Metabonomics in pharmaceutical R&D

Impact of the delay in cryopreservation timing during biobanking procedures on human liver tissue metabolomics

The liver is a highly specialized organ involved in regulating systemic metabolism. Understanding metabolic reprogramming of liver disease is key in discovering clinical biomarkers, which relies on robust tissue biobanks. However, sample collection and storage procedures pose a threat to obtaining reliable results, as metabolic alterations may occur during sample handling. This study aimed to elucidate the impact of pre-analytical delay during liver resection surgery on liver tissue metabolomics. Patients were enrolled for liver resection during which normal tissue was collected and snap-frozen at three timepoints: before transection, after transection, and after analysis in Pathology. Metabolomics analyses were performed using 1H Nuclear Magnetic Resonance (NMR) and Liquid Chromatography-Mass Spectrometry (LC-MS). Time at cryopreservation was the principal variable contributing to differences between liver specimen metabolomes, which superseded even interindividual variability. NMR revealed global changes in the abundance of an array of metabolites, namely a decrease in most metabolites and an increase in β-glucose and lactate. LC-MS revealed that succinate, alanine, glutamine, arginine, leucine, glycerol-3-phosphate, lactate, AMP, glutathione, and NADP were enhanced during cryopreservation delay (all p<0.05), whereas aspartate, iso(citrate), ADP, and ATP, decreased (all p<0.05). Cryopreservation delays occurring during liver tissue biobanking significantly alter an array of metabolites. Indeed, such alterations compromise the integrity of metabolomic data from liver specimens, underlining the importance of standardized protocols for tissue biobanking in hepatology.

Metabolomic Profiling in Children with Celiac Disease: Beyond the Gluten-Free Diet

Celiac disease (CD) is included in the group of complex or multifactorial diseases, i.e., those caused by the interaction of genetic and environmental factors. Despite a growing understanding of the pathophysiological mechanisms of the disease, diagnosis is still often delayed and there are no effective biomarkers for early diagnosis. The only current treatment, a gluten-free diet (GFD), can alleviate symptoms and restore intestinal villi, but its cellular effects remain poorly understood. To gain a comprehensive understanding of CD's progression, it is crucial to advance knowledge across various scientific disciplines and explore what transpires after disease onset. Metabolomics studies hold particular significance in unravelling the complexities of multifactorial and multisystemic disorders, where environmental factors play a significant role in disease manifestation and progression. By analyzing metabolites, we can gain insights into the reasons behind CD's occurrence, as well as better comprehend the impact of treatment initiation on patients. In this review, we present a collection of articles that showcase the latest breakthroughs in the field of metabolomics in pediatric CD, with the aim of trying to identify CD biomarkers for both early diagnosis and treatment monitoring. These advancements shed light on the potential of metabolomic analysis in enhancing our understanding of the disease and improving diagnostic and therapeutic strategies. More studies need to be designed to cover metabolic profiles in subjects at risk of developing the disease, as well as those analyzing biomarkers for follow-up treatment with a GFD.

Practical Aspects of NMR-Based Metabolomics

While NMR-based metabolomics is only about 20 years old, NMR has been a key part of metabolic and metabolism studies for &gt;40 years. Historically, metabolic researchers used NMR because of its high level of reproducibility, superb instrument stability, facile sample preparation protocols, inherently quantitative character, non-destructive nature, and amenability to automation. In this chapter, we provide a short history of NMR-based metabolomics. We then provide a detailed description of some of the practical aspects of performing NMR-based metabolomics studies including sample preparation, pulse sequence selection, and spectral acquisition and processing. The two different approaches to metabolomics data analysis, targeted vs. untargeted, are briefly outlined. We also describe several software packages to help users process NMR spectra obtained via these two different approaches. We then give several examples of useful or interesting applications of NMR-based metabolomics, ranging from applications to drug toxicology, to identifying inborn errors of metabolism to analyzing the contents of biofluids from dairy cattle. Throughout this chapter, we will highlight the strengths and limitations of NMR-based metabolomics. Additionally, we will conclude with descriptions of recent advances in NMR hardware, methodology, and software and speculate about where NMR-based metabolomics is going in the next 5-10 years.

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.

A Preliminary Pilot Study: Metabolomic Analysis of Saliva in Oral Candidiasis

Early detection of oral candidiasis is essential. However, most currently available methods are time-consuming and useful only for screening patients. Previous studies on the relationship between oral candidiasis and saliva have focused on saliva volume and not on its components. Therefore, to clarify the effects of oral candidiasis on salivary metabolites, the relationship between salivary components and oral candidiasis was investigated by comparing the salivary metabolites of oral candidiasis patients and those not previously diagnosed with candidiasis. Forty-five participants visiting our university hospital were included and classified into two groups, the Candida group and the control group, based on the Candida detection test results. The unstimulated saliva was collected using the spitting method over 15 min, and the stimulated saliva was collected using the gum-chewing method over 10 min. The saliva volume was measured, and the saliva samples were frozen and analyzed metabolomically. Metabolome analysis revealed 51 metabolites with peak detection rates exceeding 50%. There was no significant difference in age and sex between the Candida and control groups. In the Candida group, five metabolites (tyrosine, choline, phosphoenolpyruvate, histidine, and 6-phosphogluconate) were significantly elevated in the unstimulated, two (octanoic acid and uridine monophosphate(UMP)) were significantly increased, and four (ornithine, butyrate, aminovalerate and aminolevulinate) were significantly decreased in the stimulated saliva. This study suggests the possibility of identifying metabolites specific to patients with oral candidiasis, which could aid prompt diagnosis.

Metabolomics Work Flow and Analytics in Systems Biology

Metabolomics is an omics approach of systems biology that involves the development and assessment of large-scale, comprehensive biochemical analysis tools for metabolites in biological systems. This review describes the metabolomics workflow and provides an overview of current analytic tools used for the quantification of metabolic profiles. We explain analytic tools such as mass spectrometry (MS), nuclear magnetic resonance (NMR) spectroscopy, ionization techniques, and approaches for data extraction and analysis.

