Quantitative determination of metabolites in human urine by <Superscript>1</Superscript>H NMR spectroscopy

Conditions for registration of urinary ¹H NMR spectra have been optimized in order to achieve maximal accuracy of quantitative analysis. Urinary samples from patients with acute pancreatitis have been investigated and spectral data of identified urinary metabolites and results of their quantitative determination are given. Employment of ¹H NMR spectra is perspective for the development of new laboratory diagnostic methods.     

Metabolic assessment of a novel chronic myelogenous leukemic cell line and an imatinib resistant subline by <Superscript>1</Superscript>H NMR spectroscopy

The goal of this study was to examine metabolic differences between a novel chronic myelogenous leukemic (CML) cell line, MyL, and a sub-clone, MyL-R, which displays enhanced resistance to the targeted Bcr-Abl tyrosine kinase inhibitor imatinib. ¹H nuclear magnetic resonance (NMR) spectroscopy was carried out on cell extracts and conditioned media from each cell type. Both principal component analysis (PCA) and specific metabolite identification and quantification were used to examine metabolic differences between the cell types. MyL cells showed enhanced glucose removal from the media compared to MyL-R cells with significant differences in production rates of the glycolytic end-products, lactate and alanine. Interestingly, the total intracellular creatine pool (creatine + phosphocreatine) was significantly elevated in MyL-R compared to MyL cells. We further demonstrated that the MyL-R cells converted the creatine to phosphocreatine using non-invasive monitoring of perfused alginate-encapsulated MyL-R and MyL cells by in vivo ³¹P NMR spectroscopy and subsequent HPLC analysis of extracts. Our data demonstrated a clear difference in the metabolite profiles of drug-resistant and sensitive cells, with the biggest difference being an elevation of creatine metabolites in the imatinib-resistant MyL-R cells.     

Nitrogen metabolism of asparagine and glutamate in Vero cells studied by <Superscript>1</Superscript>H/<Superscript>15</Superscript>N NMR spectroscopy

Glutamine-free culture of Vero cells has previously been shown to cause higher cell yield and lower ammonia accumulation than that in glutamine-containing culture. Nitrogen metabolism of asparagine and glutamate as glutamine replacer was studied here using nuclear magnetic resonance (NMR) spectroscopy. ¹⁵N-labelled glutamate or asparagine was added and their incorporation into nitrogenous metabolites was monitored by heteronuclear multiple bond coherence (HMBC) NMR spectroscopy. In cells incubated with l-[¹⁵N]glutamate, the ¹⁵N label was subsequently found in a number of metabolites including alanine, aspartate, proline, and an unidentified compound. No detectable signal occurred, indicating that glutamate was utilized by transamination rather than by oxidative deamination. In cells incubated with l-[2-¹⁵N]asparagine, the ¹⁵N label was subsequently found in aspartate, the amine group of glutamate/glutamine, and in two unidentified compounds. Incubation of cells with l-[4-¹⁵N]asparagine showed that the amide nitrogen of asparagine was predominantly transferred to glutamine amide. There was no detectable production of , showing that most of the asparagine amide was transaminated by asparagine synthetase rather than deaminated by asparaginase. Comparing with a glutamine-containing culture, the activities of phosphate-activated glutaminase (PAG), glutamate dehydrogenase (GDH) and alanine aminotransferase (ALT) decreased significantly and the activity of aspartate aminotransferase (AST) decreased slightly.     

<Superscript>1</Superscript>H NMR metabolic profiling of gastric cancer patients with lymph node metastasis

Introduction

Gastric cancer (GC) is a malignant tumor worldwide. As primary pathway for metastasis, the lymphatic system is an important prognostic factor for GC patients. Although the metabolic changes of gastric cancer have been investigated in extensive studies, little effort focused on the metabolic profiling of lymph node metastasis (LNM)-positive or negative GC patients.

Objectives

We performed ¹H NMR spectrum of GC tissue samples with and without LNM to identify novel potential metabolic biomarkers in the process of LNM of GC.

Methods

¹H NMR-based untargeted metabolomics approach combined with multivariate statistical analyses were used to study the metabolic profiling of tissue samples from LNM-positive GC patients (n?=?40), LNM-negative GC patients (n?=?40) and normal controls (n?=?40).

