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

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

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s41467-020-17033-7.pdf

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sword-2021-03-19T14:26:48.original.xml (130 B)
Original SWORD entry document
Author(s)
Blume, John E
•
Manning, William C
•
Troiano, Gregory
•
Hornburg, Daniel
•
Figa, Michael
•
Hesterberg, Lyndal
•
Platt, Theodore L
•
Zhao, Xiaoyan
•
Cuaresma, Rea A
•
Everley, Patrick A
more
Date Issued
2020
Journal
Nature Communications
Publisher
Springer Science and Business Media LLC
Version
Final published version
Abstract
© 2020, The Author(s). 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.
MIT Department
Koch Institute for Integrative Cancer Research at MIT
Sloan School of Management
Massachusetts Institute of Technology. Operations Research Center
Terms of Use
Creative Commons Attribution 4.0 International license
https://creativecommons.org/licenses/by/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/135998
DOI of Published Version
https://doi.org/10.1038/S41467-020-17033-7
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