Author response: Quantitative neuroanatomy for connectomics in Drosophila

Full text Figures and data Side by side Abstract eLife digest Introduction Results Discussion Materials and methods References Decision letter Author response Article and author information Metrics Abstract Neuronal circuit mapping using electron microscopy demands laborious proofreading or reconciliation of multiple independent reconstructions. Here, we describe new methods to apply quantitative arbor and network context to iteratively proofread and reconstruct circuits and create anatomically enriched wiring diagrams. We measured the morphological underpinnings of connectivity in new and existing reconstructions of Drosophila sensorimotor (larva) and visual (adult) systems. Synaptic inputs were preferentially located on numerous small, microtubule-free 'twigs' which branch off a single microtubule-containing 'backbone'. Omission of individual twigs accounted for 96% of errors. However, the synapses of highly connected neurons were distributed across multiple twigs. Thus, the robustness of a strong connection to detailed twig anatomy was associated with robustness to reconstruction error. By comparing iterative reconstruction to the consensus of multiple reconstructions, we show that our method overcomes the need for redundant effort through the discovery and application of relationships between cellular neuroanatomy and synaptic connectivity. https://doi.org/10.7554/eLife.12059.001 eLife digest The nervous system contains cells called neurons, which connect to each other to form circuits that send and process information. Each neuron receives and transmits signals to other neurons via very small junctions called synapses. Neurons are shaped a bit like trees, and most input synapses are located in the tiniest branches. Understanding the architecture of a neuron's branches is important to understand the role that a particular neuron plays in processing information. Therefore, neuroscientists strive to reconstruct the architecture of these branches and how they connect to one another using imaging techniques. One imaging technique known as serial electron microscopy generates highly detailed images of neural circuits. However, reconstructing neural circuits from such images is notoriously time consuming and error prone. These errors could result in the reconstructed circuit being very different than the real-life circuit. For example, an error that leads to missing out a large branch could result in researchers failing to notice many important connections in the circuit. On the other hand, some errors may not matter much because the neurons share other synapses that are included in the reconstruction. To understand what effect errors have on the reconstructed circuits, neuroscientists need to have a more detailed understanding of the relationship between the shape of a neuron, its synaptic connections to other neurons, and where errors commonly occur. Here, Schneider-Mizell, Gerhard et al. study this relationship in detail and then devise a faster reconstruction method that uses the shape and other properties of neurons without sacrificing accuracy. The method includes a way to include data from the shape of neurons in the circuit wiring diagrams, revealing circuit patterns that would otherwise go unnoticed. The experiments use serial electron microscopy images of neurons from fruit flies and show that, from the tiniest larva to the adult fly, neurons form synapses with each other in a similar way. Most errors in the reconstruction only affect the tips of the smallest branches, which generally only host a single synapse. Such omissions do not have a big effect on the reconstructed circuit because strongly connected neurons make multiple synapses onto each other. Schneider-Mizell, Gerhard et al.'s approach will help researchers to reconstruct neural circuits and analyze them more effectively than was possible before. The algorithms and tools developed in this study are available in an open source software package so that they can be used by other researchers in the future. https://doi.org/10.7554/eLife.12059.002 Introduction Mapping neuronal circuits from electron microscopy (EM) volumes is hard (Helmstaedter, 2013). Manually working through large volumes is slow and prone to attentional errors (Kreshuk et al., 2011; Helmstaedter et al., 2011). Combining multiple independent reconstructions of the same neuron can reduce errors (Helmstaedter et al., 2011; Kim et al., 2014) at the cost of multiplying the required labor. Current computational approaches operate only with 'local' information, that is, the EM micrographs and algorithmically detected fine structures such as cell membranes and mitochondria. They are therefore sensitive to noise (Jain et al., 2010), particularly in anisotropic EM data where the smallest neurites may be thinner than the thickness of individual serial sections (Veeraraghavan et al., 2010; Helmstaedter, 2013). Machine-generated neuron reconstructions are therefore proof-read by humans (Chklovskii et al., 2010; Haehn et al., 2014). Expert neuroanatomists are able