Deciphering HLA-I motifs across HLA peptidomes improves neo-antigen predictions and identifies allostery regulating HLA specificity

<div><p>The precise identification of Human Leukocyte Antigen class I (HLA-I) binding motifs plays a central role in our ability to understand and predict (neo-)antigen presentation in infectious diseases and cancer. Here, by exploiting co-occurrence of HLA-I alleles across ten newly generated as well as forty public HLA peptidomics datasets comprising more than 115,000 unique peptides, we show that we can rapidly and accurately identify many HLA-I binding motifs and map them to their corresponding alleles without any <i>a priori</i> knowledge of HLA-I binding specificity. Our approach recapitulates and refines known motifs for 43 of the most frequent alleles, uncovers new motifs for 9 alleles that up to now had less than five known ligands and provides a scalable framework to incorporate additional HLA peptidomics studies in the future. The refined motifs improve neo-antigen and cancer testis antigen predictions, indicating that unbiased HLA peptidomics data are ideal for <i>in silico</i> predictions of neo-antigens from tumor exome sequencing data. The new motifs further reveal distant modulation of the binding specificity at P2 for some HLA-I alleles by residues in the HLA-I binding site but outside of the B-pocket and we unravel the underlying mechanisms by protein structure analysis, mutagenesis and <i>in vitro</i> binding assays.</p></div

Analysis of newly identified HLA-I motifs.

<p><b>A</b>: Structural view of two different HLA-I alleles with N90 as in HLA-A02:20 (PDB: 2BVQ [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005725#pcbi.1005725.ref040" target="_blank">40</a>], pink sidechains) or K90 as in HLA-A02:01 (PDB: 2BNR [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005725#pcbi.1005725.ref041" target="_blank">41</a>], green sidechains). For clarity, the α₁ helix has been truncated. <b>B</b>: B pocket residues’ conservation across HLA-I alleles displaying preference for histidine at P2. The last line shows the sequence of HLA-B14:02, which does not show histidine preference at P2 (see motif in <b>C</b>), but has the same B pocket as HLA-B15:18. The last column shows amino acids at position 97, which is not part of the B pocket. <b>C</b>: Structural view of HLA-B14:02 in complex with a peptide with arginine at P2 (PDB: 3BVN [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005725#pcbi.1005725.ref042" target="_blank">42</a>]). Residues not conserved between HLA-B15:18 and HLA-B14:02 are displayed in orange. None of them are making direct contact with the arginine residue at P2. <b>D</b>: Stability values (half-lives) obtained for peptides with H or R at P2 for both HLA-B14:02 wt and W97R mutant. NB stands for no binding. Dashed lines indicate lower bounds for half-lives values. Residue numbering follows the one used in most X-ray structures in the PDB.</p

Comparison between our predictor (MixMHCpred1.0) and existing tools.

<p><b>A</b>: Fraction of the true positives among the top 1% predictions (PP1%) for the naturally presented HLA-I ligand identified in mono-allelic cell lines, with 99-fold excess of decoy peptides. Of note, PP1% is equivalent to the both Precision and Recall, since the number of actual positives is the same as the number of predicted positives. <b>B-C</b>: Graphical representation of results in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005725#pcbi.1005725.t001" target="_blank">Table 1</a> and Table C in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005725#pcbi.1005725.s001" target="_blank">S1 Supporting Information</a>. Panel B shows the AUC values and panel C the fraction of neo-antigens predicted in the top 1% of predictions (which typically corresponds to what is experimentally tested for immunogenicity). <b>D-E</b>: Predictions of Cancer Testis Antigens from the CTDatabase. Panel D shows AUC values and panel E shows PP1%. Truncated y-axes are explicitly indicated.</p

General pipeline for HLA-I motif identification and annotation, and training of predictors.

<p>High accuracy HLA peptidomics data were first generated for 10 samples and collected from publicly available data for 40 other samples. In each sample motifs were identified using on our recent mixture model algorithm [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005725#pcbi.1005725.ref024" target="_blank">24</a>]. Motifs were then annotated to their respective allele based on co-occurrence of alleles across samples (e.g., first HLA-A24:02, then HLA-A01:01 and HLA-C06:02, see also Fig B in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005725#pcbi.1005725.s001" target="_blank">S1 Supporting Information</a> for another example). Finally all peptides assigned to each motif were pooled together to train our new HLA-I ligand predictor for each HLA-I allele (MixMHCpred v1.0).</p

Ranking of the neo-antigens identified in four melanoma samples [17,20].

<p>Column 2 shows the mutated neo-antigens (the mutated residue is highlighted in bold). Column 5 shows the ranking based on our predictions (i.e. number of peptide to be tested to find this neo-antigen). Columns 6 to 8 show the ranking based on NetMHC [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005725#pcbi.1005725.ref008" target="_blank">8</a>], NetMHCpan [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005725#pcbi.1005725.ref012" target="_blank">12</a>] and NetMHCstabpan [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005725#pcbi.1005725.ref036" target="_blank">36</a>], respectively. The last column shows the total number of neo-antigen candidates (i.e., all possible 9- and 10-mers encompassing all missense mutations).</p

Comparison between motifs predicted by our algorithm and known motifs.

<p><b>A</b>: Comparison with IEDB motifs for 44 HLA-I binding motifs identified with the fully unsupervised approach. Alleles without previously documented ligands are highlighted in red. For HLA-B56:01, the three known ligands are shown. <b>B</b>: Comparison with motifs obtained from mono-allelic cell lines [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005725#pcbi.1005725.ref031" target="_blank">31</a>]. <b>C</b>: Motif identified with the semi-supervised approach.</p

Correlation between amino acids frequencies at positions P4 to P7 in our HLA peptidomics data and in the human proteome.

