Metabolite discovery through global annotation of untargeted metabolomics data

Liquid chromatography-high-resolution mass spectrometry (LC-MS)-based metabolomics aims to identify and quantify all metabolites, but most LC-MS peaks remain unidentified. Here we present a global network optimization approach, NetID, to annotate untargeted LC-MS metabolomics data. The approach aims...

Full description

Saved in:

Bibliographic Details
Published in:	Nature methods Vol. 18; no. 11; pp. 1377 - 1385
Main Authors:	Chen, Li, Lu, Wenyun, Wang, Lin, Xing, Xi, Chen, Ziyang, Teng, Xin, Zeng, Xianfeng, Muscarella, Antonio D, Shen, Yihui, Cowan, Alexis, McReynolds, Melanie R, Kennedy, Brandon J, Lato, Ashley M, Campagna, Shawn R, Singh, Mona, Rabinowitz, Joshua D
Format:	Journal Article
Language:	English
Published:	United States Nature Publishing Group 01.11.2021
Subjects:	Algorithms Animals Annotations Chromatography, Liquid - methods Data Curation - methods Data Curation - standards Fragmentation Global optimization Isotopes Liquid chromatography Liver - metabolism Mass spectrometry Mass spectroscopy Metabolites Metabolome Metabolomics Metabolomics - methods Metabolomics - standards Mice Network management systems Optimization Saccharomyces cerevisiae - metabolism Scientific imaging Spectroscopy Tandem Mass Spectrometry - methods Taurine Thiamine Yeast
ISSN:	1548-7091, 1548-7105, 1548-7105
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	Liquid chromatography-high-resolution mass spectrometry (LC-MS)-based metabolomics aims to identify and quantify all metabolites, but most LC-MS peaks remain unidentified. Here we present a global network optimization approach, NetID, to annotate untargeted LC-MS metabolomics data. The approach aims to generate, for all experimentally observed ion peaks, annotations that match the measured masses, retention times and (when available) tandem mass spectrometry fragmentation patterns. Peaks are connected based on mass differences reflecting adduction, fragmentation, isotopes, or feasible biochemical transformations. Global optimization generates a single network linking most observed ion peaks, enhances peak assignment accuracy, and produces chemically informative peak-peak relationships, including for peaks lacking tandem mass spectrometry spectra. Applying this approach to yeast and mouse data, we identified five previously unrecognized metabolites (thiamine derivatives and N-glucosyl-taurine). Isotope tracer studies indicate active flux through these metabolites. Thus, NetID applies existing metabolomic knowledge and global optimization to substantially improve annotation coverage and accuracy in untargeted metabolomics datasets, facilitating metabolite discovery.
AbstractList	Liquid chromatography-high-resolution mass spectrometry (LC-MS)-based metabolomics aims to identify and quantify all metabolites, but most LC-MS peaks remain unidentified. Here we present a global network optimization approach, NetID, to annotate untargeted LC-MS metabolomics data. The approach aims to generate, for all experimentally observed ion peaks, annotations that match the measured masses, retention times and (when available) tandem mass spectrometry fragmentation patterns. Peaks are connected based on mass differences reflecting adduction, fragmentation, isotopes, or feasible biochemical transformations. Global optimization generates a single network linking most observed ion peaks, enhances peak assignment accuracy, and produces chemically informative peak-peak relationships, including for peaks lacking tandem mass spectrometry spectra. Applying this approach to yeast and mouse data, we identified five previously unrecognized metabolites (thiamine derivatives and N-glucosyl-taurine). Isotope tracer studies indicate active flux through these metabolites. Thus, NetID applies existing metabolomic knowledge and global optimization to substantially improve annotation coverage and accuracy in untargeted metabolomics datasets, facilitating metabolite discovery. Liquid chromatography-high-resolution mass spectrometry (LC-MS)-based