Neural network-assisted single-molecule localization microscopy with a weak-affinity protein tag.
Journal
Biophysical reports
ISSN: 2667-0747
Titre abrégé: Biophys Rep (N Y)
Pays: United States
ID NLM: 9918266001106676
Informations de publication
Date de publication:
13 Sep 2023
13 Sep 2023
Historique:
received:
23
06
2023
accepted:
16
08
2023
medline:
8
9
2023
pubmed:
8
9
2023
entrez:
8
9
2023
Statut:
epublish
Résumé
Single-molecule localization microscopy achieves nanometer spatial resolution by localizing single fluorophores separated in space and time. A major challenge of single-molecule localization microscopy is the long acquisition time, leading to low throughput, as well as to a poor temporal resolution that limits its use to visualize the dynamics of cellular structures in live cells. Another challenge is photobleaching, which reduces information density over time and limits throughput and the available observation time in live-cell applications. To address both challenges, we combine two concepts: first, we integrate the neural network DeepSTORM to predict super-resolution images from high-density imaging data, which increases acquisition speed. Second, we employ a direct protein label, HaloTag7, in combination with exchangeable ligands (xHTLs), for fluorescence labeling. This labeling method bypasses photobleaching by providing a constant signal over time and is compatible with live-cell imaging. The combination of both a neural network and a weak-affinity protein label reduced the acquisition time up to ∼25-fold. Furthermore, we demonstrate live-cell imaging with increased temporal resolution, and capture the dynamics of the endoplasmic reticulum over extended time without signal loss.
Identifiants
pubmed: 37680382
doi: 10.1016/j.bpr.2023.100123
pii: S2667-0747(23)00024-1
pmc: PMC10480660
doi:
Types de publication
Journal Article
Langues
eng
Pagination
100123Informations de copyright
© 2023 The Author(s).
Déclaration de conflit d'intérêts
J.K. and K.J. are listed as inventors on a patent application related to this work and filed by the Max Planck Society.
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