Metabolomics: an emerging but powerful tool for precision medicine

Molecular Case Studies, Journal Year: 2015, Volume and Issue: 1(1), P. a000588 - a000588

Published: Sept. 24, 2015

Metabolomics, which is defined as the comprehensive analysis of metabolites in a biological specimen, an emerging technology that holds promise to inform practice precision medicine. Historically, small numbers have been used diagnose complex metabolic diseases well monogenic disorders such inborn errors metabolism. Current metabolomic technologies go beyond scope standard clinical chemistry techniques and are capable precise analyses hundreds thousands metabolites. Consequently, metabolomics affords detailed characterization phenotypes can enable medicine at number levels, including derangements underlie disease, discovery new therapeutic targets, biomarkers may be either disease or monitor activity therapeutics.

Language: Английский

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Metabolite Measurement: Pitfalls to Avoid and Practices to Follow

Annual Review of Biochemistry, Journal Year: 2017, Volume and Issue: 86(1), P. 277 - 304

Published: June 20, 2017

Metabolites are the small biological molecules involved in energy conversion and biosynthesis. Studying metabolism is inherently challenging due to metabolites’ reactivity, structural diversity, broad concentration range. Herein, we review common pitfalls encountered metabolomics provide concrete guidelines for obtaining accurate metabolite measurements, focusing on water-soluble primary metabolites. We show how seemingly straightforward sample preparation methods can introduce systematic errors (e.g., owing interconversion among metabolites) proper selection of quenching solvent acidic acetonitrile:methanol:water) mitigate such problems. discuss specific strengths, pitfalls, best practices each analytical platform: liquid chromatography-mass spectrometry (LC-MS), gas (GC-MS), nuclear magnetic resonance (NMR), enzyme assays. Together this information provides a pragmatic knowledge base carrying out biologically informative measurements.

Language: Английский

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Two-Dimensional Liquid Chromatography: A State of the Art Tutorial

Analytical Chemistry, Journal Year: 2016, Volume and Issue: 89(1), P. 519 - 531

Published: Nov. 28, 2016

ADVERTISEMENT RETURN TO ISSUEPREVFeatureNEXTTwo-Dimensional Liquid Chromatography: A State of the Art TutorialIn this tutorial, we discuss motivations for doing two-dimensional liquid chromatography (2D-LC) and describe commonly used implementations method. We review important guiding principles method development, state art in 2D-LC performance as measured by peak capacity, example applications from different fields that hope will inspire new users to adopt their analytical problems.Dwight R. Stoll*† Peter W. Carr‡View Author Information† Department Chemistry, Gustavus Adolphus College, Saint Peter, Minnesota 56082, United States‡ University Minnesota, Minneapolis, 55104, States*E-mail: [email protected]. Phone: 507-933-0699.Cite this: Anal. Chem. 2017, 89, 1, 519–531Publication Date (Web):November 28, 2016Publication History Published online9 December 2016Published inissue 3 January 2017https://pubs.acs.org/doi/10.1021/acs.analchem.6b03506https://doi.org/10.1021/acs.analchem.6b03506newsACS PublicationsCopyright © 2016 American Chemical Society. This publication is available under these Terms Use. Request reuse permissions free access through site. Learn MoreArticle Views26081Altmetric-Citations235LEARN ABOUT THESE METRICSArticle Views are COUNTER-compliant sum full text article downloads since November 2008 (both PDF HTML) across all institutions individuals. These metrics regularly updated reflect usage leading up last few days.Citations number other articles citing article, calculated Crossref daily. Find more information about citation counts.The Altmetric Attention Score a quantitative measure attention research has received online. Clicking on donut icon load page at altmetric.com with additional details score social media presence given article. how calculated. Share Add toView InAdd Full Text ReferenceAdd Description ExportRISCitationCitation abstractCitation referencesMore Options onFacebookTwitterWechatLinked InRedditEmail (5 MB) Get e-AlertscloseSUBJECTS:Chromatography,Computer simulations,Mixtures,Peptides proteins,Selectivity e-Alerts

Language: Английский

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Beyond the paradigm: Combining mass spectrometry and nuclear magnetic resonance for metabolomics

Progress in Nuclear Magnetic Resonance Spectroscopy, Journal Year: 2017, Volume and Issue: 100, P. 1 - 16

Published: Jan. 11, 2017

Language: Английский

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Optimized Analytical Procedures for the Untargeted Metabolomic Profiling of Human Urine and Plasma by Combining Hydrophilic Interaction (HILIC) and Reverse-Phase Liquid Chromatography (RPLC)–Mass Spectrometry*

Molecular & Cellular Proteomics, Journal Year: 2015, Volume and Issue: 14(6), P. 1684 - 1695

Published: March 19, 2015

Profiling of body fluids is crucial for monitoring and discovering metabolic markers health disease providing insights into human physiology. Since urine plasma each contain an extreme diversity metabolites, a single liquid chromatographic system when coupled to mass spectrometry (MS) not sufficient achieve reasonable metabolome coverage. Hydrophilic interaction chromatography (HILIC) offers complementary information reverse-phase (RPLC) by retaining polar metabolites. With the objective finding optimal combined solution profile plasma, we systematically investigated performance five HILIC columns with different chemistries operated at three pH (acidic, neutral, basic) C18-silica RPLC columns. The zwitterionic column ZIC-HILIC neutral provided on large set hydrophilic Hypersil GOLD Zorbax SB aq were proven be best suited profiling respectively. Importantly, optimized HILIC-MS method showed excellent intrabatch peak area reproducibility (CV < 12%) good long-term interbatch (40 days) 22%) that similar those RPLC-MS procedures. Finally, combining HILIC- approaches greatly expanded coverage 44% 108% new features detected compared alone proposed LC-MS improve comprehensiveness global thus are valuable changes associated in clinical research studies. Metabolomics relatively recent "omic" aims measuring quantity collection metabolites (i.e. low-molecular-weight organic compounds, typically 1,500 Da). It often applied study diseases (1Sreekumar A. Poisson L.M. Rajendiran T.M. Khan A.P. Cao Q. Yu J. Laxman B. Mehra R. Lonigro R.J. Li Y. Nyati M.K. Ahsan Kalyana-Sundaram S. Han X. Byun Omenn G.S. Ghosh D. Pennathur Alexander D.C. Berger Shuster J.R. Wei J.T. Varambally Beecher C. Chinnaiyan A.M. Metabolomic profiles delineate potential role sarcosine prostate cancer progression.Nature. 2009; 457: 910-914Crossref PubMed Scopus (1741) Google Scholar, 2Kim K. Aronov P. Zakharkin S.O. Anderson Perroud Thompson I.M. Weiss R.H. Urine metabolomics analysis kidney detection biomarker discovery.Mol. Cell. Proteomics. 8: 558-570Abstract Full Text PDF (235) Scholar) characterization deregulated pathways discovery therapeutic targets biomarkers), drug toxicity efficacy (3Kaddurah-Daouk Kristal B.S. Weinshilboum R.M. Metabolomics: A biochemical approach response disease.Ann. Rev. Pharm. Toxicol. 2008; 48: 653-683Crossref (545) Scholar), environmental exposure (e.g. food (4Tulipani Llorach Jáuregui O. López-Uriarte Garcia-Aloy M. Bullo Salas-Salvadó Andrés-Lacueva unveils urinary subjects syndrome following 12-week nut consumption.J. Proteome Res. 2011; 10: 5047-5058Crossref (88) 5Pujos-Guillot E. Hubert Martin J.F. Lyan Quintana Claude Chabanas Rothwell J.A. Bennetau-Pelissero Scalbert Comte Hercberg Morand Galan Manach Mass spectrometry-based biomarkers fruit vegetable intake: Citrus as case study.J. 2013; 12: 1645-1659Crossref (128) Scholar)) lifestyle fitness (6Morris Grada C.O. Ryan Roche H.M. De Vito G. Gibney M.J. E.R. Brennan L. relationship between aerobic level healthy adults.Mol. Nutr. Food 57: 1246-1254Crossref (48) health. advantageous over other "omics" genomics, transcriptomics, proteomics) because it measures more direct functional readout activity phenotype (7Patti G.J. Yanes Siuzdak Innovation: apogee omics trilogy.Molecular Cell Biology. 2012; 13: 263-269Google Scholar). When biofluids blood), reveals snapshot "metabolic status" subject such holds great promise personalized medicine (8Chen Mias G.I. Li-Pook-Than Jiang Lam H.Y. Chen Miriami Karczewski K.J. Hariharan Dewey F.E. Cheng Clark Im H. Habegger Balasubramanian O'Huallachain Dudley Hillenmeyer Haraksingh Sharon Euskirchen Lacroute Bettinger Boyle Kasowski Grubert F. Seki Garcia Whirl-Carrillo Gallardo Blasco M.A. Greenberg P.L. Snyder Klein T.E. Altman R.B. Butte A.J. Ashley E.A. Gerstein Nadeau K.C. Tang Personal dynamic molecular medical phenotypes.Cell. 148: 1293-1307Abstract (908) 9Snyder X.Y. robust tool systems biology medicine: An open letter community.Metabolomics. 9: 532-534Crossref Metabolic studies mostly performed using i) instruments, including gas (GC)-MS (LC)-MS, well ii) nuclear magnetic resonance (NMR) spectroscopy platforms. Few have highlighted benefit multiplatform blood (10Büscher J.M. Czernik Ewald J.C. Sauer U. Zamboni N. Cross-platform comparison methods quantitative primary metabolism.Anal. Chem. 81: 2135-2143Crossref (264) 11Psychogios Hau D.D. Peng Guo A.C. Mandal Bouatra Sinelnikov I. Krishnamurthy Eisner Gautam Young Xia J.G. Knox Dong Huang Hollander Z. Pedersen T.L. Smith S.R. Bamforth Greiner McManus Newman J.W. Goodfriend T. Wishart D.S. serum metabolome.PloS One. 6: e16957Crossref (1153) 12Bouatra Aziat Wilson M.R. Bjorndahl T.C. Saleem Liu Dame Z.T. Poelzer Huynh Yallou F.S. Psychogios Bogumil Roehring e73076Crossref (928) However, due instrumentation limitation, most laboratories use analytical approach. Because its high sensitivity wide range can analyzed, utilization has rapidly past 10 years (13Kuehnbaum N.L. Britz-McKibbin New advances separation science metabolomics: Resolving chemical post-genomic era.Chem. 113: 2437-2468Crossref (250) Most untargeted (RPLC, mainly C18-bonded silica columns) generates reproducible data (non- moderately compounds) (14Want E.J. I.D. Gika Theodoridis Plumb R.S. Shockcor Holmes Nicholson J.K. Global procedures UPLC-MS.Nature Protocols. 2010; 5: 1005-1018Crossref (754) 15Dunn W.B. Broadhurst Begley Zelena Francis-McIntyre Brown Knowles J.D. Halsall Haselden J.N. Nicholls A.W. Kell D.B. Goodacre Human Serum Metabolome Procedures large-scale spectrometry.Nature 1060-1083Crossref (1720) many water soluble, polar, ionic amino acids, sulfates, sugars) usually retained columns, hindering their identification accurate quantification (16Roux Xu Heilier Olivier M.F. Ezan Tabet Junot Annotation adult metabolite ultra linear quadrupole ion trap-Orbitrap spectrometer.Anal. 84: 6429-6437Crossref (95) 17Boudah Aros-Calt Oliveira Fenaille coupling high-resolution spectrometry.J. Chrom. B Anal. Tech. Biomed. Life Sci. 2014; 966: 34-47Crossref (82) 1The abbreviations used are:HILIChydrophilic chromatographyRPLCreverse-phase chromatographyHMDBhuman database. now becoming popular selectivity (18Bajad S.U. Lu W. Kimball E.H. Yuan Peterson Rabinowitz Separation quantitation soluble cellular chromatography-tandem 2006; 1125: 76-88Crossref (484) 19Cubbon Antonio Thomas-Oates applications HILIC-LC-MS.Mass Spectrom. 