Deciphering the Genetic Crosstalk between Microglia and Oligodendrocyte Precursor Cells during Demyelination and Remyelination Using Transcriptomic Data.
Jennifer Enrich-BengoaGemma ManichIrene R DéganoÀlex Perálvarez-MarínPublished in: International journal of molecular sciences (2022)
Demyelinating disorders show impaired remyelination due to failure in the differentiation of oligodendrocyte progenitor cells (OPCs) into mature myelin-forming oligodendrocytes, a process driven by microglia-OPC crosstalk. Through conducting a transcriptomic analysis of microarray studies on the demyelination-remyelination cuprizone model and using human samples of multiple sclerosis (MS), we identified molecules involved in this crosstalk. Differentially expressed genes (DEGs) of specific regions/cell types were detected in GEO transcriptomic raw data after cuprizone treatment and in MS samples, followed by functional analysis with GO terms and WikiPathways. Additionally, microglia-OPC crosstalk between microglia ligands, OPC receptors and target genes was examined with the NicheNet model. We identified 108 and 166 DEGs in the demyelinated corpus callosum (CC) at 2 and 4 weeks of cuprizone treatment; 427 and 355 DEGs in the remyelinated (4 weeks of cuprizone treatment + 14 days of normal diet) compared to 2- and 4-week demyelinated CC; 252 DEGs in MS samples and 2730 and 12 DEGs in OPC and microglia of 4-week demyelinated CC. At this time point, we found 95 common DEGs in the CC and OPCs, and one common DEG in microglia and OPCs, mostly associated with myelin and lipid metabolism. Crosstalk analysis identified 47 microglia ligands, 43 OPC receptors and 115 OPC target genes, all differentially expressed in cuprizone-treated samples and associated with myelination. Our differential expression pipeline identified demyelination/remyelination transcriptomic biomarkers in studies using diverse platforms and cell types/tissues. Cellular crosstalk analysis yielded novel markers of microglia ligands, OPC receptors and target genes.
Keyphrases
- inflammatory response
- multiple sclerosis
- neuropathic pain
- single cell
- genome wide
- mass spectrometry
- rna seq
- ms ms
- gene expression
- bioinformatics analysis
- white matter
- endothelial cells
- spinal cord
- clinical trial
- big data
- electronic health record
- cell therapy
- stem cells
- physical activity
- genome wide identification
- transcription factor
- dna methylation
- deep learning
- copy number
- study protocol
- artificial intelligence
- pi k akt