bioRxiv ScienceSearch

bioRxiv · 10.1101/2020.11.04.367821

High behavioural variability mediated by altered neuronal excitability in auts2 mutant zebrafish

Abstract

Autism spectrum disorders (ASDs) are characterized by abnormal behavioral traits arising from neural circuit dysfunction. While a number of genes have been implicated in ASDs, in most cases, a clear understanding of how mutations in these genes lead to circuit dysfunction and behavioral abnormality is absent. The autism susceptibility candidate 2 (AUTS2) gene is one such gene, associated with ASDs, intellectual disability and a range of other neurodevelopmental conditions. Yet, the function of AUTS2 in neural development and circuit function is not at all known. Here, we undertook functional analysis of Auts2a, the main homolog of AUTS2 in zebrafish, in the context of the escape behavior. Escape behavior in wild type zebrafish is critical for survival and is therefore, reliable, rapid, and has well-defined kinematic properties. Auts2a-/- zebrafish are viable, have normal gross morphology and can generate escape behavior with normal kinematics. However, the behavior is unreliable and delayed, with high trial-to-trial variability in the latency. We demonstrate that this is due to the reduced excitability of Mauthner neurons resulting in unreliable firing with stimuli that normally elicit the escape response. Combined with previous studies that show Auts2-regulation of the transcription of ion channel proteins, our results suggest that Auts2 sets the excitability of neurons by activating a set transcriptional program. Significance statementAUTS2 is one among recently identified autism susceptibility candidate genes, whose function in neuronal circuits is unclear. Using zebrafish as a model organism, we probe the function of Auts2a (homolog of mammalian AUTS2) at the cellular, network and behavioral levels. The escape behavior of Auts2a mutant zebrafish is highly variable with normal short latency escapes, long latency escapes and total failures across trials in the same fish. This occurs because neuronal excitability is inappropriately set in the Mauthner neurons of mutants leading to the large trial-to-trial variability in responses. The behavioral variability is fully explained by variability in firing action potentials in the Mauthner neuron, providing an integrative understanding of how behavioral variability arises from mutations at the genetic level.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Jha, U., Kondrychyn, I., Korzh, V., Thirumalai, V.. 2020-11-04. High behavioural variability mediated by altered neuronal excitability in auts2 mutant zebrafish. https://doi.org/10.1101/2020.11.04.367821

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience