Resolving the complexity of oviduct biology and pathology by comprehensive single-cell sequencing across species


The recent past has witnessed a substantial revolution in the omics fields due to the exponential development of powerful cutting-edge platforms and the optimisation of their protocols. Concretely, the ability to survey single transcriptomes composing a biological network through single-cell RNA sequencing (scRNA-seq) has translated into substantial innovation and exciting scientific discoveries in both basic and applied research. In this project, this technique was combined with a biological systems approach to gain a deeper understanding of the identities and processes regulating the human fallopian tube and the mouse oviduct, two equivalent reproductive organs that play a key role in female health and fertilisation. The first part of this thesis focuses on establishing a comprehensive single-cell atlas of the mouse oviducts, which was one of the few mouse organs that had not been deeply characterised yet. To this end, an extensive and careful technical optimisation was undertaken, followed by an experimental phase and a subsequent analysis and initial validation of the high-throughput murine data. The second part of the work then focused on advancing our understanding of the fallopian tubes and establishing, for the first time, inter-species comparisons between the murine and human tubes. Furthermore, the results obtained by scRNA-seq were used to interrogate large bulk transcriptomic datasets from ovarian cancers, in search of putative biological mechanisms that under homeostatic conditions maintain the physiological status of this organ, but under unfavourable conditions could play a role in these pathological conditions.
The initial technical optimisation enabled the design of the most effective cell isolation protocol, specifically tailored for this organ. This optimised protocol maximised cell recovery, improved cell viability and allowed the isolation of a balanced and representative oviduct cell population. This protocol generated novel scRNA-seq data from the mouse oviducts, which along with the creation of a robust and consistent bioinformatics analytical pipeline, enabled the extraction of functional insights into the oviduct biology, some of which, were initially validated. Importantly, this bioinformatics analysis was able to capture not only the previously known cell lineages comprising the oviducts, but also, to identify novel ones, including new cellular subtypes and intermediate cell phenotypes requiring further investigation due to their potential importance in the organ differentiation and homeostasis. Moreover, the newly generated oviduct data allowed a comparison between the human fallopian tube versus the mouse oviduct populations and cell-cell interactions maintaining their biology for the first time. Results from this analysis highlighted the dominant presence of the adaptive immune system in the fallopian tube in contrast to the oviduct situation, where the innate system was more represented. Furthermore, profound differences between the oviduct and fallopian tube cell identities were detected, even for those belonging to the same lineage and type. Despite these differences, the identified biological interactions among the cellular components and the molecular pathways underlying such interactions remained very similar across species. Finally, this project was also able to demonstrate how advanced insights into the cell identities and molecular processes characterising the healthy fallopian tubes and oviducts can serve the purpose of advancing our understanding of the diseased state and the mechanisms behind it. Indeed, scRNA-seq analysis of both species’ organs enabled a series of bioinformatic analyses that highlighted pathways and cell populations potentially relevant for the pathogenesis of ovarian cancers. A finding that could open the door to new therapeutical avenues subject to the appropriate mechanistic validation of the data-driven evidence.

Advisor: Ahmed, A