A quantitative comparison of single-dye tracking analysis tools using Monte Carlo simulations

Single-particle tracking (SPT) is widely used to study processes from membrane receptor organization to the dynamics of RNAs in living cells. While single-dye labeling strategies have the benefit of being minimally invasive, this comes at the expense of data quality; typically a data set of short tr...

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Main Authors: Weimann, L, Ganzinger, K, McColl, J, Irvine, K, Davis, S, Gay, N, Bryant, C, Klenerman, D
Format: Journal article
Language:English
Published: Public Library of Science 2013
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author Weimann, L
Ganzinger, K
McColl, J
Irvine, K
Davis, S
Gay, N
Bryant, C
Klenerman, D
author_facet Weimann, L
Ganzinger, K
McColl, J
Irvine, K
Davis, S
Gay, N
Bryant, C
Klenerman, D
author_sort Weimann, L
collection OXFORD
description Single-particle tracking (SPT) is widely used to study processes from membrane receptor organization to the dynamics of RNAs in living cells. While single-dye labeling strategies have the benefit of being minimally invasive, this comes at the expense of data quality; typically a data set of short trajectories is obtained and analyzed by means of the mean square displacements (MSD) or the distribution of the particles' displacements in a set time interval (jump distance, JD). To evaluate the applicability of both approaches, a quantitative comparison of both methods under typically encountered experimental conditions is necessary. Here we use Monte Carlo simulations to systematically compare the accuracy of diffusion coefficients (D-values) obtained for three cases: one population of diffusing species, two populations with different D-values, and a population switching between two D-values. For the first case we find that the MSD gives more or equally accurate results than the JD analysis (relative errors of D-values <6%). If two diffusing species are present or a particle undergoes a motion change, the JD analysis successfully distinguishes both species (relative error <5%). Finally we apply the JD analysis to investigate the motion of endogenous LPS receptors in live macrophages before and after treatment with methyl-β-cyclodextrin and latrunculin B.
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spelling oxford-uuid:bf0dd55f-50b2-470c-898c-aac959c44f282022-03-27T05:44:36ZA quantitative comparison of single-dye tracking analysis tools using Monte Carlo simulationsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:bf0dd55f-50b2-470c-898c-aac959c44f28EnglishSymplectic Elements at OxfordPublic Library of Science2013Weimann, LGanzinger, KMcColl, JIrvine, KDavis, SGay, NBryant, CKlenerman, DSingle-particle tracking (SPT) is widely used to study processes from membrane receptor organization to the dynamics of RNAs in living cells. While single-dye labeling strategies have the benefit of being minimally invasive, this comes at the expense of data quality; typically a data set of short trajectories is obtained and analyzed by means of the mean square displacements (MSD) or the distribution of the particles' displacements in a set time interval (jump distance, JD). To evaluate the applicability of both approaches, a quantitative comparison of both methods under typically encountered experimental conditions is necessary. Here we use Monte Carlo simulations to systematically compare the accuracy of diffusion coefficients (D-values) obtained for three cases: one population of diffusing species, two populations with different D-values, and a population switching between two D-values. For the first case we find that the MSD gives more or equally accurate results than the JD analysis (relative errors of D-values <6%). If two diffusing species are present or a particle undergoes a motion change, the JD analysis successfully distinguishes both species (relative error <5%). Finally we apply the JD analysis to investigate the motion of endogenous LPS receptors in live macrophages before and after treatment with methyl-β-cyclodextrin and latrunculin B.
spellingShingle Weimann, L
Ganzinger, K
McColl, J
Irvine, K
Davis, S
Gay, N
Bryant, C
Klenerman, D
A quantitative comparison of single-dye tracking analysis tools using Monte Carlo simulations
title A quantitative comparison of single-dye tracking analysis tools using Monte Carlo simulations
title_full A quantitative comparison of single-dye tracking analysis tools using Monte Carlo simulations
title_fullStr A quantitative comparison of single-dye tracking analysis tools using Monte Carlo simulations
title_full_unstemmed A quantitative comparison of single-dye tracking analysis tools using Monte Carlo simulations
title_short A quantitative comparison of single-dye tracking analysis tools using Monte Carlo simulations
title_sort quantitative comparison of single dye tracking analysis tools using monte carlo simulations
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