NMR metabolomics in genetically engineered mouse models

Metabolomics has become a central approach for elucidating metabolic alterations associated with disease pathogenesis, therapeutic responses, and genetic perturbations. Among the dominant analytical platforms, nuclear magnetic resonance (NMR) spectroscopy is particularly valued for its reproducibility, quantitative accuracy, and minimal sample preparation. These strengths make NMR especially powerful for studies employing genetically engineered mouse models (GEMMs), which remain indispensable for investigating the molecular basis of human disease. This review examines key methodological aspects of NMR metabolomics, including data analysis platforms, the choice of pulse sequences, and strategies to enhance sensitivity and resolution. We summarize applications across major disease areas such as cancer, diabetes, and neurological disorders, with particular emphasis on stable isotope-resolved metabolomics, a powerful approach for dynamic pathway analysis and metabolic flux modeling in intact systems. We also highlight how NMR studies of knockout models have uncovered subtle metabolic perturbations and clarified gene-metabolism relationships. A recurring theme is the evaluation of reproducibility across GEMMs and the challenge of translating metabolic findings from mouse models to human pathophysiology. Finally, we outline current limitations and future directions for advancing the role of NMR metabolomics in preclinical and biomedical research. © 2025 Elsevier B.V., All rights reserved.

Авторы
Aysin Kamil N. 1, 2 , Rudenko Alexander Yu 2 , Mariasina Sofia S. 1, 2, 3 , Polshakov Vladimir I. 1
Язык
Английский
Статус
Опубликовано
Год
2025
Организации
  • 1 Department of Chemistry, Lomonosov Moscow State University, Moscow, Russian Federation
  • 2 Lomonosov Moscow State University, Moscow, Russian Federation
  • 3 Research and Education Resource Center, RUDN University, Moscow, Russian Federation
Ключевые слова
Genetically engineered mouse models (GEMM); Isotope labeling; Model organisms; NMR metabolomics
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