期刊
JOURNAL OF PROTEOME RESEARCH
卷 20, 期 2, 页码 1165-1177出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.0c00350
关键词
bacterial pathogen/host interaction; data-dependent acquisition (DDA); data-independent acquisition (DIA); Salmonella; spectral library
资金
- European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (PROPHECY grant) [803972]
- Research Foundation-Flanders (FWO-Vlaanderen) [G.0511.20N]
- Ghent University Concerted Research Actions [BOF14/GOA/013]
To study physiological responses in bacterial infections, an optimized hybrid library generation workflow for DIA mass spectrometry was found to significantly improve sensitivity and depth of protein detection, without the need for prior enrichment of bacterial pathogens.
In the context of bacterial infections, it is imperative that physiological responses can be studied in an integrated manner, meaning a simultaneous analysis of both the host and the pathogen responses. To improve the sensitivity of detection, data-independent acquisition (DIA)-based proteomics was found to outperform data-dependent acquisition (DDA) workflows in identifying and quantifying low-abundant proteins. Here, by making use of representative bacterial pathogen/host proteome samples, we report an optimized hybrid library generation workflow for DIA mass spectrometry relying on the use of data-dependent and in silico-predicted spectral libraries. When compared to searching DDA experiment-specific libraries only, the use of hybrid libraries significantly improved peptide detection to an extent suggesting that infection-relevant host-pathogen conditions could be profiled in sufficient depth without the need of a priori bacterial pathogen enrichment when studying the bacterial proteome. Proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD017904 and PXD017945.
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