Modelling learning in Caenorhabditis elegans chemosensory and locomotive circuitry for T-maze navigation.

Recently, a new type of Caenorhabditis elegans associative learning was reported, where nematodes learn to reach a target arm in an empty T-maze, after they have successfully located reward (food) in the same side arm of a similar, baited, training maze. Here, we present a simplified mathematical model of C. elegans chemosensory and locomotive circuitry that replicates C. elegans navigation in a T-maze and predicts the underlying mechanisms generating maze learning. Based on known neural circuitry, the model circuit responds to food-released chemical cues by modulating motor neuron activity that drives simulated locomotion. We show that, through modulation of interneuron activity, such a circuit can mediate maze learning by acquiring a turning bias, even after a single training session. Simulated nematode maze navigation during training conditions in food-baited mazes and during testing conditions in empty mazes is validated by comparing simulated behaviour with new experimental video data, extracted through the implementation of a custom-made maze tracking algorithm. Our work provides a mathematical framework for investigating the neural mechanisms underlying this novel learning behaviour in C. elegans. Model results predict neuronal components involved in maze and spatial learning and identify target neurons and potential neural mechanisms for future experimental investigations into this learning behaviour.

A journey to 'tame a small metazoan organism', ‡ seen through the artistic eyes of C. elegans researchers.

In the following pages, we share a collection of photos, drawings, and mixed-media creations, most of them especially made for this JoN issue, manifesting C. elegans researchers' affection for their model organism and the founders of the field. This is a celebration of our community's growth, flourish, spread, and bright future. Descriptions provided by the contributors, edited for space. 1.

Three-Dimensional Arenas for the Assessment of Caenorhabditis elegans Behavior.

Caenorhabditis elegans nematode is a well-established model organism in numerous fields of experimental biology. In nature, C. elegans live in a rich three-dimensional (3D) environment. However, their behavior has been assessed almost exclusively on the open, flat surface of nematode growth medium (NGM) plates, the golden standard for C. elegans culture in the laboratory. We present two methods to build 3D behavioral arenas for C. elegans, by casting and by directly 3D-printing NGM hydrogel. The latter is achieved using a highly customized fused deposition modeling (FDM) 3D printer, modified to employ NGM hydrogel as ink. The result is the advancement of 3D complexity of behavioral assays. To demonstrate the potential of our method, we use the 3D-printed arenas to assess C. elegans physical barriers crossing. C. elegans decision to cross physical obstacles is affected by aging, physiological status (i.e., starvation), and prior experience. The 3D-printed structures can be used to spatially confine C. elegans behaviors, that is, egg laying. We consider these findings a decisive step toward characterizing C. elegans 3D behavior, an area long overlooked due to technical constrains. We envision our method of 3D-printing NGM arenas as a powerful tool in behavioral neurogenetics, neuroethology, and invertebrate model organisms' neurobiology.

A maze platform for the assessment of Caenorhabditis elegans behavior and learning.

Mazes are broadly used to investigate animal decision-making and spatial learning. However, they have been sparsely employed to explore C. elegans behavior and training-improved performance. This protocol describes a highly reproducible, low-cost maze platform, made of the standard, agar-based, nematode culturing material. It can be used to reliably assess C. elegans' maze behavior, and we have recently applied this protocol to establish multisensory learning. Limitations include challenges in locomotion tracking and in distinguishing learning formation versus retrieval. For complete details on the use and execution of this protocol, please refer to Gourgou et al. (2021).

Caenorhabditis elegans learning in a structured maze is a multisensory behavior.

We show that C. elegans nematodes learn to associate food with a combination of proprioceptive cues and information on the structure of their surroundings (maze), perceived through mechanosensation. By using the custom-made Worm-Maze platform, we demonstrate that C. elegans young adults can locate food in T-shaped mazes and, following that experience, learn to reach a specific maze arm. C. elegans learning inside the maze is possible after a single training session, it resembles working memory, and it prevails over conflicting environmental cues. We provide evidence that the observed learning is a food-triggered multisensory behavior, which requires mechanosensory and proprioceptive input, and utilizes cues about the structural features of nematodes' environment and their body actions. The CREB-like transcription factor and dopamine signaling are also involved in maze performance. Lastly, we show that the observed aging-driven decline of C. elegans learning ability in the maze can be reversed by starvation.

A mathematical and computational model of the calcium dynamics in Caenorhabditis elegans ASH sensory neuron.

We propose a mathematical and computational model that captures the stimulus-generated Ca2+ transients in the C. elegans ASH sensory neuron. The rationale is to develop a tool that will enable a cross-talk between modeling and experiments, using modeling results to guide targeted experimental efforts. The model is built based on biophysical events and molecular cascades known to unfold as part of neurons' Ca2+ homeostasis mechanism, as well as on Ca2+ signaling events. The state of ion channels is described by their probability of being activated or inactivated, and the remaining molecular states are based on biochemically defined kinetic equations or known biochemical motifs. We estimate the parameters of the model using experimental data of hyperosmotic stimulus-evoked Ca2+ transients detected with a FRET sensor in young and aged worms, unstressed and exposed to oxidative stress. We use a hybrid optimization method composed of a multi-objective genetic algorithm and nonlinear least-squares to estimate the model parameters. We first obtain the model parameters for young unstressed worms. Next, we use these values of the parameters as a starting point to identify the model parameters for stressed and aged worms. We show that the model, in combination with experimental data, corroborates literature results. In addition, we demonstrate that our model can be used to predict ASH response to complex combinations of stimulation pulses. The proposed model includes for the first time the ASH Ca2+ dynamics observed during both "on" and "off" responses. This mathematical and computational effort is the first to propose a dynamic model of the Ca2+ transients' mechanism in C. elegans neurons, based on biochemical pathways of the cell's Ca2+ homeostasis machinery. We believe that the proposed model can be used to further elucidate the Ca2+ dynamics of a key C. elegans neuron, to guide future experiments on C. elegans neurobiology, and to pave the way for the development of more mathematical models for neuronal Ca2+ dynamics.

Rate of recovery from perturbations as a means to forecast future stability of living systems.

Anticipating critical transitions in complex ecological and living systems is an important need because it is often difficult to restore a system to its pre-transition state once the transition occurs. Recent studies demonstrate that several indicators based on changes in ecological time series can indicate that the system is approaching an impending transition. An exciting question is, however, whether we can predict more characteristics of the future system stability using measurements taken away from the transition. We address this question by introducing a model-less forecasting method to forecast catastrophic transition of an experimental ecological system. The experiment is based on the dynamics of a yeast population, which is known to exhibit a catastrophic transition as the environment deteriorates. By measuring the system's response to perturbations prior to transition, we forecast the distance to the upcoming transition, the type of the transition (i.e., catastrophic/non-catastrophic) and the future equilibrium points within a range near the transition. Experimental results suggest a strong potential for practical applicability of this approach for ecological systems which are at risk of catastrophic transitions, where there is a pressing need for information about upcoming thresholds.

Synaptic Impairment and Robustness of Excitatory Neuronal Networks with Different Topologies.

Synaptic deficiencies are a known hallmark of neurodegenerative diseases, but the diagnosis of impaired synapses on the cellular level is not an easy task. Nonetheless, changes in the system-level dynamics of neuronal networks with damaged synapses can be detected using techniques that do not require high spatial resolution. This paper investigates how the structure/topology of neuronal networks influences their dynamics when they suffer from synaptic loss. We study different neuronal network structures/topologies by specifying their degree distributions. The modes of the degree distribution can be used to construct networks that consist of rich clubs and resemble small world networks, as well. We define two dynamical metrics to compare the activity of networks with different structures: persistent activity (namely, the self-sustained activity of the network upon removal of the initial stimulus) and quality of activity (namely, percentage of neurons that participate in the persistent activity of the network). Our results show that synaptic loss affects the persistent activity of networks with bimodal degree distributions less than it affects random networks. The robustness of neuronal networks enhances when the distance between the modes of the degree distribution increases, suggesting that the rich clubs of networks with distinct modes keep the whole network active. In addition, a tradeoff is observed between the quality of activity and the persistent activity. For a range of distributions, both of these dynamical metrics are considerably high for networks with bimodal degree distribution compared to random networks. We also propose three different scenarios of synaptic impairment, which may correspond to different pathological or biological conditions. Regardless of the network structure/topology, results demonstrate that synaptic loss has more severe effects on the activity of the network when impairments are correlated with the activity of the neurons.

Chemically induced oxidative stress affects ASH neuronal function and behavior in C. elegans.