metabolomics aims to identify and quantify all metabolites, but most LC-MS peaks remain unidentified. Here we present a global network optimization approach, NetID, to annotate untargeted LC-MS metabolomics data. The approach aims to generate, for all experimentally observed ion peaks, annotations that match the measured masses, retention times and (when available) tandem mass spectrometry fragmentation patterns. Peaks are connected based on mass differences reflecting adduction, fragmentation, isotopes, or feasible biochemical transformations. Global optimization generates a single network linking most observed ion peaks, enhances peak assignment accuracy, and produces chemically informative peak-peak relationships, including for peaks lacking tandem mass spectrometry spectra. Applying this approach to yeast and mouse data, we identified five previously unrecognized metabolites (thiamine derivatives and N-glucosyl-taurine). Isotope tracer studies indicate active flux through these metabolites. Thus, NetID applies existing metabolomic knowledge and global optimization to substantially improve annotation coverage and accuracy in untargeted metabolomics datasets, facilitating metabolite discovery.Liquid chromatography-high-resolution mass spectrometry (LC-MS)-based metabolomics aims to identify and quantify all metabolites, but most LC-MS peaks remain unidentified. Here we present a global network optimization approach, NetID, to annotate untargeted LC-MS metabolomics data. The approach aims to generate, for all experimentally observed ion peaks, annotations that match the measured masses, retention times and (when available) tandem mass spectrometry fragmentation patterns. Peaks are connected based on mass differences reflecting adduction, fragmentation, isotopes, or feasible biochemical transformations. Global optimization generates a single network linking most observed ion peaks, enhances peak assignment accuracy, and produces chemically informative peak-peak relationships, including for peaks lacking tandem mass spectrometry spectra. Applying this approach to yeast and mouse data, we identified five previously unrecognized metabolites (thiamine derivatives and N-glucosyl-taurine). Isotope tracer studies indicate active flux through these metabolites. Thus, NetID applies existing metabolomic knowledge and global optimization to substantially improve annotation coverage and accuracy in untargeted metabolomics datasets, facilitating metabolite discovery. Liquid chromatography–high-resolution mass spectrometry (LC-MS)-based metabolomics aims to identify and quantify all metabolites, but most LC-MS peaks remain unidentified. Here we present a global network optimization approach, NetID, to annotate untargeted LC-MS metabolomics data. The approach aims to generate, for all experimentally observed ion peaks, annotations that match the measured masses, retention times and (when available) tandem mass spectrometry fragmentation patterns. Peaks are connected based on mass differences reflecting adduction, fragmentation, isotopes, or feasible biochemical transformations. Global optimization generates a single network linking most observed ion peaks, enhances peak assignment accuracy, and produces chemically informative peak–peak relationships, including for peaks lacking tandem mass spectrometry spectra. Applying this approach to yeast and mouse data, we identified five previously unrecognized metabolites (thiamine derivatives and N-glucosyl-taurine). Isotope tracer studies indicate active flux through these metabolites. Thus, NetID applies existing metabolomic knowledge and global optimization to substantially improve annotation coverage and accuracy in untargeted metabolomics datasets, facilitating metabolite discovery.The NetID algorithm annotates untargeted LC-MS metabolomics data by combining known biochemical and metabolomic principles with a global network optimization strategy.
Author	Zeng, Xianfeng Xing, Xi Chen, Ziyang Muscarella, Antonio D Lu, Wenyun Teng, Xin Singh, Mona Chen, Li Cowan, Alexis Kennedy, Brandon J Wang, Lin Shen, Yihui Campagna, Shawn R McReynolds, Melanie R Lato, Ashley M Rabinowitz, Joshua D
Author_xml	– sequence: 1 givenname: Li surname: Chen fullname: Chen, Li organization: Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA – sequence: 2 givenname: Wenyun orcidid: 0000-0003-1787-2617 surname: Lu fullname: Lu, Wenyun organization: Department of Chemistry, Princeton University, Princeton, NJ, USA – sequence: 3 givenname: Lin orcidid: 0000-0002-9370-6891 surname: Wang fullname: Wang, Lin organization: Department of Chemistry, Princeton University, Princeton, NJ, USA – sequence: 4 givenname: Xi surname: Xing fullname: Xing, Xi organization: Department of Chemistry, Princeton University, Princeton, NJ, USA – sequence: 5 givenname: Ziyang surname: Chen fullname: Chen, Ziyang organization: Department of Molecular Biology, Princeton University, Princeton, NJ, USA – sequence: 6 givenname: Xin surname: Teng fullname: Teng, Xin organization: Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA – sequence: 7 givenname: Xianfeng surname: Zeng fullname: Zeng, Xianfeng organization: Department of Chemistry, Princeton University, Princeton, NJ, USA – sequence: 8 givenname: Antonio D orcidid: 0000-0001-8399-4378 surname: Muscarella fullname: Muscarella, Antonio D organization: Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA – sequence: 9 givenname: Yihui surname: Shen fullname: Shen, Yihui organization: Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA – sequence: 10 givenname: Alexis surname: Cowan fullname: Cowan, Alexis organization: Department of Molecular Biology, Princeton University, Princeton, NJ, USA – sequence: 11 givenname: Melanie R orcidid: 0000-0001-5427-2739 surname: McReynolds fullname: McReynolds, Melanie R organization: Department of Chemistry, Princeton University, Princeton, NJ, USA – sequence: 12 givenname: Brandon J orcidid: 0000-0003-1892-8926 surname: Kennedy fullname: Kennedy, Brandon J organization: Lotus Separations, LLC, Department of Chemistry, Princeton University, Princeton, NJ, USA – sequence: 13 givenname: Ashley M orcidid: 0000-0003-4076-9714 surname: Lato fullname: Lato, Ashley M organization: Department of Chemistry, The University of Tennessee at Knoxville, Knoxville, TN, USA – sequence: 14 givenname: Shawn R surname: Campagna fullname: Campagna, Shawn R organization: Department of Chemistry, The University of Tennessee at Knoxville, Knoxville, TN, USA – sequence: 15 givenname: Mona surname: Singh fullname: Singh, Mona organization: Department of Computer Science, Princeton University, Princeton, NJ, USA – sequence: 16 givenname: Joshua D orcidid: 0000-0002-1247-4727 surname: Rabinowitz fullname: Rabinowitz, Joshua D email: joshr@princeton.edu, joshr@princeton.edu, joshr@princeton.edu, joshr@princeton.edu organization: Ludwig Institute for Cancer Research, Princeton Branch, Princeton, NJ, USA. joshr@princeton.edu
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/34711973$$D View this record in MEDLINE/PubMed
BookMark	eNpdkDtPwzAUhS1URB_wBxiQJRaWwL2xncQjqnhJBRaYIye221SJXWIHqf-eoNKF6Zzhu1efzpxMnHeGkEuEWwRW3AWOQqYJpJgAMmAJOyEzFLxIcgQxOXaQOCXzELYAjPFUnJEp4zmizNmMvL2aqCrfNtFQ3YTaf5t-T-Om98N6Q9etr1RLlXM-qth4R72lg4uqX5toNO0Ox75r6kC1iuqcnFrVBnPxlwvy-fjwsXxOVu9PL8v7VVJnjMeEy0yO2qmtrNSIyioODHUhuJFpJsAW1qJCjhXkXJrMalFpYEqAUlDVNVuQm8PfXe-_BhNi2Y3ypm2VM34IZSokYFqAhBG9_odu_dC70e6XSvOM5-MuC3L1Rw1VZ3S565tO9fvyuBT7ARwUbM8
CitedBy_id	crossref_primary_10_1134_S1061934824020126 crossref_primary_10_1186_s12870_025_06704_6 crossref_primary_10_1007_s00726_022_03179_9 crossref_primary_10_1016_j_ejphar_2024_176539 crossref_primary_10_1021_acs_analchem_4c05315 crossref_primary_10_1080_14789450_2025_2463324 crossref_primary_10_1128_mmbr_00164_22 crossref_primary_10_1111_jipb_13774 crossref_primary_10_1073_pnas_2505532122 crossref_primary_10_1038_s41467_024_50128_z crossref_primary_10_3389_fpls_2025_1478061 crossref_primary_10_1016_j_ecoenv_2025_117711 crossref_primary_10_1016_j_cell_2022_11_023 crossref_primary_10_1016_j_iliver_2024_100142 crossref_primary_10_1016_j_cej_2024_150224 crossref_primary_10_1016_j_tibs_2025_01_010 crossref_primary_10_1038_s42255_024_01119_3 crossref_primary_10_1002_EXP_20210222 crossref_primary_10_1002_smtd_202200130 crossref_primary_10_3389_fevo_2022_841824 crossref_primary_10_1007_s12288_025_02059_y crossref_primary_10_1016_j_freeradbiomed_2025_02_031 crossref_primary_10_1016_j_jchromb_2025_124564 crossref_primary_10_1016_j_aca_2023_341308 crossref_primary_10_1021_acs_analchem_5c01213 crossref_primary_10_1016_j_mib_2022_102195 crossref_primary_10_1016_j_fbio_2024_103997 crossref_primary_10_1155_jcpt_5516416 crossref_primary_10_7554_eLife_91597_3 crossref_primary_10_1016_j_pbi_2025_102729 crossref_primary_10_1016_j_lfs_2023_121619 crossref_primary_10_1186_s12967_024_05100_2 crossref_primary_10_1016_j_jpha_2022_11_006 crossref_primary_10_3389_fpls_2021_803603 crossref_primary_10_1038_s41467_023_44035_y crossref_primary_10_3390_metabo13030460 crossref_primary_10_1038_s41392_023_01399_3 crossref_primary_10_7554_eLife_91597 crossref_primary_10_1038_s41467_023_39617_9 crossref_primary_10_1186_s12951_023_01908_0 crossref_primary_10_1093_nar_gkac376 crossref_primary_10_1038_s41556_023_01117_9 crossref_primary_10_1002_bmc_5733 crossref_primary_10_1021_jasms_2c00153 crossref_primary_10_3390_microorganisms13040915 crossref_primary_10_1038_s41575_024_00914_3 crossref_primary_10_1093_bib_bbae498 crossref_primary_10_3390_metabo12050456 crossref_primary_10_1016_j_ecoenv_2024_115975 crossref_primary_10_1038_s41592_023_01851_w crossref_primary_10_1016_j_trac_2022_116903 crossref_primary_10_1042_EBC20230019 crossref_primary_10_3390_metabo13040522 crossref_primary_10_1093_bioinformatics_btaf161 crossref_primary_10_1186_s43897_022_00038_9 crossref_primary_10_1038_s41467_025_60640_5 crossref_primary_10_3389_fmicb_2023_1097148 crossref_primary_10_1007_s11306_025_02309_0 crossref_primary_10_1038_s41467_024_48009_6 crossref_primary_10_3389_fmolb_2023_1305439 crossref_primary_10_1038_s41586_025_09535_5 crossref_primary_10_1146_annurev_nutr_062322_030557 crossref_primary_10_1016_j_jep_2023_117637 crossref_primary_10_1007_s42994_024_00194_0 crossref_primary_10_1007_s00210_023_02750_9 crossref_primary_10_1101_gad_352277_124 crossref_primary_10_3389_fcimb_2023_1091083 crossref_primary_10_1021_acs_analchem_4c06210 crossref_primary_10_1186_s40001_025_02824_9 crossref_primary_10_1016_j_tplants_2022_06_010 crossref_primary_10_1038_s41467_022_32155_w crossref_primary_10_1016_j_talanta_2025_128327 crossref_primary_10_1146_annurev_immunol_101220_031513 crossref_primary_10_1038_s41598_024_55356_3 crossref_primary_10_1016_j_cell_2025_04_041 crossref_primary_10_1016_j_ymben_2023_01_001 crossref_primary_10_1161_ATVBAHA_122_318332 crossref_primary_10_3390_metabo15060401 crossref_primary_10_1021_jasms_4c00175 crossref_primary_10_1038_s41467_025_56646_8 crossref_primary_10_1016_j_heliyon_2024_e36267 crossref_primary_10_1038_s12276_022_00803_2 crossref_primary_10_1021_acs_analchem_5c00314 crossref_primary_10_1016_j_soilbio_2024_109382 crossref_primary_10_1016_S1875_5364_25_60852_1 crossref_primary_10_1038_s41467_022_35734_z crossref_primary_10_3390_foods14183217 crossref_primary_10_1007_s12672_025_03374_6 crossref_primary_10_1016_j_chroma_2025_465986 crossref_primary_10_1016_j_phrs_2025_107675 crossref_primary_10_1021_envhealth_5c00091 crossref_primary_10_1038_s41467_024_51433_3 crossref_primary_10_1016_j_csbj_2022_09_004 crossref_primary_10_1016_j_jconrel_2024_05_029 crossref_primary_10_1371_journal_pone_0294355 crossref_primary_10_1038_s41592_023_01850_x crossref_primary_10_1016_j_ecoenv_2023_114763 crossref_primary_10_1186_s12859_023_05383_0 crossref_primary_10_1021_acs_est_5c07353 crossref_primary_10_1016_j_aquatox_2025_107522 crossref_primary_10_1007_s00277_025_06302_4 crossref_primary_10_1016_j_tem_2023_09_006 crossref_primary_10_1210_clinem_dgac555 crossref_primary_10_1016_j_scitotenv_2022_159932 crossref_primary_10_1128_msystems_00151_23 crossref_primary_10_1016_j_trac_2023_117287 crossref_primary_10_1371_journal_pone_0326164 crossref_primary_10_1021_jasms_5c00038 crossref_primary_10_1007_s11306_025_02273_9 crossref_primary_10_1186_s12931_025_03250_5 crossref_primary_10_1016_j_cclet_2024_109627 