A Connectome of the Male Drosophila Ventral Nerve Cord

Reviewer #1 (Public Review):

Summary:

Drosophila is one of the most studied model organisms to understand how neural circuits form and function to control intricate animal behaviors. The ventral nerve cord (VNC) part of the fly's CNS serves as a sensory processing and motor output center just like our spinal cord. Over the last decade, the VNC has become a fruitful platform to understand neural circuits responsible for motor behavior such as walking and flying. The missing resource was the complete connectome of the VNC neurons. This study provides this needed resource. The authors documented their approaches on how to generate the data from tissue preparation to computer-assisted reconstruction in a simple manner and left the in-depth analysis of the network features of the connecting neurons to two other well-written companion articles.

Strengths:
Unlike many other previously published EM datasets, the authors presented a ready-to-view connectome dataset of the adult fly VNC. Readers, without needing permission, can access the dataset to find their neurons of interest and determine their synaptic partners with a few clicks. The authors also share their novel approaches in a detailed manner for others to reproduce similar EM volumes for other tissues.

Weaknesses:

The reconstruction completion, around 50%, might be considered a weakness. However, the data appear to have ~ %50 completion across all different neuropils suggesting that sampling is homogenous and does not induce bias. Nevertheless, a higher percentage will give a more complete picture.

Reviewer #2 (Public Review):

Summary:

Takemura et al. achieved a milestone in connectomics with their dense reconstruction of the Male Adult Nerve Cord (MANC) in Drosophila, revealing the neural circuitry of the primary premotor and motor domains in the CNS of the fruit fly. The team meticulously reconstructed neuron morphologies and synaptic connections and registered these data with light microscopy datasets (of driver lines for example), made neuronal lineage annotations and neurotransmitter predictions, providing the basis for new hypotheses about motor control. A description of the dataset and methods are presented here, while cell type annotations and characterisation of connectivity between brain descending neurons and motor neurons are provided in two companion papers, Marin et al. and Cheong, Eichler, Stürner et al., respectively. This dataset and analysis will provide a rich resource for future neuroscientific exploration.

Strengths:

The authors fully utilise a wealth of tools and techniques developed over the course of over a decade to produce a new publicly available dataset with an impressive number of reconstructed neurons and synapses. The precision and recall of connections are as high or higher than past datasets (e.g. the Hemibrain), pointing to the reliability of any downstream analyses performed on this connectome. These data are augmented with neurotransmitter identities, providing essential information for modelling and computational analysis. The MANC connectome can also be linked to genetic tools through registration to pre-existing light microscopy datasets, allowing experimentalists to test hypotheses made based on the connectome.

Weaknesses:

This dataset presents the nerve cord connectome of just a single animal, so connectivity variability and validity will be hard to assess. However, it is bilaterally reconstructed, which does allow comparison between bilaterally symmetrical neurons on the left and right sides of the nerve cord, increasing confidence in connections observed on both sides. Damage occurred to the nerves during sample preparation, which will have to be considered when analysing sensory connectivity.