Ca <sup>2+</sup> /Calmodulin‐Dependent Protein Kinase Kinase β Negatively Regulates Progesterone Mediated PGRMC1 Signaling and the Warburg Effect
Notice bibliographique
Résumé
Objectives Ca 2+ /calmodulin‐dependent protein kinase kinase β (CaMKKβ) signaling cascades directly regulate a variety of physiological processes and have been implicated in several human diseases, including cancer and neurodegenerative disorders. We discovered p rogesterone‐ r eceptor m embrane c omponent 1 (PGRMC1) is differentially phosphorylated in CaMKKβ knockout (KO) HEK293 cells. PGRMC1 is a member of the membrane‐associated progesterone receptor (MAPR) family with a cytochrome b5‐like heme‐binding region. The gene is known to be involved in diverse functions, including regulation of cytochrome P450, steroidogenesis, vesicle trafficking, progesterone signaling and mitotic spindle and cell cycle regulation. PGRMC1 is associated with multiple progesterone‐dependent effects in diverse cell types. However, direct progesterone binding to PGRMC1 is yet to be demonstrated. The lack of credible ligand binding to PGRMC1 may be due to the fact that bacterially expressed PGRMC1 preparations may not possess the necessary post‐translational modifications (PTMs) required for progesterone binding. Therefore, we hypothesized that CaMKKβ is an upstream kinase that mediates phosphorylation of PGRMC1 and, thereby, regulates progesterone signaling. Methodology We used TiO 2 column enrichment followed by mass spectrometry to identify differentially expressed phosphopeptides derived from CaMKKβ KO versus wild type HEK293 cells. We interrogated cellular metabolism by measuring oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) as an indicator of mitochondrial respiration and glycolysis, respectively. Further, we used isolectric focusing (IEF) followed by SDS‐PAGE and immunoblotting to identify different charged fractions of PGRMC1. Results Loss of CaMKKβ significantly decreased PGRMC1 protein expression in multiple CaMKKβ KO cell lines. TiO 2 column enriched phosphopeptide analysis revealed the presence of phosphorylated S57, T178, Y180 and S181 peptides in CaMKKβ KO cells whereas only S181 phosphorylation was found in wild type cells. In addition, IEF analysis revealed multiple charged fractions of PGRMC1. The ~pI/pH‐3 fraction was significantly higher in CaMKKβ KO cells which may correspond to increased phosphorylation. Loss of CaMKKβ significantly increased the rate of glycolysis but reduced mitochondrial OCR. Treatment with 10μM progesterone significantly increased the rate of glycolysis within 30 mins in wild type cells; however it failed to show a similar effect in CaMKKβ KO cells. In contrast, progesterone treatment significantly lowered OCR in both wild type and CaMKKβ KO cells within 30 mins. Conclusion CaMKKβ negatively regulates PRGMC1 phosphorylation which may, in turn, control the relative turnover of the protein. CaMKKβ negatively regulates the progesterone‐mediated Warburg effect which may explain the role of CaMKKβ in tumorigenesis and neurodegenerative disease. Our study identifies a link between CaMKKβ and progesterone signaling which may be used for therapeutic targeting. Support or Funding Information Supported by CIHR grant # MOP‐130282 (PF) 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) | 0,002 | 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 ».