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      The Human Urine Metabolome

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          Abstract

          Urine has long been a “favored” biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing the complete set of 2651 confirmed human urine metabolite species, their structures (3079 in total), concentrations, related literature references and links to their known disease associations are freely available at http://www.urinemetabolome.ca.

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          Most cited references74

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          HMDB: a knowledgebase for the human metabolome

          The Human Metabolome Database (HMDB, http://www.hmdb.ca) is a richly annotated resource that is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community. Since its first release in 2007, the HMDB has been used to facilitate the research for nearly 100 published studies in metabolomics, clinical biochemistry and systems biology. The most recent release of HMDB (version 2.0) has been significantly expanded and enhanced over the previous release (version 1.0). In particular, the number of fully annotated metabolite entries has grown from 2180 to more than 6800 (a 300% increase), while the number of metabolites with biofluid or tissue concentration data has grown by a factor of five (from 883 to 4413). Similarly, the number of purified compounds with reference to NMR, LC-MS and GC-MS spectra has more than doubled (from 380 to more than 790 compounds). In addition to this significant expansion in database size, many new database searching tools and new data content has been added or enhanced. These include better algorithms for spectral searching and matching, more powerful chemical substructure searches, faster text searching software, as well as dedicated pathway searching tools and customized, clickable metabolic maps. Changes to the user-interface have also been implemented to accommodate future expansion and to make database navigation much easier. These improvements should make the HMDB much more useful to a much wider community of users.
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            The Universal Protein Resource (UniProt)

            The Universal Protein Resource (UniProt) provides a stable, comprehensive, freely accessible, central resource on protein sequences and functional annotation. The UniProt Consortium is a collaboration between the European Bioinformatics Institute (EBI), the Protein Information Resource (PIR) and the Swiss Institute of Bioinformatics (SIB). The core activities include manual curation of protein sequences assisted by computational analysis, sequence archiving, development of a user-friendly UniProt website, and the provision of additional value-added information through cross-references to other databases. UniProt is comprised of four major components, each optimized for different uses: the UniProt Knowledgebase, the UniProt Reference Clusters, the UniProt Archive and the UniProt Metagenomic and Environmental Sequences database. UniProt is updated and distributed every three weeks, and can be accessed online for searches or download at http://www.uniprot.org.
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              ChEBI: a database and ontology for chemical entities of biological interest

              Chemical Entities of Biological Interest (ChEBI) is a freely available dictionary of molecular entities focused on ‘small’ chemical compounds. The molecular entities in question are either natural products or synthetic products used to intervene in the processes of living organisms. Genome-encoded macromolecules (nucleic acids, proteins and peptides derived from proteins by cleavage) are not as a rule included in ChEBI. In addition to molecular entities, ChEBI contains groups (parts of molecular entities) and classes of entities. ChEBI includes an ontological classification, whereby the relationships between molecular entities or classes of entities and their parents and/or children are specified. ChEBI is available online at http://www.ebi.ac.uk/chebi/
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                4 September 2013
                : 8
                : 9
                : e73076
                Affiliations
                [1 ]Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
                [2 ]Department of Computing Sciences, University of Alberta, Edmonton, Alberta, Canada
                [3 ]Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
                [4 ]BIOCRATES Life Sciences AG, Innsbruck, Austria
                [5 ]National Institute for Nanotechnology, Edmonton, Alberta, Canada
                Mayo Clinic, United States of America
                Author notes

                Competing Interests: Ralf Bogumil and Cornelia Roehring are employed by BIOCRATES Life Sciences AG. This company produces kits for targeted metabolomic analyses. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: SB FA RM RK DSW. Performed the experiments: SB FA RM RK ZTD NP RB CR. Analyzed the data: SB FA RM RK ACG ZTD DSW. Contributed reagents/materials/analysis tools: ACG MRW CK TCB FS PL ZTD JP JH FSY ED RB CR DSW. Wrote the paper: SB FA RM RK TCB FS PL NP DSW.

                Article
                PONE-D-13-23764
                10.1371/journal.pone.0073076
                3762851
                24023812
                849d6081-0bfa-4810-a58b-f33da4f6fd18
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 7 June 2013
                : 9 July 2013
                Page count
                Pages: 28
                Funding
                Funding for this research has been provided by Genome Canada, Genome Alberta, The Canadian Institutes of Health Research, Alberta Innovates BioSolutions, Alberta Innovates Health Solutions, The National Research Council, The National Institute of Nanotechnology. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Biochemistry
                Metabolism
                Carbohydrate Metabolism
                Metabolic Pathways
                Nitrogen Metabolism
                Small Molecules
                Computational Biology
                Biological Data Management
                Text Mining
                Systems Biology
                Chemistry
                Analytical Chemistry
                Chemical Analysis
                Quantitative Analysis
                Chromatography
                Computer Science
                Medicine
                Diagnostic Medicine
                Clinical Laboratory Sciences
                Urology

                Uncategorized
                Uncategorized

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