Abstract
Extensive phylogenetic conservation of molecular pathways and neuroanatomical structures, associated with efficient methods for genetic modification, have been exploited increasingly to generate zebrafish models of human disease. A range of powerful approaches can be deployed to analyze these models with the ultimate goal of elucidating pathogenic mechanisms and accelerating efforts to find effective treatments. Unbiased neurobehavioral assays can provide readouts that parallel clinical abnormalities found in patients, although some of the most useful assays quantify responses that are not routinely evaluated clinically, and differences between zebrafish and human brains preclude expression of the full range of neurobehavioral abnormalities seen in disease. Imaging approaches that use fluorescent reporters and standardized brain atlases coupled with quantitative measurements of brain structure offer an unbiased means to link experimental manipulations to changes in neural architecture. Together, quantitative structural and functional analyses allow dissection of the cellular and physiological basis underlying neurological phenotypes. These approaches can be used as outputs in chemical modifier screens, which provide a major opportunity to exploit zebrafish models to identify small molecule modulators of pathophysiology that may be informative for understanding disease mechanisms and possible therapeutic approaches.
Keywords: zebrafish, disease models, neurological disorders, behavior, brain imaging, chemical screens
INTRODUCTION
In the accompanying article, we outlined the premise for using zebrafish models to study neurological disorders: abundant genetic and neural homology, coupled with advanced methods for manipulating the genome make the zebrafish an attractive experimental system for this application [1]. A full discussion of the many creative techniques that have been used to analyze the resulting models is beyond the scope of this review. Instead, we focus here on neurobehavioral profiling and brain structural imaging to evaluate neurological function and neuroanatomy and to disclose phenotypic changes. We continue by outlining the power of chemical screening in zebrafish models and speculating on potentially exciting new technologies that may be applied to this system.
NEUROBEHAVIORAL PHENOTYPING
Behavioral measurements are a powerful tool for detecting changes in brain function. Even simple sensorimotor reflex tests are useful because swimming behavior provides an integrative readout of stimulus detection by sensory systems, transmission through central processing systems and activation of the motor system. Subtle changes in brain structure or activity that result from genetic manipulations are often difficult to detect using histological or electrophysiological techniques without a priori knowledge of likely phenotypes, yet still result in robust behavioral changes.
In general, there are two frameworks that motivate use of behavioral phenotyping. One approach is to regard the nervous system as a ‘black box’, where specific neurobiological changes that cause a behavioral deficit are not the main focus of study. In such experiments, behavior represents a sensitive screening tool to assess whether changes due to a genetic manipulation can be ameliorated or rescued by chemicals, or other interventions. For such experiments, there is no special need that a behavioral phenotype in zebrafish share a close resemblance to human symptoms associated with a disease (indeed this is an unrealistic expectation for human-specific functions, such as language or complex social behaviors). Functional abnormalities still add value to neurological disease models even when the behavioral phenotypes of the human disease and zebrafish model are not fully aligned; indeed, the molecular and physiological basis of the phenotypes might be strikingly similar, and the incompletely shared clinical appearances therefore remain useful as functional assays. Interventions that rescue a phenotype in zebrafish may also show activity in disease, even though the phenotype itself may differ from the disease. For example, despite the absence of cerebral cortex in zebrafish, manipulations that broadly disrupt inhibitory signaling cause irregular bouts of movement that are accompanied by synchronous discharges in brainstem neurons and that may have physiological parallels to seizures [2]. Such episodes can be induced by pro-convulsant drugs, or by mutations in homologs of human epilepsy genes, and they have proven to be a valuable readout for discovering novel compounds with anti-convulsant actions [3].
A second approach is to use zebrafish to shed light on the neural basis for behavioral changes in human disorders. As mentioned in the companion article [1], no species can be expected to reproduce the entire range of abnormalities that occur in a human disease. Thus, animal studies often focus on ‘endophenotypes,’ which are quantitative disease-associated changes that fall short of a clinical phenotype. In schizophrenia research, a commonly used endophenotype in rodent models is prepulse inhibition of the startle response, which measures suppression of the startle response by a weak pre-stimulus. Prepulse inhibition is not a clinical symptom of schizophrenia, but like other useful endophenotypes has several helpful qualities: it can be measured objectively in human and animal species, is reliably impaired in schizophrenic patients whether the illness is active or not, and is heritable, co-segregating with schizophrenia in families [4]. Endophenotypes may reflect the outcome of disease-associated changes at a lower biological level than clinical symptoms (such as cognitive changes), and therefore be linked more closely to cellular changes that cause the disorder, and in some cases are manifest before overt clinical signs. Importantly, it may be possible to adduce that animal and human endophenotypes are related, even where there is doubt whether more complex human symptoms can be reproduced in an animal model [5].
Neurobehavioral readouts in zebrafish are primarily motor. In human patients, disorders of the motor system produce characteristic constellations of symptoms and physical signs, that are a consequence of the selective involvement of discrete cellular populations (or focal pathology such as stroke or tumor) and of the specific way the human motor system is organized and regulated. Like other model organisms, the challenges that zebrafish must address to maintain posture and execute movements differ from those of humans. Unlike humans, zebrafish continuously sustain balance under water, produce propulsive and turning movements through contractions of truncal musculature, and do not have limbs with finely skilled motor control. Not surprisingly, for diseases that are characterized by deficits in movement or balance, the corresponding zebrafish models might not include the characteristic clinical signs. It is unhelpful to apply terms used in clinical neurology incorrectly to describe phenotypic abnormalities in zebrafish. In our view it is strongly preferable to use descriptive terms, in order to avoid misleading anthropomorphisms that suggest equivalence between zebrafish phenotypes and human neurological deficits without supporting evidence. The following paragraphs outline how the motor phenotypes found in larval zebrafish models compare with the neurological abnormalities found in patients with diseases affecting homologous parts of the nervous system.
Paresis and paralysis
Pathology affecting muscle, neuromuscular junction, peripheral nerves and spinal cord can cause paresis or paralysis in zebrafish, similar to other vertebrates including humans [6–9]. In clinical neurology, tone is defined as the resistance of a relaxed body part to passive movement. Diseases affecting the spinal cord, or other supraspinal projections to motor neurons, cause a velocity-dependent increase in tone called spasticity, which is usually associated with exaggerated muscle stretch reflexes. It is not currently possible to measure tone or elicit deep tendon reflexes in zebrafish, and so terms like spasticity should be avoided. The motor cortex and corticospinal tracts, which are involved in voluntary control of appendicular muscles and fine motor movements in humans, are of clinical importance because of the frequency with which they are damaged in stroke and other diseases, such as amyotrophic lateral sclerosis (ALS). However, these structures are not present in zebrafish, and so there are no zebrafish motor phenotypes that correlate directly to corticospinal signs in humans.
Balance and coordination
The zebrafish cerebellum displays striking similarities of morphology and connectivity to the human cerebellum, including large GABAergic Purkinje cells that receive climbing fiber input from the inferior olive and mossy fiber input from cerebellar granule cells. However, there are no deep nuclei and outputs to other brain regions occur through eurydendroid cells in the Purkinje cell layer. Despite a wealth of high-quality and carefully executed studies on cerebellar morphology/development [10] and physiology [11, 12], relatively little is known about the phenotypic deficits occurring after cerebellar damage in zebrafish. Many of the characteristic signs of cerebellar disease found in patients relate to motor functions not found in zebrafish, such as speech (dysarthria), limb placement/fine motor skills (dysmetria, dysdiadochokinesia, intention tremor), and voluntary ocular movements (saccadic dysmetria, nystagmus). Some abnormalities seen in patients with cerebellar lesions, such as loss of balance, gait abnormalities or axial tremor, potentially could be measured in zebrafish models, and indeed ablation of Purkinje cells impairs proper coordination of pectoral fin and trunk movements during vertical swim movements [13]. Progressive degeneration of the cerebellum in a zebrafish spinocerebellar ataxia type 1 genetic model was not accompanied by overt changes in swimming behavior, although quantitative changes in novel tank exploration were seen [14]. Interestingly, however, adjustments to motor behaviors in response to prolonged visual perturbation in zebrafish are dependent on cerebellar function [15]. This may have parallels to classical experiments in patients with cerebellar lesions, demonstrating involvement of the cerebellum in long-term motor adaptation triggered by wearing prism glasses that alter expected visual outcomes from movements [16].
Lesions affecting the peripheral vestibular apparatus, or its central connections adversely affect postural maintenance [13] and control of image-stabilizing ocular movements in zebrafish [17], similar to humans. The terms impaired balance or postural instability, and impaired vestibular ocular reflex, are preferred for describing these abnormalities.
Hypokinetic movement disorders
Structures homologous to the human basal ganglia are recognized in zebrafish, and there has been much interest in developing zebrafish models of human diseases with prominent basal ganglia pathology. The hypokinetic diseases in humans, including Parkinson's disease, progressive supranuclear palsy and neuroleptic-induced parkinsonism, are characterized by difficulty initiating motor activity, slowed voluntary movements and a paucity of spontaneous movement. These disorders all involve pathology or dysfunction of the ascending dopaminergic projection from the substantia nigra to the putamen. As discussed in the accompanying article, the mesostriatral dopaminergic pathway is not precisely conserved in zebrafish. However, pharmacological or chemogenetic approaches targeting the dopaminergic system in larval zebrafish do reduce the frequency and speed with which spontaneous movement episodes are executed (Figure 1) [18–20]. The resulting hypokinesia may have parallels to parkinsonism in humans, but there are aspects of human parkinsonism that are not replicated in these models. In particular, the term bradykinesia—which has a strict clinical definition including progressively decreasing velocity and amplitude of rapid, repetitive voluntary movements—should be avoided, as there is currently no way to evaluate this in zebrafish, and the characteristic abnormalities in patients are elicited in appendicular muscle groups that have no clear correlate in zebrafish. Likewise, demonstration of muscular rigidity, a characteristic component of parkinsonism, would require some means to evaluate tone in zebrafish, which has not yet been described. The distinctive appearance of tremor at rest in patients with Parkinson's disease also occurs most prominently in appendicular muscle groups that have no correlate in zebrafish. Furthermore, rest tremor is not even a consistent feature in primate models with dopaminergic lesions [21] and so it would be unrealistic to expect damage to the dopamine system to cause tremor at rest in zebrafish.
