Drosophila Brain Research Articles

Bacterial peptidoglycan serves as a critical modulator of the gut-immune-brain axis in Drosophila

Metabolites and compounds derived from gut-associated bacteria can modulate numerous physiological processes in the host, including immunity and behavior. Using a model of oral bacterial infection, we previously demonstrated that gut-derived peptidoglycan (PGN), an essential constituent of the bacterial cell envelope, influences female fruit fly egg-laying behavior by activating the NF-κB cascade in a subset of brain neurons. These findings underscore PGN as a potential mediator of communication between gut bacteria and the brain in Drosophila, prompting further investigation into its impact on all brain cells. Through high-resolution mass spectrometry, we now show that PGN fragments produced by gut bacteria can rapidly reach the central nervous system. In Addition, by employing a combination of whole-genome transcriptome analyses, comprehensive genetic assays, and reporter gene systems, we reveal that gut bacterial infection triggers a PGN dose-dependent NF-κB immune response in perineurial glia, forming the continuous outer cell layer of the blood–brain barrier. Furthermore, we demonstrate that persistent PGN-dependent NF-κB activation in perineurial glial cells correlates with a reduction in lifespan and early neurological decline. Overall, our findings establish gut-derived PGN as a critical mediator of the gut-immune-brain axis in Drosophila.

Tissue-specific O-GlcNAcylation profiling identifies substrates in translational machinery in Drosophila mushroom body contributing to olfactory learning.

O-GlcNAcylation is a dynamic post-translational modification that diversifies the proteome. Its dysregulation is associated with neurological disorders that impair cognitive function, and yet identification of phenotype-relevant candidate substrates in a brain-region specific manner remains unfeasible. By combining an O-GlcNAc binding activity derived from Clostridium perfringens OGA (CpOGA) with TurboID proximity labeling in Drosophila, we developed an O-GlcNAcylation profiling tool that translates O-GlcNAc modification into biotin conjugation for tissue-specific candidate substrates enrichment. We mapped the O-GlcNAc interactome in major brain regions of Drosophila and found that components of the translational machinery, particularly ribosomal subunits, were abundantly O-GlcNAcylated in the mushroom body of Drosophila brain. Hypo-O-GlcNAcylation induced by ectopic expression of active CpOGA in the mushroom body decreased local translational activity, leading to olfactory learning deficits that could be rescued by dMyc overexpression-induced increase of protein synthesis. Our study provides a useful tool for future dissection of tissue-specific functions of O-GlcNAcylation in Drosophila, and suggests a possibility that O-GlcNAcylation impacts cognitive function via regulating regional translational activity in the brain.

Iterative assay for transposase-accessible chromatin by sequencing to isolate functionally relevant neuronal subtypes.

The Drosophila brain contains tens of thousands of distinct cell types. Thousands of different transgenic lines reproducibly target specific neuron subsets, yet most still express in several cell types. Furthermore, most lines were developed without a priori knowledge of where the transgenes would be expressed. To aid in the development of cell type-specific tools for neuronal identification and manipulation, we developed an iterative assay for transposase-accessible chromatin (ATAC) approach. Open chromatin regions (OCRs) enriched in neurons, compared to whole bodies, drove transgene expression preferentially in subsets of neurons. A second round of ATAC-seq from these specific neuron subsets revealed additional enriched OCR2s that further restricted transgene expression within the chosen neuron subset. This approach allows for continued refinement of transgene expression, and we used it to identify neurons relevant for sleep behavior. Furthermore, this approach is widely applicable to other cell types and to other organisms.

Biochemical Fractionation of Human α-Synuclein in a Drosophila Model of Synucleinopathies.

