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1
Szczerbinski, Lukasz, Gladys Wojciechowska, Adam Olichwier, Mark A. Taylor, Urszula Puchta, Paulina Konopka, Adam Paszko, et al. "Untargeted Metabolomics Analysis of the Serum Metabolic Signature of Childhood Obesity." Nutrients 14, no. 1 (January 4, 2022): 214. http://dx.doi.org/10.3390/nu14010214.
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Obesity rates among children are growing rapidly worldwide, placing massive pressure on healthcare systems. Untargeted metabolomics can expand our understanding of the pathogenesis of obesity and elucidate mechanisms related to its symptoms. However, the metabolic signatures of obesity in children have not been thoroughly investigated. Herein, we explored metabolites associated with obesity development in childhood. Untargeted metabolomic profiling was performed on fasting serum samples from 27 obese Caucasian children and adolescents and 15 sex- and age-matched normal-weight children. Three metabolomic assays were combined and yielded 726 unique identified metabolites: gas chromatography–mass spectrometry (GC–MS), hydrophilic interaction liquid chromatography coupled to mass spectrometry (HILIC LC–MS/MS), and lipidomics. Univariate and multivariate analyses showed clear discrimination between the untargeted metabolomes of obese and normal-weight children, with 162 significantly differentially expressed metabolites between groups. Children with obesity had higher concentrations of branch-chained amino acids and various lipid metabolites, including phosphatidylcholines, cholesteryl esters, triglycerides. Thus, an early manifestation of obesity pathogenesis and its metabolic consequences in the serum metabolome are correlated with altered lipid metabolism. Obesity metabolite patterns in the adult population were very similar to the metabolic signature of childhood obesity. Identified metabolites could be potential biomarkers and used to study obesity pathomechanisms.
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Kim, Hyun Woo. "Metabolomic Approaches to Investigate the Effect of Metformin: An Overview." International Journal of Molecular Sciences 22, no. 19 (September 24, 2021): 10275. http://dx.doi.org/10.3390/ijms221910275.
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Metformin is the first-line antidiabetic drug that is widely used in the treatment of type 2 diabetes mellitus (T2DM). Even though the various therapeutic potential of metformin treatment has been reported, as well as the improvement of insulin sensitivity and glucose homeostasis, the mechanisms underlying those benefits are still not fully understood. In order to explain the beneficial effects on metformin treatment, various metabolomics analyses have been applied to investigate the metabolic alterations in response to metformin treatment, and significant systemic metabolome changes were observed in biofluid, tissues, and cells. In this review, we compare the latest metabolomic research including clinical trials, animal models, and in vitro studies comprehensively to understand the overall changes of metabolome on metformin treatment.
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Qi, Jinwei, Kang Li, Yunxia Shi, Yufei Li, Long Dong, Ling Liu, Mingyang Li, et al. "Cross-Species Comparison of Metabolomics to Decipher the Metabolic Diversity in Ten Fruits." Metabolites 11, no. 3 (March 12, 2021): 164. http://dx.doi.org/10.3390/metabo11030164.
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Fruits provide humans with multiple kinds of nutrients and protect humans against worldwide nutritional deficiency. Therefore, it is essential to understand the nutrient composition of various fruits in depth. In this study, we performed LC-MS-based non-targeted metabolomic analyses with ten kinds of fruit, including passion fruit, mango, starfruit, mangosteen, guava, mandarin orange, grape, apple, blueberry, and strawberry. In total, we detected over 2500 compounds and identified more than 300 nutrients. Although the ten fruits shared 909 common-detected compounds, each species accumulated a variety of species-specific metabolites. Additionally, metabolic profiling analyses revealed a constant variation in each metabolite’s content across the ten fruits. Moreover, we constructed a neighbor-joining tree using metabolomic data, which resembles the single-copy protein-based phylogenetic tree. This indicates that metabolome data could reflect the genetic relationship between different species. In conclusion, our work enriches knowledge on the metabolomics of fruits, and provides metabolic evidence for the genetic relationships among these fruits.
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Patterson, Jeffrey, Xiaojian Shi, William Bresette, Ryan Eghlimi, Sarah Atlas, Kristin Farr, Sonia Vega-López, and Haiwei Gu. "A Metabolomic Analysis of the Sex-Dependent Hispanic Paradox." Metabolites 11, no. 8 (August 20, 2021): 552. http://dx.doi.org/10.3390/metabo11080552.
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In Mexican Americans, metabolic conditions, such as obesity and type 2 diabetes (T2DM), are not necessarily associated with an increase in mortality; this is the so-called Hispanic paradox. In this cross-sectional analysis, we used a metabolomic analysis to look at the mechanisms behind the Hispanic paradox. To do this, we examined dietary intake and body mass index (BMI; kg/m2) in men and women and their effects on serum metabolomic fingerprints in 70 Mexican Americans (26 men, 44 women). Although having different BMI values, the participants had many similar anthropometric and biochemical parameters, such as systolic and diastolic blood pressure, total cholesterol, and LDL cholesterol, which supported the paradox in these subjects. Plasma metabolomic phenotypes were measured using liquid chromatography tandem mass spectrometry (LC-MS/MS). A two-way ANOVA assessing sex, BMI, and the metabolome revealed 23 significant metabolites, such as 2-pyrrolidinone (p = 0.007), TMAO (p = 0.014), 2-aminoadipic acid (p = 0.019), and kynurenine (p = 0.032). Pathway and enrichment analyses discovered several significant metabolic pathways between men and women, including lysine degradation, tyrosine metabolism, and branch-chained amino acid (BCAA) degradation and biosynthesis. A log-transformed OPLS-DA model was employed and demonstrated a difference due to BMI in the metabolomes of both sexes. When stratified for caloric intake (<2200 kcal/d vs. >2200 kcal/d), a separate OPLS-DA model showed clear separation in men, while females remained relatively unchanged. After accounting for caloric intake and BMI status, the female metabolome showed substantial resistance to alteration. Therefore, we provide a better understanding of the Mexican-American metabolome, which may help demonstrate how this population—particularly women—possesses a longer life expectancy despite several comorbidities, and reveal the underlying mechanisms of the Hispanic paradox.
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Delporte, Cédric, Nausicaa Noret, Cécile Vanhaverbeke, Olivier J. Hardy, Jean-François Martin, Marie Tremblay-Franco, David Touboul, et al. "Does the Phytochemical Diversity of Wild Plants Like the Erythrophleum genus Correlate with Geographical Origin?" Molecules 26, no. 6 (March 17, 2021): 1668. http://dx.doi.org/10.3390/molecules26061668.
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Secondary metabolites are essential for plant survival and reproduction. Wild undomesticated and tropical plants are expected to harbor highly diverse metabolomes. We investigated the metabolomic diversity of two morphologically similar trees of tropical Africa, Erythrophleum suaveolens and E. ivorense, known for particular secondary metabolites named the cassaine-type diterpenoids. To assess how the metabolome varies between and within species, we sampled leaves from individuals of different geographic origins but grown from seeds in a common garden in Cameroon. Metabolites were analyzed using reversed phase LC-HRMS(/MS). Data were interpreted by untargeted metabolomics and molecular networks based on MS/MS data. Multivariate analyses enabled us to cluster samples based on species but also on geographic origins. We identified the structures of 28 cassaine-type diterpenoids among which 19 were new, 10 were largely specific to E. ivorense and five to E. suaveolens. Our results showed that the metabolome allows an unequivocal distinction of morphologically-close species, suggesting the potential of metabolite fingerprinting for these species. Plant geographic origin had a significant influence on relative concentrations of metabolites with variations up to eight (suaveolens) and 30 times (ivorense) between origins of the same species. This shows that the metabolome is strongly influenced by the geographical origin of plants (i.e., genetic factors).
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Cheng, Leo L., Adam S. Feldman, Lindsey A. Vandergrift, Isabella H. Muti, Florian Rumpf, Andrew Gusev, Yannick Berker, et al. "Abstract 2222: Detecting clinically significant prostate cancers: Tissue metabolomics refines multiparametric MRI-ultrasound fusion prostate biopsy." Cancer Research 82, no. 12_Supplement (June 15, 2022): 2222. http://dx.doi.org/10.1158/1538-7445.am2022-2222.
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Abstract The advent of prostate specific antigen (PSA) testing led to increased early prostate cancer (PCa) detection and has decreased PCa-related death. However, PSA is not cancer-specific, and the challenge persists of differentiating those PCa patients with indolent tumors from those requiring definitive therapy. Metabolomic profiles have the potential to capture molecular dynamics of disease and to reflect disease status before cellular manifestations become observable by histopathology. With clinical, multiparametric magnetic resonance imaging (mpMRI)-positive, fusion biopsy-targeted tissue cores and mpMRI-negative controls in a training-testing cohort design, we studied the potential of magnetic resonance spectroscopy (MRS) to yield cancer metabolomic profiles that could help discriminate likely indolent from clinically significant disease. Using MRS-based PCa metabolomic analyses, performed prior to histology, our approach is able to: determine metabolomic relevations identified in fusion biopsy targets, estimate the scale of PCa metabolomic fields, and detect clinically significant disease in tissues deemed benign or low-risk PCa by pathology and imaging. Our intact tissue MRS metabolomics evaluations indicated significant differences in individual prostate tissue metabolites based on Target-Contralateral (Contral) paired comparisons for both Training and Testing cohorts. We identified metabolomic differences among Target prostate biopsy cores obtained from mpMRI lesions of different PI-RADS scores, and between Target and non-target Contral cores. As a retrospective study, we also analyzed data collected at the time of the initial prostate biopsy alongside patient status across follow up. By introducing metabolomics, as compared with using PSAd or PI-RADS alone, the sensitivity predictions increased by 80.0% and 25.0%, respectively; NPV increased by 18.1% and 8.0%; and accuracy for PSAd increased by 13.0%. PI-RADS accuracy stayed the same Our results show that tissue metabolomic profiles could augment current MR-based imaging findings and histopathological evaluations of fusion biopsies for certain patient populations by more accurately characterizing them into clinically significant or insignificant subgroups. In our analyses, tissue metabolomics alone, or its combination with other clinical parameters, improved sensitivity and negative predictive values, as well as overall accuracy, for our testing cohort. This method, which relies on performing tissue MRS of needle biopsy cores prior to histopathologic analysis, causes no interruption to patient care. Findings from our study demonstrate the utility and translational potential of cancer metabolomics in personalized treatment for PCa and encourages the development of in vivo PCa metabolomic imaging to enhance the diagnostic utility of mpMRI. Citation Format: Leo L. Cheng, Adam S. Feldman, Lindsey A. Vandergrift, Isabella H. Muti, Florian Rumpf, Andrew Gusev, Yannick Berker, Marcella R. Cardoso, Taylor L. Fuss, Emily D. Negroponte, Shulin Wu, Felix Ehret, Christopher A. Dietz, Sarah S. Dinges, Thitinan Chulroek, Edouard Nicaise, Piet Habbel, Martin Ayree, Johannes Nowak, Douglas M. Dahl, Chin-Lee Wu, Mukesh Harisinghani. Detecting clinically significant prostate cancers: Tissue metabolomics refines multiparametric MRI-ultrasound fusion prostate biopsy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2222.
