Nucleic Acids ResearchSystems BiologyPeer-reviewed journal article
BFG-PCA: tools and resources that expand the potential for binary protein interaction discovery
Daniel Evans-YamamotoiD, François D. RouleauiD, Piyush NandaiD, Koji MakanaeiD, Yin LiuiD, Philippe C DesprésiD, Hitoshi MatsuoiD, M. SekiiD, Alexandre K. DubéiD, Diana AscencioiD, Nozomu YachieiD, Christian R. LandryiD
Abstract
Barcode fusion genetics (BFG) utilizes deep sequencing to improve the throughput of protein-protein interaction (PPI) screening in pools. BFG has been implemented in Yeast two-hybrid (Y2H) screens (BFG-Y2H). While Y2H requires test protein pairs to localize in the nucleus for reporter reconstruction, Dihydrofolate Reductase Protein-Fragment Complementation Assay (DHFR-PCA) allows proteins to localize in broader subcellular contexts and proves to be largely orthogonal to Y2H. Here, we implemented BFG to DHFR-PCA (BFG-PCA). This plasmid-based system can leverage ORF collections across model organisms to perform comparative analysis, unlike the original DHFR-PCA that requires yeast genomic integration. The scalability and quality of BFG-PCA were demonstrated by screening human and yeast interactions for >11,000 protein pairs. BFG-PCA showed high-sensitivity and high-specificity for capturing known interactions for both species. BFG-Y2H and BFG-PCA capture distinct sets of PPIs, which can partially be explained based on the domain orientation of the reporter tags. BFG-PCA is a high-throughput protein interaction technology to interrogate binary PPIs that exploits clone collections from any species of interest, expanding the scope of PPI assays.
- organism: human
- organism: yeast
- assay: protein structure
- research focus: protein structure prediction
- research focus: protein design
- research focus: benchmarking
- research focus: database / resource
- approach: experimental assay
- Citations
- 7
- FWCI
- 0.57
- Field percentile
- top 44%
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