key: cord-1005946-lba4wf9y
authors: Hamelin, David J.; Fournelle, Dominique; Grenier, Jean-Christophe; Schockaert, Jana; Kovalchik, Kevin A.; Kubiniok, Peter; Mostefai, Fatima; Duquette, Jérôme D.; Saab, Frederic; Sirois, Isabelle; Smith, Martin A.; Pattijn, Sofie; Soudeyns, Hugo; Decaluwe, Hélène; Hussin, Julie; Caron, Etienne
title: The mutational landscape of SARS-CoV-2 variants diversifies T cell targets in an HLA supertype-dependent manner
date: 2021-10-06
journal: Cell Syst
DOI: 10.1016/j.cels.2021.09.013
sha: 006c656a10dcb824724a9ae22796605ee1da67e0
doc_id: 1005946
cord_uid: lba4wf9y

The rapid, global dispersion of SARS-CoV-2 has led to the emergence of a diverse range of variants. Here, we describe how the mutational landscape of SARS-CoV-2 has shaped HLA-restricted T cell immunity at the population level during the first year of the pandemic. We analyzed a total of 330,246 high quality SARS-CoV-2 genome assemblies, sampled across 143 countries and all major continents from December 2019 to December 2020 before mass vaccination or the rise of the Delta variant. We observed that proline residues are preferentially removed from the proteome of prevalent mutants, leading to a predicted global loss of SARS-CoV-2 T cell epitopes in individuals expressing HLA-B alleles of the B7 supertype family; this is largely driven by a dominant C-to-U mutation type at the RNA level. These results indicate that B7 supertype associated epitopes, including the most immunodominant ones, were more likely to escape CD8+ T cell immunosurveillance during the first year of the pandemic.

We found that specific amino acid residues were preferentially removed (proline, alanine and 268 threonine) or introduced (isoleucine, phenylalanine, leucine and tyrosine) in SARS-CoV-2 269 proteomes (Figure 3) . Most of these amino acids act as key epitope anchor residues for multiple 270 HLA class I supertypes ( Figure S4 ). For instance, phenylalanine and tyrosine are key anchor 271 residues for all known A*24 alleles of the A24 supertype family, whereas proline is known to play 272 a critical role in the anchoring of epitopes to alleles of the B7 supertype family (Figure 5) . 273 Therefore, one would expect the introduction of phenylalanine and tyrosine in SARS-CoV-2 274 proteomes to facilitate peptide presentation by A24, whereas the removal of proline would disrupt 275 peptide presentation by B7. With this concept in mind, we hypothesized that the distinct amino 276 acid mutational biases found throughout prevalent SARS-CoV-2 mutations could systematically 277 mold epitope presentation in an HLA supertype-dependent manner. 278

In order to compare supertypes to each other, we generated a 'Gain/Loss plot' for each 279 supertype assessed ( Figure 5C ). Gain/Loss plot were generated by computing the number of 280 mutations that resulted in 'Gain' or 'Loss' of epitopes for representative class I alleles selected for 281 each supertype (see methods for details). 'Gain' was assigned for mutated epitopes that were 282 predicted to transit from non-HLA binders (NetMHCpan %rank > 2) to strong HLA binders 283 13 (NetMHCpan %rank < 0.5), whereas 'Loss' was assigned for mutated epitopes that were predicted 284 to transit from strong HLA binders to non-HLA binders. Our analysis shows that most supertypes 285 preferentially gain new epitopes as a result of SARS-CoV-2 mutations: A1 (p = 4.5x10 -11 ), A2 (p 286 = 0.001), A24 (p = 1.0x10 -26 ), B8 (p = 2.4x10 -14 ), B27 (p = 2.5x10 -6 ). Preferential loss of epitopes 287 was only shown to be statistically significant for B7 supertype (p = 0.0012). Note that we explain 288 the relatively low statistical value obtained for B7 supertype by the presence of isoleucine and 289 phenylalanine (preferentially introduced in SARS-CoV-2 proteomes; see Figure 3 ) at anchor 290 residue P9 for certain HLA types (namely HLA-B*51:01 and HLA-B*53:01) ( Figure 5A ). In fact, 291 omitting motifs containing isoleucine or phenylalanine increased the significance of epitope lost 292 versus gained (p = 2.6x10 -7 ) ( Figure 5C ). Together, our results show that the amino acid 293 mutational biases that feature the global diversity of SARS-CoV-2 proteomes can positively or 294 negatively affect binding affinities of mutated epitopes for a wide range of HLA class I molecules 295 in a supertype-dependent manner. 296

The C-to-U point mutation bias largely drives diversification of SARS-CoV-2 T cell epitopes 298

Next, we sought to better understand the genetic determinants that drive the association between 299 epitope presentation and the amino acid mutational biases found in the SARS-CoV-2 population. 300