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Byerley, Lauri O., Karyn M. Gallivan, Courtney J. Christopher, Christopher M. Taylor, Meng Luo, Scot E. Dowd, Gregory M. Davis, Hector F. Castro, Shawn R. Campagna, and Kristin S. Ondrak. "Gut Microbiome and Metabolome Variations in Self-Identified Muscle Builders Who Report Using Protein Supplements." Nutrients 14, no. 3 (January 26, 2022): 533. http://dx.doi.org/10.3390/nu14030533.
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Muscle builders frequently consume protein supplements, but little is known about their effect on the gut microbiota. This study compared the gut microbiome and metabolome of self-identified muscle builders who did or did not report consuming a protein supplement. Twenty-two participants (14 males and 8 females) consumed a protein supplement (PS), and seventeen participants (12 males and 5 females) did not (No PS). Participants provided a fecal sample and completed a 24-h food recall (ASA24). The PS group consumed significantly more protein (118 ± 12 g No PS vs. 169 ± 18 g PS, p = 0.02). Fecal metabolome and microbiome were analyzed by using untargeted metabolomics and 16S rRNA gene sequencing, respectively. Metabolomic analysis identified distinct metabolic profiles driven by allantoin (VIP score = 2.85, PS 2.3-fold higher), a catabolic product of uric acid. High-protein diets contain large quantities of purines, which gut microbes degrade to uric acid and then allantoin. The bacteria order Lactobacillales was higher in the PS group (22.6 ± 49 No PS vs. 136.5 ± 38.1, PS (p = 0.007)), and this bacteria family facilitates purine absorption and uric acid decomposition. Bacterial genes associated with nucleotide metabolism pathways (p < 0.001) were more highly expressed in the No PS group. Both fecal metagenomic and metabolomic analyses revealed that the PS group’s higher protein intake impacted nitrogen metabolism, specifically altering nucleotide degradation.
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Loras, Alba, M. Carmen Martínez-Bisbal, Guillermo Quintás, Salvador Gil, Ramón Martínez-Máñez, and José Luis Ruiz-Cerdá. "Urinary Metabolic Signatures Detect Recurrences in Non-Muscle Invasive Bladder Cancer." Cancers 11, no. 7 (June 29, 2019): 914. http://dx.doi.org/10.3390/cancers11070914.
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Patients with non-muscle invasive bladder cancer (NMIBC) undergo lifelong monitoring based on repeated cystoscopy and urinary cytology due to the high recurrence rate of this tumor. Nevertheless, these techniques have some drawbacks, namely, low accuracy in detection of low-grade tumors, omission of pre-neoplastic lesions and carcinomas in situ (CIS), invasiveness, and high costs. This work aims to identify a urinary metabolomic signature of recurrence by proton Nuclear Magnetic Resonance (1H NMR) spectroscopy for the follow-up of NMIBC patients. To do this, changes in the urinary metabolome before and after transurethral resection (TUR) of tumors are analyzed and a Partial Least Square Discriminant Analysis (PLS-DA) model is developed. The usefulness of this discriminant model for the detection of tumor recurrences is assessed using a cohort of patients undergoing monitoring. The trajectories of the metabolomic profile in the follow-up period provide a negative predictive value of 92.7% in the sample classification. Pathway analyses show taurine, alanine, aspartate, glutamate, and phenylalanine perturbed metabolism associated with NMIBC. These results highlight the potential of 1H NMR metabolomics to detect bladder cancer (BC) recurrences through a non-invasive approach.
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Mok, Jeong-Hun, Minjoong Joo, Van-An Duong, Seonghyeon Cho, Jong-Moon Park, Young-Sic Eom, Tae-Hwa Song, Hee-Joung Lim, and Hookeun Lee. "Proteomic and Metabolomic Analyses of Maggots in Porcine Corpses for Post-Mortem Interval Estimation." Applied Sciences 11, no. 17 (August 26, 2021): 7885. http://dx.doi.org/10.3390/app11177885.
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Post-mortem interval (PMI) estimation is a critical task in forensic science. In this study, we used maggots collected from pig carcasses and applied an integrated proteomics and metabolomics approach to determine potential candidate substances for the estimation of PMI. After methanol precipitation, the supernatant containing metabolites and the protein pellet were separated and subjected to metabolomic and proteomic analyses using liquid chromatography-tandem mass spectrometry (LC-MS/MS). MS/MS data were analyzed for identification and quantification using Proteome Discoverer and Compound Discoverer software. A total of 573 metabolites and more than 800 porcine proteins were identified in maggots. This is the first dataset of proteins and metabolites in maggots collected from porcine carcasses. In this study, guanosine monophosphate, xanthine, inosine, adenosine, and guanine were detected with a similar tendency to increase during early days of maggot development and then decreased gradually. We broadly profiled various biomolecules through analysis in the spot of incident. Especially, we confirmed that proteome and metabolome profiling could be performed directly and indirectly.
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Fitzpatrick, Garrett, Maryam Rahman, Timothy Garrett, and Jesse Kresak. "MNGI-11. HIGH-GRADE AND LOW-GRADE MENINGIOMAS HARBOR DIFFERING METABOLOMIC PROFILES." Neuro-Oncology 21, Supplement_6 (November 2019): vi141—vi142. http://dx.doi.org/10.1093/neuonc/noz175.593.
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Abstract BACKGROUND Meningiomas are the most common primary brain tumor in adults. While the majority of meningiomas are low-grade and effectively treated by resection alone, there is a subset of tumors that have a high incidence of recurrence, metastatic potential, and morbidity. Radiation has been employed with variable success for high-grade meningiomas. No chemotherapeutic approaches have proven effective against these tumors to date. There is a need for a better understanding of this tumor type in order to provide our patients with better treatment options. OBJECTIVE The purpose of this study is to investigate the metabolomic profile of meningiomas with a focus on comparing low- and high-grade tumors and identifying biologically significant metabolites which could correlate with overall and disease-free survival. METHODS Ten tumor samples of each meningioma grade (WHO grades I-III) were collected from the Florida Center for Brain Tumor Research. Global metabolomic profiling by liquid chromatography mass spectrometry was performed on the frozen tumor samples. Statistical analyses were performed using the Southeast Center for Integrated Metabolomics Galaxy interface. Select metabolites which significantly differed between low-grade (WHO Grade I) and high-grade (WHO grade II-III) were identified using the Human Metabolome Database. RESULTS Differing metabolomic profiles between low-grade and high-grade meningiomas were confirmed by multivariate analysis and demonstrated by unsupervised hierarchical clustering. Notably, lysophospholipid and sphingolipid metabolism was increased in the high-grade tumors, while FAPy-adenine, an oxidized nucleoside which may serve as a tumor marker, was decreased. Guanine was found to be consistently decreased in patients with negative outcomes. CONCLUSIONS High-grade and low-grade meningiomas harbor different metabolomic profiles. The significance of these specific differences requires further investigation.
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Merwin, Nishanth J., Walaa K. Mousa, Chris A. Dejong, Michael A. Skinnider, Michael J. Cannon, Haoxin Li, Keshav Dial, Mathusan Gunabalasingam, Chad Johnston, and Nathan A. Magarvey. "DeepRiPP integrates multiomics data to automate discovery of novel ribosomally synthesized natural products." Proceedings of the National Academy of Sciences 117, no. 1 (December 23, 2019): 371–80. http://dx.doi.org/10.1073/pnas.1901493116.
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Microbial natural products represent a rich resource of evolved chemistry that forms the basis for the majority of pharmacotherapeutics. Ribosomally synthesized and posttranslationally modified peptides (RiPPs) are a particularly interesting class of natural products noted for their unique mode of biosynthesis and biological activities. Analyses of sequenced microbial genomes have revealed an enormous number of biosynthetic loci encoding RiPPs but whose products remain cryptic. In parallel, analyses of bacterial metabolomes typically assign chemical structures to only a minority of detected metabolites. Aligning these 2 disparate sources of data could provide a comprehensive strategy for natural product discovery. Here we present DeepRiPP, an integrated genomic and metabolomic platform that employs machine learning to automate the selective discovery and isolation of novel RiPPs. DeepRiPP includes 3 modules. The first, NLPPrecursor, identifies RiPPs independent of genomic context and neighboring biosynthetic genes. The second module, BARLEY, prioritizes loci that encode novel compounds, while the third, CLAMS, automates the isolation of their corresponding products from complex bacterial extracts. DeepRiPP pinpoints target metabolites using large-scale comparative metabolomics analysis across a database of 10,498 extracts generated from 463 strains. We apply the DeepRiPP platform to expand the landscape of novel RiPPs encoded within sequenced genomes and to discover 3 novel RiPPs, whose structures are exactly as predicted by our platform. By building on advances in machine learning technologies, DeepRiPP integrates genomic and metabolomic data to guide the isolation of novel RiPPs in an automated manner.
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Patti, Gary J., Ralf Tautenhahn, Bryan R. Fonslow, Yonghoon Cho, Adam Deutschbauer, Adam Arkin, Trent Northen, and Gary Siuzdak. "Meta-analysis of global metabolomics and proteomics data to link alterations with phenotype." Spectroscopy 26, no. 3 (2011): 151–54. http://dx.doi.org/10.1155/2011/923017.
