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Tissue-based absolute quantification using large-scale TMT and LFQ experiments

Wang, Hong ; Dai, Chengxin ; Pfeuffer, Julianus ; Sachsenberg, Timo ; Sanchez, Aniel LU ; Bai, Mingze and Perez-Riverol, Yasset (2023) In Proteomics 23(20).
Abstract

Relative and absolute intensity-based protein quantification across cell lines, tissue atlases and tumour datasets is increasingly available in public datasets. These atlases enable researchers to explore fundamental biological questions, such as protein existence, expression location, quantity and correlation with RNA expression. Most studies provide MS1 feature-based label-free quantitative (LFQ) datasets; however, growing numbers of isobaric tandem mass tags (TMT) datasets remain unexplored. Here, we compare traditional intensity-based absolute quantification (iBAQ) proteome abundance ranking to an analogous method using reporter ion proteome abundance ranking with data from an experiment where LFQ and TMT were measured on the same... (More)

Relative and absolute intensity-based protein quantification across cell lines, tissue atlases and tumour datasets is increasingly available in public datasets. These atlases enable researchers to explore fundamental biological questions, such as protein existence, expression location, quantity and correlation with RNA expression. Most studies provide MS1 feature-based label-free quantitative (LFQ) datasets; however, growing numbers of isobaric tandem mass tags (TMT) datasets remain unexplored. Here, we compare traditional intensity-based absolute quantification (iBAQ) proteome abundance ranking to an analogous method using reporter ion proteome abundance ranking with data from an experiment where LFQ and TMT were measured on the same samples. This new TMT method substitutes reporter ion intensities for MS1 feature intensities in the iBAQ framework. Additionally, we compared LFQ-iBAQ values to TMT-iBAQ values from two independent large-scale tissue atlas datasets (one LFQ and one TMT) using robust bottom-up proteomic identification, normalisation and quantitation workflows.

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author
; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
absolute protein expression, big data, LFQ, proteomics data reanalysis, public data, TMT
in
Proteomics
volume
23
issue
20
publisher
John Wiley & Sons Inc.
external identifiers
  • pmid:37488995
  • scopus:85165602080
ISSN
1615-9853
DOI
10.1002/pmic.202300188
language
English
LU publication?
yes
id
b3d079e4-68a2-4662-b708-6d4cebf2aa74
date added to LUP
2023-09-20 11:19:42
date last changed
2024-04-19 01:10:24
@article{b3d079e4-68a2-4662-b708-6d4cebf2aa74,
  abstract     = {{<p>Relative and absolute intensity-based protein quantification across cell lines, tissue atlases and tumour datasets is increasingly available in public datasets. These atlases enable researchers to explore fundamental biological questions, such as protein existence, expression location, quantity and correlation with RNA expression. Most studies provide MS1 feature-based label-free quantitative (LFQ) datasets; however, growing numbers of isobaric tandem mass tags (TMT) datasets remain unexplored. Here, we compare traditional intensity-based absolute quantification (iBAQ) proteome abundance ranking to an analogous method using reporter ion proteome abundance ranking with data from an experiment where LFQ and TMT were measured on the same samples. This new TMT method substitutes reporter ion intensities for MS1 feature intensities in the iBAQ framework. Additionally, we compared LFQ-iBAQ values to TMT-iBAQ values from two independent large-scale tissue atlas datasets (one LFQ and one TMT) using robust bottom-up proteomic identification, normalisation and quantitation workflows.</p>}},
  author       = {{Wang, Hong and Dai, Chengxin and Pfeuffer, Julianus and Sachsenberg, Timo and Sanchez, Aniel and Bai, Mingze and Perez-Riverol, Yasset}},
  issn         = {{1615-9853}},
  keywords     = {{absolute protein expression; big data; LFQ; proteomics data reanalysis; public data; TMT}},
  language     = {{eng}},
  number       = {{20}},
  publisher    = {{John Wiley & Sons Inc.}},
  series       = {{Proteomics}},
  title        = {{Tissue-based absolute quantification using large-scale TMT and LFQ experiments}},
  url          = {{http://dx.doi.org/10.1002/pmic.202300188}},
  doi          = {{10.1002/pmic.202300188}},
  volume       = {{23}},
  year         = {{2023}},
}