Email updates

Keep up to date with the latest news and content from BMC Evolutionary Biology and BioMed Central.

Open Access Research article

Evolutionary proteomics identifies amino acids essential for ligand-binding of the cytokinin receptor CHASE domain

Alexander Heyl1, Klaas Wulfetange1, Birgit Pils2, Nicola Nielsen1, Georgy A Romanov3 and Thomas Schmülling1*

Author Affiliations

1 Institute of Biology/Applied Genetics, Free University of Berlin, Albrecht-Thaer-Weg 6, 14195 Berlin, Germany

2 Department of Bioinformatics, Biocenter, Julius Maximilian University, 97074 Würzburg, Germany

3 Institute of Plant Physiology, Russian Academy of Sciences, 127276 Moscow. Russia

For all author emails, please log on.

BMC Evolutionary Biology 2007, 7:62  doi:10.1186/1471-2148-7-62

Published: 17 April 2007

Abstract

Background

In plants the hormone cytokinin is perceived by members of a small cytokinin receptor family, which are hybrid sensor histidine kinases. While the immediate downstream signaling pathway is well characterized, the domain of the receptor responsible for ligand binding and which residues are involved in this process has not been determined experimentally.

Results

Using a live cell hormone-binding assay, we show that cytokinin is bound by a receptor domain predicted to be extracellular, the so called CHASE (cyclases, histidine kinase associated sensory extracellular) domain. The CHASE domain occurs not only in plant cytokinin receptors but also in numerous orphan receptors in lower eukaryotes and bacteria. Taking advantage of this fact, we used an evolutionary proteomics approach to identify amino acids important for cytokinin binding by looking for residues conserved in cytokinin receptors, but not in other receptors. By comparing differences in evolutionary rates, we predicted five amino acids within the plant CHASE domains to be crucial for cytokinin binding. Mutagenesis of the predicted sites and subsequent binding assays confirmed the relevance of four of the selected amino acids, showing the biological significance of site-specific evolutionary rate differences.

Conclusion

This work demonstrates the use of a bioinformatic analysis to mine the huge set of genomic data from different taxa in order to generate a testable hypothesis. We verified the hypothesis experimentally and identified four amino acids which are to a different degree required for ligand-binding of a plant hormone receptor.