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>