Genetic Control of Collective Behavior in Zebrafish

Rearing in a Physically Enriched Environment Affects Shoaling and Stress Responses of Zebrafish (Danio rerio) Exposed to Novel Conditions

The impact of enrichment on stress reduction in zebrafish (Danio rerio) exposed to a novel environment was assessed. Four control shoals (CTRL) and five treated shoals (TRT), each with eight fish, were observed; in TRT tanks, a PVC pipe was included (three-way tube, 11.7 × 4 cm) as enrichment for 90 days. Subsequently, fish were moved to a new tank for a shoaling test, and behavior was evaluated over periods of 0'-5' and 5'-10'. Cortisol dissolved in water was measured before and after the test. No differences were found between the two groups in distance moved, swimming speed, or shoal acceleration. Both groups reduced interindividual distance in the second phase of the test (CTRL: t = 8.977, p ≤ 0.0001; TRT: t = 8.247, p ≤ 0.0001), though TRT fish maintained greater spacing (t = 2.292, p ≤ 0.05). TRT fish spent more time without contact during both phases (first: t = 2.645, p ≤ 0.05; second: t = 3.134, p ≤ 0.01), while CTRL fish reduced this time in the second phase (t = 2.991, p ≤ 0.05). Cortisol rose significantly in CTRL after the test (t = 2.452, p ≤ 0.05) but not in TRT fish. These results suggest that environmental enrichment mitigates stress, as seen by reduced cohesiveness and cortisol in TRT fish.

Tuning collective behaviour in zebrafish with genetic modification

Zebrafish collective behaviour is widely used to assess their physical and mental state, serving as a valuable tool to assess the impact of ageing, disease genetics, and the effect of drugs. The essence of these macroscopic phenomena can be represented by active matter models, where the individuals are abstracted as interactive self-propelling agents. The behaviour of these agents depends on a set of parameters in a manner reminiscent of those between the constituents of physical systems. In a few cases, the system may be controlled at the level of the individual constituents such as the interactions between colloidal particles, or the enzymatic behaviour of de novo proteins. Usually, however, while the collective behaviour may be influenced by environmental factors, it typically cannot be changed at will. Here, we challenge this scenario in a biological context by genetically modifying zebrafish. We thus demonstrate the potential of genetic modification in the context of controlling the collective behaviour of biological active matter systems at the level of the constituents, rather than externally. In particular, we probe the effect of the lack of col11a2 gene in zebrafish, which causes the early onset of osteoarthritis. The resulting col11a2 -/- zebrafish exhibited compromised vertebral column properties, bent their body less while swimming, and took longer to change their orientations. Surprisingly, a group of 25 mutant fish exhibited more orderly collective motion than the wildtype. We show that the collective behaviour of wildtype and col11a2 -/- zebrafish are captured with a simple active matter model, in which the mutant fish are modelled by self-propelling agents with a higher orientational noise on average. In this way, we demonstrate the possibility of tuning a biological system, changing the state space it occupies when interpreted with a simple active matter model.

From grouping and cooperation to menstruation: Spiny mice (Acomys cahirinus) are an emerging mammalian model for sociality and beyond

While spiny mice are primarily used as a model for Type II diabetes and for studying complex tissue regeneration, they are also an emerging model for a variety of studies examining hormones, behavior, and the brain. We began studying the spiny mouse to take advantage of their highly gregarious phenotype to examine how the brain facilitates large group-living. However, this unique rodent can be readily bred and maintained in the lab and can be used to ask a wide variety of scientific questions. In this brief communication we provide an overview of studies that have used spiny mice for exploring physiology and behavior. Additionally, we describe how the spiny mouse can serve as a useful model for researchers interested in studying precocial development, menstruation, cooperation, and various grouping behaviors. With increasingly available technological advancements for non-traditional organisms, spiny mice are well-positioned to become a valuable organism in the behavioral neuroscience community.

Changes in local interaction rules during ontogeny underlie the evolution of collective behavior

Collective motion emerges from individual interactions which produce group-wide patterns in behavior. While adaptive changes to collective motion are observed across animal species, how local interactions change when these collective behaviors evolve is poorly understood. Here, we use the Mexican tetra, Astyanax mexicanus, which exists as a schooling surface form and a non-schooling cave form, to study differences in how fish alter their swimming in response to neighbors across ontogeny and between evolutionarily diverged populations. We find that surface fish undergo a transition to schooling mediated by changes in the way fish modulate speed and turning relative to neighbors. This transition begins with the tendency to align to neighbors emerging by 28 days post-fertilization and ends with the emergence of robust attraction by 70 days post-fertilization. Cavefish exhibit neither alignment nor attraction at any stage of development. These results reveal how evolution alters local interactions to produce striking differences in collective behavior.

Environmentally relevant concentrations of antidepressant mirtazapine impair the neurodevelopment of zebrafish (Danio rerio)

Mirtazapine is a commonly prescribed antidepressant and has been found widespread in aquatic environments. However, its toxicities to aquatic organisms has rarely been explored. Herein, we conducted a comprehensive study on the developmental effects of mirtazapine on early life stages of zebrafish at environmentally relevant concentrations (3.9 ng/L and 43.5 ng/L). Out of the endpoints measured, spontaneous contraction of embryos at 24 h post fertilization (hpf) and hatching rate and heart rate of embryos at 50 hpf and 56 hpf, respectively, were significantly affected. In light-dark transition behavior test, mirtazapine significantly reduced the swimming frequency and swimming speed of embryos at both concentrations of 3.9 ng/L and 43.5 ng/L. Furthermore, the total swimming distances in dark conditions were also significantly reduced. Transcriptomic analysis was further conducted. It demonstrated that the decreased neural activities in embryos may be associated with altered epinephrine and neuregulin signaling. The present results fill a data gap regarding the exposure of fish to mirtazapine at environmentally relevant concentrations and provide new insights into the neurotoxic mechanisms of mirtazapine exposure.

Behavioral analysis through the lifespan of disc1 mutant zebrafish identifies defects in sensorimotor transformation

DISC1 is a genetic risk factor for multiple psychiatric disorders. Compared to the dozens of murine Disc1 models, there is a paucity of zebrafish disc1 models-an organism amenable to high-throughput experimentation. We conducted the longitudinal neurobehavioral analysis of disc1 mutant zebrafish across key stages of life. During early developmental stages, disc1 mutants exhibited abrogated behavioral responses to sensory stimuli across multiple testing platforms. Moreover, during exposure to an acoustic sensory stimulus, loss of disc1 resulted in the abnormal activation of neurons in the pallium, cerebellum, and tectum-anatomical sites involved in the integration of sensory perception and motor control. In adulthood, disc1 mutants exhibited sexually dimorphic reduction in anxiogenic behavior in novel paradigms. Together, these findings implicate disc1 in sensorimotor processes and the genesis of anxiogenic behaviors, which could be exploited for the development of novel treatments in addition to investigating the biology of sensorimotor transformation in the context of disc1 deletion.

An overall view of the most common experimental models for multiple sclerosis

Multiple sclerosis (MS) is a complex chronic disease with an unknown etiology. It is considered an inflammatory demyelinating and neurodegenerative disorder of the central nervous system (CNS) characterized, in most cases, by an unpredictable onset of relapse and remission phases. The disease generally starts in subjects under 40; it has a higher incidence in women and is described as a multifactorial disorder due to the interaction between genetic and environmental risk factors. Unfortunately, there is currently no definitive cure for MS. Still, therapies can modify the disease's natural history, reducing the relapse rate and slowing the progression of the disease or managing symptoms. The limited access to human CNS tissue slows down. It limits the progression of research on MS. This limit has been partially overcome over the years by developing various experimental models to study this disease. Animal models of autoimmune demyelination, such as experimental autoimmune encephalomyelitis (EAE) and viral and toxin or transgenic MS models, represent the most significant part of MS research approaches. These models have now been complemented by ex vivo studies, using organotypic brain slice cultures and in vitro, through induced Pluripotent Stem cells (iPSCs). We will discuss which clinical features of the disorders might be reproduced and investigated in vivo, ex vivo, and in vitro in models commonly used in MS research to understand the processes behind the neuropathological events occurring in the CNS of MS patients. The primary purpose of this review is to give the reader a global view of the main paradigms used in MS research, spacing from the classical animal models to transgenic mice and 2D and 3D cultures.

Long-Term Continuous Computer Registration and Analysis of Motor Activity of a Group of Zebrafish Danio rerio

A new algorithm for long-term continuous computer recording and analysis of motor activity of a group of zebrafish in the home tank has been developed. The movements of a group of Danio rerio during the entire light period and for several days are recorded at a frequency of 1 frame/sec in the form of short (15 min) files. Then these files are analyzed by the unique DanioStudo software, which, using a threshold algorithm and appropriate masks, calculates for each frame the sum of pixels associated with fish (the sum of fish silhouettes), and for two consecutive frames, the sum of altered pixels (the sum of altered fish silhouettes). The following indexes are calculated: the rate of sum of silhouettes alteration as the ratio of the sum of altered silhouettes to the sum of silhouettes (1) and the time spent in the selected area of the home tank as the ratio of the sum of silhouettes in this area to the sum of silhouettes in the entire tank (2). The mean rate of silhouette alteration correlates to the length of the path travelled by the fish and, therefore, serves as a correct measure of the motor activity of a group of fish. Using these algorithms, completely new data were obtained: it was shown that the motor activity of fish remains constant throughout the entire light period, but depends on the size of the home tank. The proposed approach, together with the DanioStudio software, can be effective in studying the dynamics of changes in the behavior of fish under long-term exposure to short daylight, drugs and toxic substances.

