Angewandte Chemie - International Edition
Angewandte Chemie - International Edition
5 years ago

Detection of Localized Hepatocellular Amino Acid Kinetics by using Mass Spectrometry Imaging of Stable Isotopes

Detection of Localized Hepatocellular Amino Acid Kinetics by using Mass Spectrometry Imaging of Stable Isotopes
Benjamin Balluff, Natasja G. Lieuwes, Martijn Arts, Shane R. Ellis, Stijn M. Agten, Keely A. Pierzchalski, Steven W. M. Olde Damink, Zita Soons, Ludwig J. Dubois, Luc J. C. van Loon, Tilman M. Hackeng, Ron M. A. Heeren, Gert B. Eijkel
Mass spectrometry imaging (MSI) simultaneously detects and identifies the spatial distribution of numerous molecules throughout tissues. Currently, MSI is limited to providing a static and ex vivo snapshot of highly dynamic systems in which molecules are constantly synthesized and consumed. Herein, we demonstrate an innovative MSI methodology to study dynamic molecular changes of amino acids within biological tissues by measuring the dilution and conversion of stable isotopes in a mouse model. We evaluate the method specifically on hepatocellular metabolism of the essential amino acid l-phenylalanine, associated with liver diseases. Crucially, the method reveals the localized dynamics of l-phenylalanine metabolism, including its in vivo hydroxylation to l-tyrosine and co-localization with other liver metabolites in a time course of samples from different animals. This method thus enables the dynamics of localized biochemical synthesis to be studied directly from biological tissues. Imaging isotopes: A mass spectrometry imaging method using isotope labeling to study dynamic molecular changes of l-phenylalanine (Phe) in mouse liver tissue was developed. Using this method, hydroxylation of Phe to l-tyrosine (Tyr), as well as its co-localization with other amino acids could be monitored. This study demonstrates the potential to spatially detect local molecular kinetics of amino acids in research and clinical applications.

Publisher URL: http://onlinelibrary.wiley.com/resolve/doi

DOI: 10.1002/anie.201702669

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