Synucleinopathies are a group of central nervous system pathologies that are characterized by the intracellular accumulation of misfolded and aggregated α-synuclein in proteinaceous depositions known as Lewy Bodies (LBs). The transition of α-synuclein from its physiological to pathological form has been associated with several post-translational modifications such as phosphorylation and an increasing degree of insolubility, which also correlate with disease progression in post-mortem specimens from human patients. Neuronal expression of α-synuclein in model organisms, including Drosophila melanogaster, has been a typical approach employed to study its physiological effects. Biochemical analysis of α-synuclein solubility via high-speed ultracentrifugation with buffers of increasing detergent strength offers a potent method for identification of α-synuclein biochemical properties and the associated pathology stage. Unfortunately, the development of a robust and reproducible method for the evaluation of human α-synuclein solubility isolated from Drosophila tissues has remained elusive. Here, we tested different detergents for their ability to solubilize human α-synuclein carrying the pathological mutation A53T from the brains of aged flies. We also assessed the effect of sonication on the solubility of human α-synuclein and optimized a protocol to discriminate the relative amounts of soluble/insoluble human α-synuclein from dopaminergic neurons of the Drosophila brain. Our data established that, using a 5% SDS buffer, the three-step protocol separates cytosolic soluble, detergent-soluble and insoluble proteins in three sequential fractions according to their chemical properties. This protocol shows that sonication breaks down α-synuclein insoluble complexes from the fly brain, making them soluble in the SDS buffer and thus enriching the detergent-soluble fraction of the protocol.

Seed-Induced Accumulation of β-Amyloid Exacerbates Oxidative Stress in Drosophila

Background: Progression of Alzheimer's disease (AD) was considered involving fibrosis and amyloidosis of abnormal proteins that kill cells and disrupt neuronal connections. The polymerization process of Amyloid β (Aβ) is resistant to degradation. Aβ42, one of the major isoforms of Aβ, could be a "seed" to accelerate the aggregation and deposition of homologous or heterologous erroneous proteins in the brain. Methods: A new drosophila model was constructed by exogenous injection of Aβ42 to explore the neural mechanism of amyloid plaque formation in the brain. Results: Aβ aggregates in the brains of APP-injected flies decreased in the early stage and increased in the later stage, suggesting that Aβ42 may act as an innate immune defense molecule to activate brain immune responses to protect the host from infection. To demonstrate the effect of exogenous injections on antioxidant capacity, reactive oxygen species (ROS) were measured in a drosophila model. It was found that injection of Aβ42 accelerated ROS accumulation in the brain only in the short term, but ROS accumulated and accelerated Aβ accumulation in brain-induced neurodegeneration over time. Both crawling ability tests and lifespan tests showed more severe AD symptoms. However, in the monitoring of fly sleep after Aβ42 injection, sleep was compensated in APP flies injected with Aβ42. Conclusion: A seed mechanism is involved in the propagation and development of Aβ in the brain of Drosophila. It also provides new insights into Alzheimer's disease research.

Joint Learning Neuronal Skeleton and Brain Circuit Topology with Permutation Invariant Encoders for Neuron Classification

Determining the types of neurons within a nervous system plays a significant role in the analysis of brain connectomics and the investigation of neurological diseases. However, the efficiency of utilizing anatomical, physiological, or molecular characteristics of neurons is relatively low and costly. With the advancements in electron microscopy imaging and analysis techniques for brain tissue, we are able to obtain whole-brain connectome consisting neuronal high-resolution morphology and connectivity information. However, few models are built based on such data for automated neuron classification. In this paper, we propose NeuNet, a framework that combines morphological information of neurons obtained from skeleton and topological information between neurons obtained from neural circuit. Specifically, NeuNet consists of three components, namely Skeleton Encoder, Connectome Encoder, and Readout Layer. Skeleton Encoder integrates the local information of neurons in a bottom-up manner, with a one-dimensional convolution in neural skeleton's point data; Connectome Encoder uses a graph neural network to capture the topological information of neural circuit; finally, Readout Layer fuses the above two information and outputs classification results. We reprocess and release two new datasets for neuron classification task from volume electron microscopy(VEM) images of human brain cortex and Drosophila brain. Experiments on these two datasets demonstrated the effectiveness of our model with accuracies of 0.9169 and 0.9363, respectively. Code and data are available at: https://github.com/WHUminghui/NeuNet.

Neuronal ageing is promoted by the decay of the microtubule cytoskeleton.

