APOC3 is produced mainly by the liver and intestine and approximately half of plasma APOC3 associates with HDL. Though it was believed that APOC3 associates with HDL by simple binding to preexisting particles, recent data support that biogenesis of APOC3-containing HDL (APOC3-HDL) requires Abca1. Moreover, APOC3-HDL contributes to plasma triglyceride homeostasis by preventing APOC3 association with triglyceride-rich lipoproteins. Interestingly, APOC3-HDL also shows positive correlation with the morbidly obese phenotype. However, the roles of APOC3 in HDL functionality and adipose tissue metabolic activity remain unknown. Therefore, here we investigated the direct effects of APOC3 expression on HDL structure and function, as well as white adipose tissue (WAT) and brown adipose tissue (BAT) metabolic activity. C57BL/6 mice were infected with an adenovirus expressing human APOC3 or a recombinant attenuated control adenovirus expressing green fluorescent protein and blood and tissue samples were collected at 5 days postinfection. HDL was then analyzed for its apolipoprotein and lipid composition and particle functionality. Additionally, purified mitochondria from BAT and WAT were analyzed for uncoupling protein 1, cytochrome c (Cytc), and Cytc oxidase subunit 4 protein levels as an indirect measure of their metabolic activity. Serum metabolomic analysis was performed by NMR. Combined, our data show that APOC3 modulates HDL structure and function, while it selectively promotes BAT metabolic activation.

Blood is one of the most used biofluids in metabolomics studies, and the serum and plasma fractions are routinely used as a proxy for blood itself. Here we investigated the association networks of an array of 29 metabolites identified and quantified via NMR in the plasma and serum samples of two cohorts of ∼1000 healthy blood donors each. A second study of 377 individuals was used to extract plasma and serum samples from the same individual on which a set of 122 metabolites were detected and quantified using FIA–MS/MS. Four different inference algorithms (ARANCE, CLR, CORR, and PCLRC) were used to obtain consensus networks. The plasma and serum networks obtained from different studies showed different topological properties with the serum network being more connected than the plasma network. On a global level, metabolite association networks from plasma and serum fractions obtained from the same blood sample of healthy people show similar topologies, and at a local level, some differences arise like in the case of amino acids.

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Surface active agents are characterized for their capacity to adsorb to fluid and solid-water interfaces. They can be classified as surfactants and emulsifiers based on their molecular weight (MW) and properties. Over the years, the chemical surfactant industry has been rapidly increasing to meet consumer demands. Consequently, such a boost has led to the search for more sustainable and biodegradable alternatives, as chemical surfactants are non-biodegradable, thus causing an adverse effect on the environment. To these ends, many microbial and/or marine-derived molecules have been shown to possess various biological properties that could allow manufacturers to make additional health-promoting claims for their products. Our aim, in this review article, is to provide up to date information of critical health-promoting properties of these molecules and their use in blue-based biotechnology (i.e., biotechnology using aquatic organisms) with a focus on food, cosmetic and pharmaceutical/biomedical applications.

Context Inhibitors of sodium-glucose cotransporters-2 have cardio- and renoprotective properties. However, the underlying mechanisms remain indeterminate. Objective To evaluate the effect of dapagliflozin on renal metabolism assessed by urine metabolome analysis in patients with type 2 diabetes. Design Prospective cohort study. Setting Outpatient diabetes clinic of a tertiary academic centre. Patients Eighty patients with HbA1c> 7% on metformin monotherapy were prospectively enrolled. Intervention Fifty patients were treated with dapagliflozin for 3 months. To exclude that the changes observed in urine metabolome were merely the result of the improvement in glycemia, 30 patients treated with insulin degludec were used for comparison. Main Outcome Measure: Changes in urine metabolic profile before and after the administration of dapagliflozin and insulin degludec were assessed by Proton-Nuclear Magnetic Resonance spectroscopy (1H-NMR). Results In multivariate analysis urine metabolome was significantly altered by dapagliflozin (R 2X=0.819, R 2Y=0.627, Q 2Y=0.362, and CV-ANOVA, p<0.001) but not insulin. After dapagliflozin the urine concentrations of ketone bodies, lactate, branched chain amino acids (p<0.001), betaine, myo-inositol (p<0001) and N-Methylhydantoin (p< 0.005) were significantly increased. Additionally, the urine levels of alanine, creatine, sarcosine and citrate were also increased (p<0001, <0.0001 and <0.0005, respectively) whereas anserine decreased (p<0005). Conclusions Dapagliflozin significantly affects urine metabolome in patients with type 2 diabetes in a glucose lowering-independent way. Most of the observed changes can be considered beneficial and may contribute to the renoprotective properties of dapagliflozin.