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P-051 Changes in selective lipids during treatment-induced remission of active pediatric IBD V. Brahmbhatt1 *, F.P. Martin2, N. Bosco1, I. Montoliu1, M. Oliveira1, P. Guy1, S. Schatz3, K. Werkstetter3, E. Schiffrin1, B. Koletzko3, J. Benyacoub1, S. Koletzko3. 1Nestle Research Center, Lausanne, Switzerland, 2Nestle Institute of Health Sciences, Lausanne, Switzerland, 3Dr. von Hauner Children’s Hospital, Munich, Germany

The methionine cycle is a key pathway contributing to the regulation of human health, with well-established involvement in cardiovascular diseases and cognitive function. Changes in one-carbon cycle metabolites have also been associated with mild cognitive decline, vascular dementia, and Alzheimer’s disease. Today, there is no single analytical method to monitor both metabolites and co-factors of the methionine cycle. To address this limitation, we here report for the first time a new method for the simultaneous quantitation of 17 metabolites in the methionine cycle, which are homocysteic acid, taurine, serine, cysteine, glycine, homocysteine, riboflavin, methionine, pyridoxine, cystathionine, pyridoxamine, S-adenosylhomocysteine, S-adenosylmethionine, betaine, choline, dimethylglycine, and 5-methyltetrahydrofolic acid. This multianalyte method, developed using ultra-performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS), provides a highly accurate and precise quantitation of these 17 metabolites for both plasma and cerebrospinal fluid metabolite monitoring. The method requires a simple sample preparation, which, combined with a short chromatographic run time, ensures a high sample throughput. This analytical strategy will thus provide a novel metabolomics approach to be employed in large-scale observational and intervention studies. We expect such a robust method to be particularly relevant for broad and deep molecular phenotyping of individuals in relation to their nutritional requirements, health monitoring, and disease risk management. Electronic supplementary material The online version of this article (doi:10.1007/s00216-016-0003-1) contains supplementary material, which is available to authorized users.

Visceral adiposity is increasingly recognized as a key condition for the development of obesity related disorders, with the ratio between visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) reported as the best correlate of cardiometabolic risk. In this study, using a cohort of 40 obese females (age: 25-45 y, BMI: 28-40 kg/m(2)) under healthy clinical conditions and monitored over a 2 weeks period we examined the relationships between different body composition parameters, estimates of visceral adiposity and blood/urine metabolic profiles. Metabonomics and lipidomics analysis of blood plasma and urine were employed in combination with in vivo quantitation of body composition and abdominal fat distribution using iDXA and computerized tomography. Of the various visceral fat estimates, VAT/SAT and VAT/total abdominal fat ratios exhibited significant associations with regio-specific body lean and fat composition. The integration of these visceral fat estimates with metabolic profiles of blood and urine described a distinct amino acid, diacyl and ether phospholipid phenotype in women with higher visceral fat. Metabolites important in predicting visceral fat adiposity as assessed by Random forest analysis highlighted 7 most robust markers, including tyrosine, glutamine, PC-O 44∶6, PC-O 44∶4, PC-O 42∶4, PC-O 40∶4, and PC-O 40∶3 lipid species. Unexpectedly, the visceral fat associated inflammatory profiles were shown to be highly influenced by inter-days and between-subject variations. Nevertheless, the visceral fat associated amino acid and lipid signature is proposed to be further validated for future patient stratification and cardiometabolic health diagnostics.

Summary Lysine acetylation is involved in various biological processes and is considered a key reversible post-translational modification in the regulation of gene expression, enzyme activity, and subcellular localization. This post-translational modification is therefore highly relevant in the context of circadian biology, but its characterization on the proteome-wide scale and its circadian clock dependence are still poorly described. Here, we provide a comprehensive and rhythmic acetylome map of the mouse liver. Rhythmic acetylated proteins showed subcellular localization-specific phases that correlated with the related metabolites in the regulated pathways. Mitochondrial proteins were over-represented among the rhythmically acetylated proteins and were highly correlated with SIRT3-dependent deacetylation. SIRT3 activity being nicotinamide adenine dinucleotide (NAD)+ level-dependent, we show that NAD+ is orchestrated by both feeding rhythms and the circadian clock through the NAD+ salvage pathway but also via the nicotinamide riboside pathway. Hence, the diurnal acetylome relies on a functional circadian clock and affects important diurnal metabolic pathways in the mouse liver., Graphical Abstract, Highlights • Phase of daily acetylated proteins is subcellular localization-dependent • Mitochondrial proteins are over-represented among the rhythmically acetylated proteins • Acetylated mitochondrial protein are enriched in SIRT3 targets • Circadian clock regulates the NAD+-dependent SIRT3 activity through the NR pathway, Mauvoisin et al. provide a rhythmic acetylome map of the mouse liver. Rhythmic acetylated proteins showed subcellular localization-specific phases with an over-representation of SIRT3 targets. Feeding rhythms and the circadian clock regulate NAD+ synthesis through the salvage and nicotinamide riboside pathways, affecting metabolite accumulation.

Summary Nuclear magnetic resonance (NMR)-based metabolomics is widely used to obtain metabolic fingerprints of biological systems. While targeted workflows require previous knowledge of metabolites, prior to statistical analysis, untargeted approaches remain a challenge. Computational tools dealing with fully untargeted NMR-based metabolomics are still scarce or not user-friendly. Therefore, we developed AlpsNMR (Automated spectraL Processing System for NMR), an R package that provides automated and efficient signal processing for untargeted NMR metabolomics. AlpsNMR includes spectra loading, metadata handling, automated outlier detection, spectra alignment and peak-picking, integration and normalization. The resulting output can be used for further statistical analysis. AlpsNMR proved effective in detecting metabolite changes in a test case. The tool allows less experienced users to easily implement this workflow from spectra to a ready-to-use dataset in their routines. Availability and implementation The AlpsNMR R package and tutorial is freely available to download from http://github.com/sipss/AlpsNMR under the MIT license. Supplementary information Supplementary data are available at Bioinformatics online.