Untargeted Metabolomics using Ultra-High Performance LC-MS: Applications in Systems Biology
Main Article Content
Abstract
Background: Untargeted metabolomics using ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) enables global, hypothesis-free exploration of metabolic networks, advancing systems biology and complex disease studies. Methodology: The high resolution, sensitivity, and separation efficiency of UHPLC-MS allow identification and quantification of diverse small molecules in multiple biological matrices.
Applications extend to precision medicine, microbiome studies, agriculture, and environmental sciences. Results and Analysis: This approach has been instrumental in biomarker discovery, drug development, and understanding plant–microbe and ecosystem interactions. Challenges include data complexity, unknown compound identification, and multi-omics integration. Advances in machine learning and computational tools have enhanced interpretability and opened real-time dynamic metabolomics for flux monitoring. Conclusion: UHPLC-MS-based untargeted metabolomics is reshaping systems biology, enabling deconvolution of intricate biological processes and supporting future advances in personalized medicine, environmental sustainability, and health research.
Article Details
Section
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This is an Open Access article distributed under the terms of the Attribution-Noncommercial 4.0 International License [CC BY-NC 4.0], which requires that reusers give credit to the creator. It allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, for noncommercial purposes only.