Figure 1.
Hypokinesia in zebrafish with impaired dopaminergic function. Larval zebrafish at 6 dpf were exposed to incremental bath concentrations of haloperidol, a highly potent dopamine D2 receptor antagonist and antipsychotic medication that commonly provokes parkinsonism in human patients. (A) Example 30-second swimming vectors for four replicate zebrafish at each haloperidol concentration. Video recordings of larvae housed in 96-well plates were analyzed to show the vector track of the larval centroid in successive video frames. (B) Quantitative motor performance of 24 zebrafish in each group over 1 hour of video recording. A dose-dependent decrease in mean speed (= displacement/duration of assay) was caused by a modest decrease in the speed at which movements were executed (active swim speed) combined with a more robust change in the proportion of each assay during which the zebrafish were motile and progressively longer pauses between movement events (p < *0.05, **0.01, ***0.001, ****0.0001 versus 0 μM control, 1-way ANOVA with Dunnett's multiple comparisons test).
Hyperkinetic movement disorders
Hyperkinetic disorders are a heterogeneous group of conditions characterized by involuntary movements. Huntington's disease and other forms of chorea may cause involuntary movements by impairing function of the basal ganglia indirect pathway (including the projection from the putamen to the external globus pallidus and subthalamic nucleus). The ventral telencephalic area of several fish species includes GABAergic neurons and cells expressing substance P [22], enkephalin [23] and D1 and D2 dopamine receptors [24, 25], which are markers of the direct and indirect pathway striatal neurons in mammals. However, the details of this region are still being resolved in zebrafish and no clear correlate of the subthalamic nucleus has yet been described. Furthermore, the characteristic movements of chorea are generally most prominent in distal muscles, although it can involve the trunk, face, tongue and soft palate. Mouse models of Huntington's disease do not show chorea, although gene knock-in pigs did show rapid irregular abnormal movements reminiscent of chorea [26]. It is currently unclear whether the motor manifestations of chorea can be replicated in zebrafish models. Expression of a Huntingtin fragment with an expanded polyglutamine tract in transgenic zebrafish caused irregular movement patterns, with decreased frequency and increased duration of movement events, followed by loss of lateral and then vertical stability, but no movements suggestive of chorea [27]. This does not detract from studies aiming to exploit zebrafish expressing mutant Huntingtin to understand neuronal pathophysiology and the cell biological and molecular events that cause neurodegeneration, but these models are less likely to yield insights into the nature of the circuit disruptions that cause the characteristic movements in patients.
Other types of involuntary movements in human patients include dystonia (sustained muscular co-contractions resulting in abnormal postures), tics (repetitive, stereotyped, simple or complex movements often produced voluntarily to relieve an unpleasant premonitory sensation), myoclonus (brief shock-like muscle contractions), and tremor (involuntary oscillating movements caused by phasic contractions of antagonist muscles). However, both the brain regions that mediate these involuntary movements, and the molecular factors underlying their etiology, are uncertain in many cases. Zebrafish movements resembling these symptoms have not been described, and it is unclear whether molecular manipulations designed to mimic genetic causes of these conditions will provoke such movements. However, the presence of neurobiological phenotypes, for example axon outgrowth defects in a zebrafish Teneurin Transmembrane Protein 4 model of essential tremor may still be useful for understanding genetics and disease pathophysiology [28].
Sensorimotor integration
Larval zebrafish offer several tests of sensorimotor function that are not routinely measured in clinical practice, but which are easily evaluated in zebrafish and useful for analysis. For example, studies using the zebrafish escape circuit can take advantage of a rich literature spanning more than a century where the behavioral similarity to the human startle response is backed by consistent effects of pharmacological and genetic manipulations [29]. The fish escape response, and mammalian startle behavior are both mediated by giant brainstem reticulospinal neurons, that are developmentally derived either exclusively or in part from embryonic rhombomere 4, receive short latency sensory information, and directly activate motor neurons in the spinal cord [30]. Despite this similarity, mutations that affect the regulation of these neurons may have consequences that superficially appear distinct in humans and zebrafish. In humans, mutations in the glycine receptor beta subunit gene cause hyperekplexia: an exaggerated startle followed by transient muscle rigidity due to a failure of glycinergic inhibitory signaling that normally regulates and terminates startle behavior [31]. In contrast, zebrafish bandoneon mutants, that carry mutations in the homologous glycine receptor, beta b (glrbb) gene, show a muted response to stimuli, performing an abnormal contraction of the trunk, instead of a lateral tail flexion [32]. The zebrafish response is also due to an absence of glycinergic neurotransmission, but here the failure of glycine-mediated reciprocal inhibition in spinal circuits leads to co-contraction of the left and right trunk musculature, rather than to one side predominating.
Auditory evoked escapes provide a window into multiple aspects of brain function. Changes in auditory sensitivity or sensorimotor transmission are reflected in differences in responsiveness—the mean proportion of trials on which a fish reacts. Behavioral tracking also provides detailed information on movement kinematics, which may be perturbed if motor systems are abnormal. Thus, the highly stereotyped form of the auditory startle response in zebrafish larvae presents an efficient way to assess auditory sensory function, central integration and motor output (Figure 2).
Figure 2.
Measuring the auditory startle response in zebrafish larvae. (A) Auditory/vibrational cues are delivered using a minishaker device, synchronized to a high-speed camera to monitor responses. (B) Response of individual larvae are tracked allowing the response rate to be calculated. (C) The statoacoustic ganglion (VIII) delivers auditory information to the Mauthner cells (m) that drive rapid escape responses, and a population of prepontine neurons (pp) that control a slower, longer-latency mode of escape. (D) To measure prepulse inhibition, a calibrated weak prepulse is delivered 30–3000 ms before an intense stimulus. The graph shows the mean escape probability per trial (% response) for larvae that are exposed on different trials to the intense stimulus delivered alone (red marker), or when the same stimulus is preceded by a weak prepulse at different ‘interstimulus intervals’ (the time between the prepulse and the intense stimulus; black markers). On trials including a prepulse, larvae show a reduced response probability, compared with when the intense stimulus is delivered alone. Distinct cellular mechanisms control prepulse inhibition at different interstimulus intervals.
Startle thresholds are dysregulated in several brain disorders. A commonly used endophenotype for schizophrenia is a reduction in ‘prepulse inhibition’—the suppression of the auditory startle response by a brief pre-stimulus [33]. Prepulse inhibition is disrupted by mutations in N-methyl-d-aspartate (NMDA) receptor genes, of interest because depressed signaling through glutamatergic NMDA receptors has long been postulated in the etiology of schizophrenia [34–36]. Zebrafish perform two distinct types of escape behavior in reaction to an intense auditory stimulus, only one of which (the ‘short-latency’ escape response) is susceptible to prepulse inhibition [37]. As in rodents, preventing signaling through NMDA receptors, whether via gene mutations or chemical antagonists, suppresses prepulse inhibition of short-latency escapes in zebrafish [38, 39]. These findings provided a basis for using the zebrafish system to reveal conserved vertebrate cellular pathways for prepulse inhibition. For instance, experiments using zebrafish revealed specific interneurons that mediate prepulse inhibition and demonstrated that at least part of the effect is due to presynaptic inhibition [40], consistent with evidence implicating presynaptic deficits in schizophrenia [41]. Thus, behavioral experiments using zebrafish may lead to cellular-level insights into how disease-relevant circuits are changed by experimental manipulations that mimic those underlying human brain disorders. Interpreting the meaning of these changes for human brain function requires an understanding of where zebrafish and human circuits are similar, and where they diverge functionally.
Ocular movements
Zebrafish can produce image-stabilizing ocular movements such as the vestibuloocular reflexes and optokinetic response; the latter is especially useful because of the ease with which it is elicited experimentally [42]. The optokinetic response is provoked by a moving grating pattern that occupies a large portion of the visual field. This results in slow eye movements that track the stimulus. If the stimulus continues so that eyes reach the limit of movement, fast positional resetting movements occur in the opposite direction; the alternation of fast and slow movements in response to a unidirectional stimulus is called optokinetic nystagmus [43, 44]. The speed, contrast and spatial frequency of the stimulus can be modified readily to assess visual acuity and sensitivity in mutant models [45]. For example, Allan-Herndon-Dudley syndrome is an intellectual disability disorder that includes abnormal eye movements due to mutations in the monocarboxylate transporter 8 gene [46]. Accordingly, zebrafish mct8 mutants show a quantitative reduction in the optokinetic response, and correspondingly, a reduction in expression of cone photoreceptor genes that may explain why visual function is impaired [47]. In both fish and mammals, brainstem neurons including neurons in the medial vestibular nucleus encode eye velocity, while motor neurons in the abducens and oculomotor nuclei control the extraocular muscles [48]. However, the optokinetic reflex in mammals is mediated by both a subcortical pathway through the pretectal nucleus of the optic tract, and a pathway involving the visual cortex [49, 50]. Pretectal neurons also mediate the optokinetic response in zebrafish [51]. But because the cortical pathway, which is absent in fish, predominates in humans, phenotypes may diverge. Thus, in humans, mutations in the roundabout guidance receptor 3 gene (ROBO3) cause horizontal gaze palsy with progressive scoliosis, that includes a near complete loss of horizontal eye movements due to loss of commissures that transmit information between hemispheres [52]. Interhemispheric transfer can be assessed in zebrafish using monocular presentation of the moving grating to only one eye; in wildtype fish, this drives the conjugate movements of both eyes [42, 53]. In zebrafish robo3 mutants, major abnormalities in optokinetic responses appear during monocular stimulation, due to deficits in commissure formation [54].
Stress and anxiety
Although many behavioral measurements in zebrafish are related to human behavior through homology of their underlying neural pathways, there are several tests that do not benefit from a rigorous neurobiological basis. One such measure is the propensity of larval zebrafish to be located close to the walls of a testing arena, which is sometimes posited as an indication of stress or anxiety. This behavior has been described as ‘thigmotaxis’ (wall-hugging), and by analogy to the behavior of mice in an open-field test, used to infer stress or anxiety. However, even in rodents, it is questionable whether the open-field test is a valid measure of these traits and wall proximity correlates poorly with indices of anxiety in humans [55]. Moreover, when placed in a large area, zebrafish larvae execute a high ratio of forward swimming movements to turning movements. When forward movements predominate in a bounded arena, wall-following behavior naturally arises [56]. Thus, the outward swimming pattern of larvae naturally leads to wall proximity without implicating stress or anxiety [57]. Moreover, if the same large arena includes a circular inner perimeter (for example, in a donut shaped arena), larvae do not ‘hug’ the inner convex wall, as would be expected for true thigmotaxis. In fact, outward swimming behavior has been interpreted as part of an environmental exploratory strategy, which could even suggest that larvae with a high degree of wall proximity manifest boldness rather than anxiety. Variants of the open field test in larval zebrafish do not currently show sufficient construct validity to be used to measure stress.
Leaving aside the difficulty in adequately defining ‘stress’ and ‘anxiety’ as neurobiological traits, and the equally difficult question of whether zebrafish have any conscious experiences approximating these states in humans, it is not yet clear whether behavioral assays can be used to measure related functions in zebrafish larvae. Alternative physiological measurements of environmental stress responses may be more robust and meaningful. The main corticosteroid in both teleost fish and humans is cortisol, and cortisol levels increase when larvae are exposed to almost any potential stressor, ranging from thermal shock to chemical exposure [58, 59]. Heart rate measures may also be a fruitful assay to measure autonomic activity as provoked by stressors: as in mammals, repeated electric shocks elicit tachycardia (elevated heart rate) resulting from activation of the sympathetic nervous system [60]. It has been long established in mammals that startle magnitude increases when paired with a noxious stimulus [61] and likewise, elevated startle is observed in zebrafish lacking neuropeptide parathyroid hormone 2 (pth2), a gene that is involved in stress-related responses [62].
Social behavior
A second class of experiment that requires cautious interpretation is measurement of social behavior. Adult zebrafish show a range of sophisticated social behaviors, including dominance hierarchies, aggression, and affiliative behavior such as shoaling. Shoaling can be measured in larvae as early as the second week of development, triggered by complex visual and olfactory cues [63–65]. Zebrafish homologs of oxytocin and arginine-vasopressin modulate shoaling, consistent with their role in regulating social behavior in mammals [66]. As in humans, affiliative behavior in fish is likely driven by diverse factors, including predator avoidance, foraging efficiency and reproductive success [67, 68]. However, given the broad range of triggers and pathways for social behavior in both fish and humans, it cannot be assumed that genetic changes in humans that disrupt affiliative behavior (as in autistic spectrum disorder) will produce similar manifestations in zebrafish.
Experimental considerations
Behavior is notoriously variable, even in the face of attempts to carefully control experimental conditions, sometimes making it difficult to obtain reliable measurements. As for other species, genetic background can strongly influence results obtained with behavioral experiments in zebrafish [18, 69]. It has not proven possible to generate congenic zebrafish strains. In fact, wildtype stocks comprise such extensive internal genetic heterogeneity, that variants of the same strain maintained in different labs may be genetically distinct [70]. Naturally, this may lead to a high degree of variability in behavior, even among sibling animals of the same strain. The lack of inbred strains has important ramifications for behavioral experiments with mutants, as it demands that not only should control animals be of the same strain, but in rigorous experiments, controls should also be sibling clutch mates that harbor the same constellation of background variant alleles. Even ‘cousin’ experiments, where mutant larvae are compared to wildtypes that are each offspring of sibling homozygous mutant and wildtype parents respectively, risk actually testing the effect of a background variant unrelated to the genetic lesion of interest but that differently segregated during breeding. Similar considerations are present in experiments using transgenic manipulations. In some cases, transgenes may integrate and disrupt endogenous genes, or be tightly linked to alleles that influence behavior. To control for such effects, independent transgenic lines may be used, or when using binary systems like Gal4/UAS, sibling controls that contain each of required transgenes alone can be tested to assess the effects on behavior.
Another confound to interpreting zebrafish phenotypes is the strong influence on locomotor behavior of the circadian cycle, and short-term periods of arousal (as in other vertebrates) [71, 72]. These processes, already present in early larval stages, alter the frequency with which zebrafish initiate swimming movements. Changes in swimming behavior do not invariably reflect alterations in movement control but may be due to differences in internal state.
In the natural environment, zebrafish thrive in a wide range of conditions [73]. Perhaps in consequence of this adaptability, differences in laboratory conditions may alter larval behavior significantly. For example, although zebrafish survive across a large range of water oxygen levels, low oxygen conditions may decelerate development greatly and modify subsequent effects of hypoxic conditions at adult stages [74, 75]. Similarly, not only do illumination conditions during rearing affect the rate of embryonic development but also specific light wavelengths influence behavior [76, 77]. Thus, in many labs, embryos to be used in behavioral experiments are raised in incubators that not only regulate temperature but also mimic daily light/dark cycles. The standard for zebrafish laboratory experiments is to preserve a temperature of 28.5°C, although embryos tolerate temperatures ranging from 23°C to 34°C, and in nature, temperature also fluctuates across the circadian cycle [78]. Feeding status and diet also strongly influences larval growth rates [79, 80]. To avoid variability introduced by nutritional status, many behavioral studies are performed during the first week post-fertilization, before external feeding is essential—larvae show the same rate of growth and survival irrespective of whether food is introduced at day 5 or day 8 [81]. Finally, rearing density must also be carefully controlled; larvae raised at low or high density show distinct sensorimotor responses to at least some types of stimulus [69, 82, 83]. This may be particularly important for studies on social behavior involving olfactory-stimulus based kin-recognition, as imprinting for kin-derived odors appears to occur during a narrow critical period during the first week of development [84]. Although all of these factors may be diligently controlled by an individual lab to maximize reproducibility, raising conditions are not yet standardized across labs, and likely contribute to variable replicability between research groups.
STRUCTURAL BRAIN IMAGING
Brain imaging has been a staple technique for phenotypic analysis since the first zebrafish mutants were isolated. In the earliest studies, optical methods were used to examine neurons identifiable by their large size and stereotyped position within the embryo, and histological techniques applied to reveal organization in neural tissue slices [7, 85]. This was quickly followed by antibody stains that disclosed morphological abnormalities in specific neuronal cell types and transgenic lines with fluorescently labeled neuron types of interest [6, 86]. All these methods have been widely used to probe the molecular genetic control of brain development, and phenotypic consequences of mutations in homologs of human disease genes.
Given the complexity of even the larval brain, and the many types of measurements that are possible, it helps greatly if one has a priori knowledge of what kind of phenotype to expect (for example from human symptoms or mouse models) in order to focus examination on relevant structures. To some extent, this defeats the purpose of studying zebrafish models. Many studies report that a zebrafish phenotype recapitulates deficits seen in patients, but do not describe new biological insights. Rather than searching under the spotlight cast by prior information, one would ideally systematically analyze the entire brain in an unbiased manner, to discover unexpected phenotypes.
More recent work in zebrafish has emulated human brain imaging studies, where the entire brain is scanned, and abnormalities identified by comparing images acquired from patients and control subjects quantitatively [87]. Whole-brain images can be acquired readily using confocal microscopy, from zebrafish in which neurons are labeled with either transgenically expressed fluorescent proteins or immunohistochemical stains [88, 89]. Computational methods then enable highly accurate registration of each image volume to a zebrafish brain template, with precision approaching that of a single neuron diameter (Figure 3) [90]. Voxel-based morphometry—a method that compares statistically the intensity of the fluorescent signal at each voxel in mutant and wildtype brains—can then be performed to identify clusters of voxels that are significantly different between groups (Figure 4) [91]. Even in overtly normal fish, this method may disclose subtle phenotypes, such as in potassium channel tetramerization domain containing 15 a/b (kctd15a/b) double mutant zebrafish where voxel-based morphometry revealed restricted loss of a small midbrain nucleus—the torus lateralis (TLa)—that would have been difficult to detect visually. The TLa produces growth hormone releasing hormone, and consistent with its absence, kctd15a/b mutants show a delayed growth phenotype that was reproduced by laser ablation of the TLa [92]. Thus, voxel-based morphometry has great potential as a powerful unbiased approach for phenotype discovery in zebrafish.
Figure 3.
Registration of larval zebrafish brain images. (A) Maximum projections of brain images from three transgenic vglut2a:DsRed larvae, pseudocolored red, green and blue. Left image shows that superimposition has limited overlap due to biological and imaging differences. Right image is after computational co-registration, resulting in a close alignment, which is even more apparent when the position of the Mauthner cell in different fish is compared (bottom panels). (B) Computational registration allows expression patterns of different transgene expression patterns to be compared. Top images show brain images from four different transgenes that were each co-expressed with the vglut2a:DsRed transgene. Brain images may then be each registered to a vglut2a:DsRed reference brain, allowing comparison of transgene expression patterns.
Figure 4.
A pipeline for voxel-based morphometry in zebrafish. Whole-brain confocal scans are registered to a template brain. From here, differences between groups can be identified either by identifying clusters of pixels that are statistically different, or by comparing mean fluorescence intensity within brain regions defined by a reference atlas.
Extending this technique, signals from multiple fluorescent reporters can be acquired simultaneously, allowing different sets of neurons to be visualized and compared in the same fish, for example, labeling all neurons with elavl3:mCardinal (pan-neuronal), vglut2a:GFP (glutamatergic neurons) and gad1b:RFP (GABAergic neurons) transgenic lines. In this way, a single experiment can probe the microarchitecture of the entire brain and its cellular level composition [91]. Live brain imaging in transgenic lines rather than through immunohistochemical stains is advantageous, in that it avoids the tissue distortion that occurs during fixation and permeabilization, although to some extent these artifacts are corrected during elastic brain registration [90]. Still, by reducing sample variability, live imaging augments the sensitivity of voxel-based morphometry. Alternatively, fluorescent stains can label brain tissue, in particular the lipophilic dye lysotracker [93]. This avoids the necessity to cross a genetic modification of interest into a transgenic reporter background, but also tends to produce a labeling intensity gradient such that superficial structures are over-stained while deep internal areas like the hypothalamus are weakly labeled. Note that when using transgenic lines that label a specific neuronal subclass with a fluorescent protein, changes in fluorescence intensity flagged by voxel-based morphometry generally reflect differences in the number, organization, or density of neurons, rather than a change in the expression level of the reporter.