A multi-scale review of the dynamics of collective behaviour: from rapid responses to ontogeny and evolution

Collective behaviours, such as flocking in birds or decision making by bee colonies, are some of the most intriguing behavioural phenomena in the animal kingdom. The study of collective behaviour focuses on the interactions between individuals within groups, which typically occur over close ranges and short timescales, and how these interactions drive larger scale properties such as group size, information transfer within groups and group-level decision making. To date, however, most studies have focused on snapshots, typically studying collective behaviour over short timescales up to minutes or hours. However, being a biological trait, much longer timescales are important in animal collective behaviour, particularly how individuals change over their lifetime (the domain of developmental biology) and how individuals change from one generation to the next (the domain of evolutionary biology). Here, we give an overview of collective behaviour across timescales from the short to the long, illustrating how a full understanding of this behaviour in animals requires much more research attention on its developmental and evolutionary biology. Our review forms the prologue of this special issue, which addresses and pushes forward understanding the development and evolution of collective behaviour, encouraging a new direction for collective behaviour research. This article is part of a discussion meeting issue 'Collective behaviour through time'.

Inferring social influence in animal groups across multiple timescales

Many animal behaviours exhibit complex temporal dynamics, suggesting there are multiple timescales at which they should be studied. However, researchers often focus on behaviours that occur over relatively restricted temporal scales, typically ones that are more accessible to human observation. The situation becomes even more complex when considering multiple animals interacting, where behavioural coupling can introduce new timescales of importance. Here, we present a technique to study the time-varying nature of social influence in mobile animal groups across multiple temporal scales. As case studies, we analyse golden shiner fish and homing pigeons, which move in different media. By analysing pairwise interactions among individuals, we show that predictive power of the factors affecting social influence depends on the timescale of analysis. Over short timescales the relative position of a neighbour best predicts its influence and the distribution of influence across group members is relatively linear, with a small slope. At longer timescales, however, both relative position and kinematics are found to predict influence, and nonlinearity in the influence distribution increases, with a small number of individuals being disproportionately influential. Our results demonstrate that different interpretations of social influence arise from analysing behaviour at different timescales, highlighting the importance of considering its multiscale nature. This article is part of a discussion meeting issue 'Collective behaviour through time'.

Changes in local interaction rules during ontogeny underlie the evolution of collective behavior

Collective motion emerges from individual interactions which produce groupwide patterns in behavior. While adaptive changes to collective motion are observed across animal species, how local interactions change when these collective behaviors evolve is poorly understood. Here, we use the Mexican tetra, A. mexicanus, which exists as a schooling surface form and a non-schooling cave form, to study differences in how fish alter their swimming in response to neighbors across ontogeny and between evolutionarily diverged populations. We find that surface fish undergo a transition to schooling during development that occurs through increases in inter-individual alignment and attraction mediated by changes in the way fish modulate speed and turning relative to neighbors. Cavefish, which have evolved loss of schooling, exhibit neither of these schooling-promoting interactions at any stage of development. These results reveal how evolution alters local interaction rules to produce striking differences in collective behavior.

Collective motions of fish originate from balanced local perceptual interactions and individual stochastics

The movement of a group of biological individuals, such as fish schools, can evolve from disordered motions to synergistic movements or even ordered patterns. However, the physical origins behind such emergent phenomena of complex systems remain elusive. Here, we established a high-precision protocol for studying the collective behavior of biological groups in quasi-two-dimensional systems. Based on our video recording of ∼600h of fish movements, we extracted a force map of the interactions between fish from their trajectories using the convolution neural network. Presumably, this force implies the fish's perception of the surrounding individuals, the environment, and their response to social information. Interestingly, the fish in our experiments were predominantly in a seemingly disordered swarm state, but their local interactions were clearly specific. Combining such local interactions with the inherent stochasticity of the fish movements, we reproduced the collective motions of the fish through simulations. We demonstrated that a delicate balance between the specific local force and the intrinsic stochasticity is essential for ordered movements. This study presents implications for self-organized systems that use basic physical characterization to produce higher-level sophistication.

Social behavioral profiling by unsupervised deep learning reveals a stimulative effect of dopamine D3 agonists on zebrafish sociality

It has been a major challenge to systematically evaluate and compare how pharmacological perturbations influence social behavioral outcomes. Although some pharmacological agents are known to alter social behavior, precise description and quantification of such effects have proven difficult. We developed a scalable social behavioral assay for zebrafish named ZeChat based on unsupervised deep learning to characterize sociality at high resolution. High-dimensional and dynamic social behavioral phenotypes are automatically classified using this method. By screening a neuroactive compound library, we found that different classes of chemicals evoke distinct patterns of social behavioral fingerprints. By examining these patterns, we discovered that dopamine D3 agonists possess a social stimulative effect on zebrafish. The D3 agonists pramipexole, piribedil, and 7-hydroxy-DPAT-HBr rescued social deficits in a valproic-acid-induced zebrafish autism model. The ZeChat platform provides a promising approach for dissecting the pharmacology of social behavior and discovering novel social-modulatory compounds.

Zebrafish as a Mainstream Model for In Vivo Systems Pharmacology and Toxicology

Pharmacology and toxicology are part of a much broader effort to understand the relationship between chemistry and biology. While biomedicine has necessarily focused on specific cases, typically of direct human relevance, there are real advantages in pursuing more systematic approaches to characterizing how health and disease are influenced by small molecules and other interventions. In this context, the zebrafish is now established as the representative screenable vertebrate and, through ongoing advances in the available scale of genome editing and automated phenotyping, is beginning to address systems-level solutions to some biomedical problems. The addition of broader efforts to integrate information content across preclinical model organisms and the incorporation of rigorous analytics, including closed-loop deep learning, will facilitate efforts to create systems pharmacology and toxicology with the ability to continuously optimize chemical biological interactions around societal needs. In this review, we outline progress toward this goal.

