Changes in Postural Syntax Characterize Sensory Modulation and Natural Variation of C. elegans Locomotion

Abstract

Locomotion is driven by shape changes coordinated by the nervous system through time; thus, enumerating an animal's complete repertoire of shape transitions would provide a basis for a comprehensive understanding of locomotor behaviour. Here we introduce a discrete representation of behaviour in the nematode C. elegans. At each point in time, the worm’s posture is approximated by its closest matching template from a set of 90 postures and locomotion is represented as sequences of postures. The frequency distribution of postural sequences is heavy-tailed with a core of frequent behaviours and a much larger set of rarely used behaviours. Responses to optogenetic and environmental stimuli can be quantified as changes in postural syntax: worms show different preferences for different sequences of postures drawn from the same set of templates. A discrete representation of behaviour will enable the use of methods developed for other kinds of discrete data in bioinformatics and language processing to be harnessed for the study of behaviour.

Visualizing Calcium Flux in Freely Moving Nematode Embryos

“…In neurons, functional data will help to define the relationships among activity, process outgrowth, and synaptogenesis. While adult locomotion has been the focus of much research (43)(44)(45), movement of the embryo remains almost completely unexplored. Detailed behavioral characterization of the embryo in the post-twitching regime will help focus future calcium imaging experiments to periods when neural circuits are wiring up and coming online.…”

In vitro and in vivo defensive effect of probiotic LAB against Pseudomonas aeruginosa using Caenorhabditis elegans model

“…In addition, 2 clinical studies have been conducted to assess the safety of probiotics in small groups of specific immunocompromised patients (e.g. patients with HIV infection), and the findings of these studies support the safety of probiotics consumed by such groups [74–76] Immunocompromised treated with – ( Pediacoccus pentosaceus, Leuconostoc mesenteroides, Lactobacillus paracasei subspecies paracasei F19, Lactobacillus plantarum , LGG, L. johnsonii LA 1, VSL 3, L. plantarum 299V (liver transplant), S. boulardii (HIV) – Absence of toxicity were determined [77–79] previously likewise pregnant women – (LGG, LC705, Bb99, and Propionibacterium freudenreichii spp shermanii) Absence of toxicity [80], Inflammatory bowel disease – ( Lactobaccillus acidophilus LA-5, Lactobacillus delbrueckii subsp. bulgaricus LBY-27, Bifidobacterium animalis subsp.…”

Inactivity periods and postural change speed can explain atypical postural change patterns of Caenorhabditis elegans mutants

“…While quantification of the transition frequencies between postural states is a powerful approach for computationally analyzing animal behavior, our results demonstrate that even very atypical state transition patterns can result from simple factors. Analyses of inactivity periods and postural change speeds both require consideration of time duration; the compression of state time duration abolishes their effects in the analysis [18]. To effectively detect strains that show truly interesting behavior, e.g., strains whose neural circuits encode special decision-making criteria, computational analyses of animal behavior must be accompanied by evaluation of the effects of more “trivial” factors such as overall change in speed (of course, we note that these trivial factors themselves would also provide many insights into worm behavior).…”

“…Second, K -means clustering was applied to the pooled distribution. The model parameters were estimated by the Lloyd algorithm [25] with initial parameters estimated by K -means++ algorithm [24], where K was set to 90 (a parameter used in a previous study [18]) or 44, 95, or 459 (parameters estimated by the GMM-based method earlier). Third, after the convergence of the Lloyd algorithm, a centroid of each cluster was regarded as a postural state.…”

“…Whereas the behavioral motif approach detects atypical behaviors as continuous stretches, the postural state approach detects those that rather reflect worms’ prompt reaction, which might reflect their decision-making criteria, for instance. As a pioneering work, Schwarz et al used K -means clustering to bin worm postures, and observed condition-specific state transition patterns [18]. However, the factors underlying atypical worm postural movement patterns were not sufficiently dissected, particularly because postures and transition patterns between them should not be independent from each other.…”