Journal articles: 'Metabolomic chemistry'

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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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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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Meiliana, Anna, Nurrani Mustika Dewi, and Andi Wijaya. "Metabolomics: An Emerging Tool for Precision Medicine." Indonesian Biomedical Journal 13, no. 1 (March 1, 2021): 1–18. http://dx.doi.org/10.18585/inabj.v13i1.1309.

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BACKGROUND: Metabolomics is a developed technology that comprehensively analyzes the metabolites in biological specimens. It appears to be a prospective method in the practice of precision medicine.CONTENT: Metabolomic technologies currently surpass beyond the traditional clinical chemistry techniques. Metabolomic is capable to perform a precise analysis for hundreds to thousands of metabolites, therefore provide a detailed characterization of metabolic phenotypes and metabolic derangements that underlie disease, to represent an individual’s overall health status, furthermore to discover new precise therapeutic targets, and discovery of biomarkers, either for diagnosis or therapy monitoring purpose.SUMMARY: Adequate data processing and quantification methods are still needed to be developed to boost integrated -omics as a powerful clinical practice platform.KEYWORDS: metabolomic, precision medicine, phenotyping, biomarker, nutritional pattern

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Segers, Karen, Sven Declerck, Debby Mangelings, Yvan Vander Heyden, and Ann Van Eeckhaut. "Analytical techniques for metabolomic studies: a review." Bioanalysis 11, no. 24 (December 2019): 2297–318. http://dx.doi.org/10.4155/bio-2019-0014.

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Metabolomics is the comprehensive study of small-molecule metabolites. Obtaining a wide coverage of the metabolome is challenging because of the broad range of physicochemical properties of the small molecules. To study the compounds of interest spectroscopic (NMR), spectrometric (MS) and separation techniques (LC, GC, supercritical fluid chromatography, CE) are used. The choice for a given technique is influenced by the sample matrix, the concentration and properties of the metabolites, and the amount of sample. This review discusses the most commonly used analytical techniques for metabolomic studies, including their advantages, drawbacks and some applications.

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Tsuchida, Sachio, and Tomohiro Nakayama. "Metabolomics Research in Periodontal Disease by Mass Spectrometry." Molecules 27, no. 9 (April 30, 2022): 2864. http://dx.doi.org/10.3390/molecules27092864.

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Periodontology is a newer field relative to other areas of dentistry. Remarkable progress has been made in recent years in periodontology in terms of both research and clinical applications, with researchers worldwide now focusing on periodontology. With recent advances in mass spectrometry technology, metabolomics research is now widely conducted in various research fields. Metabolomics, which is also termed metabolomic analysis, is a technology that enables the comprehensive analysis of small-molecule metabolites in living organisms. With the development of metabolite analysis, methods using gas chromatography–mass spectrometry, liquid chromatography–mass spectrometry, capillary electrophoresis–mass spectrometry, etc. have progressed, making it possible to analyze a wider range of metabolites and to detect metabolites at lower concentrations. Metabolomics is widely used for research in the food, plant, microbial, and medical fields. This paper provides an introduction to metabolomic analysis and a review of the increasing applications of metabolomic analysis in periodontal disease research using mass spectrometry technology.

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Kiseleva, Olga, Ilya Kurbatov, Ekaterina Ilgisonis, and Ekaterina Poverennaya. "Defining Blood Plasma and Serum Metabolome by GC-MS." Metabolites 12, no. 1 (December 24, 2021): 15. http://dx.doi.org/10.3390/metabo12010015.

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Metabolomics uses advanced analytical chemistry methods to analyze metabolites in biological samples. The most intensively studied samples are blood and its liquid components: plasma and serum. Armed with advanced equipment and progressive software solutions, the scientific community has shown that small molecules’ roles in living systems are not limited to traditional “building blocks” or “just fuel” for cellular energy. As a result, the conclusions based on studying the metabolome are finding practical reflection in molecular medicine and a better understanding of fundamental biochemical processes in living systems. This review is not a detailed protocol of metabolomic analysis. However, it should support the reader with information about the achievements in the whole process of metabolic exploration of human plasma and serum using mass spectrometry combined with gas chromatography.

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Main, Sawyer C., Lindsay P. Brown, Kelly R. Melvin, Shawn R. Campagna, Brynn H. Voy, Hector F. Castro, Lewrell G. Strickland, et al. "Metabolomic Profiles in Starved Light Breed Horses during the Refeeding Process." Animals 12, no. 19 (September 21, 2022): 2527. http://dx.doi.org/10.3390/ani12192527.

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The large population of emaciated horses continues to be an issue troubling the equine industry. However, little is known regarding the collection of equine metabolites (metabolome) during a malnourished state and the changes that occur throughout nutritional rehabilitation. In this study, ten emaciated horses underwent a refeeding process, during which blood samples were collected for a blood chemistry panel and metabolomics analysis via ultrahigh performance liquid chromatography–high resolution mass spectrometry (UHPLC-HRMS). Significant differences among blood chemistry analytes and metabolite abundance during the critical care period (CCP; Days 1–10 of rehabilitation) and the recovery period (RP; the remainder of the rehabilitation process) were observed. Potentially toxic compounds, analytes related to liver, kidney, and muscle function, as well as energy-related metabolites were altered during the refeeding process. The combination of blood chemistry and metabolomics analyses on starved equine during rehabilitation provide vital biological insight and evidence that the refeeding process has a significant impact on the equine metabolome.

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Paganelli, Alessia, Valeria Righi, Elisabetta Tarentini, and Cristina Magnoni. "Current Knowledge in Skin Metabolomics: Updates from Literature Review." International Journal of Molecular Sciences 23, no. 15 (August 7, 2022): 8776. http://dx.doi.org/10.3390/ijms23158776.

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Metabolomic profiling is an emerging field consisting of the measurement of metabolites in a biological system. Since metabolites can vary in relation to different stimuli, specific metabolic patterns can be closely related to a pathological process. In the dermatological setting, skin metabolomics can provide useful biomarkers for the diagnosis, prognosis, and therapy of cutaneous disorders. The main goal of the present review is to present a comprehensive overview of the published studies in skin metabolomics. A search for journal articles focused on skin metabolomics was conducted on the MEDLINE, EMBASE, Cochrane, and Scopus electronic databases. Only research articles with electronically available English full text were taken into consideration. Studies specifically focused on cutaneous microbiomes were also excluded from the present search. A total of 97 papers matched all the research criteria and were therefore considered for the present work. Most of the publications were focused on inflammatory dermatoses and immune-mediated cutaneous disorders. Skin oncology also turned out to be a relevant field in metabolomic research. Only a few papers were focused on infectious diseases and rarer genetic disorders. All the major metabolomic alterations published so far in the dermatological setting are described extensively in this review.

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Satori, Chad P., Marzieh Ramezani, Joseph S. Koopmeiners, Audrey F. Meyer, Jose A. Rodriguez-Navarro, Michelle M. Kuhns, Thane H. Taylor, Christy L. Haynes, Joseph J. Dalluge, and Edgar A. Arriaga. "Checkpoints for preliminary identification of small molecules found enriched in autophagosomes and activated mast cell secretions analyzed by comparative UPLC/MSe." Analytical Methods 9, no. 1 (2017): 46–54. http://dx.doi.org/10.1039/c6ay02500e.

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Miettinen, Teemu, Anni I. Nieminen, Pekka Mäntyselkä, Eija Kalso, and Jörn Lötsch. "Machine Learning and Pathway Analysis-Based Discovery of Metabolomic Markers Relating to Chronic Pain Phenotypes." International Journal of Molecular Sciences 23, no. 9 (May 3, 2022): 5085. http://dx.doi.org/10.3390/ijms23095085.

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Recent scientific evidence suggests that chronic pain phenotypes are reflected in metabolomic changes. However, problems associated with chronic pain, such as sleep disorders or obesity, may complicate the metabolome pattern. Such a complex phenotype was investigated to identify common metabolomics markers at the interface of persistent pain, sleep, and obesity in 71 men and 122 women undergoing tertiary pain care. They were examined for patterns in d = 97 metabolomic markers that segregated patients with a relatively benign pain phenotype (low and little bothersome pain) from those with more severe clinical symptoms (high pain intensity, more bothersome pain, and co-occurring problems such as sleep disturbance). Two independent lines of data analysis were pursued. First, a data-driven supervised machine learning-based approach was used to identify the most informative metabolic markers for complex phenotype assignment. This pointed primarily at adenosine monophosphate (AMP), asparagine, deoxycytidine, glucuronic acid, and propionylcarnitine, and secondarily at cysteine and nicotinamide adenine dinucleotide (NAD) as informative for assigning patients to clinical pain phenotypes. After this, a hypothesis-driven analysis of metabolic pathways was performed, including sleep and obesity. In both the first and second line of analysis, three metabolic markers (NAD, AMP, and cysteine) were found to be relevant, including metabolic pathway analysis in obesity, associated with changes in amino acid metabolism, and sleep problems, associated with downregulated methionine metabolism. Taken together, present findings provide evidence that metabolomic changes associated with co-occurring problems may play a role in the development of severe pain. Co-occurring problems may influence each other at the metabolomic level. Because the methionine and glutathione metabolic pathways are physiologically linked, sleep problems appear to be associated with the first metabolic pathway, whereas obesity may be associated with the second.

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Udayakumar, M., D. Prem Chandar, N. Arun, J. Mathangi, K. Hemavathi, and R. Seenivasagam. "PMDB: Plant Metabolome Database—A Metabolomic Approach." Medicinal Chemistry Research 21, no. 1 (November 21, 2010): 47–52. http://dx.doi.org/10.1007/s00044-010-9506-z.

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Beyoğlu, Diren, Cedric Simillion, Federico Storni, Andrea De Gottardi, and Jeffrey R. Idle. "A Metabolomic Analysis of Cirrhotic Ascites." Molecules 27, no. 12 (June 20, 2022): 3935. http://dx.doi.org/10.3390/molecules27123935.

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Ascites is a common complication of decompensated liver cirrhosis, and yet relatively little is known about its biochemical composition. We conducted two metabolomic investigations, comparing the profile of ascites from 33 cirrhotic patients and postoperative peritoneal drainage fluid from 33 surgical patients (Experiment 1). The profile of paired ascites and plasma was also compared in 17 cirrhotic patients (Experiment 2). Gas chromatography–mass spectrometry-based metabolomics identified 29 metabolites that significantly characterized ascites fluid, whether postoperative drainage fluid or plasma were used as controls. Ten elevated amino acids (glutamine, proline, histidine, tyrosine, glycine, valine, threonine, methionine, lysine, phenylalanine) and seven diminished lipids (laurate, myristate, palmitate, oleate, vaccenate, stearate, cholesterol) largely comprised the cirrhotic ascites metabolomic phenotype that differed significantly (adjusted p < 0.002 to 0.03) from peritoneal drainage fluid or plasma. The pattern of upregulated amino acids in cirrhotic ascites did not indicate albumin proteolysis by peritoneal bacteria. Bidirectional clustering showed that the more severe the cirrhosis, the lower the lipid concentration in ascitic fluid. The metabolomic compartment of ascites in patients with decompensated cirrhosis is characterized by increased amino acids and decreased lipids. These novel findings have potential relevance for diagnostic purposes.

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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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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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Yelamanchi, Soujanya D., Sumaithangi Thattai Arun Kumar, Archita Mishra, Thottethodi Subrahmanya Keshava Prasad, and Avadhesha Surolia. "Metabolite Dysregulation by Pranlukast in Mycobacterium tuberculosis." Molecules 27, no. 5 (February 24, 2022): 1520. http://dx.doi.org/10.3390/molecules27051520.

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Mycobacterium tuberculosis has been infecting millions of people worldwide over the years, causing tuberculosis. Drugs targeting distinct cellular mechanisms including synthesis of the cell wall, lipids, proteins, and nucleic acids in Mtb are currently being used for the treatment of TB. Although extensive research is being carried out at the molecular level in the infected host and pathogen, the identification of suitable drug targets and drugs remains under explored. Pranlukast, an allosteric inhibitor of MtArgJ (Mtb ornithine acetyltransferase) has previously been shown to inhibit the survival and virulence of Mtb. The main objective of this study was to identify the altered metabolic pathways and biological processes associated with the differentially expressed metabolites by PRK in Mtb. Here in this study, metabolomics was carried out using an LC-MS/MS-based approach. Collectively, 50 metabolites were identified to be differentially expressed with a significant p-value through a global metabolomic approach using a high-resolution mass spectrometer. Metabolites downstream of argJ were downregulated in the arginine biosynthetic pathway following pranlukast treatment. Predicted human protein interactors of pranlukast-treated Mtb metabolome were identified in association with autophagy, inflammation, DNA repair, and other immune-related processes. Further metabolites including N-acetylglutamate, argininosuccinate, L-arginine, succinate, ergothioneine, and L-phenylalanine were validated by multiple reaction monitoring, a targeted mass spectrometry-based metabolomic approach. This study facilitates the understanding of pranlukast-mediated metabolic changes in Mtb and holds the potential to identify novel therapeutic approaches using metabolic pathways in Mtb.

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di Meo, Nicola Antonio, Davide Loizzo, Savio Domenico Pandolfo, Riccardo Autorino, Matteo Ferro, Camillo Porta, Alessandro Stella, et al. "Metabolomic Approaches for Detection and Identification of Biomarkers and Altered Pathways in Bladder Cancer." International Journal of Molecular Sciences 23, no. 8 (April 10, 2022): 4173. http://dx.doi.org/10.3390/ijms23084173.

