Optimization of sample preparation and green color imaging using the mNeonGreen fluorescent protein in bacterial cells for photoactivated localization microscopy.

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State: Public
Version: Final published version
Serval ID
serval:BIB_AF489DBA71A2
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Optimization of sample preparation and green color imaging using the mNeonGreen fluorescent protein in bacterial cells for photoactivated localization microscopy.
Journal
Scientific Reports
Author(s)
Stockmar I., Feddersen H., Cramer K., Gruber S., Jung K., Bramkamp M., Shin J.Y.
ISSN
2045-2322 (Electronic)
ISSN-L
2045-2322
Publication state
Published
Issued date
2018
Peer-reviewed
Oui
Volume
8
Number
1
Pages
10137
Language
english
Abstract
mNeonGreen fluorescent protein is capable of photo-switching, hence in principle applicable for super-resolution imaging. However, difficult-to-control blinking kinetics that lead to simultaneous emission of multiple nearby mNeonGreen molecules impedes its use for PALM. Here, we determined the on- and off- switching rate and the influence of illumination power on the simultaneous emission. Increasing illumination power reduces the probability of simultaneous emission, but not enough to generate high quality PALM images. Therefore, we introduce a simple data post-processing step that uses temporal and spatial information of molecule localizations to further reduce artifacts arising from simultaneous emission of nearby emitters. We also systematically evaluated various sample preparation steps to establish an optimized protocol to preserve cellular morphology and fluorescence signal. In summary, we propose a workflow for super-resolution imaging with mNeonGreen based on optimization of sample preparation, data acquisition and simple post-acquisition data processing. Application of our protocol enabled us to resolve the expected double band of bacterial cell division protein DivIVA, and to visualize that the chromosome organization protein ParB organized into sub-clusters instead of the typically observed diffraction-limited foci. We expect that our workflow allows a broad use of mNeonGreen for super-resolution microscopy, which is so far difficult to achieve.
Pubmed
Web of science
Open Access
Yes
Create date
29/07/2018 12:11
Last modification date
20/08/2019 15:18
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