Highlights
- •A complete adult Drosophila brain was imaged with EM and has been made publicly available
- •The imaged volume enables brain-spanning mapping of circuits at synaptic resolution
- •All mushroom body (MB) calyx inputs were mapped, revealing a new cell type, MB-CP2
- •Previously unidentified synaptic partners form recurrent microcircuits in MB calyx
Summary
Video Abstract
Graphical Abstract
Keywords
Introduction
Results
New Tools for Volume EM Data Acquisition
- Video S1. FEI CompuStage versus Custom Fast Stage, Related to Figure 1
The custom Fast Stage (right) makes 16 moves in the time it takes the commercial FEI CompuStage to move once. Each move is one camera FOV (∼8 μm) in length. Scale Bar: 1 μm.
- Video S2. ATPS Cutaway, Related to Figure 1
Computer-aided design (CAD) animation of ATPS detailing actions to retrieve grids and insert them into the TEM column.
- Video S3. ATPS Pick-and-Place, Related to Figure 1
The ATPS pick-and-place routine. The ATPS locates the grid within the cassette, moves to a pre-pick location, confirms positioning, picks grid from cassette in a two-step process with positioning assessments during the process, moves to the aligner, assesses the rotational angle of the grid, if necessary places the grid on the aligner and aligns the grid, retrieves the grid from the aligner, and inserts the grid into the TEM column (insertion to column not shown). Following imaging, the ATPS locates the correct cassette pocket, confirms positioning, replaces the grid in the cassette, and confirms that the grid is correctly located within the cassette. Changes in movie quality indicate a change in camera frame rate. High quality frames (long exposure time) are used for automated calculation of grid position; lower quality frames (short exposure time) are used to generate a video log of all pick-and-place events.
EM Image Acquisition and Volume Reconstruction of a Complete Adult Fly Brain
- Video S4. Whole-Brain EM Volume, Related to Figure 1
All sections through the whole brain are shown in sequence. Left, a low-resolution view of each entire section. The white square is centered on the x, y position of the microglomerulus shown in Figure S1A. Right, a zoom-in of an FOV at the center of the white square. Section number 5372 shows the microglomerulus of Figure S1A.
Independent Tracing of Fine Dendrites Shows Reproducibility of Reconstruction
A Complete Survey of KC Inputs Reveals Tight Clustering of Homotypic PN Arbors
- Manton J.D.
- Ostrovsky A.D.
- Goetz L.
- Costa M.
- Rohlfing T.
- Jefferis G.S.
- Manton J.D.
- Ostrovsky A.D.
- Goetz L.
- Costa M.
- Rohlfing T.
- Jefferis G.S.
A Previously Unknown Cell Type, MB-CP2, Provides Input to KC Claws
- Video S5. Synapses in Neuropil Compartments Innervated by MB-CP2, Related to Figure 6
The MB-CP2 neurons (orange skeletons) are shown inside the whole-brain surface mesh (gray) and other brain region meshes (multiple colors). In the right hemisphere, MB-CP2 is purely postsynaptic (blue dots) in the MB pedunculus, ATL, LH, PLP, SCL, SMP, SIP, and SLP (synapses shown first). MB-CP2 is both presynaptic (red dots) and postsynaptic in the dAC (surface mesh not shown), LH, and SLP. In the MB, MB-CP2 is postsynaptic in the pedunculus and both pre- and postsynaptic in the calyx (synapses shown second), forming MB recurrent circuits. See Figure 6F for synaptic input/output summary schematic by brain region. Video begins from an anterior perspective with dorsal at top and ventral at bottom.
