Extending the Scope of 1H NMR-Based Blood Metabolomics for the Analysis of Labile Antioxidants: Reduced and Oxidized Glutathione

A difunctional NMR&CD probe for specific detection and enantiomeric recognition of biothiols in complex mixtures

BACKGROUND

Biothiols are important for numerous cellular processes, such as resisting oxidative stress and protecting cell health. Their abnormal levels and molecular configurations have been associated with various diseases. So, establishing an effective and reliable method for the specific detection and enantiomeric discrimination of diverse biothiols is highly meaningful.

RESULTS

We have developed a new NMR and CD probe using 1,4-dinitroimidazole, specifically targeting the thiol group. This probe allows for the specific detection and enantiomeric recognition of biothiols in complex mixtures. We achieved this by identifying the distinguishable 1H NMR signals of 2nd in imidazole-ring of the resulting 4NI-biothiols in the downfield region at 7-8 ppm and newly discovered induced CD signals within 290-430 nm. Using this probe, the limits of detection of Cys, GSH, and Hcy, the recovery rates, and the concentration of GSH extracted from HEK293T cells were determined by measuring the unique downfield 1H NMR signals. Moreover, Cys, GSH, and Hcy can be discriminated simultaneously in complicated samples at a pH range of 2-3.5. Furthermore, this probe can also be utilized to sense chiral thiol-drugs.

SIGNIFICANCE

This method offers a cost-effective and accurate sensing solution for the specific detection of biothiols in complex mixtures, with stereochemical recognition.

Discovery of Hypoxanthine and Inosine as Robust Biomarkers for Predicting the Preanalytical Quality of Human Plasma and Serum for Metabolomics

In cold human blood, the anomalous dynamics of adenosine triphosphate (ATP) result in the progressive accumulation of adenosine diphosphate (ADP), adenosine monophosphate (AMP), inosine monophosphate (IMP), inosine, and hypoxanthine. While the ATP, ADP, AMP, and IMP are confined to red blood cells (RBCs), inosine and hypoxanthine are excreted into plasma/serum. The plasma/serum levels of inosine and hypoxanthine depend on the temperature of blood and the plasma/serum contact time with the RBCs, and hence they represent robust biomarkers for evaluating the preanalytical quality of plasma/serum. These biomarkers are highly specific since they are generally absent or at very low levels in fresh plasma/serum and are highly sensitive since they are derived from ATP, one of the most abundant metabolites in blood. Further, whether blood was kept at room temperature or on ice could be predicted based on inosine levels. An analysis of >2000 plasma/serum samples processed for metabolomics-centric analyses showed alarmingly high levels of inosine and hypoxanthine. The results highlight the gravity of sample quality challenges with high risk of grossly inaccurate measurements and incorrect study outcomes. The discovery of these robust biomarkers provides new ways to address the longstanding and underappreciated preanalytical sample quality challenges in the blood metabolomics field.

Synergism Variation between intracellular Glutathione, phycocyanin and SOD in microalgae by carbon quantum dot fluorescence

Based on the use of CQDs as fluorescent probe and covalent coupling method to detect biological molecules with amino groups, to deeply analysis and detect the metabolism of Microcystis aeruginosa. The metabolic changes of carboxyl biomolecules in Microcystis aeruginosa were analyzed by covalent coupling method, including GSH, phycocyanin and SOD enzyme. The changes of GSH content and its correlation between phycocyanin, SOD were analyzed. The content of phycocyanin and SOD reached the maximum on the 65th day, and GSH was more sensitive to the growth and metabolism of microalgae. GSH plays an important role in reducing the external oxidative damage of microalgae cells. The synthesis of glutathione (GSH), GSH/GSSG mutual transformation, the production of phytochelating peptide (PC), the ASA-GSH cycle, and other physiological processes are interconnected. These interactions are crucial for preserving the antioxidant properties of microalgae and regulating redox-sensitive signal transduction.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Labile Metabolite Profiling in Human Blood Using Phosphorus NMR Spectroscopy

Phosphorus metabolites occupy a unique place in cellular function as critical intermediates and products of cellular metabolism. Human blood is the most widely used biospecimen in the clinic and in the metabolomics field, and hence an ability to profile phosphorus metabolites in blood, quantitatively, would benefit a wide variety of investigations of cellular functions in health and diseases. Mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy are the two premier analytical platforms used in the metabolomics field. However, detection and quantitation of phosphorus metabolites by MS can be challenging due to their lability, high polarity, structural isomerism, and interaction with chromatographic columns. The conventionally used 1H NMR, on the other hand, suffers from poor resolution of these compounds. As a remedy, 31P NMR promises an important alternative to both MS and 1H NMR. However, numerous challenges including the instability of phosphorus metabolites, their chemical shift sensitivity to solvent composition, pH, salt, and temperature, and the lack of identified metabolites have so far restricted the scope of 31P NMR. In the current study, we describe a method to analyze nearly 25 phosphorus metabolites in blood using a simple one-dimensional (1D) NMR spectrum. Establishment of the identity of unknown metabolites involved a combination of (a) comprehensively analyzing an array of 1D and two-dimensional (2D) 1H/31P homonuclear and heteronuclear NMR spectra of blood; (b) mapping the central carbon metabolic pathway; (c) developing and using 1H and 31P spectral and chemical shift databases; and finally (d) confirming the putative metabolite peaks with spiking using authentic compounds. The resulting simple 1D 31P NMR-based method offers an ability to visualize and quantify the levels of intermediates and products of multiple metabolic pathways, including central carbon metabolism, in one step. Overall, the findings represent a new dimension for blood metabolite analysis and are anticipated to greatly impact the blood metabolomics field.