Natural ageing is accompanied by a decline in motor, sensory, and cognitive functions, all impacting quality of life. Ageing is also the predominant risk factor for many neurodegenerative diseases, including Parkinson's disease and Alzheimer's disease. We need to therefore gain a better understanding of the cellular and physiological processes underlying age-related neuronal decay. However, gaining this understanding is a slow process due to the large amount of time required to age mammalian or vertebrate animal models. Here, we introduce a new cellular model within the Drosophila brain, in which we report classical ageing hallmarks previously observed in the primate brain. These hallmarks include axonal swellings, cytoskeletal decay, a reduction in axonal calibre, and morphological changes arising at synaptic terminals. In the fly brain, these changes begin to occur within a few weeks, ideal to study the underlying mechanisms of ageing. We discovered that the decay of the neuronal microtubule (MT) cytoskeleton precedes the onset of other ageing hallmarks. We showed that the MT-binding factors Tau, EB1, and Shot/MACF1, are necessary for MT maintenance in axons and synapses, and that their functional loss during ageing triggers MT bundle decay, followed by a decline in axons and synaptic terminals. Furthermore, genetic manipulations that improve MT networks slowed down the onset of neuronal ageing hallmarks and confer aged specimens the ability to outperform age-matched controls. Our work suggests that MT networks are a key lesion site in ageing neurons and therefore the MT cytoskeleton offers a promising target to improve neuronal decay in advanced age.

Sample Preparation for Chromatin Immunoprecipitation (ChIP) from Drosophila Antennal and Brain Samples.

Chromatin immunoprecipitation (ChIP) is a well-characterized procedure used to reveal specific patterns of protein-DNA interactions and identify the binding sites of proteins on DNA. ChIP has been used to study many aspects of Drosophila biology, including neurobiology. This protocol describes in detail how to prepare cross-linked chromatin from Drosophila antennae and brains followed by immunoprecipitation (X-ChIP). We first describe tissue dissection, chromatin cross-linking with formaldehyde, quenching of the cross-linking, homogenization of tissues, and sonication for shearing the chromatin. Additionally, we describe how to optimize the sonication efficiency and fixation time and concentration using Drosophila brain samples as an example. These parameters are crucial for successful ChIP.

Chromatin Immunoprecipitation (ChIP) Using Drosophila Antennal and Brain Samples.

Chromatin immunoprecipitation (ChIP) is a common approach for studying the binding pattern of proteins on DNA sequences or the landscape of histones with different marks throughout the genome. ChIP is used on various organisms, including Drosophila This protocol provides a detailed overview of the immunoprecipitation portion of a ChIP procedure from samples of Drosophila nervous systems, specifically antennae and brains, that have already been fixed and sheared. These methods can be applied to other tissues of interest after optimizing for sample size and other relevant parameters.

Performing Quantitative PCR after Chromatin Immunoprecipitation (ChIP) of Drosophila Antennal and Brain Samples.

Chromatin immunoprecipitation (ChIP) is a technique used to study specific protein-DNA interaction. Briefly, in this technique, antibodies to proteins of interest are used to isolate regions of DNA where these proteins bind. ChIP samples can be processed and analyzed in different ways. One of the approaches for assessing the results of ChIP experiments is quantitative PCR (qPCR). qPCR is used to quantitatively measure the amount of DNA fragments that have been isolated, reflecting the signal of specific proteins interacting with these fragments. This protocol describes both the "percent input" method and the "fold enrichment" method for ChIP-qPCR data analysis using Drosophila tissues as an example. The "percent input" method measures signals of DNA fragments against the input measurement. In contrast, the "fold enrichment" method quantifies the amplified signal strength relative to a background control. Because the quality of primers is critical for the reliability of ChIP-qPCR results, this protocol also describes how to measure primer amplification efficiency using Drosophila genomic DNA.

The neuropeptide pigment-dispersing factor signals independently of Bruchpilot-labelled active zones in daily remodelled terminals of Drosophila clock neurons.

