Selection and characterization of FcεRI phospho-ITAM specific antibodies.

Post-translational modifications, such as the phosphorylation of tyrosines, are often the initiation step for intracellular signaling cascades. Pan-reactive antibodies against modified amino acids (e.g., anti-phosphotyrosine), which are often used to assay these changes, require isolation of the specific protein prior to analysis and do not identify the specific residue that has been modified (in the case that multiple amino acids have been modified). Phosphorylation state-specific antibodies (PSSAs) developed to recognize post-translational modifications within a specific amino acid sequence can be used to study the timeline of modifications during a signal cascade. We used the FcεRI receptor as a model system to develop and characterize high-affinity PSSAs using phage and yeast display technologies. We selected three ß-subunit antibodies that recognized: 1) phosphorylation of tyrosines Y218 or Y224; 2) phosphorylation of the Y228 tyrosine; and 3) phosphorylation of all three tyrosines. We used these antibodies to study the receptor activation timeline of FcεR1 in rat basophilic leukemia cells (RBL-2H3) upon stimulation with DNP24-BSA. We also selected an antibody recognizing the N-terminal phosphorylation site of the γ-subunit (Y65) of the receptor and applied this antibody to evaluate receptor activation. Recognition patterns of these antibodies show different timelines for phosphorylation of tyrosines in both ß and γ subunits. Our methodology provides a strategy to select antibodies specific to post-translational modifications and provides new reagents to study mast cell activation by the high-affinity IgE receptor, FcεRI.

Designing bacterial signaling interactions with coevolutionary landscapes.

Selecting amino acids to design novel protein-protein interactions that facilitate catalysis is a daunting challenge. We propose that a computational coevolutionary landscape based on sequence analysis alone offers a major advantage over expensive, time-consuming brute-force approaches currently employed. Our coevolutionary landscape allows prediction of single amino acid substitutions that produce functional interactions between non-cognate, interspecies signaling partners. In addition, it can also predict mutations that maintain segregation of signaling pathways across species. Specifically, predictions of phosphotransfer activity between the Escherichia coli histidine kinase EnvZ to the non-cognate receiver Spo0F from Bacillus subtilis were compiled. Twelve mutations designed to enhance, suppress, or have a neutral effect on kinase phosphotransfer activity to a non-cognate partner were selected. We experimentally tested the ability of the kinase to relay phosphate to the respective designed Spo0F receiver proteins against the theoretical predictions. Our key finding is that the coevolutionary landscape theory, with limited structural data, can significantly reduce the search-space for successful prediction of single amino acid substitutions that modulate phosphotransfer between the two-component His-Asp relay partners in a predicted fashion. This combined approach offers significant improvements over large-scale mutations studies currently used for protein engineering and design.