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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.
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.3.
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.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.
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.6.
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.7.
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.8.
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.9.
Shayne Mason Karin Terburgh Roan Louw 《Metabolomics : Official journal of the Metabolomic Society》2018,14(6):74
Introduction
The analysis of limited-quantity samples remains a challenge associated with mouse models, especially for multi-platform metabolomics studies. Although inherently insensitive, the highly specific characteristics of nuclear magnetic resonance (NMR) spectroscopy make it an advantageous platform for global metabolite profiling, particularly in mitochondrial disease research.Objectives
Show method equivalency between a well-established standard operating protocol (SOP) and our novel miniaturized 1H-NMR method.Method
The miniaturized method was performed in a 2 mm NMR tube on a standard 500 MHz NMR spectrometer with a 5 mm triple-resonance inverse TXI probe at room temperature.Results
Firstly, using synthetic urine spiked with low (50 µM), medium (250 µM) and high (500 µM) levels (n?=?10) of nine standards, both the SOP and miniaturized method were shown to have acceptable precision (CV?<?15%), relative accuracy (80–120%), and linearity (R2?>?0.95), except for taurine. Furthermore, statistical equivalence was shown using the two one-sided test. Secondly, pooled mouse quadriceps muscle extract was used to further confirm method equivalence (n?=?3), as well as explore the analytical dynamics of this novel approach by analyzing more-concentrated versions of samples (up to 10× concentration) to expand identification of metabolites qualitatively, with quantitative linearity. Lastly, we demonstrate the new technique’s application in a pilot metabolomics study using minute soleus muscle tissue from a mouse model of Leigh syndrome using Ndufs4 KO mice.Conclusion
We demonstrate method equivalency, supporting our novel miniaturized 1H-NMR method as a financially feasible alternative to cryoprobe technology—for limited-quantity biological samples in metabolomics studies that requires a volume one-tenth of the SOP.10.
Anup Paul Surendra Kumar Anubhav Raj Abhinav A. Sonkar Sudha Jain Atin Singhai Raja Roy 《Metabolomics : Official journal of the Metabolomic Society》2018,14(9):119
Introduction
Breast cancer is the most frequent diagnosed cancer among women with a mortality rate of 15% of all cancer related deaths in women. Breast cancer is heterogeneous in nature and produces plethora of metabolites allowing its early detection using molecular diagnostic techniques like magnetic resonance spectroscopy.Objectives
To evaluate the variation in metabolic profile of breast cancer focusing on lipids as triglycerides (TG) and free fatty acids (FFA) that may alter in malignant breast tissues and lymph nodes from adjacent benign breast tissues by HRMAS 1H NMR spectroscopy.Methods
The 1H NMR spectra recorded on 173 tissue specimens comprising of breast tumor tissues, adjacent tissues, few lymph nodes and overlying skin tissues obtained from 67 patients suffering from breast cancer. Multivariate statistical analysis was employed to identify metabolites acting as major confounders for differentiation of malignancy.Result
Reduction in lipid content were observed in malignant breast tissues along with a higher fraction of FFA. Four small molecule metabolites e.g., choline containing compounds (Chocc), taurine, glycine, and glutamate were also identified as major confounders. The test set for prediction provided sensitivity and specificity of more than 90% excluding the lymph nodes and skin tissues.Conclusion
Fatty acids composition in breast cancer using in vivo magnetic resonance spectroscopy (MRS) is gaining its importance in clinical settings (Coum et al. in Magn Reson Mater Phys Biol Med 29:1–4, 2016). The present study may help in future for precise evaluation of lipid classification including small molecules as a source of early diagnosis of invasive ductal carcinoma by employing in vivo magnetic resonance spectroscopic methods.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.
