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Updated: Mar 29, 2026
Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
Simple, Scalable Proteomic Imaging for High-Dimensional Profiling of Intact Systems
Evan Murray1, Jae Hun Cho2, Daniel Goodwin3
1Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Researchers developed SWITCH, a novel proteomic imaging method for scalable, high-dimensional phenotyping. This technique uniformly preserves tissues, enabling over 20 rounds of multiplexed imaging for deeper biological insights.
Area of Science:
- Molecular Biology
- Biotechnology
- Neuroscience
Background:
- Integrating molecular and anatomical data across biological scales presents significant challenges.
- Existing methods often struggle with preserving tissue integrity and enabling multi-modal analysis.
Purpose of the Study:
- To introduce a novel method for scalable, integrated, high-dimensional phenotyping of biological tissues.
- To enable simultaneous analysis of molecular and anatomical traits in animal and human samples.
Main Methods:
- Developed SWITCH (Synchronized, Uniform, Integrated, Tissue-preserving, Chemical, Heat-resistant) method.
- SWITCH uniformly secures tissue architecture, biomolecules, and antigenicity via synchronized preservation.
- Enabled over 20 rounds of multiplexed labeling and imaging on single tissue samples with precise co-registration.
Main Results:
- Demonstrated uniform probe penetration and staining with synchronized labeling reactions.
- Successfully performed combinatorial protein expression profiling of the human cortex.
- Interrogated the geometric structure of fiber pathways in mouse brains using integrated datasets.
Conclusions:
- SWITCH provides a robust framework for scalable, high-dimensional phenotyping of diverse biological samples.
- The method facilitates integrated analysis of molecular and anatomical data, advancing biological understanding.
- This approach holds promise for accelerating discoveries in complex biological systems.
