Functional development of a V3-specific broadly neutralizing antibody isolated from a case of HIV superinfection

Functional development of a V3-specific broadly neutralizing antibody isolated from a case of HIV superinfection | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Functional development of a V3-specific broadly neutralizing antibody isolated from a case of HIV superinfection View ORCID Profile Mackenzie M. Shipley , Vidya Mangala Prasad , View ORCID Profile Laura E. Doepker , View ORCID Profile Adam Dingens , Duncan Ralph , Elias Harkins , Amrit Dhar , Dana Arenz , Vrasha Chohan , Haidyn Weight , Kishor Mandaliya , View ORCID Profile Jesse D. Bloom , Frederick A. Matsen IV , Kelly K. Lee , View ORCID Profile Julie M. Overbaugh doi: https://doi.org/10.1101/2021.03.15.435484 Mackenzie M. Shipley 1 Division of Human Biology, Fred Hutchinson Cancer Research Center , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Mackenzie M. Shipley Vidya Mangala Prasad 2 Department of Medicinal Chemistry, University of Washington , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Laura E. Doepker 1 Division of Human Biology, Fred Hutchinson Cancer Research Center , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Laura E. Doepker Adam Dingens 3 Division of Basic Sciences, Fred Hutchinson Cancer Research Center , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Adam Dingens Duncan Ralph 4 Division of Public Health Sciences, Fred Hutchinson Cancer Research Center , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Elias Harkins 4 Division of Public Health Sciences, Fred Hutchinson Cancer Research Center , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Amrit Dhar 4 Division of Public Health Sciences, Fred Hutchinson Cancer Research Center , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Dana Arenz 1 Division of Human Biology, Fred Hutchinson Cancer Research Center , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Vrasha Chohan 1 Division of Human Biology, Fred Hutchinson Cancer Research Center , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Haidyn Weight 1 Division of Human Biology, Fred Hutchinson Cancer Research Center , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kishor Mandaliya 5 Coast Provincial General Hospital , Women’s Health Project, Mombasa, Kenya Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jesse D. Bloom 3 Division of Basic Sciences, Fred Hutchinson Cancer Research Center , Seattle, Washington, USA 6 Department of Genome Sciences, University of Washington , Seattle, Washington, USA 7 Howard Hughes Medical Institute , Chevy Chase, Maryland, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Jesse D. Bloom Frederick A. Matsen IV 4 Division of Public Health Sciences, Fred Hutchinson Cancer Research Center , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kelly K. Lee 2 Department of Medicinal Chemistry, University of Washington , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: joverbau{at}fredhutch.org kklee{at}uw.edu Julie M. Overbaugh 1 Division of Human Biology, Fred Hutchinson Cancer Research Center , Seattle, Washington, USA 4 Division of Public Health Sciences, Fred Hutchinson Cancer Research Center , Seattle, Washington, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Julie M. Overbaugh For correspondence: joverbau{at}fredhutch.org kklee{at}uw.edu Abstract Full Text Info/History Metrics Preview PDF Abstract Stimulating broadly neutralizing antibodies (bnAbs) directly from germline remains a barrier for HIV vaccines. HIV superinfection elicits bnAbs more frequently than single infection, providing clues of how to elicit such responses. We used longitudinal antibody sequencing and structural studies to characterize bnAb development from a superinfection case. Mature bnAb QA013.2 bound both initial transmitted and superinfecting virus, but its inferred naïve bound only the superinfecting strain and was not neutralizing. QA013.2 requires residues spanning FWRH1-CDRH1 to attain breadth, which is uncommon for V3-specific bnAbs. A 4.15 Å cryo-EM structure of QA013.2 bound to heterologous native-like trimer showed recognition of V3 signatures (N301, N332, and GDIR). Antigenic profiling revealed that viral escape was achieved not only by changes in the structurally-defined epitope, but also by mutations in V1. These results highlight shared and distinct properties of QA013.2 relative to other V3-specific bnAbs in the setting of sequential, diverse antigenic variants. Introduction Developing a vaccine that elicits broadly neutralizing antibodies (bnAbs) against HIV is considered critical to achieving protection from the extensive diversity of circulating HIV subtypes ( Burton and Hangartner, 2016 ; Doria-Rose, 2010 ). The potency and protective efficacy of these bnAbs has been demonstrated in passive immunization trials ( Pegu et al., 2017 ), however thus far, no vaccine design has been capable of eliciting potent HIV bnAbs. In part, this may be because HIV-specific bnAbs typically take years to develop in adults, requiring exposure of the immune system to significant, evolving viral diversity, and have unusual features including extended complementary determining regions (CDRs), widespread somatic hypermutation (SHM), and polyreactivity ( Mascola and Haynes, 2013 ). Developing a vaccine that stimulates the production of neutralizing antibodies with such rare features may require a series of immunogens that each engage key intermediate members of the antibody’s lineage, leading to eventual bnAb emergence ( Andrabi et al., 2018 ; Kwong and Mascola, 2018 ). Using deep sequencing and phylogenetic approaches to define maturation pathways of bnAbs from their naïve predecessors in the setting of natural infection provides insight that can guide the design of tailored vaccine immunogens aimed at recapitulating the evolution and development of HIV-specific bnAbs ( Briney et al., 2016 ; Doria-Rose and Joyce, 2015 ). Such antibody lineage reconstruction has been performed for a handful of HIV bnAbs, with particular focus on core bnAb epitopes including the CD4-binding site, the variable loop 1/2 (V1/V2) apex, and the conserved glycan supersite in V3 of HIV Envelope (Env) ( Bonsignori et al., 2017a ; Doria-Rose et al., 2016 ; Garces et al., 2015 ; MacLeod et al., 2016 ; N. Doria-Rose et al., 2014 ; Simonich et al., 2019 ; Wu et al., 2011 ). The glycan supersite in the V3 loop of Env is an advantageous target for vaccine immunogens because bnAbs recognizing this site are not germline restricted and often require less SHM than several other bnAb classes ( MacLeod et al., 2016 ; Simonich et al., 2019 ). While V3-specific bnAbs have a shared requirement of the core glycan at site N332, they are also capable of recognizing heterogeneous glycan moieties with overlapping epitopes and they achieve this recognition using a variety of binding angles and approaches ( Barnes et al., 2018 ; Bonsignori et al., 2017a ; Doores et al., 2015 ; Freund et al., 2017 ; Julien et al., 2013 ; Mouquet et al., 2012 ; Pejchal et al., 2011 ; Sok et al., 2016 ; Trkola et al., 1996 , p. 12; Walker et al., 2011 ). The majority of HIV isolates are able to escape V3-specific bnAb recognition and neutralization by shifting the sites of glycosylation on the surface of Env ( Dingens et al., 2019 ), but combination immunotherapy with bnAbs that target distinct epitopes has demonstrated the ability to thwart viral escape, without the emergence of resistance mutations ( Bar-On et al., 2018 ; Klein et al., 2012 ; Mendoza et al., 2018 ). These findings support the use of genetically diverse immunogens during vaccination to generate a polyclonal neutralizing antibody response that targets distinct epitopes, as is observed following natural HIV superinfection ( Cortez et al., 2015 ; Doria-Rose and Joyce, 2015 ; Williams et al., 2018 ). HIV superinfection (SI) represents a unique setting to study the evolution of bnAbs, as antigenic stimulation with two genetically distinct virus strains may lead to the development of neutralizing antibody responses through mechanisms that differ from that of single infection. Indeed it has been shown that plasma from SI individuals is more broad and potently neutralizing than plasma obtained from time-matched samples of single HIV infection ( Cortez et al., 2012 ; Powell et al., 2010 ). Other studies of SI have found an additive effect to the neutralizing antibody response following secondary infection, in which disparate antibody responses are generated to distinct viral epitopes ( Sheward et al., 2018 ), suggesting that superinfection may drive a polyclonal neutralizing antibody response as opposed to only a boost in memory B cell responses. This idea is supported by plasma mapping data demonstrating the lack of a dominant viral epitope signature recognized by neutralizing antibodies present in plasma from 21 SI women ( Cortez et al., 2015 ). These data suggest that immune responses to superinfection are distinct from those to single HIV infection and, thus, could provide additional clues as to how diverse and protective bnAbs evolve. Moreover, immune stimulation by two distinct viruses produces a situation that emulates aspects of sequential vaccination with different antigenic variants. This scenario allows us to delineate how antibody responses evolve following sequential exposure to distinct heterologous antigens. To date, examination of bnAb evolution and functional development has only been assessed for one case of HIV superinfection, that of participant CAP256, who developed a potent V1/V2-specific bnAb lineage (CAP256-VRC26) that recognized the SI virus ( Doria-Rose et al., 2016 ; N. Doria-Rose et al., 2014 ). Here, we detail the functional development of a V3-specific bnAb QA013.2 isolated approximately six years post initial infection from a HIV superinfected woman in Mombasa, Kenya ( Williams et al., 2018 ). This bnAb binds the V3 glycan at site N332, with a footprint similar to that of the bnAb PGT128 ( Williams et al., 2018 ). SHM gave QA013.2 the ability to bind and recognize the initial infecting virus that lacks the N332 glycan, despite the bnAb evolving only with the constraint to neutralize the SI virus ( Williams et al., 2018 ). A cryo-EM structure of the mature Fab bound to heterologous HIV Env trimer reveals that QA013.2 evolved to establish a conformational epitope that spans V3, with the majority of the antigen contacts mediated by the antibody’s heavy chain, with additional contributions from residues in the light chain framework (FWR) and CDR loops. However, unlike many other V3-specific bnAbs reported in the literature, this bnAb emerging from HIV superinfection relies on residues that span FWRH1 and CDRH1 to achieve cross-clade Tier 2 heterologous neutralization, while residues in CDRH3 are less impactful. The heavy chain-driven antigen recognition by QA013.2 elicited viral escape at sites beyond the V3 region of Env in the variable loop 1, suggesting a more complex conformational epitope than other V3-specific bnAbs. These findings shed light on at least one demonstrable route to an immune response achieving bnAb breadth – a prerequisite for vaccine immunogen design. Results QA013.2 clonal lineage development Study participant QA013 was initially infected with a HIV clade D virus in 1995. At just over one year post initial infection (pii), a clade A variant was identified that had not been detected at the previous visit a few months earlier, indicating superinfection (SI) occurred in the intervening period: approximately 264-385 dpii ( Chohan et al., 2005 ). Both viruses persisted in this individual for at least six years, and our lab previously isolated the bnAb QA013.2 at 2282 dpii (just over 6 years pii), along with several less potent nAbs that also contributed to plasma breadth. ( Williams et al., 2018 ). To investigate the functional development of this V3-specific bnAb, we performed deep sequencing of the subject’s antibody repertoire using four longitudinal peripheral blood mononuclear cell (PBMC) samples spanning time points from pre-HIV infection (D-379) to 765 dpii (D765) ( Fig. 1A ). With these deep sequencing data, computational inference methods designed for antibody lineage analyses were used to infer probable naïve B cell receptors (BCRs) that seeded the heavy and light clonal families of QA013.2. We then performed ancestral sequence reconstruction using Bayesian phylogenetics to determine the most probable routes of development from inferred naïve sequence to mature sequence ( Fig. 1B , Fig. 1 – figure supplement 1 - 3 ) ( Dhar et al., 2020 ; Ralph and Matsen, 2016 ). Antibodies were constructed based on the most statistically probable routes of development for the QA013.2 bnAb heavy and light chains, which involved eight variable heavy chain (VH) intermediate sequences and six variable light chain (VL) intermediate sequences between respective naïve and mature sequences ( Fig. 1C , Supp. File 1 ). Of note, several of the inferred intermediate sequences shared ≥98% nucleotide identity with sequences sampled from the longitudinal B cell repertoire of QA013, and in some cases there were identical sequences observed ( Fig. 1C , Supp. File 2 ). Download figure Open in new tab Figure 1: QA013.2 inferred clonal lineage development. A) Timeline of HIV infection, isolation of QA013.2 bnAb, and longitudinal PBMC samples used for antibody variable region sequencing. Days post initial HIV infection are listed above the timeline and black arrows below the timeline correspond to the specific PBMC samples that were used for deep sequencing. Approximate heterologous plasma breadth as determined previously ( Cortez et al., 2012 ) is depicted above the timeline, which is not to scale. Estimated timing of superinfection as previously described ( Chohan et al., 2005 ) is shown in purple on the timeline, with the timing of superinfection estimated as the midpoint, 324.5 days post initial infection. The QA013.2 bnAb was not isolated until 2282 days, or about 6.2 years post initial infection, as indicated. B) Lineage graphics representing probable developmental paths for heavy and light chain lineages between inferred naïve and mature QA013.2 sequences. Nodes represent inferred ancestral sequences, while arrows in between each node represent amino acid transitions. The red shading of nodes is proportional to the posterior probability that this ancestral sequence was present in the true lineage. For each given node, the blue shading of arrows arising from that node is proportional to the corresponding transition probability. Low probability nodes were filtered out, resulting in some incomplete pathways within the graphics. Dashed arrows indicate possible developmental paths that were not chosen based on low probability. See Figure 1 – figure supplement 1 - 3 . C) Probable lineage sequences for the developing QA013.2 heavy (blue) and light chains (orange) are displayed in their inferred chronological order. With respect to the inferred naive sequence at the top of each lineage, variable region amino acid substitutions are indicated by black lines. Dashed lines demarcate the CDRs that are flanked by FWRs. Red percentages to the right of each sequence represent the nucleotide identity of each computationally-inferred lineage member to sampled NGS sequences present in the longitudinal B cell repertoire of QA013, rounded to the nearest percent. See also Supplemental Files 1 and 2 for fasta files of computationally-inferred lineage members and sampled NGS sequences with high nucleotide identity to inferred lineage members. The heavy chain clonal family of QA013.2 included a total of 42 members and ranked among the top ten largest clonal family clusters that were sampled in this subject’s immune repertoire. These clonally-related sequences derived from an inferred naïve BCR that used VH3-7*01, VD1-1*01, and VJ5*02 genes and had a 21-residue CDRH3 loop. The VH lineage matured over the course of six years to accumulate 20% somatic hypermutation (SHM) – which corresponded to a total of 38 amino acid mutations across the variable region in the mature QA013.2 bnAb ( Fig. 1C ). The QA013.2 light chain clonal family included >1000 members likely due to overclustering, but it did not rank among the top ten largest light chain clonal families that were sampled in the repertoire (also due to overclustering, see Methods). The naïve light chain BCR used germline genes VL1-40*01 and VJ2*01 and the lineage acquired fewer mutations over the course of maturation, with a total of 12% SHM present in the mature lambda light chain ( Fig. 1C ). From the deep sequencing data, which was informed by samples up to 765 dpii, we observed that the inferred antibody lineages acquired limited SHM between the inferred naïves and the latest inferred intermediates (Int6 VH and Int5 VL ). More than 70% of the total SHM (84 of 117 nucleotide mutations across VH and VL regions combined) present in QA013.2 was not detected in the sequence data through 765 dpii, suggesting that either we did not sample sequences containing these mutations, or that these mutations accumulated between 765 dpii and the time when QA103.2 was isolated at 2282 dpii. Thus, we can only reliably infer the lineage through the early stages of development; the later stages of the bnAb’s evolutionary pathway are beyond the scope of the computationally inferred lineage ( Fig. 1B,C ). Despite this lack of resolution, the lineage and longitudinal development that we were able to decipher offer a means to dissect the determinants of antibody binding, potency, and breadth for QA013.2. Here we defined neutralization breadth as the mediation of cross-clade heterologous neutralization of Tier 2 HIV pseudoviruses as measured by the TZM-bl assay. QA013.2 heavy chain maturation enables antigen binding and neutralization To determine whether key residues mediating breadth were represented in the inferred intermediate sequences defined through 765 dpii, we selected these intermediates (Int6 VH and Int5 VL ; Fig 1 ), as well as inferred naïve heavy and light chain sequences and paired them together in various combinations ( Fig. 2A ) to test their capacity to bind and neutralize HIV relative to the mature QA013.2 bnAb. The resulting monoclonal antibodies (mAbs) were tested for binding to autologous and heterologous Envelope protein (Env) by biolayer interferometry (BLI). The inferred naïve had weak but detectable binding to the Env-gp120 from a clade A autologous superinfecting virus variant from 765 dpii; there was even weaker binding to heterologous clade A BG505.SOSIP.664 trimer ( Fig. 2B,C ). While these data were insufficient for calculating reliable binding kinetics, they suggest that the naïve BCR of the QA013.2 bnAb lineage is capable of recognizing the superinfecting virus. The inferred naïve antibody did not detectably bind to the clade D virus from initial infection ( Fig. 2 – figure supplement 1 ). Download figure Open in new tab Figure 2: Binding and neutralization analyses of QA013.2 inferred VH and VL antibody chains demonstrates that heavy chain maturation is critical for bnAb function. A) Schematic depicting antibody chain pairings of inferred lineage member heavy (blue) and light chains (orange) with one another. B,C) Biolayer interferometry (BLI) analysis of QA013.2 inferred lineage mAbs at 10 μg mL -1 binding to B) the Env-gp120 monomer from a clade A autologous superinfecting virus variant from 765 dpii (QA013.765M.C1, 2 μM) and C) the heterologous clade A Env trimer (BG505.SOSIP.664, 500 nM). All BLI curves were subjected to double reference background subtraction and data were fit to a global model of 1:1 ligand:analyte binding to obtain K D , k on , and k dis values. The resulting lines of best fit are shown in green. Dotted line across the graphs marks 0.00 on the y-axis. All data are representative of at least two independent experiments. D) QA013.2 inferred lineage mAb neutralization of autologous and heterologous pseudoviruses as measured by the TZM-bl assay. The half maximal inhibitory concentration (IC 50 ) for each tested pseudovirus is shown in a row across the top of the table. Darker blue indicates more potent neutralization, while white demonstrates weak neutralization, and grey represents no neutralization observed at the highest antibody concentration tested. Simian immunodeficiency virus (SIV) was used as a negative control; none of the tested mAbs showed evidence of SIV neutralization (data not shown). IC 50 values are the average of at least two independent replicates. See Figure 2 – figure supplement 1 . By contrast, the mature QA013.2 bnAb exhibited strong binding kinetics to both the autologous SI gp120 and heterologous BG505 Env trimer, with equilibrium dissociation constants of 94.9 nM and 3.2 nM, respectively. A mAb consisting of the mature heavy chain paired with the naïve light chain (mat VH 0 VL ) bound to autologous SI gp120, however the binding affinity was much weaker relative to the mature bnAb and not suitable for calculating binding kinetics. This same mAb bound to heterologous BG505 Env trimer (K D = 89.6 nM) with an affinity that was approximately 30-fold less than that of the mature bnAb ( Fig. 2B,C ). The converse mAb pairing (0 VH mat VL ) did not result in any binding capacity to either tested antigen. Intermediate mAb Int6 VH Int5 VL , with 6% total SHM, represents the final inferred intermediates from the deep sequencing data, and they were detected in the sampled NGS sequences at 99-100% nucleotide identity, further validating the sequence of these inferred intermediates ( Supp. File 2 ). We could not detect binding of the intermediate mAb to the gp120 of the autologous SI virus, but there was clear evidence of binding to heterologous BG505 Env trimer (K D = 513 nM) ( Fig. 2C ), demonstrating HIV Env specificity. However, the binding affinity to heterologous trimer was more than 100-fold lower when compared to the mature bnAb. Together these studies demonstrate that VH is important for facilitating initial HIV recognition and binding. This finding is supported by data collected for both autologous Env-gp120 and heterologous native-like trimer, despite the native-like Env trimer yielding tighter binding affinities and dissociation constants for all tested mAbs. While early affinity maturation of the QA013.2 VH lineage led to measurable binding to heterologous Env antigen ( Fig. 2C ), higher affinity binding required subsequent mutations, including acquisition of 30 non-synonymous mutations across the variable region between Int6 VH and mature VH . ( Fig. 1B,C and 2B,C ). We tested the same lineage mAbs for neutralization using a subset of HIV Env pseudoviruses that were neutralized by the mature QA013.2 bnAb, including the same clade A autologous Env variant from 765 dpii used to generate gp120 for binding studies ( Williams et al., 2018 ). Neutralization was not observed for the inferred naïve (0 VH 0 VL ) ( Fig. 2D ). While binding was detected between the intermediate mAb (Int6 VH Int5 VL ) and the heterologous BG505 Env trimer, it did not neutralize the same virus ( Fig 2C,D ). Thus, the naïve and intermediate Int6 VH Int5 VL mAbs represent early members of the lineage with the capacity to bind HIV Env trimer that have not yet acquired the ability to neutralize either autologous or heterologous variants. While the inferred Int6 VH Int5 VL intermediate was validated by near-perfect sequence matches in the sampled NGS sequences ( Supp. File 2 ), we cannot rule out the possibility that another lineage member with neutralization capacity was also present by 765 dpii, because deep sequencing antibody variable regions from blood PBMC samples often results in incomplete sampling ( Horns et al., 2019 ; Laserson et al., 2014 ). Indeed, we observed low sequence read depth across all QA013 PBMC sample timepoints and antibody isotypes ( Table 1 ). View this table: View inline View popup Download powerpoint Table 1: Sequencing statistics of longitudinal PBMC samples from subject QA013. When the mature VH was paired with the naïve light chain (mat VH 0 VL ), autologous and cross-clade Tier 2 heterologous neutralization was achieved, suggesting that the approximate timeframe in which neutralization-mediating mutations were acquired in VH likely occurred between 765 dpii (resolution of computationally inferred lineage) and 2282 dpii (isolation of mature bnAb QA013.2). The naïve heavy chain paired with the mature light chain (0 VH mat VL ) did not result in any detectable neutralization of the virus panel ( Fig. 2D ), suggesting that affinity maturation of the heavy chain is critical for imparting both binding and neutralization. When Int5 VL was paired with the mature heavy chain (mat VH Int5 VL ), there was an average four-fold increase in neutralization potency for all viruses tested compared to mat VH naïve VL ( Fig. 2D ). Cryo-EM structure of QA013.2 Fab bound to Env trimer demonstrates widespread antibody contacts and shared structural characteristics with other V3-specific bnAbs To better identify which residues contribute to QA013.2’s ability to bind and neutralize Env, we performed single particle cryo-electron microscopy (cryo-EM) on the QA013.2 Fab and BG505.SOSIP.664 trimer complex ( Fig. 3A,B ). The known structure of BG505.SOSIP.664 trimer (PDB ID: 5aco) was fit into the resulting 4.15Å resolution EM density map along with a homology model for the variable domain of QA013.2 Fab ( Fig. 3A,B ). The map density corresponding to the Fab variable domain was well resolved, with prominent loops and separation of strands in beta sheet regions. These features facilitated high confidence docking of the Fab homology model into the EM map. Subsequent real-space refinement of the BG505.SOSIP.664 + QA013.2 Fab model against the map enabled a good fit of secondary structural elements within the EM density ( Fig. 3 – Source Data 1 ). The complex structure of QA013.2 Fab bound to BG505.SOSIP.664 delineated antigen contacts characteristic of other V3-specific bnAbs, including conserved glycans as well as the linear GDIR motif ( Barnes et al., 2018 ; Mouquet et al., 2012 ; Pejchal et al., 2011 ). Download figure Open in new tab Figure 3: Cryo-EM structure of QA013.2 Fab bound to BG505.SOSIP.664 trimer. A) Cryo-EM reconstruction of QA013.2 Fab bound to BG505.SOSIP.664 trimer. Gp120 chains are shown in dark blue, gp41 in light blue, Fab heavy chain in orange, and Fab light chain in green. B) Side-view of cryo-EM reconstruction with a single copy of the PDB model shown. The black oval indicates the region of interaction between QA013.2 Fab and HIV BG505 gp120 that is enlarged and highlighted in detail in panels C-E. C) N332 