Metabolite profiling of the carnivorous pitcher plants Darlingtonia and Sarracenia

Sarraceniaceae is a New World carnivorous plant family comprising three genera: Darlingtonia, Heliamphora, and Sarracenia. The plants occur in nutrient-poor environments and have developed insectivorous capability in order to supplement their nutrient uptake. Sarracenia flava contains the alkaloid coniine, otherwise only found in Conium maculatum, in which its biosynthesis has been studied, and several Aloe species. Its ecological role and biosynthetic origin in S. flava is speculative. The aim of the current research was to investigate the occurrence of coniine in Sarracenia and Darlingtonia and to identify common constituents of both genera, unique compounds for individual variants and floral scent chemicals. In this comprehensive metabolic profiling study, we looked for compound patterns that are associated with the taxonomy of Sarracenia species. In total, 57 different Sarracenia and D. californica accessions were used for metabolite content screening by gas chromatography-mass spectrometry. The resulting high-dimensional data were studied using a data mining approach. The two genera are characterized by a large number of metabolites and huge chemical diversity between different species. By applying feature selection for clustering and by integrating new biochemical data with existing phylogenetic data, we were able to demonstrate that the chemical composition of the species can be explained by their known classification. Although transcriptome analysis did not reveal a candidate gene for coniine biosynthesis, the use of a sensitive selected ion monitoring method enabled the detection of coniine in eight Sarracenia species, showing that it is more widespread in this genus than previously believed.Peer reviewe

A simplified procedure for indole alkaloid extraction from Catharanthus roseus combined with a semi-synthetic production process for vinblastine

Peer reviewe

Whole-genome metabolic model of Trichoderma reesei built by comparative reconstruction

Background: Trichoderma reesei is one of the main sources of biomass-hydrolyzing enzymes for the biotechnology industry. There is a need for improving its enzyme production efficiency. The use of metabolic modeling for the simulation and prediction of this organism's metabolism is potentially a valuable tool for improving its capabilities. An accurate metabolic model is needed to perform metabolic modeling analysis. Results: A whole-genome metabolic model of T. reesei has been reconstructed together with metabolic models of 55 related species using the metabolic model reconstruction algorithm CoReCo. The previously published CoReCo method has been improved to obtain better quality models. The main improvements are the creation of a unified database of reactions and compounds and the use of reaction directions as constraints in the gap-filling step of the algorithm. In addition, the biomass composition of T. reesei has been measured experimentally to build and include a specific biomass equation in the model. Conclusions: The improvements presented in this work on the CoReCo pipeline for metabolic model reconstruction resulted in higher-quality metabolic models compared with previous versions. A metabolic model of T. reesei has been created and is publicly available in the BIOMODELS database. The model contains a biomass equation, reaction boundaries and uptake/export reactions which make it ready for simulation. To validate the model, we dem1on-strate that the model is able to predict biomass production accurately and no stoichiometrically infeasible yields are detected. The new T. reesei model is ready to be used for simulations of protein production processes.Peer reviewe

Composition and lipid spatial distribution of HDL particles in subjects with low and high HDL-cholesterol

Peer reviewe

Differences in muscle and adipose tissue gene expression and cardio-metabolic risk factors in the member of physical activity discordant twin pairs

High physical activity/aerobic fitness predicts low morbidity and mortality. Our aim was to identify the most up-regulated gene sets related to long-term physical activity vs. inactivity in skeletal muscle and adipose tissues and to obtain further information about their link with cardio-metabolic risk factors. We studied ten same-sex twin pairs (age range 50-74 years) who had been discordant for leisure-time physical activity for 30 years. The examinations included biopsies from m. vastus lateralis and abdominal subcutaneous adipose tissue. RNA was analyzed with the genome-wide Illumina Human WG-6 v3.0 Expression BeadChip. For pathway analysis we used Gene Set Enrichment Analysis utilizing active vs. inactive co-twin gene expression ratios. Our findings showed that among the physically active members of twin pairs, as compared to their inactive co-twins, gene expression in the muscle tissue samples was chronically up-regulated for the central pathways related to energy metabolism, including oxidative phosphorylation, lipid metabolism and supportive metabolic pathways. Up-regulation of these pathways was associated in particular with aerobic fitness and high HDL cholesterol levels. In fat tissue we found physical activity-associated increases in the expression of polyunsaturated fatty acid metabolism and branched-chain amino acid degradation gene sets both of which associated with decreased 'high-risk' ectopic body fat and plasma glucose levels. Consistent with other findings, plasma lipidomics analysis showed up-regulation of the triacylglycerols containing the polyunsaturated fatty acids. Our findings identified skeletal muscle and fat tissue pathways which are associated with the long-term physical activity and reduced cardio-metabolic disease risk, including increased aerobic fitness. In particular, improved skeletal muscle oxidative energy and lipid metabolism as well as changes in adipocyte function and redistribution of body fat are associated with reduced cardio-metabolic risk.Peer reviewe

Serum Lipidomics Meets Cardiac Magnetic Resonance Imaging: Profiling of Subjects at Risk of Dilated Cardiomyopathy

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Hepatic Stearoyl-CoA Desaturase (SCD)-1 Activity and Diacylglycerol but Not Ceramide Concentrations Are Increased in the Nonalcoholic Human Fatty Liver

OBJECTIVE—To determine whether 1) hepatic ceramide and diacylglycerol concentrations, 2) SCD1 activity, and 3) hepatic lipogenic index are increased in the human nonalcoholic fatty liver

Statistical Analysis of the Processes Controlling Choline and Ethanolamine Glycerophospholipid Molecular Species Composition

The regulation and maintenance of the cellular lipidome through biosynthetic, remodeling, and catabolic mechanisms are critical for biological homeostasis during development, health and disease. These complex mechanisms control the architectures of lipid molecular species, which have diverse yet highly regulated fatty acid chains at both the sn1 and sn2 positions. Phosphatidylcholine (PC) and phosphatidylethanolamine (PE) serve as the predominant biophysical scaffolds in membranes, acting as reservoirs for potent lipid signals and regulating numerous enzymatic processes. Here we report the first rigorous computational dissection of the mechanisms influencing PC and PE molecular architectures from high-throughput shotgun lipidomic data. Using novel statistical approaches, we have analyzed multidimensional mass spectrometry-based shotgun lipidomic data from developmental mouse heart and mature mouse heart, lung, brain, and liver tissues. We show that in PC and PE, sn1 and sn2 positions are largely independent, though for low abundance species regulatory processes may interact with both the sn1 and sn2 chain simultaneously, leading to cooperative effects. Chains with similar biochemical properties appear to be remodeled similarly. We also see that sn2 positions are more regulated than sn1, and that PC exhibits stronger cooperative effects than PE. A key aspect of our work is a novel statistically rigorous approach to determine cooperativity based on a modified Fisher's exact test using Markov Chain Monte Carlo sampling. This computational approach provides a novel tool for developing mechanistic insight into lipidomic regulation

EFSA Panel on Dietetic Products, Nutrition, and Allergies (NDA); Scientific Opinion on Dietary Reference Values for fats, including saturated fatty acids, polyunsaturated fatty acids, monounsaturated fatty acids, trans fatty acids, and cholesterol

This Opinion of the EFSA Panel on Dietetic Products, Nutrition, and Allergies (NDA) deals with the setting of Dietary Reference Values (DRVs) for fats. A lower bound of the reference intake range for total fat of 20 energy % (E%) and an upper bound of 35 E% are proposed. Fat intake in infants can gradually be reduced from 40 E% in the 6-12 month period to 35-40 E% in the 2nd and 3rd year of life. For specific fatty acids the following is proposed: saturated fatty acid (SFA) and trans fatty acid intake should be as low as possible; not to set any DRV for cis-monounsaturated fatty acids; not to formulate a DRV for the intake of total cis-polyunsaturated fatty acids (PUFA); not to set specific values for the n-3/n-6 ratio; to set an Adequate Intake (AI) of 4 E% for linolenic acid; not to set any DRV for arachidonic acid; not to set an UL for total or any of the n-6 PUFA; to set an AI for alpha-linilenic acid (ALA) of 0.5 E%; not to set an UL for ALA; to set an AI of 250 mg for eicosapentaenoic acid (EPA) plus docosahexaenoic acid (DHA) for adults; to set an AI of 100 mg DHA for infants (>6 months) and young children <24 months; to increase by 100-200 mg preformed DHA in addition to the AI for adults as an adequate supply of n-3 long chain PUFA during pregnancy and lactation; not to set any DRV for conjugated linoleic acid. For cholesterol it was decided not to propose a reference value beside the limitation on the intake of SF

Genetic architecture of human plasma lipidome and its link to cardiovascular disease

Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P <5 x10(-8)), 10 of which associate with CVD risk including five new loci-COL5A1, GLTPD2, SPTLC3, MBOAT7 and GALNT16 (false discovery rate<0.05). We identify loci for lipid species that are shown to predict CVD e.g., SPTLC3 for CER(d18:1/24:1). We show that lipoprotein lipase (LPL) may more efficiently hydrolyze medium length triacylglycerides (TAGs) than others. Polyunsaturated lipids have highest heritability and genetic correlations, suggesting considerable genetic regulation at fatty acids levels. We find low genetic correlations between traditional lipids and lipid species. Our results show that lipidomic profiles capture information beyond traditional lipids and identify genetic variants modifying lipid levels and risk of CVD