Magda Marečková

Abstract Gonadal development is a complex process that involves sex determination followed by divergent maturation into either testes or ovaries 1 . Historically, limited tissue accessibility, a lack of reliable in vitro models and critical differences between humans and mice have hampered our knowledge of human gonadogenesis, despite its importance in gonadal conditions and infertility. Here, we generated a comprehensive map of first- and second-trimester human gonads using a combination of single-cell and spatial transcriptomics, chromatin accessibility assays and fluorescent microscopy. We extracted human-specific regulatory programmes that control the development of germline and somatic cell lineages by profiling equivalent developmental stages in mice. In both species, we define the somatic cell states present at the time of sex specification, including the bipotent early supporting population that, in males, upregulates the testis-determining factor SRY and sPAX8s, a gonadal lineage located at the gonadal–mesonephric interface. In females, we resolve the cellular and molecular events that give rise to the first and second waves of granulosa cells that compartmentalize the developing ovary to modulate germ cell differentiation. In males, we identify human SIGLEC15 + and TREM2 + fetal testicular macrophages, which signal to somatic cells outside and inside the developing testis cords, respectively. This study provides a comprehensive spatiotemporal map of human and mouse gonadal differentiation, which can guide in vitro gonadogenesis.

The complex and dynamic cellular composition of the human endometrium remains poorly understood. Previous endometrial single-cell atlases profiled few donors and lacked consensus in defining cell types. We introduce the Human Endometrial Cell Atlas (HECA), a high-resolution single-cell reference atlas (313,527 cells) combining published and new endometrial single-cell transcriptomics datasets of 63 women with and without endometriosis. HECA assigns consensus and identifies previously unreported cell types, mapped in situ using spatial transcriptomics and validated using a new independent single-nuclei dataset (312,246 nuclei, 63 donors). In the functionalis, we identify intricate stromal-epithelial cell coordination via transforming growth factor beta (TGFβ) signaling. In the basalis, we define signaling between fibroblasts and an epithelial population expressing progenitor markers. Integration of HECA with large-scale endometriosis genome-wide association study data pinpoints decidualized stromal cells and macrophages as most likely dysregulated in endometriosis. The HECA is a valuable resource for studying endometrial physiology and disorders, and for guiding microphysiological in vitro systems development.

Maternal exposure to increased steroid hormones, including estrogens, androgens or glucocorticoids during pregnancy results in chronic conditions in offspring that manifest in adulthood. Little is known about effects of progesterone administration in early pregnancy on fetal development. We hypothesised that maternal early pregnancy progesterone supplementation would increase fetal progesterone, affect progesterone target tissues in the developing fetal reproductive system and be metabolised to other bioactive steroids in the fetus. We investigated the effects of progesterone treatment during early pregnancy on maternal and fetal plasma progesterone concentrations, transcript abundance in the fetal pituitary and testes and circulating steroids, at day 75 gestation, using a clinically realistic ovine model. Endogenous progesterone concentrations were lower in male than female fetuses. Maternal progesterone administration increased male, but not female, fetal progesterone concentrations, also increasing circulating 11-dehydrocorticosterone in male fetuses. Maternal progesterone administration altered fetal pituitary and testicular function in ovine male fetuses. This suggests that there may be fetal sex specific effects of the use of progesterone in early pregnancy, and highlights that progesterone supplementation should be used only when there is clear evidence of efficacy and for as limited time as necessary.

The development of therapies promoting recovery after spinal cord injury is a challenge. Alginate hydrogels offer the possibility to develop biocompatible implants with mechanical properties tailored to the nervous tissue, which could provide a permissive environment for tissue repair. Here, the effects of non-functionalized soft calcium alginate hydrogel were investigated in a rat model of thoracic spinal cord hemisection and compared to lesioned untreated controls. Open field locomotion tests were employed to evaluate functional recovery. Tissue analysis was performed with label-free multiphoton microscopy using a multimodal approach that combines coherent anti-Stokes Raman scattering to visualize axonal structures, two-photon fluorescence to visualize inflammation, second harmonic generation to visualize collagenous scarring. Treated animals recovered hindlimb function significantly better than controls. Multiphoton microscopy revealed that the implant influenced the injury-induced tissue response, leading to decreased inflammation, reduced scarring with different morphology and increased presence of axons. Demyelination of contralateral white matter near the lesion was prevented. Reduced chronic inflammation and increased amount of axons in the lesion correlated with improved hindlimb functions, being thus relevant for locomotion recovery. In conclusion, non-functionalized hydrogel improved functional outcome after spinal cord injury in rats. Furthermore, label-free multiphoton microscopy qualified as suitable technique for regeneration studies.

Metabolism supplies energy, building blocks, and signaling molecules vital for cell function and communication, but methods to directly measure it at single-cell and/or spatial resolutions remain technically challenging and inaccessible for most researchers. Single-cell and spatial transcriptomics offer high-throughput data alternatives with a rich ecosystem of computational tools. Here, we present scCellFie, a computational framework to infer metabolic activities from human and mouse transcriptomic data at single-cell and spatial resolution. Applied to ~30 million cell profiles, we generated a comprehensive metabolic atlas across human organs, identifying organ- and cell-type-specific activities. In the endometrium, scCellFie reveals metabolic programs contributing to healthy tissue remodeling during the menstrual cycle, with temporal patterns replicated in data from in vitro cultures. We also uncover disease-associated metabolic alterations in endometriosis and endometrial carcinoma, linked to proinflammatory macrophages, and metabolite-mediated epithelial cell communication, respectively. Ultimately, scCellFie provides a scalable toolbox for extracting interpretable metabolic functionalities from transcriptomic data.