共查询到20条相似文献,搜索用时 31 毫秒
1.
Douglas B. Kell Stephen G. Oliver 《Metabolomics : Official journal of the Metabolomic Society》2016,12(9):148
Background
The term ‘metabolome’ was introduced to the scientific literature in September 1998.Aim and key scientific concepts of the review
To mark its 18-year-old ‘coming of age’, two of the co-authors of that paper review the genesis of metabolomics, whence it has come and where it may be going.2.
H. S. Arathi L. Bjostad E. Bernklau 《Metabolomics : Official journal of the Metabolomic Society》2018,14(6):86
Background and aims
Pollen is essential for successful plant reproduction and critical for plant-pollinator mutualisms, as pollen is essential larval nutrition. However, we understand very little about the chemical constituents of pollen leading us to this exploratory study characterizing plant and beehive pollen.Methods
We performed a metabolomics assay of canola flower pollen and beehive pollen.Results and discussion
The metabolome of canola pollen is affected by irrigation showing differences in lipids and non-polar secondary metabolites. Metabolome of beehive pollen is affected by plant source showing differences in pentose sugars, myo-inositol and furanose. Further research is needed to document the nutritional bases of plant-pollinator mutualism.3.
Tie-juan Shao Zhi-xing He Zhi-jun Xie Hai-chang Li Mei-jiao Wang Cheng-ping Wen 《Metabolomics : Official journal of the Metabolomic Society》2016,12(4):70
Introduction
The differences in fecal metabolome between ankylosing spondylitis (AS)/rheumatoid arthritis (RA) patients and healthy individuals could be the reason for an autoimmune disorder.Objectives
The study explored the fecal metabolome difference between AS/RA patients and healthy controls to clarify human immune disturbance.Methods
Fecal samples from 109 individuals (healthy controls 34, AS 40, and RA 35) were analyzed by 1H NMR spectroscopy. Data were analyzed with principal component analysis (PCA) and orthogonal projection to latent structure discriminant (OPLS-DA) analysis.Results
Significant differences in the fecal metabolic profiles could distinguish AS/RA patients from healthy controls but could not distinguish between AS and RA patients. The significantly decreased metabolites in AS/RA patients were butyrate, propionate, methionine, and hypoxanthine. Significantly increased metabolites in AS/RA patients were taurine, methanol, fumarate, and tryptophan.Conclusion
The metabolome variations in feces indicated AS and RA were two homologous diseases that could not be distinguished by 1H NMR metabolomics.4.
Antonio Rosato Leonardo Tenori Marta Cascante Pedro Ramon De Atauri Carulla Vitor A. P. Martins dos Santos Edoardo Saccenti 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):37
Introduction
Metabolomics is a well-established tool in systems biology, especially in the top–down approach. Metabolomics experiments often results in discovery studies that provide intriguing biological hypotheses but rarely offer mechanistic explanation of such findings. In this light, the interpretation of metabolomics data can be boosted by deploying systems biology approaches.Objectives
This review aims to provide an overview of systems biology approaches that are relevant to metabolomics and to discuss some successful applications of these methods.Methods
We review the most recent applications of systems biology tools in the field of metabolomics, such as network inference and analysis, metabolic modelling and pathways analysis.Results
We offer an ample overview of systems biology tools that can be applied to address metabolomics problems. The characteristics and application results of these tools are discussed also in a comparative manner.Conclusions
Systems biology-enhanced analysis of metabolomics data can provide insights into the molecular mechanisms originating the observed metabolic profiles and enhance the scientific impact of metabolomics studies.5.
Rachel A. Spicer Christoph Steinbeck 《Metabolomics : Official journal of the Metabolomic Society》2018,14(1):16
Introduction
Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.Objectives
(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.Methods
A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.Results
Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.Conclusion
Further efforts are required to improve data sharing in metabolomics.6.
Jean-Pierre Trezzi Alexandre Bulla Camille Bellora Michael Rose Pierre Lescuyer Michael Kiehntopf Karsten Hiller Fay Betsou 《Metabolomics : Official journal of the Metabolomic Society》2016,12(6):96
Introduction
Metabolome analysis is complicated by the continuous dynamic changes of metabolites in vivo and ex vivo. One of the main challenges in metabolomics is the robustness and reproducibility of results, partially driven by pre-analytical variations.Objectives
The objective of this study was to analyse the impact of pre-centrifugation time and temperature, and to determine a quality control marker in plasma samples.Methods
Plasma metabolites were measured by gas chromatography-mass spectrometry (GC–MS) and analysed with the MetaboliteDetector software. The metabolites, which were the most labile to pre-analytical variations, were further measured by enzymatic assays. A score was calculated for their use as quality control markers.Results
The pre-centrifugation temperature was shown to be critical in the stability of plasma samples and had a significant impact on metabolite concentration profiles. In contrast, pre-centrifugation delay had only a minor impact. Based on the results of this study, whole blood should be kept on wet ice and centrifuged within maximum 3 h as a prerequisite for preparing EDTA plasma samples fit for the purpose of metabolome analysis.Conclusions
We have established a novel blood sample quality control marker, the LacaScore, based on the ascorbic acid to lactic acid ratio in plasma, which can be used as an indicator of the blood pre-centrifugation conditions, and hence the suitability of the sample for metabolome analyses. This method can be applied in research institutes and biobanks, enabling assessment of the quality of their plasma sample collections.7.
