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1.
Markus Rotter Stefan Brandmaier Cornelia Prehn Jonathan Adam Sylvia Rabstein Katarzyna Gawrych Thomas Brüning Thomas Illig Heiko Lickert Jerzy Adamski Rui Wang-Sattler 《Metabolomics : Official journal of the Metabolomic Society》2017,13(1):4
Introduction
Few studies have investigated the influence of storage conditions on urine samples and none of them used targeted mass spectrometry (MS).Objectives
We investigated the stability of metabolite profiles in urine samples under different storage conditions using targeted metabolomics.Methods
Pooled, fasting urine samples were collected and stored at ?80 °C (biobank standard), ?20 °C (freezer), 4 °C (fridge), ~9 °C (cool pack), and ~20 °C (room temperature) for 0, 2, 8 and 24 h. Metabolite concentrations were quantified with MS using the AbsoluteIDQ? p150 assay. We used the Welch-Satterthwaite-test to compare the concentrations of each metabolite. Mixed effects linear regression was used to assess the influence of the interaction of storage time and temperature.Results
The concentrations of 63 investigated metabolites were stable at ?20 and 4 °C for up to 24 h when compared to samples immediately stored at ?80 °C. When stored at ~9 °C for 24 h, few amino acids (Arg, Val and Leu/Ile) significantly decreased by 40% in concentration (P < 7.9E?04); for an additional three metabolites (Ser, Met, Hexose H1) when stored at ~20 °C reduced up to 60% in concentrations. The concentrations of four more metabolites (Glu, Phe, Pro, and Thr) were found to be significantly influenced when considering the interaction between exposure time and temperature.Conclusion
Our findings indicate that 78% of quantified metabolites were stable for all examined storage conditions. Particularly, some amino acid concentrations were sensitive to changes after prolonged storage at room temperature. Shipping or storing urine samples on cool packs or at room temperature for more than 8 h and multiple numbers of freeze and thaw cycles should be avoided.2.
Caroline Muschet Gabriele Möller Cornelia Prehn Martin Hrabě de Angelis Jerzy Adamski Janina Tokarz 《Metabolomics : Official journal of the Metabolomic Society》2016,12(10):151
Introduction
Although cultured cells are nowadays regularly analyzed by metabolomics technologies, some issues in study setup and data processing are still not resolved to complete satisfaction: a suitable harvesting method for adherent cells, a fast and robust method for data normalization, and the proof that metabolite levels can be normalized to cell number.Objectives
We intended to develop a fast method for normalization of cell culture metabolomics samples, to analyze how metabolite levels correlate with cell numbers, and to elucidate the impact of the kind of harvesting on measured metabolite profiles.Methods
We cultured four different human cell lines and used them to develop a fluorescence-based method for DNA quantification. Further, we assessed the correlation between metabolite levels and cell numbers and focused on the impact of the harvesting method (scraping or trypsinization) on the metabolite profile.Results
We developed a fast, sensitive and robust fluorescence-based method for DNA quantification showing excellent linear correlation between fluorescence intensities and cell numbers for all cell lines. Furthermore, 82–97 % of the measured intracellular metabolites displayed linear correlation between metabolite concentrations and cell numbers. We observed differences in amino acids, biogenic amines, and lipid levels between trypsinized and scraped cells.Conclusion
We offer a fast, robust, and validated normalization method for cell culture metabolomics samples and demonstrate the eligibility of the normalization of metabolomics data to the cell number. We show a cell line and metabolite-specific impact of the harvesting method on metabolite concentrations.3.
Tilman Kühn Disorn Sookthai Ulrike Rolle-Kampczyk Wolfgang Otto Martin von Bergen Rudolf Kaaks Theron Johnson 《Metabolomics : Official journal of the Metabolomic Society》2016,12(12):184
Introduction
Plasma metabolites measured by metabolomics techniques have been shown to be associated with chronic disease risk in epidemiological studies. However, in most prospective studies metabolomic profiles can only be obtained at a single time point and data on intra-individual variation in metabolite levels over time are sparse.Objectives
Here, we evaluated the intra-individual variation in the concentrations of 177 metabolites over time using repeat blood samples of 104 adults (50% female).Methods
Blood samples were obtained at a baseline visit between 1994 and 1998 and during two further examinations 14 and 15 years later. Plasma metabolite levels were quantified by tandem mass spectrometry with the MetaDisIDQ? p180 Kit. Intra-individual variation was assessed by Spearman’s correlation coefficients (ρ).Results
Mid-term correlations over 1 year were good (ρ ≥ 0.7) for 5.1% and reasonable (ρ ≥ 0.4 < 0.7) for 61.0% of the metabolites, while long-term correlations over 15 years were good for 2.8% and reasonable for 27.1%. The strongest mid-term correlations between metabolite concentrations were observed for the acylcarnitine C3–OH (0.72) and metabolites from the amino acid/biogenic amine groups, i.e. creatinine (0.83), proline (0.79), lysine (0.77), isoleucine (0.76), and ornithine (0.74). C3–OH (0.78) as well as several amino acids/biogenic amines, i.e. ornithine (0.76), sarcosine (0.76), lysine (0.75), spermine (0.73), and glutamine (0.69) showed the strongest long-term correlations.Conclusions
The biological reproducibility of plasma concentrations of a majority of metabolites occurs reasonable over 1 year. In contrast, concentrations of many metabolites seem to be affected by substantial intra-individual variation over 15 years.4.
Masahito Uji Yukihiro Yokoyama Katsuya Ohbuchi Kazuaki Tsuchiya Chiharu Sadakane Chika Shimobori Masahiro Yamamoto Masato Nagino 《Metabolomics : Official journal of the Metabolomic Society》2017,13(12):155
Introduction
In patients with obstructive jaundice, biliary drainage sometimes fails to result in improvement. A pharmaceutical-grade choleretic herbal medicine, Inchinkoto (ICKT), has been proposed to exert auxiliary effects on biliary drainage; however, its effects are variable among patients.Objectives
The aim of this study is to explore serum biomarkers that are associated with pharmaceutical efficacy of ICKT.Methods
Obstructive jaundice patients who underwent external biliary decompression were enrolled (n?=?37). ICKT was given orally 3 times a day at daily dose of 7.5 g. Serum and bile samples were collected before, 3 h after, and 24 h after ICKT administration. The concentrations of total bilirubin, direct bilirubin, and total bile acid in bile specimens were measured. Metabolites in serum samples were comprehensively profiled using LC–MS/MS and GC–MS/MS. Pharmacokinetic analysis of major ICKT components was also performed.Results
ICKT administration significantly decreased serum ALT and increased bile volume after 24 h. The serum concentrations of ICKT components were not well correlated with the efficacy of ICKT. However, the ratio of 2-hydroxyisobutyric acid to arachidonic acid and the ratio of glutaric acid to niacinamide, exhibited good performance as biomarkers for the efficacy of ICKT on bile flow and ALT, respectively. Additionally, comprehensive correlation analysis revealed that serum glucuronic acid was highly correlated with serum total bilirubin, suggesting that this metabolite may be deeply involved in the pathogenesis of jaundice.Conclusions
The present study indicates that ICKT is efficacious and provides candidates for predicting ICKT efficacy. Further validation studies are warranted.5.
Yuji Sawada Hirokazu Tsukaya Yimeng Li Muneo Sato Kensuke Kawade 《Metabolomics : Official journal of the Metabolomic Society》2017,13(6):75
Introduction
In plant metabolomics, metabolite contents are often normalized by sample weight. However, accurate weighing of very small samples, such as individual Arabidopsis thaliana seeds (approximately 20 µg), is difficult, which may lead to irreproducible results.Objectives
We aimed to establish alternative normalization methods for seed-grain-based comparative metabolomics of A. thaliana.Methods
Arabidopsis thaliana seeds were assumed to have a prolate spheroid shape. Using a microscope image of each seed, the lengths of major and minor axes were measured by fitting a projected 2-dimensional shape of each seed as an ellipse. Metabolic profiles of individual diploid or tetraploid A. thaliana seeds were measured by our highly sensitive protocol (“widely targeted metabolomics”) that uses liquid chromatography coupled with tandem quadrupole mass spectrometry. Mass spectrometric analysis of 1 µL of solution extract identified more than 100 metabolites. The data were normalized by various seed-size measures, including seed volume (single-grain-based analysis). For comparison, metabolites were extracted from 4 mg of diploid and tetraploid A. thaliana seeds and their metabolic profiles were analyzed by normalization of weight (weight-based analysis).Results
A small number of metabolites showed statistically significant differences in the single-grain-based analysis compared to weight-based analysis. A total of 17 metabolites showed statistically different accumulation between ploidy types with similar fold changes in both analyses.Conclusion
Seed-size measures obtained by microscopic imaging were useful for data normalization. Single-grain-based analysis enables evaluation of metabolism of each seed and elucidates the metabolic profiles of precious bioresources by using small amounts of samples.6.
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.7.
Amanda J. Lloyd Manfred Beckmann Kathleen Tailliart Wendy Y. Brown John Draper David Allaway 《Metabolomics : Official journal of the Metabolomic Society》2016,12(4):72
Introduction
Dog breeds are a consequence of artificial selection for specific attributes. These closed genetic populations have metabolic and physiological characteristics that may be revealed by metabolomic analysis.Objectives
To identify and characterise the drivers of metabolic differences in the fasted plasma metabolome and then determine metabolites differentiating breeds.Methods
Fasted plasma samples were collected from dogs maintained under two environmental conditions (controlled and client-owned at home). The former (n = 33) consisted of three breeds (Labrador Retriever, Cocker Spaniel and Miniature Schnauzer) fed a single diet batch, the latter (n = 96), client-owned dogs consisted of 9 breeds (Beagle, Chihuahua, Cocker Spaniel, Dachshund, Golden Retriever, Greyhound, German Shepherd, Labrador Retriever and Maltese) consuming various diets under differing feeding regimens. Triplicate samples were taken from Beagle (n = 10) and Labrador Retriever (n = 9) over 3 months. Non-targeted metabolite fingerprinting was performed using flow infusion electrospray-ionization mass spectrometry which was coupled with multivariate data analysis. Metadata factors including age, gender, sexual status, weight, diet and breed were investigated.Results
Breed differences were identified in the plasma metabolome of dogs housed in a controlled environment. Triplicate samples from two breeds identified intra-individual variability, yet breed separation was still observed. The main drivers of variance in dogs maintained in the home environment were associated with breed and gender. Furthermore, metabolite signals were identified that discriminated between Labrador Retriever and Cocker Spaniels in both environments.Conclusion
Metabolite fingerprinting of plasma samples can be used to investigate breed differences in client-owned dogs, despite added variance of diet, sexual status and environment.8.
Basetti Madhu Greg L. Shaw Anne Y. Warren David E. Neal John R. Griffiths 《Metabolomics : Official journal of the Metabolomic Society》2016,12(7):120
Introduction
The androgen receptor (AR) is the master regulator of prostate cancer cell metabolism. Degarelix is a novel gonadotrophin-releasing hormone blocker, used to decrease serum androgen levels in order to treat advanced human prostate cancer. Little is known of the rapid metabolic response of the human prostate cancer tissue samples to the decreased androgen levels.Objectives
To investigate the metabolic responses in benign and cancerous tissue samples from patients after treatment with Degarelix by using HRMAS 1H NMR spectroscopy.Methods
Using non-destructive HR-MAS 1H NMR spectroscopy we analysed the metabolic changes induced by decreased AR signalling in human prostate cancer tissue samples. Absolute concentrations of the metabolites alanine, lactate, glutamine, glutamate, citrate, choline compounds [t-choline = choline + phosphocholine (PC) + glycerophosphocholine (GPC)], creatine compounds [t-creatine = creatine (Cr) + phosphocreatine (PCr)], taurine, myo-inositol and polyamines were measured in benign prostate tissue samples (n = 10), in prostate cancer specimens from untreated patients (n = 7) and prostate cancer specimens from patients treated with Degarelix (n = 6).Results
Lactate, alanine and t-choline concentrations were significantly elevated in high-grade prostate cancer samples when compared to benign samples in untreated patients. Decreased androgen levels resulted in significant decreases of lactate and t-choline concentrations in human prostate cancer biopsies.Conclusions
The reduced concentrations of lactate and t-choline metabolites due to Degarelix could in principle be monitored by in vivo 1H MRS, which suggests that it would be possible to monitor the effects of physical or chemical castration in patients by that non-invasive method.9.
Antonio Murgia Christine Hinz Sonia Liggi Jùlìa Denes Zoe Hall James West Maria Laura Santoru Cristina Piras Cristina Manis Paolo Usai Luigi Atzori Julian L. Griffin Pierluigi Caboni 《Metabolomics : Official journal of the Metabolomic Society》2018,14(10):140
Background
Inflammatory bowel disease is a group of pathologies characterised by chronic inflammation of the intestine and an unclear aetiology. Its main manifestations are Crohn’s disease and ulcerative colitis. Currently, biopsies are the most used diagnostic tests for these diseases and metabolomics could represent a less invasive approach to identify biomarkers of disease presence and progression.Objectives
The lipid and the polar metabolite profile of plasma samples of patients affected by inflammatory bowel disease have been compared with healthy individuals with the aim to find their metabolomic differences. Also, a selected sub-set of samples was analysed following solid phase extraction to further characterise differences between pathological samples.Methods
A total of 200 plasma samples were analysed using drift tube ion mobility coupled with time of flight mass spectrometry and liquid chromatography for the lipid metabolite profile analysis, while liquid chromatography coupled with triple quadrupole mass spectrometry was used for the polar metabolite profile analysis.Results
Variations in the lipid profile between inflammatory bowel disease and healthy individuals were highlighted. Phosphatidylcholines, lyso-phosphatidylcholines and fatty acids were significantly changed among pathological samples suggesting changes in phospholipase A2 and arachidonic acid metabolic pathways. Variations in the levels of cholesteryl esters and glycerophospholipids were also found. Furthermore, a decrease in amino acids levels suggests mucosal damage in inflammatory bowel disease.Conclusions
Given good statistical results and predictive power of the model produced in our study, metabolomics can be considered as a valid tool to investigate inflammatory bowel disease.10.
Marta Michalczuk Beata Urban Tadeusz Porowski Anna Wasilewska Alina Bakunowicz-Łazarczyk 《Metabolomics : Official journal of the Metabolomic Society》2018,14(6):82
Introduction
Citrate is an old metabolite which is best known for the role in the Krebs cycle. Citrate is widely used in many branches of medicine. In ophthalmology citrate is considered as a therapeutic agent and an useful diagnostic tool—biomarker.Objectives
To summarize the published literature on citrate usage in the leading causes of blindness and highlight the new possibilities for this old metabolite.Methods
We conducted a systematic search of the scientific literature about citrate usage in ophthalmology up to January 2018. The reference lists of identified articles were searched for providing in-depth information.Results
This systematic review included 30 articles. The role of citrate in the leading causes of blindness is presented.Conclusions
Citrate might help inhibit cataract progression, in case of questions confirm glaucoma diagnosis or improve cornea repair treatment as adjuvant agent (therapy of ulcerating cornea after alkali injury, crosslinking procedure). However, the knowledge about possible citrate usage in ophthalmology is not widely known. Promoting recent scientific knowledge about citrate usage in ophthalmology may not only benefit of medical improvement but may also limit economic costs caused by leading causes of blindness. Further studies on citrate usage in ophthalmology should continuously be the field of scientific interest.11.
Geoffrey A. Mueller Peter M. Thompson Eugene F. DeRose Thomas M. O’Connell Robert E. London 《Metabolomics : Official journal of the Metabolomic Society》2016,12(12):187
Background
Studies on ragweed and birch pollen extracts suggested that the adenosine content is an important factor in allergic sensitization. However, exposure levels from other pollens and considerations of geographic and seasonal factors have not been evaluated.Objective
This study compared the metabolite profile of pollen species important for allergic disease, specifically measured the adenosine content, and evaluated exposure to pollen-derived adenosine.Methods
An NMR metabolomics approach was used to measure metabolite concentrations in 26 pollen extracts. Pollen count data was analyzed from five cities to model exposure.Results
A principal component analysis of the various metabolites identified by NMR showed that pollen extracts could be differentiated primarily by sugar content: glucose, fructose, sucrose, and myo-inositol. In extracts of 10 mg of pollen/ml, the adenosine was highest for grasses (45 µM) followed by trees (23 µM) and weeds (19 µM). Pollen count data showed that tree pollen was typically 5–10 times the amount of other pollens. At the daily peaks of tree, grass, and weed season the pollen-derived adenosine exposure per day is likely to be only 1.1, 0.11, and 0.12 µg, respectively. Seasonal models of pollen exposure and respiration suggest that it would be a rare event limited to tree pollen season for concentrations of pollen-derived adenosine to approach physiological levels.Conclusion
Sugar content and other metabolites may be useful in classifying pollens. Unless other factors create localized exposures that are very different from these models, pollen-derived adenosine is unlikely to be a major factor in allergic sensitization.12.
Ruifang Li-Gao Renée de Mutsert Patrick C. N. Rensen Jan Bert van Klinken Cornelia Prehn Jerzy Adamski Astrid van Hylckama Vlieg Martin den Heijer Saskia le Cessie Frits R. Rosendaal Ko Willems van Dijk Dennis O. Mook-Kanamori 《Metabolomics : Official journal of the Metabolomic Society》2018,14(1):13
Introduction
Fasting metabolite profiles have been shown to distinguish type 2 diabetes (T2D) patients from normal glucose tolerance (NGT) individuals.Objectives
We investigated whether, besides fasting metabolite profiles, postprandial metabolite profiles associated with T2D can stratify individuals with impaired fasting glucose (IFG) by their similarities to T2D.Methods
Three groups of individuals (age 45–65 years) without any history of IFG or T2D were selected from the Netherlands Epidemiology of Obesity study and stratified by baseline fasting glucose concentrations (NGT (n?=?176), IFG (n?=?186), T2D (n?=?171)). 163 metabolites were measured under fasting and postprandial states (150 min after a meal challenge). Metabolite profiles specific for a high risk of T2D were identified by LASSO regression for fasting and postprandial states. The selected profiles were utilised to stratify IFG group into high (T2D probability?≥?0.7) and low (T2D probability?≤?0.5) risk subgroups. The stratification performances were compared with clinically relevant metabolic traits.Results
Two metabolite profiles specific for T2D (nfasting = 12 metabolites, npostprandial = 4 metabolites) were identified, with all four postprandial metabolites also being identified in the fasting state. Stratified by the postprandial profile, the high-risk subgroup of IFG individuals (n?=?72) showed similar glucose concentrations to the low-risk subgroup (n?=?57), yet a higher BMI (difference: 3.3 kg/m2 (95% CI 1.7–5.0)) and postprandial insulin concentrations (21.5 mU/L (95% CI 1.8–41.2)).Conclusion
Postprandial metabolites identified T2D patients as good as fasting metabolites and exhibited enhanced signals for IFG stratification, which offers a proof of concept that metabolomics research should not focus on the fasting state alone.13.
Arianna Filntisi Charalambos Fotakis Pantelis Asvestas George K. Matsopoulos Panagiotis Zoumpoulakis Dionisis Cavouras 《Metabolomics : Official journal of the Metabolomic Society》2017,13(12):146
Introduction
Metabolite identification in biological samples using Nuclear Magnetic Resonance (NMR) spectra is a challenging task due to the complexity of the biological matrices.Objectives
This paper introduces a new, automated computational scheme for the identification of metabolites in 1D 1H NMR spectra based on the Human Metabolome Database.Methods
The methodological scheme comprises of the sequential application of preprocessing, data reduction, metabolite screening and combination selection.Results
The proposed scheme has been tested on the 1D 1H NMR spectra of: (a) an amino acid mixture, (b) a serum sample spiked with the amino acid mixture, (c) 20 blood serum, (d) 20 human amniotic fluid samples, (e) 160 serum samples from publicly available database. The methodological scheme was compared against widely used software tools, exhibiting good performance in terms of correct assignment of the metabolites.Conclusions
This new robust scheme accomplishes to automatically identify peak resonances in 1H-NMR spectra with high accuracy and less human intervention with a wide range of applications in metabolic profiling.14.
Miriam Banas Sindy Neumann Johannes Eiglsperger Eric Schiffer Franz Josef Putz Simone Reichelt-Wurm Bernhard Karl Krämer Philipp Pagel Bernhard Banas 《Metabolomics : Official journal of the Metabolomic Society》2018,14(9):116
Introduction
Allograft rejection is still an important complication after kidney transplantation. Currently, monitoring of these patients mostly relies on the measurement of serum creatinine and clinical evaluation. The gold standard for diagnosing allograft rejection, i.e. performing a renal biopsy is invasive and expensive. So far no adequate biomarkers are available for routine use.Objectives
We aimed to develop a urine metabolite constellation that is characteristic for acute renal allograft rejection.Methods
NMR-Spectroscopy was applied to a training cohort of transplant recipients with and without acute rejection.Results
We obtained a metabolite constellation of four metabolites that shows promising performance to detect renal allograft rejection in the cohorts used (AUC of 0.72 and 0.74, respectively).Conclusion
A metabolite constellation was defined with the potential for further development of an in-vitro diagnostic test that can support physicians in their clinical assessment of a kidney transplant patient.15.
16.
Normalization and integration of large-scale metabolomics data using support vector regression 总被引:1,自引:0,他引:1
Xiaotao Shen Xiaoyun Gong Yuping Cai Yuan Guo Jia Tu Hao Li Tao Zhang Jialin Wang Fuzhong Xue Zheng-Jiang Zhu 《Metabolomics : Official journal of the Metabolomic Society》2016,12(5):89
Introduction
Untargeted metabolomics studies for biomarker discovery often have hundreds to thousands of human samples. Data acquisition of large-scale samples has to be divided into several batches and may span from months to as long as several years. The signal drift of metabolites during data acquisition (intra- and inter-batch) is unavoidable and is a major confounding factor for large-scale metabolomics studies.Objectives
We aim to develop a data normalization method to reduce unwanted variations and integrate multiple batches in large-scale metabolomics studies prior to statistical analyses.Methods
We developed a machine learning algorithm-based method, support vector regression (SVR), for large-scale metabolomics data normalization and integration. An R package named MetNormalizer was developed and provided for data processing using SVR normalization.Results
After SVR normalization, the portion of metabolite ion peaks with relative standard deviations (RSDs) less than 30 % increased to more than 90 % of the total peaks, which is much better than other common normalization methods. The reduction of unwanted analytical variations helps to improve the performance of multivariate statistical analyses, both unsupervised and supervised, in terms of classification and prediction accuracy so that subtle metabolic changes in epidemiological studies can be detected.Conclusion
SVR normalization can effectively remove the unwanted intra- and inter-batch variations, and is much better than other common normalization methods.17.
Clara Pérez-Rambla Leonor Puchades-Carrasco María García-Flores José Rubio-Briones José Antonio López-Guerrero Antonio Pineda-Lucena 《Metabolomics : Official journal of the Metabolomic Society》2017,13(5):52
Introduction
Prostate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results.Objectives
In this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH.Methods
Urine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using 1H nuclear magnetic resonance (1H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches.Results
The urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH.Conclusion
PCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.18.
Strategies to assess and optimize stability of endogenous amines during cerebrospinal fluid sampling
Marek J. Noga Ronald Zielman Robin M. van Dongen Sabine Bos Amy Harms Gisela M. Terwindt Arn M. J. M. van den Maagdenberg Thomas Hankemeier Michel D. Ferrari 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):44
Introduction
Metabolic profiling of cerebrospinal fluid (CSF) is a promising technique for studying brain diseases. Measurements should reflect the in vivo situation, so ex vivo metabolism should be avoided.Objective
To investigate the effects of temperature (room temperature vs. 4 °C), centrifugation and ethanol, as anti-enzymatic additive during CSF sampling on concentrations of glutamic acid, glutamine and other endogenous amines.Methods
CSF samples from 21 individuals were processed using five different protocols. Isotopically-labeled alanine, isoleucine, glutamine, glutamic acid and dopamine were added prior to sampling to trace any degradation. Metabolomics analysis of endogenous amines, isotopically-labeled compounds and degradation products was performed with a validated LC–MS method.Results
Thirty-six endogenous amines were quantified. There were no statistically significant differences between sampling protocols for 31 out of 36 amines. For GABA there was primarily an effect of temperature (higher concentrations at room temperature than at 4 °C) and a small effect of ethanol (lower concentrations if added) due to possible degradation. O-phosphoethanolamine concentrations were also lower when ethanol was added. Degradation of isotopically-labeled compounds (e.g. glutamine to glutamic acid) was minor with no differences between protocols.Conclusion
Most amines can be considered stable during sampling, provided that samples are cooled immediately to 4 °C, centrifuged, and stored at ??80 °C within 2 h. The effect of ethanol addition for more unstable metabolites needs further investigation. This was the first time that labeled compounds were used to monitor ex vivo metabolism during sampling. This is a useful strategy to study the stability of other metabolites of interest.19.
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.20.
Kimberley Joanne Hatfield Guro Kristin Melve Øystein Bruserud 《Metabolomics : Official journal of the Metabolomic Society》2017,13(1):2