Protein ScienceBioengineeringPeer-reviewed journal article
MemPPI platform for measuring and engineering membrane protein-protein interactions in mammalian cells via split nanoluciferase
Weiyi TangiD, Sebastian Jojoa-CruziD, Jiayi LiiD, George GoldenfeldiD, Marco MraviciD
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- 3
- FWCI
- 4.10
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- top 8%
Abstract
Membrane protein-protein interactions (memPPIs) underlie critical biological processes including mediating signal transduction, transport, cell communication, and membrane organization. Despite their importance, systematic and quantitative measurement of protein transmembrane (TM) domains laterally interacting in mammalian cells remains challenging. Conventional fusion protein assays directed at memPPIs suffer from low dynamic range, due to the crowded membrane environment and interference from overexpression, trafficking, or self-complementation artifacts. Here, we assessed and further developed the split luciferase complementation NanoBit system to establish suitable expression constructs and working conditions for robust quantification of TM PPIs within human cells. We benchmarked the platform using a panel of natural and synthetic memPPI pairs with diverse architectures, insertion topologies, and trafficking patterns, finding assay settings that robustly distinguish true positive interactions from co-expressed non-interacting pairs. Adding a novel procedure measuring and normalizing protein expression levels in situ in parallel, we drastically improve assay dynamic range and consistency in discerning relative interaction propensities across broad expression levels - which also enhanced compatibility with protein engineering screens. To extend measurements to versatile protein contexts, we developed membrane expression constructs and validated tagging strategies to improve trafficking with defined TM orientations. By incorporating topological control and accounting for variations in expression levels, this memPPI platform becomes a viable approach for high-throughput interaction analyses and experimental screens for membrane protein design such as TM binders targeting human membrane proteins. Owing to its sensitivity, scalability, and adaptability, we expect this assay platform to have broad cross-disciplinary utility in protein science, design, and drug discovery.
- organism: human
- assay: proteomics
- research focus: cell type annotation
- research focus: protein folding & dynamics
- approach: deep learning
- approach: statistical model
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