Lateral line morphology, sensory perception and collective behaviour in African cichlid fish

The lateral line system of fishes provides cues for collective behaviour, such as shoaling, but it remains unclear how anatomical lateral line variation leads to behavioural differences among species. Here we studied associations between lateral line morphology and collective behaviour using two morphologically divergent species and their second-generation hybrids. We identify collective behaviours associated with variation in canal and superficial lateral line morphology, with closer proximities to neighbouring fish associated with larger canal pore sizes and fewer superficial neuromasts. A mechanistic understanding of the observed associations was provided by hydrodynamic modelling of an artificial lateral line sensor, which showed that simulated canal-based neuromasts were less susceptible to saturation during unidirectional movement than simulated superficial neuromasts, while increasing the canal pore size of the simulated lateral line sensor elevated sensitivity to vortices shed by neighbouring fish. Our results propose a mechanism behind lateral line flow sensing during collective behaviour in fishes.

CRISPR/Cas9-Induced Inactivation of the Autism-Risk Gene setd5 Leads to Social Impairments in Zebrafish

Haploinsufficiency of the SETD5 gene, encoding a SET domain-containing histone methyltransferase, has been identified as a cause of intellectual disability and Autism Spectrum Disorder (ASD). Recently, the zebrafish has emerged as a valuable model to study neurodevelopmental disorders because of its genetic tractability, robust behavioral traits and amenability to high-throughput drug screening. To model human SETD5 haploinsufficiency, we generated zebrafish setd5 mutants using the CRISPR/Cas9 technology and characterized their morphological, behavioral and molecular phenotypes. According to our observation that setd5 is expressed in adult zebrafish brain, including those areas controlling social behavior, we found that setd5 heterozygous mutants exhibit defective aggregation and coordination abilities required for shoaling interactions, as well as indifference to social stimuli. Interestingly, impairment in social interest is rescued by risperidone, an antipsychotic drug used to treat behavioral traits in ASD individuals. The molecular analysis underscored the downregulation of genes encoding proteins involved in the synaptic structure and function in the adult brain, thus suggesting that brain hypo-connectivity could be responsible for the social impairments of setd5 mutant fishes. The zebrafish setd5 mutants display ASD-like features and are a promising setd5 haploinsufficiency model for drug screening aimed at reversing the behavioral phenotypes.

Differential Gene Expression Correlates with Behavioural Polymorphism during Collective Behaviour in Cockroaches

Simple Summary

It is currently well accepted that animals differ from one another in their behaviour and tendency to perform actions, a property we refer to as animal personality. In group-living animals, variation in animal personality can be important to determine group survival, as it determines how individuals interact with each other and with their environment. However, we have little knowledge of the proximal mechanisms underlying personality, particularly in group-living organisms. Here, we investigate the relationship between gene expression and two behavioural types (bold and shy) in a gregarious species: the American cockroach. Our results show that bold individuals have upregulated genes with functions associated with sensory activity (phototaxis and odour detection) and aggressive/dominant behaviour, and suggest that social context can modulate gene expression related to bold/shy characteristics. This work could help identify genes important in the earliest stages of group living and social life, and provides a first step toward establishing cockroaches as a focal group for the study of the evolution of sociality.

Abstract

Consistent inter-individual variation in the propensity to perform different tasks (animal personality) can contribute significantly to the success of group-living organisms. The distribution of different personalities in a group influences collective actions and therefore how these organisms interact with their environment. However, we have little understanding of the proximate mechanisms underlying animal personality in animal groups, and research on this theme has often been biased towards organisms with advanced social systems. The goal of this study is to investigate the mechanistic basis for personality variation during collective behaviour in a species with rudimentary societies: the American cockroach. We thus use an approach which combines experimental classification of individuals into behavioural phenotypes (‘bold’ and ‘shy’ individuals) with comparative gene expression. Our analyses reveal differences in gene expression between behavioural phenotypes and suggest that social context may modulate gene expression related to bold/shy characteristics. We also discuss how cockroaches could be a valuable model for the study of genetic mechanisms underlying the early steps in the evolution of social behaviour and social complexity. This study provides a first step towards a better understanding of the molecular mechanisms associated with differences in boldness and behavioural plasticity in these organisms.

Modeling neurodegenerative disorders in zebrafish

Neurodegeneration is a major cause of Alzheimer's, Parkinson's, Huntington's, multiple and amyotrophic lateral sclerosis, pontocerebellar hypoplasia, dementia and other related brain disorders. Their complex pathogenesis commonly includes genetic and neurochemical deficits, misfolded protein toxicity, demyelination, apoptosis and mitochondrial dysfunctions. Albeit differing in specific underlying mechanisms, neurodegenerative disorders typically display evolutionarily conserved mechanisms across taxa. Here, we review the role of zebrafish models in recapitulating major human and rodent neurodegenerative conditions, demonstrating this species as a highly relevant experimental model for research on neurodegenerative diseases, and discussing how these fish models can further clarify the underlying genetic, neurochemical, neuroanatomical and behavioral pathogenic mechanisms.

