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1.
Gontse P. Moutloatse Madeleine J. Bunders Mari van Reenen Shayne Mason Taco W. Kuijpers Udo F. H. Engelke Ron A. Wevers Carools J. Reinecke 《Metabolomics : Official journal of the Metabolomic Society》2016,12(11):175
Introduction
Antiretroviral therapy (ART) for HIV-infected pregnant women is highly effective in preventing mother-to-child transmission (PMTCT) of the virus, but deleterious metabolic and mitochondrial observations in infants born to HIV-infected women treated with ART during pregnancy are periodically reported.Objectives
This study addresses the concern of HIV-ART-induced metabolic perturbations through a metabolomics study of cord blood collected during transitional neonatal hypoglycaemia following birth from newborns either exposed or unexposed to fetal HIV-ART.Methods
Proton magnetic resonance spectra from cord blood of 11 in utero HIV-ART-exposed and 14 unexposed newborns, as well as serum from 8 control infants, generated 114 spectral bins which were used to identify significant metabolites by means of univariate and multivariate statistical analyses.Results
The metabolite profiles differed significantly between that from the unexposed newborns and that from infants—interpreted to characterize the state of transitional neonatal hypoglycaemia (low glucose and high lactic acid and ketone bodies). Quantitative analysis of potential ATP generation showed no meaningful difference in the global metabolite profiles of HIV-ART-exposed and unexposed neonates, but Volcano plot analysis, affirmed by odds ratios, indicated that exposure to HIV-ART affected the plasma 3-hydroxybutyric acid and hypoxanthine concentrations.Conclusions
The metabolite profile for transitional neonatal hypoglycaemia indicated that HIV-ART did not compromise the exposed neonates to the energy stress of allostasis experienced at birth. Increased hypoxanthine and 3-hydroxybutyric acid indicates metabolic stress at birth in some of the newborns exposed to HIV-ART and raises a concern about unrecognized prolonged allostasis with potential neurological consequences for these infants.2.
John M. Wentworth Naiara G. Bediaga Megan A. S. Penno Esther Bandala-Sanchez Komal N. Kanojia Konstantinos A. Kouremenos Jennifer J. Couper Leonard C. Harrison ENDIA Study Group 《Metabolomics : Official journal of the Metabolomic Society》2018,14(10):130
Background
Cord blood lipids are potential disease biomarkers. We aimed to determine if their concentrations were affected by delayed blood processing.Method
Refrigerated cord blood from six healthy newborns was centrifuged every 12 h for 4 days. Plasma lipids were analysed by liquid chromatography/mass spectroscopy.Results
Of 262 lipids identified, only eight varied significantly over time. These comprised three dihexosylceramides, two phosphatidylserines and two phosphatidylethanolamines whose relative concentrations increased and one sphingomyelin that decreased.Conclusion
Delay in separation of plasma from refrigerated cord blood has minimal effect overall on the plasma lipidome.3.
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.4.
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.5.
Izabella Surowiec Erik Johansson Frida Torell Helena Idborg Iva Gunnarsson Elisabet Svenungsson Per-Johan Jakobsson Johan Trygg 《Metabolomics : Official journal of the Metabolomic Society》2017,13(10):114
Introduction
Availability of large cohorts of samples with related metadata provides scientists with extensive material for studies. At the same time, recent development of modern high-throughput ‘omics’ technologies, including metabolomics, has resulted in the potential for analysis of large sample sizes. Representative subset selection becomes critical for selection of samples from bigger cohorts and their division into analytical batches. This especially holds true when relative quantification of compound levels is used.Objectives
We present a multivariate strategy for representative sample selection and integration of results from multi-batch experiments in metabolomics.Methods
Multivariate characterization was applied for design of experiment based sample selection and subsequent subdivision into four analytical batches which were analyzed on different days by metabolomics profiling using gas-chromatography time-of-flight mass spectrometry (GC–TOF–MS). For each batch OPLS-DA® was used and its p(corr) vectors were averaged to obtain combined metabolic profile. Jackknifed standard errors were used to calculate confidence intervals for each metabolite in the average p(corr) profile.Results
A combined, representative metabolic profile describing differences between systemic lupus erythematosus (SLE) patients and controls was obtained and used for elucidation of metabolic pathways that could be disturbed in SLE.Conclusion
Design of experiment based representative sample selection ensured diversity and minimized bias that could be introduced at this step. Combined metabolic profile enabled unified analysis and interpretation.6.
