Protective antibodies against some pathogens require features not easily elicited through affinity maturation from the human antibody repertoire (Kepler and Wiehe, 2017). We wanted to add these features into the repertoire directly by modifying BCRs using genome-editing technologies. The existence of antibodies with protective paratopes encoded mostly within their HCs (Heydarchi et al., 2016; Lee et al., 2017; Sok et al., 2017; Sui et al., 2009) suggested that it might be possible to achieve this goal through replacement of the recombined HC variable region alone. In order for engineered HCs to then function as desired, they must pair with endogenous LCs and retain their ability to recognize antigen as chimeric cell surface-expressed BCRs (Feige et al., 2010).

We used HIV as a model because, while broadly neutralizing antibodies (bnAbs) against this virus are protective (Pegu et al., 2017) and their gene sequences have been well defined (McCoy and Burton, 2017), they remain exceedingly difficult to elicit by vaccination (Mascola and Haynes, 2013). Previous studies have suggested that the breadth and neutralization potency of a number of bnAbs targeting the HIV Envelope glycoprotein (Env) 'V2 apex’ region are largely encoded within unusually long HC complementarity-determining region 3 (CDRH3) loops, which form the majority of contacts with Env (Julien et al., 2013; Lee et al., 2017; McLellan et al., 2011; Pejchal et al., 2010). We found that the IgG HC from the V2 apex-targeting bnAb PG9 could pair and be secreted with a diversity of lambda (λ) and kappa (k) LCs (Figure 1—figure supplement 1) when co-transfected in HEK293 cells. These included a LC endogenous to a well characterized human B cell line in which we wanted to develop BCR engineering strategies, the Ramos (RA 1) Burkitt’s lymphoma (Klein et al., 1975). Size exclusion chromatography (SEC) profiles and SDS-PAGE gels of these secreted chimeric antibodies were comparable with the normal PG9 HC/LC pair (Figure 1—figure supplement 2). Chimeras were evaluated for their ability to neutralize HIV pseudovirus using the TZM-bl assay (Sarzotti-Kelsoe et al., 2014). Twelve HIV pseudoviruses representing the global diversity of HIV-1 strains (deCamp et al., 2014) were examined along with six viruses known to be highly sensitive to neutralization by PG9 (Andrabi et al., 2015). All PG9 chimeric antibodies neutralized one or more of the PG9-sensitive viruses, and most neutralized multiple viruses from different clades in the global panel (Figure 1). No chimeric antibody was as broadly neutralizing as the original PG9 HC/LC pair, indicating significant LC-dependent restriction to neutralization breadth for this HIV bnAb. Most chimeras had measurable binding affinity to 5 strains of recombinant soluble HIV envelope native trimers (SOSIPs) (Andrabi et al., 2015; Voss et al., 2017) by biolayer interferometry (BLI) (Frenzel and Willbold, 2014) (Figure 1—figure supplement 3). Autoreactivity was detected for about 60% of PG9 chimeras in the HEp-2 assay (Copple et al., 2012) as might be expected because of novel HC/LC interfaces in these antibodies (Figure 1—figure supplement 4). We opted to move forward with the development of engineering strategies using the PG9 HC paratope in Ramos B cells because, despite a loss of neutralization breadth with some LCs, the PG9 HC pairs well with diverse LCs (including the functional Ramos λLC). Further, these LC chimeras can be readily detected with a variety of available recombinant native trimer probes, giving us a simple and specific method for detecting successfully engineered B cells.

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It is possible to replace segments of genomic DNA in eukaryotic cells by introducing double strand DNA (dsDNA) breaks on either side of the segment in the presence of exogenous donor DNA that will be incorporated between these break sites by host cell DNA repair machinery. This replacement DNA must be flanked by regions of sequence homology (HR) to the genome upstream and downstream of the two break sites in order to be incorporated by homology directed repair (HDR) mechanisms (Doudna and Charpentier, 2014; Schwank et al., 2013). This presented a unique challenge for the development of donor DNA HRs that would be universally present on either side of the VDJ region in polyclonal human B cells. This is because each human B cell undergoes genomic rearrangements during its genesis to assemble the HC VDJ gene from; 1 of at least 55 functional V genes (along with its individual 5’ promoter); 1 of 23 functional D genes; and 1 of 6 functional J genes. Together, these gene segments span nearly one megabase (Mb) when in germline configuration and constitute the immunoglobulin heavy chain variable (IGHV) locus on chromosome 14 (at 14q32.33) (Giudicelli et al., 2005; Watson and Breden, 2012) (Figure 2A). To respond to this challenge, we developed a long-range HDR strategy that introduced dsDNA breaks after the most 5’ V-gene promoter (V7-81), and after the most distal J gene (J6), because HRs 5’ and 3’ to these sites respectively are retained in all B cells. The distance between these cut sites will vary depending on which V and J genes were assembled in a given B cell. Thus, regardless of which genes were previously assembled, our editing strategy introduces the new VDJ gene in a way that allows transcription using a naturally regulated V-gene promoter from its native locus where it would be subject to hypermutation by AID. When paired with an endogenous cell LC, a chimeric immunoglobulin (Ig) will be secreted as the isotype determined by the genomic configuration of the HC constant region in the engineered cell.

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B cell VDJ editing was first performed in the Ramos (RA 1) B cell lymphoma line. This human monoclonal line expresses an Ig HC that uses the IGHV4-34 (V), IGHD3-10 (D) and IGHJ6 (J) genes as IgM (Borchert et al., 2010). V4-34 lies halfway through the IGHV locus placing the 5’ most V-gene promoter (V7-81) about 0.5 Mb upstream (Figure 2A). In addition to our universal B cell editing strategy, which grafts the PG9 VDJ gene between the V7-81 promoter and J6 splice site (Figure 2B), we developed an engineering strategy specific for this line that introduced a dsDNA cut 3’ of the V4-34 promoter (instead of the V7-81), and which used donor DNA with a V4-34 promoter sequence 5’ HR (Figure 2C). This strategy replaces only the 400 bp Ramos VDJ rather than a 0.5 Mb region using the ‘universal’ BCR editing strategy. Cas9 cut sites were identified in the desired regions of the human HC variable locus (red scissors in Figure 2A, Figure 2—figure supplement 1). Guide RNA sequences synthesized as DNA oligos were cloned into the pX330-SpCas9 and guide RNA expression plasmid using previously published methods (Ran et al., 2013b). Cutting activity was assessed for several different guide RNAs targeting each of the three sites using the pCAG-eGxxFP recombination assay in 293 cells (Mashiko et al., 2013). Once the highest efficiency cutters were detected using this assay (Figure 2—figure supplement 1), corresponding mutations in the PAM sites in donor DNA plasmids were mutated to prevent Cas9 cutting of the donor DNA inside transfected cells (Figure 2—figure supplement 2). We introduced either the ‘V4-34/Ramos-specific’ or the ‘V7-81/universal B cell’ VDJ editing reagents into cells as two plasmids encoding 5’ and 3’ dsDNA cutting by Cas9, and one plasmid encoding PG9 VDJ donor DNA (Figure 2—figure supplement 2) using nucleofection. Cells were cultured for 3 days to allow for PG9 VDJ gene replacement and HC expression to occur.

