Biology subjects

Heinze, S.

Publications and source records attributed to Heinze, S..

12 recordsLinked to original sources

bioRxiv2026

Deep conservation of head direction circuits in bees, ants and flies

To navigate, animal brains must continuously estimate the bodys heading in space and compare it with internal goals to guide movement. In the fruit fly Drosophila melanogaster a neural circuit in the central complex of the brain serves as an internal compass, exploiting a network architecture called a ring attractor1, 2. While this region is highly conserved and involved in navigation in many insects3, 4, it remains unclear whether the fly circuit represents a general blueprint for head direction computation, or whether different ecologies have driven distinct circuit solutions. Using synaptic-resolution circuit mapping, we identified homologous head direction networks in bees and ants and compared them to the fly circuit. We show that the insect head direction network is conserved across at least 300 million years of evolution. At the level of cell types and projection patterns, all studied species share a nearly identical neural layout, both qualitatively and quantitatively. At the synaptic level, however, the fly and bee circuits differed fundamentally. The distinct wiring principles of homologous neurons expose highly evolvable elements within this otherwise stable circuit. Using these differences in circuit architecture to constrain computational models, we show that both the bee and fly circuits can effectively function as ring attractors with similar, yet distinct, properties. These results demonstrate that complex neural circuits can remain stable over many hundreds of millions of years, while still offering access points for evolution to flexibly adjust neural computations to changing ecological demands, illustrating how evolution balances stability and flexibility in brain circuits.

neuroscience↗

bioRxiv2026

A multi-resolution imaging and analysis pipeline for comparative circuit reconstruction in insects

Connectomics has become essential for the study of brain function, yet for most research groups it remains prohibitively costly in imaging time, data storage, and analysis. Here, we present an imaging, processing, and analysis pipeline for multi-resolution image acquisition and circuit reconstruction. Applied to the central complex of six insect species, we were able to obtain global projectomes at cellular resolution (40-50 nm) with embedded local connectomes describing key computational compartments at synaptic resolution (8-12 nm). We provide standardized protocols for volume EM sample preparation, image acquisition and image alignment, combined with existing methods for {micro}CT block trimming, automatic segmentation, synapse detection, collaborative skeleton tracing with CATMAID, and segmentation proofreading via CAVE. We validated our workflow by reconstructing head direction cells across all six insect species, which revealed deep conservation at the level of cell types, cell numbers and projection patterns, while also revealing circuit level specializations. Overall, our pipeline democratizes comparative connectomics by making this method accessible for small research groups with modest resources.

neuroscience↗

bioRxiv2022

Parallel motion vision pathways in the brain of a tropical bee

Spatial orientation is a prerequisite for most behaviors. In insects, the underlying neural computations take place in the central complex (CX), the brains navigational center. In this region different streams of sensory information converge to enable context-dependent navigational decisions. Accordingly, a variety of CX input neurons deliver information about different navigation-relevant cues. In bees, direction encoding polarized light signals converge with translational optic flow signals that are suited to encode the flight speed of the animals. The continuous integration of speed and directions in the CX can be used to generate a vector memory of the bees current position in space in relation to its nest, i.e. perform path integration. This process depends on specific, complex features of the optic flow encoding CX input neurons, but it is unknown how this information is derived from the visual periphery. Here, we thus aimed at gaining insight into how simple motion signals are reshaped upstream of the speed encoding CX input neurons to generate their complex features. Using electrophysiology and anatomical analyses of the halictic bees Megalopta genalis and Megalopta centralis, we identified a wide range of motion-sensitive neurons connecting the optic lobes with the central brain. While most neurons formed pathways with characteristics incompatible with CX speed neurons, we showed that one group of lobula projection neurons possess some physiological and anatomical features required to generate the visual responses of CX optic-flow encoding neurons. However, as these neurons cannot explain all features of CX speed cells, local interneurons of the central brain or alternative input cells from the optic lobe are additionally required to construct inputs with sufficient complexity to deliver speed signals suited for path integration in bees.

neuroscience↗

bioRxiv2022

Bumblebees navigate using path integration while walking

Path integration is a computational strategy that allows an animal to maintain an internal estimate of its position relative to a point of origin. Many species use path integration to navigate back to specific locations, typically their homes, after lengthy and convoluted excursions. Hymenopteran insects are impressive path integrators, directly returning to their hives after hundreds of meters of outward travel. Recent neurobiological insights have established hypotheses for how path integration may be mediated by the brains of bees, but clear ways to test these hypotheses in the laboratory are currently unavailable. Here we report that the bumblebee, Bombus terrestris, uses path integration while walking over short distances in an indoor arena. They estimate accurate vector distances after displacement and orient by artificial celestial cues. Walking bumblebees also exhibited systematic search patterns when home vectors failed to lead them accurately back to the nest, closely resembling searches performed by other species in natural conditions. We thus provide a robust experimental system to test navigation behavior in the laboratory that reflects most aspects of natural path integration. Importantly, we established this assay in an animal that is both readily available and resilient to invasive manipulations. In the future, our behavioral assay therefore can be combined with current electrophysiological techniques, opening a path towards directly probing the neural basis of the sophisticated vector navigation abilities of bees.

