scholarly journals Flow Cytometric Analysis of Bimolecular Fluorescence Complementation: A High Throughput Quantitative Method to Study Protein-protein Interaction

10.3791/50529 ◽  
2013 ◽  
Author(s):  
Li Wang ◽  
Graeme K. Carnegie
Keyword(s):  
High Throughput ◽  
Protein Interaction ◽  
Quantitative Method ◽  
Flow Cytometric Analysis ◽  
Bimolecular Fluorescence Complementation ◽  
Protein Protein Interaction ◽  
Flow Cytometric ◽  
Fluorescence Complementation ◽  
Bimolecular Fluorescence

scholarly journals Combining Unique Multiplex Gateway Cloning and Bimolecular Fluorescence Complementation (BiFC) for High-Throughput Screening of Protein–Protein Interactions

2016 ◽  
Vol 21 (10) ◽  
pp. 1100-1111 ◽  
Author(s):  
Adriana Lepur ◽  
Lucija Kovačević ◽  
Robert Belužić ◽  
Oliver Vugrek
Keyword(s):  
High Throughput ◽  
Protein Interaction ◽  
Protein Interactions ◽  
High Throughput Screening ◽  
Cellular Localization ◽  
Interaction Analysis ◽  
Bimolecular Fluorescence Complementation ◽  
Galectin 3 ◽  
Fluorescence Complementation ◽  
Bimolecular Fluorescence

Protein interaction networks are the basis for human metabolic and signaling systems. Interaction studies often use bimolecular fluorescence complementation (BiFC) to reveal the formation and cellular localization of protein complexes. However, large-scale studies were either far from native conditions in human cells or limited by laborious restriction/ligation cloning techniques. Here, we describe a new tool for protein interaction screening based on Gateway-compatible BiFC vectors. We made a set of four new vectors that permit fusion of candidate proteins to the N or C fragment of Venus in all fusion positions. We have validated the vectors and confirmed self-association of AHCY, AHCYL1, and galectin-3. In a high-throughput BiFC screen, we identified new AHCY interaction partners: galectin-3 and PUS7L. We also describe additional steps in protein interaction analysis, applied for AHCY–galectin-3 interaction. First, we classified the interaction in intracellular vesicles using CellCognition, machine learning free software. Then we identified the vesicles as endosomal pathway compartments, in line with known galectin-3 trafficking route. This offers a platform to rapidly identify and localize new protein interactions inside living cells, a prerequisite to validate in silico interactome data, and ultimately decode complex protein networks.

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