Effect of pH on 1H-NMR Spectroscopy of Mouse Urine

NMR-Based Urinary Metabolomics Applications

The field of metabolomics has been growing tremendously over the recent years and, consistent with that growth, a number of investigators have been looking at the potential of NMR-based urinary metabolomics for several applications. While such applications have shown promising results, there still remains an enormous amount of work to be done before this approach becomes accepted and widely used in clinical diagnostics and other biomedical applications. To achieve such goals, optimization of parameters and standardization of protocols are of paramount importance. In view of this, in this chapter, we present some recommended methods and procedures that can help researchers in the field. Furthermore, we have highlighted some of the challenges encountered in such applications and suggested some possible ways to overcome those challenges.

The value of universally available raw NMR data for transparency, reproducibility, and integrity in natural product research

Covering: up to 2018With contributions from the global natural product (NP) research community, and continuing the Raw Data Initiative, this review collects a comprehensive demonstration of the immense scientific value of disseminating raw nuclear magnetic resonance (NMR) data, independently of, and in parallel with, classical publishing outlets. A comprehensive compilation of historic to present-day cases as well as contemporary and future applications show that addressing the urgent need for a repository of publicly accessible raw NMR data has the potential to transform natural products (NPs) and associated fields of chemical and biomedical research. The call for advancing open sharing mechanisms for raw data is intended to enhance the transparency of experimental protocols, augment the reproducibility of reported outcomes, including biological studies, become a regular component of responsible research, and thereby enrich the integrity of NP research and related fields.

Diagnostic Applications of Nuclear Magnetic Resonance-Based Urinary Metabolomics

Metabolomics is a rapidly growing field with potential applications in various disciplines. In particular, metabolomics has received special attention in the discovery of biomarkers and diagnostics. This is largely due to the fact that metabolomics provides critical information related to the downstream products of many cellular and metabolic processes which could provide a snapshot of the health/disease status of a particular tissue or organ. Many of these cellular products eventually find their way to urine; hence, analysis of urine via metabolomics has the potential to yield useful diagnostic and prognostic information. Although there are a number of analytical platforms that can be used for this purpose, this review article will focus on nuclear magnetic resonance-based metabolomics. Furthermore, although there have been many studies addressing different diseases and metabolic disorders, the focus of this review article will be in the following specific applications: urinary tract infection, kidney transplant rejection, diabetes, some types of cancer, and inborn errors of metabolism. A number of methodological considerations that need to be taken into account for the development of a clinically useful optimal test are discussed briefly.

NMR Chemical Shift Ranges of Urine Metabolites in Various Organic Solvents

Signal stability is essential for reliable multivariate data analysis. Urine samples show strong variance in signal positions due to inter patient differences. Here we study the exchange of the solvent of a defined urine matrix and how it affects signal and integral stability of the urinary metabolites by NMR spectroscopy. The exchange solvents were methanol, acetonitrile, dimethyl sulfoxide, chloroform, acetone, dichloromethane, and dimethyl formamide. Some of these solvents showed promising results with a single batch of urine. To evaluate further differences between urine samples, various acid, base, and salt solutions were added in a defined way mimicking to some extent inter human differences. Corresponding chemical shift changes were monitored.

Recent developments in sample preparation and data pre-treatment in metabonomics research

Metabonomics is a powerful approach for biomarker discovery and an effective tool for pinpointing endpoint metabolic effects of external stimuli, such as pathogens and disease development. Due to its wide applications, metabonomics is required to deal with various biological samples of different properties. Hence sample preparation and corresponding data pre-treatment become important factors in ensuring validity of an investigation. In this review, we summarize some recent developments in metabonomics sample preparation and data-pretreatment procedures.

MetaboQuant: a tool combining individual peak calibration and outlier detection for accurate metabolite quantification in 1D (1)H and (1)H-(13)C HSQC NMR spectra

Solution nuclear magnetic resonance (NMR) spectroscopy is widely used to analyze complex mixtures of organic compounds such as biological fluids and tissue extracts. Targeted profiling approaches with reliable compound quantitifcation are hampered, however, by signal overlap and other interferences. Here, we present a tool named MetaboQuant for automated compound quantification from pre-processed 1D and 2D heteronuclear single quantum coherence (HSQC) NMR spectral data and concomitant validation of results. Performance of MetaboQuant was tested on a urinary spike-in data set and compared with other quantification strategies. The use of individual calibration factors in combination with the validation algorithms of MetaboQuant raises the reliability of the quantification results. MetaboQuant can be downloaded at http://genomics.uni-regensburg.de/site/institute/software/metaboquant/ as stand-alone software for Windows or run on other operating systems from within Matlab. Separate software for peak fitting and integration is necessary in order to use MetaboQuant.

Reproducibility of NMR analysis of urine samples: impact of sample preparation, storage conditions, and animal health status

Introduction. Spectroscopic analysis of urine samples from laboratory animals can be used to predict the efficacy and side effects of drugs. This employs methods combining ¹H NMR spectroscopy with quantification of biomarkers or with multivariate data analysis. The most critical steps in data evaluation are analytical reproducibility of NMR data (collection, storage, and processing) and the health status of the animals, which may influence urine pH and osmolarity. Methods. We treated rats with a solvent, a diuretic, or a nephrotoxicant and collected urine samples. Samples were titrated to pH 3 to 9, or salt concentrations increased up to 20-fold. The effects of storage conditions and freeze-thaw cycles were monitored. Selected metabolites and multivariate data analysis were evaluated after ¹H NMR spectroscopy. Results. We showed that variation of pH from 3 to 9 and increases in osmolarity up to 6-fold had no effect on the quantification of the metabolites or on multivariate data analysis. Storage led to changes after 14 days at 4°C or after 12 months at −20°C, independent of sample composition. Multiple freeze-thaw cycles did not affect data analysis. Conclusion. Reproducibility of NMR measurements is not dependent on sample composition under physiological or pathological conditions.

NMR-Based Milk Metabolomics

Milk is a key component in infant nutrition worldwide and, in the Western parts of the world, also in adult nutrition. Milk of bovine origin is both consumed fresh and processed into a variety of dairy products including cheese, fermented milk products, and infant formula. The nutritional quality and processing capabilities of bovine milk is closely associated to milk composition. Metabolomics is ideal in the study of the low-molecular-weight compounds in milk, and this review focuses on the recent nuclear magnetic resonance (NMR)-based metabolomics trends in milk research, including applications linking the milk metabolite profiling with nutritional aspects, and applications which aim to link the milk metabolite profile to various technological qualities of milk. The metabolite profiling studies encompass the identification of novel metabolites, which potentially can be used as biomarkers or as bioactive compounds. Furthermore, metabolomics applications elucidating how the differential regulated genes affects milk composition are also reported. This review will highlight the recent advances in NMR-based metabolomics on milk, as well as give a brief summary of when NMR spectroscopy can be useful for gaining a better understanding of how milk composition is linked to nutritional or quality traits.

Eliminating the dication-induced intersample chemical-shift variations for NMR-based biofluid metabonomic analysis

NMR-based urinary metabonomic analysis is an essential aspect of systems biology for understanding mammalian physiology and pathophysiology though intersample chemical-shift variations can cause serious problems. Here, we report two optimized and validated methods to eliminate such variations resulting from intersample differences in pH and dication concentration. We found that the Ca(2+) concentration was 7.41 ± 3.48, 1.03 ± 0.34 and 0.87 ± 0.52 mM whereas the Mg(2+) concentration was 3.02 ± 1.41, 2.65 ± 1.20 and 0.80 ± 0.59 mM in rat, mouse and human urine samples, respectively; urinary Ca-EDTA, Mg-EDTA and free EDTA had spin-lattice relaxation time values (600.13 MHz) of 0.38, 0.41 and 0.55 s, respectively. We also found that the combined treatments with potassium fluoride, phosphate buffer and a small amount of K(3)EDTA eliminated intersample chemical-shift variations for all metabolites. EDTA treatment followed with phosphate buffer also achieved similar results although resonances from EDTA and its complexes obscured some metabolite signals. We systematically optimized the amount of additives for rat, mouse and human urine samples taking into consideration the pH control, signal-to-noise ratio and intersample uniformity for metabolite chemical-shifts. Based on thorough validation, we established some optimized procedures for rat, mouse and human urine, respectively. By eliminating both pH and dication effects, these methods enable the reduction of intersample chemical-shift variations to 1.5 Hz for all metabolites. The methods will offer ensured data quality for high-throughput, especially robotic urinary metabonomics studies with no need for peak alignments or corrections.

NMR-based metabonomics analysis of mouse urine and fecal extracts following oral treatment with the broad-spectrum antibiotic enrofloxacin (Baytril)

The human gastrointestinal tract is home to hundreds of species of bacteria and the balance between beneficial and pathogenic bacteria plays a critical role in human health and disease. The human infant, however, is born with a sterile gut and the complex gastrointestinal host/bacterial ecosystem is only established after birth by rapid bacterial colonization. Composition of newborn gut flora depends on several factors including type of birth (Ceasarian or natural), manner of early feeding (breast milk or formula), and exposure to local, physical environment. Imbalance in normal, healthy gut flora contributes to several adult human diseases including inflammatory bowel (ulcerative colitis and Crohn's disease) and Clostridium difficile associated disease, and early childhood diseases such as necrotizing enterocolitis. As a first step towards characterization of the role of gut bacteria in human health and disease, we conducted an 850 MHz (1)H nuclear magnetic resonance spectroscopy study to monitor changes in metabolic profiles of urine and fecal extracts of 15 mice following gut sterilization by the broad-spectrum antibiotic enrofloxacin (also known as Baytril). Ten metabolites changed in urine following enrofloxacin treatment including decreased acetate due to loss of microbial catabolism of sugars and polysaccharides, decreased trimethylamine-N-oxide due to loss of microbial catabolism of choline, and increased creatine and creatinine due to loss of microbial enzyme degradation. Eight metabolites changed in fecal extracts of mice treated with enrofloxacin including depletion of amino acids produced by microbial proteases, reduction in metabolites generated by lactate-utilizing bacteria, and increased urea caused by loss of microbial ureases.

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.