Miriam Reverter Marie-Aude Tribalat Thierry Pérez Olivier P. Thomas 《Metabolomics : Official journal of the Metabolomic Society》2018,14(9):114
Introduction
The study of natural variation of metabolites brings valuable information on the physiological state of the organisms as well as their phenotypic traits. In marine organisms, metabolome variability has mostly been addressed through targeted studies on metabolites of ecological or pharmaceutical interest. However, comparative metabolomics has demonstrated its potential to address the overall and complex metabolic variability of organisms.Objectives
In this study, the intraspecific (temporal and spatial) variability of two Mediterranean Haliclona sponges (H. fulva and H. mucosa) was investigated through an untargeted and then targeted metabolomics approach and further compared to their interspecific variability.Methods
Samples of both species were collected monthly during 1 year in the coralligenous habitat of the Northwestern Mediterranean sae at Marseille and Nice. Their metabolomic profiles were obtained by UHPLC-QqToF analyses.Results
Marked variations were noticed in April and May for both species including a decrease in Shannon’s diversity and concentration in specialized metabolites together with an increase in fatty acids and lyso-PAF like molecules. Spatial variations across different sampling sites could also be observed for both species, however in a lesser extent.Conclusions
Synchronous metabolic changes possibly triggered by physiological factors like reproduction and/or environmental factors like an increase in the water temperature were highlighted for both Mediterranean Haliclona species inhabiting close habitats but displaying different biosynthetic pathways. Despite significative intraspecific variations, metabolomic variability remains minor when compared to interspecific variations for these congenerous species, therefore suggesting the predominance of genetic information of the holobiont in the observed metabolome.8.
N. Cesbron A.-L. Royer Y. Guitton A. Sydor B. Le Bizec G. Dervilly-Pinel 《Metabolomics : Official journal of the Metabolomic Society》2017,13(8):99
Introduction
Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.Objectives
In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.Methods
The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.Results
A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.Conclusion
The workflow generated repeatable and informative fingerprints for robust metabolome characterization.9.
Effect of gut microbiota on host whole metabolome 总被引:1,自引:0,他引:1
Takeo Moriya Yoshinori Satomi Shumpei Murata Hiroshi Sawada Hiroyuki Kobayashi 《Metabolomics : Official journal of the Metabolomic Society》2017,13(9):101
Introduction
Recent advances in microbiome research have revealed the diverse participation of gut microbiota in a number of diseases. Bacteria-specific endogenous small molecules are produced in the gut, are transported throughout the whole body by circulation, and play key roles in disease establishment. However, the factors and mechanisms underlying these microbial influences largely remain unknown.Objectives
The purpose of this study was to use metabolomics to better understand the influence of microbiota on host physiology.Methods
Germ-free mice (GF) were orally administered with the feces of specific pathogen-free (SPF) mice and were maintained in a vinyl isolator for 4 weeks for establishing the so-called ExGF mice. Comparative metabolomics was performed on luminal contents, feces, urine, plasma, and tissues of GF and ExGF mice.Results
The metabolomics profile of 1716 compounds showed marked difference between GF and ExGF for each matrix. Intestinal differences clearly showed the contribution of microbiota to host digestive activities. In addition, colonic metabolomics revealed the efficient conversion of primary to secondary metabolites by microbiota. Furthermore, metabolomics of tissues and excrements demonstrated the effect of microbiota on the accumulation of metabolites in tissues and during excretion. These effects included known bacterial effects (such as bile acids and amino acids) as well as novel ones, including a drastic decrease of sphingolipids in the host.Conclusion
The diverse effects of microbiota on different sites of the host metabolome were revealed and novel influences on host physiology were demonstrated. These findings should contribute to a deeper understanding of the influence of gut microbiota on disease states and aid in the development of effective intervention strategies.10.