Voxel-based morphometry does not require neuroanatomical information to identify clusters of voxels that differ between groups. However, because cellular resolution brain scans comprise several million voxels, it is critical to control significance thresholds for multiple comparisons; this can greatly diminish statistical power to resolve subtle differences. A complementary approach that retains high sensitivity is to compare the mean voxel intensity between mutants and wildtypes, within neuroanatomically defined brain regions (Figure 4). This method leverages zebrafish brain atlases, that define three-dimensional digital masks corresponding to annotated brain regions in larval and adult reference brains [89, 94–97].
Neuroanatomical atlases also help to resolve differences in brain volume, or in the size of individual brain regions. Previously, changes in brain size were estimated by measuring the inter-ocular distance, for example enlarged brains in zebrafish mutants for chd8, a gene strongly associated with macrocephalic autism in patients [98]. In human subjects, macrocephaly may reflect increases in brain size, but may also result from hydrocephalus or skeletal dysplasias, factors that may also influence interocular measures in zebrafish [99]. Interocular distance reflects differences in forebrain volume. In contrast, after registering brain images computationally to a reference brain atlas, one may then back-transform the atlas onto the original brain scans. The volume of each brain is then easily measured simply by counting voxels labeled as ‘brain’.
A similar approach is used to assess the volume of individual brain regions. X-linked acrogigantism, characterized by large physical stature, results from duplications of an orphan receptor encoded by G protein-coupled receptor 101 (GPR101). Conversely, maternal zygotic zebrafish with mutations in gpr101 exhibit reduced growth, and morphometry revealed an expansion of the hypothalamus [93]. An enlarged hypothalamic phenotype may result from an overactive wnt signaling system during neural development [100], and accordingly several wnt pathway genes were significantly upregulated in gpr101 mutants. In assessing changes in regional brain volume, it is important to consider whether absolute or relative regional brain volumes should be compared, especially as microcephaly is a relatively common mutant phenotype [101]. Finally, much of the larval zebrafish brain can be designated as cell-rich or neuropil-rich. Global changes in ‘grey-matter’ or ‘white-matter’ density and volume can therefore be assessed, and compared to deficits seen in human brain imaging studies.
Given the incompleteness of current zebrafish brain atlases, it is also useful to be able to detect spatially restricted changes in brain volume, without relying on neuroanatomical annotations. This can be achieved through ‘tensor-based’ morphometry. During elastic brain registration, individual voxels are dilated or compressed in order to best match the local structure of the reference brain. The extent to which each brain voxel is so modified may be then subject to voxel- or region-wise comparisons as above [91].
Brain morphometry has not yet been widely applied in zebrafish, and there is substantial room for optimization. Systems that enable automated confocal or light sheet microscopy could enable large numbers of fish to be imaged per day, improving sensitivity, and potentially reducing variability due to handling [102–104]. Morphometry would also benefit from better ways to normalize fluorescence within and between fish: brain regions such as the hypothalamus that are several hundred microns deep, produce a much weaker signal than superficial structures. It is possible to compensate for these differences by increasing laser power during acquisition at defined depths within the brain, however a more powerful method is to normalize images computationally post-acquisition, using models of light passage through brain tissue [105].
Finally, it is worth noting that the same considerations involved in raising larvae for behavior also apply to brain imaging studies. Genetic background is likely to influence brain morphometry: across species domestication generally (but not always) reduces brain size [106, 107]. As in other species, sensory experience modifies initially hard-wired connectivity, for example, in refining retinal ganglion cell axonal arborizations within the optic tectum [108]. However, even motor activity may influence brain development: increased movement stimulates proliferation of neurons in the developing zebrafish forebrain at the expense of differentiation [109]. Likewise changes in environmental rearing conditions may modify brain development: increased salinity reduces the proliferation of pituitary lactotrophic cells that regulate osmotic homeostasis [110]. It is therefore essential to control rearing conditions carefully in brain morphometry experiments.
CHEMICAL MODIFIER SCREENING
Zebrafish larvae can be bred in large numbers and housed in multi-well plates. Coupled with high-throughput phenotypic readouts, a large number of experimental interventions can be analyzed rapidly. This general approach allowed large genetic screens, for which zebrafish became well-established as a powerful model for investigating the molecular basis of vertebrate development in the 1990s. In these studies, panels of random N-ethyl-N-nitrosourea (ENU)- or retroviral-induced genetic mutants were bred to homozygosity and screened for phenotypes of interest. With several critical adaptations relating to the practicalities inherent in chemical exposure, high throughput approaches have been used more recently to screen chemical libraries for molecular structures that modify phenotypes of interest in zebrafish models (Figure 5).
Figure 5.
Overview of a phenotype based chemical modifier screen using a larval zebrafish model. Schematic depiction of how a small molecule library can be screened against the neurological phenotype of a zebrafish model. Machine vision and computational approaches to measure neurobehavioral phenotypes yield unbiased outputs, providing opportunities for rigorous detection of quantitative neurological rescue by chemicals.
Objectives of chemical screens
Chemical modifier screens in zebrafish neurological disease models are attractive for several reasons, and there is correspondingly a range of possible approaches. Small libraries of chemicals with well-annotated pharmacological actions, for example kinase inhibitors, can be used as molecular probes for understanding the biology underlying phenotypes of interest. Larger libraries containing drugs that are currently used in clinical practice can be screened as a first step in repurposing established pharmaceuticals for new indications in neurological disease. Potentially, even larger libraries of diverse chemical structures could be screened to identify novel compounds with effects in mitigating a disease phenotype as a first step in drug discovery. Finally, focused panels of analogs derived from initial hits in zebrafish or other models may be assayed against neurological phenotypes to determine structure–activity relationships, assist in identification of targets, and help with lead optimization prior to testing in more complex systems. Not surprisingly, studies so far have focused on smaller chemical panels given the complexities of chemical screening and the resources necessary for scale up to larger libraries.
Screening chemicals for activity in vivo using zebrafish disease models presents several potential advantages, both for probing biology and for initial steps in drug repurposing or discovery. First, for many neurological diseases the optimal molecular targets for therapeutics are currently unknown (and many central nervous system (CNS)-active drugs in clinical use have multiple targets). Historically, many first-in-class drugs have been discovered using phenotypic screens (often in vitro), but neurological diseases present a challenging problem for this approach [111]. Disease phenotypes frequently arise from cell non-autonomous events such as neurotransmission and synaptic pruning, neuronal-glial signaling or neurovascular coupling, which would be very difficult to replicate in vitro. Zebrafish offer in vivo models that balance complexity with practicability and are therefore particularly well-suited to screen for compounds that modify neurological phenotypes. Second, given the inexact relationship between biochemical markers of diseases and clinical outcomes, it is important to ensure that putative therapeutics are primarily directed at improving functional neurological endpoints, which can be measured easily using automated assays in zebrafish models. This presents the opportunity to find compounds both with disease-modifying and symptomatic activity, to identify modifiers of diseases in which neurological phenotypes are manifest prior to morphological abnormalities, and to identify mechanisms and possible therapeutic targets in diseases for which there are no reliable morphological or biochemical endpoints, such as many psychiatric diseases or some types of dystonia or epilepsy. Since assays are carried out in a whole animal, endpoints represent a complex composite of: (i) pharmacodynamic activity at some point in the molecular pathways mediating the phenotype; (ii) the potential for adverse outcomes from off-target effects at the chemical concentrations tested (either in the CNS or systemically); and (iii) pharmacokinetic properties that dictate whether chemicals reach the CNS at efficacious concentrations. Although at first sight this may seem hopelessly complicated, embracing the complexity of the system might allow isolation of compounds with strong activity, limited toxicity and good CNS penetration, essential properties of drug candidates.
Chemical application
There are several practical considerations for chemical screens. The first relates to chemical exposure. This is conveniently accomplished by dissolving chemicals in the water housing zebrafish larvae. Zebrafish can survive in as little as 50 μL of fluid [112], so in theory only very small amounts of library chemicals are needed. In practice, chemical exposures are usually carried out in multiple larvae each housed in single wells of 96-well plates (200– 300 μL) or in groups of larvae housed in 6-well plates (up to 2 mL), to provide replicate data points and ensure animal health and optimal performance in neurophenotyping assays. In any case, the large volume of water compared with the tiny volume of larval zebrafish, thought to be around 300 nL [113], ensures prolonged exposure to stable concentrations of dissolved chemical, even for those that are rapidly metabolized or have a short half-life in vivo.
A related question concerns the penetration of chemicals into zebrafish larvae. During early embryogenesis, chemicals diffuse from the water directly into the embryo (prior to hatching, this also necessitates chemicals passing through the chorion). Later in development, CNS exposure may depend more on delivery via the circulation, more closely mimicking the route of exposure that would be used clinically for drugs. Because toxicity during early embryonic exposure may obscure later effects relevant to disease phenotypes, chemical screens frequently start exposure at 2–3 days post-fertilization (dpf), after initial organogenesis is complete. This also eliminates any uncertainties associated with penetration through the chorion but adds a translationally relevant level of complexity relating to the blood–brain barrier. Tight junctions between endothelial cells, apposition of astrocyte foot processes to the perivascular spaces, and a series of active membrane transporters in humans regulate the entry and egress of many molecules from the CNS [114]. Zebrafish, like mammals, show selectivity in which molecules can pass between the circulation and the brain, which may be advantageous for discovering or optimizing chemical structures that are CNS-penetrant. CNS vascularization in zebrafish starts around 32 hours post-fertilization (hpf) with invasion of hindbrain tissue by sprouts from perineural vessels (reviewed in [115]). By 48 hpf, vessels with patent lumens (central arteries) pass through the CNS substance, from the basilar and basal communicating arteries, and drain into the choroid vascular plexus in the midbrain and to the primordial hindbrain channel. It is thought that formation of the blood–brain barrier occurs concurrently with angiogenesis, so that many genes implicated in regulation of vascular transport are expressed immediately when angiogenesis in the CNS is complete. This includes expression of genes involved in tight junction formation between endothelia, and expression of genes encoding specific transporters for importing nutrients or excluding metabolites or xenobiotic species. Cells that contribute to the neurovascular unit in mammals include glia and pericytes that are also found in close proximity to CNS vessels in zebrafish larvae. These limit leakage of macromolecules from CNS capillaries by as early as 60 hpf. However, the maturation of the blood–brain barrier continues until at least 10 dpf and possibly later, as evidenced by macromolecule leakage studies at different developmental points [116].
