Loss-of-Function Models of the Metabotropic Glutamate Receptor Genes Grm8a and Grm8b Display Distinct Behavioral Phenotypes in Zebrafish Larvae (Danio rerio).

Members of the family of metabotropic glutamate receptors are involved in the pathomechanism of several disorders of the nervous system. Besides the well-investigated function of dysfunctional glutamate receptor signaling in neurodegenerative diseases, neurodevelopmental disorders (NDD), like autism spectrum disorders (ASD) and attention-deficit and hyperactivity disorder (ADHD) might also be partly caused by disturbed glutamate signaling during development. However, the underlying mechanism of the type III metabotropic glutamate receptor 8 (mGluR8 or GRM8) involvement in neurodevelopment and disease mechanism is largely unknown. Here we show that the expression pattern of the two orthologs of human GRM8, grm8a and grm8b, have evolved partially distinct expression patterns in the brain of zebrafish (Danio rerio), especially at adult stages, suggesting sub-functionalization of these two genes during evolution. Using double in situ hybridization staining in the developing brain we demonstrate that grm8a is expressed in a subset of gad1a-positive cells, pointing towards glutamatergic modulation of GABAergic signaling. Building on this result we generated loss-of-function models of both genes using CRISPR/Cas9. Both mutant lines are viable and display no obvious gross morphological phenotypes making them suitable for further analysis. Initial behavioral characterization revealed distinct phenotypes in larvae. Whereas grm8a mutant animals display reduced swimming velocity, grm8b mutant animals show increased thigmotaxis behavior, suggesting an anxiety-like phenotype. We anticipate that our two novel metabotropic glutamate receptor 8 zebrafish models may contribute to a deeper understanding of its function in normal development and its role in the pathomechanism of disorders of the central nervous system.

Increased locomotor activity via regulation of GABAergic signalling in foxp2 mutant zebrafish-implications for neurodevelopmental disorders.

Recent advances in the genetics of neurodevelopmental disorders (NDDs) have identified the transcription factor FOXP2 as one of numerous risk genes, e.g. in autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). FOXP2 function is suggested to be involved in GABAergic signalling and numerous studies demonstrate that GABAergic function is altered in NDDs, thus disrupting the excitation/inhibition balance. Interestingly, GABAergic signalling components, including glutamate-decarboxylase 1 (Gad1) and GABA receptors, are putative transcriptional targets of FOXP2. However, the specific role of FOXP2 in the pathomechanism of NDDs remains elusive. Here we test the hypothesis that Foxp2 affects behavioural dimensions via GABAergic signalling using zebrafish as model organism. We demonstrate that foxp2 is expressed by a subset of GABAergic neurons located in brain regions involved in motor functions, including the subpallium, posterior tuberculum, thalamus and medulla oblongata. Using CRISPR/Cas9 gene-editing we generated a novel foxp2 zebrafish loss-of-function mutant that exhibits increased locomotor activity. Further, genetic and/or pharmacological disruption of Gad1 or GABA-A receptors causes increased locomotor activity, resembling the phenotype of foxp2 mutants. Application of muscimol, a GABA-A receptor agonist, rescues the hyperactive phenotype induced by the foxp2 loss-of-function. By reverse translation of the therapeutic effect on hyperactive behaviour exerted by methylphenidate, we note that application of methylphenidate evokes different responses in wildtype compared to foxp2 or gad1b loss-of-function animals. Together, our findings support the hypothesis that foxp2 regulates locomotor activity via GABAergic signalling. This provides one targetable mechanism, which may contribute to behavioural phenotypes commonly observed in NDDs.

On the objectivity, reliability, and validity of deep learning enabled bioimage analyses.

