Ischemic heart disease (IHD) is a major cause of mortality and morbidity worldwide, with novel therapeutic strategies urgently needed. Endothelial dysfunction is a hallmark of IHD, contributing to its development and progression. Hypoxia-inducible factors (HIFs) are transcription factors activated in response to low oxygen levels, playing crucial roles in various pathophysiological processes related to cardiovascular diseases. Among the HIF isoforms, HIF2α is predominantly expressed in cardiac vascular endothelial cells and has a key role in cardiovascular diseases. HIFβ, also known as ARNT, is the obligate binding partner of HIFα subunits and is necessary for HIFα’s transcriptional activity. ARNT itself plays an essential role in the development of the cardiovascular system, regulating angiogenesis, limiting inflammatory cytokine production, and protecting against cardiomyopathy. This review provides an overview of the current understanding of HIF2α and ARNT signaling in endothelial cell function and dysfunction and their involvement in IHD pathogenesis. We highlight their roles in inflammation and maintaining the integrity of the endothelial barrier, as well as their potential as therapeutic targets for IHD.
Heart tissue sample preparation for mass spectrometry
(MS) analysis
that includes prefractionation reduces the cellular protein dynamic
range and increases the relative abundance of nonsarcomeric proteins.
We previously described “IN-Sequence” (IN-Seq) where
heart tissue lysate is sequentially partitioned into three subcellular
fractions to increase the proteome coverage more than a single direct
tissue analysis by mass spectrometry. Here, we report an adaptation
of the high-field asymmetric ion mobility spectrometry (FAIMS) coupled
to mass spectrometry, and the establishment of a simple one step sample
preparation coupled with gas-phase fractionation. The FAIMS approach
substantially reduces manual sample handling, significantly shortens
the MS instrument processing time, and produces unique protein identification
and quantification approximating the commonly used IN-Seq method in
less time.
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