Publications
1002 results found
Vonhof EV, Piotto M, Holmes E, et al., 2020, Improved spatial resolution of metabolites in tissue biopsies using high-resolution magic-angle-spinning slice localization NMR spectroscopy., Analytical Chemistry, Vol: 92, Pages: 11516-11519, ISSN: 0003-2700
High-resolution magic-angle-spinning 1H NMR spectroscopy (HR-MAS NMR) is a well-established technique for assessing the biochemical composition of intact tissue samples. In this study, we utilized a method based on HR-MAS NMR spectroscopy with slice localization (SLS) to achieve spatial resolution of metabolites. The obtained 7 slice spectra from each of the model samples (i.e., chicken thigh muscle with skin and murine renal biopsy including medulla (M) and cortex (C)) showed distinct metabolite compositions. Furthermore, we analyzed previously acquired 1H HR-MAS NMR spectra of separated cortex and medulla samples using multivariate statistical methods. Concentrations of glycerophosphocholine (GPC) were found to be significantly higher in the renal medulla compared to the cortex. Using GPC as a biomarker, we identified the tissue slices that were predominantly the cortex or medulla. This study demonstrates that HR-MAS SLS combined with multivariate statistics has the potential for identifying tissue heterogeneity and detailed biochemical characterization of complex tissue samples.
Kimhofer T, Lodge S, Whiley L, et al., 2020, Integrative modelling of quantitative plasma lipoprotein, metabolic and amino acid data reveals a multi-organ pathological signature of SARS-CoV-2 infection, Journal of Proteome Research, Vol: 19, Pages: 4442-4454, ISSN: 1535-3893
The metabolic effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on human blood plasma were characterized using multi-platform metabolic phenotyping with Nuclear Magnetic Resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS). Quantitative measurements of lipoprotein sub-fractions, alpha-1-acid glycoprotein, glucose and biogenic amines were made on samples from symptomatic coronavirus disease 19 (COVID-19) patients who had tested positive for the SARS-CoV-2 virus (n = 17) and from age and gender-matched controls (n = 25). Data were analyzed using an orthogonal-projections to latent structures (O-PLS) method and used to construct an exceptionally strong (AUROC=1) hybrid NMR-MS model that enabled detailed metabolic discrimination between the groups and their biochemical relationships. Key discriminant metabolites included markers of inflammation including elevated alpha-1 acid glycoprotein and an increased kynurenine/tryptophan ratio. There was also an abnormal lipoprotein, glucose and amino acid signature consistent with diabetes and coronary artery disease (low total and HDL Apolipoprotein A1, low HDL triglycerides, high LDL and VLDL triglycerides). Plus, multiple highly significant amino acid markers of liver dysfunction (including the elevated glutamine/glutamate and Fischer’s ratios) that present themselves as part of a distinct SARS-CoV-2 infection pattern. A multivariate training-test set model was validated using independent samples from additional SARS-CoV-2 positive patients and controls. The predictive model showed a sensitivity of 100% for SARS-CoV-2 positivity. The breadth of the disturbed pathways indicates a systemic signature of SARS-CoV-2 positivity that includes elements of liver dysfunction, dyslipidaemia, diabetes, and coronary heart disease risk that are consistent with recent reports that COVID-19 is a systemic disease affecting multiple organs and systems. Metabolights study referenc
Garcia Perez I, Posma JM, Serrano Contreras JI, et al., 2020, Identifying unknown metabolites using NMR-based metabolic profiling techniques, Nature Protocols, Vol: 15, Pages: 2538-2567, ISSN: 1750-2799
Metabolic profiling of biological samples provides important insights into multiple physiological and pathological processes, but is hindered by a lack of automated annotation and standardised methods for structure elucidation of candidate disease biomarkers. Here, we describe a system for identifying molecular species derived from NMR spectroscopy based metabolic phenotyping studies, with detailed info on sample preparation, data acquisition, and data modelling. We provide eight different modular workflows to be followed in a recommended sequential order according to their level of difficulty. This multi-platform system involves the use of statistical spectroscopic tools such as STOCSY, STORM and RED-STORM to identify other signals in the NMR spectra relating to the same molecule. It also utilizes 2D-NMR spectroscopic analysis, separation and pre-concentration techniques, multiple hyphenated analytical platforms and data extraction from existing databases. The complete system, using all eight workflows, would take up to a month, as it includes multidimensional NMR experiments that require prolonged experiment times. However, easier identification cases using fewer steps would take two or three days. This approach to biomarker discovery is efficient, cost-effective and offers increased chemical space coverage of the metabolome, resulting in faster and more accurate assignment of NMR-generated biomarkers arising from metabolic phenotyping studies. Finally, it requires basic understanding of Matlab in order to perform statistical spectroscopic tools and analytical skills to perform Solid Phase Extraction, LC-fraction collection, LC-NMR-MS and 1D and 2D NMR experiments.
West K, Kanu C, Maric T, et al., 2020, Longitudinal metabolic and gut bacterial profiling of pregnant women with previous bariatric surgery, Gut, Vol: 69, Pages: 1452-1459, ISSN: 0017-5749
Due to the global increase in obesity rates and success of bariatric surgery in weight reduction, an increasing number of women now present pregnant with a previous bariatric procedure. This study investigates the extent of bariatric-associated metabolic and gut microbial alterations during pregnancy and their impact on fetal development.DesignA parallel metabonomic (1H NMR spectroscopy) and gut bacterial (16S rRNA gene amplicon sequencing) profiling approach was used to determine maternal longitudinal phenotypes associated with malabsorptive/mixed (n=25) or restrictive (n=16) procedures, compared to women with similar early pregnancy body mass index but without bariatric surgery (n=70). Metabolic profiles of offspring at birth were also analysed.ResultsPrevious malabsorptive, but not restrictive, procedures induced significant changes in maternal metabolic pathways involving branched-chain and aromatic amino acids with decreased circulation of leucine, isoleucine and isobutyrate, increased excretion of microbial-associated metabolites of protein putrefaction (phenylacetlyglutamine, p-cresol sulfate, indoxyl sulfate and p-hydroxyphenylacetate), and a shift in the gut microbiota. Urinary concentration of phenylacetylglutamine was significantly elevated in malabsorptive patients relative to controls (P=0.001) and was also elevated in urine of neonates born from these mothers (P=0.021). Furthermore, the maternal metabolic changes induced by malabsorptive surgery were associated with reduced maternal insulin resistance and fetal/birth weight.ConclusionMetabolism is altered in pregnant women with a previous malabsorptive bariatric surgery. These alterations may be beneficial for maternal outcomes, but the effect of elevated levels of phenolic and indolic compounds on fetal and infant health should be investigated further.
Letertre M, Munjoma NC, Slade SE, et al., 2020, Metabolic phenotyping using UPLC–MS and rapid microbore UPLC–IM–MS: determination of the effect of different dietary regimes on the urinary metabolome of the rat, Chromatographia, Vol: 83, Pages: 853-861, ISSN: 0009-5893
A rapid reversed-phase gradient method employing a 50 mm × 1 mm i.d., C18 microbore column, combined with ion mobility and high-resolution mass spectrometry, was applied to the metabolic phenotyping of urine samples obtained from rats receiving different diets. This method was directly compared to a “conventional” method employing a 150 × 2.1 mm i.d. column packed with the same C18 bonded phase using the same samples. Multivariate statistical analysis of the resulting data showed similar class discrimination for both microbore and conventional methods, despite the detection of fewer mass/retention time features by the former. Multivariate statistical analysis highlighted a number of ions that represented diet-specific markers in the samples. Several of these were then identified using the combination of mass, ion-mobility-derived collision cross section and retention time including N-acetylglutamate, urocanic acid, and xanthurenic acid. Kynurenic acid was tentatively identified based on mass and ion mobility data.
Posma JM, Garcia Perez I, Frost G, et al., 2020, Nutriome-metabolome relationships provide insights into dietary intake and metabolism, Nature Food, Vol: 1, Pages: 426-436, ISSN: 2662-1355
Dietary assessment traditionally relies on self-reported data which are often inaccurate and may result in erroneous diet-disease risk associations. We illustrate how urinary metabolic phenotyping can be used as alternative approach for obtaining information on dietary patterns. We used two multi-pass 24-hr dietary recalls, obtained on two occasions on average three weeks apart, paired with two 24-hr urine collections from 1,848 U.S. individuals; 67 nutrients influenced the urinary metabotype measured with ¹H-NMR spectroscopy characterized by 46 structurally identified metabolites. We investigated the stability of each metabolite over time and showed that the urinary metabolic profile is more stable within individuals than reported dietary patterns. The 46 metabolites accurately predicted healthy and unhealthy dietary patterns in a free-living U.S. cohort and replicated in an independent U.K. cohort. We mapped these metabolites into a host-microbial metabolic network to identify key pathways and functions. These data can be used in future studies to evaluate how this set of diet-derived, stable, measurable bioanalytical markers are associated with disease risk. This knowledge may give new insights into biological pathways that characterize the shift from a healthy to unhealthy metabolic phenotype and hence give entry points for prevention and intervention strategies.
Koundouros N, Karali E, Tripp A, et al., 2020, Metabolic fingerprinting links oncogenic PIK3CA with enhanced arachidonic acid-derived eicosanoids, Cell, Vol: 181, Pages: 1596-1611.e27, ISSN: 0092-8674
Oncogenic transformation is associated with profound changes in cellular metabolism, but whether tracking these can improve disease stratification or influence therapy decision-making is largely unknown. Using the iKnife to sample the aerosol of cauterized specimens, we demonstrate a new mode of real-time diagnosis, coupling metabolic phenotype to mutant PIK3CA genotype. Oncogenic PIK3CA results in an increase in arachidonic acid and a concomitant overproduction of eicosanoids, acting to promote cell proliferation beyond a cell-autonomous manner. Mechanistically, mutant PIK3CA drives a multimodal signaling network involving mTORC2-PKCζ-mediated activation of the calcium-dependent phospholipase A2 (cPLA2). Notably, inhibiting cPLA2 synergizes with fatty acid-free diet to restore immunogenicity and selectively reduce mutant PIK3CA-induced tumorigenicity. Besides highlighting the potential for metabolic phenotyping in stratified medicine, this study reveals an important role for activated PI3K signaling in regulating arachidonic acid metabolism, uncovering a targetable metabolic vulnerability that largely depends on dietary fat restriction.
