Workflow methodology for rat brain metabolome exploration using NMR, LC–MS and GC–MS analytical platforms

Temporal metabolomics state in pregnant rat: Analysis of amniotic fluid, placenta, and maternal plasma at embryonic and fetal time points

INTRODUCTION

During pregnancy, the dynamic metabolic demands for fetal growth require a continuous supply of essential metabolites. Understanding maternal metabolome changes during gestation is crucial for predicting disease risks in neonates.

METHODS

The study aimed to characterize the placental and amniotic fluid (AF) metabolomes during gestation in rats at gestational days GD-13 and 19 reflecting the end of the embryonic and fetal periods, respectively, and the maternal plasma, using metabolomics (LC-MS) and chemometrics. The objective was to highlight, through univariate and multivariate analyses, the complementarity of the data obtained from these different biological matrices.

RESULTS

The biological matrix had more impact on the metabolome composition than the gestational stage. The placental and AF metabolomes showed specific metabolome evolving over the two gestational stages. Analyzing the three targeted metabolomes revealed evolving pathways in arginine and proline metabolism/glutathione metabolism and phenylalanine metabolism; purine metabolism; and carbohydrate metabolism. Significantly, lipid metabolism in the placenta exhibited substantial changes with higher levels of certain phosphatidylethanolamine and sphingomyelins at GD19 while some cholesteryl esters and some glycosphingolipids levels being in higher levels at GD13.

DISCUSSION

These data highlight the metabolic gradients (mainly in placenta, also in AF, but only a few in plasma) observed through embryonic patterning and organ development during mid-to late gestation.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Untargeted metabolomic study by liquid chromatography-mass spectrometry in brain tissues on the effects of combined cocaine and ethanol self-administration in male and female young rats

The combined use of ethanol and cocaine is frequent among drug-abuse users and leads to further exacerbation of health consequences compared to individual consumption and this is of special concern during the transition to adulthood. Despite its high prevalence, the effect of combined consumption of cocaine and ethanol has been scarcely studied. In this work, we report the first untargeted metabolomic study in brain tissues to contribute to the advancement in the knowledge of the possible neurobiological effects of this polysubstance dependence. Liquid Chromatography coupled to high resolution Mass Spectrometry was employed to analyze three different brain tissues samples, prefrontal cortex, striatum and hippocampus, from male and female young rats exposed intravenously to a self-administration of these drugs. After optimizing the best sample treatment and selecting the chromatographic and detection conditions to find the maximum number of significant features (possible biomarker metabolites), the high resolution of the Orbitrap analyzer used in this work has made it possible to find up to 761 significant features with assigned molecular formula, of which up to 190 were tentatively identified and 44 unequivocally confirmed. The results demonstrated that the altered metabolic pathways are involved in multiple functions: receptor systems, such as the Glutamine-Glutamic acid-GABA axis or the catecholamine pathway, purinergic and pyrimidine pathways, fatty acids or oxidative stress, among others.

Validation of metabolomic and lipidomic analyses of human tears using ultra-high-performance liquid chromatography tandem mass spectrometry

To facilitate application in ophthalmological and systemic diseases, there is a need to standardize preanalytical and analytical steps for metabo-lipidomics in human tears. We assessed different methods for each step of the workflow, from sampling to omics profiles acquisition, to provide the largest metabo-lipidomic coverage with the most robust analytical criteria in human tears. We compared reproducibility according to different extraction methods, two sampling techniques, three volumes (2 μL, 5 μL, 10 μL) and eye laterality using ultra-high-performance liquid chromatography coupled with tandem high-resolution mass spectrometry for metabolomic and lipidomic application. The effect of age on the tear metabo-lipidome was also investigated in healthy subjects. The extraction method using methanol/water provided the best results for Schirmer strip metabolomics, while Folch extraction was superior for lipidomics, whatever the sampling method used. When comparing both sampling methods, microcapillary glass tube was superior to Schirmer strip for metabolomics but comparable for lipidomics. The 5 μL volume provided a satisfying metabo-lipidomic coverage. There was no significant difference in tear metabo-lipidome between both eyes in healthy subjects. While most metabolites and lipids where not influenced by age, the phenylalanine-tyrosine-tryptophan pathway, aminoacyl t-RNA biosynthesis, and alanine-aspartate-glutamate metabolism were the 3 principal pathways associated with the 15 most variable metabolites according to age. The current findings will contribute to improve metabo-lipidomic workflow in human tears for the identification of new biomarkers. Preanalytical and analytical standardization is mandatory in order to perform better between-study comparisons and increase the chances of transferring laboratory findings into clinical practice.

Sánchez B, León C, Nozal L, Mora-Rodríguez JM, Castro F, Crego AL, Díaz-Laviada I. Metabolic fingerprinting of chemotherapy-resistant prostate cancer stem cells. An untargeted metabolomic approach by liquid chromatography-mass spectrometry

Chemoresistance is one of the most important challenges in cancer therapy. The presence of cancer stem cells within the tumor may contribute to chemotherapy resistance since these cells express high levels of extrusion pumps and xenobiotic metabolizing enzymes that inactivate the therapeutic drug. Despite the recent advances in cancer cell metabolism adaptations, little is known about the metabolic adaptations of the cancer stem cells resistant to chemotherapy. In this study, we have undertaken an untargeted metabolomic analysis by liquid chromatography–high-resolution spectrometry combined with cytotoxicity assay, western blot, quantitative real-time polymerase chain reaction (qPCR), and fatty acid oxidation in a prostate cancer cell line resistant to the antiandrogen 2-hydroxiflutamide with features of cancer stem cells, compared to its parental androgen-sensitive cell line. Metabolic fingerprinting revealed 106 out of the 850 metabolites in ESI+ and 67 out of 446 in ESI- with significant differences between the sensitive and the resistant cell lines. Pathway analysis performed with the unequivocally identified metabolites, revealed changes in pathways involved in energy metabolism as well as posttranscriptional regulation. Validation by enzyme expression analysis indicated that the chemotherapy-resistant prostate cancer stem cells were metabolically dormant with decreased fatty acid oxidation, methionine metabolism and ADP-ribosylation. Our results shed light on the pathways underlying the entry of cancer cells into dormancy that might contribute to the mechanisms of drug resistance.

Metabolomics application for the design of an optimal diet

Precision nutrition is an emerging branch of nutrition science that aims to use modern omics technologies (genomics, proteomics, and metabolomics) to assess an individual's response to specific foods or dietary patterns and thereby determine the most effective diet or lifestyle interventions to prevent or treat specific diseases. Metabolomics is vital to nearly every aspect of precision nutrition. It can be targeted or untargeted, and it has many applications. Indeed, it can be used to comprehensively characterize the thousands of chemicals in foods, identify food by-products in human biofluids or tissues, characterize nutrient deficiencies or excesses, monitor biochemical responses to dietary interventions, track long- or short-term dietary habits, and guide the development of nutritional therapies. Indeed, metabolomics can be coupled with genomics and proteomics to study and advance the field of precision nutrition. Integrating omics with epidemiological and clinical data will begin to define the beneficial effects of human food metabolites. In this review, we present the metabolome and its relationship to precision nutrition. Moreover, we describe the different techniques used in metabolomics and present how metabolomics has been applied to advance the field of precision nutrition by providing notable examples and cases.

First Metabolomic Signature of Blood-Brain Barrier Opening Induced by Microbubble-Assisted Ultrasound

Microbubble (MB)-assisted ultrasound (US) is a promising physical method to increase non-invasively, transiently, and precisely the permeability of the blood-brain barrier (BBB) to therapeutic molecules. Previous preclinical studies established the innocuity of this procedure using complementary analytical strategies including transcriptomics, histology, brain imaging, and behavioral tests. This cross-sectional study using rats aimed to investigate the metabolic processes following acoustically-mediated BBB opening in vivo using multimodal and multimatrices metabolomics approaches. After intravenous injection of MBs, the right striata were exposed to 1-MHz sinusoidal US waves at 0.6 MPa peak negative pressure with a burst length of 10 ms, for 30 s. Then, the striata, cerebrospinal fluid (CSF), blood serum, and urine were collected during sacrifice in three experimental groups at 3 h, 2 days, and 1 week after BBB opening (BBBO) and were compared to a control group where no US was applied. A well-established analytical workflow using nuclear magnetic resonance spectrometry and non-targeted and targeted high-performance liquid chromatography coupled to mass spectrometry were performed on biological tissues and fluids. In our experimental conditions, a reversible BBBO was observed in the striatum without physical damage or a change in rodent weight and behavior. Cerebral, peri-cerebral, and peripheral metabolomes displayed specific and sequential metabolic kinetics. The blood serum metabolome was more impacted in terms of the number of perturbated metabolisms than in the CSF, the striatum, and the urine. In addition, perturbations of arginine and arginine-related metabolisms were detected in all matrices after BBBO, suggesting activation of vasomotor processes and bioenergetic supply. The exploration of the tryptophan metabolism revealed a transient vascular inflammation and a perturbation of serotoninergic neurotransmission in the striatum. For the first time, we characterized the metabolic signature following the acoustically-mediated BBBO within the striatum and its surrounding biological compartments.

Metabolomic Studies in Inner Ear Pathologies

Sensorineural hearing loss is the most common sensory deficit. The etiologies of sensorineural hearing loss have been described and can be congenital or acquired. For congenital non-syndromic hearing loss, mutations that are related to sites of cochlear damage have been discovered (e.g., connexin proteins, mitochondrial genes, etc.). For cytomegalovirus infection or auditory neuropathies, mechanisms are also well known and well researched. Although the etiologies of sensorineural hearing loss may be evident for some patients, the damaged sites and pathological mechanisms remain unclear for patients with progressive post-lingual hearing loss. Metabolomics is an emerging technique in which all metabolites present in a sample at a given time are analyzed, reflecting a physiological state. The objective of this study was to review the literature on the use of metabolomics in hearing loss. The findings of this review suggest that metabolomic studies may help to develop objective tests for diagnosis and personalized treatment.

Metabolic Impact of Anticancer Drugs Pd2Spermine and Cisplatin on the Brain of Healthy Mice

The new palladium agent Pd2Spermine (Spm) has been reported to exhibit promising cytotoxic properties, while potentially circumventing the known disadvantages associated to cisplatin therapeutics, namely acquired resistance and high toxicity. This work presents a nuclear magnetic resonance (NMR) metabolomics study of brain extracts obtained from healthy mice, to assess the metabolic impacts of the new Pd2Spm complex in comparison to that of cisplatin. The proton NMR spectra of both polar and nonpolar brain extracts were analyzed by multivariate and univariate statistics, unveiling several metabolite variations during the time course of exposition to each drug (1–48 h). The distinct time-course dependence of such changes revealed useful information on the drug-induced dynamics of metabolic disturbances and recovery periods, namely regarding amino acids, nucleotides, fatty acids, and membrane precursors and phospholipids. Putative biochemical explanations were proposed, based on existing pharmacokinetics data and previously reported metabolic responses elicited by the same metal complexes in the liver of the same animals. Generally, results suggest a more effective response of brain metabolism towards the possible detrimental effects of Pd2Spm, with more rapid recovery back to metabolites’ control levels and, thus, indicating that the palladium drug may exert a more beneficial role than cDDP in relation to brain toxicity.

Analytical Methodology for a Metabolome Atlas of Goat's Plasma, Milk and Feces Using 1H-NMR and UHPLC-HRMS

Metabolomics has been increasingly used in animal and food sciences. Animal health is one of the most important factor that can also alter animal integrity and welfare. Some studies have already investigated the link between health and metabolic profile of dairy animals. These studies in metabolomics often consider a single type of sample using a single analytical platform (nuclear magnetic resonance or mass spectrometry). Only few studies with multi-platform approaches are also used with a single or a multi type of sample, but they mainly consider dairy cows’ metabolome although dairy goats present similar diseases, that it could be interesting to detect early to preserve animal health and milk production. This study aims to create a metabolic atlas of goat plasma, milk and feces, based on healthy animals. Our study describes a standard operating procedure for three goat matrices: blood plasma, milk, and feces using multiple platforms (NMR (¹H), UHPLC (RP)-MS and UHPLC (HILIC)-MS) that follows a unique sample preparation procedure for each sample type to be analyzed on multi-platforms basis. Our method was evaluated for its robustness and allowed a better characterization of goat metabolic profile in healthy conditions.

Deletion of Mocos Induces Xanthinuria with Obstructive Nephropathy and Major Metabolic Disorders in Mice

Background

Xanthinuria type II is a rare autosomal purine disorder. This recessive defect of purine metabolism remains an under-recognized disorder.

Methods

Mice with targeted disruption of the molybdenum cofactor sulfurase (Mocos) gene were generated to enable an integrated understanding of purine disorders and evaluate pathophysiologic functions of this gene which is found in a large number of pathways and is known to be associated with autism.

Results

Mocos-deficient mice die with 4 weeks of age due to renal failure of distinct obstructive nephropathy with xanthinuria, xanthine deposits, cystic tubular dilation, Tamm-Horsfall (uromodulin) protein (THP) deposits, tubular cell necrosis with neutrophils, and occasionally hydronephrosis with urolithiasis. Obstructive nephropathy is associated with moderate interstitial inflammatory and fibrotic responses, anemia, reduced detoxification systems, and important alterations of the metabolism of purines, amino acids, and phospholipids. Conversely, heterozygous mice expressing reduced MOCOS protein are healthy with no apparent pathology.

Conclusions

Mocos-deficient mice develop a lethal obstructive nephropathy associated with profound metabolic changes. Studying MOCOS functions may provide important clues about the underlying pathogenesis of xanthinuria and other diseases requiring early diagnosis.

Maternal Rat Metabolomics: Amniotic Fluid and Placental Metabolic Profiling Workflows

Studying the metabolome of specific gestational compartments is of growing interest in the context of fetus developmental disorders. However, the metabolomes of the placenta and amniotic fluid (AF) are poorly characterized. Therefore, we present the validation of a fingerprinting methodology. Using pregnant rats, we performed exhaustive and robust extractions of metabolites in the AF and lipids and more polar metabolites in the placenta. For the AF, we compared the extraction capabilities of methanol (MeOH), acetonitrile (ACN), and a mixture of both. For the placenta, we compared (i) the extraction capabilities of dichloromethane, methyl t-butyl ether (MTBE), and butanol, along with (ii) the impact of lyophilization of the placental tissue. Analyses were performed on a C18 and hydrophilic interaction liquid chromatography combined with high-resolution mass spectrometry. The efficiency and the robustness of the extractions were compared based on the number of the features or metabolites (for untargeted or targeted approach, respectively), their mean total intensity, and their coefficient of variation (% CV). The extraction capabilities of MeOH and ACN on the AF metabolome were equivalent. Lyophilization also had no significant impact and usefulness on the placental tissue metabolome profiling. Considering the placental lipidome, MTBE extraction was more informative because it allowed extraction of a slightly higher number of lipids, in higher concentration. This proof-of-concept study assessing the metabolomics and lipidomics of the AF and the placenta revealed changes in both metabolisms, at two different stages of rat gestation, and allowed a detailed prenatal metabolic fingerprinting.

SHR/NCrl rats as a model of ADHD can be discriminated from controls based on their brain, blood, or urine metabolomes

Attention-Deficit Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorder characterized by inattention, impulsivity, and hyperactivity. The neurobiological mechanisms underlying ADHD are still poorly understood, and its diagnosis remains difficult due to its heterogeneity. Metabolomics is a recent strategy for the holistic exploration of metabolism and is well suited for investigating the pathophysiology of diseases and finding molecular biomarkers. A few clinical metabolomic studies have been performed on peripheral samples from ADHD patients but are limited by their access to the brain. Here, we investigated the brain, blood, and urine metabolomes of SHR/NCrl vs WKY/NHsd rats to better understand the neurobiology and to find potential peripheral biomarkers underlying the ADHD-like phenotype of this animal model. We showed that SHR/NCrl rats can be differentiated from controls based on their brain, blood, and urine metabolomes. In the brain, SHR/NCrl rats displayed modifications in metabolic pathways related to energy metabolism and oxidative stress further supporting their importance in the pathophysiology of ADHD bringing news arguments in favor of the Neuroenergetic theory of ADHD. Besides, the peripheral metabolome of SHR/NCrl rats also shared more than half of these differences further supporting the importance of looking at multiple matrices to characterize a pathophysiological condition of an individual. This also stresses out the importance of investigating the peripheral energy and oxidative stress metabolic pathways in the search of biomarkers of ADHD.

Stop the rot. Enzyme inactivation at brain harvest prevents artifacts: A guide for preservation of the in vivo concentrations of brain constituents

Post-mortem metabolism is widely recognized to cause rapid and prolonged changes in the concentrations of multiple classes of compounds in brain, that is, they are labile. Post-mortem changes from levels in living brain include components of pathways of metabolism of glucose and energy compounds, amino acids, lipids, signaling molecules, neuropeptides, phosphoproteins, and proteins. Methods that stop enzyme activity at brain harvest were developed almost 50 years ago and have been extensively used in studies of brain functions and diseases. Unfortunately, these methods are not commonly used to harvest brain tissue for mass spectrometry-based metabolomic studies or for imaging mass spectrometry studies (IMS, also called mass spectrometry imaging, MSI, or matrix-assisted laser desorption/ionization-MSI, MALDI-MSI). Instead these studies commonly kill animals, decapitate, dissect out brain and regions of interest if needed, then 'snap' freeze the tissue to stop enzymatic activity after harvest, with post-mortem intervals typically ranging from ~0.5 to 3 min. To increase awareness of the importance of stopping metabolism at harvest and preventing the unnecessary complications of not doing so, this commentary provides examples of labile metabolites and the magnitudes of their post-mortem changes in concentrations during brain harvest. Brain harvest methods that stop metabolism at harvest eliminate post-mortem enzymatic activities and can improve characterization of normal and diseased brain. In addition, metabolomic studies would be improved by reporting absolute units of concentration along with normalized peak areas or fold changes. Then reported values can be evaluated and compared with the extensive neurochemical literature to help prevent reporting of artifactual data.

Hot water pretreatment-induced significant metabolite changes in the sea cucumber Apostichopus japonicus

Hot water pretreatment of sea cucumbers potentially changes nutritional benefits. This study aimed to quantify hot water pretreatment-induced changes in metabolite profiles of sea cucumber body walls. ICP-OES, GC-MS, and LC-MS analyses of untreated- (UT-BW), hot water-treated body walls (HW-BW) of Apostichopus japonicus, and the hot water extract (HW-E) determined significant losses of minerals (25-50% w/w), protein (~11% w/w), carbohydrate (33% w/w), saponins (~41% w/w), and spermidine (100%), a potential antipsychotic from hot water-treated samples. Multivariate comparisons of HW-BW with UT-BW and HW-BW with HW-E showed increases in amino acids and fatty acids, suggesting hot water-induced degradation or transformation or easier extraction of protein, lipid or other components. Presence of 80 to 88.5% of compounds in the HW-E and lower DHA, EPA and glycerophospholipids levels in HW-BW suggested extraction of these metabolites. These data indicate that novel processing technologies are required to preserve the full nutritional benefits of sea cucumbers.

Optimised lyophilisation-based method for different biomolecule single-extractions from the same rat brain sample: Suitability for RNA and protein expression analyses after ischemic stroke

BACKGROUND

Optimisation of tissue processing procedures in preclinical studies reduces the number of animals used and allows integrated multilevel study in the same sample. Multiple extraction of different biomolecules from the same sample has several limitations.

NEW METHOD

Using brain samples from rats subjected to ischemic stroke, we combined lyophilisation of flash-frozen tissue, mechanical pulverisation and cryopreservation in a method to optimise tissue handling and preservation for independent RNA or protein single-extract methods, and subsequent RT-qPCR or Western blot analyses.

RESULTS

Lyophilisation resulted in 70% tissue weight loss. RNA (OD_260/280∼1.8) and protein yields were similar in non-ischemic and ischemic brain samples, subjected to either flash freezing (FF) or flash freezing followed by lyophilisation (FF + Lyo). RNA transcription of reference genes (Actb and Rn18s), expression of housekeeping proteins (β-actin and α-tubulin), and mRNA overexpression of stroke-regulated genes (Nos2, Mmp9 and Tnfa) was similar in FF and FF + Lyo samples.

COMPARISON WITH EXISTING METHOD(S)

Contrary to high heat stress of baking method in a drying oven, lyophilisation maintains the integrity of dried samples for subsequent extractions and analyses. Sample lyophilisation allows different manual representative extractions/analyses from the same rat, it is much cheaper than using commercial kits, and shows higher yields that multiple manual or kit-based extractions.

