Search bioRxiv⌕ Search

Biology subjects

Pleijzier, M. W.

Publications and source records attributed to Pleijzier, M. W..

8 recordsLinked to original sources

Structured Connectivity Across Multiple Drosophila Mushroom Bodies

Learning and memory depend on plasticity within neural circuits, but the extent to which the underlying architecture of memory networks is stereotyped or structured remains unclear. Random connectivity may maximise stimulus discrimination, whereas structured connectivity could preferentially route behaviourally relevant information. Here, we compare five adult Drosophila melanogaster Mushroom Body (MB) hemispheres across three connectomes and establish a unified cross-connectome framework for uniglomerular projection neurons (uPNs), Kenyon Cells (KCs), Mushroom Body Output Neurons (MBONs) and Lateral Horn Centrifugal Neurons (LHCENTs). Despite variation in KC abundance and fine-scale connectivity, we identify reproducible organisation across the uPN[->]KC and KC[->]MBON pathways. Food-associated uPN channels consistently contact a greater proportion of KCs than expected by chance, and this bias is preferentially routed through KCs towards approach-promoting MBONs. Sensory input also remains stereotyped across sister MBONs from the same hemisphere despite variation in their individual KC partners. Finally, recurrent LHCENT feedback (predicted-inhibitory) preferentially targets KCs receiving these food-associated inputs. Together, these findings show that a memory network can accommodate local variability while preserving structured pathways that prioritise ethologically relevant sensory information.

neuroscience↗

Sexual dimorphism in the complete connectome of the Drosophila male central nervous system

Sex differences in behaviour exist across all animals, typically under strong genetic regulation. In Drosophila, fruitless/doublesex transcription factors can identify dimorphic neurons but their organisation into functional circuits remains unclear. We present the connectome of the entire Drosophila male central nervous system. This contains 166,691 neurons spanning the brain and nerve cord, fully proofread and annotated including fruitless/doublesex expression and 11,691 types. We provide the first comprehensive comparison between male and female brain connectomes to synaptic resolution, finding 7,205 isomorphic, 114 dimorphic, 262 male-specific and 69 female-specific types. This resource enables analysis of full sensory-to-motor circuits underlying complex behaviours and the impact of dimorphic elements. Sex-specific/dimorphic neurons are concentrated in higher brain centres while the sensory and motor periphery are largely isomorphic. Within higher centres, male-specific connections are organised into hotspots defined by male-specific neurons or arbours. Numerous circuit switches reroute sensory information to form antagonistic circuits controlling opposing behaviours.

neuroscience↗

A consensus cell type atlas from multiple connectomes reveals principles of circuit stereotypy and variation

The fruit fly Drosophila melanogaster combines surprisingly sophisticated behaviour with a highly tractable nervous system. A large part of the flys success as a model organism in modern neuroscience stems from the concentration of collaboratively generated molecular genetic and digital resources. As presented in our FlyWire companion paper1, this now includes the first full brain connectome of an adult animal. Here we report the systematic and hierarchical annotation of this [~]130,000-neuron connectome including neuronal classes, cell types and developmental units (hemilineages). This enables any researcher to navigate this huge dataset and find systems and neurons of interest, linked to the literature through the Virtual Fly Brain database2. Crucially, this resource includes 4,552 cell types. 3,094 are rigorous consensus validations of cell types previously proposed in the "hemibrain" connectome3. In addition, we propose 1,458 new cell types, arising mostly from the fact that the FlyWire connectome spans the whole brain, whereas the hemibrain derives from a subvolume. Comparison of FlyWire and the hemibrain showed that cell type counts and strong connections were largely stable, but connection weights were surprisingly variable within and across animals. Further analysis defined simple heuristics for connectome interpretation: connections stronger than 10 unitary synapses or providing >1% of the input to a target cell are highly conserved. Some cell types showed increased variability across connectomes: the most common cell type in the mushroom body, required for learning and memory, is almost twice as numerous in FlyWire as the hemibrain. We find evidence for functional homeostasis through adjustments of the absolute amount of excitatory input while maintaining the excitation-inhibition ratio. Finally, and surprisingly, about one third of the cell types proposed in the hemibrain connectome could not yet be reliably identified in the FlyWire connectome. We therefore suggest that cell types should be defined to be robust to inter-individual variation, namely as groups of cells that are quantitatively more similar to cells in a different brain than to any other cell in the same brain. Joint analysis of the FlyWire and hemibrain connectomes demonstrates the viability and utility of this new definition. Our work defines a consensus cell type atlas for the fly brain and provides both an intellectual framework and open source toolchain for brain-scale comparative connectomics.