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.7.
Saleh Alseekh Luisa Bermudez Luis Alejandro de Haro Alisdair R. Fernie Fernando Carrari 《Metabolomics : Official journal of the Metabolomic Society》2018,14(11):148
Background
Until recently, plant metabolomics have provided a deep understanding on the metabolic regulation in individual plants as experimental units. The application of these techniques to agricultural systems subjected to more complex interactions is a step towards the implementation of translational metabolomics in crop breeding.Aim of Review
We present here a review paper discussing advances in the knowledge reached in the last years derived from the application of metabolomic techniques that evolved from biomarker discovery to improve crop yield and quality.Key Scientific Concepts of Review
Translational metabolomics applied to crop breeding programs.8.
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.9.
Alexis Catala Rachel Culp-Hill Travis Nemkov Angelo D’Alessandro 《Metabolomics : Official journal of the Metabolomic Society》2018,14(7):100
Introduction
Mass spectrometry and computational biology have advanced significantly in the past ten years, bringing the field of metabolomics a step closer to personalized medicine applications. Despite these analytical advancements, collection of blood samples for routine clinical analysis is still performed through traditional blood draws.Objective
TAP capillary blood collection has been recently introduced for the rapid, painless draw of small volumes of blood (~?100 μL), though little is known about the comparability of metabolic phenotypes of blood drawn via traditional venipuncture and TAP devices.Methods
UHPLC-MS-targeted metabolomics analyses were performed on blood drawn traditionally or through TAP devices from 5 healthy volunteers. Absolute quantitation of 45 clinically-relevant metabolites was calculated against stable heavy isotope-labeled internal standards.Results
Ranges for 39 out of 45 quantified metabolites overlapped between drawing methods. Pyruvate and succinate were over threefold higher in the TAP samples than in traditional blood draws. No significant changes were observed for other carboxylates, glucose or lactate. TAP samples were characterized by increases in reduced glutathione and decreases in urate and cystine, markers of oxidation of purines and cysteine—overall suggesting decreased oxidation during draws. The absolute levels of bile acids and acyl-carnitines, as well as almost all amino acids, perfectly correlated among groups (Spearman r?≥?0.95).Conclusion
Though further more extensive studies will be mandatory, this pilot suggests that TAP-derived blood may be a logistically-friendly source of blood for large scale metabolomics studies—especially those addressing amino acids, glycemia and lactatemia as well as bile acids, acyl-carnitine levels.10.
Anna Lindahl Rainer Heuchel Jenny Forshed Janne Lehtiö Matthias Löhr Anders Nordström 《Metabolomics : Official journal of the Metabolomic Society》2017,13(5):61
Introduction
Pancreatic ductal adenocarcinoma (PDAC) is the fifth most common cause of cancer-related death in Europe with a 5-year survival rate of <5%. Chronic pancreatitis (CP) is a risk factor for PDAC development, but in the majority of cases malignancy is discovered too late for curative treatment. There is at present no reliable diagnostic marker for PDAC available.Objectives
The aim of the study was to identify single blood-based metabolites or a panel of metabolites discriminating PDAC and CP using liquid chromatography-mass spectrometry (LC-MS).Methods
A discovery cohort comprising PDAC (n?=?44) and CP (n?=?23) samples was analyzed by LC-MS followed by univariate (Student’s t test) and multivariate (orthogonal partial least squares-discriminant analysis (OPLS-DA)) statistics. Discriminative metabolite features were subject to raw data examination and identification to ensure high feature quality. Their discriminatory power was then confirmed in an independent validation cohort including PDAC (n?=?20) and CP (n?=?31) samples.Results
Glycocholic acid, N-palmitoyl glutamic acid and hexanoylcarnitine were identified as single markers discriminating PDAC and CP by univariate analysis. OPLS-DA resulted in a panel of five metabolites including the aforementioned three metabolites as well as phenylacetylglutamine (PAGN) and chenodeoxyglycocholate.Conclusion
Using LC-MS-based metabolomics we identified three single metabolites and a five-metabolite panel discriminating PDAC and CP in two independent cohorts. Although further study is needed in larger cohorts, the metabolites identified are potentially of use in PDAC diagnostics.11.
D. Jacob C. Deborde M. Lefebvre M. Maucourt A. Moing 《Metabolomics : Official journal of the Metabolomic Society》2017,13(4):36
Introduction
Concerning NMR-based metabolomics, 1D spectra processing often requires an expert eye for disentangling the intertwined peaks.Objectives
The objective of NMRProcFlow is to assist the expert in this task in the best way without requirement of programming skills.Methods
NMRProcFlow was developed to be a graphical and interactive 1D NMR (1H & 13C) spectra processing tool.Results
NMRProcFlow (http://nmrprocflow.org), dedicated to metabolic fingerprinting and targeted metabolomics, covers all spectra processing steps including baseline correction, chemical shift calibration and alignment.Conclusion
Biologists and NMR spectroscopists can easily interact and develop synergies by visualizing the NMR spectra along with their corresponding experimental-factor levels, thus setting a bridge between experimental design and subsequent statistical analyses.12.
Hye Jin Yoo Minjoo Kim Minkyung Kim Minsik Kang Keum Ji Jung Se-mi Hwang Sun Ha Jee Jong Ho Lee 《Metabolomics : Official journal of the Metabolomic Society》2018,14(6):85
Introduction
Since blood is in contact with all tissues in the body and is considered to dynamically reflect the body’s pathophysiological status, serum metabolomics changes are important and have diagnostic value in early cancer detection.Objectives
In this prospective study, we investigated the application of metabolomics to differentiate subjects with incident breast cancer (BC) from subjects who remained free of cancer during a mean follow-up period of 7 years with the aim of identifying valuable biomarkers for BC.Methods
Baseline serum samples from 84 female subjects with incident BC (BC group) and 88 cancer-free female subjects (control group) were used. Metabolic alterations associated with BC were investigated via metabolomics analysis of the baseline serum samples using ultra-performance liquid chromatography-linear-trap quadrupole-Orbitrap mass spectrometry.Results
A total of 57 metabolites were identified through the metabolic analysis. Among them, 20 metabolite levels were significantly higher and 22 metabolite levels were significantly lower in the BC group than in the control group at baseline. Ten metabolic pathways, including amino acid metabolism, arachidonic acid (AA) metabolism, fatty acid metabolism, linoleic acid metabolism, and retinol metabolism, showed significant differences between the BC group and the control group. Logistic regression revealed that the incidence of BC was affected by leucine, AA, prostaglandin (PG)J2, PGE2, and γ-linolenic acid (GLA).Conclusions
This prospective study showed the clinical relevance of dysregulation of various metabolisms on the incidence of BC. Additionally, leucine, AA, PGJ2, PGE2, and GLA were identified as independent variables affecting the incidence of BC.13.
Leonie Venter Du Toit Loots Lodewyk Japie Mienie Peet J. Jansen van Rensburg Shayne Mason Andre Vosloo Jeremie Zander Lindeque 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):49
Introduction
Oxygen is essential for metabolic processes and in the absence thereof alternative metabolic pathways are required for energy production, as seen in marine invertebrates like abalone. Even though hypoxia has been responsible for significant losses to the aquaculture industry, the overall metabolic adaptations of abalone in response to environmental hypoxia are as yet, not fully elucidated.Objective
To use a multiplatform metabolomics approach to characterize the metabolic changes associated with energy production in abalone (Haliotis midae) when exposed to environmental hypoxia.Methods
Metabolomics analysis of abalone adductor and foot muscle, left and right gill, hemolymph, and epipodial tissue samples were conducted using a multiplatform approach, which included untargeted NMR spectroscopy, untargeted and targeted LC–MS spectrometry, and untargeted and semi-targeted GC-MS spectrometric analyses.Results
Increased levels of anaerobic end-products specific to marine animals were found which include alanopine, strombine, tauropine and octopine. These were accompanied by elevated lactate, succinate and arginine, of which the latter is a product of phosphoarginine breakdown in abalone. Primarily amino acid metabolism was affected, with carbohydrate and lipid metabolism assisting with anaerobic energy production to a lesser extent. Different tissues showed varied metabolic responses to hypoxia, with the largest metabolic changes in the adductor muscle.Conclusions
From this investigation, it becomes evident that abalone have well-developed (yet understudied) metabolic mechanisms for surviving hypoxic periods. Furthermore, metabolomics serves as a powerful tool for investigating the altered metabolic processes in abalone.14.
Lia Bally Cédric Bovet Christos T. Nakas Thomas Zueger Jean-Christophe Prost Jean-Marc Nuoffer Alexander B. Leichtle Georg Martin Fiedler Christoph Stettler 《Metabolomics : Official journal of the Metabolomic Society》2017,13(7):78
Introduction
Exercise-associated metabolism in type 1 diabetes (T1D) remains under-studied due to the complex interplay between exogenous insulin, counter-regulatory hormones and insulin-sensitivity.Objective
To identify the metabolic differences induced by two exercise modalities in T1D using ultra high-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC–HRMS) based metabolomics.Methods
Twelve T1D adults performed intermittent high-intensity (IHE) and continuous-moderate-intensity (CONT) exercise. Serum samples were analysed by UHPLC–HRMS.Results
Metabolic profiling of IHE and CONT highlighted exercise-induced changes in purine and acylcarnitine metabolism.Conclusion
IHE may increase beta-oxidation through higher ATP-turnover. UHPLC–HRMS based metabolomics as a data-driven approach without an a priori hypothesis may help uncover distinctive metabolic effects during exercise in T1D.Clinical trial registration number is www.clinicaltrials.gov: NCT02068638.15.
Jialin Wang Tao Zhang Xiaotao Shen Jia Liu Deli Zhao Yawen Sun Lu Wang Yingjun Liu Xiaoyun Gong Yanxun Liu Zheng-Jiang Zhu Fuzhong Xue 《Metabolomics : Official journal of the Metabolomic Society》2016,12(7):116
Introduction
Previous metabolomics studies have revealed perturbed metabolic signatures in esophageal squamous cell carcinoma (ESCC) patients, however, most of these studies included mainly late-staged ESCC patients due to the difficulties of collecting the early-staged samples from asymptotic ESCC subjects.Objectives
This study aims to explore the early-staged ESCC metabolic signatures and potential of serum metabolomics to diagnose ESCC at early stages.Methods
Serum samples of 97 ESCC patients (stage 0, 39 cases; stage I, 17 cases; stage II, 11 cases, stage III, 30 cases) and 105 healthy controls (HC) were enrolled and randomly separated into training data (77 ESCCs, 84 HCs) and validation data (20 ESCCs, 21 HCs). Untargeted metabolomics was performed to identify ESCC-related metabolic signatures.Results
The global metabolomics profiles could clearly distinguish ESCC from HC in training data. 16 ascertained metabolites were found to be disturbed in the metabolic pathways characterized by dysregulated fatty acid biosynthesis, glycerophospholipid metabolism, choline metabolism in cancer and linoleic acid metabolism. The AUC value in validation data was 0.895, with sensitivity 85.0 % and specificity 90.5 %. Good diagnostic performances were also achieved for early stage ESCC, with the values of area under the curve (AUC) 0.881 for the ESCC patients in both stage 0 and I–II. In addition, six metabolites were found to discriminate ESCC stages. Among them, three biomarkers, dodecanoic acid, LysoPA(18:1), and LysoPC(14:0), exhibited clear trend for ESCC progression.Conclusion
These findings suggest serum metabolomics, performed in a minimally noninvasive and convenient manner, may possess great potential for early diagnosis of ESCC patients.16.
