A Metabolomics-Inspired Strategy for the Identification of Protein Covalent Modifications

João Nunes, Catarina Charneira, Carolina Nunes, Sofia Gouveia-Fernandes, Jacinta Serpa, Judit Morello, Alexandra M M Antunes

Research output: Contribution to journalArticle

Abstract

Identification of protein covalent modifications (adducts) is a challenging task mainly due to the lack of data processing approaches for adductomics studies. Despite the huge technological advances in mass spectrometry (MS) instrumentation and bioinformatics tools for proteomics studies, these methodologies have very limited success on the identification of low abundant protein adducts. Herein we report a novel strategy inspired on the metabolomics workflows for the identification of covalently-modified peptides that consists on LC-MS data preprocessing followed by statistical analysis. The usefulness of this strategy was evaluated using experimental LC-MS data of histones isolated from HepG2 and THLE2 cells exposed to the chemical carcinogen glycidamide. LC-MS data was preprocessed using the open-source software MZmine and potential adducts were selected based on the m/z increments corresponding to glycidamide incorporation. Then, statistical analysis was applied to reveal the potential adducts as those ions are differently present in cells exposed and not exposed to glycidamide. The results were compared with the ones obtained upon the standard proteomics methodology, which relies on producing comprehensive MS/MS data by data dependent acquisition and analysis with proteomics data search engines. Our novel strategy was able to differentiate HepG2 and THLE2 and to identify adducts that were not detected by the standard methodology of adductomics. Thus, this metabolomics driven approach in adductomics will not only open new opportunities for the identification of protein epigenetic modifications, but also adducts formed by endogenous and exogenous exposure to chemical agents.

Original languageEnglish
Article number532
JournalFrontiers in Chemistry
Volume7
DOIs
Publication statusPublished - 31 Jul 2019

Fingerprint

Mass spectrometry
Proteins
Statistical methods
Bioinformatics
Search engines
Carcinogens
Histones
Metabolomics
Ions
Peptides
Proteomics
glycidamide

Keywords

  • adductomics
  • metabolomics
  • mass spectrometry
  • chemometrics
  • toxicology
  • acrylamide
  • glycidamide
  • histones

Cite this

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title = "A Metabolomics-Inspired Strategy for the Identification of Protein Covalent Modifications",
abstract = "Identification of protein covalent modifications (adducts) is a challenging task mainly due to the lack of data processing approaches for adductomics studies. Despite the huge technological advances in mass spectrometry (MS) instrumentation and bioinformatics tools for proteomics studies, these methodologies have very limited success on the identification of low abundant protein adducts. Herein we report a novel strategy inspired on the metabolomics workflows for the identification of covalently-modified peptides that consists on LC-MS data preprocessing followed by statistical analysis. The usefulness of this strategy was evaluated using experimental LC-MS data of histones isolated from HepG2 and THLE2 cells exposed to the chemical carcinogen glycidamide. LC-MS data was preprocessed using the open-source software MZmine and potential adducts were selected based on the m/z increments corresponding to glycidamide incorporation. Then, statistical analysis was applied to reveal the potential adducts as those ions are differently present in cells exposed and not exposed to glycidamide. The results were compared with the ones obtained upon the standard proteomics methodology, which relies on producing comprehensive MS/MS data by data dependent acquisition and analysis with proteomics data search engines. Our novel strategy was able to differentiate HepG2 and THLE2 and to identify adducts that were not detected by the standard methodology of adductomics. Thus, this metabolomics driven approach in adductomics will not only open new opportunities for the identification of protein epigenetic modifications, but also adducts formed by endogenous and exogenous exposure to chemical agents.",
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note = "This work was supported by Funda{\cc}{\~a}o para a Ci{\^e}ncia e a Tecnologia (FCT), Portugal, through projects UID/QUI/00100/2019, IF/01091/2013/CP1163/CT0001 and PTDC/QUIQAN/32242/2017 as well as doctoral fellowships SFRH/BD/102846/2014 (to CC) and SFRH/BD/140157/2018 (to JN);joint funding from FCT and the COMPETE Program is also acknowledge through RNEM-LISBOA-01-0145-FEDER-022125-funded postdoctoral fellowship (to JM).",
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A Metabolomics-Inspired Strategy for the Identification of Protein Covalent Modifications. / Nunes, João; Charneira, Catarina; Nunes, Carolina; Gouveia-Fernandes, Sofia; Serpa, Jacinta; Morello, Judit; Antunes, Alexandra M M.

In: Frontiers in Chemistry, Vol. 7, 532, 31.07.2019.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A Metabolomics-Inspired Strategy for the Identification of Protein Covalent Modifications

AU - Nunes, João

AU - Charneira, Catarina

AU - Nunes, Carolina

AU - Gouveia-Fernandes, Sofia

AU - Serpa, Jacinta

AU - Morello, Judit

AU - Antunes, Alexandra M M

N1 - This work was supported by Fundação para a Ciência e a Tecnologia (FCT), Portugal, through projects UID/QUI/00100/2019, IF/01091/2013/CP1163/CT0001 and PTDC/QUIQAN/32242/2017 as well as doctoral fellowships SFRH/BD/102846/2014 (to CC) and SFRH/BD/140157/2018 (to JN);joint funding from FCT and the COMPETE Program is also acknowledge through RNEM-LISBOA-01-0145-FEDER-022125-funded postdoctoral fellowship (to JM).

PY - 2019/7/31

Y1 - 2019/7/31

N2 - Identification of protein covalent modifications (adducts) is a challenging task mainly due to the lack of data processing approaches for adductomics studies. Despite the huge technological advances in mass spectrometry (MS) instrumentation and bioinformatics tools for proteomics studies, these methodologies have very limited success on the identification of low abundant protein adducts. Herein we report a novel strategy inspired on the metabolomics workflows for the identification of covalently-modified peptides that consists on LC-MS data preprocessing followed by statistical analysis. The usefulness of this strategy was evaluated using experimental LC-MS data of histones isolated from HepG2 and THLE2 cells exposed to the chemical carcinogen glycidamide. LC-MS data was preprocessed using the open-source software MZmine and potential adducts were selected based on the m/z increments corresponding to glycidamide incorporation. Then, statistical analysis was applied to reveal the potential adducts as those ions are differently present in cells exposed and not exposed to glycidamide. The results were compared with the ones obtained upon the standard proteomics methodology, which relies on producing comprehensive MS/MS data by data dependent acquisition and analysis with proteomics data search engines. Our novel strategy was able to differentiate HepG2 and THLE2 and to identify adducts that were not detected by the standard methodology of adductomics. Thus, this metabolomics driven approach in adductomics will not only open new opportunities for the identification of protein epigenetic modifications, but also adducts formed by endogenous and exogenous exposure to chemical agents.

AB - Identification of protein covalent modifications (adducts) is a challenging task mainly due to the lack of data processing approaches for adductomics studies. Despite the huge technological advances in mass spectrometry (MS) instrumentation and bioinformatics tools for proteomics studies, these methodologies have very limited success on the identification of low abundant protein adducts. Herein we report a novel strategy inspired on the metabolomics workflows for the identification of covalently-modified peptides that consists on LC-MS data preprocessing followed by statistical analysis. The usefulness of this strategy was evaluated using experimental LC-MS data of histones isolated from HepG2 and THLE2 cells exposed to the chemical carcinogen glycidamide. LC-MS data was preprocessed using the open-source software MZmine and potential adducts were selected based on the m/z increments corresponding to glycidamide incorporation. Then, statistical analysis was applied to reveal the potential adducts as those ions are differently present in cells exposed and not exposed to glycidamide. The results were compared with the ones obtained upon the standard proteomics methodology, which relies on producing comprehensive MS/MS data by data dependent acquisition and analysis with proteomics data search engines. Our novel strategy was able to differentiate HepG2 and THLE2 and to identify adducts that were not detected by the standard methodology of adductomics. Thus, this metabolomics driven approach in adductomics will not only open new opportunities for the identification of protein epigenetic modifications, but also adducts formed by endogenous and exogenous exposure to chemical agents.

KW - adductomics

KW - metabolomics

KW - mass spectrometry

KW - chemometrics

KW - toxicology

KW - acrylamide

KW - glycidamide

KW - histones

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DO - 10.3389/fchem.2019.00532

M3 - Article

VL - 7

JO - Frontiers in Chemistry

JF - Frontiers in Chemistry

SN - 2296-2646

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