neuroscience↗

Diversification of neuropil organization in specialized and broadly tuned olfactory glomerular circuits in Drosophila melanogaster

In the Drosophila olfactory system most odorants are encoded in the antennal lobe in a combinatory way, activating several glomerular circuits. However, odorants of particular ecological role for the fly are encoded through activation of a single specialized olfactory pathway. Comparative analyses of densely reconstructed connectomes of one broadly tuned glomerulus (DL5) and one narrowly tuned glomerulus (DA2) gained detailed insight into the variations of synaptic circuitries of glomeruli with different computational tasks. Our approach combined laser-branding of glomeruli of interest with volume based focused ion beam-scanning electron microscopy (FIB-SEM) to enable precise targeting and analysis of the two glomeruli. We discovered differences in their neuronal innervation, synaptic composition and specific circuit diagrams of their major cell types: olfactory sensory neurons (OSNs), uniglomerular projection neurons (uPNs) and multiglomerular neurons (MGNs). By comparing our data with a previously mapped narrowly tuned glomerulus (VA1v), we identified putative generic features of narrowly tuned glomerular circuits, including higher density of neuronal fibers and synapses, lower degree of OSN lateralization, stronger axo-axonic connections between OSNs, dendro-dendritic connections between many uPNs, and lower degree of presynaptic input on OSN axons. In addition, this work revealed that the dendrites of the single uPN in DL5 contain a substantial amount of autapses interconnecting distant regions of the dendritic tree. The comparative analysis of glomeruli allows to formulate synaptic motifs implemented in olfactory circuits with different computational demands.

neuroscience↗

The connectome of the adult Drosophila mushroom body: implications for function

Making inferences about the computations performed by neuronal circuits from synapse-level connectivity maps is an emerging opportunity in neuroscience. The mushroom body (MB) is well positioned for developing and testing such an approach due to its conserved neuronal architecture, recently completed dense connectome, and extensive prior experimental studies of its roles in learning, memory and activity regulation. Here we identify new components of the MB circuit in Drosophila, including extensive visual input and MB output neurons (MBONs) with direct connections to descending neurons. We find unexpected structure in sensory inputs, in the transfer of information about different sensory modalities to MBONs, and in the modulation of that transfer by dopaminergic neurons (DANs). We provide insights into the circuitry used to integrate MB outputs, connectivity between the MB and the central complex and inputs to DANs, including feedback from MBONs. Our results provide a foundation for further theoretical and experimental work.

neuroscience↗

Input connectivity reveals additional heterogeneity of dopaminergic reinforcement in Drosophila

Different types of Drosophila dopaminergic neurons (DANs) reinforce memories of unique valence and provide state-dependent motivational control [1]. Prior studies suggest that the compartment architecture of the mushroom body (MB) is the relevant resolution for distinct DAN functions [2, 3]. Here we used a recent electron microscope volume of the fly brain [4] to reconstruct the fine anatomy of individual DANs within three MB compartments. We find the 20 DANs of the {gamma}5 compartment, at least some of which provide reward teaching signals, can be clustered into 5 anatomical subtypes that innervate different regions within {gamma}5. Reconstructing 821 upstream neurons reveals input selectivity, supporting the functional relevance of DAN sub-classification. Only one PAM-{gamma}5 DAN subtype {gamma}5(fb) receives direct recurrent input from {gamma}5{beta}2a mushroom body output neurons (MBONs) and behavioral experiments distinguish a role for these DANs in memory revaluation from those reinforcing sugar memory. Other DAN subtypes receive major, and potentially reinforcing, inputs from putative gustatory interneurons or lateral horn neurons, which can also relay indirect feedback from MBONs. We similarly reconstructed the single aversively reinforcing PPL1-{gamma}1pedc DAN. The {gamma}1pedc DAN inputs mostly differ from those of {gamma}5 DANs and they cluster onto distinct dendritic branches, presumably separating its established roles in aversive reinforcement and appetitive motivation [5, 6]. Tracing also identified neurons that provide broad input to {gamma}5, {beta}2a and {gamma}1pedc DANs suggesting that distributed DAN populations can be coordinately regulated. These connectomic and behavioral analyses therefore reveal further complexity of dopaminergic reinforcement circuits between and within MB compartments. HighlightsO_LINanoscale anatomy reveals additional subtypes of rewarding dopaminergic neurons. C_LIO_LIConnectomics reveals extensive input specificity to subtypes of dopaminergic neurons. C_LIO_LIAxon morphology implies dopaminergic neurons provide subcompartment-level function. C_LIO_LIUnique dopaminergic subtypes serve aversive memory extinction and sugar learning. C_LI

neuroscience↗

Connectomics analysis reveals first, second, and third order thermosensory and hygrosensory neurons in the adult Drosophila brain

