Biology subjects

Clements, J.

Publications and source records attributed to Clements, J..

At least 19 recordsLinked to original sources

bioRxiv2025

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↗

bioRxiv2025

HortaCloud: An Open and Collaborative Platform for Whole Brain Neuronal Reconstructions

HortaCloud is a cloud-based, open-source platform designed to facilitate the collaborative reconstruction of long-range projection neurons from whole-brain light microscopy data. By providing virtual environments directly within the cloud, it eliminates the need for costly and time-consuming data downloads, allowing researchers to work efficiently with terabyte-scale volumetric datasets. Standardization of computational resources in the cloud make deployment easier and more predictable. The pay-as-you-go cloud model reduces adoption barriers by eliminating upfront investments in expensive hardware. Finally, HortaClouds decentralized architecture enables global collaboration between researchers and between institutions.

neuroscience↗

bioRxiv2024

Connectomic Analysis of Mitochondria in the Central Brain of Drosophila

Mitochondria are integral to the metabolism and cell biology of a neuron. Electron microscopy images of fly brain volumes, taken for connectomics, can be analyzed for mitochondria as well as the cells and synapses already reported. Here, from the Drosophila Hemibrain connectome dataset, we extract, classify, and measure approximately 6 million mitochondria, with the majority located among more than 20 thousand neurons and over 5500 cell types. Each mitochondrion is annotated with its location, orientation, voxel size, and appearance (dark and dense, light and sparse, or medium), and each synapse is linked to its closest mitochondrion. Using these data, we show how the most basic characteristics of mitochondria--volume, distance from synapses, and appearance--vary considerably between cell types and between brain regions. Mitochondria are larger and closer at presynapses than at postsynapses, and presynapses typically have a mitochondrion within one micron. However, cells important for learning and memory, Kenyon cells, have unusually small and sparse mitochondria that are placed with unusual precision near only half of presynapses. We find that mitochondria occupy a greater fraction of cell volume in inhibitory neurons than excitatory cells, dopaminergic neurons have a distinct synaptic positioning of mitochondria, and that glutamatergic neurons have a high fraction of mitochondria with a light appearance. We also find that synapses with more postsynaptic partners have larger presynaptic mitochondria and more distant postsynaptic mitochondria. Finally, we have extended the data model of our public web interface, neuPrint, to record our mitochondria data as searchable subcellular components of neurons in a connectomic database. These results indicate wide-ranging principles for how mitochondrial organization varies by cell type in a dataset of unprecedented size and coverage.

neuroscience↗

bioRxiv2024

Connectome-driven neural inventory of a complete visual system

Vision provides animals with detailed information about their surroundings, conveying diverse features such as color, form, and movement across the visual scene. Computing these parallel spatial features requires a large and diverse network of neurons, such that in animals as distant as flies and humans, visual regions comprise half the brains volume. These visual brain regions often reveal remarkable structure-function relationships, with neurons organized along spatial maps with shapes that directly relate to their roles in visual processing. To unravel the stunning diversity of a complex visual system, a careful mapping of the neural architecture matched to tools for targeted exploration of that circuitry is essential. Here, we report a new connectome of the right optic lobe from a male Drosophila central nervous system FIB-SEM volume and a comprehensive inventory of the flys visual neurons. We developed a computational framework to quantify the anatomy of visual neurons, establishing a basis for interpreting how their shapes relate to spatial vision. By integrating this analysis with connectivity information, neurotransmitter identity, and expert curation, we classified the [~]53,000 neurons into 727 types, about half of which are systematically described and named for the first time. Finally, we share an extensive collection of split-GAL4 lines matched to our neuron type catalog. Together, this comprehensive set of tools and data unlock new possibilities for systematic investigations of vision in Drosophila, a foundation for a deeper understanding of sensory processing.

