Evidence mapPaperPMID 42437933Full record

ReviewPlant methods2026

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

Muhammad Ans Hussain, Ameer Hamza Hafeez, Iqra Noor, Adeena Shakoor, Hammad Hussain, Fatemeh Gholizadeh, Hamza Sohail

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In one paragraph

Review in Plant methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Muhammad Ans Hussain *National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
Ameer Hamza Hafeez *National Key Laboratory for Germplasm Innovation and Utilization of Horticultural Crops, National R&D Centre for Citrus Preservation, College of Horticulture and Forestry Science, Huazhong Agricultural University, Wuhan, P. R. China.
Iqra NoorCollege of Horticulture and Forestry, Tarim University, Aral, 843300, China.
Adeena ShakoorDepartment of Plant Breeding and Genetics, Faculty of Agriculture, Akdeniz University, Antalya, Turkey.
Hammad HussainCollege of Horticulture and Landscape Architecture, Yangzhou University, Yangzhou, 225009, China.
Fatemeh GholizadehDepartment of Plant Physiology and Metabolomics, Agricultural Institute, HUN-REN Centre for Agricultural Research, Martonvásár, 2462, Hungary. fatemeh.gholizadeh@atk.hun-ren.hu.
Hamza SohailCollege of Horticulture and Forestry, Tarim University, Aral, 843300, China. hamzasohail@yzu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProtein-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. MAIN BODY: 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.

conclusionWe 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.

Indexed as

Interactome mappingIn vivo interactomicsPlant signalingProtein–protein interactionProximity labelingSplit-luciferase complementation

Identifiers

PMID42437933
PMCPMC13425787

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.