The nematode Caenorhabditis elegans has become an essential model organism in neuroscience research because of its stereotyped anatomy, relevance to human biology, and capacity for genetic manipulation. To solve the intrinsic challenges associated with performing manual operations on C. elegans, many automated chip designs based on immobilization-imaging-release approaches have been proposed. These designs are prone to limitations such as the exertion of physical stress on the worms and limited throughput. In this work, a continuous-flow, high-throughput, automated C. elegans analyzer based on droplet encapsulation and real-time image processing was developed to analyze fluorescence expression in worms. To demonstrate its capabilities, two strains of C. elegans nematodes with different levels of expression of green fluorescent protein (GFP) were first mixed in a buffer solution. The worms were encapsulated in water-in-oil droplets to restrict random locomotion. The droplets were closely packed in a two-layer polydimethylsiloxane (PDMS) platform and were flowed through a narrow straight channel, in which a region of interest (ROI) was defined and continuously recorded by a frame acquisition device. Based on the number of pixels counted in the selected color range, our custom software analyzed GFP expression to differentiate between two strains with nearly 100% accuracy and a throughput of 0.5 seconds/worm.
Yan, Yuanjun, Daryl Boey, Li Theng Ng, Jan Gruber, Andrew Bettiol, Nitish V. Thakor, Chia-Hung Chen
Biosensors and Bioelectronics