Garcia Perez I, Posma JM, Chambers E, et al., 2020, Dietary metabotype modelling predicts individual responses to dietary interventions, Nature Food, Vol: 1, Pages: 355-364, ISSN: 2662-1355
Habitual consumption of poor quality diets is linked directly to risk factors for many non-communicable disease. This has resulted in the vast majority of countries globally and the World Health Organisation developing policies for healthy eating to reduce the prevalence of non communicable disease in the population. However, there is mounting evidence of variability in individual metabolic responses to any dietary intervention. We have developed a method for applying a pipeline for understanding inter-individual differences in response to diet, based on coupling data from highly-controlled dietary studies with deep metabolic phenotyping. In this feasibility study, we create an individual Dietary Metabotype Score (DMS) that embodies inter-individual variability in dietary response and captures consequent dynamic changes in concentrations of urinary metabolites. We find an inverse relationship between the DMS and blood glucose concentration. There is also a relationship between the DMS and urinary metabolic energy loss. Furthermore we employ a metabolic entropy approach to visualize individual and collective responses to dietary. Potentially, the DMS offers a method to target and to enhance dietary response at an individual level therefore reducing burden of non communicable diseases at a population level.
Letertre MPM, Munjoma NC, Wolfer K, et al., 2020, A two-way interaction between methotrexate and the gut microbiota of male Sprague Dawley rats, Journal of Proteome Research, Vol: 19, Pages: 3326-3339, ISSN: 1535-3893
Methotrexate (MTX) is a chemotherapeutic agent that cancause a range of toxic side effects including gastrointestinal damage,hepatotoxicity, myelosuppression, and nephrotoxicity and has potentiallycomplex interactions with the gut microbiome. Following untargeted UPLCqtof-MS analysis of urine and fecal samples from male Sprague−Dawley ratsadministered at either 0, 10, 40, or 100 mg/kg of MTX, dose-dependentchanges in the endogenous metabolite profiles were detected. Semiquantitativetargeted UPLC-MS detected MTX excreted in urine as well as MTX and twometabolites, 2,4-diamino-N-10-methylpteroic acid (DAMPA) and 7-hydroxyMTX, in the feces. DAMPA is produced by the bacterial enzymecarboxypeptidase glutamate 2 (CPDG2) in the gut. Microbiota profiling(16S rRNA gene amplicon sequencing) of fecal samples showed an increase inthe relative abundance of Firmicutes over the Bacteroidetes at low doses ofMTX but the reverse at high doses. Firmicutes relative abundance was positively correlated with DAMPA excretion in feces at 48 h,which were both lower at 100 mg/kg compared to that seen at 40 mg/kg. Overall, chronic exposure to MTX appears to inducecommunity and functionality changes in the intestinal microbiota, inducing downstream perturbations in CPDG2 activity, and thusmay delay MTX detoxication to DAMPA. This reduction in metabolic clearance might be associated with increased gastrointestinaltoxicity.
Barbas-Bernardos C, Garcia-Perez I, Lorenzo MP, et al., 2020, Development and validation of a high performance liquid chromatography-tandem mass spectrometry method for the absolute analysis of 17 alpha D-amino acids in cooked meals, Journal of Chromatography A, Vol: 1611, Pages: 1-17, ISSN: 0021-9673
In the nutrition field, there is a lack of understanding about the impact that dietary chiral composition may have on health, especially regarding cooked meals. Chiral amino acids (AAs) are naturally present in food and their proportion may vary quite a lot. Besides, the D-amino acids (D-AAs) are present in very low concentration compared to L-AAs, so very sensitive methods are required for their accurate quantitation. Moreover, some of them have been described as indicators of quality and different food processes. In this research, we propose a robust method for the absolute quantitation and enantiomeric ratio of 17 D-AAs in cooked meals. The AAs were extracted from 1 g of the homogenised meal with methanol, derivatised with (S)-N-(4-nitrophenoxycarbonyl) phenylalanine methoxyethyl ester ((S)-NIFE) and analysed by RP-LC-MS/MS. The separation was carried out with an Acquity BEH C18 (100 mm x 2.1 mm, 1.7 µm) column at 70 ºC, with 10 mmol/L ammonium bicarbonate in water as eluent A and acetonitrile as eluent B at a 0.3 mL/min flow rate in gradient elution. The MS operated in positive electrospray ionisation method in multiple reaction monitoring (MRM) mode. Isotopically labelled AAs were used as internal standards for the quantitation. The method was validated for 17 D-AAs in the cooked food samples in terms of specificity, linearity, precision, accuracy, matrix effect and stability. LLOQ are 2.0 ng/mL for most of them. Additionally, linearity was also studied for L-AAs. After optimization and validation, the method was applied to real breakfast, lunch and dinner samples of cooked meals (n = 18) that were part of a diet with a very high concordance with WHO dietary guidelines. Level of concentration of major and minor D-AAs have been described per total daily intake and within each of the three main meals. This method can be used for quality control purposes as well as to investigate the role of chiral composition in food and clinical outcomes.
