Dataset Information

High-resolution quantitative metabolome analysis of urine by automated flow injection NMR.

ABSTRACT: Metabolism is essential to understand human health. To characterize human metabolism, a high-resolution read-out of the metabolic status under various physiological conditions, either in health or disease, is needed. Metabolomics offers an unprecedented approach for generating system-specific biochemical definitions of a human phenotype through the capture of a variety of metabolites in a single measurement. The emergence of large cohorts in clinical studies increases the demand of technologies able to analyze a large number of measurements, in an automated fashion, in the most robust way. NMR is an established metabolomics tool for obtaining metabolic phenotypes. Here, we describe the analysis of NMR-based urinary profiles for metabolic studies, challenged to a large human study (3007 samples). This method includes the acquisition of nuclear Overhauser effect spectroscopy one-dimensional and J-resolved two-dimensional (J-Res-2D) (1)H NMR spectra obtained on a 600 MHz spectrometer, equipped with a 120 ?L flow probe, coupled to a flow-injection analysis system, in full automation under the control of a sampler manager. Samples were acquired at a throughput of ~20 (or 40 when J-Res-2D is included) min/sample. The associated technical analysis error over the full series of analysis is 12%, which demonstrates the robustness of the method. With the aim to describe an overall metabolomics workflow, the quantification of 36 metabolites, mainly related to central carbon metabolism and gut microbial host cometabolism, was obtained, as well as multivariate data analysis of the full spectral profiles. The metabolic read-outs generated using our analytical workflow can therefore be considered for further pathway modeling and/or biological interpretation.

SUBMITTER: Da Silva L

PROVIDER: S-EPMC3690541 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

High-resolution quantitative metabolome analysis of urine by automated flow injection NMR.

Da Silva Laeticia L Godejohann Markus M Martin François-Pierre J FP Collino Sebastiano S Bürkle Alexander A Moreno-Villanueva María M Bernhardt Jürgen J Toussaint Olivier O Grubeck-Loebenstein Beatrix B Gonos Efstathios S ES Sikora Ewa E Grune Tilman T Breusing Nicolle N Franceschi Claudio C Hervonen Antti A Spraul Manfred M Moco Sofia S

Analytical chemistry 20130529 12

Metabolism is essential to understand human health. To characterize human metabolism, a high-resolution read-out of the metabolic status under various physiological conditions, either in health or disease, is needed. Metabolomics offers an unprecedented approach for generating system-specific biochemical definitions of a human phenotype through the capture of a variety of metabolites in a single measurement. The emergence of large cohorts in clinical studies increases the demand of technologies ...[more]

PMID: 23718684

Similar Datasets

Project description:A rare viroid disease, Orange Spotting (OS), has been associated with Coconut cadang-cadang viroid variant (named OS-CCCVd) in oil palm. The low concentration of OS-CCCVd in oil palm leaf tissues makes it tedious to obtain high-quality RNA. Various conventional extraction protocols are available for extracting RNA; however, the bottleneck to the methods is the acquisition of good yields of high-quality RNA suitable for use in viroid detection. Studies looking into the automation of magnetic bead extraction systems for viroid detection in oil palm are limited. In this study, we have compared four extraction methods, namely the MagMAX™ mirVana Total RNA isolation kit (Mag-A), MagMAX™ plant RNA isolation kit (Mag-B), modification of MagMAX™ mirVana Total RNA isolation kit (Mag-Mod) and the convention method (NETME buffer). The KingFisher Flex System uses a 96-well plate format for the three automated approaches. The major modification in the Mag-Mod protocol is the inclusion of lithium chloride solution and NETME buffer to the lysis buffer (which enhances RNA recovery) and the reduction in the volume of reagents used per reaction and run conditions, including time. High-quality small RNA was produced as a result of altering the buffers and reagent volume in the Mag-Mod method, which also increased sample productivity (48 samples per day) and detection sensitivity. These effects indirectly decreased the number of technical replicates in a run. Importantly, the alteration permitted the use of ground plant tissue samples with a small sample amount of 0.05- 0.1 g as opposed to the 2-4 grequired with the conventional method. The development of the modified Mag-Mod method using the 96-deep well plate with a magnetic bead system vastly increased our sample throughput, complementing the detection methods (e.g. RT-PCR and HRM-qPCR). Aside from developing an improved extraction method (Mag-Mod method), a novel HRM-qPCR assay successfully differentiated OS-CCCVd variants and identified the presence of OS-CCCVd in samples, obviating the need for Sanger Sequencing.

Project description:Background: Metabolism is essential for cell survival and proliferation. A deep understanding of the metabolic network and its regulatory processes is often vital to understand and overcome disease. Stable isotope tracing of metabolism using nuclear magnetic resonance (NMR) and mass spectrometry (MS) is a powerful tool to derive mechanistic information of metabolic network activity. However, to retrieve meaningful information, automated tools are urgently needed to analyse these complex spectra and eliminate the bias introduced by manual analysis. Here, we present a data-driven algorithm to automatically annotate and analyse NMR signal multiplets in 2D- 1H, 13C-HSQC NMR spectra arising from 13C - 13C scalar couplings. The algorithm minimises the need for user input to guide the analysis of 2D- 1H, 13C-HSQC NMR spectra by performing automated peak picking and multiplet analysis. This enables non-NMR specialists to use this technology. The algorithm has been integrated into the existing MetaboLab software package. Methods: To evaluate the algorithm performance two criteria are tested: is the peak correctly annotated and secondly how confident is the algorithm with its analysis. For the latter a coefficient of determination is introduced. Three datasets were used for testing. The first was to test reproducibility with three biological replicates, the second tested the robustness of the algorithm for different amounts of scaling of the apparent J-coupling constants and the third focused on different sampling amounts. Results: The algorithm annotated overall >90% of NMR signals correctly with average coefficient of determination ρ of 94.06 ± 5.08%, 95.47 ± 7.20% and 80.47 ± 20.98% respectively. Conclusions: Our results indicate that the proposed algorithm accurately identifies and analyses NMR signal multiplets in ultra-high resolution 2D- 1H, 13C-HSQC NMR spectra. It is robust to signal splitting enhancement and up to 25% of non-uniform sampling.

Dataset Information

High-resolution quantitative metabolome analysis of urine by automated flow injection NMR.

Publications

High-resolution quantitative metabolome analysis of urine by automated flow injection NMR.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets