58 results found
Barlow I, Feriani L, Minga E, et al., 2022, Megapixel camera arrays enable high-resolution animal tracking in multiwell plates, Communications Biology, Vol: 5, ISSN: 2399-3642
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.
Nambyiah P, Brown AEX, 2021, Quantitative behavioural phenotyping to investigate anaesthesia induced neurobehavioural impairment, Scientific Reports, Vol: 11, Pages: 1-10, ISSN: 2045-2322
Anaesthesia exposure to the developing nervous system causes neuroapoptosis and behavioural impairment in vertebrate models. Mechanistic understanding is limited, and target-based approaches are challenging. High-throughput methods may be an important parallel approach to drug-discovery and mechanistic research. The nematode worm Caenorhabditis elegans is an ideal candidate model. A rich subset of its behaviour can be studied, and hundreds of behavioural features can be quantified, then aggregated to yield a ‘signature’. Perturbation of this behavioural signature may provide a tool that can be used to quantify the effects of anaesthetic regimes, and act as an outcome marker for drug screening and molecular target research. Larval C. elegans were exposed to: isoflurane, ketamine, morphine, dexmedetomidine, and lithium (and combinations). Behaviour was recorded, and videos analysed with automated algorithms to extract behavioural features. Anaesthetic exposure during early development leads to persisting behavioural variation (in total, 125 features across exposure combinations). Higher concentrations, and combinations of isoflurane with ketamine, lead to persistent change in a greater number of features. Morphine and dexmedetomidine do not appear to lead to behavioural impairment. Lithium rescues the neurotoxic phenotype produced by isoflurane. Findings correlate well with vertebrate research: impairment is dependent on agent, is concentration-specific, is more likely with combination therapies, and can potentially be rescued by lithium. These results suggest that C. elegans may be an appropriate model with which to pursue phenotypic screens for drugs that mitigate the neurobehavioural impairment. Some possibilities are suggested for how high-throughput platforms might be organised in service of this field.
McDermott-Rouse A, Minga E, Barlow I, et al., 2021, Behavioral fingerprints predict insecticide and anthelmintic mode of action, Molecular Systems Biology, Vol: 17, Pages: 1-14, ISSN: 1744-4292
Novel invertebrate-killing compounds are required in agriculture and medicine to overcome resistance to existing treatments. Because insecticides and anthelmintics are discovered in phenotypic screens, a crucial step in the discovery process is determining the mode of action of hits. Visible whole-organism symptoms are combined with molecular and physiological data to determine mode of action. However, manual symptomology is laborious and requires symptoms that are strong enough to see by eye. Here, we use high-throughput imaging and quantitative phenotyping to measure Caenorhabditis elegans behavioral responses to compounds and train a classifier that predicts mode of action with an accuracy of 88% for a set of ten common modes of action. We also classify compounds within each mode of action to discover substructure that is not captured in broad mode-of-action labels. High-throughput imaging and automated phenotyping could therefore accelerate mode-of-action discovery in invertebrate-targeting compound development and help to refine mode-of-action categories.
Hadjieconomou D, King G, Gaspar P, et al., 2020, Enteric neurons increase maternal food intake during reproduction (vol 587, pg 455, 2020), Nature, Vol: 588, Pages: E36-E36, ISSN: 0028-0836
Miguel-Aliaga I, Hadjieconomou D, King G, et al., 2020, Enteric neurons increase maternal food intake during reproduction, Nature, Vol: 587, Pages: 455-459, ISSN: 0028-0836
Reproduction induces increased food intake across females of many animal species1,2,3,4, providing a physiologically relevant paradigm for the exploration of appetite regulation. Here, by examining the diversity of enteric neurons in Drosophila melanogaster, we identify a key role for gut-innervating neurons with sex- and reproductive state-specific activity in sustaining the increased food intake of mothers during reproduction. Steroid and enteroendocrine hormones functionally remodel these neurons, which leads to the release of their neuropeptide onto the muscles of the crop—a stomach-like organ—after mating. Neuropeptide release changes the dynamics of crop enlargement, resulting in increased food intake, and preventing the post-mating remodelling of enteric neurons reduces both reproductive hyperphagia and reproductive fitness. The plasticity of enteric neurons is therefore key to reproductive success. Our findings provide a mechanism to attain the positive energy balance that sustains gestation, dysregulation of which could contribute to infertility or weight gain.
Marques F, Thapliyal S, Javer A, et al., 2020, Tissue-specific isoforms of the single C. elegans Ryanodine receptor gene unc-68 control specific functions, PLoS Genetics, Vol: 16, Pages: 1-21, ISSN: 1553-7390
Ryanodine receptors (RyR) are essential regulators of cellular calcium homeostasis and signaling. Vertebrate genomes contain multiple RyR gene isoforms, expressed in different tissues and executing different functions. In contrast, invertebrate genomes contain a single RyR-encoding gene and it has long been proposed that different transcripts generated by alternative splicing may diversify their functions. Here, we analyze the expression and function of alternative exons in the C. elegans RyR gene unc-68. We show that specific isoform subsets are created via alternative promoters and via alternative splicing in unc-68 Divergent Region 2 (DR2), which actually corresponds to a region of high sequence variability across vertebrate isoforms. The expression of specific unc-68 alternative exons is enriched in different tissues, such as in body wall muscle, neurons and pharyngeal muscle. In order to infer the function of specific alternative promoters and alternative exons of unc-68, we selectively deleted them by CRISPR/Cas9 genome editing. We evaluated pharyngeal function, as well as locomotor function in swimming and crawling with high-content computer-assisted postural and behavioral analysis. Our data provide a comprehensive map of the pleiotropic impact of isoform-specific mutations and highlight that tissue-specific unc-68 isoforms fulfill distinct functions. As a whole, our work clarifies how the C. elegans single RyR gene unc-68 can fulfill multiple tasks through tissue-specific isoforms, and provide a solid foundation to further develop C. elegans as a model to study RyR channel functions and malfunctions.
Li Y, Osuma A, Correa E, et al., 2020, Establishment and maintenance of motor neuron identity via temporal modularity in terminal selector function, eLife, Vol: 9, ISSN: 2050-084X
Terminal selectors are transcription factors (TFs) that establish during development and maintain throughout life post-mitotic neuronal identity. We previously showed that UNC-3/Ebf, the terminal selector of C. elegans cholinergic motor neurons (MNs), acts indirectly to prevent alternative neuronal identities (Feng et al., 2020). Here, we globally identify the direct targets of UNC-3. Unexpectedly, we find that the suite of UNC-3 targets in MNs is modified across different life stages, revealing 'temporal modularity' in terminal selector function. In all larval and adult stages examined, UNC-3 is required for continuous expression of various protein classes (e.g. receptors, transporters) critical for MN function. However, only in late larvae and adults, UNC-3 is required to maintain expression of MN-specific TFs. Minimal disruption of UNC-3's temporal modularity via genome engineering affects locomotion. Another C. elegans terminal selector (UNC-30/Pitx) also exhibits temporal modularity, supporting the potential generality of this mechanism for the control of neuronal identity.
Newton H, Wang Y-F, Camplese L, et al., 2020, Systemic muscle wasting and coordinated tumour response drive tumourigenesis, Nature Communications, Vol: 11, ISSN: 2041-1723
Cancer cells demand excess nutrients to support their proliferation, but how tumours exploit extracellular amino acids during systemic metabolic perturbations remain incompletely understood. Here, we use a Drosophila model of high-sugar diet (HSD)-enhanced tumourigenesis to uncover a systemic host-tumour metabolic circuit that supports tumour growth. We demonstrate coordinate induction of systemic muscle wasting with tumour-autonomous Yorkie-mediated SLC36-family amino acid transporter expression as a proline-scavenging programme to drive tumourigenesis. We identify Indole-3-propionic acid as an optimal amino acid derivative to rationally target the proline-dependency of tumour growth. Insights from this whole-animal Drosophila model provide a powerful approach towards the identification and therapeutic exploitation of the amino acid vulnerabilities of tumourigenesis in the context of a perturbed systemic metabolic network.
