The gut metabolite indole-3 propionate promotes nerve regeneration and repair.

The regenerative potential of mammalian peripheral nervous system neurons after injury is critically limited by their slow axonal regenerative rate1. Regenerative ability is influenced by both injury-dependent and injury-independent mechanisms2. Among the latter, environmental factors such as exercise and environmental enrichment have been shown to affect signalling pathways that promote axonal regeneration3. Several of these pathways, including modifications in gene transcription and protein synthesis, mitochondrial metabolism and the release of neurotrophins, can be activated by intermittent fasting (IF)4,5. However, whether IF influences the axonal regenerative ability remains to be investigated. Here we show that IF promotes axonal regeneration after sciatic nerve crush in mice through an unexpected mechanism that relies on the gram-positive gut microbiome and an increase in the gut bacteria-derived metabolite indole-3-propionic acid (IPA) in the serum. IPA production by Clostridium sporogenes is required for efficient axonal regeneration, and delivery of IPA after sciatic injury significantly enhances axonal regeneration, accelerating the recovery of sensory function. Mechanistically, RNA sequencing analysis from sciatic dorsal root ganglia suggested a role for neutrophil chemotaxis in the IPA-dependent regenerative phenotype, which was confirmed by inhibition of neutrophil chemotaxis. Our results demonstrate the ability of a microbiome-derived metabolite, such as IPA, to facilitate regeneration and functional recovery of sensory axons through an immune-mediated mechanism.

Statin therapy is associated with lower prevalence of gut microbiota dysbiosis.

Microbiome community typing analyses have recently identified the Bacteroides2 (Bact2) enterotype, an intestinal microbiota configuration that is associated with systemic inflammation and has a high prevalence in loose stools in humans1,2. Bact2 is characterized by a high proportion of Bacteroides, a low proportion of Faecalibacterium and low microbial cell densities1,2, and its prevalence varies from 13% in a general population cohort to as high as 78% in patients with inflammatory bowel disease2. Reported changes in stool consistency3 and inflammation status4 during the progression towards obesity and metabolic comorbidities led us to propose that these developments might similarly correlate with an increased prevalence of the potentially dysbiotic Bact2 enterotype. Here, by exploring obesity-associated microbiota alterations in the quantitative faecal metagenomes of the cross-sectional MetaCardis Body Mass Index Spectrum cohort (n = 888), we identify statin therapy as a key covariate of microbiome diversification. By focusing on a subcohort of participants that are not medicated with statins, we find that the prevalence of Bact2 correlates with body mass index, increasing from 3.90% in lean or overweight participants to 17.73% in obese participants. Systemic inflammation levels in Bact2-enterotyped individuals are higher than predicted on the basis of their obesity status, indicative of Bact2 as a dysbiotic microbiome constellation. We also observe that obesity-associated microbiota dysbiosis is negatively associated with statin treatment, resulting in a lower Bact2 prevalence of 5.88% in statin-medicated obese participants. This finding is validated in both the accompanying MetaCardis cardiovascular disease dataset (n = 282) and the independent Flemish Gut Flora Project population cohort (n = 2,345). The potential benefits of statins in this context will require further evaluation in a prospective clinical trial to ascertain whether the effect is reproducible in a randomized population and before considering their application as microbiota-modulating therapeutics.

High Resolution Ambient MS Imaging of Biological Samples by Desorption Electro-Flow Focussing Ionization.

In this study, we examine the suitability of desorption electro-flow focusing ionization (DEFFI) for mass spectrometry imaging (MSI) of biological tissue. We also compare the performance of desorption electrospray ionization (DESI) with and without the flow focusing setup. The main potential advantages of applying the flow focusing mechanism in DESI is its rotationally symmetric electrospray jet, higher intensity, more controllable parameters, and better portability due to the robustness of the sprayer. The parameters for DEFFI have therefore been thoroughly optimized, primarily for spatial resolution but also for intensity. Once the parameters have been optimized, DEFFI produces similar images to the existing DESI. MS images for mouse brain samples, acquired at a nominal pixel size of 50 µm, are comparable for both DESI setups, albeit the new sprayer design yields better sensitivity. Furthermore, the two methods are compared with regard to spectral intensity as well as the area of the desorbed crater on rhodamine-coated slides. Overall, the implementation of a flow focusing mechanism in DESI is shown to be highly suitable for imaging biological tissue and has potential to overcome some of the shortcomings experienced with the current geometrical design of DESI.

Human and preclinical studies of the host-gut microbiome co-metabolite hippurate as a marker and mediator of metabolic health.

