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Lateral diffusion of CD14 and TLR2 in macrophage plasma membrane assessed by raster image correlation spectroscopy and single particle tracking.

ABSTRACT: The diffusion of membrane receptors is central to many biological processes, such as signal transduction, molecule translocation, and ion transport, among others; consequently, several advanced fluorescence microscopy techniques have been developed to measure membrane receptor mobility within live cells. The membrane-anchored receptor cluster of differentiation 14 (CD14) and the transmembrane toll-like receptor 2 (TLR2) are important receptors in the plasma membrane of macrophages that activate the intracellular signaling cascade in response to pathogenic stimuli. The aim of the present work was to compare the diffusion coefficients of CD14 and TLR2 on the apical and basal membranes of macrophages using two fluorescence-based methods: raster image correlation spectroscopy (RICS) and single particle tracking (SPT). In the basal membrane, the diffusion coefficients obtained from SPT and RICS were found to be comparable and revealed significantly faster diffusion of CD14 compared with TLR2. In addition, RICS showed that the diffusion of both receptors was significantly faster in the apical membrane than in the basal membrane, suggesting diffusion hindrance by the adhesion of the cells to the substrate. This finding highlights the importance of selecting the appropriate membrane (i.e., basal or apical) and corresponding method when measuring receptor diffusion in live cells. Accurately knowing the diffusion coefficient of two macrophage receptors involved in the response to pathogen insults will facilitate the study of changes that occur in signaling in these cells as a result of aging and disease.

SUBMITTER: Makaremi S

PROVIDER: S-EPMC7652837 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Single-particle tracking is an important technique in the life sciences to understand the kinetics of biomolecules. The analysis of apparent diffusion coefficients in vivo, for example, enables researchers to determine whether biomolecules are moving alone, as part of a larger complex, or are bound to large cellular components such as the membrane or chromosomal DNA. A remaining challenge has been to retrieve quantitative kinetic models, especially for molecules that rapidly switch between different diffusional states. Here, we present analytical diffusion distribution analysis (anaDDA), a framework that allows for extracting transition rates from distributions of apparent diffusion coefficients calculated from short trajectories that feature less than 10 localizations per track. Under the assumption that the system is Markovian and diffusion is purely Brownian, we show that theoretically predicted distributions accurately match simulated distributions and that anaDDA outperforms existing methods to retrieve kinetics, especially in the fast regime of 0.1-10 transitions per imaging frame. AnaDDA does account for the effects of confinement and tracking window boundaries. Furthermore, we added the option to perform global fitting of data acquired at different frame times to allow complex models with multiple states to be fitted confidently. Previously, we have started to develop anaDDA to investigate the target search of CRISPR-Cas complexes. In this work, we have optimized the algorithms and reanalyzed experimental data of DNA polymerase I diffusing in live Escherichia coli. We found that long-lived DNA interaction by DNA polymerase are more abundant upon DNA damage, suggesting roles in DNA repair. We further revealed and quantified fast DNA probing interactions that last shorter than 10 ms. AnaDDA pushes the boundaries of the timescale of interactions that can be probed with single-particle tracking and is a mathematically rigorous framework that can be further expanded to extract detailed information about the behavior of biomolecules in living cells.

Dataset Information

Lateral diffusion of CD14 and TLR2 in macrophage plasma membrane assessed by raster image correlation spectroscopy and single particle tracking.

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