Ding SS, Muhle LS, Brown A, et al., 2020, Comparison of solitary and collective foraging strategies of Caenorhabditis elegans in patchy food distributions, Philosophical Transactions of the Royal Society B: Biological Sciences, Vol: 375, ISSN: 0962-8436
Collective foraging has been shown to benefit organisms in environments where food is patchily distributed, but whether this is true in the case where organisms do not rely on long range communications to coordinate their collective behaviour has been understudied. To address this question, we use the tractable laboratory model organism Caenorhabditis elegans, where a social strain (npr-1 mutant) and a solitary strain (N2) are available for directcomparison of foraging strategies. We first developed an on-lattice minimal model for comparing collective and solitary foraging strategies, finding that social agents benefit from feeding faster and more efficiently simply due to group formation. Our laboratory foraging experiments with npr-1 and N2 worm populations, however, show an advantage for solitary N2 in all food distribution environments that we tested. We incorporated additional strain43 specific behavioural parameters of npr-1 and N2 worms into our model and computationally identified N2’s higher feeding rate to be the key factor underlying its advantage, without which it is possible to recapitulate the advantage of collective foraging in patchy environments. Our work highlights the theoretical advantage of collective foraging due to group formation alone without long-range interactions, and the valuable role of modelling to guide experiments.
Martineau CN, Brown AEX, Laurent P, 2020, Multidimensional phenotyping predicts lifespan and quantifies health in C. elegans, PLoS Computational Biology, Vol: 16, ISSN: 1553-734X
Ageing affects a wide range of phenotypes at all scales, but an objective measure of ageing remains challenging, even in simple model organisms. To measure the ageing process, we characterized the sequence of alterations of multiple phenotypes at organismal scale. Hundreds of morphological, postural, and behavioral features were extracted from high-resolution videos. Out of the 1019 features extracted, 896 are ageing biomarkers, defined as those that show a significant correlation with relative age (age divided by lifespan). We used support vector regression to predict age, remaining life and lifespan of individual C. elegans. The quality of these predictions (age R2 = 0.79; remaining life R2 = 0.77; lifespan R2 = 0.72) increased with the number of features added to the model, supporting the use of multiple features to quantify ageing. We quantified the rate of ageing as how quickly animals moved through a phenotypic space; we quantified health decline as the slope of the declining predicted remaining life. In both ageing dimensions, we found that short lived-animals aged faster than long-lived animals. In our conditions, for isogenic wild-type worms, the health decline of the individuals was scaled to their lifespan without significant deviation from the average for short- or long-lived animals.
Essmann CL, Martinez-Martinez D, Pryor R, et al., 2020, Mechanical properties measured by Atomic Force Microscopy define health biomarkers in ageing C. elegans, Nature Communications, Vol: 11, Pages: 1-16, ISSN: 2041-1723
Genetic and environmental factors are key drivers regulating organismal lifespan but how these impact healthspan is less well understood. Techniques capturing biomechanical properties of tissues on a nano-scale level are providing new insights into disease mechanisms. Here, we apply Atomic Force Microscopy (AFM) to quantitatively measure the change in biomechanical properties associated with ageing Caenorhabditis elegans in addition to capturing high-resolution topographical images of cuticle senescence. We show that distinct dietary restriction regimes and genetic pathways that increase lifespan lead to radically different healthspan outcomes. Hence, our data support the view that prolonged lifespan does not always coincide with extended healthspan. Importantly, we identify the insulin signalling pathway in C. elegans and interventions altering bacterial physiology as increasing both lifespan and healthspan. Overall, AFM provides a highly sensitive technique to measure organismal biomechanical fitness and delivers an approach to screen for health-improving conditions, an essential step towards healthy ageing.
