IrGSEA is an R package designed to assess the outcomes of various gene set scoring methods when applied to single-cell RNA sequencing data. This package incorporates six distinct scoring methods that rely on the expression ranks of genes, emphasizing relative expression levels over absolute values. The implemented methods include AUCell, UCell, singscore, ssGSEA, JASMINE and Viper. Previous studies have demonstrated the robustness of these methods to variations in dataset size and composition, generating enrichment scores based solely on the relative gene expression of individual cells. By employing the robust rank aggregation algorithm, irGSEA amalgamates results from all six methods to ascertain the statistical significance of target gene sets across diverse scoring methods. The package prioritizes user-friendliness, allowing direct input of expression matrices or seamless interaction with Seurat objects. Furthermore, it facilitates a comprehensive visualization of results. The irGSEA package and its accompanying documentation are accessible on GitHub (https://github.com/chuiqin/irGSEA). The workflow of irGSEA. Individual cells were independently scored using AUCell, UCell, singscore, ssGSEA, JASMINE and Viper. Differential gene sets were calculated for each cell cluster using distinct enrichment score matrices, with significance determined at an adjusted P-value of ≤ 0.05 (Wilcoxon test). The ‘Up’ or ‘Down’ designation indicates whether the enrichment degree of the differential gene set in the cell cluster is higher or lower compared to other clusters. The robust rank aggregation algorithm was employed to filter statistically significant gene sets that exhibited similar levels of enrichment across all six methods.

Islet transplantation involves the transplantation of pancreatic islets from the pancreas of a donor to another individual. It has proven to be an effective method for the treatment of type 1 diabetes. However, islet transplantation is hampered by immune rejection, as well as the shortage of donor islets. Human umbilical cord Wharton's jelly-derived mesenchymal stem cells (HUMSCs) are an ideal cell source for use in transplantation due to their biological characteristics and their use does not provoke any ethical issues. In this study, we investigated the immunological characteristics of HUMSCs and their effects on lymphocyte proliferation and the secretion of interferon (IFN)-γ, and explored whether direct cell-to-cell interactions and soluble factors, such as IFN-γ were important for balancing HUMSC-mediated immune regulation. We transplanted HUMSCs into diabetic rats to investigate whether these cells can colonize in vivo and differentiate into pancreatic β-cells, and whether the hyperglycemia of diabetic rats can be improved by transplantation. Our results revealed that HUMSCs did not stimulate the proliferation of lymphocytes and did not induce allogeneic or xenogeneic immune cell responses. qRT-PCR demonstrated that the HUMSCs produced an immunosuppressive isoform of human leukocyte antigen (HLA-I) and did not express HLA-DR. Flow cytometry revealed that the HUMSCs did not express immune response-related surface antigens such as, CD40, CD40L, CD80 and CD86. IFN-γ secretion by human peripheral blood lymphocytes was reduced when the cells were co-cultured with HUMSCs. These results suggest that HUMSCs are tolerated by the host in an allogeneic transplant. We transplanted HUMSCs into diabetic rats, and the cells survived in the liver and pancreas. Hyperglycemia of the diabetic rats was improved and the destruction of pancreatic cells was partly repaired by HUMSC transplantation. Hyperglycemic improvement may be related to the immunomodulatory effects of HUMSCs. However, the exact mechanisms involved remain to be further clarified.

Microenvironment signals play a critical role in directing the differentiation of stem cells. Sertoli cells (SCs) provide a unique microenvironment that is essential for germ cell differentiation. Our previous study has demonstrated that human umbilical cord Wharton’s jelly-derived mesenchymal stem cells (HUMSCs) could differentiate towards male germ cells in vitro, but HUMSC-derived germ-like cells expressed only few germ cell markers. The aim of this study was to investigate the effect of SCs on the differentiation of HUMSCs towards male germ cells using a co-culture system that mimicked the in vivo male germ cell microenvironment. HUMSCs formed clump-like features on SC monolayers after seeding for 3 weeks. Differentiated cells formed round colonies that share the morphological features of spermatogonial colonies. RT-PCR, immunofluorescence, confocal microscopy, and Western blot analyses revealed the expression of early germ cell markers STELLA and VASA and male germ cell-specific marker DAZL in differentiated HUMSCs, confirming the presence of cells with characteristics of male germ cells. The HUMSC-SC co-culture system mimics a native microenvironment for germ cell colonization without any in vitro artificial manipulation and can be used to explore the mechanisms controlling the differentiation of male germ cells from HUMSCs. Male germ cells derived from HUMSCs may be used in the therapy for male infertility.

Background: Mesenchymal stromal cells (MSCs) and fibroblasts show similar morphology, surface marker expression, and proliferation, differentiation, and immunomodulatory capacities. These similarities not only blur their cell identities but also limit their application.Methods: We performed single-cell transcriptome sequencing of the human umbilical cord and foreskin MSCs (HuMSCs and FSMSCs) and extracted the single-cell transcriptome data of the bone marrow and adipose MSCs (BMSCs and ADMSCs) from the Gene Expression Omnibus (GEO) database. Then, we performed quality control, batch effect correction, integration, and clustering analysis of the integrated single-cell transcriptome data from the HuMSCs, FMSCs, BMSCs, and ADMSCs. The cell subsets were annotated based on the surface marker phenotypes for the MSCs (CD105⁺, CD90⁺, CD73⁺, CD45⁻, CD34⁻, CD19⁻, HLA-DRA⁻, and CD11b⁻), fibroblasts (VIM⁺, PECAM1⁻, CD34⁻, CD45⁻, EPCAM⁻, and MYH11⁻), and pericytes (CD146⁺, PDGFRB⁺, PECAM1⁻, CD34⁻, and CD45⁻). The expression levels of common fibroblast markers (ACTA2, FAP, PDGFRA, PDGFRB, S100A4, FN1, COL1A1, POSTN, DCN, COL1A2, FBLN2, COL1A2, DES, and CDH11) were also analyzed in all cell subsets. Finally, the gene expression profiles, differentiation status, and the enrichment status of various gene sets and regulons were compared between the cell subsets.Results: We demonstrated 15 distinct cell subsets in the integrated single-cell transcriptome sequencing data. Surface marker annotation demonstrated the MSC phenotype in 12 of the 15 cell subsets. C10 and C14 subsets demonstrated both the MSC and pericyte phenotypes. All 15 cell subsets demonstrated the fibroblast phenotype. C8, C12, and C13 subsets exclusively demonstrated the fibroblast phenotype. We identified 3,275 differentially expressed genes, 305 enriched gene sets, and 34 enriched regulons between the 15 cell subsets. The cell subsets that exclusively demonstrated the fibroblast phenotype represented less primitive and more differentiated cell types.Conclusion: Cell subsets with the MSC phenotype also demonstrated the fibroblast phenotype, but cell subsets with the fibroblast phenotype did not necessarily demonstrate the MSC phenotype, suggesting that MSCs represented a subclass of fibroblasts. We also demonstrated that the MSCs and fibroblasts represented highly heterogeneous populations with distinct cell subsets, which could be identified based on the differentially enriched gene sets and regulons that specify proliferating, differentiating, metabolic, and/or immunomodulatory functions.