Plasma metabolomics reveals major changes in carbohydrate, lipid, and protein metabolism of abruptly weaned beef calves.

1H NMR-based metabolomics was used to study the effect of abrupt weaning on the blood metabolome of beef calves. Twenty Angus calves (258 ± 5 kg BW; 5 to 6 months old) were randomly assigned to a non-weaned (NW) group that remained grazing with their dam or a weaned (W) group that underwent abrupt separation from their dam to a separate paddock on d 0 of the study. Body weight, behaviour, and blood samples for cortisol and metabolomics were measured at d 0, 1, 2, 7, and 14 of the study. On d 1 and 2, W calves spent less time grazing and ruminating, and more time vocalising and walking, had a greater concentration of cortisol, NEFA, 3-hydroxybutyrate, betaine, creatine, and phenylalanine, and lesser abundance of tyrosine (P < 0.05) compared to NW calves. Compared to NW calves at d 14, W calves had greater (P < 0.01) relative abundance of acetate, glucose, allantoin, creatinine, creatine, creatine phosphate, glutamate, 3-hydroxybutyrate, 3-hydroxyisobutyrate, and seven AA (alanine, glutamate, leucine, lysine, phenylalanine, threonine and valine) but lesser (P < 0.05) relative abundance of low density and very low-density lipids, and unsaturated lipids. Both PCA and OPLS-DA showed no clustering or discrimination between groups at d 0 and increasing divergence to d 14. Blood metabolomics is a useful tool to quantify the acute effects of stress in calves during the first 2 days after abrupt weaning, and longer-term changes in carbohydrate, lipid and protein metabolism due to nutritional changes from cessation of milk intake and greater reliance on forage intake.

Urinary metabolite prognostic biomarker panel for pancreatic ductal adenocarcinomas.

BACKGROUND: Patients with pancreatic ductal adenocarcinoma (PDAC) have a very low survival rate and surgical resection is the only curative intent treatment available. However, the majority of patients relapse after surgery and identification of biomarkers for accurate prognostication of PDAC patients is required. We have recently identified a six biomarker (i.e., trigonelline, glycolate, hippurate, creatine, myoinositol and hydroxyacetone) urinary metabolite panel with very high potential to diagnose PDAC (Int J Cancer 2021;148:1508-18). This study aimed to assess the prognostic ability of these previously identified diagnostic metabolites in the urine of PDAC patients. METHODS: Metabolite data from 88 PDAC patients was statistically assessed for their prognostic ability. RESULTS: A panel of three metabolites (i.e., trigonelline, hippurate and myoinositol) was able to stratify patients with good- or poor-prognosis based on overall survival. The PDAC patients with abnormal levels of 2 or more metabolites in their urine demonstrated significantly lower survival compared to patients with abnormal levels of one or less metabolites. CONCLUSION: These results demonstrate that the selected three metabolite panel could be used to stratify patients based on their prognostic outcomes and if independently validated may lead to the development of a urinary prognostic biomarker test for PDAC. GENERAL SIGNIFICANCE: This study highlights the potential of using 1H-nuclear magnetic resonance spectroscopy for the identification of novel metabolites which can prognosticate cancer patients.

Seasonal Regulation of Metabolism: The Effect of Wintertime Fasting and Autumnal Fattening on Key Central Regulators of Metabolism and the Metabolic Profile of the Raccoon Dog (Nyctereutes Procyonoides).

Investigations into the mechanisms regulating obesity are frantic and novel translational approaches are needed. The raccoon dog (Nyctereutes procyonoides) is a canid species representing a promising model to study metabolic regulation in a species undergoing cycles of seasonal obesity and fasting. To understand the molecular mechanisms of metabolic regulation in seasonal adaptation, we analyzed key central nervous system and peripheral signals regulating food intake and metabolism from raccoon dogs after autumnal fattening and winter fasting. Expressions of neuropeptide Y (NPY), orexin-2 receptor (OX2R), pro-opiomelanocortin (POMC) and leptin receptor (ObRb) were analyzed as examples of orexigenic and anorexigenic signals using qRT-PCR from raccoon dog hypothalamus samples. Plasma metabolic profiles were measured with 1H NMR-spectroscopy and LC-MS. Circulating hormones and cytokines were determined with canine specific antibody assays. Surprisingly, NPY and POMC were not affected by the winter fasting nor autumn fattening and the metabolic profiles showed a remarkable equilibrium, indicating conserved homeostasis. However, OX2R and ObRb expression changes suggested seasonal regulation. Circulating cytokine levels were not increased, demonstrating that the autumn fattening did not induce subacute inflammation. Thus, the raccoon dog developed seasonal regulatory mechanisms to accommodate the autumnal fattening and prolonged fasting making the species unique in coping with the extreme environmental challenges.

Oral pre-treatment with thiocyanate (SCN-) protects against myocardial ischaemia-reperfusion injury in rats.

Despite improvements in revascularization after a myocardial infarction, coronary disease remains a major contributor to global mortality. Neutrophil infiltration and activation contributes to tissue damage, via the release of myeloperoxidase (MPO) and formation of the damaging oxidant hypochlorous acid. We hypothesized that elevation of thiocyanate ions (SCN-), a competitive MPO substrate, would modulate tissue damage. Oral dosing of rats with SCN-, before acute ischemia-reperfusion injury (30 min occlusion, 24 h or 4 week recovery), significantly reduced the infarct size as a percentage of the total reperfused area (54% versus 74%), and increased the salvageable area (46% versus 26%) as determined by MRI imaging. No difference was observed in fractional shortening, but supplementation resulted in both left-ventricle end diastolic and left-ventricle end systolic areas returning to control levels, as determined by echocardiography. Supplementation also decreased antibody recognition of HOCl-damaged myocardial proteins. SCN- supplementation did not modulate serum markers of damage/inflammation (ANP, BNP, galectin-3, CRP), but returned metabolomic abnormalities (reductions in histidine, creatine and leucine by 0.83-, 0.84- and 0.89-fold, respectively), determined by NMR, to control levels. These data indicate that elevated levels of the MPO substrate SCN-, which can be readily modulated by dietary means, can protect against acute ischemia-reperfusion injury.

A unique urinary metabolomic signature for the detection of pancreatic ductal adenocarcinoma.

Our study aimed to identify a urinary metabolite panel for the detection/diagnosis of pancreatic ductal adenocarcinoma (PDAC). PDAC continues to have poor survival outcomes. One of the major reasons for poor prognosis is the advanced stage of the disease at diagnosis. Hence, identification of a novel and cost-effective biomarker signature for early detection/diagnosis of PDAC could lead to better survival outcomes. Untargeted metabolomics was employed to identify a novel metabolite-based biomarker signature for PDAC diagnosis. Urinary metabolites from 92 PDAC patients (56 discovery cohort and 36 validation cohort) were compared with 56 healthy volunteers using 1 H nuclear magnetic resonance spectroscopy. Multivariate (partial-least squares discriminate analysis) and univariate (Mann-Whitney's U-test) analyses were performed to identify a metabolite panel which can be used to detect PDAC. The selected metabolites were further validated for their diagnostic potential using the area under the receiver operating characteristic (AUROC) curve. Statistical analysis identified a six-metabolite panel (trigonelline, glycolate, hippurate, creatine, myoinositol and hydroxyacetone), which demonstrated high potential to diagnose PDAC, with AUROC of 0.933 and 0.864 in the discovery and validation cohort, respectively. Notably, the identified panel also demonstrated very high potential to diagnose early-stage (I and II) PDAC patients with AUROC of 0.897. These results demonstrate that the selected metabolite signature could be used to detect PDAC and will pave the way for the development of a urinary test for detection/diagnosis of PDAC.

Changes in the blood metabolome of Wagyu crossbred steers with time in the feedlot and relationships with marbling.

Wagyu crossbred steers (n = 167) were used to (1) compare the metabolome of individual animals at two distant time-points (days 196 and 432) in a feedlot (this corresponded to 272 and 36 days before slaughter); and (2) determine relationships between the metabolome and marbling, and the effect of days in the feedlot (time-points) on these relationships. 1H NMR spectroscopy followed by standard recoupling of variables analysis produced 290 features or 'peaks' from which 38 metabolites were identified. There was a positive correlation between the relative concentration (RC) at days 196 and 432 for 35 of 38 metabolites (P > 0.05). The RC of 21 metabolites mostly involved in muscle energy and glucose metabolism increased (P < 0.05) from day 196 to 432, and the RC of 13 metabolites mostly involved in lipid metabolism decreased (P < 0.05). There were 14 metabolites correlated with marbling including metabolites involved in energy and fat metabolism (glucose, propionate, 3-hydroxybutyrate, lipids). The relationship between marbling and the RC of metabolites was affected by time-point, being positive for 3-hydroxybutyrate and acetate (P < 0.05) at day 432 but not at day 196. The findings indicate that the blood metabolome in Wagyu crossbred steers changes with time in a feedlot. Notwithstanding, the metabolome has potential to predict marbling in Wagyu. The ability to predict marbling from the blood metabolome appears to be influenced by days in a feedlot and presumably the stage of development towards a mature body conformation.

Remote Ischemic Preconditioning induces Cardioprotective Autophagy and Signals through the IL-6-Dependent JAK-STAT Pathway.

: Autophagy is a cellular process by which mammalian cells degrade and assist in recycling damaged organelles and proteins. This study aimed to ascertain the role of autophagy in remote ischemic preconditioning (RIPC)-induced cardioprotection. Sprague Dawley rats were subjected to RIPC at the hindlimb followed by a 30-min transient blockade of the left coronary artery to simulate ischemia reperfusion (I/R) injury. Hindlimb muscle and the heart were excised 24 h post reperfusion. RIPC prior to I/R upregulated autophagy in the rat heart at 24 h post reperfusion. In vitro, autophagy inhibition or stimulation prior to RIPC, respectively, either ameliorated or stimulated the cardioprotective effect, measured as improved cell viability to mimic the preconditioning effect. Recombinant interleukin-6 (IL-6) treatment prior to I/R increased in vitro autophagy in a dose-dependent manner, activating the Janus kinase/signal transducers and activators of transcription (JAK-STAT) pathway without affecting the other kinase pathways, such as p38 mitogen-activated protein kinases (MAPK), and glycogen synthase kinase 3 Beta (GSK-3ß) pathways. Prior to I/R, in vitro inhibition of the JAK-STAT pathway reduced autophagy upregulation despite recombinant IL-6 pre-treatment. Autophagy is an essential component of RIPC-induced cardioprotection that may upregulate autophagy through an IL-6/JAK-STAT-dependent mechanism, thus identifying a potentially new therapeutic option for the treatment of ischemic heart disease.

Nuclear magnetic resonance spectroscopy of human body fluids and in vivo magnetic resonance spectroscopy: Potential role in the diagnosis and management of prostate cancer.

Prostate cancer is the most common solid organ cancer in men, and the second most common cause of male cancer-related mortality. It has few effective therapies, and is difficult to diagnose accurately. Prostate-specific antigen (PSA), which is currently the most effective diagnostic tool available, cannot reliably discriminate between different pathologies, and in fact only around 30% of patients found to have elevated levels of PSA are subsequently confirmed to actually have prostate cancer. As such, there is a desperate need for more reliable diagnostic tools that will allow the early detection of prostate cancer so that the appropriate interventions can be applied. Nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance spectroscopy (MRS) are 2 high throughput, noninvasive analytical procedures that have the potential to enable differentiation of prostate cancer from other pathologies using metabolomics, by focusing specifically on certain metabolites which are associated with the development of prostate cancer cells and its progression. The value that this type of approach has for the early detection, diagnosis, prognosis, and personalized treatment of prostate cancer is becoming increasingly apparent. Recent years have seen many promising developments in the fields of NMR spectroscopy and MRS, with improvements having been made to hardware as well as to techniques associated with the acquisition, processing, and analysis of related data. This review focuses firstly on proton NMR spectroscopy of blood serum, urine, and expressed prostatic secretions in vitro, and then on 1- and 2-dimensional proton MRS of the prostate in vivo. Major advances in these fields and methodological principles of data collection, acquisition, processing, and analysis are described along with some discussion of related challenges, before prospects that proton MRS has for future improvements to the clinical management of prostate cancer are considered.

Relationship of the blood metabolome to subsequent carcass traits at slaughter in feedlot Wagyu crossbred steers.

The aim of the present study was to determine the relationships between the blood metabolome and (1) carcass traits with a focus on intramuscular fat (marbling), and (2) the length of time cattle consumed a high-starch diet in feedlot cattle. Blood samples were obtained from 181 Wagyu-crossbred steers between 300-400 days before slaughter when carcass data was collected. 1H NMR spectroscopy identified 35 metabolites with 7 positively associated with marbling (3-hydroxybutyrate, propionate, acetate, creatine, histidine, valine, and isoleucine; P ≤ 0.05). Subcutaneous rump fat thickness was positively associated with glucose, leucine and lipids (P ≤ 0.05) and negatively associated with anserine and arabinose (P ≤ 0.05). Carcass weight and growth rate were negatively associated with 3-hydroxybutyrate (P < 0.05), and growth rate was negatively associated with creatine (P < 0.05) and positively associated with aspartate (P < 0.05). Glucose and arginine showed a significant interaction between marbling and number of days animals consumed a high-starch diet (P < 0.05). Sire was the single variable with the largest effect on the relative concentration of metabolites and carcass and production traits. Blood metabolomics helps understand fat and muscle metabolism, and is associated with genotype, and carcass and production traits in cattle offering potential biomarkers suitable to select animals for management and genetic improvement.

Circulating mediators of remote ischemic preconditioning: search for the missing link between non-lethal ischemia and cardioprotection.

Acute myocardial infarction (AMI) is one of the leading causes of mortality and morbidity worldwide. There has been an extensive search for cardioprotective therapies to reduce myocardial ischemia-reperfusion (I/R) injury. Remote ischemic preconditioning (RIPC) is a phenomenon that relies on the body's endogenous protective modalities against I/R injury. In RIPC, non-lethal brief I/R of one organ or tissue confers protection against subsequent lethal I/R injury in an organ remote to the briefly ischemic organ or tissue. Initially it was believed to be limited to direct myocardial protection, however it soon became apparent that RIPC applied to other organs such as kidney, liver, intestine, skeletal muscle can reduce myocardial infarct size. Intriguing discoveries have been made in extending the concept of RIPC to other organs than the heart. Over the years, the underlying mechanisms of RIPC have been widely sought and discussed. The involvement of blood-borne factors as mediators of RIPC has been suggested by a number of research groups. The main purpose of this review article is to summarize the possible circulating mediators of RIPC, and recent studies to establish the clinical efficacy of these mediators in cardioprotection from lethal I/R injury.

Proteo-metabolomics reveals compensation between ischemic and non-injured contralateral kidneys after reperfusion.

Ischaemia and reperfusion injury (IRI) is the leading cause of acute kidney injury (AKI), which contributes to high morbidity and mortality rates in a wide range of injuries as well as the development of chronic kidney disease. The cellular and molecular responses of the kidney to IRI are complex and not fully understood. Here, we used an integrated proteomic and metabolomic approach to investigate the effects of IRI on protein abundance and metabolite levels. Rat kidneys were subjected to 45 min of warm ischaemia followed by 4 h and 24 h reperfusion, with contralateral and separate healthy kidneys serving as controls. Kidney tissue proteomics after IRI revealed elevated proteins belonging to the acute phase response, coagulation and complement pathways, and fatty acid (FA) signalling. Metabolic changes were already evident after 4 h reperfusion and showed increased level of glycolysis, lipids and FAs, whilst mitochondrial function and ATP production was impaired after 24 h. This deficit was partially compensated for by the contralateral kidney. Such a metabolic balance counteracts for the developing energy deficit due to reduced mitochondrial function in the injured kidney.

Utility of metabolic profiling of serum in the diagnosis of pregnancy complications.

INTRODUCTION: Currently there are no clinical screening tests available to identify pregnancies at risk of developing preeclampsia (PET) and/or intrauterine growth restriction (IUGR), both of which are associated with abnormal placentation. Metabolic profiling is now a stable analytical platform used in many laboratories and has successfully been used to identify biomarkers associated with various pathological states. METHODS: We used nuclear magnetic resonance spectroscopy (NMR) to metabolically profile serum samples collected from 143 pregnant women at 26-41 weeks gestation with pregnancy outcomes of PET, IUGR, PET IUGR or small for gestational age (SGA) that were age-matched to normal pre/term pregnancies. RESULTS: Spectral analysis found no difference in the measured metabolites from normal term, pre-term and SGA samples, and of 25 identified metabolites, only glutamate was marginally different between groups. Of the identified metabolites, 3-methylhistidine, creatinine, acetyl groups and acetate, were determined to be independent predictors of PET and produced area under the curves (AUC) = 0.938 and 0.936 for the discovery and validation sets. Only 3-hydroxybutyrate was determined to be an independent predictor of IUGR, however the model had low predictive power (AUC = 0.623 and 0.581 for the discovery and validation sets). CONCLUSIONS: A sub-panel of metabolites had strong predictive power for identifying PET samples in a validation dataset, however prediction of IUGR was more difficult using the identified metabolites. NMR based metabolomics can identify metabolites strongly associated with disease and has the potential to be useful in developing early clinical screening tests for at risk pregnancies.

Improving Visualization and Interpretation of Metabolome-Wide Association Studies: An Application in a Population-Based Cohort Using Untargeted 1H NMR Metabolic Profiling.

1H NMR spectroscopy of biofluids generates reproducible data allowing detection and quantification of small molecules in large population cohorts. Statistical models to analyze such data are now well-established, and the use of univariate metabolome wide association studies (MWAS) investigating the spectral features separately has emerged as a computationally efficient and interpretable alternative to multivariate models. The MWAS rely on the accurate estimation of a metabolome wide significance level (MWSL) to be applied to control the family wise error rate. Subsequent interpretation requires efficient visualization and formal feature annotation, which, in-turn, call for efficient prioritization of spectral variables of interest. Using human serum 1H NMR spectroscopic profiles from 3948 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), we have performed a series of MWAS for serum levels of glucose. We first propose an extension of the conventional MWSL that yields stable estimates of the MWSL across the different model parameterizations and distributional features of the outcome. We propose both efficient visualization methods and a strategy based on subsampling and internal validation to prioritize the associations. Our work proposes and illustrates practical and scalable solutions to facilitate the implementation of the MWAS approach and improve interpretation in large cohort studies.

Workflow for Integrated Processing of Multicohort Untargeted 1H NMR Metabolomics Data in Large-Scale Metabolic Epidemiology.

Large-scale metabolomics studies involving thousands of samples present multiple challenges in data analysis, particularly when an untargeted platform is used. Studies with multiple cohorts and analysis platforms exacerbate existing problems such as peak alignment and normalization. Therefore, there is a need for robust processing pipelines that can ensure reliable data for statistical analysis. The COMBI-BIO project incorporates serum from ∼8000 individuals, in three cohorts, profiled by six assays in two phases using both 1H NMR and UPLC-MS. Here we present the COMBI-BIO NMR analysis pipeline and demonstrate its fitness for purpose using representative quality control (QC) samples. NMR spectra were first aligned and normalized. After eliminating interfering signals, outliers identified using Hotelling's T2 were removed and a cohort/phase adjustment was applied, resulting in two NMR data sets (CPMG and NOESY). Alignment of the NMR data was shown to increase the correlation-based alignment quality measure from 0.319 to 0.391 for CPMG and from 0.536 to 0.586 for NOESY, showing that the improvement was present across both large and small peaks. End-to-end quality assessment of the pipeline was achieved using Hotelling's T2 distributions. For CPMG spectra, the interquartile range decreased from 1.425 in raw QC data to 0.679 in processed spectra, while the corresponding change for NOESY spectra was from 0.795 to 0.636, indicating an improvement in precision following processing. PCA indicated that gross phase and cohort differences were no longer present. These results illustrate that the pipeline produces robust and reproducible data, successfully addressing the methodological challenges of this large multifaceted study.

Development and Application of Ultra-Performance Liquid Chromatography-TOF MS for Precision Large Scale Urinary Metabolic Phenotyping.

