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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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          Density-functional thermochemistry. III. The role of exact exchange

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            Ab Initio Calculation of Vibrational Absorption and Circular Dichroism Spectra Using Density Functional Force Fields

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              An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database.

              A method to correlate the uninterpreted tandem mass spectra of peptides produced under low energy (10-50 eV) collision conditions with amino acid sequences in the Genpept database has been developed. In this method the protein database is searched to identify linear amino acid sequences within a mass tolerance of ±1 u of the precursor ion molecular weight A cross-correlation function is then used to provide a measurement of similarity between the mass-to-charge ratios for the fragment ions predicted from amino acid sequences obtained from the database and the fragment ions observed in the tandem mass spectrum. In general, a difference greater than 0.1 between the normalized cross-correlation functions of the first- and second-ranked search results indicates a successful match between sequence and spectrum. Searches of species-specific protein databases with tandem mass spectra acquired from peptides obtained from the enzymatically digested total proteins of E. coli and S. cerevisiae cells allowed matching of the spectra to amino acid sequences within proteins of these organisms. The approach described in this manuscript provides a convenient method to interpret tandem mass spectra with known sequences in a protein database.
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                Author and article information

                Journal
                Bioanalysis
                Bioanalysis
                BIO
                Bioanalysis
                Future Science Ltd (London, UK )
                1757-6180
                1757-6199
                January 2017
                06 December 2016
                : 9
                : 1
                : 81-98
                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
                Article
                10.4155/bio-2016-0244
                5674211
                27921453
                © 2017 Future Science Ltd

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

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