Introduction
BATMAN and BAYESIL are software tools, which can provide a solution for automated metabolite quantifications based on the proton nuclear magnetic resonance (1H-NMR) spectral data of bio-fluids. However, their specific application for the quantitative 1H-NMR based metabolomics of urine has not been investigated.Objectives
The aim of this study is to evaluate the performance of BATMAN and BAYESIL in the quantitative metabolite analysis of urine based on its 1H-NMR spectra.Methods
BATMAN and BAYESIL were used for automated metabolite quantification based on the 1H-NMR spectra of the urine from the lean, obese and obese-diabetic rat groups. PLS-DA model was used to discriminate the three different groups based on the results from the quantifications.Results
BATMAN was found to be superior to BAYESIL in identifying and quantifying the metabolites in the urine samples, owing to its flexibility that allows users to define and adjust the relevant signals of the pure standard metabolites in the database in order to fit the signals in the samples, a necessary step since variations and peak shift are natural in most 1H-NMR spectra. The results of BATMAN also agreed well with that of the manual deconvolution method, which indicated the higher accuracy in metabolite quantification, despite the need of pre-processing and longer processing time than BAYESIL. However, in the case where the problems in baseline correction and peak shift of 1H-NMR spectra are absent, the use of BAYESIL is more advantageous. Application of quantitative 1H-NMR based metabolomics of the urine showed that PLS-DA model derived from BATMAN could satisfactorily discriminate the lean, obese, and obese-diabetic rat groups.Conclusion
Both BATMAN and BAYESIL are useful for the quantitative automation of urine metabolites based on its 1H-NMR spectra. The results from BATMAN method is superior to BAYESIL but require expertise in spectroscopy and longer computer time. Both methods help in simplifying the interpretation of metabolite status in the VIP analysis.13.
Jérémy Marchand Estelle Martineau Yann Guitton Bruno Le Bizec Gaud Dervilly-Pinel Patrick Giraudeau 《Metabolomics : Official journal of the Metabolomic Society》2018,14(5):60
Introduction
Although it is still at a very early stage compared to its mass spectrometry (MS) counterpart, proton nuclear magnetic resonance (NMR) lipidomics is worth being investigated as an original and complementary solution for lipidomics. Dedicated sample preparation protocols and adapted data acquisition methods have to be developed to set up an NMR lipidomics workflow; in particular, the considerable overlap observed for lipid signals on 1D spectra may hamper its applicability.Objectives
The study describes the development of a complete proton NMR lipidomics workflow for application to serum fingerprinting. It includes the assessment of fast 2D NMR strategies, which, besides reducing signal overlap by spreading the signals along a second dimension, offer compatibility with the high-throughput requirements of food quality characterization.Method
The robustness of the developed sample preparation protocol is assessed in terms of repeatability and ability to provide informative fingerprints; further, different NMR acquisition schemes—including classical 1D, fast 2D based on non-uniform sampling or ultrafast schemes—are evaluated and compared. Finally, as a proof of concept, the developed workflow is applied to characterize lipid profiles disruption in serum from β-agonists diet fed pigs.Results
Our results show the ability of the workflow to discriminate efficiently sample groups based on their lipidic profile, while using fast 2D NMR methods in an automated acquisition framework.Conclusion
This work demonstrates the potential of fast multidimensional 1H NMR—suited with an appropriate sample preparation—for lipidomics fingerprinting as well as its applicability to address chemical food safety issues.14.
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.15.
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.16.
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
17.
Simon Roques Catherine Deborde Nadège Richard Luce Sergent Francis Kurz Sandrine Skiba-Cassy Benoît Fauconneau Annick Moing 《Metabolomics : Official journal of the Metabolomic Society》2018,14(12):155
Introduction
Fish feed formulations are constantly evolving to improve the quality of diets for farmed fish and to ensure the sustainability of the aquaculture sector. Nowadays, insect, microalgae and yeast are feedstuff candidates for new feeds. However, the characterization of aquafeed is still based on proximate and targeted analyses which may not be sufficient to assess feed quality.Objectives
Our aim was to highlight the soluble compounds that specifically differ between selected plant-based feeds complemented with alternative feedstuffs and discuss their origin and potential for fish nutrition.Methods
A growth trial was carried out to evaluate growth performances and feed conversion ratios of fish fed plant-based, commercial, insect, spirulina and yeast feeds. 1H NMR metabolomics profiling of each feed was performed using a CPMG sequence on polar extracts. Spectra were processed, and data were analyzed using multivariate and univariate analyses to compare alternative feeds to a plant-based feed.Results
Fish fed insect or yeast feed showed the best growth performances associated with the lowest feed conversion ratios compared to plant-based feed. Soluble compound 1H NMR profiles of insect and spirulina alternative feeds differed significantly from the plant-based one that clustered with yeast feed. In insect and spirulina feeds, specific differences compared to plant-based feed concerned glycerol and 3-hydroxybutyrate, respectively.Conclusion
This strategy based on compositional differences between plant-based and alternative feeds can be useful for detecting compounds unsuspected until now that could impact fish metabolism.18.
Agnieszka Skorupa Łukasz Boguszewicz Marek Kijonka Maria Sokół 《Metabolomics : Official journal of the Metabolomic Society》2017,13(4):34
Introduction
In recent years multivariate projection techniques of data analysis (PCA, PLS-DA) have been increasingly used for detection of complex 1H MRS derived metabolic signatures in pathologic conditions. However, these techniques have not been applied in the studies of metabolic heterogeneity of the normal human brain.Objective
In this work we extended current knowledge about regional distribution of metabolites by multivariate analysis of metabolite levels obtained from various cortical and subcortical regions.Methods
The studied group consisted of 71 volunteers with no neurological disorders. The metabolite levels obtained from short echo time 1H MRS in vivo spectra were subjected to univariate and multivariate analysis.Results
The major variance direction in the dataset was dominated by glutamine?+?glutamate, creatine, myo-inositol and was successful in differentiation of the cortical grey matter and cerebellar vermis from the cortical white matter, pons, basal ganglia, hippocampus and thalamus. The projection plane formed by the second and third variance directions was dominated by N-acetylaspartate?+?N-acetylaspartylglutamate, choline and glutamine?+?glutamate variation not explained by the first direction. This plane revealed a huge metabolic contrast between the pons and basal ganglia, differentiation between the cortical grey matter regions and cerebellar vermis as well as biochemical heterogeneity between the regions such as: thalamus, basal ganglia and hippocampus.Conclusion
Multivariate approach to 1H MRS data analysis provides an insight into the normal brain biochemistry and is helpful in understanding the regional heterogeneity of the normal brain. Such knowledge is crucial for a proper interpretation of altered metabolic pathways in diseases.19.
Manuja Kaluarachchi Claire L. Boulangé Ibrahim Karaman John C. Lindon Timothy M. D. Ebbels Paul Elliott Russell P. Tracy Nels C. Olson 《Metabolomics : Official journal of the Metabolomic Society》2018,14(3):32
Introduction
Differences in the metabolite profiles between serum and plasma are incompletely understood.Objectives
To evaluate metabolic profile differences between serum and plasma and among plasma sample subtypes.Methods
We analyzed serum, platelet rich plasma (PRP), platelet poor plasma (PPP), and platelet free plasma (PFP), collected from 8 non-fasting apparently healthy women, using untargeted standard 1D and CPMG 1H NMR and reverse phase and hydrophilic (HILIC) UPLC-MS. Differences between metabolic profiles were evaluated using validated principal component and orthogonal partial least squares discriminant analysis.Results
Explorative analysis showed the main source of variation among samples was due to inter-individual differences with no grouping by sample type. After correcting for inter-individual differences, lipoproteins, lipids in VLDL/LDL, lactate, glutamine, and glucose were found to discriminate serum from plasma in NMR analyses. In UPLC-MS analyses, lysophosphatidylethanolamine (lysoPE)(18:0) and lysophosphatidic acid(20:0) were higher in serum, and phosphatidylcholines (PC)(16:1/18:2, 20:3/18:0, O-20:0/22:4), lysoPC(16:0), PE(O-18:2/20:4), sphingomyelin(18:0/22:0), and linoleic acid were lower. In plasma subtype analyses, isoleucine, leucine, valine, phenylalanine, glutamate, and pyruvate were higher among PRP samples compared with PPP and PFP by NMR while lipids in VLDL/LDL, citrate, and glutamine were lower. By UPLC-MS, PE(18:0/18:2) and PC(P-16:0/20:4) were higher in PRP compared with PFP samples.Conclusions
Correction for inter-individual variation was required to detect metabolite differences between serum and plasma. Our results suggest the potential importance of inter-individual effects and sample type on the results from serum and plasma metabolic phenotyping studies.20.
Nadine Strehmel David Strunk Veronika Strehmel 《Metabolomics : Official journal of the Metabolomic Society》2017,13(11):135