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      Metabolomics Test Materials for Quality Control: A Study of a Urine Materials Suite

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          Abstract

          There is a lack of experimental reference materials and standards for metabolomics measurements, such as urine, plasma, and other human fluid samples. Reasons include difficulties with supply, distribution, and dissemination of information about the materials. Additionally, there is a long lead time because reference materials need their compositions to be fully characterized with uncertainty, a labor-intensive process for material containing thousands of relevant compounds. Furthermore, data analysis can be hampered by different methods using different software by different vendors. In this work, we propose an alternative implementation of reference materials. Instead of characterizing biological materials based on their composition, we propose using untargeted metabolomic data such as nuclear magnetic resonance (NMR) or gas and liquid chromatography-mass spectrometry (GC-MS and LC-MS) profiles. The profiles are then distributed with the material accompanying the certificate, so that researchers can compare their own metabolomic measurements with the reference profiles. To demonstrate this approach, we conducted an interlaboratory study (ILS) in which seven National Institute of Standards and Technology (NIST) urine Standard Reference Material ®s (SRM ®s) were distributed to participants, who then returned the metabolomic data to us. We then implemented chemometric methods to analyze the data together to estimate the uncertainties in the current measurement techniques. The participants identified similar patterns in the profiles that distinguished the seven samples. Even when the number of spectral features is substantially different between platforms, a collective analysis still shows significant overlap that allows reliable comparison between participants. Our results show that a urine suite such as that used in this ILS could be employed for testing and harmonization among different platforms. A limited quantity of test materials will be made available for researchers who are willing to repeat the protocols presented here and contribute their data.

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          Most cited references21

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          XCMS Online: a web-based platform to process untargeted metabolomic data.

          Recently, interest in untargeted metabolomics has become prevalent in the general scientific community among an increasing number of investigators. The majority of these investigators, however, do not have the bioinformatic expertise that has been required to process metabolomic data by using command-line driven software programs. Here we introduce a novel platform to process untargeted metabolomic data that uses an intuitive graphical interface and does not require installation or technical expertise. This platform, called XCMS Online, is a web-based version of the widely used XCMS software that allows users to easily upload and process liquid chromatography/mass spectrometry data with only a few mouse clicks. XCMS Online provides a solution for the complete untargeted metabolomic workflow including feature detection, retention time correction, alignment, annotation, statistical analysis, and data visualization. Results can be browsed online in an interactive, customizable table showing statistics, chromatograms, and putative METLIN identities for each metabolite. Additionally, all results and images can be downloaded as zip files for offline analysis and publication. XCMS Online is available at https://xcmsonline.scripps.edu.
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            Global metabolic profiling of animal and human tissues via UPLC-MS.

            Obtaining comprehensive, untargeted metabolic profiles for complex solid samples, e.g., animal tissues, requires sample preparation and access to information-rich analytical methodologies such as mass spectrometry (MS). Here we describe a practical two-step process for tissue samples that is based on extraction into 'aqueous' and 'organic' phases for polar and nonpolar metabolites. Separation methods such as ultraperformance liquid chromatography (UPLC) in combination with MS are needed to obtain sufficient resolution to create diagnostic metabolic profiles and identify candidate biomarkers. We provide detailed protocols for sample preparation, chromatographic procedures, multivariate analysis and metabolite identification via tandem MS (MS/MS) techniques and high-resolution MS. By using these optimized approaches, analysis of a set of samples using a 96-well plate format would take ~48 h: 1 h for system setup, 8-10 h for sample preparation, 34 h for UPLC-MS analysis and 2-3 h for preliminary/exploratory data processing, representing a robust method for untargeted metabolic screening of tissue samples.
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              Metabolite profiling of a NIST Standard Reference Material for human plasma (SRM 1950): GC-MS, LC-MS, NMR, and clinical laboratory analyses, libraries, and web-based resources.

              Recent progress in metabolomics and the development of increasingly sensitive analytical techniques have renewed interest in global profiling, i.e., semiquantitative monitoring of all chemical constituents of biological fluids. In this work, we have performed global profiling of NIST SRM 1950, "Metabolites in Human Plasma", using GC-MS, LC-MS, and NMR. Metabolome coverage, difficulties, and reproducibility of the experiments on each platform are discussed. A total of 353 metabolites have been identified in this material. GC-MS provides 65 unique identifications, and most of the identifications from NMR overlap with the LC-MS identifications, except for some small sugars that are not directly found by LC-MS. Also, repeatability and intermediate precision analyses show that the SRM 1950 profiling is reproducible enough to consider this material as a good choice to distinguish between analytical and biological variability. Clinical laboratory data shows that most results are within the reference ranges for each assay. In-house computational tools have been developed or modified for MS data processing and interactive web display. All data and programs are freely available online at http://peptide.nist.gov/ and http://srmd.nist.gov/ .
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                Author and article information

                Journal
                Metabolites
                Metabolites
                metabolites
                Metabolites
                MDPI
                2218-1989
                07 November 2019
                November 2019
                : 9
                : 11
                : 270
                Affiliations
                [1 ]Chemical Sciences Division, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA; danbearden@ 123456metabolomicspartners.com (D.W.B.); wfrocha@ 123456inmetro.gov.br (W.F.C.R.); niksa.blonder@ 123456nist.gov (N.B.); katrice.lippa@ 123456nist.gov (K.A.L.)
                [2 ]Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA; yamil.simon@ 123456nist.gov
                [3 ]National Institute of Metrology, Quality, and Technology—INMETRO, 25250-020 Duque de Caxias, RJ, Brazil
                [4 ]Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR 72079, USA; richard.beger@ 123456fda.hhs.gov (R.D.B.); laura.schnackenberg@ 123456fda.hhs.gov (L.K.S.); jinchun.sun@ 123456fda.hhs.gov (J.S.)
                [5 ]Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA; kym8@ 123456georgetown.edu (K.Y.M.); akc27@ 123456georgetown.edu (A.K.C.)
                [6 ]Departments of Oncology and Biochemistry, Molecular and Cellular Biology, Georgetown University Medical Center, Washington, DC 20057, USA
                [7 ]College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA; haiweigu@ 123456asu.edu
                [8 ]Clinical Toxicology at CIAN Diagnostics, Frederick, MD 21703, USA; rameshmrpk@ 123456gmail.com
                [9 ]Department of Anesthesiology and Pain Medicine, Mitochondria and Metabolism Center, University of Washington, Seattle, WA 98109, USA; ngowda@ 123456uw.edu (G.A.N.G.); draftery@ 123456uw.edu (D.R.)
                Author notes
                [* ]Correspondence: david.sheen@ 123456nist.gov ; Tel.: +1-301-975-2603
                [†]

                Retired.

                Author information
                https://orcid.org/0000-0003-1958-1848
                https://orcid.org/0000-0002-5462-1748
                https://orcid.org/0000-0003-1466-605X
                https://orcid.org/0000-0002-2613-1362
                https://orcid.org/0000-0002-7909-194X
                https://orcid.org/0000-0002-0544-7464
                https://orcid.org/0000-0003-2467-8118
                Article
                metabolites-09-00270
                10.3390/metabo9110270
                6918257
                31703392
                39a98e38-3569-4ab8-bd3d-8389e5e66d06
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 26 August 2019
                : 01 November 2019
                Categories
                Article

                interlaboratory study,nuclear magnetic resonance,chromatography,principal components analysis,reproducibility

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