Dataset Information

Dissecting Oligomeric States with Photoactivated Localization Microscopy: A Numerical Model.

ABSTRACT: Although photoactivated localization microscopy offers the potential to interrogate protein interactions in the physiological environment of a cell, uncertainties in the detection efficiency of photoactivatable proteins lead to complications with data interpretation. Here, we present a numerical model that provides probabilities to detect neighboring molecules dependent on their oligomerization status, density, detection efficiency, and radius, and can be used to assess oligomeric states or detection efficiencies of two molecular species. © 2020 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

SUBMITTER: Daniels B

PROVIDER: S-EPMC7754424 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dissecting Oligomeric States with Photoactivated Localization Microscopy: A Numerical Model.

Daniels Brian B Wunder Christian C Chen Vanessa V Renz Malte M

Cytometry. Part A : the journal of the International Society for Analytical Cytology 20200618 11

Although photoactivated localization microscopy offers the potential to interrogate protein interactions in the physiological environment of a cell, uncertainties in the detection efficiency of photoactivatable proteins lead to complications with data interpretation. Here, we present a numerical model that provides probabilities to detect neighboring molecules dependent on their oligomerization status, density, detection efficiency, and radius, and can be used to assess oligomeric states or dete ...[more]

PMID: 32558006

Similar Datasets

Project description:Localization-based superresolution microscopy techniques such as Photoactivated Localization Microscopy (PALM) and Stochastic Optical Reconstruction Microscopy (STORM) have allowed investigations of cellular structures with unprecedented optical resolutions. One major obstacle to interpreting superresolution images, however, is the overcounting of molecule numbers caused by fluorophore photoblinking. Using both experimental and simulated images, we determined the effects of photoblinking on the accurate reconstruction of superresolution images and on quantitative measurements of structural dimension and molecule density made from those images. We found that structural dimension and relative density measurements can be made reliably from images that contain photoblinking-related overcounting, but accurate absolute density measurements, and consequently faithful representations of molecule counts and positions in cellular structures, require the application of a clustering algorithm to group localizations that originate from the same molecule. We analyzed how applying a simple algorithm with different clustering thresholds (t(Thresh) and d(Thresh)) affects the accuracy of reconstructed images, and developed an easy method to select optimal thresholds. We also identified an empirical criterion to evaluate whether an imaging condition is appropriate for accurate superresolution image reconstruction with the clustering algorithm. Both the threshold selection method and imaging condition criterion are easy to implement within existing PALM clustering algorithms and experimental conditions. The main advantage of our method is that it generates a superresolution image and molecule position list that faithfully represents molecule counts and positions within a cellular structure, rather than only summarizing structural properties into ensemble parameters. This feature makes it particularly useful for cellular structures of heterogeneous densities and irregular geometries, and allows a variety of quantitative measurements tailored to specific needs of different biological systems.

Dataset Information

Dissecting Oligomeric States with Photoactivated Localization Microscopy: A Numerical Model.

Publications

Dissecting Oligomeric States with Photoactivated Localization Microscopy: A Numerical Model.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets