985 results found
Barbas-Bernardos C, Garcia-Perez I, Lorenzo MP, et al., 2019, Development and validation of a high performance liquid chromatography-tandem mass spectrometry method for the absolute analysis of 17 α D-amino acids in cooked meals., J Chromatogr A
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 outcome
Everett JR, Holmes E, Veselkov KA, et al., 2019, A Unified Conceptual Framework for Metabolic Phenotyping in Diagnosis and Prognosis, TRENDS IN PHARMACOLOGICAL SCIENCES, Vol: 40, Pages: 763-773, ISSN: 0165-6147
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
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
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.
Sands C, Wolfer A, DS Correia G, et al., The nPYc-Toolbox, a Python module for the pre-processing, quality-control, and analysis of metabolic profiling datasets, Bioinformatics, 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
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.
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.
Tzoulaki I, Karaman I, Dehghan A, et al., Serum metabolic signatures of coronary and carotid atherosclerosis and subsequent cardiovascular disease, European Heart Journal, 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
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, 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, Publisher: Cold Spring Harbor Laboratory
<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>email@example.com</jats:email>; LH: <jats:email>firstname.lastname@example.org</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.
Poynter L, Mirnezami R, Galea D, et al., 2019, Network mapping of molecular biomarkers influencing radiation response in rectal cancer, Clinical Colorectal Cancer, 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.
Gray N, Plumb RS, Wilson ID, et al., 2019, A validated UPLC-MS/MS assay for the quantification of amino acids and biogenic amines in rat urine, JOURNAL OF CHROMATOGRAPHY B-ANALYTICAL TECHNOLOGIES IN THE BIOMEDICAL AND LIFE SCIENCES, Vol: 1106, Pages: 50-57, ISSN: 1570-0232
Inglese P, Correia G, Takats Z, et al., 2019, SPUTNIK: an R package for filtering of spatially related peaks in mass spectrometry imaging data, Bioinformatics, Vol: 35, Pages: 178-180, ISSN: 1367-4803
Summary: SPUTNIK is an R package consisting of a series of tools to filter mass spectrometry imaging peaks characterized by a noisy or unlikely spatial distribution. SPUTNIK can produce mass spectrometry imaging datasets characterized by a smaller but more informative set of peaks, reduce the complexity of subsequent multi-variate analysis and increase the interpretability of the statistical results. Availability: SPUTNIK is freely available online from CRAN repository and at https://github.com/paoloinglese/SPUTNIK. The package is distributed under the GNU General Public License version 3 and is accompanied by example files and data. Supplementary information: Supplementary data are available at Bioinformatics online.
Adesina-Georgiadis KN, Gray N, Plumb RS, et al., 2018, The metabolic fate and effects of 2-bromophenol in male Sprague-Dawley rats, Xenobiotica, ISSN: 0049-8254
1. The metabolic fate and urinary excretion of 2-bromophenol, a phenolic metabolite of bromobenzene, was investigated in male Sprague Dawley rats following single intraperitoneal doses at either 0, 100 or 200 mg/kg. 2. Urine was collected for seven days and samples analysed using 1H NMR spectroscopy, inductively coupled plasma (ICP)MS, and UPLC-MS. 3. 1H NMR spectroscopy of the urine samples showed that, at these doses, 2-bromophenol had little effect on endogenous metabolite profiles, supporting histopathology and clinical chemistry data which showed no changes associated with the administration of 2-bromophenol at these doses. 4. The use of ICP-MS Provided a means for the selective detection and quantification of bromine-containing species and showed that between 15 and 30% of the dose was excreted via the urine over the 7 days of the study for both the 100 and 200 mg doses respectively. 6. The bulk of the excretion of Br-containing material had occurred by 8 hr post administration. UPLC-MS of urine revealed a number of metabolites of 2-bromophenol, with 2-bromophenol glucuronide and 2-bromophenol sulphate identified as the major species. A number of minor hydroxylated metabolites were also detected as their glucuronide, sulphate or O-methyl conjugates. There was no evidence for the production of reactive metabolites.
