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Related Concept Videos

Proteomics01:33

Proteomics

8.3K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano-bio interactions.

Shadi Ferdosi1, Behzad Tangeysh1, Tristan R Brown1

  • 1Seer, Inc., Redwood City, CA 94065.

Proceedings of the National Academy of Sciences of the United States of America
|March 11, 2022
PubMed
Summary

We developed a novel nanoparticle method for deep plasma proteomics, improving precision and throughput. This technique enables large-scale, multiomic studies by making proteome analysis more accessible and efficient.

Keywords:
machine learningmass spectrometrynanoparticlenano–bio interactionproteomics

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Area of Science:

  • Biochemistry
  • Nanotechnology
  • Proteomics

Background:

  • Deep plasma proteome profiling is crucial for biological insights but challenging with traditional methods.
  • Existing workflows face limitations in precision, depth, and throughput for large-scale analysis.

Purpose of the Study:

  • To develop and validate a novel nanoparticle-based workflow for deep plasma proteomics.
  • To enhance the precision, depth, and throughput of proteomic analysis.
  • To enable large-scale, multiomic studies by integrating proteomics with genomics.

Main Methods:

  • Utilized surface-functionalized superparamagnetic nanoparticles for protein capture.
  • Developed an automated workflow leveraging competitive nanoparticle-protein binding equilibria.
  • Employed machine learning to analyze nanoparticle physicochemical properties and protein corona composition.

Main Results:

  • Achieved superior performance in precision, depth, and throughput compared to conventional proteomics workflows.
  • Demonstrated quantitative compression of the proteome's dynamic range using nanoparticle binding.
  • Identified that nanoparticle functionalization can be tailored for specific protein sets.

Conclusions:

  • The developed nanoparticle workflow offers a significant advancement for deep plasma proteomics.
  • This method enables precise, unbiased proteomic analysis at a scale compatible with large-scale genomics.
  • Facilitates future multiomic studies by providing a scalable proteomics solution.