Direct measurement of drug absorption into larvae has revealed that some chemicals are almost completely excluded, whereas others are concentrated more than 10-fold in larval tissue, making it difficult to ascertain the effective dose applied to the larva [112, 117]. Nevertheless, comparative studies between adult zebrafish and mice show that brain-to-plasma ratios for panels of small molecules are very similar between the species suggesting phylogenetic conservation of blood–brain barrier (BBB) properties [118]. The extent to which the larval zebrafish BBB replicates the transport properties of the human blood–brain barrier for drug delivery to the CNS is currently unclear, but compounds that do not enter the CNS and therefore appear inactive in larval zebrafish screens are unlikely to be useful in mammalian models and this may add value to larval screening platforms.
Finally, the timing of chemical exposure is a key consideration that is influenced by the nature and time course of the pathophysiological events being investigated. One strength of chemical screens is the ease with which exposure to inhibitors can be started at a chosen timepoint. This might be early in development if the aim is to modify a process that occurs during patterning or morphogenesis, or much later if the aim is to target events in end-differentiated neural or glial cells. In the latter case, starting exposure later can help avoid complications inherent in interpreting phenotypic endpoints that might represent a composite of off-target developmental effects and intended effects in established cell populations and circuits, particularly since both might be mediated by the same molecular targets. The duration of treatment is another factor, which is influenced by the time course of the phenotype and practical concerns. Pharmacological agents that modulate circuit function directly, for example anticonvulsants, might modulate phenotypes immediately after CNS entry and cognate receptor binding, necessitating relatively short exposures. In contrast, interruption of upstream cellular mechanisms indirectly driving phenotypes that represent pathophysiological end stages, such as cell death, will likely require more prolonged chemical exposures. In general, longer exposures complicate screens by necessitating repeated replacement of the media with fresh chemical, which reduces throughput and increases cost. Consequently, the exposure regimen is usually determined by designing the most efficient way to investigate the underlying biology of interest.
Measuring chemical modifier effects
A second practical consideration for chemical screens concerns assay outputs. The earliest developmental genetic screens in zebrafish used predominantly morphological endpoints, defined by light microscopy or by labeling structures of interest with specific probes using RNA in situ hybridization [119, 120]. These simple and robust assays may be useful in chemical screens in zebrafish models of disorders characterized by overt changes in CNS morphology or alterations in the distribution or number of cells expressing specific markers. In the latter case, labeling the cell populations of interest with transgene markers helps to eliminate laborious downstream steps. Combining this with automated image capture and analysis increases throughput and removes biases inherent in manual observations [121]. Quantitative imaging also potentially adds opportunities for measuring pathophysiological endpoints using biosensors for specific processes such as reactive oxygen species (ROS) elaboration, neurotransmitter release, or cytosolic calcium levels. However, we anticipate that the major utility of zebrafish models in chemical screens will leverage neurobehavioral assays, since these are more likely to reflect translationally relevant restoration of neurological function (Figure 5).
Neurobehavioral assays in larval zebrafish chemical screens take advantage of computational analysis of video streams. Automating both testing platforms and data analysis produces quantitative measurements, eliminates biases inherent in manual assays and increases throughout. This enables experimental groups to be tested in parallel and boosts sample size (in terms of both animals and replicate measurements), factors which are critically important to address the intrinsic variability in behavioral tests.
Conventionally, biochemical assays used for chemical screening are expected to produce quantitative outputs that are entirely non-overlapping between positive and negative controls. These stringent assay performance metrics are essential to prevent a prohibitively high false discovery rate resulting from the large number of measurements made during a screen. Ensuring that the assay outputs for the model and rescue control do not overlap requires a difference of 6 standard deviations between positive and negative control means, if the data are parametrically distributed and the variances are equal, since 99% of each distribution falls within ±3 standard deviations of its mean. This threshold forms the basis for the Z-factor metric commonly used to evaluate assay performance [122]. However, it is difficult to achieve this with behavioral endpoints, which are inherently variable and in which signal sizes are constrained by basic physiology: unless a phenotype is very severe, it is unusual for any model to show such a large difference from controls. By including replicate larvae and normalizing outputs to controls run at the same time, it may be possible to achieve this high standard in some situations. However, it is currently unclear that satisfying these conservative criteria is necessary for useful screening applications, and it may be more appropriate to evaluate quantitative assays using metrics used for other biological applications, such as siRNA screens [123].
An example is provided by a screen for compounds that suppressed paroxysmal swimming episodes in a zebrafish Dravet syndrome model. Positives were defined as compounds reducing locomotion by more than two standard deviations of the change caused simply by media replacement, resulting in identification of promising candidates [3, 124]. Further work revealed high affinity of several of these positives for serotonin receptors, leading to promising therapeutic trials using a serotonin agonist in Dravet syndrome patients [125]. Impressive results were also recently obtained using a screen for compounds that suppress opioid self-administration in a sophisticated new zebrafish addiction model [126]. A lead candidate obtained in this system acutely reduced hydrocodone and fentanyl self-administration in rats [127].
Even successful chemical screens will not always generate leads that are effective in mammals. First, many chemicals bind with differing affinities to a range of molecular targets. Varying degrees of conservation of chemical binding sites between zebrafish and other species may mean that drugs that strongly affect behavior in zebrafish may not act similarly in humans. Second, there has been a persistent concern that chemicals introduced into the water may produce behavioral responses due to interaction with external sensory systems, including through irritation or damage to skin [128]. Similarly, at least some molecules may penetrate most readily into the eyes, leading to the possibility that behavioral changes are secondary to alterations in retinal signaling [129].
FUTURE DIRECTIONS
Neurobehavioral studies are valuable in analyzing mutant models, in that they provide an unbiased window into nervous system activity. Potentially even more powerful are techniques for directly measuring activity throughout the intact brain. The last decade has seen rapid development of techniques for whole-brain functional imaging in early larval zebrafish, primarily by imaging neuronal activity using pan-neuronally expressed genetically encoded calcium indicators [130]. High-throughput whole-brain calcium imaging has been used to assess the effects of a panel of drugs on brain activity during seizures, in the zebrafish Dravet syndrome model [131]. In this study, identifying drugs with complementary effects on activity facilitated selection of combination treatments most effective at reversing seizures. However, while whole-brain calcium imaging is a powerful way to assess brain function in mutant animals, the instrumentation required is challenging to build. Simpler alternatives are to assess records of past activity in neurons in the form of phosphoylated-ERK, or expression of the cfos (fosab) gene, which can be visualized throughout the brain using immunohistochemistry or in situ hybridization respectively [2, 89]. Using the phospho-ERK mapping method, Kozol et al detected localized changes in brain activity in zebrafish carrying mutations in the autism susceptibility gene SH3 and multiple ankyrin repeat domains 3a (shank3) [132]. A related method that offers greater control over the timing of the ‘snapshot’ of brain activity is to use a genetically encoded reporter CaMPARI, that permanently switches from green to red fluorescent only in the presence of both high concentrations of calcium (ie, while neurons are firing) and the presence of ultraviolet light [133]. Pan-neuronal CaMPARI imaging would enable relatively simple comparisons of brain-wide activity patterns in zebrafish disease models across a wide range of behavioral assays.
A second promising approach using zebrafish will be to combine genetic and environmental manipulations. There have been persistent indications for a two-hit model for brain disorders like autism and schizophrenia that have neurodevelopmental origins. Here, the notion is genetic susceptibility, coupled with an acute environmental insult, act together to subtly destabilize brain development, resulting in post-natal risk for the disorder. Prenatal infection, especially in association with maternal fever, has been repeatedly linked to increased risk for autism and developmental delay [134]. Likewise, pre- and peri-natal complications have been linked to schizophrenia risk, including maternal malnutrition [135], infection (reviewed in [136]) and childbirth difficulties (reviewed in [137]). Because zebrafish embryos develop externally, environmental manipulations (including infection, temperature, microbiome and even nutritional availability after depletion of the yolk) are relatively easy to perform compared to other models. Mapping potentially synergistic effects of environmental and genetic manipulations on disease-relevant phenotypic traits may offer important insights into the etiology of common brain disorders.
Finally, the availability of rapid and facile methods for reverse genetics in zebrafish, particularly CRISPants and stable CRISPR-induced alleles opens the door to several possibilities concerning how to move from genetic signals in genome-wide association studies (GWAS) to understanding the functions of relevant genes in disease pathophysiology. We anticipate that zebrafish models may allow interrogation of candidate genetic contributors to pathology against disease-relevant phenotypes, either by modulating gene expression, or by directly introducing risk-associated gene variants into homologous loci in zebrafish models. The high-throughput and scalable nature of the zebrafish model may also allow combinations of multiple interacting variants to mimic the genetic landscape associated with pathogenesis, while employing phenotypic assays that are sensitive to cell non-autonomous mechanisms or processes specific to disease-susceptible neuronal groups in vivo. It remains to be seen whether genetic homology and cellular function are sufficiently conserved between zebrafish and human to allow quantitative changes in gene expression or function to influence pathophysiology, but this approach is potentially exciting as it may help address the challenges inherent in moving from small quantitative risk signals at the genome level to identifying targetable nodes and pathogenic cascades.