Izzi-Engbeaya CN, Comninos AN, Clarke S, et al., 2018, The effects of kisspeptin on β-cell function, serum metabolites and appetite in humans, Diabetes, Obesity and Metabolism, Vol: 20, Pages: 2800-2810, ISSN: 1462-8902
AimsTo investigate the effect of kisspeptin on glucose‐stimulated insulin secretion and appetite in humans.Materials and methodsIn 15 healthy men (age: 25.2 ± 1.1 years; BMI: 22.3 ± 0.5 kg m−2), we compared the effects of 1 nmol kg−1 h−1 kisspeptin versus vehicle administration on glucose‐stimulated insulin secretion, metabolites, gut hormones, appetite and food intake. In addition, we assessed the effect of kisspeptin on glucose‐stimulated insulin secretion in vitro in human pancreatic islets and a human β‐cell line (EndoC‐βH1 cells).ResultsKisspeptin administration to healthy men enhanced insulin secretion following an intravenous glucose load, and modulated serum metabolites. In keeping with this, kisspeptin increased glucose‐stimulated insulin secretion from human islets and a human pancreatic cell line in vitro. In addition, kisspeptin administration did not alter gut hormones, appetite or food intake in healthy men.ConclusionsCollectively, these data demonstrate for the first time a beneficial role for kisspeptin in insulin secretion in humans in vivo. This has important implications for our understanding of the links between reproduction and metabolism in humans, as well as for the ongoing translational development of kisspeptin‐based therapies for reproductive and potentially metabolic conditions.
Jimenez B, Holmes E, Heude C, et al., 2018, Quantitative lipoprotein subclass and low molecular weight metabolite analysis in human serum and plasma by 1H NMR spectroscopy in a multilaboratory trial, Analytical Chemistry, Vol: 90, Pages: 11962-11971, ISSN: 0003-2700
We report an extensive 600 MHz NMR trial of a quantitative lipoprotein and small molecule measurements in human blood serum and plasma. Five centers with eleven 600 MHz NMR spectrometers were used to analyze 98 samples including: 20 QCs, 37 commercially sourced, paired serum and plasma samples and 2 National Institute of Science and Technology, NIST, reference material 1951c replicates. Samples were analyzed using rigorous protocols for sample preparation and experimental acquisition. A commercial lipoprotein subclass analysis was used to quantify 105 lipoprotein subclasses and 24 low molecular weight metabolites from the nuclear magnetic resonance, NMR, spectra. For all spectrometers, the instrument specific variance in measuring internal quality controls, QCs, was lower than the percentage described by the National Cholesterol Education Program, NCEP, criteria for lipid testing (triglycerides<2.7%, cholesterol<2.8%; LDL-cholesterol<2.8%; HDL-cholesterol<2.3%), showing exceptional reproducibility for direct quantitation of lipoproteins in both matrices. The average RSD for the 105 lipoprotein parameters in the 11 instruments was 4.6% and 3.9% for the two NIST samples while it was 38% and 40% for the 37 commercially sourced plasmas and sera, respectively, showing negligible analytical compared to biological variation. The coefficient of variance, CV, obtained for the quantification of the small molecules across the 11 spectrometers was below 15% for 20 out of the 24 metabolites analyzed. This study provides further evidence of the suitability of NMR for high-throughput lipoprotein subcomponent analysis and small molecule quantitation with the exceptional reproducibility required for clinical and other regulatory settings.
