Preference for dietary fat induced by release of beta-endorphin in rats

AimsTo determine whether beta-endorphin contributes to the ingestion of and preference for dietary oil, we examined the relationship between the dynamics of beta-endorphin, before and after the ingestion of corn oil, and the intake volume of corn oil.Main methodsRats were offered 5% corn oil for 20 min for 5 consecutive days so they could acquire a preference for corn oil. On day 6, seven groups of rats were presented with the oil for defined time periods, and we measured the beta-endorphin levels in the serum and cerebrospinal fluid (CSF) before and after the presentation of corn oil as well as the consumed volume of corn oil at defined time points.Key findingsBeta-endorphin levels in serum and CSF were significantly increased 15 min after the ingestion of corn oil, followed by a rapid decrease and maintenance at the basal level throughout the rest of the experimental period. The intake of corn oil was the lowest in the time period of 15–30 min, when the beta-endorphin level reached a peak value. The intake volume of corn oil might be inversely correlated with beta-endorphin levels in serum and CSF. The pretreatment of naloxone, an antagonist of the opioid receptor, decreased the initial licking rate for corn oil and increased the latency for corn oil in the licking test.SignificanceThe beta-endorphin was rapidly released after oil ingestion, which contributed to the hedonic preference and ingestive behavior for fat.     

Cytosolic lipid droplets: From mechanisms of fat storage to disease

Abstract

The lipid droplet (LD) is a phylogenetically conserved organelle. In eukaryotes, it is born from the endoplasmic reticulum, but unlike its parent organelle, LDs are the only known cytosolic organelles that are micellar in structure. LDs are implicated in numerous physiological and pathophysiological functions. Many aspects of the LD has captured the attention of diverse scientists alike and has recently led to an explosion in information on the LD biogenesis, expansion and fusion, identification of LD proteomes and diseases associated with LD biology. This review will provide a brief history of this fascinating organelle and provide some contemporary views of unanswered questions in LD biogenesis.     

Brown and beige fat: From molecules to physiology

The recent re-discovery of brown adipose tissue (BAT) and even more recent discovery of the browning of white adipose tissue (WAT) in humans have generated intense scientific interest in the role of adipose tissue as potential target against obesity and its metabolic complications. The purpose of this review is to: i) critically evaluate the current evidence on the physiological significance of BAT and the browning of WAT in metabolic function in humans and ii) discuss factors that have been reported to regulate BAT and/or the browning of WAT in humans. The current literature supports that BAT and the browning of WAT constitute promising emerging targets for interventions aiming to prevent and/or treat of obesity and its metabolic complications. Further research is needed to better understand the physiological significance of BAT and browning of WAT in health and disease along with the factors modulating their metabolic function in humans.     

Brown and beige fat: From molecules to physiology and pathophysiology

The adipose organ portrays adipocytes of diverse tones: white, brown and beige, each type with distinct functions. Adipocytes orchestrate their adaptation and expansion to provide storage to excess nutrients, the quick mobilisation of fuel to supply peripheral functional demands, insulation, and, in their thermogenic form, heat generation to maintain core body temperature. Thermogenic adipocytes could be targets for anti-obesity and anti-diabetic therapeutic approaches aiming to restore adipose tissue functionality and increase energy dissipation. However, for thermogenic adipose tissue to become therapeutically relevant, a better understanding of its development and origins, its progenitors and their characteristics and the composition of its niche, is essential. Also crucial is the identification of stimuli and molecules promoting its specific differentiation and activation. Here we highlight the structural/cellular differences between human and rodent brown adipose tissue and discuss how obesity and metabolic complication affects brown and beige cells as well as how they could be targeted to improve their activation and improve global metabolic homeostasis. Finally, we describe the limitations of current research models and the advantages of new emerging approaches.     

Rumen microbiota and dietary fat: a mutual shaping

Although fat content in usual ruminant diets is very low, fat supplements can be given to farm ruminants to modulate rumen activity or the fatty acid (FA) profile of meat and milk. Unsaturated FAs, which are dominant in common fat sources for ruminants, have negative effects on microbial growth, especially protozoa and fibrolytic bacteria. In turn, the rumen microbiota detoxifies unsaturated FAs (UFAs) through a biohydrogenation (BH) process, transforming dietary UFAs with cis geometrical double‐bonds into mainly trans UFAs and, finally, into saturated FAs. Culture studies have provided a large amount of data regarding bacterial species and strains that are affected by UFAs or involved in lipolysis or BH, with a major focus on the Butyrivibrio genus. More recent data using molecular approaches to rumen microbiota extend and challenge these data, but further research will be necessary to improve our understanding of fat and rumen microbiota interactions.     

Transaldolase: From biochemistry to human disease

The role of the enzyme transaldolase (TAL) in central metabolism, its biochemical properties, structure, and role in human disease is reviewed. The nearly ubiquitous enzyme transaldolase is a part of the pentose phosphate pathway and transfers a dihydroxyacetone group from donor compounds (fructose 6-phosphate or sedoheptulose 7-phosphate) to aldehyde acceptor compounds. The phylogeny of transaldolases shows that five subfamilies can be distinguished, three of them with proven TAL enzyme activity, one with unclear function, and the fifth subfamily comprises transaldolase-related enzymes, the recently discovered fructose 6-phosphate aldolases. The three-dimensional structure of a bacterial (Escherichia coli TAL B) and the human enzyme (TALDO1) has been solved. Based on the 3D-structure and mutagenesis studies, the reaction mechanism was deduced. The cofactor-less enzyme proceeds with a Schiff base intermediate (bound dihydroxyacetone). While a transaldolase deficiency is well tolerated in many microorganisms, it leads to severe symptoms in homozygous TAL-deficient human patients. The involvement of TAL in oxidative stress and apoptosis, in multiple sclerosis, and in cancer is discussed.     

The lipid messenger OEA links dietary fat intake to satiety

The association between fat consumption and obesity underscores the need to identify physiological signals that control fat intake. Previous studies have shown that feeding stimulates small-intestinal mucosal cells to produce the lipid messenger oleoylethanolamide (OEA) which, when administered as a drug, decreases meal frequency by engaging peroxisome proliferator-activated receptors-alpha (PPAR-alpha). Here, we report that duodenal infusion of fat stimulates OEA mobilization in the proximal small intestine, whereas infusion of protein or carbohydrate does not. OEA production utilizes dietary oleic acid as a substrate and is disrupted in mutant mice lacking the membrane fatty-acid transporter CD36. Targeted disruption of CD36 or PPAR-alpha abrogates the satiety response induced by fat. The results suggest that activation of small-intestinal OEA mobilization, enabled by CD36-mediated uptake of dietary oleic acid, serves as a molecular sensor linking fat ingestion to satiety.     

From leaf to label: A robust automated workflow for stomata detection

1. Plant leaf stomata are the gatekeepers of the atmosphere–plant interface and are essential building blocks of land surface models as they control transpiration and photosynthesis. Although more stomatal trait data are needed to significantly reduce the error in these model predictions, recording these traits is time‐consuming, and no standardized protocol is currently available. Some attempts were made to automate stomatal detection from photomicrographs; however, these approaches have the disadvantage of using classic image processing or targeting a narrow taxonomic entity which makes these technologies less robust and generalizable to other plant species. We propose an easy‐to‐use and adaptable workflow from leaf to label. A methodology for automatic stomata detection was developed using deep neural networks according to the state of the art and its applicability demonstrated across the phylogeny of the angiosperms.
2. We used a patch‐based approach for training/tuning three different deep learning architectures. For training, we used 431 micrographs taken from leaf prints made according to the nail polish method from herbarium specimens of 19 species. The best‐performing architecture was tested on 595 images of 16 additional species spread across the angiosperm phylogeny.
3. The nail polish method was successfully applied in 78% of the species sampled here. The VGG19 architecture slightly outperformed the basic shallow and deep architectures, with a confidence threshold equal to 0.7 resulting in an optimal trade‐off between precision and recall. Applying this threshold, the VGG19 architecture obtained an average F‐score of 0.87, 0.89, and 0.67 on the training, validation, and unseen test set, respectively. The average accuracy was very high (94%) for computed stomatal counts on unseen images of species used for training.
4. The leaf‐to‐label pipeline is an easy‐to‐use workflow for researchers of different areas of expertise interested in detecting stomata more efficiently. The described methodology was based on multiple species and well‐established methods so that it can serve as a reference for future work.