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Global metabolomics has emerged as a powerful tool to interrogate cellular biochemistry at the systems level by tracking alterations in the levels of small molecules. One approach to define cellular dynamics with respect to this dysregulation of small molecules has been to consider metabolic flux as a function of time. While flux measurements have proven effective for model organisms, acquiring multiple time points at appropriate temporal intervals for many sample types (e.g., clinical specimens) is challenging. As an alternative, meta-analysis provides another strategy for delineating metabolic cause and effect perturbations. That is, the combination of untargeted metabolomic data from multiple pairwise comparisons enables the association of specific changes in small molecules with unique phenotypic alterations. We recently developed metabolomic software called metaXCMS to automate these types of higher order comparisons. Here we discuss the potential of metaXCMS for analyzing proteomic datasets and highlight the biological value of combining meta-results from both metabolomic and proteomic analyses. The combined meta-analysis has the potential to facilitate efforts in functional genomics and the identification of metabolic disruptions related to disease pathogenesis.
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Cao, M., L. Johnson, R. Johnson, A. Koulman, G. A. Lane, and S. Rasmussen. "joint analyses of transcriptomic and metabolomic data to probe ryegrass-endophyte symbiosis." NZGA: Research and Practice Series 13 (January 1, 2007): 195–98. http://dx.doi.org/10.33584/rps.13.2006.3051.
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Fungal endophytes (Neotyphodium lolii) in perennial ryegrass (Lolium perenne) produce a range of bioactive alkaloids which are implicated in both toxicity to grazing animals and resistance to insects. The understanding of regulatory and biochemical mechanisms of the symbiosis will provide clues for the genetic manipulation of beneficial alkaloid production. This paper presents approaches to analyse data from high-throughput microarray experiments and targeted metabolomic analyses. Combined with bioinformatics analyses, potential genes were found associated with the accumulation of alkaloids and other metabolites. The advantages and limitations of our approach to address the molecular mechanisms of the symbiosis will be discussed. Keywords: Lolium perenne, Neotyphodium lolii, metabolomics, microarray
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Salzer, Liesa, and Michael Witting. "Quo Vadis Caenorhabditis elegans Metabolomics—A Review of Current Methods and Applications to Explore Metabolism in the Nematode." Metabolites 11, no. 5 (April 29, 2021): 284. http://dx.doi.org/10.3390/metabo11050284.
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Metabolomics and lipidomics recently gained interest in the model organism Caenorhabditis elegans (C. elegans). The fast development, easy cultivation and existing forward and reverse genetic tools make the small nematode an ideal organism for metabolic investigations in development, aging, different disease models, infection, or toxicology research. The conducted type of analysis is strongly depending on the biological question and requires different analytical approaches. Metabolomic analyses in C. elegans have been performed using nuclear magnetic resonance (NMR) spectroscopy, direct infusion mass spectrometry (DI-MS), gas-chromatography mass spectrometry (GC-MS) and liquid chromatography mass spectrometry (LC-MS) or combinations of them. In this review we provide general information on the employed techniques and their advantages and disadvantages in regard to C. elegans metabolomics. Additionally, we reviewed different fields of application, e.g., longevity, starvation, aging, development or metabolism of secondary metabolites such as ascarosides or maradolipids. We also summarised applied bioinformatic tools that recently have been used for the evaluation of metabolomics or lipidomics data from C. elegans. Lastly, we curated metabolites and lipids from the reviewed literature, enabling a prototypic collection which serves as basis for a future C. elegans specific metabolome database.
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Stockard, Bradley, Timothy Garrett, Soheil Meshinchi, and Jatinder K. Lamba. "Metabolomic Profiling Defines Distinct Metabolic Signature Associated with FLT3/ITD AML." Blood 128, no. 22 (December 2, 2016): 1692. http://dx.doi.org/10.1182/blood.v128.22.1692.1692.
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Abstract AML is a hematological disorder resulting from proliferation and expansion of malignant myeloid cells. Clinical outcome for AML remains dismal despite intensive therapy in part due to the disease heterogeneity with various cytogenetic and molecular lesions. Fms-Like Tyrosine Kinase-3 (FLT3) is a receptor tyrosine kinase expressed hematopoietic stem/progenitor cells. Activating mutations of FLT3 gene due to internal tandem duplication of the juxtamembrane domain coding sequence (FLT3/ITD) causes autonomous cellular proliferations leading to disease progression. Metabolomic profiling has been successfully utilized to identify metabolic alterations in hematological disorders. However, no studies on metabolic alterations associated with pediatric AML have been reported at this time. In this study we propose to establish the metabolomic landscape in pediatric AML patients and identify differential expression of metabolites based on FLT3/ITD status. Cellular and plasma metabolomics profile was generated from 32 matching diagnostic material from 16 patients with and without FLT3/ITD (N=8 for each cohort and each sample was run in duplicate) treated on COG-AAML0531 study. Global metabolomics profiling was performed on a Thermo Q-Exactive Oribtrap mass spectrometer with Dionex UHPLC and autosampler. All samples were analyzed in duplicate in positive and negative heated electrospray ionization with a mass resolution of 35,000 at m/z 200 as separate injections. Separation was achieved on an ACE 18-pfp 100 x 2.1 mm, 2 µm column with mobile phase A as 0.1% formic acid in water and mobile phase B as acetonitrile. This is a polar embedded stationary phase that provides comprehensive coverage, but does have some limitation is the coverage of very polar species. The flow rate was 350 µL/min with a column temperature of 25¡C. 4 µL was injected for negative ions and 2 µL for positive ions. Statistical analysis was performed using MetaboAnalyst software using all metabolites (known and unknown) as well as only the annotated metabolites. Univariate analysis was performed by volcano plot and Multivariate analysis was performed using PCA, PLS-DA and OPLS-DA. Total of 2966 plasma metabolome (779 negative and 2187 positive) and 1742 (227 negative and 1515 positive) cellular metabolome features were identified. All subsequent data analyses were normalized to the sum of metabolites for each sample. Comparison of the cellular metabolome in patients with and without FLT3/ITD identified 12 known and 135 unknown metabolites that were significantly different between two cohorts (p<0.05). Similar comparison of the plasma metabolome identified19 known and 300 unknown metabolites in the patient with and without FLT3/ITD (top results are shown in Fig.1). Orthogonal partial least squares-discriminant analysis (OPLS-DA) showed clear separation between the 2 groups (Fig.2). Some of the top known plasma metabolites (p<0.01) differentiating patients by FLT3 status include guanine, pyrimidine-2-3dicarboxylate, acetylglycine, acetyl-L-alanine, aminobutonate gaba, L-carnitine, methyl-2 oxovaleric acid, asparagine, acetyl arginine, Hydroxydecanoic acid, cysteic acid and glycocholic acid. Within leukemic cells top metabolites differentiating between FLT3 status included actyly carnitine, adenosine monophosphate, hypoxanthine, diaminohepatanedioate, guanine and sphingosine. Metaboanalyst Pathway analysis module mapped the differentiating metabolites to aminoacyl-tRNA biosynthesis, Glycerophospholipid metabolism, Cysteine and methionine metabolism, Pantothenate and CoA biosynthesis, Purine metabolism. This pilot study defines distinct metabolomics signature associated with genomic subtype of AML (FLT3/ITD). As metabolomics provides an insight into the ultimate metabolic destination of normal and malignant hematopoiesis, it has a potential to provide a unique insight into the altered metabolic pathways in AML and identify pathways and networks that might be shared by varied genomic subtypes of AML. Such data can help merge rare genomic variants based on shared metabolic signatures and more appropriately guide directed therapies. Disclosures No relevant conflicts of interest to declare.
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Solanki, Hiren, Manon Pierdet, Olivier P. Thomas, and Mayalen Zubia. "Insights into the Metabolome of the Cyanobacterium Leibleinia gracilis from the Lagoon of Tahiti and First Inspection of Its Variability." Metabolites 10, no. 5 (May 24, 2020): 215. http://dx.doi.org/10.3390/metabo10050215.
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Cyanobacteria are known to produce a large diversity of specialized metabolites that can cause severe (eco)toxicological effects. In the lagoon of Tahiti, the benthic cyanobacterium Leibleinia gracilis is commonly found overgrowing the proliferative macroalga Turbinaria ornata or dead branching corals. The specialized metabolome of the cyanobacterium L. gracilis was therefore investigated together with its variability on both substrates and changes in environmental parameters. For the study of the metabolome variability, replicates of L. gracilis were collected in the same location of the lagoon of Tahiti before and after a raining event, both on dead corals and on T. ornata. The variability in the metabolome was inferred from a comparative non-targeted metabolomic using high resolution mass spectrometry (MS) data and a molecular network analysis built through MS/MS analyses. Oxidized fatty acid derivatives including the unusual 11-oxopalmitelaidic acid were found as major constituents of the specialized metabolome of this species. Significant variations in the metabolome of the cyanobacteria were observed, being more important with a change in environmental factors. Erucamide was found to be the main chemical marker highly present when the cyanobacterium grows on the macroalga. This study highlights the importance of combined approaches in metabolomics and molecular networks to inspect the variability in the metabolome of cyanobacteria with applications for ecological questions.
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Philbin, Casey S., Matthew Paulsen, and Lora A. Richards. "Opposing Effects of Ceanothus velutinus Phytochemistry on Herbivore Communities at Multiple Scales." Metabolites 11, no. 6 (June 7, 2021): 361. http://dx.doi.org/10.3390/metabo11060361.
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Identifying the interactions of functional, biotic, and abiotic factors that define plant–insect communities has long been a goal of community ecologists. Metabolomics approaches facilitate a broader understanding of how phytochemistry mediates the functional interactions among ecological factors. Ceanothus velutinus communities are a relatively unstudied system for investigating chemically mediated interactions. Ceanothus are nitrogen-fixing, fire-adapted plants that establish early post-fire, and produce antimicrobial cyclic peptides, linear peptides, and flavonoids. This study takes a metabolomic approach to understanding how the diversity and variation of C. velutinus phytochemistry influences associated herbivore and parasitoid communities at multiple spatiotemporal scales. Herbivores and foliar samples were collected over three collection times at two sites on the east slope of the Sierra Nevada Mountain range. Foliar tissue was subjected to LC-MS metabolomic analysis, and several novel statistical analyses were applied to summarize, quantify, and annotate variation in the C. velutinus metabolome. We found that phytochemistry played an important role in plant–insect community structure across an elevational gradient. Flavonoids were found to mediate biotic and abiotic influences on herbivores and associated parasitoids, while foliar oligopeptides played a significant positive role in herbivore abundance, even more than abundance of host plants and leaf abundance. The importance of nutritional and defense chemistry in mediating ecological interactions in C. velutinus plant–herbivore communities was established, justifying larger scale studies of this plant system that incorporate other mediators of phytochemistry such as genetic and metageomic contributions.
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Suissa, Laurent, Jean-Marie Guigonis, Fanny Graslin, Emmanuelle Robinet-Borgomano, Yves Chau, Jacques Sedat, Sabine Lindenthal, and Thierry Pourcher. "Combined Omic Analyzes of Cerebral Thrombi: A New Molecular Approach to Identify Cardioembolic Stroke Origin." Stroke 52, no. 9 (September 2021): 2892–901. http://dx.doi.org/10.1161/strokeaha.120.032129.
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Background and Purpose: The diagnosis of cardioembolic stroke can be challenging for patient management in secondary stroke prevention, particularly in the case of covert paroxysmal atrial fibrillation. The molecular composition of a cerebral thrombus is related to its origin. Therefore, proteomic and metabolomic analyses of the retrieved thrombotic material should allow the identification of biomarkers or signatures to improve the etiological diagnosis of stroke. Methods: In this pilot study, the proteome and metabolome of cerebral thrombi from atherothrombotic and cardioembolic stroke patients were studied according to ASCOD phenotyping (A: atherosclerosis; S: small-vessel disease; C: cardiac pathology; O: other causes; D: dissection), with the highest causality grade, from the ThrombiOMIC cohort (consecutive patients with stroke recanalized by mechanical thrombectomy in an acute phase). Proteomic and metabolomic results were used separately or combined, and the obtained omic signatures were compared with classical cardioembolic stroke predictors using pairwise comparisons of the area under receiver operating characteristics. Results: Among 59 patients of the ThrombiOMIC cohort, 34 patients with stroke showed a cardioembolic phenotype and 7 had an atherothrombotic phenotype. Two thousand four hundred fifty-six proteins and 5019 molecular features of the cerebral thrombi were identified using untargeted proteomic and metabolomic approaches, respectively. Area under receiver operating characteristics to predict the cardioembolic origin of stroke were calculated using the proteomic results (0.945 [95% CI, 0.871–1]), the metabolomic results (0.836 [95% CI, 0.714–0.958]), and combined signatures (0.996 [95% CI, 0.984–1]). The diagnostic performance of the combined signatures was significantly higher than that of classical predictors such as the plasmatic BNP (B-type natriuretic peptide) level (area under receiver operating characteristics, 0.803 [95% CI, 0.629–0.976]). Conclusions: The combined proteomic and metabolomic analyses of retrieved cerebral thrombi is a very promising molecular approach to predict the cardioembolic cause of stroke and to improve secondary stroke prevention strategies.
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Aliakbari, Amir, Alireza Ehsani, Rasoul Vaez Torshizi, Peter Løvendahl, Hadi Esfandyari, Just Jensen, and Pernille Sarup. "Genetic variance of metabolomic features and their relationship with body weight and body weight gain in Holstein cattle1." Journal of Animal Science 97, no. 9 (July 5, 2019): 3832–44. http://dx.doi.org/10.1093/jas/skz228.
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Abstract In recent years, metabolomics has been used to clarify the biology underlying biological samples. In the field of animal breeding, investigating the magnitude of genetic control on the metabolomic profiles of animals and their relationships with quantitative traits adds valuable information to animal improvement schemes. In this study, we analyzed metabolomic features (MFs) extracted from the metabolomic profiles of 843 male Holstein calves. The metabolomic profiles were obtained using nuclear magnetic resonance (NMR) spectroscopy. We investigated 2 alternative methods to control for peak shifts in the NMR spectra, binning and aligning, to determine which approach was the most efficient for assessing genetic variance. Series of univariate analyses were implemented to elucidate the heritability of each MF. Furthermore, records on BW and ADG from 154 to 294 d of age (ADG154–294), 294 to 336 d of age (ADG294–336), and 154 to 336 d of age (ADG154–336) were used in a series of bivariate analyses to establish the genetic and phenotypic correlations with MFs. Bivariate analyses were only performed for MFs that had a heritability significantly different from zero. The heritabilities obtained in the univariate analyses for the MFs in the binned data set were low (<0.2). In contrast, in the aligned data set, we obtained moderate heritability (0.2 to 0.5) for 3.5% of MFs and high heritability (more than 0.5) for 1% of MFs. The bivariate analyses showed that ~12%, ~3%, ~9%, and ~9% of MFs had significant additive genetic correlations with BW, ADG154–294, ADG294–336, and ADG154–336, respectively. In all of the bivariate analyses, the percentage of significant additive genetic correlations was higher than the percentage of significant phenotypic correlations of the corresponding trait. Our results provided insights into the influence of the underlying genetic mechanisms on MFs. Further investigations in this field are needed for better understanding of the genetic relationship among the MFs and quantitative traits.
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Furukawa, Hiroshi, Shomi Oka, Kota Shimada, Atsushi Hashimoto, Akiko Komiya, Toshihiro Matsui, Naoshi Fukui, and Shigeto Tohma. "Serum Metabolomic Profiles of Rheumatoid Arthritis Patients With Acute-Onset Diffuse Interstitial Lung Disease." Biomarker Insights 14 (January 2019): 117727191987047. http://dx.doi.org/10.1177/1177271919870472.
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Objective: Acute-onset diffuse interstitial lung disease (AoDILD) includes acute exacerbation of interstitial lung disease (ILD), drug-induced ILD, and Pneumocystis pneumonia, and frequently occurs in patients with rheumatoid arthritis (RA). Since AoDILD causes a poor prognosis in RA, biomarkers for AoDILD were eagerly desired. Metabolomic analyses were extensively performed in cancer patients and successfully generated better diagnostic biomarkers. In the present study, serum metabolomic profiles of AoDILD in RA were investigated to generate better potential metabolomic biomarkers. Methods: Serum samples of 10 RA patients with AoDILD were collected on admission and in a stable state, more than 3 months before the admission. Serum metabolomic analyses were conducted on the samples from these RA patients with AoDILD. Results: Apparently distinct serum metabolomic profiles in AoDILD were not observed in univariate or hierarchical cluster analyses. Partial least squares-discriminant analysis (PLS-DA) was performed to select candidate metabolites based on variable importance in projection (VIP) scores. The PLS-DA model generated from the four metabolites with VIP scores more than 2.25 (mannosamine, alliin, kynurenine, and 2-hydroxybutyric acid) could successfully discriminate AoDILD from the stable condition (area under the curve: 0.962, 95% confidence interval: 0.778–1.000). Conclusion: It was demonstrated that metabolomic profiling was useful to generate better biomarkers in AoDILD.
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Du, Fuyong, Anthony Virtue, Hong Wang, and Xiao-Feng Yang. "Metabolomic analyses for atherosclerosis, diabetes, and obesity." Biomarker Research 1, no. 1 (2013): 17. http://dx.doi.org/10.1186/2050-7771-1-17.
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Chu, Ching Yan, Xin Xiao, Xiao Guang Zhou, Tze Kin Lau, Michael Scott Rogers, Tai Fai Fok, Lap Kay Law, Chi Pui Pang, and Chi Chiu Wang. "Metabolomic and bioinformatic analyses in asphyxiated neonates." Clinical Biochemistry 39, no. 3 (March 2006): 203–9. http://dx.doi.org/10.1016/j.clinbiochem.2006.01.006.
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Guillamón, J., A. S. Prudencio, J. E. Yuste, F. Dicenta, and R. Sánchez-Pérez. "Dormancy release in almond by metabolomic analyses." Acta Horticulturae, no. 1307 (March 2021): 343–50. http://dx.doi.org/10.17660/actahortic.2021.1307.53.
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Jiang, Baoping, Liang Le, Wenting Wan, Wei Zhai, Keping Hu, Lijia Xu, and Peigen Xiao. "The Flower Tea Coreopsis tinctoria Increases Insulin Sensitivity and Regulates Hepatic Metabolism in Rats Fed a High-Fat Diet." Endocrinology 156, no. 6 (June 1, 2015): 2006–18. http://dx.doi.org/10.1210/en.2015-1015.
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AbstractAn infusion of Coreopsis tinctoria (CT) flowering tops is traditionally used in Portugal to control hyperglycemia; however, the effects of CT protection against high-fat diet (HFD)-induced hepatic insulin resistance have not been systematically studied and the precise mechanism of action is not clear. The metabolomic profiles of insulin-resistant rats fed a HFD and a CT-supplemented diet (HFD supplemented with CT drinking) for 8 weeks were investigated. Serum samples for clinical biochemistry and liver samples for histopathology and liquid chromatography-mass spectrometry-based metabolomic research were collected. Western blot and quantitative real-time PCR analyses were further used to measure the expression of several relevant enzymes together with perturbed metabolic pathways. Using analysis software, the CT treatment was found to significantly ameliorate the disturbance in 10 metabolic pathways. Combined metabolomic, Western blot, and quantitative real-time PCR analyses revealed that CT treatment significantly improved the glucose homeostasis by, on the one hand, through inhibiting the expression of gluconeogenic pathway key proteins glucose-6-phosphatase and phosphoenolpyruvate carboxykinase and, on the other hand, via regulating the mRNA or protein levels of the Krebs cycle critical enzymes (citrate synthase, succinate dehydrogenase complex, subunit A, flavoprotein, and dihydrolipoamide S-succinyltransferase). These results provide metabolic evidence of the complex pathogenic mechanism involved in hepatic insulin resistance and that the supplementation with CT improves insulin resistance at a global scale. Liquid chromatography-mass spectrometry-based metabolomics approaches are helpful to further understand diabetes-related mechanisms.
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Lette, Emily D., Nathan G. Lawler, Quinton F. Burnham, Mary C. Boyce, Rodney Duffy, Annette Koenders, and David I. Broadhurst. "Metabolomic profiling of crayfish haemolymph distinguishes sister species and sex: implications for conservation, aquaculture and physiological studies." Freshwater Crayfish 25, no. 1 (April 15, 2020): 89–101. http://dx.doi.org/10.5869/fc.2020.v25-1.089.
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Abstract Hairy marron (Cherax tenuimanus Smith) are critically endangered freshwater crayfish found only in a single river in south-west Australia. Conservation efforts have included a captive breeding program, which has been largely unsuccessful, despite the closely related smooth marron (Cherax cainii Austin) being successfully bred for aquaculture. Using an untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomic approach we created a profile of the metabolites in the haemolymph for males and females of the two species of marron. A non-lethal method was used to collect haemolymph and 84 reproducible annotated metabolites were identified. Variation in the levels of some metabolites were detected between species and between sexes within species. Multivariate analyses clearly differentiated the congeneric species and univariate analyses identified differences between species, sex and for some metabolite interactions between species and sex. This study created a baseline metabolome dataset for the two species and began to investigate the biological significance of metabolites that varied between species. We have shown metabolomics could be used for targeted studies to potentially assist reproductive success. This approach will be beneficial for conservation and aquaculture practices with potential applications for other aquatic taxa worldwide.
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Lazcano-Ramírez, Hugo Gerardo, Roberto Gamboa-Becerra, Irving J. García-López, Ricardo A. Chávez Montes, David Díaz-Ramírez, Octavio Martínez de la Vega, José Juan Ordaz-Ortíz, et al. "Effects of the Developmental Regulator BOLITA on the Plant Metabolome." Genes 12, no. 7 (June 29, 2021): 995. http://dx.doi.org/10.3390/genes12070995.
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Transcription factors are important regulators of gene expression. They can orchestrate the activation or repression of hundreds or thousands of genes and control diverse processes in a coordinated way. This work explores the effect of a master regulator of plant development, BOLITA (BOL), in plant metabolism, with a special focus on specialized metabolism. For this, we used an Arabidopsis thaliana line in which the transcription factor activity can be induced. Fingerprinting metabolomic analyses of whole plantlets were performed at different times after induction. After 96 h, all induced replicas clustered as a single group, in contrast with all controls which did not cluster. Metabolomic analyses of shoot and root tissues enabled the putative identification of differentially accumulated metabolites in each tissue. Finally, the analysis of global gene expression in induced vs. non-induced root samples, together with enrichment analyses, allowed the identification of enriched metabolic pathways among the differentially expressed genes and accumulated metabolites after the induction. We concluded that the induction of BOL activity can modify the Arabidopsis metabolome. Future work should investigate whether its action is direct or indirect, and the implications of the metabolic changes for development regulation and bioprospection.
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Pann, Patrick, Martin Hrabě de Angelis, Cornelia Prehn, and Jerzy Adamski. "Mouse Age Matters: How Age Affects the Murine Plasma Metabolome." Metabolites 10, no. 11 (November 19, 2020): 472. http://dx.doi.org/10.3390/metabo10110472.
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A large part of metabolomics research relies on experiments involving mouse models, which are usually 6 to 20 weeks of age. However, in this age range mice undergo dramatic developmental changes. Even small age differences may lead to different metabolomes, which in turn could increase inter-sample variability and impair the reproducibility and comparability of metabolomics results. In order to learn more about the variability of the murine plasma metabolome, we analyzed male and female C57BL/6J, C57BL/6NTac, 129S1/SvImJ, and C3HeB/FeJ mice at 6, 10, 14, and 20 weeks of age, using targeted metabolomics (BIOCRATES AbsoluteIDQ™ p150 Kit). Our analysis revealed high variability of the murine plasma metabolome during adolescence and early adulthood. A general age range with minimal variability, and thus a stable metabolome, could not be identified. Age-related metabolomic changes as well as the metabolite profiles at specific ages differed markedly between mouse strains. This observation illustrates the fact that the developmental timing in mice is strain specific. We therefore stress the importance of deliberate strain choice, as well as consistency and precise documentation of animal age, in metabolomics studies.
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Yuan, Pingli, Nan He, Muhammad Jawad Umer, Shengjie Zhao, Weinan Diao, Hongju Zhu, Junling Dou, et al. "Comparative Metabolomic Profiling of Citrullus spp. Fruits Provides Evidence for Metabolomic Divergence during Domestication." Metabolites 11, no. 2 (January 28, 2021): 78. http://dx.doi.org/10.3390/metabo11020078.
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Watermelon (Citrullus lanatus) is one of the most nutritional fruits that is widely distributed in the whole world. The nutritional compositions are mainly influenced by the genotype and environment. However, the metabolomics of different domestication status and different flesh colors watermelon types is not fully understood. In this study, we reported an extensive assessment of metabolomic divergence in the fruit flesh among Citrullus sp. and within Citrullus sp. We demonstrate that metabolic profiling was significantly different between the wild and cultivated watermelons, the apigenin 6-C-glucoside, luteolin 6-C-glucoside, chrysoeriol C-hexoside, naringenin C-hexoside, C-pentosyl-chrysoeriol O-hexoside, and sucrose are the main divergent metabolites. Correlation analysis results revealed that flavonoids were present in one tight metabolite cluster. The main divergent metabolites in different flesh-colored cultivated watermelon fruits are p-coumaric acid, 2,3-dihydroflavone, catechin, N-(3-indolylacetyl)-l-alanine, 3,4-dihydroxycinnamic acid, and pelargonidin o-hexoside. A total of 431 differentially accumulated metabolites were identified from pairwise comparative analyses. C. lanatus edible-seed watermelon (cultivars) and C. mucosospermus (wild) have similar fruit metabolic profiles and phenotypic traits, indicating that edible-seed watermelon may be a relative of wild species and a relatively primitive differentiation type of cultivated watermelon. Our data provide extensive knowledge for metabolomics-based watermelon improvement of Citrullus fruits meet their enhanced nutritive properties or upgraded germplasm utility values.
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Zeng, Huawei, Shahid Umar, Zhenhua Liu, and Michael R. Bukowski. "Azoxymethane Alters the Plasma Metabolome to a Greater Extent in Mice Fed a High-Fat Diet Compared to an AIN-93 Diet." Metabolites 11, no. 7 (July 9, 2021): 448. http://dx.doi.org/10.3390/metabo11070448.
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Consumption of a high-fat diet (HFD) links obesity to colon cancer in humans. Our data show that a HFD (45% energy fat versus 16% energy fat in an AIN-93 diet (AIN)) promotes azoxymethane (AOM)-induced colonic aberrant crypt foci (ACF) formation in a mouse cancer model. However, the underlying metabolic basis remains to be determined. In the present study, we hypothesize that AOM treatment results in different plasma metabolomic responses in diet-induced obese mice. An untargeted metabolomic analysis was performed on the plasma samples by gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). We found that 53 of 144 identified metabolites were different between the 4 groups of mice (AIN, AIN + AOM, HFD, HFD + AOM), and sparse partial least-squares discriminant analysis showed a separation between the HFD and HFD + AOM groups but not the AIN and AIN + AOM groups. Moreover, the concentrations of dihydrocholesterol and cholesterol were inversely associated with AOM-induced colonic ACF formation. Functional pathway analyses indicated that diets and AOM-induced colonic ACF modulated five metabolic pathways. Collectively, in addition to differential plasma metabolomic responses, AOM treatment decreases dihydrocholesterol and cholesterol levels and alters the composition of plasma metabolome to a greater extent in mice fed a HFD compared to the AIN.
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Chatterjee, Ranee, Clemontina Davenport, Lydia Kwee, David D'Alessio, Laura Svetkey, Pao-Hwa Lin, Cris Slentz, et al. "Effects of Potassium Chloride on a Metabolomic Path to Cardiovascular Disease and Diabetes." Current Developments in Nutrition 4, Supplement_2 (May 29, 2020): 1784. http://dx.doi.org/10.1093/cdn/nzaa067_011.
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Abstract Objectives Metabolomic profiling is used to identify biological pathways and biomarkers for cardiovascular disease (CVD) and diabetes. Thus, metabolomics could be used to identify metabolic effects and demonstrate short-term efficacy of interventions designed to reduce longer-term risk of these conditions. Low potassium (K) intake has been linked to high blood pressure and increased CVD and diabetes risk. The effects of increasing K intake on metabolomic measures related to CVD and diabetes risk are not known. In this ancillary study, we tested the hypothesis that potassium chloride (KCl) supplementation would be associated with improvements in metabolomic biomarkers, such as branched-chain amino acids (BCAA) which are associated with CVD and diabetes risk. Methods We performed targeted mass-spectrometry-based metabolomic profiling of 60 metabolites on baseline and 12-week (end-of-study) plasma samples from 26 African-American participants with prediabetes randomized to KCl supplements vs. placebo. Principal component analysis (PCA) was used for dimensionality reduction. Univariate and multivariable analyses were used to assess differences between the two intervention arms in the changes in metabolomic factor scores and individual metabolites. Results In univariate comparisons, compared to placebo, a PCA factor composed of long-chain acylcarnitines (LCA) increased in the KCl arm (P = 0.02). In multivariable models adjusted for baseline factor score, age, and sex, this association with the LCA factor was no longer significant; but those taking KCl had significant reductions in the BCAA factor (P = 0.004) and in valine levels (P = 0.02). Conclusions These results suggest that KCl supplementation may be associated with improvements in BCAA metabolism. Further studies among a larger population and with longer-term follow-up are warranted to verify these results and to determine if KCl supplementation may be an effective intervention for CVD and diabetes prevention. Funding Sources NIH/Duke CTSA.
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Bagheri, Minoo, Walter Willett, Mary K. Townsend, Peter Kraft, Kerry L. Ivey, Eric B. Rimm, Kathryn Marie Wilson, et al. "A lipid-related metabolomic pattern of diet quality." American Journal of Clinical Nutrition 112, no. 6 (September 16, 2020): 1613–30. http://dx.doi.org/10.1093/ajcn/nqaa242.
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ABSTRACT Background Adherence to a healthy diet has been associated with reduced risk of chronic diseases. Identifying nutritional biomarkers of diet quality may be complementary to traditional questionnaire-based methods and may provide insights concerning disease mechanisms and prevention. Objective To identify metabolites associated with diet quality assessed via the Alternate Healthy Eating Index (AHEI) and its components. Methods This cross-sectional study used FFQ data and plasma metabolomic profiles, mostly lipid related, from the Nurses’ Health Study (NHS, n = 1460) and Health Professionals Follow-up Study (HPFS, n = 1051). Linear regression models assessed associations of the AHEI and its components with individual metabolites. Canonical correspondence analyses (CCAs) investigated overlapping patterns between AHEI components and metabolites. Principal component analysis (PCA) and explanatory factor analysis were used to consolidate correlated metabolites into uncorrelated factors. We used stepwise multivariable regression to create a metabolomic score that is an indicator of diet quality. Results The AHEI was associated with 83 metabolites in the NHS and 96 metabolites in the HPFS after false discovery rate adjustment. Sixty-three of these significant metabolites overlapped between the 2 cohorts. CCA identified “healthy” AHEI components (e.g., nuts, whole grains) and metabolites (n = 27 in the NHS and 33 in the HPFS) and “unhealthy” AHEI components (e.g., red meat, trans fat) and metabolites (n = 56 in the NHS and 63 in the HPFS). PCA-derived factors composed of highly saturated triglycerides, plasmalogens, and acylcarnitines were associated with unhealthy AHEI components while factors composed of highly unsaturated triglycerides were linked to healthy AHEI components. The stepwise regression analysis contributed to a metabolomics score as a predictor of diet quality. Conclusion We identified metabolites associated with healthy and unhealthy eating behaviors. The observed associations were largely similar between men and women, suggesting that metabolomics can be a complementary approach to self-reported diet in studies of diet and chronic disease.