Ocvirk S, Wilson AS, Posma JM, et al., 2019, A prospective cohort analysis of gut microbial co-metabolism in Alaska Native and rural African people at high and low risk of colorectal cancer, American Journal of Clinical Nutrition, Vol: 111, Pages: 406-419, ISSN: 0002-9165
BACKGROUND: Alaska Native (AN) people have the world's highest recorded incidence of sporadic colorectal cancer (CRC) (∼91:100,000), whereas rural African (RA) people have the lowest risk (<5:100,000). Previous data supported the hypothesis that diet affected CRC risk through its effects on the colonic microbiota that produce tumor-suppressive or -promoting metabolites. OBJECTIVES: We investigated whether differences in these metabolites may contribute to the high risk of CRC in AN people. METHODS: A cross-sectional observational study assessed dietary intake from 32 AN and 21 RA healthy middle-aged volunteers before screening colonoscopy. Analysis of fecal microbiota composition by 16S ribosomal RNA gene sequencing and fecal/urinary metabolites by 1H-NMR spectroscopy was complemented with targeted quantification of fecal SCFAs, bile acids, and functional microbial genes. RESULTS: Adenomatous polyps were detected in 16 of 32 AN participants, but not found in RA participants. The AN diet contained higher proportions of fat and animal protein and less fiber. AN fecal microbiota showed a compositional predominance of Blautia and Lachnoclostridium, higher microbial capacity for bile acid conversion, and low abundance of some species involved in saccharolytic fermentation (e.g., Prevotellaceae, Ruminococcaceae), but no significant lack of butyrogenic bacteria. Significantly lower concentrations of tumor-suppressive butyrate (22.5 ± 3.1 compared with 47.2 ± 7.3 SEM µmol/g) coincided with significantly higher concentrations of tumor-promoting deoxycholic acid (26.7 ± 4.2 compared with 11 ± 1.9 µmol/g) in AN fecal samples. AN participants had lower quantities of fecal/urinary metabolites than RA participants and metabolite profiles correlated with the abundance of distinct microbial genera in feces. The main microbial and metabolic CRC-associated markers were not significantly altered in
Sands C, Wolfer A, DS Correia G, et al., 2019, The nPYc-Toolbox, a Python module for the pre-processing, quality-control, and analysis of metabolic profiling datasets, Bioinformatics, Vol: 35, Pages: 5359-5360, ISSN: 1367-4803
Summary: As large-scale metabolic phenotyping studies become increasingly common, the need forsystemic methods for pre-processing and quality control (QC) of analytical data prior to statistical analysishas become increasingly important, both within a study, and to allow meaningful inter-study comparisons.The nPYc-Toolbox provides software for the import, pre-processing, QC, and visualisation of metabolicphenotyping datasets, either interactively, or in automated pipelines.Availability and Implementation: The nPYc-Toolbox is implemented in Python, and is freelyavailable from the Python package index https://pypi.org/project/nPYc/, source isavailable at https://github.com/phenomecentre/nPYc-Toolbox. Full documentation canbe found at http://npyc-toolbox.readthedocs.io/ and exemplar datasets and tutorials athttps://github.com/phenomecentre/nPYc-toolbox-tutorials
Kundu P, Lee HU, Garcia-Perez I, et al., 2019, Neurogenesis and prolongevity signaling in young germ-free mice transplanted with the gut microbiota of old mice., Science Translational Medicine, Vol: 11, Pages: 1-13, ISSN: 1946-6234
The gut microbiota evolves as the host ages, yet the effects of these microbial changes on host physiology and energy homeostasis are poorly understood. To investigate these potential effects, we transplanted the gut microbiota of old or young mice into young germ-free recipient mice. Both groups showed similar weight gain and skeletal muscle mass, but germ-free mice receiving a gut microbiota transplant from old donor mice unexpectedly showed increased neurogenesis in the hippocampus of the brain and increased intestinal growth. Metagenomic analysis revealed age-sensitive enrichment in butyrate-producing microbes in young germ-free mice transplanted with the gut microbiota of old donor mice. The higher concentration of gut microbiota-derived butyrate in these young transplanted mice was associated with an increase in the pleiotropic and prolongevity hormone fibroblast growth factor 21 (FGF21). An increase in FGF21 correlated with increased AMPK and SIRT-1 activation and reduced mTOR signaling. Young germ-free mice treated with exogenous sodium butyrate recapitulated the prolongevity phenotype observed in young germ-free mice receiving a gut microbiota transplant from old donor mice. These results suggest that gut microbiota transplants from aged hosts conferred beneficial effects in responsive young recipients.
Everett JR, Holmes E, Veselkov KA, et al., 2019, A uified conceptual framework for metabolic phenotyping in diagnosis and prognosis, Trends in Pharmacological Sciences, Vol: 40, Pages: 763-773, ISSN: 0165-6147
Understanding metabotype (multicomponent metabolic characteristics) variation can help to generate new diagnostic and prognostic biomarkers, as well as models, with potential to impact on patient management. We present a suite of conceptual approaches for the generation, analysis, and understanding of metabotypes from body fluids and tissues. We describe and exemplify four fundamental approaches to the generation and utilization of metabotype data via multiparametric measurement of (i) metabolite levels, (ii) metabolic trajectories, (iii) metabolic entropies, and (iv) metabolic networks and correlations in space and time. This conceptual framework can underpin metabotyping in the scenario of personalized medicine, with the aim of improving clinical outcomes for patients, but the framework will have value and utility in areas of metabolic profiling well beyond this exemplar.
Nye LC, Williams JP, Munjoma NC, et al., 2019, A comparison of collision cross section values obtained via travelling wave ion mobility-mass spectrometry and ultra high performance liquid chromatography-ion mobility-mass spectrometry: Application to the characterisation of metabolites in rat urine, Journal of Chromatography A, Vol: 1602, Pages: 386-396, ISSN: 0021-9673
A comprehensive Collision Cross Section (CCS) library was obtained via Travelling Wave Ion Guide mobility measurements through direct infusion (DI). The library consists of CCS and Mass Spectral (MS) data in negative and positive ElectroSpray Ionisation (ESI) mode for 463 and 479 endogenous metabolites, respectively. For both ionisation modes combined, TWCCSN2 data were obtained for 542 non-redundant metabolites. These data were acquired on two different ion mobility enabled orthogonal acceleration QToF MS systems in two different laboratories, with the majority of the resulting TWCCSN2 values (from detected compounds) found to be within 1% of one another. Validation of these results against two independent, external TWCCSN2 data sources and predicted TWCCSN2 values indicated to be within 1–2% of these other values. The same metabolites were then analysed using a rapid reversed-phase ultra (high) performance liquid chromatographic (U(H)PLC) separation combined with IM and MS (IM-MS) thus providing retention time (tr), m/z and TWCCSN2 values (with the latter compared with the DI-IM-MS data). Analytes for which TWCCSN2 values were obtained by U(H)PLC-IM-MS showed good agreement with the results obtained from DI-IM-MS. The repeatability of the TWCCSN2 values obtained for these metabolites on the different ion mobility QToF systems, using either DI or LC, encouraged the further evaluation of the U(H)PLC-IM-MS approach via the analysis of samples of rat urine, from control and methotrexate-treated animals, in order to assess the potential of the approach for metabolite identification and profiling in metabolic phenotyping studies. Based on the database derived from the standards 63 metabolites were identified in rat urine, using positive ESI, based on the combination of tr, TWCCSN2 and MS data.
