Studying Myeloid Cell Heterogeneity After Spinal Cord Injury via Time-Resolved Single-Cell RNA Sequencing

Regan Hamel, Apollo-University Of Cambridge Repository, Stefano Pluchino, John Marioni
Spinal cord injury (SCI) is a devastating pathology that affects thousands of individuals annually, resulting in the requirement for long-term physical and medical care and thus significant personal, societal, and economic burdens. The SCI pathology is characterised by an initial mechanical insult, followed by a spatiotemporally dynamic secondary injury. Decades of research have worked to assemble a general picture of this secondary pathology. We now understand that compared to the normal wound
more » ... healing observed in the periphery, tissue recovery after SCI is dysregulated and results in a chronic wound state characterized by persistent inflammation and functional deficits. The primary drivers of this inflammation are central nervous system (CNS) resident microglia and infiltrating myeloid cells. However, the precise role of these myeloid cell subsets remains unclear as upon crossing the blood-spinal cord barrier (BSCB), infiltrating monocyte-derived macrophages may take on the morphology of microglia, and upregulate canonical microglia markers, making the two populations difficult to distinguish. In this PhD project, I employed single-cell RNA sequencing (scRNAseq) to deconvolute the complex heterogeneity of infiltrating and resident myeloid cells in mouse models of thoracic contusion SCI at an unprecedented resolution. To fully appreciate the temporal dynamics of the pathology, I collected samples across the acute, subacute, and early chronic phases of SCI, plus a sham-injured control. Recent experiments have demonstrated that CNS infiltrating macrophages also take on the transcriptional profiles of microglia, which led me to question whether I had accurately annotated infiltrating macrophages in the dataset. To address this, I repeated the experiment with a transgenic fate-mapping mouse line then integrated these two datasets to generate a time-resolved SCI myeloid cell atlas with definitive ontogeny labelling. With this dataset I generated a putative time resolved map of myeloid cell dynamics across the SCI path [...]
doi:10.17863/cam.81960 fatcat:ubdfjsynvje7dffbthdvv2roaq