Biology subjects

Siwanowicz, I.

Publications and source records attributed to Siwanowicz, I..

14 recordsLinked to original sources

bioRxiv2026

Non-cell-autonomous removal of protein aggregates via trogocytosis

Protein aggregate formation can cause cell damage and contribute to tissue pathologies including neurodegeneration. Protein aggregates are normally eliminated by cell-intrinsic mechanisms of lysosomal (autophagic) degradation. However, degradative capacity varies between cell types, raising the possibility that high-capacity cell types, such as macrophages, may contribute to aggregate disposal from the low-capacity cells. Here, we show that cellular protein aggregates are removed by macrophages via trogocytosis -- a partial engulfment of the target cells. Lysosomal stress upon protein aggregate accumulation promotes cell surface expression of the transmembrane isoform of the macrophage growth factor CSF1 (tmCSF1), which is detected by macrophages through the CSF1 receptor to drive trogocytosis. Insufficient or impaired degradation of protein aggregates in lysosomes results in their transport along microtubules to the plasma membrane where they physically associate with tmCSF1. This enables macrophages to specifically trogocytose protein aggregates. These findings reveal a protein homeostasis system that eliminates protein aggregates in a non-cell-autonomous manner.

cell biology↗

bioRxiv2026

Motor control of the Drosophila antennae

Animals actively sense their surroundings to acquire behaviorally relevant environmental cues and stimuli. This dynamic acquisition of sensory information is enabled by active positioning of sensors and helps guide behavioral responses in dynamic environments. Yet how these active movements are controlled during behavior and coordinated with ongoing sensory acquisition is not fully understood. In the fruit fly Drosophila melanogaster, the antennae are crucial sensors for extracting important information from the environment including mechanosensory, olfactory, and auditory signals. Just four distinct muscles command movement of the antennae, providing a tractable model system for understanding efferent control of sensation. This work characterizes motor neurons used by Drosophila to actively position the antennae. We first identify antennal motor neurons in the central brain, and map each one from a comprehensive connectomic dataset to its peripheral muscle target. Our analysis of presynaptic inputs to the entire antennal motor system reveals a diverse array of premotor neurons for antennal motor control. We then provide genetic access to each motor unit by building a library of genetic lines with expression in antennal motor neurons. Using this library of antennal motor neuron lines, we next characterize motor unit function with quantitative behavior and optogenetics, revealing that the antennal motor system produces two primary movements in the dorsal-ventral and medial-lateral axes. Together, this work provides a comprehensive framework for understanding the motor control of an active sensor.

neuroscience↗

bioRxiv2025

Proprioceptive limit detectors mediate sensorimotor control of the Drosophila leg

Many animals possess mechanosensory neurons that fire when a limb nears the limit of its physical range, but the function of these proprioceptive limit detectors remains poorly understood. Here, we investigate a class of proprioceptors on the Drosophila leg called hair plates. Using calcium imaging in behaving flies, we find that a hair plate on the fly coxa (CxHP8) detects the limits of anterior leg movement. Reconstructing CxHP8 axons in the connectome, we found that they are wired to excite posterior leg movement and inhibit anterior leg movement. Consistent with this connectivity, optogenetic activation of CxHP8 neurons elicited posterior postural reflexes, while silencing altered the swing-to-stance transition during walking. Finally, we use comprehensive reconstruction of peripheral morphology and downstream connectivity to predict the function of other hair plates distributed across the fly leg. Our results suggest that each hair plate is specialized to control specific sensorimotor reflexes that are matched to the joint limit it detects. They also illustrate the feasibility of predicting sensorimotor reflexes from a connectome with identified proprioceptive inputs and motor outputs.

neuroscience↗

bioRxiv2024

Wireless recordings from dragonfly target detecting neurons during prey interception flight

Target interception is a complex sensorimotor behavior which requires fine tuning of the sensory system and its strategic coordination with the motor system. Despite various theories about how interception is achieved, its neural implementation remains unknown. We have previously shown that hunting dragonflies employ a balance of reactive and predictive control to intercept prey, using sophisticated model driven predictions to account for expected prey and self-motion. Here we explore the neural substrate of this interception system by investigating a well-known class of target-selective descending neurons (TSDNs). These cells have long been speculated to underlie interception steering but have never been studied in a behaving dragonfly. We combined detailed neuroanatomy, high-precision kinematics data and state-of-the-art neural telemetry to measure TSDN activity during flight. We found that TSDNs are exquisitely tuned to prey angular size and speed at ethological distances, and that they synapse directly onto neck and wing motoneurons in an unusual manner. However, we found that TSDNs were only weakly active during flight and are thus unlikely to provide the primary steering signal. Instead, they appear to drive the foveating head movements that stabilize prey on the eye before and likely throughout the interception flight. We suggest the TSDN population implements the reactive portion of the interception steering control system, coordinating head and wing movements to compensate for unexpected prey motion.

