1,648 research outputs found
Keeping track of worm trackers
C. elegans is used extensively as a model system in the neurosciences due to its well defined nervous system. However, the seeming simplicity of this nervous system in anatomical structure and neuronal connectivity, at least compared to higher animals, underlies a rich diversity of behaviors. The usefulness of the worm in genome-wide mutagenesis or RNAi screens, where thousands of strains are assessed for phenotype, emphasizes the need for computational methods for automated parameterization of generated behaviors. In addition, behaviors can be modulated upon external cues like temperature, O2 and CO2 concentrations, mechanosensory and chemosensory inputs. Different machine vision tools have been developed to aid researchers in their efforts to inventory and characterize defined behavioral βoutputsβ. Here we aim at providing an overview of different worm-tracking packages or video analysis tools designed to quantify different aspects of locomotion such as the occurrence of directional changes (turns, omega bends), curvature of the sinusoidal shape (amplitude, body bend angles) and velocity (speed, backward or forward movement)
Long-tail Behavior in Locomotion of Caenorhabditis elegans
The locomotion of Caenorhabditis elegans exhibits complex patterns. In
particular, the worm combines mildly curved runs and sharp turns to steer its
course. Both runs and sharp turns of various types are important components of
taxis behavior. The statistics of sharp turns have been intensively studied.
However, there have been few studies on runs, except for those on klinotaxis
(also called weathervane mechanism), in which the worm gradually curves toward
the direction with a high concentration of chemicals; this phenomenon was
discovered recently. We analyzed the data of runs by excluding sharp turns. We
show that the curving rate obeys long-tail distributions, which implies that
large curving rates are relatively frequent. This result holds true for
locomotion in environments both with and without a gradient of NaCl
concentration; it is independent of klinotaxis. We propose a phenomenological
computational model on the basis of a random walk with multiplicative noise.
The assumption of multiplicative noise posits that the fluctuation of the force
is proportional to the force exerted. The model reproduces the long-tail
property present in the experimental data.Comment: 30 pages, 11 figures, some errors were correcte
Nemo: a computational tool for analyzing nematode locomotion
The nematode Caenorhabditis elegans responds to an impressive range of
chemical, mechanical and thermal stimuli and is extensively used to investigate
the molecular mechanisms that mediate chemosensation, mechanotransduction and
thermosensation. The main behavioral output of these responses is manifested as
alterations in animal locomotion. Monitoring and examination of such
alterations requires tools to capture and quantify features of nematode
movement. In this paper, we introduce Nemo (nematode movement), a
computationally efficient and robust two-dimensional object tracking algorithm
for automated detection and analysis of C. elegans locomotion. This algorithm
enables precise measurement and feature extraction of nematode movement
components. In addition, we develop a Graphical User Interface designed to
facilitate processing and interpretation of movement data. While, in this
study, we focus on the simple sinusoidal locomotion of C. elegans, our approach
can be readily adapted to handle complicated locomotory behaviour patterns by
including additional movement characteristics and parameters subject to
quantification. Our software tool offers the capacity to extract, analyze and
measure nematode locomotion features by processing simple video files. By
allowing precise and quantitative assessment of behavioral traits, this tool
will assist the genetic dissection and elucidation of the molecular mechanisms
underlying specific behavioral responses.Comment: 12 pages, 2 figures. accepted by BMC Neuroscience 2007, 8:8
Multi-Behavioral Endpoint Testing Of An 87-Chemical Compound Library In Freshwater Planarians
There is an increased recognition in the field of toxicology of the value of medium-to-high-throughput screening methods using in vitro and alternative animal models. We have previously introduced the asexual freshwater planarian Dugesia japonica as a new alternative animal model and proposed that it is particularly well-suited for the study of developmental neurotoxicology. In this paper, we discuss how we have expanded and automated our screening methodology to allow for fast screening of multiple behavioral endpoints, developmental toxicity, and mortality. Using an 87-compound library provided by the National Toxicology Program (NTP), consisting of known and suspected neurotoxicants, including drugs, flame retardants, industrial chemicals, polycyclic aromatic hydrocarbons (PAHs), pesticides and presumptive negative controls, we further evaluate the benefits and limitations of the system for medium-throughput screening, focusing on the technical aspects of the system. We show that, in the context of this library, planarians are the most sensitive to pesticides with 16/16 compounds causing toxicity and the least sensitive to PAHs, with only 5/17 causing toxicity. Furthermore, while none of the presumptive negative controls were bioactive in adult planarians, 2/5, acetaminophen and acetylsalicylic acid, were bioactive in regenerating worms. Notably, these compounds were previously reported as developmentally toxic in mammalian studies. Through parallel screening of adults and developing animals, planarians are thus a useful model to detect such developmental-specific effects, which was observed for 13 chemicals in this library. We use the data and experience gained from this screen to propose guidelines for best practices when using planarians for toxicology screens
Microbial light-activatable proton pumps as neuronal inhibitors to functionally dissect neuronal networks in C. elegans
Essentially any behavior in simple and complex animals depends on neuronal network function. Currently, the best-defined system to study neuronal circuits is the nematode Caenorhabditis elegans, as the connectivity of its 302 neurons is exactly known. Individual neurons can be activated by photostimulation of Channelrhodopsin-2 (ChR2) using blue light, allowing to directly probe the importance of a particular neuron for the respective behavioral output of the network under study. In analogy, other excitable cells can be inhibited by expressing Halorhodopsin from Natronomonas pharaonis (NpHR) and subsequent illumination with yellow light. However, inhibiting C. elegans neurons using NpHR is difficult. Recently, proton pumps from various sources were established as valuable alternative hyperpolarizers. Here we show that archaerhodopsin-3 (Arch) from Halorubrum sodomense and a proton pump from the fungus Leptosphaeria maculans (Mac) can be utilized to effectively inhibit excitable cells in C. elegans. Arch is the most powerful hyperpolarizer when illuminated with yellow or green light while the action spectrum of Mac is more blue-shifted, as analyzed by light-evoked behaviors and electrophysiology. This allows these tools to be combined in various ways with ChR2 to analyze different subsets of neurons within a circuit. We exemplify this by means of the polymodal aversive sensory ASH neurons, and the downstream command interneurons to which ASH neurons signal to trigger a reversal followed by a directional turn. Photostimulating ASH and subsequently inhibiting command interneurons using two-color illumination of different body segments, allows investigating temporal aspects of signaling downstream of ASH
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