Bioimage analysis of fluorescent labels is widely used in the life sciences. Recent advances in deep learning (DL) allow automating time-consuming manual image analysis processes based on annotated training data. However, manual annotation of fluorescent features with a low signal-to-noise ratio is somewhat subjective. Training DL models on subjective annotations may be instable or yield biased models. In turn, these models may be unable to reliably detect biological effects. An analysis pipeline integrating data annotation, ground truth estimation, and model training can mitigate this risk. To evaluate this integrated process, we compared different DL-based analysis approaches. With data from two model organisms (mice, zebrafish) and five laboratories, we show that ground truth estimation from multiple human annotators helps to establish objectivity in fluorescent feature annotations. Furthermore, ensembles of multiple models trained on the estimated ground truth establish reliability and validity. Our research provides guidelines for reproducible DL-based bioimage analyses.

Research in biology generates many image datasets, mostly from microscopy. These images have to be analyzed, and much of this analysis relies on a human expert looking at the images and manually annotating features. Image datasets are often large, and human annotation can be subjective, so automating image analysis is highly desirable. This is where machine learning algorithms, such as deep learning, have proven to be useful. In order for deep learning algorithms to work first they have to be 'trained'. Deep learning algorithms are trained by being given a training dataset that has been annotated by human experts. The algorithms extract the relevant features to look out for from this training dataset and can then look for these features in other image data. However, it is also worth noting that because these models try to mimic the annotation behavior presented to them during training as well as possible, they can sometimes also mimic an expert's subjectivity when annotating data. Segebarth, Griebel et al. asked whether this was the case, whether it had an impact on the outcome of the image data analysis, and whether it was possible to avoid this problem when using deep learning for imaging dataset analysis. For this research, Segebarth, Griebel et al. used microscopy images of mouse brain sections, where a protein called cFOS had been labeled with a fluorescent tag. This protein typically controls the rate at which DNA information is copied into RNA, leading to the production of proteins. Its activity can be influenced experimentally by testing the behaviors of mice. Thus, this experimental manipulation can be used to evaluate the results of deep learning-based image analyses. First, the fluorescent images were interpreted manually by a group of human experts. Then, their results were used to train a large variety of deep learning models. Models were trained either on the results of an individual expert or on the results pooled from all experts to come up with a consensus model, a deep learning model that learned from the personal annotation preferences of all experts. This made it possible to test whether training a model on multiple experts reduces the risk of subjectivity. As the training of deep learning models is random, Segebarth, Griebel et al. also tested whether combining the predictions from multiple models in a so-called model ensemble improves the consistency of the analyses. For evaluation, the annotations of the deep learning models were compared to those of the human experts, to ensure that the results were not influenced by the subjective behavior of one person. The results of all bioimage annotations were finally compared to the experimental results from analyzing the mice's behaviors in order to check whether the models were able to find the behavioral effect on cFOS. Segebarth, Griebel et al. concluded that combining the expert knowledge of multiple experts reduces the subjectivity of bioimage annotation by deep learning algorithms. Combining such consensus information in a group of deep learning models improves the quality of bioimage analysis, so that the results are reliable, transparent and less subjective.

Glycine Receptor Autoantibodies Impair Receptor Function and Induce Motor Dysfunction.

OBJECTIVE: Impairment of glycinergic neurotransmission leads to complex movement and behavioral disorders. Patients harboring glycine receptor autoantibodies suffer from stiff-person syndrome or its severe variant progressive encephalomyelitis with rigidity and myoclonus. Enhanced receptor internalization was proposed as the common molecular mechanism upon autoantibody binding. Although functional impairment of glycine receptors following autoantibody binding has recently been investigated, it is still incompletely understood. METHODS: A cell-based assay was used for positive sample evaluation. Glycine receptor function was assessed by electrophysiological recordings and radioligand binding assays. The in vivo passive transfer of patient autoantibodies was done using the zebrafish animal model. RESULTS: Glycine receptor function as assessed by glycine dose-response curves showed significantly decreased glycine potency in the presence of patient sera. Upon binding of autoantibodies from 2 patients, a decreased fraction of desensitized receptors was observed, whereas closing of the ion channel remained fast. The glycine receptor N-terminal residues 29 A to 62 G were mapped as a common epitope of glycine receptor autoantibodies. An in vivo transfer into the zebrafish animal model generated a phenotype with disturbed escape behavior accompanied by a reduced number of glycine receptor clusters in the spinal cord of affected animals. INTERPRETATION: Autoantibodies against the extracellular domain mediate alterations of glycine receptor physiology. Moreover, our in vivo data demonstrate that the autoantibodies are a direct cause of the disease, because the transfer of human glycine receptor autoantibodies to zebrafish larvae generated impaired escape behavior in the animal model compatible with abnormal startle response in stiff-person syndrome or progressive encephalitis with rigidity and myoclonus patients. ANN NEUROL 2020;88:544-561.

