Synthetic long peptides (SLPs) are a promising candidate for therapeutic vaccine due to its characteristics. To design an effective SLP-based vaccine, knowing the presented immunopeptidome after the vaccine is very important. Also, if the adjuvant will impact the repository of immunopeptidome is also unknown.
Here, scientists from the Netherlands proposed a sensitive LC-MS/MS based immunopeptidome workflow to profile the immunopeptidome repository on dendritic cells (DC) after loading SLPs w/o different adjuvants. First, they use conventional data dependent acquisition (DDA) method to generate the data, and then use PEAKS Studio to analyze the data. In total, 34315 unique peptides were confidently identified on 6 samples. Further analysis including peptide length distribution, binding ratio and bind motifs show that there is only minimum difference between different adjuvants.
Beside conventional DDA data, they also generate data independent acquisition (DIA) data on the sample sample. Still with PEAKS Studio, DIA data show similar performance (only a little lower identification number). More interesting, DIA data reported one new SLP-derived peptide and also expanded the sequence coverage for several peptides.
Further downstream analysis covers that those SLP-derived peptides can be constantly presented in DC cells across different patients, also some peptides involved in TRIF signaling pathway show enrichment after some adjuvants were applied.
Above all, the workflow shows immunopeptidomics as a valuable tool for therapeutic vaccine design.
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