Oligodendrocytes (oligodendroglia when referring to the whole cell lineage) are glial cells from the central nervous system (CNS) that produce myelin, a lipid rich membrane protein, which has the function to insulate neuronal axons. During proliferation of the oligodendrocyte precursors cells (OPCs) different transcription factors and chromatin modifiers interact for the acquisition of final functional cell states. The disruption of these processes can lead to defective myelination with consequences as neurodegeneration. Multiple sclerosis (MS) is the most frequent cause of neurological incapacity in young adults (20-40 years), with a prevalence of 100-200 cases per 100.000 habitants in Europe and USA, with 2.3 million people affected worldwide. MS, is characterized by abnormal or defective myelination with spontaneous remyelination events occurring at initial stages of MS, at the regions called shadow plaques. This process progressively starts occurring with less efficiency with an eventual failure. Remyelination has been linked to oligodendrocyte precursor cells (OPCs) based on several studies of mainly mouse models. In order to achieve remyelination processes in MS, we have to be able to characterize the cell states at epigenomic and transcriptional level of the oligodendrocyte populations and their precursors in healthy states and disease. One of the current challenges in biology is the characterization of cell types and cell states. With the current single cell technologies we are able to investigate the transcriptional and epigenetic states of the cells. This will allow us to identify the specific oligodendroglia populations in healthy states and the similarities and differences with the MS disease. In the last years several computational methodologies have been developed to confront the challenges of a highly sparse zero inflated and multi-dimensional data. Moreover, the development of different single cell technologies such as scATAC-seq, for the study of open chromatin sites, required a new whole group of methods to integrate different types of data source in an standard and appropriate way.
There is a need for a detailed characterization of these oligodendroglia populations and the standard use of computational methods to study the highly complex single cell data in a reproducible manner. Mouse based studies showed a heterogeneity in oligodendroglia populations in both development and mouse MS models like Experimental autoimmune encephalomyelitis (EAE). The completion of the SOLO MSCA led to the implementation and to share methodology for the study of oligodendroglia in development and MS. The results also include web base open access to data. Moreover, the results using brains from MS patients for the first time using single cell technologies open new perspectives in the knowledge of the disease in patients and the relevance of oligodendroglia in MS (Jäckel and Agirre et al. Nature 2019). The results also showed a preliminary new classification of the MS lesion types based on transcriptional profiles complementary to the histopathological classification.
The objectives of this project include;
1) Correlate single cell transcriptomics and epigenomics data in healthy states and disease; 2) Establish specific OL lineage classes and its links to MS; 3) Identify specific regulatory pathways determining the healthy and disease populations.
