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MetaboKit : a comprehensive data extraction tool for untargeted metabolomics

Narayanaswamy, Pradeep ; Teo, Guoshou ; Ow, Jin Rong ; Lau, Adam ; Kaldis, Philipp LU ; Tate, Stephen and Choi, Hyungwon (2020) In Molecular omics
Abstract

We have developed MetaboKit, a comprehensive software package for compound identification and relative quantification in mass spectrometry-based untargeted metabolomics analysis. In data dependent acquisition (DDA) analysis, MetaboKit constructs a customized spectral library with compound identities from reference spectral libraries, adducts, dimers, in-source fragments (ISF), MS/MS fragmentation spectra, and more importantly the retention time information unique to the chromatography system used in the experiment. Using the customized library, the software performs targeted peak integration for precursor ions in DDA analysis and for precursor and product ions in data independent acquisition (DIA) analysis. With its stringent... (More)

We have developed MetaboKit, a comprehensive software package for compound identification and relative quantification in mass spectrometry-based untargeted metabolomics analysis. In data dependent acquisition (DDA) analysis, MetaboKit constructs a customized spectral library with compound identities from reference spectral libraries, adducts, dimers, in-source fragments (ISF), MS/MS fragmentation spectra, and more importantly the retention time information unique to the chromatography system used in the experiment. Using the customized library, the software performs targeted peak integration for precursor ions in DDA analysis and for precursor and product ions in data independent acquisition (DIA) analysis. With its stringent identification algorithm requiring matches by both MS and MS/MS data, MetaboKit provides identification results with significantly greater specificity than the competing software packages without loss in sensitivity. The proposed MS/MS-based screening of ISFs also reduces the chance of unverifiable identification of ISFs considerably. MetaboKit's quantification module produced peak area values highly correlated with known concentrations in a DIA analysis of the metabolite standards at both MS1 and MS2 levels. Moreover, the analysis of Cdk1Liv-/- mouse livers showed that MetaboKit can identify a wide range of lipid species and their ISFs, and quantitatively reconstitute the well-characterized fatty liver phenotype in these mice. In DIA data, the MS1-level and MS2-level peak area data produced similar fold change estimates in the differential abundance analysis, and the MS2-level peak area data allowed for quantitative comparisons in compounds whose precursor ion chromatogram was too noisy for peak integration.

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Contribution to journal
publication status
epub
subject
in
Molecular omics
publisher
Royal Society of Chemistry
external identifiers
  • scopus:85092944926
  • pmid:32519713
ISSN
2515-4184
DOI
10.1039/d0mo00030b
language
English
LU publication?
yes
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3c642eba-a5cd-4d6f-80bd-ab28a94c2353
date added to LUP
2020-06-12 10:35:19
date last changed
2020-11-15 03:15:12
@article{3c642eba-a5cd-4d6f-80bd-ab28a94c2353,
  abstract     = {<p>We have developed MetaboKit, a comprehensive software package for compound identification and relative quantification in mass spectrometry-based untargeted metabolomics analysis. In data dependent acquisition (DDA) analysis, MetaboKit constructs a customized spectral library with compound identities from reference spectral libraries, adducts, dimers, in-source fragments (ISF), MS/MS fragmentation spectra, and more importantly the retention time information unique to the chromatography system used in the experiment. Using the customized library, the software performs targeted peak integration for precursor ions in DDA analysis and for precursor and product ions in data independent acquisition (DIA) analysis. With its stringent identification algorithm requiring matches by both MS and MS/MS data, MetaboKit provides identification results with significantly greater specificity than the competing software packages without loss in sensitivity. The proposed MS/MS-based screening of ISFs also reduces the chance of unverifiable identification of ISFs considerably. MetaboKit's quantification module produced peak area values highly correlated with known concentrations in a DIA analysis of the metabolite standards at both MS1 and MS2 levels. Moreover, the analysis of Cdk1Liv-/- mouse livers showed that MetaboKit can identify a wide range of lipid species and their ISFs, and quantitatively reconstitute the well-characterized fatty liver phenotype in these mice. In DIA data, the MS1-level and MS2-level peak area data produced similar fold change estimates in the differential abundance analysis, and the MS2-level peak area data allowed for quantitative comparisons in compounds whose precursor ion chromatogram was too noisy for peak integration.</p>},
  author       = {Narayanaswamy, Pradeep and Teo, Guoshou and Ow, Jin Rong and Lau, Adam and Kaldis, Philipp and Tate, Stephen and Choi, Hyungwon},
  issn         = {2515-4184},
  language     = {eng},
  month        = {06},
  publisher    = {Royal Society of Chemistry},
  series       = {Molecular omics},
  title        = {MetaboKit : a comprehensive data extraction tool for untargeted metabolomics},
  url          = {http://dx.doi.org/10.1039/d0mo00030b},
  doi          = {10.1039/d0mo00030b},
  year         = {2020},
}