Results

There was a clear separation between GC patients and normal controls, and 33 differential metabolites were identified in the study. Moreover, GC patients were also well-classified according to LNM-positive or negative. Totally eight distinguishing metabolites were selected in the metabolic profiling of GC patients with LNM-positive or negative, suggesting the metabolic dysfunction in the process of LNM. According to further validation and analysis, especially BCAAs metabolism (leucine, isoleucine, valine), GSH and betaine may be as potential factors of diagnose and prognosis of GC patients with or without LNM.

Conclusion

To our knowledge, this is the first metabolomics study focusing on LNM of GC. The identified distinguishing metabolites showed a promising application on clinical diagnose and therapy prediction, and understanding the mechanism underlying the carcinogenesis, invasion and metastasis of GC.

     

Response of Degarelix treatment in human prostate cancer monitored by HR-MAS <Superscript>1</Superscript>H NMR spectroscopy

Introduction

The androgen receptor (AR) is the master regulator of prostate cancer cell metabolism. Degarelix is a novel gonadotrophin-releasing hormone blocker, used to decrease serum androgen levels in order to treat advanced human prostate cancer. Little is known of the rapid metabolic response of the human prostate cancer tissue samples to the decreased androgen levels.

Objectives

To investigate the metabolic responses in benign and cancerous tissue samples from patients after treatment with Degarelix by using HRMAS ¹H NMR spectroscopy.

Methods

Using non-destructive HR-MAS ¹H NMR spectroscopy we analysed the metabolic changes induced by decreased AR signalling in human prostate cancer tissue samples. Absolute concentrations of the metabolites alanine, lactate, glutamine, glutamate, citrate, choline compounds [t-choline = choline + phosphocholine (PC) + glycerophosphocholine (GPC)], creatine compounds [t-creatine = creatine (Cr) + phosphocreatine (PCr)], taurine, myo-inositol and polyamines were measured in benign prostate tissue samples (n = 10), in prostate cancer specimens from untreated patients (n = 7) and prostate cancer specimens from patients treated with Degarelix (n = 6).

Results

Lactate, alanine and t-choline concentrations were significantly elevated in high-grade prostate cancer samples when compared to benign samples in untreated patients. Decreased androgen levels resulted in significant decreases of lactate and t-choline concentrations in human prostate cancer biopsies.

Conclusions

The reduced concentrations of lactate and t-choline metabolites due to Degarelix could in principle be monitored by in vivo ¹H MRS, which suggests that it would be possible to monitor the effects of physical or chemical castration in patients by that non-invasive method.

     

<Superscript>1</Superscript>H, <Superscript>13</Superscript>C and <Superscript>15</Superscript>N chemical shift assignments of Saccharomyces cerevisiae type 1 thioredoxin in the oxidized state by solution NMR spectroscopy

Thioredoxins (Trx) are ubiquitous proteins that regulate several biochemical processes inside the cell. Trx is an important player, displaying oxidoreductase activity and helping to keep and regulate the oxidative state of the cellular environment. Trx also participates in the regulation of many cellular functions, such as DNA synthesis, protection against oxidative stress, cell cycle and signal transduction. The oxidized Trx is the target for another set of proteins, such as thioredoxin reductase (TrR), which used the reductive potential of NADPH. The oxidized state of Trx also plays important role in regulation of redox state in the cells. In this regard, the oxidized form of Trx is a putative conformer that contributes to the cellular redox environment. Here we report the chemical shift assignments (¹H, ¹³C and ¹⁵N) in solution at 15 °C. We also showed the secondary structure analysis of the oxidized form of yeast thioredoxin (yTrx1) as basis for future NMR studies of protein–target interactions and dynamics. The assignment was done at low concentration (200 µM) because it is important to keep intact the water cavity.     

Metabolic profiling of Rhodiola rosea rhizomes by 1H NMR spectroscopy

Introduction – Rhodiola rosea is a broadly used medicinal plant with largely unexplored natural variability in secondary metabolite levels. Objective – The aim of this work was to develop a non‐target procedure for ¹H NMR spectroscopic fingerprinting of rhizome extracts for pattern recognition analysis and identification of secondary metabolites responsible for differences in sample composition. To achieve this, plants from three different geographic areas (Swiss Alps, Finland, and Altai region in Siberia) were investigated. Results – A sample preparation procedure was developed in order to remove polymeric polyphenols as the ¹H NMR analysis of low‐molecular‐weight metabolites was hampered by the presence of tannins. Principal component analysis disclosed tight clustering of samples according to population. PCA models based on the aromatic region of the spectra showed that the first two components reflected changes in the content of salidroside and rosavin, respectively, the rosavin content being negatively correlated to that of rhodiocyanoside A and minor aromatics. Score plots and non‐parametric variance tests demonstrated population‐dependent changes according to harvest time. Data consistency was assessed using score plots and box‐and‐whisker graphs. In addition, a procedure for presenting loadings of PCA models based on bucketed data as high‐resolution plots, which are reminiscent of real ¹H NMR spectra and help to identify latent biomarkers, is presented. Conclusion – This study demonstrated the usefulness of the established procedure for multivariate non‐target ¹H NMR metabolic profiling of Rhodiola rosea. Copyright © 2010 John Wiley & Sons, Ltd.     

<Superscript>1</Superscript>H NMR metabolic fingerprinting of saffron extracts

The aim of this study was to explore feasibility of ¹H NMR metabolic fingerprinting for discrimination of authenticity of saffron using principal component analysis (PCA) modeling. Authentic reference Iranian saffron (n = 31) and commercial samples (n = 32) were used. Cross-validated PCA models based on ¹H NMR spectra of solutions prepared by direct extraction of grinded saffron with methanol-d ₄ distinguished reference Iranian saffron samples from commercial samples that formed several distinct clusters, some of which represent falsified samples as confirmed by microscopic analysis. The production sites and drying conditions of the authentic reference Iranian samples were not reflected in the current dataset. Picrocrocin and glycosyl esters of crocetin emerged as the most important ¹H NMR markers of authentic saffron by using statistical correlation spectroscopy. In conclusion, ¹H NMR spectra of saffron extracts combined with pattern recognition by PCA provide immediate means of unsupervised classification of saffron samples.     

Comprehensive <Superscript>1</Superscript>H NMR metabolic profiling of body fluids for differentiation of meningitis in adults

Introduction

Meningitis, a morbidly infectious central nervous system pathology is accompanied by acute inflammation of the meninges, causing raised intracranial pressure linked with serious neurological sequelae.

Objective

To observe the variation in the metabolic profile, that may occur in serum and urine along with CSF in adults using ¹H NMR spectroscopy, with an attempt of appropriate and timely treatment regimen.

Methods

The ¹H NMR-based metabolomics has been performed in 115 adult subjects for differentiating bacterial meningitis (BM) and tubercular meningitis (TBM).

Results

The discriminant function analysis (DFA) of the three bio-fluids collectively identified 3-hydroxyisovalerate, lactate, glucose, formate, valine, alanine, ketonic bodies, malonate and choline containing compounds (choline and GPC) as significant metabolites among cases versus control group. The differentiation of bacterial meningitis and tuberculous meningitis (BM vs. TBM) can be done on the basis of identification of 3-hydroxyisovalerate, isobutyrate and formate in case of CSF (with a correct classification of 78 %), alanine in serum (correct classification 60 %), valine and acetone in case of urine (correct classification 89.1 %). The NMR spectral bins based orthogonal signal correction principal component analysis score plots of significant metabolites obtained from DFA also provided group classification among cases versus control group in CSF, serum and urine samples. The variable importance in projection scores also identified similar significant metabolites as obtained from DFA, collectively in CSF, serum and urine samples, responsible for differentiation of meningitis.

Conclusion

The CSF contained metabolites which are formed during infection and inflammation, and these were also found in significant quantity in serum and urine samples.

     

Detection of adulteration in Iranian saffron samples by <Superscript>1</Superscript>H NMR spectroscopy and multivariate data analysis techniques

Introduction

The high market value of saffron (Crocus sativus L.) has made it an attractive candidate for adulteration. Safflower (Carthamus tinctorius L.) and tartrazine are among the most common herbal and synthetic foreign materials that may be added to pure saffron for the purpose of adulteration. In spite of encouraging advances achieved in the identification of adulteration in saffron samples, the lack of a simple method with sufficient power for discrimination of pure high grade saffron from meticulously adulterated saffron samples persuaded us to perform this study.

Objectives

In this work, we show that ¹H NMR spectroscopy together with chemometric multivariate data analysis methods can be used for the detection of adulteration in saffron.

Methods

Authentic Iranian saffron samples (n?=?20) and adulterated samples that were prepared by adding either different quantities of natural plant materials such as safflower, or synthetic dyes such as tartrazine or naphthol yellow to pure saffron (n?=?22) composed the training set. This training set was used to build multivariate Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) models. The predictive power of the PLS-DA model was validated by testing the model against an external dataset (n?=?13).

Results

PCA and PLS-DA models could both discriminate between the authentic and adulterated samples, and the external validation showed 100% sensitivity and specificity for predicting the authenticity of suspicious samples. Peaks specific to authentic and adulterated samples were also characterized. Proximity of samples with unknown adulteration status to the samples adulterated with known compounds in the PCA provided insight regarding the identity of the adulterant in the suspicious samples. Furthermore, the authentic samples could be distinguished based on their cultivation site.

Conclusion

The present study demonstrates that the application of ¹H NMR spectroscopy coupled with multivariate data analysis is a suitable approach for detection of adulteration in saffron specimens. Outstanding sensitivity and specificity of the PLS-DA model in discriminating the authentic from adulterated samples in external validation confirmed the high predictive power of the model. The advantage of the present method is its power for detecting a wide spectrum of adulterants, ranging from synthetic dyes to herbal materials, in a single assay.

     

A comparison of human serum and plasma metabolites using untargeted <Superscript>1</Superscript>H NMR spectroscopy and UPLC-MS

Introduction

Differences in the metabolite profiles between serum and plasma are incompletely understood.

Objectives

To evaluate metabolic profile differences between serum and plasma and among plasma sample subtypes.

Methods

We analyzed serum, platelet rich plasma (PRP), platelet poor plasma (PPP), and platelet free plasma (PFP), collected from 8 non-fasting apparently healthy women, using untargeted standard 1D and CPMG ¹H NMR and reverse phase and hydrophilic (HILIC) UPLC-MS. Differences between metabolic profiles were evaluated using validated principal component and orthogonal partial least squares discriminant analysis.

Results

Explorative analysis showed the main source of variation among samples was due to inter-individual differences with no grouping by sample type. After correcting for inter-individual differences, lipoproteins, lipids in VLDL/LDL, lactate, glutamine, and glucose were found to discriminate serum from plasma in NMR analyses. In UPLC-MS analyses, lysophosphatidylethanolamine (lysoPE)(18:0) and lysophosphatidic acid(20:0) were higher in serum, and phosphatidylcholines (PC)(16:1/18:2, 20:3/18:0, O-20:0/22:4), lysoPC(16:0), PE(O-18:2/20:4), sphingomyelin(18:0/22:0), and linoleic acid were lower. In plasma subtype analyses, isoleucine, leucine, valine, phenylalanine, glutamate, and pyruvate were higher among PRP samples compared with PPP and PFP by NMR while lipids in VLDL/LDL, citrate, and glutamine were lower. By UPLC-MS, PE(18:0/18:2) and PC(P-16:0/20:4) were higher in PRP compared with PFP samples.

Conclusions

Correction for inter-individual variation was required to detect metabolite differences between serum and plasma. Our results suggest the potential importance of inter-individual effects and sample type on the results from serum and plasma metabolic phenotyping studies.

