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      Guidelines and considerations for the use of system suitability and quality control samples in mass spectrometry assays applied in untargeted clinical metabolomic studies

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          Abstract

          Background

          Quality assurance (QA) and quality control (QC) are two quality management processes that are integral to the success of metabolomics including their application for the acquisition of high quality data in any high-throughput analytical chemistry laboratory. QA defines all the planned and systematic activities implemented before samples are collected, to provide confidence that a subsequent analytical process will fulfil predetermined requirements for quality. QC can be defined as the operational techniques and activities used to measure and report these quality requirements after data acquisition.

          Aim of review

          This tutorial review will guide the reader through the use of system suitability and QC samples, why these samples should be applied and how the quality of data can be reported.

          Key scientific concepts of review

          System suitability samples are applied to assess the operation and lack of contamination of the analytical platform prior to sample analysis. Isotopically-labelled internal standards are applied to assess system stability for each sample analysed. Pooled QC samples are applied to condition the analytical platform, perform intra-study reproducibility measurements (QC) and to correct mathematically for systematic errors. Standard reference materials and long-term reference QC samples are applied for inter-study and inter-laboratory assessment of data.

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          Most cited references34

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          Global metabolic profiling procedures for urine using UPLC-MS.

          The production of 'global' metabolite profiles involves measuring low molecular-weight metabolites (<1 kDa) in complex biofluids/tissues to study perturbations in response to physiological challenges, toxic insults or disease processes. Information-rich analytical platforms, such as mass spectrometry (MS), are needed. Here we describe the application of ultra-performance liquid chromatography-MS (UPLC-MS) to urinary metabolite profiling, including sample preparation, stability/storage and the selection of chromatographic conditions that balance metabolome coverage, chromatographic resolution and throughput. We discuss quality control and metabolite identification, as well as provide details of multivariate data analysis approaches for analyzing such MS data. Using this protocol, the analysis of a sample set in 96-well plate format, would take ca. 30 h, including 1 h for system setup, 1-2 h for sample preparation, 24 h for UPLC-MS analysis and 1-2 h for initial data processing. The use of UPLC-MS for metabolic profiling in this way is not faster than the conventional HPLC-based methods but, because of improved chromatographic performance, provides superior metabolome coverage.
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            Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy.

            The study of biological systems in a holistic manner (systems biology) is increasingly being viewed as a necessity to provide qualitative and quantitative descriptions of the emergent properties of the complete system. Systems biology performs studies focussed on the complex interactions of system components; emphasising the whole system rather than the individual parts. Many perturbations to mammalian systems (diet, disease, drugs) are multi-factorial and the study of small parts of the system is insufficient to understand the complete phenotypic changes induced. Metabolomics is one functional level tool being employed to investigate the complex interactions of metabolites with other metabolites (metabolism) but also the regulatory role metabolites provide through interaction with genes, transcripts and proteins (e.g. allosteric regulation). Technological developments are the driving force behind advances in scientific knowledge. Recent advances in the two analytical platforms of mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy have driven forward the discipline of metabolomics. In this critical review, an introduction to metabolites, metabolomes, metabolomics and the role of MS and NMR spectroscopy will be provided. The applications of metabolomics in mammalian systems biology for the study of the health-disease continuum, drug efficacy and toxicity and dietary effects on mammalian health will be reviewed. The current limitations and future goals of metabolomics in systems biology will also be discussed (374 references).
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              metaX: a flexible and comprehensive software for processing metabolomics data

              Background Non-targeted metabolomics based on mass spectrometry enables high-throughput profiling of the metabolites in a biological sample. The large amount of data generated from mass spectrometry requires intensive computational processing for annotation of mass spectra and identification of metabolites. Computational analysis tools that are fully integrated with multiple functions and are easily operated by users who lack extensive knowledge in programing are needed in this research field. Results We herein developed an R package, metaX, that is capable of end-to-end metabolomics data analysis through a set of interchangeable modules. Specifically, metaX provides several functions, such as peak picking and annotation, data quality assessment, missing value imputation, data normalization, univariate and multivariate statistics, power analysis and sample size estimation, receiver operating characteristic analysis, biomarker selection, pathway annotation, correlation network analysis, and metabolite identification. In addition, metaX offers a web-based interface (http://metax.genomics.cn) for data quality assessment and normalization method evaluation, and it generates an HTML-based report with a visualized interface. The metaX utilities were demonstrated with a published metabolomics dataset on a large scale. The software is available for operation as either a web-based graphical user interface (GUI) or in the form of command line functions. The package and the example reports are available at http://metax.genomics.cn/. Conclusions The pipeline of metaX is platform-independent and is easy to use for analysis of metabolomics data generated from mass spectrometry. Electronic supplementary material The online version of this article (doi:10.1186/s12859-017-1579-y) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                +44 (0)121 4145458 , w.dunn@bham.ac.uk
                Journal
                Metabolomics
                Metabolomics
                Metabolomics
                Springer US (New York )
                1573-3882
                1573-3890
                18 May 2018
                18 May 2018
                2018
                : 14
                : 6
                : 72
                Affiliations
                [1 ]ISNI 0000 0004 0389 4302, GRID grid.1038.a, School of Science, Centre for Integrative Metabolomics and Computational Biology, , Edith Cowan University, ; Joondalup, Perth, Australia
                [2 ]ISNI 0000000121662407, GRID grid.5379.8, School of Chemistry, , Manchester Institute of Biotechnology, University of Manchester, ; Manchester, M1 7DN UK
                [3 ]ISNI 0000 0004 0436 6763, GRID grid.1025.6, Separation Sciences and Metabolomics Laboratory, , Murdoch University, ; Perth, WA Australia
                [4 ]ISNI 0000 0001 0360 9602, GRID grid.84393.35, Neonatal Research Unit, , Health Research Institute La Fe, ; Avda. Fernando Abril Martorell 106, 46026 Valencia, Spain
                [5 ]ISNI 0000 0001 2113 8111, GRID grid.7445.2, Division of Computational and Systems Medicine, Department of Surgery and Cancer, , Imperial College London, ; Sir Alexander Fleming Building, Exhibition Road, South Kensington, London, SW7 2AZ UK
                [6 ]ISNI 0000 0004 1936 7486, GRID grid.6572.6, School of Biosciences, , University of Birmingham, ; Edgbaston, Birmingham, B15 2TT UK
                [7 ]ISNI 0000 0004 1936 7486, GRID grid.6572.6, Phenome Centre Birmingham, , University of Birmingham, ; Edgbaston, Birmingham, B15 2TT UK
                [8 ]ISNI 0000 0004 1936 7486, GRID grid.6572.6, Institute of Metabolism and Systems Research, , University of Birmingham, ; Edgbaston, Birmingham, B15 2TT UK
                Article
                1367
                10.1007/s11306-018-1367-3
                5960010
                29805336
                35a104b9-e326-478f-aecd-92e6d1a80d75
                © The Author(s) 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 4 March 2018
                : 3 May 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: MR/M009157/1
                Categories
                Review Article
                Custom metadata
                © Springer Science+Business Media, LLC, part of Springer Nature 2018

                Molecular biology
                quality assurance (qa),quality control (qc),system suitability samples,pooled qc samples,standard reference materials (srms),long-term reference (ltr) qc samples

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