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1.
Hailong Zhang Longzhen Cui Wen Liu Zhenfeng Wang Yang Ye Xue Li Huijuan Wang 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):47
Introduction
Gastric cancer (GC) is a malignant tumor worldwide. As primary pathway for metastasis, the lymphatic system is an important prognostic factor for GC patients. Although the metabolic changes of gastric cancer have been investigated in extensive studies, little effort focused on the metabolic profiling of lymph node metastasis (LNM)-positive or negative GC patients.Objectives
We performed 1H NMR spectrum of GC tissue samples with and without LNM to identify novel potential metabolic biomarkers in the process of LNM of GC.Methods
1H NMR-based untargeted metabolomics approach combined with multivariate statistical analyses were used to study the metabolic profiling of tissue samples from LNM-positive GC patients (n?=?40), LNM-negative GC patients (n?=?40) and normal controls (n?=?40).Results
There was a clear separation between GC patients and normal controls, and 33 differential metabolites were identified in the study. Moreover, GC patients were also well-classified according to LNM-positive or negative. Totally eight distinguishing metabolites were selected in the metabolic profiling of GC patients with LNM-positive or negative, suggesting the metabolic dysfunction in the process of LNM. According to further validation and analysis, especially BCAAs metabolism (leucine, isoleucine, valine), GSH and betaine may be as potential factors of diagnose and prognosis of GC patients with or without LNM.Conclusion
To our knowledge, this is the first metabolomics study focusing on LNM of GC. The identified distinguishing metabolites showed a promising application on clinical diagnose and therapy prediction, and understanding the mechanism underlying the carcinogenesis, invasion and metastasis of GC.2.
Manvendra Pratap Singh Mona Saxena Charanjit S. Saimbi Jamal M. Arif Raja Roy 《Metabolomics : Official journal of the Metabolomic Society》2017,13(11):137
Introduction
Periodontitis is a chronic, non-reversible inflammatory disease of the oral cavity leading to destruction of periodontal tissues. Thus, the estimation of bacterial metabolite, tissue damage and secretory metabolites of the triggered inflammatory cells likely to yield results. It may be of value for understanding the pathophysiology of the disease by metabolic profiling of saliva samples using high-resolution NMR spectroscopy.Objective
The study will evaluate the difference in salivary metabolites in healthy and periodontal condition along with fetching of possible biomarkers in case of chronic periodontitis.Methods
1H- NMR spectroscopy has been employed in 114 saliva samples in search of distinctive differences and spectral data were further subjected to multivariate analysis.Result
One-hundred metabolites were characterised and assigned in the 1H NMR spectra of saliva. The statistical analysis of control (Healthy subjects) and diseased (Periodontal subjects) using PLS-DA model resulted in R2 of 0.84 and Q2 of 0.79. There was an elevation in the concentration of statistically discriminant metabolites. The twenty newly identified metabolites in saliva indicates bacterial population shift along with change in homeostasis. These disturbs the biofilm, a real protector against any possible bio-damage on tooth surface. These newly identified metabolites could define better geographically diversified periodontal condition.Conclusion
Analysis clearly differentiates healthy subjects from the diseased ones. Few newly identified metabolites along with the pool of metabolites may serve as biomarkers for distinguishing the severity and complexity of periodontitis.3.
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.4.
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.5.
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.6.
Tanushri Chatterji Suruchi Singh Manodeep Sen Ajai Kumar Singh Pradeep Kumar Maurya Nuzhat Husain Janmejai Kumar Srivastava Sudhir Kumar Mandal Raja Roy 《Metabolomics : Official journal of the Metabolomic Society》2016,12(8):130
Introduction
Meningitis, a morbidly infectious central nervous system pathology is accompanied by acute inflammation of the meninges, causing raised intracranial pressure linked with serious neurological sequelae.Objective
To observe the variation in the metabolic profile, that may occur in serum and urine along with CSF in adults using 1H NMR spectroscopy, with an attempt of appropriate and timely treatment regimen.Methods
The 1H NMR-based metabolomics has been performed in 115 adult subjects for differentiating bacterial meningitis (BM) and tubercular meningitis (TBM).Results
The discriminant function analysis (DFA) of the three bio-fluids collectively identified 3-hydroxyisovalerate, lactate, glucose, formate, valine, alanine, ketonic bodies, malonate and choline containing compounds (choline and GPC) as significant metabolites among cases versus control group. The differentiation of bacterial meningitis and tuberculous meningitis (BM vs. TBM) can be done on the basis of identification of 3-hydroxyisovalerate, isobutyrate and formate in case of CSF (with a correct classification of 78 %), alanine in serum (correct classification 60 %), valine and acetone in case of urine (correct classification 89.1 %). The NMR spectral bins based orthogonal signal correction principal component analysis score plots of significant metabolites obtained from DFA also provided group classification among cases versus control group in CSF, serum and urine samples. The variable importance in projection scores also identified similar significant metabolites as obtained from DFA, collectively in CSF, serum and urine samples, responsible for differentiation of meningitis.Conclusion
The CSF contained metabolites which are formed during infection and inflammation, and these were also found in significant quantity in serum and urine samples.7.
Patrick J. C. Tardivel Cécile Canlet Gaëlle Lefort Marie Tremblay-Franco Laurent Debrauwer Didier Concordet Rémi Servien 《Metabolomics : Official journal of the Metabolomic Society》2017,13(10):109
Introduction
Experiments in metabolomics rely on the identification and quantification of metabolites in complex biological mixtures. This remains one of the major challenges in NMR/mass spectrometry analysis of metabolic profiles. These features are mandatory to make metabolomics asserting a general approach to test a priori formulated hypotheses on the basis of exhaustive metabolome characterization rather than an exploratory tool dealing with unknown metabolic features.Objectives
In this article we propose a method, named ASICS, based on a strong statistical theory that handles automatically the metabolites identification and quantification in proton NMR spectra.Methods
A statistical linear model is built to explain a complex spectrum using a library containing pure metabolite spectra. This model can handle local or global chemical shift variations due to experimental conditions using a warping function. A statistical lasso-type estimator identifies and quantifies the metabolites in the complex spectrum. This estimator shows good statistical properties and handles peak overlapping issues.Results
The performances of the method were investigated on known mixtures (such as synthetic urine) and on plasma datasets from duck and human. Results show noteworthy performances, outperforming current existing methods.Conclusion
ASICS is a completely automated procedure to identify and quantify metabolites in 1H NMR spectra of biological mixtures. It will enable empowering NMR-based metabolomics by quickly and accurately helping experts to obtain metabolic profiles.8.
Nathan C Hall Stephen P Povoski Douglas A Murrey Michael V Knopp Edward W MartinJr 《World journal of surgical oncology》2007,5(1):143
Background
18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) has become an established method for detecting hypermetabolic sites of known and occult disease and is widely used in oncology surgical planning. Intraoperatively, it is often difficult to localize tumors and verify complete resection of tumors that have been previously detected on diagnostic PET/CT at the time of the original evaluation of the cancer patient. Therefore, we propose an innovative approach for intraoperative tumor localization and verification of complete tumor resection utilizing 18F-FDG for perioperative PET/CT imaging and intraoperative gamma probe detection.Methods
Two breast cancer patients were evaluated. 18F-FDG was administered and PET/CT was acquired immediately prior to surgery. Intraoperatively, tumors were localized and resected with the assistance of a handheld gamma probe. Resected tumors were scanned with specimen PET/CT prior to pathologic processing. Shortly after the surgical procedure, patients were re-imaged with PET/CT utilizing the same preoperatively administered 18F-FDG dose.Results
One patient had primary carcinoma of breast and a metastatic axillary lymph node. The second patient had a solitary metastatic liver lesion. In both cases, preoperative PET/CT verified these findings and demonstrated no additional suspicious hypermetabolic lesions. Furthermore, intraoperative gamma probe detection, specimen PET/CT, and postoperative PET/CT verified complete resection of the hypermetabolic lesions.Conclusion
Immediate preoperative and postoperative PET/CT imaging, utilizing the same 18F-FDG injection dose, is feasible and image quality is acceptable. Such perioperative PET/CT imaging, along with intraoperative gamma probe detection and specimen PET/CT, can be used to verify complete tumor resection. This innovative approach demonstrates promise for assisting the oncologic surgeon in localizing and verifying resection of 18F-FDG positive tumors and may ultimately positively impact upon long-term patient outcomes.9.