neuroscience↗

bioRxiv2023

A Connectome of the Male Drosophila Ventral Nerve Cord

Animal behavior is principally expressed through neural control of muscles. Therefore understanding how the brain controls behavior requires mapping neuronal circuits all the way to motor neurons. We have previously established technology to collect large-volume electron microscopy data sets of neural tissue and fully reconstruct the morphology of the neurons and their chemical synaptic connections throughout the volume. Using these tools we generated a dense wiring diagram, or connectome, for a large portion of the Drosophila central brain. However, in most animals, including the fly, the majority of motor neurons are located outside the brain in a neural center closer to the body, i.e. the mammalian spinal cord or insect ventral nerve cord (VNC). In this paper, we extend our effort to map full neural circuits for behavior by generating a connectome of the VNC of a male fly.

neuroscience↗

bioRxiv2023

PEELing: an integrated and user-centric platform for cell-surface proteomics analysis

SummaryMolecular compartmentalization is vital for cellular physiology. Spatially-resolved proteomics allows biologists to survey protein composition and dynamics with subcellular resolution. Here we present PEELing, an integrated package and user-friendly web service for analyzing spatially- resolved proteomics data. PEELing assesses data quality using curated or user-defined references, performs cutoff analysis to remove contaminants, connects to databases for functional annotation, and generates data visualizations--providing a streamlined and reproducible workflow to explore spatially-resolved proteomics data. Availability and ImplementationPEELing and its tutorial are publicly available at https://peeling.janelia.org/. A Python package of PEELing is available at https://github.com/JaneliaSciComp/peeling/. ContactTechnical support for PEELing: peeling@janelia.hhmi.org.

systems biology↗

bioRxiv2022

NeuronBridge: an intuitive web application for neuronal morphology search across large data sets

Neuroscience research in Drosophila is benefiting from large-scale connectomics efforts using electron microscopy (EM) to reveal all the neurons in a brain and their connections. In order to exploit this knowledge base, researchers target individual neurons and study their function. Therefore, vast libraries of fly driver lines expressing fluorescent reporter genes in sets of neurons have been created and imaged using confocal light microscopy (LM). However, creating a fly line for driving gene expression within a single neuron found in the EM connectome remains a challenge, as it typically requires identifying a pair of fly lines where only the neuron of interest is expressed in both. This task and other emerging scientific workflows require finding similar neurons across large data sets imaged using different modalities. Here, we present NeuronBridge, a web application for easily and rapidly finding putative morphological matches between large datasets of neurons imaged using different modalities. We describe the functionality and construction of the NeuronBridge service, including its user-friendly GUI, data model, serverless cloud architecture, and massively parallel image search engine. NeuronBridge is openly accessible at http://neuronbridge.janelia.org/.

neuroscience↗

bioRxiv2022

Sharp cell-type-identity changes differentiate the retrosplenial cortex from the neocortex

The laminae of the neocortex are fundamental processing layers of the mammalian brain. Notably, such laminae are believed to be relatively stereotyped across short spatial scales, such that shared laminae between nearby brain regions exhibit similar constituent cells. Here, we considered a potential exception to this rule by studying the retrosplenial cortex (RSC), a brain region known for sharp cytoarchitectonic differences across its granular-dysgranular border. Using a variety of transcriptomics techniques, we identified, spatially mapped, and interpreted the excitatory cell-type landscape of the mouse RSC. In doing so, we surprisingly uncovered that RSC gene expression and cell types change sharply at the granular-dysgranular border. Additionally, supposedly homologous laminae between the RSC and neocortex are effectively wholly distinct in their cell-type composition. In collection, the RSC exhibits a variety of intrinsic cell-type specializations, and embodies a new neocortical organizational principle wherein cell-type identities vary sharply within and between brain regions.

neuroscience↗

bioRxiv2022

Genome-wide analysis identifies Homothorax and Extradenticle as regulators of insulin in Drosophila Insulin-Producing cells