Anita H. Lewin Peter Silinski James Hayes Amanda Gilbert S. Wayne Mascarella Herbert H. Seltzman 《Metabolomics : Official journal of the Metabolomic Society》2017,13(10):117
Introduction
Metabolomics analysis depends on the identification and validation of specific metabolites. This task is significantly hampered by the absence of well-characterized reference standards. The one-carbon carrier 10-formyltetrahydrofolate acts as a donor of formyl groups in anabolism, where it is a substrate in formyltransferase reactions in purine biosynthesis. It has been reported as an unstable substance and is currently unavailable as a reference standard for metabolomics analysis.Objectives
The current study was undertaken to provide the metabolomics community thoroughly characterized 10-formyltetrahydrofolate along with analytical methodology and guidelines for its storage and handling.Methods
Anaerobic base treatment of 5,10-methenyltetrahydrofolate chloride in the presence of antioxidant was utilized to prepare 10-formyltetrahydrofolate.Results
Pure 10-formyltetrahydrofolate has been prepared and physicochemically characterized. Conditions toward maintaining the stability of a solution of the dipotassium salt of 10-formyltetrahydrofolate have been determined.Conclusion
This study describes the facile preparation of pure (>90%) 10-formyltetrahydrofolate, its qualitative physicochemical characterization, as well as conditions to enable its use as a reference standard in physiologic samples.17.
18.
Dina Kao Kathleen P. Ismond Victor Tso Braden Millan Naomi Hotte Richard N. Fedorak 《Metabolomics : Official journal of the Metabolomic Society》2016,12(8):135
Introduction
Recurrent Clostridium difficile infection (CDI) is associated with intestinal dysbiosis. Currently, there is no diagnostic test to predict at-risk patients for CDI recurrences. Urine metabolomics may have prognostic value, but have not been characterized in this patient population.Objective
The aim of this pilot study was to profile the urine metabolomics of patients with various frequencies of CDI.Methods
Spot urine samples were prospectively collected from 31 adults who at various stages of recurrent CDI (1 to >5 episodes). Patients were age- and sex-matched in a 1:1 ratio with healthy controls. Urine metabolomics was performed and spectra were assessed using Chenomx NMRSuite v7 and analyzed using multivariate statistics with MetaboAnalyst 3.0. Stool metagenomic analyses were performed in six patients with >3 episodes of CDI and compared to 7 healthy controls, which were correlated with urine metabolomics.Results
Using 53 metabolites, a two-component, partial least squares—discriminant analysis (PLS-DA) was built that clearly discriminated between healthy controls and CDI patients. The anticipated gender-based difference was not found within the CDI patient group. However, separations between (1) healthy control and CDI patients, as well as (2) patients with different episodes of CDI were possible and the permutations found were significant. Furthermore, choline was found to be the single most important urine metabolite separating healthy controls from CDI patients, and the microbiota from recurrent CDI patients was found to have decreased abundance of choline metabolizing bacteria.Conclusions
Using small groups in a preliminary study, we have demonstrated that urine metabolomics has the potential to distinguish between healthy controls and patients with CDI. Furthermore, it could discriminate between patients experiencing different frequencies of recurrent CDI. If validated in larger cohorts, urine metabolomics has potential at identifying patients who are at risk for recurrent CDI. The significance of choline-deficient microbiota in CDI patients should be further examined.19.
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.20.
Mu Wang Ouyan Rang Fang Liu Wei Xia Yuanyuan Li Yu Zhang Songfeng Lu Shunqing Xu 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):45