Author response:
eLife assessment
This fundamental study provides a near-comprehensive anatomical description and annotation of neurons in a male Drosophila ventral nerve cord, based on large-scale circuit reconstruction from electron microscopy. This connectome resource will be of substantial interest to neuroscientists interested in sensorimotor control, neural development, and analysis of brain connectivity. However, although the evidence is extensive and compelling, the presentation of results in this very large manuscript lacks clarity and concision.
We thank the reviewers for their detailed and thoughtful feedback and the time that they invested to provide it. Organising this manuscript (which is clearly not a standard research article) was quite challenging as it had to fulfil a number of functions: presenting a guide to the system of annotations and the associated online resources; providing an atlas for the annotated cell types; and showcasing various analyses to illustrate the value of the dataset as well as just a few of the many questions it can be used to address. We gave careful consideration to its structure and attempted to signpost the sections that would be most useful to particular types of readers. Nevertheless we can see that this was not completely successful and we thank the reviewers for their suggestions for improvement.
We acknowledge that the resulting manuscript was very large and will endeavour to streamline our text in the revision without compromising the accessibility of the data. We do note that there is some precedent for comprehensive and lengthy connectome papers going all the way back to White et al. 1986 which took 340 pages to describe the 302 neurons of the C. elegans connectome. More recently, we can compare the “hemibrain papers” published in eLife: Scheffer et al., 2020, Li et al., 2020, Schlegel et al., 2021, Hulse et al., 2021. These papers would also be difficult to digest at a single sitting but were game-changing for the Drosophila neuroscience field and have already been cited hundreds of times, a testament to their utility. In the same way that these papers provided the first comprehensively proofread and annotated EM connectome for (a large part of) the adult fly brain, our work now provides the first fully proofread and annotated EM connectome for the nerve cord. Given the pioneering nature of this dataset we feel that the lengthy but highly structured atlas sections of the paper are justified and will prove impactful in the long term.
Whilst no EM dataset is perfect, we have endeavoured to make this one as comprehensive as possible. We found 74.4 million postsynapses and 15,765 neurons of VNC origin, all of which have been carefully proofread, reviewed, annotated and typed. For comparison, the female adult nerve cord dataset (FANC, Azevedo et al., Nature, 2024) contains roughly 45 million synapses and 14,600 neuronal cell bodies of which at the time of writing 5576 have received preliminary proofreading and 222 high quality proofreading. We emphasise that these are highly complementary datasets, given the difference in sex and the fact that each dataset has different artefacts (MANC has poorer preservation of neurons in the leg nerves; FANC is missing part of the abdominal ganglion and has lower synapse recovery). We reconstructed 5484 sensory neurons from the thoracic nerves, 84% of the ~6500 estimated from FANC. The overall recovery rate was ~86.5% if we include the ~1100 sensory neurons from abdominal nerves, which were in excellent condition.
Reviewer #1 (Public Review):
Summary:
The authors present a close to complete annotation of the male Drosophila ventral nerve cord, a critical part of the fly's central nervous system.
Strengths:
The manuscript describes an enormous amount of work that takes the first steps towards presenting and comprehending the complexity and organization of the ventral nerve cord. The analysis is thorough and complete. It also makes the effort to connect this EM-centric view of the nervous system to more classical analyses, such as the previously defined hemilineages, that also describe the organization of the fly nervous system. There are many, many insights that come from this work that will be valuable to the field for the foreseeable future.
We thank the reviewer for acknowledging the enormous collaborative effort represented by this manuscript. We tried to synthesise decades of light-level work by neuroscientists and developmental biologists working in Drosophila and other insects in order to create a standard, systematic nomenclature for >22,000 neurons, most of which had not been typed at light level. We hope that the MANC dataset and this guide to its contents will prove to be useful resources to Drosophila neurobiologists and the wider neuroscience field.
Weaknesses:
With more than 60 primary figures, the paper is overwhelming and cannot be read and digested in a single sitting. The result is more like a detailed resource rather than a typical research paper.
In writing this paper, we had two aims: first, to describe and validate our extensive biological annotation of the connectome and second, to provide interesting illustrative examples of the many analyses that could be carried out on this dataset using the atlas we generated. The resulting paper is intended primarily as a detailed reference rather than a typical research paper. At the end of the Introduction, we outline the structure of the paper and explicitly direct non-specialist readers to focus on the initial and concluding sections for orientation to the dataset so that they would not get bogged down in the details. We will review our section organisation and headings to try to make the paper more straightforward to navigate, and we will add specific figure numbers to the outline.
