Maximizing binary interactome mapping with a minimal number of assays

Area of Science:

• Molecular Biology
• Biochemistry
• Systems Biology

Background:

• Comprehensive mapping of biological entities like proteomes requires complementary assays.
• Optimizing the combination of different assays for maximal coverage and precision is challenging.

Purpose of the Study:

• To propose a framework for binary protein-protein interaction (PPI) mapping by optimally combining assay versions.
• To maximize the detection of true positive PPIs while minimizing false positives.

Main Methods:

• Engineered a novel NanoLuc two-hybrid (N2H) system integrating 12 distinct versions.
• Varied protein expression systems and tagging configurations within the N2H system.

Main Results:

• The union of N2H versions recovered as many PPIs as 10 distinct assays combined.
• Demonstrated that optimizing assay versions can be as effective as developing new assays for PPI mapping.

Conclusions:

• Developing alternative versions of existing assays is a productive strategy for improving PPI mapping.
• The proposed framework and findings are applicable to systematic mapping of other biological landscapes.