neuroscience↗

bioRxiv2024

Mechanosensory representation of wing deformations

Locomotor control is facilitated by mechanosensory inputs that report how the body interacts with a physical medium. Effective representation of compliant wing deformations is particularly challenging due to the many degrees of freedom. Structural configurations can constrain the stimulus space, and strategic placement of sensors can simplify computation. Here, we measured and modelled wing displacement fields and characterized spatiotemporal encoding of the wing mechanosensors. Our data show how dragonfly wing architecture prescribes deformation modes consistent across models and measurements. We found that the wings state under normal flapping conditions is detected by the spike timing of few sensors, with additional sensors recruited under perturbation. The functional integration of wing biomechanics and sensor placement enables a straightforward solution for information transfer. Significance StatementMany systems in nature precisely control highly deformable structures, yet monitoring structural deformations has posed a significant challenge for biologists and engineers. By measuring and modelling the intricate structure of compliant dragonfly wings, we demonstrate an elegant solution for mechanosensory representation. We show that the functional integration of natural wing biomechanics and sensor placement provides a straightforward solution for information transfer. Wing morphology passively constrains the range of natural deformations, producing strain patterns that align with sensor locations, allowing them to monitor the wing using a simple timing-dependent encoding strategy. The way insects monitor aerodynamic and inertial forces via wing deformations during flight could apply to many sensory systems in nature and inspire artificial neural networks for controlling diverse dynamic systems.

neuroscience↗

bioRxiv2024

Whole-body simulation of realistic fruit fly locomotion with deep reinforcement learning

The body of an animal influences how the nervous system produces behavior. Therefore, detailed modeling of the neural control of sensorimotor behavior requires a detailed model of the body. Here we contribute an anatomically-detailed biomechanical whole-body model of the fruit fly Drosophila melanogaster in the MuJoCo physics engine. Our model is general-purpose, enabling the simulation of diverse fly behaviors, both on land and in the air. We demonstrate the generality of our model by simulating realistic locomotion, both flight and walking. To support these behaviors, we have extended MuJoCo with phenomenological models of fluid forces and adhesion forces. Through data-driven end-to-end reinforcement learning, we demonstrate that these advances enable the training of neural network controllers capable of realistic locomotion along complex trajectories based on high-level steering control signals. We demonstrate the use of visual sensors and the re-use of a pre-trained general-purpose flight controller by training the model to perform visually guided flight tasks. Our project is an open-source platform for modeling neural control of sensorimotor behavior in an embodied context.

animal behavior and cognition↗

bioRxiv2023

Driver lines for studying associative learning in Drosophila

AbstractThe mushroom body (MB) is the center for associative learning in insects. In Drosophila, intersectional split-GAL4 drivers and electron microscopy (EM) connectomes have laid the foundation for precise interrogation of the MB neural circuits. However, investigation of many cell types upstream and downstream of the MB has been hindered due to lack of specific driver lines. Here we describe a new collection of over 800 split-GAL4 and split-LexA drivers that cover approximately 300 cell types, including sugar sensory neurons, putative nociceptive ascending neurons, olfactory and thermo-/hygro-sensory projection neurons, interneurons connected with the MB-extrinsic neurons, and various other cell types. We characterized activation phenotypes for a subset of these lines and identified a sugar sensory neuron line most suitable for reward substitution. Leveraging the thousands of confocal microscopy images associated with the collection, we analyzed neuronal morphological stereotypy and discovered that one set of mushroom body output neurons, MBON08/MBON09, exhibits striking individuality and asymmetry across animals. In conjunction with the EM connectome maps, the driver lines reported here offer a powerful resource for functional dissection of neural circuits for associative learning in adult Drosophila.

neuroscience↗

bioRxiv2023

Transforming descending input into behavior: The organization of premotor circuits in the Drosophila Male Adult Nerve Cord connectome

In most animals, a relatively small number of descending neurons (DNs) connect higher brain centers in the animals head to circuits and motor neurons (MNs) in the nerve cord of the animals body that effect movement of the limbs. To understand how brain signals generate behavior, it is critical to understand how these descending pathways are organized onto the body MNs. In the fly, Drosophila melanogaster, MNs controlling muscles in the leg, wing, and other motor systems reside in a ventral nerve cord (VNC), analogous to the mammalian spinal cord. In companion papers, we introduced a densely-reconstructed connectome of the Drosophila Male Adult Nerve Cord (MANC, (Takemura et al., 2024)), including cell type and developmental lineage annotation (Marin et al., 2024), which provides complete VNC connectivity at synaptic resolution. Here, we present a first look at the organization of the VNC networks connecting DNs to MNs based on this new connectome information. We proofread and curated all DNs and MNs to ensure accuracy and reliability, then systematically matched DN axon terminals and MN dendrites with light microscopy data to link their VNC morphology with their brain inputs or muscle targets. We report both broad organizational patterns of the entire network and fine-scale analysis of selected circuits of interest. We discover that direct DN-MN connections are infrequent and identify communities of intrinsic neurons linked to control of different motor systems, including putative ventral circuits for walking, dorsal circuits for flight steering and power generation, and intermediate circuits in the lower tectulum for coordinated action of wings and legs. Our analysis generates hypotheses for future functional experiments and, together with the MANC connectome, empowers others to investigate these and other circuits of the Drosophila ventral nerve cord in richer mechanistic detail.

neuroscience↗

bioRxiv2023

Single-cell type analysis of wing premotor circuits in the ventral nerve cord of Drosophila melanogaster

To perform most behaviors, animals must send commands from higher-order processing centers in the brain to premotor circuits that reside in ganglia distinct from the brain, such as the mammalian spinal cord or insect ventral nerve cord. How these circuits are functionally organized to generate the great diversity of animal behavior remains unclear. An important first step in unraveling the organization of premotor circuits is to identify their constituent cell types and create tools to monitor and manipulate these with high specificity to assess their functions. This is possible in the tractable ventral nerve cord of the fly. To generate such a toolkit, we used a combinatorial genetic technique (split-GAL4) to create 195 sparse transgenic driver lines targeting 196 individual cell types in the ventral nerve cord. These included wing and haltere motoneurons, modulatory neurons, and interneurons. Using a combination of behavioral, developmental, and anatomical analyses, we systematically characterized the cell types targeted in our collection. In addition, we identified correspondences between the cells in this collection and a recent connectomic data set of the ventral nerve cord. Taken together, the resources and results presented here form a powerful toolkit for future investigations of neuronal circuits and connectivity of premotor circuits while linking them to behavioral outputs.

neuroscience↗

bioRxiv2022

Eye structure shapes neuron function in Drosophila motion vision

Many animals rely on vision to navigate through their environment. The pattern of changes in the visual scene induced by self-motion is the optic flow1, which is first estimated in local patches by directionally selective (DS) neurons2-4. But how should the arrays of DS neurons, each responsive to motion in a preferred direction at a specific retinal position, be organized to support robust decoding of optic flow by downstream circuits? Understanding this global organization is challenging because it requires mapping fine, local features of neurons across the animals field of view3. In Drosophila, the asymmetric dendrites of the T4 and T5 DS neurons establish their preferred direction, making it possible to predict DS responses from anatomy4,5. Here we report that the preferred directions of fly DS neurons vary at different retinal positions and show that this spatial variation is established by the anatomy of the compound eye. To estimate the preferred directions across the visual field, we reconstructed hundreds of T4 neurons in a full brain EM volume6 and discovered unexpectedly stereotypical dendritic arborizations that are independent of location. We then used whole-head CT scans to map the viewing directions of all compound eye facets and found a non-uniform sampling of visual space that explains the spatial variation in preferred directions. Our findings show that the organization of preferred directions in the fly is largely determined by the compound eye, exposing an intimate and unexpected connection between the peripheral structure of the eye, functional properties of neurons deep in the brain, and the control of body movements.

