An automated system for measuring parameters of nematode sinusoidal movement

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.

Zebrafish and nematodes as whole organism models to measure developmental neurotoxicity

Despite the growing epidemiological evidence of an association between toxin exposure and developmental neurotoxicity (DNT), systematic testing of DNT is not mandatory in international regulations for admission of pharmaceuticals or industrial chemicals. However, to date around 200 compounds, ranging from pesticides, pharmaceuticals and industrial chemicals, have been tested for DNT in the current OECD test guidelines (TG-443 or TG-426). There are calls for the development of new approach methodologies (NAMs) for DNT, which has resulted in a DNT testing battery using in vitro human cell-based assays. These assays provide a means to elucidate the molecular mechanisms of toxicity in humans which is lacking in animal-based toxicity tests. However, cell-based assays do not represent all steps of the complex process leading to DNT. Validated models with a multi-organ network of pathways that interact at the molecular, cellular and tissue level at very specific timepoints in a life cycle are currently missing. Consequently, whole model organisms are being developed to screen for, and causally link, new molecular targets of DNT compounds and how they affect whole brain development and neurobehavioral endpoints. Given the practical and ethical restraints associated with vertebrate testing, lower animal models that qualify as 3 R (reduce, refine and replace) models, including the nematode (Caenorhabditis elegans) and the zebrafish (Danio rerio) will prove particularly valuable for unravelling toxicity pathways leading to DNT. Although not as complex as the human brain, these 3 R-models develop a complete functioning brain with numerous neurodevelopmental processes overlapping with human brain development. Importantly, the main signalling pathways relating to (neuro)development, metabolism and growth are highly conserved in these models. We propose the use of whole model organisms specifically zebrafish and C. elegans for DNT relevant endpoints.

How neurobehavior and brain development in alternative whole-organism models can contribute to prediction of developmental neurotoxicity

Developmental neurotoxicity (DNT) is not routinely evaluated in chemical risk assessment because current test paradigms for DNT require the use of mammalian models which are ethically controversial, expensive, and resource demanding. Consequently, efforts have focused on revolutionizing DNT testing through affordable novel alternative methods for risk assessment. The goal is to develop a DNT in vitro test battery amenable to high-throughput screening (HTS). Currently, the DNT in vitro test battery consists primarily of human cell-based assays because of their immediate relevance to human health. However, such cell-based assays alone are unable to capture the complexity of a developing nervous system. Whole organismal systems that qualify as 3 R (Replace, Reduce and Refine) models are urgently needed to complement cell-based DNT testing. These models can provide the necessary organismal context and be used to explore the impact of chemicals on brain function by linking molecular and/or cellular changes to behavioural readouts. The nematode Caenorhabditis elegans, the planarian Dugesia japonica, and embryos of the zebrafish Danio rerio are all suited to low-cost HTS and each has unique strengths for DNT testing. Here, we review the strengths and the complementarity of these organisms in a novel, integrative context and highlight how they can augment current cell-based assays for more comprehensive and robust DNT screening of chemicals. Considering the limitations of all in vitro test systems, we discuss how a smart combinatory use of these systems will contribute to a better human relevant risk assessment of chemicals that considers the complexity of the developing brain.

Rapid measurement of ageing by automated monitoring of movement of C. elegans populations

Finding new interventions that slow ageing and maintain human health is a huge challenge of our time. The nematode Caenorhabditis elegans offers a rapid in vivo method to determine whether a compound extends its 2 to 3-week lifespan. Measuring lifespan is the standard method to monitor ageing, but a compound that extends lifespan will not necessarily maintain health. Here, we describe the automated monitoring of C. elegans movement from early to mid-adulthood as a faster healthspan-based method to measure ageing. Using the WormGazer™ technology, multiple Petri dishes each containing several C. elegans worms are imaged simultaneously and non-invasively by an array of cameras that can be scaled easily. This approach demonstrates that most functional decline in C. elegans occurs during the first week of adulthood. We find 7 days of imaging is sufficient to measure the dose-dependent efficacy of sulfamethoxazole to slow ageing, compared to 40 days required for a parallel lifespan experiment. Understanding any negative consequences of interventions that slow ageing is important. We show that the long-lived mutant age-1(hx546) stays active for longer than the wild type but it moves slower in early adulthood. Thus, continuous analysis of movement can rapidly identify interventions that slow ageing while simultaneously revealing any negative effects on health.

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 .

Discovering sparse control strategies in neural activity

Biological circuits such as neural or gene regulation networks use internal states to map sensory input to an adaptive repertoire of behavior. Characterizing this mapping is a major challenge for systems biology. Though experiments that probe internal states are developing rapidly, organismal complexity presents a fundamental obstacle given the many possible ways internal states could map to behavior. Using C. elegans as an example, we propose a protocol for systematic perturbation of neural states that limits experimental complexity and could eventually help characterize collective aspects of the neural-behavioral map. We consider experimentally motivated small perturbations—ones that are most likely to preserve natural dynamics and are closer to internal control mechanisms—to neural states and their impact on collective neural activity. Then, we connect such perturbations to the local information geometry of collective statistics, which can be fully characterized using pairwise perturbations. Applying the protocol to a minimal model of C. elegans neural activity, we find that collective neural statistics are most sensitive to a few principal perturbative modes. Dominant eigenvalues decay initially as a power law, unveiling a hierarchy that arises from variation in individual neural activity and pairwise interactions. Highest-ranking modes tend to be dominated by a few, “pivotal” neurons that account for most of the system’s sensitivity, suggesting a sparse mechanism of collective control.

Megapixel camera arrays enable high-resolution animal tracking in multiwell plates

Tracking small laboratory animals such as flies, fish, and worms is used for phenotyping in neuroscience, genetics, disease modelling, and drug discovery. An imaging system with sufficient throughput and spatiotemporal resolution would be capable of imaging a large number of animals, estimating their pose, and quantifying detailed behavioural differences at a scale where hundreds of treatments could be tested simultaneously. Here we report an array of six 12-megapixel cameras that record all the wells of a 96-well plate with sufficient resolution to estimate the pose of C. elegans worms and to extract high-dimensional phenotypic fingerprints. We use the system to study behavioural variability across wild isolates, the sensitisation of worms to repeated blue light stimulation, the phenotypes of worm disease models, and worms' behavioural responses to drug treatment. Because the system is compatible with standard multiwell plates, it makes computational ethological approaches accessible in existing high-throughput pipelines.