to resolve ambiguities that novices and current algorithmic approaches cannot by using large-scale features of neurons to inform decisions made at the level of nanometer-scale image data. For example in Drosophila, where neurons are highly stereotyped, large branches in an EM reconstruction of a given cell can be confirmed by comparing the observed anatomy to that of homologous cells from light microscopy data or other reconstructions (Takemura et al., 2013; Ohyama et al., 2015). This suggests that one way to improve the toolkit for neuron reconstruction and circuit mapping is to facilitate the use of cell- and circuit-level features to find and resolve errors and ambiguities. Crucially, different errors do not alter the wiring diagram equally. Missing small dendrites can be acceptable. Useful and reproducible wiring diagrams can be created even when omitting 56% of all postsynaptic sites (Takemura et al., 2013), but missing a single large branch hosting all the synapses in one neuropil region could omit connectivity to entire populations of partners. Prioritizing proofreading time toward those errors that most significantly affect the interpretation of the data improves reconstruction efficiency (Plaza et al., 2012; Kim et al., 2014). To understand the effect of reconstruction errors on measured synaptic connectivity, we need to understand the relationship between synaptic connectivity and cellular neuroanatomy. Mesoscale anatomy, particularly the placement of large branches, is a key component of circuit structure (Zlatić et al., 2003, 2009; Wu et al., 2011; Couton et al., 2015). Similarly, the connectivity graph of a stereotyped circuit can relate back to anatomy by consideration of the location of the synaptic sites between pairs of neurons. However, little is known about the smallest scales of synaptic connectivity, the distribution of individual synapses on a neuron. Microtubule-free and actin-rich structures have been identified as key sites of excitatory input in the adult Drosophila visual system (Scott et al., 2003; Leiss et al., 2009), but it is unclear how ubiquitous these are in the nervous system. Here, we describe a collection of quantitative anatomical and connectivity features across scales, from fine dendritic branches to multi-neuron graphs, and tools for measuring them to swiftly and accurately map a wiring diagram from EM. We implemented the calculation and visualization of such features on-demand as an extension of the web-based large image data viewer CATMAID (Saalfeld et al., 2009). We propose a novel method for interactively using these features to reconstruct neuronal circuits through iterative proofreading at the level of both EM images and higher level features. We validated this approach by comparing the speed and accuracy of our iterative method to a consensus method, where multiple independent reconstructions are used to calculate regions of agreement across individuals (Helmstaedter et al., 2013). Because the detection of high-impact errors can occur concurrently with reconstruction via interactive analysis, our tool removes the need for time-consuming repeated reconstructions (Helmstaedter et al., 2013; Kim et al., 2014). Moreover, because reconstructed neurons did not need to be hidden to ensure independence between repeated reconstructions, our method facilitates concurrent, synergistic collaboration between expert neuroanatomists who, for example, map circuits in different brain regions that happen to spatially overlap or synaptically interact. We demonstrate our methods by mapping a sensorimotor circuit in the Drosophila larva from proprioceptive sensory neurons to motor neurons. Results Collaborative circuit mapping We extended the web-based image data viewer CATMAID (Saalfeld et al., 2009) to enable a geographically distributed group of researchers to map neuronal circuitry. A neuron is reconstructed with a skeleton, a directed tree graph with one or more nodes in every cross-section of neurite in an EM volume (Helmstaedter et al., 2011; Cardona et al., 2012). Nodes have a spatial coordinate, as well as metadata including authorship, timestamp, review status, and optional annotations such as a radius value, text labels. Importantly, nodes also have a confidence value that can be lowered to indicate uncertainty in following a branch. Where possible, we root skeletons at the soma to model the anatomical notions of proximal and distal in the data structure. Synapses (Figure 1A and Figure 1—figure supplement 1) are annotated as a relation from a node on the presynaptic neuron skeleton to an intermediate 'connector node' and then to a node of a postsynaptic neuron skeleton. To express the polyadic nature of insect synapses (Meinertzhagen and O'Neil, 1991), connector nodes can have multiple postsynaptic 'targets', but only one presynaptic 'source'. Reconstructions are immediately synchronized across all collaborators to avoid duplicate or conflicting work, and to take advantage of existing reconstructions to aid further reconstruction and circuit discovery. Figure 1 with 1 supplement see all Download asset Open asset EM