Young and Especially Senescent Endothelial Microvesicles Produce NADPH: The Fuel for Their Antioxidant Machinery.
Guillermo BodegaMatilde AliqueLourdes BohórquezMiriam MoránLuis MagroLilian PueblaSergio CiordiaMaría C MenaElvira ArzaManuel R RamírezPublished in: Oxidative medicine and cellular longevity (2018)
In a previous study, we demonstrated that endothelial microvesicles (eMVs) have a well-developed enzymatic team involved in reactive oxygen species detoxification. In the present paper, we demonstrate that eMVs can synthesize the reducing power (NAD(P)H) that nourishes this enzymatic team, especially those eMVs derived from senescent human umbilical vein endothelial cells. Moreover, we have demonstrated that the molecules that nourish the enzymatic machinery involved in NAD(P)H synthesis are blood plasma metabolites: lactate, pyruvate, glucose, glycerol, and branched-chain amino acids. Drastic biochemical changes are observed in senescent eMVs to optimize the synthesis of reducing power. Mitochondrial activity is diminished and the glycolytic pathway is modified to increase the activity of the pentose phosphate pathway. Different dehydrogenases involved in NADPH synthesis are also increased. Functional experiments have demonstrated that eMVs can synthesize NADPH. In addition, the existence of NADPH in eMVs was confirmed by mass spectrometry. Multiphoton confocal microscopy images corroborate the synthesis of reducing power in eMVs. In conclusion, our present and previous results demonstrate that eMVs can act as autonomous reactive oxygen species scavengers: they use blood metabolites to synthesize the NADPH that fuels their antioxidant machinery. Moreover, senescent eMVs have a stronger reactive oxygen species scavenging capacity than young eMVs.
Keyphrases
- reactive oxygen species
- endothelial cells
- oxidative stress
- mass spectrometry
- hydrogen peroxide
- ms ms
- palliative care
- amino acid
- middle aged
- anti inflammatory
- quality improvement
- blood glucose
- deep learning
- liquid chromatography
- machine learning
- skeletal muscle
- convolutional neural network
- insulin resistance
- weight loss
- gas chromatography