A journey through 50 years of research relevant to the control of gastrointestinal nematodes in ruminant livestock and thoughts on future directions

This review article provides an historical perspective on some of the major research advances of relevance to ruminant livestock gastrointestinal nematode control over the last 50 years. Over this period, gastrointestinal nematode control has been dominated by the use of broad-spectrum anthelmintic drugs. Whilst this has provided unprecedented levels of successful control for many years, this approach has been gradually breaking down for more than two decades and is increasingly unsustainable which is due, at least in part, to the emergence of anthelmintic drug resistance and a number of other factors discussed in this article. We first cover the remarkable success story of the discovery and development of broad-spectrum anthelmintic drugs, the changing face of anthelmintic drug discovery research and the emergence of anthelmintic resistance. This is followed by a review of some of the major advances in the increasingly important area of non-pharmaceutical gastrointestinal nematode control including immunology and vaccine development, epidemiological modelling and some of the alternative control strategies such as breeding for host resistance, refugia-based methods and biological control. The last 50 years have witnessed remarkable innovation and success in research aiming to improve ruminant livestock gastrointestinal nematode control, particularly given the relatively small size of the research community and limited funding. In spite of this, the growing global demand for livestock products, together with the need to maximise production efficiencies, reduce environmental impacts and safeguard animal welfare - as well as specific challenges such as anthelmintic drug resistance and climate change- mean that gastrointestinal nematode researchers will need to be as innovative in the next 50 years as in the last.

Comparative toxicities of BPA, BPS, BPF, and TMBPF in the nematode Caenorhabditis elegans and mammalian fibroblast cells

Bisphenol A (BPA) is a chemical compound commonly used in the production of plastics for daily lives and industry. As BPA is well known for its adverse health effects, several alternative materials have been developed. This study comprehensively analyzed the toxicity of BPA and its three substitutes including bisphenol S (BPS), bisphenol F (BPF), and tetramethyl bisphenol F (TMBPF) on aging, healthspan, and mitochondria using an in vivo Caenorhabditis elegans (C. elegans) model animal and cultured mammalian fibroblast cells. C. elegans treated with 1 mM BPA exhibited abnormalities in the four tested parameters related to development and growth, including delayed development, decreased body growth, reduced reproduction, and abnormal tissue morphology. Exposure to the same concentration of each alternative including TMBPF, which has been proposed as a relatively safe BPA alternative, detrimentally affected at least three of these events. Moreover, all bisphenols (except BPS) remarkably shortened the organismal lifespan and increased age-related changes in neurons. Exposure to BPA and BPF resulted in mitochondrial abnormalities, such as reduced oxygen consumption and mitochondrial membrane potential. In contrast, the ATP levels were noticeably higher after treatment with all bisphenols. In mammalian fibroblast cells, exposure to increasing concentrations of all bisphenols (ranging from 50 μM to 500 μM) caused a severe decrease in cell viability in a dose-dependent manner. BPA increased ATP levels and decreased ROS but did not affect mitochondrial permeability transition pores (mPTP). Notably, TMBPF was the only bisphenol that caused a significant increase in mitochondrial ROS and mPTP opening. These results suggest that the potentially harmful physiological effects of BPA alternatives should be considered.

Mask R-CNN Based C. Elegans Detection with a DIY Microscope

Caenorhabditis elegans (C. elegans) is an important model organism for studying molecular genetics, developmental biology, neuroscience, and cell biology. Advantages of the model organism include its rapid development and aging, easy cultivation, and genetic tractability. C. elegans has been proven to be a well-suited model to study toxicity with identified toxic compounds closely matching those observed in mammals. For phenotypic screening, especially the worm number and the locomotion are of central importance. Traditional methods such as human counting or analyzing high-resolution microscope images are time-consuming and rather low throughput. The article explores the feasibility of low-cost, low-resolution do-it-yourself microscopes for image acquisition and automated evaluation by deep learning methods to reduce cost and allow high-throughput screening strategies. An image acquisition system is proposed within these constraints and used to create a large data-set of whole Petri dishes containing C. elegans. By utilizing the object detection framework Mask R-CNN, the nematodes are located, classified, and their contours predicted. The system has a precision of 0.96 and a recall of 0.956, resulting in an F1-Score of 0.958. Considering only correctly located C. elegans with an AP@0.5 IoU, the system achieved an average precision of 0.902 and a corresponding F1 Score of 0.906.

Small flexible automated system for monitoring Caenorhabditis elegans lifespan based on active vision and image processing techniques

Traditionally Caenorhabditis elegans lifespan assays are performed by manually inspecting nematodes with a dissection microscope, which involves daily counting of live/dead worms cultured in Petri plates for 21–25 days. This manual inspection requires the screening of hundreds of worms to ensure statistical robustness, and is therefore a time-consuming approach. In recent years, various automated artificial vision systems have been reported to increase the throughput, however they usually provide less accurate results than manual assays. The main problems identified when using these vision systems are the false positives and false negatives, which occur due to culture media changes, occluded zones, dirtiness or condensation of the Petri plates. In this work, we developed and described a new C. elegans monitoring machine, SiViS, which consists of a flexible and compact platform design to analyse C. elegans cultures using the standard Petri plates seeded with E. coli. Our system uses an active vision illumination technique and different image-processing pipelines for motion detection, both previously reported, providing a fully automated image processing pipeline. In addition, this study validated both these methods and the feasibility of the SiViS machine for lifespan experiments by comparing them with manual lifespan assays. Results demonstrated that the automated system yields consistent replicates (p-value log rank test 0.699), and there are no significant differences between automated system assays and traditionally manual assays (p-value 0.637). Finally, although we have focused on the use of SiViS in longevity assays, the system configuration is flexible and can, thus, be adapted to other C. elegans studies such as toxicity, mobility and behaviour.

A Neuromechanical Model of Multiple Network Rhythmic Pattern Generators for Forward Locomotion in C. elegans

Multiple mechanisms contribute to the generation, propagation, and coordination of the rhythmic patterns necessary for locomotion in Caenorhabditis elegans. Current experiments have focused on two possibilities: pacemaker neurons and stretch-receptor feedback. Here, we focus on whether it is possible that a chain of multiple network rhythmic pattern generators in the ventral nerve cord also contribute to locomotion. We use a simulation model to search for parameters of the anatomically constrained ventral nerve cord circuit that, when embodied and situated, can drive forward locomotion on agar, in the absence of pacemaker neurons or stretch-receptor feedback. Systematic exploration of the space of possible solutions reveals that there are multiple configurations that result in locomotion that is consistent with certain aspects of the kinematics of worm locomotion on agar. Analysis of the best solutions reveals that gap junctions between different classes of motorneurons in the ventral nerve cord can play key roles in coordinating the multiple rhythmic pattern generators.

Reducing Results Variance in Lifespan Machines: An Analysis of the Influence of Vibrotaxis on Wild-Type Caenorhabditis elegans for the Death Criterion

Nowadays, various artificial vision-based machines automate the lifespan assays of C. elegans. These automated machines present wider variability in results than manual assays because in the latter worms can be poked one by one to determine whether they are alive or not. Lifespan machines normally use a “dead or alive criterion” based on nematode position or pose changes, without poking worms. However, worms barely move on their last days of life, even though they are still alive. Therefore, a long monitoring period is necessary to observe motility in order to guarantee worms are actually dead, or a stimulus to prompt worm movement is required to reduce the lifespan variability measure. Here, a new automated vibrotaxis-based method for lifespan machines is proposed as a solution to prompt a motion response in all worms cultured on standard Petri plates in order to better distinguish between live and dead individuals. This simple automated method allows the stimulation of all animals through the whole plate at the same time and intensity, increasing the experiment throughput. The experimental results exhibited improved live-worm detection using this method, and most live nematodes (>93%) reacted to the vibration stimulus. This method increased machine sensitivity by decreasing results variance by approximately one half (from ±1 individual error per plate to ±0.6) and error in lifespan curve was reduced as well (from 2.6% to 1.2%).

