Mapping the dynamic plant interactome: from in vitro assays to in vivo quantitative approaches

Protein-protein interactions underpin virtually all biological processes in plants, from signal transduction and immune responses to development and stress adaptation. Despite their fundamental importance, the plant interactome remains far from complete, and existing maps are systematically biased by the technical limitations inherent to conventional detection platforms.

This review critically traces the evolution of protein-protein interaction methodologies, from foundational approaches to advance in vivo and quantitative platforms. Classical techniques such as the yeast two-hybrid system and in vitro pull-down assays operate outside physiological cellular environments and are poorly suited to capturing transient or condition-dependent interactions. Affinity purification coupled with mass spectrometry improves throughput but remains vulnerable to artifacts introduced during cell lysis and to the preferential loss of weak interactors. To address these shortcomings, proximity labeling with engineered biotin ligases, most notably the fast-acting variant TurboID, has emerged as a powerful strategy, enabling covalent biotinylation of protein neighborhoods within living cells prior to lysis and thereby preserving associations that conventional methods routinely miss. Because TurboID reports proximity rather than direct binding, its output requires downstream binary validation. Complementary in planta validation tools are equally critical for moving beyond discovery. Split-luciferase complementation assays based on the NanoLuciferase reporter provide exceptional sensitivity for binary interaction detection under native expression conditions, while Förster Resonance Energy Transfer measured through fluorescence lifetime imaging microscopy offers quantitative biophysical evidence of molecular proximity at endogenous expression levels, serving as a high-confidence validation approach. Emerging technologies, including high-throughput protein microarrays and optogenetically controlled dimerization systems, further expand the methodological repertoire available to the plant biology community.

We propose a practical, integrative three-tier framework, combining proximity labeling for broad in vivo discovery, split-luciferase complementation for sensitive binary validation, and fluorescence lifetime imaging microscopy for quantitative confirmation, that systematically funnels candidate interactions from initial identification to physiologically rigorous verification. This framework synthesizes established best practices into a structured workflow applicable to mapping dynamic plant interactomes, though its optimal implementation will depend on the biological question, target protein class, and available resources.