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The nematode Caenorhabditis elegans is a widely used model organism for neuroscience. Although its nervous system has been fully reconstructed, the physiological bases of single-neuron functioning are still poorly explored. Recently, many efforts have been dedicated to measuring signals from C. elegans neurons, revealing a rich repertoire of dynamics, including bistable responses, graded responses, and action potentials. Still, biophysical models able to reproduce such a broad range of electrical responses lack. Realistic electrophysiological descriptions started to be developed only recently, merging gene expression data with electrophysiological recordings, but with a large variety of cells yet to be modeled. In this work, we contribute to filling this gap by providing biophysically accurate models of six classes of C. elegans neurons, the AIY, RIM, and AVA interneurons, and the VA, VB, and VD motor neurons. We test our models by comparing computational and experimental time series and simulate knockout neurons, to identify the biophysical mechanisms at the basis of inter and motor neuron functioning. Our models represent a step forward toward the modeling of C. elegans neuronal networks and virtual experiments on the nematode nervous system., Competing Interests: Viola Folli is an employee and scientific advisor of D-tails s.r.l. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2024 Nicoletti et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Amphid wing "C" (AWC) neurons are among the most important and studied neurons of the nematode Caenorhabditis elegans. In this work, we unify the existing electrical and intracellular calcium dynamics descriptions to obtain a biophysically accurate model of olfactory transduction in AWC ON neurons. We study the membrane voltage and the intracellular calcium dynamics at different exposure times and odorant concentrations to grasp a complete picture of AWC ON functioning. Moreover, we investigate the complex cascade of biochemical processes that allow AWC activation upon odor removal. We analyze the behavior of the different components of the models and, by suppressing them selectively, we extrapolate their contribution to the overall neuron response and study the resilience of the dynamical system. Our results are all in agreement with the available experimental data. Therefore, we provide an accurate mathematical and biophysical model for studying olfactory signal processing in C. elegans., (© 2023 the author(s), published by De Gruyter.)

Studying the binding processes of G protein-coupled receptors (GPCRs) proteins is of particular interest both to better understand the molecular mechanisms that regulate the signaling between the extracellular and intracellular environment and for drug design purposes. In this study, we propose a new computational approach for the identification of the binding site for a specific ligand on a GPCR. The method is based on the Zernike polynomials and performs the ligand-GPCR association through a shape complementarity analysis of the local molecular surfaces. The method is parameter-free and it can distinguish, working on hundreds of experimentally GPCR-ligand complexes, binding pockets from randomly sampled regions on the receptor surface, obtaining an Area Under ROC curve of 0.77. Given its importance both as a model organism and in terms of applications, we thus investigated the olfactory receptors of the C. elegans, building a list of associations between 21 GPCRs belonging to its olfactory neurons and a set of possible ligands. Thus, we can not only carry out rapid and efficient screenings of drugs proposed for GPCRs, key targets in many pathologies, but also we laid the groundwork for computational mutagenesis processes, aimed at increasing or decreasing the binding affinity between ligands and receptors., (© 2021. The Author(s).)

Chemosensory receptors play a crucial role in distinguishing the wide range of volatile/soluble molecules by binding them with high accuracy. Chemosensation is the main sensory modality in organisms lacking long-range sensory mechanisms like vision/hearing. Despite its low number of sensory neurons, the nematode Caenorhabditis elegans possesses several chemosensory receptors, allowing it to detect about as many odorants as mammals. Here, we show that C. elegans displays attraction towards urine samples of women with breast cancer, avoiding control ones. Behavioral assays on animals lacking AWC sensory neurons demonstrate the relevance of these neurons in sensing cancer odorants: calcium imaging on AWC increases the accuracy of the discrimination (97.22%). Also, chemotaxis assays on animals lacking GPCRs expressed in AWC allow to identify receptors involved in binding cancer metabolites, suggesting that an alteration of a few metabolites is sufficient for the cancer discriminating behavior of C. elegans, which may help identify a fundamental fingerprint of breast cancer., (© 2021. The Author(s).)

The molecular mechanisms regulating the complex sensory system that underlies olfaction are still not completely understood. The compounds formed from the interaction of Olfactory Receptors (ORs) with volatile molecules play a crucial role in producing the sense of olfaction. Therefore, it is necessary to investigate the binding mechanisms between these receptors and small ligands. In this work, we focus our attention on C.elegans, this is a particularly suitable model organism because it is characterized by a nervous system composed of only 302 neurons. To study olfaction in C.elegans, we select 21 ORs from its olfactory neurons, and present a pipeline, consisting of several computational methods, with the aim of proposing a set of possible candidates for binding the selected C.elegans ORs. This pipeline introduces an approach based on the selection of templates, and threading, that takes advantage of the structural redundancy among membrane receptors. This procedure is widely replicable because it is based on algorithms that are publicly available and are freely hosted on institutional servers., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

