Abstract
Single cell analysis techniques, like mass cytometry and single cell RNA sequencing, allow for comprehensive characterization of cell phenotypes at the protein and transcriptomic level. When applied to developmental systems, these technologies can be used to follow molecular phenotypes and cell trajectories, elucidating the complex pathways underlying cell specification. Identifying the molecular mechanisms that control the progression of neural development can provide critical insights into the underlying processes of neural cell specification in neural development and disease. The precise hierarchy of cell diversification as well as the signaling that drives these lineage choices remains ambiguous. Furthermore, these high dimensional analysis techniques have yet to be applied to in vitro models of neural development, which would allow researchers to harness the benefits of working in vitro while using these systems to model and study developmental processes in even greater detail. Also, it is not clear how well in vitro differentiation reproduces in vivo development, or whether this approach results in non-physiological cell types. To further increase the overall understanding of in vitro neural development and address these gaps in knowledge, in this dissertation single cell mass cytometry is applied to molecularly profile neural cell populations throughout mouse in vitro neural development at the protein level, using a targeted antibody panel for detection of neural surface markers, transcription factors, neural filament proteins, and cell signaling molecules. First, an updated single cell debarcoder for mass cytometry analysis is described, which allows for improved data analysis of simultaneously multiplexed samples analyzed by mass cytometry. Then, this updated tool and mass cytometry are combined to analyze in vitro differentiation samples, creating a molecular roadmap of in vitro neural development. Mass cytometry is used to investigate the cellular architecture of mouse in vitro neural differentiation and the resulting dataset is compared to in vivo mouse embryonic development. This comparison identifies relevant in vivo correlates to cell types generated in these in vitro cultures. Single cell RNA sequencing is then used to understand the transcriptomic profile of neural cell types generated in vitro and compared to protein defined phenotypes. Additionally, using these robust methods to molecularly classify cell types, the power of in vitro systems is harnessed to provide fine-level control for rapidly profiling perturbations to neural development. This is demonstrated by an experiment where in vitro cultures are exposed to varying amounts of retinoic acid, a key modulator of neurodevelopmental processes, and the resulting dynamic changes in neural progenitors and terminal cell populations over the course of in vitro neural differentiation are described. This scalable approach for rapid cell phenotyping can be used in future experiments to probe the effect of inhibitors, cytokines, and genetic manipulation on neural cell differentiation and, once applied in disease models, to neurodevelopmental disorders and neurodegeneration. Taken together, the work described in this dissertation advances the tools available for mass cytometry analysis and provides a framework to understand the etiology of neurological disorders with a neurodevelopmental link using in vitro systems.