Anomalous Dynamics of Labile Metabolites in Cold Human Blood Detected Using 1H NMR Spectroscopy

Recent efforts in our laboratory have enabled access to an unprecedented number (∼90) of quantifiable metabolites in human blood by a simple nuclear magnetic resonance (NMR) spectroscopy method, which includes energy coenzymes, redox coenzymes, and antioxidants that are fundamental to cellular functions [ J. Magn. Reson. Open 2022, 12-13, 100082]. The coenzymes and antioxidants, however, are notoriously labile and are extremely sensitive to specimen harvesting, extraction, and measurement conditions. This problem is largely underappreciated and carries the risk of grossly inaccurate measurements and incorrect study outcomes. As a part of addressing this challenge, in this study, human blood specimens were comprehensively and quantitatively investigated using 1H NMR spectroscopy. Freshly drawn human blood specimens were treated or not treated with methanol, ethanol, or a mixture of methanol and chloroform, and stored on ice or on bench, at room temperature for different time periods from 0 to 24 h, prior to storing at -80 °C. Interestingly, the labile metabolite levels were stable in blood treated with an organic solvent. However, their levels in blood in untreated samples increased or decreased by factors of up to 5 or more within 3 h. Further, surprisingly, and contrary to the current knowledge about metabolite stability, the variation of coenzyme levels was more dramatic in blood stored on ice than on bench, at room temperature. In addition, unlike the generally observed phenomenon of oxidation of redox coenzymes, reduction was observed in untreated blood. Such preanalytical dynamics of the labile metabolites potentially arises from the active cellular metabolism. From the metabolomics perspective, the massive variation of the labile metabolite levels even in blood stored on ice is alarming and stresses the critical need to immediately quench the cellular metabolism for reliable analyses. Overall, the results provide compelling evidence that warrants a paradigm shift in the sample collection protocol for blood metabolomics involving labile metabolites.

Whole Body Distribution of Labile Coenzymes and Antioxidants in a Mouse Model as Visualized Using 1H NMR Spectroscopy

Coenzyme A, acetyl coenzyme A, coenzymes of cellular energy, coenzymes of redox reactions, and antioxidants mediate biochemical reactions fundamental to the functioning of all living cells. There is an immense interest in measuring them routinely in biological specimens to gain insights into their roles in cellular functions and to help characterize the biological status. However, it is challenging to measure them ex vivo as they are sensitive to specimen harvesting, extraction, and measurement conditions. This challenge is largely underappreciated and carries the risk of grossly inaccurate measurements that lead to incorrect inferences. To date, several efforts have been focused on alleviating this challenge using NMR spectroscopy. However, a comprehensive solution for the measurement of the compounds in a wide variety of biological specimens is still lacking. As a part of addressing this challenge, we demonstrate here that the total pool of each group of unstable metabolites offers a starting place for the representation of labile metabolites in biological specimens. Based on this approach, in this proof-of-concept study, we determine the distribution of the labile compounds in different organs including heart, kidney, liver, brain, and skeletal muscle of a mouse model. The results were independently validated using different specimens and a different metabolite extraction protocol. Further, we show that both stable and unstable metabolites were distributed differentially in different organs, which signifies their differential functional roles, the knowledge of which is currently lacking for many metabolites. Intriguingly, the concentration of taurine, an amino sulfonic acid, in skeletal muscle is >30 mM, which is the highest for any metabolite in a mammalian tissue known to date. To the best of our knowledge, this is the first study to profile the whole body distribution of the labile and other high-concentration metabolites using NMR spectroscopy. The results may pave ways for gaining new insights into cellular functions in health and diseases.

