DNA methylation-based immune cell profiling in mouse blood using MouseRS-CMD.

Area of Science:

• Immunology
• Genomics
• Bioinformatics

Background:

• Immune cell heterogeneity complicates molecular studies in mice.
• Accurate immune cell profiling is crucial for understanding disease mechanisms.

Purpose of the Study:

• To develop a DNA methylation-based computational tool for deconvolution of murine immune cell types.
• To enable accurate immune cell profiling in archival and challenging sample types.

Main Methods:

• Purification of major murine immune cell types (neutrophils, monocytes, NK cells, B cells, CD4+ T cells, CD8+ T cells).
• DNA methylation measurement using Illumina Mouse Methylation BeadChip (>285,000 CpG loci).
• Development of a reference library using the IDOL algorithm for cell deconvolution.

Main Results:

• MouseRS-CMD identified an optimal reference library of 300 CpGs.
• Achieved low Root Mean Square Error (RMSE) values (<2.7 for four cell types, <3.5 for all cell types).
• Validated the tool using flow cytometry measurements in whole blood and eye samples.

Conclusions:

• MouseRS-CMD provides a robust method for immune cell deconvolution in mice using DNA methylation data.
• The tool facilitates immune profiling in archival samples, reducing confounding factors.
• Enhances the reliability of molecular studies by accounting for immune cell heterogeneity.