crossref_primary_10_1016_j_tifs_2024_104555 crossref_primary_10_1021_acs_jnatprod_4c00740 crossref_primary_10_3389_fpls_2024_1361183 crossref_primary_10_3390_gucdd1010006 crossref_primary_10_1016_j_clim_2023_109764 crossref_primary_10_1038_s41467_023_39889_1 crossref_primary_10_3389_fphar_2022_894099 crossref_primary_10_1038_s41467_025_63536_6 crossref_primary_10_1016_j_ab_2023_115036 crossref_primary_10_1016_j_indcrop_2025_121126 crossref_primary_10_1111_tpj_16277 crossref_primary_10_1016_j_lwt_2022_113852 crossref_primary_10_1038_s41467_022_34537_6 crossref_primary_10_1016_j_heliyon_2023_e16083 crossref_primary_10_1039_D4RA01384K crossref_primary_10_1093_bib_bbac553 crossref_primary_10_1007_s12031_025_02382_z crossref_primary_10_1016_j_cell_2022_10_011 crossref_primary_10_1128_jvi_00586_23 crossref_primary_10_3389_fpls_2025_1496200 crossref_primary_10_1093_lifemeta_load048 crossref_primary_10_1155_jfbc_9920574 crossref_primary_10_3390_ijms25031682 crossref_primary_10_3390_metabo14110586 crossref_primary_10_1016_j_cmet_2021_12_011
ContentType	Journal Article
Copyright	2021. The Author(s), under exclusive licence to Springer Nature America, Inc. The Author(s), under exclusive licence to Springer Nature America, Inc. 2021.
Copyright_xml	– notice: 2021. The Author(s), under exclusive licence to Springer Nature America, Inc. – notice: The Author(s), under exclusive licence to Springer Nature America, Inc. 2021.
DBID	CGR CUY CVF ECM EIF NPM 3V. 7QL 7QO 7SS 7TK 7U9 7X2 7X7 7XB 88E 88I 8AO 8FD 8FE 8FG 8FH 8FI 8FJ 8FK ABJCF ABUWG AEUYN AFKRA ARAPS ATCPS AZQEC BBNVY BENPR BGLVJ BHPHI BKSAR C1K CCPQU D1I DWQXO FR3 FYUFA GHDGH GNUQQ H94 HCIFZ K9. KB. L6V LK8 M0K M0S M1P M2P M7N M7P M7S P5Z P62 P64 PATMY PCBAR PDBOC PHGZM PHGZT PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS PTHSS PYCSY Q9U RC3 7X8
DOI	10.1038/s41592-021-01303-3
DatabaseName	Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed ProQuest Central (Corporate) Bacteriology Abstracts (Microbiology B) Biotechnology Research Abstracts Entomology Abstracts (Full archive) Neurosciences Abstracts Virology and AIDS Abstracts Agricultural Science Collection ProQuest Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) Science Database (Alumni Edition) ProQuest Pharma Collection Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Natural Science Journals ProQuest Hospital Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) Materials Science & Engineering Collection ProQuest Central (Alumni) ProQuest One Sustainability ProQuest Central Advanced Technologies & Computer Science Collection Agricultural & Environmental Science Collection ProQuest Central Essentials Biological Science Collection ProQuest Central Technology Collection Natural Science Collection Earth, Atmospheric & Aquatic Science Collection Environmental Sciences and Pollution Management ProQuest One Community College ProQuest Materials Science Collection ProQuest Central Engineering Research Database Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student AIDS and Cancer Research Abstracts SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) ProQuest Materials Science Database (NC LIVE) ProQuest Engineering Collection Biological Sciences Agricultural Science Database ProQuest Health & Medical Collection ProQuest Medical Database Science Database Algology Mycology and Protozoology Abstracts (Microbiology C) Biological Science Database Engineering Database Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection Biotechnology and BioEngineering Abstracts Environmental Science Database Earth, Atmospheric & Aquatic Science Database Materials Science Collection ProQuest Central Premium ProQuest One Academic ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China Engineering Collection ProQuest Environmental Science Collection (NC LIVE) ProQuest Central Basic Genetics Abstracts MEDLINE - Academic