A new limit for blood metabolite analysis using 1H NMR spectroscopy

Human blood is the most widely used biospecimen in the clinic and the metabolomics field. While both mass spectrometry and NMR spectroscopy are the two premier analytical platforms in the metabolomics field, NMR exhibits several unsurpassed characteristics for blood metabolite analysis, the most important of which are its ability to identify unknown metabolites and its quantitative nature. However, the relatively small number of metabolites accessible by NMR has restricted the scope of its applications. Enhancing the limit of identified metabolites in blood will therefore greatly impact NMR-based metabolomics. Continuing our efforts to address this major issue, our current study describes the identification of 12 metabolites, which expands the number of quantifiable blood metabolites by ~15%. These results, in combination with our earlier efforts, now provide access to nearly 90 metabolites, which is the highest to date for a simple 1D 1H NMR experiment that is widely used in the metabolomics field. Metabolites were identified based on the comprehensive investigation of human blood and plasma using 1D/2D NMR techniques. The newly identified metabolites were validated based on chemical shift databases, spectra of authentic compounds obtained under conditions identical to blood/plasma, and, finally, spiking experiments using authentic compounds. Considering the high reproducibility of NMR and the sensitivity of chemical shifts to altered sample conditions, experimental protocols and peak annotations are provided for the newly identified metabolites, which serve as a template for identification of blood metabolites for routine applications. Separately, the identified metabolites were evaluated for their sensitivity to preanalytical conditions. The results reveal that among the newly identified metabolites, inosine monophosphate (IMP) and nicotinamide are associated with labile coenzymes and their levels are sensitive to preanalytical conditions. The study demonstrates the expansion of quantifiable blood metabolites using NMR to a new height and is expected to greatly impact blood metabolomics.

NMR-based isotope editing, chemoselection and isotopomer distribution analysis in stable isotope resolved metabolomics

NMR is a very powerful tool for identifying and quantifying compounds within complex mixtures without the need for individual standards or chromatographic separation. Stable Isotope Resolved Metabolomics (or SIRM) is an approach to following the fate of individual atoms from precursors through metabolic transformation, producing an atom-resolved metabolic fate map. However, extracts of cells or tissue give rise to very complex NMR spectra. While multidimensional NMR experiments may partially overcome the spectral overlap problem, additional tools may be needed to determine site-specific isotopomer distributions. NMR is especially powerful by virtue of its isotope editing capabilities using NMR active nuclei such as 13C, 15N, 19F and 31P to select molecules containing just these atoms in a complex mixture, and provide direct information about which atoms are present in identified compounds and their relative abundances. The isotope-editing capability of NMR can also be employed to select for those compounds that have been selectively derivatized with an NMR-active stable isotope at particular functional groups, leading to considerable spectral simplification. Here we review isotope analysis by NMR, and methods of chemoselection both for spectral simplification, and for enhanced isotopomer analysis.

Hydrogen-Deuterium Addition and Exchange in N-Ethylmaleimide Reaction with Glutathione Detected by NMR Spectroscopy

Glutathione (GSH) is an important and ubiquitous thiol compound abundantly present in virtually every living cell. It is a powerful antioxidant critically required to protect cells from oxidative damage and free radical injury. Its quantification in ex vivo analysis remains a major challenge because it spontaneously oxidizes to form glutathione disulfide. N-Ethylmaleimide (NEM) is a well-known Michael acceptor, which reacts rapidly and irreversibly with thiol and prevents disulfide bond formation. Based on thiol conjugation to NEM, recently, the concentration of GSH was determined in human blood using NMR spectroscopy [Anal. Chem, 2021, 93(44): 14844-14850]. It was found that hydrogen-deuterium addition and exchange occur during the thiol-maleimide reaction as well as NMR analysis, generating a series of poorly explored diastereomers/isotopomers. Here, we establish a general NMR approach to identify the thiosuccinimide diastereomers/isotopomers derived from the thiol-maleimide reaction. The thiol-Michael addition reaction was conducted for GSH and another thiol compound, cysteine, separately, using D2O and H2O. The conjugates were characterized by 1H/13C 1D/2D NMR under different solvent, buffer, and pH conditions. The Michael addition combined with the H/D exchange formed twelve unique diastereomers/isotopomers. NMR measurements allowed the distinct assignment of all structures in solutions and quantification of H/D addition and exchange. Interestingly, the deuterium exchange rate was dependent on structure, pH, and buffer. The elucidation of the thiol-maleimide reaction and H/D exchange mechanism can potentially impact areas including metabolomics, small molecule synthesis, and bioconjugation chemistry.

Facile synthesis of a glutathione-depleting Cu(II)-half-salamo-based coordination polymer for enhanced chemodynamic therapy

Chemodynamic therapy (CDT), utilizing Fenton catalysts to convert intracellular H₂O₂ into toxic hydroxyl radicals (˙OH) to kill cancer cells, has a wide application prospect in tumor treatment because of its high selectivity. Its anticancer effect, however, is unsatisfactory due to the overexpressed glutathione (GSH). Herein, a GSH-depleting Cu(II)-half-salamo-based coordination polymer (CuCP) was prepared and validated by single crystal X-ray crystallography, Hirshfeld surface analyses and DFT calculations. The Cu(II) ions in the coordination polymer are five-coordinated bearing slightly twisted square pyramidal coordination environments and are bridged by phenoxy and alkoxy groups. After internalization by tumor cells, the CuCP could be biodegraded and reduced by GSH to generate a large amount of Cu(I), simultaneously depleting GSH. Subsequently, the Cu(I) ions interact with H₂O₂ to generate toxic ˙OH through a Fenton-like reaction to enhance their anticancer efficacy. Our study provides useful insights into designing smarter metal-based anticancer agents to improve the CDT efficiency in cancer therapy.