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Related Concept Videos

Proteomics01:33

Proteomics

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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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MALDI-TOF Mass Spectrometry01:19

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Mass spectrometry is a powerful characterization technique that can identify and separate a wide variety of compounds ranging from chemical to biological entities, based on their mass-to-charge ratio (m/z). The instruments that allow this detection, known as mass spectrometers, have three components: an ion source, a mass analyzer, and a detector. These spectrometers differ based on the nature of their ion source and analyzers.
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Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

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Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
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Related Experiment Video

Updated: Jun 30, 2025

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples
14:51

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples

Published on: November 13, 2021

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Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows.

Yumi Kwon1, Jongmin Woo1, Fengchao Yu2

  • 1Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, United States.

Biorxiv : the Preprint Server for Biology
|March 18, 2024
PubMed
Summary

Benchmarking spatial proteome mapping methods reveals label-free quantification offers deep protein coverage, while TMT-MS2 excels in throughput. This comparison aids biomarker discovery in complex tissue microenvironments.

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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions
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A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

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Last Updated: Jun 30, 2025

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A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions
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A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

Published on: April 18, 2025

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Area of Science:

  • Proteomics
  • Spatial Biology
  • Biomarker Discovery

Background:

  • Spatial omics enables deep insight into tissue microenvironments.
  • Proteome-scale tissue mapping is crucial for identifying diagnostic biomarkers and therapeutic targets.
  • Current proteome mapping methods face challenges in protein coverage and analytical throughput.

Purpose of the Study:

  • To benchmark three protein quantification methods for spatial proteome mapping: label-free, TMT-MS2, and TMT-MS3.
  • To evaluate their performance in terms of protein coverage, quantification dynamic range, and analytical throughput.
  • To assess their robustness in identifying differentially abundant proteins and spatially co-variable clusters.

Main Methods:

  • Benchmarking of label-free, TMT-MS2, and TMT-MS3 quantification methods for spatial proteome mapping.
  • Performance evaluation based on protein coverage, spatial resolution, quantification dynamic range, and throughput.
  • Application of deep proteome mapping to study the pancreatic islet microenvironment.

Main Results:

  • Label-free quantification achieved the deepest protein coverage (~3500 proteins) at 50 µm resolution with the highest dynamic range.
  • TMT-MS2 method demonstrated high mapping throughput (>125 pixels/day).
  • Both label-free and TMT-MS2 methods provided robust quantification for differential protein abundance and spatial co-expression analysis.

Conclusions:

  • Spatial proteome mapping methods offer distinct advantages for different research needs.
  • Deep proteome mapping can identify cell-type-specific protein markers.
  • Spatial co-expression analysis reveals novel protein patterns within tissue microenvironments, such as pancreatic islets.