Login / Signup

Visualization of β-adrenergic receptor dynamics and differential localization in cardiomyocytes.

Marc Bathe-PetersPhilipp GmachHorst-Holger BoltzJürgen EinsiedelMichael GotthardtHarald HübnerPeter GmeinerMartin J LohsePaolo Annibale
Published in: Proceedings of the National Academy of Sciences of the United States of America (2021)
A key question in receptor signaling is how specificity is realized, particularly when different receptors trigger the same biochemical pathway(s). A notable case is the two β-adrenergic receptor (β-AR) subtypes, β1 and β2, in cardiomyocytes. They are both coupled to stimulatory Gs proteins, mediate an increase in cyclic adenosine monophosphate (cAMP), and stimulate cardiac contractility; however, other effects, such as changes in gene transcription leading to cardiac hypertrophy, are prominent only for β1-AR but not for β2-AR. Here, we employ highly sensitive fluorescence spectroscopy approaches, in combination with a fluorescent β-AR antagonist, to determine the presence and dynamics of the endogenous receptors on the outer plasma membrane as well as on the T-tubular network of intact adult cardiomyocytes. These techniques allow us to visualize that the β2-AR is confined to and diffuses within the T-tubular network, as opposed to the β1-AR, which is found to diffuse both on the outer plasma membrane as well as on the T-tubules. Upon overexpression of the β2-AR, this compartmentalization is lost, and the receptors are also seen on the cell surface. Such receptor segregation depends on the development of the T-tubular network in adult cardiomyocytes since both the cardiomyoblast cell line H9c2 and the cardiomyocyte-differentiated human-induced pluripotent stem cells express the β2-AR on the outer plasma membrane. These data support the notion that specific cell surface targeting of receptor subtypes can be the basis for distinct signaling and functional effects.
Keyphrases
  • cell surface
  • high glucose
  • induced pluripotent stem cells
  • endothelial cells
  • transcription factor
  • single molecule
  • machine learning
  • dna methylation
  • young adults
  • electronic health record
  • copy number