Power-law behaviour of transcription factor dynamics at the single-molecule level implies a continuum affinity model

Autores
Garcia, David A.; Fettweis, Gregory; Presman, Diego Martin; Paakinaho, Ville; Jarzynski, Christopher; Upadhyaya, Arpita; Hager, Gordon L.
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Single-molecule tracking (SMT) allows the study of transcription factor (TF) dynamics in the nucleus, giving important information regarding the diffusion and binding behavior of these proteins in the nuclear environment. Dwell time distributions obtained by SMT for most TFs appear to follow bi-exponential behavior. This has been ascribed to two discrete populations of TFs-one non-specifically bound to chromatin and another specifically bound to target sites, as implied by decades of biochemical studies. However, emerging studies suggest alternate models for dwell-time distributions, indicating the existence of more than two populations of TFs (multi-exponential distribution), or even the absence of discrete states altogether (power-law distribution). Here, we present an analytical pipeline to evaluate which model best explains SMT data. We find that a broad spectrum of TFs (including glucocorticoid receptor, oestrogen receptor, FOXA1, CTCF) follow a power-law distribution of dwell-times, blurring the temporal line between non-specific and specific binding, suggesting that productive binding may involve longer binding events than previously believed. From these observations, we propose a continuum of affinities model to explain TF dynamics, that is consistent with complex interactions of TFs with multiple nuclear domains as well as binding and searching on the chromatin template.
Fil: Garcia, David A.. National Institutes of Health; Estados Unidos
Fil: Fettweis, Gregory. National Institutes of Health; Estados Unidos
Fil: Presman, Diego Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; Argentina
Fil: Paakinaho, Ville. University Of Eastern Finland.; Finlandia
Fil: Jarzynski, Christopher. University of Maryland; Estados Unidos
Fil: Upadhyaya, Arpita. University of Maryland; Estados Unidos
Fil: Hager, Gordon L.. National Institutes of Health; Estados Unidos
Materia
POWER-LAW
TRANSCRIPTION FACTOR
GLUCOCORTICOID RECEPTOR
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/175225
Acceder
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spelling Power-law behaviour of transcription factor dynamics at the single-molecule level implies a continuum affinity modelGarcia, David A.Fettweis, GregoryPresman, Diego MartinPaakinaho, VilleJarzynski, ChristopherUpadhyaya, ArpitaHager, Gordon L.POWER-LAWTRANSCRIPTION FACTORGLUCOCORTICOID RECEPTORhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Single-molecule tracking (SMT) allows the study of transcription factor (TF) dynamics in the nucleus, giving important information regarding the diffusion and binding behavior of these proteins in the nuclear environment. Dwell time distributions obtained by SMT for most TFs appear to follow bi-exponential behavior. This has been ascribed to two discrete populations of TFs-one non-specifically bound to chromatin and another specifically bound to target sites, as implied by decades of biochemical studies. However, emerging studies suggest alternate models for dwell-time distributions, indicating the existence of more than two populations of TFs (multi-exponential distribution), or even the absence of discrete states altogether (power-law distribution). Here, we present an analytical pipeline to evaluate which model best explains SMT data. We find that a broad spectrum of TFs (including glucocorticoid receptor, oestrogen receptor, FOXA1, CTCF) follow a power-law distribution of dwell-times, blurring the temporal line between non-specific and specific binding, suggesting that productive binding may involve longer binding events than previously believed. From these observations, we propose a continuum of affinities model to explain TF dynamics, that is consistent with complex interactions of TFs with multiple nuclear domains as well as binding and searching on the chromatin template.Fil: Garcia, David A.. National Institutes of Health; Estados UnidosFil: Fettweis, Gregory. National Institutes of Health; Estados UnidosFil: Presman, Diego Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Paakinaho, Ville. University Of Eastern Finland.; FinlandiaFil: Jarzynski, Christopher. University of Maryland; Estados UnidosFil: Upadhyaya, Arpita. University of Maryland; Estados UnidosFil: Hager, Gordon L.. National Institutes of Health; Estados UnidosOxford University Press2021-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/175225Garcia, David A.; Fettweis, Gregory; Presman, Diego Martin; Paakinaho, Ville; Jarzynski, Christopher; et al.; Power-law behaviour of transcription factor dynamics at the single-molecule level implies a continuum affinity model; Oxford University Press; Nucleic Acids Research; 49; 12; 7-2021; 6605-66201362-4962CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1093/nar/gkab072info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:05:17Zoai:ri.conicet.gov.ar:11336/175225instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:05:17.45CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Power-law behaviour of transcription factor dynamics at the single-molecule level implies a continuum affinity model
title Power-law behaviour of transcription factor dynamics at the single-molecule level implies a continuum affinity model
spellingShingle Power-law behaviour of transcription factor dynamics at the single-molecule level implies a continuum affinity model
Garcia, David A.
