Track-a-worm, an open-source system for quantitative assessment of C. elegans locomotory and bending behavior

Track-A-Worm 2.0 : A Software Suite for Quantifying Properties of C. elegans Locomotion, Bending, Sleep, and Action Potentials

Comparative analyses of locomotor behavior and cellular electrical properties between wild-type and mutant C. elegans are crucial for exploring the gene basis of behaviors and the underlying cellular mechanisms. Although many tools have been developed by research labs and companies, their application is often hindered by implementation difficulties or lack of features specifically suited for C. elegans . Track-A-Worm 2.0 addresses these challenges with three key components: WormTracker , SleepTracker , and Action Potential (AP) Analyzer . WormTracker accurately quantifies a comprehensive set of locomotor and body bending metrics, reliably distinguish between the ventral and dorsal sides, continuously tracks the animal using a motorized stage, and seamlessly integrates external devices, such as a light source for optogenetic stimulation. SleepTracker detects and quantifies sleep-like behavior in freely moving animals. AP Analyzer assesses the resting membrane potential, afterhyperpolarization level, and various AP properties, including threshold, amplitude, mid-peak width, rise and decay times, and maximum and minimum slopes. Importantly, it addresses the challenge of AP threshold quantification posed by the absence of a pre-upstroke inflection point. Track-A-Worm 2.0 is potentially a valuable tool for many C. elegans research labs due to its powerful functionality and ease of implementation.

An automated, high-resolution phenotypic assay for adult Brugia malayi and microfilaria

Brugia malayi are thread-like parasitic worms and one of the etiological agents of Lymphatic filariasis (LF). Existing anthelmintic drugs to treat LF are effective in reducing the larval microfilaria (mf) counts in human bloodstream but are less effective on adult parasites. To test potential drug candidates, we report a multi-parameter phenotypic assay based on tracking the motility of adult B. malayi and mf in vitro. For adult B. malayi, motility is characterized by the centroid velocity, path curvature, angular velocity, eccentricity, extent, and Euler Number. These parameters are evaluated in experiments with three anthelmintic drugs. For B. malayi mf, motility is extracted from the evolving body skeleton to yield positional data and bending angles at 74 key point. We achieved high-fidelity tracking of complex worm postures (self-occlusions, omega turns, body bending, and reversals) while providing a visual representation of pose estimates and behavioral attributes in both space and time scales.

Locomotion modulates olfactory learning through proprioception in C. elegans

Locomotor activities can enhance learning, but the underlying circuit and synaptic mechanisms are largely unknown. Here we show that locomotion facilitates aversive olfactory learning in C. elegans by activating mechanoreceptors in motor neurons, and transmitting the proprioceptive information thus generated to locomotion interneurons through antidromic-rectifying gap junctions. The proprioceptive information serves to regulate experience-dependent activities and functional coupling of interneurons that process olfactory sensory information to produce the learning behavior. Genetic destruction of either the mechanoreceptors in motor neurons, the rectifying gap junctions between the motor neurons and locomotion interneurons, or specific inhibitory synapses among the interneurons impairs the aversive olfactory learning. We have thus uncovered an unexpected role of proprioception in a specific learning behavior as well as the circuit, synaptic, and gene bases for this function.

Fast detection of slender bodies in high density microscopy data

Computer-aided analysis of biological microscopy data has seen a massive improvement with the utilization of general-purpose deep learning techniques. Yet, in microscopy studies of multi-organism systems, the problem of collision and overlap remains challenging. This is particularly true for systems composed of slender bodies such as swimming nematodes, swimming spermatozoa, or the beating of eukaryotic or prokaryotic flagella. Here, we develop a end-to-end deep learning approach to extract precise shape trajectories of generally motile and overlapping slender bodies. Our method works in low resolution settings where feature keypoints are hard to define and detect. Detection is fast and we demonstrate the ability to track thousands of overlapping organisms simultaneously. While our approach is agnostic to area of application, we present it in the setting of and exemplify its usability on dense experiments of swimming Caenorhabditis elegans. The model training is achieved purely on synthetic data, utilizing a physics-based model for nematode motility, and we demonstrate the model's ability to generalize from simulations to experimental videos.

Automated recognition and analysis of body bending behavior in C. elegans

BACKGROUND

Locomotion behaviors of Caenorhabditis elegans play an important role in drug activity screening, anti-aging research, and toxicological assessment. Previous studies have provided important insights into drug activity screening, anti-aging, and toxicological research by manually counting the number of body bends. However, manual counting is often low-throughput and takes a lot of time and manpower. And it is easy to cause artificial bias and error in counting results.

RESULTS

In this paper, an algorithm is proposed for automatic counting and analysis of the body bending behavior of nematodes. First of all, the numerical coordinate regression method with convolutional neural network is used to obtain the head and tail coordinates. Next, curvature-based feature point extraction algorithm is used to calculate the feature points of the nematode centerline. Then the maximum distance between the peak point and the straight line between the pharynx and the tail is calculated. The number of body bends is counted according to the change in the maximum distance per frame.

CONCLUSION

Experiments are performed to prove the effectiveness of the proposed algorithm. The accuracy of head coordinate prediction is 0.993, and the accuracy of tail coordinate prediction is 0.990. The Pearson correlation coefficient between the results of the automatic count and manual count of the number of body bends is 0.998 and the mean absolute error is 1.931. Different strains of nematodes are selected to analyze differences in body bending behavior, demonstrating a relationship between nematode vitality and lifespan. The code is freely available at https://github.com/hthana/Body-Bend-Count .

A Compact Imaging Platform for Conducting C. elegans Phenotypic Assays on Earth and in Spaceflight

The model organism Caenorhabditis elegans is used in a variety of applications ranging from fundamental biological studies, to drug screening, to disease modeling, and to space-biology investigations. These applications rely on conducting whole-organism phenotypic assays involving animal behavior and locomotion. In this study, we report a 3D printed compact imaging platform (CIP) that is integrated with a smart-device camera for the whole-organism phenotyping of C. elegans. The CIP has no external optical elements and does not require mechanical focusing, simplifying the optical configuration. The small footprint of the system powered with a standard USB provides capabilities ranging from plug-and-play, to parallel operation, and to housing it in incubators for temperature control. We demonstrate on Earth the compatibility of the CIP with different C. elegans substrates, including agar plates, liquid droplets on glass slides and microfluidic chips. We validate the system with behavioral and thrashing assays and show that the phenotypic readouts are in good agreement with the literature data. We conduct a pilot study with mutants and show that the phenotypic data collected from the CIP distinguishes these mutants. Finally, we discuss how the simplicity and versatility offered by CIP makes it amenable to future C. elegans investigations on the International Space Station, where science experiments are constrained by system size, payload weight and crew time. Overall, the compactness, portability and ease-of-use makes the CIP desirable for research and educational outreach applications on Earth and in space.

A Markerless Pose Estimator Applicable to Limbless Animals

The analysis of kinematics, locomotion, and spatial tasks relies on the accurate detection of animal positions and pose. Pose and position can be assessed with video analysis programs, the “trackers.” Most available trackers represent animals as single points in space (no pose information available) or use markers to build a skeletal representation of pose. Markers are either physical objects attached to the body (white balls, stickers, or paint) or they are defined in silico using recognizable body structures (e.g., joints, limbs, color patterns). Physical markers often cannot be used if the animals are small, lack prominent body structures on which the markers can be placed, or live in environments such as aquatic ones that might detach the marker. Here, we introduce a marker-free pose-estimator (LACE Limbless Animal traCkEr) that builds the pose of the animal de novo from its contour. LACE detects the contour of the animal and derives the body mid-line, building a pseudo-skeleton by defining vertices and edges. By applying LACE to analyse the pose of larval Drosophila melanogaster and adult zebrafish, we illustrate that LACE allows to quantify, for example, genetic alterations of peristaltic movements and gender-specific locomotion patterns that are associated with different body shapes. As illustrated by these examples, LACE provides a versatile method for assessing position, pose and movement patterns, even in animals without limbs.

Automated recognition and analysis of head thrashes behavior in C. elegans

Background

Locomotive behaviors are a rapid evaluation indicator reflecting whether the nervous system of worms is damaged, and has been proved to be sensitive to chemical toxicity. In many toxicological studies, C. elegans head thrashes is a key indicator of locomotive behaviors to measure the vitality of worms. In previous studies, the number of head thrashes was manually counted, which is time-consuming and labor-intensive.

Results

This paper presents an automatic recognition and counting method for head thrashes behavior of worms from experimental videos. First, the image processing algorithm is designed for worm morphology features calculation, mean gray values of head and tail are used to locate the head of worm accurately. Next, the worm skeleton is extracted and divided into equal parts. The angle formulas are used to calculate the bending angle of the head of worm. Finally, the number of head thrashes is counted according to the bending angle of the head in each frame. The robustness of the proposed algorithm is evaluated by comparing the counting results of the manual counting. It is proved that the proposed algorithm can recognize the occurrence of head thrashes of C. elegans of different strains. In addition, the difference of the head thrashes behavior of different worm strains is analyzed, it is proved that the relationship between worm head thrashes behavior and lifespan.

Conclusions

A new method is proposed to automatically count the number of head thrashes of worms. This algorithm makes it possible to count the number of head thrashes from the worm videos collected by the automatic tracking system. The proposed algorithm will play an important role in toxicological research and worm vitality research. The code is freely available at https://github.com/hthana/HTC.

An economical and highly adaptable optogenetics system for individual and population-level manipulation of Caenorhabditis elegans

Background

Optogenetics allows the experimental manipulation of excitable cells by a light stimulus without the need for technically challenging and invasive procedures. The high degree of spatial, temporal, and intensity control that can be achieved with a light stimulus, combined with cell type-specific expression of light-sensitive ion channels, enables highly specific and precise stimulation of excitable cells. Optogenetic tools have therefore revolutionized the study of neuronal circuits in a number of models, including Caenorhabditis elegans. Despite the existence of several optogenetic systems that allow spatial and temporal photoactivation of light-sensitive actuators in C. elegans, their high costs and low flexibility have limited wide access to optogenetics. Here, we developed an inexpensive, easy-to-build, modular, and adjustable optogenetics device for use on different microscopes and worm trackers, which we called the OptoArm.

Results

The OptoArm allows for single- and multiple-worm illumination and is adaptable in terms of light intensity, lighting profiles, and light color. We demonstrate OptoArm’s power in a population-based multi-parameter study on the contributions of motor circuit cells to age-related motility decline. We found that individual components of the neuromuscular system display different rates of age-dependent deterioration. The functional decline of cholinergic neurons mirrors motor decline, while GABAergic neurons and muscle cells are relatively age-resilient, suggesting that rate-limiting cells exist and determine neuronal circuit ageing.

Conclusion

We have assembled an economical, reliable, and highly adaptable optogenetics system which can be deployed to address diverse biological questions. We provide a detailed description of the construction as well as technical and biological validation of our set-up. Importantly, use of the OptoArm is not limited to C. elegans and may benefit studies in multiple model organisms, making optogenetics more accessible to the broader research community.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-01085-2.

Fast whole-body motor neuron calcium imaging of freely moving Caenorhabditis elegans without coverslip pressed

Caenorhabditis elegans (C. elegans) is an ideal model organism for studying neuronal functions at the system level. This article develops a customized system for whole-body motor neuron calcium imaging of freely moving C. elegans without the coverslip pressed. Firstly, we proposed a fast centerline localization algorithm that could deal with most topology-variant cases costing only 6 ms for one frame, not only benefits for real-time localization but also for post-analysis. Secondly, we implemented a full-time two-axis synchronized motion strategy by adaptively adjusting the motion parameters of two motors in every short-term motion step (~50 ms). Following the above motion tracking configuration, the tracking performance of our system has been demonstrated to completely support the high spatiotemporal resolution calcium imaging on whole-body motor neurons of wild-type (N2) worms as well as two mutants (unc-2, unc-9), even the instantaneous speed of worm moving without coverslip pressed was extremely up to 400 μm/s.

GABAergic motor neurons bias locomotor decision-making in C. elegans

Proper threat-reward decision-making is critical to animal survival. Emerging evidence indicates that the motor system may participate in decision-making but the neural circuit and molecular bases for these functions are little known. We found in C. elegans that GABAergic motor neurons (D-MNs) bias toward the reward behavior in threat-reward decision-making by retrogradely inhibiting a pair of premotor command interneurons, AVA, that control cholinergic motor neurons in the avoidance neural circuit. This function of D-MNs is mediated by a specific ionotropic GABA receptor (UNC-49) in AVA, and depends on electrical coupling between the two AVA interneurons. Our results suggest that AVA are hub neurons where sensory inputs from threat and reward sensory modalities and motor information from D-MNs are integrated. This study demonstrates at single-neuron resolution how motor neurons may help shape threat-reward choice behaviors through interacting with other neurons.

Assessing motor-related phenotypes of Caenorhabditis elegans with the wide field-of-view nematode tracking platform

Caenorhabditis elegans is a valuable model organism in biomedical research that has led to major discoveries in the fields of neurodegeneration, cancer and aging. Because movement phenotypes are commonly used and represent strong indicators of C. elegans fitness, there is an increasing need to replace manual assessments of worm motility with automated measurements to increase throughput and minimize observer biases. Here, we provide a protocol for the implementation of the improved wide field-of-view nematode tracking platform (WF-NTP), which enables the simultaneous analysis of hundreds of worms with respect to multiple behavioral parameters. The protocol takes only a few hours to complete, excluding the time spent culturing C. elegans, and includes (i) experimental design and preparation of samples, (ii) data recording, (iii) software management with appropriate parameter choices and (iv) post-experimental data analysis. We compare the WF-NTP with other existing worm trackers, including those having high spatial resolution. The main benefits of WF-NTP relate to the high number of worms that can be assessed at the same time on a whole-plate basis and the number of phenotypes that can be screened for simultaneously.

Neuromedin U signaling regulates retrieval of learned salt avoidance in a C. elegans gustatory circuit

Learning and memory are regulated by neuromodulatory pathways, but the contribution and temporal requirement of most neuromodulators in a learning circuit are unknown. Here we identify the evolutionarily conserved neuromedin U (NMU) neuropeptide family as a regulator of C. elegans gustatory aversive learning. The NMU homolog CAPA-1 and its receptor NMUR-1 are required for the retrieval of learned salt avoidance. Gustatory aversive learning requires the release of CAPA-1 neuropeptides from sensory ASG neurons that respond to salt stimuli in an experience-dependent manner. Optogenetic silencing of CAPA-1 neurons blocks the expression, but not the acquisition, of learned salt avoidance. CAPA-1 signals through NMUR-1 in AFD sensory neurons to modulate two navigational strategies for salt chemotaxis. Aversive conditioning thus recruits NMU signaling to modulate locomotor programs for expressing learned avoidance behavior. Because NMU signaling is conserved across bilaterian animals, our findings incite further research into its function in other learning circuits.

Slo2 potassium channel function depends on RNA editing-regulated expression of a SCYL1 protein

Slo2 potassium channels play important roles in neuronal function, and their mutations in humans may cause epilepsies and cognitive defects. However, it is largely unknown how Slo2 is regulated by other proteins. Here we show that the function of C. elegans Slo2 (SLO-2) depends on adr-1, a gene important to RNA editing. ADR-1 promotes SLO-2 function not by editing the transcripts of slo-2 but those of scyl-1, which encodes an orthologue of mammalian SCYL1. Transcripts of scyl-1 are greatly decreased in adr-1 mutants due to deficient RNA editing at a single adenosine in their 3’-UTR. SCYL-1 physically interacts with SLO-2 in neurons. Single-channel open probability (P_o) of neuronal SLO-2 is ~50% lower in scyl-1 knockout mutant than wild type. Moreover, human Slo2.2/Slack P_o is doubled by SCYL1 in a heterologous expression system. These results suggest that SCYL-1/SCYL1 is an evolutionarily conserved regulator of Slo2 channels.

Motion prediction enables simulated MR-imaging of freely moving model organisms

Magnetic resonance tomography typically applies the Fourier transform to k-space signals repeatedly acquired from a frequency encoded spatial region of interest, therefore requiring a stationary object during scanning. Any movement of the object results in phase errors in the recorded signal, leading to deformed images, phantoms, and artifacts, since the encoded information does not originate from the intended region of the object. However, if the type and magnitude of movement is known instantaneously, the scanner or the reconstruction algorithm could be adjusted to compensate for the movement, directly allowing high quality imaging with non-stationary objects. This would be an enormous boon to studies that tie cell metabolomics to spontaneous organism behaviour, eliminating the stress otherwise necessitated by restraining measures such as anesthesia or clamping. In the present theoretical study, we use a phantom of the animal model C. elegans to examine the feasibility to automatically predict its movement and position, and to evaluate the impact of movement prediction, within a sufficiently long time horizon, on image reconstruction. For this purpose, we use automated image processing to annotate body parts in freely moving C. elegans, and predict their path of movement. We further introduce an MRI simulation platform based on bright field videos of the moving worm, combined with a stack of high resolution transmission electron microscope (TEM) slice images as virtual high resolution phantoms. A phantom provides an indication of the spatial distribution of signal-generating nuclei on a particular imaging slice. We show that adjustment of the scanning to the predicted movements strongly reduces distortions in the resulting image, opening the door for implementation in a high-resolution NMR scanner.

Magnetic resonance imaging (MRI) requires its subjects not to move, since movement will cause image artifacts. This is hard to achieve for adult humans, whom we can ask to comply, but can currently only be achieved by sedation for other freely moving biological specimens. Because of the importance of non-invasive MRI as a technique to also capture metabolic information during activity, this is a huge deficiency of the methodology that is hampering progress. In our paper we ask the question whether it is possible to computationally combine optical information on specimen movement with MRI. Our approach is to predict the future movement and position of the specimen and thereby anticipate where it will be so as to specify correct MRI parameters. Our computer simulations show, for a freely moving worm, that a reasonable prediction is already possible for a short time window, and that we can control the amount of error of the resulting MRI image. Importantly, with the continuous speedup of computation, our simulations suggest that it is opportune now to implement such a system in hardware.

Powerful and interpretable behavioural features for quantitative phenotyping of Caenorhabditis elegans

Behaviour is a sensitive and integrative readout of nervous system function and therefore an attractive measure for assessing the effects of mutation or drug treatment on animals. Video data provide a rich but high-dimensional representation of behaviour, and so the first step of analysis is often some form of tracking and feature extraction to reduce dimensionality while maintaining relevant information. Modern machine-learning methods are powerful but notoriously difficult to interpret, while handcrafted features are interpretable but do not always perform as well. Here, we report a new set of handcrafted features to compactly quantify Caenorhabditis elegans behaviour. The features are designed to be interpretable but to capture as much of the phenotypic differences between worms as possible. We show that the full feature set is more powerful than a previously defined feature set in classifying mutant strains. We then use a combination of automated and manual feature selection to define a core set of interpretable features that still provides sufficient power to detect behavioural differences between mutant strains and the wild-type. Finally, we apply the new features to detect time-resolved behavioural differences in a series of optogenetic experiments targeting different neural subsets.

This article is part of a discussion meeting issue ‘Connectome to behaviour: modelling C. elegans at cellular resolution’.

Massively parallel C. elegans tracking provides multi-dimensional fingerprints for phenotypic discovery

BACKGROUND

The nematode worm C. elegans is a model organism widely used for studies of genetics and of human disease. The health and fitness of the worms can be quantified in different ways, such as by measuring their bending frequency, speed or lifespan. Manual assays, however, are time consuming and limited in their scope providing a strong motivation for automation.

