10.1184/R1/6097676.v1 Jacob H. Boysen Jacob H. Boysen Saranna Fanning Saranna Fanning Justin Newberg Justin Newberg Robert Murphy Robert Murphy Aaron Mitchell Aaron Mitchell Detection of protein-protein interactions through vesicle targeting. Carnegie Mellon University 2009 Candida albicans Computational Biology Endosomal Sorting Complexes Required for Transport Endosomes Fungal Proteins Green Fluorescent Proteins Image Processing Computer-Assisted Nuclear Proteins Protein Binding Protein Interaction Mapping Recombinant Fusion Proteins Saccharomyces cerevisiae Saccharomyces cerevisiae Proteins Transport Vesicles 2009-05-01 00:00:00 Journal contribution https://kilthub.cmu.edu/articles/journal_contribution/Detection_of_protein-protein_interactions_through_vesicle_targeting_/6097676 <p>The detection of protein-protein interactions through two-hybrid assays has revolutionized our understanding of biology. The remarkable impact of two-hybrid assay platforms derives from their speed, simplicity, and broad applicability. Yet for many organisms, the need to express test proteins in Saccharomyces cerevisiae or Escherichia coli presents a substantial barrier because variations in codon specificity or bias may result in aberrant protein expression. In particular, nonstandard genetic codes are characteristic of several eukaryotic pathogens, for which there are currently no genetically based systems for detection of protein-protein interactions. We have developed a protein-protein interaction assay that is carried out in native host cells by using GFP as the only foreign protein moiety, thus circumventing these problems. We show that interaction can be detected between two protein pairs in both the model yeast S. cerevisiae and the fungal pathogen Candida albicans. We use computational analysis of microscopic images to provide a quantitative and automated assessment of confidence.</p>