Goslin is the first grammar-based computational library for the recognition/parsing and normalization of lipid names following the hierarchical lipid shorthand nomenclature. The new version Goslin 2.0 implements the latest nomenclature and adds an additional grammar to recognize systematic IUPAC-IUB fatty acyl names as stored, e.g., in the LIPID MAPS database and is perfectly suited to update lipid names in LIPID MAPS or HMDB databases to the latest nomenclature. Goslin 2.0 is available as a standalone web application with a REST API as well as C++, C#, Java, Python 3, and R libraries. Importantly, it can be easily included in lipidomics tools and scripts providing direct access to translation functions. All implementations are open source.

Styrian pumpkin seed oil is a conditioned green-colored oil renowned for nutty smell and taste. Due to α-linolenic acid (ALA) contents below 1% of total fatty acids and the prospect of nutritional health claims based on its potential oxidation products, we investigated the fate of ALA and product oxylipins in the course of down-stream processing of seeds and in oils. Lipidomic analyses with Lipid Data Analyzer 2.8.1 revealed: Processing did not change (1) main fatty acid composition in the oils, (2) amounts of triacylglycerol species, (3) structures of triacylglycerol molecular species containing ALA. (4) Minor precursor ALA in fresh Styrian and normal pumpkins produced 6 product phytoprostanes in either cultivar, quantitatively more in the latter. (5) In oil samples 7 phytoprostanes and 2 phytofurans were detected. The latter two are specific for their presence in pumpkin seed oils, of note, quantitatively more in conditioned oils than in cold-pressed native oils.

A comprehensive and standardized system to report lipid structures analyzed by MS is essential for the communication and storage of lipidomics data. Herein, an update on both the LIPID MAPS classification system and shorthand notation of lipid structures is presented for lipid categories Fatty Acyls (FA), Glycerolipids (GL), Glycerophospholipids (GP), Sphingolipids (SP), and Sterols (ST). With its major changes, i.e., annotation of ring double bond equivalents and number of oxygens, the updated shorthand notation facilitates reporting of newly delineated oxygenated lipid species as well. For standardized reporting in lipidomics, the hierarchical architecture of shorthand notation reflects the diverse structural resolution powers provided by mass spectrometric assays. Moreover, shorthand notation is expanded beyond mammalian phyla to lipids from plant and yeast phyla. Finally, annotation of atoms is included for the use of stable isotope-labeled compounds in metabolic labeling experiments or as internal standards. This update on lipid classification, nomenclature, and shorthand annotation for lipid mass spectra is considered a standard for lipid data presentation.

We have lost a distinguished biochemist who dedicated his career to the study of phosphatidylinositol signalling in metabolic regulation and to the advancement of lipidomics.

We achieve automated and reliable annotation of lipid species and their molecular structures in high-throughput data from chromatography-coupled tandem mass spectrometry using decision rule sets embedded in Lipid Data Analyzer (LDA; http://genome. tugraz. at/lda2). Using various low-and high-resolution mass spectrometry instruments with several collision energies, we proved the method's platform independence. We propose that the software's reliability, flexibility, and ability to identify novel lipid molecular species may now render current state-of-the-art lipid libraries obsolete.

Numerous areas of chemistry can benefit from the ongoing genomic revolution. Here, we discuss and highlight trends in chemistry in the postgenomic era. The areas of interest include combinatorial approaches in organic chemistry; design and analysis of proteins containing unnatural amino acids; trace element-containing proteins; design and characterization of new enzyme types; applications of postgenomic chemistry in drug design; identification of lipid networks and global characterization of lipid molecular species; development of recombinant and selfproliferating polymers; and applications in food chemistry and bioanalytical chemistry based on new nanoanalytical systems and novel recognition elements.

Numerous areas of chemistry can benefit from the ongoing genomic revolution. Here, we discuss and highlight trends in chemistry in the postgenomic era. The areas of interest include combinatorial approaches in organic chemistry; design and analysis of proteins containing unnatural amino acids; trace element-containing proteins; design and characterization of new enzyme types; applications of postgenomic chemistry in drug design; identification of lipid networks and global characterization of lipid molecular species; development of recombinant and selfproliferating polymers; and applications in food chemistry and bioanalytical chemistry based on new nanoanalytical systems and novel recognition elements.

