To investigate the functional role of the allosteric regulatory site of ERAP1 we set forth to analyze the effect of targeting that site using an allosteric inhibitor on the immunopeptidome of cells. As a cellular model, we utilized the A375 melanoma cancer cell line since, as previously demonstrated, its immunopeptidome is sensitive to ERAP1 inhibition 5. We thus treated A375 cells with 10 µM of the compound (4aR,5S,6R,8S,8aR)-5-(2-(Furan-3-yl)ethyl)-8-hydroxy-5,6,8a-trimethyl-3,4,4a,5,6,7,8,8a-octahydronaphthalene-1-carboxylic acid (Fig. 1) for a total period of 6 days. The utilized concentration is 10-fold over the calculated cellular EC50 of this compound and should result in to > 90% inhibition of ERAP1 in the cell, while having no adverse toxicity effects 18. As a positive control, we subjected the same cell line to CRISRP/Cas9 with a guide RNA targeting the ERAP1 gene. This led to undetectable ERAP1 expression as evidenced by western blotting and thus corresponds to a positive control condition simulating complete inhibition of the enzyme (Supplemental Figure S1). Wild-type cells were also analyzed as a negative control. For each condition, we grew the cells to about 0.4–0.5 x 109 cells in three separate biological replicates (a total of about 1-1.5 x 109 cells per condition). Each condition was later analyzed in triplicate by LC/MS-MS resulting in a maximum of 9 replicates (3 biological and 3 technical) per condition. MHC-I-peptide complexes were isolated by affinity chromatography using the W6/32 antibody as previously described5. Eluted peptides from MHC-I complexes were sequenced by LC-MS/MS using data-independent acquisition27. One biological replicate for the wild-type and knock-out conditions gave a very low peptide signal and was not analyzed further. In total, we identified 3443 unique peptide sequences. 309 peptide sequences were common with a blank injection control and were removed, leaving 3134 unique peptides (Supplemental Table 1). A heatmap of identified peptides clustered by signal intensity is shown in Fig. 2. All replicates from each experimental condition cluster together validating the reproducibility of the analysis. Visual inspection of the heatmap suggests that there are significant differences between the three conditions, indicating that both pharmacological and genetic inhibition of ERAP1 is sufficient to shift the immunopeptidome as shown previously 28–30. Surprisingly, however, the overall profiles of the knock-out and inhibitor-treated cells were strikingly different suggesting that the immunopeptidome shifts induced by a total lack of ERAP1 enzyme or allosteric inhibition are not equivalent.
To better understand the differences in peptide presentation between the three conditions, we performed a pairwise analysis of the conditions that disrupt ERAP1 function (inhibitor or knock-out) and the wild-type cells. The volcano-type plots for these comparisons are shown in Fig. 3. Comparing the inhibitor-treated cells to the wild-type 1295 peptides were upregulated by more than 2-fold and in a statistically significant manner (Q Value ≥ 0.05) (Fig. 3A). Similarly, 422 peptides were downregulated. In addition, 23 peptides were found in the inhibitor-treated cells but not identified in the wild-type cells and 252 peptides were unique to the wild-type cells and not present in the inhibitor-treated cells. By summing the quantitatively affected with the unique peptides, we concluded that the presentation of 1318 peptides were enhanced by the inhibitor and 674 peptides were downregulated (Fig. 3B). Similar analysis on the comparison of the effect of the knock-out indicated that from 3125 peptides detected, 1095 peptides were upregulated by the knock-out and 1277 peptides were downregulated (Fig. 3C and D). Overall, the inhibitor resulted in the upregulation of 51% and the downregulation of 26% of the immunopeptidome of A375 melanoma cells and the knock-out resulted in the upregulation of 35% and the downregulation of 41% of the immunopeptidome. In summary, although the effect of ERAP1 modulation was relatively small in terms of novel sequences presented it was major in terms of changes in levels of presentation of existing peptides.
While both ways to interfere with ERAP1 function yielded similar, albeit not identical, overall effects on the immunopeptidome, the exact nature of peptides presented was different. To compare the different experimental conditions, we performed principal component analysis (Fig. 4). This analysis indicated that, while all experiments from each condition clustered together, all three conditions were distinct, suggesting statistically significant changes in the sequence patterns of peptides generated.
Since length is a key parameter for MHC-I binding, we analyzed the length distribution of peptides identified to be either upregulated or downregulated in each condition. ERAP1 has been shown to both help generate correct-length peptides for MHC-I and to also over-trim peptides to lengths too short for binding. Peptides in the wild-type cells that were unaffected by ERAP1 disruption were primarily 9mers as expected based on the binding preferences on MHC-I (Fig. 5). The inhibitor downregulated and KO downregulated peptides showed a similar distribution. The KO upregulated peptides were primarily 10mers and 11mers consistent with a lack of a length-limiting aminopeptidase. Strikingly, although the inhibitor-upregulated peptides also displayed a shift towards longer peptides, this effect was much less pronounced compared to the KO-upregulated peptides, with most peptides being 9mers. This surprising result suggests that ERAP1 inhibition through the allosteric regulatory site does not sufficiently reduce the processing of longer peptides to allow their accumulation as it occurs in the complete absence of the enzyme.
To validate that the identified peptides are indeed ligands of the MHC-I haplotypes carried by A375 cells (HLA-A*01:01:01, HLA-A*02:01:01, HLA- B*44:03:01, HLA-B*57:01:01, HLA-C*06:02:01, and HLA-C*16:01:01) we used the HLAthena server to score the peptides with lengths between 8–11 amino acids for predicted binding to at least one HLA allele31. In all experimental conditions over 90% of identified peptides scored a rank below 2 and are thus considered binders for at least one of the MHC-I alleles carried by A375 cells (Fig. 6). In comparison, > 95% of a randomly generated set of peptides are predicted not to bind onto any of the MHC-I alleles. This finding provides validation that the peptides identified are indeed eluted from MHC-I but also suggests that there is no significant change in peptide affinity between peptides affected by the inhibitor or the ERAP1 KO. Thus, both pharmacological and genetic inhibition of ERAP1, can affect the immunopeptidome in qualitative and quantitative manners while not degrading the binding capacity of presented peptides. This finding is in contrast with initial observations that ERAP1 functional disruption leads to the presentation of sub-optimal peptides32.
To investigate whether the different modes of ERAP1 perturbation could translate to different cellular antigenicity, we searched identified peptides for known melanoma cancer antigenic peptides from the MAGE-A Tumor-Associated Antigen and the P antigen family 33. Table 1 lists identified peptides. The inhibitor-treated cells demonstrated a distinct pattern over the KO cells and upregulated presentation of most MAGE-A antigenic peptides. This finding suggests that allosteric inhibitors may indeed be useful in enhancing the antigenicity of cancer cells.
Table 1
List of cancer antigenic peptides that are affected by the inhibitor or the knockout
Antigenic peptide
|
Gene
|
Inhibitor upreg.
|
Inhibitor downreg.
|
Knock-out upreg.
|
Knock-out downreg.
|
MEVDPIGHLY
|
MAGEA3
|
|
+
|
|
+
|
KEADPTGHSY
|
MAGEA1
|
+
|
|
+
|
|
EVDPIGHLY
|
MAGEA3
|
+
|
|
|
+
|
GVYDGREHTV
|
MAGEA4
|
+
|
|
|
|
KVLEHVVRV
|
MAGEA4
|
+
|
|
|
|
FVYGEPREL
|
MAGEC2
|
+
|
|
|
+
|
EEVPSGVIPNL
|
MAGEC2
|
+
|
|
|
|
EVDPTSHSY
|
MAGEA11
|
+
|
|
|
|
YGEPRKL
|
MAGEA9
|
+
|
|
|
|
TLPTFDPTKV
|
PAGE5
|
|
|
|
+
|
SAYGEPRKL
|
MAGEA1
|
|
+
|
+
|
|
For a more direct comparison of the immunopeptidomes of the inhibitor-treated and knock-out cells, we performed a volcano-type analysis, shown in Fig. 7A. From this analysis, it was evident that many peptides are differentially regulated by the inhibitor compared to the KO cells. Accordingly, 516 peptides were upregulated in the KO compared to the inhibitor, and 1487 were downregulated. Most importantly, when comparing the lists of upregulated or downregulated peptides by the inhibitor or the KO compared to the wild-type cells (data presented in Fig. 3), up to 2/3 of the peptides were distinct (Fig. 7B). Thus, it appears that although both the inhibitor and the KO induce significant shifts in the immunopeptidome of A375 cells, these shifts have a very limited overlap, a finding that suggests significant mechanistic differences between the two methods of ERAP1 disruption.
The observed differences in peptides presented when ERAP1 is disrupted by different methods may be translated to the cell surface presence of different HLA alleles. To address this question, we calculated the relative percentage of peptides predicted to bind best to one of the 6 HLA alleles carried by A375 cells (Fig. 8). Interestingly, when comparing the inhibitor to the KO, the inhibitor-treated cells presented more peptides bound onto HLA-A*01:01 whereas the KO cells presented more peptides onto HLA-B alleles. The overall pattern was largely reversed for the downregulated peptides in which the inhibitor showed enhancement for HLA-B alleles. Thus, it appears that the different modes of ERAP1 functional disruption can be reflected in the relative presentation of HLA alleles.
The observation that the two different modes of inhibition may translate to changes in the presentation by specific HLA alleles, suggested that changes in the sequence motifs of presented peptides may be observable. Although ERAP1 activity has been reported to be sequence-dependent, how well ERAP1 sequence specificity translates to surface presentation is not well-understood14,26,34. While ERAP1 can edit the peptide repertoire in the ER, HLA binding specificity and editing chaperones such as the peptide loading complex, may filter out most ERAP1 sequence selectivity7. To approach this question we performed non-metric multidimensional scaling (NMDS) 35. This analysis projects peptides in two-dimensional space based on the similarity of the amino acid sequences. We performed pairwise comparisons of the inhibitor-upregulated versus the KO-upregulated peptides predicted to bind to at least one HLA allele (as in Fig. 6) as well as the inhibitor-downregulated versus the KO-downregulated binders (Fig. 9). For the upregulated peptides, the stark difference in length distribution between the inhibitor-treated cells and the KO cells (Fig. 5), would bias the analysis towards the most populated clusters and thus we focused our analysis on the 10mers which are roughly equal in numbers in both conditions. NMDS analysis revealed 5 major clusters (Fig. 9A) and distinct patterns for co-clustered peptides, with inhibitor-upregulated peptides positioned in a different way than KO-upregulated peptides (Fig. 9B). In an attempt to quantify the differences, the 181 inhibitor-upregulated (Fig. 9C, in red) versus the 224 KO-upregulated (Fig. 9C, in green) peptides were plotted per cluster. Statistical analysis revealed that inhibitor-upregulated peptides were overrepresented in cluster 5 (X2, Bonferroni n = clusters, Padj= 4.46e-03), while the KO-upregulated peptides were overrepresented in clusters 1 (X2, Bonferroni n = clusters, Padj= 4.07e-05) and 2 (X2, Bonferroni n = clusters, Padj= 2.1e-04). Cluster 1 (Fig. 9D) fits the sequence motif of HLA-B*57:01, cluster 2 the motif of HLA-B*44:03 and HLA-A*02:01, whereas cluster 5 is typical for HLA-A*01:01. These results are in concordance with the results shown in Fig. 8, which indicate a shift from HLA-A*01:01 in the inhibitor-treated cells to HLA-B*57:01 in the KO cells. Cluster 5 differs from the other two clusters mainly in position 3, where D is the most abundant amino acid, and position 10, which is occupied only by Y. These positions are also anchor positions for the represented allele. Cluster 1 is characterized by S,T,A & V in position 2 and W and F in position 10, which are also considered anchor positions for HLA-B*57:01. Furthermore, position 1 is dominated by the positively charged amino acids K and R, which are considered poor substrates for ERAP136. These amino acids are not unusual for this allele, as seen in supplemental Figure S2, and could indicate that peptides that do not require ERAP1 for trimming, which are expected to be represented to a higher extent upon complete inhibition of the enzyme, are preferred in this case.
For the down-regulated peptides NMDS analysis, we again focused our analysis on the 10-mers which are roughly equal in numbers between the two conditions (Fig. 9E-H). Cluster 3 was significantly overrepresented in KO-downregulated peptides (X2, Bonferroni n = clusters, Padj= 0.022). A similar trend was seen for cluster 6, which however was not statistically significant after multiple comparison corrections (X2, Bonferroni n = clusters, Padj= 0.087, P = 0.012). Cluster 2 was overrepresented by inhibitor downregulated peptides, although with low statistical significance (X2, Bonferroni n = clusters, Padj= 0.066, P = 0.009). Sequence motifs in clusters 2 and 3 (Fig. 9D) are representative of HLA-B*44:03. Although this allele was the most presented in the upregulated peptides of both treated samples, some differences in the exact preferences would still be possible and it may as well be that depending on the treatment (inhibitor or KO), different sub-motifs may be affected. The motif depicted in cluster 6, which includes the most KO-downregulated peptides (30% of KO-downregulated 10-mers) matches the preferences of HLA-A*01:01 and, despite poor statistical significance, is further supporting the observation that the presentation of peptides to this allele is negatively affected. Finally, cluster 5, was more populated in the KO and fits HLA-A*02:01 consistent with the results in Fig. 6. Overall, NMDS analysis suggested that while presented peptide sequences are dominated by HLA binding preferences, different methods of perturbation of ERAP1 function can still influence the relative abundance of HLA-compatible sequence motifs. How exactly ERAP1 substrate preferences and the ERAP1 allosteric site can regulate the ER repertoire of “MHC-ready” peptides will likely require integrated analysis in more controlled systems to help deconvolute the relative influence of these antigen processing components.