Regulation of Spermatogonial Stem Cells by MicroRNAs.
Notice bibliographique
Résumé
MicroRNAs (miRNAs) have recently been identified as a new class of short single-stranded endogenous RNA molecules (~22 nt in length). Although miRNAs were first discovered in Caenorhabditis elegans in 1993, it was only 10 years ago that they were identified in mammals. MiRNAs are highly conserved across species and it has been estimated that miRNAs may regulate up to 30% of all genes in the human genome. MiRNAs have critical functions in many diverse biological processes, including the regulation of stemness, cell proliferation, differentiation, and apoptosis. The miRNA 17-92 cluster has been suggested to play important roles in regulating renewal and/or differentiation of stem cells, including in ES cells and in other adult stem cells. However, the function of miRNAs in regulating spermatogonial stem cells (SSCs) is still unknown. In this study, we explored the expression, the role, and the targets of the miRNA 17-92 cluster in SSCs, specifically miRNA-20, miRNA-106a, and miRNA-93. Real-time PCR and fluorescent in situ hybridization revealed that miRNA-20 and miRNA-106a were abundantly expressed in mouse SSCs (GFRA1+ spermatogonia), whereas their expression decreased significantly in the differentiated c-kit+ spermatogonia, suggesting that miRNA-20 and miRNA-106a play a role in regulating renewal of the SSCs. MiRNA-93 was significantly lower in the SSCs compared to the differentiated spermatogonia, suggesting that miRNA-93 regulates differentiation. Using miRNA microarrays, we identified a list of miRNAs that were enriched in the SSCs compared to non-stem cells, e.g., Let-7G and Let-7I. To identify cell phenotype and genes regulated by a particular miRNA, we used mimics to miRNA-20, miRNA-106a, and miRNA-93, both in vitro and in vivo. The miRNA mimics are chemically synthesized RNA designed to mimic individual endogenous mature miRNAs. The mimics enter the miRNA-processing pathway and are treated identical to their endogenous counterpart. Semi-quantitative RT-PCR demonstrated that miRNA-20 and miRNA-106a mimics increased expression of PCNA and Plzf mRNA in the SSCs. In contrast, miRNA-20 and miRNA-106a inhibitors induced the expression of c-kit mRNA. These results further suggest that miRNA-20 and miRNA-106a may be involved in renewal of SSCs. Using software prediction and an in vitro study, we demonstrated that Stat3 is a target of miRNA-20 and miRNA-106a. We next examined the role of these miRNAs in vivo using mimics transfected into the GFRA1+ SSCs. These miRNA-transfected stem cells were then transplanted into seminiferous tubules of sterile busulfan treated mice. The miRNA-20 and miRNA-106a mimics increased significantly the number of SSCs in the testes of the busulfan treated mice, compared to controls, when analyzed by immunohistochemistry after 60 days. Our study provides novel insights into the endogenous small RNA molecules that regulate SSCs and has important implications on offering new therapeutic targets for the treatment of male infertility as well as a novel approach for the treatment of male contraception. (platform)
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».