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Metabolomic analysis has proven to be a useful tool in biomarker discovery and the molecular classification of cancers. In order to find new biomarkers, and to better understand its pathological behavior, bladder cancer also has been studied using a metabolomics approach. In this article, we review the literature on metabolomic studies of bladder cancer, focusing on the different available samples (urine, blood, tissue samples) used to perform the studies and their relative findings. Moreover, the multi-omic approach in bladder cancer research has found novel insights into its metabolic behavior, providing excellent start-points for new diagnostic and therapeutic strategies. Metabolomics data analysis can lead to the discovery of a “signature pathway” associated with the progression of bladder cancer; this aspect could be potentially valuable in predictions of clinical outcomes and the introduction of new treatments. However, further studies are needed to give stronger evidence and to make these tools feasible for use in clinical practice.

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Liu, Rui, Zheng-Xue Bao, Pei-Ji Zhao, and Guo-Hong Li. "Advances in the Study of Metabolomics and Metabolites in Some Species Interactions." Molecules 26, no. 11 (May 31, 2021): 3311. http://dx.doi.org/10.3390/molecules26113311.

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In the natural environment, interactions between species are a common natural phenomena. The mechanisms of interaction between different species are mainly studied using genomic, transcriptomic, proteomic, and metabolomic techniques. Metabolomics is a crucial part of system biology and is based on precision instrument analysis. In the last decade, the emerging field of metabolomics has received extensive attention. Metabolomics not only provides a qualitative and quantitative method for studying the mechanisms of interactions between different species, but also helps clarify the mechanisms of defense between the host and pathogen, and to explore new metabolites with various biological activities. This review focuses on the methods and progress of interspecies metabolomics. Additionally, the prospects and challenges of interspecies metabolomics are discussed.

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Lin, Chuwei, Aneirin Alan Lott, Wei Zhu, Craig P. Dufresne, and Sixue Chen. "Mitogen-Activated Protein Kinase 4-Regulated Metabolic Networks." International Journal of Molecular Sciences 23, no. 2 (January 14, 2022): 880. http://dx.doi.org/10.3390/ijms23020880.

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Mitogen-activated protein kinase 4 (MPK4) was first identified as a negative regulator of systemic acquired resistance. It is also an important kinase involved in many other biological processes in plants, including cytokinesis, reproduction, and photosynthesis. Arabidopsis thaliana mpk4 mutant is dwarf and sterile. Previous omics studies including genomics, transcriptomics, and proteomics have revealed new functions of MPK4 in different biological processes. However, due to challenges in metabolomics, no study has touched upon the metabolomic profiles of the mpk4 mutant. What metabolites and metabolic pathways are potentially regulated by MPK4 are not known. Metabolites are crucial components of plants, and they play important roles in plant growth and development, signaling, and defense. Here we used targeted and untargeted metabolomics to profile metabolites in the wild type and the mpk4 mutant. We found that in addition to the jasmonic acid and salicylic acid pathways, MPK4 is involved in polyamine synthesis and photosynthesis. In addition, we also conducted label-free proteomics of the two genotypes. The integration of metabolomics and proteomics data allows for an insight into the metabolomic networks that are potentially regulated by MPK4.

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Brockbals, Lana, Michael Habicht, Irka Hajdas, Francesco M. Galassi, Frank J. Rühli, and Thomas Kraemer. "Untargeted metabolomics-like screening approach for chemical characterization and differentiation of canopic jar and mummy samples from Ancient Egypt using GC-high resolution MS." Analyst 143, no. 18 (2018): 4503–12. http://dx.doi.org/10.1039/c8an01288a.

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Li, Kefeng, Jane C. Naviaux, Jonathan M. Monk, Lin Wang, and Robert K. Naviaux. "Improved Dried Blood Spot-Based Metabolomics: A Targeted, Broad-Spectrum, Single-Injection Method." Metabolites 10, no. 3 (February 27, 2020): 82. http://dx.doi.org/10.3390/metabo10030082.

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Dried blood spots (DBS) have proven to be a powerful sampling and storage method for newborn screening and many other applications. However, DBS methods have not yet been optimized for broad-spectrum targeted metabolomic analysis. In this study, we developed a robust, DBS-based, broad-spectrum, targeted metabolomic method that was able to measure over 400 metabolites from a 6.3 mm punch from standard Whatman 903TM filter paper cards. The effects of blood spot volumes, hematocrit, vacutainer chemistry, extraction methods, carryover, and comparability with plasma and fingerstick capillary blood samples were analyzed. The stability of over 400 metabolites stored under varying conditions over one year was also tested. No significant impacts of blood volume and hematocrit variations were observed when the spotted blood volume was over 60 µL and the hematocrit was between 31% and 50%. The median area under the curve (AUC) of metabolites in the DBS metabolome declined by 40% in the first 3 months and then did not decline further for at least 1 year. All originally detectable metabolites remained within detectable limits. The optimal storage conditions for metabolomic analysis were −80 °C with desiccants and without an O2 scavenger. The method was clinically validated for its potential utility in the diagnosis of the mitochondrial disease mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS). Our method provides a convenient alternative to freezing, storing, and shipping liquid blood samples for comparative metabolomic studies.

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Gebel, Erika. "Wine’s metabolomic bouquet." Analytical Chemistry 82, no. 9 (May 2010): 3407. http://dx.doi.org/10.1021/ac1006602.

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Pérez-Míguez, Raquel, María Castro-Puyana, Elena Sánchez-López, Merichel Plaza, and María Luisa Marina. "Untargeted HILIC-MS-Based Metabolomics Approach to Evaluate Coffee Roasting Process: Contributing to an Integrated Metabolomics Multiplatform." Molecules 25, no. 4 (February 17, 2020): 887. http://dx.doi.org/10.3390/molecules25040887.

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An untargeted metabolomics strategy using hydrophilic interaction chromatography-mass spectrometry (HILIC-MS) was developed in this work enabling the study of the coffee roasting process. Green coffee beans and coffee beans submitted to three different roasting degrees (light, medium, and strong) were analyzed. Chromatographic separation was carried out using water containing 10 mM ammonium formate with 0.2 % formic acid (mobile phase A) and acetonitrile containing 10 mM ammonium formate with 0.2 % formic acid (mobile phase B). A total of 93 molecular features were considered from which 31 were chosen as the most statistically significant using variable in the projection values. 13 metabolites were tentatively identified as potential biomarkers of the coffee roasting process using this metabolomic platform. Results obtained in this work were complementary to those achieved using orthogonal techniques such as reversed-phase liquid chromatography-mass spectrometry (RPLC-MS) and capillary electrophoresis-mass spectrometry (CE-MS) since only one metabolite was found to be common between HILIC-MS and RPLC-MS platforms (caffeoylshikimic acid isomer) and other between HILIC-MS and CE-MS platforms (choline). On the basis of these results, an untargeted metabolomics multiplatform is proposed in this work based on the integration of the three orthogonal techniques as a powerful tool to expand the coverage of the roasted coffee metabolome.

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Iwamoto, Hitoshi, Masaaki Okihara, Isao Akashi, Yu Kihara, Osamu Konno, Shigeyuki Kawachi, Makoto Sunamura, and Masahiro Sugimoto. "Metabolomic Profiling of Plasma, Urine, and Saliva of Kidney Transplantation Recipients." International Journal of Molecular Sciences 23, no. 22 (November 11, 2022): 13938. http://dx.doi.org/10.3390/ijms232213938.