glycan interaction with CDRL3 and CDRH3. D) N301 glycan interaction with CDRH1 and CDRH2. E) Heavy chain CDR3 interacts with the linear GDIR motif of gp120. See also Figure 3 – figure supplement 1 , 2 and Figure 3 – Source Data 1 . From the cryo-EM structure, it is apparent that QA013.2 interacts not only with the N332 glycan as previously reported ( Williams et al., 2018 ), but also with the glycan at site N301, and the linear GDIR motif at the base of the V3 loop ( Fig. 3C-E ). Key regions of the antibody paratope include the CDRH1 and CDRH2 which are nearest the N301 glycan, as well as CDRH3 and CDRL3, which are in close proximity to the N332 glycan. We observe that the CDR loops of the heavy chain contain many polar and charged residues, which likely facilitate hydrogen bonding interaction with the Env glycans and the charged residues in the GDIR motif ( Fig. 3 – figure supplement 1A ). The CDRH3 loop is distinctively long (21 residues) and appears to tilt away from the rest of the heavy chain towards the light chain, generating a cleft between CDRH2 and CDRH3 and exposing an extended interface that has been observed for other V3-specific bnAbs including 10-1074 and PGT121 ( Fig. 3 – figure supplement 1B ) ( Mouquet et al., 2012 ). Seven key residues in the Fab CDRH3 loop (L103 – I109) lie adjacent to the conserved GDIR motif. Based on our sequencing data of the sampled repertoire of this subject, these amino acids (excluding Y105 and D107) were likely introduced during affinity maturation of the heavy chain between 765 dpii and 2282 dpii because they were not detected by NGS through 765 dpii ( Fig. 1C ), suggesting a potential role for these residues in facilitating antibody breadth and/or potency. Substitutions in FWRH1-CDRH1 are required for bnAb neutralization breadth With paratope data in hand, we had the opportunity to show which regions of QA013.2 were playing a role in its functional activity by dissecting the regional and individual residue contributions interpreted through the structure. We began by examining the functional importance of VH mutations surrounding the CDR loops that were present in the mature antibody but not in the ≤765 dpii inferred intermediates. We synthesized six additional variations of QA013.2 VH, illustrated in Fig. 4A , that we based on Int6 VH as the template and included all CDR-localized and CDR-adjacent FWR residues present in the mature QA013.2 VH ( Supp. File 3 ). All VH chimeras were paired with the mature light chain (mat VL ) and tested for neutralization capacity ( Fig. 4A ). Mutations in individual CDRs, including adjacent FWR mutations, were not sufficient to achieve potent neutralization comparable to the mature antibody when paired with the mature light chain. We did observe weak autologous neutralization when mutations surrounding FWRH3-CDRH3 were added to Int6 VH . Mutations spanning both FWRH1-CDRH1 and FWRH3-CDRH3 of the mature VH together were required to obtain heterologous neutralization, consistent with the cryo-EM map of key antigen contacts ( Fig. 3 and 4A ). Interestingly, the determinants of autologous and heterologous neutralization in this antibody lineage were different, in which autologous virus neutralization required less SHM and was facilitated by residues spanning CDRH2-FWRH3-CDRH3 ( Fig. 4A ). To determine the importance of the framework residues and examine loss of function, we reverted all framework mutations in the mature VH back to the inferred naïve residues (ΔFWR). This reversion resulted in no detectable binding or neutralization activity, demonstrating that residues in the heavy chain FWRs are essential for QA013.2 binding and neutralization, as has been noted for other HIV bnAbs ( Fig. 4A,B ) ( Klein et al., 2013 ). Download figure Open in new tab Figure 4: Interrogating the QA013.2 heavy chain paratope through binding and neutralization studies using chimeric antibodies. Schematic of heavy chain chimeras that were generated and paired with the mature light chain. Names of each heavy chain variant are listed on the left, with colored bars representing the VH region including FWR and CDR loops colored by lineage member to visualize how each variant was generated. Naïve heavy chain is represented in grey, latest inferred heavy chain intermediate (Int6 VH ) is shown in light blue, and the mature heavy chain is shown in dark blue. The middle plot shows the individual mutations represented as black lines across VH relative to the inferred naïve, with CDRs demarcated by dashed lines. Red lines represent all mutations added to the Int6 VH template. Neutralization table on the far right shows the average IC 50 values for each tested chimeric antibody across a panel of pseudoviruses shown at the top. Characteristics of the neutralization table are consistent with those listed in the Figure 2 legend. B) Biolayer interferometry kinetic curves of a select subset of tested antibody variants (10 μg mL -1 against heterologous trimer - BG505.SOSIP.664 at 500 nM). BLI curves were analyzed as described in the Figure 2 legend. See also Supplemental File 3 for fasta file of all chimeric and mutant VH and VL antibody chains used in Figures 4 - 6 . In a complementary approach, we used the mature VH as a template and reverted the mutations spanning FWRH1-CDRH1 (ΔCDR1 VH ) and CDRH3 (ΔCDR3 VH ) back to naïve and as above, paired these variants with the mature light chain ( Fig 4A ). We observed a 89-fold increase in half maximal inhibitory concentration (IC 50 ) neutralization of autologous superinfecting virus and nearly complete ablation of all tested heterologous virus neutralization when the six consecutive residues spanning FWRH1 and CDRH1 (ΔCDR1 VH ) were reverted back to naïve. Reversion of these six residues also led to weakened binding to heterologous BG505.SOSIP.664 trimer (K D = 40.6 nM) relative to the mature bnAb ( Fig. 4A,B ). When the CDRH3 was reverted back to naïve (ΔCDR3 VH ), binding and neutralization of both autologous and heterologous virus was maintained, but there was an impact on potency across all viruses tested; although this antibody could still neutralize a heterologous clade C variant, it did not neutralize SF162 at the highest antibody concentration tested ( Fig. 3 and 4A,B ). These data suggest that the CDRH3 does contribute to the overall breadth and potency of QA013.2, while mutations in FWRH1-CDRH1 are critical for achieving complete cross-clade Tier 2 neutralization breadth. To further interrogate the above hypothesis, we generated single point mutations in the mature VH at residues of interest in FWRH1-CDRH1 and CDRH3 that reverted them to naïve ( Fig. 5A,B ). These heavy chain point mutants were also paired with the mature light chain and tested for binding to Env and neutralization. We found that four of the six residues spanning FWRH1-CDRH1 individually contributed to the mature bnAb’s ability to neutralize autologous and heterologous virus. Residues E26, G28, and I24 were most critical, with average increase in IC 50 of 191-, 27-, and 25-fold, respectively, across all pseudoviruses tested when these residues were reverted to naïve ( Fig. 5C,D ). While reversion of individual CDRH3 residues did not abolish neutralization, which correlates with the chimeric antibody results ( Fig. 4 ), one residue in particular (D106) demonstrated a much higher IC 50 value when mutated back to naïve. D106 is adjacent to the GDIR motif in the structure. Reversion of this residue to naïve did not inhibit clade A autologous virus neutralization, but did substantially impact heterologous neutralization, with an average 40-fold increase in IC 50 across all tested pseudoviruses ( Fig. 5E ). However, the D106V point mutant only resulted in a modest decrease in binding to heterologous BG505.SOSIP.664 trimer relative to the mature bnAb ( Fig. 5F ). These data suggest that while D106 is not critical for Env binding, this residue does contribute to heterologous neutralization, likely by interacting directly with the linear GDIR motif. Taken together, it is clear that although the antibody paratope of QA013.2 includes the CDRH3, where interaction with the N332 glycan and GDIR motif occurs, the QA013.2 paratope is also comprised of critical residues in FWRH1 and CDRH1. Download figure Open in new tab Figure 5: Binding and neutralization of VH point mutant antibodies demonstrates that residues spanning FWRH1-CDRH1 are essential for conferring bnAb neutralization breadth. Schematic of heavy chain point mutants generated in A) FWRH1-CDRH1 that were paired with the mature light chain. Names of each heavy chain point mutant are listed on the left, with colored bars representing the VH region including FWR and CDR loops (dashed lines) colored by lineage member to visualize how each point mutant was generated. Naïve heavy chain is represented in grey and the mature heavy chain is shown in dark blue. B) FWRH1-CDRH1 point mutant neutralization of a subset of autologous and heterologous pseudoviruses as measured by the TZM-bl assay. IC 50 values of each antibody are shown for each pseudovirus column, where darker blue indicates more potent neutralization and grey indicates no neutralization was observed at the highest antibody concentration tested. Average fold change in IC 50 for a particular point mutant relative to the mature bnAb across all pseudoviruses is reported as a final column on the right. C) BLI kinetic curve of a selected FWRH1-CDRH1 point mutant antibody E26G at 10 μg mL -1 against heterologous trimer (BG505.SOSIP.664 at 500 nM). D) Schematic of CDRH3 mutants that were paired with the mature light chain. E) CDRH3 point mutant neutralization of a subset of autologous and heterologous pseudoviruses as measured and displayed in panel B. F) BLI kinetic curve of a selected CDRH3 point mutant antibody D106V at 10 μg mL -1 against heterologous trimer (BG505.SOSIP.664 at 500 nM). BLI curves were analyzed as described in the Figure 2 legend. See also Supplemental File 3 for fasta file of all chimeric and mutant VH and VL antibody chains used in Figures 4 - 6 . QA013.2 light chain confers higher bnAb potency Though less impactful than the heavy chain, our aforementioned data suggested that light chain development indeed contributes to QA013.2 neutralization potency ( Fig 2 ). To identify which regions of the light chain were essential for these contributions, we reverted regions of SHM within Int5 VL back to naïve (Int5ΔFWR2-FWR3 VL and Int5ΔCDR3 VL ) and paired these with the mature heavy chain ( Fig. 6A ). Reversion of the residues spanning FWRL2-FWRL3 abrogated antibody binding to BG505.SOSIP.664 heterologous Env (K D = 1.3 μM) relative to the mature bnAb by more than 400-fold. This effect was less pronounced when residues in the CDRL3 were reverted to naïve ( Fig. 6A,B ). These light chain variants also demonstrated reduced neutralization potency relative to the mature bnAb. Reversion of residues present in FWRL2-FWRL3 resulted in an average 19-fold increase in IC 50 (range 6-42 fold) and reversion of residues in CDRL3 causing a 14-fold increase in average IC 50 (range 1-41 fold) across all pseudoviruses tested when compared to the mature bnAb IC 50 values ( Fig. 6A ). Together, these data demonstrate that residues in FWRL2-FWRL3 and CDRL3, which are situated along the cleft between heavy and light chains and near the N332 glycan, contribute to the mature bnAb’s binding affinity and neutralization potency, with residues in FWRL2-FWRL3 appearing to have a larger influence on bnAb binding. Notably, the residues spanning FWRL2-FWRL3 do not interact directly with the N332 glycan on Env. However, the residues in FWRL3 may influence the conformation of residues in the adjacent CDRL3 loop, which interacts with the N332 glycan. Furthermore, the residues in FWRL2 interact with FWRH4 of the Fab heavy chain (residues 117-120) which follows the CDRH3 loop ( Fig. 6C ). Attempts to identify the light chain residues in FWRL2-FWRL3 responsible for mediating this interaction were inconclusive, as reversion of the residues located in FWRL2 and CDRL2-FWRL3, separately, did not influence the IC 50 values of the tested pseudoviruses, indicating that the cumulative effect of these mutations was beneficial ( Fig. 6A ). Download figure Open in new tab Figure 6: Construction of chimeric VL antibodies to investigate the contribution of QA013.2 light chain to bnAb breadth and potency. A) Schematic of light chain intermediates that were generated and paired with the mature heavy chain. Names of each light chain intermediate are listed on the left, with colored bars representing the VL region including FWR and CDR loops (dashed lines) colored by lineage member to visualize how each variant was generated. Naïve light chain is represented in grey, latest inferred light chain intermediate (Int5 VL ) is shown in light orange, and the mature light chain is shown in dark orange. The plot in the middle shows the individual mutations across VL relative to the inferred naïve, with FWR regions flanking CDR loops that are demarcated by dashed lines. Neutralization table on the far right shows the average IC 50 values for each tested intermediate against a panel of pseudoviruses grouped by clade shown at the top. Characteristics of the neutralization table are the same as those listed in the Figure 2 legend. B) Biolayer interferometry kinetic curves of a select subset of tested antibody variants (10 μg mL -1 against heterologous trimer BG505.SOSIP.664 at 500 nM). BLI curves were analyzed as described in the Figure 2 legend. All data are representative of at least two independent experiments. C) Ribbon structure of QA013.2 Fab bound to BG505.SOSIP.664 Env trimer. Protruding N332 glycan on BG505.SOSIP.664 trimer is shown as a stick model, Fab heavy chain is shown in orange, and Fab light chain in green. Key regions of the structure are labeled including the N332 glycan as well as the VL regions that contribute to bnAb potency and antibody-antigen complex formation. FWRL2 interacts with FWRH4 of the heavy chain, while CDRL3 appears to interact with the tip of the N332 glycan. See also Supplemental File 3 for fasta file of all chimeric and mutant VH and VL antibody chains used in Figures 4 - 6 . Mutational antigenic profiling of QA013.2 identifies unique viral escape mutations in Env variable loop 1 We used mutational antigenic profiling to interrogate the effect of all functionally tolerated single amino acid mutations in BG505.W6.C2 T332N Env on viral escape when under selective pressure from the mature QA013.2 bnAb ( Dingens et al., 2017 ) ( Fig. 7 ). In addition to the more traditional signatures of Env escape from V3-specific bnAbs, including mutations that disrupt the N301 and N332 potential N-linked glycosylation sites (PNGS) or alter the GDIR motif ( Dingens et al., 2019 ), we also observed viral escape via mutations in the V1 loop ( Fig. 7A,B ). In addition to the two PNGS, enrichment of viral escape mutations was strongest at sites D325, R327, and H330; validation of these data using pseudoviruses with individual mutations in TZM-bl neutralization assays showed that mutations to these sites can result in >32-fold change in IC 50 relative to the wildtype BG505.T332N ( Fig. 7B,C ). However, not all mutations to these sites resulted in viral escape. Similar to 10-1074 ( Dingens et al., 2019 ), while D325E was enriched in mutational antigenic profiling and had a >32-fold effect in the TZM-bl assay, D325N/S mutants were not enriched and had negligible effects when tested individually via TZM-bl neutralization assay. Download figure Open in new tab Figure 7: Mutational antigenic profiling of QA013.2 identifies unique viral escape mutations. A) Line plot showing the median positive differential selection across the mutagenized portion of BG505.W6.C2 T332N Env. B) Logoplots showing the mutation-level enrichment for areas of escape in A. C) Table of average fold change in IC 50 for each BG505.W6.C2 T332N viral escape mutant relative to the wildtype BG505.W6.C2 T332N pseudovirus as tested in the TZM-bl neutralization assay. Darker red colors indicate a larger fold change in average IC 50 . In vitro neutralization data are representative of three independent replicates. D) Heavy chain CDR3 loop is within 8Å distance to the V1 loop when measured between the C α chains. See also Figure 7 – figure supplement 1 , 2 . Viral escape in the V1 loop occurred at two sites that are adjacent in the BG505 structure; D141 and R151 (HXB2 numbering), both of which caused a modest ∼3-fold change in IC 50 relative to the wildtype virus ( Fig. 7B,C ). While the V1 loop of Env does not appear to be in direct contact with QA013.2 Fab in the complex structure, the backbone Cα atoms of the Fab CDRH3 loop and Env V1 loop are within 8Å of each other ( Fig. 7D ), suggesting there could be amino acid side-chain interactions between the two loops that can affect neutralization. Interestingly, while the glycan at N332 is essential for bnAb neutralization and disrupting this motif results in viral escape, we observed that it is not required to achieve antibody binding – as demonstrated by the mature bnAb binding to the gp120s from the autologous clade D and BG505.W6.C1 viruses, both of which lack the PNGS at site 332 ( Fig. 7 – figure supplement 1 ). It is likely that this binding, while measurable, is too weak to confer neutralization, confirming the importance of the N332 glycan. Discussion Vaccine approaches aimed at recapitulating the natural stimulation and maturation of bnAbs may require honing of the immune response through exposure to a series of diverse HIV immunogens. HIV-specific bnAbs have been shown to emerge more commonly in cases involving HIV superinfection ( Cortez et al., 2012 ; Powell et al., 2010 ) and thus, provide a unique opportunity to identify the emergence