A Novel Osteoclastic Network Determines In Vitro Niche for Mouse and Human Hematopoietic Stem Cells
Notice bibliographique
Résumé
Abstract Abstract 1325 New innovative strategies are needed to expand human hematopoietic stem cells (HSCs) for clinical applications. In this perspective, we recently developed an in vitro/in vivo screening strategy, which revealed 18 nuclear factors that enhance HSC activity (Deneault et al., Cell 2009). During these experiments, mouse HSCs were kept for 12 days in mini-cultures that included viral producer cells for each tested factor. Interestingly, 4 of the 18 hits identified in this initial screen, i.e., Fos, Tcfec, Hmgb1 and Sfpi1 operated through non-HSC autonomous (NHA) mechanisms: expanded HSCs were not infected with retrovirus. This suggested that the transfected viral producer cells (feeder cells) produced membrane-bound or soluble molecules that promote expansion of HSCs introduced in these cultures. We now provide evidence that seven additional factors, i.e., Smarcc1, Vps72, Sox4, Klf10, Ski, Prdm16 and Erdr1 significantly enhance HSC activity through NHA mechanisms, hereafter called “NHA factors”. Moreover, we found that Vps72, Fos and Klf10 also promote expansion of human HSCs by NHA mechanisms. Interestingly at least for feeders expressing Klf10, we observed that physical contact between HSCs and these engineered support cells was not necessary, suggesting the presence of secreted molecule(s) in the medium. Expression profiling was next performed using mRNA extracted from feeder cells transduced with each of the NHA factors. Firstly, we shed light on the transcriptional make up and potential convergence of signaling pathways in the engineered feeder cells: our results reveal two independent but interconnected transcriptional regulatory subnetworks. Strikingly, some constituents of the subnetworks, i.e., Sfpi1, Fos, Klf10 and Tcfec (Mitf-related) have previously been shown to play critical roles in the regulation of osteoclasts, which are a myeloid-derived population of cells residing in the HSC bone marrow niche. In addition, all of the NHA factors act in concert to increase Prdm16 expression levels in a range from 2.5- to 54.6-fold. For this reason, Prdm16 clearly holds the position of central hub of the osteoclastic network. However, Tcfec represents the ultimate downstream effector of this pathway as Prdm16 elevates its expression levels by 18.9-fold. In parallel, Prdm16 can also increase the expression of Sfpi1, which in turn can upregulate Tcfec expression up to 874-fold. Moreover, upregulated mRNA targets corresponding to factors that are secreted or associated with the plasma membrane were considered as potential candidate agonists of HSC self-renewal. A high degree of overlap was observed between the sets of proteins produced by feeder cells engineered to overexpress Sfpi1, Fos, Klf10, Tcfec or Ski. These secreted and membrane bound proteins include Agt, Aspn, Ogn, Ptgds, Nckap1l, Rgs16 and Lcn2. Studies are ongoing to characterize the contribution of these newly identified NHA proteins in HSC expansion. Validation of these NHA proteins in human HSC expansion will have a clear potential for translational medicine. Disclosures: No relevant conflicts of interest to declare.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| 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) | 0,002 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».