Aaron D. Ostrovsky

Sexual Dimorphism in the Fly Brain

Summary Background Sex-specific behavior may originate from differences in brain structure or function. In Drosophila, the action of the male-specific isoform of fruitless in about 2000 neurons appears to be necessary and sufficient for many aspects of male courtship behavior. Initial work found limited evidence for anatomical dimorphism in these fru+ neurons. Subsequently, three discrete anatomical differences in central brain fru+ neurons have been reported, but the global organization of sex differences in wiring is unclear. Results A global search for structural differences in the Drosophila brain identified large volumetric differences between males and females, mostly in higher brain centers. In parallel, saturating clonal analysis of fru+ neurons using mosaic analysis with a repressible cell marker identified 62 neuroblast lineages that generate fru+ neurons in the brain. Coregistering images from male and female brains identified 19 new dimorphisms in males; these are highly concentrated in male-enlarged higher brain centers. Seven dimorphic lineages also had female-specific arbors. In addition, at least 5 of 51 fru+ lineages in the nerve cord are dimorphic. We use these data to predict >700 potential sites of dimorphic neural connectivity. These are particularly enriched in third-order olfactory neurons of the lateral horn, where we provide strong evidence for dimorphic anatomical connections by labeling partner neurons in different colors in the same brain. Conclusion Our analysis reveals substantial differences in wiring and gross anatomy between male and female fly brains. Reciprocal connection differences in the lateral horn offer a plausible explanation for opposing responses to sex pheromones in male and female flies.

A Bidirectional Circuit Switch Reroutes Pheromone Signals in Male and Female Brains

Summary The Drosophila sex pheromone cVA elicits different behaviors in males and females. First- and second-order olfactory neurons show identical pheromone responses, suggesting that sex genes differentially wire circuits deeper in the brain. Using in vivo whole-cell electrophysiology, we now show that two clusters of third-order olfactory neurons have dimorphic pheromone responses. One cluster responds in females; the other responds in males. These clusters are present in both sexes and share a common input pathway, but sex-specific wiring reroutes pheromone information. Regulating dendritic position, the fruitless transcription factor both connects the male-responsive cluster and disconnects the female-responsive cluster from pheromone input. Selective masculinization of third-order neurons transforms their morphology and pheromone responses, demonstrating that circuits can be functionally rewired by the cell-autonomous action of a switch gene. This bidirectional switch, analogous to an electrical changeover switch, provides a simple circuit logic to activate different behaviors in males and females.

NBLAST: Rapid, Sensitive Comparison of Neuronal Structure and Construction of Neuron Family Databases

Summary Neural circuit mapping is generating datasets of tens of thousands of labeled neurons. New computational tools are needed to search and organize these data. We present NBLAST, a sensitive and rapid algorithm, for measuring pairwise neuronal similarity. NBLAST considers both position and local geometry, decomposing neurons into short segments; matched segments are scored using a probabilistic scoring matrix defined by statistics of matches and non-matches. We validated NBLAST on a published dataset of 16,129 single Drosophila neurons. NBLAST can distinguish neuronal types down to the finest level (single identified neurons) without a priori information. Cluster analysis of extensively studied neuronal classes identified new types and unreported topographical features. Fully automated clustering organized the validation dataset into 1,052 clusters, many of which map onto previously described neuronal types. NBLAST supports additional query types, including searching neurons against transgene expression patterns. Finally, we show that NBLAST is effective with data from other invertebrates and zebrafish. Video Abstract

Combining genome-scale Drosophila 3D neuroanatomical data by bridging template brains

To analyse neuron data at scale, neuroscientists expend substantial effort reading documentation, installing dependencies and moving between analysis and visualisation environments. To facilitate this, we have developed a suite of interoperable open source R packages called the natverse. The natverse allows users to read local and remote data, perform popular analyses including visualisation, clustering and graph theoretic analysis of neuronal branching. Unlike most tools, the natverse enables comparison of morphology and connectivity across many neurons after imaging or co-registration within a common space. The natverse also enables transformations between different template spaces and imaging modalities. We demonstrate tools that integrate the vast majority of Drosophila neuroanatomical light microscopy and electron microscopy connectomic datasets. The natverse is an easy-to-use environment for neuroscientists to solve complex, large-scale analysis challenges as well as an open platform to create new code and packages to share with the community.The stereotyped structure of mammalian and invertebrate brains is a crucial determinant of their circuit organization. Thus large scale efforts to map circuit organization using 3D image data are underway in a number of model systems, including flies and mice. Many of these studies use registration of sample images to a standard template brain to enable co-visualization and spatial querying. However, studies often use distinct template brains, resulting in large islands of data which cannot be directly compared. To enable this comparison, we have constructed bridging registrations between template brains accounting for the vast majority of Drosophila melanogaster 3D neuroanatomical data. Furthermore, we solve the related problem of mapping data between the left and right brain hemispheres via the construction of mirroring registrations. Finally, we extend our approach across species to demonstrate its potential use in evolutionary studies of neural circuit structure and provide bridging registrations that link a new set of template brains generated for four Drosophila species that are divergent over 40 million years of evolution. We describe our strategy, document the freely available anatomical data and open source com- puter tools that we have generated and provide numerous examples of their use. This effort has unified data from over 30,000 publicly available images, with resources including the 3D atlas embodying the new standard Drosophila anatomical nomenclature and the largest single neuron databank yet available in any species. Over 20,000 registered images have been contributed to the Virtual Fly Brain project and can be viewed online at www.virtualflybrain.org.

Clonal Analysis of Olfaction in Drosophila: Image Registration

Clonal analysis with the MARCM (mosaic analysis with a repressible cell marker) system can be used for studying cell lineage, development, and anatomy in the Drosophila olfactory system and other parts of the fly brain. To compare confocal images of labeled neurons in different brains, it may be desirable to register them to a template or standard brain. There are various image registration approaches available. Some depend on manually specifying landmarks on the brains to be registered. Others depend only on the grayscale intensity value of one of the channels in the confocal image. Another important difference between registration approaches is whether they apply linear or nonlinear (warping) transformations. Linear transformations typically include translation, rotation, and scaling along each axis. Nonlinear transformations are much more computationally intensive, but are required to register brains with different shapes. Here we describe the practical steps required for an intensity-based nonlinear registration that has been used to map the higher olfactory centers of the Drosophila brain using the staining for the presynaptic marker Bruchpilot (nc82). This registration is in fact a two-step process. The first step is a linear transformation that roughly aligns the two brains, followed by a second nonlinear step that allows different parts of the brain to move in slightly different directions.

A Mutual Information Approach to Automate Identification of Neuronal Clusters in Drosophila Brain Images

Mapping neural circuits can be accomplished by labeling a small number of neural structures per brain, and then combining these structures across multiple brains. This sparse labeling method has been particularly effective in Drosophila melanogaster, where clonally related clusters of neurons derived from the same neural stem cell (neuroblast clones) are functionally related and morphologically highly stereotyped across animals. However identifying these neuroblast clones (approximately 180 per central brain hemisphere) manually remains challenging and time consuming. Here, we take advantage of the stereotyped nature of neural circuits in Drosophila to identify clones automatically, requiring manual annotation of only an initial, smaller set of images. Our procedure depends on registration of all images to a common template in conjunction with an image processing pipeline that accentuates and segments neural projections and cell bodies. We then measure how much information the presence of a cell body or projection at a particular location provides about the presence of each clone. This allows us to select a highly informative set of neuronal features as a template that can be used to detect the presence of clones in novel images. The approach is not limited to a specific labeling strategy and can be used to identify partial (e.g., individual neurons) as well as complete matches. Furthermore this approach could be generalized to studies of neural circuits in other organisms.

Clonal analysis of olfaction in Drosophila: immunochemistry and imaging of fly brains.

Clonal analysis with the MARCM (mosaic analysis with a repressible cell marker) system can be used for studying cell lineage, development, and anatomy in the Drosophila olfactory system and other parts of the fly brain. This protocol describes the dissection, staining, and imaging of brains from Drosophila with mosaic labeling. Staining for the presynaptic marker Bruchpilot (nc82) is performed in the example given here. The well-stained whole brain images that are obtained can be used to examine neuronal morphology. They are of sufficient quality to be used for image registration, which allows one to compare confocal images of labeled neurons in different brains.

Clonal Analysis of Olfaction in Drosophila: Generation of Flies with Mosaic Labeling

Clonal analysis with the MARCM (mosaic analysis with a repressible cell marker) system can be used for studying cell lineage, development, and anatomy in the Drosophila olfactory system and other parts of the fly brain. This protocol gives a method for generating flies with mosaic labeling. It describes how to establish a mating cage for MARCM in PNs (projection neurons) of the fly antennal lobe and then select appropriate flies for dissection and staining using immunohistochemistry. The protocol can be adapted to determine the birth order of neuroblast lineages or individual cells. Alternatively, it can be used to dissect a complicated Gal4 line into its component neuroblast lineages to help elucidate projection patterns and connectivity. Collecting newly hatched larvae during a short time window allows for precise control of the stage during development at which the heat shock is applied.