Distribution of transcripts of the GFOD gene family members gfod1 and gfod2 in the zebrafish central nervous system.

The glucose-fructose oxidoreductase domain containing gene family (GFOD) is small and contains only two members in human (GFOD1 and GFOD2). Information about its function is scarce. As the name implies the proteins contain an enzyme-defining domain, however, if this is functional and has enzymatic activity remains to be shown. A single nucleotide polymorphism situated in an intron of GFOD1 was found to be associated with inattentive symptomology in patients with attention-deficit/hyperactivity disorder. Further, in a large schizophrenia genome-wide association study the GFOD2 locus was found to be associated with the psychiatric condition. Until now, however, it is unclear what specific functions are associated with the two GFOD-family members, if they might be involved in neurodevelopment and how this may relate to the development of psychiatric disorders. In order to gain first insights into the hypothesis that GFOD-family members are involved in brain development and/or function we performed RNA in situ hybridization on zebrafish (Danio rerio) tissues at different developmental stages. We found that both family members are expressed in the central nervous system at embryonic, larvae and adult stages. We were able to define subtle differences of expression of the two gfod genes and we showed that a subset of GABAergic neurons express gfod1. Taken together, we conclude that both gfod gene family members are expressed in overlapping as well as in distinct regions in the zebrafish central nervous system. Our data suggest that gfod1 and gfod2 are relevant both for the developing and adult zebrafish brain. This study paves the way for further functional analyses of this yet unexplored gene family.

Transcript Analysis of Zebrafish GLUT3 Genes, slc2a3a and slc2a3b, Define Overlapping as Well as Distinct Expression Domains in the Zebrafish (Danio rerio) Central Nervous System.

The transport of glucose across the cell plasma membrane is vital to most mammalian cells. The glucose transporter (GLUT; also called SLC2A) family of transmembrane solute carriers is responsible for this function in vivo. GLUT proteins encompass 14 different isoforms in humans with different cell type-specific expression patterns and activities. Central to glucose utilization and delivery in the brain is the neuronally expressed GLUT3. Recent research has shown an involvement of GLUT3 genetic variation or altered expression in several different brain disorders, including Huntington's and Alzheimer's diseases. Furthermore, GLUT3 was identified as a potential risk gene for multiple psychiatric disorders. To study the role of GLUT3 in brain function and disease a more detailed knowledge of its expression in model organisms is needed. Zebrafish (Danio rerio) has in recent years gained popularity as a model organism for brain research and is now well-established for modeling psychiatric disorders. Here, we have analyzed the sequence of GLUT3 orthologs and identified two paralogous genes in the zebrafish, slc2a3a and slc2a3b. Interestingly, the Glut3b protein sequence contains a unique stretch of amino acids, which may be important for functional regulation. The slc2a3a transcript is detectable in the central nervous system including distinct cellular populations in telencephalon, diencephalon, mesencephalon and rhombencephalon at embryonic and larval stages. Conversely, the slc2a3b transcript shows a rather diffuse expression pattern at different embryonic stages and brain regions. Expression of slc2a3a is maintained in the adult brain and is found in the telencephalon, diencephalon, mesencephalon, cerebellum and medulla oblongata. The slc2a3b transcripts are present in overlapping as well as distinct regions compared to slc2a3a. Double in situ hybridizations were used to demonstrate that slc2a3a is expressed by some GABAergic neurons at embryonic stages. This detailed description of zebrafish slc2a3a and slc2a3b expression at developmental and adult stages paves the way for further investigations of normal GLUT3 function and its role in brain disorders.

