Improved Annotation of Untargeted Metabolomics Data through Buffer Modifications That Shift Adduct Mass and Intensity

Lu, Wenyun; Xing, Xi; Wang, Lin; Chen, Li; Zhang, Sisi; McReynolds, Melanie R.; Rabinowitz, Joshua D.

doi:10.1021/acs.analchem.0c00985

Improved Annotation of Untargeted Metabolomics Data through Buffer Modifications That Shift Adduct Mass and Intensity

Journal Article · Thu Jul 02 00:00:00 EDT 2020 · Analytical Chemistry

DOI:https://doi.org/10.1021/acs.analchem.0c00985· OSTI ID:1807696

^[1]; Xing, Xi ^[2]; ^[2]; Chen, Li ^[2]; Zhang, Sisi ^[2]; McReynolds, Melanie R. ^[2]; ^[2]

Princeton Univ., NJ (United States); Princeton University
Princeton Univ., NJ (United States)

Annotation of untargeted high-resolution full-scan LC-MS metabolomics data remains challenging due to individual metabolites generating multiple LC-MS peaks arising from isotopes, adducts and fragments. Adduct annotation is a particular challenge, as the same mass difference between peaks can arise from adduct formation, fragmentation, or different biological species. To address this, here we describe a Buffer Modification Workflow (BMW), in which the same sample is run by LC-MS in both liquid chromatography solvent with ¹⁴NH₃-acetate buffer, and in solvent with the buffer modified with ¹⁵NH₃-formate. Buffer switching results in characteristic mass and signal intensity changes for adduct peaks, facilitating their annotation. This relatively simple and convenient chromatography modification annotated yeast metabolomics data with similar effectiveness to growing the yeast in isotope-labeled media. Application to mouse liver data annotated both known metabolite and known adduct peaks with 95% accuracy. Altogether, it identified 26% of ~ 27,000 liver LC-MS features as putative metabolites, of which ~ 2600 showed HMDB or KEGG database formula match. This workflow is well-suited to biological samples that cannot be readily isotope labeled, including plants, mammalian tissues, and tumors.

View Accepted Manuscript (DOE)

Research Organization:: Center for Advanced Bioenergy and Bioproducts Innovation (CABBI), Urbana, IL (United States)

Sponsoring Organization:: NIH; USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: SC0018420

OSTI ID:: 1807696

Alternate ID(s):: OSTI ID: 1803418

Journal Information:: Analytical Chemistry, Journal Name: Analytical Chemistry Journal Issue: 17 Vol. 92; ISSN 0003-2700

Publisher:: American Chemical Society (ACS)Copyright Statement

Country of Publication:: United States

Language:: English

References (39)

