Dataset Information

The choice of search engine for interpretation of immunopeptidomics datasets affects the sequencing depth and the extent of detected HLA allele-specific peptide repertoires

ABSTRACT: Standardisation of Immunopeptidomics experiments across laboratories is a pressing issue within the field, and currently a variety of different methods for sample preparation and data analysis tools are applied. Here, we compared different software packages commonly used to interrogate immunopeptidomics datasets, in order to understand to which extent differences in performance can be observed. We found that a de novo-assisted database search reports substantially more peptide sequences (~30-70%) compared to three database search engines at a global FDR of <1%. This effect was reproducible across four immunopeptidomic datasets. We validated the results using data generated with a synthetic library of 2000 HLA-associated peptides from four HLA alleles, half of which were previously observed by LC-MS, and half were predicted only. Our investigation reveals that search engines create a bias in peptide sequence length distribution and peptide amino acid composition. Therefore, the choice of peptide identification method highly influences the proportion of peptide sequences identified for each HLA allele, and resulting data should be interpreted with caution.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture

SUBMITTER: Robert Parker

LAB HEAD: Nicola Ternette

PROVIDER: PXD023202 | Pride | 2024-08-27

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	FL707_IPP85_Xu_DOTC2_MHCI_even.mzxml	Mzxml
	FL707_IPP85_Xu_DOTC2_MHCI_odd.mzxml	Mzxml
	FL811_Elastase_standard.mzXML	Mzxml
	HF324_20180302_XuPeng_S2_dotc1.mzXML	Mzxml
	HFX0068_JPT_library_mix__standard_A.mzXML	Mzxml

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Publications

The Choice of Search Engine Affects Sequencing Depth and HLA Class I Allele-Specific Peptide Repertoires.

Parker Robert R Tailor Arun A Peng Xu X Nicastri Annalisa A Zerweck Johannes J Reimer Ulf U Wenschuh Holger H Schnatbaum Karsten K Ternette Nicola N

Molecular & cellular proteomics : MCP 20210723

Standardization of immunopeptidomics experiments across laboratories is a pressing issue within the field, and currently a variety of different methods for sample preparation and data analysis tools are applied. Here, we compared different software packages to interrogate immunopeptidomics datasets and found that Peaks reproducibly reports substantially more peptide sequences (~30-70%) compared with Maxquant, Comet, and MS-GF+ at a global false discovery rate (FDR) of <1%. We noted that these di ...[more]

PMID: 34303857

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Project description:Background: Patient derived organoids (PDOs) can be established from colorectal cancers as in vitro models to interrogate cancer biology and its clinical relevance. We applied mass spectrometry (MS) immunopeptidomics to investigate neoantigen presentation and whether this can be augmented through interferon gamma (IFN) or MEK-inhibitors. Methods: Four PDOs from chemotherapy refractory and one from a treatment naïve CRC were expanded to replicates with 100 million cells each, and HLA class I and class II peptide ligands were analysed by MS. Results: We identified an average of 9,936 unique peptides per PDO which compares favourably against published immunopeptidomics studies, suggesting high sensitivity. Loss of heterozygosity of the HLA locus was associated with low peptide diversity in one PDO. Peptides from genes without detectable expression by RNA-sequencing were rarely identified by MS. Only 3 out of 612 non-silent mutations encoded for neoantigens that were detected by MS. Treatment of four PDOs with IFN upregulated HLA class I expression and qualitatively changed the immunopeptidome, with increased presentation of IFN-inducible genes. HLA class II presented peptides increased on average 16-fold with IFN treatment. MEK-inhibitor treatment showed no consistent effect on class I or II HLA expression or the peptidome. Importantly, no additional HLA class I or II presented neoantigens became detectable with any treatment. Conclusions: Only 3 out of 612 non-synonymous mutations encoded for neoantigens that were detectable by MS. Although MS has sensitivity limits and biases, and likely underestimated the true neoantigen burden, this established a lower bound of the percentage of non-silent mutations that encode for presented neoantigens, which may be as low as 0.5%. This could be a reason for the poor responses of non-hypermutated CRCs to immune checkpoint inhibitors. MEK-inhibitors recently failed to improve checkpoint-inhibitor efficacy in CRC and the observed lack of HLA upregulation or improved peptide presentation may explain this.