Robert M Kirby Abdul Basit Quang T Nguyen Anthony Jaipersad Rebecca Billingham 《International Seminars in Surgical Oncology : ISSO》2007,4(1):30
Aims
This paper describes a simple technique of axillary and breast massage which improves the successful identification of blue sentinel nodes using patent blue dye alone.Methods
Patent blue dye was injected in the subdermal part of the retroaroelar area in 167 patients having surgical treatment for invasive breast cancer. Three stage axillary lymphatic massage was performed prior to making the axillary incision for sentinel lymph node biopsy. All patients had completion axillary sampling or clearance.Results
A blue lymphatic duct leading to lymph nodes of the first drainage was identified in 163 (97%) of the patients. Results are compared with 168 patients who had sentinel lymph node biopsy using blue dye without axillary massage. Allergic reactions were observed in four patients (1.2%).Conclusion
Three stage axillary lymphatic massage improves the successful identification of a blue sentinel lymph node in breast cancer patients.10.
Gregory D. Tredwell Jacob G. Bundy Maria De Iorio Timothy M. D. Ebbels 《Metabolomics : Official journal of the Metabolomic Society》2016,12(10):152
Introduction
Despite the use of buffering agents the 1H NMR spectra of biofluid samples in metabolic profiling investigations typically suffer from extensive peak frequency shifting between spectra. These chemical shift changes are mainly due to differences in pH and divalent metal ion concentrations between the samples. This frequency shifting results in a correspondence problem: it can be hard to register the same peak as belonging to the same molecule across multiple samples. The problem is especially acute for urine, which can have a wide range of ionic concentrations between different samples.Objectives
To investigate the acid, base and metal ion dependent 1H NMR chemical shift variations and limits of the main metabolites in a complex biological mixture.Methods
Urine samples from five different individuals were collected and pooled, and pre-treated with Chelex-100 ion exchange resin. Urine samples were either treated with either HCl or NaOH, or were supplemented with various concentrations of CaCl2, MgCl2, NaCl or KCl, and their 1H NMR spectra were acquired.Results
Nonlinear fitting was used to derive acid dissociation constants and acid and base chemical shift limits for peaks from 33 identified metabolites. Peak pH titration curves for a further 65 unidentified peaks were also obtained for future reference. Furthermore, the peak variations induced by the main metal ions present in urine, Na+, K+, Ca2+ and Mg2+, were also measured.Conclusion
These data will be a valuable resource for 1H NMR metabolite profiling experiments and for the development of automated metabolite alignment and identification algorithms for 1H NMR spectra.11.
Panita Prathomya Wassana Prisingkorn Ivan Jakovlić Fang-Yu Deng Yu-Hua Zhao Wei-Min Wang 《Metabolomics : Official journal of the Metabolomic Society》2017,13(2):17
Introduction
High-fat and high-carbohydrate diets cause a number of metabolic disorders in mammals. However, little is known about metabolomic changes caused by dietary imbalances in fish.Objectives
The objective of this study was to assess the impacts of high-fat diet (HFD), high-carbohydrate diet (HCD) and high-fat-high-carbohydrate diet (HFHCD) on metabolites in a farmed cyprinid fish Megalobrama amblycephala.Methods
We have employed the 1H NMR-based metabolomic approach to measure the concentrations of metabolites in plasma and liver of four different diet groups: HFD, HCD, HFHCD and control. Multivariate statistical analyses were used to determine significantly changed metabolites between all group-pairs.Results
All three test diets have affected metabolic profiles, phenotypes and clinical chemistry. High-fat diets (HFD, HFHCD) resulted in a higher average weight than HCD, but high-carbohydrate diets (HCD, HFHCD) caused signs of liver damage. HCD has resulted in elevated metabolites in energy pathways, leading to further disturbances in creatine pathway. Excess of carbohydrate and lipid metabolism products in the HFHCD group appears to have caused “congestion” of the TCA cycle, causing a significant decline in the numbers of amino acids entering the cycle, which in turn resulted in elevated levels of seven amino acids in this group. Gut microbiota metabolites (TMA) exhibited a strong positive correlation with the carbohydrate content and a negative correlation with the fat content in diets.Conclusion
These results provide an important insight into the diet-affected metabolic disorders that often lead to financial losses in the aquaculture of Megalobrama amblycephala.Graphical Abstract
12.
Ł. Boguszewicz A. Hajduk J. Mrochem-Kwarciak A. Skorupa M. Ciszek A. Heyda K. Składowski M. Sokół 《Metabolomics : Official journal of the Metabolomic Society》2016,12(6):102
Introduction
Anticancer treatment results in temporary or permanent toxicity considered as changes in normal tissues and/or involved regions. The net effect is mirrored in morphological, functional and molecular disturbances—thus in a systemic response of the human body. To date, specific NMR biomarkers of radiation therapy toxicity in head and neck squamous cell carcinoma (HNSCC) patients are scarce or even missing.Objectives
We aimed to investigate molecular processes reflecting acute radiation sequelae (ARS) in HNSCC patients using NMR-based metabolomics of blood serum.Methods
45 patients with HNSCC were treated with radiotherapy (RT) or chemoradiotherapy (CHRT). Blood samples were collected within a week after RT/CHRT completion. Patients were divided into two classes (of high and low ARS) on the basis of the highest individual ARS value observed during the treatment. 1H NMR spectra of serum samples were acquired on a Bruker 400.13 MHz spectrometer at 310 K and analyzed using principal component analysis and orthogonal partial least squares discriminant analysis. Additional statistical analyses were performed on quantified metabolites.Results
1D projections of the J-resolved NMR spectra seem to be of the great potential in the quest for the HNSCC treatment toxicity biomarker. The metabolic features characteristic for high ARS are the increased signals of N-acetyl-glycoprotein and acetate, as well as decrease of choline and the metabolites involved in energy metabolism: branched chain amino acids (BCAAs), alanine, creatinine and carnitine. Furthermore, we observed significant correlations between N-acetyl-glycoprotein and clinical markers of inflammation as well as acetate and a percentage-weight-loss during the treatment. CRP was also negatively correlated with alanine and BCAAs.Conclusion
NMR-based metabolomics provides relevant biomarkers of RT/CHRT toxicity (ARS) in HNSCC patients. The results indicate at least three concomitant processes related to high ARS: inflammation, altered energy metabolism and disturbed membrane metabolism, and indicate an exciting potential of J-resolved NMR spectroscopy combined with multivariate projection techniques.13.
14.
Yanhui Ge Mengmeng Sun Luis F. Salomé-Abarca Mei Wang Young Hae Choi 《Metabolomics : Official journal of the Metabolomic Society》2018,14(10):137
Introduction
The pharmacological activities of medicinal plants are reported to be due to a wide range of metabolites, therein, the concentrations of which are greatly affected by many genetic and/or environmental factors. In this context, a metabolomics approach has been applied to reveal these relationships. The investigation of such complex networks that involve the correlation between multiple biotic and abiotic factors and the metabolome, requires the input of information acquired by more than one analytical platform. Thus, development of new metabolomics techniques or hyphenations is continuously needed.Objectives
Feasibility of high performance thin-layer chromatography (HPTLC) were investigated as a supplementary tool for medicinal plants metabolomics supporting 1H nuclear magnetic resonance (1H NMR) spectroscopy.Method
The overall metabolic difference of plant material collected from two species (Rheum palmatum and Rheum tanguticum) in different geographical locations and altitudes were analyzed by 1H NMR- and HPTLC-based metabolic profiling. Both NMR and HPTLC data were submitted to multivariate data analysis including principal component analysis and orthogonal partial least square analysis.Results
The NMR and HPTLC profiles showed that while chemical variations of rhubarb are in some degree affected by all the factors tested in this study, the most influential factor was altitude of growth. The metabolites responsible for altitude differentiation were chrysophanol, emodin and sennoside A, whereas aloe emodin, catechin, and rhein were the key species-specific markers.Conclusion
These results demonstrated the potential of HTPLC as a supporting tool for metabolomics due to its high profiling capacity of targeted metabolic groups and preparative capability.15.
Daniel Cañueto Josep Gómez Reza M. Salek Xavier Correig Nicolau Cañellas 《Metabolomics : Official journal of the Metabolomic Society》2018,14(3):24
Introduction
Adoption of automatic profiling tools for 1H-NMR-based metabolomic studies still lags behind other approaches in the absence of the flexibility and interactivity necessary to adapt to the properties of study data sets of complex matrices.Objectives
To provide an open source tool that fully integrates these needs and enables the reproducibility of the profiling process.Methods
rDolphin incorporates novel techniques to optimize exploratory analysis, metabolite identification, and validation of profiling output quality.Results
The information and quality achieved in two public datasets of complex matrices are maximized.Conclusion
rDolphin is an open-source R package (http://github.com/danielcanueto/rDolphin) able to provide the best balance between accuracy, reproducibility and ease of use.16.
Shiwei Zhang Qiding Zhong Daobing Wang Zhanbin Huang Guohui Li 《Biotechnology letters》2017,39(12):1853-1857
Objectives
To determine the origin of 15N-labeled phenylalanine in microbial metabolic flux analysis using 15N as a tracer, a method for measuring phenylalanine δ15N using HPLC coupled with elemental analysis-isotope ratio mass spectrometry (EA-IRMS) was developed.Results
The original source of the 15N-labeled phenylalanine was determined using this new method that consists of three steps: optimization of the HPLC conditions, evaluation of the isotope fractionation effects, and evaluation of the effect of pre-processing on the phenylalanine nitrogen stable isotope. In addition, the use of a 15N-labeled inorganic nitrogen source, rather than 15N-labeled amino acids, was explored using this method.Conclusions
The method described here can also be applied to the analysis of metabolic flux.17.
Background
Metastatic cancer to bone is well-known to produce extreme pain. It has been suggested that the magnitude of this perceived pain is associated with disease progression and poor prognosis. These data suggest a potential cross-talk between cancer cells and nociceptors that contribute not only to pain, but also to cancer aggressiveness although the underlying mechanisms are yet to be stablished.Methods
The in vitro dose dependent effect of neuropeptides (NPs) (substance P [SP], calcitonin gene-related peptide and neurokinin A [NKA]) and/or its combination, on the migration and invasion of MDA-MB-231LUC+ were assessed by wound healing and collagen-based cell invasion assays, respectively. The effect of NPs on the expression of its receptors (SP [NK1] and neurokinin A receptors [NK2], CALCRL and RAMP1) and kininogen (high-molecular-weight kininogen) release to the cell culture supernatant of MDA-MB-231LUC+, were measured using western-blot analysis and an ELISA assay, respectively. Statistical significance was tested using one-way ANOVA, repeated measures ANOVA, or the paired t-test. Post-hoc testing was performed with correction for multiple comparisons as appropriate.Results
Our data show that NPs strongly modify the chemokinetic capabilities of a cellular line commonly used as a model of metastatic cancer to bone (MDA-MB-231LUC+) and increased the expression of their receptors (NK1R, NK2R, RAMP1, and CALCRL) on these cells. Finally, we demonstrate that NPs also trigger the acute release of HMWK (Bradykinin precursor) by MDA-MB-231LUC+, a molecule with both tumorigenic and pro-nociceptive activity.Conclusions
Based on these observations we conclude that NPs exposure modulates this breast cancer cellular line aggressiveness by increasing its ability to migrate and invade new tissues. Furthermore, these results also support the pro nociceptive and cancer promoter role of the peripheral nervous system, during the initial stages of the disease.18.
Ryo Nakabayashi Hiroshi Tsugawa Tetsuya Mori Kazuki Saito 《Metabolomics : Official journal of the Metabolomic Society》2016,12(11):168
Introduction
Sulfur-containing metabolites (S-metabolites) in organisms including plants have unique benefits to humans. So far, few analytical methods have explored such metabolites.Objectives
We aimed to develop an automatic chemically assigning platform by metabolomics and chemoinformatics with 34S labeling to identify the molecular formula of S-metabolites.Methods
Direct infusion analysis using Fourier transform ion cyclotron resonance-mass spectrometry provided ultra-high-resolution data including clearly separated isotopic ions—15N, 34S, 18O, and 13C2—in the flower, silique, leaf, stem, and root of non-labeled and 34S-labeled Arabidopsis thaliana. Chemoinformatic analysis assigned several elemental compositions of S-metabolites to the acquired S-containing monoisotopic ions using mass accuracy and peak resolution in the non-labeled metabolome data. Possible elemental compositions were characterized on the basis of diagnostic scores of the exact mass and isotopic ion pattern, and a database search. By comparing elemental compositions assigned to the 34S-labeled data with those assigned to the non-labeled data, the elemental composition of S-metabolites were determined. The determined elemental compositions were surveyed using the in-house database, which stores molecular formulae downloaded from metabolome databases.Results
We identified 35 molecular formulae for known S-metabolites and characterized 72 for unknown. Chemoinformatics required around 1.5 min to analyze a pair of the non-labeled and 34S-labeled data of the organ.Conclusion
In this study, we developed an automation platform for automatically identifying the presence of S-metabolites. We identified the molecular formula of known S-metabolites, which are accessible in free databases, together with that of unknown. This analytical method did not focus on identifying the structure of S-metabolites, but on the automatic identification of their molecular formula.19.
Paulin N. Wahjudi Qing-Yi Lu Mary E. Patterson Xuemei Zhang Vay Liang Go Jian Chen Wei-Lin Li W. N. Paul Lee 《Metabolomics : Official journal of the Metabolomic Society》2017,13(8):91
Introduction
Loquat leaf extract (LLE) is commonly used in China for a variety of ailments including diabetes. Several recent reports implicate LLE and a sesquiterpene glycoside, one of its components, as being an anti-hyperglycemic agent. However, the underlying mechanism of action of this anti-hyperglycemic agent has not been reported.Objective
We have conducted a tracer-based metabolomics study to investigate the effects of sesquiterpene and loquat extract on the balance of flux of central glucose metabolism in HepG2 cells and to compare with those of “insulin sensitizers”, metformin and rosiglitazone.Methods
Human hepatoma HepG2 cells in confluence culture were incubated in Dulbecco’s modified Eagle’s medium containing 50% [1, 2 13C2]-glucose in the presence of rosiglitazone, metformin, LLE or pure sesquiterpene. Cells were harvested in 48 h. Mass isotopomers of metabolites (glycogen, ribose, deoxyribose, glutamate and palmitate) were determined.Results
13C labeling in metabolic intermediates were summarized in a mass isotopomer matrix. Treatment with loquat extract/sesquiterpene, metformin and rosiglitazone each produced distinctive mass isotopomer patterns reflecting disparate effects on the contribution of glucose to various metabolites production, and on several metabolic flux ratios. The overall effect of LLE and sesquiterpene on glucose metabolism is clearly different from those of the known “insulin sensitizers”.Conclusion
Our study demonstrates the utility of isotopomer matrix in summarizing metabolic actions of LLE on the balance of fluxes occurring within the central glucose metabolism in HepG2 cells. 13C carbon tracing (tracer-based metabolomics) is a useful systems biology tool to elucidate glucose metabolic pathways affected by diabetes and its treatment.20.