Recovering mixtures of fast-diffusing states from short single-particle trajectories.

Animals Bayes Theorem Diffusion Mammals Single Molecule Imaging / methods
U2OS osteosarcoma biochemistry chemical biology human mammalian cell culture physics of living systems single-particle tracking

Journal

eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614

Informations de publication

Date de publication:
06 09 2022
Historique:
received: 07 05 2021
accepted: 04 08 2022
entrez: 6 9 2022
pubmed: 7 9 2022
medline: 9 9 2022
Statut: epublish

Résumé

Single-particle tracking (SPT) directly measures the dynamics of proteins in living cells and is a powerful tool to dissect molecular mechanisms of cellular regulation. Interpretation of SPT with fast-diffusing proteins in mammalian cells, however, is complicated by technical limitations imposed by fast image acquisition. These limitations include short trajectory length due to photobleaching and shallow depth of field, high localization error due to the low photon budget imposed by short integration times, and cell-to-cell variability. To address these issues, we investigated methods inspired by Bayesian nonparametrics to infer distributions of state parameters from SPT data with short trajectories, variable localization precision, and absence of prior knowledge about the number of underlying states. We discuss the advantages and disadvantages of these approaches relative to other frameworks for SPT analysis.

Identifiants

DOI: 10.7554/eLife.70169 PMID: 36066004 PMC: PMC9451534
pubmed: 36066004
doi: 10.7554/eLife.70169
pii: 70169
pmc: PMC9451534
doi:
pii:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Howard Hughes Medical Institute
ID : CC34430
Pays : United States

Informations de copyright

© 2022, Heckert et al.

Déclaration de conflit d'intérêts

AH, LD, RT, XD No competing interests declared

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Auteurs

Alec Heckert (A)

Department of Molecular and Cell Biology, Li Ka Shing Center for Biomedical and Health Sciences, University of California, Berkeley, Berkeley, United States.
ORCID: 0000-0001-8748-6645

Liza Dahal (L)

Department of Molecular and Cell Biology, Li Ka Shing Center for Biomedical and Health Sciences, University of California, Berkeley, Berkeley, United States.
CIRM Center of Excellence, University of California, Berkeley, Berkeley, United States.

Robert Tjian (R)

CIRM Center of Excellence, University of California, Berkeley, Berkeley, United States.
Howard Hughes Medical Institute, Berkeley, United States.

Xavier Darzacq (X)

Department of Molecular and Cell Biology, Li Ka Shing Center for Biomedical and Health Sciences, University of California, Berkeley, Berkeley, United States.
ORCID: 0000-0003-2537-8395

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Classifications MeSH

questionsmedicales.fr › Eucaryotes › Animaux › Recovering mixtures of fast-diffusing states...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Statistiques comme sujet › Probabilité › Théorème de Bayes › Recovering mixtures of fast-diffusing states...
questionsmedicales.fr › Phénomènes chimiques › Diffusion › Recovering mixtures of fast-diffusing states...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Recovering mixtures of fast-diffusing states...
questionsmedicales.fr › Techniques d'investigation › Techniques de sonde moléculaire › Imagerie moléculaire › Imagerie de molécules uniques › Recovering mixtures of fast-diffusing states...