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Effects of resolution, target density and labeling on co-localization estimates – nanoscopy and modified algorithms to suppress false positives
KTH, School of Engineering Sciences (SCI), Applied Physics, Experimental Biomolecular Physics.
KTH, School of Engineering Sciences (SCI), Applied Physics, Experimental Biomolecular Physics.
Karolinska Institute, Department of Microbiology, Tumor and Cell Biology .
Karolinska Institute, Department of Microbiology, Tumor and Cell Biology .
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Co-localization analysis of fluorescence images is an important and extensively used tool to quantify molecular interactions in cells. In recent years, fluorescence nanoscopy techniques have made great progress and approach resolutions close to molecular dimensions. Although a strong increase in image resolution evidently influences different co-localization estimates it has to date not been systematically evaluated to what extent co-localization analyses can benefit from such techniques. . In this work, we apply simulations and resolution-tunable stimulated emission depletion (STED) microscopy to evaluate how resolution, molecular density and label size for the targeted molecules, as well as intensity variation and signal-to-noise ratio influence the estimates of the most commonly used co-localization algorithms (Pearson correlation coefficient, Manders M1 & M2 coefficients, and the image cross correlation spectroscopy (ICCS) method). We investigated the practically measureable extents of co-localization when using STED microscopy with positive and negative control samples and discussed the strengths and weaknesses of using nanoscopic techniques for co-localization studies. At a typical optical resolution of a confocal microscope (200-300 nm) our results indicate that the extent of co-localization is typically over-estimated by the tested algorithms, especially at high molecular densities. Only minor effects of this kind were observed at higher resolutions (< 60 nm). Apart from higher resolution, we introduced as an additional remedy a statistical variant of Costes threshold searching algorithm to set intensity thresholds separating background noise from signals. By this variant, combined with correlation-based methods like the Pearson coefficient and the ICCS approach, false positives at confocal resolutions and high molecular densities were found to be strongly suppressed.

Keyword [en]
co-localization analysis, automatic threshold search, stimulated emission depletion (STED) microscopy
National Category
Biophysics Physical Sciences
Identifiers
URN: urn:nbn:se:kth:diva-146169OAI: oai:DiVA.org:kth-146169DiVA: diva2:722577
Note

QS 2014

Available from: 2014-06-09 Created: 2014-06-09 Last updated: 2014-06-10Bibliographically approved

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CiteExportLink to record
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  • apa
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Output format
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