Human Oligodendrocyte Differences Due to Environmental Signals Rather Than Lineage
Researchers used single-cell RNA sequencing on adult, pediatric, and infant surgical tissues to study oligodendrocyte types in order to better understand multiple sclerosis.
Julia Luo
A recent study used whole-cell single-cell RNA sequencing (scRNAseq) analysis to clarify human oligodendrocyte lineage and functional states. The study’s findings were presented at the Americas Committee for Treatment and Research in Multiple Sclerosis (ACTRIMS) Forum 2021, February 25-27, by Julia Luo, graduate student, McGill University, and colleagues.
“Myelin repair in the central nervous system is largely attributed to oligodendrocyte progenitor cell (OPCs) though recent studies have suggested that mature oligodendrocytes (OLs) can contribute in remyelination. Remyelination capacity decreases with age despite the presence of OPCs in demyelinated lesions. Defining OL biology in terms of age and differentiation stage is crucial to understanding multiple sclerosis (MS) disease pathology and developing therapeutic targets,” Luo and colleagues wrote.
Luo and colleagues employed scRNAseq with the aim of describing the molecular profile and age group differences of human OL lineage in surgical tissue samples. These samples were derived from fetal, pediatric, and adult patients undergoing surgery: 4 from the Montreal Neurological Institute and Hospital, 7 from the Montreal Children’s Hospital, as well as 4 samples of fetal telencephalon tissue provided by the University of Washington Birth Defects Research Lab. For the scRNAseq, the R packages Seurat and PhateR were used for processing and trajectory inference and ClueGO was used for pathway analysis.
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They then used unbiased clustering analysis and canonical marker expression of MBP, PLP1, PTPRZ1, PDGFRA, and SOX10 to identify 4 OL-lineage cell types: early-OPC, late-OPC, pre-OL, and mature-OL. They found that pediatric samples had a significantly higher proportion of late-OPCs and significantly lower proportion of mOLs than adult samples. Pre-OLs persisted in both age groups.
The researchers identified 4 subclusters of mature OLs: immune-OL, mOL1, mOL2, and mOL3. They used pseudotime trajectory inference analysis to plot the developmental lineage of the cells types and found that the heterogeneity in mature OLs likely reflects differences in functional states rather than distinct cell types.
All told, they found that immune-OLs were present at similar levels in adult and pediatric samples. The biological pathway enrichments of these subtypes include regulation of inflammatory response and response to interferon-gamma. Mature OL1s were identified to have associated pathways involved in stress response, while mature OL2s and mature OL3s had pathways in myelination. Pathways enriched in mature OL3s in adults had negative regulation of cell-to-cell adhesion and adherens junction organization when compared pediatric patients.
“Whole-cell scRNAseq of human brain tissue over a wide age group indicated differences in the frequency of OL-lineage cells between adult and pediatric samples. Pseudotime and pathway analysis indicate that the heterogeneity of functional properties within the [mature] OL population likely reflect responses to environmental signals rather than differences in developmental lineage,” Luo and colleagues concluded.
For more coverage of ACTRIMS Forum 2021, click here.