C. elegans neuronal system constitutes the ideal framework for studying simple, yet realistic, neuronal activity, since the whole nervous system is fully characterized with respect to the exact number of neurons and the neuronal connections. Most recent efforts are devoted to investigate and clarify the signal processing and functional connectivity, which are at the basis of sensing mechanisms, signal transmission, and motor control. In this framework, a refined modelof whole neuron dynamics constitutes a key ingredient to describe the electrophysiological processes, both at thecellular and at the network scale. In this work, we present Hodgkin-Huxley-based models of ion channels dynamics black, built on data available both from C. elegans and from other organisms, expressing homologous channels. We combine these channel models to simulate the electrical activity oftwo among the most studied neurons in C. elegans, which display prototypical dynamics of neuronal activation, the chemosensory AWCON and the motor neuron RMD. Our model properly describes the regenerative responses of the two cells. We analyze in detail the role of ion currents, both in wild type and in in silico knockout neurons. Moreover, we specifically investigate the behavior of RMD, identifying a heterogeneous dynamical response which includes bistable regimes and sustained oscillations. We are able to assess the critical role of T-type calcium currents, carried by CCA-1 channels, and leakage currents in the regulation of RMD response. Overall, our results provide new insights in the activity of key C. elegans neurons. The developed mathematical framework constitute a basis for single-cell and neuronal networks analyses, opening new scenarios in the in silico modeling of C. elegans neuronal system., Competing Interests: The authors have declared that no competing interests exist.

C. elegans neuronal system constitutes the ideal framework for studying simple, yet realistic, neuronal activity, since the whole nervous system is fully characterized with respect to the exact number of neurons and the neuronal connections. Most recent efforts are devoted to investigate and clarify the signal processing and functional connectivity, which are at the basis of sensing mechanisms, signal transmission, and motor control. In this framework, a refined modelof whole neuron dynamics constitutes a key ingredient to describe the electrophysiological processes, both at thecellular and at the network scale. In this work, we present Hodgkin-Huxley-based models of ion channels dynamics black, built on data available both from C. elegans and from other organisms, expressing homologous channels. We combine these channel models to simulate the electrical activity oftwo among the most studied neurons in C. elegans, which display prototypical dynamics of neuronal activation, the chemosensory AWCON and the motor neuron RMD. Our model properly describes the regenerative responses of the two cells. We analyze in detail the role of ion currents, both in wild type and in in silico knockout neurons. Moreover, we specifically investigate the behavior of RMD, identifying a heterogeneous dynamical response which includes bistable regimes and sustained oscillations. We are able to assess the critical role of T-type calcium currents, carried by CCA-1 channels, and leakage currents in the regulation of RMD response. Overall, our results provide new insights in the activity of key C. elegans neurons. The developed mathematical framework constitute a basis for single-cell and neuronal networks analyses, opening new scenarios in the in silico modeling of C. elegans neuronal system. [ABSTRACT FROM AUTHOR]

In panels A-C we report the steady-state activation and inactivation curves (left), the activation time constant function (center), and the inactivation time constant function (right). Corresponding steady-state activation/inactivation and time constant functions, computed with the fitted parameters, are shown in S1-S5 Figs. In panels A-D we report the steady-state activation and inactivation curves (left), and the activation time constant function (right). [Extracted from the article]

Although the synaptic connections of the C. elegans connectome have been precisely mapped with detailed electron microscopy studies of nematode slices, their excitatory or inhibitory character is mostly unknown. This makes the C. elegans neural dynamics unpredictable, and limits our understanding of how specific sub-circuits work. The present study proposes a recurrent neural network model that reproduces known escape behaviours of C. elegans. To do this, our model uses the known information about the connectome, and makes guesses on the excitatory or inhibitory character of the synapses, which are iteratively updated until the model is able to reproduce the known behaviours. Specifically, we apply this model-based approach to study the neuronal sub-circuits involved in the association of aversive stimuli with escape responses. To form an escape response dataset that allows us to adjust our model parameters, we performed a meta-study on the C. elegans stimulus–response behaviours reported in literature, focusing on robust escape reactions triggered by aversive stimuli. Given a wide sample of all possible parameter sets that satisfy the behavioural constraints of the dataset, we find that more than 75% of the synaptic connections reach a univocal optimal assignment of the inhibitory or excitatory character. To validate our model, we show that in the few cases where the excitatory/inhibitory character is already known, our retrieved optimum in synaptic characters matches the results reported in literature. Finally, we assess the accuracy of this approach by applying it on recurrent neural networks that have the same connectivity structure of C. elegans but random inhibitory or excitatory character. These findings confirm the predictive power of the proposed method. [ABSTRACT FROM AUTHOR]