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CRISPR-Cas-mediated Multianalyte Synthetic Urine Biomarker Test for Portable Diagnostics
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CRISPR-Cas-mediated Multianalyte Synthetic Urine Biomarker Test for Portable Diagnostics

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Human urinary peptide database for multiple disease biomarker discovery.

Justyna Siwy1, William Mullen, Igor Golovko

  • 1Mosaiques diagnostics GmbH, Hannover, Germany.

Proteomics. Clinical Applications
|May 19, 2011
PubMed
Summary

This study updates the human urinary peptide database, identifying 953 urinary peptides and 47 disease biomarkers. This resource aids in understanding disease pathogenesis and developing diagnostics for various conditions.

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Area of Science:

  • Clinical proteomics
  • Biomarker discovery
  • Human urinary peptidome

Background:

  • Human urine is an accessible biofluid for clinical diagnostics.
  • Urine analysis correlates with disease pathophysiology, making it valuable for proteomics.
  • Clinical proteomics utilizes urine for disease biomarker identification.

Purpose of the Study:

  • To provide an updated human urinary peptide database.
  • To detail identified urinary peptides and their associated pathophysiological conditions.
  • To enhance understanding of disease mechanisms through molecular-level analysis.

Main Methods:

  • Analysis of over 13,000 datasets using capillary electrophoresis-mass spectrometry (CE-MS).
  • Sequencing of 953 urinary peptides using top-down MS/MS.

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Last Updated: Jun 1, 2026

CRISPR-Cas-mediated Multianalyte Synthetic Urine Biomarker Test for Portable Diagnostics
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CRISPR-Cas-mediated Multianalyte Synthetic Urine Biomarker Test for Portable Diagnostics

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Proteomic Profile of EPS-Urine through FASP Digestion and Data-Independent Analysis
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Proteomic Profile of EPS-Urine through FASP Digestion and Data-Independent Analysis

Published on: May 8, 2021

  • Inclusion of urine samples from patients and healthy individuals across 47 conditions.

    • Main Results:

    • An updated human urinary peptide database.
    • Identification of 953 sequenced urinary peptides.
    • Listing of biomarkers from clinical proteomic studies, including their regulation.

    Conclusions:

    • The updated database facilitates biomarker discovery for disease management.
    • Combining database information aids in understanding disease pathogenesis at a molecular level.
    • This approach is particularly relevant for diseases affecting urine production and excretion.