Fgf3 is crucial for the generation of monoaminergic cerebrospinal fluid contacting cells in zebrafish.

In most vertebrates, including zebrafish, the hypothalamic serotonergic cerebrospinal fluid-contacting (CSF-c) cells constitute a prominent population. In contrast to the hindbrain serotonergic neurons, little is known about the development and function of these cells. Here, we identify fibroblast growth factor (Fgf)3 as the main Fgf ligand controlling the ontogeny of serotonergic CSF-c cells. We show that fgf3 positively regulates the number of serotonergic CSF-c cells, as well as a subset of dopaminergic and neuroendocrine cells in the posterior hypothalamus via control of proliferation and cell survival. Further, expression of the ETS-domain transcription factor etv5b is downregulated after fgf3 impairment. Previous findings identified etv5b as critical for the proliferation of serotonergic progenitors in the hypothalamus, and therefore we now suggest that Fgf3 acts via etv5b during early development to ultimately control the number of mature serotonergic CSF-c cells. Moreover, our analysis of the developing hypothalamic transcriptome shows that the expression of fgf3 is upregulated upon fgf3 loss-of-function, suggesting activation of a self-compensatory mechanism. Together, these results highlight Fgf3 in a novel context as part of a signalling pathway of critical importance for hypothalamic development.

A novel evolutionary conserved mechanism of RNA stability regulates synexpression of primordial germ cell-specific genes prior to the sex-determination stage in medaka.

Dmrt1 is a highly conserved transcription factor, which is critically involved in regulation of gonad development of vertebrates. In medaka, a duplicate of dmrt1-acting as master sex-determining gene-has a tightly timely and spatially controlled gonadal expression pattern. In addition to transcriptional regulation, a sequence motif in the 3' UTR (D3U-box) mediates transcript stability of dmrt1 mRNAs from medaka and other vertebrates. We show here that in medaka, two RNA-binding proteins with antagonizing properties target this D3U-box, promoting either RNA stabilization in germ cells or degradation in the soma. The D3U-box is also conserved in other germ-cell transcripts, making them responsive to the same RNA binding proteins. The evolutionary conservation of the D3U-box motif within dmrt1 genes of metazoans-together with preserved expression patterns of the targeting RNA binding proteins in subsets of germ cells-suggest that this new mechanism for controlling RNA stability is not restricted to fishes but might also apply to other vertebrates.

Intraspinal serotonergic signaling suppresses locomotor activity in larval zebrafish.

Serotonin (5HT) is a modulator of many vital processes in the spinal cord (SC), such as production of locomotion. In the larval zebrafish, intraspinal serotonergic neurons (ISNs) are a source of spinal 5HT that, despite the availability of numerous genetic and optical tools, has not yet been directly shown to affect the spinal locomotor network. In order to better understand the functions of ISNs, we used a combination of strategies to investigate ISN development, morphology, and function. ISNs were optically isolated from one another by photoconverting Kaede fluorescent protein in individual cells, permitting morphometric analysis as they developed in vivo. ISN neurite lengths and projection distances exhibited the greatest amount of change between 3 and 4 days post-fertilization (dpf) and appeared to stabilize by 5 dpf. Overall ISN innervation patterns were similar between cells and between SC regions. ISNs possessed rostrally-extending neurites resembling dendrites and a caudally-extending neurite resembling an axon, which terminated with an enlarged growth cone-like structure. Interestingly, these enlargements remained even after neurite extension had ceased. Functionally, application of exogenous 5HT reduced spinally-produced motor nerve bursting. A selective 5HT reuptake inhibitor and ISN activation with channelrhodopsin-2 each produced similar effects to 5HT, indicating that spinally-intrinsic 5HT originating from the ISNs has an inhibitory effect on the spinal locomotor network. Taken together this suggests that the ISNs are morphologically mature by 5 dpf and supports their involvement in modulating the activity of the spinal locomotor network. © 2018 Wiley Periodicals, Inc. Develop Neurobiol, 2018.