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Fast DNA-PAINT imaging using a deep neural network.

ABSTRACT: DNA points accumulation for imaging in nanoscale topography (DNA-PAINT) is a super-resolution technique with relatively easy-to-implement multi-target imaging. However, image acquisition is slow as sufficient statistical data has to be generated from spatio-temporally isolated single emitters. Here, we train the neural network (NN) DeepSTORM to predict fluorophore positions from high emitter density DNA-PAINT data. This achieves image acquisition in one minute. We demonstrate multi-colour super-resolution imaging of structure-conserved semi-thin neuronal tissue and imaging of large samples. This improvement can be integrated into any single-molecule imaging modality to enable fast single-molecule super-resolution microscopy.

SUBMITTER: Narayanasamy KK 

PROVIDER: S-EPMC9420107 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Fast DNA-PAINT imaging using a deep neural network.

Narayanasamy Kaarjel K KK   Rahm Johanna V JV   Tourani Siddharth S   Heilemann Mike M  

Nature communications 20220827 1

DNA points accumulation for imaging in nanoscale topography (DNA-PAINT) is a super-resolution technique with relatively easy-to-implement multi-target imaging. However, image acquisition is slow as sufficient statistical data has to be generated from spatio-temporally isolated single emitters. Here, we train the neural network (NN) DeepSTORM to predict fluorophore positions from high emitter density DNA-PAINT data. This achieves image acquisition in one minute. We demonstrate multi-colour super-  ...[more]

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