To better understand the molecular mechanisms underpinning physiological variation in human populations, metabolic phenotyping approaches are increasingly being applied to studies involving hundreds and thousands of biofluid samples. Hyphenated ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) has become a fundamental tool for this purpose. However, the seemingly inevitable need to analyze large studies in multiple analytical batches for UPLC-MS analysis poses a challenge to data quality which has been recognized in the field. Herein, we describe in detail a fit-for-purpose UPLC-MS platform, method set, and sample analysis workflow, capable of sustained analysis on an industrial scale and allowing batch-free operation for large studies. Using complementary reversed-phase chromatography (RPC) and hydrophilic interaction liquid chromatography (HILIC) together with high resolution orthogonal acceleration time-of-flight mass spectrometry (oaTOF-MS), exceptional measurement precision is exemplified with independent epidemiological sample sets of approximately 650 and 1000 participant samples. Evaluation of molecular reference targets in repeated injections of pooled quality control (QC) samples distributed throughout each experiment demonstrates a mean retention time relative standard deviation (RSD) of <0.3% across all assays in both studies and a mean peak area RSD of <15% in the raw data. To more globally assess the quality of the profiling data, untargeted feature extraction was performed followed by data filtration according to feature intensity response to QC sample dilution. Analysis of the remaining features within the repeated QC sample measurements demonstrated median peak area RSD values of <20% for the RPC assays and <25% for the HILIC assays. These values represent the quality of the raw data, as no normalization or feature-specific intensity correction was applied. While the data in each experiment was acquired in a single continuous batch, instances of minor time-dependent intensity drift were observed, highlighting the utility of data correction techniques despite reducing the dependency on them for generating high quality data. These results demonstrate that the platform and methodology presented herein is fit-for-use in large scale metabolic phenotyping studies, challenging the assertion that such screening is inherently limited by batch effects. Details of the pipeline used to generate high quality raw data and mitigate the need for batch correction are provided.

A guide to the identification of metabolites in NMR-based metabonomics/metabolomics experiments.

Metabonomics/metabolomics is an important science for the understanding of biological systems and the prediction of their behaviour, through the profiling of metabolites. Two technologies are routinely used in order to analyse metabolite profiles in biological fluids: nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), the latter typically with hyphenation to a chromatography system such as liquid chromatography (LC), in a configuration known as LC-MS. With both NMR and MS-based detection technologies, the identification of the metabolites in the biological sample remains a significant obstacle and bottleneck. This article provides guidance on methods for metabolite identification in biological fluids using NMR spectroscopy, and is illustrated with examples from recent studies on mice.

Translational and emerging clinical applications of metabolomics in cardiovascular disease diagnosis and treatment.

Numerous molecular screening strategies have recently been developed to measure the chemical diversity of a population's biofluids with the ultimate aim to provide clinicians, medical scientists and epidemiologists with a clearer picture of the presence and severity of cardiovascular disease; prognosis; and response to treatment. Current cardiology practice integrates clinical history and examination with state-of-the-art imaging, invasive measures, and electrical interrogation. Biomarkers in common clinical use are relatively limited to troponin and brain natriuretic peptide, dependent on damage to heart muscle, or myocyte 'stretch' respectively. Although they have been recently applied to risk stratification in asymptomatic individuals at higher risk, the development of markers capable of detecting earlier phases of disease development would facilitate targeted strategies to prevent pathological complications in the general community. Metabolomics is the systematic study of small molecules in biological fluids. Profiling strategies aim to comprehensively measure and quantify such biomarkers in a fast, cost-effective and clinically informative manner. Techniques tend to be applied in an unbiased fashion, with advanced statistical methods allowing for identification of signature profiles in particular cohorts. In this manner, metabolomics has the potential to identify new pathophysiological pathways, and thus therapeutic targets, as well as assist in improved risk-stratification and personalized cardiovascular medicine. The latter has great potential in the primary and secondary cardiovascular disease prevention settings, integrating known and as yet unidentified host and environmental factors. The current review discusses applications of metabolomic techniques relevant to both the research and the clinical cardiologist.