     

Alteration of dietary fat intake to prevent weight gain: Jayhawk Observed Eating Trial

Objective: To examine the effects of ad libitum diets with three distinct levels of fat intake for the prevention of weight gain in sedentary, normal‐weight and overweight men and women. Methods and Procedures: Three hundred and five participants were randomized to one of three diets. The diets targeted <25% of energy from fat (low fat (LF)), between 28 and 32% of energy from fat (moderate fat (MF)), or >35% of energy from fat (high fat (HF)). Participants consumed two meals per day on weekdays and one meal per day on weekends in a university cafeteria over a 12‐week period. Energy and nutrient content of cafeteria foods were measured by digital photography. All meals and snacks consumed outside the cafeteria were measured by dietary recall. All analysis of energy and nutrient content was completed using Nutrition Data System for Research (NDS‐R) version 2005. Results: Two hundred and sixty participants completed the study. LF gained 0.1 ± 3.1 kg, MF gained 0.8 ± 2.5 kg, and HF gained 1.0 ± 2.2 kg and there was no gender or age effect. Longitudinal mixed modeling indicated a significant difference among the groups in weight over time (P = 0.0366). When adjusting for total energy intake, which was a significant predictor of weight over time, the global effect for the group was eliminated. Thus, increasing weight was a function of increasing energy but not increasing percentage of fat intake. Discussion: Energy intake, but not percentage of energy from fat, appears responsible for the observed weight gain. LF diets may contribute to weight maintenance and HF diets may promote weight gain due to the influence of fat intake on total energy intake.     

The ddY mouse: a model of postprandial hypertriglyceridemia in response to dietary fat

Postprandial hyperlipidemia (lipemia) is a risk factor for atherosclerosis. However, mouse models of postprandial hyperlipidemia have not been reported. Here, we report that ddY mice display marked postprandial hypertriglyceridemia in response to dietary fat. In ddY mice, the fasting serum total triacylglyceride (TG) concentration was 134 mg/dl, which increased to 571 mg/dl after an intragastric safflower oil load (0.4 ml/mouse). In C57BL/6J mice, these concentrations were 57 and 106 mg/dl, respectively. By lipoprotein analysis, ddY mice showed increases in chylomicron- and VLDL-sized TG fractions (remnants and VLDL) after fat load. In C57BL/6J mice, post-heparin plasma LPL activity after fat load was increased 4.8-fold relative to fasting. However, in ddY mice, the increase of LPL activity after fat load was very small (1.2-fold) and not significant. High fat feeding for 10 weeks led to obesity in ddY mice. A difference in LPL amino acid composition between C57BL/6J and ddY mice was detected but was deemed unlikely to cause hypertriglyceridemia because hypertriglyceridemia was not evident in other strains harboring the ddY-type LPL sequence. These findings indicate that postprandial hypertriglyceridemia in ddY mice is induced by decreased LPL activity after fat load and is associated with obesity induced by a high-fat diet.     

Systems genetics: From GWAS to disease pathways

Most common diseases are complex, involving multiple genetic and environmental factors and their interactions. In the past decade, genome-wide association studies (GWAS) have successfully identified thousands of genetic variants underlying susceptibility to complex diseases. However, the results from these studies often do not provide evidence on how the variants affect downstream pathways and lead to the disease. Therefore, in the post-GWAS era the greatest challenge lies in combining GWAS findings with additional molecular data to functionally characterize the associations. The advances in various ~omics techniques have made it possible to investigate the effect of risk variants on intermediate molecular levels, such as gene expression, methylation, protein abundance or metabolite levels. As disease aetiology is complex, no single molecular analysis is expected to fully unravel the disease mechanism. Multiple molecular levels can interact and also show plasticity in different physiological conditions, cell types and disease stages. There is therefore a great need for new integrative approaches that can combine data from different molecular levels and can help construct the causal inference from genotype to phenotype. Systems genetics is such an approach; it is used to study genetic effects within the larger scope of systems biology by integrating genotype information with various ~omics datasets as well as with environmental and physiological variables. In this review, we describe this approach and discuss how it can help us unravel the molecular mechanisms through which genetic variation causes disease. This article is part of a Special Issue entitled: From Genome to Function.     

From one well to 9000: using high-density streptavidin-coated membranes for kinase detection

The study of kinases and their role in cellular regulation continues to expand as the human genome is sequenced and new kinases are identified as expression products of newly discovered genes. Reagents and assay systems that allow for sensitive, accurate, and high-throughput analysis of both purified kinases as well as crude extracts will enhance the characterization of these important cellular components and will speed the identification of appropriate therapeutic targets and the development of new and more effective treatments.