It seems likely that zebrafish will remain a popular model to investigate disease mechanisms in human brain disorders and to screen for modifiers that provide a starting point for novel mechanistic insights and new therapies. We share this enthusiasm—the striking phylogenetic conservation of genetics and CNS structure with respect to humans, coupled with the sophisticated and automated approaches available for the genetic modification and phenotypic analysis of zebrafish is potentially powerful. However, in order to exploit these models for maximum impact on human disease, it is critical to acknowledge some basic biological differences between zebrafish and humans. We not only advocate strongly for the further development and deployment of zebrafish models but also encourage recognition of the limitations of the system, and care in the interpretation of how data from zebrafish models might apply to human diseases.
Supplementary Material
Acknowledgments
This article does not represent the views of the United States government.
Funding
Dr. Burgess was supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute for Child Health and Human Development (NICHD). Dr. Burton was supported by research grants from NINDS (NS123211, NS125280, NS080881), NIEHS (ES025606, ES022644), The United States Department of Veterans Affairs (BX003168), CurePSP (655-2018-06, 468-08), Pittsburgh Foundation (AD2015-77642), and the University of Pittsburgh (Endowed Chair).
Supplementary Material
Supplementary data is available at Oxford Open Neuroscience online.
Contributor Information
Edward A Burton, Pittsburgh Institute of Neurodegenerative Diseases, University of Pittsburgh, Pittsburgh, PA 15260, USA; Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15260, USA; Geriatric Research, Education, and Clinical Center, Pittsburgh VA Healthcare System, Pittsburgh, PA 15240, USA.
Harold A Burgess, Division of Developmental Biology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD 20892, USA.
Author contributions
E.A.B. and H.A.B. co-wrote and edited the manuscript.
Conflict of Interest
None declared.
Data availability
The data underlying this article will be shared on reasonable request to the corresponding author.
References
- 1.Burgess HA, Burton EA.. A critical review of zebrafish neurological disease models - 1, The Premise: Neuroanatomical, Cellular and Genetic Homology and Experimental Tractability. Oxford Open Neuroscience. 2023. 10.1093/oons/kvac018 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Baraban SC, Taylor MR, Castro PA, Baier H. Pentylenetetrazole induced changes in zebrafish behavior, neural activity and c-fos expression. Neuroscience. 2005;131:759–68 [DOI] [PubMed] [Google Scholar]
- 3.Baraban SC, Dinday MT, Hortopan GA. Drug screening in Scn1a zebrafish mutant identifies clemizole as a potential Dravet syndrome treatment. Nat Commun. 2013;4:2410. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Leboyer M, Bellivier F, Nosten-Bertrand Met al. Psychiatric genetics: search for phenotypes. Trends Neurosci. 1998;21:102–5 [DOI] [PubMed] [Google Scholar]
- 5.Owen MJ, Craddock N, O’Donovan MC. Schizophrenia: genes at last? Trends Genet. 2005;21:518–25 [DOI] [PubMed] [Google Scholar]
- 6.Granato M, van Eeden FJ, Schach Uet al. Genes controlling and mediating locomotion behavior of the zebrafish embryo and larva. Development. 1996;123:399–413 [DOI] [PubMed] [Google Scholar]
- 7.Grunwald D, Kimmel C, Westerfield Met al. A neural degeneration mutation that spares primary neurons in the zebrafish. Dev Biol. 1988;126:115–28 [DOI] [PubMed] [Google Scholar]
- 8.Hirata H, Watanabe T, Hatakeyama Jet al. Zebrafish relatively relaxed mutants have a ryanodine receptor defect, show slow swimming and provide a model of multi-minicore disease. Development. 2007;134:2771–81 [DOI] [PubMed] [Google Scholar]
- 9.Hossainian D, Shao E, Jiao Bet al. Quantification of functional recovery in a larval zebrafish model of spinal cord injury. J Neurosci Res. 2022;100:2044–54. 10.1002/jnr.25118 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Bae YK, Kani S, Shimizu Tet al. Anatomy of zebrafish cerebellum and screen for mutations affecting its development. Dev Biol. 2009;330:406–26 [DOI] [PubMed] [Google Scholar]
- 11.Chang W, Pedroni A, Köster RWet al. Purkinje cells located in the adult zebrafish valvula cerebelli exhibit variable functional responses. Sci Rep. 2021;11:18408. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Chang W, Pedroni A, Hohendorf Vet al. Functionally distinct Purkinje cell types show temporal precision in encoding locomotion. Proc Natl Acad Sci U S A. 2020;117:17330–7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Ehrlich DE, Schoppik D. A primal role for the vestibular sense in the development of coordinated locomotion. elife. 2019;8:e45839 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Elsaey MA, Namikawa K, Köster RW. Genetic modeling of the neurodegenerative disease spinocerebellar ataxia type 1 in zebrafish. Int J Mol Sci. 2021;22:7351. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Markov DA, Petrucco L, Kist AM, Portugues R. A cerebellar internal model calibrates a feedback controller involved in sensorimotor control. Nat Commun. 2021;12:6694. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Martin TA, Keating JG, Goodkin HPet al. Throwing while looking through prisms: I. focal olivocerebellar lesions impair adaptation. Brain. 1996;119:1183–98 [DOI] [PubMed] [Google Scholar]
- 17.Schoppik D, Bianco IH, Prober DAet al. Gaze-stabilizing central vestibular neurons project asymmetrically to extraocular Motoneuron pools. J Neurosci. 2017;37:11353–65 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Farrell TC, Cario CL, Milanese Cet al. Evaluation of spontaneous propulsive movement as a screening tool to detect rescue of parkinsonism phenotypes in zebrafish models. Neurobiol Dis. 2011;44:9–18 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Godoy R, Noble S, Yoon Ket al. Chemogenetic ablation of dopaminergic neurons leads to transient locomotor impairments in zebrafish larvae. J Neurochem. 2015;135:249–60 [DOI] [PubMed] [Google Scholar]
- 20.Irons TD, Kelly PE, Hunter DLet al. Acute administration of dopaminergic drugs has differential effects on locomotion in larval zebrafish. Pharmacol Biochem Behav. 2013;103:792–813 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Pan M-K, Ni C-L, Wu Y-Cet al. Animal models of tremor: relevance to human tremor disorders. Tremor and Other Hyperkinetic Movements. 2018;8:587. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Sharma SC, Berthoud VM, Breckwoldt R. Distribution of substance P-like immunoreactivity in the goldfish brain. J Comp Neurol. 1989;279:104–16 [DOI] [PubMed] [Google Scholar]
- 23.Reiner A, Northcutt RG. An immunohistochemical study of the telencephalon of the Senegal bichir (Polypterus senegalus). J Comp Neurol. 1992;319:359–86 [DOI] [PubMed] [Google Scholar]
- 24.Boehmler W, Obrecht-Pflumio S, Canfield Vet al. Evolution and expression of D2 and D3 dopamine receptor genes in zebrafish. Dev Dyn. 2004;230:481–93 [DOI] [PubMed] [Google Scholar]
- 25.Kapsimali M, Vidal B, Gonzalez Aet al. Distribution of the mRNA encoding the four dopamine D(1) receptor subtypes in the brain of the european eel (Anguilla anguilla): comparative approach to the function of D(1) receptors in vertebrates. J Comp Neurol. 2000;419:320–43 [DOI] [PubMed] [Google Scholar]
- 26.Yan S, Tu Z, Liu Zet al. A huntingtin Knockin pig model recapitulates features of selective neurodegeneration in Huntington’s disease. Cell. 2018;173:989, 1002.e13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Veldman MB, Rios-Galdamez Y, Lu X-Het al. The N17 domain mitigates nuclear toxicity in a novel zebrafish Huntington’s disease model. Mol Neurodegener. 2015;10:67. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Hor H, Francescatto L, Bartesaghi Let al. Missense mutations in TENM4, a regulator of axon guidance and central myelination, cause essential tremor. Hum Mol Genet. 2015;24:5677–86 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Bartelmez GW. Mauthner’s cell and the nucleus motorius tegmenti. J Comp Neurol. 1915;25:87–128 [Google Scholar]
- 30.Di Bonito M, Studer M, Puelles L. Nuclear derivatives and axonal projections originating from rhombomere 4 in the mouse hindbrain. Brain Struct Funct. 2017;222:3509–42 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Rees MI, Lewis TM, Kwok JBJet al. Hyperekplexia associated with compound heterozygote mutations in the beta-subunit of the human inhibitory glycine receptor (GLRB). Hum Mol Genet. 2002;11:853–60 [DOI] [PubMed] [Google Scholar]
- 32.Hirata H, Saint-Amant L, Downes GBet al. Zebrafish bandoneon mutants display behavioral defects due to a mutation in the glycine receptor beta-subunit. Proc Natl Acad Sci U S A. 2005;102:8345–50 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Braff D, Stone C, Callaway Eet al. Prestimulus effects on human startle reflex in normals and schizophrenics. Psychophysiology. 1978;15:339–43 [DOI] [PubMed] [Google Scholar]
- 34.Duncan GE, Moy SS, Perez Aet al. Deficits in sensorimotor gating and tests of social behavior in a genetic model of reduced NMDA receptor function. Behav Brain Res. 2004;153:507–19 [DOI] [PubMed] [Google Scholar]
- 35.Javitt DC, Zukin SR. Recent advances in the phencyclidine model of schizophrenia. Am J Psychiatry. 1991;148:1301–8 [DOI] [PubMed] [Google Scholar]
- 36.Mansbach R, Geyer M. Effects of phencyclidine and phencyclidine biologs on sensorimotor gating in the rat. Neuropsychopharmacology. 1989;2:299–308 [DOI] [PubMed] [Google Scholar]