OBJECTIVE: Gut microbial products are involved in regulation of host metabolism. In human and experimental studies, we explored the potential role of hippurate, a hepatic phase 2 conjugation product of microbial benzoate, as a marker and mediator of metabolic health. DESIGN: In 271 middle-aged non-diabetic Danish individuals, who were stratified on habitual dietary intake, we applied 1H-nuclear magnetic resonance (NMR) spectroscopy of urine samples and shotgun-sequencing-based metagenomics of the gut microbiome to explore links between the urine level of hippurate, measures of the gut microbiome, dietary fat and markers of metabolic health. In mechanistic experiments with chronic subcutaneous infusion of hippurate to high-fat-diet-fed obese mice, we tested for causality between hippurate and metabolic phenotypes. RESULTS: In the human study, we showed that urine hippurate positively associates with microbial gene richness and functional modules for microbial benzoate biosynthetic pathways, one of which is less prevalent in the Bacteroides 2 enterotype compared with Ruminococcaceae or Prevotella enterotypes. Through dietary stratification, we identify a subset of study participants consuming a diet rich in saturated fat in which urine hippurate concentration, independently of gene richness, accounts for links with metabolic health. In the high-fat-fed mice experiments, we demonstrate causality through chronic infusion of hippurate (20 nmol/day) resulting in improved glucose tolerance and enhanced insulin secretion. CONCLUSION: Our human and experimental studies show that a high urine hippurate concentration is a general marker of metabolic health, and in the context of obesity induced by high-fat diets, hippurate contributes to metabolic improvements, highlighting its potential as a mediator of metabolic health.

Dominant gut Prevotella copri in gastrectomised non-obese diabetic Goto-Kakizaki rats improves glucose homeostasis through enhanced FXR signalling.

AIMS/HYPOTHESIS: Drug and surgical-based therapies in type 2 diabetes are associated with altered gut microbiota architecture. Here we investigated the role of the gut microbiome in improved glucose homeostasis following bariatric surgery. METHODS: We carried out gut microbiome analyses in gastrectomised (by vertical sleeve gastrectomy [VSG]) rats of the Goto-Kakizaki (GK) non-obese model of spontaneously occurring type 2 diabetes, followed by physiological studies in the GK rat. RESULTS: VSG in the GK rat led to permanent improvement of glucose tolerance associated with minor changes in the gut microbiome, mostly characterised by significant enrichment of caecal Prevotella copri. Gut microbiota enrichment with P. copri in GK rats through permissive antibiotic treatment, inoculation of gut microbiota isolated from gastrectomised GK rats, and direct inoculation of P. copri, resulted in significant improvement of glucose tolerance, independent of changes in body weight. Plasma bile acids were increased in GK rats following inoculation with P. copri and P. copri-enriched microbiota from VSG-treated rats; the inoculated GK rats then showed increased liver glycogen and upregulated expression of Fxr (also known as Nr1h4), Srebf1c, Chrebp (also known as Mlxipl) and Il10 and downregulated expression of Cyp7a1. CONCLUSIONS: Our data underline the impact of intestinal P. copri on improved glucose homeostasis through enhanced bile acid metabolism and farnesoid X receptor (FXR) signalling, which may represent a promising opportunity for novel type 2 diabetes therapeutics.

pJRES Binning Algorithm (JBA): a new method to facilitate the recovery of metabolic information from pJRES 1H NMR spectra.

MOTIVATION: Data processing is a key bottleneck for 1H NMR-based metabolic profiling of complex biological mixtures, such as biofluids. These spectra typically contain several thousands of signals, corresponding to possibly few hundreds of metabolites. A number of binning-based methods have been proposed to reduce the dimensionality of 1 D 1H NMR datasets, including statistical recoupling of variables (SRV). Here, we introduce a new binning method, named JBA ("pJRES Binning Algorithm"), which aims to extend the applicability of SRV to pJRES spectra. RESULTS: The performance of JBA is comprehensively evaluated using 617 plasma 1H NMR spectra from the FGENTCARD cohort. The results presented here show that JBA exhibits higher sensitivity than SRV to detect peaks from low-abundance metabolites. In addition, JBA allows a more efficient removal of spectral variables corresponding to pure electronic noise, and this has a positive impact on multivariate model building. AVAILABILITY AND IMPLEMENTATION: The algorithm is implemented using the MWASTools R/Bioconductor package. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MWASTools: an R/bioconductor package for metabolome-wide association studies.