Ding SS, Romenskyy M, Sarkisyan KS, et al., 2020, Measuring Caenorhabditis elegans spatial foraging and food intake using bioluminescent bacteria, Genetics, ISSN: 0016-6731
For most animals, feeding includes two behaviors: foraging to find a food patch and food intake once a patch is found. The nematode Caenorhabditis elegans is a useful model for studying the genetics of both behaviors. However, most methods of measuring feeding in worms quantify either foraging behavior or food intake but not both. Imaging the depletion of fluorescently labeled bacteria provides information on both the distribution and amount of consumption, but even after patch exhaustion a prominent background signal remains, which complicates quantification. Here, we used a bioluminescent Escherichia coli strain to quantify C. elegans feeding. With light emission tightly coupled to active metabolism, only living bacteria are capable of bioluminescence so the signal is lost upon ingestion. We quantified the loss of bioluminescence using N2 reference worms and eat-2 mutants, and found a nearly 100-fold increase in signal-to-background ratio and lower background compared to loss of fluorescence. We also quantified feeding using aggregating npr-1 mutant worms. We found that groups of npr-1 mutants first clear bacteria from within the cluster before foraging collectively for more food; similarly, during large population swarming, only worms at the migrating front are in contact with bacteria. These results demonstrate the usefulness of bioluminescent bacteria for quantifying feeding and for generating insights into the spatial pattern of food consumption.
Feng W, Li Y, Dao P, et al., 2020, A terminal selector prevents a Hox transcriptional switch to safeguard motor neuron identity throughout life, eLife, Vol: 9, ISSN: 2050-084X
To become and remain functional, individual neuron types must select during development and maintain throughout life their distinct terminal identity features, such as expression of specific neurotransmitter receptors, ion channels and neuropeptides. Here, we report a molecular mechanism that enables cholinergic motor neurons (MNs) in the C. elegans ventral nerve cord to select and maintain their unique terminal identity. This mechanism relies on the dual function of the conserved terminal selector UNC-3 (Collier/Ebf). UNC-3 synergizes with LIN-39 (Scr/Dfd/Hox4-5) to directly co-activate multiple terminal identity traits specific to cholinergic MNs, but also antagonizes LIN-39's ability to activate terminal features of alternative neuronal identities. Loss of unc-3 causes a switch in the transcriptional targets of LIN-39, thereby alternative, not cholinergic MN-specific, terminal features become activated and locomotion defects occur. The strategy of a terminal selector preventing a transcriptional switch may constitute a general principle for safeguarding neuronal identity throughout life.
Ding SS, Sarkisyan K, Brown A, 2019, Measuring C. elegans spatial foraging and food intake using bioluminescent bacteria, Publisher: bioRxiv
ABSTRACT For most animals, feeding includes two behaviours: foraging to find a food patch and food intake once a patch is found. The nematode Caenorhabditis elegans is a useful model for studying the genetics of both behaviours. However, most methods of measuring feeding in worms quantify either foraging behaviour or food intake but not both. Imaging the depletion of fluorescently labelled bacteria provides information on both the distribution and amount of consumption, but even after patch exhaustion a prominent background signal remains, which complicates quantification. Here, we used a bioluminescent Escherichia coli strain to quantify C. elegans feeding. With light emission tightly coupled to active metabolism, only living bacteria are capable of bioluminescence so the signal is lost upon ingestion. We quantified the loss of bioluminescence using N2 reference worms and eat-2 mutants, and found a nearly 100-fold increase in signal-to-background ratio and lower background compared to loss of fluorescence. We also quantified feeding using aggregating npr-1 mutant worms. We found that groups of npr-1 mutants first clear bacteria from each other before foraging collectively for more food; similarly, during high density swarming, only worms at the migrating front are in contact with bacteria. These results demonstrate the usefulness of bioluminescent bacteria for quantifying feeding and suggest a hygiene hypothesis for the function of C. elegans aggregation and swarming.