The small ventrolateral neurons (sLNvs) are key components of the central clock in the Drosophila brain. They signal via the neuropeptide pigment-dispersing factor (PDF) to align the molecular clockwork of different central clock neurons and to modulate downstream circuits. The dorsal terminals of the sLNvs undergo daily morphological changes that affect presynaptic sites organised by the active zone protein Bruchpilot (BRP), a homolog of mammalian ELKS proteins. However, the role of these presynaptic sites for PDF release is ill-defined. Here, we combined expansion microscopy with labelling of active zones by endogenously tagged BRP to examine the spatial correlation between PDF-containing dense-core vesicles and BRP-labelled active zones. We found that the number of BRP-labelled puncta in the sLNv terminals was similar while their density differed between Zeitgeber time (ZT) 2 and 14. The relative distance between BRP- and PDF-labelled puncta was increased in the morning, around the reported time of PDF release. Spontaneous dense-core vesicle release profiles of sLNvs in a publicly available ssTEM dataset (FAFB) consistently lacked spatial correlation to BRP-organised active zones. RNAi-mediated downregulation of brp and other active zone proteins expressed by the sLNvs did not affect PDF-dependent locomotor rhythmicity. In contrast, down-regulation of genes encoding proteins of the canonical vesicle release machinery, the dense-core vesicle-related protein CADPS, as well as PDF impaired locomotor rhythmicity. Taken together, our study suggests that PDF release from the sLNvs is independent of BRP-organised active zones, while BRP may be redistributed to active zones in a time-dependent manner.

A linearized modeling framework for the frequency selectivity in neurons postsynaptic to vibration receptors.

Vibration is an indispensable part of the tactile perception, which is encoded to oscillatory synaptic currents by receptors and transferred to neurons in the brain. The A2 and B1 neurons in the drosophila brain postsynaptic to the vibration receptors exhibit selective preferences for oscillatory synaptic currents with different frequencies, which is caused by the specific voltage-gated Na+ and K+ currents that both oppose the variations in membrane potential. To understand the peculiar role of the Na+ and K+ currents in shaping the filtering property of A2 and B1 neurons, we develop a linearized modeling framework that allows to systematically change the activation properties of these ionic channels. A data-driven conductance-based biophysical model is used to reproduce the frequency filtering of oscillatory synaptic inputs. Then, this data-driven model is linearized at the resting potential and its frequency response is calculated based on the transfer function, which is described by the magnitude-frequency curve. When we regulate the activation properties of the Na+ and K+ channels by changing the biophysical parameters, the dominant pole of the transfer function is found to be highly correlated with the fluctuation of the active current, which represents the strength of suppression of slow voltage variation. Meanwhile, the dominant pole also shapes the magnitude-frequency curve and further qualitatively determines the filtering property of the model. The transfer function provides a parsimonious description of how the biophysical parameters in Na+ and K+ channels change the inhibition of slow variations in membrane potential by Na+ and K+ currents, and further illustrates the relationship between the filtering properties and the activation properties of Na+ and K+ channels. This computational framework with the data-driven conductance-based biophysical model and its linearized model contributes to understanding the transmission and filtering of vibration stimulus in the tactile system.

Converting an allocentric goal into an egocentric steering signal.

Neuronal signals that are relevant for spatial navigation have been described in many species1-10. However, a circuit-level understanding of how such signals interact to guide navigational behaviour is lacking. Here we characterize a neuronal circuit in the Drosophila central complex that compares internally generated estimates of the heading and goal angles of the fly-both of which are encoded in world-centred (allocentric) coordinates-to generate a body-centred (egocentric) steering signal. Past work has suggested that the activity of EPG neurons represents the fly's moment-to-moment angular orientation, orheading angle, during navigation2,11. An animal's moment-to-moment heading angle, however, is not always aligned with its goal angle-that is, the allocentric direction in which it wishes to progress forward. We describe FC2 cells12, a second set of neurons in the Drosophila brain with activity that correlates with the fly's goal angle. Focal optogenetic activation of FC2 neurons induces flies to orient along experimenter-defined directions as they walk forward. EPG and FC2 neurons connect monosynaptically to a third neuronal class, PFL3 cells12,13. We found that individual PFL3 cells show conjunctive, spike-rate tuning to both the heading angle and the goal angle during goal-directed navigation. Informed by the anatomy and physiology of these three cell classes, we develop a model that explains how this circuit compares allocentric heading and goal angles to build an egocentric steering signal in the PFL3 output terminals. Quantitative analyses and optogenetic manipulations of PFL3 activity support the model. Finally, using a new navigational memory task, we show that flies expressing disruptors of synaptic transmission in subsets of PFL3 cells have a reduced ability to orient along arbitrary goal directions, with an effect size in quantitative accordance with the prediction of our model. The biological circuit described here reveals how two population-level allocentric signals are compared in the brain to produce an egocentric output signal that is appropriate for motor control.

