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Aims: A variety of vessels, such as resistance pulmonary arteries (PA) and fetoplacental arteries and the ductus arteriosus (DA) are specialized in sensing and responding to changes in oxygen tension. Despite opposite stimuli, normoxic DA contraction and hypoxic fetoplacental and PA vasoconstriction share some mechanistic features. Activation of neutral sphingomyelinase (nSMase) and subsequent ceramide production has been involved in hypoxic pulmonary vasoconstriction (HPV). Herein we aimed to study the possible role of nSMase-derived ceramide as a common factor in the acute oxygen-sensing function of specialized vascular tissues. Results: The nSMase inhibitor GW4869 and an anticeramide antibody reduced the hypoxic vasoconstriction in chicken PA and chorioallantoic arteries (CA) and the normoxic contraction of chicken DA. Incubation with interference RNA targeted to SMPD3 also inhibited HPV. Moreover, ceramide and reactive oxygen species production were increased by hypoxia in PA and by normoxia in DA. Either bacterial sphingomyelinase or ceramide mimicked the contractile responses of hypoxia in PA and CA and those of normoxia in the DA. Furthermore, ceramide inhibited voltage-gated potassium currents present in smooth muscle cells from PA and DA. Finally, the role of nSMase in acute oxygen sensing was also observed in human PA and DA. Innovation: These data provide evidence for the proposal that nSMase-derived ceramide is a critical player in acute oxygen-sensing in specialized vascular tissues. Conclusion: Our results indicate that an increase in ceramide generation is involved in the vasoconstrictor responses induced by two opposite stimuli, such as hypoxia (in PA and CA) and normoxia (in DA)., Depto. de Farmacología y Toxicología, Fac. de Medicina, TRUE, pub

Microvascular dysfunction and resulting tissue hypoxia is a major contributor to the pathogenesis and evolution of cardiovascular diseases (CVD). Diverse gene and cell therapies have been proposed to preserve the microvasculature or boost angiogenesis in CVD with moderate benefit. In this study, we tested in vivo the impact of sequential delivery by bone marrow cells of the pro-angiogenic factors vascular endothelial growth factor (VEGFA) and sphingosine-1-phosphate (S1P) in a myocardial infarction model. For that we transduced mouse bone marrow cells with lentiviral vectors coding for VEGFA or sphingosine kinase (SPHK1), which catalyzes S1P production, and injected them intravenously 4 and 7 days after cardiac ischemia/reperfusion in mice. Sequential delivery by transduced BM cells of VEGFA and S1P led to increased endothelial cell numbers and shorter extravascular distances in the infarct zone which support better oxygen diffusion 28 days post-MI as shown by automated 3D image analysis of the microvasculature. Milder effects were observed in the remote zone together with increased proportion of capillaries. BM cells delivering VEGFA and S1P also decreased myofibroblast abundance and restricted adverse cardiac remodeling without major impact on cardiac contractility. Our results indicate that BM cells engineered to sequentially deliver VEGFA/S1P angiogenic factors may constitute a promising strategy to improve micro-vascularization and oxygen diffusion thus limiting the adverse consequences of cardiac ischemia.

Cardiovascular disease (CVD) is the leading cause of mortality in the world, with most CVD-related deaths resulting from myocardial infarction or stroke. The main underlying cause of thrombosis and cardiovascular events is atherosclerosis, an inflammatory disease that can remain asymptomatic for long periods. There is an urgent need for therapeutic and diagnostic options in this area. Atherosclerotic plaques contain autoantibodies, and there is a connection between atherosclerosis and autoimmunity. However, the immunogenic trigger and the effects of the autoantibody response during atherosclerosis are not well understood. Here we performed high-throughput single-cell analysis of the atherosclerosis-associated antibody repertoire. Antibody gene sequencing of more than 1,700 B cells from atherogenic Ldlr and control mice identified 56 antibodies expressed by in-vivo-expanded clones of B lymphocytes in the context of atherosclerosis. One-third of the expanded antibodies were reactive against atherosclerotic plaques, indicating that various antigens in the lesion can trigger antibody responses. Deep proteomics analysis identified ALDH4A1, a mitochondrial dehydrogenase involved in proline metabolism, as a target antigen of one of these autoantibodies, A12. ALDH4A1 distribution is altered during atherosclerosis, and circulating ALDH4A1 is increased in mice and humans with atherosclerosis, supporting the potential use of ALDH4A1 as a disease biomarker. Infusion of A12 antibodies into Ldlr mice delayed plaque formation and reduced circulating free cholesterol and LDL, suggesting that anti-ALDH4A1 antibodies can protect against atherosclerosis progression and might have therapeutic potential in CVD.