<p>Correlation between amino acids frequencies at positions P4 to P7 in our HLA peptidomics data and in the human proteome.</p

Day-2, Day-4 and Day-7 DCs pulsed with UVBL or FTL mature normally following LPS and IFN-γ stimulation.

<p>Following lysate loading, DCs were stimulated with LPS (60 EU/ml) and IFN-γ (2000 IU/ml) for 16 h. DCs were identified by HLA-DR, CD11c and one of the markers shown. Unpulsed immature DCs (iDCs) and mature (mDCs) were set up in parallel and harvested at the same time as the other tumor lysate-loaded mature DCs for analysis. (A–C) Upregulation of maturation markers CD80, CD40, CD86, ICAM-1, and CCR7 is observed on mature Day-2, Day-4 and Day-7 DCs. The open histograms represent the isotype control, while shaded histograms represent the DC markers. The solid line marks the MFI of the different markers on iDCs for each condition. Representative histogram results from 1 out of 6 donors are shown here. (D) Fold-increase in expression levels of maturation and adhesion markers on mDCs, UVBL-loaded DCs (UVBL-DC) or FTL-loaded DCs (FTL-DC) over iDC was determined by expressing the MFIs as a ratio of the DCs to unpulsed iDCs. Highly significant differences were detected in CD86 (**<i>P</i> value = 0.002), ICAM-1 (**<i>P</i> value = <0.001), and CCR7 (**<i>P</i> value = 0.002, <0.001 and 0.008, respectively; ANOVA followed by <i>post-hoc</i> testing) on unpulsed matured Day-4 DCs compared to unpulsed matured Day-7 DCs. Similar highly significant differences were detected in CD86 and CCR7 (**<i>P</i> value = 0.001, and 0.01, respectively; ANOVA followed by <i>post-hoc</i> testing) on Day-4 UVBL-DCs compared to Day-7 UVBL-DCs. CD86 and ICAM-1 (**<i>P</i> value = 0.001, and 0.01, respectively; ANOVA followed by <i>post-hoc</i> testing) were also significantly different on Day-4 FTL-DCs compared to Day-7 FTL-DCs. (E) The overall immunophenotypes of DCs loaded with UVBL or FTL were similar to unpulsed mature DCs, however Day-4 DCs loaded with UVBL consistently expressed slightly higher levels of most markers including CD80, CD86 and CCR7 relative to any other lysate-DC preparations.</p

Day-4 DCs produce the highest levels of IL-12p70 and IP-10.

<p>Day-2, Day-4, and Day-7 DCs were first pulsed with either UVBL or FTL for 16 h, and then stimulated with LPS (60 EU/ml) and IFN-γ (2000 IU/ml) to determine (A) IL-12p70 and, (B) IP-10 production. Supernatants from the DC-tumor lysate cocultures were collected and evaluated by ELISA as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0028732#s2" target="_blank">Materials and Methods</a>. The results are from 4 different normal healthy donors and are expressed as mean (pg/ml) ± standard errors.</p

Day-4 DCs, but not Day-2 DCs, were as phagocytic as Day-7 DCs in actively engulfing ovarian tumor lysate.

<p>(A) Day-2, Day-4, and Day-7 DCs were cocultured with UVB lysate (UVBL) or freeze-thaw lysate (FTL) of PKH26-labeled SKOV3 cells at 37°C for 4 h or 24 h to determine active phagocytosis of tumor lysates. Representative dot plot results from 1 out of 6 donors are shown here. DCs that had engulfed PKH26-labeled tumor lysate appear as the HLA-DR⁺ PKH26⁺ double-positive population, and are expressed as the percentage of the total number of HLA-DR⁺ DCs as indicated in the upper-right quadrant of the dot plots. (B) DCs were cocultured with lysate at 4°C for 4 h or 24 h as controls to determine passive transfer of the PKH26 dye to DCs. Representative dot plot results from 1 out of 6 donors are shown here. HLA-DR⁺ PKH26⁺ double-positive DCs are expressed as the percentage of the total number of HLA-DR⁺ DCs as indicated in the upper-right quadrant of the dot plots. (C) Summary results of the percentages of Day-2, Day-4, and Day-7 DCs that have engulfed PKH26-labeled UVBL or FTL after 4 h or 24 h, at both 4°C and 37°C. Data displayed are the means ± standard errors of six independent experiments. There are no significant differences among Day-2, Day-4 and Day-7 DCs for the precentage of DCs taking up UVBL (ANOVA <i>P</i> value = 0.13) or FTL (ANOVA <i>P</i> value = 0.59) at 4 h. However, there is a significant difference for % of DCs taking up UVBL at 24 h (ANOVA <i>P</i> value = 0.02). By <i>post hoc</i> paired testing, % of Day-2 DCs taking up UVBL was significantly lower than either Day-7 or Day-4 DCs (*<i>P</i> values = 0.05 and 0.02, respectively). Highly significant differences were also observed for the uptake of FTL at 24 h (ANOVA**<i>P</i> value<0.001). The % of Day-2 DCs taking up FTL was significantly lower than either Day-7 or Day-4 DCs (**<i>P</i> values<0.001 for each). The differences between Day-4 and Day-7 DCs were insignificant for uptake of both UVBL (<i>P</i> value = 0.90) and FTL (<i>P</i> value = 0.92).</p