To distinguish between the chimeric PG9 HC BCR and the unmodified BCR endogenous to Ramos cells, we used fluorescently labeled soluble HIV envelope trimer (SOSIP) from an isolate of HIV shown to be neutralized by an IgG chimera composed of PG9 HC and Ramos λLC (Figure 1), clade AE isolate C108.c03 (Andrabi et al., 2015; Voss et al., 2017). Cells positive for PG9 HC/Ramos LC chimeric IgM were detected by fluorescence activated cell sorting (FACS) (Figure 2D). Cells engineered by the V434 or V781 strategies reproducibly converted an average of 1.75%(SD = 0.20) or 0.21%(SD = 0.03) of transfected cells into Env binding cells, respectively (Figure 2E). It was encouraging that the universal editing strategy that removed 0.5 Mb of the IGHV locus was only about 8 times less efficient than the Ramos-specific strategy that replaces just 400 bp. It remains to be determined if this success is particular to the Ig locus in Ramos cells or is a general feature of B cells, which naturally undergo such long distance recombinations during B cell ontogeny (Ebert et al., 2015; Jung et al., 2006; Montefiori et al., 2016). A similar strategy was reported to remove up to 5 Mb of genomic DNA from chromosome 11 in mouse embryonic stem cells suggesting the method may work universally (Kato et al., 2017). C108 SOSIP was used to sort successfully engineered HIV-specific cells to produce enriched subpopulations for further experiments. Genomic DNA extracted from these PG9-enriched cells was PCR amplified using primers that annealed upstream and downstream of the expected insertion sites and outside of the donor DNA HRs ('out/out PCR', Figure 2B, 2F). Sanger sequencing of these products confirmed that the new PG9 gene was grafted as expected between Cas9 cut sites within the IGHV locus by HDR (Figure 2—figure supplements 3–5).

Amplification-free whole genome sequencing of C108 SOSIP-selected cells (engineered with either the V434 or V781 strategy) was performed using fragmented gDNA from these lines using the Illumina HiSeq X. Reads were mapped to the human reference genome hg19 (International Human Genome Sequencing Consortium, 2004) showing approximately 30x coverage depth for diploid regions of the genome (Figure 2—figure supplement 6). Coverage depth was consistent with removal of the V781-J6 region in the expressed allele in C108 SOSIP-selected cells engineered with the universal strategy, but not from the excluded allele which is not expressed due to a chromosomal translocation of the IGHV region to chr8 in this Burkitt's lymphoma line (Klein et al., 1975). Coverage depth analysis showed a deletion between the V3-11 and V3-7 genes in the excluded allele (relative to the reference genome), and a D-J recombination event in this allele between D3-9 and the J6 gene that would have occurred during the maturation of this B cell in vivo. The high read coverage depth for the 5’ and 3’ HRs in engineered cells (especially using the V7-81 strategy), suggests the integration of multiple donor DNAs by NHEJ mechanisms (Figure 2—figure supplement 6). The presence of donor DNA backbone sequences in this assembly on the outside of HR mapped reads (Figure 2—figure supplements 7–8) confirms that integration did occur in both V781 and V434-engineered, C108 SOSIP-selected cells by NHEJ, in addition to the intended HR driven graft of PG9 VDJ into the expected sites. It is normal for DNA introduced as plasmid to be incorporated into the mammalian genome at the site of dsDNA breaks non-specifically by NHEJ (Vasquez et al., 2001). The donor DNA format should be adapted to skew repair towards HDR mechanisms if incorporation by NHEJ is to be reduced or eliminated in future experiments. Our design should not allow for expression of PG9 HC when the donor is incorporated by most off-target repair mechanisms because the PG9 VDJ gene promoter must be in proximity to the downstream enhancer for transcription, and because the gene must be transcribed with the downstream constant gene and spliced in order to make a functional heavy chain protein.

Some predicted, off-target editing events were detected by PCR (Figure 2—figure supplement 9) in V781 PG9-engineered unselected or C108 SOSIP-selected cells. Deletions between Cas9 cut sites as have been previously reported to occur (Kato et al., 2017) were detected in unselected cells, but not in cells enriched for C108 SOSIP binding. One SOSIP selectable off-target donor DNA incorporation event was detected. This event involved HDR within the 3’ HR of the donor DNA, allowing for promoter activity (encoded within the 5’HR of the donor) and transcription with downstream constant regions for expression of functional PG9 HC, but with no accompanying 5’ HDR from within the same donor DNA plasmid, indicated by the PCR product shown in Figure 2—figure supplement 9D. Integration of donor DNA completely by NHEJ mechanisms was also detected and appeared in both unselected and C108-selected cell lines (Figure 2—figure supplement 9F). While evidence for incorporation by NHEJ exists at Cas9 cut sites from these data, it remains to be determined if integration events also occurred elsewhere in the genome.

We then assessed the ability of engineered B cells to undergo two key genome alterations that occur during affinity maturation; class switching and somatic hypermutation. Both of these processes are mediated by AID, which is active in Ramos B cells and is regulated to direct the bulk of its activity within the Ig loci (Kenter et al., 2016). It was previously shown that in vitro class switching occurs only in a specific Ramos sub-clone, 2G6 (Ford et al., 1998). Thus, we repeated the engineering and selected PG9 HC expressing cells in the 2G6 line. RT-PCR amplification using PG9 forward and IgM or IgG reverse primers generated amplicons which were sequenced to show that the engineered locus successfully transcribed PG9 and spliced it in the correct reading frame to either the native Ramos µ constant gene (PG9-IgM), or after culture with CD40 ligand-expressing feeder cells, IL-2 and IL-4, the native Ramos Y constant gene (PG9-IgG) (Figure 2G, Figure 2—figure supplement 10). Thus, the engineered locus retained the ability to undergo isotype switching.

While isotype switching is not inducible in Ramos RA1, random somatic hypermutation does occur due to constitutive activity of AID (Baughn et al., 2011; Sale and Neuberger, 1998). We assessed the ability of edited V781-engineered Ramos RA1 B cells to undergo somatic hypermutation to generate higher affinity variants of the PG9-Ramos chimeric antibody in vitro by repeatedly selecting B cell populations with superior binding to Env using flow cytometry. We chose to use Env SOSIP trimers derived from strains MGRM8 (clade AG) and WITO.4130 (clade B) (Andrabi et al., 2015; Voss et al., 2017) as sorting probes because these proteins showed relatively weak binding to engineered cells (Figure 3—figure supplement 1A), and therefore gave the greatest scope for improvement (Figure 3A). Sorts were designed using an anti-human lambda light chain probe (Figure 3—figure supplement 2) to eliminate the selection of cells with brighter antigen staining that could result from an upregulation of BCR expression on the cell surface. Three rounds of selection and expansion in culture improved the binding of engineered cell lines to SOSIP probes in FACS experiments (Figure 3—figure supplement 1B). mRNA was purified from cell cultures at the time points indicated in Figure 3A. Ig variable genes were then amplified from cDNA using gene specific primers as previously described (Briney et al., 2016). Libraries were sequenced using the Illumina MiSeq and quality trimmed reads were aligned and filtered to remove all sequences corresponding to the Ramos VDJ or a non-functional lambda chain transcript, confirmed in this study by IMGT analysis (Ye et al., 2013) to derive from a VJ recombination event between IGLV2-23 and IGLJ3 on the excluded lambda allele in this cell line. Sequences from different samples were compared to detect the enrichment of coding changes during subsequent rounds of selection that could account for improved binding of the cell lines to HIV Env by FACS. A dominant change within the functional Ramos λLC was increasingly enriched in both MGRM8 and WITO SOSIP-selected lines at an AID hotspot, an S97N substitution within the CDRL3. This mutation predicts a shift in a potential N-linked glycosylation site (PNGS) from N95 to 97. Coding changes resulting in the deletion of this glycan were also observed to a lesser degree (Figure 3B). Because no interesting residues in the HC of these lines were likewise selected, we investigated whether the LC changes had a functional effect by expressing the PG9-RamosλLC chimeras as IgG with mutations to either remove or shift the PNGS to 97 as selected (LC S97G or S97N). Antibodies with either of these mutations generally improved affinity for HIV SOSIPs from different clades (Figure 3C). Furthermore, these mutations resulted in more potent neutralization of a number of HIV strains, including a virus from the panel designed to represent global HIV diversity, not neutralized by the original chimera (Figure 3D). These mutants remained non-autoreactive in the HeP-2 assay (Figure 1—figure supplement 4) and did not strongly alter expression based on SEC profiles (Figure 1—figure supplement 2). PG9 crystal structures and homology modeling suggest that, in this chimera, steric clashes involving the Ramos CDRL3 N-linked glycan at position 95 may impede access of the PG9 CDRH3 to its bnAb epitope (Figure 3E). This result also suggests that breadth of neutralization by PG9 chimeras may be relatively easy to recover through affinity maturation by a number of possible pathways requiring few mutations to adapt the new light chain.

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While interesting coding changes were not significantly enriched in the new PG9 VDJ gene during consecutive rounds of SOSIP selection, we wanted to confirm whether AID was actively mutating this gene over time. The replacement and selection of a defined starting VDJ sequence greatly simplified assessment of mutations introduced at this locus. To eliminate confounding changes in the PG9 VDJ sequence accumulated during RT-PCR amplification, we incorporated unique nucleotide sequence molecular identifiers (UMIs) into the 5’ end of each Ig HC mRNA molecule using a barcoded 5’ template switch adapter during first strand synthesis by 5’ RACE with Ig constant region primers as has been recently described (Turchaninova et al., 2016). Illumina adapters were added to PCR amplified libraries for MiSeq sequencing. Consensus sequences derived from reads with identical UMIs (molecular identifier groups, MIGs), were constructed using the previously referenced method. We analyzed only MIGs derived from >29 reads and eliminated unique sequences from the data set to reduce or eliminate chimeric PCR product and any polymerase-introduced mutations from the analysis. We compared data sets coming from two cell lines that had spent the longest time in culture since the original transfection with VDJ gene editing reagents (about 2.5 months). One of these underwent three consecutive selections steps using MGRM8 SOSIP (M3), and one was simply passaged after the initial C108 enrichment and experienced no further selection pressure for SOSIP binding (PU), (Figure 3A). Clear differences from the starting PG9 VDJ gene sequences were observed in both data sets and the positions of many of these mutations appear to fall within regions known to be canonical AID hotspots (WRCY) (Smith et al., 1996) (Figure 3F). This suggests that genes being introduced into the locus undergo normal somatic hypermutation which could be manipulated through the use of codon optimization to encourage or discourage mutations at certain positions by modifying AID hotspot motifs in donor DNA-introduced antibody genes.

We then wanted to test the universal editing strategy in human primary polyclonal B cells that have undergone a diversity of VDJ recombination events, use a variety of different LCs, and which are readily available in the periphery. We changed the system from one which uses the V7-81 promoter, to one which uses V3-74, (the V gene immediately downstream of V7-81 in the IGHV locus, Figure 2A, Figure 4—figure supplement 1). In engineered Ramos cells, PG9 expressed using the V3-74 promoter stained more brightly with the HIV envelope probe than did those using V7-81, presumably due to differing promoter strengths. Switching to V3-74 would thus allow for maximal PG9 staining in primary cells which may express lower levels of BCR than the Ramos lymphoma cell line. In addition, engineering efficiency was routinely higher (0.35% of the live cell gate) compared with V7-81 (Figure 4—figure supplement 1). PBMCs from different donors were purified by density gradient centrifugation. CD19+ B cells were positively selected by magnetic-activated cell sorting (MACS) and placed into culture with human CD40L and IL-4 to activate and induce cell proliferation. Because cell cycling and/or persistence in the S/G2 phases promote HDR (Hung et al., 2018), we stained cells with CFSE to assess the dynamics of B cell division in order to correctly time the introduction of our engineering reagents. Cells were mostly static for the first three days in culture but went through a burst of division by day five under these conditions (Figure 4A). We therefore chose to engineer cells on day 4 of culture. We first tested AMAXA nucleofection of a 7.7 Kb GFP plasmid (HR210-PA) into cells at different concentrations (Figure 4B). We found that 2 or 3μgs of plasmid per million cells resulted in acceptable levels of transfection allowing us to continue forward testing our engineering reagents in plasmid format. We tested nucleofection of our three-plasmid system at different DNA concentrations and used a ‘PG9 chimera’ gating strategy (below) to detect successful engineering and expression of the new BCR in cells by FACS at 2, 3 and 6 days post engineering (Figure 4C). 2 or 3 μg each of the 5’ Cas9, the 3’ Cas9, and the V374 donor plasmids/million cells yielded engineering efficiencies approaching 0.1% of the live single cell gate. Because 9 μg of total DNA was significantly toxic to cells reducing their numbers dramatically, we chose to test engineering of B cells from three different donors using 2 μg of each plasmid for a total of 6 μg/million cells (Figure 4D). To detect cells expressing PG9 HC as chimeric BCRs with native cell LCs 6 days after engineering, we used ZM233 HIV envelope (in SOSIP format) as a FACS probe, because this strain of virus was observed to be the most broadly neutralized virus in our panel by PG9 chimeras regardless of the LC pair (Figure 1). We stained cells using a biotinylated version of this probe bound to either streptavidin-BB515 or streptavidin-APC and selected BB515/APC positive cells to eliminate non-specific or fluorophore-specific binders. We also stained with a version of ZM233 SOSIP (bound to streptavidin-BV421) with a deletion of the N160 glycan, which is a critical component of the PG9 HC binding epitope, in order to gate-out cells binding to other epitopes on the SOSIP. All three engineered donor samples had at least 10-fold more cells in the APC+/BV421-/BB515+ ‘PG9 chimeric BCR gate’ than did non-engineered controls. After a further 7 days in CD40L/IL-4 culture, cells were harvested, and mRNA was purified (Figure 4E). RT-PCR using PG9-specific primers amplified PG9 (confirmed by Sanger sequencing) both as IgM and IgG from engineered cell mRNA (+) but not from nonengineered controls (-) (Figure 4F). To quantify PG9 transcripts, RACE-PCR was also performed in order to amplify all transcribed HCs from engineered cell samples (Turchaninova et al., 2016). NGS sequencing of these amplicons showed PG9 mRNA-read frequencies similar to the PG9 chimeric BCR-gated cell frequencies observed by FACS seven days earlier (for two of three donors), suggesting survival and similar rates of division for engineered and non-engineered cells in culture. No PG9 mRNA could be detected in non-engineered negative controls. Moreover, PG9 isotypes observed in NGS datasets from engineered cells included IgM, IgD, IgG1 and IgG4 (Figure 4D). 3 PG9 MIGs (derived from at least 17 reads) in the donor 1 and 3 error compensated datasets had nucleotide mutations. One of these was a substitution of a C for a T at a predicted AID hot spot motif (WRCY), suggesting the new genes could be undergoing somatic hypermutation as might be expected for primary B cells under these culture conditions (Johnson et al., 2018; Moens and Tangye, 2014). Despite effective compensation for errors introduced during library preparation by the repertoire analysis methods applied here, there is still a small possibility that these mutations could have arisen during cDNA synthesis, or very early on in PCR amplification of these genes (Turchaninova et al., 2016). The AID dependence of observed mutations in engineered genes could be confirmed by comparing these with sequences from engineered cells cotransfected with a guide RNA designed to knock out the AID gene.

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This report demonstrates a universal B cell genome editing strategy that introduces novel paratopes into the human antibody repertoire by VDJ replacement in B cells using homology directed repair mechanisms. Using endogenous LCs, engineered cells express immunoglobulins with a defined specificity, which would be optimally poised to signal antigen-stimulated expansion and affinity maturation in vivo as B cell receptors. The ability to introduce novel paratopes into the human antibody repertoire in this way, could help to surmount difficulties eliciting protective antibody responses against evolved pathogens if it could be done safely and efficiently enough in primary B cells to reproducibly expand protective, self-tolerant antibody responses upon autologous re-engraftment through vaccination. Other reports successfully employing HDR to engineer primary human B cell genomes using ribonucleoproteins (RNPs) and ssDNA donor DNA (nucleofected or AAV6 delivered), suggest this should be possible (Hung et al., 2018) (Johnson et al., 2018). Further exploration of such a chimeric antigen receptor-B cell (CAR-B) vaccine in animal models should be done in order to test the feasibility of developing this technology for prophylactic or therapeutic use in humans, and as a tool to enhance infectious disease experimental model systems in general.

Next generation sequencing data from RT-PCR amplicons have been deposited at Dryad: DOI: https://doi.org/10.5061/dryad.45j0r70. Amplification free whole genome sequencing reads mapped to the human reference genome have been deposited to NCBI with BioSample accession numbers SAMN09404498 and SAMN09404497

1. 1. James E Voss
   2. Alicia Gonzalez-Martin
   3. Raiees Andrabi
   4. Roberta P Fuller
   5. Ben Murrell
   6. Laura E McCoy
   7. Katelyn Porter
   8. Deli Huang
   9. Wenjuan Li
   10. Devin Sok
   11. Khoa Le
   12. Bryan Briney
   13. Morgan Chateau
   14. Geoffrey Rogers
   15. Lars Hangartner
   16. Ann J Feeney
   17. David Nemazee
   18. Paula Cannon
   19. Dennis R Burton

   (2018) Dryad

   Data from: Reprogramming the antigen specificity of B cells using genome-editing technologies.

   https://doi.org/10.5061/dryad.45j0r70
2. 1. James E Voss
   2. Alicia Gonzalez-Martin
   3. Raiees Andrabi
   4. Roberta P Fuller
   5. Ben Murrell
   6. Laura E McCoy
   7. Katelyn Porter
   8. Deli Huang

   (2018) NCBI Sequence Read Archive

   ID SAMN09404498. PG9HC(V434)Ramos-WGS.

   https://www.ncbi.nlm.nih.gov/sra?LinkName=biosample_sra&from_uid=9404498
3. 1. James E Voss
   2. Alicia Gonzalez-Martin
   3. Raiees Andrabi
   4. Roberta P Fuller
   5. Ben Murrell
   6. Laura E McCoy
   7. Katelyn Porter
   8. Deli Huang
   9. Wenjuan Li
   10. Devin Sok
   11. Khoa Le
   12. Bryan Briney
   13. Morgan Chateau

   (2018) NCBI Sequence Read Archive

   ID SAMN09404497. PG9HC(V781)Ramos-WGS.

   https://www.ncbi.nlm.nih.gov/sra?LinkName=biosample_sra&from_uid=9404497

1. 1. Andrabi R
   2. Voss JE
   3. Liang CH
   4. Briney B
   5. McCoy LE
   6. Wu CY
   7. Wong CH
   8. Poignard P
   9. Burton DR

   (2015) Identification of common features in prototype broadly neutralizing antibodies to HIV envelope V2 apex to facilitate vaccine design

   Immunity 43:959–973.

   https://doi.org/10.1016/j.immuni.2015.10.014

   • PubMed
   • Google Scholar
2. 1. Baughn LB
   2. Kalis SL
   3. MacCarthy T
   4. Wei L
   5. Fan M
   6. Bergman A
   7. Scharff MD

   (2011) Recombinase-mediated cassette exchange as a novel method to study somatic hypermutation in ramos cells

   mBio 2:e00186.

   https://doi.org/10.1128/mBio.00186-11

   • PubMed
   • Google Scholar
3. 1. Borchert GM
   2. Holton NW
   3. Edwards KA
   4. Vogel LA
   5. Larson ED

   (2010) Histone H2A and H2B are monoubiquitinated at AID-targeted loci

   PLOS ONE 5:e11641.

   https://doi.org/10.1371/journal.pone.0011641

   • PubMed
   • Google Scholar
4. 1. Briney B
   2. Sok D
   3. Jardine JG
   4. Kulp DW
   5. Skog P
   6. Menis S
   7. Jacak R
   8. Kalyuzhniy O
   9. de Val N
   10. Sesterhenn F
   11. Le KM
   12. Ramos A
   13. Jones M
   14. Saye-Francisco KL
   15. Blane TR
   16. Spencer S
   17. Georgeson E
   18. Hu X
   19. Ozorowski G
   20. Adachi Y
   21. Kubitz M
   22. Sarkar A
   23. Wilson IA
   24. Ward AB
   25. Nemazee D
   26. Burton DR
   27. Schief WR

   (2016) Tailored immunogens direct affinity maturation toward HIV neutralizing antibodies

   Cell 166:1459–1470.

   https://doi.org/10.1016/j.cell.2016.08.005

   • PubMed
   • Google Scholar
5. 1. Copple SS
   2. Giles SR
   3. Jaskowski TD
   4. Gardiner AE
   5. Wilson AM
   6. Hill HR

   (2012) Screening for IgG antinuclear autoantibodies by HEp-2 indirect fluorescent antibody assays and the need for standardization

   American Journal of Clinical Pathology 137:825–830.

   https://doi.org/10.1309/AJCPICNFG7UCES1S

   • PubMed
   • Google Scholar
6. 1. deCamp A
   2. Hraber P
   3. Bailer RT
   4. Seaman MS
   5. Ochsenbauer C
   6. Kappes J
   7. Gottardo R
   8. Edlefsen P
   9. Self S
   10. Tang H
   11. Greene K
   12. Gao H
   13. Daniell X
   14. Sarzotti-Kelsoe M
   15. Gorny MK
   16. Zolla-Pazner S
   17. LaBranche CC
   18. Mascola JR
   19. Korber BT
   20. Montefiori DC

   (2014) Global panel of HIV-1 env reference strains for standardized assessments of vaccine-elicited neutralizing antibodies

   Journal of Virology 88:2489–2507.

   https://doi.org/10.1128/JVI.02853-13

   • PubMed
   • Google Scholar
7. 1. Doudna JA
   2. Charpentier E

   (2014) Genome editing. the new frontier of genome engineering with CRISPR-Cas9

   Science 346:1258096.

   https://doi.org/10.1126/science.1258096

   • PubMed
   • Google Scholar
8. 1. Ebert A
   2. Hill L
   3. Busslinger M

   (2015) Spatial regulation of V-(D)J recombination at antigen receptor loci

   Advances in Immunology 128:93–121.

   https://doi.org/10.1016/bs.ai.2015.07.006

   • PubMed
   • Google Scholar
9. 1. Feige MJ
   2. Hendershot LM
   3. Buchner J

   (2010) How antibodies fold

   Trends in Biochemical Sciences 35:189–198.

   https://doi.org/10.1016/j.tibs.2009.11.005

   • PubMed
   • Google Scholar
10. 1. Ford GS
    2. Yin CH
    3. Barnhart B
    4. Sztam K
    5. Covey LR

    (1998)

    CD40 ligand exerts differential effects on the expression of I gamma transcripts in subclones of an IgM+ human B cell lymphoma line

    Journal of Immunology 160:595–605.

    • Google Scholar
11. 1. Frenzel D
    2. Willbold D

    (2014) Kinetic titration series with biolayer interferometry

    PLOS ONE 9:e106882.

    https://doi.org/10.1371/journal.pone.0106882

    • PubMed
    • Google Scholar
12. 1. Giudicelli V
    2. Chaume D
    3. Lefranc MP

    (2005) IMGT/GENE-DB: a comprehensive database for human and mouse immunoglobulin and T cell receptor genes

    Nucleic Acids Research 33:D256–D261.

    https://doi.org/10.1093/nar/gki010

    • PubMed
    • Google Scholar
13. 1. Heydarchi B
    2. Quiroz NAS
    3. Purcell DFJ

    (2016) Broad neutralizing antibodies to HIV env and other complex viral antigens from vaccinated cows

    Journal of Vaccines & Vaccination 07:347.

    https://doi.org/10.4172/2157-7560.1000347

    • Google Scholar
14. 1. Hung KL
    2. Meitlis I
    3. Hale M
    4. Chen CY
    5. Singh S
    6. Jackson SW
    7. Miao CH
    8. Khan IF
    9. Rawlings DJ
    10. James RG

    (2018) Engineering Protein-Secreting plasma cells by Homology-Directed repair in primary human B cells

    Molecular Therapy 26:456–467.

    https://doi.org/10.1016/j.ymthe.2017.11.012

    • PubMed
    • Google Scholar
15. 1. International Human Genome Sequencing Consortium

    (2004) Finishing the euchromatic sequence of the human genome

    Nature 431:931–945.

    https://doi.org/10.1038/nature03001

    • PubMed
    • Google Scholar
16. 1. Johnson MJ
    2. Laoharawee K
    3. Lahr WS
    4. Webber BR
    5. Moriarity BS

    (2018) Engineering of primary human B cells with CRISPR/Cas9 targeted nuclease

    Scientific Reports 8:12144.

    https://doi.org/10.1038/s41598-018-30358-0

    • PubMed
    • Google Scholar
17. 1. Julien JP
    2. Lee JH
    3. Cupo A
    4. Murin CD
    5. Derking R
    6. Hoffenberg S
    7. Caulfield MJ
    8. King CR
    9. Marozsan AJ
    10. Klasse PJ
    11. Sanders RW
    12. Moore JP
    13. Wilson IA
    14. Ward AB

    (2013) Asymmetric recognition of the HIV-1 trimer by broadly neutralizing antibody PG9

    PNAS 110:4351–4356.

    https://doi.org/10.1073/pnas.1217537110

    • PubMed
    • Google Scholar
18. 1. Jung D
    2. Giallourakis C
    3. Mostoslavsky R
    4. Alt FW

    (2006) Mechanism and control of V(D)J recombination at the immunoglobulin heavy chain locus

    Annual Review of Immunology 24:541–570.

    https://doi.org/10.1146/annurev.immunol.23.021704.115830

    • PubMed
    • Google Scholar
19. 1. Kato T
    2. Hara S
    3. Goto Y
    4. Ogawa Y
    5. Okayasu H
    6. Kubota S
    7. Tamano M
    8. Terao M
    9. Takada S

    (2017) Creation of mutant mice with megabase-sized deletions containing custom-designed breakpoints by means of the CRISPR/Cas9 system

    Scientific Reports 7:59.

    https://doi.org/10.1038/s41598-017-00140-9

    • PubMed
    • Google Scholar
20. 1. Kenter AL
    2. Kumar S
    3. Wuerffel R
    4. Grigera F

    (2016) AID hits the jackpot when missing the target

    Current Opinion in Immunology 39:96–102.

    https://doi.org/10.1016/j.coi.2016.01.008

    • PubMed
    • Google Scholar
21. 1. Kepler TB
    2. Wiehe K

    (2017) Genetic and structural analyses of affinity maturation in the humoral response to HIV-1

    Immunological Reviews 275:129–144.

    https://doi.org/10.1111/imr.12513

    • PubMed
    • Google Scholar
22. 1. Klein G
    2. Giovanella B
    3. Westman A
    4. Stehlin JS
    5. Mumford D

    (1975) An EBV-genome-negative cell line established from an american burkitt lymphoma; receptor characteristics. EBV infectibility and permanent conversion into EBV-positive sublines by in vitro infection

    Intervirology 5:319–334.

    https://doi.org/10.1159/000149930

    • PubMed
    • Google Scholar
23. 1. Lee JH
    2. Andrabi R
    3. Su CY
    4. Yasmeen A
    5. Julien JP
    6. Kong L
    7. Wu NC
    8. McBride R
    9. Sok D
    10. Pauthner M
    11. Cottrell CA
    12. Nieusma T
    13. Blattner C
    14. Paulson JC
    15. Klasse PJ
    16. Wilson IA
    17. Burton DR
    18. Ward AB

    (2017) A broadly neutralizing antibody targets the dynamic HIV envelope trimer apex via a long, rigidified, and anionic β-Hairpin structure

    Immunity 46:690–702.

    https://doi.org/10.1016/j.immuni.2017.03.017

    • PubMed
    • Google Scholar
24. 1. Lefranc MP
    2. Giudicelli V
    3. Duroux P
    4. Jabado-Michaloud J
    5. Folch G
    6. Aouinti S
    7. Carillon E
    8. Duvergey H
    9. Houles A
    10. Paysan-Lafosse T
    11. Hadi-Saljoqi S
    12. Sasorith S
    13. Lefranc G
    14. Kossida S

    (2015) IMGT, the international ImMunoGeneTics information system 25 years on

    Nucleic Acids Research 43:D413–D422.

    https://doi.org/10.1093/nar/gku1056

    • PubMed
    • Google Scholar
25. 1. Mascola JR
    2. Haynes BF

    (2013) HIV-1 neutralizing antibodies: understanding nature's pathways

    Immunological Reviews 254:225–244.

    https://doi.org/10.1111/imr.12075

    • PubMed
    • Google Scholar
26. 1. Masella AP
    2. Bartram AK
    3. Truszkowski JM
    4. Brown DG
    5. Neufeld JD

    (2012) PANDAseq: paired-end assembler for illumina sequences

    BMC Bioinformatics 13:31.

    https://doi.org/10.1186/1471-2105-13-31

    • PubMed
    • Google Scholar
27. 1. Mashiko D
    2. Fujihara Y
    3. Satouh Y
    4. Miyata H
    5. Isotani A
    6. Ikawa M

    (2013) Generation of mutant mice by pronuclear injection of circular plasmid expressing Cas9 and single guided RNA

    Scientific Reports 3:3355.

    https://doi.org/10.1038/srep03355

    • PubMed
    • Google Scholar
28. 1. McCoy LE
    2. Burton DR

    (2017) Identification and specificity of broadly neutralizing antibodies against HIV

    Immunological Reviews 275:11–20.

    https://doi.org/10.1111/imr.12484

    • PubMed
    • Google Scholar
29. 1. McLellan JS
    2. Pancera M
    3. Carrico C
    4. Gorman J
    5. Julien JP
    6. Khayat R
    7. Louder R
    8. Pejchal R
    9. Sastry M
    10. Dai K
    11. O'Dell S
    12. Patel N
    13. Shahzad-ul-Hussan S
    14. Yang Y
    15. Zhang B
    16. Zhou T
    17. Zhu J
    18. Boyington JC
    19. Chuang GY
    20. Diwanji D
    21. Georgiev I
    22. Kwon YD
    23. Lee D
    24. Louder MK
    25. Moquin S
    26. Schmidt SD
    27. Yang ZY
    28. Bonsignori M
    29. Crump JA
    30. Kapiga SH
    31. Sam NE
    32. Haynes BF
    33. Burton DR
    34. Koff WC
    35. Walker LM
    36. Phogat S
    37. Wyatt R
    38. Orwenyo J
    39. Wang LX
    40. Arthos J
    41. Bewley CA
    42. Mascola JR
    43. Nabel GJ
    44. Schief WR
    45. Ward AB
    46. Wilson IA
    47. Kwong PD

    (2011) Structure of HIV-1 gp120 V1/V2 domain with broadly neutralizing antibody PG9

    Nature 480:336–343.

    https://doi.org/10.1038/nature10696

    • PubMed
    • Google Scholar
30. 1. Moens L
    2. Tangye SG

    (2014) Cytokine-Mediated regulation of plasma cell generation: il-21 takes center stage

    Frontiers in Immunology 5:65.

    https://doi.org/10.3389/fimmu.2014.00065

    • PubMed
    • Google Scholar
31. 1. Montefiori L
    2. Wuerffel R
    3. Roqueiro D
    4. Lajoie B
    5. Guo C
    6. Gerasimova T
    7. De S
    8. Wood W
    9. Becker KG
    10. Dekker J
    11. Liang J
    12. Sen R
    13. Kenter AL

    (2016) Extremely Long-Range chromatin loops link topological domains to facilitate a diverse antibody repertoire

    Cell Reports 14:896–906.

    https://doi.org/10.1016/j.celrep.2015.12.083

    • PubMed
    • Google Scholar
32. 1. Pegu A
    2. Hessell AJ
    3. Mascola JR
    4. Haigwood NL

    (2017) Use of broadly neutralizing antibodies for HIV-1 prevention

    Immunological Reviews 275:296–312.

    https://doi.org/10.1111/imr.12511

    • PubMed
    • Google Scholar
33. 1. Pejchal R
    2. Walker LM
    3. Stanfield RL
    4. Phogat SK
    5. Koff WC
    6. Poignard P
    7. Burton DR
    8. Wilson IA

    (2010) Structure and function of broadly reactive antibody PG16 reveal an H3 subdomain that mediates potent neutralization of HIV-1

    PNAS 107:11483–11488.

    https://doi.org/10.1073/pnas.1004600107

    • PubMed
    • Google Scholar
34. 1. Raczy C
    2. Petrovski R
    3. Saunders CT
    4. Chorny I
    5. Kruglyak S
    6. Margulies EH
    7. Chuang HY
    8. Källberg M
    9. Kumar SA
    10. Liao A
    11. Little KM
    12. Strömberg MP
    13. Tanner SW

    (2013) Isaac: ultra-fast whole-genome secondary analysis on illumina sequencing platforms

    Bioinformatics 29:2041–2043.

    https://doi.org/10.1093/bioinformatics/btt314

    • PubMed
    • Google Scholar
35. 1. Ran FA
    2. Hsu PD
    3. Wright J
    4. Agarwala V
    5. Scott DA
    6. Zhang F

    (2013a) Genome engineering using the CRISPR-Cas9 system

    Nature Protocols 8:2281–2308.

    https://doi.org/10.1038/nprot.2013.143

    • PubMed
    • Google Scholar
36. 1. Ran FA
    2. Hsu PD
    3. Wright J
    4. Agarwala V
    5. Scott DA
    6. Zhang F

    (2013b) Genome engineering using the CRISPR-Cas9 system

    Nature Protocols 8:2281–2308.

    https://doi.org/10.1038/nprot.2013.143

    • PubMed
    • Google Scholar
37. 1. Sale JE
    2. Neuberger MS

    (1998) TdT-accessible breaks are scattered over the immunoglobulin V domain in a constitutively hypermutating B cell line

    Immunity 9:859–869.

    https://doi.org/10.1016/S1074-7613(00)80651-2

    • PubMed
    • Google Scholar
38. 1. Sarzotti-Kelsoe M
    2. Bailer RT
    3. Turk E
    4. Lin CL
    5. Bilska M
    6. Greene KM
    7. Gao H
    8. Todd CA
    9. Ozaki DA
    10. Seaman MS
    11. Mascola JR
    12. Montefiori DC

    (2014) Optimization and validation of the TZM-bl assay for standardized assessments of neutralizing antibodies against HIV-1

    Journal of Immunological Methods 409:131–146.

    https://doi.org/10.1016/j.jim.2013.11.022

    • PubMed
    • Google Scholar
39. 1. Schwank G
    2. Koo BK
    3. Sasselli V
    4. Dekkers JF
    5. Heo I
    6. Demircan T
    7. Sasaki N
    8. Boymans S
    9. Cuppen E
    10. van der Ent CK
    11. Nieuwenhuis EE
    12. Beekman JM
    13. Clevers H

    (2013) Functional repair of CFTR by CRISPR/Cas9 in intestinal stem cell organoids of cystic fibrosis patients

    Cell Stem Cell 13:653–658.

    https://doi.org/10.1016/j.stem.2013.11.002

    • PubMed
    • Google Scholar
40. 1. Seaman MS
    2. Janes H
    3. Hawkins N
    4. Grandpre LE
    5. Devoy C
    6. Giri A
    7. Coffey RT
    8. Harris L
    9. Wood B
    10. Daniels MG
    11. Bhattacharya T
    12. Lapedes A
    13. Polonis VR
    14. McCutchan FE
    15. Gilbert PB
    16. Self SG
    17. Korber BT
    18. Montefiori DC
    19. Mascola JR

    (2010) Tiered categorization of a diverse panel of HIV-1 env pseudoviruses for assessment of neutralizing antibodies

    Journal of Virology 84:1439–1452.

    https://doi.org/10.1128/JVI.02108-09

    • PubMed
    • Google Scholar
41. 1. Smith DS
    2. Creadon G
    3. Jena PK
    4. Portanova JP
    5. Kotzin BL
    6. Wysocki LJ

    (1996)

    Di- and trinucleotide target preferences of somatic mutagenesis in normal and autoreactive B cells

    Journal of Immunology 156:2642–2652.

    • Google Scholar
42. 1. Sok D
    2. Le KM
    3. Vadnais M
    4. Saye-Francisco KL
    5. Jardine JG
    6. Torres JL
    7. Berndsen ZT
    8. Kong L
    9. Stanfield R
    10. Ruiz J
    11. Ramos A
    12. Liang CH
    13. Chen PL
    14. Criscitiello MF
    15. Mwangi W
    16. Wilson IA
    17. Ward AB
    18. Smider VV
    19. Burton DR

    (2017) Rapid elicitation of broadly neutralizing antibodies to HIV by immunization in cows

    Nature 548:108–111.

    https://doi.org/10.1038/nature23301

    • PubMed
    • Google Scholar
43. 1. Sui J
    2. Hwang WC
    3. Perez S
    4. Wei G
    5. Aird D
    6. Chen LM
    7. Santelli E
    8. Stec B
    9. Cadwell G
    10. Ali M
    11. Wan H
    12. Murakami A
    13. Yammanuru A
    14. Han T
    15. Cox NJ
    16. Bankston LA
    17. Donis RO
    18. Liddington RC
    19. Marasco WA

    (2009) Structural and functional bases for broad-spectrum neutralization of avian and human influenza A viruses

    Nature Structural & Molecular Biology 16:265–273.

    https://doi.org/10.1038/nsmb.1566

    • PubMed
    • Google Scholar
44. 1. Turchaninova MA
    2. Davydov A
    3. Britanova OV
    4. Shugay M
    5. Bikos V
    6. Egorov ES
    7. Kirgizova VI
    8. Merzlyak EM
    9. Staroverov DB
    10. Bolotin DA
    11. Mamedov IZ
    12. Izraelson M
    13. Logacheva MD
    14. Kladova O
    15. Plevova K
    16. Pospisilova S
    17. Chudakov DM

    (2016) High-quality full-length immunoglobulin profiling with unique molecular barcoding

    Nature Protocols 11:1599–1616.

    https://doi.org/10.1038/nprot.2016.093

    • PubMed
    • Google Scholar
45. 1. Vasquez KM
    2. Marburger K
    3. Intody Z
    4. Wilson JH

    (2001) Manipulating the mammalian genome by homologous recombination

    PNAS 98:8403–8410.

    https://doi.org/10.1073/pnas.111009698

    • PubMed
    • Google Scholar
46. 1. Voss JE
    2. Andrabi R
    3. McCoy LE
    4. de Val N
    5. Fuller RP
    6. Messmer T
    7. Su CY
    8. Sok D
    9. Khan SN
    10. Garces F
    11. Pritchard LK
    12. Wyatt RT
    13. Ward AB
    14. Crispin M
    15. Wilson IA
    16. Burton DR

    (2017) Elicitation of neutralizing antibodies targeting the V2 apex of the HIV envelope trimer in a Wild-Type animal model

    Cell Reports 21:222–235.

    https://doi.org/10.1016/j.celrep.2017.09.024

    • PubMed
    • Google Scholar
47. 1. Walker LM
    2. Huber M
    3. Doores KJ
    4. Falkowska E
    5. Pejchal R
    6. Julien JP
    7. Wang SK
    8. Ramos A
    9. Chan-Hui PY
    10. Moyle M
    11. Mitcham JL
    12. Hammond PW
    13. Olsen OA
    14. Phung P
    15. Fling S
    16. Wong CH
    17. Phogat S
    18. Wrin T
    19. Simek MD
    20. Koff WC
    21. Wilson IA
    22. Burton DR
    23. Poignard P
    24. Protocol G Principal Investigators

    (2011) Broad neutralization coverage of HIV by multiple highly potent antibodies

    Nature 477:466–470.

    https://doi.org/10.1038/nature10373

    • PubMed
    • Google Scholar
48. 1. Watson CT
    2. Breden F

    (2012) The immunoglobulin heavy chain locus: genetic variation, missing data, and implications for human disease

    Genes & Immunity 13:363–373.

    https://doi.org/10.1038/gene.2012.12

    • PubMed
    • Google Scholar
49. Software

    1. Wolfram research

    (2018)

    Mathematica, version 11.3

    Wolfram.
50. 1. Ye J
    2. Ma N
    3. Madden TL
    4. Ostell JM

    (2013) IgBLAST: an immunoglobulin variable domain sequence analysis tool

    Nucleic Acids Research 41:W34–W40.

    https://doi.org/10.1093/nar/gkt382

    • PubMed
    • Google Scholar

Author details

1. James E Voss

   1. Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, United States
   2. International AIDS Vaccine Initiative Neutralizing Antibody Center, The Scripps Research Institute, La Jolla, United States
   3. Scripps Center for HIV/AIDS Vaccine Immunology and Immunogen Discovery (CHAVI-ID), The Scripps Research Institute, La Jolla, United States

   Contribution

   Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing—original draft, Project administration, Writing—review and editing

   Contributed equally with

   Alicia Gonzalez-Martin and Raiees Andrabi

   For correspondence

   jvoss@scripps.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4777-1596

2. Alicia Gonzalez-Martin

   Department of Biochemistry, Universidad Autónoma de Madrid (UAM) and Instituto de Investigaciones Biomédicas Alberto Sols (CSIC-UAM), Madrid, Spain

   Contribution

   Validation, Investigation, Methodology, Writing—original draft, Writing—review and editing

   Contributed equally with

   James E Voss and Raiees Andrabi

   For correspondence

   alicia.gonzalezm@uam.es

   Competing interests

   No competing interests declared

3. Raiees Andrabi

   1. Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, United States
   2. International AIDS Vaccine Initiative Neutralizing Antibody Center, The Scripps Research Institute, La Jolla, United States
   3. Scripps Center for HIV/AIDS Vaccine Immunology and Immunogen Discovery (CHAVI-ID), The Scripps Research Institute, La Jolla, United States

   Contribution

   Conceptualization, Supervision, Investigation, Methodology, Writing—review and editing

   Contributed equally with

   James E Voss and Alicia Gonzalez-Martin

   Competing interests

   No competing interests declared

4. Roberta P Fuller

   1. Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, United States
   2. International AIDS Vaccine Initiative Neutralizing Antibody Center, The Scripps Research Institute, La Jolla, United States
   3. Scripps Center for HIV/AIDS Vaccine Immunology and Immunogen Discovery (CHAVI-ID), The Scripps Research Institute, La Jolla, United States

   Contribution

   Validation, Investigation, Visualization

   Contributed equally with

   Ben Murrell, Laura E McCoy and Katelyn Porter

   Competing interests

   No competing interests declared

5. Ben Murrell

   1. Department of Medicine, University of California, San Diego, San Diego, United States
   2. Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden

   Contribution

   Software, Formal analysis, Visualization

   Contributed equally with

   Roberta P Fuller, Laura E McCoy and Katelyn Porter

   Competing interests

   No competing interests declared

6. Laura E McCoy

   Division of Infection and Immunity, University College London, London, United Kingdom

   Contribution

   Conceptualization, Resources, Writing—review and editing

   Contributed equally with

   Roberta P Fuller, Ben Murrell and Katelyn Porter

   Competing interests

   No competing interests declared

7. Katelyn Porter

   1. Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, United States
   2. International AIDS Vaccine Initiative Neutralizing Antibody Center, The Scripps Research Institute, La Jolla, United States
   3. Scripps Center for HIV/AIDS Vaccine Immunology and Immunogen Discovery (CHAVI-ID), The Scripps Research Institute, La Jolla, United States

   Contribution

   Resources

   Contributed equally with

   Roberta P Fuller, Ben Murrell and Laura E McCoy

   Competing interests

   No competing interests declared

8. Deli Huang

   Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, United States

   Contribution

   Methodology

   Competing interests

   No competing interests declared

9. Wenjuan Li

   Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, United States

   Contribution

   Investigation

   Competing interests

   No competing interests declared

10. Devin Sok

    1. Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, United States
    2. International AIDS Vaccine Initiative Neutralizing Antibody Center, The Scripps Research Institute, La Jolla, United States
    3. Scripps Center for HIV/AIDS Vaccine Immunology and Immunogen Discovery (CHAVI-ID), The Scripps Research Institute, La Jolla, United States

    Contribution

    Supervision

    Competing interests

    No competing interests declared

11. Khoa Le

    1. Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, United States
    2. International AIDS Vaccine Initiative Neutralizing Antibody Center, The Scripps Research Institute, La Jolla, United States
    3. Scripps Center for HIV/AIDS Vaccine Immunology and Immunogen Discovery (CHAVI-ID), The Scripps Research Institute, La Jolla, United States

    Contribution

    Investigation

    Competing interests

    No competing interests declared

12. Bryan Briney

    1. Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, United States
    2. International AIDS Vaccine Initiative Neutralizing Antibody Center, The Scripps Research Institute, La Jolla, United States
    3. Scripps Center for HIV/AIDS Vaccine Immunology and Immunogen Discovery (CHAVI-ID), The Scripps Research Institute, La Jolla, United States

    Contribution

    Software

    Competing interests

    No competing interests declared

13. Morgan Chateau

    Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, United States

    Contribution

    Writing—review and editing

    Competing interests

    No competing interests declared

14. Geoffrey Rogers

    Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, United States

    Contribution

    Writing—review and editing

    Competing interests

    No competing interests declared

15. Lars Hangartner

    Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, United States

    Contribution

    Writing—review and editing

    Competing interests

    No competing interests declared

16. Ann J Feeney

    Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, United States

    Contribution

    Resources, Methodology, Writing—review and editing

    Competing interests

    No competing interests declared

17. David Nemazee

    Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, United States

    Contribution

    Resources, Methodology, Writing—review and editing

    Competing interests

    No competing interests declared

18. Paula Cannon

    Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, United States

    Contribution

    Funding acquisition, Writing—review and editing

    Competing interests

    No competing interests declared

19. Dennis R Burton

    1. Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, United States
    2. International AIDS Vaccine Initiative Neutralizing Antibody Center, The Scripps Research Institute, La Jolla, United States
    3. Scripps Center for HIV/AIDS Vaccine Immunology and Immunogen Discovery (CHAVI-ID), The Scripps Research Institute, La Jolla, United States
    4. Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology, and Harvard, Cambridge, United States

    Contribution

    Funding acquisition, Writing—original draft, Writing—review and editing

    For correspondence

    burton@scripps.edu

    Competing interests

    No competing interests declared

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