Optimized tools for multicolor stochastic labeling reveal diverse stereotyped cell arrangements in the fly visual system

Abstract

We describe the development and application of methods for high-throughput neuroanatomy in Drosophila using light microscopy. These tools enable efficient multicolor stochastic labeling of neurons at both low and high densities. Expression of multiple membrane-targeted and distinct epitope-tagged proteins is controlled both by a transcriptional driver and by stochastic, recombinase-mediated excision of transcription-terminating cassettes. This MultiColor FlpOut (MCFO) approach can be used to reveal cell shapes and relative cell positions and to track the progeny of precursor cells through development. Using two different recombinases, the number of cells labeled and the number of color combinations observed in those cells can be controlled separately. We demonstrate the utility of MCFO in a detailed study of diversity and variability of Distal medulla (Dm) neurons, multicolumnar local interneurons in the adult visual system. Similar to many brain regions, the medulla has a repetitive columnar structure that supports parallel information processing together with orthogonal layers of cell processes that enable communication between columns. We find that, within a medulla layer, processes of the cells of a given Dm neuron type form distinct patterns that reflect both the morphology of individual cells and the relative positions of their arbors. These stereotyped cell arrangements differ between cell types and can even differ for the processes of the same cell type in different medulla layers. This unexpected diversity of coverage patterns provides multiple independent ways of integrating visual information across the retinotopic columns and implies the existence of multiple developmental mechanisms that generate these distinct patterns.neuroanatomy | Drosophila | interneuron diversity | light microscopy | recombinase N ervous systems contain numerous and diverse cells displaying complex anatomical relationships. The specification and patterning of these cells must be generated by the execution of a much smaller set of instructions encoded in the genome. How many different genetic algorithms are needed? How precise are their outcomes? What types of rules do they follow? Answering such questions requires knowledge of the anatomy of neuronal processes for many different cell types, for numerous cells of the same type, and in multiple individuals. We describe here the development of a set of methods for collecting such data by light microscopy and their application in the adult visual system of Drosophila.Neuronal morphology is often sufficiently stereotyped to identify cell types. For example, many cell populations in vertebrate and invertebrate visual systems can be reliably distinguished on the basis of cell shape (1-3). In at least some cases, these anatomical cell types have been shown to correlate well with classifications based on genetic marker expression or functional properties. Important anatomical features are not limited to cell shape, but also include the spatial relationships between cells. One critical ...

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