Engineered Nanoparticles Enable Deep Proteomics Studies at Scale by Leveraging Tunable Nano-bio Interactions

Overview

Journal Proc Natl Acad Sci U S A

Specialty Science

Date 2022 Mar 11

PMID 35275789

Authors

Shadi Ferdosi

Behzad Tangeysh

Tristan R Brown

Patrick A Everley

Michael Figa

Matthew McLean

Eltaher M Elgierari

Xiaoyan Zhao

Veder J Garcia

Tianyu Wang

Matthew E K Chang

Kateryna Riedesel

Jessica Chu

Max Mahoney

Hongwei Xia

Evan S OBrien

Craig Stolarczyk

Damian Harris

Theodore L Platt

Philip Ma

Martin Goldberg

Robert Langer

Mark R Flory

Ryan Benz

Wei Tao

Juan Cruz Cuevas

Serafim Batzoglou

John E Blume

Asim Siddiqui

Daniel Hornburg

Omid C Farokhzad

Affiliations

Soon will be listed here.

Abstract

SignificanceDeep profiling of the plasma proteome at scale has been a challenge for traditional approaches. We achieve superior performance across the dimensions of precision, depth, and throughput using a panel of surface-functionalized superparamagnetic nanoparticles in comparison to conventional workflows for deep proteomics interrogation. Our automated workflow leverages competitive nanoparticle-protein binding equilibria that quantitatively compress the large dynamic range of proteomes to an accessible scale. Using machine learning, we dissect the contribution of individual physicochemical properties of nanoparticles to the composition of protein coronas. Our results suggest that nanoparticle functionalization can be tailored to protein sets. This work demonstrates the feasibility of deep, precise, unbiased plasma proteomics at a scale compatible with large-scale genomics enabling multiomic studies.

Citing Articles

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