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

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 fract...

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Autores principales: Ferdosi, Shadi, Tangeysh, Behzad, Brown, Tristan R., Everley, Patrick A., Figa, Michael, McLean, Matthew, Elgierari, Eltaher M., Zhao, Xiaoyan, Garcia, Veder J., Wang, Tianyu, Chang, Matthew E. K., Riedesel, Kateryna, Chu, Jessica, Mahoney, Max, Xia, Hongwei, O’Brien, Evan S., Stolarczyk, Craig, Harris, Damian, Platt, Theodore L., Ma, Philip, Goldberg, Martin, Langer, Robert, Flory, Mark R., Benz, Ryan, Tao, Wei, Cuevas, Juan Cruz, Batzoglou, Serafim, Blume, John E., Siddiqui, Asim, Hornburg, Daniel, Farokhzad, Omid C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8931255/
https://www.ncbi.nlm.nih.gov/pubmed/35275789
http://dx.doi.org/10.1073/pnas.2106053119
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author Ferdosi, Shadi
Tangeysh, Behzad
Brown, Tristan R.
Everley, Patrick A.
Figa, Michael
McLean, Matthew
Elgierari, Eltaher M.
Zhao, Xiaoyan
Garcia, Veder J.
Wang, Tianyu
Chang, Matthew E. K.
Riedesel, Kateryna
Chu, Jessica
Mahoney, Max
Xia, Hongwei
O’Brien, Evan S.
Stolarczyk, Craig
Harris, Damian
Platt, Theodore L.
Ma, Philip
Goldberg, Martin
Langer, Robert
Flory, Mark R.
Benz, Ryan
Tao, Wei
Cuevas, Juan Cruz
Batzoglou, Serafim
Blume, John E.
Siddiqui, Asim
Hornburg, Daniel
Farokhzad, Omid C.
author_facet Ferdosi, Shadi
Tangeysh, Behzad
Brown, Tristan R.
Everley, Patrick A.
Figa, Michael
McLean, Matthew
Elgierari, Eltaher M.
Zhao, Xiaoyan
Garcia, Veder J.
Wang, Tianyu
Chang, Matthew E. K.
Riedesel, Kateryna
Chu, Jessica
Mahoney, Max
Xia, Hongwei
O’Brien, Evan S.
Stolarczyk, Craig
Harris, Damian
Platt, Theodore L.
Ma, Philip
Goldberg, Martin
Langer, Robert
Flory, Mark R.
Benz, Ryan
Tao, Wei
Cuevas, Juan Cruz
Batzoglou, Serafim
Blume, John E.
Siddiqui, Asim
Hornburg, Daniel
Farokhzad, Omid C.
author_sort Ferdosi, Shadi
collection PubMed
description 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.
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spelling pubmed-89312552022-03-19 Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano–bio interactions Ferdosi, Shadi Tangeysh, Behzad Brown, Tristan R. Everley, Patrick A. Figa, Michael McLean, Matthew Elgierari, Eltaher M. Zhao, Xiaoyan Garcia, Veder J. Wang, Tianyu Chang, Matthew E. K. Riedesel, Kateryna Chu, Jessica Mahoney, Max Xia, Hongwei O’Brien, Evan S. Stolarczyk, Craig Harris, Damian Platt, Theodore L. Ma, Philip Goldberg, Martin Langer, Robert Flory, Mark R. Benz, Ryan Tao, Wei Cuevas, Juan Cruz Batzoglou, Serafim Blume, John E. Siddiqui, Asim Hornburg, Daniel Farokhzad, Omid C. Proc Natl Acad Sci U S A Biological Sciences 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. National Academy of Sciences 2022-03-11 2022-03-15 /pmc/articles/PMC8931255/ /pubmed/35275789 http://dx.doi.org/10.1073/pnas.2106053119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Biological Sciences
Ferdosi, Shadi
Tangeysh, Behzad
Brown, Tristan R.
Everley, Patrick A.
Figa, Michael
McLean, Matthew
Elgierari, Eltaher M.
Zhao, Xiaoyan
Garcia, Veder J.
Wang, Tianyu
Chang, Matthew E. K.
Riedesel, Kateryna
Chu, Jessica
Mahoney, Max
Xia, Hongwei
O’Brien, Evan S.
Stolarczyk, Craig
Harris, Damian
Platt, Theodore L.
Ma, Philip
Goldberg, Martin
Langer, Robert
Flory, Mark R.
Benz, Ryan
Tao, Wei
Cuevas, Juan Cruz
Batzoglou, Serafim
Blume, John E.
Siddiqui, Asim
Hornburg, Daniel
Farokhzad, Omid C.
Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano–bio interactions
title Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano–bio interactions
title_full Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano–bio interactions
title_fullStr Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano–bio interactions
title_full_unstemmed Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano–bio interactions
title_short Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano–bio interactions
title_sort engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano–bio interactions
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8931255/
https://www.ncbi.nlm.nih.gov/pubmed/35275789
http://dx.doi.org/10.1073/pnas.2106053119
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