Improving lifespan automation for Caenorhabditis elegans by using image processing and a post-processing adaptive data filter

Automated lifespan determination for C. elegans cultured in standard Petri dishes is challenging. Problems include occlusions of Petri dish edges, aggregation of worms, and accumulation of dirt (dust spots on lids) during assays, etc. This work presents a protocol for a lifespan assay, with two image-processing pipelines applied to different plate zones, and a new data post-processing method to solve the aforementioned problems. Specifically, certain steps in the culture protocol were taken to alleviate aggregation, occlusions, contamination, and condensation problems. This method is based on an active illumination system and facilitates automated image sequence analysis, does not need human threshold adjustments, and simplifies the techniques required to extract lifespan curves. In addition, two image-processing pipelines, applied to different plate zones, were employed for automated lifespan determination. The first image-processing pipeline was applied to a wall zone and used only pixel level information because worm size or shape features were unavailable in this zone. However, the second image-processing pipeline, applied to the plate centre, fused information at worm and pixel levels. Simple death event detection was used to automatically obtain lifespan curves from the image sequences that were captured once daily throughout the assay. Finally, a new post-processing method was applied to the extracted lifespan curves to filter errors. The experimental results showed that the errors in automated counting of live worms followed the Gaussian distribution with a mean of 2.91% and a standard deviation of ±12.73% per Petri plate. Post-processing reduced this error to 0.54 ± 8.18% per plate. The automated survival curve incurred an error of 4.62 ± 2.01%, while the post-process method reduced the lifespan curve error to approximately 2.24 ± 0.55%.

Autism-associated missense genetic variants impact locomotion and neurodevelopment in Caenorhabditis elegans

Autism spectrum disorder (ASD) involves thousands of alleles in over 850 genes, but the current functional inference tools are not sufficient to predict phenotypic changes. As a result, the causal relationship of most of these genetic variants in the pathogenesis of ASD has not yet been demonstrated and an experimental method prioritizing missense alleles for further intensive analysis is crucial. For this purpose, we have designed a pipeline that uses Caenorhabditis elegans as a genetic model to screen for phenotype-changing missense alleles inferred from human ASD studies. We identified highly conserved human ASD-associated missense variants in their C. elegans orthologs, used a CRISPR/Cas9-mediated homology-directed knock-in strategy to generate missense mutants and analyzed their impact on behaviors and development via several broad-spectrum assays. All tested missense alleles were predicted to perturb protein function, but we found only 70% of them showed detectable phenotypic changes in morphology, locomotion or fecundity. Our findings indicate that certain missense variants in the C. elegans orthologs of human CACNA1D, CHD7, CHD8, CUL3, DLG4, GLRA2, NAA15, PTEN, SYNGAP1 and TPH2 impact neurodevelopment and movement functions, elevating these genes as candidates for future study into ASD. Our approach will help prioritize functionally important missense variants for detailed studies in vertebrate models and human cells.

Drug discovery technologies: Caenorhabditis elegans as a model for anthelmintic therapeutics

Helminthiasis is one of the gravest problems worldwide. There is a growing concern on less available anthelmintics and the emergence of resistance creating a major threat to human and livestock health resources. Novel and broad-spectrum anthelmintics are urgently needed. The free-living nematode Caenorhabditis elegans could address this issue through automated high-throughput technologies for the screening of large chemical libraries. This review discusses the strong advantages and limitations for using C elegans as a screening method for anthelmintic drug discovery. C elegans is the best model available for the validation of novel effective drugs in treating most, if not all, helminth infections, and for the elucidation the mode of action of anthelmintic candidates. This review also focuses on available technologies in the discovery of anthelmintics published over the last 15 years with particular attention to high-throughput technologies over conventional screens. On the other hand, this review highlights how combinatorial and nanomedicine strategies could prolong the use of anthelmintics and control resistance problems.

Digging deeper: methodologies for high-content phenotyping in Caenorhabditis elegans

Deep phenotyping is an emerging conceptual paradigm and experimental approach aimed at measuring and linking many aspects of a phenotype to understand its underlying biology. To date, deep phenotyping has been applied mostly in cultured cells and used less in multicellular organisms. However, in the past decade, it has increasingly been recognized that deep phenotyping could lead to a better understanding of how genetics, environment and stochasticity affect the development, physiology and behavior of an organism. The nematode Caenorhabditis elegans is an invaluable model system for studying how genes affect a phenotypic trait, and new technologies have taken advantage of the worm's physical attributes to increase the throughput and informational content of experiments. Coupling of these technical advancements with computational and analytical tools has enabled a boom in deep-phenotyping studies of C. elegans. In this Review, we highlight how these new technologies and tools are digging into the biological origins of complex, multidimensional phenotypes.

Active backlight for automating visual monitoring: An analysis of a lighting control technique for Caenorhabditis elegans cultured on standard Petri plates

Lifespan and healthspan machines can undergo C. elegans image segmentation errors due to changes in lighting conditions, which produce non-uniform images. Most C. elegans monitoring machines use backlight techniques based on the transparency of both the container and media. Backlight illumination obtains high-contrast images with dark C. elegans and a bright background. However, changes in illumination or media transparency conditions can produce non-uniform images, which are currently alleviated by image processing techniques. Besides, these machines should avoid C. elegans exposure to light as much as possible because light stresses worms, and can even affect their lifespan, mainly when using (1) long exposure times, (2) high intensities or (3) wavelengths that come close to ultraviolet. However, if short exposure of worms to light is required for visual monitoring, then light can also be used as a movement stimulus. In this paper, an active backlight method is analysed. The proposed method consists of controlling the light intensities and wavelengths of an illumination dots matrix with PID regulators. These regulators adapt illumination to some changing conditions. The experimental results shows that this method simplifies the image segmentation problem because it is able to automatically compensate not only changes in media transparency throughout assay days, but also changes in ambient conditions, such as smooth condensation on the lid and light derivatives of the illumination source during its lifetime. In addition, the strategic application of wavelengths could be adapted for the requirements of each assay. For instance, a specific control strategy has been proposed to minimise stress to worms and trying to stimulate C. elegans movement in lifespan assays.

From head to tail: a neuromechanical model of forward locomotion in Caenorhabditis elegans

With 302 neurons and a near-complete reconstruction of the neural and muscle anatomy at the cellular level, Caenorhabditis elegans is an ideal candidate organism to study the neuromechanical basis of behaviour. Yet despite the breadth of knowledge about the neurobiology, anatomy and physics of C. elegans, there are still a number of unanswered questions about one of its most basic and fundamental behaviours: forward locomotion. How the rhythmic pattern is generated and propagated along the body is not yet well understood. We report on the development and analysis of a model of forward locomotion that integrates the neuroanatomy, neurophysiology and body mechanics of the worm. Our model is motivated by experimental analysis of the structure of the ventral cord circuitry and the effect of local body curvature on nearby motoneurons. We developed a neuroanatomically grounded model of the head motoneuron circuit and the ventral nerve cord circuit. We integrated the neural model with an existing biomechanical model of the worm's body, with updated musculature and stretch receptors. Unknown parameters were evolved using an evolutionary algorithm to match the speed of the worm on agar. We performed 100 evolutionary runs and consistently found electrophysiological configurations that reproduced realistic control of forward movement. The ensemble of successful solutions reproduced key experimental observations that they were not designed to fit, including the wavelength and frequency of the propagating wave. Analysis of the ensemble revealed that head motoneurons SMD and RMD are sufficient to drive dorsoventral undulations in the head and neck and that short-range posteriorly directed proprioceptive feedback is sufficient to propagate the wave along the rest of the body.This article is part of a discussion meeting issue 'Connectome to behaviour: modelling C. elegans at cellular resolution'.

Algorithmic Mapping and Characterization of the Drug-Induced Phenotypic-Response Space of Parasites Causing Schistosomiasis

Neglected tropical diseases, especially those caused by helminths, constitute some of the most common infections of the world's poorest people. Amongst these, schistosomiasis (bilharzia or 'snail fever'), caused by blood flukes of the genus Schistosoma, ranks second only to malaria in terms of human impact: two hundred million people are infected and close to 800 million are at risk of infection. Drug screening against helminths poses unique challenges: the parasite cannot be cloned and is difficult to target using gene knockouts or RNAi. Consequently, both lead identification and validation involve phenotypic screening, where parasites are exposed to compounds whose effects are determined through the analysis of the ensuing phenotypic responses. The efficacy of leads thus identified derives from one or more or even unknown molecular mechanisms of action. The two most immediate and significant challenges that confront the state-of-the-art in this area are: the development of automated and quantitative phenotypic screening techniques and the mapping and quantitative characterization of the totality of phenotypic responses of the parasite. In this paper, we investigate and propose solutions for the latter problem in terms of the following: (1) mathematical formulation and algorithms that allow rigorous representation of the phenotypic response space of the parasite, (2) application of graph-theoretic and network analysis techniques for quantitative modeling and characterization of the phenotypic space, and (3) application of the aforementioned methodology to analyze the phenotypic space of S. mansoni - one of the etiological agents of schistosomiasis, induced by compounds that target its polo-like kinase 1 (PLK 1) gene - a recently validated drug target. In our approach, first, bio-image analysis algorithms are used to quantify the phenotypic responses of different drugs. Next, these responses are linearly mapped into a low- dimensional space using Principle Component Analysis (PCA). The phenotype space is modeled using neighborhood graphs which are used to represent the similarity amongst the phenotypes. These graphs are characterized and explored using network analysis algorithms. We present a number of results related to both the nature of the phenotypic space of the S. mansoni parasite as well as algorithmic issues encountered in constructing and analyzing the phenotypic-response space. In particular, the phenotype distribution of the parasite was found to have a distinct shape and topology. We have also quantitatively characterized the phenotypic space by varying critical model parameters. Finally, these maps of the phenotype space allows visualization and reasoning about complex relationships between putative drugs and their system-wide effects and can serve as a highly efficient paradigm for assimilating and unifying information from phenotypic screens both during lead identification and lead optimization.

Self-organization in a bimotility mixture of model microswimmers

We study the cooperation and segregation dynamics in a bimotility mixture of microorganisms which swim at low Reynolds numbers via periodic deformations along the body. We employ a multiparticle collision dynamics method to simulate a two component mixture of artificial swimmers, termed as Taylor lines, which differ from each other only in the propulsion speed. The analysis reveals that a contribution of slower swimmers towards clustering, on average, is much larger as compared to the faster ones. We notice distinctive self-organizing dynamics, depending on the percentage difference in the speed of the two kinds. If this difference is large, the faster ones fragment the clusters of the slower ones in order to reach the boundary and form segregated clusters. Contrarily, when it is small, both kinds mix together at first, the faster ones usually leading the cluster and then gradually the slower ones slide out thereby also leading to segregation.

Effective drug combination for Caenorhabditis elegans nematodes discovered by output-driven feedback system control technique

Infections from parasitic nematodes (or roundworms) contribute to a significant disease burden and productivity losses for humans and livestock. The limited number of anthelmintics (or antinematode drugs) available today to treat these infections are rapidly losing their efficacy as multidrug resistance in parasites becomes a global health challenge. We propose an engineering approach to discover an anthelmintic drug combination that is more potent at killing wild-type Caenorhabditis elegans worms than four individual drugs. In the experiment, freely swimming single worms are enclosed in microfluidic drug environments to assess the centroid velocity and track curvature of worm movements. After analyzing the behavioral data in every iteration, the feedback system control (FSC) scheme is used to predict new drug combinations to test. Through a differential evolutionary search, the winning drug combination is reached that produces minimal centroid velocity and high track curvature, while requiring each drug in less than their EC₅₀ concentrations. The FSC approach is model-less and does not need any information on the drug pharmacology, signaling pathways, or animal biology. Toward combating multidrug resistance, the method presented here is applicable to the discovery of new potent combinations of available anthelmintics on C. elegans, parasitic nematodes, and other small model organisms.

Scalable electrophysiology in intact small animals with nanoscale suspended electrode arrays

Electrical measurements from large populations of animals would help reveal fundamental properties of the nervous system and neurological diseases. Small invertebrates are ideal for these large-scale studies; however, patch-clamp electrophysiology in microscopic animals typically requires invasive dissections and is low-throughput. To overcome these limitations, we present nano-SPEARs: suspended electrodes integrated into a scalable microfluidic device. Using this technology, we have made the first extracellular recordings of body-wall muscle electrophysiology inside an intact roundworm, Caenorhabditis elegans. We can also use nano-SPEARs to record from multiple animals in parallel and even from other species, such as Hydra littoralis. Furthermore, we use nano-SPEARs to establish the first electrophysiological phenotypes for C. elegans models for amyotrophic lateral sclerosis and Parkinson's disease, and show a partial rescue of the Parkinson's phenotype through drug treatment. These results demonstrate that nano-SPEARs provide the core technology for microchips that enable scalable, in vivo studies of neurobiology and neurological diseases.

Automated Wormscan

There has been a recent surge of interest in computer-aided rapid data acquisition to increase the potential throughput and reduce the labour costs of large scale Caenorhabditis elegans studies. We present Automated WormScan, a low-cost, high-throughput automated system using commercial photo scanners, which is extremely easy to implement and use, capable of scoring tens of thousands of organisms per hour with minimal operator input, and is scalable. The method does not rely on software training for image recognition, but uses the generation of difference images from sequential scans to identify moving objects. This approach results in robust identification of worms with little computational demand. We demonstrate the utility of the system by conducting toxicity, growth and fecundity assays, which demonstrate the consistency of our automated system, the quality of the data relative to manual scoring methods and congruity with previously published results.

