Geschmack ist vorhersagbar: Mit FlavorMiner. FlavorMiner heißt das Tool, das IPB-Chemiker und Partner aus Kolumbien jüngst entwickelt haben. Das Programm kann, basierend auf maschinellem Lernen (KI), anhand der…
Seit Februar 2021 bietet Wolfgang Brandt, ehemaliger Leiter der Arbeitsgruppe Computerchemie am IPB, sein Citizen Science-Projekt zur Pilzbestimmung an. Dafür hat er in regelmäßigen Abständen öffentliche Vorträge zur Vielfalt…
Dunn, W. B.; Erban, A.; Weber, R. J. M.; Creek, D. J.; Brown, M.; Breitling, R.; Hankemeier, T.; Goodacre, R.; Neumann, S.; Kopka, J.; Viant, M. R.;Mass appeal: metabolite identification in mass spectrometry-focused untargeted metabolomicsMetabolomics944-66(2013)DOI: 10.1007/s11306-012-0434-4
Metabolomics has advanced significantly in the past 10 years with important developments related to hardware, software and methodologies and an increasing complexity of applications. In discovery-based investigations, applying untargeted analytical methods, thousands of metabolites can be detected with no or limited prior knowledge of the metabolite composition of samples. In these cases, metabolite identification is required following data acquisition and processing. Currently, the process of metabolite identification in untargeted metabolomic studies is a significant bottleneck in deriving biological knowledge from metabolomic studies. In this review we highlight the different traditional and emerging tools and strategies applied to identify subsets of metabolites detected in untargeted metabolomic studies applying various mass spectrometry platforms. We indicate the workflows which are routinely applied and highlight the current limitations which need to be overcome to provide efficient, accurate and robust identification of metabolites in untargeted metabolomic studies. These workflows apply to the identification of metabolites, for which the structure can be assigned based on entries in databases, and for those which are not yet stored in databases and which require a de novo structure elucidation.
Publikation
Farag, M. A.; Porzel, A.; Schmidt, J.; Wessjohann, L. A.;Metabolite profiling and fingerprinting of commercial cultivars of Humulus lupulus L. (hop): a comparison of MS and NMR methods in metabolomicsMetabolomics8492-507(2012)DOI: 10.1007/s11306-011-0335-y
Hop (Humulus lupulus L. Cannabaceae) is an economically important crop. In addition to its role in beer brewing, its pharmaceutical applications have been of increasing importance in recent years. Bitter acids (prenylated polyketides), prenylflavonoids and essential oils, are the primary phytochemical components that account for hop medicinal value. An integrated approach utilizing nuclear magnetic resonance (NMR) and mass spectrometry (MS) techniques was used for the first large-scale metabolite profiling in Humulus lupulus. Resins and extracts prepared from 13 hop cultivars were analysed using NMR, liquid chromatography (LC)-MS and fourier transform ion cyclotron resonance (FTICR)-MS in parallel and subjected to principal component analysis (PCA). A one pot extraction method, compatible with both MS and NMR measurement was developed to help rule out effects due to differences in extraction protocols. Under optimised conditions, we were able to simultaneously quantify and identify 46 metabolites including 18 bitter acids, 12 flavonoids, 3 terpenes, 3 fatty acids and 2 sugars. Cultivars segregation in PCA plots generated from both LC-MS and NMR data were found comparable and mostly influenced by differences in bitter acids composition among cultivars. FTICR-MS showed inconsistent PCA loading plot results which are likely due to preferential ionisation and also point to the presence of novel isoprenylated metabolites in hop. This comparative metabolomic approach provided new insights for the complementariness and coincidence for these different technology platform applications in hop and similar plant metabolomics projects.