Asymmetric neurons are necessary for olfactory learning in the Drosophila brain

Animals have complementary parallel memory systems that process signals from various sensory modalities. In the brain of the fruit fly Drosophila melanogaster, mushroom body (MB) circuitry is the primary associative neuropil, critical for all stages of olfactory memory. Here, our findings suggest that active signaling from specific asymmetric body (AB) neurons is also crucial for this process. These AB neurons respond to odors and electric shock separately and exhibit timing-sensitive neuronal activity in response to paired stimulation while leaving a decreased memory trace during retrieval. Our experiments also show that rutabaga-encoded adenylate cyclase, which mediates coincidence detection, is required for learning and short-term memory in both AB and MB. We observed additive effects when manipulating rutabaga co-expression in both structures. Together, these results implicate the AB in playing a critical role in associative olfactory learning and short-term memory.

Disrupted nuclear import of cell cycle proteins in Huntington's/PolyQ disease causes neurodevelopment defects in cellular and Drosophila model

Huntington's disease is caused by an expansion of CAG repeats in exon 1 of the huntingtin gene encoding an extended PolyQ tract within the Huntingtin protein (mHtt). This expansion results in selective degeneration of striatal medium spiny projection neurons in the basal ganglia. The mutation causes abnormalities during neurodevelopment in human and mouse models. Here, we report that mHtt/PolyQ aggregates inhibit the cell cycle in the Drosophila brain during development. PolyQ aggregates disrupt the nuclear pore complexes of the cells preventing the translocation of cell cycle proteins such as Cyclin E, E2F and PCNA from cytoplasm to the nucleus, thus affecting cell cycle progression. PolyQ aggregates also disrupt the nuclear pore complex and nuclear import in mHtt expressing mammalian CAD neurons. PolyQ toxicity and cell cycle defects can be restored by enhancing RanGAP-mediated nuclear import, suggesting a potential therapeutic approach for this disease.

High-Performance Genetically Encoded Green Fluorescent Biosensors for Intracellular l-Lactate.

l-Lactate is a monocarboxylate produced during the process of cellular glycolysis and has long generally been considered a waste product. However, studies in recent decades have provided new perspectives on the physiological roles of l-lactate as a major energy substrate and a signaling molecule. To enable further investigations of the physiological roles of l-lactate, we have developed a series of high-performance (ΔF/F = 15 to 30 in vitro), intensiometric, genetically encoded green fluorescent protein (GFP)-based intracellular l-lactate biosensors with a range of affinities. We evaluated these biosensors in cultured cells and demonstrated their application in an ex vivo preparation of Drosophila brain tissue. Using these biosensors, we were able to detect glycolytic oscillations, which we analyzed and mathematically modeled.

Use-Dependent, Untapped Dual Kinase Signaling Localized in Brain Learning Circuitry.

