical parameters they detect. These particle counters are classified into three categories: optical-based counters, electrical-based particle counters, and other counters. Within each category, subcategories are established to consider structural differences. Each type of counter is described not only in terms of its working principle but also the methods employed to enhance sensitivity and throughput. Additionally, an analysis of future trends related to each counter type is provided.

Improvement of Sensitivity and Speed of Virus Sensing Technologies Using nm- and μm-Scale Components

Various viral diseases can be widespread and cause severe disruption to global society. Highly sensitive virus detection methods are needed to take effective measures to prevent the spread of viral infection. This required the development of rapid virus detection technology to detect viruses at low concentrations, even in the biological fluid of patients in the early stages of the disease or environmental samples. This review describes an overview of various virus detection technologies and then refers to typical technologies such as beads-based assay, digital assay, and pore-based sensing, which are the three modern approaches to improve the performance of viral sensing in terms of speed and sensitivity.

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.

Ultra-High-Throughput Absorbance-Activated Droplet Sorting for Enzyme Screening at Kilohertz Frequencies

Droplet microfluidics is a valuable method to "beat the odds" in high throughput screening campaigns such as directed evolution, where valuable hits are infrequent and large library sizes are required. Absorbance-based sorting expands the range of enzyme families that can be subjected to droplet screening by expanding possible assays beyond fluorescence detection. However, absorbance-activated droplet sorting (AADS) is currently ∼10-fold slower than typical fluorescence-activated droplet sorting (FADS), meaning that, in comparison, a larger portion of sequence space is inaccessible due to throughput constraints. Here we improve AADS to reach kHz sorting speeds in an order of magnitude increase over previous designs, with close-to-ideal sorting accuracy. This is achieved by a combination of (i) the use of refractive index matching oil that improves signal quality by removal of side scattering (increasing the sensitivity of absorbance measurements); (ii) a sorting algorithm capable of sorting at this increased frequency with an Arduino Due; and (iii) a chip design that transmits product detection better into sorting decisions without false positives, namely a single-layered inlet to space droplets further apart and injections of "bias oil" providing a fluidic barrier preventing droplets from entering the incorrect sorting channel. The updated ultra-high-throughput absorbance-activated droplet sorter increases the effective sensitivity of absorbance measurements through better signal quality at a speed that matches the more established fluorescence-activated sorting devices.

Acoustic sorting of microfluidic droplets at kHz rates using optical absorbance

Droplet microfluidics allows one to address the ever-increasing demand to screen large libraries of biological samples. Absorbance spectroscopy complements the golden standard of fluorescence detection by label free target identification and providing more quantifiable data. However, this is limited by speed and sensitivity. In this paper we increase the speed of sorting by including acoustofluidics, achieving sorting rates of target droplets of 1 kHz. We improved the device design for detection of absorbance using fibre-based interrogation of samples with integrated lenses in the microfluidic PDMS device for focusing and collimation of light. This optical improvement reduces the scattering and refraction artefacts, improving the signal quality and sensitivity. The novel design allows us to overcome limitations based on dielectrophoresis sorting, such as droplet size dependency, material and dielectric properties of samples. Our acoustic activated absorbance sorter removes the need for offset dyes or matching oils and sorts about a magnitude faster than current absorbance sorters.

Plasmonic Amyloid Tactoids

Despite their link to neurodegenerative diseases, amyloids of natural and synthetic sources can also serve as building blocks for functional materials, while possessing intrinsic photonic properties. Here, it is demonstrated that orientationally ordered amyloid fibrils exhibit polarization-dependent fluorescence, and can mechanically align rod-shaped plasmonic nanoparticles codispersed with them. The coupling between the photonic fibrils in liquid crystalline phases and the plasmonic effect of the nanoparticles leads to selective activation of plasmonic extinctions as well as enhanced fluorescence from the hybrid material. These findings are consistent with numerical simulations of the near-field plasmonic enhancement around the nanoparticles. The study provides an approach to synthesize the intrinsic photonic and mechanical properties of amyloid into functional hybrid materials, and may help improve the detection of amyloid deposits based on their enhanced intrinsic luminescence.

UV-Vis Spectra-Activated Droplet Sorting for Label-Free Chemical Identification and Collection of Droplets

We introduce the UV-vis spectra-activated droplet sorter (UVADS) for high-throughput label-free chemical identification and enzyme screening. In contrast to previous absorbance-based droplet sorters that relied on single-wavelength absorbance in the visible range, our platform collects full UV-vis spectra from 200 to 1050 nm at up to 2100 spectra per second. Our custom-built open-source software application, "SpectraSorter," enables real-time data processing, analysis, visualization, and selection of droplets for sorting with any set of UV-vis spectral features. An optimized UV-vis detection region extended the absorbance path length for droplets and allowed for the direct protein quantification down to 10 μM of bovine serum albumin at 280 nm. UV-vis spectral data can distinguish a variety of different chemicals or spurious events (such as air bubbles) that are inaccessible at a single wavelength. The platform is used to measure ergothionase enzyme activity from monoclonal microcolonies isolated in droplets. In a label-free manner, we directly measure the ergothioneine substrate to thiourocanic acid product conversion while tracking the microcolony formation. UVADS represents an important new tool for high-throughput label-free in-droplet chemical analysis.