DatabaseTitle	MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Agricultural Science Database ProQuest Central Student ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials SciTech Premium Collection ProQuest Central China Environmental Sciences and Pollution Management ProQuest One Applied & Life Sciences ProQuest One Sustainability Health Research Premium Collection Natural Science Collection Health & Medical Research Collection Biological Science Collection ProQuest Central (New) ProQuest Medical Library (Alumni) Engineering Collection Advanced Technologies & Aerospace Collection Engineering Database Virology and AIDS Abstracts ProQuest Science Journals (Alumni Edition) ProQuest Biological Science Collection ProQuest One Academic Eastern Edition Earth, Atmospheric & Aquatic Science Database Agricultural Science Collection ProQuest Hospital Collection ProQuest Technology Collection Health Research Premium Collection (Alumni) Biological Science Database Neurosciences Abstracts ProQuest Hospital Collection (Alumni) Biotechnology and BioEngineering Abstracts Environmental Science Collection Entomology Abstracts ProQuest Health & Medical Complete ProQuest One Academic UKI Edition Environmental Science Database Engineering Research Database ProQuest One Academic ProQuest One Academic (New) Technology Collection Technology Research Database ProQuest One Academic Middle East (New) Materials Science Collection ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest One Health & Nursing ProQuest Natural Science Collection ProQuest Pharma Collection ProQuest Central Earth, Atmospheric & Aquatic Science Collection ProQuest Health & Medical Research Collection Genetics Abstracts ProQuest Engineering Collection Biotechnology Research Abstracts Health and Medicine Complete (Alumni Edition) ProQuest Central Korea Bacteriology Abstracts (Microbiology B) Algology Mycology and Protozoology Abstracts (Microbiology C) Agricultural & Environmental Science Collection AIDS and Cancer Research Abstracts Materials Science Database ProQuest Materials Science Collection ProQuest Central Basic ProQuest Science Journals ProQuest SciTech Collection Advanced Technologies & Aerospace Database ProQuest Medical Library Materials Science & Engineering Collection ProQuest Central (Alumni) MEDLINE - Academic
DatabaseTitleList	MEDLINE MEDLINE - Academic Agricultural Science Database
Database_xml	– sequence: 1 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Biology
EISSN	1548-7105
EndPage	1385
ExternalDocumentID	34711973
Genre	Research Support, U.S. Gov't, Non-P.H.S Research Support, Non-U.S. Gov't Journal Article Research Support, N.I.H., Extramural
GrantInformation_xml	– fundername: Howard Hughes Medical Institute – fundername: NHGRI NIH HHS grantid: T32 HG003284 – fundername: NCI NIH HHS grantid: R50 CA211437
GroupedDBID	--- -~X 0R~ 123 29M 39C 4.4 53G 7X2 7X7 7XC 88E 88I 8AO 8CJ 8FE 8FG 8FH 8FI 8FJ 8R4 8R5 AAHBH AAYZH ABAWZ ABDBF ABJCF ABJNI ABLJU ABUWG ACBWK ACGFS ACGOD ACIWK ACPRK ACUHS ADBBV AENEX AEUYN AFANA AFBBN AFKRA AFRAH AFSHS AGAYW AHBCP AHMBA AHSBF AIBTJ ALFFA ALIPV ALMA_UNASSIGNED_HOLDINGS ARAPS ARMCB ASPBG ATCPS ATHPR AVWKF AXYYD AZFZN AZQEC BBNVY BENPR BGLVJ BHPHI BKKNO BKSAR BPHCQ BVXVI CCPQU CGR CS3 CUY CVF D1I D1J D1K DB5 DU5 DWQXO EBS ECM EE. EIF EJD EMOBN ESX F5P FEDTE FSGXE FYUFA FZEXT GNUQQ HCIFZ HMCUK HVGLF HZ~ IAO IHR INH INR ITC K6- KB. L6V LK5 LK8 M0K M1P M2P M7P M7R M7S NFIDA NNMJJ NPM O9- ODYON P2P P62 PATMY PCBAR PDBOC PHGZM PHGZT PJZUB PPXIY PQGLB PQQKQ PROAC PSQYO PTHSS PYCSY Q2X RNS RNT RNTTT SHXYY SIXXV SJN SNYQT SOJ SV3 TAOOD TBHMF TDRGL TSG TUS UKHRP ~8M 3V. 7QL 7QO 7SS 7TK 7U9 7XB 8FD 8FK AARCD AGSTI C1K FR3 H94 K9. M7N P64 PKEHL PQEST PQUKI PRINS Q9U RC3 7X8 PUEGO
ID	FETCH-LOGICAL-c634t-49690212fbf9d11afa4031d854e92650f8ff1a141b0749e6fd5bd03a50aa0bcc3
IEDL.DBID	M7P
ISICitedReferencesCount	171
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000712400000005&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1548-7091 1548-7105
IngestDate	Wed Oct 01 09:23:16 EDT 2025 Mon Oct 06 17:11:12 EDT 2025 Fri Aug 08 01:51:53 EDT 2025
IsDoiOpenAccess	false
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Issue	11
Language	English
License	2021. The Author(s), under exclusive licence to Springer Nature America, Inc.