Summary: MWASTools is an R package designed to provide an integrated pipeline to analyse metabonomic data in large-scale epidemiological studies. Key functionalities of our package include: quality control analysis; metabolome-wide association analysis using various models (partial correlations, generalized linear models); visualization of statistical outcomes; metabolite assignment using statistical total correlation spectroscopy (STOCSY); and biological interpretation of metabolome-wide association studies results. Availability and implementation: The MWASTools R package is implemented in R (version > =3.4) and is available from Bioconductor: https://bioconductor.org/packages/MWASTools/. Contact: m.dumas@imperial.ac.uk. Supplementary information: Supplementary data are available at Bioinformatics online.

Implication of gut microbiota metabolites in cardiovascular and metabolic diseases.

Evidence from the literature keeps highlighting the impact of mutualistic bacterial communities of the gut microbiota on human health. The gut microbita is a complex ecosystem of symbiotic bacteria which contributes to mammalian host biology by processing, otherwise, indigestible nutrients, supplying essential metabolites, and contributing to modulate its immune system. Advances in sequencing technologies have enabled structural analysis of the human gut microbiota and allowed detection of changes in gut bacterial composition in several common diseases, including cardiometabolic disorders. Biological signals sent by the gut microbiota to the host, including microbial metabolites and pro-inflammatory molecules, mediate microbiome-host genome cross-talk. This rapidly expanding line of research can identify disease-causing and disease-predictive microbial metabolite biomarkers, which can be translated into novel biodiagnostic tests, dietary supplements, and nutritional interventions for personalized therapeutic developments in common diseases. Here, we review results from the most significant studies dealing with the association of products from the gut microbial metabolism with cardiometabolic disorders. We underline the importance of these postbiotic biomarkers in the diagnosis and treatment of human disorders.

Untargeted Mass Spectrometry Lipidomics identifies correlation between serum sphingomyelins and plasma cholesterol.

BACKGROUND: Lipoproteins are major players in the development and progression of atherosclerotic plaques leading to coronary stenosis and myocardial infarction. Epidemiological, genetic and experimental observations have implicated the association of sphingolipids and intermediates of sphingolipid synthesis in atherosclerosis. We aimed to investigate relationships between quantitative changes in serum sphingolipids, the regulation of the metabolism of lipoproteins (LDL, HDL), and endophenotypes of coronary artery disease (CAD). METHODS: We carried out untargeted liquid chromatography - mass spectrometry (UPLC-MS) lipidomics of serum samples of subjects belonging to a cross-sectional study and recruited on the basis of absence or presence of angiographically-defined CAD, and extensively characterized for clinical and biochemical phenotypes. RESULTS: Among the 2998 spectral features detected in the serum samples, 1328 metabolic features were significantly correlated with at least one of the clinical or biochemical phenotypes measured in the cohort. We found evidence of significant associations between 34 metabolite signals, corresponding to a set of sphingomyelins, and serum HDL cholesterol. Many of these metabolite associations were also observed with serum LDL and total cholesterol levels but not as much with serum triglycerides. CONCLUSION: Among patients with CAD, sphingolipids in the form of sphingomyelins are directly correlated with serum levels of lipoproteins and total cholesterol. Results from this study support the fundamental role of sphingolipids in modulating lipid serum levels, highlighting the importance to identify novel targets in the sphingolipid metabolic pathway for anti-atherogenic therapies.

MetaboSignal: a network-based approach for topological analysis of metabotype regulation via metabolic and signaling pathways.

Summary: MetaboSignal is an R package that allows merging metabolic and signaling pathways reported in the Kyoto Encyclopaedia of Genes and Genomes (KEGG). It is a network-based approach designed to navigate through topological relationships between genes (signaling- or metabolic-genes) and metabolites, representing a powerful tool to investigate the genetic landscape of metabolic phenotypes. Availability and Implementation: MetaboSignal is available from Bioconductor: https://bioconductor.org/packages/MetaboSignal/. Contact: m.dumas@imperial.ac.uk . Supplementary information: Supplementary data are available at Bioinformatics online.

J-Resolved 1H NMR 1D-Projections for Large-Scale Metabolic Phenotyping Studies: Application to Blood Plasma Analysis.

1H nuclear magnetic resonance (NMR) spectroscopy-based metabolic phenotyping is now widely used for large-scale epidemiological applications. To minimize signal overlap present in 1D 1H NMR spectra, we have investigated the use of 2D J-resolved (JRES) 1H NMR spectroscopy for large-scale phenotyping studies. In particular, we have evaluated the use of the 1D projections of the 2D JRES spectra (pJRES), which provide single peaks for each of the J-coupled multiplets, using 705 human plasma samples from the FGENTCARD cohort. On the basis of the assessment of several objective analytical criteria (spectral dispersion, attenuation of macromolecular signals, cross-spectral correlation with GC-MS metabolites, analytical reproducibility and biomarker discovery potential), we concluded that the pJRES approach exhibits suitable properties for implementation in large-scale molecular epidemiology workflows.

Akkermansia muciniphila and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecology.

OBJECTIVE: Individuals with obesity and type 2 diabetes differ from lean and healthy individuals in their abundance of certain gut microbial species and microbial gene richness. Abundance of Akkermansia muciniphila, a mucin-degrading bacterium, has been inversely associated with body fat mass and glucose intolerance in mice, but more evidence is needed in humans. The impact of diet and weight loss on this bacterial species is unknown. Our objective was to evaluate the association between faecal A. muciniphila abundance, faecal microbiome gene richness, diet, host characteristics, and their changes after calorie restriction (CR). DESIGN: The intervention consisted of a 6-week CR period followed by a 6-week weight stabilisation diet in overweight and obese adults (N=49, including 41 women). Faecal A. muciniphila abundance, faecal microbial gene richness, diet and bioclinical parameters were measured at baseline and after CR and weight stabilisation. RESULTS: At baseline A. muciniphila was inversely related to fasting glucose, waist-to-hip ratio and subcutaneous adipocyte diameter. Subjects with higher gene richness and A. muciniphila abundance exhibited the healthiest metabolic status, particularly in fasting plasma glucose, plasma triglycerides and body fat distribution. Individuals with higher baseline A. muciniphila displayed greater improvement in insulin sensitivity markers and other clinical parameters after CR. These participants also experienced a reduction in A. muciniphila abundance, but it remained significantly higher than in individuals with lower baseline abundance. A. muciniphila was associated with microbial species known to be related to health. CONCLUSIONS: A. muciniphila is associated with a healthier metabolic status and better clinical outcomes after CR in overweight/obese adults. The interaction between gut microbiota ecology and A. muciniphila warrants further investigation. TRIAL REGISTRATION NUMBER: NCT01314690.

The microbial-mammalian metabolic axis: a critical symbiotic relationship.

PURPOSE OF REVIEW: The microbial-mammalian symbiosis plays a critical role in metabolic health. Microbial metabolites emerge as key messengers in the complex communication between the gut microbiota and their host. These chemical signals are mainly derived from nutritional precursors, which in turn are also able to modify gut microbiota population. Recent advances in the characterization of the gut microbiome and the mechanisms involved in this symbiosis allow the development of nutritional interventions. This review covers the latest findings on the microbial-mammalian metabolic axis as a critical symbiotic relationship particularly relevant to clinical nutrition. RECENT FINDINGS: The modulation of host metabolism by metabolites derived from the gut microbiota highlights the importance of gut microbiota in disease prevention and causation. The composition of microbial populations in our gut ecosystem is a critical pathophysiological factor, mainly regulated by diet, but also by the host's characteristics (e.g. genetics, circadian clock, immune system, age). Tailored interventions, including dietary changes, the use of antibiotics, prebiotic and probiotic supplementation and faecal transplantation are promising strategies to manipulate microbial ecology. SUMMARY: The microbiome is now considered as an easily reachable target to prevent and treat related diseases. Recent findings in both mechanisms of its interactions with host metabolism and in strategies to modify gut microbiota will allow us to develop more effective treatments especially in metabolic diseases.

A multiplexed targeted assay for high-throughput quantitative analysis of serum methylamines by ultra performance liquid chromatography coupled to high resolution mass spectrometry.

Methylamines are biologically-active metabolites present in serum and urine samples, which play complex roles in metabolic diseases. Methylamines can be detected by proton nuclear magnetic resonance (NMR), but specific methods remain to be developed for their routine assay in human serum in clinical settings. Here we developed and validated a novel reliable "methylamine panel" method for simultaneous quantitative analysis of trimethylamine (TMA), its major detoxification metabolite trimethylamine-N-oxide (TMAO), and precursors choline, betaine and l-carnitine in human serum using Ultra Performance Liquid Chromatography (UPLC) coupled to High Resolution Mass Spectrometry (HRMS). Metabolite separation was carried out on a HILIC stationary phase. For all metabolites, the assay was linear in the range of 0.25-12.5 µmol/L and enabled to reach limit of detection of about 0.10 µmol/L. Relative standard deviations were below 16% for the three levels of concentrations. We demonstrated the strong reliability and robustness of the method, which was applied to serum samples from healthy individuals to establish the range of concentrations of the metabolites and their correlation relationships and detect gender differences. Our data provide original information for implementing in a clinical environment a MS-based diagnostic method with potential for targeted metabolic screening of patients at risk of cardiometabolic diseases.

