Motivation: Labelling experiments in biology usually make use of isotopically enriched substrates, with the two most commonly employed isotopes for metabolism being H-2 and C-13. At the end of the experiment some metabolites will have incorporated the labelling isotope, to a degree that depends on the metabolic turnover. In order to propose a meaningful biological interpretation, it is necessary to estimate the amount of labelling, and one possible route is to exploit the fact that MS isotopic patterns reflect the isotopic distributions. Results: We developed the IsotopicLabelling R package, a tool able to extract and analyze isotopic patterns from liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-MS (GC-MS) data relative to labelling experiments. This package estimates the isotopic abundance of the employed stable isotope (either H-2 or C-13) within a specified list of analytes.
IsotopicLabelling: an R package for the analysis of MS isotopic patterns of labelled analytes
Guella G;
2017
Abstract
Motivation: Labelling experiments in biology usually make use of isotopically enriched substrates, with the two most commonly employed isotopes for metabolism being H-2 and C-13. At the end of the experiment some metabolites will have incorporated the labelling isotope, to a degree that depends on the metabolic turnover. In order to propose a meaningful biological interpretation, it is necessary to estimate the amount of labelling, and one possible route is to exploit the fact that MS isotopic patterns reflect the isotopic distributions. Results: We developed the IsotopicLabelling R package, a tool able to extract and analyze isotopic patterns from liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-MS (GC-MS) data relative to labelling experiments. This package estimates the isotopic abundance of the employed stable isotope (either H-2 or C-13) within a specified list of analytes.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.