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Ultrafast tissue staining with chemical tags

Johannes Kohl,J. Ng,S. Cachero,E. Ciabatti,Michael-John Dolan,Ben Sutcliffe,Adam J. B. Tozer,Sabine Ruehle,Daniel Krueger,S. Frechter,T. Branco,Marco Tripodi,G. Jefferis

Published 2014 in Proceedings of the National Academy of Sciences of the United States of America

ABSTRACT

Significance Cellular and subcellular structures in thick biological samples typically are visualized either by genetically encoded fluorescent proteins or by antibody staining against proteins of interest. However, both approaches have drawbacks. Fluorescent proteins do not survive treatments for tissue preservation well, are available in only a few colors, and often emit weak signals. Antibody stainings are slow, do not penetrate thick samples well, and often result in considerable background staining. We have overcome these limitations by using genetically encoded chemical tags that result in rapid, even staining of thick biological samples with high-signal and low-background labeling. We introduce tools for flies and mice that drastically improve the speed and specificity for labeling genetically marked cells in biological tissues. Genetically encoded fluorescent proteins and immunostaining are widely used to detect cellular and subcellular structures in fixed biological samples. However, for thick or whole-mount tissue, each approach suffers from limitations, including limited spectral flexibility and lower signal or slow speed, poor penetration, and high background labeling, respectively. We have overcome these limitations by using transgenically expressed chemical tags for rapid, even, high-signal and low-background labeling of thick biological tissues. We first construct a platform of widely applicable transgenic Drosophila reporter lines, demonstrating that chemical labeling can accelerate staining of whole-mount fly brains by a factor of 100. Using viral vectors to deliver chemical tags into the mouse brain, we then demonstrate that this labeling strategy works well in mice. Thus this tag-based approach drastically improves the speed and specificity of labeling genetically marked cells in intact and/or thick biological samples.

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