To this end, we analyzed the abundance of all the possible nucleotide mutation types (i.e. A-to-C, 301

A-to-G, A-to-U, C-to-A, C-to-G, C-to-U, etc.). This analysis indicates that C-to-U is the most 302 common mutation type (43%), followed by G-to-U (28%), as well as A-to-G, G-to-A and U-to-C 303 (from 9.7% to 11.6%) (Figure S5A ), in line with observations made by others (Giorgio et al.,  304 14 Next, we aimed to determine the contribution of these different nucleic acid mutation types 307 to the global mutational pattern observed at the amino acid level in Figure 3 . To do so, we 308 generated simulated population samples of 1000 SARS-CoV-2 genomes using SANTA-SIM 309 (Jariani et al., 2019), applying various extents of mutational biases corresponding to the two most 310 common mutation types observed (i.e. C-to-U and G-to-U). The resulting simulated viral 311 populations were then analyzed to elucidate the global amino acid mutational pattern engendered 312 by these simulated nucleic acid point mutation biases, and whether they recapitulate the observed 313 patterns. Indeed, our data show that the mutational pattern resulting from the simulated C-to-U 314 bias very closely mimicked the mutational pattern observed in the real-life dataset ( Figure 6A) . 315 Namely, the in silico introduction of a C-to-U mutation bias resulted in the preferential removal 316 of alanine, proline, and threonine, by 6.7% (p = 5.1x10 -11 ), 6.9% (p = 1.2x10 -11 ) and 8% (p = 317 4.8x10 -12 ), respectively, as well as the introduction of isoleucine and phenylalanine by 8.2% (p = 318 1.3x10 -8 ) and 5.2% (p = 4.3x10 -11 ), respectively (Figure 6A) . The G-to-U mutation bias also 319 contributed to the introduction of isoleucine and phenylalanine ( Figure S5B ). Together, these 320 results show that the predominant C-to-U point mutations largely contribute to shaping the global 321 proteomic diversity of SARS-CoV-2. 322

Given the significant impact of the C-to-U point mutation bias on the amino acid content 323 of SARS-CoV-2 proteomes, we reasoned that C-to-U could be the main driver shaping the 324 repertoire and diversification of SARS-CoV-2 T cell targets in human populations, including 325 targets presented by the particularly interesting B7 supertype molecules. To investigate this, we 326 used all the SARS-CoV-2 CD8+ T cell epitopes that were experimentally validated using 327 peripheral blood mononuclear cells (PBMC) of acute and convalescent COVID-19 patients 328 (Quadeer et al., 2021; Tarke et al., 2021a) and matched them with their corresponding nucleic acid 329 J o u r n a l P r e -p r o o f 15 sequence found in reference/mutated genome pairs. We then calculated the frequency of the 330 various mutation types (i.e. A-to-C, A-to-G, A-to-U, C-to-A, C-to-G, C-to-U, etc.) coding for the 331 mutated form of those experimentally validated CD8+ T cell epitopes. We found that C-to-U and 332 G-to-U were the two main mutation types leading to mutated epitopes, both accounting for 37% 333 of all mutation types amongst prevalent mutations (>100 individuals) ( Figure 6B ). In addition, 334 our data show that 62% of the prevalent mutations predicted to disrupt the presentation of epitopes 335 by HLA alleles for the B7 supertype were found to derive from the C-to-U mutation type (Figure  336 6B). These results strongly suggest that the dominant C-to-U point mutation bias found amongst 337 prevalent SARS-CoV-2 mutants has the potential to contribute to shaping the repertoire of SARS-338

CoV-2 T cell epitopes in B7 supertype individuals across human populations. Collectively, our 339 study lets us to propose the model that C-to-U editing enzymes play a fundamental role in shaping 340 the mutational landscape dynamics of SARS-CoV-2 CD8+ T cell targets in humans (Figure 6C) , 341 and hence, may contribute to molding T cell immunity against COVID-19 at the population level. a novel virus such as SARS-CoV-2, such a relationship remains to be established and  353 does not constitute the scope of our work. Here, we rationalized that an alternative approach to 354 interrogating SARS-CoV-2 epitope-associated variants is by investigating the global genomic and 355 proteomic diversity of SARS-CoV-2 for any outstanding mutational biases, and then, assessing 356 the relationship between such biases and epitope presentation for a broad set of HLA alleles. In 357 other words, in this study, we did not seek to understand how viral mutations are shaped by T cell 358 immunity, but rather to understand how mutational biases in SARS-CoV-2 may have shaped T 359 cell immunity at the population level during the first year of the pandemic. This approach was 360 possible thanks to an unprecedented number of SARS-CoV-2 genome sequences available for 361 downstream analysis. Our approach is universal and could be applied to other epidemic or 362 pandemic viruses in the future, given the development of distinct, prevalent mutational biases. Our 363 global approach has led to several conclusions to help understand how the increasing genomic 364 diversity of SARS-CoV-2 may shape T cell immunity in human populations. Our findings have 365 important implications that are discussed below in the context of disease severity, viral evolution 366 and vaccine resistance. 367

In this study, we found that prevalent SARS-CoV-2 mutations are governed by defined 368 mutational patterns, with C-to-U being a predominant mutation type, as previously shown by the C-to-U mutation bias in SARS-CoV-2 genomes has a remarkably intimate relationship with 372 the observed amino acid mutational biases, indicating that C-to-U mutations largely contribute to 373 the global proteomic diversity of SARS-CoV-2. Moreover, we show that this mutational bias leads 374 to the preferential substitution of proline residues with leucine or serine residues in the P2 anchor 375 position of SARS-CoV-2 CD8+ T cell epitopes, and hence, drastically compromise epitope 376 binding to B7 supertype molecules. These molecules, which represent ~35% of the human 377 population, preferentially bind epitopes with proline at P2 (Francisco et al., 2015) (Francisco et al., 378 2015) . Therefore, the C-to-U mutational bias observed amongst prevalent mutants may partially 379 disrupt SARS-CoV-2 T cell immunity in a very significant proportion of the human population. 380

Noteworthy, this impact of C-to-U mutations on B7-dependent epitope escape was somehow 381 predictable. In fact, proline residues originate from codons that are highly rich in C whereas serine 382 and leucine residues originate from codons that are rich in U. One could therefore predict, at least 383 to some extent, that a strong C-to-U bias would lead to proline-to-leucine or proline-to-serine 384 substitutions. Thus, this study highlights the impact of viral mutational biases and codon usage in 385

shaping the diversity of CD8+ T cell targets. The impact of the loss of several B7 epitopes on the 386 immune response of an individual, however, remains unclear. 387

In this study, we observed that prolineX mutations were more enriched amongst 388 prevalent mutations (>100 genomes) predicted to abrogate the presentation of experimentally 389 validated CD8+ T cell epitopes than across the global mutation landscape of SARS-CoV-2 390 proteomes (31% and 9.1%, respectively). These two percentages are in fact indicative of different 391 phenomena. The former reflects the susceptibility of certain HLA alleles to specific mutational 392 patterns (the removal of proline in this case), whereas the latter reflects the overall mutational 393 biases observed across SARS-CoV-2 proteomes. This noticeable difference may suggest that 394 certain mutation types play a particularly important role in HLA type-dependant cytotoxic T 395 lymphocyte (CTL) escape. This concept becomes evident when considering the 13 common alleles 396 investigated in this study. The detrimental impact of prolineX mutations on the presentation of 397 peptides by B7 alleles is reflected in the higher proportion of prolineX mutations (31%) leading 398 to the loss of epitopes. This being said, it is important to realize that we do not make the claim that 399 the presence of proline-to-leucine or proline-to-serine mutations in the SARS-CoV-2 proteomes 400 depend on patients being B7 supertype-positive, or that the B7 supertype drives the evolution of 401 proline-to-leucine/serine mutations. We do, however, demonstrate that the prevalent mutations 402 currently in circulation are enriched for proline-to-leucine/serine, and our in silico predictions 403 suggest that the high occurrence of this mutation type leads to widespread hinderance of epitope 404 presentation in B7 supertype-positive individuals. 405

A key question to address is to what extent does the C-to-U bias drive SARS-CoV-2 406 evolution and adaptation over the course of the ongoing pandemic. As proposed by others, the 407 most likely explanation for the observed C-to-U bias is the action of the host-mediated RNA-408 editing APOBEC enzymes, a family of cytidine deaminases that catalyze deamination of cytidine 409 with our findings. Indeed, we showed that amino acid mutation biases in SARS-CoV-2 proteomes 420 generally positively affect epitope binding for various HLA class I supertypes, and most strikingly 421 for A24, whereas B7 is the only supertype that is consistently negatively affected by the mutation 422 biases given the markable loss of proline residues in SARSCoV-2 proteomes. Together, our results 423 raise the important hypothesis that host-mediated RNA editing systems shape the repertoire of 424 SARS-CoV-2 T cell epitopes in a positive and negative HLA-dependant manner. 425

Another question is whether populations of B7 supertype individuals represent an 426 advantageous reservoir for the virus to evolve toward more transmissible variants. As the genetic 427 diversity of the SARS-CoV-2 population continue to increase, and as new variants emerge, our 428 global analysis suggests that the probability for SARS-CoV-2 epitopes to escape CD8+ T cell 429 immunosurveillance is higher in B7 individuals compared to A24 individuals. In fact, mutated 430 epitopes are predicted to be unfavorably and favorably presented by B7 and A24 supertypes, Saharan Africa) (http://www.allelefrequencies.net/top10freqs.asp) may provide insights into this 466 concern. As new variants of concern continue to emerge and as new epitope data are continuously 467 In summary, our study shows that mutation biases in the SARS-CoV-2 population diversify 484 the repertoire of SARS-CoV-2 T cell targets in humans in an HLA-supertype dependent manner. 485

Hence, we provide a foundation model to help understand how SARS-CoV-2 may continue to 486 mutate over time to shape T cell immunity at a global population scale. The proposed process will 487 likely continue to influence the evolution and diversification of SARS-CoV-2 lineages as the virus 488 is under tremendous pressure to adapt in response to mass vaccination. Our analyses focused on class I molecules for which predictors are established to be more accurate 492 in comparison with class II. HLA-C and non-classical HLA were not included in this study. 493

Predictions were performed on the most common HLA class I alleles and rare HLA alleles were 494 not included. Study has been performed using the GISAID dataset available in December 31 st 495 2020, i.e. first year of the pandemic, before mass vaccination. Our epitope binding results rely on 496 in silico predictions using a method that has been widely benchmarked, but is designed to predict 497 peptide presentation rather than immunogenicity. Figure S4 ) were used to generate the graphs and p-604 values (*p ≤ 0.001, **p < 1e-5, ***p < 1e-10). 605 

All SARS-CoV-2 nucleotide sequences were acquired from the GISAID on 31/12/2021. A total of 647 330,246 SARS-CoV-2 sequences spanning 143 countries were acquired and analyzed. All 648 sequences isolated from animals (including viral RNA isolated from bat, pangolin, mink, cat and 649 tiger) were removed from the list and only high-quality sequences were further analysed. 650

Consensus sequences were aligned to the reference sequence, Wuhan-1 (NC_045512.2) using 651 minimap2 2.17-r974. All mapped sequences were then merged back with all others in a single 652 alignment bam file. The variant calling was done using bcftools mpileup v1.91 in a haploid calling 653 mode. Sequences were processed by batches of 1000 to overcome technical issues with very low-654 frequency variants. With the variant calling obtained for each batch, vcf-merge (from the vcftools 655 suite) was used to merge all the variant calls across the entire dataset. A total of 24,220 variants in 656 at least two consensus sequences were identified. Mutations appearing in only one genome were 657 excluded as they are likely enriched for sequencing errors. A list of all missense mutations 658 considered in our analyses is provided in Table S1 . The 1,933 prevalent mutations observed in 659 more than 100 genomes are also clearly shown in Table S2 . Regarding your request, we are pleased to grant you non-exclusive, non-transferable permission, to republish the AAAS material identified above in your work identified above, subject to the terms and conditions herein. We must be contacted for permission for any uses other than those specifically identified in your request above.

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Permission is granted to use the AAAS material on the cover of a journal issue, newsletter issue, book, textbook, or annual report in print and electronic formats provided the AAAS material reproduced as permitted herein remains in situ and is not exploited separately The dominant CU mutation type was found to diversify the repertoire of experimentally validated SARS-CoV-2 CD8+ T cell epitopes in an HLA supertype-dependant manner. Notably, the prevalent removal of proline was predicted to preferentially abrogate epitopes presented by the B7 HLA supertype. This model lays a foundation for testing the impact of SARS-COV-2 mutants on T-cell escape in an HLA-dependant manner.

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concern partially escape humoral but not T-cell responses in COVID-19 convalescent donors and  870 vaccinees. Sci Immunol 6, eabj1750. This permission is not valid for the use of the AAAS and/or Science logos. AAAS makes no representations or warranties as to the accuracy of any information contained in the AAAS material covered by this permission, including any warranties of merchantability or fitness for a particular purpose.If permission fees for this use are waived, please note that AAAS reserves the right to charge for reproduction of this material in the future.Permission is not valid unless payment is received within sixty (60) days of the issuance of this permission. If payment is not received within this time period then all rights granted herein shall be revoked and this permission will be considered null and void.In the event of breach of any of the terms and conditions herein or any of CCC's Billing and Payment terms and conditions, all rights granted herein shall be revoked and this permission will be considered null and void.AAAS reserves the right to terminate this permission and all rights granted herein at its discretion, for any purpose, at any time. In the event that AAAS elects to terminate this permission, you will have no further right to publish, publicly perform, publicly display, distribute or otherwise use any matter in which the AAAS content had been included, and all fees paid hereunder shall be fully refunded to you. Notification of termination will be sent to the contact information as supplied by you during the request process and termination shall be immediate upon sending the notice. Neither AAAS nor CCC shall be liable for any costs, expenses, or damages you may incur as a result of the termination of this permission, beyond the refund noted above.This Permission may not be amended except by written document signed by both parties.The terms above are applicable to all permissions granted for the use of AAAS material. Below you will find additional conditions that apply to your particular type of use.

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