Academic Journal

Methodology for Quantitative Characterization of Fluorophore Photoswitching to Predict Superresolution Microscopy Image Quality

التفاصيل البيبلوغرافية
العنوان: Methodology for Quantitative Characterization of Fluorophore Photoswitching to Predict Superresolution Microscopy Image Quality
المؤلفون: Bittel, Amy M., Nickerson, Andrew, Saldivar, Isaac S., Dolman, Nick J., Nan, Xiaolin, Gibbs, Summer L.
المصدر: Scientific Reports ; volume 6, issue 1 ; ISSN 2045-2322
بيانات النشر: Springer Science and Business Media LLC
سنة النشر: 2016
الوصف: Single-molecule localization microscopy (SMLM) image quality and resolution strongly depend on the photoswitching properties of fluorophores used for sample labeling. Development of fluorophores with optimized photoswitching will considerably improve SMLM spatial and spectral resolution. Currently, evaluating fluorophore photoswitching requires protein-conjugation before assessment mandating specific fluorophore functionality, which is a major hurdle for systematic characterization. Herein, we validated polyvinyl alcohol (PVA) as a single-molecule environment to efficiently quantify the photoswitching properties of fluorophores and identified photoswitching properties predictive of quality SMLM images. We demonstrated that the same fluorophore photoswitching properties measured in PVA films and using antibody adsorption, a protein-conjugation environment analogous to labeled cells, were significantly correlated to microtubule width and continuity, surrogate measures of SMLM image quality. Defining PVA as a fluorophore photoswitching screening platform will facilitate SMLM fluorophore development and optimal image buffer assessment through facile and accurate photoswitching property characterization, which translates to SMLM fluorophore imaging performance.
نوع الوثيقة: article in journal/newspaper
اللغة: English
DOI: 10.1038/srep29687
الاتاحة: http://dx.doi.org/10.1038/srep29687
https://www.nature.com/articles/srep29687.pdf
https://www.nature.com/articles/srep29687
Rights: https://creativecommons.org/licenses/by/4.0 ; https://creativecommons.org/licenses/by/4.0
رقم الانضمام: edsbas.AA85D988
قاعدة البيانات: BASE