Publication details for Dr Junli LiuLiu, J., Whalley, H.J. & Knight, M.R. (2015). Combining modelling and experimental approaches to explain how calcium signatures are decoded by calmodulin-binding transcription activators (CAMTAs) to produce specific gene expression responses. New Phytologist 208(1): 174-187.
- Publication type: Journal Article
- ISSN/ISBN: 0028-646X, 1469-8137
- DOI: 10.1111/nph.13428
- Keywords: Arabidopsis, Ccalcium signatures, Calmodulin (CaM), Calmodulin-binding transcription activators (CAMTAs), Gene expression, Mathematical modelling.
- Further publication details on publisher web site
- Durham Research Online (DRO) - may include full text
Author(s) from Durham
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 Ca2+–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 Ca2+, CaM and CAMTAs; amplification of Ca2+ 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.