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

BACKGROUND

With rapid advances in genome sequencing and editing technologies, systematic and quantitative analysis of animal behavior is expected to be another key to facilitating data-driven behavioral genetics. The nematode Caenorhabditis elegans is a model organism in this field. Several video-tracking systems are available for automatically recording behavioral data for the nematode, but computational methods for analyzing these data are still under development.

RESULTS

In this study, we applied the Gaussian mixture model-based binning method to time-series postural data for 322 C. elegans strains. We revealed that the occurrence patterns of the postural states and the transition patterns among these states have a relationship as expected, and such a relationship must be taken into account to identify strains with atypical behaviors that are different from those of wild type. Based on this observation, we identified several strains that exhibit atypical transition patterns that cannot be fully explained by their occurrence patterns of postural states. Surprisingly, we found that two simple factors-overall acceleration of postural movement and elimination of inactivity periods-explained the behavioral characteristics of strains with very atypical transition patterns; therefore, computational analysis of animal behavior must be accompanied by evaluation of the effects of these simple factors. Finally, we found that the npr-1 and npr-3 mutants have similar behavioral patterns that were not predictable by sequence homology, proving that our data-driven approach can reveal the functions of genes that have not yet been characterized.

CONCLUSION

We propose that elimination of inactivity periods and overall acceleration of postural change speed can explain behavioral phenotypes of strains with very atypical postural transition patterns. Our methods and results constitute guidelines for effectively finding strains that show "truly" interesting behaviors and systematically uncovering novel gene functions by bioimage-informatic approaches.

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.

SSBD: a database of quantitative data of spatiotemporal dynamics of biological phenomena

Motivation: Rapid advances in live-cell imaging analysis and mathematical modeling have produced a large amount of quantitative data on spatiotemporal dynamics of biological objects ranging from molecules to organisms. There is now a crucial need to bring these large amounts of quantitative biological dynamics data together centrally in a coherent and systematic manner. This will facilitate the reuse of this data for further analysis.

Results: We have developed the Systems Science of Biological Dynamics database (SSBD) to store and share quantitative biological dynamics data. SSBD currently provides 311 sets of quantitative data for single molecules, nuclei and whole organisms in a wide variety of model organisms from Escherichia coli to Mus musculus. The data are provided in Biological Dynamics Markup Language format and also through a REST API. In addition, SSBD provides 188 sets of time-lapse microscopy images from which the quantitative data were obtained and software tools for data visualization and analysis.

Availability and Implementation: SSBD is accessible at http://ssbd.qbic.riken.jp.

Contact:sonami@riken.jp

CAP protein superfamily members in Toxocara canis

BACKGROUND

Proteins of the cysteine-rich secretory proteins, antigen 5 and pathogenesis-related 1 (CAP) superfamily are recognized or proposed to play roles in parasite development and reproduction, and in modulating host immune attack and infection processes. However, little is known about these proteins for most parasites.

RESULTS

In the present study, we explored CAP proteins of Toxocara canis, a socioeconomically important zoonotic roundworm. To do this, we mined and curated transcriptomic and genomic data, predicted and curated full-length protein sequences (n = 28), conducted analyses of these data and studied the transcription of respective genes in different developmental stages of T. canis. In addition, based on information available for Caenorhabditis elegans, we inferred that selected genes (including lon-1, vap-1, vap-2, scl-1, scl-8 and scl-11 orthologs) of T. canis and their interaction partners likely play central roles in this parasite's development and/or reproduction via TGF-beta and/or insulin-like signaling pathways, or via host interactions.

CONCLUSION

In conclusion, this study could provide a foundation to guide future studies of CAP proteins of T. canis and related parasites, and might assist in finding new interventions against diseases caused by these parasites.

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.

C. elegans

Random search is a behavioral strategy used by organisms from bacteria to humans to locate food that is randomly distributed and undetectable at a distance. We investigated this behavior in the nematode Caenorhabditis elegans, an organism with a small, well-described nervous system. Here we formulate a mathematical model of random search abstracted from the C. elegans connectome and fit to a large-scale kinematic analysis of C. elegans behavior at submicron resolution. The model predicts behavioral effects of neuronal ablations and genetic perturbations, as well as unexpected aspects of wild type behavior. The predictive success of the model indicates that random search in C. elegans can be understood in terms of a neuronal flip-flop circuit involving reciprocal inhibition between two populations of stochastic neurons. Our findings establish a unified theoretical framework for understanding C. elegans locomotion and a testable neuronal model of random search that can be applied to other organisms.

An animal’s ability to rapidly and efficiently locate new sources of food in its environment can mean the difference between life and death. As a result, animals have evolved foraging strategies that are adapted to the distribution and detectability of food sources. Organisms ranging from bacteria to humans use one such strategy, called random search, to locate food that cannot be detected at a distance and that is randomly distributed in their surroundings. The biological mechanisms that underpin random search are relatively well understood in single-cell organisms such as bacteria, but this information tells us little about the mechanisms that are used by animals, which use their nervous system to control their foraging behavior.

Roberts et al. have now investigated the biological basis for random search behavior in a tiny roundworm called Caenorhabditis elegans. This worm forages for pockets of bacteria in decaying plant matter and has a simple and well-understood nervous system. Roberts et al. used information on how the cells in this worm’s nervous system connect together into so-called “neural circuits” to generate a mathematical model of random searching.

The model revealed that the worm’s neural circuitry for random searching can be understood in terms of two groups of neuron-like components that switch randomly between “ON” and “OFF” states. While one group promotes forward movement, the other promotes backward movement, which is associated with a change in search direction. These two groups inhibit each other so that only one group usually is active at a given time. By adjusting this model to reproduce the behavioral records of real worms searching for food, Roberts et al. could predict the key neuronal connections involved. These predictions were then confirmed by taking electrical recordings from neurons. The model could also account for the unexpected behavioral effects that are seen when a neuron in one of these groups was destroyed or altered by a genetic mutation.

These findings thus reveal a biological mechanism for random search behavior in worms that might operate in other animals as well. The findings might also provide future insight into the neural circuits involved in sleep and wakefulness in mammals, which is organized in a similar way.

