High-throughput BioSorter quantification of relative mitochondrial content and membrane potential in living Caenorhabditis elegans.

Mitochondrial respiratory chain disease is caused by a wide range of individually rare genetic disorders that impair cellular energy metabolism. While fluorescence microscopy analysis of nematodes fed MitoTracker Green (MTG) and tetramethylrhodamine ethyl ester (TMRE) can reliably quantify relative mitochondrial density and membrane potential, respectively, in C. elegans models of mitochondrial dysfunction, it is a tedious process with limitations in the number and age of animals that can be studied. A novel, large particle, flow cytometry-based method reported here accelerates and automates the relative quantitation of mitochondrial physiology in nematode populations. Relative fluorescence profiles of nematode populations co-labeled with MTG and TMRE were obtained and analyzed by BioSorter (Union Biometrica). Variables tested included genetic mutation (wild-type N2 Bristol versus nuclear-encoded respiratory chain complex I mutant gas-1(fc21) worms), animal age (day 1 versus day 4 adults), classical respiratory chain inhibitor and uncoupler effects (oligomycin, FCCP), and pharmacologic therapy duration (24h versus 96h treatments with glucose or nicotinic acid). A custom MATLAB script, which can be run on any computer with MATLAB runtime, was written to automatically quantify and analyze results in large animal populations. BioSorter analysis independently validated relative MTG and TMRE changes that we had previously performed by fluorescence microscopy in a variety of experimental conditions, with notably greater animal population sizes and substantially reduced experimental time. Older, fragile animal populations that are difficult to study by microscopy approaches were readily amenable to analysis with the BioSorter method. Overall, this high-throughput method enables efficient relative quantitation of in vivo mitochondrial physiology over time in a living animal in response to gene mutations and candidate therapies, which can be used to accelerate the translation of basic research into optimization of clinical therapies for mitochondrial disease.