The fraction of activated N-methyl-d-Aspartate receptors during synaptic transmission remains constant in the presence of the glutamate release inhibitor riluzole

Excessive N-methyl-d-aspartate (NMDA) receptor activation is widely accepted to mediate calcium-dependent glutamate excitotoxicity. The uncompetitive, voltage-dependent NMDA receptor antagonist memantine has been successfully used clinically in the treatment of neurodegenerative dementia and is internationally registered for the treatment of moderate to severe Alzheimer′s disease. Glutamate release inhibitors (GRIs) may also be promising for the therapy of some neurodegenerative diseases. During the clinical use of GRIs, it could be questioned whether there would still be a sufficient number of active NMDA receptors to allow any additional effects of memantine or similar NMDA receptor antagonists. To address this question, we determined the fraction of NMDA receptors contributing to postsynaptic events in the presence of therapeutically relevant concentrations of the GRI riluzole (1 μM) using an in vitro hippocampal slice preparation. We measured the charge transfer of pharmacologically isolated excitatory synaptic responses before and after the application of the selective, competitive NMDA receptor antagonist D-AP5 (100 μM). The fraction of activated NMDA receptors under control conditions did not differ from those in the presence of riluzole. It is therefore likely that NMDA receptor antagonists would be able to exert additional therapeutic effects in combination therapy with GRIs

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Impaired neural development in a zebrafish model for Lowe syndrome

Lowe syndrome, which is characterized by defects in the central nervous system, eyes and kidneys, is caused by mutation of the phosphoinositide 5-phosphatase OCRL1. The mechanisms by which loss of OCRL1 leads to the phenotypic manifestations of Lowe syndrome are currently unclear, in part, owing to the lack of an animal model that recapitulates the disease phenotype. Here, we describe a zebrafish model for Lowe syndrome using stable and transient suppression of OCRL1 expression. Deficiency of OCRL1, which is enriched in the brain, leads to neurological defects similar to those reported in Lowe syndrome patients, namely increased susceptibility to heat-induced seizures and cystic brain lesions. In OCRL1-deficient embryos, Akt signalling is reduced and there is both increased apoptosis and reduced proliferation, most strikingly in the neural tissue. Rescue experiments indicate that catalytic activity and binding to the vesicle coat protein clathrin are essential for OCRL1 function in these processes. Our results indicate a novel role for OCRL1 in neural development, and support a model whereby dysregulation of phosphoinositide metabolism and clathrin-mediated membrane traffic leads to the neurological symptoms of Lowe syndrome

Lipidomics: A Tool for Studies of Atherosclerosis

Lipids, abundant constituents of both the vascular plaque and lipoproteins, play a pivotal role in atherosclerosis. Mass spectrometry-based analysis of lipids, called lipidomics, presents a number of opportunities not only for understanding the cellular processes in health and disease but also in enabling personalized medicine. Lipidomics in its most advanced form is able to quantify hundreds of different molecular lipid species with various structural and functional roles. Unraveling this complexity will improve our understanding of diseases such as atherosclerosis at a level of detail not attainable with classical analytical methods. Improved patient selection, biomarkers for gauging treatment efficacy and safety, and translational models will be facilitated by the lipidomic deliverables. Importantly, lipid-based biomarkers and targets should lead the way as we progress toward more specialized therapeutics

Genetics Meets Metabolomics: A Genome-Wide Association Study of Metabolite Profiles in Human Serum

The rapidly evolving field of metabolomics aims at a comprehensive measurement of ideally all endogenous metabolites in a cell or body fluid. It thereby provides a functional readout of the physiological state of the human body. Genetic variants that associate with changes in the homeostasis of key lipids, carbohydrates, or amino acids are not only expected to display much larger effect sizes due to their direct involvement in metabolite conversion modification, but should also provide access to the biochemical context of such variations, in particular when enzyme coding genes are concerned. To test this hypothesis, we conducted what is, to the best of our knowledge, the first GWA study with metabolomics based on the quantitative measurement of 363 metabolites in serum of 284 male participants of the KORA study. We found associations of frequent single nucleotide polymorphisms (SNPs) with considerable differences in the metabolic homeostasis of the human body, explaining up to 12% of the observed variance. Using ratios of certain metabolite concentrations as a proxy for enzymatic activity, up to 28% of the variance can be explained (p-values 10−16 to 10−21). We identified four genetic variants in genes coding for enzymes (FADS1, LIPC, SCAD, MCAD) where the corresponding metabolic phenotype (metabotype) clearly matches the biochemical pathways in which these enzymes are active. Our results suggest that common genetic polymorphisms induce major differentiations in the metabolic make-up of the human population. This may lead to a novel approach to personalized health care based on a combination of genotyping and metabolic characterization. These genetically determined metabotypes may subscribe the risk for a certain medical phenotype, the response to a given drug treatment, or the reaction to a nutritional intervention or environmental challenge