Bidirectional communication between the Aryl hydrocarbon Receptor (AhR) and the microbiome tunes host metabolism.

The ligand-induced transcription factor, aryl hydrocarbon receptor (AhR) is known for its capacity to tune adaptive immunity and xenobiotic metabolism-biological properties subject to regulation by the indigenous microbiome. The objective of this study was to probe the postulated microbiome-AhR crosstalk and whether such an axis could influence metabolic homeostasis of the host. Utilising a systems-biology approach combining in-depth 1H-NMR-based metabonomics (plasma, liver and skeletal muscle) with microbiome profiling (small intestine, colon and faeces) of AhR knockout (AhR-/-) and wild-type (AhR+/+) mice, we assessed AhR function in host metabolism. Microbiome metabolites such as short-chain fatty acids were found to regulate AhR and its target genes in liver and intestine. The AhR signalling pathway, in turn, was able to influence microbiome composition in the small intestine as evident from microbiota profiling of the AhR+/+ and AhR-/- mice fed with diet enriched with a specific AhR ligand or diet depleted of any known AhR ligands. The AhR-/- mice also displayed increased levels of corticosterol and alanine in serum. In addition, activation of gluconeogenic genes in the AhR-/- mice was indicative of on-going metabolic stress. Reduced levels of ketone bodies and reduced expression of genes involved in fatty acid metabolism in the liver further underscored this observation. Interestingly, exposing AhR-/- mice to a high-fat diet showed resilience to glucose intolerance. Our data suggest the existence of a bidirectional AhR-microbiome axis, which influences host metabolic pathways.

(1)H NMR Spectroscopy of Fecal Extracts Enables Detection of Advanced Colorectal Neoplasia.

Colorectal cancer (CRC) is a growing cause of mortality in developing countries, warranting investigation into its etiopathogenesis and earlier diagnosis. Here, we investigated the fecal metabolic phenotype of patients with advanced colorectal neoplasia and controls using (1)H-nuclear magnetic resonance (NMR) spectroscopy and multivariate modeling. The fecal microbiota composition was assessed by quantitative real-time PCR as well as Wif-1 methylation levels in stools, serum, and urine and correlated to the metabolic profile of each patient. The predictivity of the model was 0.507 (Q(2)Y), and the explained variance was 0.755 (R(2)Y). Patients with advanced colorectal neoplasia demonstrated increased fecal concentrations of four short-chain fatty acids (valerate, acetate, propionate, and butyrate) and decreased signals relating to ß-glucose, glutamine, and glutamate. The predictive accuracy of the multivariate (1)H NMR model was higher than that of the guaiac-fecal occult blood test and the Wif-1 methylation test for predicting advanced colorectal neoplasia. Correlation analysis between fecal metabolites and bacterial profiles revealed strong associations between Faecalibacterium prausnitzii and Clostridium leptum species with short-chain fatty acids concentration and inverse correlation between Faecalibacterium prausnitzii and glucose. These preliminary results suggest that fecal metabonomics may potentially have a future role in a noninvasive colorectal screening program and may contribute to our understanding of the role of these dysregulated molecules in the cross-talk between the host and its bacterial microbiota.

Precision high-throughput proton NMR spectroscopy of human urine, serum, and plasma for large-scale metabolic phenotyping.

Proton nuclear magnetic resonance (NMR)-based metabolic phenotyping of urine and blood plasma/serum samples provides important prognostic and diagnostic information and permits monitoring of disease progression in an objective manner. Much effort has been made in recent years to develop NMR instrumentation and technology to allow the acquisition of data in an effective, reproducible, and high-throughput approach that allows the study of general population samples from epidemiological collections for biomarkers of disease risk. The challenge remains to develop highly reproducible methods and standardized protocols that minimize technical or experimental bias, allowing realistic interlaboratory comparisons of subtle biomarker information. Here we present a detailed set of updated protocols that carefully consider major experimental conditions, including sample preparation, spectrometer parameters, NMR pulse sequences, throughput, reproducibility, quality control, and resolution. These results provide an experimental platform that facilitates NMR spectroscopy usage across different large cohorts of biofluid samples, enabling integration of global metabolic profiling that is a prerequisite for personalized healthcare.