Ding SS, Muhle L, Brown A, et al., 2019, Comparison of solitary and collective foraging strategies of Caenorhabditis elegansin patchy food distributions, Publisher: bioRxiv
Abstract The benefits of social behaviour in insects and vertebrates are well-documented in terms of mating success and predator avoidance. Social foraging has also been shown to benefit organisms in environments where food is patchily distributed, but whether this is true in the case where organisms do not rely on long-range communications to coordinate their social behaviour has been understudied. To address this question, we use the tractable laboratory model organism Caenorhabditis elegans , where a social strain ( npr-1 mutant) and a solitary strain (N2) are available for direct comparison of foraging strategies. We first develop an on-lattice minimal model for comparing social and solitary feeding strategies, finding that social agents benefit from feeding faster and more efficiently simply due to group formation. To compare these simulation results with real experimental data, we modify our minimal model to incorporate the specific feeding behaviours of the npr-1 and N2 strains. Surprisingly, the resultant strain-specific model predicts that the solitary strain performs better than the social one in all food distribution environments that we tested, which we confirm with lab experiments. Additional computational experiments identify the N2 strain’s higher feeding rate to be the key factor underlying its advantage over npr-1 worms. Our work highlights the difficulties in addressing questions of optimal behaviour, and the valuable role of modelling as a guiding principle.
Ding SS, Schumacher L, Javer A, et al., 2019, Shared behavioral mechanisms underlie C. elegans aggregation and swarming, eLife, Vol: 8, ISSN: 2050-084X
In complex biological systems, simple individual-level behavioral rules can give rise to emergent group-level behavior. While collective behavior has been well studied in cells and larger organisms, the mesoscopic scale is less understood, as it is unclear which sensory inputs and physical processes matter a priori. Here, we investigate collective feeding in the roundworm C. elegans at this intermediate scale, using quantitative phenotyping and agent-based modeling to identify behavioral rules underlying both aggregation and swarming—a dynamic phenotype only observed at longer timescales. Using fluorescence multi-worm tracking, we quantify aggregation in terms of individual dynamics and population-level statistics. Then we use agent-based simulations and approximate Bayesian inference to identify three key behavioral rules for aggregation: cluster-edge reversals, a density-dependent switch between crawling speeds, and taxis towards neighboring worms. Our simulations suggest that swarming is simply driven by local food depletion but otherwise employs the same behavioral mechanisms as the initial aggregation.
Javer A, Brown AEX, Kokkinos I, et al., 2019, Identification of C. elegans Strains Using a Fully Convolutional Neural Network on Behavioural Dynamics, 15th European Conference on Computer Vision (ECCV), Publisher: SPRINGER INTERNATIONAL PUBLISHING AG, Pages: 455-464, ISSN: 0302-9743
Chew YL, Grundy LJ, Brown AEX, et al., 2018, Neuropeptides encoded by nlp-49 modulate locomotion, arousal and egg-laying behaviours in Caenorhabditis elegans via the receptor SEB-3, Philosophical Transactions of the Royal Society of London: Biological Sciences, Vol: 373, ISSN: 0962-8436
Neuropeptide signalling has been implicated in a wide variety of biological processes in diverse organisms, from invertebrates to humans. The Caenorhabditis elegans genome has at least 154 neuropeptide precursor genes, encoding over 300 bioactive peptides. These neuromodulators are thought to largely signal beyond ‘wired’ chemical/electrical synapse connections, therefore creating a ‘wireless’ network for neuronal communication. Here, we investigated how behavioural states are affected by neuropeptide signalling through the G protein-coupled receptor SEB-3, which belongs to a bilaterian family of orphan secretin receptors. Using reverse pharmacology, we identified the neuropeptide NLP-49 as a ligand of this evolutionarily conserved neuropeptide receptor. Our findings demonstrate novel roles for NLP-49 and SEB-3 in locomotion, arousal and egg-laying. Specifically, high-content analysis of locomotor behaviour indicates that seb-3 and nlp-49 deletion mutants cause remarkably similar abnormalities in movement dynamics, which are reversed by overexpression of wild-type transgenes. Overexpression of NLP-49 in AVK interneurons leads to heightened locomotor arousal, an effect that is dependent on seb-3. Finally, seb-3 and nlp-49 mutants also show constitutive egg-laying in liquid medium and alter the temporal pattern of egg-laying in similar ways. Together, these results provide in vivo evidence that NLP-49 peptides act through SEB-3 to modulate behaviour, and highlight the importance of neuropeptide signalling in the control of behavioural states.This article is part of a discussion meeting issue ‘Connectome to behaviour: modelling C. elegans at cellular resolution’.
