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. 2021 Jan 11;12:254. doi: 10.1038/s41467-020-20509-1

Fig. 1. In-depth diGly proteomics for DIA identification.

Fig. 1

a Experimental workflow for in-depth diGly peptide library construction (upper panel) and our single-run data-independent acquisition (DIA)-based workflow (lower panel). Protein digestion and peptide extraction are followed by basic reversed-phase (bRP) fractionation and diGly peptide enrichment. For library construction, samples were measured by data-dependent acquisition (DDA) and computationally processed (Spectronaut Pulsar). Individual samples are measured by our DIA workflow, including matching against a library for identification (Spectronaut software). b Number of identified diGly peptides in three different spectral libraries (MG132 treated HEK293 library—green, MG132 treated U2OS library—violet, U2OS library—light violet, all diGly peptides—gray). c Commonly and exclusively identified diGly peptides for different libraries (MG132 treated HEK293 library—green, MG132 treated U2OS library—violet, U2OS library—light violet). d Identified diGly sites (mean ± SEM) of MG132 treated HEK293 cells using different DIA library search strategies (n = 6, three workflow replicates measured in analytical duplicates). Source data are provided as a Source data file.