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Antigen identification and high-throughput interaction mapping by reprogramming viral entry

Deciphering immune recognition is critical for understanding a broad range of diseases and for the development of effective vaccines and immunotherapies. Efforts to do so are limited by a lack of technologies capable of simultaneously capturing the complexity of adaptive immune receptor repertoires and the landscape of potential antigens. To address this, we present RAPTR (Receptor-Antigen Pairing by Targeted Retroviruses). RAPTR combines viral pseudotyping and molecular engineering approaches to enable one-pot library on library interaction screens by displaying antigens on the surface of lentiviruses and encoding their identity in the viral genome. Antigen-specific viral infection of cell lines expressing human T or B cell receptors allows readout of both antigen and receptor identities via single-cell sequencing. The resulting system is modular, scalable, and compatible with any cell type. These techniques provide a suite of new tools for targeted viral entry, molecular engineering, and interaction screens with broad potential applications.

to drive expression of a reporter gene. Other previously established approaches include 80 automated individual ELISA screens of recombinantly expressed protein pairs 17-19 , as 81 well as mass-spectrometry-based identification of interacting pairs 20,21 . There have been 82 several recent efforts at designing novel systems, including those based on yeast mating 83 or spatial colocalization of DNA-barcoded molecules 22,23 . However, these approaches 84 can be labor-intensive, are often not suited for complex, extracellular protein complexes 85 such as immune receptors, and may be inefficient at low (i.e. micromolar) affinities. 86 Together, these limitations have thus far rendered such approaches unsuitable for 87 applications such as identifying TCR-pMHC pairs. 88 To overcome the above limitations, we have developed a technique that combines 89 lentiviral surface display 24-26 with a versatile pseudotyping strategy and viral genome 90 engineering to enable one-pot library vs library screening (Figure 1). We demonstrate 91 that our pseudotyping strategy -an engineered fusogen termed VSVGmut co-expressed 92 with a targeting moiety -is general and versatile for both receptor and ligand usage. We

B) Broad range of receptors and ligands for targeted viral entry
Antigen Specificity Via TCR, BCR Lineage CD3, CD19, CD20

Following the observation that anti-CD3 viruses yielded infection of T cells via a 148
component of the TCR complex, we next sought to determine whether we could achieve 149 antigen-specific cell entry via the TCR itself. One potential challenge to repurposing the 150 TCR-pMHC interaction for viral entry is its affinity, which is typically 1-50 μM 39 . We 151 therefore generated cell lines expressing a range of previously characterized affinity 152 variants for the 1G4 TCR 40,41 , which recognizes a peptide derived from the NY-ESO-1 153 cancer testis antigen (SLLMWITQV) presented in the context of HLA-A*02:01, with 154 reported affinities ranging from picomolar to micromolar (Figure 2A). To display these 155 molecules on the virus surface, we expressed them as single-chain trimers 42 , which are 156 comprised of covalently linked peptide, beta-2-microglobulin, and MHC. We found that 157 pMHC-displaying lentiviruses are able to efficiently infect T cells in an antigen-dependent 158 manner. We observed similar infection efficiency across the tested affinity range, with 159 only a modest reduction for the lowest-affinity variant ( Figure 2B). To ensure that TCR-160 mediated infection was generalizable, we displayed several individual pMHCs as single-161 chain trimers alongside VSVGmut and used them to infect either Jurkat cells expressing 162 its parental TCR (off-target) or on-target J76 cell lines expressing their cognate TCRs 163 ( Figure 2C). We observed specific infection across 3 different TCR-pMHC pairs with 164 minimal background infection. As VSVG enables cell entry via an endocytic route 43 , and 165 because endocytosis is one of the earliest downstream events following T cell 166 activation 44-46 , we next sought to determine whether viral infection was accompanied by 167 TCR signaling. We measured CD69 expression following viral infection (Figure 2D), and Figure 2 | TCR-mediated infection is sensitive, specific, and induces signaling A, Schematic of the 1G4 TCR-HLA-A2/NY-ESO-1 system used for TCR-pMHC characterization. B, Representative infection data for various 1G4 TCR affinity variants by HLA-A2/NY-ESO-1 displaying VSVGmut lentiviruses. C, infection of J76 cells via specific TCR-pMHC interactions via pMHC-displaying VSVGmut lentiviruses for three independent TCR-pMHC pairs (HLA-A2/SL9-displaying viruses infecting 868 TCR-expressing J76 cells; HLA-A2/NLV-displaying viruses infecting C7 TCR-expressing J76 cells; HLA-A2-NY-ESO-1-displaying viruses infecting 1G4 TCR-expressing J76 cells). D, Upregulation of CD69 on J76 cells transduced with the 1G4wt TCR during viral entry demonstrates that viral entry induces TCR signaling; data shown represent mean + SD across three biological replicates, dashed line represents CD69 expression in untreated J76-1G4wt cells. E, Selectivity ratio of on target to off target infection of J76 cells expressing 1G4 TCR variants mixed at indicated ratios with off-target Jurkat cells; representative of three independent experiments, flow plots correspond to 1G4wt TCR-expressing J76 cells with target cell frequencies indicated in red.

D)
Infection (GFP) Side Scatter observed robust CD69 upregulation during TCR-mediated viral entry, but not during off-169 target combinations. Moreover, TCR-mediated entry was inhibited by dasatinib, a TCR 170 signaling inhibitor 47 , while TCR-independent infection via VSVGwt was unaffected 171 (Supplementary Figure 2B). Thus, we concluded that pMHC-targeted viruses integrate 172 both binding and signaling as a means of infection. 173 We next sought to determine the limitations of our system by characterizing its 174 sensitivity and specificity using the 1G4-NY-ESO-1 system. To determine the ability of 175 our approach to discern on-target interactions in complex mixtures, we labeled 1G4-176 expressing cells with a cell tracking dye, mixed them at varying ratios with unlabeled 177 Jurkats, and infected the mixture with NY-ESO-1/HLA-A2 displaying viruses ( Figure 2E). 178 We calculated a selectivity ratio of on-target infection relative to off-target infection, and 179 observed on-target selectivity greater than 200:1, down to target cell frequencies of 1x  Figure 3A). In functional genomics, this leads to well-Figure 3 | LeAPS-based lentiviral packaging enables scalable viral library construction A, Schematic overview of the limitation of conventional lentiviral packaging strategies for surface displayed lentiviral libraries, in which a mixture of displayed surface proteins disrupts the linkage between viral pseudotype and genomic identity. B, Schematic overview of the mechanism of promoter translocation used in the LeAPS system, in which a promoter sequence placed internally in the lentiviral genome is placed 5' of the 5' LTR during the viral lifecycle, thus allowing the integrated vector to produce viral genomes at high copy number. If cells are infected with a single lentiviral vector, each infected cell is ensured to produce viruses that match viral surface phenotype and genotype. C, Packaging cells transduced with viruses containing LeAPS-encoding genomes and then transfected with lentiviral helper plasmids produce high titer virus (top), while those transduced with viruses containing standard genomes produce minimal functional

Infection (GFP) Side Scatter
virus (bottom). D, LeAPS-produced viruses maintain TCR specificity in two independent TCR-pMHC systems, demonstrating functional targeted viruses can be created. E, Schematic overview of the implementation of LeAPS for viral library assembly. 293T cells are co-transduced with known combinations of LeAPS-fluorophore-barcode viruses and pMHC expression viruses, all cells are pooled and sorted to generate a library packaging line that generates virus following helper plasmid transfection. F, On-target enrichment of libraries using defined mixtures of A2-NY-ESO-1 and A2-SL9 packaging cells to represent 100-or 1,000-variant libraries.  verified that viruses produced in this manner maintain antigen-specific targeting capability 215 ( Figure 3D). 216 To develop a scalable library assembly strategy, we co-transduced 293T cells with 217 two VSVGwt-pseudotyped viruses: one that drives surface expression of a known pMHC 218 using a conventional lentivirus, and another that uses the LeAPS system to deliver a 219 repackageable genome driving expression of a fluorescent protein and a defined barcode 220  from influenza A (Figure 4D and Supplementary Figure 4C). In all cases, we observed 254 robust enrichment of on-target, but not off-target, barcodes.

