The depletion of protein signals in metabonomics analysis with the WET-CPMG pulse sequence

Identifying ligands directly interacting with target protein in medicinal herbs by metabolomic analysis of T2-filtered HSQC spectra

A protocol for efficiently identifying ligands directly interacting with a target protein in complex extracts of medicinal herbs was proposed by combining an adapted 2D perfect-echo Carr-Purcell-Meiboom-Gill heteronuclear single quantum correlation (PE-CPMG HSQC) spectrum with metabolomic analysis. PE-CPMG HSQC can suppress the signal interference from the target protein, allowing more accurate peak quantification than conventional HSQC. Inspired from untargeted metabolomics, regions of interest (ROIs) are constructed and quantified for the mixture or complex extract samples with and without a target protein, and then a binding index (BI) of each ROI is determined. ROIs or corresponding peaks significantly perturbed by the presence of the target protein (BI ≥1.5) are detected as differential features, and potential binding ligands identified from the differential features can be equated with bioactive markers associated with the 'treatment' of the target protein. Quantifying ROI can inclusively report the ligand bindings to a target protein in fast, intermediate and slow exchange regimes on nuclear magnetic resonance (NMR) time scale. The approach was successfully implemented and identified Angoroside C, Cinnamic acid and Harpagoside from the extract of Scrophularia ningpoensis Hemsl. as ligands binding to peroxisome proliferator-activated receptor γ. The proposed 2D NMR-based approach saves excess steps for sample processing and has a higher chance of detecting the weaker ligands in the complex extracts of medicinal herbs. We expect that this approach can be applied as an alternative to mining the potential ligands binding to a variety of target proteins from traditional Chinese medicines and herbal extracts.

Metabolomics and NMR

The purpose of this manuscript will be to convince the reader to dive deeper into NMR spectroscopy and prevent the technique from being just another "black-box" in the lab. We will try to concisely highlight interesting topics and supply additional references for further exploration at each stage. The advantages of delving into the technique will be shown. The secondary objective, i.e., avoiding common problems before starting, will hopefully then become clear. Lastly, we will emphasize the spectrometer information needed for manuscript reporting to allow reproduction of results and confirm findings.

Unraveling the Rewired Metabolism in Lung Cancer Using Quantitative NMR Metabolomics

Lung cancer cells are well documented to rewire their metabolism and energy production networks to enable proliferation and survival in a nutrient-poor and hypoxic environment. Although metabolite profiling of blood plasma and tissue is still emerging in omics approaches, several techniques have shown potential in cancer diagnosis. In this paper, the authors describe the alterations in the metabolic phenotype of lung cancer patients. In addition, we focus on the metabolic cooperation between tumor cells and healthy tissue. Furthermore, the authors discuss how metabolomics could improve the management of lung cancer patients.

Fibromyalgia and Depression in Women: An 1H-NMR Metabolomic Study

Fibromyalgia is a chronic and systemic syndrome characterized by muscle, bone, and joint pain. It is a gender-specific condition with a 9:1 incidence ratio between women and men. Fibromyalgia is frequently associated with psychic disorders affecting the cognitive and emotional spheres. In the reported work, we compared 31 female fibromyalgia patients to 31 female healthy controls. They were analyzed for biochemical clinical parameters, for autoimmune markers, and were subjected to 1H-NMR metabolomics analysis. To identify a correlation between the metabolomic profile and the psychic condition, a subset of 19 fibromyalgia patients was subjected to HAM-A and HAM-D Hamilton depression tests. Multivariate statistical analysis showed the dysmetabolism of several metabolites involved in energy balance that are associated with systemic inflammatory conditions. The severity of depression worsens dysmetabolic conditions; conversely, glycine and glutamate, known for their critical role as neuromodulators, appear to be potential biomarkers of fibromyalgia and are associated with different severity depression conditions.

Effect of Very-Low-Calorie Ketogenic Diet on Psoriasis Patients: A Nuclear Magnetic Resonance-Based Metabolomic Study

Psoriasis is an inflammatory disease of the epidermis based on an immunological mechanism involving Langerhans cells and T lymphocytes that produce pro-inflammatory cytokines. Genetic factors, environmental factors, and improper nutrition are considered triggers of the disease. Numerous studies have reported that in a high number of patients, psoriasis is associated with obesity. Excess adipose tissue, typical of obesity, causes a systemic inflammatory status coming from the inflammatory active adipose tissue; therefore, weight reduction is a strategy to fight this pro-inflammatory state. This study aimed to evaluate how a nutritional regimen based on a ketogenic diet influenced the clinical parameters, metabolic profile, and inflammatory state of psoriasis patients. To this end, 30 psoriasis patients were subjected to a ketogenic nutritional regimen and monitored for 4 weeks by evaluating the clinical data, biochemical and clinical parameters, NMR metabolomic profile, and IL-2, IL-1β, TNF-α, IFN-γ, and IL-4 concentrations before and after the nutritional regimen. Our data show that a low-calorie ketogenic diet can be considered a successful strategy and therapeutic option to gain an improvement in psoriasis-related dysmetabolism, with significant correction of the full metabolic and inflammatory status.

A multivariate approach to investigate the NMR CPMG pulse sequence for analysing low MW species in polymers

Detection and quantification of low molecular weight components in polymeric samples via nuclear magnetic resonance (NMR) spectroscopy can be difficult due to overlapping signal caused by line broadening characteristics of polymers. A way of overcoming this problem could be the exploitation of the difference in relaxation between small molecules and macromolecular species, such as the application of a T₂ filter by using the Carr-Purcell-Meiboom-Gill (CPMG) spin-echo pulse sequence. This technique, largely exploited in metabolomics studies, is applied here to material sciences. A Design of Experiments approach was used for evaluating the effect of different acquisition parameters (relaxation delay, echo time and number of cycles) and sample-related ones (concentration and polymer molecular weight) on selected responses, with a particular interest in performing a reliable quantitative analysis. Polymeric samples containing small molecules were analysed by NMR with and without the application of the filter, and analysis of variance was used to identify the most influential parameters. Results indicated that increasing the polymer concentration, hence sample viscosity, further attenuates polymer signals in CPMG experiments because the T₂ of those signals tends to decrease with increasing viscosity. The signal-to-noise ratio measured for small molecules can undergo a minimum loss when specific parameters are chosen in relation to the polymer molecular weight. Furthermore, the difference in dynamics between aliphatic and aromatic nuclei, as well as between mobile and stiff polymers, translates into different results in terms of polymer signal reduction, suggesting that the relaxation filter can also be used for obtaining information on the polymer structure.

Non-Invasive Measurement of Drug and 2-HG Signals Using 19F and 1H MR Spectroscopy in Brain Tumors Treated with the Mutant IDH1 Inhibitor BAY1436032

Simple Summary

Targeted therapies are of growing interest to physicians in cancer treatment. These drugs target specific genes and proteins involved in the growth and survival of cancer cells. Brain tumor therapy is complicated by the fact that not all drugs can penetrate the blood brain barrier and reach their target. We explored the non-invasive method, Magnetic Resonance Spectroscopy, for monitoring drug penetration and its effects in live animals bearing brain tumors. We were able to show the presence of the investigated drug in mouse brains and its on-target activity.

Abstract

Background: BAY1436032 is a fluorine-containing inhibitor of the R132X-mutant isocitrate dehydrogenase (mIDH1). It inhibits the mIDH1-mediated production of 2-hydroxyglutarate (2-HG) in glioma cells. We investigated brain penetration of BAY1436032 and its effects using ¹H/¹⁹F-Magnetic Resonance Spectroscopy (MRS). Methods: ¹⁹F-Nuclear Magnetic Resonance (NMR) Spectroscopy was conducted on serum samples from patients treated with BAY1436032 (NCT02746081 trial) in order to analyze ¹⁹F spectroscopic signal patterns and concentration-time dynamics of protein-bound inhibitor to facilitate their identification in vivo MRS experiments. Hereafter, 30 mice were implanted with three glioma cell lines (LNT-229, LNT-229 IDH1-R132H, GL261). Mice bearing the IDH-mutated glioma cells received 5 days of treatment with BAY1436032 between baseline and follow-up ¹H/¹⁹F-MRS scan. All other animals underwent a single scan after BAY1436032 administration. Mouse brains were analyzed by liquid chromatography-mass spectrometry (LC-MS/MS). Results: Evaluation of ¹H-MRS data showed a decrease in 2-HG/total creatinine (tCr) ratios from the baseline to post-treatment scans in the mIDH1 murine model. Whole brain concentration of BAY1436032, as determined by ¹⁹F-MRS, was similar to total brain tissue concentration determined by Liquid Chromatography with tandem mass spectrometry (LC-MS/MS), with a signal loss due to protein binding. Intratumoral drug concentration, as determined by LC-MS/MS, was not statistically different in models with or without R132X-mutant IDH1 expression. Conclusions: Non-invasive monitoring of mIDH1 inhibition by BAY1436032 in mIDH1 gliomas is feasible.

Correction of Q Factor Effects for Simultaneous Collection of Elemental Analysis and Relaxation Times by Nuclear Magnetic Resonance

A new method for measurement of elemental analysis by nuclear magnetic resonance (NMR) of unknown samples is discussed here as a quick and robust means to measure elemental ratios without the use of internal or external calibration standards. The determination of elemental ratios was done by normalizing the signal intensities by the frequency dependent quality factor (Q) and the gyromagnetic ratios (γ) for each measured nucleus. The correction for the frequency dependence was found by characterizing the output signal of the probe as a function of the quality factor (Q) and the frequency, and the correction for γ was discussed in a previous study. A Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence was used for evaluation of the relative signal intensities, which allows for derivation of elemental ratios, and was correspondingly used to simultaneously measure the T₂* of samples for an added parameter for more accurate identification of unknown samples.

NMR-based metabolomics and fluxomics: developments and future prospects

Recent NMR developments are acting as game changers for metabolomics and fluxomics – a critical and perspective review.

Metabolomics analysis of seminal plasma in patients with idiopathic Oligoasthenoteratozoospermia using high-resolution NMR spectroscopy

BACKGROUND

Male infertility is a global health issue caused by a combination of different factors. Specialists generally rely on semen analysis to diagnose male infertility. However, it is known that diagnostic semen analysis fails to identify about 50% of male infertility disorders. Recently, metabolomics has been proven to be a powerful technique for the diagnosis of different diseases.

OBJECTIVE

To determine whether metabolites could be used as potential biomarkers for the diagnosis of male factor infertility through comparing seminal plasma samples from infertile men with oligoasthenoteratozospermia (OAT) and samples from normozoospermic controls.

MATERIALS AND METHODS

This study utilized high-resolution ¹ H NMR spectroscopy to reveal whether the metabolomic changes of seminal plasma obtained from 31 patients with oligoasthenoteratozospermia (OAT) are different from the ones obtained from 28 normozoospermic controls.

RESULTS

Multivariate statistical analysis of NMR data concluded that the metabolomic profile of samples from patients with OAT exhibits statistically significant differences when compared to the controls. The differences were based on the metabolites lactate, citrate, lysine, arginine, valine, glutamine, creatinine, α-ketoglutaric acid, spermine, putrescine, and tyrosine. Except the tyrosine, levels of the above metabolites were significantly decreased in patients with OAT compared to the controls. The levels of citrate, choline, spermine, putrescine, α-ketoglutaric acid, valine, and tyrosine were significantly different (p < 5 × 10^-4 ) between two groups. On the other hand, levels of lactate, creatinine, lysine, arginine, and glutamine were also statistically significant (0.001 < p < 0.05). However, considering the p-values, the physiological relevance of these metabolites may be lower when compared to the others. A PLS-DA model built on the NMR data achieved 89.29% sensitivity and 93.55% specificity results in a leave-one-out cross-validation process.

DISCUSSION AND CONCLUSION

¹ H NMR spectroscopy-based metabolomic analysis could be used as a diagnostic tool for the diagnosis of oligoasthenoteratozospermia.

Metabolic adaptation to feed restriction on the green sturgeon (Acipenser medirostris) fingerlings

Food restriction may cause severe biological effects on wildlife and lead to population decline and extinction. The objective of the current study was to examine the metabolic effects on green sturgeon in response to feed restriction. Green sturgeon fingerlings were fed for two weeks at 12.5, 25, 50 and 100% of the optimum feeding rate (OFR), which corresponded to 0.25, 0.50, 1.00, and 2.00% body weight per day. We characterized the changes in hydrophilic and hydrophobic metabolites from extracts of muscle, liver, and kidney using nuclear magnetic resonance spectroscopy followed by multivariate statistical analysis. The results of principal component analysis (PCA) score plots from the analyses of hydrophilic metabolites showed that they exhibited a greater response to feed restriction than hydrophobic metabolites. In general, the hydrophilic metabolites in tissues from fish fed ≦25% of the OFR were separated from those fed 100% of the OFR in the PCA score plots. Among the three types of tissues examined, the overall metabolite changes showed a greater response to feed restriction in kidney tissue than in liver or muscle tissues. Numerous glucogenic amino acids in muscle and most amino acids in the kidney were decreased under feed restriction conditions. A significant decrease in ketone bodies (3-hydroxyisobutyrate) was observed in the muscle. Most fatty acids except for glycerol, phospholipid and cholesterol in the liver and kidney tissues were decreased under feed restriction conditions. Creatine phosphate, taurine and glycine were also significantly increased in tissues under feed restriction conditions. In conclusion, this study suggests that the manipulation of feed restriction under the current conditions perturbed metabolites related to energy metabolism, osmolality regulation, and antioxidation capacity in the sturgeon.

Metabolite Profiling of Clinical Cancer Biofluid Samples by NMR Spectroscopy

Metabolomics is a comprehensive characterization of the small polar molecules (metabolites) in different biological systems. One of the analytical platforms commonly used to study metabolic alterations in biofluid samples is proton nuclear magnetic resonance (¹H NMR) spectroscopy. NMR spectroscopy is very specific, quantitative, and highly reproducible. Moreover, sample preparation for NMR experiments is very simple and straightforward, and this gives NMR spectroscopy a distinct advantage over other metabolic profiling methods. It has already been shown that ¹H NMR-based profiling of biological fluids can be effective in differentiating benign from malignant lesions and in investigating the efficacy of specific cancer treatments. Therefore, ¹H NMR spectroscopy may become a promising tool for early noninvasive diagnosis and rapid assessment of treatment effects in cancer patients. Here, we describe a detailed protocol for ¹H NMR metabolite profiling in serum, plasma, and urine samples, including sample collection procedures, sample preparation for ¹H NMR experiments, spectral acquisition and processing, and quantitative profiling of ¹H NMR spectra. We also discuss several aspects of appropriate study design and some multivariate statistical methods that are commonly used to analyze metabolomics datasets.

NMR-Based Prostate Cancer Metabolomics

Prostate cancer is the second most common malignancy, and the fifth leading cause of cancer-related death among men, worldwide. A major unsolved clinical challenge in prostate cancer is the ability to accurately distinguish indolent cancer types from the aggressive ones. Reprogramming of metabolism is now a widely accepted hallmark of cancer development, where cancer cells must be able to convert nutrients to biomass while maintaining energy production. Metabolomics is the large-scale study of small molecules, commonly known as metabolites, within cells, biofluids, tissues, or organisms. Nuclear magnetic resonance (NMR) spectroscopy is commonly applied in metabolomics studies of cancer. This chapter provides protocols for NMR-based metabolomics of cell cultures, biofluids (serum and urine), and intact tissue, with concurrent advice for optimal biobanking and sample preparation procedures.

Metabolomic characterization of experimental ovarian cancer ascitic fluid

INTRODUCTION

Malignant ascites (MA) is a major cause of morbidity that occurs in 37% of ovarian cancer patients. The accumulation of MA in the peritoneal cavity due to cancer results in debilitating symptoms and extremely poor quality of life. There is an urgent unmet need to expand the understanding of MA to design effective treatment strategies, and to improve MA diagnosis.

OBJECTIVE

Our purpose here is to contribute to a better characterization of MA metabolic composition in ovarian cancer.

METHOD

We determined the metabolic composition of ascitic fluids resulting from orthotopic growth of two ovarian cancer cell lines, the mouse ID8-vascular endothelial growth factor (VEGF)-Defb29 cell line and the human OVCAR3 cell line using high-resolution ¹H MRS. ID8-VEGF-Defb29 tumors induce large volumes of ascites, while OVCAR3 tumors induce ascites less frequently and at smaller volumes. To better understand the factors driving the metabolic composition of the fluid, we characterized the metabolism of these ovarian cancer cells in culture by analyzing cell lysates and conditioned culture media with ¹H NMR.

RESULTS

Distinct metabolite patterns were detected in ascitic fluid collected from OVCAR3 and ID8-VEGF-Defb29 tumor bearing mice that were not reflected in the corresponding cell culture or conditioned medium.

CONCLUSION

High-resolution ¹H NMR metabolic markers of MA can be used to improve characterization and diagnosis of MA. Metabolic characterization of MA can provide new insights into how MA fluid supports cancer cell growth and resistance to treatment, and has the potential to identify metabolic targeting strategies to reduce or eliminate the formation of MA.

Unravelling and Quantifying the "NMR-Invisible" Metabolites Interacting with Human Serum Albumin by Binding Competition and T2 Relaxation-Based Decomposition Analysis

Quantitative profiling of low-molecular-weight metabolites (LMWMs) by ¹H NMR is routinely used in high-throughput serum metabolomics. First, the protein background is attenuated using a T2 filter; then, the LMWM signals are resolved by line-shape fitting. However, protein-binding modifies the motional properties of LMWM, and their signal partially attenuates with the T2 filter, along with the protein background. Consequently, the quantified LMWM signals do not reflect the total concentration in serum but the nonbinding part. Here we present a novel strategy based on binding competition to promote the release of the "NMR-invisible" metabolites from serum proteins and achieve quantifications closer to total concentrations. The study focuses on five clinically relevant amino acids with different binding properties (valine, isoleucine, leucine, tyrosine, and phenylalanine). We analyzed their binding affinity to human serum albumin (HSA) in serum mimic samples and promoted the release of their bound fraction by TSP titration. Furthermore, we used a novel combination of pseudo-2D CPMG and multivariate curve resolution analysis, allowing the separation of LMWM and protein signals and providing LMWM quantifications corrected for transverse relaxation effects. We found that TSP concentrations larger than 3 mM released most of the bound fraction and validated these findings in real serum/plasma samples.

Quantification of Metabolites by NMR Spectroscopy in the Presence of Protein

The high reliability of NMR spectroscopy makes it an ideal tool for large-scale metabolomic studies. However, the complexity of biofluids and, in particular, the presence of macromolecules poses a significant challenge. Ultrafiltration and protein precipitation are established means of deproteinization and recovery of free or total metabolite content, but neither is ever complete. In addition, aside from cost and labor, all deproteinization methods constitute an additional source of experimental variation. The Carr-Purcell-Meiboom-Gill (CPMG) echo-train acquisition of NMR spectra obviates the need for prior deproteinization by attenuating signals from macromolecules, but concentration values of metabolites measured in blood plasma will not necessarily reflect total or free metabolite content. Here, in contrast to approaches that propose the determination of individual T₁ and T₂ relaxation times for the computation of correction factors, we demonstrate their determination by spike-in experiments with known amounts of metabolites in pooled samples of the matrix of interest to facilitate the measurement of total metabolite content. Provided that the protein content does not vary too much among individual samples, accurate quantitation of metabolites is feasible. Moreover, samples with significantly deviating protein content may be readily recognized by inclusion of a standard that shows moderate protein binding. It is also shown that urinary proteins when present in high concentrations may effect detection of common urinary metabolites prone to strong protein binding such as tryptophan.

N-Confused porphyrins: complexation and 1H NMR studies

The complexation of 2-aza-21-carba-tetraphenylporphyrin and 2-aza-2-methyl-5,10,15,20-tetraphenyl-21-carbaporphyrin with nickel and zinc acetates in organic solvents has been investigated by UV-Vis spectroscopy and ¹H NMR.

Melanin and humic acid-like polymer complex from olive mill waste waters. Part I. Isolation and characterization

A water soluble humic acid and melanin-like polymer complex (OMWW-ASP) was isolated from olive mill waste waters (OMWW) by ammonium sulfate fractionation to be used as natural additive in food preparations. The dark polymer complex was further characterized by a variety of biochemical, physicochemical and spectroscopic techniques. OMWW-ASP is composed mainly of proteins associated with polyphenols and carbohydrates and the distribution of its relative molecular size was determined between about 5 and 190 kDa. SDS-PAGE shows the presence of a well separated protein band of 21.3 kDa and a low molecular weight peptide. The OMWW-ASP complex exhibits a monotonically increasing UV-Vis absorption spectrum and it contains stable radicals. Antioxidant activity measurements reveal the ability of the OMWW protein fraction to scavenge both the cationic 2,2'-azino-bis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS(+)) radical, as well as the stable nitroxide free radical 4-hydroxy-2,2,6,6-tetramethylpiperidine 1-oxyl (TEMPOL).

Magnetic Resonance Spectroscopy: Principles and Techniques: Lessons for Clinicians

Magnetic resonance spectroscopy (MRS) provides a non-invasive 'window' on biochemical processes within the body. Its use is no longer restricted to the field of research, with applications in clinical practice increasingly common. MRS can be conducted at high magnetic field strengths (typically 11-14 T) on body fluids, cell extracts and tissue samples, with new developments in whole-body magnetic resonance imaging (MRI) allowing clinical MRS at the end of a standard MRI examination, obtaining functional information in addition to anatomical information. We discuss the background physics the busy clinician needs to know before considering using the technique as an investigative tool. Some potential applications of hepatic and cerebral MRS in chronic liver disease are also discussed.

Metabolomics of meat exudate: Its potential to evaluate beef meat conservation and aging

In this study we analyzed the exudate of beef to evaluate its potential as non invasive sampling for nuclear magnetic resonance (NMR) based metabolomic analysis of meat samples. Exudate, as the natural juice from raw meat, is an easy to obtain matrix that it is usually collected in small amounts in commercial meat packages. Although meat exudate could provide complete and homogeneous metabolic information about the whole meat piece, this sample has been poorly studied. Exudates from 48 beef samples of different breeds, cattle and storage times have been studied by (1)H NMR spectroscopy. The liquid exudate spectra were compared with those obtained by High Resolution Magic Angle Spinning (HRMAS) of the original meat pieces. The close correlation found between both spectra (>95% of coincident peaks in both registers; Spearman correlation coefficient = 0.945) lead us to propose the exudate as an excellent alternative analytical matrix with a view to apply meat metabolomics. 60 metabolites could be identified through the analysis of mono and bidimensional exudate spectra, 23 of them for the first time in NMR meat studies. The application of chemometric tools to analyze exudate dataset has revealed significant metabolite variations associated with meat aging. Hence, NMR based metabolomics have made it possible both to classify meat samples according to their storage time through Principal Component Analysis (PCA), and to predict that storage time through Partial Least Squares (PLS) regression.

The future of NMR metabolomics in cancer therapy: towards personalizing treatment and developing targeted drugs?

There has been a recent shift in how cancers are defined, where tumors are no longer simply classified by their tissue origin, but also by their molecular characteristics. Furthermore, personalized medicine has become a popular term and it could start to play an important role in future medical care. However, today, a "one size fits all" approach is still the most common form of cancer treatment. In this mini-review paper, we report on the role of nuclear magnetic resonance (NMR) metabolomics in drug development and in personalized medicine. NMR spectroscopy has successfully been used to evaluate current and potential therapies, both single-agents and combination therapies, to analyze toxicology, optimal dose, resistance, sensitivity, and biological mechanisms. It can also provide biological insight on tumor subtypes and their different responses to drugs, and indicate which patients are most likely to experience off-target effects and predict characteristics for treatment efficacy. Identifying pre-treatment metabolic profiles that correlate to these events could significantly improve how we view and treat tumors. We also briefly discuss several targeted cancer drugs that have been studied by metabolomics. We conclude that NMR technology provides a key platform in metabolomics that is well-positioned to play a crucial role in realizing the ultimate goal of better tailored cancer medicine.

Metabolite analysis of biological fluids and tissues by proton nuclear magnetic resonance spectroscopy

NMR-based biochemical profiling of natural products has become popular due to the development of high-resolution instruments (>400 MHz) and cryogenically cooled probes/preamplifiers, by increasing the sensitivity of NMR instruments several fold and reducing instrument noise levels. NMR provides a rapid, nondestructive, high-throughput method that requires minimal sample preparation, therefore maintaining the biological integrity of the sample. One-dimensional (1D) solution-state (1)H NMR is used in untargeted sample screening (metabolomics/metabonomics) to gain insight into spectral pattern changes associated with samples of different origins. Metabolomics and metabonomics contextually explains the systematic and quantitative measurement of metabolites that are produced from the biochemical reactions of living systems. This chapter describes some commonly used (1)H NMR experiments for identification and quantification of small molecular weight, water soluble metabolites in biological samples, some considerations for choosing the correct NMR experiment, and sample preparation protocols for isolating metabolites from a number of biological sample types.

¹H NMR-based metabolomics approach to assess toxicity of bunker a heavy oil to freshwater carp, Cyprinus carpio

Using a ¹H NMR metabolomics approach, the effects of dietary exposure of bunker A heavy oil (0.01, 0.1, 1, and 5% in diet) on freshwater carp, Cyprinus carpio, were examined. Statistical analysis by PCA score plots showed that the amount of metabolites in exposure groups 0.1, 1, and 5% differed from those in the control group. Although no discernible effects on metabolites were noted in the 0.1% exposure group as well as in the lowest concentration (0.01%) group, several metabolites such as amino acid (e.g., leucine, isoleucine, valine, glutamine, histidine, proline, and methionine), 3-D-hydroxybutyrate, and glycerol were elevated, while another metabolite such as formate was reduced in 1 and 5% groups. These changes in the metabolites associated with the tri-carboxylic-acid (TCA) cycle suggest that oil exposure resulted in the disturbance of the TCA cycle in the liver of the carp. Isobutyrate, a marker of anoxia, was also increased in 1 and 5% exposures groups and was directly related to low hemoglobin concentrations leading to reduced oxygen transport by blood. In addition, significant elevation of creatinine in the plasma of carps exposed to 5% heavy oil suggests disturbance in kidney function. Thus, metabolomics approach can detect toxic effects of hazardous pollutants on fish.

A sample preparation protocol for 1H nuclear magnetic resonance studies of water-soluble metabolites in blood and urine

We describe a general protocol for preparing protein-containing biofluids for (1)H nuclear magnetic resonance (NMR) metabolomic studies. In this protocol, untreated samples are diluted in deuterated solvents to precipitate proteins and recover metabolites quantitated relative to standard reference compounds such as 3-trimethylsilylpropionic acid (TSP) and 2,2-dimethyl-2-silapentane-5-sulfonic acid (DSS). The efficacy of this protocol was tested using a bovine serum albumin/metabolite mix and human serum samples. This sample preparation method can be readily applied to any protein-containing biofluid for (1)H NMR studies.

Investigation of chemometric instrumental transfer methods for high-resolution NMR

The implementation of direct standardization (DS), piecewise direct standardization (PDS), and double-window piecewise direct standardization (DWPDS) instrumental transfer techniques for high-resolution (1)H NMR spectral data was explored. The ability to transfer a multivariate calibration model developed for a "master or target" NMR instrument configuration to seven different ("secondary") NMR instrument configurations was measured. Partial least-squares (PLS) calibration of glucose, glycine, and citrate metabolite relative concentrations in model mixtures following mapping of the secondary instrumental configurations using DS, PDS, or DWPDS instrumental transfer allowed the performance of the different transfer methods to be assessed. Results from these studies suggest that DS and PDS transfer techniques produce similar improvements in the error of prediction compared to each other and provide a significant improvement over standard spectral preprocessing techniques including reference deconvolution and spectral binning. The DS instrumental transfer method produced the largest percent improvement in the predictions of concentrations for these model mixtures but, in general, required that additional transfer calibration standards be used. Limitations of the different instrumental transfer methods with respect to sample subset selection are also discussed.

Validation of 1H NMR spectroscopy as an analytical tool for methylamine metabolites in urine

BACKGROUND

Methylamines have many metabolic roles and there is an increasing demand for their measurement. Glycine betaine is an important osmolyte, and a reservoir for methyl groups. Proline betaine and trigonelline are important dietary betaines. Trimethylamine, derived from gut flora, is normally converted to trimethylamine oxide but in 'fish odour syndrome' is excreted as TMA. These compounds are all suitable for quantification by (1)H NMR spectroscopy as they all have methyl protons.

METHOD

Urine samples are acidified and (1)H NMR spectra are obtained using presaturation for water suppression. Peak integrals or heights are compared to an internal standard of acetonitrile.

RESULTS

Inter- and intra-assay CV's were <5% for TMAO and creatinine, and <10% for the other analytes. Responses were linear from 50 to 1000 microM for all metabolites, and recoveries were > or =97%. Limits of detection using NMR are slightly higher than alternative HPLC assays (15-25 microM). However, sensitivity is adequate for the detection of raised levels in urine, and sample analysis was complete in less than 5 min.

CONCLUSION

(1)H NMR spectroscopy is a convenient, rapid and economical option for the determination of betaines and related compounds in urine in a single analysis.

Tissue targeted metabonomics: metabolic profiling by microdialysis sampling and microcoil NMR

The concentration of low molecular weight compounds in tissues can yield valuable information about the metabolic state of an organism. Studies of changes in the metabolic state or metabonomics can reflect disease pathways, drug action, or toxicity. This research aims to develop a new approach, tissue targeted metabonomics. Microdialysis sampling and microcoil NMR analysis are employed to compare basal and ischemic metabolic states of various tissues (blood, brain, and heart) of Sprague-Dawley rats. Microdialysis sampling is localized, making the metabolic profile tissue specific. Coupling to NMR analysis is highly advantageous, because a complete metabolic profile is obtained in a single spectrum. However, small sample volumes and low analyte concentrations make analysis of microdialysis samples challenging. Microcoil NMR uses low sample volumes and has improved mass sensitivity, relative to standard 5 mm probes. The coupling of these techniques is a potentially powerful tool for metabonomics analysis.

Progress toward automated metabolic profiling of human serum: Comparison of CPMG and gradient-filtered NMR analytical methods

The investigation of drug delivery and metabolism requires the analysis of molecules in complicated biological matrices such as human serum. In NMR-based metabonomic analysis, T(2) relaxation editing with a CPMG filter is commonly used to suppress background signals from proteins and other endogenous components. Radio frequency pulse imperfections and incomplete irradiation across the spectral bandwidth can cause phase and baseline distortions in CPMG spectra. These distortions are exacerbated by water suppression techniques. Baseline correction methods included in commercially available data processing software packages may be incapable of producing artifact-free spectra. To increase the analytical precision of metabolic profiling, one NMR spectroscopist may be responsible for manually phasing and baseline correcting hundreds of spectra individually to remove operator-dependent variations, significantly reducing throughput. For metabonomic analysis of human serum, it was observed that the application of a pulsed field gradient filter produced (1)H NMR spectra well suited to automatic phasing routines. Superior baseline characteristics, an increased tolerance to radio frequency pulse imperfections, and improved water suppression were achieved. A concomitant reduction in signal intensity compared with the CPMG method was easily recovered by increasing the number of scans. Principal component analysis (PCA) of spectra, acquired under a variety of experimental conditions, revealed the improved reproducibility and robustness of (1)H NMR pulsed field gradient-filtered metabonomic analyses of serum compared to the CPMG method.

Measuring the metabolome: current analytical technologies

The post-genomics era has brought with it ever increasing demands to observe and characterise variation within biological systems. This variation has been studied at the genomic (gene function), proteomic (protein regulation) and the metabolomic (small molecular weight metabolite) levels. Whilst genomics and proteomics are generally studied using microarrays (genomics) and 2D-gels or mass spectrometry (proteomics), the technique of choice is less obvious in the area of metabolomics. Much work has been published employing mass spectrometry, NMR spectroscopy and vibrational spectroscopic techniques, amongst others, for the study of variations within the metabolome in many animal, plant and microbial systems. This review discusses the advantages and disadvantages of each technique, putting the current status of the field of metabolomics in context, and providing examples of applications for each technique employed.