Drosophila Brainbow: a recombinase-based fluorescence labeling technique to subdivide neural expression patterns

Hampel, Stefanie; Chung, Phuong; McKellar, Claire E; Hall, Donald; Looger, Loren L.; Simpson, Jeffrey H.

doi:10.1038/nmeth.1566

Cited by 211 publications

(173 citation statements)

References 51 publications

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“…Since then, systematic mutagenesis and subsequently, more sophisticated methods of genetic modifications have been implemented to isolate strains with specific defects in various proteins (Ashburner et al, 2005;Greenspan et al, 2004). Finally, the newly developed techniques enabled the researchers to mark, activate or silence specific cells or cell lines (Hampel et al, 2011;Gohl et al, 2011). Genetic modification and elimination of eyespecific proteins have led to fundamental discoveries in the visual pathway and the deciphering of the mechanisms of phototransduction in great detail (Pak, 2011).…”

Section: Introductionmentioning

confidence: 99%

ERG in Drosophila

Belušič¹

2011

Electroretinograms

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Section: Introductionmentioning

confidence: 99%

ERG in Drosophila

Belušič¹

2011

Electroretinograms

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“…Although it has been possible to collect large datasets with single-color labeling (17), visualization of neuronal arrangements by light microscopy has been greatly enhanced by the development of methods for combinatorial multicolor stochastic labeling such as Brainbow (18,19). Several adaptations of Brainbow are available in Drosophila (20,21); however, precise control of labeling density and reliable visualization of fine neuronal arbors remains challenging.…”

mentioning

confidence: 99%

“…We refer to this approach as MultiColor FlpOut (MCFO; an extension of "flp-out," an informal term for Flp-mediated stopcassette excision). Similar to other multicolor labeling methods such as Brainbow (18,20,21), MCFO has the potential to increase label diversity through marker coexpression. For example, with three stop-cassette reporters, seven potential marker combinations (not counting unlabeled cells) are predicted (Fig.…”

mentioning

confidence: 99%

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

Nern

Pfeiffer

Rubin

2015

Proc. Natl. Acad. Sci. U.S.A.

520

691

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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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“…Given this framework's reliance on signal modulation by PSFs, it neglects other ways that sources can be separated, such as color (Hampel et al, 2011) or spike waveform. Some of this information could be made compatible with our framework via virtual recording channels, e.g., in time.…”

Section: Framework Discussionmentioning

confidence: 99%

Spatial Information in Large-Scale Neural Recordings

Cybulski¹,

Glaser²,

Marblestone

et al. 2014

Preprint

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To record from a given neuron, a recording technology must be able to separate the activity of that neuron from the activity of its neighbors. Here, we develop a Fisher information based framework to determine the conditions under which this is feasible for a given technology. This framework combines measurable point spread functions with measurable noise distributions to produce theoretical bounds on the precision with which a recording technology can localize neural activities. If there is sufficient information to uniquely localize neural activities, then a technology will, from an information theoretic perspective, be able to record from these neurons. We (1) describe this framework, and (2) demonstrate its application in model experiments. This method generalizes to many recording devices that resolve objects in space and should be useful in the design of next-generation scalable neural recording systems.

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Drosophila Brainbow: a recombinase-based fluorescence labeling technique to subdivide neural expression patterns

Cited by 211 publications

References 51 publications

ERG in Drosophila

ERG in Drosophila

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

Spatial Information in Large-Scale Neural Recordings

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