Automated analysis of single-molecule photobleaching data by statistical modeling of spot populations

• Verfasst von: Liesche, Clarissa [VerfasserIn]
• Verfasst von: Grußmayer, Kristin Stefanie [VerfasserIn]
• Verfasst von: Ludwig, Michael [VerfasserIn]
• Verfasst von: Wörz, Stefan [VerfasserIn]
• Verfasst von: Rohr, Karl [VerfasserIn]
• Verfasst von: Herten, Dirk-Peter [VerfasserIn]
• Verfasst von: Beaudouin, Joël [VerfasserIn]
• Verfasst von: Eils, Roland [VerfasserIn]
• Titel: Automated analysis of single-molecule photobleaching data by statistical modeling of spot populations
• Verf.angabe: Clarissa Liesche, Kristin S. Grußmayer, Michael Ludwig, Stefan Wörz, Karl Rohr, Dirk-Peter Herten, Joël Beaudouin, and Roland Eils
• E-Jahr: 2015
• Jahr: 1 December 2015
• Umfang: 11 S.
• Fussnoten: Gesehen am 23.06.2020
• Titel Quelle: Enthalten in: Biophysical journal
• Ort Quelle: Cambridge, Mass. : Cell Press, 1960
• Jahr Quelle: 2015
• Band/Heft Quelle: 109(2015), 11, Seite 2352-2362
• ISSN Quelle: 1542-0086
• DOI: doi:10.1016/j.bpj.2015.10.035
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1701940019

Abstract

The number of fluorophores within a molecule complex can be revealed by single-molecule photobleaching imaging. A widely applied strategy to analyze intensity traces over time is the quantification of photobleaching step counts. However, several factors can limit and bias the detection of photobleaching steps, including noise, high numbers of fluorophores, and the possibility that several photobleaching events occur almost simultaneously. In this study, we propose a new approach, to our knowledge, to determine the fluorophore number that correlates the intensity decay of a population of molecule complexes with the decay of the number of visible complexes. We validated our approach using single and fourfold Atto-labeled DNA strands. As an example we estimated the subunit stoichiometry of soluble CD95L using GFP fusion proteins. To assess the precision of our method we performed in silico experiments showing that the estimates are not biased for experimentally observed intensity fluctuations and that the relative precision remains constant with increasing number of fluorophores. In case of fractional fluorescent labeling, our simulations predicted that the fluorophore number estimate corresponds to the product of the true fluorophore number with the labeling fraction. Our method, denoted by spot number and intensity correlation (SONIC), is fully automated, robust to noise, and does not require the counting of photobleaching events.