Larson SD, Gleeson P, Brown AEX, 2018, Connectome to behaviour: modelling Caenorhabditis elegans at cellular resolution, Philosophical Transactions of the Royal Society of London: Biological Sciences, Vol: 373, ISSN: 0962-8436
It has been 30 years since the ‘mind of the worm’ was published in Philosophical Transactions B (White et al. 1986 Phil. Trans. R. Soc. Lond. B 314, 1–340). Predicting Caenorhabditis elegans' behaviour from its wiring diagram has been an enduring challenge since then. This special theme issue of Philosophical Transactions B combines research from neuroscientists, physicists, mathematicians and engineers to discuss advances in neural activity imaging, behaviour quantification and multiscale simulations, and how they are bringing the goal of whole-animal modelling at cellular resolution within reach.
Javer A, Ripoll-Sanchez L, Brown AE, 2018, Powerful and interpretable behavioural features for quantitative phenotyping of C. elegans, Philosophical Transactions B: Biological Sciences, Vol: 373, ISSN: 0962-8436
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.
Javer A, Currie M, Lee CW, et al., 2018, An open source platform for analyzing and sharing worm behavior data, Nature Methods, Vol: 15, Pages: 645-646, ISSN: 1548-7091
Ding SS, Schumacher LJ, Javer AE, et al., 2018, Shared behavioral mechanisms underlie <i>C. elegans</i> aggregation and swarming, Publisher: Cold Spring Harbor Laboratory
<jats:title>Abstract</jats:title><jats:p>In complex biological systems, simple individual-level behavioral rules can give rise to emergent group-level behavior. While such collective behavior has been well studied in cells and larger organisms, the mesoscopic scale is less understood, as it is unclear which sensory inputs and physical processes matter <jats:italic>a priori</jats:italic>. Here, we investigate collective feeding in the roundworm <jats:italic>C. elegans</jats:italic> at this intermediate scale, using quantitative phenotyping and agent-based modeling to identify behavioral rules underlying both aggregation and swarming—a dynamic phenotype only observed at longer timescales. Using fluorescent multi-worm tracking, we quantify aggregation behavior in terms of individual dynamics and population-level statistics. Based on our quantification, we use agent-based simulations and approximate Bayesian inference to identify three key behavioral rules that give rise to aggregation: cluster-edge reversals, a density-dependent switch between crawling speeds, and taxis towards neighboring worms. Our simulations suggest that swarming is simply driven by local food depletion but otherwise employs the same behavioral mechanisms as the initial aggregation. Hence, mesoscopic <jats:italic>C. elegans</jats:italic> uses mechanisms familiar from microscopic systems for aggregation, but implemented via more complex behaviors characteristic of macroscopic organisms.</jats:p>
Chakraborty K, Vijayan K, Brown AEX, et al., 2018, Glassy worm-like micelles in solvent and shear mediated shape transitions., Soft Matter, Vol: 2018, ISSN: 1744-683X
The glassiness of polymer melts is generally considered to be suppressed by small dimensions, added solvent, and heat. Here, we suggest that glassiness persists at the nanoscale in worm-like micelles composed of amphiphilic diblock copolymers of poly(ethylene oxide)-polystyrene (PS). The glassiness of these worms is indicated by a lack of fluorescence recovery after photobleaching as well as micron-length rigid segments separated by hinges. The coarse-grained molecular dynamics studies probe the dynamics of the PS in these glassy worms. Addition of an organic solvent promotes a transition from hinged to fully flexible worms and to spheres or vesicles. Simulation demonstrates two populations of organic solvent in the core of the micelle-a solvent 'pool' in the micelle core and a second population that accumulates at the interface between the core and the corona. The stable heterogeneity of the residual solvent could explain the unusual hinged rigidity, but solvent removal during shear-extension could be more effective and yield - as observed - nearly straight worms without hinges.
Brown AEX, de Bivort B, 2018, Ethology as a physical science, Nature Physics, Vol: 14, Pages: 653-657, ISSN: 1745-2473
The study of animal behaviour, ethology, is becoming more quantitative. New theory is emerging, driven by better imaging and novel representations of animal posture dynamics that span the vast range of relevant behavioural timescales.
Brown AEX, de Bivort B, 2018, Ethology as a physical science, Publisher: bioRxiv
Behaviour is the ultimate output of an animal's nervous system and choosing the right action at the right time can be critical for survival. The study of the organisation of behaviour in its natural context, ethology, has historically been a primarily qualitative science. A quantitative theory of behaviour would advance research in neuroscience as well as ecology and evolution. However, animal posture typically has many degrees of freedom and behavioural dynamics vary on timescales ranging from milliseconds to years, presenting both technical and conceptual challenges. Here we review 1) advances in imaging and computer vision that are making it possible to capture increasingly complete records of animal motion and 2) new approaches to understanding the resulting behavioural data sets. With the right analytical approaches, these data are allowing researchers to revisit longstanding questions about the structure and organisation of animal behaviour and to put unifying principles on a quantitative footing. Contributions from both experimentalists and theorists are leading to the emergence of a physics of behaviour and the prospect of discovering laws and developing theories with broad applicability. We believe that there now exists an opportunity to develop theories of behaviour which can be tested using these data sets leading to a deeper understanding of how and why animals behave.
Li K, Javer A, Keaveny E, et al., 2018, Recurrent Neural Networks with Interpretable Cells Predict and Classify Worm Behaviour, Twenty-ninth Annual Conference on Neural Information Processing Systems (NIPS)
An important goal in behaviour analytics is to connect disease state or genomevariation with observable differences in behaviour. Despite advances in sensortechnology and imaging, informative behaviour quantification remains challenging.The nematode worm C. elegans provides a unique opportunity to test analysisapproaches because of its small size, compact nervous system, and the availabilityof large databases of videos of freely behaving animals with known genetic differences.Despite its relative simplicity, there are still no reports of generative modelsthat can capture essential differences between even well-described mutant strains.Here we show that a multilayer recurrent neural network (RNN) can produce diversebehaviours that are difficult to distinguish from real worms’ behaviour andthat some of the artificial neurons in the RNN are interpretable and correlate withobservable features such as body curvature, speed, and reversals. Although theRNN is not trained to perform classification, we find that artificial neuron responsesprovide features that perform well in worm strain classification.
Keaveny E, Brown AE, 2017, Predicting path from undulations for C. elegans using linear and nonlinear resistive force theory, Physical Biology, Vol: 14, ISSN: 1478-3975
A basic issuein the physics of behaviouris the mechanical relationship between an animal and its surroundings. The nematode and model organism C. elegans provides an excellent platform to explore this relationship due to its anatomical simplicity. Nonetheless,the physics of nematode crawling, in which the worm undulates its body to move on a wet surface, is not completely understoodand the mathematical models often used to describe this phenomenon are empirical. We confirm that linear resistive force theory, one such empirical model,is effective at predicting a worm’s path from its sequence of body postures for forward crawling, reversing, and turning and for a broad range of different behavioural phenotypes observedin mutant worms. However, agreement between the predicted and observed path is lost when using this model with recently measured valuesof the drag anisotropy. A recently proposed nonlinear extensionof the resistive force theory model also provides accurate predictions, but does not resolve the discrepancy between the parameters required to achieve good path prediction and the experimentally measured parameters. This meansthat while we have good effective models of worm crawling that can be used in applications such as whole-animal simulations and advanced tracking algorithms, there are still unanswered questions about the precise nature of the physical interaction between worms and their most commonly studied laboratory substrate.