Direct quantitative trait locus mapping of mammalian metabolic phenotypes in diabetic and normoglycemic rat models.

Characterizing the relationships between genomic and phenotypic variation is essential to understanding disease etiology. Information-dense data sets derived from pathophysiological, proteomic and transcriptomic profiling have been applied to map quantitative trait loci (QTLs). Metabolic traits, already used in QTL studies in plants, are essential phenotypes in mammalian genetics to define disease biomarkers. Using a complex mammalian system, here we show chromosomal mapping of untargeted plasma metabolic fingerprints derived from NMR spectroscopic analysis in a cross between diabetic and control rats. We propose candidate metabolites for the most significant QTLs. Metabolite profiling in congenic strains provided evidence of QTL replication. Linkage to a gut microbial metabolite (benzoate) can be explained by deletion of a uridine diphosphate glucuronosyltransferase. Mapping metabotypic QTLs provides a practical approach to understanding genome-phenotype relationships in mammals and may uncover deeper biological complexity, as extended genome (microbiome) perturbations that affect disease processes through transgenomic effects may influence QTL detection.

Metabolic phenotyping and systems biology approaches to understanding metabolic syndrome and fatty liver disease.

Metabolic syndrome, a cluster of risk factors for type 2 diabetes mellitus and cardiovascular disease, is becoming an increasing global health concern. Insulin resistance is often associated with metabolic syndrome and also typical hepatic manifestations such as nonalcoholic fatty liver disease. Profiling of metabolic products (metabolic phenotyping or metabotyping) has provided new insights into metabolic syndrome and nonalcoholic fatty liver disease. Data from nuclear magnetic resonance spectroscopy and mass spectrometry combined with statistical modeling and top-down systems biology have allowed us to analyze and interpret metabolic signatures in terms of metabolic pathways and protein interaction networks and to identify the genomic and metagenomic determinants of metabolism. For example, metabolic phenotyping has shown that relationships between host cells and the microbiome affect development of the metabolic syndrome and fatty liver disease. We review recent developments in metabolic phenotyping and systems biology technologies and how these methodologies have provided insights into the mechanisms of metabolic syndrome and nonalcoholic fatty liver disease. We discuss emerging areas of research in this field and outline our vision for how metabolic phenotyping could be used to study metabolic syndrome and fatty liver disease.

mQTL.NMR: an integrated suite for genetic mapping of quantitative variations of (1)H NMR-based metabolic profiles.

High-throughput (1)H nuclear magnetic resonance (NMR) is an increasingly popular robust approach for qualitative and quantitative metabolic profiling, which can be used in conjunction with genomic techniques to discover novel genetic associations through metabotype quantitative trait locus (mQTL) mapping. There is therefore a crucial necessity to develop specialized tools for an accurate detection and unbiased interpretability of the genetically determined metabolic signals. Here we introduce and implement a combined chemoinformatic approach for objective and systematic analysis of untargeted (1)H NMR-based metabolic profiles in quantitative genetic contexts. The R/Bioconductor mQTL.NMR package was designed to (i) perform a series of preprocessing steps restoring spectral dependency in collinear NMR data sets to reduce the multiple testing burden, (ii) carry out robust and accurate mQTL mapping in human cohorts as well as in rodent models, (iii) statistically enhance structural assignment of genetically determined metabolites, and (iv) illustrate results with a series of visualization tools. Built-in flexibility and implementation in the powerful R/Bioconductor framework allow key preprocessing steps such as peak alignment, normalization, or dimensionality reduction to be tailored to specific problems. The mQTL.NMR package is freely available with its source code through the Comprehensive R/Bioconductor repository and its own website ( http://www.ican-institute.org/tools/ ). It represents a significant advance to facilitate untargeted metabolomic data processing and quantitative analysis and their genetic mapping.

Bile acid profiling and quantification in biofluids using ultra-performance liquid chromatography tandem mass spectrometry.