The what, how, and why of naturalistic behavior

In the past few years, advances in machine learning have fueled an explosive growth of descriptive and generative models of animal behavior. These new approaches offer higher levels of detail and granularity than has previously been possible, allowing for fine-grained segmentation of animals' actions and precise quantitative mappings between an animal's sensory environment and its behavior. How can these new methods help us understand the governing principles shaping complex and naturalistic behavior? In this review, we will recap ways in which our ability to detect and model behavior have improved in recent years, and consider how these techniques might be used to revisit classical normative theories of behavioral control.

Validation of Candidate Sleep Disorder Risk Genes Using Zebrafish

Sleep disorders and chronic sleep disturbances are common and are associated with cardio-metabolic diseases and neuropsychiatric disorders. Several genetic pathways and neuronal mechanisms that regulate sleep have been described in animal models, but the genes underlying human sleep variation and sleep disorders are largely unknown. Identifying these genes is essential in order to develop effective therapies for sleep disorders and their associated comorbidities. To address this unmet health problem, genome-wide association studies (GWAS) have identified numerous genetic variants associated with human sleep traits and sleep disorders. However, in most cases, it is unclear which gene is responsible for a sleep phenotype that is associated with a genetic variant. As a result, it is necessary to experimentally validate candidate genes identified by GWAS using an animal model. Rodents are ill-suited for this endeavor due to their poor amenability to high-throughput sleep assays and the high costs associated with generating, maintaining, and testing large numbers of mutant lines. Zebrafish (Danio rerio), an alternative vertebrate model for studying sleep, allows for the rapid and cost-effective generation of mutant lines using the CRISPR/Cas9 system. Numerous zebrafish mutant lines can then be tested in parallel using high-throughput behavioral assays to identify genes whose loss affects sleep. This process identifies a gene associated with each GWAS hit that is likely responsible for the human sleep phenotype. This strategy is a powerful complement to GWAS approaches and holds great promise to identify the genetic basis for common human sleep disorders.

Kinematic analysis of social interactions deconstructs the evolved loss of schooling behavior in cavefish

Fish display a remarkable diversity of social behaviors, both within and between species. While social behaviors are likely critical for survival, surprisingly little is known about how they evolve in response to changing environmental pressures. With its highly social surface form and multiple populations of a largely asocial, blind, cave-dwelling form, the Mexican tetra, Astyanax mexicanus, provides a powerful model to study the evolution of social behavior. Here we use motion tracking and analysis of swimming kinematics to quantify social swimming in four Astyanax mexicanus populations. In the light, surface fish school, maintaining both close proximity and alignment with each other. In the dark, surface fish no longer form coherent schools, however, they still show evidence of an attempt to align and maintain proximity when they find themselves near another fish. In contrast, cavefish from three independently-evolved populations (Pachón, Molino, Tinaja) show little preference for proximity or alignment, instead exhibiting behaviors that suggest active avoidance of each other. Two of the three cave populations we studied also slow down when more fish are present in the tank, a behavior which is not observed in surface fish in light or the dark, suggesting divergent responses to conspecifics. Using data-driven computer simulations, we show that the observed reduction in swimming speed is sufficient to alter the way fish explore their environment: it can increase time spent exploring away from the walls. Thus, the absence of schooling in cavefish is not merely a consequence of their inability to see, but may rather be a genuine behavioral adaptation that impacts the way they explore their environment.

The neuropeptide Pth2 modulates social behavior and anxiety in zebrafish

Behavior is context-dependent and often modulated by an animal's internal state. In particular, different social contexts can alter anxiety levels and modulate social behavior. The vertebrate-specific neuropeptide parathyroid hormone 2 (pth2) is regulated by the presence of conspecifics in zebrafish. As its cognate receptor, the parathyroid hormone 2 receptor (pth2r), is widely expressed across the brain, we tested fish lacking the functional Pth2 peptide in several anxiety-related and social behavior paradigms. Here, we show that the propensity to react to sudden stimuli with an escape response was increased in pth2 -/- zebrafish, consistent with an elevated anxiety level. While overall social preference for conspecifics was maintained in pth2 -/- fish until the early juvenile stage, we found that both social preference and shoaling were altered later in development. The data presented suggest that the neuropeptide Pth2 modulates several conserved behaviors and may thus enable the animal to react appropriately in different social contexts.

