Generation and quality control of lipidomics data for the alzheimers disease neuroimaging initiative cohort.

Alzheimers disease (AD) is a major public health priority with a large socioeconomic burden and complex etiology. The Alzheimer Disease Metabolomics Consortium (ADMC) and the Alzheimer Disease Neuroimaging Initiative (ADNI) aim to gain new biological insights in the disease etiology. We report here an untargeted lipidomics of serum specimens of 806 subjects within the ADNI1 cohort (188 AD, 392 mild cognitive impairment and 226 cognitively normal subjects) along with 83 quality control samples. Lipids were detected and measured using an ultra-high-performance liquid chromatography quadruple/time-of-flight mass spectrometry (UHPLC-QTOF MS) instrument operated in both negative and positive electrospray ionization modes. The dataset includes a total 513 unique lipid species out of which 341 are known lipids. For over 95% of the detected lipids, a relative standard deviation of better than 20% was achieved in the quality control samples, indicating high technical reproducibility. Association modeling of this dataset and available clinical, metabolomics and drug-use data will provide novel insights into the AD etiology. These datasets are available at the ADNI repository at http://adni.loni.usc.edu/

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

Comparative Plasma Lipidome between Human and Cynomolgus Monkey: Are Plasma Polar Lipids Good Biomarkers for Diabetic Monkeys?

10.1371/journal.pone.0019731PLoS ONE65

Meibum Lipid Composition in Asians with Dry Eye Disease

10.1371/journal.pone.0024339PLoS ONE610

Side Chain Hydrophobicity Modulates Therapeutic Activity and Membrane Selectivity of Antimicrobial Peptide Mastoparan-X

The discovery of new anti-infective compounds is stagnating and multi-resistant bacteria continue to emerge, threatening to end the "antibiotic era". Antimicrobial peptides (AMPs) and lipo-peptides such as daptomycin offer themselves as a new potential class of antibiotics; however, further optimization is needed if AMPs are to find broad use as antibiotics. In the present work, eight analogues of mastoparan-X (MPX) were investigated, having side chain modifications in position 1, 8 and 14 to modulate peptide hydrophobicity. The self-association properties of the peptides were characterized, and the peptide-membrane interactions in model membranes were compared with the bactericidal and haemolytic properties. Alanine substitution at position 1 and 14 resulted in higher target selectivity (red blood cells versus bacteria), but also decreased bactericidal potency. For these analogues, the gain in target selectivity correlated to biophysical parameters showing an increased effective charge and reduction in the partitioning coefficient for membrane insertion. Introduction of an unnatural amino acid, with an octyl side chain by amino acid substitution, at positions 1, 8 and 14 resulted in increased bactericidal potency at the expense of radically reduced membrane target selectivity. Overall, optimized membrane selectivity or bactericidal potency was achieved by changes in side chain hydrophobicity of MPX. However, enhanced potency was achieved at the expense of selectivity and vice versa in all cases

Plasma lipid biomarker signatures in squamous carcinoma and adenocarcinoma lung cancer patients

There is a clinical need for reliable biomarkers for lung cancer that permit early diagnosis of the disease and provide prediction of histological phenotype. A prospective study design was used with a study population of patients with suspected lung cancer. Blood samples were collected from 17 patients with histologically confirmed squamous cell lung carcinoma, 17 individuals with adenocarcinoma, and 17 control individuals who did not subsequently have a diagnosis of lung cancer or any other cancer. Blood plasma samples were analysed for their lipid profiles using liquid chromatography coupled with high resolution mass spectrometry. Data were analysed using multivariate statistical methods. There was good separation between histological subtypes and control groups and also between individuals with a subsequent diagnosis of adenocarcinoma and squamous cell carcinoma (sensitivity 80 %, specificity 83 %, Q2 = 0.70). Alterations in the levels of different classes of lipids including triglycerides (TGs), phosphatidylinositols (PIs), phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), free fatty acids, lysophospholipids and sphingolipids were observed in squamous carcinoma and adenocarcinoma lung cancer patients when compared with control patients. In conclusion, this study has identified candidate lipid biomarkers of non-small cell lung cancer patients which may be helpful to indicate the tumour subtype and to differentiate them from patients who do not have lung cancer. Measuring these biomarkers has the potential to improve diagnosis in patients with suspected lung cancer and risk stratification in screening

LipidXplorer: A Software for Consensual Cross-Platform Lipidomics

LipidXplorer is the open source software that supports the quantitative characterization of complex lipidomes by interpreting large datasets of shotgun mass spectra. LipidXplorer processes spectra acquired on any type of tandem mass spectrometers; it identifies and quantifies molecular species of any ionizable lipid class by considering any known or assumed molecular fragmentation pathway independently of any resource of reference mass spectra. It also supports any shotgun profiling routine, from high throughput top-down screening for molecular diagnostic and biomarker discovery to the targeted absolute quantification of low abundant lipid species. Full documentation on installation and operation of LipidXplorer, including tutorial, collection of spectra interpretation scripts, FAQ and user forum are available through the wiki site at: https://wiki.mpi-cbg.de/wiki/lipidx/index.php/Main_Page

Lipidomic analysis of plasma samples from women with polycystic ovary syndrome

Abstract Polycystic ovary syndrome (PCOS) is a common disorder affecting between 5 and 18 % of females of reproductive age and can be diagnosed based on a combination of clinical, ultrasound and biochemical features, none of which on its own is diagnostic. A lipidomic approach using liquid chromatography coupled with accurate mass high-resolution mass-spectrometry (LCHRMS) was used to investigate if there were any differences in plasma lipidomic profiles in women with PCOS compared with control women at different stages of menstrual cycle. Plasma samples from 40 women with PCOS and 40 controls aged between 18 and 40 years were analysed in combination with multivariate statistical analyses. Multivariate data analysis (LASSO regression and OPLSDA) of the sample lipidomics datasets showed a weak prediction model for PCOS versus control samples from the follicular and mid-cycle phases of the menstrual cycle, but a stronger model (specificity 85 % and sensitivity 95 %) for PCOS versus the luteal phase menstrual cycle controls. The PCOS vs luteal phase model showed increased levels of plasma triglycerides and sphingomyelins and decreased levels of lysophosphatidylcholines and phosphatidylethanolamines in PCOS women compared with controls. Lipid biomarkers of PCOS were tentatively identified which may be useful in distinguishing PCOS from controls especially when performed during the menstrual cycle luteal phase

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

Synaptic Vesicle Docking: Sphingosine Regulates Syntaxin1 Interaction with Munc18

Consensus exists that lipids must play key functions in synaptic activity but precise mechanistic information is limited. Acid sphingomyelinase knockout mice (ASMko) are a suitable model to address the role of sphingolipids in synaptic regulation as they recapitulate a mental retardation syndrome, Niemann Pick disease type A (NPA), and their neurons have altered levels of sphingomyelin (SM) and its derivatives. Electrophysiological recordings showed that ASMko hippocampi have increased paired-pulse facilitation and post-tetanic potentiation. Consistently, electron microscopy revealed reduced number of docked vesicles. Biochemical analysis of ASMko synaptic membranes unveiled higher amounts of SM and sphingosine (Se) and enhanced interaction of the docking molecules Munc18 and syntaxin1. In vitro reconstitution assays demonstrated that Se changes syntaxin1 conformation enhancing its interaction with Munc18. Moreover, Se reduces vesicle docking in primary neurons and increases paired-pulse facilitation when added to wt hippocampal slices. These data provide with a novel mechanism for synaptic vesicle control by sphingolipids and could explain cognitive deficits of NPA patients