A Simple and Powerful Analysis of Lateral Subdiffusion Using Single Particle Tracking
In biological membranes, many factors such as cytoskeleton, lipid composition, crowding, and molecular interactions deviate lateral diffusion from the expected random walks. These factors have different effects on diffusion but act simultaneously, so the observed diffusion is a complex mixture of di...
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Published in | Biophysical journal Vol. 113; no. 11; pp. 2452 - 2463 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
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Elsevier Inc
05.12.2017
Biophysical Society The Biophysical Society |
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Abstract | In biological membranes, many factors such as cytoskeleton, lipid composition, crowding, and molecular interactions deviate lateral diffusion from the expected random walks. These factors have different effects on diffusion but act simultaneously, so the observed diffusion is a complex mixture of diffusive behaviors (directed, Brownian, anomalous, or confined). Therefore, commonly used approaches to quantify diffusion based on averaging of the displacements such as the mean square displacement, are not adapted to the analysis of this heterogeneity. We introduce a parameter—the packing coefficient Pc, which gives an estimate of the degree of free movement that a molecule displays in a period of time independently of its global diffusivity. Applying this approach to two different situations (diffusion of a lipid probe and trapping of receptors at synapses), we show that Pc detected and localized temporary changes of diffusive behavior both in time and in space. More importantly, it allowed the detection of periods with very high confinement as well as their frequency and duration, and thus it can be used to calculate the effective kon and koff of scaffolding interactions such as those that immobilize receptors at synapses. |
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AbstractList | In biological membranes, many factors such as cytoskeleton, lipid composition, crowding, and molecular interactions deviate lateral diffusion from the expected random walks. These factors have different effects on diffusion but act simultaneously, so the observed diffusion is a complex mixture of diffusive behaviors (directed, Brownian, anomalous, or confined). Therefore, commonly used approaches to quantify diffusion based on averaging of the displacements such as the mean square displacement, are not adapted to the analysis of this heterogeneity. We introduce a parameter—the packing coefficient Pc, which gives an estimate of the degree of free movement that a molecule displays in a period of time independently of its global diffusivity. Applying this approach to two different situations (diffusion of a lipid probe and trapping of receptors at synapses), we show that Pc detected and localized temporary changes of diffusive behavior both in time and in space. More importantly, it allowed the detection of periods with very high confinement as well as their frequency and duration, and thus it can be used to calculate the effective kon and koff of scaffolding interactions such as those that immobilize receptors at synapses. In biological membranes, many factors such as cytoskeleton, lipid composition, crowding, and molecular interactions deviate lateral diffusion from the expected random walks. These factors have different effects on diffusion but act simultaneously, so the observed diffusion is a complex mixture of diffusive behaviors (directed, Brownian, anomalous, or confined). Therefore, commonly used approaches to quantify diffusion based on averaging of the displacements such as the mean square displacement, are not adapted to the analysis of this heterogeneity. We introduce a parameter—the packing coefficient Pc , which gives an estimate of the degree of free movement that a molecule displays in a period of time independently of its global diffusivity. Applying this approach to two different situations (diffusion of a lipid probe and trapping of receptors at synapses), we show that Pc detected and localized temporary changes of diffusive behavior both in time and in space. More importantly, it allowed the detection of periods with very high confinement as well as their frequency and duration, and thus it can be used to calculate the effective k on and k off of scaffolding interactions such as those that immobilize receptors at synapses. In biological membranes, many factors such as cytoskeleton, lipid composition, crowding, and molecular interactions deviate lateral diffusion from the expected random walks. These factors have different effects on diffusion but act simultaneously, so the observed diffusion is a complex mixture of diffusive behaviors (directed, Brownian, anomalous, or confined). Therefore, commonly used approaches to quantify diffusion based on averaging of the displacements such as the mean square displacement, are not adapted to the analysis of this heterogeneity. We introduce a parameter-the packing coefficient Pc, which gives an estimate of the degree of free movement that a molecule displays in a period of time independently of its global diffusivity. Applying this approach to two different situations (diffusion of a lipid probe and trapping of receptors at synapses), we show that Pc detected and localized temporary changes of diffusive behavior both in time and in space. More importantly, it allowed the detection of periods with very high confinement as well as their frequency and duration, and thus it can be used to calculate the effective k and k of scaffolding interactions such as those that immobilize receptors at synapses. |
Author | Renner, Marianne Levi, Sabine Hennekinne, Laetitia Wang, Lili Triller, Antoine |
AuthorAffiliation | 2 INSERM UMR-S 839, Université Pierre et Marie Curie, Institut du Fer à Moulin, Paris, France 1 École Normale Supérieure, PSL Research University, CNRS, INSERM, Institute of Biology (IBENS), Paris, France |
AuthorAffiliation_xml | – name: 2 INSERM UMR-S 839, Université Pierre et Marie Curie, Institut du Fer à Moulin, Paris, France – name: 1 École Normale Supérieure, PSL Research University, CNRS, INSERM, Institute of Biology (IBENS), Paris, France |
Author_xml | – sequence: 1 givenname: Marianne surname: Renner fullname: Renner, Marianne email: marianne.renner@inserm.fr organization: École Normale Supérieure, PSL Research University, CNRS, INSERM, Institute of Biology (IBENS), Paris, France – sequence: 2 givenname: Lili surname: Wang fullname: Wang, Lili organization: École Normale Supérieure, PSL Research University, CNRS, INSERM, Institute of Biology (IBENS), Paris, France – sequence: 3 givenname: Sabine surname: Levi fullname: Levi, Sabine organization: INSERM UMR-S 839, Université Pierre et Marie Curie, Institut du Fer à Moulin, Paris, France – sequence: 4 givenname: Laetitia surname: Hennekinne fullname: Hennekinne, Laetitia organization: École Normale Supérieure, PSL Research University, CNRS, INSERM, Institute of Biology (IBENS), Paris, France – sequence: 5 givenname: Antoine surname: Triller fullname: Triller, Antoine email: triller@biologie.ens.fr organization: École Normale Supérieure, PSL Research University, CNRS, INSERM, Institute of Biology (IBENS), Paris, France |
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SubjectTerms | Animals Biochemistry, Molecular Biology Biological membranes Biophysics Cell Biophysics Cell Membrane - metabolism Cytoskeleton Diffusion Diffusion effects Lateral diffusion Life Sciences Lipid composition Lipids Mathematical analysis Membranes Molecular interactions Molecules Neurons - cytology Particle tracking Random walk Rats Receptors Scaffolding Single Molecule Imaging Synapses |
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Title | A Simple and Powerful Analysis of Lateral Subdiffusion Using Single Particle Tracking |
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