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Correlation Functions Quantify Super-Resolution Images and Estimate Apparent Clustering Due to Over-Counting

Author

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  • Sarah L Veatch
  • Benjamin B Machta
  • Sarah A Shelby
  • Ethan N Chiang
  • David A Holowka
  • Barbara A Baird

Abstract

We present an analytical method using correlation functions to quantify clustering in super-resolution fluorescence localization images and electron microscopy images of static surfaces in two dimensions. We use this method to quantify how over-counting of labeled molecules contributes to apparent self-clustering and to calculate the effective lateral resolution of an image. This treatment applies to distributions of proteins and lipids in cell membranes, where there is significant interest in using electron microscopy and super-resolution fluorescence localization techniques to probe membrane heterogeneity. When images are quantified using pair auto-correlation functions, the magnitude of apparent clustering arising from over-counting varies inversely with the surface density of labeled molecules and does not depend on the number of times an average molecule is counted. In contrast, we demonstrate that over-counting does not give rise to apparent co-clustering in double label experiments when pair cross-correlation functions are measured. We apply our analytical method to quantify the distribution of the IgE receptor (FcεRI) on the plasma membranes of chemically fixed RBL-2H3 mast cells from images acquired using stochastic optical reconstruction microscopy (STORM/dSTORM) and scanning electron microscopy (SEM). We find that apparent clustering of FcεRI-bound IgE is dominated by over-counting labels on individual complexes when IgE is directly conjugated to organic fluorophores. We verify this observation by measuring pair cross-correlation functions between two distinguishably labeled pools of IgE-FcεRI on the cell surface using both imaging methods. After correcting for over-counting, we observe weak but significant self-clustering of IgE-FcεRI in fluorescence localization measurements, and no residual self-clustering as detected with SEM. We also apply this method to quantify IgE-FcεRI redistribution after deliberate clustering by crosslinking with two distinct trivalent ligands of defined architectures, and we evaluate contributions from both over-counting of labels and redistribution of proteins.

Suggested Citation

  • Sarah L Veatch & Benjamin B Machta & Sarah A Shelby & Ethan N Chiang & David A Holowka & Barbara A Baird, 2012. "Correlation Functions Quantify Super-Resolution Images and Estimate Apparent Clustering Due to Over-Counting," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-13, February.
  • Handle: RePEc:plo:pone00:0031457
    DOI: 10.1371/journal.pone.0031457
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    Cited by:

    1. Carla Coltharp & Rene P Kessler & Jie Xiao, 2012. "Accurate Construction of Photoactivated Localization Microscopy (PALM) Images for Quantitative Measurements," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-15, December.
    2. Angela B Schmider & Melissa Vaught & Nicholas C Bauer & Hunter L Elliott & Matthew D Godin & Giorgianna E Ellis & Peter A Nigrovic & Roy J Soberman, 2019. "The organization of leukotriene biosynthesis on the nuclear envelope revealed by single molecule localization microscopy and computational analyses," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-19, February.
    3. Samsuzzoha Mondal & Karthik Narayan & Samuel Botterbusch & Imania Powers & Jason Zheng & Honey Priya James & Rui Jin & Tobias Baumgart, 2022. "Multivalent interactions between molecular components involved in fast endophilin mediated endocytosis drive protein phase separation," Nature Communications, Nature, vol. 13(1), pages 1-20, December.
    4. Sameera Vipat & Dipika Gupta & Sagun Jonchhe & Hele Anderspuk & Eli Rothenberg & Tatiana N. Moiseeva, 2022. "The non-catalytic role of DNA polymerase epsilon in replication initiation in human cells," Nature Communications, Nature, vol. 13(1), pages 1-15, December.

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