Cargando…

Combining modelling and experimental approaches to explain how calcium signatures are decoded by calmodulin‐binding transcription activators (CAMTAs) to produce specific gene expression responses

Experimental data show that Arabidopsis thaliana is able to decode different calcium signatures to produce specific gene expression responses. It is also known that calmodulin‐binding transcription activators (CAMTAs) have calmodulin (CaM)‐binding domains. Therefore, the gene expression responses re...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Junli, Whalley, Helen J., Knight, Marc R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4832281/
https://www.ncbi.nlm.nih.gov/pubmed/25917109
http://dx.doi.org/10.1111/nph.13428
_version_ 1782427225674481664
author Liu, Junli
Whalley, Helen J.
Knight, Marc R.
author_facet Liu, Junli
Whalley, Helen J.
Knight, Marc R.
author_sort Liu, Junli
collection PubMed
description Experimental data show that Arabidopsis thaliana is able to decode different calcium signatures to produce specific gene expression responses. It is also known that calmodulin‐binding transcription activators (CAMTAs) have calmodulin (CaM)‐binding domains. Therefore, the gene expression responses regulated by CAMTAs respond to calcium signals. However, little is known about how different calcium signatures are decoded by CAMTAs to produce specific gene expression responses. A dynamic model of Ca(2+)–CaM–CAMTA binding and gene expression responses is developed following thermodynamic and kinetic principles. The model is parameterized using experimental data. Then it is used to analyse how different calcium signatures are decoded by CAMTAs to produce specific gene expression responses. Modelling analysis reveals that: calcium signals in the form of cytosolic calcium concentration elevations are nonlinearly amplified by binding of Ca(2+), CaM and CAMTAs; amplification of Ca(2+) signals enables calcium signatures to be decoded to give specific CAMTA‐regulated gene expression responses; gene expression responses to a calcium signature depend upon its history and accumulate all the information during the lifetime of the calcium signature. Information flow from calcium signatures to CAMTA‐regulated gene expression responses has been established by combining experimental data with mathematical modelling.
format Online
Article
Text
id pubmed-4832281
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-48322812016-04-20 Combining modelling and experimental approaches to explain how calcium signatures are decoded by calmodulin‐binding transcription activators (CAMTAs) to produce specific gene expression responses Liu, Junli Whalley, Helen J. Knight, Marc R. New Phytol Research Experimental data show that Arabidopsis thaliana is able to decode different calcium signatures to produce specific gene expression responses. It is also known that calmodulin‐binding transcription activators (CAMTAs) have calmodulin (CaM)‐binding domains. Therefore, the gene expression responses regulated by CAMTAs respond to calcium signals. However, little is known about how different calcium signatures are decoded by CAMTAs to produce specific gene expression responses. A dynamic model of Ca(2+)–CaM–CAMTA binding and gene expression responses is developed following thermodynamic and kinetic principles. The model is parameterized using experimental data. Then it is used to analyse how different calcium signatures are decoded by CAMTAs to produce specific gene expression responses. Modelling analysis reveals that: calcium signals in the form of cytosolic calcium concentration elevations are nonlinearly amplified by binding of Ca(2+), CaM and CAMTAs; amplification of Ca(2+) signals enables calcium signatures to be decoded to give specific CAMTA‐regulated gene expression responses; gene expression responses to a calcium signature depend upon its history and accumulate all the information during the lifetime of the calcium signature. Information flow from calcium signatures to CAMTA‐regulated gene expression responses has been established by combining experimental data with mathematical modelling. John Wiley and Sons Inc. 2015-04-27 2015-10 /pmc/articles/PMC4832281/ /pubmed/25917109 http://dx.doi.org/10.1111/nph.13428 Text en © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Liu, Junli
Whalley, Helen J.
Knight, Marc R.
Combining modelling and experimental approaches to explain how calcium signatures are decoded by calmodulin‐binding transcription activators (CAMTAs) to produce specific gene expression responses
title Combining modelling and experimental approaches to explain how calcium signatures are decoded by calmodulin‐binding transcription activators (CAMTAs) to produce specific gene expression responses
title_full Combining modelling and experimental approaches to explain how calcium signatures are decoded by calmodulin‐binding transcription activators (CAMTAs) to produce specific gene expression responses
title_fullStr Combining modelling and experimental approaches to explain how calcium signatures are decoded by calmodulin‐binding transcription activators (CAMTAs) to produce specific gene expression responses
title_full_unstemmed Combining modelling and experimental approaches to explain how calcium signatures are decoded by calmodulin‐binding transcription activators (CAMTAs) to produce specific gene expression responses
title_short Combining modelling and experimental approaches to explain how calcium signatures are decoded by calmodulin‐binding transcription activators (CAMTAs) to produce specific gene expression responses
title_sort combining modelling and experimental approaches to explain how calcium signatures are decoded by calmodulin‐binding transcription activators (camtas) to produce specific gene expression responses
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4832281/
https://www.ncbi.nlm.nih.gov/pubmed/25917109
http://dx.doi.org/10.1111/nph.13428
work_keys_str_mv AT liujunli combiningmodellingandexperimentalapproachestoexplainhowcalciumsignaturesaredecodedbycalmodulinbindingtranscriptionactivatorscamtastoproducespecificgeneexpressionresponses
AT whalleyhelenj combiningmodellingandexperimentalapproachestoexplainhowcalciumsignaturesaredecodedbycalmodulinbindingtranscriptionactivatorscamtastoproducespecificgeneexpressionresponses
AT knightmarcr combiningmodellingandexperimentalapproachestoexplainhowcalciumsignaturesaredecodedbycalmodulinbindingtranscriptionactivatorscamtastoproducespecificgeneexpressionresponses