     

Chemometric variance analysis of <Superscript>1</Superscript>H NMR metabolomics data on the effects of oral rinse on saliva

In order to investigate exposure end effect markers of fruit and fruit fibre intake we investigated how fresh apple or apple-pectin affects the urinary metabolome of rats. Twenty-four Fisher 344 male rats were randomized into three groups and fed a standard diet with different supplementations added in two of the groups (7% apple-pectin or 10 g raw apple). After 24 days of feeding, 24 h urine was collected and analyzed by UPLC-QTOF-MS in positive and negative ionization mode. Metabolites that responded to the apple or pectin diets were selected and classified as either potential exposure or effect markers based on the magnitude and pattern of their response. An initial principal component analysis (PCA) of all detected metabolites showed a clear separation between the groups and during marker identification several new apple and/or pectin markers were found. Quinic acid, m-coumaric acid and (-)epicatechin were identified as exposure markers of apple intake whereas hippuric acid behaved as an effect marker. Pyrrole-2-carboxylic acid and 2-furoylglycine behaved as pectin exposure markers while 2-piperidinone was recognized as a potential pectin effect marker. None of them has earlier been related to intake of pectin or other fibre products. We discuss these new potential exposure and effect markers and their interpretation.     

Automated amino acid side-chain NMR assignment of proteins using <Superscript>13</Superscript>C- and <Superscript>15</Superscript>N-resolved 3D [<Superscript>1</Superscript>H,<Superscript>1</Superscript>H]-NOESY

ASCAN is a new algorithm for automatic sequence-specific NMR assignment of amino acid side-chains in proteins, which uses as input the primary structure of the protein, chemical shift lists of (1)H(N), (15)N, (13)C(alpha), (13)C(beta) and possibly (1)H(alpha) from the previous polypeptide backbone assignment, and one or several 3D (13)C- or (15)N-resolved [(1)H,(1)H]-NOESY spectra. ASCAN has also been laid out for the use of TOCSY-type data sets as supplementary input. The program assigns new resonances based on comparison of the NMR signals expected from the chemical structure with the experimentally observed NOESY peak patterns. The core parts of the algorithm are a procedure for generating expected peak positions, which is based on variable combinations of assigned and unassigned resonances that arise for the different amino acid types during the assignment procedure, and a corresponding set of acceptance criteria for assignments based on the NMR experiments used. Expected patterns of NOESY cross peaks involving unassigned resonances are generated using the list of previously assigned resonances, and tentative chemical shift values for the unassigned signals taken from the BMRB statistics for globular proteins. Use of this approach with the 101-amino acid residue protein FimD(25-125) resulted in 84% of the hydrogen atoms and their covalently bound heavy atoms being assigned with a correctness rate of 90%. Use of these side-chain assignments as input for automated NOE assignment and structure calculation with the ATNOS/CANDID/DYANA program suite yielded structure bundles of comparable quality, in terms of precision and accuracy of the atomic coordinates, as those of a reference structure determined with interactive assignment procedures. A rationale for the high quality of the ASCAN-based structure determination results from an analysis of the distribution of the assigned side chains, which revealed near-complete assignments in the core of the protein, with most of the incompletely assigned residues located at or near the protein surface.     

Liquid seaweed extracts identified using <Superscript>1</Superscript>H NMR profiles

Aqueous extracts of Ascophyllum nodosum and several other brown seaweeds are manufactured commercially and widely distributed for use on agricultural crops. The increasingly regulated international trade in such products requires that they be standardized and defined to a degree not previously required. We examined commercially available extracts using quantitative ¹H NMR and principal components analysis (PCA) techniques. Extracts manufactured over a 4-year period using the same process exhibited characteristic profiles that, on PCA, clustered as a discrete group distinct from the other commercial products examined. In addition to recognizing extracts made from different seaweeds, analysis of the ¹H spectra in the 0.35–4.70 ppm region allowed us to distinguish amongst extracts produced from the same algal species by different manufacturers. This result established that the process used to make an extract is an important variable in defining its composition. A comparison of the ¹H NMR integrals for the regions 1.0–3.0 ppm and 3.0–4.38 ppm revealed small but significant changes in the A. nodosum spectra that we attribute to seasonal variation in gross composition of the harvested seaweed. Such changes are reflected in the PCA scores plots and contribute to the scatter observed within the data point cluster observed for Acadian soluble extracts when all data are pooled. Quantitative analysis using ¹H NMR (qNMR) with a certified external standard (caffeine) showed a linear relationship with extract concentration over at least an order of magnitude (2.5–33 mg/mL; R ² > 0.97) for both spectral regions integrated. We conclude that qNMR can be used to profile (or “fingerprint”) commercial seaweed extracts and to quantify the amount of extract present relative to a suitably chosen standard. Issued as NRCC no. 42,652.     

Optimizing <Superscript>19</Superscript>F NMR protein spectroscopy by fractional biosynthetic labeling

In protein NMR experiments which employ nonnative labeling, incomplete enrichment is often associated with inhomogeneous line broadening due to the presence of multiple labeled species. We investigate the merits of fractional enrichment strategies using a monofluorinated phenylalanine species, where resolution is dramatically improved over that achieved by complete enrichment. In NMR studies of calmodulin, a 148 residue calcium binding protein, ¹⁹F and ¹H-¹⁵N HSQC spectra reveal a significant extent of line broadening and the appearance of minor conformers in the presence of complete (>95%) 3-fluorophenylalanine labeling. The effects of varying levels of enrichment of 3-fluorophenylalanine (i.e. between 3 and >95%) were further studied by ¹⁹F and ¹H-¹⁵N HSQC spectra,¹⁵N T₁ and T₂ relaxation measurements, ¹⁹F T₂ relaxation, translational diffusion and heat denaturation experiments via circular dichroism. Our results show that while several properties, including translational diffusion and thermal stability show little variation between non-fluorinated and >95% ¹⁹F labeled samples, ¹⁹F and ¹H-¹⁵N HSQC spectra show significant improvements in line widths and resolution at or below 76% enrichment. Moreover, high levels of fluorination (>80%) appear to increase protein disorder as evidenced by backbone ¹⁵N dynamics. In this study, reasonable signal to noise can be achieved between 60–76% ¹⁹F enrichment, without any detectable perturbations from labeling.     

Automated metabolite identification from biological fluid <Superscript>1</Superscript>H NMR spectra

Introduction

Metabolite identification in biological samples using Nuclear Magnetic Resonance (NMR) spectra is a challenging task due to the complexity of the biological matrices.

Objectives

This paper introduces a new, automated computational scheme for the identification of metabolites in 1D ¹H NMR spectra based on the Human Metabolome Database.

Methods

The methodological scheme comprises of the sequential application of preprocessing, data reduction, metabolite screening and combination selection.

Results

The proposed scheme has been tested on the 1D ¹H NMR spectra of: (a) an amino acid mixture, (b) a serum sample spiked with the amino acid mixture, (c) 20 blood serum, (d) 20 human amniotic fluid samples, (e) 160 serum samples from publicly available database. The methodological scheme was compared against widely used software tools, exhibiting good performance in terms of correct assignment of the metabolites.

Conclusions

This new robust scheme accomplishes to automatically identify peak resonances in ¹H-NMR spectra with high accuracy and less human intervention with a wide range of applications in metabolic profiling.

     

Metabolic profiling of serum from gadolinium chloride-treated rats by 1H NMR spectroscopy

Metabolic profiling of serum from gadolinium chloride (GdCl(3), 10 and 50 mg/kg body weight, intraperitoneal [i.p.])-treated rats was investigated by the NMR spectroscopic-based metabonomic strategy. Serum samples were collected at 48, 96, and 168h postdose (p.d.) after exposure to GdCl(3). (1)H NMR spectra of serum were analyzed by pattern recognition using principal components analysis. The studies showed that there was a dose-related biochemical effect of GdCl(3) treatment on the levels of a range of low-molecular weight compounds in serum. The liver damage induced by GdCl(3) was characterized by the elevation of lactate, pyruvate, and creatine as well as the decrease of branched-chain amino acids (valine and isoleucine), alanine, glucose, and trimethylamine-N-oxide concentration in serum samples. The biochemical effects of GdCl(3) in rats could be consulted when evaluating the biochemical profile of gadolinium-containing compounds that are being developed for nuclear magnetic resonance imaging.     

