Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano–bio interactions

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. O’Brien, Craig Stolarczyk, Damian Harris, Theodore L. Platt, Philip MaMartin 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

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Deep interrogation of plasma proteins on a large scale is a challenge due to the number and concentration of proteins, which span a dynamic range of over 10 orders of magnitude. Current plasma proteomics workflows employ labor-intensive protocols combining abundant protein depletion and sample fractionation. We previously demonstrated the superiority of multinanoparticle (multi-NP) coronas for interrogating the plasma proteome in terms of proteome depth compared to simple workflows. Here we show the superior depth and precision of a multi-NP workflow compared to conventional deep workflows evaluating multiple gradients and search engines as well as data-dependent and data-independent acquisition. We link the physicochemical properties and surface functionalization of NPs to their differential protein selectivity, a key feature in NP panel profiling performance. We find that individual proteins and protein classes are differentially attracted by specific surface properties, opening avenues to design multi-NP panels for deep interrogation of complex biological samples.

Original languageEnglish (US)
Article numbere2106053119
JournalProceedings of the National Academy of Sciences of the United States of America
Volume119
Issue number11
DOIs
StatePublished - Mar 15 2022

Keywords

  • machine learning
  • mass spectrometry
  • nanoparticle
  • nano–bio interaction
  • proteomics

ASJC Scopus subject areas

  • General

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