POWER-LAW
TRANSCRIPTION FACTOR
GLUCOCORTICOID RECEPTOR
title_short Power-law behaviour of transcription factor dynamics at the single-molecule level implies a continuum affinity model
title_full Power-law behaviour of transcription factor dynamics at the single-molecule level implies a continuum affinity model
title_fullStr Power-law behaviour of transcription factor dynamics at the single-molecule level implies a continuum affinity model
title_full_unstemmed Power-law behaviour of transcription factor dynamics at the single-molecule level implies a continuum affinity model
title_sort Power-law behaviour of transcription factor dynamics at the single-molecule level implies a continuum affinity model
dc.creator.none.fl_str_mv Garcia, David A.
Fettweis, Gregory
Presman, Diego Martin
Paakinaho, Ville
Jarzynski, Christopher
Upadhyaya, Arpita
Hager, Gordon L.
author Garcia, David A.
author_facet Garcia, David A.
Fettweis, Gregory
Presman, Diego Martin
Paakinaho, Ville
Jarzynski, Christopher
Upadhyaya, Arpita
Hager, Gordon L.
author_role author
author2 Fettweis, Gregory
Presman, Diego Martin
Paakinaho, Ville
Jarzynski, Christopher
Upadhyaya, Arpita
Hager, Gordon L.
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv POWER-LAW
TRANSCRIPTION FACTOR
GLUCOCORTICOID RECEPTOR
topic POWER-LAW
TRANSCRIPTION FACTOR
GLUCOCORTICOID RECEPTOR
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Single-molecule tracking (SMT) allows the study of transcription factor (TF) dynamics in the nucleus, giving important information regarding the diffusion and binding behavior of these proteins in the nuclear environment. Dwell time distributions obtained by SMT for most TFs appear to follow bi-exponential behavior. This has been ascribed to two discrete populations of TFs-one non-specifically bound to chromatin and another specifically bound to target sites, as implied by decades of biochemical studies. However, emerging studies suggest alternate models for dwell-time distributions, indicating the existence of more than two populations of TFs (multi-exponential distribution), or even the absence of discrete states altogether (power-law distribution). Here, we present an analytical pipeline to evaluate which model best explains SMT data. We find that a broad spectrum of TFs (including glucocorticoid receptor, oestrogen receptor, FOXA1, CTCF) follow a power-law distribution of dwell-times, blurring the temporal line between non-specific and specific binding, suggesting that productive binding may involve longer binding events than previously believed. From these observations, we propose a continuum of affinities model to explain TF dynamics, that is consistent with complex interactions of TFs with multiple nuclear domains as well as binding and searching on the chromatin template.
Fil: Garcia, David A.. National Institutes of Health; Estados Unidos
Fil: Fettweis, Gregory. National Institutes of Health; Estados Unidos
Fil: Presman, Diego Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; Argentina
Fil: Paakinaho, Ville. University Of Eastern Finland.; Finlandia
Fil: Jarzynski, Christopher. University of Maryland; Estados Unidos
Fil: Upadhyaya, Arpita. University of Maryland; Estados Unidos
Fil: Hager, Gordon L.. National Institutes of Health; Estados Unidos
description Single-molecule tracking (SMT) allows the study of transcription factor (TF) dynamics in the nucleus, giving important information regarding the diffusion and binding behavior of these proteins in the nuclear environment. Dwell time distributions obtained by SMT for most TFs appear to follow bi-exponential behavior. This has been ascribed to two discrete populations of TFs-one non-specifically bound to chromatin and another specifically bound to target sites, as implied by decades of biochemical studies. However, emerging studies suggest alternate models for dwell-time distributions, indicating the existence of more than two populations of TFs (multi-exponential distribution), or even the absence of discrete states altogether (power-law distribution). Here, we present an analytical pipeline to evaluate which model best explains SMT data. We find that a broad spectrum of TFs (including glucocorticoid receptor, oestrogen receptor, FOXA1, CTCF) follow a power-law distribution of dwell-times, blurring the temporal line between non-specific and specific binding, suggesting that productive binding may involve longer binding events than previously believed. From these observations, we propose a continuum of affinities model to explain TF dynamics, that is consistent with complex interactions of TFs with multiple nuclear domains as well as binding and searching on the chromatin template.
publishDate 2021
dc.date.none.fl_str_mv 2021-07
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/175225
Garcia, David A.; Fettweis, Gregory; Presman, Diego Martin; Paakinaho, Ville; Jarzynski, Christopher; et al.; Power-law behaviour of transcription factor dynamics at the single-molecule level implies a continuum affinity model; Oxford University Press; Nucleic Acids Research; 49; 12; 7-2021; 6605-6620
1362-4962
CONICET Digital
CONICET
url http://hdl.handle.net/11336/175225
identifier_str_mv Garcia, David A.; Fettweis, Gregory; Presman, Diego Martin; Paakinaho, Ville; Jarzynski, Christopher; et al.; Power-law behaviour of transcription factor dynamics at the single-molecule level implies a continuum affinity model; Oxford University Press; Nucleic Acids Research; 49; 12; 7-2021; 6605-6620
1362-4962
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1093/nar/gkab072
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Oxford University Press
publisher.none.fl_str_mv Oxford University Press
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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