CONCLUSIONS

The lyophilisation-based method for different biomolecule single-extractions from tissue powder aliquots, representing the same rat brain sample, is sample saving, contributes to the reduction principle in animal research, and allows coordinated analysis for accurate correlations between the transcriptome and proteome in stroke and other neuroscience research.

A multiplatform metabolomic approach to characterize fecal signatures of negative postnatal events in chicks: a pilot study

Background

Negative experiences in early life can induce long-lasting effects on the welfare, health, and performance of farm animals. A delayed placement of chicks in rearing houses has negative effects on their performance, and results in fecal-specific odors detectable by rats. Based on this observation, the volatile organic compounds (VOCs) and metabolites from the feces of 12-day-old chickens were screened for early markers of response to negative events using gas-chromatography and liquid-chromatography coupled with mass spectrometry (GC-MS, LC-HRMS).

Results

The low reproducibility of solid-phase micro-extraction of the VOCs followed by GC-MS was not suitable for marker discovery, in contrast to liquid extraction of metabolites from freeze-dried feces followed by GC-MS or LC-HRMS analysis. Therefore, the fecal metabolome from 12-day-old chicks having experienced a normal or delayed placement were recorded by GC-MS and LC-HRMS in two genotypes from two experiments. From both experiments, 25 and 35 metabolites, respectively explaining 81% and 45% of the difference between delayed and control chickens, were identified by orthogonal partial least-squares discriminant analysis from LC-HRMS and GC-MS profiling.

Conclusion

The sets of molecules identified will be useful to better understand the chicks’ response to negative events over time and will contribute to define stress or welfare biomarkers. 

Electronic supplementary material

The online version of this article (10.1186/s40104-019-0335-8) contains supplementary material, which is available to authorized users.

Brain Metabolomics Reveal the Antipyretic Effects of Jinxin Oral Liquid in Young Rats by Using Gas Chromatography⁻Mass Spectrometry

Pyrexia is considered as a part of host's defense response to the invasion of microorganisms or inanimate matter recognized as pathogenic or alien, which frequently occurs in children. Jinxin oral liquid (JXOL) is a traditional Chinese medicine formula that has been widely used to treat febrile children in China. Experimental fever was induced by injecting yeast into young male Sprague-Dawley rats (80 ± 20 g) and the rectal temperature subsequently changed. Four hours later, the excessive production of interleukin (IL)-1β and prostaglandin (PG) E2 induced by yeast was regulated to normal by JXOL administration. A rat brain metabolomics investigation of pyrexia of yeast and antipyretic effect of JXOL was performed using gas chromatography-mass spectrometry (GC-MS). Clear separation was achieved between the model and normal group. Twenty-two significantly altered metabolites were found in pyretic rats as potential biomarkers of fever. Twelve metabolites, significantly adjusted by JXOL to help relieve pyrexia, were selected out as biomarkers of antipyretic mechanism of JXOL, which were involved in glycolysis, purine metabolism, tryptophan mechanism, etc. In conclusion, the brain metabolomics revealed potential biomarkers in the JXOL antipyretic process and the associated pathways, which may aid in advanced understanding of fever and therapeutic mechanism of JXOL.

Balancing metabolome coverage and reproducibility for untargeted NMR-based metabolic profiling in tissue samples through mixture design methods

Untargeted metabolomics attempts to acquire a comprehensive and reproducible set of small-molecule metabolites in biological systems. However, metabolite extraction method significantly affects the quality of metabolomics data. In the present study, we calculated the number of peaks (NP) and coefficient of variation (CV) to reflect metabolome coverage and reproducibility in untargeted NMR-based metabolic profiling of tissue samples in rats under different methanol/chloroform/water (MCW) extraction conditions. Different MCW extractions expectedly generated diverse characteristics of metabolome. Moreover, the classic MCW method revealed tissue-specific differences in the NP and CV values. To obtain high-quality metabolomics data, therefore, we used mixture design methods to optimize the MCW extraction strategy by maximizing the NP value and minimizing the CV value in each tissue sample. Results show that the optimal formulations of MCW extraction were 2:2:8 (ml/mg tissue) for brain sample, 2:4:6 (ml/mg tissue) for heart sample, 1.3:2:8.7 (ml/mg tissue) for liver sample, 4:2:6 (ml/mg tissue) for kidney sample, 2:3:7 (ml/mg tissue) for muscle sample, and 2:4:6 (ml/mg tissue) for pancreas sample. Therefore, these findings demonstrate that different tissue samples need a specific optimal extraction condition for balancing metabolome coverage and reproducibility in the untargeted metabolomics study. Mixture design method is an effective tool to optimize metabolite extraction strategy for tissue samples. Graphical abstract ᅟ.

