MASS SPECTROMETRY IN METABOLOME ANALYSIS (original) (raw)
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Basics of mass spectrometry based metabolomics
PROTEOMICS, 2014
The emerging field of metabolomics, aiming to characterize small molecule metabolites present in biological systems, promises immense potential for different areas such as medicine, environmental sciences, agronomy, etc. The purpose of this article is to guide the reader through the history of the field, then through the main steps of the metabolomics workflow, from study design to structure elucidation, and help the reader to understand the key phases of a metabolomics investigation and the rationale underlying the protocols and techniques used. This article is not intended to give standard operating procedures as several papers related to this topic were already provided, but is designed as a tutorial aiming to help beginners understand the concept and challenges of MS-based metabolomics. A real case example is taken from the literature to illustrate the application of the metabolomics approach in the field of doping analysis. Challenges and limitations of the approach are then discussed along with future directions in research to cope with these limitations. This tutorial is part of the International Proteomics Tutorial Programme (IPTP18).
Journal of Chromatography B, 2008
The metabolome is characterized by a large number of molecules exhibiting a high diversity of chemical structures and abundances, requiring complementary analytical platforms to reach its extensive coverage. Among them, atmospheric pressure ionization mass spectrometry (API-MS)-based technologies, and especially those using electrospray ionization are now very popular. In this context, this review deals with strengths, limitations and future trends in the identification of signals highlighted by API-MS-based metabolomics. It covers the identification process from the determination of the molecular mass and/or its elemental composition to the confirmation of structural hypotheses. Furthermore, some tools that were developed in order to address the MS signal redundancy and some approaches that could facilitate identification by improving the visualization and organization of complex data sets are also reported and discussed.
Mass spectrometry strategies in metabolomics
The Journal of biological chemistry, 2011
MS has evolved as a critical component in metabolomics, which seeks to answer biological questions through large-scale qualitative and quantitative analyses of the metabolome. MS-based metabolomics techniques offer an excellent combination of sensitivity and selectivity, and they have become an indispensable platform in biology and metabolomics. In this minireview, various MS technologies used in metabolomics are briefly discussed, and future needs are suggested.
The Analyst, 2009
The chemical identification of mass spectrometric signals in metabolomic applications is important to provide conversion of analytical data to biological knowledge about metabolic pathways. The complexity of electrospray mass spectrometric data acquired from a range of samples (serum, urine, yeast intracellular extracts, yeast metabolic footprints, placental tissue metabolic footprints) has been investigated and has defined the frequency of different ion types routinely detected. Although some ion types were expected (protonated and deprotonated peaks, isotope peaks, multiply charged peaks) others were not expected (sodium formate adduct ions). In parallel, the Manchester Metabolomics Database (MMD) has been constructed with data from genome scale metabolic reconstructions, HMDB, KEGG, Lipid Maps, BioCyc and DrugBank to provide knowledge on 42,687 endogenous and exogenous metabolite species. The combination of accurate mass data for a large collection of metabolites, theoretical isotope abundance data and knowledge of the different ion types detected provided a greater number of electrospray mass spectrometric signals which were putatively identified and with greater confidence in the samples studied. To provide definitive identification metabolitespecific mass spectral libraries for UPLC-MS and GC-MS have been constructed for 1,065 commercially available authentic standards. The MMD data are available at http://dbkgroup.org/ MMD/
Nature Methods, 2021
M etabolomics, the large-scale study of the metabolic complement of the cell 1-3 , is a mature science that has been practiced for over 20 years 4. Indeed, it is now a commonly used experimental systems biology tool with demonstrated utility in both fundamental and applied aspects of plant, microbial and mammalian research 5-15. Among the many thousands of studies published in this area over the last 20 years, notable highlights 5-8,10,11,16 are briefly described in Supplementary Note 1. Despite the insight afforded by such studies, the nature of metabolites, particularly their diversity (in both chemical structure and dynamic range of abundance 9,12), remains a major challenge with regard to the ability to provide adequate coverage of the metabolome that can complement that achieved for the genome, transcriptome and proteome. Despite these comparative limitations, enormous advances have been made with regard to the number of analytes about which accurate quantitative information can be acquired, and a vast number of studies have yielded important biological information and biologically active metabolites across the kingdoms of life 14. We have previously estimated that upwards of 1 million different metabolites occur across the tree of life, with between 1,000 and 40,000 estimated to occur in a single species 4 .
