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Integrating ion mobility spectrometry into mass spectrometry-based exposome measurements: what can it add and how far can it go?

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      Abstract

      Measuring the exposome remains a challenge due to the range and number of anthropogenic molecules that are encountered in our daily lives, as well as the complex systemic responses to these exposures. One option for improving the coverage, dynamic range and throughput of measurements is to incorporate ion mobility spectrometry (IMS) into current MS-based analytical methods. The implementation of IMS in exposomics studies will lead to more frequent observations of previously undetected chemicals and metabolites. LC-IMS-MS will provide increased overall measurement dynamic range, resulting in detections of lower abundance molecules. Alternatively, the throughput of IMS-MS alone will provide the opportunity to analyze many thousands of longitudinal samples over lifetimes of exposure, capturing evidence of transitory accumulations of chemicals or metabolites. The volume of data corresponding to these new chemical observations will almost certainly outpace the generation of reference data to enable their confident identification. In this perspective, we briefly review the state-of-the-art in measuring the exposome, and discuss the potential use for IMS-MS and the physico-chemical property of collisional cross section in both exposure assessment and molecular identification.

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          HMDB 3.0—The Human Metabolome Database in 2013

          The Human Metabolome Database (HMDB) (www.hmdb.ca) is a resource dedicated to providing scientists with the most current and comprehensive coverage of the human metabolome. Since its first release in 2007, the HMDB has been used to facilitate research for nearly 1000 published studies in metabolomics, clinical biochemistry and systems biology. The most recent release of HMDB (version 3.0) has been significantly expanded and enhanced over the 2009 release (version 2.0). In particular, the number of annotated metabolite entries has grown from 6500 to more than 40 000 (a 600% increase). This enormous expansion is a result of the inclusion of both ‘detected’ metabolites (those with measured concentrations or experimental confirmation of their existence) and ‘expected’ metabolites (those for which biochemical pathways are known or human intake/exposure is frequent but the compound has yet to be detected in the body). The latest release also has greatly increased the number of metabolites with biofluid or tissue concentration data, the number of compounds with reference spectra and the number of data fields per entry. In addition to this expansion in data quantity, new database visualization tools and new data content have been added or enhanced. These include better spectral viewing tools, more powerful chemical substructure searches, an improved chemical taxonomy and better, more interactive pathway maps. This article describes these enhancements to the HMDB, which was previously featured in the 2009 NAR Database Issue. (Note to referees, HMDB 3.0 will go live on 18 September 2012.).
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            Author and article information

            Affiliations
            [1 ]Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
            [2 ]Eawag, Swiss Federal Institute of Aquatic Science & Technology, Dübendorf, Switzerland
            [3 ]Division of Analytical Chemistry, Department of Chemistry, University of Natural Resources & Life Sciences (BOKU Vienna), Vienna, Austria
            [4 ]Department of Environmental & Molecular Toxicology, Oregon State University, Corvallis, OR, USA
            Author notes
            *Author for correspondence: thomas.metz@ 123456pnnl.gov
            Journal
            Bioanalysis
            Bioanalysis
            BIO
            Bioanalysis
            Future Science Ltd (London, UK )
            1757-6180
            1757-6199
            January 2017
            06 December 2016
            : 9
            : 1
            : 81-98
            27921453 5674211 10.4155/bio-2016-0244
            © 2017 Future Science Ltd

            This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 Unported License

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