NEW METHOD

We describe the development and application of an advanced machine vision system for characterising the behaviour of C. elegans, the Wide Field-of-View Nematode Tracking Platform (WF-NTP), which enables massively parallel data acquisition and automated multi-parameter behavioural profiling of thousands of worms simultaneously.

RESULTS

We screened more than a million worms from several established models of neurodegenerative disorders and characterised the effects of potential therapeutic molecules for Alzheimer's and Parkinson's diseases. By using very large numbers of animals we show that the sensitivity and reproducibility of behavioural assays is very greatly increased. The results reveal the ability of this platform to detect even subtle phenotypes.

COMPARISON WITH EXISTING METHODS

The WF-NTP method has substantially greater capacity compared to current automated platforms that typically either focus on characterising single worms at high resolution or tracking the properties of populations of less than 50 animals.

CONCLUSIONS

The WF-NTP extends significantly the power of existing automated platforms by combining enhanced optical imaging techniques with an advanced software platform. We anticipate that this approach will further extend the scope and utility of C. elegans as a model organism.

HRPU-2, a Homolog of Mammalian hnRNP U, Regulates Synaptic Transmission by Controlling the Expression of SLO-2 Potassium Channel in Caenorhabditis elegans

Slo2 channels are large-conductance potassium channels abundantly expressed in the nervous system. However, it is unclear how their expression level in neurons is regulated. Here we report that HRPU-2, an RNA-binding protein homologous to mammalian heterogeneous nuclear ribonucleoprotein U (hnRNP U), plays an important role in regulating the expression of SLO-2 (a homolog of mammalian Slo2) in Caenorhabditis elegans Loss-of-function (lf) mutants of hrpu-2 were isolated in a genetic screen for suppressors of a sluggish phenotype caused by a hyperactive SLO-2. In hrpu-2(lf) mutants, SLO-2-mediated delayed outward currents in neurons are greatly decreased, and neuromuscular synaptic transmission is enhanced. These mutant phenotypes can be rescued by expressing wild-type HRPU-2 in neurons. HRPU-2 binds to slo-2 mRNA, and hrpu-2(lf) mutants show decreased SLO-2 protein expression. In contrast, hrpu-2(lf) does not alter the expression of either the BK channel SLO-1 or the Shaker type potassium channel SHK-1. hrpu-2(lf) mutants are indistinguishable from wild type in gross motor neuron morphology and locomotion behavior. Together, these observations suggest that HRPU-2 plays important roles in SLO-2 function by regulating SLO-2 protein expression, and that SLO-2 is likely among a restricted set of proteins regulated by HRPU-2. Mutations of human Slo2 channel and hnRNP U are strongly linked to epileptic disorders and intellectual disability. The findings of this study suggest a potential link between these two molecules in human patients.SIGNIFICANCE STATEMENT Heterogeneous nuclear ribonucleoprotein U (hnRNP U) belongs to a family of RNA-binding proteins that play important roles in controlling gene expression. Recent studies have established a strong link between mutations of hnRNP U and human epilepsies and intellectual disability. However, it is unclear how mutations of hnRNP U may cause such disorders. This study shows that mutations of HRPU-2, a worm homolog of mammalian hnRNP U, result in dysfunction of a Slo2 potassium channel, which is critical to neuronal function. Because mutations of Slo2 channels are also strongly associated with epileptic encephalopathies and intellectual disability in humans, the findings of this study point to a potential mechanism underlying neurological disorders caused by hnRNP U mutations.

AIP limits neurotransmitter release by inhibiting calcium bursts from the ryanodine receptor

Pituitary tumors are frequently associated with mutations in the AIP gene and are sometimes associated with hypersecretion of growth hormone. It is unclear whether other factors besides an enlarged pituitary contribute to the hypersecretion. In a genetic screen for suppressors of reduced neurotransmitter release, we identified a mutation in Caenorhabditis elegans AIPR-1 (AIP-related-1), which causes profound increases in evoked and spontaneous neurotransmitter release, a high frequency of spontaneous calcium transients in motor neurons and an enlarged readily releasable pool of vesicles. Calcium bursts and hypersecretion are reversed by mutations in the ryanodine receptor but not in the voltage-gated calcium channel, indicating that these phenotypes are caused by a leaky ryanodine receptor. AIPR-1 is physically associated with the ryanodine receptor at synapses. Finally, the phenotypes in aipr-1 mutants can be rescued by presynaptic expression of mouse AIP, demonstrating that a conserved function of AIP proteins is to inhibit calcium release from ryanodine receptors.

A Caenorhabditis elegans Nutritional-status Based Copper Aversion Assay

To ensure survival, organisms must be capable of avoiding unfavorable habitats while ensuring a consistent food source. Caenorhabditis elegans alter their locomotory patterns upon detection of diverse environmental stimuli and can modulate their suite of behavioral responses in response to starvation conditions. Nematodes typically exhibit a decreased aversive response when removed from a food source for over 30 min. Observation of behavioral changes in response to a changing nutritional status can provide insight into the mechanisms that regulate the transition from a well-fed to starved state. We have developed an assay that measures a nematode's ability to cross an aversive barrier (i.e. copper) then reach a food source over a prolonged period of time. This protocol builds upon previous work by integrating multiple variables in a manner that allows for continued data collection as the organisms shift towards an increasingly starved condition. Moreover, this assay permits an increased sample size so that larger populations of nematodes can be simultaneously evaluated. Organisms defective for the ability to detect or respond to copper immediately cross the chemical barrier, while wild type nematodes are initially repelled. As wild type worms are increasingly starved, they begin to cross the barrier and reach the food source. We designed this assay to evaluate a mutant that is incapable of responding to diverse environmental cues, including food sensation or detection of aversive chemicals. When evaluated via this protocol, the defective organisms immediately crossed the barrier, but were also incapable of detecting a food source. Hence, these mutants repeatedly cross the chemical barrier despite temporarily reaching a food source. This assay can straightforwardly test populations of worms to evaluate potential pathway defects related to aversion and starvation.

Automated Analysis of C. elegans Swim Behavior Using CeleST Software

Dissecting the neuronal and neuromuscular circuits that regulate behavior remains a major challenge in biology. The nematode Caenorhabditis elegans has proven to be an invaluable model organism in helping to tackle this challenge, from inspiring technological approaches, building the human brain connectome, to actually shedding light on the specific molecular drivers of basic functional patterns. The bulk of the behavioral studies in C. elegans have been performed on solid substrates. In liquid, animals exhibit behavioral patterns that include movement at a range of speeds in 3D, as well as partial body movements, such as a posterior curl without anterior shape change, which introduce new challenges for quantitation. The steps of a simple procedure, and use of a software that enables high-resolution analysis of C. elegans swim behavior, are presented here. The software, named CeleST, uses a specialized computer program that tracks multiple animals simultaneously and provides novel measures of C. elegans locomotion in liquid (swimming). The measures are mostly grounded in animal posture and based on mathematics used in computer vision and pattern recognition, without computational requirements for threshold cut-offs. The software tool can be used to both assess overall swimming prowess in hundreds of animals from combined small batch trials and to reveal novel phenotypes even in well-characterized genetic mutants. The preparation of specimens for analysis with CeleST is simple and low-tech, enabling wide adaptation by the scientific community. Use of the computational approach described here should therefore contribute to the greater understanding of behavior and behavioral circuits in the C. elegans model.

NemaCount: quantification of nematode chemotaxis behavior in a browser

Nematodes such as Caenorhabditis elegans offer a very effective and tractable system to probe the underlying mechanisms of diverse sensory behaviors. Numerous platforms exist for quantifying nematode behavior and often require separate dependencies or software. Here I describe a novel and simple tool called NemaCount that provides a versatile solution for the quantification of nematode chemotaxis behavior. The ease of installation and user-friendly interface makes NemaCount a practical tool for measuring diverse behaviors and image features of nematodes such as C. elegans. The main advantage of NemaCount is that it operates from within a modern browser such as Google Chrome or Apple Safari. Any features that change in total number, size, shape, or angular distance between control and experimental preparations are suited to NemaCount for image analysis, while commonly used chemotaxis assays can be quantified, and statistically analyzed using a suite of functions from within NemaCount. NemaCount also offers image filtering options that allow the user to improve object detection and measurements. NemaCount was validated by examining nematode chemotaxis behavior; angular distances of locomotory tracks in C. elegans; and body lengths of Heterorhabditis bacteriophora nematodes. Apart from a modern browser, no additional software is required to operate NemaCount, making NemaCount a cheap, simple option for the analysis of nematode images and chemotaxis behavior.

Life-History Traits of the Model Organism Pristionchus pacificus Recorded Using the Hanging Drop Method: Comparison with Caenorhabditis elegans

The nematode Pristionchus pacificus is of growing interest as a model organism in evolutionary biology. However, despite multiple studies of its genetics, developmental cues, and ecology, the basic life-history traits (LHTs) of P. pacificus remain unknown. In this study, we used the hanging drop method to follow P. pacificus at the individual level and thereby quantify its LHTs. This approach allowed direct comparisons with the LHTs of Caenorhabditis elegans recently determined using this method. When provided with 5×10(9) Escherichia coli cells ml(-1) at 20°C, the intrinsic rate of natural increase of P. pacificus was 1.125 (individually, per day); mean net production was 115 juveniles produced during the life-time of each individual, and each nematode laid an average of 270 eggs (both fertile and unfertile). The mean age of P. pacificus individuals at first reproduction was 65 h, and the average life span was 22 days. The life cycle of P. pacificus is therefore slightly longer than that of C. elegans, with a longer average life span and hatching time and the production of fewer progeny.

Acrylamide induces locomotor defects and degeneration of dopamine neurons in Caenorhabditis elegans

Acrylamide can form in foods during the cooking process and cause multiple adverse effects. However, the neurotoxicity and mechanisms of acrylamide have not been fully elucidated. In Caenorhabditis elegans, we showed that 48 h exposure to 10-625 mg l(-1) acrylamide resulted in a significant decline in locomotor frequency of body bending, head thrashing and pharynx pumping. In addition, acrylamide exposure reduced crawling speeds and changed angles of body bending. It indicates that acrylamide induces locomotor defects, along with parkinsonian-like movement impairment, including bradykinesia and hypokinesia. Acrylamide also affected chemotaxis plasticity and reduced learning ability. Using transgenic nematodes, we found that acrylamide induced downexpression of P(dat-1) and led to the degeneration of dopaminergic neurons. Moreover, the enhanced expression of unc-54, encoding a subunit of α-synuclein was found. It illustrates that acrylamide is efficient in inducing crucial parkinsonian pathology, including dopaminergic damage and α-synuclein aggregation. These findings suggest the acrylamide-induced locomotor defects and neurotoxicity are associated with Parkinson's disease.

Heterologous Expression in Remodeled C. elegans: A Platform for Monoaminergic Agonist Identification and Anthelmintic Screening

Monoamines, such as 5-HT and tyramine (TA), paralyze both free-living and parasitic nematodes when applied exogenously and serotonergic agonists have been used to clear Haemonchus contortus infections in vivo. Since nematode cell lines are not available and animal screening options are limited, we have developed a screening platform to identify monoamine receptor agonists. Key receptors were expressed heterologously in chimeric, genetically-engineered Caenorhabditis elegans, at sites likely to yield robust phenotypes upon agonist stimulation. This approach potentially preserves the unique pharmacologies of the receptors, while including nematode-specific accessory proteins and the nematode cuticle. Importantly, the sensitivity of monoamine-dependent paralysis could be increased dramatically by hypotonic incubation or the use of bus mutants with increased cuticular permeabilities. We have demonstrated that the monoamine-dependent inhibition of key interneurons, cholinergic motor neurons or body wall muscle inhibited locomotion and caused paralysis. Specifically, 5-HT paralyzed C. elegans 5-HT receptor null animals expressing either nematode, insect or human orthologues of a key Gαo-coupled 5-HT1-like receptor in the cholinergic motor neurons. Importantly, 8-OH-DPAT and PAPP, 5-HT receptor agonists, differentially paralyzed the transgenic animals, with 8-OH-DPAT paralyzing mutant animals expressing the human receptor at concentrations well below those affecting its C. elegans or insect orthologues. Similarly, 5-HT and TA paralyzed C. elegans 5-HT or TA receptor null animals, respectively, expressing either C. elegans or H. contortus 5-HT or TA-gated Cl- channels in either C. elegans cholinergic motor neurons or body wall muscles. Together, these data suggest that this heterologous, ectopic expression screening approach will be useful for the identification of agonists for key monoamine receptors from parasites and could have broad application for the identification of ligands for a host of potential anthelmintic targets.

Spillover transmission is mediated by the excitatory GABA receptor LGC-35 in C. elegans

Under most circumstances, GABA activates chloride-selective channels and thereby inhibits neuronal activity. Here, we identify a GABA receptor in the nematode Caenorhabditis elegans that conducts cations and is therefore excitatory. Expression in Xenopus oocytes demonstrates that LGC-35 is a homopentameric cation-selective receptor of the cys-loop family exclusively activated by GABA. Phylogenetic analysis suggests that LGC-35 evolved from GABA-A receptors, but the pore-forming domain contains novel molecular determinants that confer cation selectivity. LGC-35 is expressed in muscles and directly mediates sphincter muscle contraction in the defecation cycle in hermaphrodites, and spicule eversion during mating in the male. In the locomotory circuit, GABA release directly activates chloride channels on the muscle to cause muscle relaxation. However, GABA spillover at these synapses activates LGC-35 on acetylcholine motor neurons, which in turn cause muscles to contract, presumably to drive wave propagation along the body. These studies demonstrate that both direct and indirect excitatory GABA signaling plays important roles in regulating neuronal circuit function and behavior in C. elegans.

FIM imaging and FIMtrack: two new tools allowing high-throughput and cost effective locomotion analysis

The analysis of neuronal network function requires a reliable measurement of behavioral traits. Since the behavior of freely moving animals is variable to a certain degree, many animals have to be analyzed, to obtain statistically significant data. This in turn requires a computer assisted automated quantification of locomotion patterns. To obtain high contrast images of almost translucent and small moving objects, a novel imaging technique based on frustrated total internal reflection called FIM was developed. In this setup, animals are only illuminated with infrared light at the very specific position of contact with the underlying crawling surface. This methodology results in very high contrast images. Subsequently, these high contrast images are processed using established contour tracking algorithms. Based on this, we developed the FIMTrack software, which serves to extract a number of features needed to quantitatively describe a large variety of locomotion characteristics. During the development of this software package, we focused our efforts on an open source architecture allowing the easy addition of further modules. The program operates platform independent and is accompanied by an intuitive GUI guiding the user through data analysis. All locomotion parameter values are given in form of csv files allowing further data analyses. In addition, a Results Viewer integrated into the tracking software provides the opportunity to interactively review and adjust the output, as might be needed during stimulus integration. The power of FIM and FIMTrack is demonstrated by studying the locomotion of Drosophila larvae.

Chronic exposure to perfluorooctane sulfonate induces behavior defects and neurotoxicity through oxidative damages, in vivo and in vitro

Perfluorooctane sulfonate (PFOS) is an emerging persistent pollutant which shows multiple adverse health effects. However, the neurotoxicity of PFOS and its mechanisms have not been fully elucidated. Using a combination of in vivo and in vitro methods, the present study provides a detailed description of PFOS-induced neurotoxicity. Results showed that the median lethal concentration of PFOS was 2.03 mM in Caenorhabditis elegans for 48 h exposure. 20 µM PFOS caused decrease of locomotor behaviors including forward movement, body bend and head thrash. Additionally, PFOS exposure reduced chemotaxis index of C. elegans, which indicates the decline of chemotaxis learning ability. Using green fluorescent protein (GFP) labelled transgenic strains, we found that PFOS caused down-regulated expression of a chemoreceptor gene, gcy-5, in ASE chemosensory neurons, but did not affect cholinergic neurons and dopaminergic neurons. In SH-SY5Y cells, 48 h exposure to 25 µM and 50 µM PFOS induced cell damage, apoptosis and the reactive oxygen species (ROS) generation. PFOS caused significant increases of lipid peroxidation and superoxide dismutase activity, but an actual decrease of glutathione peroxidase activity. Furthermore, antioxidant N-acetylcysteine rescued cells from PFOS-induced apoptosis via blocking ROS. Our results demonstrate that chronic exposure to PFOS can cause obvious neurotoxicity and behavior defects. Oxidative damage and anti-oxidative deficit are crucial mechanisms in neurotoxicity of PFOS.

Quantifying subtle locomotion phenotypes of Drosophila larvae using internal structures based on FIM images

Quantitative analysis of behavioral traits requires precise image acquisition and sophisticated image analysis to detect subtle locomotion phenotypes. In the past, we have established Frustrated Total Internal Reflection (FTIR) to improve the measurability of small animals like insects. This FTIR-based Imaging Method (FIM) results in an excellent foreground/background contrast and even internal organs and other structures are visible without any complicated imaging or labeling techniques. For example, the trachea and muscle organizations are detectable in FIM images. Here these morphological details are incorporated into phenotyping by performing cluster analysis using histogram-based statistics for the first time. We demonstrate that FIM enables the precise quantification of locomotion features namely rolling behavior or muscle contractions. Both were impossible to quantify automatically before. This approach extends the range of FIM applications by enabling advanced automatic phenotyping for particular locomotion patterns.

The C. elegans healthspan and stress-resistance assay toolkit

A wealth of knowledge on the genetic mechanisms that govern aging has emerged from the study of mutants that exhibit enhanced longevity and exceptional resilience to adverse environmental conditions. In these studies, lifespan has been an excellent proxy for establishing the rate of aging, but it is not always correlated with qualitative measures of healthy aging or 'healthspan'. Although the attributes of healthspan have been challenging to define, they share some universal features that are increasingly being incorporated into aging studies. Here we describe methods used to determine Caenorhabditis elegans healthspan. These include assessments of tissue integrity and functionality and resistance to a variety of biotic and abiotic stressors. We have chosen to include simple, rapid assays in this collection that can be easily undertaken in any C. elegans laboratory, and can be relied on to provide a preliminary but thorough insight into the healthspan of a population.

Mechanistic analysis of the search behaviour of Caenorhabditis elegans

A central question in movement research is how animals use information and movement to promote encounter success. Current random search theory identifies reorientation patterns as key to the compromise between optimizing encounters for both nearby and faraway targets, but how the balance between intrinsic motor programmes and previous environmental experience determines the occurrence of these reorientation behaviours remains unknown. We used high-resolution tracking and imaging data to describe the complete motor behaviour of Caenorhabditis elegans when placed in a novel environment (one in which food is absent). Movement in C. elegans is structured around different reorientation behaviours, and we measured how these contributed to changing search strategies as worms became familiar with their new environment. This behavioural transition shows that different reorientation behaviours are governed by two processes: (i) an environmentally informed 'extrinsic' strategy that is influenced by recent experience and that controls for area-restricted search behaviour, and (ii) a time-independent, 'intrinsic' strategy that reduces spatial oversampling and improves random encounter success. Our results show how movement strategies arise from a balance between intrinsic and extrinsic mechanisms, that search behaviour in C. elegans is initially determined by expectations developed from previous environmental experiences, and which reorientation behaviours are modified as information is acquired from new environments.