Bile acids are important end products of cholesterol metabolism. While they have been identified as key factors in lipid emulsification and absorption due to their detergent properties, bile acids have also been shown to act as signaling molecules and intermediates between the host and the gut microbiota. To further the investigation of bile acid functions in humans, an advanced platform for high throughput analysis is essential. Herein, we describe the development and application of a 15 min UPLC procedure for the separation of bile acid species from human biofluid samples requiring minimal sample preparation. High resolution time-of-flight mass spectrometry was applied for profiling applications, elucidating rich bile acid profiles in both normal and disease state plasma. In parallel, a second mode of detection was developed utilizing tandem mass spectrometry for sensitive and quantitative targeted analysis of 145 bile acid (BA) species including primary, secondary, and tertiary bile acids. The latter system was validated by testing the linearity (lower limit of quantification, LLOQ, 0.25-10 nM and upper limit of quantification, ULOQ, 2.5-5 µM), precision (≈6.5%), and accuracy (81.2-118.9%) on inter- and intraday analysis achieving good recovery of bile acids (serum/plasma 88% and urine 93%). The ultra performance liquid chromatography-mass spectrometry (UPLC-MS)/MS targeted method was successfully applied to plasma, serum, and urine samples in order to compare the bile acid pool compositional difference between preprandial and postprandial states, demonstrating the utility of such analysis on human biofluids.

Objective set of criteria for optimization of sample preparation procedures for ultra-high throughput untargeted blood plasma lipid profiling by ultra performance liquid chromatography-mass spectrometry.

Exploratory or untargeted ultra performance liquid chromatography-mass spectrometry (UPLC-MS) profiling offers an overview of the complex lipid species diversity present in blood plasma. Here, we evaluate and compare eight sample preparation protocols for optimized blood plasma lipid extraction and measurement by UPLC-MS lipid profiling, including four protein precipitation methods (i.e., methanol, acetonitrile, isopropanol, and isopropanol-acetonitrile) and four liquid-liquid extractions (i.e., methanol combined with chloroform, dichloromethane, and methyl-tert butyl ether and isopropanol with hexane). The eight methods were then benchmarked using a set of qualitative and quantitative criteria selected to warrant compliance with high-throughput analytical workflows: protein removal efficiency, selectivity, repeatability, and recovery efficiency of the sample preparation. We found that protein removal was more efficient by precipitation (99%) than extraction (95%). Additionally, isopropanol appeared to be the most straightforward and robust solvent (61.1% of features with coefficient of variation (CV) < 20%) while enabling a broad coverage and recovery of plasma lipid species. These results demonstrate that isopropanol precipitation is an excellent sample preparation procedure for high-throughput untargeted lipid profiling using UPLC-MS. Isopropanol precipitation is not limited to untargeted profiling and could also be of interest for targeted UPLC-MS/MS lipid analysis. Collectively, these data show that lipid profiling greatly benefits from an isopropanol precipitation in terms of simplicity, protein removal efficiency, repeatability, lipid recovery, and coverage.

A metabolomic and systems biology perspective on the brain of the fragile X syndrome mouse model.

Fragile X syndrome (FXS) is the first cause of inherited intellectual disability, due to the silencing of the X-linked Fragile X Mental Retardation 1 gene encoding the RNA-binding protein FMRP. While extensive studies have focused on the cellular and molecular basis of FXS, neither human Fragile X patients nor the mouse model of FXS--the Fmr1-null mouse--have been profiled systematically at the metabolic and neurochemical level to provide a complementary perspective on the current, yet scattered, knowledge of FXS. Using proton high-resolution magic angle spinning nuclear magnetic resonance ((1)H HR-MAS NMR)-based metabolic profiling, we have identified a metabolic signature and biomarkers associated with FXS in various brain regions of Fmr1-deficient mice. Our study highlights for the first time that Fmr1 gene inactivation has profound, albeit coordinated consequences in brain metabolism leading to alterations in: (1) neurotransmitter levels, (2) osmoregulation, (3) energy metabolism, and (4) oxidative stress response. To functionally connect Fmr1-deficiency to its metabolic biomarkers, we derived a functional interaction network based on the existing knowledge (literature and databases) and show that the FXS metabolic response is initiated by distinct mRNA targets and proteins interacting with FMRP, and then relayed by numerous regulatory proteins. This novel "integrated metabolome and interactome mapping" (iMIM) approach advantageously unifies novel metabolic findings with previously unrelated knowledge and highlights the contribution of novel cellular pathways to the pathophysiology of FXS. These metabolomic and integrative systems biology strategies will contribute to the development of potential drug targets and novel therapeutic interventions, which will eventually benefit FXS patients.