A Functional Screen to Identify Novel Effectors of Hematopoietic Stem Cell Activity
Notice bibliographique
Résumé
Abstract The maintenance of blood homeostasis depends on hematopoietic stem cells (HSCs), which rely on two critical properties, namely multipotency and self-renewal. The former enables differentiation into multiple lineages, the latter ensures preservation of fate upon cellular division. By definition, a self-renewal division implies that a HSC is permissive to cell cycle entry, while restrained from engaging in differentiation, apoptosis or senescence pathways. Despite the tremendous progress made towards the identification of the molecular circuitry that governs ESC fate, genes controlling this process in adult HSCs have proven more difficult to unmask. This is principally due to our inability to maintain or expand HSC ex vivo as homogenous populations, to the absence of a stringent surrogate marker to follow the HSC multipotent state and to changes in cell phenotype observed shortly upon facing the selective pressures of in vitro culture conditions, impeding HSC tracking in this context. We now report the results of a novel in vitro to in vivo functional screen, which identified a series of nuclear factors that induced high levels of HSC activity similar to that previously achieved with Hoxb4. We created a database consisting of 689 nuclear factors considered as potential candidate regulators of HSC activity. This list was mostly derived from microarray gene expression profiling of normal and leukemia stem cells including our recently generated FLA2 leukemia (1 in 1.5 cells are leukemia stem cells, G.S. et coll., in preparation). It was also enriched by genes obtained following a review of the literature on stem cell self-renewal. Genes in this database were next ranked from 1 (lowest priority) to 10 (highest priority) based on 3 factors: differential expression between primitive and more mature cellular fractions (e.g., LT-HSC-enriched: 3 points), expression levels (high, highest priority: max 3 points) and the consistency of findings between datasets (max 4 points). Genes with a score of 6 and above (n=139) were selected for functional studies, of which 104 were tested in HSCs, using a high-throughput overexpression in vitro to in vivo assay tailored to circumvent current limitations imposed by the biology of HSCs. In total, 18 new determinants have emerged, 11 of which act in a cell autonomous manner, namely Ski, Smarcc1, Vps72, Trim27, Sox4, Klf10, Prdm16, Erdr1, Cnbp, Xbp1 and Hnrpdl, while the remaining provide a non-autonomous influence on HSC activity, i.e, Fos, Hmgb1, Tcfec, Sfpi1, Zfp472, Hdac1 and Pml. Clonal and phenotypic analyses of hematopoietic tissues derived from selected recipients confirmed that the majority of these factors induced HSC expansion in vitro without perturbing their differentiation in vivo. Epistatic analyses further reveals that 3 of the most potent candidates, namely Ski, Prdm16 and Klf10 may exploit both mechanisms, i.e., cell and non-cell autonomous. The utilization of this novel screening method together with the creation of a database enriched for potential determinants and candidate regulators of adult stem cell activity can now be exploited to devise regulatory networks in these cells.
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) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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 ».