Bioinformatics Tools for Mass Spectroscopy-Based Metabolomic Data Processing and Analysis
Current bioinformatics, 2012
Biological systems are increasingly being studied in a holistic manner, using omics approaches, to provide quantitative and qualitative descriptions of the diverse collection of cellular components. Among the omics approaches, metabolomics, which deals with the quantitative global profiling of small molecules or metabolites, is being used extensively to explore the dynamic response of living systems, such as organelles, cells, tissues, organs and whole organisms, under diverse physiological and pathological conditions. This technology is now used routinely in a number of applications, including basic and clinical research, agriculture, microbiology, food science, nutrition, pharmaceutical research, environmental science and the development of biofuels. Of the multiple analytical platforms available to perform such analyses, nuclear magnetic resonance and mass spectrometry have come to dominate, owing to the high resolution and large datasets that can be generated with these techniques. The large multidimensional datasets that result from such studies must be processed and analyzed to render this data meaningful. Thus, bioinformatics tools are essential for the efficient processing of huge datasets, the characterization of the detected signals, and to align multiple datasets and their features. This paper provides a state-of-the-art overview of the data processing tools available, and reviews a collection of recent reports on the topic. Data conversion, pre-processing, alignment, normalization and statistical analysis are introduced, with their advantages and disadvantages, and comparisons are made to guide the reader.
From exogenous to endogenous: the inevitable imprint of mass spectrometry in metabolomics
2007
Mass spectrometry (MS) is an established technology in drug metabolite analysis and is now expanding into endogenous metabolite research. Its utility derives from its wide dynamic range, reproducible quantitative analysis, and the ability to analyze biofluids with extreme molecular complexity. The aims of developing mass spectrometry for metabolomics range from understanding basic biochemistry to biomarker discovery and the structural characterization of physiologically important metabolites. In this review, we will discuss the techniques involved in this exciting area and the current and future applications of this field. . Ultrahigh performance liquid chromatography (UPLC) utilizes columns with smaller particle size packing material (1.4-1.7 µm) than traditional columns and can enhance several aspects of chromatography in a metabolomics context. (1) Separation of metabolites is improved, decreasing ion suppression and in turn improving data interpretability (2) Signal to Noise (S/N) is improved due to narrower peak widths allowing for increased peak capacity and improved accuracy and sensitivity. (3) Sample run time is decreased dramatically allowing for faster sample throughput.
Analytical Chemistry, 2009
A method for the preparation and GC-TOF-MS analysis of human serum samples has been developed and evaluated for application in long-term metabolomic studies. Serum samples were deproteinized using 3:1 methanol/ serum, dried in a vacuum concentrator, and chemically derivatized in a two-stage process. Samples were analyzed by GC-TOF-MS with a 25 min analysis time. In addition, quality control (QC) samples were used to quantify process variability. Optimization of chemical derivatization was performed. Products were found to be stable for 30 h after derivatization. An assessment of within-day repeatability and within-week reproducibility demonstrates that excellent performance is observed with our developed method. Analyses were consistent over a 5 month period. Additional method testing, using spiked serum samples, showed the ability to define metabolite differences between samples from a population and samples spiked with metabolites standards. This methodology allows the continuous acquisition and application of data acquired over many months in long-term metabolomic studies, including the HUSERMET project (http://www.husermet.org/).
Metabolomics, 2009
Mass spectrometry (MS) techniques, because of their sensitivity and selectivity, have become methods of choice to characterize the human metabolome and MSbased metabolomics is increasingly used to characterize the complex metabolic effects of nutrients or foods. However progress is still hampered by many unsolved problems and most notably the lack of well established and standardized methods or procedures, and the difficulties still met in the identification of the metabolites influenced by a given nutritional intervention. The purpose of this paper is to review the main obstacles limiting progress and to make recommendations to overcome them. Propositions are made to improve the mode of collection and preparation of biological samples, the coverage and quality of mass spectrometry analyses, the extraction and exploitation of the raw data, the identification of the metabolites and the biological interpretation of the results.