Stress Erythropoiesis Elicits a Program of Gene Regulation That Overlaps with Interferon-γ.
Notice bibliographique
Résumé
Abstract Erythropoietin (EPO), the primary cytokine regulator of red blood cell production, acts through binding to its cognate receptor (EPO-R), which is primarily expressed on erythroid precursors. Knockout studies have illustrated a critical role for EPO, EPO-R and the downstream tyrosine kinase JAK2 in embryogenesis as mice lacking any of these components die from a fatal anemia at E13.5. These data suggest that EPO-R and/or JAK2 are required to promote erythropoiesis in vivo. EPO provides mitogenic, differentiative and cell survival signals to erythroid progenitors. We have performed microarray studies to identify target genes regulated by EPO in cell lines and primary cells. We utilized an erythroid cell line (HCD-57), a myeloid cell line stably expressing the EPO-R (Ba/F3-EPO-R), fetal liver cells isolated from E13.5 mice as well as splenocytes isolated from Phenylhydrazine (PHZ)-primed adult mice. Fetal liver cells permit the study of normal erythropoiesis in a fetal setting whereas the PHZ-primed erythroblasts permit analysis of stress erythropoiesis in adult mice. We harvested cells at 1, 8, 12 and 24 hr after EPO stimulation which correspond to immediate early gene induction (1 hr), S phase entry (8 hr) and G2/M (24 hr) time points. RNA was prepared and hybridized to the Affymetrix U74A mouse chip. Data was analyzed and only those genes with statistical significance (p < 0.05) were considered for further characterization. Analysis of the 1 hr time points has revealed that six genes are co-regulated by EPO in all four cellular environments. Included within this co-hort are the Suppressor of Cytokine Signaling genes (Cis, SOCS-1 and SOCS-3) and Myc, as well as two novel genes. We compared our datasets with other published analyses. The Williams laboratory has identified an Interferon-Stimulated Gene “ISG” data set corresponding to genes induced by Type I or Type II Interferon’s. We queried our PHZ-primed erythroblast data set against the Williams ISG database. Of the 305 human genes in the ISG database, 218 are expressed on the Affymetrix chip. We searched our dataset for genes that are induced 1.5-fold or greater at 2 of 4, 3 of 4 or 4 of 4 time points. Thirty-four genes are also stimulated by EPO in PHZ-primed erythroblasts including classical IFN-regulated genes such as Interferon-regulator factor-1 (IRF-1), Interferon-stimulated gene-15 (ISG-15), Interferon-induced transmembrane protein 3-like (IFITM-3l), Protein Kinase R (PKR) and Signal Transducer and Activator of Transcription-1 (STAT1). We have previously demonstrated that STAT1 is a negative regulator of murine erythropoiesis utilizing STAT1-deficient mice. We also analyzed immediate early gene regulation in fetal liver cells and PHZ-primed erythroblasts isolated from STAT1-deficient mice stimulated with EPO for 1 hr. These data were compared with the relevant wild type data sets. EPO stimulates the induction of the ubiquitin-like protein, ISG-15 in both wild type and STAT1−/− erythroblasts. Several signaling proteins have been shown to be covalently modified by ISG-15 including STAT1. ISG-15 is removed from ISGylated products by the deubiquitinating enzyme, Ubp43. EPO stimulates a rapid accumulation of Ubp43 in wild type cells, however, EPO fails to induce Ubp43 mRNA in STAT1-deficient fetal liver and PHZ-primed erythroblasts. Experiments are underway to confirm that the mechanism by which STAT1 exerts negative regulation of erythropoiesis is via upregulation of the deubiquitinating enzyme, Ubp43.
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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 ».