Search bioRxiv⌕ Search

Biology subjects

Pierce, L. X.

Publications and source records attributed to Pierce, L. X..

2 recordsLinked to original sources

High-throughput multi-camera array microscope platform for automated 3D behavioral analysis of freely swimming zebrafish larvae

Understanding the behavioral and morphological dynamics of moving model organisms like the zebrafish larvae requires accurate, high-throughput 3D analysis. However, traditional single-view 2D video tracking fails to capture the full scope of natural 3D movements and postural dynamics. Here, we present a novel high-throughput 24-camera array microscope with a co-designed "mirrored well plate" that allows for snapshot imaging of up to 48 wells over a 118 mm x 82 mm field of view from two orthogonal directions (i.e., a top-view and side-view). Accurate 3D position estimation and tracking is achieved with an efficient machine learning algorithm that scales well to high-throughput measurements. The proposed approach automates parallelized 3D model organism behavioral analysis, providing 3D skeletal tracking, swim bladder morphological dynamics, and kinematics of up to 48 swimming zebrafish larvae at up to several hundred frames per second. The result is an efficient and scalable solution for high-throughput 3D behavioral studies with broad compatibility with standard workflows across laboratories and procedures working with pharmacology, toxicology, and neuroscience.

animal behavior and cognition↗

Forward genetics combined with unsupervised classifications identified zebrafish mutants affecting biliary system formation.

Impaired formation of the biliary network can lead to congenital cholestatic liver diseases; however, the genes responsible for proper biliary system formation and maintenance have not been fully identified. Combining computational network structure analysis algorithms with a zebrafish forward genetic screen, we identified 24 new zebrafish mutants that display impaired intrahepatic biliary network formation. Complementation tests suggested that these 24 mutants affect 24 different genes. We applied unsupervised clustering algorithms to classify the recovered mutants into three classes unbiasedly. Further computational analyses revealed that each of the recovered mutations in these three classes shows a unique effect on node subtype composition and connection property distribution of the intrahepatic biliary network. Besides, we found that most recovered mutations are viable. In those mutant fish, biliary network phenotypes persist into adulthood, which themselves are good animal models to study chronic cholestatic liver diseases. Altogether, this study provides unique genetic and computational toolsets that advance our understanding of the molecular pathways leading to biliary system malformation and cholestatic liver diseases.

genetics↗