SummaryThe citric acid cycle (CAC) metabolite fumarate has been proposed to be cardioprotective; however, its mechanisms of action remain to be determined. To augment cardiac fumarate levels and to assess fumarate's cardioprotective properties, we generated fumarate hydratase (Fh1) cardiac knockout (KO) mice. These fumarate-replete hearts were robustly protected from ischemia-reperfusion injury (I/R). To compensate for the loss of Fh1 activity, KO hearts maintain ATP levels in part by channeling amino acids into the CAC. In addition, by stabilizing the transcriptional regulator Nrf2, Fh1 KO hearts upregulate protective antioxidant response element genes. Supporting the importance of the latter mechanism, clinically relevant doses of dimethylfumarate upregulated Nrf2 and its target genes, hence protecting control hearts, but failed to similarly protect Nrf2-KO hearts in an in vivo model of myocardial infarction. We propose that clinically established fumarate derivatives activate the Nrf2 pathway and are readily testable cytoprotective agents.
Objective. Inflammatory arthritis is associated with systemic manifestations including alterations in metabolism. We used nuclear magnetic resonance (NMR) spectroscopy–based metabolomics to assess metabolic fingerprints in serum from patients with established rheumatoid arthritis (RA) and those with early arthritis.Methods. Serum samples were collected from newly presenting patients with established RA who were naive for disease-modifying antirheumatic drugs, matched healthy controls, and 2 groups of patients with synovitis of ≤3 months' duration whose outcomes were determined at clinical followup. Serum metabolomic profiles were assessed using 1-dimensional 1H-NMR spectroscopy. Discriminating metabolites were identified, and the relationships between metabolomic profiles and clinical variables including outcomes were examined.Results. The serum metabolic fingerprint in established RA was clearly distinct from that of healthy controls. In early arthritis, we were able to stratify the patients according to the level of current inflammation, with C-reactive protein correlating with metabolic differences in 2 separate groups (P < 0.001). Lactate and lipids were important discriminators of inflammatory burden in both early arthritis patient groups. The sensitivities and specificities of models to predict the development of either RA or persistent arthritis in patients with early arthritis were low.Conclusion. The metabolic fingerprint reflects inflammatory disease activity in patients with synovitis, demonstrating that underlying inflammatory processes drive significant changes in metabolism that can be measured in the peripheral blood. The identification of metabolic alterations may provide insights into disease mechanisms operating in patients with inflammatory arthritis.
The 1H chemical shifts of 124 compounds containing a variety of functional groups have been recorded in CDCl3 and DMSO-d6 (henceforth DMSO) solvents. The 1H solvent shift Delta delta = delta(DMSO) - delta(CDCl3) varies from -0.3 to +4.6 ppm. This solvent shift can be accurately predicted (rms error 0.05 ppm) using the charge model of alpha, beta, gamma and long-range contributions. The labile protons of alcohols, acids, amines and amides give both, the largest solvent shifts and the largest errors. The contributions for the various groups are tabulated and it is shown that for H.C.C.X gamma-effects (X = OH, NH, =O, NH.CO) there is a dihedral angle dependence of the gamma-effect. The group contributions are discussed in terms of the possible solvent-solute interactions. For protic hydrogens, hydrogen bonding is the dominant interaction, but for the remaining protons solvent anisotropy and electric field effects appear to be the major factors.
Public databases of NMR spectra of low molecular weight metabolites must be constructed to remove the major bottleneck of metabolite identification and quantification in the analysis of metabolomics data. Two-dimensional (2-D) 1 H J-resolved spectroscopy represents a popular alternative to 1-D NMR methods, resolving the highly overlapped signals characteristic of complex metabolite mixtures across two frequency dimensions. Here we report the design, measurement and curation of, primarily, a database of 2-D J-resolved NMR spectra.Metabolites were selected based upon their importance within metabolic pathways and their detection potential by NMR, and prepared for analysis at pH 6.6, 7.0 and 7.4. Sixteen NMR spectra were recorded for each metabolite using a 500 MHz spectrometer, including 1-D and 2-D J-resolved spectra, different water suppression methods and different acquisition parameters. Some metabolites were removed due to limited solubility, poor NMR signal quality or contamination, and the final dataset comprised of 3328 NMR spectra arising from 208 metabolite standards. These data are housed in a purpose-built MySQL database (Birmingham Metabolite Library; BML-NMR) containing over 100 separate tables and allowing the efficient storage of raw free-induction-decays (FIDs), 1-D and 2-D NMR spectra and associated metadata. The database is compliant with the Metabolomics Standards Initiative (MSI) endorsed reporting requirements, with some necessary amendments. Library data can be accessed freely and searched through a custom written web interface (www.bml-nmr.org). FIDs, NMR spectra and associated metadata can be downloaded according to a newly implemented MSI-compatible XML schema.
It is shown that the difference in the 1H NMR chemical shift of a protic hydrogen in DMSO and CDCl3 solvents is directly related to the overall, or summation, hydrogen bond acidity for a wide range of solutes. This provides a new and direct method of measuring the hydrogen bond acidity. For 54 compounds, the observed shifts for 72 protic hydrogens could be correlated to the Abraham solute hydrogen bond acidity parameter, A, with a correlation coefficient squared, R2, of 0.938 and a standard deviation, SD, of 0.054 units in A. A training equation that used half the data could predict A values for the remaining data with an average error of 0.001 and a standard deviation, SD, of 0.053 units, thus demonstrating the predictive power of the method. Unlike any previous method for the determination of solute hydrogen bond acidities, the NMR method allows the determination of A values for individual protic hydrogens in multifunctional solutes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.