Identification of Cell Types Postsynaptic to KCs in the MB Calyx
Discussion
STAR★Methods
Key Resources Table
REAGENT or RESOURCE | SOURCE | IDENTIFIER |
---|---|---|
Deposited Data | ||
The full adult fly brain electron microscopy image dataset | This paper | http://www.temca2data.org/bigtiles.html |
The full adult fly brain electron microscopy image dataset at virtualflybrain.org | This paper | https://catmaid-fafb.virtualflybrain.org |
Experimental Models: Organisms/Strains | ||
Drosophila [iso] Canton-S G1 females | Janelia Research Campus, Howard Hughes Medical Institute (HHMI) | N/A |
Software and Algorithms | ||
TEMCA2 control software | This paper | N/A |
ATPS control software | This paper | N/A |
CATMAID: source code | Saalfeld et al., 2009 , Schneider-Mizell et al., 2016 | https://github.com/catmaid/CATMAID |
CATMAID: user documentation | Saalfeld et al., 2009 , Schneider-Mizell et al., 2016 | http://catmaid.readthedocs.io/en/stable/user.html |
CATMAID: administrator documentation | Saalfeld et al., 2009 , Schneider-Mizell et al., 2016 | http://catmaid.readthedocs.io/en/stable/administrator.html |
CATMAID: developer documentation | Saalfeld et al., 2009 , Schneider-Mizell et al., 2016 | http://catmaid.readthedocs.io/en/stable/developer.html |
TrakEM2 | Cardona et al., 2012 | https://imagej.net/TrakEM2; https://github.com/trakem2/TrakEM2 |
mpicbg transformation library and feature-based point match generation | Saalfeld et al., 2010 | https://github.com/axtimwalde/mpicbg |
Section order correction | Hanslovsky et al., 2017 | https://github.com/saalfeldlab/section-sort |
Cross-correlation-based point match generation and slab alignment | This paper | https://github.com/billkarsh/Alignment_Projects/blob/master/00_DOC/method_overview.md |
Global volume alignment | This paper | https://github.com/khaledkhairy/EM_aligner |
Renderer | This paper | https://github.com/saalfeldlab/render |
Image tile intensity correction (Distributed Gradient-Domain Processing) | Kazhdan et al., 2010 ; this paper | http://www.cs.jhu.edu/∼misha/Code/DMG/ |
Signal-to-noise ratio quantification | This paper | https://github.com/bocklab/temca2data/tree/master/SNR |
Neuron skeleton analysis code | This paper | https://github.com/bocklab/temca2data/tree/master/geometry_analysis |
Electron-light microscopy tools (ELM) | Bogovic et al., 2016 | https://github.com/saalfeldlab/elm |
elmr | This paper | https://github.com/jefferis/elmr |
NBLAST | Costa et al., 2016 | https://github.com/jefferislab/nat.nblast |
NBLAST online | Costa et al., 2016 | http://jefferislab.org/si/nblast |
R neuroanatomy toolbox | Jefferis et al., 2007 , Costa et al., 2016 | https://github.com/jefferis/nat |
R flycircuit | Costa et al., 2016 | https://github.com/jefferis/flycircuit |
nat.flybrains | Manton et al., 2014
Combining genome-scale Drosophila 3D neuroanatomical data by bridging template brains. bioRxiv. 2014; https://doi.org/10.1101/006353 | https://github.com/jefferislab/nat.flybrains |
rcatmaid | This paper | https://github.com/jefferis/rcatmaid |
CATMAID-to-Blender | Schlegel et al., 2016 | https://github.com/schlegelp/CATMAID-to-Blender |
Other | ||
CATMAID-in-a-box: installation documentation | This paper | http://www.temca2data.org/data.html |
CATMAID-in-a-box: workstation | Dell | Dell Precision 5720 with 16 GB of RAM, i5-7600 processor |
CATMAID-in-a-box: operating system | Dell, pre-installed | Ubuntu 16.04 |
CATMAID-in-a-box: CATMAID with Docker | Saalfeld et al., 2009 | http://catmaid.readthedocs.io/en/stable/docker.html |
CATMAID-in-a-box: installation code | This paper | https://www.github.com/bocklab/temca2-catmaid |
