An automatic measurement method for the response of Caenorhabditis elegans to chemicals

Technol Health Care. 2024 Apr 25. doi: 10.3233/THC-248013. Online ahead of print.

Abstract

Background: Caenorhabditis elegans is a widely used model animal. Chemotaxis assay is one of the experiments that study the effects of different chemicals on nematodes. It is mainly used to study the effects of different chemicals on the perception behavior of nematodes. By conducting this experiment, not only can the neurotoxicity of chemicals be reflected, but also the impact of chemicals on physiological functions regulated by the nervous system, such as nematode feeding behavior and basic motor ability.

Objective: The experiment of detecting the response of nematode to chemicals is also a common method of chemical toxicity testing based on nematode models. In the analysis of worm tendency behavior, manual operations are generally used. Manually processing a large number of worms under a microscope is very time-consuming and labor-intensive. The current quantitative methods for nematode chemotaxis experiments are not only time-consuming and labor-intensive, but also biased in experimental results due to differences in judgment standards among experimenters. The automatic and efficient quantification method for nematode chemotaxis experiments is a very important technical difficulty in the field of nematode experiments.

Methods: Here, we have designed an automatic quantification method for nematode chemotaxis experiments by incorporating image acquisition and processing techniques into the nematode experiment.

Results: The experimental results show that the Pearson correlation coefficient between manual and automatic counting results is 0.978.

Conclusion: This proves the effectiveness of our method. Applying the automatic measurement method to replace manual counting by the experimenter can improve work efficiency, and reduce errors in human counting operations.

Keywords: C. elegans; automatic quantification; behavior analysis; image processing.