animal behavior and cognition↗

bioRxiv2021

Protein shape sampled by ion mobility mass spectrometry consistently improves protein structure prediction

Among a wide variety of mass spectrometry (MS) methodologies available for structural characterizations of proteins, ion mobility (IM) provides structural information about protein shape and size in the form of an orientationally averaged collision cross-section (CCS). While IM data have been predominantly employed for the structural assessment of protein complexes, CCS data from IM experiments have not yet been used to predict tertiary structure from sequence. Here, we are showing that IM data can significantly improve protein structure determination using the modeling suite Rosetta. The Rosetta Projection Approximation using Rough Circular Shapes (PARCS) algorithm was developed that allows for fast and accurate prediction of CCS from structure. Following successful rigorous testing for accuracy, speed, and convergence of PARCS, an integrative modelling approach was developed in Rosetta to use CCS data from IM experiments. Using this method, we predicted protein structures from sequence for a benchmark set of 23 proteins. When using IM data, the predicted structure improved or remained unchanged for all 23 proteins, compared to the predicted models in the absence of CCS data. For 15/23 proteins, the RMSD (root-mean-square deviation) of the predicted model was less than 5.50 [A], compared to only 10/23 without IM data. We also developed a confidence metric that successfully identified near-native models in the absence of a native structure. These results demonstrate the ability of IM data in de novo structure determination.

biophysics↗

bioRxiv2021

A projectome of the bumblebee central complex

Insects have evolved diverse and remarkable strategies for navigating in various ecologies all over the world. Regardless of species, insects share the presence of a group of morphologically conserved neuropils known collectively as the central complex (CX). The CX is a navigational hub, involved in sensory integration and coordinated motor activity. Despite the fact that our understanding of navigational behavior comes predominantly from ants and bees, most of what we know about the underlying neural circuitry of such behavior comes from work in fruit flies. Here we aim to close this gap, by providing the first comprehensive map of all major columnar neurons and their projection patterns in the CX of a bee. We find numerous components of the circuit that appear to be highly conserved between the fly and the bee, but also highlight several key differences which are likely to have important functional ramifications.

neuroscience↗

bioRxiv2020

InsectBrainDatabase - A unified platform to manage, share, and archive morphological and functional data

Insect neuroscience generates vast amounts of highly diverse data, of which only a small fraction are findable, accessible and reusable, despite open data mandates by funding bodies. We have therefore developed the InsectBrainDatabase (IBdb), an open platform for depositing, sharing and managing a wide range of insect neuroanatomical and functional data. It facilities biological insight by enabling effective cross-species comparisons, by intimately linking data on structure and function, and by serving as hub for information on insect neuroethology. The IBdb provides novel visualization and search tools, which are also available in a unique private mode of the database, before data is made public. This allows users to manage and visualize unpublished data, creating a strong incentive for data contribution and eliminating additional effort when publicly depositing the data at a later stage. These design principles could also serve as a blueprint for similar databases in other fields.

neuroscience↗

bioRxiv2020

A neural model for insect steering applied to olfaction and path integration

Many animal behaviours require orientation and steering with respect to the environment. For insects, a key brain area involved in spatial orientation and navigation is the central complex. Activity in this neural circuit has been shown to track the insects current heading relative to its environment, and has also been proposed to be the substrate of path integration. However, it remains unclear how the output of the central complex is integrated into motor commands. Central complex output neurons project to the lateral accessory lobes (LAL), from which descending neurons project to thoracic motor centres. Here, we present a computational model of a simple neural network that has been described anatomically and physiologically in the LALs of male silkworm moths, in the context of odour-mediated steering. We present and analyze two versions of this network, both implemented in the Nengo framework, one rate-based and one based on spiking neurons. The modelled network consists of an inhibitory local interneuron and a bistable descending neuron ( flip-flop), which both receive input in the LAL. The flip-flop neuron projects onto neck motor neurons to induce steering. We show that this simple computational model not only replicates the basic parameters of male silkworm moth behaviour in a simulated odour plume, but can also take input from a computational model of path integration in the central complex and use it to steer back to a point of origin. Furthermore, we find that increasing the level of detail within the model improves the realism of the models behaviour. Our results suggest that descending neurons originating in the lateral accessory lobes, such as flip-flop neurons, are sufficient to mediate multiple steering behaviours. This study is therefore a first step to close the gap between orientation circuits in the central complex and downstream motor centres. Author summaryTargeted movements and steering within an environment are essential for many behaviours. In insects, the brains center for spatial orientation and navigation is the central complex, which processes information about the configuration of the local environment as well as global orientation cues such as the Sun position. Neural networks in the central complex also compute the insects heading direction, and are thought to be involved in generating steering commands. However, it is unclear how these steering commands are transmitted to downstream motor centers. Output neurons from the central complex project to the lateral accessory lobes, a neuropil which also gives rise to descending pre-motor neurons that are involved in steering in the silkworm moth Bombyx mori. In this study, we provide a computational model of a pre-motor neural network in the lateral accessory lobes. We show that this network can steer an agent towards the source of a simulated odor plume, but that it can also steer efficiently when getting input from an anatomically constrained network model of the central complex. This model is therefore a first step to close the gap between the central complex and thoracic motor circuits.

