High‐Throughput Metabolomics by 1D NMR

Angewandte Chemie International Edition, Journal Year: 2018, Volume and Issue: 58(4), P. 968 - 994

Published: July 12, 2018

Metabolomics deals with the whole ensemble of metabolites (the metabolome). As one -omic sciences, it relates to biology, physiology, pathology and medicine; but are chemical entities, small organic molecules or inorganic ions. Therefore, their proper identification quantitation in complex biological matrices requires a solid ground. With respect for example, DNA, much more prone oxidation enzymatic degradation: we can reconstruct large parts mammoth's genome from specimen, unable do same its metabolome, which was probably largely degraded few hours after animal's death. Thus, need standard operating procedures, good skills sample preparation storage subsequent analysis, accurate analytical broad knowledge chemometrics advanced statistical tools, at least two metabolomic techniques, MS NMR. All these traditionally cultivated by chemists. Here focus on metabolomics standpoint restrict ourselves From point view, NMR has pros cons does provide peculiar holistic perspective that may speak future adoption as population-wide health screening technique.

Language: Английский

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Elucidating cancer metabolic plasticity by coupling gene regulation with metabolic pathways

Proceedings of the National Academy of Sciences, Journal Year: 2019, Volume and Issue: 116(9), P. 3909 - 3918

Published: Feb. 7, 2019

Metabolic plasticity enables cancer cells to switch their metabolism phenotypes between glycolysis and oxidative phosphorylation (OXPHOS) during tumorigenesis metastasis. However, it is still largely unknown how orchestrate gene regulation balance OXPHOS activities. Previously, by modeling the of we have reported that can acquire a stable hybrid metabolic state in which both be used. Here, comprehensively characterize activity, establish theoretical framework coupling with pathways. Our results demonstrate direct association activities AMPK HIF-1, master regulators glycolysis, respectively, three major pathways: glucose oxidation, fatty acid oxidation. model further characterizes metabolically inactive where low activity OXPHOS. We verify prediction using metabolomics transcriptomics data from paired tumor adjacent benign tissue samples cohort breast patients RNA-sequencing The Cancer Genome Atlas. validate vitro studies aggressive triple-negative (TNBC) cells. experimental confirm TNBC maintain phenotype targeting necessary eliminate plasticity. In summary, our work serves as platform symmetrically study tuning modulates pathway vice versa.

Language: Английский

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Biostimulants for Plant Growth and Mitigation of Abiotic Stresses: A Metabolomics Perspective

Metabolites, Journal Year: 2020, Volume and Issue: 10(12), P. 505 - 505

Published: Dec. 10, 2020

Adverse environmental conditions due to climate change, combined with declining soil fertility, threaten food security. Modern agriculture is facing a pressing situation where novel strategies must be developed for sustainable production and Biostimulants, conceptually defined as non-nutrient substances or microorganisms the ability promote plant growth health, represent potential provide economically favorable solutions that could introduce approaches improve agricultural practices crop productivity. Current knowledge phenotypic observations suggest biostimulants potentially function in regulating modifying physiological processes plants growth, alleviate stresses, quality yield. However, successfully develop biostimulant-based formulations programs, understanding biostimulant-plant interactions, at molecular, cellular levels, prerequisite. Metabolomics, multidisciplinary omics science, offers unique opportunities predictively decode mode of action on plants, identify signatory markers biostimulant action. Thus, this review intends highlight current scientific efforts gaps research industry, context promotion stress responses. The firstly revisits models have been elucidated describe molecular machinery employed by coping stresses. Furthermore, definitions, claims applications are pointed out, also indicating lack biological basis accurately postulate mechanisms biostimulants. articulates briefly key aspects metabolomics workflow (potential) science industry.

Language: Английский

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Corruption of the Pearson correlation coefficient by measurement error and its estimation, bias, and correction under different error models

Scientific Reports, Journal Year: 2020, Volume and Issue: 10(1)

Published: Jan. 16, 2020

Correlation coefficients are abundantly used in the life sciences. Their use can be limited to simple exploratory analysis or construct association networks for visualization but they also basic ingredients sophisticated multivariate data methods. It is therefore important have reliable estimates correlation coefficients. In modern sciences, comprehensive measurement techniques measure metabolites, proteins, gene-expressions and other types of data. All these errors. Whereas old days, with measurements, errors were simple, that not case anymore. Errors heterogeneous, non-constant independent. This hampers quality estimated seriously. We will discuss different as present science show theory, simulations real-life how affect briefly ways improve estimation such

Language: Английский

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The contribution of gut bacterial metabolites in the human immune signaling pathway of non-communicable diseases

Gut Microbes, Journal Year: 2021, Volume and Issue: 13(1)

Published: Jan. 1, 2021

The interaction disorder between gut microbiota and its host has been documented in different non-communicable diseases (NCDs) such as metabolic syndrome, neurodegenerative disease, autoimmune disease. majority of these altered interactions arise through cross-talk immune system, inducing a low-grade chronic inflammation that characterizes all NCDs. In this review, we discuss the contribution bacterial metabolites to signaling pathways involved We then review recent advances aid rationally design microbial therapeutics. A deeper understanding intersections metabolism using metabolomics-based system biology platform promises reveal fundamental mechanisms drive predispositions disease suggest new avenues use therapeutic opportunities for NCDs treatment prevention.

Language: Английский

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Pathway analysis in metabolomics: Recommendations for the use of over-representation analysis

PLoS Computational Biology, Journal Year: 2021, Volume and Issue: 17(9), P. e1009105 - e1009105

Published: Sept. 7, 2021

Over-representation analysis (ORA) is one of the commonest pathway approaches used for functional interpretation metabolomics datasets. Despite widespread use ORA in metabolomics, community lacks guidelines detailing its best-practice use. Many factors have a pronounced impact on results, but to date their effects received little systematic attention. Using five publicly available datasets, we demonstrated that changes parameters such as background set, differential metabolite selection methods, and database can result profoundly different results. The non-assay-specific example, resulted large numbers false-positive pathways. Pathway choice, evaluated using three most popular metabolic databases (KEGG, Reactome, BioCyc), led vastly results both number function significantly enriched Factors are specific data, reliability compound identification chemical bias analytical platforms also impacted Simulated misidentification rates low 4% gain pathways loss truly significant across all Our several practical implications users, well those alternative methods. We offer set recommendations alongside minimal reporting guidelines, first step towards standardisation metabolomics.

Language: Английский

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Drug-microbiota interactions: an emerging priority for precision medicine

Signal Transduction and Targeted Therapy, Journal Year: 2023, Volume and Issue: 8(1)

Published: Oct. 9, 2023

Abstract Individual variability in drug response (IVDR) can be a major cause of adverse reactions (ADRs) and prolonged therapy, resulting substantial health economic burden. Despite extensive research pharmacogenomics regarding the impact individual genetic background on pharmacokinetics (PK) pharmacodynamics (PD), diversity explains only limited proportion IVDR. The role gut microbiota, also known as second genome, its metabolites modulating therapeutic outcomes human diseases have been highlighted by recent studies. Consequently, burgeoning field pharmacomicrobiomics aims to explore correlation between microbiota variation IVDR or ADRs. This review presents an up-to-date overview intricate interactions classical agents for systemic diseases, including cancer, cardiovascular (CVDs), endocrine others. We summarise how directly indirectly, modify absorption, distribution, metabolism, excretion (ADME) drugs. Conversely, drugs modulate composition function leading changes microbial metabolism immune response. discuss practical challenges, strategies, opportunities this field, emphasizing critical need develop innovative approach multi-omics, integrate various data types, genomic data, well translate lab into clinical practice. To sum up, represents promising avenue address improve patient outcomes, further is imperative unlock full potential precision medicine.

Language: Английский

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Metabolomics in the study of retinal health and disease

Progress in Retinal and Eye Research, Journal Year: 2018, Volume and Issue: 69, P. 57 - 79

Published: Nov. 10, 2018

Language: Английский

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PhenoMeNal: processing and analysis of metabolomics data in the cloud

GigaScience, Journal Year: 2018, Volume and Issue: 8(2)

Published: Dec. 7, 2018

Metabolomics is the comprehensive study of a multitude small molecules to gain insight into an organism's metabolism. The research field dynamic and expanding with applications across biomedical, biotechnological, many other applied biological domains. Its computationally intensive nature has driven requirements for open data formats, repositories, analysis tools. However, rapid progress resulted in mosaic independent, sometimes incompatible, methods that are difficult connect useful complete solution. PhenoMeNal (Phenome Metabolome aNalysis) advanced solution set up Infrastructure-as-a-Service (IaaS) brings workflow-oriented, interoperable metabolomics platforms cloud. seamlessly integrates wide array existing open-source tools tested packaged as Docker containers through project's continuous integration process deployed based on kubernetes orchestration framework. It also provides number standardized, automated, published workflows user interfaces Galaxy, Jupyter, Luigi, Pachyderm. constitutes keystone cloud e-infrastructures available metabolomics. unique setting easy-to-use web can be scaled any custom public private environment. By harmonizing automating software installation configuration ready-to-use scientific workflow interfaces, succeeded providing scientists workflow-driven, reproducible, shareable interfaced standard representative datasets, versioned, have been reproducibility interoperability. elastic implementation further allows easy adaptation infrastructure application areas 'omics

Language: Английский

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Recurrent Topics in Mass Spectrometry-Based Metabolomics and Lipidomics—Standardization, Coverage, and Throughput

Analytical Chemistry, Journal Year: 2020, Volume and Issue: 93(1), P. 519 - 545

Published: Nov. 28, 2020

RETURN TO ISSUEPREVReviewNEXTRecurrent Topics in Mass Spectrometry-Based Metabolomics and Lipidomics—Standardization, Coverage, ThroughputEvelyn RamplerEvelyn RamplerDepartment of Analytical Chemistry, Faculty University Vienna, Währinger Str. 38, 1090 AustriaVienna Center (VIME), Althanstraße 14, AustriaUniversity AustriaMore by Evelyn RamplerView Biographyhttp://orcid.org/0000-0002-9429-7663, Yasin El AbieadYasin AbieadDepartment AbieadView Biography, Harald SchoenyHarald SchoenyDepartment SchoenyView Biographyhttp://orcid.org/0000-0001-8696-481X, Mate RuszMate RuszDepartment AustriaInstitute Inorganic Straße 42, RuszView Felina HildebrandFelina HildebrandDepartment HildebrandView Veronika FitzVeronika FitzDepartment FitzView Gunda Koellensperger*Gunda KoellenspergerDepartment Austria*Email: [email protected]. Phone: +43-1-4277-52303.More KoellenspergerView Biographyhttp://orcid.org/0000-0002-1460-4919Cite this: Anal. Chem. 2021, 93, 1, 519–545Publication Date (Web):November 28, 2020Publication History Published online28 November 2020Published inissue 12 January 2021https://doi.org/10.1021/acs.analchem.0c04698Copyright © 2020 American Chemical SocietyRIGHTS & PERMISSIONSACS AuthorChoicewith CC-BYlicenseArticle Views7341Altmetric-Citations10LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum full text article downloads since 2008 (both PDF HTML) across all institutions individuals. These metrics regularly updated to reflect usage leading up last few days.Citations number other articles citing this article, calculated Crossref daily. Find more information about citation counts.The Altmetric Attention Score is a quantitative measure attention that research has received online. Clicking on donut icon will load page at altmetric.com with additional details score social media presence for given article. how calculated. Share Add toView InAdd Full Text ReferenceAdd Description ExportRISCitationCitation abstractCitation referencesMore Options onFacebookTwitterWechatLinked InReddit (5 MB) Get e-AlertsSUBJECTS:Lipids,Metabolomics,Metabolism,Fungi,Materials e-Alerts

Language: Английский

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