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bioRxiv · 10.1101/2024.09.10.612356

Causality Analysis of Protein Corona Composition: Phosphatidylcholine-Enhances Plasma Proteome Profiling by Proteomics

Abstract

The study of the protein corona, the immediate and evolving biomolecular coating that forms on the surface of nanoparticles when exposed to a biological environment, is a crucial area in nanomedicine. This phenomenon significantly influences the behavior, functionality, and biological interactions of nanoparticles with biosystems. Until now, conclusions regarding the role of the protein corona in specific biological applications have been based on establishing correlation rather than causation. By understanding causality, researchers can predict how changes in nanoparticle properties or biological conditions will affect protein corona composition, in turn affecting the nanoparticle interactions with the biosystems and their applications. This predictive capability is essential for designing nanoparticles with specific characteristics tailored for therapeutic and diagnostic nanomedicine applications. Here, we explore the concept of "actual causality" (by Halpern and Pearl) to mathematically prove how various small molecules, including metabolites, lipids, vitamins, and nutrients, spiked into plasma can induce diverse protein corona patterns on identical nanoparticles. This approach significantly enhances the depth of plasma proteome profiling. Our findings reveal that among the various spiked small molecules, phosphatidylcholine was the actual cause of the observed increase in the proteomic depth of the plasma sample. By considering the concept of causality in the field of protein corona, the nanomedicine community can substantially improve their ability to design safer and more efficient nanoparticles for both diagnostic and therapeutic purposes.

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BibTeXRIS

Rafieioskouei, A., Rogale, K., Dibavar, A. S., Mahmoudi, M., Bonakdarpour, B.. 2024-09-14. Causality Analysis of Protein Corona Composition: Phosphatidylcholine-Enhances Plasma Proteome Profiling by Proteomics. https://doi.org/10.1101/2024.09.10.612356

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