Michael B. Orger

Proper regulation of arousal maintains the balance of rest and activity and enables appropriate responses to stimuli; its disruption is a hallmark of many neurodevelopmental disorders. Although transcriptional mechanisms of arousal control are well defined, the contribution of posttranscriptional processes such as alternative splicing remains unclear. Here, we identify a critical role for the microexon splicing regulator srrm3 in maintaining arousal homeostasis in zebrafish. srrm3 mutants exhibit persistent hyperarousal characterized by sleep loss, sensory hypersensitivity, and elevated behavioral and neuronal activity. We identify the cyclic adenosine monophosphate (cAMP)–cAMP-dependent protein kinase (PKA)–cAMP response element–binding protein (CREB) signaling axis as a central driver of mutant hyperarousal. Specifically, pharmacological inhibition of cAMP signaling rescues mutant hyperactivity and associated transcriptional changes whereas wild-type cAMP activation phenocopies the mutant. Down-regulation of immediate early genes and reduced CREB phosphorylation further suggest adaptation to sustained neuronal activation. These findings establish srrm3 -dependent microexon splicing as a key molecular layer of arousal regulation linking RNA-processing defects to neuromodulatory imbalance.

We present Sardine, a software framework built with .NET to control experimental setups through the reliable execution of dynamic networks of independent modules, where each module can interface with a hardware device (e.g., camera, motor) or represent an operation over data (e.g., image filter, data stream). The Sardine framework delivers robust fault-tolerant hardware control and eliminates downstream delays by implementing dedicated data processing queues for each module. Any .NET class can be seamlessly adapted into a Sardine module, enabling effortless integration with existing codebases. Sardine’s modular architecture ensures flexibility to accommodate changes in experimental paradigms, simplifying the adaptation of essential features, such as swapping hardware components or redefining the logic of their interactions. The core of Sardine is a novel aggregation system that connects modules in two layers, designed to streamline complex workflows such as those in microscopy applications. The first layer (link layer) enables concurrent operations between modules, such as synchronizing a camera module with a stage controller or a laser module, while maintaining a dependency tree to ensure devices operate as intended. For example, in an imaging experiment, Sardine oversees individual module malfunctions, such as a camera failure or stage misalignment, gracefully handling errors and dynamically restoring functionality to impacted network segments to minimize disruption. The second layer (data layer) facilitates the transmission of information across modules by associating them with operations that produce, consume, or transform data. In an imaging context, this could involve processing raw image data from a camera module, passing it through a real-time analysis module for feature detection, and forwarding the results to a visualization module for immediate feedback. This two-layer architecture ensures seamless data flow and robust error handling, making Sardine ideal for dynamic and complex experimental setups. Sardine also integrates logging, a metadata collection system, and tools to create graphical applications.

Mitochondria-derived acyl-coenzyme A (acyl-CoA) species chemically modify proteins, causing damage when acylation reactions are not adequately detoxified by enzymatic removal or protein turnover. Defects in genes encoding the mitochondrial respiratory complex and TCA cycle enzymes have been shown to increase acyl-CoA levels due to reduced enzymatic flux and result in proteome-wide hyperacylation. How pathologically elevated acyl-CoA levels contribute to bioenergetics failure in mitochondrial diseases is not well understood. Here, we demonstrate that bulk succinylation from succinyl-CoA excess consumes the enzymatic cofactor NAD ⁺ and propagates mitochondrial respiratory defects in a zebrafish model of succinyl-CoA ligase deficiency, a childhood-onset encephalomyopathy. To explore this mechanism as a therapeutic target, we developed a workflow to monitor behavioral defects in sucla2 ^–/– zebrafish and show that hypersuccinylation is associated with reduced locomotor behavior and impaired ability to execute food hunting patterns. Postembryonic NAD ⁺ precursor supplementation restores NAD ⁺ levels and improves locomotion and survival of sucla2 ^–/– zebrafish. Mechanistically, nicotinamide and nicotinamide riboside require the NAD ⁺ -dependent desuccinylase Sirt5 to enhance oxidative metabolism and nitrogen elimination through the urea cycle. Collectively, NAD ⁺ supplementation activates Sirt5 to protect against damage to mitochondria and locomotor circuits caused by protein succinylation.

Accurate quantification of animal behavior is crucial for advancing neuroscience and for defining reliable physiological markers. We introduce Megabouts (megabouts.ai), a software package standardizing zebrafish larvae locomotion analysis across experimental setups. Its flexibility, achieved with a Transformer neural network, allows the classification of actions regardless of tracking methods or frame rates. We demonstrate Megabouts’ ability to quantify sensorimotor transformations and enhance sensitivity to drug-induced phenotypes through high-throughput, high-resolution behavioral analysis.

We present Sardine, a software framework built with.NET to control experimental setups through the reliable execution of dynamic networks of independent modules, where each module can interface with a hardware device (e.g., camera, motor) or represent an operation over data (e.g., image filter, data stream). The Sardine framework delivers robust fault-tolerant hardware control and eliminates downstream delays by implementing dedicated data processing queues for each module. Any.NET class can be seamlessly adapted into a Sardine module, enabling effortless integration with existing codebases. Sardine’s modular architecture ensures flexibility to accommodate changes in experimental paradigms, simplifying the adaptation of essential features, such as swapping hardware components or redefining the logic of their interactions. The core of Sardine is a novel aggregation system that connects modules in two layers, designed to streamline complex workflows such as those in microscopy applications. The first layer (link layer) enables concurrent operations between modules, such as synchronizing a camera module with a stage controller or a laser module, while maintaining a dependency tree to ensure devices operate as intended. For example, in an imaging experiment, Sardine oversees individual module malfunctions, such as a camera failure or stage misalignment, gracefully handling errors and dynamically restoring functionality to impacted network segments to minimize disruption. The second layer (data layer) facilitates the transmission of information across modules by associating them with operations that produce, consume, or transform data. In an imaging context, this could involve processing raw image data from a camera module, passing it through a real-time analysis module for feature detection, and forwarding the results to a visualization module for immediate feedback. This two-layer architecture ensures seamless data flow and robust error handling, making Sardine ideal for dynamic and complex experimental setups. Sardine also integrates logging, a metadata collection system, and tools to create graphical applications.

From lamprey to monkeys, the organization of the descending control of locomotion is conserved across vertebrates. Reticulospinal neurons (RSNs) form a bottleneck for descending commands, receiving innervation from diencephalic and mesencephalic locomotor centers and providing locomotor drive to spinal motor circuits. Given their optical accessibility in early development, larval zebrafish offer a unique opportunity to study reticulospinal circuitry. In fish, RSNs are few, highly stereotyped, uniquely identifiable, large neurons spanning from the midbrain to the medulla. Classically labeled by tracer dye injections into the spinal cord, recent advances in genetic tools have facilitated the targeted expression of transgenes in diverse brainstem neurons of larval zebrafish. Here, we provide a comparative characterization of four existing and three newly established transgenic lines in larval zebrafish. We determine which identified neurons are consistently labeled and offer projection-specific genetic access to subpopulations of RSNs. We showcase transgenic lines that label most or all RSNs (nefma, adcyap1b^ccu96Et) or subsets of RSNs, including ipsilateral (vsx2, calca^ccu75Et), contralateral (pcp4a^ccu97Tg) or all (tiam2a^y264Et) components of the Mauthner array, or midbrain-only RSNs (s1171tEt). In addition to RSNs, selected transgenic lines (nefma, s1171tEt, calca^ccu75Et) labeled other potential neurons of interest in the brainstem. For those, we performed in situ hybridization to show expression patterns of several excitatory and inhibitory neurotransmitters at larval stages as well as glutamatergic expression patterns in juvenile fish. We provide an overview of transgene expression in the brainstem of larval zebrafish that serves to lay a foundation for future studies in the supraspinal control of locomotion.

From lamprey to monkeys, the organization of the descending control of locomotion is conserved across vertebrates. Reticulospinal neurons ( RSNs ) form a bottleneck for descending commands, receiving innervation from diencephalic and mesencephalic locomotor centres and providing locomotor drive to spinal motor circuits. Given their optical accessibility in early development, larval zebrafish offer a unique opportunity to study reticulospinal circuitry. In fish, RSNs are few, highly stereotyped, uniquely identifiable, large neurons spanning from the midbrain to the medulla. Classically labelled by tracer dye injections into the spinal cord, recent advances in genetic tools have facilitated the targeted expression of transgenes in diverse brainstem neurons of larval zebrafish. Here, we provide a comparative characterization of four existing and three newly established transgenic lines in larval zebrafish. We determine which identified neurons are consistently labelled and offer projection-specific genetic access to subpopulations of RSNs. We showcase transgenic lines that label most or all RSNs ( nefma, adcyap1b ^ccu96Et ) or subsets of RSNs, including ipsilateral ( vsx2, calca ^ccu75Et ), contralateral ( pcp4a ^ccu97Tg ) or all ( tiam2a ^y264Et ) components of the Mauthner array, or midbrain-only RSNs ( s1171tEt ). In addition to RSNs, selected transgenic lines (nefma, s1171tEt, calca ^ccu75Et ) labelled other potential neurons of interest in the brainstem. For those, we performed in situ hybridisation to show expression patterns of several excitatory and inhibitory neurotransmitters at larval stages as well as glutamatergic expression patterns in juvenile fish. We provide an overview of transgene expression in the brainstem of larval zebrafish that serves to lay a foundation for future studies in the supraspinal control of locomotion. Significance Statement: Genetic access to subpopulations of brainstem neurons greatly facilitates the dissection of supraspinal circuitry and function. Here, we present several new transgenic lines and rigorously describe existing ones, all in terms of their degree of overlap with the reticulospinal system, variability in transgenic labelling and neurotransmitter identity. Having transgenic access to different subpopulations of reticulospinal neurons enables targeted functional calcium imaging, anatomical tracing and optogenetic manipulations to decipher the role of individual reticulospinal neurons in movement production, ultimately clarifying existing understanding and facilitating future studies in the supraspinal control of locomotion. Abstract Figure:

Animals chain movements into long-lived motor strategies, exhibiting variability across scales that reflects the interplay between internal states and environmental cues. To reveal structure in such variability, we build Markov models of movement sequences that bridge across timescales and enable a quantitative comparison of behavioral phenotypes among individuals. Applied to larval zebrafish responding to diverse sensory cues, we uncover a hierarchy of long-lived motor strategies, dominated by changes in orientation distinguishing cruising versus wandering strategies. Environmental cues induce preferences along these modes at the population level: while fish cruise in the light, they wander in response to aversive stimuli, or in search for appetitive prey. As our method encodes the behavioral dynamics of each individual fish in the transitions among coarse-grained motor strategies, we use it to uncover a hierarchical structure in the phenotypic variability that reflects exploration–exploitation trade-offs. Across a wide range of sensory cues, a major source of variation among fish is driven by prior and/or immediate exposure to prey that induces exploitation phenotypes. A large degree of variability that is not explained by environmental cues unravels hidden states that override the sensory context to induce contrasting exploration–exploitation phenotypes. Altogether, by extracting the timescales of motor strategies deployed during navigation, our approach exposes structure among individuals and reveals internal states tuned by prior experience.

Accurate quantification of animal behavior is crucial for advancing neuroscience and for defining reliable physiological markers. We introduce Megabouts (megabouts.ai), a software package standardizing zebrafish larvae locomotion analysis across experimental setups. Its flexibility, achieved with a Transformer neural network, allows the classification of actions regardless of tracking methods or frame rates. We demonstrate Megabouts’ ability to quantify sensorimotor transformations and enhance sensitivity to drug-induced phenotypes through high-throughput, high-resolution behavioral analysis.