RAPTR can be adapted to BCRs 256
Many of the same constraints that limit TCR-pMHC interaction screens are also 257 shared by efforts to identify B cell antigens at scale. Most approaches rely on barcoded 258 multimers for very few targets, and the largest antigen library reported to date is 9 259 antigens 15 . As BCRs are also rapidly endocytosed upon antigen engagement 58,59 , we 260 reasoned that we could use stabilized viral surface antigens or known immunogens as targeting ligands for viral infection. We thus generated a "hybrid" pseudotype co-262 expressing either the surface-tethered receptor binding domain (RBD) or the full-length, 263 pre-fusion stabilized spike (S2P) protein from SARS-CoV-2 60 alongside VSVGmut 264 ( Figure 5A). We used each of these to achieve efficient, antigen-specific infection of a 265 Ramos cell line expressing CR3022, a B cell receptor clone that is cross-reactive for the 266 RBDs of SARS-CoV-1 and 2 61,62 (Figure 5B). Similarly, hybrid pseudotypes incorporating 267 HIV env CD4 binding site (CD4bs) constructs from diverse clades 63 each infected cell 268 lines expressing the bNab VRC01 64 , and a known affinity-reducing mutation (D368R) 269 dramatically reduced, but did not fully abrogate, infection 65 . 270 To determine the sensitivity for BCR-mediated cell entry, we mixed Ramos cells 271 expressing either the CR3022 BCR (IgM + ) or no BCR (IgM-negative), and tracked on-272 target cells via surface IgM expression ( Figure 5C). Using RBD-displaying viruses, we 273 observed specific infection at target cell frequencies at least as rare as 1x10 -5 , but could 274 not calculate a meaningful selectivity ratio due to a lack of off-target infection. Next, to 275 assess the potential feasible library size, we mixed on-target RBD-displaying viruses 276 encoding GFP with off-target CD4bs-displaying viruses encoding mCherry. and used 277 them to infect CR3022 BCR-expressing Ramos cells ( Figure 5D). Keeping the total virus 278 amount constant, we were able to robustly detect on-target interactions with minimal off-279 target infection in mixtures as dilute as 1:1,000 on-target viruses. We observed similar 280 results when displaying SARS-CoV-2 S2P instead of RBD (Supplementary Figure 5). 281 These results gave us confidence in the feasibility of extracting meaningful signal from 282 interaction screens using lentiviral infection via the BCR.

Figure 5 | RAPTR enables profiling of B cell reactivity via infection of BCR knock-in cells A,
Overview of BCR-based targeting via the VSVGmut hybrid pseudotype in which a viral protein is coexpressed with VSVGmut. B, Targeting of Ramos cells expressing the SARS-CoV S protein specific CR3022 BCR via VSVGmut lentiviruses displaying either SARS-CoV-2 spike (2P) or surface-bound SARS-CoV-2 S protein RBD, or VRC01 BCR via env constructs representing multiple clades of HIV; representative data from 2 independent experiments. C, Infection of CR3022 BCR-expressing Ramos cells mixed into IgM-negative Ramos cells at target cell frequencies indicated in red, demonstrating selectivity in a mixed population of cells. D, Infection of CR3022 BCR-expressing Ramos cells with mixtures of SARS-CoV-2 RBD (on-target, expressing mCherry) and HIV env (off-target, expressing GFP) viruses; variant library size indicates the ratio of off-target to on-target virus present. Infection of VRC01-expressing Ramos cells with HIV env hybrid pseudotyped viruses (right) demonstrates that the viral particles remain functional. E, Enrichment of antigen barcodes following viral glycoprotein library infection of Ramos cells expressing BCRs for VRC01, mature CR3022, or the germline-reverted version CR3022 demonstrating selectivity even for antibody sequences before affinity maturation. Affinity ablated

Transduction (GFP) IgM (APC)
10 -1 10 -2 10 -3 10 -4 10 -5 10 -6  (Figure 5E) To fully realize the potential of RAPTR for antigen identification, we sought to apply 297 it to library vs library screening by using our 96-member pMHC viral library to pan a 298 previously reported library of >450,000 TCRs 67 . To simplify the first attempt, we pre-299 enriched for potentially reactive cells using tetramers for CMV, EBV, and Flu (CEF) 300 antigens presented by HLA-A2, resulting in a polyclonal pool of TCRs with greater 301 prevalence of these specificities, similar to the routine process of pre-expanding cells 302 ( Figure 6A). Following transduction and FACS to isolate transduced cells, we used bulk 303 sequencing to identify which antigens were enriched in aggregate. In line with tetramer 304 staining of the untransduced cells, we observed strong enrichment of Flu GL9, and more 305 modest enrichment of EBV GLC (Figure 6B, Supplementary Figure 6).   (Figures 6C and 6E). We grouped cells of common clonotype together and 312 analyzed pMHC barcode expression to determine enrichment relative to packaging library 313 frequency. The most prevalent TCR clone, GL9.1, demonstrated strong enrichment of 314 GL9 pMHC signal (Figure 6D). Upon literature search, we noted that GL9.1 represents a 315 well-characterized public clonotype known to recognize GL9 peptide presented by HLA-316

A)
The next most abundant clone, GLC.1, was identified in a previous screen of this 318 same TCR library by recombinant HLA-A2 GLC dextramer 67 . Our screen also identified 319 GLC as the target pMHC ( Figure 6D). Notably, this was the only clone previously 320 identified by GLC dextramer panning that was validated by monoclonal binding and 321 functional tests. Our approach did not identify any of the previously reported false 322 positives as hits, providing further evidence that RAPTR is an efficient means of 323 identifying T cell antigens that integrates both binding and signaling.  We demonstrated a system for efficient, antigen-specific infection via both the TCR and 332 the BCR that integrates both binding and target cell activation. We then exploited this mode of infection to match receptors with target antigens in complex mixtures and in a 334 library vs library format. 335 We demonstrated that the VSVGmut pseudotyping system is efficient, specific, 336 and uniquely modular by targeting a variety of cell surface proteins, including cytokine 337 receptors, costimulatory molecules, lineage markers, and both T and B cell receptors. We 338 report here as many different targeting approaches for VSVGmut as have been reported 339 for any other single pseudotyping system 27 , including the first true antigen-specific 340 infection of lymphocytes and the first combinatorial targeting approach. In addition, the 341 VSVGmut system produces viruses at higher average titers than other systems while 342 maintaining a high degree of specificity. Whereas most pseudotyping systems have been 343 limited to the use of small, stable, high-affinity targeting ligands (e.g. scFvs or DARPins), 344 VSVGmut is uniquely versatile in ligand usage due to the modular design it permits. We 345 report targeting even at micromolar affinities, whereas the efficiency of infection by 346 paramyxoviral pseudotypes was reported to dramatically decrease in the low nanomolar 347 range 71 . 348

Applications of RAPTR 349
We have demonstrated the utility of RAPTR for identifying antigens recognized by 350 TCRs and BCRs. For T cell reactivity, our approach could be directly applied to rapidly 351 deorphanize TCRs from existing single-cell studies, which routinely pair TCR sequences 352 with gene expression for cancer, autoimmunity, or infectious disease. Existing As with any technology, RAPTR has several limitations. Our proof of concept 392 studies were performed on ~100-antigen scale, and while our control experiments 393 indicate this could be readily increased to 1,000s, these scales will still require pre-394 selection of antigen targets for analysis. Future work will focus on further streamlining 395 library assembly and increasing transduction efficiency toward larger-scale assays. In 396 addition, the single-cell sequencing step must be performed in sufficient depth to facilitate 397 acceptable signal to noise determinations. While we chose to use a commercially 398 available platform to ensure broad applicability, recent and future advances in the scale 399 of single-cell analysis 75 will improve the utility of RAPTR regardless of platform. Like other 400 genetically encoded techniques, RAPTR also requires prior selection of MHC 401 haplotype(s) to generate libraries. Finally, the antigen identification studies we presented were on cell lines with receptors knocked in, rather than primary cells. While the 403 decreasing cost and turnaround time of gene synthesis will make such resources 404 increasingly available, future studies can apply RAPTR directly to primary cells. 405 Altogether, RAPTR is a versatile platform for high-throughput interaction screens 406 that uniquely incorporates diversity of both receptors and ligands in a single assay. The 407 resulting tools will enable detailed studies of antigen recognition for understanding and 408 engineering the adaptive immune response, as well as broader interactome studies. to make library packaging cell pools. To produce lentiviruses, library packaging cells were 517 transfected as described above, but using only psPAX2.1 and pMD2-VSVGmut. For 518 library creation, both transfer plasmids and the pMD2 targeting plasmid were omitted, as 519 they were replaced by the LeAPS packaging line. After 48 hours, virus was then collected 520 and concentrated as described above. The next-generation sequencing datasets generated during and/or analyzed during the 561 current study are available in the NCBI sequence read archive (accession numbers to be 562 assigned before publication). All data generated or analyzed during this study are 563 included in this published article, the sequence read archive, and its supplementary 564 information files. 565 566

Code Availability 567
A sample R workspace for extracting barcode counts based on CITEseq 68 will be posted 568 to Birnbaum lab code repository upon publication. 569 Kaposi's sarcoma-associated virus (HHV-8) 3