Measuring the repertoire of age-related behavioral changes in Drosophila melanogaster

Mapping the developmental structure of stereotyped and individual-unique behavioral spaces in C. elegans

Developmental patterns of behavior are variably organized in time and among different individuals. However, long-term behavioral diversity was previously studied using pre-defined behavioral parameters, representing a limited fraction of the full individuality structure. Here, we continuously extract ∼1.2 billion body postures of ∼2,200 single C. elegans individuals throughout their full development time to create a complete developmental atlas of stereotyped and individual-unique behavioral spaces. Unsupervised inference of low-dimensional movement modes of each single individual identifies a dynamic developmental trajectory of stereotyped behavioral spaces and exposes unique behavioral trajectories of individuals that deviate from the stereotyped patterns. Moreover, classification of behavioral spaces within tens of neuromodulatory and environmentally perturbed populations shows plasticity in the temporal structures of stereotyped behavior and individuality. These results present a comprehensive atlas of continuous behavioral dynamics across development time and a general framework for unsupervised dissection of shared and unique developmental signatures of behavior.

Longitudinal activity monitoring and lifespan: quantifying the interface

Understanding the relationship between activity over the entire lifespan and longevity is an important facet of aging research. We present a comprehensive framework for the statistical analysis of longitudinal activity and behavioral monitoring and their relationship with age-at-death at the individual level, highlighting the importance of advanced methodological approaches in aging research. The focus is on animal models, where continuous monitoring activity in terms of movement, reproduction and behaviors over the entire lifespan is feasible at the individual level. We specifically demonstrate the methodology with data on activity monitoring for Mediterranean fruit flies. Advanced statistical methodologies to explore the interface between activity and age-at-death include functional principal component analysis, concurrent regression, Fréchet regression and point processes. While the focus of this perspective is on relating age-at-death with data on movement, reproduction, behavior and nutrition of Mediterranean fruit flies, the methodology equally pertains to data from other species, including human data.

Aging in zebrafish is associated with reduced locomotor activity and strain dependent changes in bottom dwelling and thigmotaxis

Aging is associated with a wide range of physiological and behavioral changes in many species. Zebrafish, like humans, rodents, and birds, exhibits gradual senescence, and thus may be a useful model organism for identifying evolutionarily conserved mechanisms related to aging. Here, we compared behavior in the novel tank test of young (6-month-old) and middle aged (12-month-old) zebrafish from two strains (TL and TU) and both sexes. We find that this modest age difference results in a reduction in locomotor activity in male fish. We also found that background strain modulated the effects of age on predator avoidance behaviors related to anxiety: older female TL fish increased bottom dwelling whereas older male TU fish decreased thigmotaxis. Although there were no consistent effects of age on either short-term (within session) or long-term (next day) habituation to the novel tank, strain affected the habituation response. TL fish tended to increase their distance from the bottom of the tank whereas TU fish had no changes in bottom distance but instead tended to increase thigmotaxis. Our findings support the use of zebrafish for the study of how age affects locomotion and how genetics interacts with age and sex to alter exploratory and emotional behaviors in response to novelty.

Capturing continuous, long timescale behavioral changes in Drosophila melanogaster postural data

Animal behavior spans many timescales, from short, seconds-scale actions to circadian rhythms over many hours to life-long changes during aging. Most quantitative behavior studies have focused on short-timescale behaviors such as locomotion and grooming. Analysis of these data suggests there exists a hierarchy of timescales; however, the limited duration of these experiments prevents the investigation of the full temporal structure. To access longer timescales of behavior, we continuously recorded individual Drosophila melanogaster at 100 frames per second for up to 7 days at a time in featureless arenas on sucrose-agarose media. We use the deep learning framework SLEAP to produce a full-body postural data set for 47 individuals resulting in nearly 2 billion pose instances. We identify stereotyped behaviors such as grooming, proboscis extension, and locomotion and use the resulting ethograms to explore how the flies' behavior varies across time of day and days in the experiment. We find distinct circadian patterns in all of our stereotyped behavior and also see changes in behavior over the course of the experiment as the flies weaken and die.