Computational Methods for Tracking, Quantitative Assessment, and Visualization of C. elegans Locomotory Behavior

The nematode Caenorhabditis elegans provides a unique opportunity to interrogate the neural basis of behavior at single neuron resolution. In C. elegans, neural circuits that control behaviors can be formulated based on its complete neural connection map, and easily assessed by applying advanced genetic tools that allow for modulation in the activity of specific neurons. Importantly, C. elegans exhibits several elaborate behaviors that can be empirically quantified and analyzed, thus providing a means to assess the contribution of specific neural circuits to behavioral output. Particularly, locomotory behavior can be recorded and analyzed with computational and mathematical tools. Here, we describe a robust single worm-tracking system, which is based on the open-source Python programming language, and an analysis system, which implements path-related algorithms. Our tracking system was designed to accommodate worms that explore a large area with frequent turns and reversals at high speeds. As a proof of principle, we used our tracker to record the movements of wild-type animals that were freshly removed from abundant bacterial food, and determined how wild-type animals change locomotory behavior over a long period of time. Consistent with previous findings, we observed that wild-type animals show a transition from area-restricted local search to global search over time. Intriguingly, we found that wild-type animals initially exhibit short, random movements interrupted by infrequent long trajectories. This movement pattern often coincides with local/global search behavior, and visually resembles Lévy flight search, a search behavior conserved across species. Our mathematical analysis showed that while most of the animals exhibited Brownian walks, approximately 20% of the animals exhibited Lévy flights, indicating that C. elegans can use Lévy flights for efficient food search. In summary, our tracker and analysis software will help analyze the neural basis of the alteration and transition of C. elegans locomotory behavior in a food-deprived condition.

Tissue mechanics govern the rapidly adapting and symmetrical response to touch

Interactions with the physical world are deeply rooted in our sense of touch and depend on ensembles of somatosensory neurons that invade and innervate the skin. Somatosensory neurons convert the mechanical energy delivered in each touch into excitatory membrane currents carried by mechanoelectrical transduction (MeT) channels. Pacinian corpuscles in mammals and touch receptor neurons (TRNs) in Caenorhabditis elegans nematodes are embedded in distinctive specialized accessory structures, have low thresholds for activation, and adapt rapidly to the application and removal of mechanical loads. Recently, many of the protein partners that form native MeT channels in these and other somatosensory neurons have been identified. However, the biophysical mechanism of symmetric responses to the onset and offset of mechanical stimulation has eluded understanding for decades. Moreover, it is not known whether applied force or the resulting indentation activate MeT channels. Here, we introduce a system for simultaneously recording membrane current, applied force, and the resulting indentation in living C. elegans (Feedback-controlled Application of mechanical Loads Combined with in vivo Neurophysiology, FALCON) and use it, together with modeling, to study these questions. We show that current amplitude increases with indentation, not force, and that fast stimuli evoke larger currents than slower stimuli producing the same or smaller indentation. A model linking body indentation to MeT channel activation through an embedded viscoelastic element reproduces the experimental findings, predicts that the TRNs function as a band-pass mechanical filter, and provides a general mechanism for symmetrical and rapidly adapting MeT channel activation relevant to somatosensory neurons across phyla and submodalities.

The barber's pole worm CAP protein superfamily--A basis for fundamental discovery and biotechnology advances

Parasitic worm proteins that belong to the cysteine-rich secretory proteins, antigen 5 and pathogenesis-related 1 (CAP) superfamily are proposed to play key roles in the infection process and the modulation of immune responses in host animals. However, there is limited information on these proteins for most socio-economically important worms. Here, we review the CAP protein superfamily of Haemonchus contortus (barber's pole worm), a highly significant parasitic roundworm (order Strongylida) of small ruminants. To do this, we mined genome and transcriptomic datasets, predicted and curated full-length amino acid sequences (n=45), undertook systematic phylogenetic analyses of these data and investigated transcription throughout the life cycle of H. contortus. We inferred functions for selected Caenorhabditis elegans orthologs (including vap-1, vap-2, scl-5 and lon-1) based on genetic networking and by integrating data and published information, and were able to infer that a subset of orthologs and their interaction partners play pivotal roles in growth and development via the insulin-like and/or the TGF-beta signalling pathways. The identification of the important and conserved growth regulator LON-1 led us to appraise the three-dimensional structure of this CAP protein by comparative modelling. This model revealed the presence of different topological moieties on the canonical fold of the CAP domain, which coincide with an overall charge separation as indicated by the electrostatic surface potential map. These observations suggest the existence of separate sites for effector binding and receptor interactions, and thus support the proposal that these worm molecules act in similar ways as venoms act as ligands for chemokine receptors or G protein-coupled receptor effectors. In conclusion, this review should guide future molecular studies of these molecules, and could support the development of novel interventions against haemonchosis.

Cuticle integrity and biogenic amine synthesis in Caenorhabditis elegans require the cofactor tetrahydrobiopterin (BH4)

Tetrahydrobiopterin (BH4) is the natural cofactor of several enzymes widely distributed among eukaryotes, including aromatic amino acid hydroxylases (AAAHs), nitric oxide synthases (NOSs), and alkylglycerol monooxygenase (AGMO). We show here that the nematode Caenorhabditis elegans, which has three AAAH genes and one AGMO gene, contains BH4 and has genes that function in BH4 synthesis and regeneration. Knockout mutants for putative BH4 synthetic enzyme genes lack the predicted enzymatic activities, synthesize no BH4, and have indistinguishable behavioral and neurotransmitter phenotypes, including serotonin and dopamine deficiency. The BH4 regeneration enzymes are not required for steady-state levels of biogenic amines, but become rate limiting in conditions of reduced BH4 synthesis. BH4-deficient mutants also have a fragile cuticle and are generally hypersensitive to exogenous agents, a phenotype that is not due to AAAH deficiency, but rather to dysfunction in the lipid metabolic enzyme AGMO, which is expressed in the epidermis. Loss of AGMO or BH4 synthesis also specifically alters the sensitivity of C. elegans to bacterial pathogens, revealing a cuticular function for AGMO-dependent lipid metabolism in host-pathogen interactions.

An automated system for quantitative analysis of Drosophila larval locomotion

BACKGROUND

Drosophila larvae have been used as a model to study to genetic and cellular circuitries modulating behaviors. One of the challenges in behavioral study is the quantification of complex phenotypes such as locomotive behaviors. Experimental capability can be greatly enhanced by an automatic single-animal tracker that records an animal at a high resolution for an extended period, and analyzes multiple behavioral parameters.

RESULTS

Here we present MaggotTracker, a single-animal tracking system for Drosophila larval locomotion analysis. This system controls the motorized microscope stage while taking a video, so that the animal remains in the viewing center. It then reduces the animal to 13 evenly distributed points along the midline, and computes over 20 parameters evaluating the shape, peristalsis movement, stamina, and track of the animal. To demonstrate its utility, we applied MaggotTracker to analyze both wild-type and mutant animals to identify factors affecting locomotive behaviors. Each animal was tracked for four minutes. Our analysis on Canton-S third-instar larvae revealed that the distance an animal travelled was correlated to its striding speed rather than the percentage of time the animal spent striding, and that the striding speed was correlated to both the distance and the duration of one stride. Sexual dimorphism was observed in body length but not in locomotive parameters such as speed. Locomotive parameters were affected by animal developmental stage and the crawling surface. No significant changes in movement speed were detected in mutants of circadian genes such as period (per), timeout, and timeless (tim). The MaggotTracker analysis showed that ether a go-go (eag), Shaker (Sh), slowpoke (slo), and dunce (dnc) mutant larvae had severe phenotypes in multiple locomotive parameters such as stride distance and speed, consistent with their function in neuromuscular junctions. Further, the phenotypic patterns of the K(+) channel genes eag, Sh and slo are highly similar.

CONCLUSIONS

These results showed that MaggotTracker is an efficient tool for automatic phenotyping. The MaggotTracker software as well as the data presented here can be downloaded from our open-access site www.WormLoco.org/Mag.

Robust tracking and quantification of C. elegans body shape and locomotion through coiling, entanglement, and omega bends

The behavior of the well-characterized nematode, Caenorhabditis elegans (C. elegans), is often used to study the neurologic control of sensory and motor systems in models of health and neurodegenerative disease. To advance the quantification of behaviors to match the progress made in the breakthroughs of genetics, RNA, proteins, and neuronal circuitry, analysis must be able to extract subtle changes in worm locomotion across a population. The analysis of worm crawling motion is complex due to self-overlap, coiling, and entanglement. Using current techniques, the scope of the analysis is typically restricted to worms to their non-occluded, uncoiled state which is incomplete and fundamentally biased. Using a model describing the worm shape and crawling motion, we designed a deformable shape estimation algorithm that is robust to coiling and entanglement. This model-based shape estimation algorithm has been incorporated into a framework where multiple worms can be automatically detected and tracked simultaneously throughout the entire video sequence, thereby increasing throughput as well as data validity. The newly developed algorithms were validated against 10 manually labeled datasets obtained from video sequences comprised of various image resolutions and video frame rates. The data presented demonstrate that tracking methods incorporated in WormLab enable stable and accurate detection of these worms through coiling and entanglement. Such challenging tracking scenarios are common occurrences during normal worm locomotion. The ability for the described approach to provide stable and accurate detection of C. elegans is critical to achieve unbiased locomotory analysis of worm motion.

Caenorhabditis elegans segmentation using texture-based models for motility phenotyping

With widening interests in using model organisms for reverse genetic approaches and biomimmetic microrobotics, motility phenotyping of the nematode Caenorhabditis elegans is expanding across a growing array of locomotive environments. One ongoing bottleneck lies in providing users with automatic nematode segmentations of C. elegans in image sequences featuring complex and dynamic visual cues, a first and necessary step prior to extracting motility phenotypes. Here, we propose to tackle such automatic segmentation challenges by introducing a novel texture factor model (TFM). Our approach revolves around the use of combined intensity- and texture-based features integrated within a probabilistic framework. This strategy first provides a coarse nematode segmentation from which a Markov random field model is used to refine the segmentation by inferring pixels belonging to the nematode using an approximate inference technique. Finally, informative priors can then be estimated and integrated in our framework to provide coherent segmentations across image sequences. We validate our TFM method across a wide range of motility environments. Not only does TFM assure comparative performances to existing segmentation methods on traditional environments featuring static backgrounds, it importantly provides state-of-the-art C. elegans segmentations for dynamic environments such as the recently introduced wet granular media. We show how such segmentations may be used to compute nematode "skeletons" from which motility phenotypes can then be extracted. Overall, our TFM method provides users with a tangible solution to tackle the growing needs of C. elegans segmentation in challenging motility environments.

Size-dependent impacts of silver nanoparticles on the lifespan, fertility, growth, and locomotion of Caenorhabditis elegans

The increased bioavailability of nanoparticles engineered for good dispersion in water may have biological and environmental impacts. To examine this issue, the authors assessed the biological effects in nematodes as they relate to exposure to silver nanoparticles (AgNPs) of different sizes at low (1 mg/L Ag), medium (10 mg/L Ag), and high concentrations (100 mg/L Ag). Over multiple generations, the authors found that the smallest particle, at 2 nm, had a notable impact on nematode fertility. In contrast, the largest particle, at 10 nm, significantly reduced the lifespan of parent nematodes (P0 ) by 28.8% and over the span of 3 generations (F1 -F3). In addition, a computer vision system automatically measured the adverse effects in body length and motility, which were not size-dependent.

Automated, high-throughput, motility analysis in Caenorhabditis elegans and parasitic nematodes: Applications in the search for new anthelmintics

The scale of the damage worldwide to human health, animal health and agricultural crops resulting from parasitic nematodes, together with the paucity of treatments and the threat of developing resistance to the limited set of widely-deployed chemical tools, underlines the urgent need to develop novel drugs and chemicals to control nematode parasites. Robust chemical screens which can be automated are a key part of that discovery process. Hitherto, the successful automation of nematode behaviours has been a bottleneck in the chemical discovery process. As the measurement of nematode motility can provide a direct scalar readout of the activity of the neuromuscular system and an indirect measure of the health of the animal, this omission is acute. Motility offers a useful assay for high-throughput, phenotypic drug/chemical screening and several recent developments have helped realise, at least in part, the potential of nematode-based drug screening. Here we review the challenges encountered in automating nematode motility and some important developments in the application of machine vision, statistical imaging and tracking approaches which enable the automated characterisation of nematode movement. Such developments facilitate automated screening for new drugs and chemicals aimed at controlling human and animal nematode parasites (anthelmintics) and plant nematode parasites (nematicides).

Biological Dynamics Markup Language (BDML): an open format for representing quantitative biological dynamics data

Motivation: Recent progress in live-cell imaging and modeling techniques has resulted in generation of a large amount of quantitative data (from experimental measurements and computer simulations) on spatiotemporal dynamics of biological objects such as molecules, cells and organisms. Although many research groups have independently dedicated their efforts to developing software tools for visualizing and analyzing these data, these tools are often not compatible with each other because of different data formats.

Results: We developed an open unified format, Biological Dynamics Markup Language (BDML; current version: 0.2), which provides a basic framework for representing quantitative biological dynamics data for objects ranging from molecules to cells to organisms. BDML is based on Extensible Markup Language (XML). Its advantages are machine and human readability and extensibility. BDML will improve the efficiency of development and evaluation of software tools for data visualization and analysis.

Availability and implementation: A specification and a schema file for BDML are freely available online at http://ssbd.qbic.riken.jp/bdml/.

Contact:sonami@riken.jp

Supplementary Information:Supplementary data are available at Bioinformatics online.

An integrated in vitro imaging platform for characterizing filarial parasite behavior within a multicellular microenvironment

Lymphatic Filariasis, a Neglected Tropical Disease, is caused by thread-like parasitic worms, including B. malayi, which migrate to the human lymphatic system following transmission. The parasites reside in collecting lymphatic vessels and lymph nodes for years, often resulting in lymphedema, elephantiasis or hydrocele. The mechanisms driving worm migration and retention within the lymphatics are currently unknown. We have developed an integrated in vitro imaging platform capable of quantifying B. malayi migration and behavior in a multicellular microenvironment relevant to the initial site of worm injection by incorporating the worm in a Polydimethylsiloxane (PDMS) microchannel in the presence of human dermal lymphatic endothelial cells (LECs) and human dermal fibroblasts (HDFs). The platform utilizes a motorized controllable microscope with CO2 and temperature regulation to allow for worm tracking experiments with high resolution over large length and time scales. Using post-acquisition algorithms, we quantified four parameters: 1) speed, 2) thrashing intensity, 3) percentage of time spent in a given cell region and 4) persistence ratio. We demonstrated the utility of our system by quantifying these parameters for L3 B. malayi in the presence of LECs and HDFs. Speed and thrashing increased in the presence of both cell types and were altered within minutes upon exposure to the anthelmintic drug, tetramisole. The worms displayed no targeted migration towards either cell type for the time course of this study (3 hours). When cells were not present in the chamber, worm thrashing correlated directly with worm speed. However, this correlation was lost in the presence of cells. The described platform provides the ability to further study B. malayi migration and behavior.