Imaging brain learning and memory circuit kinase signaling is a monumental challenge. The separation of phases-based activity reporter of kinase (SPARK) biosensors allow circuit-localized studies of multiple interactive kinases in vivo, including protein kinase A (PKA) and extracellular signal-regulated kinase (ERK) signaling. In the precisely-mapped Drosophila brain learning/memory circuit, we find PKA and ERK signaling differentially enriched in distinct Kenyon cell connectivity nodes. We discover that potentiating normal circuit activity induces circuit-localized PKA and ERK signaling, expanding kinase function within new presynaptic and postsynaptic domains. Activity-induced PKA signaling shows extensive overlap with previously selective ERK signaling nodes, while activity-induced ERK signaling arises in new connectivity nodes. We find targeted synaptic transmission blockade in Kenyon cells elevates circuit-localized ERK induction in Kenyon cells with normally high baseline ERK signaling, suggesting lateral and feedback inhibition. We discover overexpression of the pathway-linking Meng-Po (human SBK1) serine/threonine kinase to improve learning acquisition and memory consolidation results in dramatically heightened PKA and ERK signaling in separable Kenyon cell circuit connectivity nodes, revealing both synchronized and untapped signaling potential. Finally, we find that a mechanically-induced epileptic seizure model (easily shocked "bang-sensitive" mutants) has strongly elevated, circuit-localized PKA and ERK signaling. Both sexes were used in all experiments, except for the hemizygous male-only seizure model. Hyperexcitable, learning-enhanced, and epileptic seizure models have comparably elevated interactive kinase signaling, suggesting a common basis of use-dependent induction. We conclude that PKA and ERK signaling modulation is locally coordinated in use-dependent spatial circuit dynamics underlying seizure susceptibility linked to learning/memory potential.

Mapping the neural dynamics of locomotion across the Drosophila brain

Locomotion engages widely distributed networks of neurons. However, our understanding of the spatial architecture and temporal dynamics of the networks that underpin walking remains incomplete. We use volumetric two-photon imaging to map neural activity associated with walking across the entire brain of Drosophila. We define spatially clustered neural signals selectively associated with changes in either forward or angular velocity, demonstrating that neurons with similar behavioral selectivity are clustered. These signals reveal distinct topographic maps in diverse brain regions involved in navigation, memory, sensory processing, and motor control, as well as regions not previously linked to locomotion. We identify temporal trajectories of neural activity that sweep across these maps, including signals that anticipate future movement, representing the sequential engagement of clusters with different behavioral specificities. Finally, we register these maps to a connectome and identify neural networks that we propose underlie the observed signals, setting a foundation for subsequent circuit dissection. Overall, our work suggests a spatiotemporal framework for the emergence and execution of complex walking maneuvers and links this brain-wide neural activity to single neurons and local circuits.

Cell type-specific regulation of m6 A modified RNAs in the aging Drosophila brain.

The aging brain is highly vulnerable to cellular stress, and neurons employ numerous mechanisms to combat neurotoxic proteins and promote healthy brain aging. The RNA modification m6 A is highly enriched in the Drosophila brain and is critical for the acute heat stress response of the brain. Here we examine m6 A in the fly brain with the chronic stresses of aging and degenerative disease. m6 A levels dynamically increased with both age and disease in the brain, marking integral neuronal identity and signaling pathway transcripts that decline in level with age and disease. Unexpectedly, there is opposing impact of m6 A transcripts in neurons versus glia, which conferred different outcomes on animal health span upon Mettl3 knockdown to reduce m6 A: whereas Mettl3 function is normally beneficial to neurons, it is deleterious to glia. Moreover, knockdown of Mettl3 in glial tauopathy reduced tau pathology and increased animal survival. These findings provide mechanistic insight into regulation of m6 A modified transcripts with age and disease, highlighting an overall beneficial function of Mettl3 in neurons in response to chronic stresses, versus a deleterious impact in glia.

Maintaining Toll signaling in Drosophila brain is required to sustain autophagy for dopamine neuron survival

Macroautophagy/autophagy is a conserved process in eukaryotic cells to degrade and recycle damaged intracellular components. Higher level of autophagy in the brain has been observed, and autophagy dysfunction has an impact on neuronal health, but the molecular mechanism is unclear. In this study, we showed that overexpression of Toll-1 and Toll-7 receptors, as well as active Spätzle proteins in Drosophila S2 cells enhanced autophagy, and Toll-1/Toll-7 activated autophagy was dependent on Tube-Pelle-PP2A. Interestingly, Toll-1 but not Toll-7 mediated autophagy was dMyd88 dependent. Importantly, we observed that loss of functions in Toll-1 and Toll-7 receptors and PP2A activity in flies decreased autophagy level, resulting in the loss of dopamine (DA) neurons and reduced fly motion. Our results indicated that proper activation of Toll-1 and Toll-7 pathways and PP2A activity in the brain are necessary to sustain autophagy level for DA neuron survival.