mapping-molecular-diffusion-plasma-membrane-multiple-target-tracing

Mapping Molecular Diffusion in the Plasma Membrane by Multiple-Target Tracing (MTT)

Our goal is to obtain a comprehensive description of molecular processes occurring at cellular membranes in different biological functions. We aim at ...

spot-variation-fluorescence-correlation-spectroscopy-for-analysis

Spot Variation Fluorescence Correlation Spectroscopy for Analysis of Molecular Diffusion at the Plasma Membrane of Living Cells

Dynamic biological processes in living cells, including those associated with plasma membrane organization, occur on various spatial and temporal scales, ...

Technopôle de Château-Gombert

Aix-Marseille University

Aix Marseille Univ

Although the highly dynamic and mosaic organization of the plasma membrane is well-recognized, depicting a resolved, global view of this organization remains challenging. We present an analytical single-particle tracking (SPT) method and tool, multiple-target tracing (MTT), that takes advantage of the high spatial resolution provided by single-fluorophore sensitivity. MTT can be used to generate dynamic maps at high densities of tracked particles, thereby providing global representation of molecular dynamics in cell membranes. Deflation by subtracting detected peaks allows detection of lower-intensity peaks. We exhaustively detected particles using MTT, with performance reaching theoretical limits, and then reconnected trajectories integrating the statistical information from past trajectories. We demonstrate the potential of this method by applying it to the epidermal growth factor receptor (EGFR) labeled with quantum dots (Qdots), in the plasma membrane of live cells. We anticipate the use of MTT to explore molecular dynamics and interactions at the cell membrane.

Dynamic multiple-target tracing to probe spatiotemporal cartography of cell membranes.

Single-molecule localization microscopy (SMLM) enables the production of high-resolution images by imaging spatially isolated fluorescent particles. Although challenging, the result of SMLM analysis lists the position of individual molecules, leading to a valuable quantification of the stoichiometry and spatial organization of molecular actors. Both the signal/noise ratio and the density (D), i.e., the number of fluorescent particles per μm per frame, have previously been identified as determining factors for reaching a given SMLM precision. Establishing a comprehensive theoretical study relying on these two parameters is therefore of central interest to delineate the achievable limits for accurate SMLM observations. Our study reports that in absence of prior knowledge of the signal intensity α, the density effect on particle localization is more prominent than that anticipated from theoretical studies performed at known α. A first limit appears when, under a low-density hypothesis (i.e., one-Gaussian fitting hypothesis), any fluorescent particle distant by less than ∼600 nm from the particle of interest biases its localization. In fact, all particles should be accounted for, even those dimly fluorescent, to ascertain unbiased localization of any surrounding particles. Moreover, even under a high-density hypothesis (i.e., multi-Gaussian fitting hypothesis), a second limit arises because of the impossible distinction of particles located too closely. An increase in D is thus likely to deteriorate the localization precision, the image reconstruction, and more generally the quantification accuracy. Our study firstly provides a density-signal/noise ratio space diagram for use as a guide in data recording toward reaching an achievable SMLM resolution. Additionally, it leads to the identification of the essential requirements for implementing UNLOC, a parameter-free and fast computing algorithm approaching the Cramér-Rao bound for particles at high-density per frame and without any prior knowledge of their intensity. UNLOC is available as an ImageJ plugin.

ArticleTotal : 2	Year
Publication title Cited by 4	2012
Publication title Cited by 10	2020

Article	Year
Applied optics\| PubMed ID: 12389988	2002
Journal of the Optical Society of America. A, Optics, image science, and vision\| PubMed ID: 15603063	2004
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society\| PubMed ID: 18237972	2003
Dynamic multiple-target tracing to probe spatiotemporal cartography of cell membranes. Nature methods\| PubMed ID: 18604216	2008
Optics letters\| PubMed ID: 19037438	2008
Optics express\| PubMed ID: 19532364	2007
A Theoretical High-Density Nanoscopy Study Leads to the Design of UNLOC, a Parameter-free Algorithm. Biophysical journal\| PubMed ID: 30029772	2018

Nicolas Bertaux

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