of neutralization potency and breadth. Here we investigated the functional development of V3-specific bnAb QA013.2, isolated from a case of HIV superinfection. QA013.2 uses unique gene segments (VH3-7*01 VD1-1*01 VJ5*02 and VL1-40*01 VJ2*01), has moderate levels of somatic hypermutation (≤ 20%), and unlike many HIV bnAbs, was not found to be polyreactive ( Fig. 8 – figure supplement 1 ). We present data detailing the lineage development and structure-function relationships of QA013.2 using antibody variable region deep sequencing and single particle cryo-EM respectively. The high-resolution structure of QA013.2 Fab bound to the heterologous native-like Env trimer revealed specific regions of the bnAb paratope that interact with HIV Env, which guided targeted mutational approaches to identify the antibody determinants of potency and breadth. From our structural data and functional investigations, we demonstrate that while QA013.2 shares traits with other V3-specific bnAbs, such as targeting conserved glycans and the linear GDIR motif at the base of V3, it also relies less on the CDRH3 loop, which often plays a pivotal role in achieving bnAb neutralization breadth. Rather, residues spanning FWRH1-CDRH1 region were most critical for QA013.2 neutralization breadth. Thus, our results highlight universal aspects of the core V3 epitope on Env as well as the multitude of ways in which bnAbs evolve to target it. Biolayer interferometry data collected on the QA013.2 bnAb lineage showed that in contrast to many other V3-specific bnAbs, the inferred naïve antibody was capable of binding autologous gp120 monomer from the Env protein of the infecting HIV strain, in this case, the superinfecting strain. While we were unable to quantify the binding affinity of the inferred naïve antibody, it has been estimated that affinities in the range of ≤ 1 μM are needed to initiate naïve BCR activation, with the frequency of the precursor B cells playing a critical role in the success of B cell activation, germinal center competition, and memory B cell production ( Abbott et al., 2018 ). Despite precursor B cell frequencies in this subject not being known, the largest variable gene family, VH3, which QA013.2 bnAb uses (VH3-7), comprises nearly half of the VH repertoire in adult peripheral B cells ( Demaison et al., n.d .). Taken together, our data indicate that the bnAb lineage was likely stimulated by the second infection. The inferred naïve antibody did not bind the autologous clade D Env from the initial infecting virus and thus did not appear to play a role in initiating the activation and expansion of the QA013.2 bnAb lineage. Interestingly, the mature antibody could bind to the Env of this initial infecting virus, despite being unable to neutralize it. These data suggested that the development and affinity maturation of the QA013.2 bnAb lineage may have been influenced by both the initial and superinfecting viruses in this individual. Moreover, the presence of clade A/D recombinants in the viral population amplified as early as 385 dpi may have also played a role in this antibody’s affinity maturation and development ( Williams et al., 2018 ). QA013.2 embodies several unique traits. Unlike other V3-targeting bnAbs such as PGT128 that have required significant modification of the paratope through insertions and deletions, we observed that antigen contacts here are mediated by a paratope that does not include indels but includes key framework residues in both the heavy (E23-I25) and light chains (FWRL2 and FWRL3) ( Fig. 8 ). In this case, we observed that without the acquired mutations in FWRL2-FWRL3, QA013.2 had a substantially slower k on rate, indicating that these residues contribute to bnAb affinity and antibody-antigen complex formation. The importance of framework substitutions to HIV bnAbs has been documented, in which they often provide flexibility that facilitates enhanced binding affinity and in some cases, interact directly with antigen ( Klein et al., 2013 ). Additional involvement of framework regions in QA013.2 may result from a “tilted” angle of approach adopted by the heavy chain of the Fab. A similar configuration was observed in 10-1074 and PGT121 bnAbs ( Mouquet et al., 2012 ), In this case, the CDRH3 loop is tilted away from the rest of the heavy chain, towards the light chain resulting in a large portion of the CDRH3 loop being exposed at the antigen interface of the N332 glycan. We propose that this may facilitate additional interactions with this core glycan. The tilting also brings FWRH4 on the opposing side of the CDRH3 loop into close proximity with the light chain. Despite the minimal affinity maturation in this region, FWRH4 (residues 117-120) was found to interact with residues in the light chain FWRL2, likely stabilizing the conformations of the CDRH3 and CDRL3 loops, which in turn, contributes to the overall binding affinity of this bnAb. In contrast to other V3-targeting bnAbs, QA013.2 required residues outside of the CDRH3 region in FWRH1-CDRH1 to achieve cross-clade neutralization breadth. Based on our targeted mutagenesis studies, the CDRH3 as a whole did not appear to mediate heterologous neutralization breadth. Only D106 alone was critical for cross-clade neutralization. The CDRH3 of the mature bnAb contains many hydrophobic residues, which could be implicated in Van der Waals interactions with the surface of Env or possibly in shielding water molecules from interacting with the charged residues of the GDIR motif, thus enabling D106 to interact with this linear motif instead. Alternatively, the charged D106 residue may be important for electrostatic interactions with the polar GDIR motif. From the cryo-EM structure, the FWRH1-CDRH1 region is adjacent to the conserved N301 glycan, highlighting this interaction as a possible driver of neutralization breadth. It’s possible that the N332 glycan required for neutralization may have served as the initial anchor for the QA013.2 lineage and subsequent affinity maturation to accommodate and interact with N301 promoted neutralization breadth as has been previously reported for sialic acid-bearing glycans and VRC01-class bnAbs ( Andrabi et al., 2017 ; Umotoy et al., 2019 , p. 01). These findings may inform future immunogen design aimed at eliciting V3-specific bnAbs as they illuminate structural regions of the bnAb paratope that may promote neutralization breadth and increased potency when modified appropriately. Download figure Open in new tab Figure 8: Summary of QA013.2 determinants of HIV neutralization breadth, potency, and autologous neutralization. Ribbon structure of QA013.2 Fab variable domain complexed to BG505.SOSIP.664 trimer in two different orientations are shown. Env structure is colored in blue with protruding glycans at sites N301 and N332 shown as stick models, Fab heavy chain in orange, and Fab light chain in green. Key regions of the Fab structure that confer breadth (yellow) or potency (pink) are labeled and colored categorically. Teal colored regions (CDRH2 and FWRH3) confer autologous neutralization. Important Env epitopes of interaction such as the linear GDIR motif and V1 loop are also labeled. See also Figure 8 – figure supplement 1 . The ability of HIV to escape recognition by neutralizing antibodies in vivo is well documented ( Bonsignori et al., 2017b , pp. 10–10; Caskey et al., 2017 , pp. 10–1074; Klein et al., 2012 ; Scheid et al., 2016 ; Wei et al., 2003 ; Wibmer et al., 2013 ) and can be comprehensively measured using antigenic profiling with a library of all possible amino acid mutations across HIV Env ( Dingens et al., 2019 , 2017 ). Using this technique, we found that QA013.2 elicited viral escape mutations throughout the V3 loop of Env. Unlike V3-bnAbs BF520.1 and 10-1074 that have more focused escape signatures concentrated on a handful of sites within V3, QA013.2 elicited escape mutations from more sites across this variable region of Env ( Dingens et al., 2019 ). Selection for escape mutations was strongest at sites D325, N332, and S334, which supports the documented viral escape that occurred in this patient in vivo , resulting in an observed glycan shift from site N332 to N334 ( Williams et al., 2018 ). Moreover, these data highlight the functional importance of the GDIR motif residues in mediating bnAb binding via the CDRH3. QA013.2 also selected for escape mutations outside of V3, in nearby V1 at sites 141 and 151, which are separated by a single residue in BG505 Env due to a shorter V1 loop relative to the reference strain. While we do not observe direct interaction between the Fab and Env V1 loop based on our cryo-EM structure, the main chain of the CDRH3 loop is in close proximity to the V1 loop, suggesting possible side chain electrostatic interactions between residues comprising the two regions. In vivo data have demonstrated evidence of V1-mediated escape from members of the DH270 antibody lineage and structural studies of the PGT121 family of bnAbs and BG18 have demonstrated that these antibodies interact with residues and glycans in this region ( Barnes et al., 2018 ; Bonsignori et al., 2017a ; Garces et al., 2015 ). Moreover, there is evidence supporting an inverse correlation between V1 loop length and bnAb breadth ( Barnes et al., 2018 ; Bonsignori et al., 2017a ; Fera et al., 2018 ; Liu et al., 2011 ; Rusert et al., 2011 ; Saunders et al., 2019 ). There are also data supporting a relationship between V1/V2 and V3, in which mutations in V1/V2 were shown to influence the ‘flickering’ of V3 between occluded and available conformational states ( Powell et al., 2017 ; Zolla-Pazner et al., 2016 ). Together, these data suggest that immunogens with a relatively short (≤ 28 residues) V1 loop comprised of polar residues at sites 141 and 151 may stimulate a similar neutralization profile to that of QA013.2. It is also possible that immunogens with even shorter V1 loops than studied here (≤ 18 residues) may inhibit the electrostatic interactions we hypothesize for QA013.2 and prevent the possibility of viral escape in this region, likely leading to increased breadth. Collectively, our study reveals several features of V3-specific bnAb development in a case of HIV superinfection. These include paratope differences for autologous and heterologous neutralization as well as non-overlapping determinants of neutralization breadth and potency providing a potential mechanism by which distinct genetically diverse immunogens contribute to such results. In addition, our data highlight features of the conformation-dependent V3 epitope that could be valuable for immunogen design, including short V1 regions and accommodation of the conserved glycan at N301 as a potential driver of neutralization breadth. Designing immunogens that lack nearby obstructive Env features may influence nAb accommodation of N301 and drive subsequent breadth as has been shown previously for a VRC01-class bnAb and the N276 glycan ( Umotoy et al., 2019 , p. 01). In summary, our findings suggest a strategy that promotes immunogen recognition via conserved V-gene features and stimulation of framework substitutions in order to elicit potent and broad neutralizing antibodies targeting the V3 supersite of vulnerability. Methods Human Subjects Peripheral blood mononuclear cell (PBMC) samples were collected between 1994-1997 from female subject QA013 at various times pre- and post-HIV infection. QA013 was enrolled in a prospective cohort of HIV negative, high-risk women in Mombasa, Kenya and was 30 years old at the time of her enrollment in 1993 (Martin, Jr. et al., 1998). During the study, QA013 seroconverted following initial infection with a clade D virus (1995), and was subsequently superinfected with a clade A virus between 265 and 385 days post initial infection ( Chohan et al., 2005 ). Study participants were treated according to Kenyan National Guidelines and did not receive any antiretroviral treatment during the time period in which the samples used in this study were collected. Antiretroviral therapy was offered as of March 2004, with support from the President’s Emergency Plan for AIDS Relief. This study was approved by members of the ethical review committees at the University of Nairobi, the Fred Hutchinson Cancer Research Center, and the University of Washington. Study participants provided written informed consent prior to enrollment. RNA Isolation, Library Preparation, and Full Length Antibody Gene Deep Sequencing Four longitudinal PBMC samples from 379 days pre-HIV infection (D-379), D-351, 385 days post initial infection (D385), and D765 were thawed in a 37°C water bath, diluted 10-fold in RPMI, and pelleted at 300 x g for 10 min. Cell pellets were washed with 1X phosphate-buffered saline (PBS), counted using trypan blue solution, centrifuged, and then total RNA was extracted using the AllPrep DNA/RNA Mini Kit (Qiagen, Germantown, MD) according to the manufacturer’s protocol. Isolated RNA was stored at −80°C. Antibody sequencing was performed as previously described ( Simonich et al., 2019 ; Vigdorovich et al., 2016 ) using the SMARTer RACE 5’/3’ Kit (Takara Bio USA Inc., Mountainview, CA). Briefly, RACE-ready cDNA synthesis was performed using primers specific for IgM, IgG, IgK, and IgL as previously described ( Simonich et al., 2019 ). We used molecular barcoding to eliminate errors introduced during library preparation and sequencing, which facilitated accurate measurement of genetic diversity and improved ancestral sequence reconstruction. Template switch adaptor primers that included unique molecular identifiers were used in the cDNA synthesis step: SmartNNNa 5’ AAGCAGUGGTAUCAACGCAGAGUNNNNUNNNNUNNNNUCTTrGrGrGrGrG 3’ ( Turchaninova et al., 2016 ), where ‘rG’ indicates ribonucleoside guanosine bases. Following synthesis, cDNA was diluted in 10mM Tricine-EDTA according to the manufacturer’s recommended protocol. First-round PCR of 14 cycles was performed using Q5 High-Fidelity Master Mix (New England BioLabs, Ipswich, MA) and nested gene-specific primers at 20 μM. First-round amplicons were used as templates for second-round PCR amplification (6 cycles), which added MiSeq adaptors. Second-round products were gel purified and indexed using Nextera XT P5 and P7 indices (Illumina, San Diego, CA). Gel-purified indexed libraries were quantified using the KAPA library quantification kit (Kapa Biosystems, Wilmington, MA) using an Applied Biosystems 7500 real-time PCR machine. Libraries were denatured and loaded onto an Illumina MiSeq using 600-cycle V3 cartridges, according to the manufacturer’s instructions. Sequence Analysis and Clonal Family Clustering Following next-generation sequencing, sequence reads were pre-processed into amplicons using FLASH, primers were trimmed using cutadapt, and the FASTX-toolkit was used to remove sequence reads containing low-confidence base calls (N’s) as previously described ( Simonich et al., 2019 ; Vigdorovich et al., 2016 ). Sequence reads from each timepoint were merged together into an aggregate dataset that was deduplicated and annotated using partis ( https://github.com/psathyrella/partis ) with default settings. Sequences that were out of frame or contained internal stop codons were removed, while singletons, or sequences that were observed only once in the sampled repertoire, were included in an attempt to retain undersampled or rare sequences. Sequencing statistics for this study can be found in Table 1 . Clonal family clustering was performed on both individual timepoint and aggregated datasets using both partis seeded and unseeded clustering methods ( Ralph and Matsen, 2016 ). The seeded method extracts all sequences that are clonally related to a particular ‘seed’ sequence of interest. The ‘seeds’ here refer to the previously-isolated QA013.2 VH and VL sequences ( Williams et al., 2018 ). Unseeded clustering, on the other hand, clusters all sequences in the repertoire into clonal families. Since this is more computationally demanding, some of the very large datasets were subsampled down to 50-150k sequences. Three random subsamples were analyzed and compared in order to measure statistical uncertainties. No subsampling was done for the seeded analyses. Because the light chain has much lower diversity than the heavy chain, and because B cells proliferate after successful heavy chain rearrangement but before light chain rearrangement, light chain clustering without heavy/light chain pairing information inevitably incorrectly clusters together many different light chain families. This overclustering artificially inflates the number of sequences in the clonal family, resulting in most inferred light chain families containing sequences stemming from several different light chain rearrangements. Naïve Inference and Lineage Reconstruction The light chain family resulting from clonal family clustering was very large (1158 members), and because this apparent family was likely composed of sequences from several different light chain rearrangements, each of which are likely confined to separate lineages, a pruning procedure was performed based on phylogenetic relatedness to the QA013.2 antibody chain using FastTree 2 ( Price et al., 2010 ). This resulted in the light chain clonal family being reduced to the most relevant 100 sequences ( https://github.com/matsengrp/cft/blob/master/bin/prune.py ). The VH clonal family did not undergo any such pruning as it contained fewer than 100 sequences (note that the tenfold different in size between VH and VL clonal families is itself strong evidence for overclustering). The heavy and pruned light chain clonal families were then analyzed with linearham ( https://github.com/matsengrp/linearham ), a phylogenetic hidden Markov model that accounts for both VDJ recombination and SHM when inferring ancestral sequences including