Periodic Reporting for period 1 - SOLO (Single cell omics of the Oligodendrocyte Lineage in develOpment and disease)
Reporting period: 2018-06-01 to 2020-05-31
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.
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.
During the development of the SOLO action I have studied the oligodendrocytes and their precursors cells at single cell transcriptional and chromatin level comparing healthy states to disease conditions. In the case of the MS mouse model I was able to apply and develop procedures to integrate and analyze single cell transcriptional and chromatin accessibility data. The results from this study showed priming of immune genes in the disease oligodendrocyte populations and validation of the immune oligodendrocytes identified at transcriptional level in previous studies. The results from Jäckel and Agirre et al. Nature 2019, showed the first single cell transcriptomics study on MS patients brains with a focus in oligodendroglia. All the data can be browse through a web based app developed during the action with the code used in the study available through github repository.
The results from this action have been communicated in international conferences and are present as several high open green access publications. Moreover, results from the snRNA-seq study of skewed oligodendrocyte heterogeneity in MS was selected as Scientific highlights at the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS) Congress 2019.
The results from this action have been communicated in international conferences and are present as several high open green access publications. Moreover, results from the snRNA-seq study of skewed oligodendrocyte heterogeneity in MS was selected as Scientific highlights at the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS) Congress 2019.
Results from this action include open access reproducible code and data. Moreover, the biomarker candidates found with this action would be of interest for different companies, which will facilitate the transfer of knowledge from basic research to applied research allowing the future treatment of diseases like MS, matching with societal challenges proposed by Horizon H2020. The project was selected as part of the EU Innovation Radar, showing innovation potential.
The computational and methodological aspect of the action has resulted in openly shared code and data that it has been accessed through repositories like Github by the scientific and computational community. Advances in computational biology and more specifically single cell methodologies require a fast development of methodology to address the challenges on biomedicine. The objectives completed with this action are and will be clue for the advances in the study of demyelinating and neurodegenerative diseases that have high impact on the society. Follow up research projects are expected from the results and resources generated during the project.
The computational and methodological aspect of the action has resulted in openly shared code and data that it has been accessed through repositories like Github by the scientific and computational community. Advances in computational biology and more specifically single cell methodologies require a fast development of methodology to address the challenges on biomedicine. The objectives completed with this action are and will be clue for the advances in the study of demyelinating and neurodegenerative diseases that have high impact on the society. Follow up research projects are expected from the results and resources generated during the project.