Sublethal behavioral impacts of resource limitation and insecticide exposure reinforce negative fitness outcomes for a solitary bee

Contemporary landscapes present numerous challenges for bees and other beneficial insects that play critical functional roles in natural ecosystems and agriculture. Pesticides and the loss of food resources from flowering plants are two stressors known to act together to impair bee fitness. The impact of these stressors on key behaviors like foraging and nesting can limit pollination services and population persistence, making it critical to understand these sublethal effects. We investigated the effects of insecticide exposure and floral resource limitation on the foraging and nesting behavior of the solitary blue orchard bee, Osmia lignaria. Bees in field cages foraged on wildflowers at high or low densities, some treated with the common insecticide, imidacloprid, in a fully crossed design. Both stressors influenced behavior, but they had differential impacts. Bees with limited food resources made fewer, but longer foraging trips and misidentified their nests more often. Insecticide exposure reduced bee foraging activity. Additionally, insecticides interacted with bee age to influence antagonistic behavior among neighboring females, such that insecticide-exposed bees were less antagonistic with age. Our findings point towards mechanisms underlying effects on populations and ecosystem function and reinforce the importance of studying multiple drivers to understand the consequences of anthropogenic change.

A GNN-based model for capturing spatio-temporal changes in locomotion behaviors of aging C. elegans

Investigating the locomotion of aging C. elegans is an important way for understanding the basic mechanisms behind age-related changes in organisms. However, the locomotion of aging C. elegans is often quantified using insufficient physical variables, which makes it challenging to capture essential dynamics. To study changes in the locomotion pattern of aging C. elegans, we developed a novel data-driven model based on graph neural networks, in which the C. elegans body is modeled as a long chain with interactions within and between adjacent segments, and their interactions are described by high-dimensional variables. Using this model, we discovered that each segment of the C. elegans body generally tends to maintain its locomotion, i.e., tries to keep the bending angle unchanged, and expects to change the locomotion of the adjacent segments. The ability to maintain its locomotion strengthens with age. Besides, a subtle distinguish in the changes in the locomotion pattern of C. elegans at various aging stages were observed. Our model is anticipated to provide a data-driven method for quantifying the changes in the locomotion pattern of aging C. elegans and for mining the underlying causes of these changes.

Leveraging big data to uncover the eco-evolutionary factors shaping behavioural development

Mapping the eco-evolutionary factors shaping the development of animals' behavioural phenotypes remains a great challenge. Recent advances in 'big behavioural data' research-the high-resolution tracking of individuals and the harnessing of that data with powerful analytical tools-have vastly improved our ability to measure and model developing behavioural phenotypes. Applied to the study of behavioural ontogeny, the unfolding of whole behavioural repertoires can be mapped in unprecedented detail with relative ease. This overcomes long-standing experimental bottlenecks and heralds a surge of studies that more finely define and explore behavioural-experiential trajectories across development. In this review, we first provide a brief guide to state-of-the-art approaches that allow the collection and analysis of high-resolution behavioural data across development. We then outline how such approaches can be used to address key issues regarding the ecological and evolutionary factors shaping behavioural development: developmental feedbacks between behaviour and underlying states, early life effects and behavioural transitions, and information integration across development.

The C. elegans Observatory: High-throughput exploration of behavioral aging

Organisms undergo a variety of characteristic changes as they age, suggesting a substantial commonality in the mechanistic basis of aging. Experiments in model organisms have revealed a variety of cellular systems that impact lifespan, but technical challenges have prevented a comprehensive evaluation of how these components impact the trajectory of aging, and many components likely remain undiscovered. To facilitate the deeper exploration of aging trajectories at a sufficient scale to enable primary screening, we have created the Caenorhabditis elegans Observatory, an automated system for monitoring the behavior of group-housed C. elegans throughout their lifespans. One Observatory consists of a set of computers running custom software to control an incubator containing custom imaging and motion-control hardware. In its standard configuration, the Observatory cycles through trays of standard 6 cm plates, running four assays per day on up to 576 plates per incubator. High-speed image processing captures a range of behavioral metrics, including movement speed and stimulus-induced turning, and a data processing pipeline continuously computes summary statistics. The Observatory software includes a web interface that allows the user to input metadata and view graphs of the trajectory of behavioral aging as the experiment unfolds. Compared to the manual use of a plate-based C. elegans tracker, the Observatory reduces the effort required by close to two orders of magnitude. Within the Observatory, reducing the function of known lifespan genes with RNA interference (RNAi) gives the expected phenotypic changes, including extended motility in daf-2(RNAi) and progeria in hsf-1(RNAi). Lifespans scored manually from worms raised in conventional conditions match those scored from images captured by the Observatory. We have used the Observatory for a small candidate-gene screen and identified an extended youthful vigor phenotype for tank-1(RNAi) and a progeric phenotype for cdc-42(RNAi). By utilizing the Observatory, it is now feasible to conduct whole-genome screens for an aging-trajectory phenotype, thus greatly increasing our ability to discover and analyze new components of the aging program.