Search Results (2)

Background and Aims: Myeloperoxidase (MPO) plays a critical role in the innate immune response and has been suggested to be a surrogate marker of oxidative stress and inflammation, with elevated levels implicated in cardiovascular diseases, such as atherosclerosis and heart failure, as well as in conditions like rheumatoid arthritis and cancer. While MPO is well-known in leukocytes, its expression and function in human endothelial cells remain unclear. This study investigates MPO expression in patient-derived endothelial colony-forming cells (ECFCs) and its potential association with CAD and mitochondrial function. Methods: ECFCs were cultured from the peripheral blood of 93 BioHEART-CT patients. MPO expression and associated functions were examined using qRT-PCR, immunochemistry, flow cytometry, and MPO activity assays. CAD presence was defined using CT coronary angiography (CACS > 0). Results: We report MPO presence in patient-derived ECFCs for the first time. MPO protein expression occurred in 70.7% of samples (n = 41) which had nuclear co-localisation, an atypical observation given its conventional localisation in the granules of neutrophils and monocytes. This suggests potential alternative roles for MPO in nuclear processes. MPO mRNA expression was detected in 66.23% of samples (n = 77). CAD patients had a lower proportion of MPO-positive ECFCs compared to non-CAD controls (57.45% vs. 80%, p = 0.04), a difference that persisted in the statin-naïve sub-cohort (53.85% vs. 84.62%, p = 0.02). Non-CAD patients with MPO expression showed upregulated mitochondrial-antioxidant genes (AIFM2, TXNRD1, CAT, PRDX3, PRDX6). In contrast, CAD patients with MPO gene expression had heightened mROS production and mitochondrial mass and decreased mitochondrial function compared to that of CAD patients without MPO gene expression. Conclusions: MPO is present in the nucleus of ECFCs. In non-CAD ECFCs, MPO expression is linked to upregulated mitochondrial-antioxidant genes, whereas in CAD ECFCs, it is associated with greater mitochondrial dysfunction. Full article

Peroxisomes are ubiquitous membrane-bound organelles, and aberrant localisation of peroxisomal proteins contributes to the pathogenesis of several disorders. Many computational methods focus on assigning protein sequences to subcellular compartments, but there are no specific tools tailored for the sub-localisation (matrix vs. membrane) of peroxisome proteins. We present here In-Pero, a new method for predicting protein sub-peroxisomal cellular localisation. In-Pero combines standard machine learning approaches with recently proposed multi-dimensional deep-learning representations of the protein amino-acid sequence. It showed a classification accuracy above 0.9 in predicting peroxisomal matrix and membrane proteins. The method is trained and tested using a double cross-validation approach on a curated data set comprising 160 peroxisomal proteins with experimental evidence for sub-peroxisomal localisation. We further show that the proposed approach can be easily adapted (In-Mito) to the prediction of mitochondrial protein localisation obtaining performances for certain classes of proteins (matrix and inner-membrane) superior to existing tools. Full article