29: 671-684Crossref (144) 20Spagou Tsoukali Raikos MS metabonomic/metabolomic studies.J. 33: 716-727Crossref (181) 21Tang D.Q. Zou Yin X.X. Ong C.N. attractive RPLC-MS.Mass plethora stationary phases been developed separated four categories: anionic (mostly bare silica), cationic (silica derivatized positively charged group, aminopropyl), iii) uncharged amide), iv) group bearing positive negative charge, sulfobetaine). extensively reviewed (22Hemström Irgum chromatography.J. 1784-1821Crossref (1039) 23Guo Gaiki Retention 1218: 5920-5938Crossref (254) 24Jandera Stationary mobile chromatography: review.Anal. Chim. Acta. 692: 1-25Crossref (538) methodologies targeted analyses focusing small subset nucleosides derivatives (25Kawachi Ikegami Takubo Miyamoto Tanaka Chromatographic phases: Hydrophilicity, charge effects, structural selectivity, efficiency.J. 5903-5919Crossref (149) neurotransmitters (26Chirita R.I. West Finaru A.L. Elfakir Approach selection: application analysis.J. 1217: 3091-3104Crossref (109) peptides (27Van Dorpe Vergote V. Pezeshki Burvenich Peremans Spiegeleer LC peptides: Columns clustering.J. 728-739Crossref (50) Scholar)). Despite usefulness analyses, still represents challenge less (retention time signal drift time) requires longer equilibration than (19Cubbon As such, 15% LC-MS-based metabolomic published 2013 both (28Ivanisevic Zhu Z.J. Plate Tautenhahn O'Brien P.J. Johnson C.H. Marletta Patti Toward omic scale profiling: dual separation-mass lipid central carbon 85: 6876-6884Crossref (208) 29Townsend Clish C.B. Kraft Wu Souza Deik A.A. Tworoger S.S. Wolpin B.M. Reproducibility among men women 2 cohort studies.Clin. 59: 1657-1667Crossref (148) 30Trushina Dutta Persson X.M. Mielke M.M. Petersen R.C. Identification altered CSF mild cognitive impairment Alzheimer's metabolomics.PloS e63644Crossref (293) 31Yang Cruickshank Armstrong Mahaffey Reisdorph sample preparation results improved metabolome.J. 1300: 217-226Crossref (93) 32Zhang Watson D.G. Wang Abbas Murdoch Bashford Ahmad N.Y. Ng Leung Application holistic chromatography-high resolution based discovery.PloS e65880Crossref (49) Among these studies, there was no consensus procedure (column conditions) will produce blood. In this context, variety under conditions standard mixtures biological samples. After having determined from RPLC-MS, estimated intra- retention conditions. Adequate conditioning resulted approaches. complementarity electrospray ionization (ESI) modes found condition detected, Analytical grade standards purchased various companies detailed supplementary Excel file S1. Four containing total 174 diverse compounds prepared final concentration μm 50% acetonitrile. For RPLC, one mixture 22 5% Ammonium acetate, ammonium hydroxide, formic acid, acetic acid Sigma Aldrich (St. Louis, MO, USA). MS-grade water, acetonitrile, methanol Fischer Scientific (Morris Plains, NJ, Residual samples obtained de-identified donors informed consent approved Stanford's Institutional Review Board. collection, immediately centrifuged 21,000g min 4 °C. supernatant aliquoted stored −80 °C prior analysis. diluted factor 75% acetonitrile 100% experiments, Blood Stanford Center. Plasma whole treated anti-clot EDTA kept h before being volumes acetone:acetonitrile:methanol (1:1:1, v/v) solvent mixture, mixed 15 incubated −20 allow protein precipitation collected after centrifugation 10,000 rpm evaporated dryness. dry extracts reconstituted Standard mixtures, analyzed Agilent 1260 Infinity HPLC 6538 UHD Q-TOF MS. equipped ESI probe full scan mode. acquired 50 1,000 m/z rate 1.5 spectra/s centroid mode (m/z 127). source follow: temperature 325 °C, drying 9 l/min, nebulizer 45 psig, fragmentor 125 V, skimmer 47 V capillary voltage 3,500V or −3,500V modes, Reference masses 121.0509 (Purine) 922.0098 (hexakis(1H, 1H, 3H-tetrafluoropropoxy)phosphazine, HP-0921) 112.9856 (TFA anion) 980.0164 (HP-0921 + acetate) internal calibration during runs. Five compared: BEH (Ethylene Bridged Hybrid) amide, HILIC, Syncronis (see experimental section details). Mobile 6.9 consisted mm acetate 5/95 acetonitrile/water (A) 95/5 (B). modified 0.1% acidic 3.4 0.5% 25% hydroxide basic 10.15 measured absence Metabolites eluted 0.5 ml/min 1–50% phase gradient min. Before injection, equilibrated 5 1% oven 40 injection volume μl. GOLD, aq, C18, Kinetex, 0.06% MeOH flow leading backpressure 260–280 bar 99% 1–80% 9–10 section). 60 (characterized unique mass/charge ratio extracted MassHunter Qualitative Analysis Software B.05.00 (Agilent Technologies, Santa Clara, CA) absolute height filter counts. scoring created assign score takes account time, shape, calculated, XCMS (various forms (X) spectrometry) (33Smith C.A. Want O'Maille Abagyan XCMS: Processing Nonlinear alignment, matching, identification.Anal. 78: 779-787Crossref (3246) package (version 1.39.4) R 3.0.1) 2,000 Grouping annotation CAMERA (34Kuhl Böttcher Larson T.R. Neumann CAMERA: integrated strategy compound spectra extraction chromatography/mass sets.Anal. 283-289Crossref (710) 1.16.0). parameters section. Features putatively identified matching (± ppm) against local database 33,442 entries generated Creek et al., (35Creek D.J. Jankevics Breitling Barrett M.P. Burgess K.E. chromatography-mass spectrometry: Improved prediction.Anal. 83: 8703-8710Crossref (270) slight modifications. examined; two composed (BEH amide HILIC), (Syncronis ZIC-HILIC). Bare silica, selected toward 27Van 36Lämmerhofer Richter Nogueira Bicker Lindner Mixed-mode ion-exchangers comparative reversed-phase elution modes.J. 31: 2572-2588Crossref (145) 37Periat Debrus Rudaz Guillarme Screening relevant development ultra-high 1282: 72-83Crossref (67) We did assay aminopropyl (such Luna NH2) reported shorter life 28Ivanisevic 38Yuan Breitkopf S.B. Yang Asara positive/negative ion-switching, platform bodily fluids, cells, fresh fixed tissue.Nature 7: 872-881Crossref (640) tested conditions: (pH 3.4), 6.9), 10.15). Only subjected stable above 8–9. Altogether, 11 run commonly To facilitate conditions, first complex 46 important properties (Excel S1). qualitative assigns created. calculated categorized all groups: "good" (green), "acceptable" (yellow), "unacceptable" (red). feature will: retain avoid suppression void zone; narrow provide integration; intense accurately extracted, aligned, quantified, identified. acceptable if fulfilled. remaining classified unacceptable, broad multiple peaks low intensity. Of standards, adenosine, adenine, uridine) excluded they poorly Overall, superior separating 43 had (Fig. 1A). comparison, 67% Some representative examples presented Fig. Baseline l-leucine l-isoleucine could only achieved glucose 1-phosphate 6-phosphate. Similarly, acids (aspartic glutamic acids) cystine (oxidation cysteine molecules) resolved column. next same known complexity maximize number score. tested, highest (4,549) 1B). This better pH, which yielded 4,306 4,141 scores, Interestingly, efficient prominent S2). measure

Language: Английский

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Avoiding Misannotation of In-Source Fragmentation Products as Cellular Metabolites in Liquid Chromatography–Mass Spectrometry-Based Metabolomics

Analytical Chemistry, Journal Year: 2015, Volume and Issue: 87(4), P. 2273 - 2281

Published: Jan. 15, 2015

Liquid chromatography-mass spectrometry (LC-MS) technology allows for rapid quantitation of cellular metabolites, with metabolites identified by mass and chromatographic retention time. Recently, the development scanning high-resolution high accuracy spectrometers desire throughput screening, minimal or no separation has become increasingly popular. When analyzing complex extracts, however, lack could potentially result in misannotation structurally related metabolites. Here, we show that, even using electrospray ionization, a soft ionization method, in-source fragmentation generates unwanted byproducts identical to common For example, nucleotide-triphosphates generate nucleotide-diphosphates, hexose-phosphates triose-phosphates. We evaluated yeast intracellular metabolite extracts found more than 20 cases fragments that mimic Accordingly, is required accurate many

Language: Английский

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Mass spectrometry-based metabolomics in health and medical science: a systematic review

RSC Advances, Journal Year: 2020, Volume and Issue: 10(6), P. 3092 - 3104

Published: Jan. 1, 2020

Metabolomics is the study of investigation small molecules derived from cellular and organism metabolism, which reflects outcomes complex network biochemical reactions in living systems.

Language: Английский

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Meta-Inflammation and Metabolic Reprogramming of Macrophages in Diabetes and Obesity: The Importance of Metabolites

Frontiers in Immunology, Journal Year: 2021, Volume and Issue: 12

Published: Nov. 5, 2021

Diabetes mellitus type II and obesity are two important causes of death in modern society. They characterized by low-grade chronic inflammation metabolic dysfunction (meta-inflammation), which is observed all tissues involved energy homeostasis. A substantial body evidence has established an role for macrophages these during the development diabetes obesity. Macrophages can activate into specialized subsets cues from their microenvironment to handle a variety tasks. Many different have been described diabetes/obesity literature main classifications widely used that also defined differential reprogramming taking place fuel functions. Classically activated, pro-inflammatory (often referred as M1) favor glycolysis, produce lactate instead metabolizing pyruvate acetyl-CoA, tricarboxylic acid cycle interrupted at points. Alternatively activated M2) mainly use beta-oxidation fatty acids oxidative phosphorylation create energy-rich molecules such ATP tissue repair downregulation inflammation. Since alterations organism level, may induce changes macrophage metabolism resulting unique activation patterns This review describes interactions between conditions like We focus on possibilities measuring range metabolites intra-and extracellularly precise comprehensive manner better identify polarized Advantages disadvantages currently most metabolite analysis approaches highlighted. further describe how combined serve provide overview take intracellularly

Language: Английский

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Detection and analysis of chiral molecules as disease biomarkers

Nature Reviews Chemistry, Journal Year: 2023, Volume and Issue: 7(5), P. 355 - 373

Published: March 20, 2023

Language: Английский

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Progress in Understanding Metabolic Syndrome and Knowledge of Its Complex Pathophysiology

Diabetology, Journal Year: 2023, Volume and Issue: 4(2), P. 134 - 159

Published: April 12, 2023

The metabolic syndrome (MetS), first introduced by Haller in 1975, was sometimes also known as insulin resistance syndrome, X, and plurimetabolic syndrome. In 1989, it rechristened Kaplan the “Deadly Quartet” based on a consolidation of central obesity, impaired glucose tolerance, dyslipidemia, systemic hypertension. MetS is positively associated with pro-inflammatory pro-thrombotic state, attributed to increased inflammatory marker activity. Moreover, frequently atherosclerotic cardiovascular disease, hyperuricemia, obstructive sleep apnea, chronic kidney disease. Despite concerted endeavors worldwide, complexity pathophysiology still needs be clearly understood. Currently, therapeutic possibilities are confined individual therapy for hyperglycemia, hypertension, hypertriglyceridemia, regular physical exercise, restricted diet. this review, progress regarding understanding MetS; recent emerging technologies, such metabolomics proteomics; relation diabetes, diseases; association COVID-19 discussed.

Language: Английский

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