Proposal for a chemically consistent way to annotate ions arising from the analysis of reference compounds under ESI conditions: A prerequisite to proper mass spectral database constitution in metabolomics Damont, Annelaure; Olivier, Marie-Françoise; Warnet, Anna Journal of Mass Spectrometry, Vol. 54, Issue 6 https://doi.org/10.1002/jms.4372	journal	June 2019
Identification of small molecules using accurate mass MS/MS search Kind, Tobias; Tsugawa, Hiroshi; Cajka, Tomas Mass Spectrometry Reviews, Vol. 37, Issue 4 https://doi.org/10.1002/mas.21535	journal	April 2017
Characterization of typical chemical background interferences in atmospheric pressure ionization liquid chromatography-mass spectrometry Guo, Xinghua; Bruins, Andries P.; Covey, Thomas R. Rapid Communications in Mass Spectrometry, Vol. 20, Issue 20 https://doi.org/10.1002/rcm.2715	journal	January 2006
Data Conversion with ProteoWizard msConvert Adusumilli, Ravali; Mallick, Parag Methods in Molecular Biology https://doi.org/10.1007/978-1-4939-6747-6_23	book	January 2017
El-MAVEN: A Fast, Robust, and User-Friendly Mass Spectrometry Data Processing Engine for Metabolomics Agrawal, Shubhra; Kumar, Sahil; Sehgal, Raghav High-Throughput Metabolomics https://doi.org/10.1007/978-1-4939-9236-2_19	book	January 2019
Proposed minimum reporting standards for chemical analysis: Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI) Sumner, Lloyd W.; Amberg, Alexander; Barrett, Dave Metabolomics, Vol. 3, Issue 3 https://doi.org/10.1007/s11306-007-0082-2	journal	September 2007
Inaccurate quantitation of palmitate in metabolomics and isotope tracer studies due to plastics Yao, Cong-Hui; Liu, Gao-Yuan; Yang, Kui Metabolomics, Vol. 12, Issue 9 https://doi.org/10.1007/s11306-016-1081-y	journal	August 2016
New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis Mitchell, Joshua M.; Flight, Robert M.; Wang, Qing Jun Metabolomics, Vol. 14, Issue 10 https://doi.org/10.1007/s11306-018-1426-9	journal	September 2018
Separation and quantitation of water soluble cellular metabolites by hydrophilic interaction chromatography-tandem mass spectrometry Bajad, Sunil U.; Lu, Wenyun; Kimball, Elizabeth H. Journal of Chromatography A, Vol. 1125, Issue 1, p. 76-88 https://doi.org/10.1016/j.chroma.2006.05.019	journal	August 2006
Adduct formation in electrospray ionisation-mass spectrometry with hydrophilic interaction liquid chromatography is strongly affected by the inorganic ion concentration of the samples Erngren, Ida; Haglöf, Jakob; Engskog, Mikael K. R. Journal of Chromatography A, Vol. 1600 https://doi.org/10.1016/j.chroma.2019.04.049	journal	August 2019
Stable Isotope Assisted Assignment of Elemental Compositions for Metabolomics Hegeman, Adrian D.; Schulte, Christopher F.; Cui, Qiu Analytical Chemistry, Vol. 79, Issue 18 https://doi.org/10.1021/ac070346t	journal	September 2007
CAMERA: An Integrated Strategy for Compound Spectra Extraction and Annotation of Liquid Chromatography/Mass Spectrometry Data Sets Kuhl, Carsten; Tautenhahn, Ralf; Böttcher, Christoph Analytical Chemistry, Vol. 84, Issue 1 https://doi.org/10.1021/ac202450g	journal	December 2011
Credentialing Features: A Platform to Benchmark and Optimize Untargeted Metabolomic Methods Mahieu, Nathaniel Guy; Huang, Xiaojing; Chen, Ying-Jr Analytical Chemistry, Vol. 86, Issue 19 https://doi.org/10.1021/ac503092d	journal	September 2014
Metabolite Identification for Mass Spectrometry-Based Metabolomics Using Multiple Types of Correlated Ion Information Lynn, Ke-Shiuan; Cheng, Mei-Ling; Chen, Yet-Ran Analytical Chemistry, Vol. 87, Issue 4 https://doi.org/10.1021/ac503325c	journal	January 2015
Avoiding Misannotation of In-Source Fragmentation Products as Cellular Metabolites in Liquid Chromatography–Mass Spectrometry-Based Metabolomics Xu, Yi-Fan; Lu, Wenyun; Rabinowitz, Joshua D. Analytical Chemistry, Vol. 87, Issue 4 https://doi.org/10.1021/ac504118y	journal	January 2015
xMSannotator: An R Package for Network-Based Annotation of High-Resolution Metabolomics Data Uppal, Karan; Walker, Douglas I.; Jones, Dean P. Analytical Chemistry, Vol. 89, Issue 2 https://doi.org/10.1021/acs.analchem.6b01214	journal	December 2016
Mass Spectral Feature List Optimizer (MS-FLO): A Tool To Minimize False Positive Peak Reports in Untargeted Liquid Chromatography–Mass Spectroscopy (LC-MS) Data Processing DeFelice, Brian C.; Mehta, Sajjan Singh; Samra, Stephanie Analytical Chemistry, Vol. 89, Issue 6 https://doi.org/10.1021/acs.analchem.6b04372	journal	March 2017
Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites Mahieu, Nathaniel G.; Patti, Gary J. Analytical Chemistry, Vol. 89, Issue 19 https://doi.org/10.1021/acs.analchem.7b02380	journal	September 2017
Annotation: A Computational Solution for Streamlining Metabolomics Analysis Domingo-Almenara, Xavier; Montenegro-Burke, J. Rafael; Benton, H. Paul Analytical Chemistry, Vol. 90, Issue 1 https://doi.org/10.1021/acs.analchem.7b03929	journal	November 2017
METLIN: A Technology Platform for Identifying Knowns and Unknowns Guijas, Carlos; Montenegro-Burke, J. Rafael; Domingo-Almenara, Xavier Analytical Chemistry, Vol. 90, Issue 5 https://doi.org/10.1021/acs.analchem.7b04424	journal	January 2018
Peak Annotation and Verification Engine for Untargeted LC–MS Metabolomics Wang, Lin; Xing, Xi; Chen, Li Analytical Chemistry, Vol. 91, Issue 3 https://doi.org/10.1021/acs.analchem.8b03132	journal	December 2018
Computational Metabolomics: A Framework for the Million Metabolome Uppal, Karan; Walker, Douglas I.; Liu, Ken Chemical Research in Toxicology, Vol. 29, Issue 12 https://doi.org/10.1021/acs.chemrestox.6b00179	journal	October 2016
Identifying Small Molecules via High Resolution Mass Spectrometry: Communicating Confidence Schymanski, Emma L.; Jeon, Junho; Gulde, Rebekka Environmental Science & Technology, Vol. 48, Issue 4 https://doi.org/10.1021/es5002105	journal	February 2014
Chemical Discovery in the Era of Metabolomics Sindelar, Miriam; Patti, Gary J. Journal of the American Chemical Society, Vol. 142, Issue 20 https://doi.org/10.1021/jacs.9b13198	journal	April 2020
A cheminformatics approach to characterize metabolomes in stable-isotope-labeled organisms Tsugawa, Hiroshi; Nakabayashi, Ryo; Mori, Tetsuya Nature Methods, Vol. 16, Issue 4 https://doi.org/10.1038/s41592-019-0358-2	journal	March 2019
Extraction and Quantitation of Nicotinamide Adenine Dinucleotide Redox Cofactors Lu, Wenyun; Wang, Lin; Chen, Li Antioxidants & Redox Signaling, Vol. 28, Issue 3 https://doi.org/10.1089/ars.2017.7014	journal	January 2018
Automated workflows for accurate mass-based putative metabolite identification in LC/MS-derived metabolomic datasets Brown, M.; Wedge, D. C.; Goodacre, R. Bioinformatics, Vol. 27, Issue 8 https://doi.org/10.1093/bioinformatics/btr079	journal	February 2011
AStream: an R package for annotating LC/MS metabolomic data Alonso, Arnald; Julià, Antonio; Beltran, Antoni Bioinformatics, Vol. 27, Issue 9 https://doi.org/10.1093/bioinformatics/btr138	journal	March 2011
Deep annotation of untargeted LC-MS metabolomics data with Binner Kachman, Maureen; Habra, Hani; Duren, William Bioinformatics https://doi.org/10.1093/bioinformatics/btz798	journal	October 2019
SIMCOMP/SUBCOMP: chemical structure search servers for network analyses Hattori, M.; Tanaka, N.; Kanehisa, M. Nucleic Acids Research, Vol. 38, Issue Web Server https://doi.org/10.1093/nar/gkq367	journal	May 2010
MMMDB: Mouse Multiple Tissue Metabolome Database Sugimoto, Masahiro; Ikeda, Satsuki; Niigata, Kanako Nucleic Acids Research, Vol. 40, Issue D1 https://doi.org/10.1093/nar/gkr1170	journal	December 2011
Elemental formula annotation of polar and lipophilic metabolites using ¹³ C, ¹⁵ N and ³⁴ S isotope labelling, in combination with high-resolution mass spectrometry Giavalisco, Patrick; Li, Yan; Matthes, Annemarie The Plant Journal, Vol. 68, Issue 2 https://doi.org/10.1111/j.1365-313X.2011.04682.x	journal	July 2011
Metabolite Measurement: Pitfalls to Avoid and Practices to Follow Lu, Wenyun; Su, Xiaoyang; Klein, Matthias S. Annual Review of Biochemistry, Vol. 86, Issue 1 https://doi.org/10.1146/annurev-biochem-061516-044952	journal	June 2017
Cancer Metabolomics and the Human Metabolome Database Wishart, David; Mandal, Rupasri; Stanislaus, Avalyn Metabolites, Vol. 6, Issue 1 https://doi.org/10.3390/metabo6010010	journal	March 2016
Methanol Generates Numerous Artifacts during Sample Extraction and Storage of Extracts in Metabolomics Research Sauerschnig, Claudia; Doppler, Maria; Bueschl, Christoph Metabolites, Vol. 8, Issue 1 https://doi.org/10.3390/metabo8010001	journal	December 2017
Software Tools and Approaches for Compound Identification of LC-MS/MS Data in Metabolomics Blaženović, Ivana; Kind, Tobias; Ji, Jian Metabolites, Vol. 8, Issue 2 https://doi.org/10.3390/metabo8020031	journal	May 2018
Simple data-reduction method for high-resolution LC–MS data in metabolomics Scheltema, Ra; Decuypere, S.; Dujardin, Jc Bioanalysis, Vol. 1, Issue 9 https://doi.org/10.4155/bio.09.146	journal	December 2009
Addressing the current bottlenecks of metabolomics: Isotopic Ratio Outlier Analysis™, an isotopic-labeling technique for accurate biochemical profiling de Jong, Felice A.; Beecher, Chris Bioanalysis, Vol. 4, Issue 18 https://doi.org/10.4155/bio.12.202	journal	September 2012
Categorizing Ion –Features in Liquid Chromatography/Mass Spectrometry Metobolomics Data M. Evans, Anne Journal of Postgenomics: Drug & Biomarker Development, Vol. 02, Issue 03 https://doi.org/10.4172/2153-0769.1000110	journal	January 2012

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