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Metabolites, the small non-polymeric molecules, which are the intermediate or final products of metabolic reactions, have emerged as powerful tools for biomedical research and precision medicine.The term metabolome, introduced in 1998, represents the whole entity of metabolites within a cell, tissue or entire organism.1Since then, metabolomics has gained impressive traction, especially due to its relevance in systems biology or the holistic approach of deciphering the complexity of biological processes. Metabolomics fits perfectly in that concept, with its strategic position downstream of genomics and transcriptomics in the omics cascade and also tightly connected and influenced by the surrounding environmental factors. Often, the metabolome provides insights where genomic profiling fails to explain a given phenotype, and for this, the field is gaining appreciation from a plethora of pathology-related areas, including cancer, diabetes and cardiac disease.2From a technical point of view, metabolite profiling relies on the principles of analytical chemistry. The main methods are mass spectrometry (ms), applied in a targeted or untargeted manner, nuclear magnetic resonance (NMR) and stable isotope labeling for matabolomic flux analysis. Each of these methods has its pros and cons and the choice depends on the study's final goals. 3, 4The diverse nature of the metabolome continually challenges researchers and creates a colorful array of opinions on which is the most comprehensive and precise approach.

"That's kind of the way targeted metabolomics is. You're looking for certain molecules, but you're only looking under the lights. And if it turns out that this is where you've lost your keys, then it works extremely well." Patti says. Nevertheless, the scientist highly appreciates the significance of targeted metabolomics: "Targeted metabolomics is extremely useful in the clinical arena and other areas of biology," but also acknowledges the importance of identifying novel metabolites and making new discoveries. "The advantage of untargeted metabolomics is the potential for discovering molecules or metabolites that are altered in a particular disease state or physiological condition that are not expected."

Patti's lab leverages on identifying new metabolites using untargeted metabolomics and he is no stranger to the obstacles this approach offers and how it differs from the targeted analysis. "When you do untargeted metabolomics, you don't know what you're looking for. The metabolic spaces are pretty ambiguous, and we can't optimize methods in the classical way that you would do in a targeted experiment," he reflects.

Newgard has a clear vision for the future and the potential of his method: "Where I see us going is always to have that strong foundation of targeted and quantitatively reproducible and rigorous profiling, but then link it to what's happening in metabolic pathways, through the ability to do metabolic flux analysis.

Although somewhat divided into their approaches and tools, metabolomics researchers are unified by their vision for a metabolomics-based approach to personalized medicine in the future, and by the common challenges they encounter and recognize. Their collective efforts will undoubtedly pave the way for deciphering the code of metabolomics.References:

1. Oliver S. Systematic functional analysis of the yeast genome. Trends Biotechnol. 1998;16(9):373-378. doi:10.1016/S0167-7799(98)01214-1.

2. Newgard CB. Metabolomics and Metabolic Diseases: Where Do We Stand? Cell Metab. 2017;25(1):43-56. doi:10.1016/j.cmet.2016.09.018.

3. Zamboni N, Saghatelian A, Patti GJ. Defining the Metabolome: Size, Flux, and Regulation. Mol Cell. 2015;58(4):699-706. doi:10.1016/j.molcel.2015.04.021.

4. McGarrah RW, Crown SB, Zhang G-F, Shah SH, Newgard CB. Cardiovascular Metabolomics. Circ Res. 2018;122(9):1238-1258. doi:10.1161/CIRCRESAHA.117.311002.

5. Kraus WE, Muoio DM, Stevens R, et al. Metabolomic Quantitative Trait Loci (mQTL) Mapping Implicates the Ubiquitin Proteasome System in Cardiovascular Disease Pathogenesis. Lusis AJ, ed. PLOS Genet. 2015;11(11):e1005553. doi:10.1371/journal.pgen.1005553.

6. Yao C-H, Wang L, Stancliffe E, et al. Dose-Response Metabolomics To Understand Biochemical Mechanisms and Off-Target Drug Effects with the TOXcms Software. Anal Chem. 2020;92(2):1856-1864. doi:10.1021/acs.analchem.9b03811.

7.Huang X, Chen Y-J, Cho K, Nikolskiy I, Crawford PA, Patti GJ. X 13 CMS: Global Tracking of Isotopic Labels in Untargeted Metabolomics. Anal Chem. 2014;86(3):1632-1639. doi:10.1021/ac403384n.8. Lu D, Mulder H, Zhao P, et al. 13C NMR isotopomer analysis reveals a connection between pyruvate cycling and glucose-stimulated insulin secretion (GSIS). Proc Natl Acad Sci. 2002;99(5):2708-2713. doi:10.1073/pnas.052005699.

9. Warburg O, Wind F, Negelein E. The Metabolism Of Tumors in the body. J Gen Physiol. 1927;8(6):519-530. doi:10.1085/jgp.8.6.519.

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Diverse Opinions to Common Challenges in the Field of Metabolomics - Technology Networks

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