A method for Boolean analysis of protein interactions at a molecular level

Doroteya Raykova (), Despoina Kermpatsou, Tony Malmqvist, Philip J. Harrison, Marie Rubin Sander, Christiane Stiller, Johan Heldin, Mattias Leino, Sara Ricardo, Anna Klemm, Leonor David, Ola Spjuth, Kalyani Vemuri, Anna Dimberg, Anders Sundqvist, Maria Norlin, Axel Klaesson, Caroline Kampf and Ola Söderberg ()
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Doroteya Raykova: Uppsala University, Biomedical center
Despoina Kermpatsou: Uppsala University, Biomedical center
Tony Malmqvist: Atlas Antibodies AB
Philip J. Harrison: Uppsala University, Biomedical center
Marie Rubin Sander: Uppsala University, Biomedical center
Christiane Stiller: Uppsala University, Biomedical center
Johan Heldin: Uppsala University, Biomedical center
Mattias Leino: Uppsala University, Biomedical center
Sara Ricardo: University of Porto
Anna Klemm: Uppsala University
Leonor David: University of Porto
Ola Spjuth: Uppsala University, Biomedical center
Kalyani Vemuri: Uppsala University, Rudbeck Laboratory
Anna Dimberg: Uppsala University, Rudbeck Laboratory
Anders Sundqvist: Uppsala University, Biomedical center
Maria Norlin: Uppsala University, Biomedical center
Axel Klaesson: Uppsala University, Biomedical center
Caroline Kampf: Atlas Antibodies AB
Ola Söderberg: Uppsala University, Biomedical center

Nature Communications, 2022, vol. 13, issue 1, 1-17

Abstract: Abstract Determining the levels of protein–protein interactions is essential for the analysis of signaling within the cell, characterization of mutation effects, protein function and activation in health and disease, among others. Herein, we describe MolBoolean – a method to detect interactions between endogenous proteins in various subcellular compartments, utilizing antibody-DNA conjugates for identification and signal amplification. In contrast to proximity ligation assays, MolBoolean simultaneously indicates the relative abundances of protein A and B not interacting with each other, as well as the pool of A and B proteins that are proximal enough to be considered an AB complex. MolBoolean is applicable both in fixed cells and tissue sections. The specific and quantifiable data that the method generates provide opportunities for both diagnostic use and medical research.

Date: 2022
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DOI: 10.1038/s41467-022-32395-w

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