An untargeted metabolomics approach to contaminant analysis: Pinpointing potential unknown compounds

Lommen, Arjen; Weg, G. van der; Engelen, M.C. van; Bor, Gerrit; Hoogenboom, L.A.P.; Nielen, Michel W. F.

doi:10.1016/j.aca.2006.11.018

Cited by 48 publications

(29 citation statements)

References 25 publications

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“…The data were imported to MetAlign software [25], [26] (Wageningen UR, The Netherlands, available for free at the website http://www.pri.wur.nl/UK/products/MetAlign/) for peak selection and alignment. The peak intensity of each compound was normalized based on the ribitol internal standard.…”

Section: Methodsmentioning

confidence: 99%

Metabolome Analysis of Drosophila melanogaster during Embryogenesis

Yamaguchi

Bamba

et al. 2014

PLoS ONE

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The Drosophila melanogaster embryo has been widely utilized as a model for genetics and developmental biology due to its small size, short generation time, and large brood size. Information on embryonic metabolism during developmental progression is important for further understanding the mechanisms of Drosophila embryogenesis. Therefore, the aim of this study is to assess the changes in embryos’ metabolome that occur at different stages of the Drosophila embryonic development. Time course samples of Drosophila embryos were subjected to GC/MS-based metabolome analysis for profiling of low molecular weight hydrophilic metabolites, including sugars, amino acids, and organic acids. The results showed that the metabolic profiles of Drosophila embryo varied during the course of development and there was a strong correlation between the metabolome and different embryonic stages. Using the metabolome information, we were able to establish a prediction model for developmental stages of embryos starting from their high-resolution quantitative metabolite composition. Among the important metabolites revealed from our model, we suggest that different amino acids appear to play distinct roles in different developmental stages and an appropriate balance in trehalose-glucose ratio is crucial to supply the carbohydrate source for the development of Drosophila embryo.

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Section: Methodsmentioning

confidence: 99%

Metabolome Analysis of Drosophila melanogaster during Embryogenesis

Yamaguchi

Bamba

et al. 2014

PLoS ONE

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“…The headspace samples were concentrated on a Fisons MFA 815 cold trap (CE Instruments, Milan, Italy), followed by separation on a GC-8000 top gas chromatograph (CE Instruments) equipped with a CP-Sil 5 CB low-bleed column (Chrompack, Middelburg, The Netherlands) and detection by a flame ionization detector. The GC data were processed in MetAlign, a tool (developed by Plant Research International, The Netherlands) to align spectra and to identify significant differences between the spectra (6,16).…”

Section: Methodsmentioning

confidence: 99%

Genome-Scale Model of Streptococcus thermophilus LMG18311 for Metabolic Comparison of Lactic Acid Bacteria

Pastink

Teusink

Hols

et al. 2009

Appl Environ Microbiol

118

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In this report, we describe the amino acid metabolism and amino acid dependency of the dairy bacterium Streptococcus thermophilus LMG18311 and compare them with those of two other characterized lactic acid bacteria, Lactococcus lactis and Lactobacillus plantarum. Through the construction of a genome-scale metabolic model of S. thermophilus, the metabolic differences between the three bacteria were visualized by direct projection on a metabolic map. The comparative analysis revealed the minimal amino acid auxotrophy (only histidine and methionine or cysteine) of S. thermophilus LMG18311 and the broad variety of volatiles produced from amino acids compared to the other two bacteria. It also revealed the limited number of pyruvate branches, forcing this strain to use the homofermentative metabolism for growth optimization. In addition, some industrially relevant features could be identified in S. thermophilus, such as the unique pathway for acetaldehyde (yogurt flavor) production and the absence of a complete pentose phosphate pathway.Lactic acid bacteria (LAB) are of great importance in the food industry because of their lactic acid production and their characteristic impact (e.g., texture, flavor) on the final product (19). LAB, as fastidious organisms, require a complex medium (such as milk) and are dependent on their proteolytic system for their supply of essential amino acids (34). Amino acids are not only the building blocks for proteins and peptides, but they also serve as precursors for many other biomolecules (1). Amino acids are also important for the final flavor of a product. Most amino acids do not directly influence the product flavor, but they will contribute indirectly to it because they are precursors of aromatic compounds (36). The conversion of amino acids to flavor compounds is initiated mainly by amino acid transamination, which uses an ␣-keto acid as an amino group acceptor for the aminotransferases (27). The presence (or absence) of the ␣-keto acid either by endogenous production or by addition to the medium is an important factor in flavor formation (13). The ␣-keto acids are decarboxylated into aldehydes, which are the precursors of other flavor compounds such as alcohols, esters, and carboxylic acids (27). A large variation in flavor formation between strains and species is observed. Different studies have reported this biodiversity (25, 27, 32, 33); van Hylckama Vlieg et al. studied, for instance, the difference between dairy and nondairy lactococcal strains, since the latter group has some unique flavor-forming activities (33).Amino acid catabolism and anabolism are complex processes, and thus, metabolic models will be helpful for their understanding. Genome-scale metabolic models provide an overview of all metabolic conversions in an organism based on its genome sequence and make it possible to visualize different metabolic pathways, such as amino acid metabolism. These models can be used to understand the metabolism and can then be applied for a directed study of functionality. For Lac...

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“…The processing of data was performed using MetAlign; a freeware software tool that has been effectively applied to process mass spectrometric data obtained from the quality control of fruits, plant-oil, drinking water, and grass [23,24]. This tool was also applied in the field of metabolomics which aims to develop and apply strategies for the global analysis of metabolites in cells, tissues and fluids [25].…”

Section: Discussionmentioning

confidence: 99%

Automated Signal Processing Applied to Volatile-Based Inspection of Greenhouse Crops

Jansen

Hofstee

Bouwmeester³

et al. 2010

Sensors

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Gas chromatograph–mass spectrometers (GC-MS) have been used and shown utility for volatile-based inspection of greenhouse crops. However, a widely recognized difficulty associated with GC-MS application is the large and complex data generated by this instrument. As a consequence, experienced analysts are often required to process this data in order to determine the concentrations of the volatile organic compounds (VOCs) of interest. Manual processing is time-consuming, labour intensive and may be subject to errors due to fatigue. The objective of this study was to assess whether or not GC-MS data can also be automatically processed in order to determine the concentrations of crop health associated VOCs in a greenhouse. An experimental dataset that consisted of twelve data files was processed both manually and automatically to address this question. Manual processing was based on simple peak integration while the automatic processing relied on the algorithms implemented in the MetAlign™ software package. The results of automatic processing of the experimental dataset resulted in concentrations similar to that after manual processing. These results demonstrate that GC-MS data can be automatically processed in order to accurately determine the concentrations of crop health associated VOCs in a greenhouse. When processing GC-MS data automatically, noise reduction, alignment, baseline correction and normalisation are required.

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An untargeted metabolomics approach to contaminant analysis: Pinpointing potential unknown compounds

Cited by 48 publications

References 25 publications

Metabolome Analysis of Drosophila melanogaster during Embryogenesis

Metabolome Analysis of Drosophila melanogaster during Embryogenesis

Genome-Scale Model of Streptococcus thermophilus LMG18311 for Metabolic Comparison of Lactic Acid Bacteria

Automated Signal Processing Applied to Volatile-Based Inspection of Greenhouse Crops

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