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Development of a GC/Quadrupole-Orbitrap Mass Spectrometer, Part II: New Approaches for Discovery Metabolomics

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      Abstract

      Identification of unknown peaks in gas chromatography/mass spectrometry (GC/MS)-based discovery metabolomics is challenging, and remains necessary to permit discovery of novel or unexpected metabolites that may elucidate disease processes and/or further our understanding of how genotypes relate to phenotypes. Here, we introduce two new technologies and an analytical workflow that can facilitate the identification of unknown peaks. First, we report on a GC/Quadrupole-Orbitrap mass spectrometer that provides high mass accuracy, high resolution, and high sensitivity analyte detection. Second, with an “intelligent” data-dependent algorithm, termed molecular-ion directed acquisition (MIDA), we maximize the information content generated from unsupervised tandem MS (MS/MS) and selected ion monitoring (SIM) by directing the MS to target the ions of greatest information content, that is, the most-intact ionic species. We combine these technologies with 13C- and 15N-metabolic labeling, multiple derivatization and ionization types, and heuristic filtering of candidate elemental compositions to achieve (1) MS/MS spectra of nearly all intact ion species for structural elucidation, (2) knowledge of carbon and nitrogen atom content for every ion in MS and MS/MS spectra, (3) relative quantification between alternatively labeled samples, and (4) unambiguous annotation of elemental composition.

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      Metabolomics--the link between genotypes and phenotypes.

       Oliver Fiehn (2001)
      Metabolites are the end products of cellular regulatory processes, and their levels can be regarded as the ultimate response of biological systems to genetic or environmental changes. In parallel to the terms 'transcriptome' and proteome', the set of metabolites synthesized by a biological system constitute its 'metabolome'. Yet, unlike other functional genomics approaches, the unbiased simultaneous identification and quantification of plant metabolomes has been largely neglected. Until recently, most analyses were restricted to profiling selected classes of compounds, or to fingerprinting metabolic changes without sufficient analytical resolution to determine metabolite levels and identities individually. As a prerequisite for metabolomic analysis, careful consideration of the methods employed for tissue extraction, sample preparation, data acquisition, and data mining must be taken. In this review, the differences among metabolite target analysis, metabolite profiling, and metabolic fingerprinting are clarified, and terms are defined. Current approaches are examined, and potential applications are summarized with a special emphasis on data mining and mathematical modelling of metabolism.
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        Metabolite profiling for plant functional genomics.

        Multiparallel analyses of mRNA and proteins are central to today's functional genomics initiatives. We describe here the use of metabolite profiling as a new tool for a comparative display of gene function. It has the potential not only to provide deeper insight into complex regulatory processes but also to determine phenotype directly. Using gas chromatography/mass spectrometry (GC/MS), we automatically quantified 326 distinct compounds from Arabidopsis thaliana leaf extracts. It was possible to assign a chemical structure to approximately half of these compounds. Comparison of four Arabidopsis genotypes (two homozygous ecotypes and a mutant of each ecotype) showed that each genotype possesses a distinct metabolic profile. Data mining tools such as principal component analysis enabled the assignment of "metabolic phenotypes" using these large data sets. The metabolic phenotypes of the two ecotypes were more divergent than were the metabolic phenotypes of the single-loci mutant and their parental ecotypes. These results demonstrate the use of metabolite profiling as a tool to significantly extend and enhance the power of existing functional genomics approaches.
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          Advances in structure elucidation of small molecules using mass spectrometry

          The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules. Electronic supplementary material The online version of this article (doi:10.1007/s12566-010-0015-9) contains supplementary material, which is available to authorized users.
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            Author and article information

            Affiliations
            Departments of Chemistry and Biomolecular Chemistry, University of Wisconsin−Madison , Madison, Wisconsin 53706, United States
            [§ ]Genome Center of Wisconsin, University of Wisconsin−Madison , Madison, Wisconsin 53706, United States
            Author notes
            [* ]Phone: 608-263-1718. Fax: 608-890-0167. E-mail: jcoon@ 123456chem.wisc.edu .
            Journal
            Anal Chem
            Anal. Chem
            ac
            ancham
            Analytical Chemistry
            American Chemical Society
            0003-2700
            1520-6882
            28 August 2015
            28 August 2014
            21 October 2014
            : 86
            : 20
            : 10044-10051
            25166283
            4204910
            10.1021/ac5014755
            Copyright © 2014 American Chemical Society

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            Funding
            National Institutes of Health, United States
            Categories
            Article
            Custom metadata
            ac5014755
            ac-2014-014755

            Analytical chemistry

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