Automated highly multiplexed super-resolution imaging of protein nano-architecture in cells and tissues

Maja Klevanski, Frank Herrmannsdoerfer, Steffen Sass, Varun Venkataramani, Mike Heilemann and Thomas Kuner ()
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Maja Klevanski: Heidelberg University
Frank Herrmannsdoerfer: Heidelberg University
Steffen Sass: Heidelberg University
Varun Venkataramani: Heidelberg University
Mike Heilemann: Heidelberg University
Thomas Kuner: Heidelberg University

Nature Communications, 2020, vol. 11, issue 1, 1-11

Abstract: Abstract Understanding the nano-architecture of protein machines in diverse subcellular compartments remains a challenge despite rapid progress in super-resolution microscopy. While single-molecule localization microscopy techniques allow the visualization and identification of cellular structures with near-molecular resolution, multiplex-labeling of tens of target proteins within the same sample has not yet been achieved routinely. However, single sample multiplexing is essential to detect patterns that threaten to get lost in multi-sample averaging. Here, we report maS3TORM (multiplexed automated serial staining stochastic optical reconstruction microscopy), a microscopy approach capable of fully automated 3D direct STORM (dSTORM) imaging and solution exchange employing a re-staining protocol to achieve highly multiplexed protein localization within individual biological samples. We demonstrate 3D super-resolution images of 15 targets in single cultured cells and 16 targets in individual neuronal tissue samples with

Date: 2020
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DOI: 10.1038/s41467-020-15362-1

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