Gomez-Marin A, Stephens GJ, Brown AE, 2016, Hierarchical compression of C. elegans locomotion reveals phenotypic differences in the organisation of behaviour, Journal of the Royal Society Interface, Vol: 13, ISSN: 1742-5689
Regularities in animal behaviour offer insight into the underlying organisational and functional principles of nervous systems and automated tracking provides the opportunity to extract featuresof behaviour directly from large-scale video data. Yet how to effectively analyse such behavioural data remains an open question. Here we explore whether a minimum description length principle can beexploited to identify meaningful behaviours and phenotypes. We apply a dictionary compression algorithm to behavioural sequences from the nematode worm Caenorhabditis elegans freely crawling on an agar plate both with and without food and during chemotaxis. We find that the motifs identified by the compression algorithm are rare but relevant for comparisons between worms in different environments, suggesting that hierarchical compression can be a useful step in behaviour analysis. We also use compressibility as a new quantitative phenotype and find that the behaviour of wild-isolated strains of C. elegans is more compressible than that of the laboratory strain N2 as well as the majority of mutant strains examined. Importantly, in distinction to more conventional phenotypes such as overall motor activity or aggregation behaviour, the increased compressibility of wild isolates is not explained by the loss of function of the gene npr-1, which suggests that erratic locomotion is a laboratory-derived trait with a novel genetic basis. Because hierarchical compression can be applied to any sequence, we anticipate that compressibility can offer insight into the organisation of behaviour in other animals including humans.
Brown AE, Gyenes B, 2016, Deriving shape-based features for C. elegans locomotion using dimensionality reduction methods, Frontiers in Behavioral Neuroscience, Vol: 10, ISSN: 1662-5153
High-throughput analysis of animal behavior is increasingly common following the advances of recording technology, leading to large high-dimensional data sets. This dimensionality can sometimes be reduced while still retaining relevant information. In the case of the nematode worm Caenorhabditis elegans, more than 90% of the shape variance can be captured using just four principal components. However, it remains unclear if other methods can achieve a more compact representation or contribute further biological insight to worm locomotion. Here we take a data-driven approach to worm shape analysis using independent component analysis (ICA), non-negative matrix factorization (NMF), a cosine series, and jPCA (a dynamic variant of principal component analysis [PCA]) and confirm that the dimensionality of worm shape space is close to four. Projecting worm shapes onto the bases derived using each method gives interpretable features ranging from head movements to tail oscillation. We use these as a comparison method to find differences between the wild type N2 worms and various mutants. For example, we find that the neuropeptide mutant nlp-1(ok1469) has an exaggerated head movement suggesting a mode of action for the previously described increased turning rate. The different bases provide complementary views of worm behavior and we expect that closer examination of the time series of projected amplitudes will lead to new results in the future.
Schwarz RF, Branicky R, Grundy LJ, et al., 2015, Changes in postural syntax characterize sensory modulation and natural variation of C. elegans locomotion, PLOS Computational Biology, Vol: 11, ISSN: 1553-734X
Locomotion is driven by shape changes coordinated by the nervous system through time;thus, enumerating an animal's complete repertoire of shape transitions would provide abasis for a comprehensive understanding of locomotor behaviour. Here we introduce a discreterepresentation of behaviour in the nematode C. elegans. At each point in time, theworm’s posture is approximated by its closest matching template from a set of 90 posturesand locomotion is represented as sequences of postures. The frequency distribution of posturalsequences is heavy-tailed with a core of frequent behaviours and a much larger set ofrarely used behaviours. Responses to optogenetic and environmental stimuli can be quantifiedas changes in postural syntax: worms show different preferences for differentsequences of postures drawn from the same set of templates. A discrete representation of behaviour will enable the use of methods developed for other kinds of discrete data in bioinformatics and language processing to be harnessed for the study of behaviour.
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