Chekmeneva E, Dos Santos Correia G, Gomez Romero M, et al., 2018, Ultra performance liquid chromatography-high resolution mass spectrometry and direct infusion-high resolution mass spectrometry for combined exploratory and targeted metabolic profiling of human urine, Journal of Proteome Research, Vol: 17, Pages: 3492-3502, ISSN: 1535-3893
The application of metabolic phenotyping to epidemiological studies involving thousands of biofluid samples presents a challenge for the selection of analytical platforms that meet the requirements of high-throughput precision analysis and cost-effectiveness. Here, direct infusion nanoelectrospray (DI-nESI)- was compared to an ultra-performance (UPLC)-high resolution mass spectrometry (HRMS) method for metabolic profiling of an exemplary set of 132 human urine samples from a large epidemiological cohort. Both methods were developed and optimised to allow simultaneous collection of high resolution urinary metabolic profiles and quantitative data for a selected panel of 35 metabolites. The total run time for measuring the sample set in both polarities by UPLC-HRMS was of 5 days compared to 9 hours by DI-nESI-HRMS. To compare the classification ability of the two MS methods we performed exploratory analysis of the full-scan HRMS profiles to detect sex-related differences in biochemical composition. Although metabolite identification is less specific in DI-nESI-HRMS, the significant features responsible for discrimination between sexes were mostly the same in both MS-based platforms. Using the quantitative data we showed that 10 metabolites have strong correlation (Pearson’s r > 0.9 and Passing-Bablok regression slope 0.8-1.3) and good agreement assessed by Bland-Altman plots between UPLC-HRMS and DI-nESI-HRMS and thus, can be measured using a cheaper and less sample- and time-consuming method. Only five metabolites showed weak correlation (Pearson’s r< 0.4) and poor agreement due to the overestimation of the results by DI-nESI-HRMS, and the rest of metabolites showed acceptable correlation between the two methods.
Dumas M-E, Chilloux J, Myridakis A, et al., 2018, Microbiome inhibition of IRAK-4 by trimethylamine mediates metabolic and immune benefits in high fat diet-induced insulin resistance, 54th Annual Meeting of the European-Association-for-the-Study-of-Diabetes (EASD), Publisher: SPRINGER, Pages: S267-S268, ISSN: 0012-186X
Abellona MRU, Mark P, Ladep N, et al., 2018, Elucidating Serum and Urinary Hepatocellular Carcinoma Diagnostic Biomarker Panels: Insight from the United Kingdom and West Africa, Annual Meeting of the American-Association-for-the-Study-of-Liver-Diseases (AASLD) / Liver Meeting, Publisher: WILEY, Pages: 37A-38A, ISSN: 0270-9139
Hoyles L, Fernandez-Real J-M, Federici M, et al., 2018, Molecular phenomics and metagenomics of hepatic steatosis in non-diabetic obese women (vol 24, pg 1070, 2018), NATURE MEDICINE, Vol: 24, Pages: 1628-1628, ISSN: 1078-8956
Domingo-Almenara X, Montenegro-Burke JR, Ivanisevic J, et al., 2018, CMS-MRM and METLIN-MRM: a cloud library and public resource for targeted analysis of small molecules, NATURE METHODS, Vol: 15, Pages: 681-+, ISSN: 1548-7091
Hoyles L, Fernández-Real JM, Federici M, et al., 2018, Molecular phenomics and metagenomics of hepatic steatosis in non-diabetic obese women, Nature Medicine, Vol: 24, Pages: 1080-1080, ISSN: 1078-8956
Hepatic steatosis is a multifactorial condition that is often observed in obese patients and is a prelude to non-alcoholic fatty liver disease. Here, we combine shotgun sequencing of fecal metagenomes with molecular phenomics (hepatic transcriptome and plasma and urine metabolomes) in two well-characterized cohorts of morbidly obese women recruited to the FLORINASH study. We reveal molecular networks linking the gut microbiome and the host phenome to hepatic steatosis. Patients with steatosis have low microbial gene richness and increased genetic potential for the processing of dietary lipids and endotoxin biosynthesis (notably from Proteobacteria), hepatic inflammation and dysregulation of aromatic and branched-chain amino acid metabolism. We demonstrated that fecal microbiota transplants and chronic treatment with phenylacetic acid, a microbial product of aromatic amino acid metabolism, successfully trigger steatosis and branched-chain amino acid metabolism. Molecular phenomic signatures were predictive (area under the curve = 87%) and consistent with the gut microbiome having an effect on the steatosis phenome (>75% shared variation) and, therefore, actionable via microbiome-based therapies.
McDonald JAK, Kimhofer T, West K, et al., Role of the gut microbiota in autism spectrum disorder, ISME17, Publisher: Nature Publishing Group
McDonald JAK, Mullish BH, Pechlivanis A, et al., 2018, 24 - A novel route to controlling Clostridioides Difficile growth via short chain fatty acid and bile acid modulation, Digestive Diseases Week, Publisher: Elsevier, Pages: S8-S8, ISSN: 0016-5085
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