Reviewer #2 (Public Review):
Summary and strengths:
This massive paper describes the identity and connectivity of neurons reconstructed from a volumetric EM image volume of the ventral nerve cord (VNC) of a male fruit fly. The segmentation of the EM data was described in one companion paper; the classification of the neurons entering the VNC from the brain (descending neurons or DNs) and the motor neurons leaving the VNC was described in a second companion paper. Here, the authors describe a system for annotating the remaining neurons in the VNC, which include intrinsic neurons, ascending neurons, and sensory neurons, representing the vast majority of neurons in the dataset. Another fundamental contribution of this paper is the identification of the developmental origins (hemilineage) of each intrinsic neuron in the VNC. These comprehensive hemilineage annotations can be used to understand the relationship between development and circuit structure, provide insight into neurotransmitter identity, and facilitate comparisons across insect species.Many sensory neurons are also annotated by comparison to past literature. Overall, defining and applying this annotation system provides the field with a standard nomenclature and resource for future studies of VNC anatomy, connectivity, and development. This is a monumental effort that will fundamentally transform the field of Drosophila neuroscience and provide a roadmap for similar connectomic studies in other organisms.
We thank the reviewer for acknowledging the enormous collaborative effort represented by this manuscript. We tried to synthesise decades of light-level work by neuroscientists and developmental biologists working in Drosophila and other insects in order to create a standard, systematic nomenclature for >22,000 neurons, most of which had not been typed at light level. We hope that the MANC dataset and this guide to its contents will prove to be useful resources to Drosophila neurobiologists and the wider neuroscience field.
Weaknesses:
Despite the significant merit of these contributions, the manuscript is challenging to read and comprehend. In some places, it seems to be attempting to comprehensively document everything the authors found in this immense dataset. In other places, there are gaps in scholarship and analysis. As it is currently constructed, I worry that the manuscript will intimidate general readers looking for an entry point to the system, and ostracize specialized readers who are unable to use the paper as a comprehensive reference due to its confusing organization.
In writing this paper, we had two aims: first, to describe and validate our extensive biological annotation of the connectome and second, to provide interesting illustrative examples of the many analyses that could be carried out on this dataset using the atlas we generated. The resulting paper is intended primarily as a detailed reference rather than a typical research paper. At the end of the Introduction, we outline the structure of the paper and explicitly direct non-specialist readers to focus on the initial and concluding sections for orientation to the dataset so that they would not get bogged down in the details. We will review our section organisation and headings to try to make the paper more straightforward to navigate, and we will add specific figure numbers to the outline.
The bulk of the 559 pages of the submitted paper is taken up by a set of dashboard figures for each of ~40 hemilineages. Formatting the paper as an eLife publication will certainly help condense these supplemental figures into a more manageable format, but 68 primary figures will remain, and many of these also lack quality and clarity. Without articulating a clear function for each plot, it is hard to know what the authors missed or chose not to show. As an example, many of the axis labels indicate the hemilineage of a group of neurons, but are ordered haphazardly and so small as to be illegible; if the hemilineage name is too small, and in a bespoke order for that data, then is the reader meant to ignore the specific hemilineage labels?
We will contact eLife professional editing staff to determine whether the paper can be streamlined by moving more material to supplemental without making it difficult to locate the detailed catalogues of neurons that will be of interest to specialist readers. Based on the typical eLife format, we suspect that retaining the dashboard main figures for each hemilineage will be necessary to maintain its utility as a reference. We will, however, shorten the associated main text by, for example, moving background material used to assign the hemilineages to the Methods section and moving specific results to the figure legends where possible.
We articulated the function for each plot as follows: "Below we describe in more depth every hemilineage that produces more than one or two secondary neurons. For each of these 35 hemilineages, we show (A) the overall morphology of the secondary population, (B) representative individual neurons (as estimated by highest average NBLAST score to other members of the hemilineage), and (C) specific notable examples (which in some cases are primary). We then report (D) the locations of their connectors (postsynapses and presynapses), (E) their upstream and downstream partners by class, and (F) their upstream and downstream partners by finer subdivisions corresponding to their systematic types (secondary hemilineage, target, or sensory modality). We also provide supplementary figures showing the morphology and normalised up- and downstream connectivity of all systematic types for each hemilineage."
We have plotted every secondary neuron in each hemilineage, every predicted synapse for those neurons with confidence >0.5, every connection to partner neurons by class (no threshold applied), and then the same information organised by hemilineage in a heatmap (and including partners from all birthtimes and partners of unknown hemilineage). Then the supplementary figures show all connectivity, organised in the same way, for every individual cell type assigned to the hemilineage, including both primary and early secondary neurons. We will add more detail to the figure legends to clarify these points.
We apologise that you were unable to read some of the axis labels in the review copy of the manuscript; we did submit high resolution versions of the figures as a supplemental file, but perhaps this did not reach you; they can also be found at https://www.biorxiv.org/content/10.1101/2023.06.05.543407v2.supplementary-material. The hemilineages are in a conserved (alphanumerical) order for all hemilineage-specific plots and many others. The exceptions arise when neurons are clustered based on their connectivity to hemilineages, in which case the order of the labels necessarily follows the structure of the resulting clusters.
The text has similar problems of emphasis. It is often meandering and repetitive. Overlapping information is found in multiple places, which causes the paper to be much longer than it needs to be. For example, the concept of hemilineages is introduced three times before the subtitle "Introduction to hemilineage-based organisation". When cell typing is introduced, it is unclear how this relates to serial motif, hemilineage, etc; "Secondary hemilineages" follow the Cell typing title. Like the overwhelming number of graphical elements, this gives the impression that little attention has been paid to curating and editing the text. It is unclear whether the authors intend for the paper to be read linearly or used as a reference. In addition, descriptions of the naming system are often followed by extensive caveats and exceptions, giving the impression that the system is not airtight and possibly fluid. At many points, the text vacillates between careful consideration of the dataset's limitations and overly grandiose claims. These presentation flaws overshadow the paper's fundamental contribution of describing a reasonable and useful cell-typing system and placing intrinsic neurons within this framework.
Because we intended this paper to be read primarily as a reference, we tried to make each section stand on its own, which we agree resulted in some redundancy (with more details appearing where relevant). However, we will do our best to tighten the text for the version of record.
Our description immediately under the Cell typing title includes the use of hemilineage, serial (not serial motif, which was not used), and laterality (left-right homologues) in the procedure to assign cell types. We will change this to “Cell typing of intrinsic, ascending, and efferent neurons” for clarity. The “Secondary hemilineages” title marks the start of a new section that serves as a reference for each of the secondary hemilineages; we will change this to “Secondary hemilineage catalogue” or similar for clarity.
References to past Drosophila literature are inconsistent and references to work from other insects are generally not included; for example, the extensive past work on leg sensory neurons in locusts, cockroaches, and stick insects. Such omissions are understandable in a situation where brevity is paramount. However, this paper adopts a comprehensive and authoritative tone that gives the reader an impression of completeness that does not hold up under careful scrutiny.
We did not attempt to review the sensory neuron literature in this manuscript but rather cited those specific papers which included the axon morphology data that informed our modality, peripheral origin, and cell type assignments. Most of these came from the Drosophila literature due to the availability of genetic tools used for sparse labelling of specific populations as well as the greatly increased likelihood of conserved morphology. However we certainly agree that decades of sensory neuron work in larger insects were foundational for this subfield and will add a sentence to this effect in the introduction to our sensory neuron typing.
The paper accompanies the release of the MANC dataset (EM images, segmentation, annotations) through a web browser-based tool: clio.janelia.org. The paper would be improved by distilling it down to its core elements, and then encouraging readers to explore the dataset through this interactive interface. Streamlining the paper by removing extraneous and incomplete analyses would provide the reader with a conceptual or practical framework on which to base their own queries of the connectome.
We certainly hope that this paper will encourage readers to explore the MANC dataset. Indeed, as we state in the Discussion, "Moreover, its ultimate utility depends on how widely it is leveraged in the future experimental and computational work of the entire neuroscience community. We have only revealed the tip of the iceberg in this report, with a wealth of opportunities now available in this publicly available dataset for forthcoming connectomic analyses that will feed into testable functional hypotheses." In the first few sections of the Results, we include a visual introduction to annotated features, a glossary of annotation terms, a visual guide to our cell typing nomenclature, and two video tutorials on the use of Clio Neuroglancer to query the dataset. To further encourage exploration, we have also included illustrative examples of just a few of the many analyses that can now be performed with this comprehensive and publicly available dataset.