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Creek, Darren J., Brunda Nijagal, Dong-Hyun Kim, Federico Rojas, Keith R. Matthews, and Michael P. Barrett. "Metabolomics Guides Rational Development of a Simplified Cell Culture Medium for Drug Screening against Trypanosoma brucei." Antimicrobial Agents and Chemotherapy 57, no. 6 (April 9, 2013): 2768–79. http://dx.doi.org/10.1128/aac.00044-13.
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ABSTRACTIn vitroculture methods underpin many experimental approaches to biology and drug discovery. The modification of established cell culture methods to make them more biologically relevant or to optimize growth is traditionally a laborious task. Emerging metabolomic technology enables the rapid evaluation of intra- and extracellular metabolites and can be applied to the rational development of cell culture media. In this study, untargeted semiquantitative and targeted quantitative metabolomic analyses of fresh and spent media revealed the major nutritional requirements for the growth of bloodstream formTrypanosoma brucei. The standard culture medium (HMI11) contained unnecessarily high concentrations of 32 nutrients that were subsequently removed to make the concentrations more closely resemble those normally found in blood. Our new medium, Creek's minimal medium (CMM), supportsin vitrogrowth equivalent to that in HMI11 and causes no significant perturbation of metabolite levels for 94% of the detected metabolome (<3-fold change; α = 0.05). Importantly, improved sensitivity was observed for drug activity studies in whole-cell phenotypic screenings and in the metabolomic mode of action assays. Four-hundred-fold 50% inhibitory concentration decreases were observed for pentamidine and methotrexate, suggesting inhibition of activity by nutrients present in HMI11. CMM is suitable for routine cell culture and offers important advantages for metabolomic studies and drug activity screening.
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Wang, Yiru, Junli Zhang, Minghao Sun, Cheng He, Ke Yu, Bing Zhao, Rui Li, et al. "Multi-Omics Analyses Reveal Systemic Insights into Maize Vivipary." Plants 10, no. 11 (November 12, 2021): 2437. http://dx.doi.org/10.3390/plants10112437.
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Maize vivipary, precocious seed germination on the ear, affects yield and seed quality. The application of multi-omics approaches, such as transcriptomics or metabolomics, to classic vivipary mutants can potentially reveal the underlying mechanism. Seven maize vivipary mutants were selected for transcriptomic and metabolomic analyses. A suite of transporters and transcription factors were found to be upregulated in all mutants, indicating that their functions are required during seed germination. Moreover, vivipary mutants exhibited a uniform expression pattern of genes related to abscisic acid (ABA) biosynthesis, gibberellin (GA) biosynthesis, and ABA core signaling. NCED4 (Zm00001d007876), which is involved in ABA biosynthesis, was markedly downregulated and GA3ox (Zm00001d039634) was upregulated in all vivipary mutants, indicating antagonism between these two phytohormones. The ABA core signaling components (PYL-ABI1-SnRK2-ABI3) were affected in most of the mutants, but the expression of these genes was not significantly different between the vp8 mutant and wild-type seeds. Metabolomics analysis integrated with co-expression network analysis identified unique metabolites, their corresponding pathways, and the gene networks affected by each individual mutation. Collectively, our multi-omics analyses characterized the transcriptional and metabolic landscape during vivipary, providing a valuable resource for improving seed quality.
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Jiang, Huijuan, Xiaoyu Zhao, Mengtong Zang, Rong Fu, Zonghong Shao, and Chunyan Liu. "Gut Microbiome and Plasma Metabolomic Analysis in Patients with Myelodysplastic Syndrome." Oxidative Medicine and Cellular Longevity 2022 (May 9, 2022): 1–21. http://dx.doi.org/10.1155/2022/1482811.
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Myelodysplastic syndrome (MDS) is a heterogeneous group of clonal hematopoietic stem cell disorders. Studies have shown the involvement of an abnormal immune system in MDS pathogenesis. The gut microbiota are known to influence host immunity and metabolism, thereby contributing to the development of hematopoietic diseases. In this study, we performed gut microbiome and plasma metabolomic analyses in patients with MDS and healthy controls. We found that patients with MDS had a different gut microbial composition compared to controls. The gut microbiota in MDS patients showed a continuous evolutionary relationship from the phylum to the species level. At the species level, the abundance of Haemophilus parainfluenzae, Streptococcus luteciae, Clostridium citroniae, and Gemmiger formicilis increased, while that of Prevotella copri decreased in MDS patients compared to controls. Moreover, abundance of bacterial genera correlated with the percentage of lymphocyte subsets in patients with MDS. Metabolomic analysis showed that the concentrations of hypoxanthine and pyroglutamic acid were increased, while that of 3a,7a-dihydroxy-5b-cholestan was decreased in MDS patients compared to controls. In conclusion, gut microbiome and plasma metabolomics are altered in patients with MDS, which may be involved in the immunopathogenesis of the disease.
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Krisher, Rebecca L., Adam L. Heuberger, Melissa Paczkowski, John Stevens, Courtney Pospisil, Randall S. Prather, Roger G. Sturmey, Jason R. Herrick, and William B. Schoolcraft. "Applying metabolomic analyses to the practice of embryology: physiology, development and assisted reproductive technology." Reproduction, Fertility and Development 27, no. 4 (2015): 602. http://dx.doi.org/10.1071/rd14359.
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The advent of metabolomics technology and its application to small samples has allowed us to non-invasively monitor the metabolic activity of embryos in a complex culture environment. The aim of this study was to apply metabolomics technology to the analysis of individual embryos from several species during in vitro development to gain an insight into the metabolomics pathways used by embryos and their relationship with embryo quality. Alanine is produced by both in vivo- and in vitro-derived human, murine, bovine and porcine embryos. Glutamine is also produced by the embryos of these four species, but only those produced in vitro. Across species, blastocysts significantly consumed amino acids from the culture medium, whereas glucose was not significantly taken up. There are significant differences in the metabolic profile of in vivo- compared with in vitro-produced embryos at the blastocyst stage. For example, in vitro-produced murine embryos consume arginine, asparagine, glutamate and proline, whereas in vivo-produced embryos do not. Human embryos produce more alanine, glutamate and glutamine, and consume less pyruvate, at the blastocyst compared with cleavage stages. Glucose was consumed by human blastocysts, but not at a high enough level to reach significance. Consumption of tyrosine by cleavage stage human embryos is indicative of blastocyst development, although tyrosine consumption is not predictive of blastocyst quality. Similarly, although in vivo-produced murine blastocysts consumed less aspartate, lactate, taurine and tyrosine than those produced in vitro, consumption of these four amino acids by in vitro-derived embryos with high octamer-binding transcription factor 4 (Oct4) expression, indicative of high quality, did not differ from those with low Oct4 expression. Further application of metabolomic technologies to studies of the consumption and/or production of metabolites from individual embryos in a complete culture medium could transform our understanding of embryo physiology and improve our ability to produce developmentally competent embryos in vitro.
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Santacruz, Liliana, Olivier Thomas, Carmenza Duque, Mónica Puyana, and Edisson Tello. "Comparative Analyses of Metabolomic Fingerprints and Cytotoxic Activities of Soft Corals from the Colombian Caribbean." Marine Drugs 17, no. 1 (January 9, 2019): 37. http://dx.doi.org/10.3390/md17010037.
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Soft corals (Cnidaria, Anthozoa, Octocorallia) are a diverse group of marine invertebrates that inhabit various marine environments in tropical and subtropical areas. Several species are recognized as prolific sources of compounds with a wide array of biological activities. Recent advances in analytical techniques, supported by robust statistical analyses, have allowed the analysis and characterization of the metabolome present in a single living organism. In this study, a liquid chromatography-high resolution mass spectrometry metabolomic approach was applied to analyze the metabolite composition of 28 soft corals present in the Caribbean coast of Colombia. Multivariate data analysis was used to correlate the chemical fingerprints of soft corals with their cytotoxic activity against tumor cell lines for anticancer purpose. Some diterpenoids were identified as specific markers to discriminate between cytotoxic and non-cytotoxic crude extracts of soft corals against tumor cell lines. In the models generated from the comparative analysis of PLS-DA for tumor lines, A549 and SiHa, the diterpene 13-keto-1,11-dolabell-3(E),7(E),12(18)-triene yielded a high score in the variable importance in projection. These results highlight the potential of metabolomic approaches towards the identification of cytotoxic agents against cancer of marine origin. This workflow can be useful in several studies, mainly those that are time consuming, such as traditional bioprospecting of marine natural products.
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Cosmi, Erich, Silvia Visentin, Donata Favretto, Marianna Tucci, Eugenio Ragazzi, Guido Viel, and Santo Davide Ferrara. "Selective Intrauterine Growth Restriction in Monochorionic Twin Pregnancies: Markers of Endothelial Damage and Metabolomic Profile." Twin Research and Human Genetics 16, no. 4 (May 23, 2013): 816–26. http://dx.doi.org/10.1017/thg.2013.33.
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The aim of this study was to assess the aorta–intima thickness (aIT) and serum metabolomic profile in selective intrauterine growth-restricted (sIUGR) monochorionic diamniotic (MCDA) twin fetuses presenting Doppler velocimetry alterations. Fetal abdominal aIT was measured by ultrasound at 32 weeks of gestation, enrolling 24 MCDA twin fetuses (8 sIUGR and 16 controls). sIUGR twin fetuses were classified into two groups: Group 1 consisted of sIUGR with abnormal umbilical artery (UA) Doppler waveforms and Group 2 included sIUGR with normal UA Doppler. Group 3 were control fetuses appropriate for gestational age (AGA). Fetal blood samples were obtained from the umbilical vein immediately after fetal extraction. A non-targeted metabolomic profiling investigated fetal metabolism alterations by using liquid chromatography–high-resolution mass spectrometry (LC-HRMS). Median fetal aIT was significantly larger in Group 1 (median value = 0.9 mm; range = 0.8–1.0 mm; p < .002) and Group 2 (median value = 0.8 mm; range = 0.7–0.8 mm; p < .002) than in AGA Group 3 (median value = 0.5 mm; range = 0.4–0.6 mm; p < .002). Metabolomic analyses, performed on four sIUGR cases (Group 1) compared with four AGA co-twins, showed an upregulation of phenylalanine, sphingosine, glycerophosphocholine, and choline, and a downregulation of valine, tryptophan, isoleucine, and proline sIUGR Group 1 compared with AGA. Although for metabolomics data only a statistical tendency (and not a statistical significance) was reached due to the small sample size, we believe that our results represent a valid starting point for further in-depth metabolomic and proteomic investigations of sIUGR in MCDA fetuses.
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Galati, Gianni, Anthony Gandin, Yves Jolivet, Romain Larbat, and Alain Hehn. "Untargeted Metabolomics Approach Reveals Diverse Responses of Pastinaca Sativa to Ozone and Wounding Stresses." Metabolites 9, no. 7 (July 23, 2019): 153. http://dx.doi.org/10.3390/metabo9070153.
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Stresses such as wounding or atmospheric pollutant exposure have a significant impact on plant fitness. Since it has been widely described that the metabolome directly reflects plant physiological status, a way to assess this impact is to perform a global metabolomic analysis. In this study, we investigated the effect of two abiotic stresses (mechanical wounding and ozone exposure) on parsnip metabolic balance using a liquid chromatography-mass spectrometry-based untargeted metabolomic approach. For this purpose, parsnip leaves were submitted to an acute ozone exposure or were mechanically wounded and sampled 24, 48, and 72 h post-treatment. Multivariate and univariate statistical analyses highlighted numerous differentially-accumulated metabolic features as a function of time and treatment. Mechanical wounding led to a more differentiated response than ozone exposure. We found that the levels of coumarins and fatty acyls increased in wounded leaves, while flavonoid concentration decreased in the same conditions. These results provide an overview of metabolic destabilization through differentially-accumulated compounds and provide a better understanding of global plant metabolic changes in defense mechanisms.
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Torrez Lamberti, Monica F., Evon DeBose-Scarlett, Timothy Garret, Leslie Ann Parker, Josef Neu, and Graciela L. Lorca. "Metabolomic Profile of Personalized Donor Human Milk." Molecules 25, no. 24 (December 8, 2020): 5783. http://dx.doi.org/10.3390/molecules25245783.
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Human milk could be considered an active and complex mixture of beneficial bacteria and bioactive compounds. Since pasteurization drastically reduces the microbial content, we recently demonstrated that pasteurized donor human milk (DHM) could be inoculated with different percentages (10% and 30%) of mother’s own milk (MOM) to restore the unique live microbiota, resulting in personalized milk (RM10 and RM30, respectively). Pasteurization affects not only the survival of the microbiota but also the concentration of proteins and metabolites, in this study, we performed a comparative metabolomic analysis of the RM10, RM30, MOM and DHM samples to evaluate the impact of microbial restoration on metabolite profiles, where metabolite profiles clustered into four well-defined groups. Comparative analyses of DHM and MOM metabolomes determined that over one thousand features were significantly different. In addition, significant changes in the metabolite concentrations were observed in MOM and RM30 samples after four hours of incubation, while the concentration of metabolites in DHM remained constant, indicating that these changes are related to the microbial expansion. In summary, our analyses indicate that the metabolite profiles of DHM are significantly different from that of MOM, and the profile of MOM may be partially restored in DHM through microbial expansion.
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Gong, Yiyi, Xiaolin Ni, Chenxi Jin, Xiang Li, Yujie Wang, Ou Wang, Mei Li, et al. "Serum Metabolomics Reveals Dysregulation and Diagnostic Potential of Oxylipins in Tumor-induced Osteomalacia." Journal of Clinical Endocrinology & Metabolism 107, no. 5 (December 14, 2021): 1383–91. http://dx.doi.org/10.1210/clinem/dgab885.
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Abstract Context Excessive production of fibroblast growth factor 23 (FGF23) by a tumor is considered the main pathogenesis in tumor-induced osteomalacia (TIO). Despite its importance to comprehensive understanding of pathogenesis and diagnosis, the regulation of systemic metabolism in TIO remains unclear. Objective We aimed to systematically characterize the metabolome alteration associated with TIO. Methods By means of liquid chromatography–tandem mass spectrometry–based metabolomics, we analyzed the metabolic profile from 96 serum samples (32 from TIO patients at initial diagnosis, pairwise samples after tumor resection, and 32 matched healthy control (HC) subjects). In order to screen and evaluate potential biomarkers, statistical analyses, pathway enrichment and receiver operating characteristic (ROC) were performed. Results Metabolomic profiling revealed distinct alterations between TIO and HC cohorts. Differential metabolites were screened and conducted to functional clustering and annotation. A significantly enriched pathway was found involving arachidonic acid metabolism. A combination of 5 oxylipins, 4-HDoHE, leukotriene B4, 5-HETE, 17-HETE, and 9,10,13-TriHOME, demonstrated a high sensitivity and specificity panel for TIO prediction screened by random forest algorithm (AUC = 0.951; 95% CI, 0.827-1). Supported vector machine modeling and partial least squares modeling were conducted to validate the predictive capabilities of the diagnostic panel. Conclusion Metabolite profiling of TIO showed significant alterations compared with HC. A high-sensitivity and high-specificity panel with 5 oxylipins was tested as diagnostic predictor. For the first time, we provide the global profile of metabolomes and identify potential diagnostic biomarkers of TIO. The present work may offer novel insights into the pathogenesis of TIO.
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Santos Ferreira, Diana, Hannah Maple, Matt Goodwin, Judith Brand, Vikki Yip, Josine Min, Alix Groom, Debbie Lawlor, and Susan Ring. "The Effect of Pre-Analytical Conditions on Blood Metabolomics in Epidemiological Studies." Metabolites 9, no. 4 (April 3, 2019): 64. http://dx.doi.org/10.3390/metabo9040064.
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Serum and plasma are commonly used in metabolomic-epidemiology studies. Their metabolome is susceptible to differences in pre-analytical conditions and the impact of this is unclear. Participant-matched EDTA-plasma and serum samples were collected from 37 non-fasting volunteers and profiled using a targeted nuclear magnetic resonance (NMR) metabolomics platform (n = 151 traits). Correlations and differences in mean of metabolite concentrations were compared between reference (pre-storage: 4 °C, 1.5 h; post-storage: no buffer addition delay or NMR analysis delay) and four pre-storage blood processing conditions, where samples were incubated at (i) 4 °C, 24 h; (ii) 4 °C, 48 h; (iii) 21 °C, 24 h; and (iv) 21 °C, 48 h, before centrifugation; and two post-storage sample processing conditions in which samples thawed overnight (i) then left for 24 h before addition of sodium buffer followed by immediate NMR analysis; and (ii) addition of sodium buffer, then left for 24 h before NMR profiling. We used multilevel linear regression models and Spearman’s rank correlation coefficients to analyse the data. Most metabolic traits had high rank correlation and minimal differences in mean concentrations between samples subjected to reference and the different conditions tested, that may commonly occur in studies. However, glycolysis metabolites, histidine, acetate and diacylglycerol concentrations may be compromised and this could bias results in association/causal analyses.
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Song, Tao, Ying Zhu, Peng Zhang, Minzhu Zhao, Dezhang Zhao, Shijia Ding, Shisheng Zhu, and Jianbo Li. "Integrated Proteomics and Metabolomic Analyses of Plasma Injury Biomarkers in a Serious Brain Trauma Model in Rats." International Journal of Molecular Sciences 20, no. 4 (February 20, 2019): 922. http://dx.doi.org/10.3390/ijms20040922.
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Diffuse axonal injury (DAI) is a prevalent and serious brain injury with significant morbidity and disability. However, the underlying pathogenesis of DAI remains largely unclear, and there are still no objective laboratory-based tests available for clinicians to make an early diagnosis of DAI. An integrated analysis of metabolomic data and proteomic data may be useful to identify all of the molecular mechanisms of DAI and novel potential biomarkers. Therefore, we established a rat model of DAI, and applied an integrated UPLC-Q-TOF/MS-based metabolomics and isobaric tag for relative and absolute quantitation (iTRAQ)-based proteomic analysis to obtain unbiased profiling data. Differential analysis identified 34 metabolites and 43 proteins in rat plasma of the injury group. Two metabolites (acetone and 4-Hydroxybenzaldehyde) and two proteins (Alpha-1-antiproteinase and Alpha-1-acid glycoprotein) were identified as potential biomarkers for DAI, and all may play important roles in the pathogenesis of DAI. Our study demonstrated the feasibility of integrated metabolomics and proteomics method to uncover the underlying molecular mechanisms of DAI, and may help provide clinicians with some novel diagnostic biomarkers and therapeutic targets.
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Welling, Matthew T., Myrna A. Deseo, Antony Bacic, and Monika S. Doblin. "Untargeted Metabolomic Analyses Reveal Chemical Complexity of Dioecious Cannabis Flowers." Australian Journal of Chemistry 74, no. 6 (2021): 463. http://dx.doi.org/10.1071/ch21033.
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Cannabis is a mostly dioecious multi-use flowering plant genus. Sexual dimorphism is an important characteristic in Cannabis-based commercial production systems, which has consequences for fibre, seed, and the yield of secondary metabolites, such as phytocannabinoid and terpenes for therapeutic uses. Beyond the obvious morphological differences between male and female plants, metabolic variation among dioecious flowers is largely undefined. Here, we report a pilot metabolomic study comparing staminate (male) and pistillate (female) unisexual flowers. Enrichment of the α-linolenic acid pathway and consensus evaluation of the jasmonic acid (JA) related compound 12-oxo-phytodienoicacid (OPDA) among differentially abundant metabolites suggests that oxylipin signalling is associated with secondary metabolism and sex expression in female flowers. Several putative phytocannabinoid-like compounds were observed to be upregulated in female flowers, but full identification was not possible due to the limitation of available databases. Targeted analysis of 14 phytocannabinoids using certified reference standards (cannabidiolic acid (CBDA), cannabidiol (CBD), Δ9-tetrahydrocannabinolic acid A (Δ9-THCAA), Δ9-tetrahydrocannabinol (Δ9-THC), cannabichromenic acid (CBCA), cannabichromene (CBC), cannabigerolic acid (CBGA), cannabigerol (CBG), cannabinolic acid (CBNA), cannabinol (CBN), cannabidivarinic acid (CBDVA), cannabidivarin (CBDV), tetrahydrocannabivarinic acid (THCVA), and tetrahydrocannabivarin (THCV)) showed a higher total phytocannabinoid content in female flowers compared with the male flowers, as expected. In summary, the development of a phytocannabinoid-specific accurate-mass MSn fragmentation spectral library and gene pool representative metabolome has the potential to improve small molecule compound annotation and accelerate understanding of metabolic variation underlying phenotypic diversity in Cannabis.
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Ji, Dezhong, Lina Ou, Xiaoli Ren, Xiuju Yang, Yanni Tan, Xia Zhou, and Linhong Jin. "Transcriptomic and Metabolomic Analysis Reveal Possible Molecular Mechanisms Regulating Tea Plant Growth Elicited by Chitosan Oligosaccharide." International Journal of Molecular Sciences 23, no. 10 (May 13, 2022): 5469. http://dx.doi.org/10.3390/ijms23105469.
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Chitosan oligosaccharide (COS) plays an important role in the growth and development of tea plants. However, responses in tea plants trigged by COS have not been thoroughly investigated. In this study, we integrated transcriptomics and metabolomics analysis to understand the mechanisms of chitosan-induced tea quality improvement and growth promotion. The combined analysis revealed an obvious link between the flourishing development of the tea plant and the presence of COS. It obviously regulated the growth and development of the tea and the metabolomic process. The chlorophyll, soluble sugar, and amino acid content in the tea leaves was increased. The phytohormones, carbohydrates, and amino acid levels were zoomed-in in both transcript and metabolomics analyses compared to the control. The expression of the genes related to phytohormones transduction, carbon fixation, and amino acid metabolism during the growth and development of tea plants were significantly upregulated. Our findings indicated that alerted transcriptomic and metabolic responses occurring with the application of COS could cause efficiency in substrates in pivotal pathways and hence, elicited plant growth.
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Guardiola, John J., Josiah E. Hardesty, Juliane I. Beier, Russell A. Prough, Craig J. McClain, and Matthew C. Cave. "Plasma Metabolomics Analysis of Polyvinyl Chloride Workers Identifies Altered Processes and Candidate Biomarkers for Hepatic Hemangiosarcoma and Its Development." International Journal of Molecular Sciences 22, no. 10 (May 11, 2021): 5093. http://dx.doi.org/10.3390/ijms22105093.
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Background: High-level occupational vinyl chloride (VC) exposures have been associated with hepatic hemangiosarcoma, which typically develops following a long latency period. Although VC is genotoxic, a more comprehensive mode of action has not been determined and diagnostic biomarkers have not been established. The purpose of this study is to address these knowledge gaps through plasma metabolomics. Methods: Plasma samples from polyvinyl chloride polymerization workers who developed hemangiosarcoma (cases, n = 15) and VC exposure-matched controls (n = 17) underwent metabolomic analysis. Random forest and bioinformatic analyses were performed. Results: Cases and controls had similar demographics and routine liver biochemistries. Mass spectroscopy identified 606 known metabolites. Random forest analysis had an 82% predictive accuracy for group classification. 60 metabolites were significantly increased and 44 were decreased vs. controls. Taurocholate, bradykinin and fibrin degradation product 2 were up-regulated by greater than 80-fold. The naturally occurring anti-angiogenic phenol, 4-hydroxybenzyl alcohol, was down-regulated 5-fold. Top affected ontologies involved: (i) metabolism of bile acids, taurine, cholesterol, fatty acids and amino acids; (ii) inflammation and oxidative stress; and (iii) nicotinic cholinergic signaling. Conclusions: The plasma metabolome was differentially regulated in polyvinyl chloride workers who developed hepatic hemangiosarcoma. Ontologies potentially involved in hemangiosarcoma pathogenesis and candidate biomarkers were identified.
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Kapoore, Rahul Vijay, and Seetharaman Vaidyanathan. "Towards quantitative mass spectrometry-based metabolomics in microbial and mammalian systems." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 374, no. 2079 (October 28, 2016): 20150363. http://dx.doi.org/10.1098/rsta.2015.0363.
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Metabolome analyses are a suite of analytical approaches that enable us to capture changes in the metabolome (small molecular weight components, typically less than 1500 Da) in biological systems. Mass spectrometry (MS) has been widely used for this purpose. The key challenge here is to be able to capture changes in a reproducible and reliant manner that is representative of the events that take place in vivo . Typically, the analysis is carried out in vitro , by isolating the system and extracting the metabolome. MS-based approaches enable us to capture metabolomic changes with high sensitivity and resolution. When developing the technique for different biological systems, there are similarities in challenges and differences that are specific to the system under investigation. Here, we review some of the challenges in capturing quantitative changes in the metabolome with MS based approaches, primarily in microbial and mammalian systems. This article is part of the themed issue ‘Quantitative mass spectrometry’.
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Saorin, Asia, Emanuela Di Gregorio, Gianmaria Miolo, Agostino Steffan, and Giuseppe Corona. "Emerging Role of Metabolomics in Ovarian Cancer Diagnosis." Metabolites 10, no. 10 (October 19, 2020): 419. http://dx.doi.org/10.3390/metabo10100419.
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Ovarian cancer is considered a silent killer due to the lack of clear symptoms and efficient diagnostic tools that often lead to late diagnoses. Over recent years, the impelling need for proficient biomarkers has led researchers to consider metabolomics, an emerging omics science that deals with analyses of the entire set of small-molecules (≤1.5 kDa) present in biological systems. Metabolomics profiles, as a mirror of tumor–host interactions, have been found to be useful for the analysis and identification of specific cancer phenotypes. Cancer may cause significant metabolic alterations to sustain its growth, and metabolomics may highlight this, making it possible to detect cancer in an early phase of development. In the last decade, metabolomics has been widely applied to identify different metabolic signatures to improve ovarian cancer diagnosis. The aim of this review is to update the current status of the metabolomics research for the discovery of new diagnostic metabolomic biomarkers for ovarian cancer. The most promising metabolic alterations are discussed in view of their potential biological implications, underlying the issues that limit their effective clinical translation into ovarian cancer diagnostic tools.
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Soldevilla, Beatriz, Angeles López-López, Alberto Lens-Pardo, Carlos Carretero-Puche, Angeles Lopez-Gonzalvez, Anna La Salvia, Beatriz Gil-Calderon, et al. "Comprehensive Plasma Metabolomic Profile of Patients with Advanced Neuroendocrine Tumors (NETs). Diagnostic and Biological Relevance." Cancers 13, no. 11 (May 27, 2021): 2634. http://dx.doi.org/10.3390/cancers13112634.
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Purpose: High-throughput “-omic” technologies have enabled the detailed analysis of metabolic networks in several cancers, but NETs have not been explored to date. We aim to assess the metabolomic profile of NET patients to understand metabolic deregulation in these tumors and identify novel biomarkers with clinical potential. Methods: Plasma samples from 77 NETs and 68 controls were profiled by GC−MS, CE−MS and LC−MS untargeted metabolomics. OPLS-DA was performed to evaluate metabolomic differences. Related pathways were explored using Metaboanalyst 4.0. Finally, ROC and OPLS-DA analyses were performed to select metabolites with biomarker potential. Results: We identified 155 differential compounds between NETs and controls. We have detected an increase of bile acids, sugars, oxidized lipids and oxidized products from arachidonic acid and a decrease of carnitine levels in NETs. MPA/MSEA identified 32 enriched metabolic pathways in NETs related with the TCA cycle and amino acid metabolism. Finally, OPLS-DA and ROC analysis revealed 48 metabolites with diagnostic potential. Conclusions: This study provides, for the first time, a comprehensive metabolic profile of NET patients and identifies a distinctive metabolic signature in plasma of potential clinical use. A reduced set of metabolites of high diagnostic accuracy has been identified. Additionally, new enriched metabolic pathways annotated may open innovative avenues of clinical research.
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Arend, Rebecca C., Carly B. Scalise, Emily R. Gordon, Allison M. Davis, McKenzie E. Foxall, Bobbi E. Johnston, David K. Crossman, and Sara J. Cooper. "Metabolic Alterations and WNT Signaling Impact Immune Response in HGSOC." Clinical Cancer Research 28, no. 7 (January 13, 2022): 1433–45. http://dx.doi.org/10.1158/1078-0432.ccr-21-2984.
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Abstract Purpose: Our study used transcriptomic and metabolomic strategies to determine the molecular profiles of HGSOC patient samples derived from primary tumor and ascites cells. These data identified clinically relevant heterogeneity among and within patients and highlighted global and patient-specific cellular responses to neoadjuvant chemotherapy (NACT). Experimental Design: Tissue from 61 treatment-naïve patients with HGSOC were collected. In addition, 11 benign, 32 ascites, and 18 post-NACT samples (matched to the individual patient's pre-NACT sample) were collected. RNA sequencing (RNA-seq) was performed on all samples collected. Two-dimensional spatial proteomic data was collected for two pairs of pre- and post-NACT. Untargeted metabolomics data using GCxGC-MS was generated for 30 treatment-naive tissues. Consensus clustering, analysis of differential expression, pathway enrichment, and survival analyses were performed. Results: Treatment-naïve HGSOC tissues had distinct transcriptomic and metabolomic profiles. The mesenchymal subtype harbored a metabolomic profile distinct from the other subtypes. Compared with primary tumor tissue, ascites showed significant changes in immune response and signaling pathways. NACT caused significant alterations in gene expression and WNT activity, and this corresponded to altered immune response. Overall, WNT signaling levels were inversely correlated with immune cell infiltration in HGSOC tissues and WNT signaling post-NACT was inversely correlated with progression-free survival. Conclusions: Our study concluded that HGSOC is a heterogenous disease at baseline and growing molecular differences can be observed between primary tumor and ascites cells or within tumors in response to treatment. Our data reveal potential exploratory biomarkers relevant for treatment selection and predicting patient outcomes that warrant further research.
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Huang, Hai-jun, An-ye Zhang, Hong-cui Cao, Hai-feng Lu, Bao-hong Wang, Qing Xie, Wei Xu, and Lan-Juan Li. "Metabolomic analyses of faeces reveals malabsorption in cirrhotic patients." Digestive and Liver Disease 45, no. 8 (August 2013): 677–82. http://dx.doi.org/10.1016/j.dld.2013.01.001.
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