Phosphotyrosine signaling in response to growth factors and its involvement in cell cycle regulation is widely believed to be a key signal in vertebrate and invertebrate cells to determine their fate. In multicellular organisms, protein tyrosine phosphorylation is well known to have a pivotal role in the coordination of signal transduction in response to extracellular stimuli involved in the control of a wide range of cellular processes. Until recently, tyrosine phosphorylation signaling was thought to be limited to multicellular organisms and most of the studies in this field are therefore with multicellular organisms. Some recent publications however suggest a role for tyrosine phosphorylation in signaling in unicellular eukaryotic organisms as well. Recent work in our laboratory with Tetrahymena thermophila has provided both experimental and bioinformatic computational evidence for tyrosine phosphorylation. The dynamics of tyrosine phosphorylation in T. thermophila in a mating type specific manner and the role such phosphorylation might play in this unicellular eukaryote have been examined. Key questions addressed in this work are to identify the pathway(s) of tyrosine phosphorylation in Tetrahymena including proteins associated with pathway components already identified and to identify sites of tyrosine phosphorylation on proteins that we have suggested to be involved in tyrosine phosphorylation in Tetrahymena.
Genes of interest were obtained using PCR and the available Tetrahymena complete genome sequence (www.ciliate.org) and 3’ tagged with FZZ. Constructs in this study include 4 protein tyrosine kinases and two protein tyrosine phosphatases. Plasmid DNAs were introduced into Tetrahymena by biolistic transformation and gene replacements were made homozygous using phenotypic assortment. Western blot and indirect immunofluorescence (IF) were used to confirm expression and localization of the tagged proteins. Affinity purification/mass spectrometry (AP/MS) to identify protein/protein interactions has been carried out and will be described. Bioinformatic including gene network analysis is used in combination with biological approaches such as gene knock out and gene knock down to describe the network of interacting proteins to gain additional insight into biological function.