neuroscience↗

bioRxiv2019

The heading direction circuit of two insect species

Recent studies of the Central Complex in the brain of the fruit fly have identified neurons with activity that tracks the animals heading direction. These neurons are part of a neuronal circuit with dynamics resembling those of a ring attractor. Other insects have a homologous circuit sharing a generally similar topographic structure but with significant structural and connectivity differences. We model the connectivity patterns in two insect species to investigate the effect of the differences on the dynamics of the circuit. We illustrate that the circuit found in locusts can also operate as a ring attractor and identify differences that enable the fruit fly circuit to respond faster to heading changes while they render the locust circuit more tolerant to noise. Our findings demonstrate that subtle differences in neuronal projection patterns can have a significant effect on the circuit performance and emphasise the need for a comparative approach in neuroscience.

neuroscience↗

bioRxiv2019

The brain of a nocturnal migratory insect, the Australian Bogong moth

Every year, millions of Australian Bogong moths (Agrotis infusa) complete an astonishing journey: in spring, they migrate over 1000 km from their breeding grounds to the alpine regions of the Snowy Mountains, where they endure the hot summer in the cool climate of alpine caves. In autumn, the moths return to their breeding grounds, where they mate, lay eggs and die. These moths can use visual cues in combination with the geomagnetic field to guide their flight, but how these cues are processed and integrated in the brain to drive migratory behavior is unknown. To generate an access point for functional studies, we provide a detailed description of the Bogong moths brain. Based on immunohistochemical stainings against synapsin and serotonin (5HT), we describe the overall layout as well as the fine structure of all major neuropils, including the regions that have previously been implicated in compass-based navigation. The resulting average brain atlas consists of 3D reconstructions of 25 separate neuropils, comprising the most detailed account of a moth brain to date. Our results show that the Bogong moth brain follows the typical lepidopteran ground pattern, with no major specializations that can be attributed to their spectacular migratory lifestyle. These findings suggest that migratory behavior does not require widespread modifications of brain structure, but might be achievable via small adjustments of neural circuitry in key brain areas. Locating these subtle changes will be a challenging task for the future, for which our study provides an essential anatomical framework.

neuroscience↗

bioRxiv2019

A novel major output target for pheromone-sensitive projection neurons in male moths

The male-specific macroglomerular complex (MGC) in the moth antennal lobe contains circuitry dedicated to pheromone processing. Output neurons from this region project along three parallel pathways, the medial, mediolateral, and lateral tracts. The MGC-neurons of the lateral tract are least described and their functional significance is unknown. We used mass-staining, calcium imaging, and intracellular recording/staining to characterize the morphological and physiological properties of these neurons in Helicoverpa armigera. All lateral-tract MGC neurons targeted the column, a small region within the superior intermediate neuropil. We identified this region as the major converging site for lateral-tract neurons responsive to pheromones and plant-odors. The lateral-tract MGC-neurons consistently responded with a faster onset than the well-described medial-tract neurons. Different from the medial-tract MGC neurons encoding odor quality important for signal identification, those in the lateral tract seem to convey a robust and rapid, but fixed signal - potentially important for fast control of hard-wired behavior.

neuroscience↗

bioRxiv2019

Minimal effects of proto-Y chromosomes on house fly gene expression in spite of evidence that selection maintains stable polygenic sex determination

Sex determination is the developmental process by which organismal sex is established. Sex determination evolves fast, often due to changes in the master regulators at the top of the pathway. In addition, some species are polymorphic for multiple different master regulators within natural populations. Understanding the forces that maintain this polygenic sex determination can be informative of the factors that drive the evolution of sex determination. The house fly, Musca domestica, is a well-suited model to those ends because natural populations harbor male-determining loci on each of the six chromosomes and a bi-allelic female-determiner. Multiple lines of evidence suggest that natural selection maintains polygenic sex determination in house fly. However, previous work found that there are very few sequence differences between proto-Y chromosomes and their homologous X chromosomes. This suggests that there is not much genetic variation upon which natural selection could act to maintain polygenic sex determination in house fly. To address this paradox, we performed RNA-seq experiments that examine the effects of the two most common proto-Y chromosomes on gene expression. We find that the proto-Y chromosomes do indeed have a relatively minor effect on gene expression, as expected based on the minimal X-Y sequence differences. Despite these minimal gene expression differences, we identify some patterns that are consistent with sex-specific selection acting on phenotypic effects of proto-Y chromosomes. Our results suggest that, if natural selection maintains polygenic sex determination in house fly, the phenotypic differences under selection are minor and possibly depend on ecological contexts that were not tested in our experimental design.

genomics↗