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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.
Matrix-assisted laser desorption ionization (MALDI) is a commonly...
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Peptide Identification Using Tandem Mass Spectrometry01:33

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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.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
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Related Experiment Video

Updated: Jun 12, 2025

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

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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, Washington, United States.

Molecular & Cellular Proteomics : MCP
|September 22, 2024
PubMed
Summary

Benchmarking spatial proteome mapping methods reveals label-free offers deep protein coverage, while TMT-MS2 excels in throughput. This enables discovery of cell-specific markers and hidden protein patterns in tissue microenvironments.

Keywords:
isobaric labelinglabel freenanoPOTSproteome mappingspatial proteomics

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

Published on: April 18, 2025

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Area of Science:

  • Biochemistry
  • Proteomics
  • Spatial Biology

Background:

  • Spatial omics, or multiplexed bimolecular profiling, offers deep insights into tissue microenvironments.
  • Proteome-scale tissue mapping is crucial for identifying diagnostic biomarkers and therapeutic targets.
  • Current proteome mapping faces challenges in protein coverage and analytical throughput, often linked to mass spectrometry quantification.

Purpose of the Study:

  • To benchmark three protein quantification methods for spatial proteome mapping: label-free, TMT-MS2, and TMT-MS3.
  • To evaluate the performance of these methods regarding protein coverage, quantification dynamic range, and analytical throughput.
  • To demonstrate the utility of deep proteome mapping in understanding complex biological systems like the pancreatic islet microenvironment.

Main Methods:

  • Comparative benchmarking of label-free, TMT-MS2, and TMT-MS3 quantification strategies for spatial proteome mapping.
  • Assessment of protein coverage, quantification accuracy, and throughput at a spatial resolution of 50 μm.
  • Application of deep proteome mapping to analyze the pancreatic islet microenvironment.

Main Results:

  • The label-free method achieved the deepest protein coverage (∼3500 proteins) with the highest quantification dynamic range.
  • The TMT-MS2 method demonstrated superior mapping throughput (>125 pixels per day).
  • Both label-free and TMT-MS2 methods provided robust quantification for identifying differentially abundant proteins and spatially covariable clusters.
  • Deep proteome mapping successfully identified cell-type-specific protein markers and revealed novel spatial protein coexpression patterns in pancreatic islets.

Conclusions:

  • Label-free and TMT-MS2 are valuable quantification strategies for spatial proteome mapping, each offering distinct advantages in coverage and throughput.
  • Deep proteome mapping is a powerful approach for uncovering cellular heterogeneity and complex molecular interactions within tissue microenvironments.
  • This study provides critical insights for selecting appropriate methods to advance spatial omics research and biomarker discovery.