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Related Concept Videos

Proteomics01:33

Proteomics

7.1K
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...
7.1K

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Updated: May 15, 2025

Characterization of Neuronal Lysosome Interactome with Proximity Labeling Proteomics
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Overcoming Analytical Challenges in Proximity Labeling Proteomics.

Haorong Li1, Wan Nur Atiqah Binti Mazli2, Ling Hao1,2

  • 1Department of Chemistry, The George Washington University, Washington, District of Columbia, USA.

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|April 8, 2025
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Summary

Proximity labeling (PL) proteomics captures protein interactions but faces challenges. This review discusses analytical hurdles and advancements in PL technologies for more robust and quantitative biological network analysis.

Keywords:
biotinylationmass spectrometryproximity labeling

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Area of Science:

  • Biochemistry
  • Proteomics
  • Molecular Biology

Background:

  • Proximity labeling (PL) proteomics is a key method for identifying protein interactions and cellular networks.
  • PL enables the study of both stable and transient protein associations.
  • Current PL techniques face limitations in robustness, reproducibility, specificity, and sensitivity.

Purpose of the Study:

  • To discuss the major analytical challenges in proximity labeling proteomics.
  • To highlight advancements and strategies for overcoming these technical hurdles.
  • To provide perspectives on best practices and future directions for PL technologies.

Main Methods:

  • Review of current literature and analytical challenges in PL proteomics.
  • Discussion of strategies to refine study design and tackle interferences.
  • Exploration of novel tools and platforms for enhanced PL applications.

Main Results:

  • Identified key analytical challenges hindering PL proteomics robustness and sensitivity.
  • Outlined advancements in study design, variation control, and novel tool development.
  • Emphasized the need for improved, scalable, and quantitative PL platforms.

Conclusions:

  • Proximity labeling proteomics is a powerful but challenging field.
  • Ongoing advancements are improving the reliability and scope of PL techniques.
  • Future development should focus on robust, scalable, and quantitative PL technologies for broader biological insights.