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      Transcriptome profiling reveals signaling conditions dictating human spermatogonia fate in vitro

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          Abstract

          Spermatogonial stem cells (SSCs) are essential for the generation of sperm and have potential therapeutic value for treating male infertility, which afflicts >100 million men world-wide. While much has been learned about rodent SSCs, human SSCs remain poorly understood. Here, we molecularly characterize human SSCs and define conditions favoring their culture. To achieve this, we first identified a cell-surface protein, PLPPR3, that allowed purification of human primitive undifferentiated spermatogonia (uSPG) highly enriched for SSCs. Comparative RNA-sequencing analysis of these enriched SSCs with differentiating SPG (KIT + cells) revealed the full complement of genes that shift expression during this developmental transition, including genes encoding key components in the TGF-β, GDNF, AKT, and JAK-STAT signaling pathways. We examined the effect of manipulating these signaling pathways on cultured human SPG using both conventional approaches and single-cell RNA-sequencing analysis. This revealed that GDNF and BMP8B broadly support human SPG culture, while activin A selectively supports more advanced human SPG. One condition—AKT pathway inhibition—had the unique ability to selectively support the culture of primitive human uSPG. This raises the possibility that supplementation with an AKT inhibitor could be used to culture human SSCs in vitro for therapeutic applications.

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          A single-cell resolution map of mouse hematopoietic stem and progenitor cell differentiation.

          Maintenance of the blood system requires balanced cell fate decisions by hematopoietic stem and progenitor cells (HSPCs). Because cell fate choices are executed at the individual cell level, new single-cell profiling technologies offer exciting possibilities for mapping the dynamic molecular changes underlying HSPC differentiation. Here, we have used single-cell RNA sequencing to profile more than 1600 single HSPCs, and deep sequencing has enabled detection of an average of 6558 protein-coding genes per cell. Index sorting, in combination with broad sorting gates, allowed us to retrospectively assign cells to 12 commonly sorted HSPC phenotypes while also capturing intermediate cells typically excluded by conventional gating. We further show that independently generated single-cell data sets can be projected onto the single-cell resolution expression map to directly compare data from multiple groups and to build and refine new hypotheses. Reconstruction of differentiation trajectories reveals dynamic expression changes associated with early lymphoid, erythroid, and granulocyte-macrophage differentiation. The latter two trajectories were characterized by common upregulation of cell cycle and oxidative phosphorylation transcriptional programs. By using external spike-in controls, we estimate absolute messenger RNA (mRNA) levels per cell, showing for the first time that despite a general reduction in total mRNA, a subset of genes shows higher expression levels in immature stem cells consistent with active maintenance of the stem-cell state. Finally, we report the development of an intuitive Web interface as a new community resource to permit visualization of gene expression in HSPCs at single-cell resolution for any gene of choice.
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            Long-term proliferation in culture and germline transmission of mouse male germline stem cells.

            Spermatogenesis is a complex process that originates in a small population of spermatogonial stem cells. Here we report the in vitro culture of spermatogonial stem cells that proliferate for long periods of time. In the presence of glial cell line-derived neurotrophic factor, epidermal growth factor, basic fibroblast growth factor, and leukemia inhibitory factor, gonocytes isolated from neonatal mouse testis proliferated over a 5-month period (>10(14)-fold) and restored fertility to congenitally infertile recipient mice following transplantation into seminiferous tubules. Long-term spermatogonial stem cell culture will be useful for studying spermatogenesis mechanism and has important implications for developing new technology in transgenesis or medicine.
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              The adult human testis transcriptional cell atlas

              Human adult spermatogenesis balances spermatogonial stem cell (SSC) self-renewal and differentiation, alongside complex germ cell-niche interactions, to ensure long-term fertility and faithful genome propagation. Here, we performed single-cell RNA sequencing of ~6500 testicular cells from young adults. We found five niche/somatic cell types (Leydig, myoid, Sertoli, endothelial, macrophage), and observed germline-niche interactions and key human-mouse differences. Spermatogenesis, including meiosis, was reconstructed computationally, revealing sequential coding, non-coding, and repeat-element transcriptional signatures. Interestingly, we identified five discrete transcriptional/developmental spermatogonial states, including a novel early SSC state, termed State 0. Epigenetic features and nascent transcription analyses suggested developmental plasticity within spermatogonial States. To understand the origin of State 0, we profiled testicular cells from infants, and identified distinct similarities between adult State 0 and infant SSCs. Overall, our datasets describe key transcriptional and epigenetic signatures of the normal adult human testis, and provide new insights into germ cell developmental transitions and plasticity.
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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proc Natl Acad Sci USA
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                July 13 2020
                : 202000362
                Article
                10.1073/pnas.2000362117
                7395452
                32661178
                bd6ce9d1-d6bc-4586-ac88-262bd6d568c1
                © 2020

                Free to read

                https://www.pnas.org/site/aboutpnas/licenses.xhtml

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