Maximizing binary interactome mapping with a minimal number of assays

Soon Choi; Julien Olivet; Patricia Cassonnet; Pierre-Olivier Vidalain; Katja Luck; Luke Lambourne; Kerstin Spirohn; Irma Lemmens; Mélanie Santos; Caroline Demeret; Louis Jones; Sudharshan Rangarajan; Wenting Bian; Eloi Coutant; Yves Janin; Sylvie van der Werf; Philipp Trepte; Erich Wanker; Javier de las Rivas; Jan Tavernier; Jean-Claude Twizere; Tong Hao; David Hill; Marc Vidal; Michael Calderwood; Yves Jacob

doi:10.1038/s41467-019-11809-2

Journal articles

Maximizing binary interactome mapping with a minimal number of assays

Soon Choi ¹ Julien Olivet ^{1, 2} Patricia Cassonnet ^{3, 4} Pierre-Olivier Vidalain ⁵ Katja Luck ^{1, 6} Luke Lambourne ^{1, 6} Kerstin Spirohn ^{1, 6} Irma Lemmens ^{7, 8} Mélanie Santos ^{3, 4} Caroline Demeret ^{3, 4} Louis Jones ⁹ Sudharshan Rangarajan ^{1, 6} Wenting Bian ^{1, 6} Eloi Coutant ¹⁰ Yves Janin ¹⁰ Sylvie van der Werf ^{3, 4} Philipp Trepte ¹¹ Erich Wanker ¹¹ Javier de las Rivas ¹² Jan Tavernier ^{7, 8} Jean-Claude Twizere ² Tong Hao ^{1, 6} David Hill ^{1, 6} Marc Vidal ^{1, 6} Michael Calderwood ^{1, 6} Yves Jacob ^{3, 1}

1 Dana-Farber Cancer Institute [Boston]

2 Université de Liège

3 GMV-ARN (UMR_3569 / U-Pasteur_2) - Génétique Moléculaire des Virus à ARN - Molecular Genetics of RNA Viruses

4 USPC - Université Sorbonne Paris Cité

5 LCBPT - UMR 8601 - Laboratoire de Chimie et de Biochimie Pharmacologiques et Toxicologiques

6 HMS - Harvard Medical School [Boston]

7 VIB - Vlaams Instituut voor Biotechnologie [Ghent, Belgique]

8 UGENT - Ghent University [Belgium]

9 C3BI - Centre de Bioinformatique, Biostatistique et Biologie Intégrative

10 Chimie et Biocatalyse

11 MDC - Max Delbrück Center for Molecular Medicine [Berlin]

12 Universidad de Salamanca

Abstract : Complementary assays are required to comprehensively map complex biological entities such as genomes, proteomes and interactome networks. However, how various assays can be optimally combined to approach completeness while maintaining high precision often remains unclear. Here, we propose a framework for binary protein-protein interaction (PPI) mapping based on optimally combining assays and/or assay versions to maximize detection of true positive interactions, while avoiding detection of random protein pairs. We have engineered a novel NanoLuc two-hybrid (N2H) system that integrates 12 different versions, differing by protein expression systems and tagging configurations. The resulting union of N2H versions recovers as many PPIs as 10 distinct assays combined. Thus, to further improve PPI mapping, developing alternative versions of existing assays might be as productive as designing completely new assays. Our findings should be applicable to systematic mapping of other biological landscapes.

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Journal articles

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Chemical Sciences / Organic chemistry

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Maximizing binary interactome mapping with a minimal number of assays

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