Nguyen Phuoc Long Sang Jun Yoon Nguyen Hoang Anh Tran Diem Nghi Dong Kyu Lim Yu Jin Hong Soon-Sun Hong Sung Won Kwon 《Metabolomics : Official journal of the Metabolomic Society》2018,14(8):109
Introduction
Metabolomics is an emerging approach for early detection of cancer. Along with the development of metabolomics, high-throughput technologies and statistical learning, the integration of multiple biomarkers has significantly improved clinical diagnosis and management for patients.Objectives
In this study, we conducted a systematic review to examine recent advancements in the oncometabolomics-based diagnostic biomarker discovery and validation in pancreatic cancer.Methods
PubMed, Scopus, and Web of Science were searched for relevant studies published before September 2017. We examined the study designs, the metabolomics approaches, and the reporting methodological quality following PRISMA statement.Results and Conclusion
The included 25 studies primarily focused on the identification rather than the validation of predictive capacity of potential biomarkers. The sample size ranged from 10 to 8760. External validation of the biomarker panels was observed in nine studies. The diagnostic area under the curve ranged from 0.68 to 1.00 (sensitivity: 0.43–1.00, specificity: 0.73–1.00). The effects of patients’ bio-parameters on metabolome alterations in a context-dependent manner have not been thoroughly elucidated. The most reported candidates were glutamic acid and histidine in seven studies, and glutamine and isoleucine in five studies, leading to the predominant enrichment of amino acid-related pathways. Notably, 46 metabolites were estimated in at least two studies. Specific challenges and potential pitfalls to provide better insights into future research directions were thoroughly discussed. Our investigation suggests that metabolomics is a robust approach that will improve the diagnostic assessment of pancreatic cancer. Further studies are warranted to validate their validity in multi-clinical settings.11.
Takeo Moriya Yoshinori Satomi Hiroyuki Kobayashi 《Metabolomics : Official journal of the Metabolomic Society》2016,12(12):179
Introduction
Human plasma metabolomics offer powerful tools for understanding disease mechanisms and identifying clinical biomarkers for diagnosis, efficacy prediction and patient stratification. Although storage conditions can affect the reliability of data from metabolites, strict control of these conditions remains challenging, particularly when clinical samples are included from multiple centers. Therefore, it is necessary to consider stability profiles of each analyte.Objectives
The purpose of this study was to extract unstable metabolites from vast metabolome data and identify factors that cause instability.Method
Plasma samples were obtained from five healthy volunteers, were stored under ten different conditions of time and temperature and were quantified using leading-edge metabolomics. Instability was evaluated by comparing quantitation values under each storage condition with those obtained after ?80 °C storage.Result
Stability profiling of the 992 metabolites showed time- and temperature-dependent increases in numbers of significantly changed metabolites. This large volume of data enabled comparisons of unstable metabolites with their related molecules and allowed identification of causative factors, including compound-specific enzymatic activity in plasma and chemical reactivity. Furthermore, these analyses indicated extreme instability of 1-docosahexaenoylglycerol, 1-arachidonoylglycerophosphate, cystine, cysteine and N6-methyladenosine.Conclusion
A large volume of data regarding storage stability was obtained. These data are a contribution to the discovery of biomarker candidates without misselection based on unreliable values and to the establishment of suitable handling procedures for targeted biomarker quantification.12.
Juan Manuel Chao de la Barca Nuan-Ting Huang Haihan Jiao Lydie Tessier Cédric Gadras Gilles Simard Riccardo Natoli Guillaume Tcherkez Pascal Reynier Krisztina Valter 《Metabolomics : Official journal of the Metabolomic Society》2017,13(3):22
Introduction
Light is the primary stimulus for vision, but may also cause damage to the retina. Pre-exposing the retina to sub-lethal amount of light (or preconditioning) improves chances for retinal cells to survive acute damaging light stress.Objectives
This study aims at exploring the changes in retinal metabolome after mild light stress and identifying mechanisms that may be involved in preconditioning.Methods
Retinas from 12 rats exposed to mild light stress (1000 lux?×?for 12 h) and 12 controls were collected one and seven days after light stress (LS). One retina was used for targeted metabolomics analysis using the Biocrates p180 kit while the fellow retina was used for histological and immunohistochemistry analysis.Results
Immunohistochemistry confirmed that in this experiment, a mild LS with retinal immune response and minimal photoreceptor loss occurred. Compared to controls, LS induced an increased concentration in phosphatidylcholines. The concentration in some amino acids and biogenic amines, particularly those related to the nitric oxide pathway (like asymmetric dimethylarginine (ADMA), arginine and citrulline) also increased 1 day after LS. 7 days after LS, the concentration in two sphingomyelins and phenylethylamine was found to be higher. We further found that in controls, retina metabolome was different between males and females: male retinas had an increased concentration in tyrosine, acetyl-ornithine, phosphatidylcholines and (acyl)-carnitines.Conclusions
Besides retinal sexual metabolic dimorphism, this study shows that preconditioning is mostly associated with re-organisation of lipid metabolism and changes in amino acid composition, likely reflecting the involvement of arginine-dependent NO signalling.13.
Introduction
Untargeted metabolomics is a powerful tool for biological discoveries. To analyze the complex raw data, significant advances in computational approaches have been made, yet it is not clear how exhaustive and reliable the data analysis results are.Objectives
Assessment of the quality of raw data processing in untargeted metabolomics.Methods
Five published untargeted metabolomics studies, were reanalyzed.Results
Omissions of at least 50 relevant compounds from the original results as well as examples of representative mistakes were reported for each study.Conclusion
Incomplete raw data processing shows unexplored potential of current and legacy data.14.
Pengcheng Zhou Ning Zhou Li Shao Jianzhou Li Sidi Liu Xiujuan Meng Juping Duan Xinrui Xiong Xun Huang Yuhua Chen Xuegong Fan Yixiang Zheng Shujuan Ma Chunhui Li Anhua Wu 《Metabolomics : Official journal of the Metabolomic Society》2018,14(8):102
Introduction
The fecal metabolome of Clostridium difficile (CD) infection is far from being understood, particularly its non-volatile organic compounds. The drawbacks of current tests used to diagnose CD infection hinder their application.Objective
The aims of this study were to find new characteristic fecal metabolites of CD infection and develop a metabolomics model for the diagnosis of CD infection.Methods
Ultra-performance liquid chromatography-mass spectrometry (UPLC–MS) was used to characterize the fecal metabolome of CD positive and negative diarrhea and healthy control stool samples.Results
Diarrhea and healthy control samples showed distinct clusters in the principal components analysis score plot, and CD positive group and CD negative group demonstrated clearer separation in a partial least squares discriminate analysis model. The relative abundance of sphingosine, chenodeoxycholic acid, phenylalanine, lysophosphatidylcholine (C16:0), and propylene glycol stearate was higher, and the relative abundance of fatty amide, glycochenodeoxycholic acid, tyrosine, linoleyl carnitine, and sphingomyelin was lower in CD positive diarrhea groups, than in the CD negative group. A linear discriminant analysis model based on capsiamide, dihydrosphingosine, and glycochenodeoxycholic acid was further constructed to identify CD infection in diarrhea. The leave-one-out cross-validation accuracy and area under receiver operating characteristic curve for the training set/external validation set were 90.00/78.57%, and 0.900/0.7917 respectively.Conclusions
Compared with other hospital-onset diarrhea, CD diarrhea has distinct fecal metabolome characteristics. Our UPLC–MS metabolomics model might be useful tool for diagnosing CD diarrhea.15.
Evan L. Pannkuk Evagelia C. Laiakis Tytus D. Mak Giuseppe Astarita Simon Authier Karen Wong Albert J. FornaceJr. 《Metabolomics : Official journal of the Metabolomic Society》2016,12(5):80
Introduction
Due to dangers associated with potential accidents from nuclear energy and terrorist threats, there is a need for high-throughput biodosimetry to rapidly assess individual doses of radiation exposure. Lipidomics and metabolomics are becoming common tools for determining global signatures after disease or other physical insult and provide a “snapshot” of potential cellular damage.Objectives
The current study assesses changes in the nonhuman primate (NHP) serum lipidome and metabolome 7 days following exposure to ionizing radiation (IR).Methods
Serum sample lipids and metabolites were extracted using a biphasic liquid–liquid extraction and analyzed by ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry. Global radiation signatures were acquired in data-independent mode.Results
Radiation exposure caused significant perturbations in lipid metabolism, affecting all major lipid species, including free fatty acids, glycerolipids, glycerophospholipids and esterified sterols. In particular, we observed a significant increase in the levels of polyunsaturated fatty acids (PUFA)-containing lipids in the serum of NHPs exposed to 10 Gy radiation, suggesting a primary role played by PUFAs in the physiological response to IR. Metabolomics profiling indicated an increase in the levels of amino acids, carnitine, and purine metabolites in the serum of NHPs exposed to 10 Gy radiation, suggesting perturbations to protein digestion/absorption, biological oxidations, and fatty acid β-oxidation.Conclusions
This is the first report to determine changes in the global NHP serum lipidome and metabolome following radiation exposure and provides information for developing metabolomic biomarker panels in human-based biodosimetry.16.