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c634t-49690212fbf9d11afa4031d854e92650f8ff1a141b0749e6fd5bd03a50aa0bcc3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ORCID	0000-0002-1247-4727 0000-0002-9370-6891 0000-0001-8399-4378 0000-0003-1787-2617 0000-0001-5427-2739 0000-0003-4076-9714 0000-0003-1892-8926
OpenAccessLink	https://www.osti.gov/servlets/purl/1855984
PMID	34711973
PQID	2592764703
PQPubID	28015
PageCount	9
ParticipantIDs	proquest_miscellaneous_2590128090 proquest_journals_2592764703 pubmed_primary_34711973
PublicationCentury	2000
PublicationDate	2021-11-01
PublicationDateYYYYMMDD	2021-11-01
PublicationDate_xml	– month: 11 year: 2021 text: 2021-11-01 day: 01
PublicationDecade	2020
PublicationPlace	United States
PublicationPlace_xml	– name: United States – name: New York
PublicationTitle	Nature methods
PublicationTitleAlternate	Nat Methods
PublicationYear	2021
Publisher	Nature Publishing Group
Publisher_xml	– name: Nature Publishing Group
SSID	ssj0033425
Score	2.6783836
Snippet	Liquid chromatography-high-resolution mass spectrometry (LC-MS)-based metabolomics aims to identify and quantify all metabolites, but most LC-MS peaks remain... Liquid chromatography–high-resolution mass spectrometry (LC-MS)-based metabolomics aims to identify and quantify all metabolites, but most LC-MS peaks remain...
SourceID	proquest pubmed
SourceType	Aggregation Database Index Database
StartPage	1377
SubjectTerms	Algorithms Animals Annotations Chromatography, Liquid - methods Data Curation - methods Data Curation - standards Fragmentation Global optimization Isotopes Liquid chromatography Liver - metabolism Mass spectrometry Mass spectroscopy Metabolites Metabolome Metabolomics Metabolomics - methods Metabolomics - standards Mice Network management systems Optimization Saccharomyces cerevisiae - metabolism Scientific imaging Spectroscopy Tandem Mass Spectrometry - methods Taurine Thiamine Yeast
Title	Metabolite discovery through global annotation of untargeted metabolomics data
URI	https://www.ncbi.nlm.nih.gov/pubmed/34711973 https://www.proquest.com/docview/2592764703 https://www.proquest.com/docview/2590128090
Volume	18
