A two-layer neural circuit controls fast forward locomotion in Drosophila.

Fast forward locomotion is critical for animal hunting and escaping behaviors. However, how the underlying neural circuit is wired at synaptic resolution to decide locomotion direction and speed remains poorly understood. Here, we identified in the ventral nerve cord (VNC) a set of ascending cholinergic neurons (AcNs) to be command neurons capable of initiating fast forward peristaltic locomotion in Drosophila larvae. Targeted manipulations revealed that AcNs are necessary and sufficient for fast forward locomotion. AcNs can activate their postsynaptic partners, A01j and A02j; both are interneurons with locomotory rhythmicity. Activated A01j neurons form a posterior-anteriorly descendent gradient in output activity along the VNC to launch forward locomotion from the tail. Activated A02j neurons exhibit quicker intersegmental transmission in activity that enables fast propagation of motor waves. Our work revealed a global neural mechanism that coordinately controls the launch direction and propagation speed of Drosophila locomotion, furthering the understanding of the strategy for locomotion control.

A machine learning based method for tracking of simultaneously imaged neural activity and body posture of freely moving maggot.

To understand neural basis of animal behavior, it is necessary to monitor neural activity and behavior in freely moving animal before building relationship between them. Here we use light sheet fluorescence microscope (LSFM) combined with microfluidic chip to simultaneously capture neural activity and body movement in small freely behaving Drosophila larva. We develop a transfer learning based method to simultaneously track the continuously changing body posture and activity of neurons that move together using a sub-region tracking network with a precise landmark estimation network for the inference of target landmark trajectory. Based on the tracking of each labelled neuron, the activity of the neuron indicated by fluorescent intensity is calculated. For each video, annotation of only 20 frames in a video is sufficient to yield human-level accuracy for all other frames. The validity of this method is further confirmed by reproducing the activity pattern of PMSIs (period-positive median segmental interneurons) and larval movement as previously reported. Using this method, we disclosed the correlation between larval movement and left-right asymmetry in activity of a group of unidentified neurons labelled by R52H01-Gal4 and further confirmed the roles of these neurons in bilateral balance of body contraction during larval crawling by genetic inhibition of these neurons. Our method provides a new tool for accurate extraction of neural activities and movement of freely behaving small-size transparent animals.

The tail segments are required by the performance but not the accomplishment of various modes of Drosophila larval locomotion.

The tail plays important roles in locomotion control in many animals. But in animals with multiple body segments, the roles of the hind body segments and corresponding innervating neurons in locomotion control are not clear. Here, using the Drosophila larva as the model animal, we investigated the roles of the posterior terminal segments in various modes of locomotion and found that they participate in all of them. In forward crawling, paralysis of the larval tail by blocking the Abdb-Gal4 labeled neurons in the posterior segments of VNC led to a slower locomotion speed but did not prevent the initiation of forward peristalsis. In backward crawling, larvae with the Abdb-Gal4 neurons inhibited were unable to generate effective displacement although waves of backward peristalsis could be initiated and persist. In head swing where the movement of the tail is not obvious, disabling the larval tail by blocking Abdb-Gal4 neurons led to increased bending amplitude upon touching the head. In the case of larval lateral rolling, larval tail paralysis by inhibition of Abdb-Gal4 neurons did not prevent the accomplishment of rolling, but resulted in slower rolling speed. Our work reveals that the contribution of Drosophila larval posterior VNC segments and corresponding body segments in the tail to locomotion is comprehensive but could be compensated at least partially by other body segments. We suggest that the decentralization in locomotion control with respect to animal body parts helps to maintain the robustness of locomotion in multi-segment animals.

Drosophila Larvae-Inspired Soft Crawling Robot with Multimodal Locomotion and Versatile Applications.

Soft crawling robots have been widely studied and applied because of their excellent environmental adaptability and flexible movement. However, most existing soft crawling robots typically exhibit a single-motion mode and lack diverse capabilities. Inspired by Drosophila larvae, this paper proposes a compact soft crawling robot (weight, 13 g; length, 165 mm; diameter, 35 mm) with multimodal locomotion (forward, turning, rolling, and twisting). Each robot module uses 4 sets of high-power-density shape memory alloy actuators, endowing it with 4 degrees of motion freedom. We analyze the mechanical characteristics of the robot modules through experiments and simulation analysis. The plug-and-play modules can be quickly assembled to meet different motion and task requirements. The soft crawling robot can be remotely operated with an external controller, showcasing multimodal motion on various material surfaces. In a narrow maze, the robot demonstrates agile movement and effective maneuvering around obstacles. In addition, leveraging the inherent bistable characteristics of the robot modules, we used the robot modules as anchoring units and installed a microcamera on the robot's head for pipeline detection. The robot completed the inspection in horizontal, vertical, curved, and branched pipelines, adjusted the camera view, and twisted a valve in the pipeline for the first time. Our research highlights the robot's superior locomotion and application capabilities, providing an innovative strategy for the development of lightweight, compact, and multifunctional soft crawling robots.

