Proteomic Assessment of Hypoxia-Pre-Conditioned Human Bone Marrow Mesenchymal Stem Cell-Derived Extracellular Vesicles Demonstrates Promise in the Treatment of Cardiovascular Disease.
Cynthia M XuCatherine KarbasiafsharRayane Brinck TeixeiraNagib AhsanGiana Blume CorssacFrank W SellkeM Ruhul AbidPublished in: International journal of molecular sciences (2023)
Human bone marrow mesenchymal stem cell derived-extracellular vesicles (HBMSC-EV) are known for their regenerative and anti-inflammatory effects in animal models of myocardial ischemia. However, it is not known whether the efficacy of the EVs can be modulated by pre-conditioning of HBMSC by exposing them to either starvation or hypoxia prior to EV collection. HBMSC-EVs were isolated following normoxia starvation (NS), normoxia non-starvation (NNS), hypoxia starvation (HS), or hypoxia non-starvation (HNS) pre-conditioning. The HBMSC-EVs were characterized by nanoparticle tracking analysis, electron microscopy, Western blot, and proteomic analysis. Comparative proteomic profiling revealed that starvation pre-conditioning led to a smaller variety of proteins expressed, with the associated lesser effect of normoxia versus hypoxia pre-conditioning. In the absence of starvation, normoxia and hypoxia pre-conditioning led to disparate HBMSC-EV proteomic profiles. HNS HBMSC-EV was found to have the greatest variety of proteins overall, with 74 unique proteins, the greatest number of redox proteins, and pathway analysis suggestive of improved angiogenic properties. Future HBMSC-EV studies in the treatment of cardiovascular disease may achieve the most therapeutic benefits from hypoxia non-starved pre-conditioned HBMSC. This study was limited by the lack of functional and animal models of cardiovascular disease and transcriptomic studies.
Keyphrases
- endothelial cells
- cardiovascular disease
- bone marrow
- mesenchymal stem cells
- type diabetes
- stem cells
- machine learning
- metabolic syndrome
- heart failure
- south africa
- electron microscopy
- umbilical cord
- atrial fibrillation
- left ventricular
- zika virus
- artificial intelligence
- big data
- dengue virus
- replacement therapy
- case control