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A Flexible Tool to Correct Superimposed Mass Isotopologue Distributions in GC-APCI-MS Flux Experiments.
Langenhan, Jennifer; Jaeger, Carsten; Baum, Katharina; Simon, Mareike; Lisec, Jan.
Affiliation
  • Langenhan J; Bundesanstalt für Materialforschung und -Prüfung (BAM), Division 1 Analytical Chemistry, Richard-Willstätter-Straße 11, 12489 Berlin, Germany.
  • Jaeger C; School of Analytical Sciences Adlershof (SALSA), Humboldt-Universität Zu Berlin, Albert-Einstein-Straße 5, 12489 Berlin, Germany.
  • Baum K; Bundesanstalt für Materialforschung und -Prüfung (BAM), Division 1 Analytical Chemistry, Richard-Willstätter-Straße 11, 12489 Berlin, Germany.
  • Simon M; Max-Delbrück-Center for Molecular Medicine (MDC), Mathematical Modeling of Cellular Processes, Robert-Rössle-Straße 10, 13125 Berlin, Germany.
  • Lisec J; Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Prof.-Dr.-Helmert-Straße 2-3, 14482 Potsdam, Germany.
Metabolites ; 12(5)2022 Apr 29.
Article in En | MEDLINE | ID: mdl-35629912
ABSTRACT
The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer-based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Metabolites Year: 2022 Document type: Article Affiliation country: Germany

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Metabolites Year: 2022 Document type: Article Affiliation country: Germany