Single-Cell Multiomic MALDI-MSI Analysis of Lipids and N-Glycans through Affinity Array Capture

Area of Science:

• Biotechnology
• Analytical Chemistry
• Cell Biology

Background:

• Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has faced challenges in achieving true single-cell resolution.
• Distinguishing signals from adjacent cells and computational deconvolution are significant hurdles in current MALDI-MSI single-cell analysis.

Purpose of the Study:

• To develop a novel, targeted single-cell capture and sampling method for MALDI-MSI.
• To enable rapid, multiomic data acquisition from individual cells.
• To automate single-cell selection and analysis using artificial intelligence.

Main Methods:

• Utilized micro-contact printing for targeted single-cell capture and array formation.
• Developed an AI-based application, SoloCell, for automated selection of captured single cells.
• Applied MALDI-MSI for rapid lipid and N-glycan profiling from the same captured cell.

Main Results:

• Successfully captured thousands of single cells in a grid format.
• Achieved rapid profiling of lipids and N-glycans from individual cells at a rate of 6 cells per second.
• Demonstrated a novel approach for multiomic data acquisition from the same single cell.

Conclusions:

• The developed method overcomes previous limitations in MALDI-MSI single-cell analysis.
• This technology offers an unprecedented tool for unraveling cellular population complexity.
• Combines single-cell capture, AI automation, and imaging mass spectrometry for advanced biological insights.