Tissue-Autonomous Function of Drosophila Seipin in Preventing Ectopic Lipid Droplet Formation

Obesity is characterized by accumulation of excess body fat, while lipodystrophy is characterized by loss or absence of body fat. Despite their opposite phenotypes, these two conditions both cause ectopic lipid storage in non-adipose tissues, leading to lipotoxicity, which has health-threatening consequences. The exact mechanisms underlying ectopic lipid storage remain elusive. Here we report the analysis of a Drosophila model of the most severe form of human lipodystrophy, Berardinelli-Seip Congenital Lipodystrophy 2, which is caused by mutations in the BSCL2/Seipin gene. In addition to reduced lipid storage in the fat body, dSeipin mutant flies accumulate ectopic lipid droplets in the salivary gland, a non-adipose tissue. This phenotype was suppressed by expressing dSeipin specifically within the salivary gland. dSeipin mutants display synergistic genetic interactions with lipogenic genes in the formation of ectopic lipid droplets. Our data suggest that dSeipin may participate in phosphatidic acid metabolism and subsequently down-regulate lipogenesis to prevent ectopic lipid droplet formation. In summary, we have demonstrated a tissue-autonomous role of dSeipin in ectopic lipid storage in lipodystrophy

A Role for Phosphatidic Acid in the Formation of “Supersized” Lipid Droplets

Lipid droplets (LDs) are important cellular organelles that govern the storage and turnover of lipids. Little is known about how the size of LDs is controlled, although LDs of diverse sizes have been observed in different tissues and under different (patho)physiological conditions. Recent studies have indicated that the size of LDs may influence adipogenesis, the rate of lipolysis and the oxidation of fatty acids. Here, a genome-wide screen identifies ten yeast mutants producing “supersized” LDs that are up to 50 times the volume of those in wild-type cells. The mutated genes include: FLD1, which encodes a homologue of mammalian seipin; five genes (CDS1, INO2, INO4, CHO2, and OPI3) that are known to regulate phospholipid metabolism; two genes (CKB1 and CKB2) encoding subunits of the casein kinase 2; and two genes (MRPS35 and RTC2) of unknown function. Biochemical and genetic analyses reveal that a common feature of these mutants is an increase in the level of cellular phosphatidic acid (PA). Results from in vivo and in vitro analyses indicate that PA may facilitate the coalescence of contacting LDs, resulting in the formation of “supersized” LDs. In summary, our results provide important insights into how the size of LDs is determined and identify novel gene products that regulate phospholipid metabolism

Flexibility of a Eukaryotic Lipidome – Insights from Yeast Lipidomics

Mass spectrometry-based shotgun lipidomics has enabled the quantitative and comprehensive assessment of cellular lipid compositions. The yeast Saccharomyces cerevisiae has proven to be a particularly valuable experimental system for studying lipid-related cellular processes. Here, by applying our shotgun lipidomics platform, we investigated the influence of a variety of commonly used growth conditions on the yeast lipidome, including glycerophospholipids, triglycerides, ergosterol as well as complex sphingolipids. This extensive dataset allowed for a quantitative description of the intrinsic flexibility of a eukaryotic lipidome, thereby providing new insights into the adjustments of lipid biosynthetic pathways. In addition, we established a baseline for future lipidomic experiments in yeast. Finally, flexibility of lipidomic features is proposed as a new parameter for the description of the physiological state of an organism

The Human Serum Metabolome

Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe