Trans-palmitoleic acid reduces adiposity via increased lipolysis in a rodent model of diet-induced obesity.

Obesity is defined as increased adiposity, which leads to metabolic disease. The growth of adipose tissue depends on its capacity to expand through hyperplasia or hypertrophy, in order to buffer energy surplus. Also, during the establishment of obesity, adipose tissue expansion reflects adipose lipid metabolism (lipogenesis and/or lipolysis). It is well known that dietary factors can modify lipid metabolism promoting or preventing the development of metabolic abnormalities that concur with obesity. Trans-palmitoleic acid (TP), a biomarker of dairy consumption, has been associated with reduced adiposity in clinical studies. Thus, we aimed to evaluate the effect of TP over adiposity and lipid metabolism-related genes in a rodent model of diet-induced obesity (DIO). To fulfil this aim, we fed C57BL/6 mice with a Control or a High-Fat diet, added with or without TP (3 g/kg diet), during 11 weeks. Body weight and food intake were monitored, fat pads were weighted, histology of visceral adipose tissue was analysed and lipid metabolism-related gene expression was explored by qPCR. Results show that TP consumption prevented weight gain induced by high-fat diet, reduced visceral adipose tissue weight and adipocyte size, while increasing the expression of lipolytic molecules. In conclusion, we show for the first time that TP influences adipose tissue metabolism, specifically lipolysis, resulting in decreased adiposity and reduced adipocyte size in a DIO mice model.

The Acid/Base Profile of a Large Food Chemical Database.

Molecular acid/base properties have a significant influence on membrane permeation, metabolism, absorption, and affinity for biological targets. In particular, ionizable groups are critical in the strength of target-molecule interactions, pharmacokinetics, and toxicity. In this study, we estimated the acid/base properties of the food chemicals from FooDB, a public compound collection with more than 22,000 compounds. It was found that the food chemicals have 40.9 % of neutral compounds, which is twice as many as that found in approved drugs. The most common functional groups among the acid groups in the food chemicals were phenols (16.1 %), phosphates (17.3 %), and carboxylates (17.3 %) while the single-base-containing compounds were of less interest as they accounted for just 5.5 %. To the best of our knowledge, this is the first systematic acid/base profiling of food chemicals and it is part of a continued effort to profile food chemicals for their broad interest in several areas such as nutrition and the food industry in general.

Analysis of a large food chemical database: chemical space, diversity, and complexity.

Background: Food chemicals are a cornerstone in the food industry. However, its chemical diversity has been explored on a limited basis, for instance, previous analysis of food-related databases were done up to 2,200 molecules. The goal of this work was to quantify the chemical diversity of chemical compounds stored in FooDB, a database with nearly 24,000 food chemicals. Methods: The visual representation of the chemical space of FooDB was done with ChemMaps, a novel approach based on the concept of chemical satellites. The large food chemical database was profiled based on physicochemical properties, molecular complexity and scaffold content. The global diversity of FoodDB was characterized using Consensus Diversity Plots. Results: It was found that compounds in FooDB are very diverse in terms of properties and structure, with a large structural complexity. It was also found that one third of the food chemicals are acyclic molecules and ring-containing molecules are mostly monocyclic, with several scaffolds common to natural products in other databases. Conclusions: To the best of our knowledge, this is the first analysis of the chemical diversity and complexity of FooDB. This study represents a step further to the emerging field of "Food Informatics". Future study should compare directly the chemical structures of the molecules in FooDB with other compound databases, for instance, drug-like databases and natural products collections.