Oxidative stress (OS) impact on a single neuron's function in vivo remains obscure. Using C. elegans as a model organism, we report the effect of paraquat (PQ)-induced OS on wild type worms on the function of the ASH polymodal neuron. By calcium (Ca2+) imaging, we quantified ASH activation upon stimulus delivery. PQ-treated worms displayed higher maximum depolarization (peak of the Ca2+ transients) compared to untreated animals. PQ had a similar effect on the ASH neuron response time (rising slope of the Ca2+ transients), except in very young worms. OS effect on ASH was partially abolished in vitamin C-treated worms. We performed octanol and osmotic avoidance tests, to investigate the OS effect on ASH-dependent behaviors. PQ-treated worms have enhanced avoidance behavior compared to untreated ones, suggesting that elevated ASH Ca2+ transients result in enhanced ASH-mediated behavior. The above findings suggest a possible hormetic effect of PQ, as a factor inducing mild oxidative stress. We also quantified locomotion parameters (velocity, bending amplitude), which are not mediated by ASH activation. Bending amplitude did not differ significantly between treated and untreated worms; velocity in older adults decreased. The differential effect of OS on behavioral patterns may mirror a selective impact on the organism's neurons.

On-Demand Isolation and Manipulation of C. elegans by In Vitro Maskless Photopatterning.

Caenorhabditis elegans (C. elegans) is a model organism for understanding aging and studying animal behavior. Microfluidic assay techniques have brought widespread advances in C. elegans research; however, traditional microfluidic assays such as those based on soft lithography require time-consuming design and fabrication cycles and offer limited flexibility in changing the geometric environment during experimentation. We present a technique for maskless photopatterning of a biocompatible hydrogel on an NGM (Agar) substrate, enabling dynamic manipulation of the C. elegans culture environment in vitro. Maskless photopatterning is performed using a projector-based microscope system largely built from off-the-shelf components. We demonstrate the capabilities of this technique by building micropillar arrays during C. elegans observation, by fabricating free-floating mechanisms that can be actuated by C. elegans motion, by using freehand drawing to isolate individual C. elegans in real time, and by patterning arrays of mazes for isolation and fitness testing of C. elegans populations. In vitro photopatterning enables rapid and flexible design of experiment geometry as well as real-time interaction between the researcher and the assay such as by sequential isolation of individual organisms. Future adoption of image analysis and machine learning techniques could be used to acquire large datasets and automatically adapt the assay geometry.

Acute thermal stress and various heavy metals induce tissue-specific pro- or anti-apoptotic events via the p38-MAPK signal transduction pathway in Mytilus galloprovincialis (Lam.).

We investigated the effects of various heavy metals such as copper, zinc and cadmium, as well as acute thermal stress, on the signalling mechanisms involved in the protection and/or apoptosis of Mytilus galloprovincialis mantle and gill tissues. The results of our studies revealed that mantle and gill tissues differentially respond to the stressful stimuli examined. In the mantle tissue, 1 micromol l(-1) Cu2+ and 50 micromol l(-1) Zn2+ induced a transient p38-MAPK activation, whereas 1 micromol l(-1) Cd2+ induced a biphasic profile of the kinase phosphorylation with maximal values at 15 and 120 min of treatment, respectively. Furthermore, 1 micromol l(-1) SB203580 abolished the Cu2+-induced kinase phosphorylation. In gills, both Cu2+ and Zn2+ induced a considerably higher p38-MAPK activation, which remained elevated for at least 60 min, whereas Cd2+ induced a maximal kinase activation within 60 min of treatment. Hypothermia (4 degrees C) induced a moderate kinase phosphorylation (maximised at 30 min), whereas hyperthermia (30 degrees C) induced a rapid (within 15 min) p38-MAPK phosphorylation that remained considerably above basal levels for at least 2 h. Our studies on the synergistic effect of hyperthermia and Cu2+ revealed that these two stressful stimuli are additive in the mantle tissue, inducing an almost double p38-MAPK activation. Further studies on the involvement of the p38-MAPK signalling pathway in tissue-specific pro- or anti-apoptotic events revealed that identical stressful stimuli possibly lead to apoptotic death via the caspase-3 activation in the mantle tissue and to anti-apoptotic events possibly via the induction of Hsp70 overexpression in the gill tissue.