Micro-organisms sense and chemotactically respond to aromatic compounds. Although the existence of chemoreceptors that bind to aromatic attractants and subsequently trigger chemotaxis have long been speculated, such a chemoreceptor has not been demonstrated. In this report, we demonstrated that the chemoreceptor MCP2901 from Comamonas testosteroni CNB-1 binds to aromatic compounds and initiates downstream chemotactic signaling in addition to its ability to trigger chemotaxis via citrate binding. The function of gene MCP2901 was investigated by genetic deletion from CNB-1 and genetic complementation of the methyl-accepting chemotaxis protein (MCP)-null mutant CNB-1Δ20. Results showed that the expression of MCP2901 in the MCP-null mutant restored chemotaxis toward nine tested aromatic compounds and nine carboxylic acids. Isothermal titration calorimetry (ITC) analyses demonstrated that the ligand-binding domain of MCP2901 (MCP2901LBD) bound to citrate, and weakly to gentisate and 4-hydroxybenzoate. Additionally, ITC assays indicated that MCP2901LBD bound strongly to 2,6-dihydroxybenzoate and 2-hydroxybenzoate, which are isomers of gentisate and 4-hydroxybenzoate respectively that are not metabolized by CNB-1. Agarose-in-plug and capillary assays showed that these two molecules serve as chemoattractants for CNB-1. Through constructing membrane-like MCP2901-inserted Nanodiscs and phosphorelay activity assays, we demonstrated that 2,6-dihydroxybenzoate and 2-hydroxybenzoate altered kinase activity of CheA. This is the first evidence of an MCP binding to an aromatic molecule and triggering signal transduction for bacterial chemotaxis.
We propose a simple model for the calculation of pK(a) values of ionizable residues in proteins. It is based on the premise that the pK(a) shift of ionizable residues is linearly correlated to the interaction between a particular residue and the local environment created by the surrounding residues. Despite its simplicity, the model displays good prediction performance. Under the sixfold cross test prediction over a data set of 405 experimental pK(a) values in 73 protein chains with known structures, the root-mean-square deviation (RMSD) between the experimental and calculated pK(a) was found to be 0.77. The accuracy of this model increases with increasing size of the data set: the RMSD is 0.609 for glutamate (the largest data set with 141 sites) and approximately 1 pH unit for lysine, with a data set containing 45 sites.
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