Drosophila Insulin-Producing Cells (IPCs) are the main production site of the Drosophila Insulin-like peptides or Dilps which have key roles in regulating growth, development, reproduction, lifespan and metabolism. To better understand the signalling pathways and transcriptional networks that are active in the IPCs we queried publicly available transcriptome data of over 180 highly inbred fly lines for dilp expression and used this as the input for a Genome-wide association study (GWAS). This resulted in the identification of variants in 125 genes that were associated with variation in dilp expression. The function of 57 of these genes in the IPCs was tested using an RNAi-based approach. We found that IPC-specific depletion of most genes resulted in differences in expression of one or more of the dilps. We then elaborated further on homothorax, one of the candidate genes with the strongest effect on dilp expression. We found that Homothorax and its binding partner Extradenticle are involved in regulating dilp2, -3 and -5 expression and that genetic depletion of both transcription factors leads to phenotypes associated with reduced insulin signalling. Furthermore, we provide evidence that other transcription factors involved in eye development are also functional in the IPCs. In conclusion, we showed that this GWAS approach using gene expression levels as input identified genetic regulators implicated in IPC function and dilp expression.

genetics↗

bioRxiv2022

Detection of bifenthrin, bifenazate, etoxazole resistance in Tetranychus urticae collected from mint fields and hop yards using targeted sequencing and TaqMan approaches

Tetranychus urticae (Koch) is an economically important pest of many agricultural commodities in the Pacific Northwest. Multiple miticides are currently registered for control including abamectin, bifenazate, bifenthrin, and extoxazole. However, populations of Tetranychus urticae have developed miticide resistance through multiple mechanisms, in many different growing regions. Producers of agricultural commodities where Tetranychus urticae infestations are problematic rely on integrated pest management tools to determine optimal control methods. Within this species multiple single nucleotide polymorphisms have been documented in different genes which are associated with miticide resistance phenotypes. The detection of these mutations through TaqMan qPCR has been suggested as a practical, quick, and reliable tool to inform agricultural producers of miticide resistance phenotypes present within their fields and have potential utility for making appropriate miticide application and integrated pest management decisions. Within this investigation we examined the use of a TaqMan qPCR-based approach to determine miticide resistance genotypes in field-collected populations of Tetranychus urticae from mint fields and hop yards in the Pacific Northwest of the United States and confirmed the results with a multiplex targeted sequencing. The results suggest the TaqMan approach accurately genotypes Tetranychus urticae populations collected from agricultural fields. The interpretation of the results, however, provide additional challenges for integrated pest management practitioners, including making miticide application recommendations where populations of Tetranychus urticae are a mix of resistant and wildtype individuals.

ecology↗

bioRxiv2022

Examining historical rates of leafcutting bee cell pathogens to establish baseline infectivity rates for alfalfa seed growers

The alfalfa leafcutting bee (Megachile rotundata) is one of the primary pollinators for the alfalfa seed industry. The alfalfa leafcutting bee is a solitary cavity nesting bee. Female Megachile rotundata bees will construct and provision individual brood cells lined with cut leaves (cocoon) and will gather nectar and pollen to place within the constructed cocoon. The female bee will lay a single egg within the constructed cocoon and leave the egg to undergo larval stage development and pupation into the adult stage. During this time multiple pathogens and parasitoids can prey on the developing larvae, resulting in the loss of the future adult bee. A major concern for commercial alfalfa seed growers is the presence of invertebrate pests and fugal pathogens. In the present study, we used historical data from the Parma Cocoon Diagnostic Laboratory to determine baseline rates of pathogen and parasite infection of Megachile rotundata cells and used this analysis to determine historical infection rates and cutoffs for management practices. Additionally, using a Faxitron (X-ray) analysis for Megachile rotundata cell obtained in 2020, we compared the presence of chalkbrood, pathogens, and parasitoids in samples collected from both growers stocks and newly purchased Canada bees. The results of the investigation demonstrate historical averages of the presence of chalkbrood, pathogens, and parasitoids. We also show a significant increase in chalkbrood and predators in 2007-2011 and a significant difference in chalkbrood and predators between bee samples obtained from Canada and grower stocks.

ecology↗

bioRxiv2022

Multiplex PCR reveals unique trends in pathogen and parasitoid infestations of alfalfa leafcutting brood cells.

The alfalfa leafcutting bee Megachile rotundata Fabricius (HYMENOPTERA: Megachilidae) is an important pollinator for multiple agricultural seed commodities in the United States. Megachile rotundata is a solitary bee that forms brood cocoons where its larvae can develop. During the developmental stages of growth, broods can be preyed upon by multiple different fungal and bacterial pathogens and insect predators and parasitoids, resulting in the loss of the developing larvae. Larval loss is a major concern for alfalfa (Medicago sativa L.) seed producers because they rely on pollinator services provided by Megachile rotundata and reduced pollination rates result in lower yields and increased production costs. In the present study, we examined the taxonomic composition of organisms found within M. rotundata brood cells using a multiplex PCR assay which was developed for the detection of the most common bacterial, fungal, and invertebrate pests and pathogens of M. rotundata larvae. Known pests of M. rotundata were detected, including members of the fungal genus Ascosphaera, the causative agent of chalkbrood. Co-infection of single brood cells by multiple Ascosphaera species was confirmed, with potential implications for chalkbrood disease management. The multiplex assay also identified DNA from more than 2,400 total species including multiple new predators and pathogenetic species not previously documented in associated with M. rotundata brood cells.

ecology↗

bioRxiv2021

Spatially patterned excitatory neuron subtypes and circuits within the claustrum

The claustrum is a functionally and structurally complex brain region, whose very spatial extent remains debated. Histochemical-based approaches typically treat the claustrum as a relatively narrow region that primarily projects to the neocortex, whereas circuit-based approaches suggest a broader region embedding neocortical and other neural circuits. Here, we took a bottom-up, cell-type-specific approach to complement and possibly unite these seemingly disparate conclusions. Using single-cell RNA-sequencing, we found that the claustrum is comprised of two excitatory neuron subtypes that are differentiable from the surrounding cortex. Multicolor retrograde tracing in conjunction with 12-channel multiplexed in situ hybridization revealed a core-shell spatial arrangement of these subtypes, as well as differential projection targets. Thus, the claustrum is comprised of excitatory neuron subtypes with distinct molecular and circuit properties, whose spatial patterns reflect the narrower and broader claustral extents debated in previous research. This subtype-specific heterogeneity likely shapes the functional complexity of the claustrum.

neuroscience↗

bioRxiv2020

Automatic whole cell organelle segmentation in volumetric electron microscopy

Cells contain hundreds of different organelle and macromolecular assemblies intricately organized relative to each other to meet any cellular demands. Obtaining a complete understanding of their organization is challenging and requires nanometer-level, threedimensional reconstruction of whole cells. Even then, the immense size of datasets and large number of structures to be characterized requires generalizable, automatic methods. To meet this challenge, we developed an analysis pipeline for comprehensively reconstructing and analyzing the cellular organelles in entire cells imaged by focused ion beam scanning electron microscopy (FIB-SEM) at a near-isotropic size of 4 or 8 nm per voxel. The pipeline involved deep learning architectures trained on diverse samples for automatic reconstruction of 35 different cellular organelle classes - ranging from endoplasmic reticulum to microtubules to ribosomes - from multiple cell types. Automatic reconstructions were used to directly quantify various previously inaccessible metrics about these structures, including their spatial interactions. We show that automatic organelle reconstructions can also be used to automatically register light and electron microscopy images for correlative studies. We created an open data and open source web repository, OpenOrganelle, to share the data, computer code, and trained models, enabling scientists everywhere to query and further reconstruct the datasets.

cell biology↗

bioRxiv2020

Candidatus (Ca.) phytoplasma asteris subgroups display distinct disease progression dynamics during the carrot growing season

