Advances in NMR-based biofluid analysis and metabolite profiling

Complex I, V, and MDH2 deficient human skin fibroblasts reveal distinct metabolic signatures by 1 H HR-MAS NMR

In this study, we investigated the metabolic signatures of different mitochondrial defects (two different complex I and complex V, and the one MDH2 defect) in human skin fibroblasts (HSF). We hypothesized that using a selective culture medium would cause defect specific adaptation of the metabolome and further our understanding of the biochemical implications for the studied defects. All cells were cultivated under galactose stress condition and compared to glucose-based cell culture condition. We investigated the bioenergetic profile using Seahorse XFe96 cell analyzer and assessed the extracellular metabolic footprints and the intracellular metabolic fingerprints using NMR. The galactose-based culture condition forced a bioenergetic switch from a glycolytic to an oxidative state in all cell lines which improved overall separation of controls from the different defect groups. The extracellular metabolome was discriminative for separating controls from defects but not the specific defects, whereas the intracellular metabolome suggests CI and CV changes and revealed clear MDH2 defect-specific changes in metabolites associated with the TCA cycle, malate aspartate shuttle, and the choline metabolism, which are pronounced under galactose condition.

Identification of Novel Biomarkers in Late Preterm Neonates with Respiratory Distress Syndrome (RDS) Using Urinary Metabolomic Analysis

Urine metabolomics is gaining traction as a means of identifying metabolic signatures associated with health and disease states. Thirty-one (31) late preterm (LP) neonates admitted to the neonatal intensive care unit (NICU) and 23 age-matched healthy LPs admitted to the maternity ward of a tertiary hospital were included in the study. Proton nuclear magnetic resonance (¹H NMR) spectroscopy was employed for urine metabolomic analysis on the 1st and 3rd days of life of the neonates. The data were analyzed using univariate and multivariate statistical analysis. A unique metabolic pattern of enhanced metabolites was identified in the NICU-admitted LPs from the 1st day of life. Metabolic profiles were distinct in LPs presenting with respiratory distress syndrome (RDS). The discrepancies likely reflect differences in the gut microbiota, either due to variations in nutrient intake or as a result of medical interventions, such as the administration of antibiotics and other medications. Altered metabolites could potentially serve as biomarkers for identifying critically ill LP neonates or those at high risk for adverse outcomes later in life, including metabolic risks. The discovery of novel biomarkers may uncover potential targets for drug discovery and optimal periods for effective intervention, offering a personalized approach.

Serum metabolomic profiling identifies potential biomarkers in arthritis in older adults: an exploratory study

BACKGROUND

Seronegative elderly-onset rheumatoid arthritis (EORA)^neg and polymyalgia rheumatica (PMR) have similar clinical characteristics making them difficult to distinguish based on clinical features. We hypothesized that the study of serum metabolome could identify potential biomarkers of PMR vs. EORA^neg.

METHODS

Arthritis in older adults (ARTIEL) is an observational prospective cohort with patients older than 60 years of age with newly diagnosed arthritis. Patients' blood samples were compared at baseline with 18 controls. A thorough clinical examination was conducted. A Bruker Avance 600 MHz spectrometer was used to acquire Nuclear Magnetic Resonance (NMR) spectra of serum samples. Chenomx NMR suite 8.5 was used for metabolite identification and quantification.Student t-test, one-way ANOVA, binary linear regression and ROC curve, Pearson's correlation along with pathway analyses were conducted.

RESULTS

Twenty-eight patients were diagnosed with EORA^neg and 20 with PMR. EORA^neg patients had a mean disease activity score (DAS)-Erythrocyte Sedimentation Rate (ESR) of 6.21 ± 1.00. All PMR patients reported shoulder pain, and 90% reported pelvic pain. Fifty-eight polar metabolites were identified. Of these, 3-hydroxybutyrate, acetate, glucose, glycine, lactate, and o-acetylcholine (o-ACh), were significantly different between groups. Of interest, IL-6 correlated with different metabolites in PMR and EORA^neg suggesting different inflammatory activated pathways. Finally, lactate, o-ACh, taurine, and sex (female) were identified as distinguishable factors of PMR from EORA^neg with a sensitivity of 90%, specificity of 92.3%, and an AUC of 0.925 (p < 0.001).

CONCLUSION

These results suggest that EORA^neg and PMR have different serum metabolomic profiles that might be related to their pathobiology and can be used as biomarker to discriminate between both diseases.

Potential of in vitro nuclear magnetic resonance of biofluids and tissues in clinical research

Body fluids, cells, and tissues contain a wide variety of metabolites that consist of a mixture of various low-molecular-weight compounds, including amino acids, peptides, lipids, nucleic acids, and organic acids, which makes comprehensive analysis more difficult. Quantitative nuclear magnetic resonance (NMR) spectroscopy is a well-established analytical technique for analyzing the metabolic profiles of body fluids, cells, and tissues. It enables fast and comprehensive detection, characterization, a high level of experimental reproducibility, minimal sample preparation, and quantification of various endogenous metabolites. In recent times, NMR-based metabolomics has been appreciably utilized in diverse branches of medicine, including microbiology, toxicology, pathophysiology, pharmacology, nutritional intervention, and disease diagnosis/prognosis. In this review, the utility of NMR-based metabolomics in clinical studies is discussed. The significance of in vitro NMR-based metabolomics as an effective tool for detecting metabolites and their variations in different diseases are discussed, together with the possibility of identifying specific biomarkers that can contribute to early detection and diagnosis of disease.

Qualitative and Quantitative Mass Spectrometry in Salivary Metabolomics and Proteomics

The metabolomics and proteomics analysis of saliva, an excellent biofluid that is a rich source of biological compounds, allows for the safe and frequent screening of drugs, their metabolites, and molecular biomarkers of various diseases. One of the most frequently used analytical methods in saliva analysis is liquid chromatography coupled with mass spectrometry (LC-MS) and tandem mass spectrometry. The low ionisation efficiency of some compounds and a complex matrix makes their identification by MS difficult. Furthermore, quantitative analysis by LC-MS frequently cannot be performed without isotopically labelled standards, which usually have to be specially synthesised. This review presented reports on qualitative and quantitative approaches in salivary metabolomics and proteomics. The purpose of this manuscript was to present the challenges, advances, and future prospects of mass spectrometry, both in the analysis of salivary metabolites and proteins. The presented review should appeal to those interested in the recent advances and trends in qualitative and quantitative mass spectrometry in salivary metabolomics and proteomics, which may facilitate a diagnostic accuracy, the evaluation of treatment efficacy, the early diagnosis of disease, and a forensic investigation of some unapproved drugs for any medical or dietary administration.

Computational simulation of 1 H NMR profiles of complex biofluid analyte mixtures at differential operating frequencies: Applications to low-field benchtop spectra

Estimations of accurate and reliable NMR chemical shift values, coupling patterns and constants within a reasonable timeframe remain significantly challenging, and the unavailability of reliable software strategies for the prediction of low-field (e.g., 60 MHz) spectra from those acquired at higher operating frequencies hampers their direct comparison. Hence, this study explored the applications of accessible software options for predicting these parameters in the ¹ H NMR profiles of analytes as a function of magnetic field strength; this was performed for individual analytes and also for complex biofluid matrices featured in metabolomics investigations. For this purpose, results from the very first successful experimental acquisition and simulation of the ¹ H NMR profiles of intact human salivary supernatant samples on a 60 MHz benchtop spectrometer were evaluated. Using salivary metabolite concentrations determined at 400 MHz, it was demonstrated that simulation of the low-field spectra of five biomolecules with the most prominent ¹ H resonances detectable allowed multiple component fits to be applied to experimental spectra. Hence, these salivary ¹ H NMR profiles could be successfully predicted throughout the 45-600 MHz operating frequency range. With the exception of propionate resonance multiplets, which revealed more complex coupling patterns at low field and required more astute computational and fitting options, valuable quantitative metabolomics data on salivary acetate, formate, methanol and glycine could be attained from low-field spectrometres. These studies are both timely and pertinent in view of the recent advancement of low-field benchtop NMR facilities for diagnostically significant biomarker tracking in biofluids. Experiments performed with added ammonium chloride to facilitate the release of salivary metabolites from biopolymer binding sites provided evidence that a small but nevertheless significant proportion of propionate, but not lactate, was bound to such sites, an observation of much relevance to biomolecule quantification in salivary metabolomics investigations.

Fine optimization of a dissolution dynamic nuclear polarization experimental setting for 13C NMR of metabolic samples

NMR-based analysis of metabolite mixtures provides crucial information on biological systems but mostly relies on 1D 1 H experiments for maximizing sensitivity. However, strong peak overlap of 1 H spectra often is a limitation for the analysis of inherently complex biological mixtures. Dissolution dynamic nuclear polarization (d-DNP) improves NMR sensitivity by several orders of magnitude, which enables 13 C NMR-based analysis of metabolites at natural abundance. We have recently demonstrated the successful introduction of d-DNP into a full untargeted metabolomics workflow applied to the study of plant metabolism. Here we describe the systematic optimization of d-DNP experimental settings for experiments at natural 13 C abundance and show how the resolution, sensitivity, and ultimately the number of detectable signals improve as a result. We have systematically optimized the parameters involved (in a semi-automated prototype d-DNP system, from sample preparation to signal detection, aiming at providing an optimization guide for potential users of such a system, who may not be experts in instrumental development). The optimization procedure makes it possible to detect previously inaccessible protonated 13 C signals of metabolites at natural abundance with at least 4 times improved line shape and a high repeatability compared to a previously reported d-DNP-enhanced untargeted metabolomic study. This extends the application scope of hyperpolarized 13 C NMR at natural abundance and paves the way to a more general use of DNP-hyperpolarized NMR in metabolomics studies.

Targeted Metabolomics Using LC-MS in Neurospora crassa

The filamentous fungus Neurospora crassa has historically been a model for understanding the relationship between genes and metabolism-auxotrophic mutants of N. crassa were used by Beadle and Tatum to develop the one-gene-one-enzyme hypothesis for which they earned the Nobel Prize in 1958. In the ensuing decades, several techniques have been developed for the systematic analysis of metabolites in N. crassa and other fungi. Untargeted and targeted approaches have been used, with a focus on secondary metabolites over primary metabolism. Here, we describe a pipeline for sample preparation, metabolite extraction, Liquid Chromatography-Mass Spectrometry (LC-MS), and data analysis that can be used for targeted metabolomics of primary metabolites in N. crassa. Liquid cultures are grown with shaking in a defined minimal medium and then collected using filtration. Samples are lyophilized for 2 days at -80°C, pulverized, and mixed with a solution to extract polar metabolites. The metabolites are separated and identified using LC-MS, with downstream analysis using Skyline interpretive software. Relative levels of hundreds of metabolites can be detected and compared across strains. © 2022 Wiley Periodicals LLC. Basic Protocol: Metabolite extraction and detection from Neurospora crassa cell cultures using Liquid Chromatography-Mass Spectrometry.

DREAMTIME NMR Spectroscopy: Targeted Multi-Compound Selection with Improved Detection Limits

NMR/MRI are critical tools for studying molecular structure and interactions but suffer from relatively low sensitivity and spectral overlap. Here, a Nuclear Magnetic Resonance (NMR) approach, termed DREAMTIME, is introduced that provides "a molecular window" inside complex systems, capable of showing only what the user desires, with complete molecular specificity. The user chooses a list of molecules of interest, and the approach detects only those targets while all other molecules are invisible. The approach is demonstrated in whole human blood and urine, small living aquatic organisms in 1D/2D NMR, and MRI. Finally, as proof-of-concept, once overlap is removed via DREAMTIME, a novel "multi-focusing" approach can be used to increase sensitivity. In human blood and urine, sensitivity increases of 7-12 fold over standard ¹ H NMR are observed. Applicable even to unknowns, DREAMTIME has widespread application, from monitoring product formation in organic chemistry to monitoring/identifying suites of molecular targets in complex media or in vivo.

Review on in vivo profiling of drug metabolites with LC-MS/MS in the past decade

Metabolite profiling is an indispensable part of drug discovery and development, enabling a comprehensive understanding of the drug's metabolic behavior. Liquid chromatography-mass spectrometry facilitates metabolite profiling by reducing sample complexity and providing high sensitivity. This review discusses the in vivo metabolite profiling involving LC-MS/MS and the utilization of QTOF, QQQ mass analyzers with a particular emphasis on a mass filter. Further, a summary of sample extraction procedures in biological matrices such as plasma, urine, feces, serum and hair as in vivo samples are outlined. toward the end, we present 15 case studies in biological matrices and their LC-MS/MS conditions to understand the metabolic disposition.

Joint Automatic Metabolite Identification and Quantification of a Set of 1H NMR Spectra

Metabolomics is a promising approach to characterize phenotypes or to identify biomarkers. It is also easily accessible through NMR, which can provide a comprehensive understanding of the metabolome of any living organisms. However, the analysis of ¹H NMR spectrum remains difficult, mainly due to the different problems encountered to perform automatic identification and quantification of metabolites in a reproducible way. In addition, methods that perform automatic identification and quantification of metabolites are often designed to process one given complex mixture spectrum at a time. Hence, when a set of complex mixture spectra coming from the same experiment has to be processed, the approach is simply repeated independently for every spectrum, despite their resemblance. Here, we present new methods that are the first to either align spectra or to identify and quantify metabolites by integrating information coming from several complex spectra of the same experiment. The performances of these new methods are then evaluated on both simulated and real datasets. The results show an improvement in the metabolite identification and in the accuracy of metabolite quantifications, especially when the concentration is low. This joint procedure is available in version 2.0 of ASICS package.

Metabolomics of Milk Reflects a Negative Energy Balance in Cows

Dairy cows can experience a negative energy balance (NEB) in early lactation when feed intake is too low to meet the energy requirements for body maintenance and milk production. Metabolic changes occur in mammary gland cells of animals experiencing a negative energy balance. We studied these metabolic changes in milk samples from dairy cows in relation to energy balance status using liquid chromatography–mass spectrometry (QQQ-LC–MS) and nuclear magnetic resonance (¹H NMR). NMR and LC–MS techniques are complementary techniques that enabled a comprehensive overview of milk metabolites in our study. Energy balance and milk samples were obtained from 87 dairy cows. A total of 55 milk metabolites were reliably detected, of which 15 metabolites were positively correlated to energy balance and 20 were negatively correlated to energy balance. Cows in NEB produced more milk with increased milk fat yield and higher concentrations of citrate, cis-aconitate, creatinine, glycine, phosphocreatine, galactose-1-phosphate, glucose-1-phosphate, UDP-N-acetyl-galactosamine, UDP-N-acetyl-glucosamine, and phosphocholine but lower concentrations of choline, ethanolamine, fucose, N-acetyl-neuraminic acid, N-acetyl-glucosamine, and N-acetyl-galactosamine. During NEB, we observed an increased leakage of cellular content, increased synthesis of nucleic acids and cell membrane phospholipids, an increase in one-carbon metabolic processes, and an increase in lipid-triglyceride anabolism. Overall, both apoptosis combined with cellular renewal is paramount in the mammary gland in cows in NEB.

Mesenchymal Stem/ Stromal Cells metabolomic and bioactive factors profiles: A comparative analysis on the umbilical cord and dental pulp derived Stem/ Stromal Cells secretome

Mesenchymal Stem/ Stromal Cells assume a supporting role to the intrinsic mechanisms of tissue regeneration, a feature mostly assigned to the contents of their secretome. A comparative study on the metabolomic and bioactive molecules/factors content of the secretome of Mesenchymal Stem/ Stromal Cells derived from two expanding sources: the umbilical cord stroma and the dental pulp is presented and discussed. The metabolic profile (Nuclear Magnetic Resonance Spectroscopy) evidenced some differences in the metabolite dynamics through the conditioning period, particularly on the glucose metabolism. Despite, overall similar profiles are suggested. More prominent differences are highlighted for the bioactive factors (Multiplexing Laser Bear Analysis), in which Follistatin, Growth Regulates Protein, Hepatocyte Growth Factor, Interleukin-8 and Monocyte Chemotactic Protein-1 dominate in Umbilical Cord Mesenchymal Stem/ Stromal Cells secretion, while in Dental Pulp Stem/ Stromal Cells the Vascular Endothelial Growth Factor-A and Follistatin are more evident. The distinct secretory cocktail did not result in significantly different effects on endothelial cell populations dynamics including proliferation, migration, tube formation capacity and in vivo angiogenesis, or in chemotaxis for both Mesenchymal Stem/ Stromal Cells populations.

Metabolomics and Biomarker Discovery in Traumatic Brain Injury

Traumatic brain injury (TBI) is one of the leading causes of disability and mortality worldwide. The TBI pathogenesis can induce broad pathophysiological consequences and clinical outcomes attributed to the complexity of the brain. Thus, the diagnosis and prognosis are important issues for the management of mild, moderate, and severe forms of TBI. Metabolomics of readily accessible biofluids is a promising tool for establishing more useful and reliable biomarkers of TBI than using clinical findings alone. Metabolites are an integral part of all biochemical and pathophysiological pathways. Metabolomic processes respond to the internal and external stimuli resulting in an alteration of metabolite concentrations. Current high-throughput and highly sensitive analytical tools are capable of detecting and quantifying small concentrations of metabolites, allowing one to measure metabolite alterations after a pathological event when compared to a normal state or a different pathological process. Further, these metabolic biomarkers could be used for the assessment of injury severity, discovery of mechanisms of injury, and defining structural damage in the brain in TBI. Metabolic biomarkers can also be used for the prediction of outcome, monitoring treatment response, in the assessment of or prognosis of post-injury recovery, and potentially in the use of neuroplasticity procedures. Metabolomics can also enhance our understanding of the pathophysiological mechanisms of TBI, both in primary and secondary injury. Thus, this review presents the promising application of metabolomics for the assessment of TBI as a stand-alone platform or in association with proteomics in the clinical setting.

NMR Spectroscopy for Metabolomics Research

Over the past two decades, nuclear magnetic resonance (NMR) has emerged as one of the three principal analytical techniques used in metabolomics (the other two being gas chromatography coupled to mass spectrometry (GC-MS) and liquid chromatography coupled with single-stage mass spectrometry (LC-MS)). The relative ease of sample preparation, the ability to quantify metabolite levels, the high level of experimental reproducibility, and the inherently nondestructive nature of NMR spectroscopy have made it the preferred platform for long-term or large-scale clinical metabolomic studies. These advantages, however, are often outweighed by the fact that most other analytical techniques, including both LC-MS and GC-MS, are inherently more sensitive than NMR, with lower limits of detection typically being 10 to 100 times better. This review is intended to introduce readers to the field of NMR-based metabolomics and to highlight both the advantages and disadvantages of NMR spectroscopy for metabolomic studies. It will also explore some of the unique strengths of NMR-based metabolomics, particularly with regard to isotope selection/detection, mixture deconvolution via 2D spectroscopy, automation, and the ability to noninvasively analyze native tissue specimens. Finally, this review will highlight a number of emerging NMR techniques and technologies that are being used to strengthen its utility and overcome its inherent limitations in metabolomic applications.

NMR-based metabolomics to select a surgical method for treating papillary thyroid carcinoma

OBJECTIVE

This study aims to investigate differences in the metabolomic profiles of patients who received different surgeries for papillary thyroid carcinoma (PTC).

METHODS

Two surgical methods, i.e., unilateral and total thyroidectomy, were employed according to different disease conditions. Sera from patients who were treated with levothyroxine sodium tablets before and after surgery was analyzed with a Bruker 500 Hz nuclear magnetic resonance (NMR) spectrometer. Data were analyzed via principal component analysis (PCA) and partial least squares discriminate analysis (PLS-DA) with SIMCA-P+ 11.0 software, and metabolites were obtained and compared. The first and second principal components were selected from PCA, PLS-DA, and orthogonal partial least squares discriminate analysis (OPLS-DA). A p-value less than 0.05 was considered statistically significant.

RESULTS

There were significant differences in serum metabolomics before and after surgery. Compared with unilateral thyroidectomy, total thyroidectomy reversed some highly increased metabolite levels (e.g., taurine and betaine). More significant variations in abnormal metabolites were noted after total thyroidectomy than after unilateral thyroidectomy (e.g., alanine, choline, hippurate, and formic acid).

CONCLUSIONS

The choice of surgical method for PTC patients should be based not only on the tumor condition but also on the potential consequences of metabolic variations. Total thyroidectomy reversed some increased metabolite levels but led to accumulation of some other metabolites due to the loss of thyroid function; thus, metabolic disturbances caused by thyroid hormone deficiency should be prevented in advance.

Human umbilical cord blood plasma as an alternative to animal sera for mesenchymal stromal cells in vitro expansion - A multicomponent metabolomic analysis

Mesenchymal Stromal cells (MSCs) have a potential role in cell-based therapies. Foetal bovine serum (FBS) is used to supplement the basal cell culture medium but presents several disadvantages and risks. Other alternatives have been studied, including human umbilical cord blood plasma (hUCBP), aiming at the development of xeno-free culturing protocols. A comparative characterization of multicomponent metabolic composition of hUCBP and commercial FBS based on Nuclear Magnetic Resonance (NMR) spectroscopy and multivariate statistical analysis was performed. The analysis of ¹H-NMR spectra revealed both similarities and differences between the two proposed supplements. Similar metabolites (amino acids, glucose, lipids and nucleotides) were found in the hUCBP and FBS NMR spectra. The results show that the major difference between the metabolic profiles of the two proposed supplements are due to the significantly higher levels of glucose and lower levels of lactate, glutamate, alanine and branched chain amino acids in hUCBP. Similar or slightly different levels of important proteinogenic amino acids, as well as of nucleotides, lipids were found in the hUCBP and FBS. In order to validate it’s suitability for cell culture, umbilical cord-MSCs (UC-MSCs) and dental pulp stem cells (DPSCs) were expanded using hUCBP. In both hMSCs, in vitro culture with hUCBP supplementation presented similar to improved metabolic performances when compared to FBS. The two cell types tested expressed different optimum hUCBP percentage content. For DPSCs, the optimum hUCBP content was 6% and for UC-MSCs, 4%. Cultured hMSCs displayed no changes in senescence indicators, as well as maintained characteristic surface marker’s expression. FBS substitution was associated with an increase in early apoptosis events, in a dose dependent manner, as well as to slight up- and down-regulation of targeted gene’s expression. Tri-lineage differentiation capacity was also influenced by the substitution of FBS by hUCBP.

Serum metabolomic profiling predicts synovial gene expression in rheumatoid arthritis

Background

Metabolomics is an emerging field of biomedical research that may offer a better understanding of the mechanisms of underlying conditions including inflammatory arthritis. Perturbations caused by inflamed synovial tissue can lead to correlated changes in concentrations of certain metabolites in the synovium and thereby function as potential biomarkers in blood. Here, we explore the hypothesis of whether characterization of patients’ metabolomic profiles in blood, utilizing ¹H-nuclear magnetic resonance (NMR), predicts synovial marker profiling in rheumatoid arthritis (RA).

Methods

Nineteen active, seropositive patients with RA, on concomitant methotrexate, were studied. One of the involved joints was a knee or a wrist appropriate for arthroscopy. A Bruker Avance 700 MHz spectrometer was used to acquire NMR spectra of serum samples. Gene expression in synovial tissue obtained by arthroscopy was analyzed by real-time PCR. Data processing and statistical analysis were performed in Python and SPSS.

Results

Analysis of the relationships between each synovial marker-metabolite pair using linear regression and controlling for age and gender revealed significant clustering within the data. We observed an association of serine/glycine/phenylalanine metabolism and aminoacyl-tRNA biosynthesis with lymphoid cell gene signature. Alanine/aspartate/glutamate metabolism and choline-derived metabolites correlated with TNF-α synovial expression. Circulating ketone bodies were associated with gene expression of synovial metalloproteinases. Discriminant analysis identified serum metabolites that classified patients according to their synovial marker levels.

Conclusion

The relationship between serum metabolite profiles and synovial biomarker profiling suggests that NMR may be a promising tool for predicting specific pathogenic pathways in the inflamed synovium of patients with RA.

Electronic supplementary material

The online version of this article (10.1186/s13075-018-1655-3) contains supplementary material, which is available to authorized users.

Lipidomics Insights in Health and Nutritional Intervention Studies

Lipids are among the major components of food and constitute the principal structural biomolecules of human body together with proteins and carbohydrates. Lipidomics encompasses the investigation of the lipidome, defined as the entire spectrum of lipids in a biological system at a given time. Among metabolomics technologies, lipidomics has evolved due to the relevance of lipids in nutrition and their well-recognized roles in health. Mass spectrometry advances have greatly facilitated lipidomics, but owing to the complexity and diversity of the lipids, lipidome purification and analysis are still challenging. This review focuses on lipidomics strategies, applications, and achievements of studies related to nutrition and health research.

Serum metabolomics of Indian women with polycystic ovary syndrome using 1H NMR coupled with a pattern recognition approach

Polycystic ovary syndrome (PCOS) is one of the most commonly occurring metabolic and endocrinological disorders affecting women of reproductive age. Metabolomics is an emerging field that holds promise in understanding disease pathophysiology. Recently, a few metabolomics based studies have been attempted in PCOS patients; however, none of them have included patients from the Indian population. The main objective of this study was to investigate the serum metabolomic profile of Indian women with PCOS and compare them with controls. Proton nuclear magnetic resonance (¹H NMR) was used to first identify the differentially expressed metabolites among women with PCOS from the Eastern region of India during the discovery phase and further validated in a separate cohort of PCOS and control subjects. Multivariate analysis of the binned spectra indicated 16 dysregulated bins in the sera of these women with PCOS. Out of these 16 bins, 13 identified bins corresponded to 12 metabolites including 8 amino acids and 4 energy metabolites. Amongst the amino acids, alanine, valine, leucine and threonine and amongst the energy metabolites, lactate and acetate were observed to be significantly up-regulated in women with PCOS when compared with controls. The remaining 4 amino acids, l-glutamine, proline, glutamate and histidine were down-regulated along with 2 energy metabolites: glucose and 3-hydroxybutyric acid. Our findings showed dysregulations in the expression of different metabolites in the serum of women with PCOS suggesting the involvement of multiple pathways including amino acid metabolism, carbohydrate/lipid metabolism, purine and pyrimidine metabolism and protein synthesis.

Metabolomic signature of brain cancer

Despite advances in surgery and adjuvant therapy, brain tumors represent one of the leading causes of cancer-related mortality and morbidity in both adults and children. Gliomas constitute about 60% of all cerebral tumors, showing varying degrees of malignancy. They are difficult to treat due to dismal prognosis and limited therapeutics. Metabolomics is the untargeted and targeted analyses of endogenous and exogenous small molecules, which charact erizes the phenotype of an individual. This emerging "omics" science provides functional readouts of cellular activity that contribute greatly to the understanding of cancer biology including brain tumor biology. Metabolites are highly informative as a direct signature of biochemical activity; therefore, metabolite profiling has become a promising approach for clinical diagnostics and prognostics. The metabolic alterations are well-recognized as one of the key hallmarks in monitoring disease progression, therapy, and revealing new molecular targets for effective therapeutic intervention. Taking advantage of the latest high-throughput analytical technologies, that is, nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), metabolomics is now a promising field for precision medicine and drug discovery. In the present report, we review the application of metabolomics and in vivo metabolic profiling in the context of adult gliomas and paediatric brain tumors. Analytical platforms such as high-resolution (HR) NMR, in vivo magnetic resonance spectroscopic imaging and high- and low-resolution MS are discussed. Moreover, the relevance of metabolic studies in the development of new therapeutic strategies for treatment of gliomas are reviewed.

Transcriptomic and metabolomic profiles of Chinese citrus fly, Bactrocera minax (Diptera: Tephritidae), along with pupal development provide insight into diapause program

The Chinese citrus fly, Bactrocera minax (Enderlein), is a devastating citrus pest in Asia. This univoltine insect enters obligatory pupal diapause in each generation, while little is known about the course and the molecular mechanisms of diapause. In this study, the course of diapause was determined by measuring the respiratory rate throughout the pupal stage. In addition, the variation of transcriptomic and metabolomic profiles of pupae at five developmental stages (pre-, early-, middle-, late-, and post-diapause) were evaluated by next-generation sequencing technology and ¹H nuclear magnetic resonance spectroscopy (NMR), respectively. A total of 4,808 genes were significantly altered in ten pairwise comparisons, representing major shifts in metabolism and signal transduction as well as endocrine system and digestive system. Gene expression profiles were validated by qRT-PCR analysis. In addition, 48 metabolites were identified and quantified by ¹H NMR. Nine of which significantly contributed to the variation in the metabolomic profiles, especially proline and trehalose. Moreover, the samples collected within diapause maintenance (early-, middle-, and late-diapause) only exhibited marginal transcriptomic and metabolomic variation with each other. These findings greatly improve our understanding of B. minax diapause and lay the foundation for further pertinent studies.

Toward biotechnology in space: High-throughput instruments for in situ biological research beyond Earth

Space biotechnology is a nascent field aimed at applying tools of modern biology to advance our goals in space exploration. These advances rely on our ability to exploit in situ high throughput techniques for amplification and sequencing DNA, and measuring levels of RNA transcripts, proteins and metabolites in a cell. These techniques, collectively known as "omics" techniques have already revolutionized terrestrial biology. A number of on-going efforts are aimed at developing instruments to carry out "omics" research in space, in particular on board the International Space Station and small satellites. For space applications these instruments require substantial and creative reengineering that includes automation, miniaturization and ensuring that the device is resistant to conditions in space and works independently of the direction of the gravity vector. Different paths taken to meet these requirements for different "omics" instruments are the subjects of this review. The advantages and disadvantages of these instruments and technological solutions and their level of readiness for deployment in space are discussed. Considering that effects of space environments on terrestrial organisms appear to be global, it is argued that high throughput instruments are essential to advance (1) biomedical and physiological studies to control and reduce space-related stressors on living systems, (2) application of biology to life support and in situ resource utilization, (3) planetary protection, and (4) basic research about the limits on life in space. It is also argued that carrying out measurements in situ provides considerable advantages over the traditional space biology paradigm that relies on post-flight data analysis.

β-N-Methylamino-L-alanine (BMAA) perturbs alanine, aspartate and glutamate metabolism pathways in human neuroblastoma cells as determined by metabolic profiling

β-Methylamino-L-alanine (BMAA) is a non-proteinogenic amino acid that induces long-term cognitive deficits, as well as an increased neurodegeneration and intracellular fibril formation in the hippocampus of adult rodents following short-time neonatal exposure and in vervet monkey brain following long-term exposure. It has also been proposed to be involved in the etiology of neurodegenerative disease in humans. The aim of this study was to identify metabolic effects not related to excitotoxicity or oxidative stress in human neuroblastoma SH-SY5Y cells. The effects of BMAA (50, 250, 1000 µM) for 24 h on cells differentiated with retinoic acid were studied. Samples were analyzed using LC-MS and NMR spectroscopy to detect altered intracellular polar metabolites. The analysis performed, followed by multivariate pattern recognition techniques, revealed significant perturbations in protein biosynthesis, amino acid metabolism pathways and citrate cycle. Of specific interest were the BMAA-induced alterations in alanine, aspartate and glutamate metabolism and as well as alterations in various neurotransmitters/neuromodulators such as GABA and taurine. The results indicate that BMAA can interfere with metabolic pathways involved in neurotransmission in human neuroblastoma cells.

Role of Metabolomics in Traumatic Brain Injury Research

Metabolomics is an important member of the omics community in that it defines which small molecules may be responsible for disease states. This article reviews the essential principles of metabolomics from specimen preparation, chemical analysis, to advanced statistical methods. Metabolomics in traumatic brain injury has so far been underutilized. Future metabolomics-based studies focused on the diagnoses, prognoses, and treatment effects need to be conducted across all types of traumatic brain injury.

Assessment of dietary exposure and effect in humans: The role of NMR

In human nutritional science progress has always depended strongly on analytical measurements for establishing relationships between diet and health. This field has undergone significant changes as a result of the development of NMR and mass spectrometry methods for large scale detection, identification and quantification of metabolites in body fluids. This has allowed systematic studies of the metabolic fingerprints that biological processes leave behind, and has become the research field of metabolomics. As a metabolic profiling technique, NMR is at its best when its unbiased nature, linearity and reproducibility are exploited in well-controlled nutritional intervention and cross-sectional population screening studies. Although its sensitivity is less good than that of mass spectrometry, NMR has maintained a strong position in metabolomics through implementation of standardisation protocols, hyphenation with mass spectrometry and chromatographic techniques, accurate quantification and spectral deconvolution approaches, and high-throughput automation. Thus, NMR-based metabolomics has contributed uniquely to new insights into dietary exposure, in particular by unravelling the metabolic fates of phytochemicals and the discovery of dietary intake markers. NMR profiling has also contributed to the understanding of the subtle effects of diet on central metabolism and lipoprotein metabolism. In order to hold its ground in nutritional metabolomics, NMR will need to step up its performance in sensitivity and resolution; the most promising routes forward are the analytical use of dynamic nuclear polarisation and developments in microcoil construction and automated fractionation.

Metabolomics in rheumatic diseases: desperately seeking biomarkers

Metabolomics enables the profiling of large numbers of small molecules in cells, tissues and biological fluids. These molecules, which include amino acids, carbohydrates, lipids, nucleotides and their metabolites, can be detected quantitatively. Metabolomic methods, often focused on the information-rich analytical techniques of NMR spectroscopy and mass spectrometry, have potential for early diagnosis, monitoring therapy and defining disease pathogenesis in many therapeutic areas, including rheumatic diseases. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanisms are being revealed and are shaping our understanding of cell biology, physiology and medicine. These pathways can potentially be targeted to diagnose and treat patients with immune-mediated diseases.

Qishen Yiqi Drop Pill improves cardiac function after myocardial ischemia

Myocardial ischemia (MI) is one of the leading causes of death, while Qishen Yiqi Drop Pill (QYDP) is a representative traditional Chinese medicine to treat this disease. Unveiling the pharmacological mechanism of QYDP will provide a great opportunity to promote the development of novel drugs to treat MI. 64 male Sprague-Dawley (SD) rats were divided into four groups: MI model group, sham operation group, QYDP treatment group and Fosinopril treatment group. Echocardiography results showed that QYDP exhibited significantly larger LV end-diastolic dimension (LVEDd) and LV end-systolic dimension (LVEDs), compared with the MI model group, indicating the improved cardiac function by QYDP. (1)H-NMR based metabonomics further identify 9 significantly changed metabolites in the QYDP treatment group, and the QYDP-related proteins based on the protein-metabolite interaction networks and the corresponding pathways were explored, involving the pyruvate metabolism pathway, the retinol metabolism pathway, the tyrosine metabolism pathway and the purine metabolism pathway, suggesting that QYDP was closely associated with blood circulation. ELISA tests were further employed to identify NO synthase (iNOS) and cathepsin K (CTSK) in the networks. For the first time, our work combined experimental and computational methods to study the mechanism of the formula of traditional Chinese medicine.

Repeated implantation failure versus repeated implantation success: discrimination at a metabolomic level

STUDY QUESTION

Is there any difference at the serum metabolic level between women with recurrent implantation failure (RIF) and women with recurrent implantation success (RIS) when undergoing in vitro fertilization (IVF)?

SUMMARY ANSWER

Eight metabolites, including valine, adipic acid, l-lysine, creatine, ornithine, glycerol, d-glucose and urea, were found to be significantly up-regulated in women with RIF when compared with women with RIS.

WHAT IS KNOWN ALREADY

Despite transfer of three high-grade embryos per cycle, RIF following three or more consecutive IVF attempts occurs in a group of infertile women. Conversely, there is a group of women who undergo successful implantation each cycle, yet have a poor obstetric history.

STUDY DESIGN, SIZE, DURATION

This study was conducted over a period of 10 years (January 2004-October 2014). Groups of 28 women with RIF (age ≤40 years and BMI ≤28) and 24 women with RIS (age and BMI matched) were selected from couples with primary infertility reporting at the Institute of Reproductive Medicine, Kolkata, India. Women recruited in the RIF group had history of implantation failure in at least three consecutive IVF attempts, in which three embryos of high-grade quality were transferred in each cycle.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Blood samples were collected from both the groups during the implantation window following overnight fasting for at least 10 h (7-10 days post ovulation). Samples were analyzed using a 700 MHz NMR spectrometer and acquired spectra were subjected to chemometric and statistical analysis. Serum levels of endothelial nitric oxide synthase (eNOS) were measured using an enzyme immunoassay technique.

MAIN RESULTS AND THE ROLE OF CHANCE

Valine, adipic acid, l-lysine, creatine, ornithine, glycerol, d-glucose and urea were found to be significantly down-regulated in women with RIS when compared with those with RIF, with fold change values of 0.81, 0.82, 0.79, 0.80, 0.78, 0.68, 0.76 and 0.74, respectively. Further, serum eNOS was found to be significantly lower in women with RIF when compared with RIS (P < 0.05), indicating possible impairment in nitric oxide production. Metabolites, mostly related to energy metabolism, lipid metabolism and the arginine metabolic pathway were found to be considerably altered and are likely to be associated with the RIF phenomenon. However, the interplay between these molecules in RIF is complex and holds merit for further exploration.

LIMITATIONS, REASONS FOR CAUTION

In-depth studies of the arginine metabolic pathway in endometrial tissues seem necessary to validate our findings. A limitation of the present study is that the metabolic level changes, eNOS and nitric oxide levels have not been investigated in the endometrial tissues of the two groups of women. It would be interesting to investigate whether there exists a direct link between metabolic dysregulation and genetic factors that affects implantation in RIF women.

WIDER IMPLICATIONS OF THE FINDINGS

We speculate that tissue metabolomics can provide an improved understanding of the metabolic dysfunction associated with RIF. The identification of serum metabolic marker(s) in women with RIS may help with strategies of early therapeutic intervention, which may improve the chances of implantation significantly in women otherwise susceptible to IVF failure.

STUDY FUNDING/COMPETING INTERESTS

One of the authors, S.R.C. acknowledges the Council of Scientific and Industrial Research (CSIR), Government of India [No: 9/81(1228)/14, EMR-I] for financial support.

Radiation Metabolomics: Current Status and Future Directions

Human exposure to ionizing radiation (IR) disrupts normal metabolic processes in cells and organs by inducing complex biological responses that interfere with gene and protein expression. Conventional dosimetry, monitoring of prodromal symptoms, and peripheral lymphocyte counts are of limited value as organ- and tissue-specific biomarkers for personnel exposed to radiation, particularly, weeks or months after exposure. Analysis of metabolites generated in known stress-responsive pathways by molecular profiling helps to predict the physiological status of an individual in response to environmental or genetic perturbations. Thus, a multi-metabolite profile obtained from a high-resolution mass spectrometry-based metabolomics platform offers potential for identification of robust biomarkers to predict radiation toxicity of organs and tissues resulting from exposures to therapeutic or non-therapeutic IR. Here, we review the status of radiation metabolomics and explore applications as a standalone technology, as well as its integration in systems biology, to facilitate a better understanding of the molecular basis of radiation response. Finally, we draw attention to the identification of specific pathways that can be targeted for the development of therapeutics to alleviate or mitigate harmful effects of radiation exposure.

Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis

NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to nondestructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Precise metabolite quantification is a prerequisite to move any chemical biomarker or biomarker panel from the lab to the clinic. Among the biofluids commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, and easily obtained, needs little sample preparation, and does not require invasive medical procedures for collection. Furthermore, urine captures and concentrates many "unwanted" or "undesirable" compounds throughout the body, providing a rich source of potentially useful disease biomarkers; however, incredible variation in urine chemical concentrations makes analysis of urine and identification of useful urinary biomarkers by NMR challenging. We discuss a number of the most significant issues regarding NMR-based urinary metabolomics with specific emphasis on metabolite quantification for disease biomarker applications and propose data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, sample preparation, and biomarker assessment.

Capillary Electrophoresis-Mass Spectrometry for Clinical Metabolomics

In clinical metabolomics, capillary electrophoresis-mass spectrometry (CE-MS) has become a very useful technique for the analysis of highly polar and charged metabolites in complex biologic samples. A comprehensive overview of recent developments in CE-MS for metabolic profiling studies is presented. This review covers theory, CE separation modes, capillary coatings, and practical aspects of CE-MS coupling. Attention is also given to sample pretreatment and data analysis strategies used for metabolomics. The applicability of CE-MS for clinical metabolomics is illustrated using samples ranging from plasma and urine to cells and tissues. CE-MS application to large-scale and quantitative clinical metabolomics is addressed. Conclusions and perspectives on this unique analytic strategy are presented.

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.

Can NMR solve some significant challenges in metabolomics?

The field of metabolomics continues to witness rapid growth driven by fundamental studies, methods development, and applications in a number of disciplines that include biomedical science, plant and nutrition sciences, drug development, energy and environmental sciences, toxicology, etc. NMR spectroscopy is one of the two most widely used analytical platforms in the metabolomics field, along with mass spectrometry (MS). NMR's excellent reproducibility and quantitative accuracy, its ability to identify structures of unknown metabolites, its capacity to generate metabolite profiles using intact bio-specimens with no need for separation, and its capabilities for tracing metabolic pathways using isotope labeled substrates offer unique strengths for metabolomics applications. However, NMR's limited sensitivity and resolution continue to pose a major challenge and have restricted both the number and the quantitative accuracy of metabolites analyzed by NMR. Further, the analysis of highly complex biological samples has increased the demand for new methods with improved detection, better unknown identification, and more accurate quantitation of larger numbers of metabolites. Recent efforts have contributed significant improvements in these areas, and have thereby enhanced the pool of routinely quantifiable metabolites. Additionally, efforts focused on combining NMR and MS promise opportunities to exploit the combined strength of the two analytical platforms for direct comparison of the metabolite data, unknown identification and reliable biomarker discovery that continue to challenge the metabolomics field. This article presents our perspectives on the emerging trends in NMR-based metabolomics and NMR's continuing role in the field with an emphasis on recent and ongoing research from our laboratory.

NMR-based metabolic profiling in healthy individuals overfed different types of fat: links to changes in liver fat accumulation and lean tissue mass

BACKGROUND

Overeating different dietary fatty acids influence the amount of liver fat stored during weight gain, however, the mechanisms responsible are unclear. We aimed to identify non-lipid metabolites that may differentiate between saturated (SFA) and polyunsaturated fatty acid (PUFA) overfeeding using a non-targeted metabolomic approach. We also investigated the possible relationships between plasma metabolites and body fat accumulation.

METHODS

In a randomized study (LIPOGAIN study), n=39 healthy individuals were overfed with muffins containing SFA or PUFA. Plasma samples were precipitated with cold acetonitrile and analyzed by nuclear magnetic resonance (NMR) spectroscopy. Pattern recognition techniques were used to overview the data, identify variables contributing to group classification and to correlate metabolites with fat accumulation.

RESULTS

We previously reported that SFA causes a greater accumulation of liver fat, visceral fat and total body fat, whereas lean tissue levels increases less compared with PUFA, despite comparable weight gain. In this study, lactate and acetate were identified as important contributors to group classification between SFA and PUFA (P<0.05). Furthermore, the fat depots (total body fat, visceral adipose tissue and liver fat) and lean tissue correlated (P(corr)>0.5) all with two or more metabolites (for example, branched amino acids, alanine, acetate and lactate). The metabolite composition differed in a manner that may indicate higher insulin sensitivity after a diet with PUFA compared with SFA, but this needs to be confirmed in future studies.

CONCLUSION

A non-lipid metabolic profiling approach only identified a few metabolites that differentiated between SFA and PUFA overfeeding. Whether these metabolite changes are involved in depot-specific fat storage and increased lean tissue mass during overeating needs further investigation.

Metabolic profiling of epithelial ovarian cancer cell lines: evaluation of harvesting protocols for profiling using NMR spectroscopy

BACKGROUND

Metabolic profiling represents a novel technology for analyzing tumor cells. Epithelial ovarian carcinoma has a low survival rate due to the development of aggressive and chemotherapy-resistant cells. A tailored and reliable protocol is presented for profiling of chemoresistant cells using the cell line SKOV3 and a multiresistant subline SKOV3R.

RESULTS

Harvesting protocols with cold methanol or MilliQ freeze/thaw cycles were compared. Increased reproducibility using MilliQ was evidenced. Importantly, both approaches resulted in similar profiles. Compared with parental SKOV3, the SKOV3R cells showed a significantly different profile.

CONCLUSION

The MilliQ protocol is preferred owing to higher reproducibility and increased sample preparation options. The resulting metabolic profiles summarize metabolic alterations in chemoresistant cells consistent with a progressed and aggressive phenotype.

Standardizing the experimental conditions for using urine in NMR-based metabolomic studies with a particular focus on diagnostic studies: a review

The metabolic composition of human biofluids can provide important diagnostic and prognostic information. Among the biofluids most commonly analyzed in metabolomic studies, urine appears to be particularly useful. It is abundant, readily available, easily stored and can be collected by simple, noninvasive techniques. Moreover, given its chemical complexity, urine is particularly rich in potential disease biomarkers. This makes it an ideal biofluid for detecting or monitoring disease processes. Among the metabolomic tools available for urine analysis, NMR spectroscopy has proven to be particularly well-suited, because the technique is highly reproducible and requires minimal sample handling. As it permits the identification and quantification of a wide range of compounds, independent of their chemical properties, NMR spectroscopy has been frequently used to detect or discover disease fingerprints and biomarkers in urine. Although protocols for NMR data acquisition and processing have been standardized, no consensus on protocols for urine sample selection, collection, storage and preparation in NMR-based metabolomic studies have been developed. This lack of consensus may be leading to spurious biomarkers being reported and may account for a general lack of reproducibility between laboratories. Here, we review a large number of published studies on NMR-based urine metabolic profiling with the aim of identifying key variables that may affect the results of metabolomics studies. From this survey, we identify a number of issues that require either standardization or careful accounting in experimental design and provide some recommendations for urine collection, sample preparation and data acquisition.

MSCs conditioned media and umbilical cord blood plasma metabolomics and composition

Human mesenchymal stem cells (hMSCs) from umbilical cord (UC) blood (UCB) and matrix are tested clinically for a variety of pathologies but in vitro expansion using culture media containing fetal bovine serum (FBS) is essential to achieve appropriate cell numbers for clinical use. Human UCB plasma (hUCBP) can be used as a supplement for hMSCs culture, since UCB is rich in soluble growth factors and due to worldwide increased number of cryopreserved UCB units in public and private banks, without the disadvantages listed for FBS. On the other hand, the culture media enriched in growth factors produced by these hMSCs in expansion (Conditioned medium--CM) can be an alternative to hMSCs application. The CM of the hMSCs from the UC might be a better therapeutic option compared to cell transplantation, as it can benefit from the local tissue response to the secreted molecules without the difficulties and complications associated to the engraftment of the allo- or xeno-transplanted cells. These facts drove us to know the detailed composition of the hUCBP and CM, by 1H-NMR and Multiplexing LASER Bead Technology. hUCBP is an adequate alternative for the FBS and the CM and hUCBP are important sources of growth factors, which can be used in MSCs-based therapies. Some of the major proliferative, chemotactic and immunomodulatory soluble factors (TGF-β, G-CSF, GM-CSF, MCP-1, IL-6, IL-8) were detected in high concentrations in CM and even higher in hUCBP. The results from 1H-NMR spectroscopic analysis of CM endorsed a better understanding of hMSCs metabolism during in vitro culture, and the relative composition of several metabolites present in CM and hUCBP was obtained. The data reinforces the potential use of hUCBP and CM in tissue regeneration and focus the possible use of hUCBP as a substitute for the FBS used in hMSCs in vitro culture.

Metabolomics insights into pathophysiological mechanisms of interstitial cystitis

Interstitial cystitis (IC), also known as painful bladder syndrome or bladder pain syndrome, is a chronic lower urinary tract syndrome characterized by pelvic pain, urinary urgency, and increased urinary frequency in the absence of bacterial infection or identifiable clinicopathology. IC can lead to long-term adverse effects on the patient's quality of life. Therefore, early diagnosis and better understanding of the mechanisms underlying IC are needed. Metabolomic studies of biofluids have become a powerful method for assessing disease mechanisms and biomarker discovery, which potentially address these important clinical needs. However, limited intensive metabolic profiles have been elucidated in IC. The article is a short review on metabolomic analyses that provide a unique fingerprint of IC with a focus on its use in determining a potential diagnostic biomarker associated with symptoms, a response predictor of therapy, and a prognostic marker.

Bayesian deconvolution and quantification of metabolites in complex 1D NMR spectra using BATMAN

Data processing for 1D NMR spectra is a key bottleneck for metabolomic and other complex-mixture studies, particularly where quantitative data on individual metabolites are required. We present a protocol for automated metabolite deconvolution and quantification from complex NMR spectra by using the Bayesian automated metabolite analyzer for NMR (BATMAN) R package. BATMAN models resonances on the basis of a user-controllable set of templates, each of which specifies the chemical shifts, J-couplings and relative peak intensities for a single metabolite. Peaks are allowed to shift position slightly between spectra, and peak widths are allowed to vary by user-specified amounts. NMR signals not captured by the templates are modeled non-parametrically by using wavelets. The protocol covers setting up user template libraries, optimizing algorithmic input parameters, improving prior information on peak positions, quality control and evaluation of outputs. The outputs include relative concentration estimates for named metabolites together with associated Bayesian uncertainty estimates, as well as the fit of the remainder of the spectrum using wavelets. Graphical diagnostics allow the user to examine the quality of the fit for multiple spectra simultaneously. This approach offers a workflow to analyze large numbers of spectra and is expected to be useful in a wide range of metabolomics studies.

2D NMR barcoding and differential analysis of complex mixtures for chemical identification: the Actaea triterpenes

The interpretation of NMR spectroscopic information for structure elucidation involves decoding of complex resonance patterns that contain valuable molecular information (δ and J), which is not readily accessible otherwise. We introduce a new concept of 2D-NMR barcoding that uses clusters of fingerprint signals and their spatial relationships in the δ-δ coordinate space to facilitate the chemical identification of complex mixtures. Similar to widely used general barcoding technology, the structural information of individual compounds is encoded as a specifics pattern of their C,H correlation signals. Software-based recognition of these patterns enables the structural identification of the compounds and their discrimination in mixtures. Using the triterpenes from various Actaea (syn. Cimicifuga) species as a test case, heteronuclear multiple-bond correlation (HMBC) barcodes were generated on the basis of their structural subtypes from a statistical investigation of their δH and δC data in the literature. These reference barcodes allowed in silico identification of known triterpenes in enriched fractions obtained from an extract of A. racemosa (black cohosh). After dereplication, a differential analysis of heteronuclear single-quantum correlation (HSQC) spectra even allowed for the discovery of a new triterpene. The 2D barcoding concept has potential application in a natural product discovery project, allowing for the rapid dereplication of known compounds and as a tool in the search for structural novelty within compound classes with established barcodes.