<Superscript>1</Superscript>H, <Superscript>15</Superscript>N and <Superscript>13</Superscript>C assignment of the amyloidogenic protein medin using fast-pulsing NMR techniques

Thirty-one proteins are known to form extracellular fibrillar amyloid in humans. Molecular information about many of these proteins in their monomeric, intermediate or fibrillar form and how they aggregate and interact to form the insoluble fibrils is sparse. This is because amyloid proteins are notoriously difficult to study in their soluble forms, due to their inherent propensity to aggregate. Using recent developments in fast NMR techniques, band-selective excitation short transient and band-selective optimized flip-angle short-transient heteronuclear multiple quantum coherence we have been able to assign a 5 kDa full-length amyloidogenic protein called medin. Medin is the key protein component of the most common form of localised amyloid with a proposed role in aortic aneurysm and dissection. This assignment will now enable the study of the early interactions that could influence initiation and progression of medin aggregation. The chemical shifts have been deposited in the BioMagRes-Bank accession Nos. 25399 and 26576.     

Metabolic effects of cannabinoids in zebrafish (<Emphasis Type=Italic>Danio rerio</Emphasis>) embryos determined by <Superscript>1</Superscript>H NMR metabolomics

The study of drug-driven biochemical changes is important in order to determine the biomarkers associated with a specific compound activity in an individual biological system. Rodent models have been widely used to study the metabolic changes induced by psychostimulants in a cell, tissue or whole organism. However these models are not suitable for large-scale, high-throughput screening. Here, we used zebrafish embryos to study the metabolic effects of the cannabinoid receptor type 1 (CB₁) agonist (?)-(6aR,10aR)-6,6,9-trimethyl-3-pentyl-6a,7,8,10a-tetrahydro-6H-benzo[c]chromen-1-ol (?⁹-THC) and antagonist (AM251). The zebrafish embryos were exposed to ?⁹-THC and AM251 at 24 h post fertilization (hpf) for 96 h. Proton nuclear magnetic resonance based metabolomic results show an increase in the level of choline, betaine, taurine, adenosine triphosphate and glucose upon exposure to ?⁹-THC. The levels of excitatory neurotransmitters (glutamate and glutamine) increased at lower doses of ?⁹-THC, whereas toxic dose resulted in reduction of glutamate. In contrast to ?⁹-THC, AM251 caused a dose dependent reduction of betaine, choline, taurine and also reduce the level of glutamate and glutamine. Interestingly, both compounds induce the production of the dopamine precursors, phenylalanine and tyrosine at higher doses. These findings suggest that CB₁ receptor is involved in the regulation of metabolites, which might be involved in the neurotransmission of zebrafish embryos. Furthermore, our results show that zebrafish embryo can be successfully used to provide a detailed overview of general effects of drug on the overall metabolome of an intact organism.     

Critical test of some computational methods for prediction of NMR <Superscript>1</Superscript>H and <Superscript>13</Superscript>C chemical shifts

Performance of 18 DFT functionals (B1B95, B3LYP, B3PW91, B97D, BHandHLYP, BMK, CAM-B3LYP, HSEh1PBE, M06-L, mPW1PW91, O3LYP, OLYP, OPBE, PBE1PBE, tHCTHhyb, TPSSh, wB97xD, VSXC) in combinations with six basis sets (cc-pVDZ, aug-cc-pVDZ, cc-pVTZ, aug-cc-pVTZ, IGLO-II, and IGLO-III) and three methods for calculating magnetic shieldings (GIAO, CSGT, IGAIM) was tested for predicting ¹H and ¹³C chemical shifts for 25 organic compounds, for altogether 86 H and 88 C atoms. Proton shifts varied between 1.03 ppm to 12.00 ppm and carbon shifts between 7.87 ppm to 209.28 ppm. It was found that the best method for calculating ¹³C shifts is PBE1PBE/aug-cc-pVDZ with CSGT or IGAIM approaches (mae?=?1.66 ppm), for ¹H the best results were obtained with HSEh1PBE, mPW1PW91, PBE1PBE, CAM-B3LYP, and B3PW91 functionals with cc-pVTZ basis set and with CSGT or IGAIM approaches (mae?=?0.28 ppm). We found that often larger basis sets do not give better results for chemical shifts. The best basis sets for calculating ¹H and ¹³C chemical shifts were cc-pVTZ and aug-cc-pVDZ, respectively. CSGT and IGAIM NMR approaches can perform really well and are in most cases better than popular GIAO approach.

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Graphical Abstract Mean absolute errors for ¹H and ¹³C chemical shifts and computational times of neutral toluene molecule with aug-cc-pVDZ basis set and CSGT approach