Aster Yellows phytoplasma (AYp; Candidatus (Ca.) Phytoplasma asteris) is an obligate bacterial pathogen that is the causative agent of multiple diseases in herbaceous plants. While this phytoplasma has been examined in depth for its disease characteristics, knowledge about the spatial and temporal dynamics of pathogen spread is lacking. The phytoplasma is found in plants phloem and is vectored by leafhoppers (Cicadellidae: Hemiptera), including the aster leafhopper, Macrosteles quadrilineatus Forbes. The aster leafhopper is a migratory insect pest that overwinters in the southern United States, and historical data suggest these insects migrate from southern overwintering locations to northern latitudes annually, transmitting and driving phytoplasma infection rates as they migrate. A more in-depth understanding of the spatial, temporal and genetic determinants of Aster Yellows disease progress will lead to better integrated pest management strategies for Aster Yellows disease control. Carrot, Daucus carota L., plots were established at two planting densities in central Wisconsin and monitored during the 2018 growing season for Aster Yellows disease progression. Symptomatic carrots were sampled and assayed for the presence of the Aster Yellows phytoplasma. Aster Yellows disease progression was determined to be significantly associated with calendar date, crop density, location within the field, and phytoplasma subgroup.

ecology↗

bioRxiv2020

An image resource of subdivided Drosophila GAL4-driver expression patterns for neuron-level searches

Precise, repeatable genetic access to specific neurons via GAL4/UAS and related methods is a key advantage of Drosophila neuroscience. Neuronal targeting is typically documented using light microscopy of full GAL4 expression patterns, which generally lack the single-cell resolution required for reliable cell type identification. Here we use stochastic GAL4 labeling with the MultiColor FlpOut approach to generate cellular resolution confocal images at large scale. We are releasing aligned images of 74,000 such adult central nervous systems. An anticipated use of this resource is to bridge the gap between neurons identified by electron or light microscopy. Identifying individual neurons that make up each GAL4 expression pattern improves the prediction of split-GAL4 combinations targeting particular neurons. To this end we have made the images searchable on the NeuronBridge website. We demonstrate the potential of NeuronBridge to rapidly and effectively identify neuron matches based on morphology across imaging modalities and datasets.

neuroscience↗

bioRxiv2020

A Connectome and Analysis of the Adult Drosophila Central Brain

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the flys brain.

bioinformatics↗

bioRxiv2020

A Connectome of the Adult Drosophila Central Brain

The neural circuits responsible for behavior remain largely unknown. Previous efforts have reconstructed the complete circuits of small animals, with hundreds of neurons, and selected circuits for larger animals. Here we (the FlyEM project at Janelia and collaborators at Google) summarize new methods and present the complete circuitry of a large fraction of the brain of a much more complex animal, the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses, and proofread such large data sets; new methods that define cell types based on connectivity in addition to morphology; and new methods to simplify access to a large and evolving data set. From the resulting data we derive a better definition of computational compartments and their connections; an exhaustive atlas of cell examples and types, many of them novel; detailed circuits for most of the central brain; and exploration of the statistics and structure of different brain compartments, and the brain as a whole. We make the data public, with a web site and resources specifically designed to make it easy to explore, for all levels of expertise from the expert to the merely curious. The public availability of these data, and the simplified means to access it, dramatically reduces the effort needed to answer typical circuit questions, such as the identity of upstream and downstream neural partners, the circuitry of brain regions, and to link the neurons defined by our analysis with genetic reagents that can be used to study their functions. Note: In the next few weeks, we will release a series of papers with more involved discussions. One paper will detail the hemibrain reconstruction with more extensive analysis and interpretation made possible by this dense connectome. Another paper will explore the central complex, a brain region involved in navigation, motor control, and sleep. A final paper will present insights from the mushroom body, a center of multimodal associative learning in the fly brain.

neuroscience↗