PXD010912

PXD010912 is an original dataset announced via ProteomeXchange.

Title	Label-Free Absolute Protein Quantification with Data-Independent Acquisition
Description	Label-free absolute quantitative proteomics is commonly used for absolute quantification of the proteome or specific proteins of interest in various biological samples. Current label-free absolute protein quantification (APQ) methods determine MS1 intensities, MS2 spectral counts or intensities to absolutely quantify protein concentrations from data obtained from data-dependent acquisition (DDA). In recent years, label-free data-independent acquisition (DIA) has seen increasing use as a powerful tool for relative protein quantification. Here we present a novel label-free DIA-based absolute protein quantification (DIA-APQ) method for the absolute quantification of protein expressions from DIA data. To validate this method, both DDA and DIA experiments were performed on 36 individual human liver microsome and S9 samples. The DIA-APQ assay was able to quantify approximately twice as many proteins as the DDA MS1-based APQ method whereas protein concentrations determined by the two methods were comparable. To evaluate the accuracy of the DIA-APQ method, we absolutely quantified carboxylesterase 1 concentrations in human liver samples using an established SILAC internal standard-based proteomic assay; the SILAC results were consistent with those obtained from DIA-APQ analysis. Finally, we employed a unique algorithm in DIA-APQ to distribute the MS signals from shared peptides to different protein isoforms and successfully applied the DIA-APQ method to the absolute quantification of several drug-metabolizing enzyme isoforms in human liver microsomes. This novel DIA-based APQ method not only provides a powerful approach for absolutely quantifying entire proteomes and specific candidate proteins, but also has with the capacity differentiating protein isoforms.
HostingRepository	PRIDE
AnnounceDate	2019-03-20
AnnouncementXML	Submission_2019-03-20_08:21:00.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Bing He
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	iodoacetamide derivatized residue
Instrument	TripleTOF 5600

Revision	Datetime	Status	ChangeLog Entry
0	2018-08-28 08:21:47	ID requested
⏵ 1	2019-03-20 08:21:01	announced

He B, Shi J, Wang X, Jiang H, Zhu HJ, Label-free absolute protein quantification with data-independent acquisition. J Proteomics, 200():51-59(2019) [pubmed]

curator keyword: Biological, Biomedical

submitter keyword: Human, Liver, S9, Microsome, DDA, DIA, Absolute Protein Quantification

Hao-Jie Zhu
contact affiliation	Department of Clinical Pharmacy, University of Michigan
contact email	hjzhu@med.umich.edu
lab head
Bing He
contact affiliation	University of Michigan
contact email	hbing@umich.edu
dataset submitter

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PRIDE project URI

• PRIDE
  1. PXD010912
     1. Label: PRIDE project
     2. Name: Label-Free Absolute Protein Quantification with Data-Independent Acquisition