WOSCitedRecordID	wos000712400000005&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lj9MwEB7RlpW48NoFCqUy0l5Dk9h5-IRY1AqpNIpgWVV7qezYlvZAUpoWqf-eGSeFE3vhMlKU2Io8Y883nhfApeKyQj7rwKRGooGSJgHiuDTg2lRZblFKfEuWmy9ZUeTrtSz7C7e2D6s8nYn-oDZNRXfkM4TpcZYKFNAP258BdY0i72rfQmMAI6qSwH3oXnk6iTkXvukqofIgQ8XYJ82EPJ-1qLgo7jImY5pTjtm_IaZXNYsn__uTT-FxDzLZx04qnsEDWz-Hs67t5PEcipXdI-8p-5hRVi5FcR5Z37GHdSVCmKrrpnPTs8axQ92FjFvDfnSDKZu5ZRRgegHfF_PrT5-Dvq9CUKVc7AMh0SRGleW0kyaKlFMCt7bJE2FljIjN5c5FKhKRRnwhbepMok3IVRIqFeqq4i9gWDe1fQXMZs5IHaaxw9Fo4Coj0lhrS_XIpRDhGCanhdr0m6Pd_F2lMbz78xrFmnwVqrbNwX9DqjOUOMXLjhmbbVd_Y8NRoUYy46_vn_wNPIqJvz5xcALD_e5g38LD6tf-rt1NYZCtM0_zKYyu5kX5FZ-WV--RrsIl0bicenny9BvSolwhLZPb3-Etztg
linkProvider	ProQuest
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LT9wwEB5RoKKX8n6VFiO1x4jE9ibxAVUVD4FYVhyg4hbs2JY4kADZpdo_1d_YmThpT_TGgXNiS858nvkmns8D8FULVaKdTWRTqzBBSQcR8rg0EsaWWe4QJW1Llp_DbDTKb27U5Qz87rUwVFbZ-8TWUdu6pH_k-0jTeZZKBOj3h8eIukbR6WrfQiPA4txNf2HK1hycHaF9v3F-cnx1eBp1XQWiMhVyHEmFCSE6bG-8skmivZYIbJsPpFMc-YrPvU90IhOD0VW51NuBsbHQg1jr2JSlwHnfwRzSCJ63pYKXvecXQrZNXikLiDIMxJ1IJxb5foOBkuo8OSXvgjRtL1PaNrSdLL61j7IEHzsSzX4E1C_DjKtW4H1oqzldhdGFGyO2SV3NSHVMVapT1nUkYuEKFKarqg5lCKz2bFKFknhn2X0YTGrthlEB7Rpcv8pi1mG2qiu3Ccxl3ioTp9zjaEzgtZUpN8bRfetKyngLdnrDFN3mb4p_VtmCvb-PcdvSWYyuXD1p3yFqECucYiMYv3gI94sUAglDojKx_f_Jd2Hh9OpiWAzPRuef4AMnbLUiyR2YHT9N3GeYL5_Hd83TlxalDG5fGwF_ADj_IqQ
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwEB61hVa9lFcfCwsYCY7RJrHz8AFViLJitSXaA0W9BTu2JQ4kbbPbav9af11n4qSc4NYD5ySWkvk8j_j7ZgDeKy4rtLMOTGokFihpEmAelwZcmyrLLaKkG8ny4zQrivz8XC424HbQwhCtcvCJnaM2TUX_yCeYpsdZKhCgE9fTIhYn0-OLy4AmSNFJ6zBOw0Nkbtc3WL61H2cnaOsPcTz98v3z16CfMBBUKRfLQEgsDtF5O-2kiSLllECQmzwRVsaYu7jcuUhFItIYaaVNnUm0CblKQqVCXVUc192ERxk1Le9og4shCnAuuoGvVBEEGQblXrAT8nzSYtAkzmdMhTwnfdvf09suzE2f_M8f6Cns9ck1--R3wzPYsPVz2PbjNtcvoPhml4h5Ul0zUiMTe3XN-klFzLdGYaquG09PYI1jq9pT5a1hv_3DpOJuGRFr9-HsQV7mALbqprZHwGzmjNRhGjt8Ggt7ZUQaa22pD7sUIhzBeDBS2TuFtvxjoRG8u7-M25nOaFRtm1V3D6UMocQlDj0Qygvfd6TkmEhEMuMv_734W9hBw5ens2L-CnZjglmnnRzD1vJqZV_D4-p6-au9etMBlsHPhwbAHVMUK2E
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Metabolite+discovery+through+global+annotation+of+untargeted+metabolomics+data&rft.jtitle=Nature+methods&rft.au=Chen%2C+Li&rft.au=Lu+Wenyun&rft.au=Wang%2C+Lin&rft.au=Xing+Xi&rft.date=2021-11-01&rft.pub=Nature+Publishing+Group&rft.issn=1548-7091&rft.eissn=1548-7105&rft.volume=18&rft.issue=11&rft.spage=1377&rft.epage=1385&rft_id=info:doi/10.1038%2Fs41592-021-01303-3&rft.externalDBID=HAS_PDF_LINK
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1548-7091&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1548-7091&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1548-7091&client=summon