Julia B. Honneffer Jörg M. Steiner Jonathan A. Lidbury Jan S. Suchodolski 《Metabolomics : Official journal of the Metabolomic Society》2017,13(3):26
Introduction
The fecal microbiota are relevant to the health and disease of many species. The importance of the fecal metabolome has more recently been appreciated, but our knowledge of the microbiota and metabolome at other sites along the gastrointestinal tract remains deficient.Objective
To analyze the gastrointestinal microbiota and metabolome of healthy domestic dogs at four anatomical sites.Methods
Samples of the duodenal, ileal, colonic, and rectal contents were collected from six adult dogs after humane euthanasia for an unrelated study. The microbiota were characterized using Illumina sequencing of 16S rRNA genes. The metabolome was characterized by mass spectrometry-based methods.Results
Prevalent phyla throughout the samples were Proteobacteria, Firmicutes, Fusobacteria, and Bacteroidetes, consistent with previous findings in dogs and other species. A total of 530 unique metabolites were detected; 199 of these were identified as previously named compounds, but 141 of them had at least one significantly different site-pair comparison. Noteworthy examples include relative concentrations of amino acids, which decreased from the small to large intestine; pyruvate, which peaked in the ileum; and several phenol-containing carboxylic acid compounds that increased in the large intestine.Conclusion
The microbiota and metabolome vary significantly at different sites along the canine gastrointestinal tract.17.
Chenglin Zhu Vanessa Faillace Fulvio Laus Marilena Bazzano Luca Laghi 《Metabolomics : Official journal of the Metabolomic Society》2018,14(8):106
Background
Metabolomics has been recognized as a powerful approach for disease screening. In order to highlight potential health issues in subjects, a key factor is the possibility to compare quantitatively the metabolome of their biofluids with reference values from healthy individuals. Such efforts towards the systematic characterization of the metabolome of biofluids in perfect health conditions, far from concluded for humans, have barely begun on horses.Objectives
The present work attempts, for the first time, to give reference quantitative values for the molecules mostly represented in the urine metabolome of horses at rest and under light training, as observable by 1H-NMR.Methods
The metabolome of ten trotter horses, four male and six female, ranging from 3 to 8 years of age, has been observed by 1H-NMR spectroscopy before and after three training sessions.Results
We could characterize and quantify 54 molecules in trotter horse urine, originated from diet, protein digestion, energy generation or gut-microbial co-metabolism.Conclusion
We were able to describe how gender, age and exercise affected their concentration, by means of a two steps protocol based on univariate and robust principal component analysis.18.
Sonia Liggi Christine Hinz Zoe Hall Maria Laura Santoru Simone Poddighe John Fjeldsted Luigi Atzori Julian L. Griffin 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):52
Introduction
Data processing is one of the biggest problems in metabolomics, given the high number of samples analyzed and the need of multiple software packages for each step of the processing workflow.Objectives
Merge in the same platform the steps required for metabolomics data processing.Methods
KniMet is a workflow for the processing of mass spectrometry-metabolomics data based on the KNIME Analytics platform.Results
The approach includes key steps to follow in metabolomics data processing: feature filtering, missing value imputation, normalization, batch correction and annotation.Conclusion
KniMet provides the user with a local, modular and customizable workflow for the processing of both GC–MS and LC–MS open profiling data.19.
Jamie V. de Seymour Stephanie Tu Xiaoling He Hua Zhang Ting-Li Han Philip N. Baker Karolina Sulek 《Metabolomics : Official journal of the Metabolomic Society》2018,14(6):79
Introduction
Intrahepatic cholestasis of pregnancy (ICP) is a common maternal liver disease; development can result in devastating consequences, including sudden fetal death and stillbirth. Currently, recognition of ICP only occurs following onset of clinical symptoms.Objective
Investigate the maternal hair metabolome for predictive biomarkers of ICP.Methods
The maternal hair metabolome (gestational age of sampling between 17 and 41 weeks) of 38 Chinese women with ICP and 46 pregnant controls was analysed using gas chromatography–mass spectrometry.Results
Of 105 metabolites detected in hair, none were significantly associated with ICP.Conclusion
Hair samples represent accumulative environmental exposure over time. Samples collected at the onset of ICP did not reveal any metabolic shifts, suggesting rapid development of the disease.20.
Alessia Trimigno Bekzod Khakimov Josue Leonardo Castro Mejia Mette Skau Mikkelsen Mette Kristensen Birthe Møller Jespersen Søren Balling Engelsen 《Metabolomics : Official journal of the Metabolomic Society》2017,13(10):108