Distinct Regulatory Networks Govern Human Hematopoietic Stem Cell Across Development
Notice bibliographique
Résumé
Abstract Introduction: Much of our fundamental understanding of stem cell biology comes from studies of hematopoiesis where single cells produce differentiated progeny while still retaining the ability to produce daughter stem cells (self-renewal). The cardinal property of a stem cell, whether normal or malignant, is self-renewal; the key biological process that ensures the ability of the stem cell to maintain long-term clonal growth. However, our understanding of the molecular basis of self-renewal in human hematopoiesis is limited. At the embryonic stage fetal liver is the main source of hematopoiesis; from week 6 of gestation until before birth. At this stage HSCs are in a different microenvironment but capable of self-renewing and differentiation to the full spectrum of blood lineages. While murine studies uncovered several intrinsic differences between fetal and adult HSCs, a comprehensive analysis of human HSC compartment across development is lacking. In this study we have combined HSC purification methods and xenograft quantitative assay in conjunction with low input RNA sequencing and Enhanced Reduced Representation Bisulfite Sequencing (ERRBS) to provide a comprehensive functional and molecular outlook of human stem cell compartment across development. Results: We followed the dynamics of four sub-fractions of CD34+CD38- divided by CD90 and CD49f expression across human blood development: fetal liver (hFL) and adult bone marrow (hBM). Using xenograft model, we identified human long, intermediate and short term HSCs in hFL and hBM. 5 single CD90+CD49f+ hFL cells were capable of sustaining the multilineage graft for over 52 weeks up to tertiary recipient, while BM cells only last for 20 weeks in the primary recipient. The frequency of LT-HSC in the CD90+CD49f+ compartment goes from 1/8 in hFL to 1/50 in hBM. hFL CD90-CD49f+ cells showed an intermediate repopulation capacity up to 44 weeks in secondary recipient. On average 10% of hFL long term HSC (LT-HSC) were in S/G2/M phase, in contrast only 0.4% of BM LT-HSC were in S/G2/M phase indicating that hFL HSCs are 20 times more in cycle compare to BM. We found that 320 genes were expressed differentially between LT-HSC and multipotent progenitors (MPP) in hBM as oppose to only 32 genes found to be differentially expressed in hFL (FDR<0.1). Interestingly, we found only 2 genes in common between these two groups. ERRBS showed an overall increase in methylation of HSC compartment in hBM compare to hFL and gradual demethylation of lineage associated genes in MPP. Conclusion: Our data indicate that there are distinct regulatory networks that govern hFL and hBM HSC self-renewal. We found very little differences in gene expression between all hFL HCS compartments (average 20 genes) compare to hBM (average 224), indicating that by adulthood self-renewal is becoming more restricted to the LT-HSC compartment. 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) | 0,001 | 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 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 ».