Sexual differences in mitochondrial and related proteins in rat cerebral microvessels: A proteomic approach.
Sinisa CikicPartha K ChandraJarrod C HarmanIbolya RutkaiPrasad Vg KatakamJessie J GuidryJeffrey M GiddayDavid W BusijaPublished in: Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism (2020)
Sex differences in mitochondrial numbers and function are present in large cerebral arteries, but it is unclear whether these differences extend to the microcirculation. We performed an assessment of mitochondria-related proteins in cerebral microvessels (MVs) isolated from young, male and female, Sprague-Dawley rats. MVs composed of arterioles, capillaries, and venules were isolated from the cerebrum and used to perform a 3 versus 3 quantitative, multiplexed proteomics experiment utilizing tandem mass tags (TMT), coupled with liquid chromatography/mass spectrometry (LC/MS). MS data and bioinformatic analyses were performed using Proteome Discoverer version 2.2 and Ingenuity Pathway Analysis. We identified a total of 1969 proteins, of which 1871 were quantified by TMT labels. Sixty-four proteins were expressed significantly (p < 0.05) higher in female samples compared with male samples. Females expressed more mitochondrial proteins involved in energy production, mitochondrial membrane structure, anti-oxidant enzyme proteins, and those involved in fatty acid oxidation. Conversely, males had higher expression levels of mitochondria-destructive proteins. Our findings reveal, for the first time, the full extent of sexual dimorphism in the mitochondrial metabolic protein profiles of MVs, which may contribute to sex-dependent cerebrovascular and neurological pathologies.
Keyphrases
- mass spectrometry
- oxidative stress
- liquid chromatography
- subarachnoid hemorrhage
- fatty acid
- mental health
- gene expression
- big data
- machine learning
- blood brain barrier
- high resolution mass spectrometry
- genome wide
- data analysis
- hydrogen peroxide
- artificial intelligence
- endoplasmic reticulum
- binding protein
- deep learning
- psychometric properties