Oxytocin receptors influence the development and maintenance of social behavior in zebrafish (Danio rerio)

Zebrafish are highly social teleost fish and an excellent model to study social behavior. The neuropeptide Oxytocin is associated different social behaviors as well as disorders resulting in social impairment like autism spectrum disorder. However, how Oxytocin receptor signaling affects the development and expression kinetics of social behavior is not known. In this study we investigated the role of the two oxytocin receptors, Oxtr and Oxtrl, in the development and maintenance of social preference and shoaling behavior in 2- to 8-week-old zebrafish. Using CRISPR/Cas9 mediated oxtr and oxtrl knock-out fish, we found that the development of social preference is accelerated if one of the Oxytocin receptors is knocked-out and that the knock-out fish reach significantly higher levels of social preference. Moreover, oxtr^−/− fish showed impairments in the maintenance of social preference. Social isolation prior to testing led to impaired maintenance of social preference in both wild-type and oxtr and oxtrl knock-out fish. Knocking-out either of the Oxytocin receptors also led to increased group spacing and reduced polarization in a 20-fish shoal at 8 weeks post fertilization, but not at 4. These results show that the development and maintenance of social behavior is influenced by the Oxytocin receptors and that the effects are not just pro- or antisocial, but dependent on both the age and social context of the fish.

Multiplexed Genome Editing for Efficient Phenotypic Screening in Zebrafish

Zebrafish are widely used to investigate candidate genes for human diseases. While the emergence of CRISPR-Cas9 technology has revolutionized gene editing, the use of individual guide RNAs limits the efficiency and application of this technology in functional genetics research. Multiplexed genome editing significantly enhances the efficiency and scope of gene editing. Herein, we describe an efficient multiplexed genome editing strategy to generate zebrafish mutants. Following behavioural tests and histological examination, we identified one new candidate gene (tmem183a) for hearing loss. This study provides a robust genetic platform to quickly obtain zebrafish mutants and to identify candidate genes by phenotypic readouts.

Dominating lengthscales of zebrafish collective behaviour

Collective behaviour in living systems is observed across many scales, from bacteria to insects, to fish shoals. Zebrafish have emerged as a model system amenable to laboratory study. Here we report a three-dimensional study of the collective dynamics of fifty zebrafish. We observed the emergence of collective behaviour changing between ordered to randomised, upon adaptation to new environmental conditions. We quantify the spatial and temporal correlation functions of the fish and identify two length scales, the persistence length and the nearest neighbour distance, that capture the essence of the behavioural changes. The ratio of the two length scales correlates robustly with the polarisation of collective motion that we explain with a reductionist model of self-propelled particles with alignment interactions.

Precise visuomotor transformations underlying collective behavior in larval zebrafish

Complex schooling behaviors result from local interactions among individuals. Yet, how sensory signals from neighbors are analyzed in the visuomotor stream of animals is poorly understood. Here, we studied aggregation behavior in larval zebrafish and found that over development larvae transition from overdispersed groups to tight shoals. Using a virtual reality assay, we characterized the algorithms fish use to transform visual inputs from neighbors into movement decisions. We found that young larvae turn away from virtual neighbors by integrating and averaging retina-wide visual occupancy within each eye, and by using a winner-take-all strategy for binocular integration. As fish mature, their responses expand to include attraction to virtual neighbors, which is based on similar algorithms of visual integration. Using model simulations, we show that the observed algorithms accurately predict group structure over development. These findings allow us to make testable predictions regarding the neuronal circuits underlying collective behavior in zebrafish.

Collective behavior emerges from genetically controlled simple behavioral motifs in zebrafish

It is not understood how changes in the genetic makeup of individuals alter the behavior of groups of animals. Here, we find that, even at early larval stages, zebrafish regulate their proximity and alignment with each other. Two simple visual responses, one that measures relative visual field occupancy and one that accounts for global visual motion, suffice to account for the group behavior that emerges. Mutations in genes known to affect social behavior in humans perturb these simple reflexes in individual larval zebrafish and change their emergent collective behaviors in the predicted fashion. Model simulations show that changes in these two responses in individual mutant animals predict well the distinctive collective patterns that emerge in a group. Hence, group behaviors reflect in part genetically defined primitive sensorimotor “motifs,” which are evident even in young larvae.

MIC-Drop: A platform for large-scale in vivo CRISPR screens

[Figure: see text].

Phenotypic analysis of catastrophic childhood epilepsy genes

Genetic engineering techniques have contributed to the now widespread use of zebrafish to investigate gene function, but zebrafish-based human disease studies, and particularly for neurological disorders, are limited. Here we used CRISPR-Cas9 to generate 40 single-gene mutant zebrafish lines representing catastrophic childhood epilepsies. We evaluated larval phenotypes using electrophysiological, behavioral, neuro-anatomical, survival and pharmacological assays. Local field potential recordings (LFP) were used to screen ∼3300 larvae. Phenotypes with unprovoked electrographic seizure activity (i.e., epilepsy) were identified in zebrafish lines for 8 genes; ARX, EEF1A, GABRB3, GRIN1, PNPO, SCN1A, STRADA and STXBP1. We also created an open-source database containing sequencing information, survival curves, behavioral profiles and representative electrophysiology data. We offer all zebrafish lines as a resource to the neuroscience community and envision them as a starting point for further functional analysis and/or identification of new therapies.

Griffin et al used CRISPR-Cas9 to generate 40 single-gene mutant zebrafish lines representing childhood epilepsies for which they evaluated larval phenotypes using electrophysiological, behavioral, neuro-anatomical, survival and pharmacological assays. Their study provides a useful resource for the future functional analysis and/or identification of potential anti-epileptic therapies.

