Identification of eNOS‐based Megakaryocyte Subpopulations and Their Pharmacological Characterization by IFNγ and IL‐10
Notice bibliographique
Résumé
Purpose Recently, our laboratory identified in human blood two platelet subpopulations based on the presence or absence of a functional endothelial nitric oxide synthase (eNOS)‐signalling pathway and the ability to produce nitric oxide (NO). We have found that eNOS‐negative (eNOS neg ) platelets, although less abundant are more reactive than eNOS‐positive (eNOS pos ) platelets and initiate aggregate/thrombus formation, while eNOS‐positive platelets through their ability to generate NO limit aggregate size. As platelets derive from bone marrow megakaryocytes, we hypothesized that eNOS neg and eNOS pos subpopulations of megakaryocytes exist and give rise to their respective eNOS‐based platelet subpopulations. Additionally, we hypothesized that interferon‐γ (IFNγ) and interleukin‐10 (IL‐10), which are known to counter‐regulate eNOS expression and megakaryocyte differentiation, would determine in a concentration manner the ratio of eNOS neg to eNOS pos megakaryocytes. Methods The human megakaryoblastic cell line (Meg‐01) and megakaryocytes isolated from eNOS‐GFP transgenic mice were studied. RT‐PCR and DNA sequencing were performed to validate eNOS presence within Meg‐01. Flow cytometry was used to identify eNOS neg and eNOS pos megakaryocytes, and NO production was measured using DAF‐FM, a cell‐permeable fluorescent probe. Further, Meg‐01 cells were treated for 48 hours with IFNγ (0 – 100 ng/ml) and IL‐10 (0 – 100 ng/ml), and eNOS as well as inducible NOS (iNOS) were measured by flow cytometry and immunoblot, respectively. Results The presence of eNOS was confirmed in Meg‐01 and eNOS‐GFP transgenic mice. Similar to human platelets, the majority of Meg‐01 cells were eNOS pos (91.5%±1.2 vs. 8.5%±1.2 eNOS neg , P<0.05 ) and NO‐producing (92.0%±3.34 vs. 8.0%±6.68 non‐producing, P < 0.05 ). Conversely, similar to mouse platelets, the majority of mouse megakaryocytes were eNOS neg (95.8%±0.7 vs. 4.2%±0.7 eNOS pos , P < 0.05 ). The proinflammatory cytokine IFNγ decreased the percent eNOS pos Meg‐01 in a concentration‐dependent manner and also increased the level of iNOS within Meg‐01. IL‐10 in a concentration‐dependent manner (10–100ng/ml) reversed IFNγ‐induced iNOS expression, but not the decrease in percent eNOS pos Meg‐01. The changes in eNOS expression within Meg‐01 were further confirmed by qPCR within the total Meg‐01 population and demonstrated that IFNγ (10 ng/ml) caused a 6.4 fold decrease of eNOS mRNA but only 2.2 fold decrease in the presence IL‐10 (100ng/ml). Conclusions eNOS‐based megakaryocyte subpopulations exist within the Meg‐01 cell line and in eNOS‐GFP transgenic mice. Similar to previously shown for platelets, major species differences exist in eNOS pos to eNOS neg ratios between human and mouse megakaryocytes. IFNγ decreases eNOS expression and percent eNOS pos Meg‐01; while increasing iNOS expression. However, high concentrations of IL‐10 attenuated this effect. Our data show that pro‐inflammatory IFN‐γ may promote growth/differentiation of megakaryocytes with decreased levels/absence of eNOS, which may lead to formation of higher numbers of more reactive eNOS neg platelets potentially leading to higher risk of a pro‐thrombotic state. Further experiments are required to confirm whether eNOS pos and eNOS neg megakaryocytes give rise to their respective platelet subtypes. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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 | 0,001 |
| 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 ».