Proteomics

Dataset Information

0

Nanoparticle Protein Coronas Differentially Interrogate Proteomes with Superior Performance Compared to Conventional Deep Proteome Workflows


ABSTRACT: The superior performance of a multiple NP workflow was shown compared to high-complexity, state-of-the-art, high-pH fractionation strategies in terms of depth and precision. We also evaluate the link between the physicochemical properties of NPs and their differential protein selectivity.

INSTRUMENT(S): Orbitrap Fusion Lumos, TripleTOF 6600

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Theo Platt  

LAB HEAD: Omid C. Farokhzad

PROVIDER: PXD022285 | Pride | 2022-02-24

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
20200608_EXP20030-Neat.sne Other
20200608_EXP20030-Proteograph5NP.sne Other
20200608_EXP20043-DeepFract.sne Other
20200608_EXP20043-Depleted.sne Other
20200702_Final_DIA.sne Other
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Publications

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

Ferdosi Shadi S   Tangeysh Behzad B   Brown Tristan R TR   Everley Patrick A PA   Figa Michael M   McLean Matthew M   Elgierari Eltaher M EM   Zhao Xiaoyan X   Garcia Veder J VJ   Wang Tianyu T   Chang Matthew E K MEK   Riedesel Kateryna K   Chu Jessica J   Mahoney Max M   Xia Hongwei H   O'Brien Evan S ES   Stolarczyk Craig C   Harris Damian D   Platt Theodore L TL   Ma Philip P   Goldberg Martin M   Langer Robert R   Flory Mark R MR   Benz Ryan R   Tao Wei W   Cuevas Juan Cruz JC   Batzoglou Serafim S   Blume John E JE   Siddiqui Asim A   Hornburg Daniel D   Farokhzad Omid C OC  

Proceedings of the National Academy of Sciences of the United States of America 20220311 11


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 a  ...[more]

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