Reconstruction of motor control circuits in adult Drosophila using automated transmission electron microscopy

To investigate circuit mechanisms underlying locomotor behavior, we used serial-section electron microscopy (EM) to acquire a synapse-resolution dataset containing the ventral nerve cord (VNC) of an adult female Drosophila melanogaster. To generate this dataset, we developed GridTape, a technology that combines automated serial-section collection with automated high-throughput transmission EM. Using this dataset, we studied neuronal networks that control leg and wing movements by reconstructing all 507 motor neurons that control the limbs. We show that a specific class of leg sensory neurons synapses directly onto motor neurons with the largest-caliber axons on both sides of the body, representing a unique pathway for fast limb control. We provide open access to the dataset and reconstructions registered to a standard atlas to permit matching of cells between EM and light microscopy data. We also provide GridTape instrumentation designs and software to make large-scale EM more accessible and affordable to the scientific community.

Media:
[1] A brief summary of the paper is available on Twitter.
[2] Videos associated with this paper are available on YouTube.
[3] Research highlight available from HMS News.

GridTape resources:
GridTape stage design and microscope control software: https://github.com/htem/GridTapeStage
GridTape is commercially available: https://luxel.com/gridtape

Female Adult Nerve Cord (FANC) EM dataset resources:
Visit BossDB to view the EM dataset using Neuroglancer (username: public-access | password: public).
Visit BossDB to download the EM image data using Python.
Use gsutil to download the EM image data from Google Cloud as JPEG tiles formatted for CATMAID – files are located at gs://vnc1_r066/alignmentV3/jpgs_for_catmaid

View and download neuron reconstructions:
Visit VirtualFlyBrain to view the dataset and neuron reconstructions using CATMAID.
Visit the paper’s GitHub repository to download neuron reconstructions as .swc files.

Visit the paper’s GitHub repository to:
[1] access code (Python and MATLAB) used to perform analyses and generate figures for the paper.
[2] access the command-line pipeline for elastically registering 3D image datasets, aimed at users wanting to register light microscopy stacks of VNC neurons to the VNC standard atlas.

Other:
We oversee a community of researchers collaboratively reconstructing neurons in the FANC dataset. Please contact wei-chung_lee@hms.harvard.edu for more information or to inquire about joining.