A data-independent acquisition-based global phosphoproteomics system enables deep profiling

Reta Birhanu Kitata, Wai-Kok Choong, Chia-Feng Tsai, Pei-Yi Lin, Bo-Shiun Chen, Yun-Chien Chang, Alexey I. Nesvizhskii, Ting-Yi Sung and Yu-Ju Chen ()
Additional contact information
Reta Birhanu Kitata: Academia Sinica
Wai-Kok Choong: Academia Sinica
Chia-Feng Tsai: Pacific Northwest National Laboratory
Pei-Yi Lin: Academia Sinica
Bo-Shiun Chen: Academia Sinica
Yun-Chien Chang: Academia Sinica
Alexey I. Nesvizhskii: University of Michigan Medical School
Ting-Yi Sung: Academia Sinica
Yu-Ju Chen: Academia Sinica

Nature Communications, 2021, vol. 12, issue 1, 1-14

Abstract: Abstract Phosphoproteomics can provide insights into cellular signaling dynamics. To achieve deep and robust quantitative phosphoproteomics profiling for minute amounts of sample, we here develop a global phosphoproteomics strategy based on data-independent acquisition (DIA) mass spectrometry and hybrid spectral libraries derived from data-dependent acquisition (DDA) and DIA data. Benchmarking the method using 166 synthetic phosphopeptides shows high sensitivity (

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-021-22759-z Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-22759-z

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-021-22759-z

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().