SPOTTER: Automated Tissue-Barcoding Platform for Spatial Proteomics and Phosphoproteomics

Area of Science:

• Proteomics
• Biotechnology
• Molecular Biology

Background:

• Spatial proteomics links molecular states to tissue architecture.
• Current methods face scalability and throughput limitations.
• Existing workflows are labor-intensive and low-plex.

Purpose of the Study:

• Introduce SPOTTER, a robotic platform for automated spatial proteomics.
• Enable micron-scale spatial barcoding on intact tissue sections.
• Facilitate whole-tissue proteome and phosphoproteome mapping.

Main Methods:

• Developed a customizable robotic platform (SPOTTER).
• Implemented automated, in situ protein labeling for spatial barcoding.
• Utilized high-resolution LC-MS/MS for deep proteome and phosphoproteome analysis.

Main Results:

• Achieved automated, micron-scale spatial barcoding on intact tissues.
• Enabled unbiased whole-tissue proteome mapping.
• Performed the first spatial phosphoproteome profiling from intact sections.
• Demonstrated deep proteome and phosphoproteome coverage with preserved histology.

Conclusions:

• SPOTTER offers a scalable solution for high-plex spatial proteomics.
• This platform overcomes limitations of previous spatial omics techniques.
• SPOTTER facilitates the resolution of spatially distinct molecular regions within tissues.