- 37.Burgess HA, Granato M. Sensorimotor gating in larval zebrafish. J Neurosci. 2007;27:4984–94 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Bergeron SA, Carrier N, Li GHet al. Gsx1 expression defines neurons required for Prepulse inhibition. Mol Psychiatry. 2014;20:974–85. 10.1038/mp.2014.106 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Zoodsma JD, Chan K, Bhandiwad AAet al. A model to study NMDA receptors in Early nervous system development. J Neurosci. 2020;40:3631–45 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Tabor KM, Smith TS, Brown Met al. Presynaptic inhibition selectively gates auditory transmission to the brainstem startle circuit. Curr Biol. 2018;28:2527–2535.e8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Blundell J, Kaeser PS, Sudhof TC, Powell CM. RIM1alpha and interacting proteins involved in presynaptic plasticity mediate prepulse inhibition and additional behaviors linked to schizophrenia. J Neurosci. 2010;30:5326–33 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Scheetz SD, Shao E, Zhou Yet al. An open-source method to analyze optokinetic reflex responses in larval zebrafish. J Neurosci Methods. 2018;293:329–37 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Clark DT Visual Responses in Developing Zebrafish (Brachydanio rerio), 1981
- 44.Huang YY, Neuhauss SCF. The optokinetic response in zebrafish and its applications. Front Biosci. 2008;13:1899–916 [DOI] [PubMed] [Google Scholar]
- 45.Rinner O, Rick JM, Neuhauss SC. Contrast sensitivity, spatial and temporal tuning of the larval zebrafish optokinetic response. Invest Ophthalmol Vis Sci. 2005;46:137–42 [DOI] [PubMed] [Google Scholar]
- 46.Dumitrescu AM, Liao X-H, Best TBet al. A novel syndrome combining thyroid and neurological abnormalities is associated with mutations in a monocarboxylate transporter gene. Am J Hum Genet. 2004;74:168–75 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Rozenblat R, Tovin A, Zada Det al. Genetic and neurological deficiencies in the visual system of mct8 mutant zebrafish. Int J Mol Sci. 2022;23:2464. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Brysch C, Leyden C, Arrenberg AB. Functional architecture underlying binocular coordination of eye position and velocity in the larval zebrafish hindbrain. BMC Biol. 2019;17:110. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Dhande OS, Huberman AD. Retinal ganglion cell maps in the brain: implications for visual processing. Curr Opin Neurobiol. 2014;24:133–42 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Howard IP, Ohmi M. The efficiency of the central and peripheral retina in driving human optokinetic nystagmus. Vis Res. 1984;24:969–76 [DOI] [PubMed] [Google Scholar]
- 51.Kramer A, Wu Y, Baier Het al. Neuronal architecture of a visual center that processes optic flow. Neuron. 2019;103:118–132.e7 [DOI] [PubMed] [Google Scholar]
- 52.Jen JC, Chan WM, Bosley TMet al. Mutations in a human ROBO gene disrupt hindbrain axon pathway crossing and morphogenesis. Science (New York NY). 2004;304:1509–13 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Qian H, Zhu Y, Ramsey DJet al. Directional asymmetries in the optokinetic response of larval zebrafish (Danio rerio). Zebrafish. 2005;2:189–96 [DOI] [PubMed] [Google Scholar]
- 54.Burgess HA, Johnson SL, Granato M. Unidirectional startle responses and disrupted left-right co-ordination of motor behaviors in robo3 mutant zebrafish. Genes Brain Behav. 2009;8:500–11 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Gromer D, Kiser DP, Pauli P. Thigmotaxis in a virtual human open field test. Sci Rep. 2021;11:6670. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Creed RP Jr, Miller JR. Interpreting animal wall-following behavior. Experientia. 1990;46:758–61 [Google Scholar]
- 57.Horstick EJ, Bayleyen Y, Sinclair JL, Burgess HA. Search strategy is regulated by somatostatin signaling and deep brain photoreceptors in zebrafish. BMC Biol. 2017;15:4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Alsop D, Vijayan MM. Development of the corticosteroid stress axis and receptor expression in zebrafish. Am J Physiol Regul Integr Comp Physiol. 2008;294:R711–9 [DOI] [PubMed] [Google Scholar]
- 59.Yeh C-M, Glöck M, Ryu S. An optimized whole-body cortisol quantification method for assessing stress levels in larval zebrafish. PLoS One. 2013;8:e79406 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Mann KD, Hoyt C, Feldman Set al. Cardiac response to startle stimuli in larval zebrafish: sympathetic and parasympathetic components. Am J Physiol Regul Integr Comp Physiol. 2010;298:R1288–97 [DOI] [PubMed] [Google Scholar]
- 61.Davis M, Astrachan DI. Conditioned fear and startle magnitude: effects of different footshock or backshock intensities used in training. J Exp Psychol Anim Behav Process. 1978;4:95–103 [DOI] [PubMed] [Google Scholar]
- 62.Anneser L, Gemmer A, Eilers Tet al. The neuropeptide Pth2 modulates social behavior and anxiety in zebrafish. iScience. 2022;25:103868 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63.Engeszer R, Ryan M, Parichy D. Learned social preference in zebrafish. Curr Biol. 2004;14:881–4 [DOI] [PubMed] [Google Scholar]
- 64.Engeszer RE, Da Barbiano LA, Ryan MJet al. Timing and plasticity of shoaling behaviour in the zebrafish. Danio rerio. Anim Behav. 2007;74:1269–75 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65.Mann KD, Turnell ER, Atema J, Gerlach G. Kin recognition in juvenile zebrafish (Danio rerio) based on olfactory cues. Biol Bull. 2003;205:224–5 [DOI] [PubMed] [Google Scholar]
- 66.Braida D, Donzelli A, Martucci Ret al. Neurohypophyseal hormones manipulation modulate social and anxiety-related behavior in zebrafish. Psychopharmacology. 2012;220:319–30 [DOI] [PubMed] [Google Scholar]
- 67.Griffiths SW, Magurran AE. Sex and schooling behaviour in the Trinidadian guppy. Anim Behav. 1998;56:689–93 [DOI] [PubMed] [Google Scholar]
- 68.Fish HGS Behaviour by Day, Night and Twilight. In: Pitcher TJ, (ed.), The Behavior of Teleost Fishes. Baltimore: The Johns Hopkins University Press, 1986, 366–87 [Google Scholar]
- 69.Burgess HA, Granato M. The neurogenetic frontier--lessons from misbehaving zebrafish. Briefings in functional genomics & proteomics. 2008;7:474–82 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 70.Butler MG, Iben JR, Marsden KCet al. SNPfisher: tools for probing genetic variation in laboratory-reared zebrafish. Development. 2015;142:1542–52 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 71.Bergeron SA, Hannan MC, Codore Het al. Brain selective transgene expression in zebrafish using an NRSE derived motif. Front Neural Circuits. 2012;6:110. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 72.Cahill G, Hurd M, Batchelor M. Circadian rhythmicity in the locomotor activity of larval zebrafish. Neuroreport. 1998;9:3445–9 [DOI] [PubMed] [Google Scholar]
- 73.Spence R, Fatema MK, Reichard Met al. The distribution and habitat preferences of the zebrafish in Bangladesh. J Fish Biol. 2006;69:1435–48 [Google Scholar]
- 74.Küster E, Altenburger R. Oxygen decline in biotesting of environmental samples-is there a need for consideration in the acute zebrafish embryo assay? Environ Toxicol. 2008; [DOI] [PubMed] [Google Scholar]
- 75.Marks C, West TN, Bagatto B, Moore FBG. Developmental environment alters conditional aggression in zebrafish. Copeia. 2005;2005:901–8 [Google Scholar]
- 76.Villamizar N, Vera LM, Foulkes NS, Sánchez-Vázquez FJ. Effect of lighting conditions on zebrafish growth and development. Zebrafish. 2014;11:173–81 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 77.Villamizar N, Blanco-Vives B, Oliveira Cet al. Circadian rhythms of embryonic development and hatching in fish: a comparative study of zebrafish (diurnal), Senegalese sole (nocturnal), and Somalian cavefish (blind). Chronobiol Int. 2013;30:889–900 [DOI] [PubMed] [Google Scholar]
- 78.Schirone RC, Gross L. Effect of temperature on early embryological development of the zebra fish. Brachydanio rerio. J Exp Zool. 1968;169:43–52 [Google Scholar]
- 79.Eaton RC, Farley RD. Growth and the reduction of depensation of zebrafish, Brachydanio rerio, reared in the laboratory. Copeia. 1974;1974:204–9 [Google Scholar]
- 80.Siccardi AJ, Garris HW, Jones WTet al. Growth and survival of zebrafish (Danio rerio) fed different commercial and laboratory diets. Zebrafish. 2009;6:275–80 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 81.Hernandez RE, Galitan L, Cameron Jet al. Delay of initial feeding of zebrafish larvae until 8 days Postfertilization has no impact on survival or growth through the juvenile stage. Zebrafish. 2018;15:515–8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 82.Anneser L, Alcantara IC, Gemmer Aet al. The neuropeptide Pth2 dynamically senses others via mechanosensation. Nature. 2020;588:653–7 [DOI] [PubMed] [Google Scholar]
- 83.Groneberg AH, Marques JC, Martins ALet al. Early-life social experience shapes social avoidance reactions in larval zebrafish. Curr Biol. 2020;30:4009–4021.e4 [DOI] [PubMed] [Google Scholar]
- 84.Gerlach G, Hodgins-Davis A, Avolio C, Schunter C. Kin recognition in zebrafish: a 24-hour window for olfactory imprinting. Proc Biol Sci. 2008;275:2165–70 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 85.Brockerhoff SE, Hurley JB, Janssen-Bienhold Uet al. A behavioral screen for isolating zebrafish mutants with visual system defects. Proc Natl Acad Sci U S A. 1995;92:10545–9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 86.Bingham S, Nasevicius A, Ekker SC, Chandrasekhar A. Sonic hedgehog and tiggy-winkle hedgehog cooperatively induce zebrafish branchiomotor neurons. Genesis. 2001;30:170–4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 87.Whitwell JL. Voxel-based morphometry: an automated technique for assessing structural changes in the brain. J Neurosci. 2009;29:9661–4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 88.Marquart GD, Tabor KM, Brown Met al. A 3D searchable database of transgenic zebrafish Gal4 and Cre lines for functional neuroanatomy studies. Front Neural Circuits. 2015;9:78. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 89.Randlett O, Wee CL, Naumann EAet al. Whole-brain activity mapping onto a zebrafish brain atlas. Nat Methods. 2015;12:1039–46 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 90.Marquart GD, Tabor KM, Horstick EJet al. High precision registration between zebrafish brain atlases using symmetric diffeomorphic normalization. Gigascience. 2017;6:1–15. 10.1093/gigascience/gix056 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 91.Gupta T, Marquart GD, Horstick EJet al. Morphometric analysis and neuroanatomical mapping of the zebrafish brain. Methods. 2018;150:49–62 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 92.Heffer A, Marquart GD, Aquilina-Beck Aet al. Generation and characterization of Kctd15 mutations in zebrafish. PLoS One. 2017;12:e0189162 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 93.Trivellin G, Tirosh A, Hernández-Ramírez LCet al. The X-linked acrogigantism-associated gene gpr101 is a regulator of early embryonic development and growth in zebrafish. Mol Cell Endocrinol. 2021;520:111091 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 94.Kenney JW, Steadman PE, Young Oet al. A 3D adult zebrafish brain atlas (AZBA) for the digital age. elife. 2021;10:e69988 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 95.Kunst M, Laurell E, Mokayes Net al. A cellular-resolution atlas of the larval zebrafish brain. Neuron. 2019;103:21–38.e5 [DOI] [PubMed] [Google Scholar]
- 96.Ronneberger O, Liu K, Rath Met al. ViBE-Z: a framework for 3D virtual colocalization analysis in zebrafish larval brains. Nat Methods. 2012;9:735–42 [DOI] [PubMed] [Google Scholar]
- 97.Tabor KM, Marquart GD, Hurt Cet al. Brain-wide cellular resolution imaging of Cre transgenic zebrafish lines for functional circuit-mapping. elife. 2019;8. 10.7554/eLife.42687 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 98.Bernier R, Golzio C, Xiong Bet al. Disruptive CHD8 mutations define a subtype of autism early in development. Cell. 2014;158:263–76 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 99.Accogli A, Geraldo AF, Piccolo Get al. Diagnostic approach to macrocephaly in children. Front Pediatr. 2021;9:794069 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 100.Wang X, Kopinke D, Lin Jet al. Wnt signaling regulates postembryonic hypothalamic progenitor differentiation. Dev Cell. 2012;23:624–36 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 101.Fitzgerald TW, Gerety SS, Jones WDet al. Large-scale discovery of novel genetic causes of developmental disorders. Nature. 2015;519:223–8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 102.Allalou A, Wu Y, Ghannad-Rezaie Met al. Automated deep-phenotyping of the vertebrate brain. elife. 2017;6. 10.7554/eLife.23379 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 103.Chang T-Y, Pardo-Martin C, Allalou Aet al. Fully automated cellular-resolution vertebrate screening platform with parallel animal processing. Lab Chip. 2012;12:711–6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 104.Early JJ, Marshall-Phelps KL, Williamson JMet al. An automated high-resolution in vivo screen in zebrafish to identify chemical regulators of myelination. In: Whitfield TT, (ed.), elife, Vol. 7, 2018, e35136 [DOI] [PMC free article] [PubMed]
- 105.Rath M, Nitschke R, Filippi Aet al. Generation of high quality multi-view confocal 3D datasets of zebrafish larval brains suitable for analysis using Virtual Brain Explorer (ViBE-Z) software, 2012
- 106.Burns JG, Saravanan A, Helen RF. Rearing environment affects the brain size of guppies: lab-reared guppies have smaller brains than wild-caught guppies. Ethology. 2009;115:122–33 [Google Scholar]
- 107.Hecht EE, Kukekova AV, Gutman DAet al. Neuromorphological changes following selection for tameness and aggression in the Russian fox-farm experiment. J Neurosci. 2021;JN-RM-3114-20. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 108.Ben Fredj N, Hammond S, Otsuna Het al. Synaptic activity and activity-dependent competition regulates axon arbor maturation, growth arrest, and territory in the retinotectal projection. J Neurosci. 2010;30:10939–51 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 109.Hall ZJ, Tropepe V. Movement maintains forebrain neurogenesis via peripheral neural feedback in larval zebrafish. elife. 2018;7:e31045 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 110.Liu NA, Liu Q, Wawrowsky Ket al. Prolactin receptor signaling mediates the osmotic response of embryonic zebrafish lactotrophs. Molecular endocrinology (Baltimore, MD). 2006;20:871–80 [DOI] [PubMed] [Google Scholar]
- 111.Swinney DC, Anthony J. How were new medicines discovered? Nat Rev Drug Discov. 2011;10:507–19 [DOI] [PubMed] [Google Scholar]
- 112.Berghmans S, Butler P, Goldsmith Pet al. Zebrafish based assays for the assessment of cardiac, visual and gut function--potential safety screens for early drug discovery. J Pharmacol Toxicol Methods. 2008;58:59–68 [DOI] [PubMed] [Google Scholar]
- 113.Guo Y, Veneman WJ, Spaink HP, Verbeek FJ. Three-dimensional reconstruction and measurements of zebrafish larvae from high-throughput axial-view in vivo imaging. Biomed Opt Express. 2017;8:2611–34 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 114.Jeong J-Y, Kwon H-B, Ahn J-Cet al. Functional and developmental analysis of the blood-brain barrier in zebrafish. Brain Res Bull. 2008;75:619–28 [DOI] [PubMed] [Google Scholar]
- 115.Quiñonez-Silvero C, Hübner K, Herzog W. Development of the brain vasculature and the blood-brain barrier in zebrafish. Dev Biol. 2020;457:181–90 [DOI] [PubMed] [Google Scholar]
- 116.Fleming A, Diekmann H, Goldsmith P. Functional characterisation of the maturation of the blood-brain barrier in larval zebrafish. PLoS One. 2013;8:e77548 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 117.Bretaud S, Li Q, Lockwood BLet al. A choice behavior for morphine reveals experience-dependent drug preference and underlying neural substrates in developing larval zebrafish. Neuroscience. 2007;146:1109–16 [DOI] [PubMed] [Google Scholar]
- 118.Kim SS, Im SH, Yang JYet al. Zebrafish as a screening model for testing the permeability of blood–brain barrier to small molecules. Zebrafish. 2017;14:322–30 [DOI] [PubMed] [Google Scholar]
- 119.Driever W, Solnica-Krezel L, Schier AFet al. A genetic screen for mutations affecting embryogenesis in zebrafish. Development. 1996;123:37–46 [DOI] [PubMed] [Google Scholar]
- 120.Haffter P, Granato M, Brand Met al. The identification of genes with unique and essential functions in the development of the zebrafish. Danio rerio. Development. 1996;123:1–36 [DOI] [PubMed] [Google Scholar]
- 121.Vogt A, Codore H, Day BWet al. Development of automated imaging and analysis for zebrafish chemical screens. J Vis Exp. 2010;1900: [DOI] [PMC free article] [PubMed] [Google Scholar]
- 122.Zhang JH, Chung TD, Oldenburg KR. A simple statistical parameter for use in evaluation and validation of high throughput screening assays. J Biomol Screen. 1999;4:67–73 [DOI] [PubMed] [Google Scholar]
- 123.Zhang XD. A pair of new statistical parameters for quality control in RNA interference high-throughput screening assays. Genomics. 2007;89:552–61 [DOI] [PubMed] [Google Scholar]
- 124.Dinday MT, Baraban SC. Large-scale phenotype-based antiepileptic drug screening in a zebrafish model of Dravet syndrome. eNeuro. 2015;2:ENEURO.0068–15.2015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 125.Griffin A, Hamling KR, Knupp Ket al. Clemizole and modulators of serotonin signalling suppress seizures in Dravet syndrome. Brain. 2017;140:669–83 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 126.Bossé GD, Peterson RT. Development of an opioid self-administration assay to study drug seeking in zebrafish. Behav Brain Res. 2017;335:158–66 [DOI] [PubMed] [Google Scholar]
- 127.Bosse GD, Cadeddu R, Floris Get al. The 5α-reductase inhibitor finasteride reduces opioid self-administration in animal models of opioid use disorder. J Clin Invest. 2021;131:143990 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 128.Darland T, Dowling JE. Behavioral screening for cocaine sensitivity in mutagenized zebrafish. Proc Natl Acad Sci U S A. 2001;98:11691–6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 129.Cassar S, Dunn C, Olson Aet al. From the cover: inhibitors of nicotinamide Phosphoribosyltransferase cause retinal damage in larval zebrafish. Toxicol Sci. 2018;161:300–9 [DOI] [PubMed] [Google Scholar]
- 130.Ponce-Alvarez A, Jouary A, Privat Met al. Whole-brain neuronal activity displays crackling noise dynamics. Neuron. 2018;100:1446–1459.e6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 131.Ghannad-Rezaie M, Eimon PM, Wu Y, Yanik MF. Engineering brain activity patterns by neuromodulator polytherapy for treatment of disorders. Nat Commun. 2019;10:2620. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 132.Kozol RA, James DM, Varela Iet al. Restoring Shank3 in the rostral brainstem of shank3ab−/− zebrafish autism models rescues sensory deficits. Commun Biol. 2021;4:1411. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 133.Moeyaert B, Holt G, Madangopal Ret al. Improved methods for marking active neuron populations. Nat Commun. 2018;9:4440. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 134.Zerbo O, Iosif A-M, Walker Cet al. Is maternal influenza or fever during pregnancy associated with autism or developmental delays? Results from the CHARGE (CHildhood autism risks from genetics and environment) study. J Autism Dev Disord. 2013;43:25–33 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 135.Susser E, Neugebauer R, Hoek HWet al. Schizophrenia after prenatal famine. Further evidence. Arch Gen Psychiatry. 1996;53:25–31 [DOI] [PubMed] [Google Scholar]
- 136.Brown AS. Epidemiologic studies of exposure to prenatal infection and risk of schizophrenia and autism. Developmental Neurobiology. 2012;72:1272–6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 137.Lewis DA, Levitt P. Schizophrenia as a disorder of neurodevelopment. Annu Rev Neurosci. 2002;25:409–32 [DOI] [PubMed] [Google Scholar]
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Data Availability Statement
The data underlying this article will be shared on reasonable request to the corresponding author.