High-Speed Automated Reconstruction of Drosophila Larval Brain from Volumetric EM Data.

To uncover the relationship between neural activity and behavior, it is essential to reconstruct neural circuits. However, methods typically used for neuron reconstruction from volumetric electron microscopy (EM) dataset are often time-consuming and require extensive manual proofreading, making it difficult to reproduce in a typical laboratory setting. To address this challenge, we have developed a set of acceleration techniques that build upon the Flood Filling Network (FFN), significantly reducing the time required for this task. These techniques can be easily adapted to other similar datasets and laboratory settings. To validate our approach, we tested our pipeline on a dataset of Drosophila larval brain serial section EM images at synaptic-resolution level. Our results demonstrate that our pipeline significantly reduces the inference time compared to the FFN baseline method and greatly reduces the time required for reconstructing the 3D morphology of neurons.

Clinical analysis and functional characterization of KCNQ2-related developmental and epileptic encephalopathy.

Background: Developmental and epileptic encephalopathy (DEE) is a condition characterized by severe seizures and a range of developmental impairments. Pathogenic variants in KCNQ2, encoding for potassium channel subunit, cause KCNQ2-related DEE. This study aimed to examine the relationships between genotype and phenotype in KCNQ2-related DEE. Methods: In total, 12 patients were enrolled in this study for genetic testing, clinical analysis, and developmental evaluation. Pathogenic variants of KCNQ2 were characterized through a whole-cell electrophysiological recording expressed in Chinese hamster ovary (CHO) cells. The expression levels of the KCNQ2 subunit and its localization at the plasma membrane were determined using Western blot analysis. Results: Seizures were detected in all patients. All DEE patients showed evidence of developmental delay. In total, 11 de novo KCNQ2 variants were identified, including 10 missense variants from DEE patients and one truncating variant from a patient with self-limited neonatal epilepsy (SeLNE). All variants were found to be loss of function through analysis of M-currents using patch-clamp recordings. The functional impact of variants on M-current in heteromericKCNQ2/3 channels may be associated with the severity of developmental disorders in DEE. The variants with dominant-negative effects in heteromeric channels may be responsible for the profound developmental phenotype. Conclusion: The mechanism underlying KCNQ2-related DEE involves a reduction of the M-current through dominant-negative effects, and the severity of developmental disorders in DEE may be predicted by the impact of variants on the M-current of heteromericKCNQ2/3 channels.

The Intrinsic Similarity of Topological Structure in Biological Neural Networks.

Most previous studies mainly have focused on the analysis of structural properties of individual neuronal networks from C. elegans. In recent years, an increasing number of synapse-level neural maps, also known as biological neural networks, have been reconstructed. However, it is not clear whether there are intrinsic similarities of structural properties of biological neural networks from different brain compartments or species. To explore this issue, we collected nine connectomes at synaptic resolution including C. elegans, and analyzed their structural properties. We found that these biological neural networks possess small-world properties and modules. Excluding the Drosophila larval visual system, these networks have rich clubs. The distributions of synaptic connection strength for these networks can be fitted by the truncated pow-law distributions. Additionally, compared with the power-law model, a log-normal distribution is a better model to fit the complementary cumulative distribution function (CCDF) of degree for these neuronal networks. Moreover, we also observed that these neural networks belong to the same superfamily based on the significance profile (SP) of small subgraphs in the network. Taken together, these findings suggest that biological neural networks share intrinsic similarities in their topological structure, revealing some principles underlying the formation of biological neural networks within and across species.

Modeling the Evolution of Biological Neural Networks Based on Caenorhabditis elegans Connectomes across Development.

Knowledge of the structural properties of biological neural networks can help in understanding how particular responses and actions are generated. Recently, Witvliet et al. published the connectomes of eight isogenic Caenorhabditis elegans hermaphrodites at different postembryonic ages, from birth to adulthood. We analyzed the basic structural properties of these biological neural networks. From birth to adulthood, the asymmetry between in-degrees and out-degrees over the C. elegans neuronal network increased with age, in addition to an increase in the number of nodes and edges. The degree distributions were neither Poisson distributions nor pure power-law distributions. We have proposed a model of network evolution with different initial attractiveness for in-degrees and out-degrees of nodes and preferential attachment, which reproduces the asymmetry between in-degrees and out-degrees and similar degree distributions via the tuning of the initial attractiveness values. In this study, we present the well-preserved structural properties of C. elegans neuronal networks across development, and provide some insight into understanding the evolutionary processes of biological neural networks through a simple network model.

