Transcriptional activation of elephant shark mineralocorticoid receptor by corticosteroids, progesterone, and spironolactone.
Yoshinao KatsuSatomi KohnoKaori OkaXiaozhi LinSumika OtakeNisha E PillaiWataru TakagiSusumu HyodoByrappa VenkateshMichael E BakerPublished in: Science signaling (2019)
The mineralocorticoid receptor (MR) is a nuclear receptor and part of a large and diverse family of transcription factors that also includes receptors for glucocorticoids, progesterone, androgens, and estrogens. The corticosteroid aldosterone is the physiological activator of the MR in humans and other terrestrial vertebrates; however, its activator is not known in cartilaginous fish, the oldest group of extant jawed vertebrates. Here, we analyzed the ability of corticosteroids and progesterone to activate the full-length MR from the elephant shark (Callorhinchus milii). On the basis of their measured activities, aldosterone, cortisol, 11-deoxycorticosterone, corticosterone, 11-deoxcortisol, progesterone, and 19-norprogesterone are potential physiological mineralocorticoids. However, aldosterone, the physiological mineralocorticoid in humans and other terrestrial vertebrates, is not found in cartilaginous or ray-finned fish. Although progesterone activates MRs in ray-finned fish, progesterone does not activate MRs in humans, amphibians, or alligator, suggesting that during the transition to terrestrial vertebrates, progesterone lost the ability to activate the MR. Both elephant shark MR and human MR are expressed in the brain, heart, ovary, testis, and other nonepithelial tissues, suggesting that MR expression in diverse tissues evolved in the common ancestor of jawed vertebrates. Our data suggest that 19-norprogesterone- and progesterone-activated MR may have unappreciated functions in reproductive physiology.
Keyphrases
- contrast enhanced
- estrogen receptor
- magnetic resonance
- gene expression
- transcription factor
- magnetic resonance imaging
- poor prognosis
- computed tomography
- endothelial cells
- nuclear factor
- atrial fibrillation
- binding protein
- climate change
- long non coding rna
- big data
- white matter
- deep learning
- artificial intelligence
- human health
- heat shock protein