neuroscience↗

bioRxiv2022

Biomechanical origins of proprioceptive maps in the Drosophila leg

Our ability to sense and move our bodies relies on proprioceptors, sensory neurons that detect mechanical forces within the body. Proprioceptors are diverse: different subtypes detect different features of joint kinematics, such as position, directional movement, and vibration. However, because they are located within complex and dynamic peripheral tissues, the underlying mechanisms of proprioceptor feature selectivity remain poorly understood. Here, we investigate molecular and biomechanical contributions to proprioceptor diversity in the Drosophila leg. Using single-nucleus RNA sequencing, we found that different proprioceptor subtypes express similar complements of mechanosensory and other ion channels. However, anatomical reconstruction of the proprioceptive organ and connected tendons revealed major biomechanical differences between proprioceptor subtypes. We constructed a computational model of the proprioceptors and tendons, which identified a putative biomechanical mechanism for joint angle selectivity. The model also predicted the existence of a goniotopic map of joint angle among position-tuned proprioceptors, which we confirmed using calcium imaging. Our findings suggest that biomechanical specialization is a key determinant of proprioceptor feature selectivity in Drosophila. More broadly, our discovery of proprioceptive maps in the fly leg reveals common organizational principles between proprioception and other topographically organized sensory systems.

neuroscience↗

bioRxiv2021

Complete neuroanatomy and sensor maps of Odonata wings for fly-by-feel flight control

Can mechanosensors in animal wings allow reconstruction of the wing aeroelastic states? Little is known about how flying animals utilize wing mechanosensation to monitor the dynamic state of their highly deformable wings. Odonata, dragonflies and damselflies, are a basal lineage of flying insects with excellent flight performance, and their wing mechanics have been studied extensively. Here, we present a comprehensive map of the wing sensory system for two Odonata species, including both the external sensor morphologies and internal neuroanatomy. We identified eight morphological classes of sensors; most were mechanosensors innervated by a single neuron. Their innervation patterns and morphologies minimize axon length and allow morphological latency compensation. We further mapped the major veins of another 13 Odonata species across 10 families and identified consistent sensor distribution patterns, with sensor count scaling with wing length. Finally, we constructed a high-fidelity finite element model of a dragonfly wing for structural analysis. Our dynamic loading simulations revealed features of the strain fields that wing sensor arrays could detect to encode different wing deformation states. Taken together, this work marks the first step toward an integrated understanding of fly-by-feel control in animal flight.

neuroscience↗

bioRxiv2020

A novel family of secreted proteins linked to plant gall development

In an elaborate form of inter-species exploitation, many insects hijack plant development to induce novel plant organs called galls that provide the insect with a source of nutrition and a temporary home. Galls result from dramatic reprogramming of plant cell biology driven by insect molecules, but the roles of specific insect molecules in gall development have not yet been determined. Here we study the aphid Hormaphis cornu, which makes distinctive "cone" galls on leaves of witch hazel Hamamelis virginiana. We found that derived genetic variants in the aphid gene determinant of gall color (dgc) are associated with strong downregulation of dgc transcription in aphid salivary glands, upregulation in galls of seven genes involved in anthocyanin synthesis, and deposition of two red anthocyanins in galls. We hypothesize that aphids inject DGC protein into galls, and that this results in differential expression of a small number of plant genes. Dgc is a member of a large, diverse family of novel predicted secreted proteins characterized by a pair of widely spaced cysteine-tyrosine-cysteine (CYC) residues, which we named BICYCLE proteins. Bicycle genes are most strongly expressed in the salivary glands specifically of galling aphid generations, suggesting that they may regulate many aspects of gall development. Bicycle genes have experienced unusually frequent diversifying selection, consistent with their potential role controlling gall development in a molecular arms race between aphids and their host plants. One Sentence SummaryAphid bicycle genes, which encode diverse secreted proteins, contribute to plant gall development.

genetics↗

bioRxiv2019

The yellow gene influences Drosophila male mating success through sex comb melanization

Drosophila melanogaster males perform a series of courtship behaviors that, when successful, result in copulation with a female. For over a century, mutations in the yellow gene, named for its effects on pigmentation, have been known to reduce male mating success. Prior work has suggested that yellow influences mating behavior through effects on wing extension, song, and/or courtship vigor. Here, we rule out these explanations, as well as effects on the nervous system more generally, and find instead that the effects of yellow on male mating success are mediated by its effects on pigmentation of male-specific leg structures called sex combs. Loss of yellow expression in these modified bristles reduces their melanization, which changes their structure and causes difficulty grasping females prior to copulation. These data illustrate why the mechanical properties of anatomy, and not just neural circuitry, must be considered to fully understand the development and evolution of behavior.

animal behavior and cognition↗