The composition and physical properties of the extracellular matrix (ECM) critically influence tumor progression, but the molecular mechanisms underlying ECM layering are poorly understood. Tumor–stroma interaction critically depends on cell communication mediated by exosomes, small vesicles generated within multivesicular bodies (MVBs). We show that caveolin-1 (Cav1) centrally regulates exosome biogenesis and exosomal protein cargo sorting through the control of cholesterol content at the endosomal compartment/MVBs. Quantitative proteomics profiling revealed that Cav1 is required for exosomal sorting of ECM protein cargo subsets, including Tenascin-C (TnC), and for fibroblast-derived exosomes to efficiently deposit ECM and promote tumor invasion. Cav1-driven exosomal ECM deposition not only promotes local stromal remodeling but also the generation of distant ECM-enriched stromal niches in vivo. Cav1 acts as a cholesterol rheostat in MVBs, determining sorting of ECM components into specific exosome pools and thus ECM deposition. This supports a model by which Cav1 is a central regulatory hub for tumor–stroma interactions through a novel exosome-dependent ECM deposition mechanism.

Background: A fundamental challenge in quantitation of biomolecules for cancer biomarker discovery is owing to the heterogeneous nature of human biospecimens. Although this issue has been a subject of discussion in cancer genomic studies, it has not yet been rigorously investigated in mass spectrometry based proteomic and metabolomic studies. Purification of mass spectometric data is highly desired prior to subsequent analysis, e.g., quantitative comparison of the abundance of biomolecules in biological samples. Methods: We investigated topic models to computationally analyze mass spectrometric data considering both integrated peak intensities and scan-level features, i.e., extracted ion chromatograms (EICs). Probabilistic generative models enable flexible representation in data structure and infer sample-specific pure resources. Scan-level modeling helps alleviate information loss during data preprocessing. We evaluated the capability of the proposed models in capturing mixture proportions of contaminants and cancer profiles on LC-MS based serum proteomic and GC-MS based tissue metabolomic datasets acquired from patients with hepatocellular carcinoma (HCC) and liver cirrhosis as well as synthetic data we generated based on the serum proteomic data. Results: The results we obtained by analysis of the synthetic data demonstrated that both intensity-level and scan-level purification models can accurately infer the mixture proportions and the underlying true cancerous sources with small average error ratios (< 7 %) between estimation and ground truth. By applying the topic model-based purification to mass spectrometric data, we found more proteins and metabolites with significant changes between HCC cases and cirrhotic controls. Candidate biomarkers selected after purification yielded biologically meaningful pathway analysis results and improved disease discrimination power in terms of the area under ROC curve compared to the results found prior to purification. Conclu

Background: A fundamental challenge in quantitation of biomolecules for cancer biomarker discovery is owing to the heterogeneous nature of human biospecimens. Although this issue has been a subject of discussion in cancer genomic studies, it has not yet been rigorously investigated in mass spectrometry based proteomic and metabolomic studies. Purification of mass spectometric data is highly desired prior to subsequent analysis, e.g., quantitative comparison of the abundance of biomolecules in biological samples. Methods: We investigated topic models to computationally analyze mass spectrometric data considering both integrated peak intensities and scan-level features, i.e., extracted ion chromatograms (EICs). Probabilistic generative models enable flexible representation in data structure and infer sample-specific pure resources. Scan-level modeling helps alleviate information loss during data preprocessing. We evaluated the capability of the proposed models in capturing mixture proportions of contaminants and cancer profiles on LC-MS based serum proteomic and GC-MS based tissue metabolomic datasets acquired from patients with hepatocellular carcinoma (HCC) and liver cirrhosis as well as synthetic data we generated based on the serum proteomic data. Results: The results we obtained by analysis of the synthetic data demonstrated that both intensity-level and scan-level purification models can accurately infer the mixture proportions and the underlying true cancerous sources with small average error ratios (< 7 %) between estimation and ground truth. By applying the topic model-based purification to mass spectrometric data, we found more proteins and metabolites with significant changes between HCC cases and cirrhotic controls. Candidate biomarkers selected after purification yielded biologically meaningful pathway analysis results and improved disease discrimination power in terms of the area under ROC curve compared to the results found prior to purification. Conclu