A GNN-based model for capturing spatio-temporal changes in locomotion behaviors of aging C. elegans

Ye Yuan; Kuankuan Xin; Jian Liu; Peng Zhao; Man Pok Lu; Yuner Yan; Yuchen Hu; Hong Huo; Zhaoyu Li; Tao Fang

doi:10.1016/j.compbiomed.2023.106694

A GNN-based model for capturing spatio-temporal changes in locomotion behaviors of aging C. elegans

Comput Biol Med. 2023 Mar:155:106694. doi: 10.1016/j.compbiomed.2023.106694. Epub 2023 Feb 16.

Authors

Ye Yuan¹, Kuankuan Xin², Jian Liu³, Peng Zhao³, Man Pok Lu², Yuner Yan², Yuchen Hu², Hong Huo⁴, Zhaoyu Li⁵, Tao Fang⁶

Affiliations

¹ Institute of Machine Intelligence, University of Shanghai for Science and Technology, Shanghai, 200093, China; Department of Automation, Shanghai Jiao Tong University, Shanghai, 200240, China; Key Laboratory of System Control and Information Processing, Ministry of Education, China.
² Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia.
³ Department of Automation, Shanghai Jiao Tong University, Shanghai, 200240, China; Key Laboratory of System Control and Information Processing, Ministry of Education, China.
⁴ Department of Automation, Shanghai Jiao Tong University, Shanghai, 200240, China; Key Laboratory of System Control and Information Processing, Ministry of Education, China. Electronic address: huohong@sjtu.edu.cn.
⁵ Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia. Electronic address: zhaoyu.li@uq.edu.au.
⁶ Department of Automation, Shanghai Jiao Tong University, Shanghai, 200240, China; Key Laboratory of System Control and Information Processing, Ministry of Education, China. Electronic address: tfang@sjtu.edu.cn.

PMID: 36812812
DOI: 10.1016/j.compbiomed.2023.106694

Abstract

Investigating the locomotion of aging C. elegans is an important way for understanding the basic mechanisms behind age-related changes in organisms. However, the locomotion of aging C. elegans is often quantified using insufficient physical variables, which makes it challenging to capture essential dynamics. To study changes in the locomotion pattern of aging C. elegans, we developed a novel data-driven model based on graph neural networks, in which the C. elegans body is modeled as a long chain with interactions within and between adjacent segments, and their interactions are described by high-dimensional variables. Using this model, we discovered that each segment of the C. elegans body generally tends to maintain its locomotion, i.e., tries to keep the bending angle unchanged, and expects to change the locomotion of the adjacent segments. The ability to maintain its locomotion strengthens with age. Besides, a subtle distinguish in the changes in the locomotion pattern of C. elegans at various aging stages were observed. Our model is anticipated to provide a data-driven method for quantifying the changes in the locomotion pattern of aging C. elegans and for mining the underlying causes of these changes.

Keywords: Age-related locomotion change; Bending angle prediction; C. elegans modeling; Graph neural network; Locomotion pattern.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Aging
Animals
Caenorhabditis elegans*
Locomotion*
Neural Networks, Computer