ultrastructure shows synapses and microtubule cytoskeleton. (A) EM micrograph of a typical Drosophila synapse with a single presynaptic site (red asterisk) and multiple postsynaptic sites (blue asterisks). Scale bar is 200 nm. (B) Microtubules in neural processes are visible in EM sections whether cut transverse (top inset, red arrowheads) or obliquely (bottom inset, red arrowheads). (C) Microtubules in a given neuronal process span several sections (three shown here; microtubules were traced over 16 sections) and maintain their relative orientations. Microtubules are color coded as in the processes in B and were traced and visualized in TrakEM2. (D) Synaptic distribution (red, presynaptic site; blue, postsynaptic site) across the arbor of larval neuron A23a. (E) Microtubule distribution of larval neuron A23a. Black indicates the microtubule-containing backbone continuous with the soma, green are microtubule-free twigs. See Video 1 for both microtubules and synapses shown together. https://doi.org/10.7554/eLife.12059.003 Video 1 Download asset This video cannot be played in place because your browser does support HTML5 video. You may still download the video for offline viewing. Download as MPEG-4 Download as WebM Download as Ogg Rotation of the A23a neuron showing both synapses (red, presynaptic sites; blue, postsynaptic sites) and presence of microtubules (black, with microtubules; green, without microtubules). https://doi.org/10.7554/eLife.12059.005 As a case study of our method, we focused on sensorimotor circuits in an abdominal segment of the first instar Drosophila larval central nervous system (CNS) using an EM volume covering one and a half abdominal segments (Ohyama et al., 2015). In total for this work, nine lab members reconstructed and proofread 425 neuronal arbors spanning 51.8 mm of cable, with 24,068 presynaptic and 50,927 postsynaptic relations, (see 'Materials and methods' for details). Reconstruction time was 469 hours for reconstruction with synapse annotations plus 240 hours for review (see below), for an average rate of ∼73 microns of proofread arbor with synapses per hour. Microtubule-free twigs are the principal site of synaptic input To be able to use neuronal anatomy to guide circuit reconstruction, it was crucial to better understand the distribution of synaptic input onto Drosophila neurons. We started by looking in detail at the relationship between the synaptic inputs (Figure 1A–B) and microtubule cytoskeleton (Figure 1C–E) in EM reconstructions of neurons from different regions of the nervous system and life stages. For a diverse collection of neurons, we marked all locations where the arbor continued distal to a microtubule-containing process (Figure 1E, Figure 2A). We call such a terminal branch a 'twig'. By definition, all twigs have their base on a microtubule-containing backbone shaft. Following the classification in Leiss et al. (Leiss et al., 2009), a spine is a twig with a maximal depth of less than 3 µm and that is not a presynaptic varicosity (Figure 2A). Figure 2 Download asset Open asset Twigs, small microtubule-free neurites, are the primary site of input in Drosophila neurons. (A) Twigs less than 3 µm are considered spine-like, while those longer or primarily presynaptic are not. (B–F) EM reconstructions (middle) of Drosophila neurons from different parts of the nervous system (left) showing backbone (black) and twigs (green). At right, the fraction of all synaptic inputs onto short spine-like twigs, longer twigs, and backbone. Data sets are indicated by marks: no asterisk: 1.5 segment volume. *: Whole CNS volume. **: 3rd instar abdominal segment volume. ***: Adult medulla skeletons and images, generously provided by Janelia FlyEM [9]. Neurons are individually scaled to show complete arbors. (B) motor neurons in 1st instar larva. (C) Premotor interneurons of 1st instar larva. (D) Interneurons in the brain of the 1st instar larva. (E) A somatosensory interneuron cell type across life stages, 1st instar and 3rd instar larvae. (F) Tm3 cells in the adult fly medulla. https://doi.org/10.7554/eLife.12059.006 We found twigs in all neurons investigated, across multiple CNS regions and life stages of Drosophila, and in all cases, they were the dominant sites of synaptic input (Figure 2B–F). We first considered larval motor neurons aCC and RP2 (Landgraf et al., 1997), which have functional and structural similarities to vertebrate neurons (Sánchez-Soriano et al., 2005; Nicolï et al., 2010; Günay et al., 2015). In the first instar CNS, we find aCC and RP2 have numerous twigs, which together host more than 80% of their total number of postsynaptic sites (Figure 2B). We found a similar majority of inputs onto twigs in three hemisegmental pairs of premotor interneurons (Figure 2C) and brain neurons (Ohyama et al., 2015) in the first instar larva (Figure 2D). We tested whether the observed distribution of postsynaptic sites onto twigs generalizes across larval stages by comparing a somatosensory interneuron in the first instar to its homologue in late third instar (Figure 2E). At both life stages, we find more than 80% of inputs