CATMAID-in-a-box: RAID storage device | Oyen Digital | Part#3R5-EB3-M |
CATMAID-in-a-box: Hard disk drive | Seagate | ST4000NM0035 |
Precision piezo motor | Physik Instruments | Cat#N301K151 |
Vacuum chamber extension to FEI T-12 TEM | This paper | N/A |
Sample support grids | This paper | N/A |
TEMCA2 unit camera | Fairchild | SciMOS 2051 Model F2 |
TEMCA2 scintillator, 10 mg/cm2 P43 on 5 μm Mylar | Grant Scientific | Custom part |
Fast Stage | This paper | N/A |
Automated Transport and Positioning System (ATPS) | This paper | N/A |
Contact for Reagent and Resource Sharing
Experimental Model and Subject Details
Method Details
Sample Preparation
Sample Supports, Ultramicrotomy, and Post-staining
Electron Microscopy
TEMCA2 Fast Stage
Image acquisition
ATPS grid handling
TEMCA2 and ATPS system control
Section loss
Acquiring the whole brain
Acquisition rates
Volume Reconstruction
Data migration
Calibration mosaics
Stitching and alignment
Matching point-pairs within mosaics
Matching point-pairs across mosaics
Registering high-dose/low-dose images
Section order correction
Solving the volume
Sources of error
Image Intensity Correction
Projection of tracing across alignments
Stack management and relational database
Assessment of alignment quality
Neuron Tracing
Tracing to classification
Tracing to completion
Quantification of tracing speed
Validation of tracing accuracy
Tracing of PNs
Tracing MB-CP2 to classification
Kenyon cells and their postsynaptic partners in the MB calyx
Neuronal Informatics
Electron-Light Microscopy registration tools (ELM)
Transforming data between EM and LM templates: elmr
- Manton J.D.
- Ostrovsky A.D.
- Goetz L.
- Costa M.
- Rohlfing T.
- Jefferis G.S.
Surface models of neuropil compartments
- Manton J.D.
- Ostrovsky A.D.
- Goetz L.
- Costa M.
- Rohlfing T.
- Jefferis G.S.
- Manton J.D.
- Ostrovsky A.D.
- Goetz L.
- Costa M.
- Rohlfing T.
- Jefferis G.S.
Remote deployment for tracing in the whole brain (“CATMAID-in-a-box”)
Quantification and Statistical Analysis
Comparison of SNR between Volume EM Datasets
Feature-based SNRs
The background level of the image, B, was determined by taking the mean of these noise-dominated regions (again taking a mean over the three pixel neighborhood), following on from the assumption of symmetric noise, giving
The level of signal was then taken to be the mean of the (absolute) difference of the mean of these three pixel neighborhoods around phigh, and the background. This resulted in the SNR being given by
As most images lack large areas that consist of only resin, this simple background selection is not perfect. Therefore, the SNRs generated should be considered lower limits in most cases. We show the SNR as a function of the acquisition rate for a variety of EM techniques in Figure 2G.
Cell membrane SNR
Quantification of Artifacts
Analysis of Neuronal Geometry
NBLAST search for PNs
NBLAST clustering and PN dendrogram generation
Renderings and analysis of PN arbors in MB calyx
- Manton J.D.
- Ostrovsky A.D.
- Goetz L.
- Costa M.
- Rohlfing T.
- Jefferis G.S.
- Manton J.D.
- Ostrovsky A.D.
- Goetz L.
- Costa M.
- Rohlfing T.
- Jefferis G.S.
Data and Software Availability
Additional Resources
Acknowledgments
Author Contributions
Declaration of Interests
Supplemental Information
- Table S1. Agreement between Expert and NBLAST-Based Identification of PN Subtypes, Related to Figure 4
Abbreviations: N, no NBLAST match found from the top five hits.
- Table S2. KC Postsynaptic Partners in the MB Calyx, Related to Figure 7
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