The use of hybrid data-dependent and -independent acquisition spectral libraries empower dual-proteome profiling

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 data-independent acquisition 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. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/113340v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1bbc20aorg.highwire.dtl.DTLVardef@1c0455eorg.highwire.dtl.DTLVardef@a2873org.highwire.dtl.DTLVardef@e5b0b6_HPS_FORMAT_FIGEXP M_FIG C_FIG