Animals exhibit innate and learned preferences for temperature and humidity - conditions critical for their survival and reproduction. Here, we leveraged a whole adult brain electron microscopy volume to study the circuitry associated with antennal thermosensory and hygrosensory neurons, which target specific ventroposterior (VP) glomeruli in the Drosophila melanogaster antennal lobe. We have identified two new VP glomeruli, in addition to the five known ones, and the projection neurons (VP PNs) that relay VP information to higher brain centres, including the mushroom body and lateral horn, seats of learned and innate olfactory behaviours, respectively. Focussing on the mushroom body lateral accessory calyx (lACA), a known thermosensory neuropil, we present a comprehensive connectome by reconstructing neurons downstream of heating- and cooling-responsive VP PNs. We find that a few lACA-associated mushroom body intrinsic neurons (Kenyon cells) solely receive thermosensory inputs, while most receive additional olfactory and thermo- or hygrosensory PN inputs in the main calyx. Unexpectedly, we find several classes of lACA-associated neurons that form a local network with outputs to other brain neuropils, suggesting that the lACA serves as a general hub for thermosensory circuitry. For example, we find DN1 pacemaker neurons that link the lACA to the accessory medulla, likely mediating temperature-based entrainment of the circadian clock. Finally, we survey strongly connected downstream partners of VP PNs across the protocerebrum; these include a descending neuron that receives input mainly from dry-responsive VP PNs, meaning that just two synapses might separate hygrosensory inputs from motor neurons in the nerve cord. (249) HIGHLIGHTSO_LITwo novel thermo/hygrosensory glomeruli in the fly antennal lobe C_LIO_LIFirst complete set of thermosensory and hygrosensory projection neurons C_LIO_LIFirst connectome for a thermosensory centre, the lateral accessory calyx C_LIO_LINovel third order neurons, including a link to the circadian clock C_LI

neuroscience↗

A Toolbox for Discrete Modelling of Cell Signalling Dynamics

In an age where the volume of data regarding biological systems exceeds our ability to analyse it, many researchers are looking towards systems biology and computational modelling to help unravel the complexities of gene and protein regulatory networks. In particular, the use of discrete modelling allows generation of signalling networks in the absence of full quantitative descriptions of systems, which are necessary for ordinary differential equation (ODE) models. In order to make such techniques more accessible to mainstream researchers, tools such as the BioModelAnalyzer (BMA) have been developed to provide a user-friendly graphical interface for discrete modelling of biological systems. Here we use the BMA to build a library of discrete target functions of known canonical molecular interactions, translated from ordinary differential equations (ODEs). We then show that these BMA target functions can be used to reconstruct complex networks, which can correctly predict many known genetic perturbations. This new library supports the accessibility ethos behind the creation of BMA, providing a toolbox for the construction of complex cell signalling models without the need for extensive experience in computer programming or mathematical modelling, and allows for construction and simulation of complex biological systems with only small amounts of quantitative data.\n\nAUTHOR SUMMARYOrdinary differential equation (ODE) based models are a popular approach for modelling biological networks. A limitation of ODE models is that they require complete networks and detailed kinetic parameterisation. An alternative is the use of discrete, executable models, in which nodes are assigned discrete value ranges, and the relationship between them defined with simple mathematical operations. One tool for constructing such models is the BioModelAnalyzer (BMA), an open source and publicly available (https://www.biomodelanalyzer.org) software, aimed to be fully usable by researchers without extensive computational or mathematical experience. A fundamental question for executable models is whether the high level of abstraction substantially reduces expressivity relative to continuous approaches. Here, we present a canonical library of biological signalling motifs, initially defined by Tyson et al (2003), translated for the first time into the BMA. We show that; 1) these motifs are easily and fully translatable from continuous to discrete models, 2) Combining these motifs in a computationally naive way generates a fully functional and predictive model of the yeast cell cycle.

systems biology↗