WormTracer: A precise method for worm posture analysis using temporal continuity

Abstract

AbstractThis study introduces WormTracer, a novel algorithm designed to accurately quantify temporal evolution of worm postures. Unlike conventional methods that analyze individual images separately, WormTracer estimates worm centerlines within a sequence of images concurrently. This process enables the resolution of complex postures that are difficult to assess when treated as isolated images. The centerlines obtained through WormTracer exhibit higher accuracy compared to those acquired using conventional methods. By applying principal component analysis to the centerlines obtained by WormTracer, we successfully generated new eigenworms, a basic set of postures, that enables a more precise representation of worm postures than existing eigenworms.Author summaryC. elegansis a valuable model organism for comprehensive understanding of genes, neurons and behavior. Quantification of behavior is essential for clarifying these relationships, and posture information plays a crucial role in the analyses. However, accurately quantifying the posture ofC. elegansfrom video images of worms is challenging, and while various methods have been developed to date, they have their own limitations.In this study, we developed an analytical tool called WormTracer, which can obtain worm centerlines more accurately than conventional methods, even when worms assume complex postures. Using this tool, we successfully obtained new eigenworms, basis postures of a worm, that can more accurately reproduce various postures than conventional eigenworms. WormTracer and the new eigenworms will be valuable assets for future quantitative studies on worm locomotion and sensorimotor behaviors.