ArticleAnalytical chemistry2013
Quantitative analysis of metabolic mixtures by two-dimensional 13C constant-time TOCSY NMR spectroscopy.
Article in Analytical chemistry, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed, 55 citations in OpenAlex.
- Quantification of Small Molecule Partitioning in a Biomolecular Condensate with 2D Nuclear Magnetic Resonance Spectroscopy.Chembiochem : a European journal of chemical biology · 2025Article
- Determination of fatty acid uptake and desaturase activity in mammalian cells by NMR-based stable isotope tracing.Analytica chimica acta · 2024Article
- Recent Advances and Perspectives in Relation to the Metabolomics-Based Study of Diabetic Retinopathy.Metabolites · 2023Review
- Machine Learning in Automated Monitoring of Metabolic Changes Accompanying the Differentiation of Adipose-Tissue-Derived Human Mesenchymal Stem Cells EmployingMetabolites · 2023Article
- Quantitative NMR Methods in Metabolomics.Handbook of experimental pharmacology · 2023Article
- Enhanced Nuclear Magnetic Resonance Spectroscopy with Isotropic Mixing as a Pseudodimension.Analytical chemistry · 2022Article
- Rapid quantitativeRSC advances · 2022Article
- The exposome paradigm to predict environmental health in terms of systemic homeostasis and resource balance based on NMR data science.RSC advances · 2021Review
- NMR-Based Metabolomics.Advances in experimental medicine and biology · 2021Article
- Stable Isotopes for Tracing Cardiac Metabolism in Diseases.Frontiers in cardiovascular medicine · 2021Review
- NMR Metabolomics Applied on the Discrimination of Variables Influencing Tomato (Molecules (Basel, Switzerland) · 2020Review
- Assessing the potential of quantitative 2D HSQC NMR inJournal of biomolecular NMR · 2019Article
- Recent Advances in Targeted and Untargeted Metabolomics by NMR and MS/NMR Methods.High-throughput · 2018Review
- Application of kernel principal component analysis and computational machine learning to exploration of metabolites strongly associated with diet.Scientific reports · 2018Article
- Knowns and unknowns in metabolomics identified by multidimensional NMR and hybrid MS/NMR methods.Current opinion in biotechnology · 2017Review
- The future of NMR-based metabolomics.Current opinion in biotechnology · 2017Review
- Increasing rigor in NMR-based metabolomics through validated and open source tools.Current opinion in biotechnology · 2017Review
- Comprehensive Metabolite Identification Strategy Using Multiple Two-Dimensional NMR Spectra of a Complex Mixture Implemented in the COLMARm Web Server.Analytical chemistry · 2016Article
- Review
- 2D-Cosy NMR Spectroscopy as a Quantitative Tool in Biological Matrix: Application to Cyclodextrins.The AAPS journal · 2015Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
An increasing number of organisms can be fully (13)C-labeled, which has the advantage that their metabolomes can be studied by high-resolution two-dimensional (2D) NMR (13)C-(13)C constant-time (CT) total correlation spectroscopy (TOCSY) experiments. Individual metabolites can be identified via database searching or, in the case of novel compounds, through the reconstruction of their backbone-carbon topology. Determination of quantitative metabolite concentrations is another key task. Because strong peak overlaps in one-dimensional (1D) NMR spectra prevent straightforward quantification through 1D peak integrals, we demonstrate here the direct use of (13)C-(13)C CT-TOCSY spectra for metabolite quantification. This is accomplished through the quantum mechanical treatment of the TOCSY magnetization transfer at short and long-mixing times or by the use of analytical approximations, which are solely based on the knowledge of the carbon-backbone topologies. The methods are demonstrated for carbohydrate and amino acid mixtures.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.