CeleST: computer vision software for quantitative analysis of C. elegans swim behavior reveals novel features of locomotion

In the effort to define genes and specific neuronal circuits that control behavior and plasticity, the capacity for high-precision automated analysis of behavior is essential. We report on comprehensive computer vision software for analysis of swimming locomotion of C. elegans, a simple animal model initially developed to facilitate elaboration of genetic influences on behavior. C. elegans swim test software CeleST tracks swimming of multiple animals, measures 10 novel parameters of swim behavior that can fully report dynamic changes in posture and speed, and generates data in several analysis formats, complete with statistics. Our measures of swim locomotion utilize a deformable model approach and a novel mathematical analysis of curvature maps that enable even irregular patterns and dynamic changes to be scored without need for thresholding or dropping outlier swimmers from study. Operation of CeleST is mostly automated and only requires minimal investigator interventions, such as the selection of videotaped swim trials and choice of data output format. Data can be analyzed from the level of the single animal to populations of thousands. We document how the CeleST program reveals unexpected preferences for specific swim “gaits” in wild-type C. elegans, uncovers previously unknown mutant phenotypes, efficiently tracks changes in aging populations, and distinguishes “graceful” from poor aging. The sensitivity, dynamic range, and comprehensive nature of CeleST measures elevate swim locomotion analysis to a new level of ease, economy, and detail that enables behavioral plasticity resulting from genetic, cellular, or experience manipulation to be analyzed in ways not previously possible.

Distributed effects of biological sex define sex-typical motor behavior in Caenorhabditis elegans

Sex differences in shared behaviors (for example, locomotion and feeding) are a nearly universal feature of animal biology. Though these behaviors may share underlying neural programs, their kinematics can exhibit robust differences between males and females. The neural underpinnings of these differences are poorly understood because of the often-untested assumption that they are determined by sex-specific body morphology. Here, we address this issue in the nematode Caenorhabditis elegans, which features two sexes with distinct body morphologies but similar locomotor circuitry and body muscle. Quantitative behavioral analysis shows that C. elegans and related nematodes exhibit significant sex differences in the dynamics and geometry of locomotor body waves, such that the male is generally faster. Using a recently proposed model of locomotor wave propagation, we show that sex differences in both body mechanics and the intrinsic dynamics of the motor system can contribute to kinematic differences in distinct mechanical contexts. By genetically sex-reversing the properties of specific tissues and cells, however, we find that sex-specific locomotor frequency in C. elegans is determined primarily by the functional modification of shared sensory neurons. Further, we find that sexual modification of body wall muscle together with the nervous system is required to alter body wave speed. Thus, rather than relying on a single focus of modification, sex differences in motor dynamics require independent modifications to multiple tissue types. Our results suggest shared motor behaviors may be sex-specifically optimized though distributed modifications to several aspects of morphology and physiology.

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.

Toxicity testing of neurotoxic pesticides in Caenorhabditis elegans

The use of pesticides is ubiquitous worldwide, and these chemicals exert adverse effects on both target and nontarget species. Understanding the modes of action of pesticides, as well as quantifying exposure concentration and duration, is an important goal of clinicians and environmental health scientists. Some chemical exposures result in adverse effects on the nervous system. The nematode Caenorhabditis elegans (C. elegans) is a model lab organism well established for studying neurotoxicity, since the components of its nervous system are mapped and known, and most of its neurotransmitters correspond to human homologs. This review encompasses published studies in which C. elegans nematodes were exposed to pesticides with known neurotoxic actions. Endpoints measured include changes in locomotion, feeding behavior, brood size, growth, life span, and cell death. From data presented, evidence indicates that C. elegans can serve a role in assessing the effects of neurotoxic pesticides at the sublethal cellular level, thereby advancing our understanding of the mechanisms underlying toxicity induced by these chemicals. A proposed toxicity testing scheme for water-soluble chemicals is also included.

Synaptic polarity of the interneuron circuit controlling C. elegans locomotion

Caenorhabditis elegans is the only animal for which a detailed neural connectivity diagram has been constructed. However, synaptic polarities in this diagram, and thus, circuit functions are largely unknown. Here, we deciphered the likely polarities of seven pre-motor neurons implicated in the control of worm's locomotion, using a combination of experimental and computational tools. We performed single and multiple laser ablations in the locomotor interneuron circuit and recorded times the worms spent in forward and backward locomotion. We constructed a theoretical model of the locomotor circuit and searched its all possible synaptic polarity combinations and sensory input patterns in order to find the best match to the timing data. The optimal solution is when either all or most of the interneurons are inhibitory and forward interneurons receive the strongest input, which suggests that inhibition governs the dynamics of the locomotor interneuron circuit. From the five pre-motor interneurons, only AVB and AVD are equally likely to be excitatory, i.e., they have probably similar number of inhibitory and excitatory connections to distant targets. The method used here has a general character and thus can be also applied to other neural systems consisting of small functional networks.

Developing a rapid throughput screen for detection of nematicidal activity of plant cysteine proteinases: the role of Caenorhabditis elegans cystatins

Plant cysteine proteinases (CPs) from papaya (Carica papaya) are capable of killing parasitic nematode worms in vitro and have been shown to possess anthelmintic effects in vivo. The acute damage reported in gastrointestinal parasites has not been found in free-living nematodes such as Caenorhabditis elegans nor among the free-living stages of parasitic nematodes. This apparent difference in susceptibility might be the result of active production of cysteine proteinase inhibitors (such as cystatins) by the free-living stages or species. To test this possibility, a supernatant extract of refined papaya latex (PLS) with known active enzyme content was used. The effect on wild-type (Bristol N2) and cystatin null mutant (cpi-1(-/-) and cpi-2(-/-)) C. elegans was concentration-, temperature- and time-dependent. Cysteine proteinases digested the worm cuticle leading to release of internal structures and consequent death. Both cystatin null mutant strains were highly susceptible to PLS attack irrespective of the temperature and concentration of exposure, whereas wild-type N2 worms were generally resistant but far more susceptible to attack at low temperatures. PLS was able to induce elevated cpi-1 and cpi-2 cystatin expression. We conclude that wild-type C. elegans deploy cystatins CPI-1 and CPI-2 to resist CP attack. The results suggest that the cpi-1 or cpi-2 null mutants (or a double mutant combination of the two) could provide a cheap and effective rapid throughput C. elegans-based assay for screening plant CP extracts for anthelmintic activity.