were onto twigs, suggesting that twigs are not a temporary developmental structure. In the adult fly, light microscopy-level analysis of lobula plate tangential cells of the visual system suggests a similar distribution of postsynaptic sites onto twigs (Leiss et al., 2009; Scott et al., 2003). We annotated EM skeletonizations of medullar Tm3 neurons reconstructed by Takemura et al. (2013) in the adult visual system neuropil and found that nearly all their inputs were onto twigs (Figure 2F). Our findings suggest that microtubule-free twigs are a general feature of Drosophila neurons and constitute the primary anatomical location of synaptic input. Spine-like twigs are found in all cell types, but host a variable, typically non-majority, amount of synaptic input (Figure 2C–F). We consider all twigs for the remainder of our analysis. Distribution of inputs onto motor neuron dendrites For a given presynaptic partner, a postsynaptic neuron could concentrate its input synapses onto a single region or distribute them widely. The spatial distribution of synaptic inputs has implications for dendritic processing (Polsky et al., 2004), developmental robustness (Couton et al., 2015), and as we show, reconstruction accuracy. To study the relationship between presynaptic neurons and the anatomical locations of post-synaptic sites, we reconstructed all neurons synaptically connected to motor neurons aCC and RP2 in the third abdominal segment of a first instar larva (Figure 3A–F). Figure 3 with 3 supplements see all Download asset Open asset Twigs are crucial to larval motor circuitry. (A) The EM volume covers one abdominal segment (blue box) of the ventral nerve cord. (B) Sagital view of the EM volume. Note segmentally repeated features. (C) Dorsal projections of genetically labeled motor neurons RP2 (top, from 1st instar) and aCC (bottom, from 3rd instar). Each cell type has characteristic dendritic arbors. Midline indicated by gray arrowhead. (D) EM reconstructions of each of four motor neurons aCC and RP2 in the 1st instar larva match the left and right homologs of aCC and RP2. Backbone is indicated by black, twigs by colors. Midline is shown as dashed line. (E) True spatial relationship of the four motor neurons in (D), shown dorsally (left) and in cross-section (right). Note that the boundary of the EM volume is limited. (F) All arbors presynaptic to aCC and RP2. Colors indicate if neuron is presynaptic to one or both motor neuron cell types. See Video 2 for rotated views of the arbors. (G) Histograms of premotor partners connected via number of synapses. (H) Colored lines: the cumulative fraction of total inputs as a function of ranked presynaptic partn ers for each motor neuron are extremely similar. Black dashed line: simultaneous fit for all four motor neurons to 1 - exp (-r/ρ) for rank r gives ρ = 22.34. (I) Scatterplot and histogram of the total length and number of synapses on each of the 305 twigs for each of the four motor neurons (colors as previous). (J) Number of twigs contacted by motor neuron partners as a function of the number of synapses in the connection. Crosses are median, boxes the interquartile range, whiskers the 10th to 90th percentiles. Outliers shown. https://doi.org/10.7554/eLife.12059.007 Video 2 Download asset This video cannot be played in place because your browser does support HTML5 video. You may still download the video for offline viewing. Download as MPEG-4 Download as WebM Download as Ogg Rotation of all arbors (colored skeletons) presynaptic to RP2 motor neurons (black skeletons). (Red dots are presynaptic sites, cyan are postsynaptic sites). Dorsal is up. https://doi.org/10.7554/eLife.12059.011 A dynamically generated and interactive table of synaptic connectivity in CATMAID enabled users to systematically trace all connected arbors. We found 198 identifiable neurons (Figure 3—figure supplement 1) and named them according to a developmental lineage-based nomenclature (Ohyama et al., 2015), classified 107 other arbors spanning the full segment into eight distinct intersegmental bundles (Figure 3—figure supplement 2), and classified 120 small fragments that could not be joined into larger arbors. We refer to the connection between a pre- and postsynaptic neuron as an 'edge' in the connectivity network, where each edge has a weight equal to the number of synapses between the two neurons. Motor neurons each received between 1 and 28 synaptic inputs from individual presynaptic neurons, with a maximum of 7.3% of all inputs coming from a single neuron (Figure The fraction of synapses accounted for by their presynaptic by number of is by an with a that the presynaptic partners of one motor neuron of all its synaptic inputs (Figure We how the synaptic input onto aCC and RP2 is distributed across independent twigs. Most individual twigs were small, with the twig measuring 1 µm in and hosting 1 postsynaptic The typical twig 16 µm of and postsynaptic sites (Figure We find that presynaptic neurons connect to between and twigs, with nearly all connections with 3 or more synapses per edge being distributed across multiple twigs (Figure Similarly, strong multiple twigs in the adult visual system Tm3 neurons (Figure 3—figure supplement sites are associated with and microtubules neuronal have different such as at presynaptic sites or postsynaptic response to and et al., To whether the spatial distribution of is a of different arbor we annotated the location of all in the four motor neurons and the premotor interneurons from Figure (Figure Most were associated with backbone across motor neurons (Figure and interneurons (Figure we found that of central presynaptic sites were located 3 µm of a (Figure only of was located the same A similar did not with postsynaptic sites, which were more distributed (Figure This suggests that presynaptic sites and are one a for synapse Figure Download asset Open asset are associated with presynaptic sites and cytoskeleton. (A) EM micrograph shows with and a presynaptic site (red (B) Dorsal view of motor neuron RP2 with locations of indicated (top, and synaptic sites (C) Dorsal view of interneuron with locations of indicated (top, and synaptic sites See Video 3 for both and synapses shown together. (D) Number of associated with backbone and twig locations on motor neurons. (E) Number of associated with backbone and twig locations on (F) of the between presynaptic sites and their the arbor for the interneurons in distribution indicated as a line. (H) of the between presynaptic sites and the backbone the arbor for the interneurons in distribution indicated as a line. Video 3 Download asset This video cannot be played in place because your browser does support HTML5 video. You may still download the video for offline viewing. Download as MPEG-4 Download as WebM Download as Ogg Rotation of showing both synapses (red, presynaptic sites; postsynaptic sites) and (blue is up. with presynaptic sites were typically also associated with microtubules (Figure of presynaptic sites were located on the backbone and were 3 for proprioceptive into a motor circuit We at the cell and circuit level for that could inform In the Drosophila homologous neurons are strongly stereotyped et al., quantitative analysis of their properties for between homologous Most cell are in the fly nervous system by at one homologous of individual suggests that both arbor and synaptic wiring are to developmental noise (Ohyama et al., 2015). To guide we developed a collection of that were independent of These with the structure of neurons to help and (Figure Figure Download asset Open asset CATMAID interactive views on EM and quantitative features. example of a CATMAID in the browser of a of connected neurons, and are shown across each The and neurons in each are (A) image shows the EM all reconstructed nodes in the view synapse connector nodes and the node indicated by The current node to an RP2 motor neuron and is postsynaptic to a synapse on interneuron indicated by the arrowhead. (B) of a collection of neurons, including the indicated as indicate the number of associated synapse (red (C) The of neurons indicated in shown in a viewer blue, indicated as The node in the image is shown by a green in the viewer by red also the location of the synapse shown at (D) of synapses between and in the graph by an edge (red in Each is the to that location to of (E) of quantitative morphological or network of the neurons in (F) shows neurons synaptically connected to neurons and the total number of synapses. The for the presynaptic neuron is As a case we our tools to describe a complete sensorimotor circuit. a of from to segments and et al., 2012). from the segmentally repeated proprioceptive neurons have been to via a to motor neuron of a given segment and To find between proprioceptive and motor neurons, we further reconstructed for proprioceptive sensory neurons and and et al., Because of its in proprioceptive and we further reconstructed all partners of the left and right (Figure Figure with 3 supplements see all Download asset Open asset to (A) The motor neuron RP2 and proprioceptive sensory neuron shown in (B) All synaptic partners of RP2 and in (C) pairs of identified neurons the two cell with three or of at three synapses as found by in All are observed in both the left and right for a single edge the volume boundary (red dashed see Figure supplement thickness with number of synapses and In this and all network diagrams, single synapse are not shown for (D) All identified cells in EM (left) could be to maximum projections of single neurons found in labeled see 'Materials and methods' for details). For an boundary is for the region is a of a graph we identified all from to motor neuron RP2. of the identifiable intermediate neurons pairs of homologous neurons with connectivity, and quantitative morphological properties (Figure in to further review to if they were to reconstruction developmental (Figure supplement 1) or of the data. For example, one strong in this network, the connection from to (Figure was to the synapse locations being the volume on one side but not the other (Figure supplement The pairs of identified neurons could also be to images of neurons identified through et al., 2015) of neurons a (Figure two