Model-Independent Phenotyping of C. elegans Locomotion Using Scale-Invariant Feature Transform

Abstract

To uncover the genetic basis of behavioral traits in the model organism C. elegans, a common strategy is to study locomotion defects in mutants. Despite efforts to introduce (semi-)automated phenotyping strategies, current methods overwhelmingly depend on worm-specific features that must be hand-crafted and as such are not generalizable for phenotyping motility in other animal models. Hence, there is an ongoing need for robust algorithms that can automatically analyze and classify motility phenotypes quantitatively. To this end, we have developed a fully-automated approach to characterize C. elegans’ phenotypes that does not require the definition of nematode-specific features. Rather, we make use of the popular computer vision Scale-Invariant Feature Transform (SIFT) from which we construct histograms of commonly-observed SIFT features to represent nematode motility. We first evaluated our method on a synthetic dataset simulating a range of nematode crawling gaits. Next, we evaluated our algorithm on two distinct datasets of crawling C. elegans with mutants affecting neuromuscular structure and function. Not only is our algorithm able to detect differences between strains, results capture similarities in locomotory phenotypes that lead to clustering that is consistent with expectations based on genetic relationships. Our proposed approach generalizes directly and should be applicable to other animal models. Such applicability holds promise for computational ethology as more groups collect high-resolution image data of animal behavior.

Development, structure, and maintenance of C. elegans body wall muscle

“…These programs quantify different aspects of locomotion such as posture, directional changes, curvature of the sinusoidal shape, and velocity. The programs have been used to analyze the locomotion of wild type and various mutants (e.g., Brown et al, 2013;Swierczek et al, 2011;Koren et al, 2015). However, the main focus of these studies has been on neuronal mutants, only a few muscle uncs have been analyzed.…”

Automated high-content phenotyping from the first larval stage till the onset of adulthood of the nematodeCaenorhabditis elegans

“…We adjusted a motility tracking algorithm for C. elegans in M9 buffer for our study 25 . Further details in the calculation of these phenotypes can be found in the related research of the same authors 44,45 .…”

Automated Platform for Long-Term Culture and High-Content Phenotyping of Single C. elegans Worms

“…This code allowed us to obtain 19 phenotypic parameters; however, we utilized only the most significant 6 phenotypes which were sufficient to demonstrate the dose-dependent influence of tetramisole on the growth and motility behavior. More details can be found in our previous work and the prior research that our algorithm was based on 29 and additional research articles of the authors 53,54 .…”