Photobleaching step analysis for robust determination of protein complex stoichiometries

• Verfasst von: Hummert, Johan [VerfasserIn]
• Verfasst von: Yserentant, Klaus [VerfasserIn]
• Verfasst von: Fink, Theresa [VerfasserIn]
• Verfasst von: Euchner, Jonas [VerfasserIn]
• Verfasst von: Ho, Yin Xin [VerfasserIn]
• Verfasst von: Tashev, Stanimir Asenov [VerfasserIn]
• Verfasst von: Herten, Dirk-Peter [VerfasserIn]
• Titel: Photobleaching step analysis for robust determination of protein complex stoichiometries
• Verf.angabe: Johan Hummert, Klaus Yserentant, Theresa Fink, Jonas Euchner, Yin Xin Ho, Stanimir Asenov Tashev, and Dirk-Peter Herten
• E-Jahr: 2021
• Jahr: 29 Oct 2021
• Umfang: 12 S.
• Fussnoten: Gesehen am 30.03.2022
• Titel Quelle: Enthalten in: Molecular biology of the cell
• Ort Quelle: Bethesda, Md. : American Society for Cell Biology, 1992
• Jahr Quelle: 2021
• Band/Heft Quelle: 32(2021), 21, Artikel-ID ar35, Seite 1-12
• ISSN Quelle: 1939-4586
• DOI: doi:10.1091/mbc.E20-09-0568
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1796012971

Abstract

The counting of discrete photobleaching steps in fluorescence microscopy is ideally suited to study protein complex stoichiometry in situ. The counting range of photobleaching step analysis has been significantly improved with more-sophisticated algorithms for step detection, albeit at an increasing computational cost and with the necessity for high-quality data. Here, we address concerns regarding robustness, automation, and experimental validation, optimizing both data acquisition and analysis. To make full use of the potential of photobleaching step analysis, we evaluate various labeling strategies with respect to their molecular brightness, photostability, and photoblinking. The developed analysis algorithm focuses on automation and computational efficiency. Moreover, we validate the developed methods with experimental data acquired on DNA origami labeled with defined fluorophore numbers, demonstrating counting of up to 35 fluorophores. Finally, we show the power of the combination of optimized trace acquisition and automated data analysis by counting labeled nucleoporin 107 in nuclear pore complexes of intact U2OS cells. The successful in situ application promotes this framework as a new resource enabling cell biologists to robustly determine the stoichiometries of molecular assemblies at the single-molecule level in an automated manner.