1H NMR spectroscopy of body fluids in patients with inborn errors of purine and pyrimidine metabolism

Investigation of thymine as a potential cancer biomarker employing tryptophan with nanomaterials as a biosensor

Tryptophan and tryptophan-based nanomaterials sensors in a solution have been developed to directly evaluate thymine. The determination of thymine has been done via quenching of the fluorescence of tryptophan and tryptophan-based nanomaterials such as graphene (Gr), graphene oxide (GO), gold nanoparticles (AuNPs), gold-silver nanocomposite (Au-Ag NC) in a physiological buffer. As the concentration of thymine rises, the fluorescence of tryptophan and tryptophan/nanomaterials becomes less intense. Trp, Trp/Gr, and tryptophan/(Au-Ag) NC systems' quenching mechanisms were dynamic, but tryptophan /GO and tryptophan/AuNPs' quenching mechanisms were static. The linear dynamic range for the determination of thy by tryptophan and tryptophan /nanomaterials is 10 to 200 μM. The detection limits for tryptophan, tryptophan /Gr, tryptophan /GO, tryptophan /AuNPs, and tryptophan/Au-Ag NC were 3.21, 14.20, 6.35, 4.67and 7.79 Μm, respectively. Thermodynamic parameters for the interaction of the Probes with Thy include the enthalpy (H°) and entropy (S°) change values, were assessed, as well as the binding constant (Ka) of Thy with Trp and Trp-based nanomaterials. A recovery study was conducted utilizing a human serum sample after the addition of the required quantity of the investigational thymine.

Ex vivo proton spectroscopy (1 H-NMR) analysis of inborn errors of metabolism: Automatic and computer-assisted analyses

There are about 1500 genetic metabolic diseases. A small number of treatable diseases are diagnosed by newborn screening programs, which are continually being developed. However, most diseases can only be diagnosed based on clinical symptoms or metabolic findings. The main biological fluids used are urine, plasma and, in special situations, cerebrospinal fluid. In contrast to commonly used methods such as gas chromatography and high performance liquid chromatography mass spectrometry, ex vivo proton spectroscopy (¹ H-NMR) is not yet used in routine clinical practice, although it has been recommended for more than 30 years. Automatic analysis and improved NMR technology have also expanded the applications used for the diagnosis of inborn errors of metabolism. We provide a mini-overview of typical applications, especially in urine but also in plasma, used to diagnose common but also rare genetic metabolic diseases with ¹ H-NMR. The use of computer-assisted diagnostic suggestions can facilitate interpretation of the profiles. In a proof of principle, to date, 182 reports of 59 different diseases and 500 reports of healthy children are stored. The percentage of correct automatic diagnoses was 74%. Using the same ¹ H-NMR profile-targeted analysis, it is possible to apply an untargeted approach that distinguishes profile differences from healthy individuals. Thus, additional conditions such as lysosomal storage diseases or drug interferences are detectable. Furthermore, because ¹ H-NMR is highly reproducible and can detect a variety of different substance categories, the metabolomic approach is suitable for monitoring patient treatment and revealing additional factors such as nutrition and microbiome metabolism. Besides the progress in analytical techniques, a multiomics approach is most effective to combine metabolomics with, for example, whole exome sequencing, to also diagnose patients with nondetectable metabolic abnormalities in biological fluids. In this mini review we also provide our own data to demonstrate the role of NMR in a multiomics platform in the field of inborn errors of metabolism.

Experimental and theoretical approaches for the selective detection of thymine in real samples using gold nanoparticles as a biochemical sensor

We report a simple, selective and cost effective method for the qualitative and quantitative determination of thymine in a DNA standard and urine samples using gold nanoparticles (AuNPs) as a label-free colorimetric biochemical sensor. The mechanism for the detection of thymine is demonstrated via the color change of the AuNPs from pink to blue, followed by the shift of the localized surface plasmon resonance (LSPR) absorption band to a higher wavelength with the introduction of an analyte. The selective detection of thymine was experimentally verified by performing a control experiment with nucleobases, other biomolecules, metal ions and anions. In addition, the computation density functional theory (DFT) and time dependent density functional theory (TD-DFT) using the Gaussian (C.01) program highlighted that the electrostatic potential behavior of the thymine molecule facilitated a non-covalent interaction toward gold for the selective detection of analytes, and the computation was also used to calculate a UV-Vis absorption band as well. The calculated absorption band of the AuNPs with thymine, obtained using TD-DFT, was found to be very close to the experimental data. The omnicapped truncated tetrahedral (ν₃-tetrahedral) Au₂₀ cluster structure was considered as the model for the AuNP optimization. The linear range obtained for the quantitative determination of thymine was found to be 10–1200 ng mL⁻¹ with a limit of detection of 3 ng mL⁻¹. The advantages of using the AuNPs as a biochemical sensor are that they provide a facile and low cost method and are selective for the qualitative and quantitative determination of thymine in a DNA standard and in urine samples in comparison to chromatographic and electrochemical methods.

We report a simple, selective and cost effective method for the qualitative and quantitative determination of thymine in a DNA standard and in urine samples using gold nanoparticles (AuNPs) as a label-free colorimetric biochemical sensor.

A diagnostic biomarker profile for fibromyalgia syndrome based on an NMR metabolomics study of selected patients and controls

BACKGROUND

Fibromyalgia syndrome (FMS) is a chronic pain syndrome. A plausible pathogenesis of the disease is uncertain and the pursuit of measurable biomarkers for objective identification of affected individuals is a continuing endeavour in FMS research. Our objective was to perform an explorative metabolomics study (1) to elucidate the global urinary metabolite profile of patients suffering from FMS, and (2) to explore the potential of this metabolite information to augment existing medical practice in diagnosing the disease.

METHODS

We selected patients with a medical history of persistent FMS (n = 18), who described their recent state of the disease through the Fibromyalgia Impact Questionnaire (FIQR) and an in-house clinical questionnaire (IHCQ). Three control groups were used: first-generation family members of the patients (n = 11), age-related individuals without any indications of FMS or related conditions (n = 10), and healthy young (18-22 years) individuals (n = 20). All subjects were female and the biofluid under investigation was urine. Correlation analysis of the FIQR showed the FMS patients represented a well-defined disease group for this metabolomics study. Spectral analyses of urine were conducted using a 500 MHz ¹H nuclear magnetic resonance (NMR) spectrometer; data processing and analyses were performed using Matlab, R, SPSS and SAS software.

RESULTS AND DISCUSSION

Unsupervised and supervised multivariate analyses distinguished all three control groups and the FMS patients, and significant increases in metabolites related to the gut microbiome (hippuric, succinic and lactic acids) were observed. We have developed an algorithm for the diagnosis of FMS consisting of three metabolites - succinic acid, taurine and creatine - that have a good level of diagnostic accuracy (Receiver Operating Characteristic (ROC) analysis - area under the curve 90%) and on the pain and fatigue symptoms for the selected FMS patient group.

CONCLUSION

Our data and comparative analyses indicated an altered metabolic profile of patients with FMS, analytically detectable within their urine. Validation studies may substantiate urinary metabolites to supplement information from medical assessment, tender-point measurements and FIQR questionnaires for an improved objective diagnosis of FMS.

Modelling the acid/base 1H NMR chemical shift limits of metabolites in human urine

INTRODUCTION

Despite the use of buffering agents the ¹H NMR spectra of biofluid samples in metabolic profiling investigations typically suffer from extensive peak frequency shifting between spectra. These chemical shift changes are mainly due to differences in pH and divalent metal ion concentrations between the samples. This frequency shifting results in a correspondence problem: it can be hard to register the same peak as belonging to the same molecule across multiple samples. The problem is especially acute for urine, which can have a wide range of ionic concentrations between different samples.

OBJECTIVES

To investigate the acid, base and metal ion dependent ¹H NMR chemical shift variations and limits of the main metabolites in a complex biological mixture.

METHODS

Urine samples from five different individuals were collected and pooled, and pre-treated with Chelex-100 ion exchange resin. Urine samples were either treated with either HCl or NaOH, or were supplemented with various concentrations of CaCl₂, MgCl₂, NaCl or KCl, and their ¹H NMR spectra were acquired.

RESULTS

Nonlinear fitting was used to derive acid dissociation constants and acid and base chemical shift limits for peaks from 33 identified metabolites. Peak pH titration curves for a further 65 unidentified peaks were also obtained for future reference. Furthermore, the peak variations induced by the main metal ions present in urine, Na⁺, K⁺, Ca²⁺ and Mg²⁺, were also measured.

CONCLUSION

These data will be a valuable resource for ¹H NMR metabolite profiling experiments and for the development of automated metabolite alignment and identification algorithms for ¹H NMR spectra.

An optimized buffer system for NMR-based urinary metabonomics with effective pH control, chemical shift consistency and dilution minimization

NMR-based metabonomics has been widely employed to understand the stressor-induced perturbations to mammalian metabolism. However, inter-sample chemical shift variations for metabolites remain an outstanding problem for effective data mining. In this work, we systematically investigated the effects of pH and ionic strength on the chemical shifts for a mixture of 9 urinary metabolites. We found that the chemical shifts were decreased with the rise of pH but increased with the increase of ionic strength, which probably resulted from the pH- and ionic strength-induced alteration to the ionization equilibrium for the function groups. We also found that the chemical shift variations for most metabolites were reduced to less than 0.004 ppm when the pH was 7.1-7.7 and the salt concentration was less than 0.15 M. Based on subsequent optimization to minimize chemical shift variation, sample dilution and maximize the signal-to-noise ratio, we proposed a new buffer system consisting of K(2)HPO(4) and NaH(2)PO(4) (pH 7.4, 1.5 M) with buffer-urine volume ratio of 1 : 10 for human urinary metabonomic studies; we suggest that the chemical shifts for the proton signals of citrate and aromatic signals of histidine be corrected prior to multivariate data analysis especially when high resolution data were employed. Based on these, an optimized sample preparation method has been developed for NMR-based urinary metabonomic studies.

beta-Ureidopropionase deficiency: a novel inborn error of metabolism discovered using NMR spectroscopy on urine

In this work, NMR investigations that led to the discovery of a new inborn error of metabolism, beta-ureidopropionase (UP) deficiency, are reported. 1D (1)H-NMR experiments were performed using a patient's urine. 3-Ureidopropionic acid was observed in elevated concentrations in the urine spectrum. A 1D (1)H-(1)H total correlation spectroscopy (TOCSY) and two heteronuclear 2D NMR techniques (heteronuclear multiple bond correlation (HMBC) and heteronuclear single-quantum correlation (HSQC)) were used to identify the molecular structure of the compound that caused an unknown doublet resonance at 1.13 ppm. Combining the information from the various NMR spectra, this resonance could be assigned to 3-ureidoisobutyric acid. These observations suggested a deficiency of UP. With 1D (1)H-NMR spectroscopy, UP deficiency can be easily diagnosed. The (1)H-NMR spectrum can also be used to diagnose patients suffering from other inborn errors of metabolism in the pyrimidine degradation pathway.

1H-NMR Spectroscopy of Body Fluids: Inborn Errors of Purine and Pyrimidine Metabolism

Background: The diagnosis of inborn errors of purine and pyrimidine metabolism is often difficult. We examined the potential of 1H-NMR as a tool in evaluation of patients with these disorders.

Methods: We performed 1H-NMR spectroscopy on 500 and 600 MHz instruments with a standardized sample volume of 500 μL. We studied body fluids from 25 patients with nine inborn errors of purine and pyrimidine metabolism.

Results: Characteristic abnormalities could be demonstrated in the 1H-NMR spectra of urine samples of all patients with diseases in the pyrimidine metabolism. In most urine samples from patients with defects in the purine metabolism, the 1H-NMR spectrum pointed to the specific diagnosis in a straightforward manner. The only exception was a urine from a case of adenine phosphoribosyl transferase deficiency in which the accumulating metabolite, 2,8-dihydroxyadenine, was not seen under the operating conditions used. Similarly, uric acid was not measured. We provide the 1H-NMR spectral characteristics of many intermediates in purine and pyrimidine metabolism that may be relevant for future studies in this field.

Conclusion: The overview of metabolism that is provided by 1H-NMR spectroscopy makes the technique a valuable screening tool in the detection of inborn errors of purine and pyrimidine metabolism.

Defect in Dimethylglycine Dehydrogenase, a New Inborn Error of Metabolism: NMR Spectroscopy Study

Background: A38-year-old man presented with a history of fish odor (since age 5) and unusual muscle fatigue with increased serum creatine kinase. Our aim was to identify the metabolic error in this new condition.

Methods: We used 1H NMR spectroscopy to study serum and urine from the patient.

Results: The concentration of N,N-dimethylglycine (DMG) was increased ∼100-fold in the serum and ∼20-fold in the urine. The presence of DMG as a storage product was confirmed by use of 13C NMR spectroscopy and gas chromatography–mass spectrometry. The high concentration of DMG was caused by a deficiency of the enzyme dimethylglycine dehydrogenase (DMGDH). A homozygous missense mutation was found in the DMGDH gene of the patient.

Conclusions: DMGDH deficiency must be added to the differential diagnosis of patients complaining of a fish odor. This deficiency is the first inborn error of metabolism discovered by use of in vitro 1H NMR spectroscopy of body fluids.

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Inherited defects of purine and pyrimidine metabolism: laboratory methods for diagnosis

The diagnosis of the majority of the known inherited defects of purine and pyrimidine metabolism can be achieved by analysing urinary excretion profiles. A quantitative measurement of the urinary uric acid/creatinine ratio should be the first approach for purine defects. The general screening system involves separation of the bases and nucleosides by reversed-phase high-performance liquid chromatography and multiwavelength UV detection. The catabolic defects of pyrimidine degradation can be diagnosed by gas chromatography-mass spectrometry as used for organic acids. For the detection of adenylosuccinase deficiency, several simple but effective thin-layer chromatographic methods are available. Techniques such as liquid chromatography-mass spectrometry, direct nega-tiveion fast-atom bombardment mass spectrometry, and proton nuclear magnetic resonance spectroscopy give promising results, but are not yet being used on a large scale. Patients should keep to a simple diet and preferably be free of medication in order to allow a reliable interpretation of the analytical data.