Integrated Single-Cell Mass Spectrometry Imaging and Immunofluorescence Microscopy for Multimodal Characterization of...

Area of Science:

• Biomedical research
• Cellular biology
• Translational medicine

Background:

• Understanding cellular heterogeneity is key to deciphering health and disease mechanisms.
• Single-cell lipid profiling using mass spectrometry imaging faces challenges like batch effects, hindering biological insights.
• Multimodal single-cell technologies offer powerful tools for detailed cellular analysis.

Purpose of the Study:

• To develop an integrated workflow for multimodal single-cell analysis combining protein and lipid data.
• To address and mitigate batch effects in single-cell lipid profiling.
• To identify distinct cellular phenotypes associated with disease states, specifically in liver cirrhosis.

Main Methods:

• Developed an integrated workflow combining immunofluorescence protein measurements with mass spectrometry imaging lipid analysis at single-cell resolution.
• Applied the workflow to circulating human neutrophils.
• Implemented a batch-effect correction strategy to improve data reliability across clinical samples.

Main Results:

• Successfully integrated protein and lipid data at single-cell resolution.
• Reduced batch-related variability, enabling reliable comparisons across clinical samples.
• Identified distinct molecular signatures associated with pathogenic neutrophil populations in liver cirrhosis patients.

Conclusions:

• The integrated multimodal single-cell profiling approach effectively overcomes technical challenges like batch effects.
• This method enables the discovery of novel cellular phenotypes relevant to disease.
• The technology shows significant potential for advancing translational and clinical research by providing deeper cellular insights.