Deep-learning on-chip light-sheet microscopy enabling video-rate volumetric imaging of dynamic biological specimens.

Volumetric imaging of dynamic signals in a large, moving, and light-scattering specimen is extremely challenging, owing to the requirement on high spatiotemporal resolution and difficulty in obtaining high-contrast signals. Here we report that through combining a microfluidic chip-enabled digital scanning light-sheet illumination strategy with deep-learning based image restoration, we can realize isotropic 3D imaging of a whole crawling Drosophila larva on an ordinary inverted microscope at a single-cell resolution and a high volumetric imaging rate up to 20 Hz. Enabled with high performances even unmet by current standard light-sheet fluorescence microscopes, we in toto record the neural activities during the forward and backward crawling of a 1st instar larva, and successfully correlate the calcium spiking of motor neurons with the locomotion patterns.

Intron-targeted mutagenesis reveals roles for Dscam1 RNA pairing architecture-driven splicing bias in neuronal wiring.

Drosophila melanogaster Down syndrome cell adhesion molecule (Dscam1) can generate 38,016 different isoforms through largely stochastic, yet highly biased, alternative splicing. These isoforms are required for nervous functions. However, the functional significance of splicing bias remains unknown. Here, we provide evidence that Dscam1 splicing bias is required for mushroom body (MB) axonal wiring. We generate mutant flies with normal overall protein levels and an identical number but global changes in exon 4 and 9 isoform bias (DscamΔ4D-/- and DscamΔ9D-/-), respectively. In contrast to DscamΔ4D-/-, DscamΔ9D-/- exhibits remarkable MB defects, suggesting a variable domain-specific requirement for isoform bias. Importantly, changes in isoform bias cause axonal defects but do not influence the self-avoidance of axonal branches. We conclude that, in contrast to the isoform number that provides the molecular basis for neurite self-avoidance, isoform bias may play a role in MB axonal wiring by influencing non-repulsive signaling.

The noncanonical role of the protease cathepsin D as a cofilin phosphatase.

Cathepsin D (cathD) is traditionally regarded as a lysosomal protease that degrades substrates in acidic compartments. Here we report cathD plays an unconventional role as a cofilin phosphatase orchestrating actin remodeling. In neutral pH environments, the cathD precursor directly dephosphorylates and activates the actin-severing protein cofilin independent of its proteolytic activity, whereas mature cathD degrades cofilin in acidic pH conditions. During development, cathD complements the canonical cofilin phosphatase slingshot and regulates the morphogenesis of actin-based structures. Moreover, suppression of cathD phosphatase activity leads to defective actin organization and cytokinesis failure. Our findings identify cathD as a dual-function molecule, whose functional switch is regulated by environmental pH and its maturation state, and reveal a novel regulatory role of cathD in actin-based cellular processes.

Acetyltransferase GCN5 regulates autophagy and lysosome biogenesis by targeting TFEB.

Accumulating evidence highlights the role of histone acetyltransferase GCN5 in the regulation of cell metabolism in metazoans. Here, we report that GCN5 is a negative regulator of autophagy, a lysosome-dependent catabolic mechanism. In animal cells and Drosophila, GCN5 inhibits the biogenesis of autophagosomes and lysosomes by targeting TFEB, the master transcription factor for autophagy- and lysosome-related gene expression. We show that GCN5 is a specific TFEB acetyltransferase, and acetylation by GCN5 results in the decrease in TFEB transcriptional activity. Induction of autophagy inactivates GCN5, accompanied by reduced TFEB acetylation and increased lysosome formation. We further demonstrate that acetylation at K274 and K279 disrupts the dimerization of TFEB and the binding of TFEB to its target gene promoters. In a Tau-based neurodegenerative Drosophila model, deletion of dGcn5 improves the clearance of Tau protein aggregates and ameliorates the neurodegenerative phenotypes. Together, our results reveal GCN5 as a novel conserved TFEB regulator, and the regulatory mechanisms may be involved in autophagy- and lysosome-related physiological and pathological processes.

Light Spot-Based Assay for Analysis of Drosophila Larval Phototaxis.

The larvae of Drosophila melanogaster show obvious light-avoiding behavior during the foraging stage. Drosophila larval phototaxis can be used as a model to study animal avoidance behavior. This protocol introduces a light-spot assay to investigate larval phototactic behavior. The experimental set-up includes two main parts: a visual stimulation system that generates the light spot, and an infrared light-based imaging system that records the process of larval light avoidance. This assay allows tracking of the behavior of larva before entering, during encountering, and after leaving the light spot. Details of larval movement including deceleration, pause, head casting, and turning can be captured and analyzed using this method.

A Novel Neuroprotective Role of Phosphatase of Regenerating Liver-1 against CO2 Stimulation in Drosophila.

Neuroprotection is essential for the maintenance of normal physiological functions in the nervous system. This is especially true under stress conditions. Here, we demonstrate a novel protective function of PRL-1 against CO2 stimulation in Drosophila. In the absence of PRL-1, flies exhibit a permanent held-up wing phenotype upon CO2 exposure. Knockdown of the CO2 olfactory receptor, Gr21a, suppresses the phenotype. Our genetic data indicate that the wing phenotype is due to a neural dysfunction. PRL-1 physically interacts with Uex and controls Uex expression levels. Knockdown of Uex alone leads to a similar wing held-up phenotype to that of PRL-1 mutants. Uex acts downstream of PRL-1. Elevated Uex levels in PRL-1 mutants prevent the CO2-induced phenotype. PRL-1 and Uex are required for a wide range of neurons to maintain neuroprotective functions. Expression of human homologs of PRL-1 could rescue the phenotype in Drosophila, suggesting a similar function in humans.

Correction to: Recent Advances in the Genetic Dissection of Neural Circuits in Drosophila.

In the original publication the fifth line starting with "… with circa 1000, 1000 neurons?" in section Concluding Remarks and Perspectives is incorrectly published. The correct text should read "… with circa 100, 000 neurons?"

Recent Advances in the Genetic Dissection of Neural Circuits in Drosophila.

Nervous systems endow animals with cognition and behavior. To understand how nervous systems control behavior, neural circuits mediating distinct functions need to be identified and characterized. With superior genetic manipulability, Drosophila is a model organism at the leading edge of neural circuit analysis. We briefly introduce the state-of-the-art genetic tools that permit precise labeling of neurons and their interconnectivity and investigating what is happening in the brain of a behaving animal and manipulating neurons to determine how behaviors are affected. Brain-wide wiring diagrams, created by light and electron microscopy, bring neural circuit analysis to a new level and scale. Studies enabled by these tools advances our understanding of the nervous system in relation to cognition and behavior.

A Neuronal Pathway that Commands Deceleration in Drosophila Larval Light-Avoidance.

When facing a sudden danger or aversive condition while engaged in on-going forward motion, animals transiently slow down and make a turn to escape. The neural mechanisms underlying stimulation-induced deceleration in avoidance behavior are largely unknown. Here, we report that in Drosophila larvae, light-induced deceleration was commanded by a continuous neural pathway that included prothoracicotropic hormone neurons, eclosion hormone neurons, and tyrosine decarboxylase 2 motor neurons (the PET pathway). Inhibiting neurons in the PET pathway led to defects in light-avoidance due to insufficient deceleration and head casting. On the other hand, activation of PET pathway neurons specifically caused immediate deceleration in larval locomotion. Our findings reveal a neural substrate for the emergent deceleration response and provide a new understanding of the relationship between behavioral modules in animal avoidance responses.

Author Correction: A disinhibitory mechanism biases Drosophila innate light preference.

Affiliation 2 incorrectly read 'Department of Neurology of the Second Affiliated Hospital, Department of Neurobiology, Key Laboratory of Medical Neurobiology of the Ministry of Health of China, Key Laboratory of Neurobiology, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310007, China' and affiliation 3 incorrectly read 'Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, Zhejiang 310058, China.'

A disinhibitory mechanism biases Drosophila innate light preference.

Innate preference toward environmental conditions is crucial for animal survival. Although much is known about the neural processing of sensory information, how the aversive or attractive sensory stimulus is transformed through central brain neurons into avoidance or approaching behavior is largely unclear. Here we show that Drosophila larval light preference behavior is regulated by a disinhibitory mechanism. In the disinhibitory circuit, a pair of GABAergic neurons exerts tonic inhibition on one pair of contralateral projecting neurons that control larval reorientation behavior. When a larva enters the light area, the reorientation-controlling neurons are disinhibited to allow reorientation to occur as the upstream inhibitory neurons are repressed by light. When the larva exits the light area, the inhibition on the downstream neurons is restored to repress further reorientation and thus prevents the larva from re-entering the light area. We suggest that disinhibition may serve as a common neural mechanism for animal innate preference behavior.