High-throughput single-cell antibody secretion quantification and enrichment using droplet microfluidics-based FRET assay.

High-throughput screening and enrichment of antibody-producing cells have many important applications. Herein, we present a droplet microfluidic approach for high-throughput screening and sorting of antibody-secreting cells using a Förster resonance electron transfer (FRET)-based assay. The FRET signal is mediated by the specific binding of the secreted antibody to two fluorescently labeled probes supplied within a droplet. Functional hybridoma cells expressing either membrane-bound or secreted monoclonal antibodies (mAbs), or both, were efficiently differentiated in less than 30 min. The antibody secretion rate by individual hybridoma cells was recorded in the range of 14,000 Abs/min, while the density of membrane-bound fraction was approximately 100 Abs/µm2. Combining the FRET assay with droplet-based single-cell sorting, an 800-fold enrichment of antigen-specific cells was achieved after one round of sorting. The presented system overcomes several key limitations observed in conventional FACS-based screening methods and should be applicable to assaying various other secreted proteins.

Reinforcement Learning for Dynamic Microfluidic Control.

Recent years have witnessed an explosion in the application of microfluidic techniques to a wide variety of problems in the chemical and biological sciences. Despite the many considerable advantages that microfluidic systems bring to experimental science, microfluidic platforms often exhibit inconsistent system performance when operated over extended timescales. Such variations in performance are because of a multiplicity of factors, including microchannel fouling, substrate deformation, temperature and pressure fluctuations, and inherent manufacturing irregularities. The introduction and integration of advanced control algorithms in microfluidic platforms can help mitigate such inconsistencies, paving the way for robust and repeatable long-term experiments. Herein, two state-of-the-art reinforcement learning algorithms, based on Deep Q-Networks and model-free episodic controllers, are applied to two experimental "challenges," involving both continuous-flow and segmented-flow microfluidic systems. The algorithms are able to attain superhuman performance in controlling and processing each experiment, highlighting the utility of novel control algorithms for automated high-throughput microfluidic experimentation.

Chemical and Biological Dynamics Using Droplet-Based Microfluidics.

Recent years have witnessed an increased use of droplet-based microfluidic techniques in a wide variety of chemical and biological assays. Nevertheless, obtaining dynamic data from these platforms has remained challenging, as this often requires reading the same droplets (possibly thousands of them) multiple times over a wide range of intervals (from milliseconds to hours). In this review, we introduce the elemental techniques for the formation and manipulation of microfluidic droplets, together with the most recent developments in these areas. We then discuss a wide range of analytical methods that have been successfully adapted for analyte detection in droplets. Finally, we highlight a diversity of studies where droplet-based microfluidic strategies have enabled the characterization of dynamic systems that would otherwise have remained unexplorable.

Droplet-based microfluidics: enabling impact on drug discovery.

Over the past two decades, the application of microengineered systems in the chemical and biological sciences has transformed the way in which high-throughput experimentation is performed. The ability to fabricate complex microfluidic architectures has allowed scientists to create new experimental formats for processing ultra-small analytical volumes in short periods and with high efficiency. The development of such microfluidic systems has been driven by a range of fundamental features that accompany miniaturization. These include the ability to handle small sample volumes, ultra-low fabrication costs, reduced analysis times, enhanced operational flexibility, facile automation, and the ability to integrate functional components within complex analytical schemes. Herein we discuss the impact of microfluidics in the area of high-throughput screening and drug discovery and highlight some of the most pertinent studies in the recent literature.