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Proteomics

Proteomics

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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Updated: Jul 12, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

A framework for ultra-low-input spatial tissue proteomics.

Anuar Makhmut¹, Di Qin¹, Sonja Fritzsche¹

¹Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Spatial Proteomics Group, Berlin, Germany.

|November 1, 2023

Summary

This summary is machine-generated.

Researchers developed a new spatial proteomics workflow for analyzing ultra-low-input tissue samples. This method enables detailed proteome profiling of single cells and small cell populations, advancing disease and biomarker discovery.

Keywords:

FFPE deep visual proteomics histopathology mass spectrometry proteomics single-cell proteomics spatial proteomics

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Last Updated: Jul 12, 2025

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

Published on: November 13, 2021

Area of Science:

Proteomics
Cell Biology
Mass Spectrometry

Background:

Spatial proteomics integrates microscopy and mass spectrometry for cell function studies.
Existing workflows lack optimization for preserving morphology and maximizing proteome coverage from limited cell inputs.

Purpose of the Study:

To develop and validate a robust, scalable workflow for spatial proteomic analysis of ultra-low-input archival tissue.
To enable phenotype discovery and comprehensive proteome profiling from few or single cells.

Main Methods:

Development of an optimized workflow for laser microdissected, ultra-low-input archival material.
Benchmarking using murine liver tissue at single-cell and small-region resolutions.
Application to human tonsil tissue for profiling microregions and cell niches.

Main Results:

Quantified up to 2,000 proteins from single murine hepatocytes and nearly 5,000 proteins from 50-cell regions.
Profiled 146 human tonsil microregions, identifying cell-type-specific markers, cytokines, and transcription factors.
Revealed proteome dynamics in activated germinal centers, highlighting B cell proliferation and somatic hypermutation.

Conclusions:

The developed workflow is robust and scalable for ultra-low-input spatial proteomics.
This approach facilitates detailed cell-type-specific proteomic analysis in complex tissues.
Significant implications for early disease profiling, drug target, and biomarker discovery.