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Related Experiment Video

Updated: Jul 3, 2026

Hydrogel Nanoparticle Harvesting of Plasma or Urine for Detecting Low Abundance Proteins
10:05

Hydrogel Nanoparticle Harvesting of Plasma or Urine for Detecting Low Abundance Proteins

Published on: August 7, 2014

Plasma-derived microparticles for biomarker discovery.

David M Smalley1, Klaus Ley

  • 1Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia 22908-1294, USA. dms9z@virginia.edu

Clinical Laboratory
|July 18, 2008
PubMed
Summary
This summary is machine-generated.

Advances in proteomics offer biomarker discovery potential, but the dynamic range problem limits detection of low-abundance proteins in biological fluids like plasma. Investigating the microparticle subproteome shows promise for identifying novel disease biomarkers.

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Last Updated: Jul 3, 2026

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10:05

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Published on: August 7, 2014

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Published on: April 17, 2012

Preparation of Peripheral Blood Mononuclear Cell Pellets and Plasma from a Single Blood Draw at Clinical Trial Sites for Biomarker Analysis
07:40

Preparation of Peripheral Blood Mononuclear Cell Pellets and Plasma from a Single Blood Draw at Clinical Trial Sites for Biomarker Analysis

Published on: March 20, 2021

Area of Science:

  • Biochemistry
  • Proteomics
  • Biomarker Discovery

Background:

  • Mass spectrometry-based proteomics has advanced significantly, increasing research in biomarker discovery.
  • A major challenge, the dynamic range problem, hinders the detection of low-abundance proteins in complex biological samples.
  • Abundant proteins in plasma (e.g., albumin) can mask low-concentration disease biomarkers.

Purpose of the Study:

  • To address the dynamic range problem in proteomic biomarker discovery.
  • To investigate the microparticle subproteome as a source of potential biomarkers.
  • To identify proteins altered in pathological conditions within the microparticle fraction.

Main Methods:

  • Mass spectrometry-based proteomics.
  • Sample preparation techniques to isolate microparticles.
  • Bioinformatics and computational analysis of proteomic data.

Main Results:

  • The microparticle subproteome, though a small fraction of total plasma proteome (<0.01%), is enriched with proteins relevant to disease states.
  • This subproteome contains proteins at concentrations more amenable to detection compared to the bulk plasma proteome.

Conclusions:

  • The microparticle subproteome represents a promising resource for identifying novel protein biomarkers.
  • Overcoming the dynamic range limitations is crucial for realizing the full potential of proteomics in clinical diagnostics.