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Kidney biopsy is commonly used to diagnose kidney transplant dysfunction after transplantation. Therefore, the development of minimally invasive and quantitative methods to evaluate kidney function in transplant recipients is necessary. Here, we used capillary electrophoresis-mass spectrometry to analyze the biofluids collected from transplant recipients with impaired (Group I, n = 31) and stable (Group S, n = 19) kidney function and from donors (Group D, n = 9). Metabolomics analyses identified and quantified 97 metabolites in plasma, 133 metabolites in urine, and 108 metabolites in saliva. Multivariate analyses revealed apparent differences in the metabolomic profiles of the three groups. In plasma samples, arginine biosynthesis and purine metabolism between the I and S Groups differed. In addition, considerable differences in metabolomic profiles were observed between samples collected from participants with T cell-mediated rejection (TCR), antibody-mediated rejection, and other kidney disorders (KD). The metabolomic profiles in the three types of biofluids showed different patterns between TCR and KD, wherein 3-indoxyl sulfate showed a significant increase in TCR consistently in both plasma and urine samples. These results suggest that each biofluid has different metabolite features to evaluate kidney function after transplantation and that 3-indoxyl sulfate could predict acute rejection.

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Jiang, Mingyang, Yanchun Liang, Zhili Pei, Xiye Wang, Fengfeng Zhou, Chengxi Wei, and Xiaoyue Feng. "Diagnosis of Breast Hyperplasia and Evaluation of RuXian-I Based on Metabolomics Deep Belief Networks." International Journal of Molecular Sciences 20, no. 11 (May 28, 2019): 2620. http://dx.doi.org/10.3390/ijms20112620.

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Breast cancer is estimated to be the leading cancer type among new cases in American women. Core biopsy data have shown a close association between breast hyperplasia and breast cancer. The early diagnosis and treatment of breast hyperplasia are extremely important to prevent breast cancer. The Mongolian medicine RuXian-I is a traditional drug that has achieved a high level of efficacy and a low incidence of side effects in its clinical use. However, for detecting the efficacy of RuXian-I, a rapid and accurate evaluation method based on metabolomic data is still lacking. Therefore, we proposed a framework, named the metabolomics deep belief network (MDBN), to analyze breast hyperplasia metabolomic data. We obtained 168 samples of metabolomic data from an animal model experiment of RuXian-I, which were averaged from control groups, treatment groups, and model groups. In the process of training, unlabelled data were used to pretrain the Deep Belief Networks models, and then labelled data were used to complete fine-tuning based on a limited-memory Broyden Fletcher Goldfarb Shanno (L-BFGS) algorithm. To prevent overfitting, a dropout method was added to the pretraining and fine-tuning procedures. The experimental results showed that the proposed model is superior to other classical classification methods that are based on positive and negative spectra data. Further, the proposed model can be used as an extension of the classification method for metabolomic data. For the high accuracy of classification of the three groups, the model indicates obvious differences and boundaries between the three groups. It can be inferred that the animal model of RuXian-I is well established, which can lay a foundation for subsequent related experiments. This also shows that metabolomic data can be used as a means to verify the effectiveness of RuXian-I in the treatment of breast hyperplasia.

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Girija, Aiswarya, Rattan Yadav, Fiona Corke, John Doonan, and Luis A. J. Mur. "Untargeted Metabolomic Profiling Reveals Variation in Metabolites Associated with Nutritional Values in Tef Accessions." Plant Foods for Human Nutrition 76, no. 4 (November 11, 2021): 536–39. http://dx.doi.org/10.1007/s11130-021-00931-6.

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Abstract Tef (Eragrostis tef), is a gluten-free orphan cereal, crop of nutritional and economical significance. Here we used untargeted metabolomics to survey metabolite variation in 14 diverse tef accessions at 15-days post germination. Tef genotypes were classified into four metabolomic groups where variation was linked to flavones and flavonols. Further analysis on white seeded accessions shows variation related to sucrose and important vitamins, nicotinamides (vitamin B3) riboflavin (vitamin B2) and folate (vitamin B9). Coloured seeded accessions showed variation in metabolism related to amino acid and sugars. This study highlights the potential of metabolomics in exploring the nutritional traits in tef.

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Climaco Pinto, Rui, Ibrahim Karaman, Matthew R. Lewis, Jenny Hällqvist, Manuja Kaluarachchi, Gonçalo Graça, Elena Chekmeneva, et al. "Finding Correspondence between Metabolomic Features in Untargeted Liquid Chromatography–Mass Spectrometry Metabolomics Datasets." Analytical Chemistry 94, no. 14 (March 31, 2022): 5493–503. http://dx.doi.org/10.1021/acs.analchem.1c03592.

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Sedio, Brian E., Armando Durant Archibold, Juan Camilo Rojas Echeverri, Chloé Debyser, Cristopher A. Boya P, and S. Joseph Wright. "A comparison of inducible, ontogenetic, and interspecific sources of variation in the foliar metabolome in tropical trees." PeerJ 7 (September 20, 2019): e7536. http://dx.doi.org/10.7717/peerj.7536.

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Plant interactions with other organisms are mediated by chemistry, yet chemistry varies among conspecific and within individual plants. The foliar metabolome—the suite of small-molecule metabolites found in the leaf—changes during leaf ontogeny and is influenced by the signaling molecule jasmonic acid. Species differences in secondary metabolites are thought to play an important ecological role by limiting the host ranges of herbivores and pathogens, and hence facilitating competitive coexistence among plant species in species-rich plant communities such as tropical forests. Yet it remains unclear how inducible and ontogenetic variation compare with interspecific variation, particularly in tropical trees. Here, we take advantage of novel methods to assemble mass spectra of all compounds in leaf extracts into molecular networks that quantify their chemical structural similarity in order to compare inducible and ontogenetic chemical variation to among-species variation in species-rich tropical tree genera. We ask (i) whether young and mature leaves differ chemically, (ii) whether jasmonic acid-inducible chemical variation differs between young and mature leaves, and (iii) whether interspecific exceeds intraspecific chemical variation for four species from four hyperdiverse tropical tree genera. We observed significant effects of the jasmonic acid treatment for three of eight combinations of species and ontogenetic stage evaluated. Three of the four species also exhibited large metabolomic differences with leaf ontogenetic stage. The profound effect of leaf ontogenetic stage on the foliar metabolome suggests a qualitative turnover in secondary chemistry with leaf ontogeny. We also quantified foliar metabolomes for 45 congeners of the four focal species. Chemical similarity was much greater within than between species for all four genera, even when within-species comparisons included leaves that differed in age and jasmonic acid treatment. Despite ontogenetic and inducible variation within species, chemical differences among congeneric species may be sufficient to partition niche space with respect to chemical defense.

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Yu, Shouzhi, Yao He, Wenheng Ji, Rong Yang, Yuxiu Zhao, Yan Li, Yingwei Liu, et al. "Metabolic and Proteomic Profiles Associated with Immune Responses Induced by Different Inactivated SARS-CoV-2 Vaccine Candidates." International Journal of Molecular Sciences 23, no. 18 (September 13, 2022): 10644. http://dx.doi.org/10.3390/ijms231810644.

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Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in late 2019, the virus has been mutating continuously, resulting in the continuous emergence of variants and creating challenges for epidemic prevention and control. Here, we immunized mice with different vaccine candidates, revealing the immune, protein, and metabolomic changes that take place in vaccines composed of different variants. We found that the prototype strain and Delta- and Omicron-variant inactivated vaccine candidates could all induce a high level of neutralizing antibodies and cellular immunity responses in mice. Next, we found that the metabolic and protein profiles were changed, showing a positive association with immune responses, and the level of the change was distinct in different inactivated vaccines, indicating that amino acid variations could affect metabolomics and proteomics. Our findings reveal differences between vaccines at the metabolomic and proteomic levels. These insights provide a novel direction for the immune evaluation of vaccines and could be used to guide novel strategies for vaccine design.

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Glinskikh, Anastasia, Olga Snytnikova, Ekaterina Zelentsova, Maria Borisova, Yuri Tsentalovich, and Andrey Akulov. "The Effect of Blood Contained in the Samples on the Metabolomic Profile of Mouse Brain Tissue: A Study by NMR Spectroscopy." Molecules 26, no. 11 (May 22, 2021): 3096. http://dx.doi.org/10.3390/molecules26113096.

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(1) Recently, metabolic profiling of the tissue in the native state or extracts of its metabolites has become increasingly important in the field of metabolomics. An important factor, in this case, is the presence of blood in a tissue sample, which can potentially lead to a change in the concentration of tissue metabolites and, as a result, distortion of experimental data and their interpretation. (2) In this paper, the metabolomic profiling based on NMR spectroscopy was performed to determine the effect of blood contained in the studied samples of brain tissue on their metabolomic profile. We used 13 male laboratory CD-1® IGS mice for this study. The animals were divided into two groups. The first group of animals (n = 7) was subjected to the perfusion procedure, and the second group of animals (n = 6) was not perfused. The brain tissues of the animals were homogenized, and the metabolite fraction was extracted with a water/methanol/chloroform solution. Samples were studied by high-frequency 1H-NMR spectroscopy with subsequent statistical data analysis. The group comparison was performed with the use of the Student’s test. We identified 36 metabolites in the brain tissue with the use of NMR spectroscopy. (3) For the major set of studied metabolites, no significant differences were found in the brain tissue metabolite concentrations in the native state and after the blood removal procedure. (4) Thus, it was shown that the presence of blood does not have a significant effect on the metabolomic profile of the brain in animals without pathologies.

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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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Rao, Qianru, Ting Zhang, Manyun Dai, Bin Li, Qianlun Pu, Min Zhao, Yan Cheng, et al. "Comparative Metabolomic Profiling of the Metabolic Differences of Δ9-Tetrahydrocannabinol and Cannabidiol." Molecules 27, no. 21 (November 4, 2022): 7573. http://dx.doi.org/10.3390/molecules27217573.

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More than one hundred cannabinoids have been found in cannabis. Δ9-Tetrahydrocannabinol (THC) is the recognized addictive constituent in cannabis; however, the mechanisms underlying THC-induced toxicity remain elusive. To better understand cannabis-induced toxicity, the present study compared the metabolic pathways of THC and its isomer cannabidiol (CBD) in human and mouse liver microsomes using the metabolomic approach. Thirty-two metabolites of THC were identified, including nine undescribed metabolites. Of note, two glutathione (GSH) and two cysteine (Cys) adducts were found in THC’s metabolism. Molecular docking revealed that THC conjugates have a higher affinity with GSH and Cys than with the parent compound, THC. Human recombinant cytochrome P450 enzymes, and their corresponding chemical inhibitors, demonstrated that CYP3A4 and CYP1B1 were the primary enzymes responsible for the formation of THC-GSH and THC-Cys, thus enabling conjugation to occur. Collectively, this study systematically compared the metabolism of THC with the metabolism of CBD using the metabolomic approach, which thus highlights the critical role of metabolomics in identifying novel drug metabolites. Moreover, this study also facilitates mechanistic speculation in order to expand the knowledge of drug metabolism and safety.

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Tawfike, Ahmed F., Rothwelle Tate, Gráinne Abbott, Louise Young, Christina Viegelmann, Marc Schumacher, Marc Diederich, and RuAngelie Edrada-Ebel. "Metabolomic Tools to Assess the Chemistry and Bioactivity of EndophyticAspergillusStrain." Chemistry & Biodiversity 14, no. 10 (October 2017): e1700040. http://dx.doi.org/10.1002/cbdv.201700040.

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Rajska, Anna, Magdalena Buszewska-Forajta, Dominik Rachoń, and Michał Jan Markuszewski. "Metabolomic Insight into Polycystic Ovary Syndrome—An Overview." International Journal of Molecular Sciences 21, no. 14 (July 9, 2020): 4853. http://dx.doi.org/10.3390/ijms21144853.

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Searching for the mechanisms of the polycystic ovary syndrome (PCOS) pathophysiology has become a crucial aspect of research performed in the last decades. However, the pathogenesis of this complex and heterogeneous endocrinopathy remains unknown. Thus, there is a need to investigate the metabolic pathways, which could be involved in the pathophysiology of PCOS and to find the metabolic markers of this disorder. The application of metabolomics gives a promising insight into the research on PCOS. It is a valuable and rapidly expanding tool, enabling the discovery of novel metabolites, which may be the potential biomarkers of several metabolic and endocrine disorders. The utilization of this approach could also improve the process of diagnosis and therefore, make treatment more effective. This review article aims to summarize actual and meaningful metabolomic studies in PCOS and point to the potential biomarkers detected in serum, urine, and follicular fluid of the affected women.

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Qin, Zhenxian, Dengqun Liao, Yalan Chen, Chenyang Zhang, Ruipeng An, Qing Zeng, and Xian’en Li. "A Widely Metabolomic Analysis Revealed Metabolic Alterations of Epimedium Pubescens Leaves at Different Growth Stages." Molecules 25, no. 1 (December 29, 2019): 137. http://dx.doi.org/10.3390/molecules25010137.

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Epimedium folium is the major medicinally-used organ of Epimedium species and its metabolic changes during the leaf growth have not been studied at the metabolomic level. E. pubescens is one of five recorded species in the Pharmacopoeia of the People’s Republic of China and widely grows in China. A UPLC-ESI-MS/MS-based targeted metabolomic analysis was implemented to explore the metabolite composition in E. pubescens leaves under the cultivation condition and further to investigate their temporal variations among four representative growth stages. A total of 403 metabolites, including 32 hitherto known in Epimedium species, were identified in E. pubescens leaf, of which 302 metabolites showed the growth/development-dependent alterations. Flavonoid-type compounds were the major composition of the metabolites identified in this study. Most flavonoids, together with tannin-type and lignans and coumarin-type compounds, were up-regulated with E. pubescens leaf growth and maturation after the full flowering stage. Our results not only greatly enriched the existing Epimedium phytochemical composition database and also, for the first time, provided the metabolomics-wide information on metabolic changes during E. pubescens leaf growth and development, which would facilitate in the choice of an optimum harvest time to balance a higher biomass yield of Epimedium folium with its better medicinal quality.

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Alesi, Simon, Drishti Ghelani, Kate Rassie, and Aya Mousa. "Metabolomic Biomarkers in Gestational Diabetes Mellitus: A Review of the Evidence." International Journal of Molecular Sciences 22, no. 11 (May 24, 2021): 5512. http://dx.doi.org/10.3390/ijms22115512.

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Gestational diabetes mellitus (GDM) is the fastest growing type of diabetes, affecting between 2 to 38% of pregnancies worldwide, varying considerably depending on diagnostic criteria used and sample population studied. Adverse obstetric outcomes include an increased risk of macrosomia, and higher rates of stillbirth, instrumental delivery, and birth trauma. Metabolomics, which is a platform used to analyse and characterise a large number of metabolites, is increasingly used to explore the pathophysiology of cardiometabolic conditions such as GDM. This review aims to summarise metabolomics studies in GDM (from inception to January 2021) in order to highlight prospective biomarkers for diagnosis, and to better understand the dysfunctional metabolic pathways underlying the condition. We found that the most commonly deranged pathways in GDM include amino acids (glutathione, alanine, valine, and serine), carbohydrates (2-hydroxybutyrate and 1,5-anhydroglucitol), and lipids (phosphatidylcholines and lysophosphatidylcholines). We also highlight the possibility of using certain metabolites as predictive markers for developing GDM, with the use of highly stratified modelling techniques. Limitations for metabolomic research are evaluated, and future directions for the field are suggested to aid in the integration of these findings into clinical practice.

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Zidi, Oumaima, Nessrine Souai, Henda Raies, Farhat Ben Ayed, Amel Mezlini, Sonia Mezrioui, Fabrice Tranchida, et al. "Fecal Metabolic Profiling of Breast Cancer Patients during Neoadjuvant Chemotherapy Reveals Potential Biomarkers." Molecules 26, no. 8 (April 14, 2021): 2266. http://dx.doi.org/10.3390/molecules26082266.

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Breast cancer (BC) is the most common form of cancer among women worldwide. Despite the huge advancements in its treatment, the exact etiology of breast cancer still remains unresolved. There is an increasing interest in the role of the gut microbiome in modulating the anti-cancer therapeutic response. It seems that alteration of the microbiome-derived metabolome potentially promotes carcinogenesis. Taken together, metabolomics has arisen as a fascinating new omics field to screen promising metabolic biomarkers. In this study, fecal metabolite profiling was performed using NMR spectroscopy, to identify potential biomarker candidates that can predict response to neoadjuvant chemotherapy (NAC) for breast cancer. Metabolic profiles of feces from patients (n = 8) following chemotherapy treatment cycles were studied. Interestingly, amino acids were found to be upregulated, while lactate and fumaric acid were downregulated in patients under the second and third cycles compared with patients before treatment. Furthermore, short-chain fatty acids (SCFAs) were significantly differentiated between the studied groups. These results strongly suggest that chemotherapy treatment plays a key role in modulating the fecal metabolomic profile of BC patients. In conclusion, we demonstrate the feasibility of identifying specific fecal metabolic profiles reflecting biochemical changes that occur during the chemotherapy treatment. These data give an interesting insight that may complement and improve clinical tools for BC monitoring.

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De Castro, Federica, Michele Benedetti, Laura Del Coco, and Francesco Paolo Fanizzi. "NMR-Based Metabolomics in Metal-Based Drug Research." Molecules 24, no. 12 (June 15, 2019): 2240. http://dx.doi.org/10.3390/molecules24122240.

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Thanks to recent advances in analytical technologies and statistical capabilities, the application field of metabolomics has increased significantly. Currently, this approach is used to investigate biological substrates looking for metabolic profile alterations, diseases markers, and drug effects. In particular, NMR spectroscopy has shown great potential as a detection technique, mainly for the ability to detect multiple (10s to 100s) metabolites at once without separation. Only in recent years has the NMR-based metabolomic approach been extended to investigate the cell metabolic alterations induced by metal-based antitumor drug administration. As expected, these studies are mainly focused on platinum complexes, but some palladium and ruthenium compounds are also under investigation. The use of a metabolomics approach was very effective in assessing tumor response to drugs and providing insights into the mechanism of action and resistance. Therefore, metabolomics may open new perspectives into the development of metal-based drugs. In particular, it has been shown that NMR-based, in vitro metabolomics is a powerful tool for detecting variations of the cell metabolites induced by the metal drug exposure, thus offering also the possibility of identifying specific markers for in vivo monitoring of tumor responsiveness to anticancer treatments.

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Balonov, Ilja, Max Kurlbaum, Ann-Cathrin Koschker, Christine Stier, Martin Fassnacht, and Ulrich Dischinger. "Changes in Plasma Metabolomic Profile Following Bariatric Surgery, Lifestyle Intervention or Diet Restriction—Insights from Human and Rat Studies." International Journal of Molecular Sciences 24, no. 3 (January 25, 2023): 2354. http://dx.doi.org/10.3390/ijms24032354.

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Although bariatric surgery is known to change the metabolome, it is unclear if this is specific for the intervention or a consequence of the induced bodyweight loss. As the weight loss after Roux-en-Y Gastric Bypass (RYGB) can hardly be mimicked with an evenly effective diet in humans, translational research efforts might be helpful. A group of 188 plasma metabolites of 46 patients from the randomized controlled Würzburg Adipositas Study (WAS) and from RYGB-treated rats (n = 6) as well as body-weight-matched controls (n = 7) were measured using liquid chromatography tandem mass spectrometry. WAS participants were randomized into intensive lifestyle modification (LS, n = 24) or RYGB (OP, n = 22). In patients in the WAS cohort, only bariatric surgery achieved a sustained weight loss (BMI −34.3% (OP) vs. −1.2% (LS), p ≤ 0.01). An explicit shift in the metabolomic profile was found in 57 metabolites in the human cohort and in 62 metabolites in the rodent model. Significantly higher levels of sphingolipids and lecithins were detected in both surgical groups but not in the conservatively treated human and animal groups. RYGB leads to a characteristic metabolomic profile, which differs distinctly from that following non-surgical intervention. Analysis of the human and rat data revealed that RYGB induces specific changes in the metabolome independent of weight loss.

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Łuczykowski, Kamil, Natalia Warmuzińska, Sylwia Operacz, Iga Stryjak, Joanna Bogusiewicz, Julia Jacyna, Renata Wawrzyniak, Wiktoria Struck-Lewicka, Michał J. Markuszewski, and Barbara Bojko. "Metabolic Evaluation of Urine from Patients Diagnosed with High Grade (HG) Bladder Cancer by SPME-LC-MS Method." Molecules 26, no. 8 (April 11, 2021): 2194. http://dx.doi.org/10.3390/molecules26082194.

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Bladder cancer (BC) is a common malignancy of the urinary system and a leading cause of death worldwide. In this work, untargeted metabolomic profiling of biological fluids is presented as a non-invasive tool for bladder cancer biomarker discovery as a first step towards developing superior methods for detection, treatment, and prevention well as to further our current understanding of this disease. In this study, urine samples from 24 healthy volunteers and 24 BC patients were subjected to metabolomic profiling using high throughput solid-phase microextraction (SPME) in thin-film format and reversed-phase high-performance liquid chromatography coupled with a Q Exactive Focus Orbitrap mass spectrometer. The chemometric analysis enabled the selection of metabolites contributing to the observed separation of BC patients from the control group. Relevant differences were demonstrated for phenylalanine metabolism compounds, i.e., benzoic acid, hippuric acid, and 4-hydroxycinnamic acid. Furthermore, compounds involved in the metabolism of histidine, beta-alanine, and glycerophospholipids were also identified. Thin-film SPME can be efficiently used as an alternative approach to other traditional urine sample preparation methods, demonstrating the SPME technique as a simple and efficient tool for urinary metabolomics research. Moreover, this study’s results may support a better understanding of bladder cancer development and progression mechanisms.

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Lavarello, Chiara, Sebastiano Barco, Martina Bartolucci, Isabella Panfoli, Emanuele Magi, Gino Tripodi, Andrea Petretto, and Giuliana Cangemi. "Development of an Accurate Mass Retention Time Database for Untargeted Metabolomic Analysis and Its Application to Plasma and Urine Pediatric Samples." Molecules 26, no. 14 (July 13, 2021): 4256. http://dx.doi.org/10.3390/molecules26144256.

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Liquid-chromatography coupled to high resolution mass spectrometry (LC-HRMS) is currently the method of choice for untargeted metabolomic analysis. The availability of established protocols to achieve a high confidence identification of metabolites is crucial. The aim of this work is to describe the workflow that we have applied to build an Accurate Mass Retention Time (AMRT) database using a commercial metabolite library of standards. LC-HRMS analysis was carried out using a Vanquish Horizon UHPLC system coupled to a Q-Exactive Plus Hybrid Quadrupole-Orbitrap Mass Spectrometer (Thermo Fisher Scientific, Milan, Italy). The fragmentation spectra, obtained with 12 collision energies, were acquired for each metabolite, in both polarities, through flow injection analysis. Several chromatographic conditions were tested to obtain a protocol that yielded stable retention times. The adopted chromatographic protocol included a gradient separation using a reversed phase (Waters Acquity BEH C18) and a HILIC (Waters Acquity BEH Amide) column. An AMRT database of 518 compounds was obtained and tested on real plasma and urine samples analyzed in data-dependent acquisition mode. Our AMRT library allowed a level 1 identification, according to the Metabolomics Standards Initiative, of 132 and 124 metabolites in human pediatric plasma and urine samples, respectively. This library represents a starting point for future metabolomic studies in pediatric settings.

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Troisi, Jacopo, Laura Sarno, Annamaria Landolfi, Giovanni Scala, Pasquale Martinelli, Roberta Venturella, Annalisa Di Cello, Fulvio Zullo, and Maurizio Guida. "Metabolomic Signature of Endometrial Cancer." Journal of Proteome Research 17, no. 2 (January 2, 2018): 804–12. http://dx.doi.org/10.1021/acs.jproteome.7b00503.

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Zhou, Jinna, Donghai Hou, Weiqiu Zou, Jinhu Wang, Run Luo, Mu Wang, and Hong Yu. "Comparison of Widely Targeted Metabolomics and Untargeted Metabolomics of Wild Ophiocordyceps Sinensis." Molecules 27, no. 11 (June 6, 2022): 3645. http://dx.doi.org/10.3390/molecules27113645.

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The authors of this paper conducted a comparative metabolomic analysis of Ophiocordyceps sinensis (OS), providing the metabolic profiles of the stroma (OSBSz) and sclerotia (OSBSh) of OS by widely targeted metabolomics and untargeted metabolomics. The results showed that 778 and 1449 metabolites were identified by the widely targeted metabolomics and untargeted metabolomics approaches, respectively. The metabolites in OSBSz and OSBSh are significantly differentiated; 71 and 96 differentially expressed metabolites were identified by the widely targeted metabolomics and untargeted metabolomics approaches, respectively. This suggests that these 71 metabolites (riboflavine, tripdiolide, bromocriptine, lumichrome, tetrahymanol, citrostadienol, etc.) and 96 metabolites (sancycline, vignatic acid B, pirbuterol, rubrophen, epalrestat, etc.) are potential biomarkers. 4-Hydroxybenzaldehyde, arginine, and lumichrome were common differentially expressed metabolites. Using the widely targeted metabolomics approach, the key pathways identified that are involved in creating the differentiation between OSBSz and OSBSh may be nicotinate and nicotinamide metabolism, thiamine metabolism, riboflavin metabolism, glycine, serine, and threonine metabolism, and arginine biosynthesis. The differentially expressed metabolites identified using the untargeted metabolomics approach were mainly involved in arginine biosynthesis, terpenoid backbone biosynthesis, porphyrin and chlorophyll metabolism, and cysteine and methionine metabolism. The purpose of this research was to provide support for the assessment of the differences between the stroma and sclerotia, to furnish a material basis for the evaluation of the physical effects of OS, and to provide a reference for the selection of detection methods for the metabolomics of OS.

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Kráľová, Katarína, Josef Jampílek, and Ivan Ostrovský. "Metabolomics - Useful Tool for Study of Plant Responses to Abiotic Stresses." Ecological Chemistry and Engineering S 19, no. 2 (January 1, 2012): 133–61. http://dx.doi.org/10.2478/v10216-011-0012-0.

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Metabolomics - Useful Tool for Study of Plant Responses to Abiotic Stresses Abiotic stresses are produced by inappropriate levels of physical components of the environment and cause plant injury through unique mechanisms that result in specific responses. Metabolomics is a relatively new approach aimed at improved understanding of metabolic networks and the subsequent biochemical composition of plants and other biological organisms. The paper is focused on the use of metabolomics, metabolic profiling and metabolic fingerprinting to study plant responses to some environmental stresses (eg elevated temperature, chilling and freezing, drought, high salinity, UV radiation, high ozone levels, nutrient deficiency, oxidative stress, herbicides and heavy metals). Attention is also devoted to the effects of some environmental factors on plants such as high or low levels of CO2 or different levels of irradiance. Alterations of plants metabolites due to multiple abiotic stresses (drought-heat, drought-salinity, elevated CO2-salinity) are analysed as well. In addition, metabolomic approach to study plant responses to some artificial abiotic stresses, mechanical stress or pulsed electric field-induced stress is discussed. The most important analytical methods applied in metabolomics are presented and perspectives of metabolomics exploitation in the future are outlined, too.

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Zheng, Senlin, Yanwei Hao, Silin Fan, Jiahui Cai, Weixin Chen, Xueping Li, and Xiaoyang Zhu. "Metabolomic and Transcriptomic Profiling Provide Novel Insights into Fruit Ripening and Ripening Disorder Caused by 1-MCP Treatments in Papaya." International Journal of Molecular Sciences 22, no. 2 (January 18, 2021): 916. http://dx.doi.org/10.3390/ijms22020916.

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Treatment with 1-methylcyclopropylene (1-MCP) is an effective technique to preserve fruits, but inappropriate treatment with 1-MCP causes a ripening disorder (rubbery texture) in papaya fruit. In this study, a combined metabolomic and transcriptomic analysis was conducted to reveal the possible mechanism of the ripening disorder caused by unsuitable 1-MCP in papaya. A total of 203 differential accumulated metabolites (DAMs) were identified in the metabolome analysis. Only 24 DAMs were identified in the control (CK) vs. the 1-MCP 2 h group, and they were primarily flavonoids. Ninety and 89 DAMs were identified in the CK vs. 1-MCP 16 h and 1-MCP 2 h vs. 1-MCP 16 h groups, respectively, indicating that long-term 1-MCP treatment severely altered the metabolites during fruit ripening. 1-MCP 16 h treatment severely reduced the number of metabolites, which primarily consisted of flavonoids, lipids, phenolic acids, alkaloids, and organic acids. An integrated analysis of RNA-Seq and metabolomics showed that various energy metabolites for the tricarboxylic acid cycle were reduced by long-term treatment with 1-MCP, and the glycolic acid cycle was the most significantly affected, as well as the phenylpropane pathway. These results provide valuable information for fruit quality control and new insight into the ripening disorder caused by unsuitable treatment with 1-MCP in papaya.

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Che, Xiaoyu, Christopher R. Brydges, Yuanzhi Yu, Adam Price, Shreyas Joshi, Ayan Roy, Bohyun Lee, et al. "Metabolomic Evidence for Peroxisomal Dysfunction in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome." International Journal of Molecular Sciences 23, no. 14 (July 18, 2022): 7906. http://dx.doi.org/10.3390/ijms23147906.

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Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic and debilitating disease characterized by unexplained physical fatigue, cognitive and sensory dysfunction, sleeping disturbances, orthostatic intolerance, and gastrointestinal problems. People with ME/CFS often report a prodrome consistent with infections. Using regression, Bayesian and enrichment analyses, we conducted targeted and untargeted metabolomic analysis of plasma from 106 ME/CFS cases and 91 frequency-matched healthy controls. Subjects in the ME/CFS group had significantly decreased levels of plasmalogens and phospholipid ethers (p < 0.001), phosphatidylcholines (p < 0.001) and sphingomyelins (p < 0.001), and elevated levels of dicarboxylic acids (p = 0.013). Using machine learning algorithms, we were able to differentiate ME/CFS or subgroups of ME/CFS from controls with area under the receiver operating characteristic curve (AUC) values up to 0.873. Our findings provide the first metabolomic evidence of peroxisomal dysfunction, and are consistent with dysregulation of lipid remodeling and the tricarboxylic acid cycle. These findings, if validated in other cohorts, could provide new insights into the pathogenesis of ME/CFS and highlight the potential use of the plasma metabolome as a source of biomarkers for the disease.

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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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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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Cao, Zhipeng, Tianqi Wang, Wei Xia, Baoli Zhu, Meihui Tian, Rui Zhao, and Dawei Guan. "A Pilot Metabolomic Study on Myocardial Injury Caused by Chronic Alcohol Consumption—Alcoholic Cardiomyopathy." Molecules 26, no. 8 (April 9, 2021): 2177. http://dx.doi.org/10.3390/molecules26082177.

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Chronic alcohol consumption leads to myocardial injury, ventricle dilation, and cardiac dysfunction, which is defined as alcoholic cardiomyopathy (ACM). To explore the induced myocardial injury and underlying mechanism of ACM, the Liber-DeCarli liquid diet was used to establish an animal model of ACM and histopathology, echocardiography, molecular biology, and metabolomics were employed. Hematoxylin-eosin and Masson’s trichrome staining revealed disordered myocardial structure and local fibrosis in the ACM group. Echocardiography revealed thinning wall and dilation of the left ventricle and decreased cardiac function in the ACM group, with increased serum levels of brain natriuretic peptide (BNP) and expression of myocardial BNP mRNA measured through enzyme-linked immunosorbent assay and real-time quantitative polymerase chain reaction (PCR), respectively. Through metabolomic analysis of myocardium specimens, 297 differentially expressed metabolites were identified which were involved in KEGG pathways related to the biosynthesis of unsaturated fatty acids, vitamin digestion and absorption, oxidative phosphorylation, pentose phosphate, and purine and pyrimidine metabolism. The present study demonstrated chronic alcohol consumption caused disordered cardiomyocyte structure, thinning and dilation of the left ventricle, and decreased cardiac function. Metabolomic analysis of myocardium specimens and KEGG enrichment analysis further demonstrated that several differentially expressed metabolites and pathways were involved in the ACM group, which suggests potential causes of myocardial injury due to chronic alcohol exposure and provides insight for further research elucidating the underlying mechanisms of ACM.

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Humer, Elke, Christoph Pieh, and Thomas Probst. "Metabolomic Biomarkers in Anxiety Disorders." International Journal of Molecular Sciences 21, no. 13 (July 6, 2020): 4784. http://dx.doi.org/10.3390/ijms21134784.

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Anxiety disorders range among the most prevalent psychiatric disorders and belong to the leading disorders in the study of the total global burden of disease. Anxiety disorders are complex conditions, with not fully understood etiological mechanisms. Numerous factors, including psychological, genetic, biological, and chemical factors, are thought to be involved in their etiology. Although the diagnosis of anxiety disorders is constantly evolving, diagnostic manuals rely on symptom lists, not on objective biomarkers and treatment effects are small to moderate. The underlying biological factors that drive anxiety disorders may be better suited to serve as biomarkers for guiding personalized medicine, as they are objective and can be measured externally. Therefore, the incorporation of novel biomarkers into current clinical methods might help to generate a classification system for anxiety disorders that can be linked to the underlying dysfunctional pathways. The study of metabolites (metabolomics) in a large-scale manner shows potential for disease diagnosis, for stratification of patients in a heterogeneous patient population, for monitoring therapeutic efficacy and disease progression, and for defining therapeutic targets. All of these are important properties for anxiety disorders, which is a multifactorial condition not involving a single-gene mutation. This review summarizes recent investigations on metabolomics studies in anxiety disorders.

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Knolhoff, Ann M., Katherine M. Nautiyal, Peter Nemes, Sergey Kalachikov, Irina Morozova, Rae Silver, and Jonathan V. Sweedler. "Combining Small-Volume Metabolomic and Transcriptomic Approaches for Assessing Brain Chemistry." Analytical Chemistry 85, no. 6 (March 2013): 3136–43. http://dx.doi.org/10.1021/ac3032959.

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Journal articles on the topic 'Metabolomic chemistry'

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