Relationships between digestive efficiency and metabolomic profiles of serum and intestinal contents in chickens

The increasing cost of conventional feedstuffs has bolstered interest in genetic selection for digestive efficiency (DE), a component of feed efficiency, assessed by apparent metabolisable energy corrected to zero nitrogen retention (AMEn). However, its measurement is time-consuming and constraining, and its relationship with metabolic efficiency poorly understood. To simplify selection for this trait, we searched for indirect metabolic biomarkers through an analysis of the serum metabolome using nuclear magnetic resonance (¹H NMR). A partial least squares (PLS) model including six amino acids and two derivatives from butyrate predicted 59% of AMEn variability. Moreover, to increase our knowledge of the molecular mechanisms controlling DE, we investigated ¹H NMR metabolomes of ileal, caecal, and serum contents by fitting canonical sparse PLS. This analysis revealed strong associations between metabolites and DE. Models based on the ileal, caecal, and serum metabolome respectively explained 77%, 78%, and 74% of the variability of AMEn and its constitutive components (utilisation of starch, lipids, and nitrogen). In our conditions, the metabolites presenting the strongest associations with AMEn were proline in the serum, fumarate in the ileum and glucose in caeca. This study shows that serum metabolomics offers new opportunities to predict chicken DE.

The combination of four analytical methods to explore skeletal muscle metabolomics: Better coverage of metabolic pathways or a marketing argument?

OBJECTIVES

Metabolomics is an emerging science based on diverse high throughput methods that are rapidly evolving to improve metabolic coverage of biological fluids and tissues. Technical progress has led researchers to combine several analytical methods without reporting the impact on metabolic coverage of such a strategy. The objective of our study was to develop and validate several analytical techniques (mass spectrometry coupled to gas or liquid chromatography and nuclear magnetic resonance) for the metabolomic analysis of small muscle samples and evaluate the impact of combining methods for more exhaustive metabolite covering.

DESIGN AND METHODS

We evaluated the muscle metabolome from the same pool of mouse muscle samples after 2 metabolite extraction protocols. Four analytical methods were used: targeted flow injection analysis coupled with mass spectrometry (FIA-MS/MS), gas chromatography coupled with mass spectrometry (GC-MS), liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS), and nuclear magnetic resonance (NMR) analysis. We evaluated the global variability of each compound i.e., analytical (from quality controls) and extraction variability (from muscle extracts). We determined the best extraction method and we reported the common and distinct metabolites identified based on the number and identity of the compounds detected with low analytical variability (variation coefficient<30%) for each method. Finally, we assessed the coverage of muscle metabolic pathways obtained.

RESULTS

Methanol/chloroform/water and water/methanol were the best extraction solvent for muscle metabolome analysis by NMR and MS, respectively. We identified 38 metabolites by nuclear magnetic resonance, 37 by FIA-MS/MS, 18 by GC-MS, and 80 by LC-HRMS. The combination led us to identify a total of 132 metabolites with low variability partitioned into 58 metabolic pathways, such as amino acid, nitrogen, purine, and pyrimidine metabolism, and the citric acid cycle. This combination also showed that the contribution of GC-MS was low when used in combination with other mass spectrometry methods and nuclear magnetic resonance to explore muscle samples.

CONCLUSION

This study reports the validation of several analytical methods, based on nuclear magnetic resonance and several mass spectrometry methods, to explore the muscle metabolome from a small amount of tissue, comparable to that obtained during a clinical trial. The combination of several techniques may be relevant for the exploration of muscle metabolism, with acceptable analytical variability and overlap between methods However, the difficult and time-consuming data pre-processing, processing, and statistical analysis steps do not justify systematically combining analytical methods.