Seow WJ, Shu X, Nicholson J, et al., 2019, Association of untargeted urinary metabolomics and lung cancer risk among never-smoking women in China., JAMA Network Open, Vol: 2, ISSN: 2574-3805
Importance Chinese women have the highest rate of lung cancer among female never-smokers in the world, and the etiology is poorly understood.Objective To assess the association between metabolomics and lung cancer risk among never-smoking women.Design, Setting, and Participants This nested case-control study included 275 never-smoking female patients with lung cancer and 289 never-smoking cancer-free control participants from the prospective Shanghai Women’s Health Study recruited from December 28, 1996, to May 23, 2000. Validated food frequency questionnaires were used for the collection of dietary information. Metabolomic analysis was conducted from November 13, 2015, to January 6, 2016. Data analysis was conducted from January 6, 2016, to November 29, 2018.Exposures Untargeted ultra-high-performance liquid chromatography–tandem mass spectrometry and nuclear magnetic resonance metabolomic profiles were characterized using prediagnosis urine samples. A total of 39 416 metabolites were measured.Main Outcomes and Measures Incident lung cancer.Results Among the 564 women, those who developed lung cancer (275 participants; median [interquartile range] age, 61.0 [52-65] years) and those who did not develop lung cancer (289 participants; median [interquartile range] age, 62.0 [53-66] years) at follow-up (median [interquartile range] follow-up, 10.9 [9.0-11.7] years) were similar in terms of their secondhand smoke exposure, history of respiratory diseases, and body mass index. A peak metabolite, identified as 5-methyl-2-furoic acid, was significantly associated with lower lung cancer risk (odds ratio, 0.57 [95% CI, 0.46-0.72]; P < .001; false discovery rate = 0.039). Furthermore, this peak was weakly correlated with self-reported dietary soy intake (ρ = 0.21; P < .001). Increasing tertiles of this metabolite were associated with lower lung cancer risk (in comparison with first tertile, odd
Tzoulaki I, Castagné R, Boulangé CL, et al., 2019, Serum metabolic signatures of coronary and carotid atherosclerosis and subsequent cardiovascular disease, European Heart Journal, Vol: 40, Pages: 2883-2896, ISSN: 1522-9645
Aims: To characterise serum metabolic signatures associated with atherosclerosis in the coronary or carotid arteries and subsequently their association with incident cardiovascular disease (CVD). Methods and Results: We used untargeted one-dimensional (1D) serum metabolic profiling by proton (1H) nuclear magnetic resonance (NMR) spectroscopy among 3,867 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), with replication among 3,569 participants from the Rotterdam and LOLIPOP Studies. Atherosclerosis was assessed by coronary artery calcium (CAC) and carotid intima-media thickness (IMT). We used multivariable linear regression to evaluate associations between NMR features and atherosclerosis accounting for multiplicity of comparisons. We then examined associations between metabolites associated with atherosclerosis and incident CVD available in MESA and Rotterdam and explored molecular networks through bioinformatics analyses. Overall, 30 NMR measured metabolites were associated with CAC and/or IMT, P =1.3x10-14 to 6.5x10-6 (discovery), P =4.2x10-14 to 4.4x10-2 (replication). These associations were substantially attenuated after adjustment for conventional cardiovascular risk factors. Metabolites associated with atherosclerosis revealed disturbances in lipid and carbohydrate metabolism, branched-chain and aromatic amino acid metabolism, as well as oxidative stress and inflammatory pathways. Analyses of incident CVD events showed inverse associations with creatine, creatinine and phenylalanine, and direct associations with mannose, acetaminophen-glucuronide and lactate as well as apolipoprotein B (P <0.05). Conclusion: Metabolites associated with atherosclerosis were largely consistent between the two vascular beds (coronary and carotid arteries) and predominantly tag pathways that overlap with the known cardiovascular risk factors. We present an integrated systems network that highlights a series of inter-connected pathways underlying atherosclero
McGill D, Chekmeneva E, Lindon J, et al., 2019, Application of novel solid phase extraction-NMR protocols for metabolic profiling of human urine, Faraday Discussions, Vol: 218, Pages: 395-416, ISSN: 1359-6640
Metabolite identification and annotation procedures are necessary for the discovery of biomarkers indicative of phenotypes or disease states, but these processes can be bottlenecked by the sheer complexity of biofluids containing thousands of different compounds. Here we describe low-cost novel SPE-NMR protocols utilising different cartridges and conditions, on both natural and artifical urine mixtures, which produce unique retention profiles useful to metabolic profiling. We find that different SPE methods applied to biofluids such as urine can be used to selectively retain metabolites based on compound taxonomy or other key functional groups, reducing peak overlap through concentration and fractionation of unknowns and hence promising greater control over the metabolite annotation/identification process.
Lahiri S, Kim H, Garcia-Perez I, et al., 2019, The gut microbiota influences skeletal muscle mass and function in mice, Science Translational Medicine, Vol: 11, ISSN: 1946-6234
The functional interactions between the gut microbiota and the host are important for host physiology, homeostasis, and sustained health. We compared the skeletal muscle of germ-free mice that lacked a gut microbiota to the skeletal muscle of pathogen-free mice that had a gut microbiota. Compared to pathogen-free mouse skeletal muscle, germ-free mouse skeletal muscle showed atrophy, decreased expression of insulin-like growth factor 1, and reduced transcription of genes associated with skeletal muscle growth and mitochondrial function. Nuclear magnetic resonance spectrometry analysis of skeletal muscle, liver, and serum from germ-free mice revealed multiple changes in the amounts of amino acids, including glycine and alanine, compared to pathogen-free mice. Germ-free mice also showed reduced serum choline, the precursor of acetylcholine, the key neurotransmitter that signals between muscle and nerve at neuromuscular junctions. Reduced expression of genes encoding Rapsyn and Lrp4, two proteins important for neuromuscular junction assembly and function, was also observed in skeletal muscle from germ-free mice compared to pathogen-free mice. Transplanting the gut microbiota from pathogen-free mice into germ-free mice resulted in an increase in skeletal muscle mass, a reduction in muscle atrophy markers, improved oxidative metabolic capacity of the muscle, and elevated expression of the neuromuscular junction assembly genes <jats:italic>Rapsyn</jats:italic> and <jats:italic>Lrp4</jats:italic>. Treating germ-free mice with short-chain fatty acids (microbial metabolites) partly reversed skeletal muscle impairments. Our results suggest a role for the gut microbiota in regulating skeletal muscle mass and function in mice.</jats:p>
Whiley L, Chekmeneva E, Berry DJ, et al., 2019, Systematic isolation and structure elucidation of urinary metabolites optimized for the analytical-scale molecular profiling laboratory, Analytical Chemistry, Vol: 91, Pages: 8873-8882, ISSN: 0003-2700
Annotation and identification of metabolite biomarkers is critical for their biological interpretation in metabolic phenotyping studies, presenting a significant bottleneck in the successful implementation of untargeted metabolomics. Here, a systematic multi-step protocol was developed for the purification and de novo structural elucidation of urinary metabolites. The protocol is most suited for instances where structure elucidation and metabolite annotation are critical for the downstream biological interpretation of metabolic phenotyping studies. First, a bulk urine pool was desalted using ion-exchange resins enabling large-scale fractionation using precise iterations of analytical scale chromatography. Primary urine fractions were collected and assembled into a “fraction bank” suitable for long-term laboratory storage. Secondary and tertiary fractionations exploited differences in selectivity across a range of reversed-phase chemistries, achieving the purification of metabolites of interest yielding an amount of material suitable for chemical characterisation. To exemplify the application of the systematic workflow in a diverse set of cases, four metabolites with a range of physico-chemical properties were selected and purified from urine and subjected to chemical formula and structure elucidation by respective magnetic resonance mass spectrometry (MRMS) and NMR analyses. Their structures were fully assigned as teterahydropentoxyline, indole-3-acetic-acid-O-glucuronide, p-cresol glucuronide, and pregnanediol-3-glucuronide. Unused effluent was collected, dried and returned to the fraction bank, demonstrating the viability of the system for repeat use in metabolite annotation with a high degree of efficiency.
Shen EY-L, Abellona U, Taylor-Robinson S, et al., 2019, Discovery and validation of plasma acylcarnitines for the early diagnosis of hepatocellular carcinoma, Annual Meeting of the American-Association-for-Cancer-Research (AACR), Publisher: AMER ASSOC CANCER RESEARCH, ISSN: 0008-5472
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Poynter L, Mirnezami R, Galea D, et al., 2019, Network mapping of molecular biomarkers influencing radiation response in rectal cancer, Clinical Colorectal Cancer, Vol: 18, Pages: e210-e222, ISSN: 1533-0028
IntroductionPre-operative radiotherapy (RT) has an important role in the management of locally advanced rectal cancer (RC). Tumour regression following RT shows marked variability and robust molecular methods are needed with which to predict likely response. The aim of this study was to review the current published literature and employ Gene Ontology (GO) analysis to define key molecular biomarkers governing radiation response in RC.MethodsA systematic review of electronic bibliographic databases (MEDLINE, Embase) was performed for original articles published between 2000 and 2015. Biomarkers were then classified according to biological function and incorporated into a hierarchical GO tree. Both significant and non-significant results were included in the analysis. Significance was binarized based on uni- and multivariate statistics. Significance scores were calculated for each biological domain (or node), and a direct acyclic graph was generated for intuitive mapping of biological pathways and markers involved in rectal cancer radiation response.Results72 individual biomarkers, across 74 studies, were identified through review. On highest order classification, molecular biomarkers falling within the domains of response to stress, cellular metabolism and pathways inhibiting apoptosis were found to be the most influential in predicting radiosensitivity.ConclusionsHomogenising biomarker data from original articles using controlled GO terminology demonstrates that cellular mechanisms of response to radiotherapy in RC - in particular the metabolic response to radiotherapy - may hold promise in developing radiotherapeutic biomarkers with which to predict, and in the future modulate, radiation response.
Rodriguez-Martinez A, Ayala R, Posma JM, et al., 2019, pJRES Binning Algorithm (JBA): a new method to facilitate the recovery of metabolic information from pJRES 1H NMR spectra, Bioinformatics, Vol: 35, Pages: 1916-1922, ISSN: 1367-4803
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 1D 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: The algorithm is implemented using the MWASTools R/Bioconductor package. Supplementary information: Supplementary data are available at Bioinformatics online.
Lees HJ, Swann JR, Poucher S, et al., 2019, Obesity and cage environment modulate metabolism in the Zucker rat: a multiple biological matrix approach to characterizing metabolic phenomena, Journal of Proteome Research, Vol: 18, Pages: 2160-2174, ISSN: 1535-3893
Obesity and its comorbidities are increasing worldwide imposing a heavy socioeconomic burden. The effects of obesity on the metabolic profiles of tissues (liver, kidney, pancreas), urine, and the systemic circulation were investigated in the Zucker rat model using 1H NMR spectroscopy coupled to multivariate statistical analysis. The metabolic profiles of the obese ( fa/ fa) animals were clearly differentiated from the two phenotypically lean phenotypes, ((+/+) and ( fa/+)) within each biological compartment studied, and across all matrices combined. No significant differences were observed between the metabolic profiles of the genotypically distinct lean strains. Obese Zucker rats were characterized by higher relative concentrations of blood lipid species, cross-compartmental amino acids (particularly BCAAs), urinary and liver metabolites relating to the TCA cycle and glucose metabolism; and lower amounts of urinary gut microbial-host cometabolites, and intermatrix metabolites associated with creatine metabolism. Further to this, the obese Zucker rat metabotype was defined by significant metabolic alterations relating to disruptions in the metabolism of choline across all compartments analyzed. The cage environment was found to have a significant effect on urinary metabolites related to gut-microbial metabolism, with additional cage-microenvironment trends also observed in liver, kidney, and pancreas. This study emphasizes the value in metabotyping multiple biological matrices simultaneously to gain a better understanding of systemic perturbations in metabolism, and also underscores the need for control or evaluation of cage environment when designing and interpreting data from metabonomic studies in animal models.
Katsidzira L, Ocvirk S, Wilson A, et al., 2019, Differences in fecal gut microbiota, short-chain fatty acids and bile acids link colorectal cancer risk to dietary changes associated with urbanization among Zimbabweans, Nutrition and Cancer, Vol: 71, Pages: 1313-1324, ISSN: 0163-5581
The incidence of colorectal cancer (CRC) is gradually rising in sub-Saharan Africa. This may be due to dietary changes associated with urbanization, which may induce tumor-promoting gut microbiota composition and function. We compared fecal microbiota composition and activity in 10 rural and 10 urban Zimbabweans for evidence of a differential CRC risk. Dietary intake was assessed by a food frequency questionnaire. Fecal microbiota composition, metabolomic profile, functional microbial genes were analyzed, and bile acids and short chain fatty acids quantified. Animal protein intake was higher among urban volunteers, but carbohydrate and fiber intake were similar. Bacteria related to Blautia obeum, Streptococcus bovis, and Subdoligranulum variabile were higher in urban residents, whereas bacteria related to Oscillospira guillermondii and Sporobacter termitidis were higher in rural volunteers. Fecal levels of primary bile acids, cholic acid, and chenodeoxycholic acid (P < 0.05), and secondary bile acids, deoxycholic acid (P < 0.05) and ursodeoxycholic acid (P < 0.001) were higher in urban residents. Fecal levels of acetate and propionate, but not butyrate, were higher in urban residents. The gut microbiota composition and activity among rural and urban Zimbabweans retain significant homogeneity (possibly due to retention of dietary fiber), but urban residents have subtle changes, which may indicate a higher CRC risk.
Whiley LW, Nye L, Grant I, et al., 2019, Ultrahigh-performance liquid chromatography tandem mass spectrometry with electrospray ionization quantification of tryptophan metabolites and markers of gut health in serum and plasmaapplication to clinical and epidemiology cohorts, Analytical Chemistry, Vol: 91, Pages: 5207-5216, ISSN: 0003-2700
A targeted ultrahigh-performance liquid chromatography tandem mass spectrometry with electrospray ionization (UHPLC-ESI-MS/MS) method has been developed for the quantification of tryptophan and its downstream metabolites from the kynurenine and serotonin pathways. The assay coverage also includes markers of gut health and inflammation, including citrulline and neopterin. The method was designed in 96-well plate format for application in multiday, multiplate clinical and epidemiology population studies. A chromatographic cycle time of 7 min enables the analysis of two 96-well plates in 24 h. To protect chromatographic column lifespan, samples underwent a two-step extraction, using solvent protein precipitation followed by delipidation via solid-phase extraction (SPE). Analytical validation reported accuracy of each analyte <20% for the lowest limit of quantification and <15% for all other quality control (QC) levels. The analytical precision for each analyte was 2.1–12.9%. To test the applicability of the method to multiplate and multiday preparations, a serum pool underwent periodic repeat analysis during a run consisting of 18 plates. The % CV (coefficient of variation) values obtained for each analyte were <15%. Additional biological testing applied the assay to samples collected from healthy control participants and two groups diagnosed with inflammatory bowel disease (IBD) (one group treated with the anti-inflammatory 5-aminosalicylic acid (5-ASA) and one group untreated), with results showing significant differences in the concentrations of picolinic acid, kynurenine, and xanthurenic acid. The short analysis time and 96-well plate format of the assay makes it suitable for high-throughput targeted UHPLC-ESI-MS/MS metabolomic analysis in large-scale clinical and epidemiological population studies.
Neves AL, Rodriguez-Martinez A, Ayala R, et al., 2019, A network-based data-mining approach to investigate indole-related microbiota-host co-metabolism
<jats:title>Abstract</jats:title><jats:sec><jats:title>Motivation</jats:title><jats:p>Indoles have been shown to play a significant role in cardiometabolic disorders. While some individual bacterial species are known to produce indole-adducts, to our best knowledge no studies have made use of publicly available genome data to identify prokaryotes, specifically those associated with the human gut microbiota, contributing to the indole metabolic network.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Here, we propose a computational strategy, comprising the integration of KEGG and BLAST, to identify prokaryote-specific metabolic reactions relevant for the production of indoles, as well as to predict new members of the human gut microbiota potentially involved in these reactions. By identifying relevant prokaryotic species for further validation studies<jats:italic>in vitro</jats:italic>, this strategy represents a useful approach for those interrogating the metabolism of other gut-derived microbial metabolites relevant to human health.</jats:p></jats:sec><jats:sec><jats:title>Availability</jats:title><jats:p>All R scripts and files (gut microbial dataset, FASTA protein sequences, BLASTP output files) are available from<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://github.com/AndreaRMICL/Microbial_networks">https://github.com/AndreaRMICL/Microbial_networks</jats:ext-link>.</jats:p></jats:sec><jats:sec><jats:title>Contact</jats:title><jats:p>ARM:<jats:email>andrea.rodriguez-martinez13@imperial.ac.uk</jats:email>; LH:<jats:email>lesley.hoyles@ntu.ac.uk</jats:email>.</jats:p></jats:sec>
Harbaum L, Ghataorhe P, Wharton J, et al., 2019, Reduced plasma levels of small HDL particles transporting fibrinolytic proteins in pulmonary arterial hypertension, Thorax, Vol: 74, Pages: 380-389, ISSN: 1468-3296
Background Aberrant lipoprotein metabolism has been implicated in experimental pulmonary hypertension, but the relevance to patients with pulmonary arterial hypertension (PAH) is inconclusive.Objective To investigate the relationship between circulating lipoprotein subclasses and survival in patients with PAH.Methods Using nuclear magnetic resonance spectroscopy, 105 discrete lipoproteins were measured in plasma samples from two cohorts of patients with idiopathic or heritable PAH. Data from 1124 plasma proteins were used to identify proteins linked to lipoprotein subclasses. The physical presence of proteins was confirmed in plasma lipoprotein subfractions separated by ultracentrifugation.Results Plasma levels of three lipoproteins from the small high-density lipoprotein (HDL) subclass, termed HDL-4, were inversely related to survival in both the discovery (n=127) and validation (n=77) cohorts, independent of exercise capacity, comorbidities, treatment, N-terminal probrain natriuretic peptide, C reactive protein and the principal lipoprotein classes. The small HDL subclass rich in apolipoprotein A-2 content (HDL-4-Apo A-2) exhibited the most significant association with survival. None of the other lipoprotein classes, including principal lipoprotein classes HDL and low-density lipoprotein cholesterol, were prognostic. Three out of nine proteins identified to associate with HDL-4-Apo A-2 are involved in the regulation of fibrinolysis, namely, the plasmin regulator, alpha-2-antiplasmin, and two major components of the kallikrein–kinin pathway (coagulation factor XI and prekallikrein), and their physical presence in the HDL-4 subfraction was confirmed.Conclusion Reduced plasma levels of small HDL particles transporting fibrinolytic proteins are associated with poor outcomes in patients with idiopathic and heritable PAH.
Brial F, Le Lay A, Hedjazi L, et al., 2019, Systems genetics of hepatic metabolome reveals octopamine as a target for non-alcoholic fatty liver disease treatment, Scientific Reports, Vol: 9, ISSN: 2045-2322
Non-alcoholic fatty liver disease (NAFLD) is often associated with obesity and type 2 diabetes. To disentangle etiological relationships between these conditions and identify genetically-determined metabolites involved in NAFLD processes, we mapped 1H nuclear magnetic resonance (NMR) metabolomic and disease-related phenotypes in a mouse F2 cross derived from strains showing resistance (BALB/c) and increased susceptibility (129S6) to these diseases. Quantitative trait locus (QTL) analysis based on single nucleotide polymorphism (SNP) genotypes identified diet responsive QTLs in F2 mice fed control or high fat diet (HFD). In HFD fed F2 mice we mapped on chromosome 18 a QTL regulating liver micro- and macrovesicular steatosis and inflammation, independently from glucose intolerance and adiposity, which was linked to chromosome 4. Linkage analysis of liver metabolomic profiling data identified a QTL for octopamine, which co-localised with the QTL for liver histopathology in the cross. Functional relationship between these two QTLs was validated in vivo in mice chronically treated with octopamine, which exhibited reduction in liver histopathology and metabolic benefits, underlining its role as a mechanistic biomarker of fatty liver with potential therapeutic applications.
Zalloua P, Kadar H, Hariri E, et al., 2019, Untargeted mass spectrometry lipidomics identifies correlation between serum sphingomyelins and plasma cholesterol, Lipids in Health and Disease, Vol: 18, ISSN: 1476-511X
BackgroundLipoproteins 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).MethodsWe 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.ResultsAmong 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.ConclusionAmong 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.
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