Investigating autism associated genes in C. elegans reveals candidates with a role in social behaviour

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterised by a triad of behavioural impairments and includes disruption in social behaviour. ASD has a clear genetic underpinning and hundreds of genes are implicated in its aetiology. However, how single penetrant genes disrupt activity of neural circuits which lead to affected behaviours is only beginning to be understood and less is known about how low penetrant genes interact to disrupt emergent behaviours. Investigations are well served by experimental approaches that allow tractable investigation of the underpinning genetic basis of circuits that control behaviours that operate in the biological domains that are neuro-atypical in autism. The model organism C. elegans provides an experimental platform to investigate the effect of genetic mutations on behavioural outputs including those that impact social biology. Here we use progeny-derived social cues that modulate C. elegans food leaving to assay genetic determinants of social behaviour. We used the SAFRI Gene database to identify C. elegans orthologues of human ASD associated genes. We identified a number of mutants that displayed selective deficits in response to progeny. The genetic determinants of this complex social behaviour highlight the important contribution of synaptopathy and implicates genes within cell signalling, epigenetics and phospholipid metabolism functional domains. The approach overlaps with a growing number of studies that investigate potential molecular determinants of autism in C. elegans. However, our use of a complex, sensory integrative, emergent behaviour provides routes to enrich new or underexplored biology with the identification of novel candidate genes with a definable role in social behaviour.

Animal Behaviour: Learning Social Distancing

Early-life experience has a long-lasting influence on social behaviour. A new study has revealed a role for mechanosensation in shaping social avoidance responses in zebrafish.

Dense Circuit Reconstruction to Understand Neuronal Computation: Focus on Zebrafish

The dense reconstruction of neuronal wiring diagrams from volumetric electron microscopy data has the potential to generate fundamentally new insights into mechanisms of information processing and storage in neuronal circuits. Zebrafish provide unique opportunities for dynamical connectomics approaches that combine reconstructions of wiring diagrams with measurements of neuronal population activity and behavior. Such approaches have the power to reveal higher-order structure in wiring diagrams that cannot be detected by sparse sampling of connectivity and that is essential for neuronal computations. In the brain stem, recurrently connected neuronal modules were identified that can account for slow, low-dimensional dynamics in an integrator circuit. In the spinal cord, connectivity specifies functional differences between premotor interneurons. In the olfactory bulb, tuning-dependent connectivity implements a whitening transformation that is based on the selective suppression of responses to overrepresented stimulus features. These findings illustrate the potential of dynamical connectomics in zebrafish to analyze the circuit mechanisms underlying higher-order neuronal computations.

Fish as a model in social neuroscience: conservation and diversity in the social brain network

Mechanisms for fish social behaviours involve a social brain network (SBN) which is evolutionarily conserved among vertebrates. However, considerable diversity is observed in the actual behaviour patterns amongst nearly 30000 fish species. The huge variation found in socio-sexual behaviours and strategies is likely generated by a morphologically and genetically well-conserved small forebrain system. Hence, teleost fish provide a useful model to study the fundamental mechanisms underlying social brain functions. Herein we review the foundations underlying fish social behaviours including sensory, hormonal, molecular and neuroanatomical features. Gonadotropin-releasing hormone neurons clearly play important roles, but the participation of vasotocin and isotocin is also highlighted. Genetic investigations of developing fish brain have revealed the molecular complexity of neural development of the SBN. In addition to straightforward social behaviours such as sex and aggression, new experiments have revealed higher order and unique phenomena such as social eavesdropping and social buffering in fish. Finally, observations interpreted as 'collective cognition' in fish can likely be explained by careful observation of sensory determinants and analyses using the dynamics of quantitative scaling. Understanding of the functions of the SBN in fish provide clues for understanding the origin and evolution of higher social functions in vertebrates.

Social Preference Tests in Zebrafish: A Systematic Review

The use of animal models in biology research continues to be necessary for the development of new technologies and medicines, and therefore crucial for enhancing human and animal health. In this context, the need to ensure the compliance of research with the principles Replacement, Reduction and Refinement (the 3 Rs), which underpin the ethical and human approach to husbandry and experimental design, has become a central issue. The zebrafish (Danio rerio) is becoming a widely used model in the field of behavioral neuroscience. In particular, studying zebrafish social preference, by observing how an individual fish interacts with conspecifics, may offer insights into several neuropsychiatric and neurodevelopmental disorders. The main aim of this review is to summarize principal factors affecting zebrafish behavior during social preference tests. We identified three categories of social research using zebrafish: studies carried out in untreated wild-type zebrafish, in pharmacologically treated wild-type zebrafish, and in genetically engineered fish. We suggest guidelines for standardizing social preference testing in the zebrafish model. The main advances gleaned from zebrafish social behavior testing are discussed, together with the relevance of this method to scientific research, including the study of behavioral disorders in humans. The authors stress the importance of adopting an ethical approach that considers the welfare of animals involved in experimental procedures. Ensuring a high standard of animal welfare is not only good for the animals, but also enhances the quality of our science.

Using zebrafish (Danio rerio) models to understand the critical role of social interactions in mental health and wellbeing

Social behavior represents a beneficial interaction between conspecifics that is critical for maintaining health and wellbeing. Dysfunctional or poor social interaction are associated with increased risk of physical (e.g., vascular) and psychiatric disorders (e.g., anxiety, depression, and substance abuse). Although the impact of negative and positive social interactions is well-studied, their underlying mechanisms remain poorly understood. Zebrafish have well-characterized social behavior phenotypes, high genetic homology with humans, relative experimental simplicity and the potential for high-throughput screens. Here, we discuss the use of zebrafish as a candidate model organism for studying the fundamental mechanisms underlying social interactions, as well as potential impacts of social isolation on human health and wellbeing. Overall, the growing utility of zebrafish models may improve our understanding of how the presence and absence of social interactions can differentially modulate various molecular and physiological biomarkers, as well as a wide range of other behaviors.

A simple and effective F0 knockout method for rapid screening of behaviour and other complex phenotypes

Hundreds of human genes are associated with neurological diseases, but translation into tractable biological mechanisms is lagging. Larval zebrafish are an attractive model to investigate genetic contributions to neurological diseases. However, current CRISPR-Cas9 methods are difficult to apply to large genetic screens studying behavioural phenotypes. To facilitate rapid genetic screening, we developed a simple sequencing-free tool to validate gRNAs and a highly effective CRISPR-Cas9 method capable of converting >90% of injected embryos directly into F0 biallelic knockouts. We demonstrate that F0 knockouts reliably recapitulate complex mutant phenotypes, such as altered molecular rhythms of the circadian clock, escape responses to irritants, and multi-parameter day-night locomotor behaviours. The technique is sufficiently robust to knockout multiple genes in the same animal, for example to create the transparent triple knockout crystal fish for imaging. Our F0 knockout method cuts the experimental time from gene to behavioural phenotype in zebrafish from months to one week.

Whole-brain interactions underlying zebrafish behavior

Detailed quantification of neural dynamics across the entire brain will be the key to genuinely understanding perception and behavior. With the recent developments in microscopy and biosensor engineering, the zebrafish has made a grand entrance in neuroscience as its small size and optical transparency enable imaging access to its entire brain at cellular and even subcellular resolution. However, until recently many neurobiological insights were largely correlational or provided little mechanistic insight into the brain-wide population dynamics generated by diverse types of neurons. Now with increasingly sophisticated behavioral, imaging, and causal intervention paradigms, zebrafish are revealing how entire vertebrate brains function. Here we review recent research that fulfills promises made by the early wave of technical advances. These studies reveal new features of brain-wide neural processing and the importance of integrative investigation and computational modelling. Moreover, we outline the future tools necessary for solving broader brain-scale circuit problems.

Behavioral Teleporting of Individual Ethograms onto Inanimate Robots: Experiments on Social Interactions in Live Zebrafish

Social behavior is widespread in the animal kingdom, and it remarkably influences human personal and professional lives. However, a thorough understanding of the mechanisms underlying social behavior is elusive. Integrating the seemingly different fields of robotics and preclinical research could bring new insight on social behavior. Toward this aim, we established "behavioral teleporting" as an experimental solution to independently manipulate multiple factors underpinning social interactions. Behavioral teleporting consists of real-time transfer of the complete ethogram of a live zebrafish onto a remotely-located robotic replica. Through parallel and simultaneous behavioral teleporting, we studied the interaction between two live fish swimming in remotely-located tanks: each live fish interacted with an inanimate robot that mirrored the behavior of the other fish, and the morphology of each robot was independently tailored. Our results indicate that behavioral teleporting can preserve natural interaction between two live animals, while allowing fine control over morphological features that modulate social behavior.

CRISPR Meets Zebrafish: Accelerating the Discovery of New Therapeutic Targets

Bringing a new drug to the market costs an average of US$2.6 billion and takes more than 10 years from discovery to regulatory approval. Despite the need to reduce cost and time to increase productivity, pharma companies tend to crowd their efforts in the same indications and drug targets. This results in the commercialization of drugs that share the same mechanism of action (MoA) and, in many cases, equivalent efficacies among them-an outcome that helps neither patients nor the balance sheet of the companies trying to bring therapeutics to the same patient population. Indeed, the discovery of new therapeutic targets, based on a deeper understanding of the disease biology, would likely provide more innovative MoAs and potentially greater drug efficacies. It would also bring better chances for identifying appropriate treatments according to the patient's genetic stratification. Nowadays, we count with an enormous amount of unprocessed information on potential disease targets that could be extracted from omics data obtained from patient samples. In addition, hundreds of pharmacological and genetic screenings have been performed to identify innovative drug targets. Traditionally, rodents have been the animal models of choice to perform functional genomic studies. The high experimental cost, combined with the low throughput provided by those models, however, is a bottleneck for discovering and validating novel genetic disease associations. To overcome these limitations, we propose that zebrafish, in conjunction with the use of CRISPR/Cas9 genome-editing tools, could streamline functional genomic processes to bring biologically relevant knowledge on innovative disease targets in a shorter time frame.