High content analysis enables high-throughput nematicide discovery screening for measurement of viability and movement behavior in response to natural product samples.

Abstract

Historically, monitoring nematode movement and mortality in response to various potential nematicide treatments usually involved tedious manual microscopic analysis. High-content analysis instrumentation enables rapid and high-throughput collection of experimental data points on large numbers of individual worms simultaneously. The high-throughput platform outlined here should accelerate discovery of unique classes and types of promising lead molecules and sample types to control these plant pests. Also, the ability to automate the data analysis pipeline rather than relying on manual scoring reduces a potential source of data variance. Here we describe a high-throughput process based on high-content imaging. We demonstrate the use of time-lapse image acquisition to measure movement, and viability staining to confirm nematode mortality (versus paralysis) in targeted plant-pathogenic nematodes. We present screening results from a microbial-exudate library generated from approximately 2,300 microbial fermentations that demonstrate the robustness of this high-throughput process. The described methods should be applicable to other relevant nematode parasites with human, crop, or animal hosts.