You are here

Nat Commun DOI:10.1038/s41467-020-17033-7

Rapid, deep and precise profiling of the plasma proteome with multi-nanoparticle protein corona.

Publication TypeJournal Article
Year of Publication2020
AuthorsBlume, JE, Manning, WC, Troiano, G, Hornburg, D, Figa, M, Hesterberg, L, Platt, TL, Zhao, X, Cuaresma, RA, Everley, PA, Ko, M, Liou, H, Mahoney, M, Ferdosi, S, Elgierari, EM, Stolarczyk, C, Tangeysh, B, Xia, H, Benz, R, Siddiqui, A, Carr, SA, Ma, P, Langer, R, Farias, V, Farokhzad, OC
JournalNat Commun
Date Published2020 07 22
KeywordsAdult, Aged, Aged, 80 and over, Blood Proteins, Carcinoma, Non-Small-Cell Lung, Chromatography, High Pressure Liquid, Diagnosis, Differential, Female, Healthy Volunteers, Humans, Lung Neoplasms, Male, Middle Aged, Nanoparticles, Pilot Projects, Protein Corona, Proteomics, Reproducibility of Results, Tandem Mass Spectrometry, Time Factors

Large-scale, unbiased proteomics studies are constrained by the complexity of the plasma proteome. Here we report a highly parallel protein quantitation platform integrating nanoparticle (NP) protein coronas with liquid chromatography-mass spectrometry for efficient proteomic profiling. A protein corona is a protein layer adsorbed onto NPs upon contact with biofluids. Varying the physicochemical properties of engineered NPs translates to distinct protein corona patterns enabling differential and reproducible interrogation of biological samples, including deep sampling of the plasma proteome. Spike experiments confirm a linear signal response. The median coefficient of variation was 22%. We screened 43 NPs and selected a panel of 5, which detect more than 2,000 proteins from 141 plasma samples using a 96-well automated workflow in a pilot non-small cell lung cancer classification study. Our streamlined workflow combines depth of coverage and throughput with precise quantification based on unique interactions between proteins and NPs engineered for deep and scalable quantitative proteomic studies.


Alternate JournalNat Commun
PubMed ID32699280
PubMed Central IDPMC7376165