This comprehensive review critically evaluates whether supposed health benefits propounded upon human consumption of conjugated linoleic acids (CLAs) are clinically proven or not. With a general introduction on the chemistry of CLA, major clinical evidences pertaining to intervention strategies, body composition, cardio-vascular health, immunity, asthma, cancer and diabetes are evaluated. Supposed adverse effects such as oxidative stress, insulin resistance, irritation of intestinal tract and milk fat depression are also examined. It seems that no consistent result was observed even in similar studies conducted at different laboratories, this may be due to variations in age, gender, racial and geographical disparities, coupled with type and dose of CLA supplemented. Thus, supposed promising results reported in mechanistic and pre-clinical studies cannot be extrapolated with humans, mainly due to the lack of inconsistency in analyses, prolonged intervention studies, follow-up studies and international co-ordination of concerted studies. Briefly, clinical evidences accumulated thus far show that CLA is not eliciting significantly promising and consistent health effects so as to uphold it as neither a functional nor a medical food.

Tab. f8 – PCA contributions of whole lipid droplet lipidome from ATGL-study: The columns indicate the affected principal component. The rows contain the lipid species sorted by their discriminative contribution to the separation to the sample groups. Species supporting separation are at the top; contradicting and minor contributions are at the bottom of the tables. In this analysis, we investigated each species for its discriminatory effect between the sample groups.

Lipid droplets are considered to be the hub for storage and metabolism of cellular lipids. In previous work we have phenotyped the lipidome of murine hepatocyte lipid droplets using liquid chromatography-mass spectrometry (UHPLC-MS) plus integrated MS/MS, followed by automatic analysis of the MS data. The organelles were isolated after intervention studies involving nutritional stress (extended feeding of a high fat diet or short term fasting), genetic stress due to knock-out of adipocyte triglyceride lipase, or by combined application of nutritional and genetic stress together (‘super stress’). Lipidomics at the level of lipid species (profiling of lipid classes) and lipid molecular species (structural analysis in parallel) has unraveled clear lipid droplet phenotypes as judged by patterns seen best in triacylglycerol (TG) lipidomes, but also in diacylglycerol and phosphatidylcholine lipidomes. The combined view of these data presented here validates the methods used and provides high quality lipidomic data for further bioinformatic inspections. Examples are given for identification of TG species subsets considered surrogates for whole TG lipidomes.

We showed earlier that nutritional stress like starvation or high-fat diet resulted in phenotypic changes in the lipidomes of hepatocyte lipid droplets (LDs), representative for the pathophysiological status of the mouse model. Here we extend our former study by adding genetic stress due to knockout (KO) of adipocyte triglyceride lipase (ATGL), the rate limiting enzyme in LD lipolysis. An intervention trial for 6 weeks with male wild-type (WT) and ATGL-KO mice was carried out; both genotypes were fed lab chow or were exposed to short-time starvation. Isolated LDs were analyzed by LC-MS/MS. Triacylglycerol, diacylglycerol, and phosphatidylcholine lipidomes, in that order, provided the best phenotypic signatures characteristic for respective stresses applied to the animals. This was evidenced at lipid species level by principal component analysis, calculation of average values for chain-lengths and numbers of double bonds, and by visualization in heat maps. Structural backgrounds for analyses and metabolic relationships were elaborated at lipid molecular species level. Relating our lipidomic data to nonalcoholic fatty liver diseases of nutritional and genetic etiologies with or without accompanying insulin resistance, phenotypic distinction in hepatocyte LDs dependent on insulin status emerged. Taken together, lipidomes of hepatocyte LDs are sensitive responders to nutritional and genetic stress.

There is a need for a standardized, practical annotation for structures of lipid species derived from mass spectrometric approaches; i.e., for high-throughput data obtained from instruments operating in either high- or low-resolution modes. This proposal is based on common, officially accepted terms and builds upon the LIPID MAPS terminology. It aims to add defined levels of information below the LIPID MAPS nomenclature, as detailed chemical structures, including stereochemistry, are usually not automatically provided by mass spectrometric analysis. To this end, rules for lipid species annotation were developed that reflect the structural information derived from the analysis. For example, commonly used head group-specific analysis of glycerophospholipids (GP) by low-resolution instruments is neither capable of differentiating the fatty acids linked to the glycerol backbone nor able to define their bond type (ester, alkyl-, or alk-1-enyl-ether). This and other missing structural information is covered by the proposed shorthand notation presented here. Beyond GPs, we provide shorthand notation for fatty acids/acyls (FA), glycerolipids (GL), sphingolipids (SP), and sterols (ST). In summary, this defined shorthand nomenclature provides a standard methodology for reporting lipid species from mass spectrometric analysis and for constructing databases.

The purpose of this study was to examine the induction profiles (as judged by quantitative reverse transcription polymerase chain reaction (qRT-PCR)) of peroxisome proliferator-activated receptor (PPAR) α, β, Γ subtypes and major PPAR-target genes bearing a functional peroxisome proliferator responsive element (PPRE) in HepG2 cell model upon feeding with cis-9,trans-11-octadecadienoic acid (9-CLA) or trans-10,cis-12-octadecadienoic acid (10-CLA) or their precursor fatty acids (FAs). HepG2 cells were treated with 100 μmol/L 9-CLA or 10-CLA or their precursor FAs, viz., oleic, linoleic, and trans-11-vaccenic acids against bezafibrate control to evaluate the induction/expression profiles of PPAR α, β, Γ subtypes and major PPAR-target genes bearing a functional PPRE, i.e., fatty acid transporter (FAT), glucose transporter-2 (GLUT-2), liver-type FA binding protein (L-FABP), acyl CoA oxidase-1 (ACOX-1), and peroxisomal bifunctional enzyme (PBE) with reference to β-actin as house keeping gene. Of the three housekeeping genes (glyceraldehyde 3-phosphate dehydrogenase (GAPDH), β-actin, and ubiquitin), β-actin was found to be stable. Dimethyl sulfoxide (DMSO), the common solubilizer of agonists, showed a significantly higher induction of genes analyzed. qRT-PCR profiles of CLAs and their precursor FAs clearly showed upregulation of FAT, GLUT-2, and L-FABP (∼0.5–2.0-fold). Compared to 10-CLA, 9-CLA decreased the induction of the FA metabolizing gene ACOX-1 less than did PBE, while 10-CLA decreased the induction of PBE less than did ACOX-1. Both CLAs and precursor FAs upregulated PPRE-bearing genes, but with comparatively less or marginal activation of PPAR subtypes. This indicates that the binding of CLAs and their precursor FAs to PPAR subtypes results in PPAR activation, thereby induction of the target transporter genes coupled with downstream lipid metabolising genes such as ACOX-1 and PBE. To sum up, the expression profiles of these candidate genes showed that CLAs and their precursor FAs are involved in lipid signalling by modulating the PPAR α, β, or Γ subtype for the indirect activation of the PPAR-target genes, which may in turn be responsible for the supposed health effects of CLA, and that care should be taken while calculating the actual fold induction values of candidate genes with reference to housekeeping gene and DMSO as they may impart false positive results.

ABSTRACTThis exhaustive in silico study looks into the molecular interactions of phthalates and their metabolites with human peroxisome proliferator‐activated receptor (hPPAR) and retinoid X receptor (hRXR) α, β and γ subtypes – the nuclear receptor proteins function as transcription factors by regulating the expression of downstream genes. Apart from the much discussed plasticizer bisphenol A, we examined the binding affinities of 15 common diphthalates and their monophthalates, natural (linoleic acid, conjugated linoleic acid) and synthetic (bezafibrate, pioglitazone, GW 50156) ligands with hPPARs. In addition to these phthalates, specific natural (retinoic and phytanic acids) and synthetic (bexarotene, rosiglitazone) ligands were examined with hRXRs. The Maestro, Schrödinger Suite 2012 was used for the molecular docking study. In general, natural ligands of hPPAR showed less binding efficiencies than phthalic acid esters and drugs. The diphthalate di‐iso‐decyl phthalate showed the highest G score (–9.99) with hPPAR (γ), while its monophthalate (mono‐iso‐decyl phthalate) showed a comparatively less G score (–9.56). Though the PPAR modulator GW 50156 showed strong affinity with all hPPAR subtypes, its highest G score (–12.43) was with hPPARβ. Hazardous di(2‐ethylhexyl)phthalate generally showed a greater preference to hRXRs than hPPARs, but its highest G score (–10.87) was with hRXRα; while its monophthalate (Mono(2‐ethylhexyl)phthalate) showed a lesser G score (–8.59). The drug bexarotene showed the highest G score (–13.32) with hRXRβ. Moreover, bisphenol A showed more affinity towards hRXR. Briefly, this study gives an overview on the preference of phthalic acid esters, natural and synthetic ligands on to hPPAR and hRXR subtypes, which would lead to further in vitro mechanistic as well as in vivo preclinical and clinical studies. Copyright © 2013 John Wiley & Sons, Ltd.