Metabolomics and metabolites in ischemic stroke

Stroke is a major reason for disability and the second highest cause of death in the world. When a patient is admitted to a hospital, it is necessary to identify the type of stroke, and the likelihood for development of a recurrent stroke, vascular dementia, and depression. These factors could be determined using different biomarkers. Metabolomics is a very promising strategy for identification of biomarkers. The advantage of metabolomics, in contrast to other analytical techniques, resides in providing low molecular weight metabolite profiles, rather than individual molecule profiles. Technically, this approach is based on mass spectrometry and nuclear magnetic resonance. Furthermore, variations in metabolite concentrations during brain ischemia could alter the principal neuronal functions. Different markers associated with ischemic stroke in the brain have been identified including those contributing to risk, acute onset, and severity of this pathology. In the brain, experimental studies using the ischemia/reperfusion model (IRI) have shown an impaired energy and amino acid metabolism and confirmed their principal roles. Literature data provide a good basis for identifying markers of ischemic stroke and hemorrhagic stroke and understanding metabolic mechanisms of these diseases. This opens an avenue for the successful use of identified markers along with metabolomics technologies to develop fast and reliable diagnostic tools for ischemic and hemorrhagic stroke.

Detection of Metabolite-Protein Interactions in Complex Biological Samples by High-Resolution Relaxometry: Toward Interactomics by NMR

Metabolomics, the systematic investigation of metabolites in biological fluids, cells, or tissues, reveals essential information about metabolism and diseases. Metabolites have functional roles in a myriad of biological processes, as substrates and products of enzymatic reactions but also as cofactors and regulators of large numbers of biochemical mechanisms. These functions involve interactions of metabolites with macromolecules. Yet, methods to systematically investigate these interactions are still scarce to date. In particular, there is a need for techniques suited to identify and characterize weak metabolite-macromolecule interactions directly in complex media such as biological fluids. Here, we introduce a method to investigate weak interactions between metabolites and macromolecules in biological fluids. Our approach is based on high-resolution NMR relaxometry and does not require any invasive procedure or separation step. We show that we can detect interactions between small and large molecules in human blood serum and quantify the size of the complex. Our work opens the way for investigations of metabolite (or other small molecules)-protein interactions in biological fluids for interactomics or pharmaceutical applications.

Quantitative NMR-Based Biomedical Metabolomics: Current Status and Applications

Nuclear Magnetic Resonance (NMR) spectroscopy is a quantitative analytical tool commonly utilized for metabolomics analysis. Quantitative NMR (qNMR) is a field of NMR spectroscopy dedicated to the measurement of analytes through signal intensity and its linear relationship with analyte concentration. Metabolomics-based NMR exploits this quantitative relationship to identify and measure biomarkers within complex biological samples such as serum, plasma, and urine. In this review of quantitative NMR-based metabolomics, the advancements and limitations of current techniques for metabolite quantification will be evaluated as well as the applications of qNMR in biomedical metabolomics. While qNMR is limited by sensitivity and dynamic range, the simple method development, minimal sample derivatization, and the simultaneous qualitative and quantitative information provide a unique landscape for biomedical metabolomics, which is not available to other techniques. Furthermore, the non-destructive nature of NMR-based metabolomics allows for multidimensional analysis of biomarkers that facilitates unambiguous assignment and quantification of metabolites in complex biofluids.

An optimized step-by-step protocol for isolation of nucleus pulposus, annulus fibrosus, and end plate cells from the mouse intervertebral discs and subsequent preparation of high-quality intact total RNA

Intervertebral disc degeneration is the most significant, and least understood, cause of chronic back pain, affecting almost one in seven individuals at some point of time. Each intervertebral disc has three components; central nucleus pulposus (NP), concentric layers of annulus fibrosus (AF), and a pair of end plate (EP) that connects the disc to the vertebral bodies. Understanding the molecular and cellular basis of intervertebral disc growth, health, and aging will generate significant information for developing therapeutic approaches. Rapid and efficient preparations of homogeneous and pure cells are crucial for meaningful and rigorous downstream analysis at the cellular, molecular, and biochemical level. Cross-sample contamination may influence the interpretation of the results. In addition to altering gene expression, slow or delayed isolation procedures will also cause the degradation of cells and biomolecules that create a bias in the outcomes of the study. The mouse model system is extensively used to understand the intervertebral disc biology. Here we describe two protocols: (a) for efficient isolation of pure NP, AF, and EP cells from mouse lumbar intervertebral disc. We validated the purity of the NP and AF cells using Shh Cre/+ ; R26 mT/mG/+ dual-fluorescent reporter mice where all NP cells are GPF+ve, and by the sensitive approach of qPCR analysis using TaqMan probes for Shh, and Brachyury as NP-specific markers, Tenomodulin as AF-specific marker, and Osteocalcin as bone-specific marker. (b) For isolation of high-quality intact RNA with RIN of 9.3 to 10 from disc cells. These methods will be useful for the rigorous analysis of NP and AF cells, and improve our understanding of intervertebral disc biology.

Development of a plasma pseudotargeted metabolomics method based on ultra-high-performance liquid chromatography-mass spectrometry

Untargeted methods are typically used in the detection and discovery of small organic compounds in metabolomics research, and ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) is one of the most commonly used platforms for untargeted metabolomics. Although they are non-biased and have high coverage, untargeted approaches suffer from unsatisfying repeatability and a requirement for complex data processing. Targeted metabolomics based on triple-quadrupole mass spectrometry (TQMS) could be a complementary tool because of its high sensitivity, high specificity and excellent quantification ability. However, it is usually applicable to known compounds: compounds whose identities are known and/or are expected to be present in the analyzed samples. Pseudotargeted metabolomics merges the advantages of untargeted and targeted metabolomics and can act as an alternative to the untargeted method. Here, we describe a detailed protocol of pseudotargeted metabolomics using UHPLC-TQMS. An in-depth, untargeted metabolomics experiment involving multiple UHPLC-HRMS runs with MS at different collision energies (both positive and negative) is performed using a mixture obtained using small amounts of the analyzed samples. XCMS, CAMERA and Multiple Reaction Monitoring (MRM)-Ion Pair Finder are used to find and annotate peaks and choose transitions that will be used to analyze the real samples. A set of internal standards is used to correct for variations in retention time. High coverage and high-performance quantitative analysis can be realized. The entire protocol takes ~5 d to complete and enables the simultaneously semiquantitative analysis of 800-1,300 metabolites.

Fecal Metabolomics as a Novel Noninvasive Method for Short-Term Stress Monitoring in Beef Cattle

Traditional measures of short-term stress response such as fecal glucocorticoid metabolites (FGM) are widely used in controlled settings to quantify the intensity of stimulation to which cattle are exposed. However, FGMs present several methodological and interpretation pitfalls when applied on animals in free-ranging conditions. In this study, we proposed an NMR-based fecal metabolomics strategy for noninvasive stress detection in beef cattle. Using a longitudinal sample collection, we monitored the changes in the fecal metabolome and FGM concentrations before and after an acute stressful event. Our results showed that while the fecal metabolome changed as a function of stress (p < 0.001), the mean concentrations of FGM did not change (Levene's test: F-ratio: 0.87, p-value: 0.44). Furthermore, we showed that the interanimal variability observed in the stress response was correlated with the individual fecal microbiota. This result was in line with recent findings, indicating the gut microbiome as a crucial mediator of stress response. We conclude that NMR-based fecal metabolomics proved to be a reliable methodology to assess stress response and that its future applicability to studies for stress monitoring in range animals may be more appropriate than FGM analysis.

Influence of Drying Method on NMR-Based Metabolic Profiling of Human Cell Lines

Metabolic profiling of cell line and tissue extracts involves sample processing that includes a drying step prior to re-dissolving the cell or tissue extracts in a buffer for analysis by GC/LC-MS or NMR. Two of the most commonly used drying techniques are centrifugal evaporation under vacuum (SpeedVac) and lyophilization. Here, NMR spectroscopy was used to determine how the metabolic profiles of hydrophilic extracts of three human pancreatic cancer cell lines, MiaPaCa-2, Panc-1 and AsPC-1, were influenced by the choice of drying technique. In each of the three cell lines, 40-50 metabolites were identified as having statistically significant differences in abundance in redissolved extract samples depending on the drying technique used during sample preparation. In addition to these differences, some metabolites were only present in the lyophilized samples, for example, n-methyl-α-aminoisobutyric acid, n-methylnicotimamide, sarcosine and 3-hydroxyisovaleric acid, whereas some metabolites were only present in SpeedVac dried samples, for example, trimethylamine. This research demonstrates that the choice of drying technique used during the preparation of samples of human cell lines or tissue extracts can significantly influence the observed metabolome, making it important to carefully consider the selection of a drying method prior to preparation of such samples for metabolic profiling.

Metabolomic Analysis of Platelets of Patients With Aspirin Non-Response

Background: Aspirin is the most commonly used antiplatelet agent for the prevention of cardiovascular diseases. However, a certain proportion of patients do not respond to aspirin therapy. The mechanisms of aspirin non-response remain unknown. The unique metabolomes in platelets of patients with coronary artery disease (CAD) with aspirin non-response may be one of the causes of aspirin resistance.

Materials and Methods: We enrolled 29 patients with CAD who were aspirin non-responders, defined as a study subject who were taking aspirin with a platelet aggregation time less than 193 s by PFA-100, and 31 age- and sex-matched patients with CAD who were responders. All subjects had been taking 100 mg of aspirin per day for more than 1 month. Hydrophilic metabolites from the platelet samples were extracted and analyzed by nuclear magnetic resonance (NMR). Both 1D ¹H and 2D J-resolved NMR spectra were obtained followed by spectral processing and multivariate statistical analysis, such as partial least squares discriminant analysis (PLS-DA).

Results: Eleven metabolites were identified. The PLS-DA model could not distinguish aspirin non-responders from responders. Those with low serum glycine level had significantly shorter platelet aggregation time (mean, 175.0 s) compared with those with high serum glycine level (259.5 s). However, this association became non-significant after correction for multiple tests.

Conclusions: The hydrophilic metabolic profile of platelets was not different between aspirin non-responders and responders. An association between lower glycine levels and higher platelet activity in patients younger than 65 years suggests an important role of glycine in the pathophysiology of aspirin non-response.

Missing value imputation for LC-MS metabolomics data by incorporating metabolic network and adduct ion relations

Motivation

Metabolomics data generated from liquid chromatography-mass spectrometry platforms often contain missing values. Existing imputation methods do not consider underlying feature relations and the metabolic network information. As a result, the imputation results may not be optimal.

Results

We proposed an imputation algorithm that incorporates the existing metabolic network, adduct ion relations even for unknown compounds, as well as linear and nonlinear associations between feature intensities to build a feature-level network. The algorithm uses support vector regression for missing value imputation based on features in the neighborhood on the network. We compared our proposed method with methods being widely used. As judged by the normalized root mean squared error in real data-based simulations, our proposed methods can achieve better accuracy.

Availability and implementation

The R package is available at http://web1.sph.emory.edu/users/tyu8/MINMA.

Contact

jiankang@umich.edu or tianwei.yu@emory.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Metabolite Changes in Maternal and Fetal Plasma Following Spontaneous Labour at Term in Humans Using Untargeted Metabolomics Analysis: A Pilot Study

The mechanism of human labour remains poorly understood, limiting our ability to manage complications of parturition such as preterm labour and induction of labour. In this study we have investigated the effect of labour on plasma metabolites immediately following delivery, comparing cord and maternal plasma taken from women who laboured spontaneously and delivered vaginally with women who were delivered via elective caesarean section and did not labour. Samples were analysed using ultra high-performance liquid chromatography-tandem mass spectrometry. Welch’s two-sample t-test was used to identify any significant differences. Of 826 metabolites measured, 26.9% (222/826) were significantly altered in maternal plasma and 21.1% (174/826) in cord plasma. Labour involves changes in many maternal organs and poses acute metabolic demands in the uterus and in the fetus and these are reflected in our results. While a proportion of these differences are likely to be secondary to the physiological demands of labour itself, these results present a comprehensive picture of the metabolome in the maternal and fetal circulations at the time of delivery and can be used to guide future studies. We discuss potential causal pathways for labour including endocannabinoids, ceramides, sphingolipids and steroids. Further work is necessary to confirm the specific pathways involved in the spontaneous onset of labour.

Tackling the Peak Overlap Issue in NMR Metabolomics Studies: 1D Projected Correlation Traces from Statistical Correlation Analysis on Nontilted 2D 1H NMR J-Resolved Spectra

The identification of metabolites in complex biological matrices is a challenging task in 1D ¹H-NMR-based metabolomics studies. Statistical total correlation spectroscopy (STOCSY) has emerged for aiding the structural elucidation by revealing the peaks that present a high correlation to a driver peak of interest (which would likely belong to the same molecule). However, in these studies, the signals from metabolites are normally present as a mixture of overlapping resonances, limiting the performance of STOCSY. As an alternative to avoid the overlap issue, 2D ¹H homonuclear J-resolved (JRES) spectra were projected, in their usual tilted and symmetrized processed form, and STOCSY was applied on these 1D projections (p-JRES-STOCSY). Nonetheless, this approach suffers in cases where the signals are very close. In addition, STOCSY was applied to the whole JRES spectra (also tilted) to identify correlated multiplets, although the overlap issue in itself was not addressed directly and the subsequent search in databases is complicated in cases of higher order coupling. With these limitations in mind, in the present work, we propose a new methodology based on the application of STOCSY on a set of nontilted JRES spectra, detecting peaks that would overlap in 1D spectra of the same sample set. Correlation comparison analysis for peak overlap detection (COCOA-POD) is able to reconstruct projected 1D STOCSY traces that result in more suitable database queries, as all peaks are summed at their f2 resonances instead of the resonance corresponding to the multiplet center in the tilted JRES spectra. (The peak dispersion and resolution enhancement gained are not sacrificed by the projection.) Besides improving database queries with better peak lists obtained from the projections of the 2D STOCSY analysis, the overlap region is examined, and the multiplet itself is analyzed from the correlation trace at 45° to obtain a cleaner multiplet profile, free from contributions from uncorrelated neighboring peaks.

Emerging Applications of Metabolomics in Traditional Chinese Medicine Treating Hypertension: Biomarkers, Pathways and More

Hypertension is a prevalent, complex, and polygenic cardiovascular disease, which is associated with increased mortality and morbidity. Across the world, traditional Chinese medicine (TCM) constituted by herbal medicine and non-pharmacological therapies is used to assist blood pressure management. Though widely accepted in daily practice, its mechanism remains largely unknown. Recent years saw a number of studies utilizing metabolomics technologies to elucidate the biological foundation of the antihypertensive effect of TCM. Metabolomics is a relatively "young" omics approach that has gained enormous attention recently in cardiovascular drug discovery and pharmacology studies of natural products. In this review, we described the use of metabolomics in deciphering TCM diagnostic codes for hypertension and in revealing molecular events that drive the antihypertensive effect. By corroborating the diagnostic rules, there's accumulating evidence showing that metabolic profile could be the signature of different syndromes/patterns of hypertension, which offers new perspectives for disease diagnosis and efficacy optimization. Moreover, TCM treatment significantly altered the metabolic perturbations associated with hypertension, which could be a crucial mechanism of the therapeutic effect of TCM. Not only significantly rebalances the dynamics of metabolic flux, TCM but also elicits metabolic network reorganization through restoring the functions of key metabolites, and metabolic pathways. The role of TCM in regulating metabolic perturbations will be informative to researchers seeking new leads for drug discovery. This review further envisioned the promises of employing metabolomics to explore network pharmacology, host-gut microbiota interactions and metabolic reprogramming in TCM, and possible herb-drug interactions in this field in future.

Identification of antiplasmodial triterpenes from Keetia species using NMR-based metabolic profiling

INTRODUCTION

The increase in multidrug resistance and lack of efficacy in malaria therapy has propelled the urgent discovery of new antiplasmodial drugs, reviving the screening of secondary metabolites from traditional medicine. In plant metabolomics, NMR-based strategies are considered a golden method providing both a holistic view of the chemical profiles and a correlation between the metabolome and bioactivity, becoming a corner stone of drug development from natural products.

OBJECTIVE

Create a multivariate model to identify antiplasmodial metabolites from ¹H NMR data of two African medicinal plants, Keetia leucantha and K. venosa.

METHODS

The extracts of twigs and leaves of Keetia species were measured by ¹H NMR and the spectra were submitted to orthogonal partial least squares (OPLS) for antiplasmodial correlation.

RESULTS

Unsupervised ¹H NMR analysis showed that the effect of tissues was higher than species and that triterpenoids signals were more associated to Keetia twigs than leaves. OPLS-DA based on Keetia species correlated triterpene signals to K. leucantha, exhibiting a higher concentration of triterpenoids and phenylpropanoid-conjugated triterpenes than K. venosa. In vitro antiplasmodial correlation by OPLS, validated for all Keetia samples, revealed that phenylpropanoid-conjugated triterpenes were highly correlated to the bioactivity, while the acyclic squalene was found as the major metabolite in low bioactivity samples.

CONCLUSION

NMR-based metabolomics combined with supervised multivariate data analysis is a powerful strategy for the identification of bioactive metabolites in plant extracts. Moreover, combination of statistical total correlation spectroscopy with 2D NMR allowed a detailed analysis of different triterpenes, overcoming the challenge posed by their structure similarity and coalescence in the aliphatic region.

Salivary and urinary metabolome analysis for pre-puberty-related biomarkers identification in porcine

Estrus synchronization is important for optimal management of gilt reproduction in pig farms. Hormonal treatments, such as synthetic progestogens, are used on a routine basis, but there is a growing demand for non-hormonal alternative breeding tools. Before puberty, gilts exhibit a ‘waiting period,’ related to the ovarian development and gonadotrophin secretions, during which external stimulations, such as boar exposure, could induce and synchronize first ovulation. Practical non-invasive tools for identification of this period in farms are lacking. During this period, urinary oestrone levels are high, but urine sampling is difficult in group-housed females. The aim of this work was to search for specific biomarkers of the ‘waiting period’ in saliva and urine. In total, nine 144- to 147-day-old Large White gilts were subjected to trans-abdominal ultrasonography three times a week for 5 weeks until puberty detection (week –5 to week –1 before puberty). Urine and saliva samples were collected for oestrone assay to detect the ‘waiting period’ and for metabolome analysis using ¹H-nuclear magnetic resonance spectroscopy to detect potential biomarkers of the ‘waiting period.’ Gilts were slaughtered 7 days after puberty detection for puberty confirmation. Results were consistent with ultrasonography data for six gilts. Urine and saliva samples from these six gilts were analyzed. Urinary estrone concentration significantly increased 2 weeks before puberty detection. Metabolome analysis of urine samples allowed the identification of 78 spectral bins, among them, 42 low-molecular-weight metabolites were identified. Metabolome analysis of salivary samples allowed the identification of 59 spectral bins, among them, 23 low-molecular-weight metabolites were detected and 17 were identified. No potential biomarker was identified in urinary samples. In saliva, butyrate and 2HOvalerate, 5.79 ppm (putatively uridine), formate, malonate and propionate could be biomarker candidates to ascertain the pre-puberty period in gilt reproduction. These results confirm that non-invasive salivary samples could allow the identification of the physiological status of the gilts and presumably the optimal time for application of the boar effect. This could contribute to synchronize puberty onset and hence to develop non-hormonal breeding tools.

Significant metabolic improvement by a water extract of olives: animal and human evidence

PURPOSE

Dyslipidemia and impaired glucose metabolism are the main health issues of growing prevalence and significant high healthcare cost, requiring novel prevention and/or therapeutic approaches. Epidemiological and animal studies revealed that olive oil is an important dietary constituent, inducing normolipidemia. However, no studies have specifically investigated the polyphenol-rich water extract of olives (OLWPE), generated during olive oil production.

METHODS

In the present work, we initially examined the effect of OLPWE on animals' metabolic parameters. Rats fed with a high-fat diet were treated with three different doses of OLPWE for 4 months. Additionally, bioavailability was explored. Afterwards, OLWPE's metabolic effect was explored in humans. Healthy volunteers consumed microencapsulated OLWPE for 4 weeks, in a food matrix [one portion (30 g) of a meat product].

RESULTS

High-fat-fed rats developed a metabolic dysfunction, with increased LDL and insulin levels and decreased HDL; this syndrome was significantly impaired when treated with OLWPE. Treated rats had increased total plasma antioxidant capacity, while several phenolic compounds were detected in their blood. These findings were also verified in humans that consumed OLWPE, daily, for 4 weeks. Interestingly, in individuals with elements of cardio-metabolic risk, OLWPE consumption resulted in reduced glucose, insulin, total cholesterol, LDL and oxLDL levels.

CONCLUSIONS

Our data clearly show that OLWPE can improve glucose and lipid profile, indicating its possible use in the design of functional food and/or therapeutic interventions.

Pre-clinical Pharmacokinetic and Metabolomic Analyses of Isorhapontigenin, a Dietary Resveratrol Derivative

Background: Isorhapontigenin (trans-3,5,4'-trihydroxy-3'-methoxystilbene, ISO), a dietary resveratrol (trans-3,5,4'-trihydroxystilbene) derivative, possesses various health-promoting activities. To further evaluate its medicinal potentials, the pharmacokinetic and metabolomic profiles of ISO were examined in Sprague-Dawley rats. Methods: The plasma pharmacokinetics and metabolomics were monitored by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-tandem mass spectrometry (GC-MS/MS), respectively. Results: Upon intravenous injection (90 μmol/kg), ISO exhibited a fairly rapid clearance (CL) and short mean residence time (MRT). After a single oral administration (100 μmol/kg), ISO was rapidly absorbed and showed a long residence in the systemic circulation. Dose escalation to 200 μmol/kg resulted in higher dose-normalized maximal plasma concentrations (C_max/Dose), dose-normalized plasma exposures (AUC/Dose), and oral bioavailability (F). One-week repeated daily dosing of ISO did not alter its major oral pharmacokinetic parameters. Pharmacokinetic comparisons clearly indicated that ISO displayed pharmacokinetic profiles superior to resveratrol as its C_max/Dose, AUC/Dose, and F were approximately two to three folds greater than resveratrol. Metabolomic investigation revealed that 1-week ISO administration significantly reduced plasma concentrations of arachidonic acid, cholesterol, fructose, allantoin, and cadaverine but increased tryptamine levels, indicating its impact on metabolic pathways related to health-promoting effects. Conclusion: ISO displayed favorable pharmacokinetic profiles and may be a promising nutraceutical in view of its health-promoting properties.

Anti-ageing effect of red ginseng revealed by urinary metabonomics using RRLC-Q-TOF-MS

INTRODUCTION

Red ginseng (RG) is one of the main processed products of the roots and rhizomes of Panax ginseng C.A. Meyer and is used for anti-ageing. But how metabonomic influences of RG on the progress of ageing are less researched.

OBJECTIVE

A metabonomic method was developed to study the characters of the ageing process and the effects of total ginsenosides of red ginseng (TGRG) on the progress of ageing.

METHODS

Urine samples from four different ages (4, 12, 18 and 24 months old) of rats and interference after TGRG were analysed by rapid resolution liquid chromatography coupled with quadruple-time-of-flight mass spectrometry (RRLC-Q-TOF-MS) and multivariate statistical analysis were performed for the pattern recognition and characteristic metabolites identification.

RESULTS

Fourteen potential biomarkers were found and identified by MS/MS analysis by referring to authentic chemicals. The analysis of metabolic pathways indicated that the reduced energy and lipid metabolism, the decline of kidney function and amino acids metabolism disorders were the main features of ageing. After TGRG administration, lipid and amino acids metabolism of 18 and 24 month-old rats were adjusted to restore a younger level, and nine related biomarkers in the ageing process reset to a younger level were recognised.

CONCLUSION

These changes showed that TGRG may produce an anti-ageing effect by intervening in the lipid metabolism and correcting the amino acid metabolism disorders in ageing rats.

Metabolomics study of the therapeutic mechanism of Schisandra chinensis lignans on aging rats induced by d-galactose

Objective

The aim of this study was to evaluate the antiaging effect of Schisandra chinensis lignans (SCL) by analyzing the characteristics in the serum of d-galactose (d-gal)-induced rats.

Methods

Forty male Wistar rats were randomly divided into control group, d-gal model group, low-dose SCL group (50 mg/kg/d), medium-dose SCL group (100 mg/kg/d), and high-dose SCL group (200 mg/kg/d). A serum metabolomics analysis method based on rapid resolution liquid chromatography coupled with quadruple-time-of-flight mass spectrometry was carried out to study the characteristics of d-gal-induced aging rats and evaluate the antiaging effects of SCL, and multivariate statistical analysis was performed for pattern recognition and characteristic metabolites identification. The relative levels of p19, p53, and p21 genes in the brain tissue were measured by quantitative real-time polymerase chain reaction for investigating the underlying mechanism.

Results

Metabolomics analysis showed that 15 biomarkers were identified and 13 of them recovered to the normal levels after the administration of SCL. Based on the pathway analysis, the antiaging mechanisms of SCL might be involved in the following metabolic pathways: energy, amino acid, lipid, and phospholipid metabolism. Furthermore, SCL significantly inhibited the mRNA expression level of p19, p53, and p21 in the brain of aging rats induced by d-gal.

Conclusion

These results suggest that SCL can delay rat aging induced by d-gal through multiple pathways.

Metabolomics: From liver chiromancy to personalized precision medicine in advanced chronic liver disease

Currently there is a lack of accurate biomarkers for diagnosis and prognosis in advanced liver diseases. Either the occurrence of first decompensation, or diagnosis of acute on chronic liver failure, severe alcoholic hepatitis, or hepatocellular carcinoma (HCC), none of the available biomarkers are satisfactory. Metabolomics is the newest of omics, being much closer than the others to the actual phenotype and pathologic changes that characterizes a certain condition. It deals with a much wider spectrum of low molecular weight bio-compounds providing a powerful platform for discovering novel biomarkers and biochemical pathways to improve diagnostic, prognostication and therapy. Until now metabolomics was applied in a wide spectrum of liver conditions, but the findings were contradictory. This review proposes a synthesis of the existing evidences of metabolomics use in advanced chronic liver diseases, decompensated liver cirrhosis, severe alcoholic hepatitis and HCC.

Recommended strategies for spectral processing and post-processing of 1D 1H-NMR data of biofluids with a particular focus on urine

1H NMR spectra from urine can yield information-rich data sets that offer important insights into many biological and biochemical phenomena. However, the quality and utility of these insights can be profoundly affected by how the NMR spectra are processed and interpreted. For instance, if the NMR spectra are incorrectly referenced or inconsistently aligned, the identification of many compounds will be incorrect. If the NMR spectra are mis-phased or if the baseline correction is flawed, the estimated concentrations of many compounds will be systematically biased. Furthermore, because NMR permits the measurement of concentrations spanning up to five orders of magnitude, several problems can arise with data analysis. For instance, signals originating from the most abundant metabolites may prove to be the least biologically relevant while signals arising from the least abundant metabolites may prove to be the most important but hardest to accurately and precisely measure. As a result, a number of data processing techniques such as scaling, transformation and normalization are often required to address these issues. Therefore, proper processing of NMR data is a critical step to correctly extract useful information in any NMR-based metabolomic study. In this review we highlight the significance, advantages and disadvantages of different NMR spectral processing steps that are common to most NMR-based metabolomic studies of urine. These include: chemical shift referencing, phase and baseline correction, spectral alignment, spectral binning, scaling and normalization. We also provide a set of recommendations for best practices regarding spectral and data processing for NMR-based metabolomic studies of biofluids, with a particular focus on urine.

Peripheral inflammatory markers in Alzheimer's disease: a systematic review and meta-analysis of 175 studies

OBJECTIVES

Increasing evidence suggests that inflammation is involved in Alzheimer's disease (AD) pathology. This study quantitatively summarised the data on peripheral inflammatory markers in patients with AD compared with healthy controls (HC).

METHODS

Original reports containing measurements of peripheral inflammatory markers in AD patients and HC were included for meta-analysis. Standardised mean differences were calculated using a random effects model. Meta-regression and exploration of heterogeneity was performed using publication year, age, gender, Mini-Mental State Examination (MMSE) scores, plasma versus serum measurements and immunoassay type.

RESULTS

A total of 175 studies were combined to review 51 analytes in 13 344 AD and 12 912 HC patients. Elevated peripheral interleukin (IL)-1β, IL-2, IL-6, IL-18, interferon-γ, homocysteine, high-sensitivity C reactive protein, C-X-C motif chemokine-10, epidermal growth factor, vascular cell adhesion molecule-1, tumour necrosis factor (TNF)-α converting enzyme, soluble TNF receptors 1 and 2, α1-antichymotrypsin and decreased IL-1 receptor antagonist and leptin were found in patients with AD compared with HC. IL-6 levels were inversely correlated with mean MMSE scores.

CONCLUSIONS

These findings suggest that AD is accompanied by a peripheral inflammatory response and that IL-6 may be a useful biological marker to correlate with the severity of cognitive impairment. Further studies are needed to determine the clinical utility of these markers.

Metabolomics study of the therapeutic mechanism of Schisandra Chinensis lignans in diet-induced hyperlipidemia mice

Background

Schisandra, a globally distributed plant, has been widely applied for the treatment of diseases such as hyperlipidemia, fatty liver and obesity in China. In the present work, a rapid resolution liquid chromatography coupled with quadruple-time-of-flight mass spectrometry (RRLC-Q-TOF-MS)-based metabolomics was conducted to investigate the intervention effect of Schisandra chinensis lignans (SCL) on hyperlipidemia mice induced by high-fat diet (HFD).

Methods

Hyperlipidemia mice were orally administered with SCL (100 mg/kg) once a day for 4 weeks. Serum biochemistry assay of triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c) and high-density lipoprotein cholesterol (HDL-c) was conducted to confirm the treatment of SCL on lipid regulation. Metabolomics analysis on serum samples was carried out, and principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were carried out for the pattern recognition and characteristic metabolites identification. The relative levels of critical regulatory factors of liver lipid metabolism, sterol regulatory element-binding proteins (SREBPs) and its related gene expressions were measured by quantitative real-time polymerase chain reaction (RT-PCR) for investigating the underlying mechanism.

Results

Oral administration of SCL significantly decreased the serum levels of TC, TG and LDL-c and increased the serum level of HDL-c in the hyperlipidemia mice, and no effect of SCL on blood lipid levels was observed in control mice. Serum samples were scattered in the PCA scores plots in response to the control, HFD and SCL group. Totally, thirteen biomarkers were identified and nine of them were recovered to the normal levels after SCL treatment. Based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis, the anti-hyperlipidemia mechanisms of SCL may be involved in the following metabolic pathways: tricarboxylic acid (TCA) cycle, synthesis of ketone body and cholesterol, choline metabolism and fatty acid metabolism. Meanwhile, SCL significantly inhibited the mRNA expression level of hepatic lipogenesis genes such as SREBP-1c, fatty acid synthase (FAS) and acetyl-CoA carboxylase (ACC), and decreased the mRNA expression of liver X receptor α (LXRα). Moreover, SCL also significantly decreased the expression level of SREBP-2 and 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) in the liver of hyperlipidemia mice.

Conclusion

Anti-hyperlipidemia effect of SCL was confirmed by both serum biochemistry and metabolomics analysis. The mechanism may be related to the down-regulation of LXRα/SREBP-1c/FAS/ACC and SREBP2/HMGCR signaling pathways.

Renal Medulla is More Sensitive to Cisplatin than Cortex Revealed by Untargeted Mass Spectrometry-Based Metabolomics in Rats

Nephrotoxicity has long been the most severe and life-threatening side-effect of cisplatin, whose anticancer effect is therefore restricted. Previous pathological studies have shown that both renal cortex and medulla could be injured by cisplatin. Our TUNEL (terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling) assay results further uncovered that medulla subjected more severe injury than cortex. In order to depict the underlying metabolic mechanism of spatial difference in response to cisplatin, in the present study, mass spectrometry-based untargeted metabolomics approach was applied to profile renal cortex and medulla metabolites of rat after receiving a single dose of cisplatin (2.5, 5 or 10 mg/kg). Eventually, 53 and 55 differential metabolites in cortex and medulla were screened out, respectively. Random forest, orthogonal partial least squares-discriminant analysis and metabolic cumulative fold change analysis revealed that metabolic changes in medulla were more obviously dose-dependent than those in cortex, which confirmed the conclusion that medulla was more sensitive to cisplatin exposure. Furthermore, 29 intermediates were recognized as the most contributive metabolites for the sensitivity difference. Metabolic pathways interrupted by cisplatin mainly included amino acid, energy, lipid, pyrimidine, purine, and creatine metabolism. Our findings provide new insight into the mechanism study of cisplatin-induced nephrotoxicity.

Association of blood lipids with Alzheimer's disease: A comprehensive lipidomics analysis

INTRODUCTION

The aim of this study was to (1) replicate previous associations between six blood lipids and Alzheimer's disease (AD) (Proitsi et al 2015) and (2) identify novel associations between lipids, clinical AD diagnosis, disease progression and brain atrophy (left/right hippocampus/entorhinal cortex).

METHODS

We performed untargeted lipidomic analysis on 148 AD and 152 elderly control plasma samples and used univariate and multivariate analysis methods.

RESULTS

We replicated our previous lipids associations and reported novel associations between lipids molecules and all phenotypes. A combination of 24 molecules classified AD patients with >70% accuracy in a test and a validation data set, and we identified lipid signatures that predicted disease progression (R2 = 0.10, test data set) and brain atrophy (R2 ≥ 0.14, all test data sets except left entorhinal cortex). We putatively identified a number of metabolic features including cholesteryl esters/triglycerides and phosphatidylcholines.

DISCUSSION

Blood lipids are promising AD biomarkers that may lead to new treatment strategies.

Metabolomic blood test: purpose, implementation and interpretation of data

The human body is an open system that receives a variety of xenobiotics in the course of dietary route or respiration and in the form of the drugs. As a lump sum scores of toxic and potentially toxic substances are detected in a human body that significantly affect health and human lifespan. There are also thousands of diseases, dozens of which latently occur in the body of each person. Traditional diagnosis is not able to screen all the variety of xenobiotics and potential human diseases. For this purpose metabolomic blood test is available which is of non-targeted (review) nature. The test can reveal all the diversity of low molecular weight substances in blood, including tens of thousands of xenobiotics and markers of different diseases. Detection of xenobiotics in the blood, directional detoxification and subsequent monitoring of “body's chemical purity” together with the control of “normality” of all biochemical processes in the organism, using metabolomics blood tests is a necessary and presumably a sufficient condition in the implementation of inherent human genotype longevity. This article describes the purpose, implementation and interpretation of metabolomic blood test facilitating the implementation of this method in the Russian Federation, in order to significantly increase the average life expectancy.

High-throughput and multi-dimensional omics approach uncovers a huaxian capsule to ameliorate the dysregulated expression profiling of severe sepsis rats

Multi-dimensional omics could be helpful to interpret the underlying mechanisms of disease.

FREE FATTY ACIDS PROFILING IN RESPONSE TO CARNITINE SYNERGIZE WITH LUTEIN IN DIABETIC RATS

BACKGROUND

The objective of this study was to investigate the fatty acids profiling in diabetic rats induced by sterptozocine (STZ) and their response to administration of lutein and carnitine.

MATERIALS AND METHODS

Ninety male albino rats were divided into 6 groups as follows: Normal control. The remaining rats were injected i.p a single dose of STZ (65 mg /kg bw) for induction of diabetes. Diabetic rats were grouped as: GP II: (Untreated): GP III: Rats were given orally with L-lutein (100 mg/kg bw).GP IV: Rats were given carnitine (30 μg/kg) i.p. GP V: Rats were given carnitine and lutein GP VI were given metformin (100mg/kg bw/d) for 6 weeks.

RESULTS

Treatment of diabetic rats with lutein, L-carnitine, combined decreased the levels of glucose, HA1C compared with untreated diabetic (p<0.001). Administration of L-lutein, carnitine, combined to normal rats significantly decreased the levels of myristic, palmitice, palmitoleic, stearic, linoleic, α-linolenic, arachidic and eicosadienoic when compared with control normal rats (p<0.001).

CONCLUSION

Abnormalities of fatty acids composition was observed in diabetic rats. Combination treatment with lutein and carnitine could ameliorate deleterious effect induced by STZ and attenuate the changed fatty acid composition.

Noninvasive metabolic profiling for painless diagnosis of human diseases and disorders

Metabolic profiling provides a powerful diagnostic tool complementary to genomics and proteomics. The pain, discomfort and probable iatrogenic injury associated with invasive or minimally invasive diagnostic methods, render them unsuitable in terms of patient compliance and participation. Metabolic profiling of biomatrices like urine, breath, saliva, sweat and feces, which can be collected in a painless manner, could be used for noninvasive diagnosis. This review article covers the noninvasive metabolic profiling studies that have exhibited diagnostic potential for diseases and disorders. Their potential applications are evident in different forms of cancer, metabolic disorders, infectious diseases, neurodegenerative disorders, rheumatic diseases and pulmonary diseases. Large scale clinical validation of such diagnostic methods is necessary in future.

Emerging applications of metabolomics in drug discovery and precision medicine

Metabolomics is an emerging 'omics' science involving the comprehensive characterization of metabolites and metabolism in biological systems. Recent advances in metabolomics technologies are leading to a growing number of mainstream biomedical applications. In particular, metabolomics is increasingly being used to diagnose disease, understand disease mechanisms, identify novel drug targets, customize drug treatments and monitor therapeutic outcomes. This Review discusses some of the latest technological advances in metabolomics, focusing on the application of metabolomics towards uncovering the underlying causes of complex diseases (such as atherosclerosis, cancer and diabetes), the growing role of metabolomics in drug discovery and its potential effect on precision medicine.

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.

Probiotic supplementation influences faecal short chain fatty acids in infants at high risk for eczema

The composition of the gut microbiota plays a role in the development of allergies. Based on the immunomodulating capacities of bacteria, various studies have investigated the potential role for probiotics in the prevention of childhood eczema. In a previous study we have shown that significantly less children developed eczema after probiotic supplementation (Bifidobacterium bifidum W23, Bifidobacterium animalis subsp. lactis W52 and Lactococcus lactis W58, Ecologic®Panda) at three months of age as compared to controls. Here, metabolites in faecal samples of these 3-month old children were measured by 1H-nuclear magnetic resonance to investigate possible gut metabolic alterations. Lower amounts of short-chain fatty acids (SCFAs), succinate, phenylalanine and alanine were found in faecal samples of children later developing eczema, whereas the amounts of glucose, galactose, lactate and lactose were higher compared to the children not developing eczema. Although these differences were already present at the age of 3 months, eczema did not develop in the majority of children before the age of 1 year. Supplementation of multispecies probiotics seems to induce higher levels of lactate and SCFAs, and lower levels of lactose and succinate when compared with the placebo group. This might explain the temporary preventive effect of probiotics on the development of eczema. These results highlight the role bacterial metabolites may play in development of the immune system, even before clinical manifestations of allergic disease arise.

LC-MS untargeted metabolomic analysis of drug-induced hepatotoxicity in HepG2 cells

Hepatotoxicity is the number one cause for agencies not approving and withdrawing drugs for the market. Drug-induced human hepatotoxicity frequently goes undetected in preclinical safety evaluations using animal models. Human-derived in vitro models represent a common alternative to in vivo tests to detect toxic effects during preclinical testing. Most current in vitro toxicity assays rely on the measurement of nonspecific or low sensitive endpoints, which result in poor concordance with human liver toxicity. Therefore, making more accurate predictions of the potential hepatotoxicity of new drugs remains a challenge. Metabolomics, whose aim is to globally assess all the metabolites present in a biological sample, may represent an alternative in the search for sensitive sublethal markers of drug-induced hepatotoxicity. To this end, a comprehensive LC-MS-based untargeted metabolite profiling analysis of HepG2 cells, exposed to a set of well-described model hepatotoxins and innocuous compounds, was performed. It allowed to determine meaningful metabolic changes triggered by a toxic insult and gave a first estimation of the main toxicity-related pathways. Based on these metabolic patterns, a partial least squares-discriminant analysis model, able to discriminate between nontoxic and hepatotoxic compounds, was constructed. The approach described herein may provide an alternative for animal testing in preclinical stages of drug development and a controlled experimental approach to gain a better understanding of the underlying causes of hepatotoxicity.