the naïve B cell receptor (BCR) ( Dhar et al., 2020 ). Partis software also infers the unmutated common ancestor, or naïve sequence, however the version of partis used here assumed a balanced, star-like clonal family tree architecture, and the alternative naïve sequences it returns are not based on a rigorous probabilistic model (current versions of partis no longer assume star-like phylogenies). Linearham is thus more accurate for trees, and also returns proper uncertainty estimates, because it samples naïve sequences from their posterior distribution and accounts for uncertainty in the naïve rearrangement process. As part of the linearham package, RevBayes ( Höhna et al., 2016 ) was run using an unrooted tree model with the general time-reversible (GTR) substitution model. Each RevBayes run had customized settings to ensure that likelihood and posterior estimated sample sizes were >100 for the heavy and light chain lineages. For both VH and VL lineage inference, MCMC iterations were 100,000 with a thinning frequency of 100 iterations and 10,000 burn-in samples. Linearham generates summary graphics following phylogenetic inference that display only the edges that satisfy the given posterior probability threshold, and only the nodes that contact edges above the threshold. These graphics detail the relative confidence in unique inferred sequences and amino acid substitutions ( Fig. 1 and Fig. 1 – figure supplement 2 ). Inferred intermediate sequences present in the most probable lineage paths were selected for study (see Figure 1 ). Identification of Lineage-representative NGS Sequences To determine whether the computationally-inferred naïve and intermediate ancestor sequences for VH and VL lineages were observed in the sampled NGS sequences, we ran the following script: https://github.com/matsengrp/cft/blob/master/bin/blast.py . A local BLAST database was created for the two seeded clonal families and queried for sampled NGS sequences that had high nucleotide sequence identity to each of the VH and VL lineage members using the ‘blastn’ command (Biopython package). E-value of 0.001 was used; other settings were default. Blastn “hits” for each lineage member were sorted according to their percent nucleotide identity and alignment length. Percent nucleotide identity of the top blastn “hit” for each lineage member is listed in Figure 1 . Monoclonal Antibody Generation and Mutagenesis Antibody heavy and light chain sequences were synthesized as “fragmentGENES” by Genewiz (GENEWIZ®, South Plainfield, NJ) or gene blocks by Integrated DNA Technologies (IDT, Coralville, IA) and cloned into IgG1 and IgL vectors as previously described ( Williams et al., 2015 ). Human embryonic kidney (HEK) 293-F cells (RRID:CVCL_D603; Thermo Fisher Scientific, Waltham, MA, catalog #R790-07) were transfected with equal amounts of heavy and light chain plasmid DNA using the Freestyle Max transfection system (Thermo Fischer Scientific, catalog #16447100) according to the manufacturer’s instructions. Transfections proceeded at 37°C with 8% CO 2 in baffled-bottom flasks, rotating at 135 rpm and were harvested after 3-6 days. Supernatants were collected following centrifugation of cells at 1,900 rpm for 10 minutes. Antibody supernatants were passed three times over columns packed with immobilized Protein G resin (Thermo Fisher, catalog #20397) as previously described ( Scherer et al., 2014 ). Antibody chimeras were synthesized as fragmentGENES as shown in Fig. 4A , while VH mutagenesis ( Fig. 5 ) was performed using phosphorylated primers (25 μM) that introduced the mutation of interest into the variable heavy chain, using mature QA013.2 VH DNA in the IgG1 plasmid as a template (2.5 ng/μL). PCR-mediated mutagenesis was performed using Phusion Hi Fidelity polymerase (Thermo Fisher Scientific) with the following thermocycler settings: denature at 98°C for 1 min, 30 cycles of 98°C for 30 sec, annealing at 55-70°C for 30 sec, extension at 72°C for 5 min, and final extension at 72°C for 10 min. PCR products were digested with DpnI (New England BioLabs) overnight at 37°C and purified using Qiagen PCR Purification kit, with products eluted in ddH 2 0. Mutants were ligated at room temperature for at least two hours prior to transformation into One Shot™ TOP10 chemically competent cells (Thermo Fisher Scientific). Mutant antibody chains were sequence-confirmed prior to transfection and antibody purification as described above. Pseudovirus Production and TZM-bl Neutralization Assay HIV pseudovirus (PSV) was produced in HEK 293-T cells (ATCC®, Manassas, VA, CRL-3216™) and used in TZM-bl neutralization assays as previously described ( Goo et al., 2012 ). Briefly, monoclonal antibodies were incubated with PSV at 37°C for one hour and TZM-bl cells (obtained through the NIH AIDS Reagent Program, Germantown, MD, catalog #8129 from Dr. John C. Kappes, and Dr. Xiaoyun Wu) were added at 10,000 cells/well and the assay was harvested after 48 hours at 37°C by adding Gal-Screen substrate (Thermo Fisher Scientific, catalog #T1028) as previously described ( Simonich et al., 2019 ). IC 50 values represent the half maximal inhibitory concentration in ug mL -1 at which 50% of the virus was neutralized. All neutralization data are the average of at least two independent experiments, each performed in technical duplicate (see Figures 2 , 4 - 7 – Neut Source Data 1 ). IC 50 values that deviated from the technical replicates by >10-fold were excluded as outliers from the average IC 50 calculation. Biolayer Interferometry QA013 monoclonal antibody binding was measured using biolayer interferometry on an Octet RED instrument (Forte Bio, Fremont, CA). All antibodies were diluted to 10 μg mL -1 in a 0.22 μm filtered binding buffer solution composed of 1X PBS, 0.1% bovine serum albumin, 0.005% Tween-20, and 0.02% sodium azide. Antibodies were immobilized onto anti-human IgG Fc capture biosensors (Forte Bio) and dipped into analyte solution of several different antigens as detailed in the text ( Fig. 2 and 4 - 6 ): autologous gp120 monomers from the initial infecting virus Env (clade D) at 2 μM, the superinfecting virus variant from 765 days post initial infection (clade A) at 2 μM, heterologous BG505.SOSIP.664 Env trimer containing the N332 glycan (clade A) at 500 nM, or wildtype BG505.W6.C1 gp120 monomer at 2 μM. Antigens were diluted to their respective starting concentrations in the same buffer as above and a series of six, two-fold dilutions were tested as analyte in solution at a shake speed of 600 rpm at 23°C. The kinetics of mAb binding were measured as follows: association was monitored for 180 sec, dissociation was monitored for 180 sec, and regeneration was performed in 10mM Glycine HCl (pH 1.5, GE Healthcare, Chicago, IL, BR-1003-54). Binding-affinity constants (K D ; on-rate, k on ; off-rate, k dis ) were calculated using ForteBio’s Data Analysis Software 7.0. Responses (nanometer shift) were calculated using data that were double reference subtracted using reference wells and non-specific binding of biosensor to analyte. Data were processed by Savitzky-Golay filtering, prior to fitting using a 1:1 model of binding kinetics. Prism v9.0 (GraphPad, San Diego, CA) was used to plot both the processed data (following double reference subtraction) and fit data (after global analysis) of each antibody + antigen combination. Each biolayer interferometry experiment presented in this study was performed a minimum of two independent times, each time using freshly diluted antibodies in binding buffer (see Figures 2 , 4 - 6 – BLI Source Data 1 and 2 ). Both QA013 gp120 monomers were synthesized as custom proteins through Cambridge Biologics (Brookline, MA). BG505.SOSIP.664 trimer was expressed and purified as previously described ( Verkerke et al., 2016 ) and the BG505.W6.C1 gp120 protein was ordered through Immune-Tech (Immune Technology Corp., New York, NY, IT-001-176p). Cryo-EM Purified BG505.SOSIP.664 trimers were mixed with three-fold molar excess of QA013.2 Fab (fragment antigen binding) in 1X PBS at pH 7.4. The mixture was diluted with PBS to approximately 0.04 mg/mL final protein concentration and incubated for 45 minutes on ice. Lacey grids with a thin continuous carbon film (400 mesh) (Electron Microscopy Sciences, Hatfield, PA) were glow discharged (negative charge) under vacuum using 20-25 mA current for 30 seconds. A 3.0 μL aliquot of sample was applied to these grids at 4°C and 100% humidity, blotted for 3.5 seconds and immediately plunge frozen in liquid ethane using a Vitrobot Mark IV specimen preparation unit (FEI Company, Hillsboro, OR). Vitrified grids were imaged using an FEI Titan Krios operating at 300 keV equipped with a Gatan K2 summit direct detector and a post-specimen energy filter. Micrographs were collected at 105,000X magnification with a pixel size of 1.35 Å per pixel in counting mode. Each image received a dose rate of ∼8 e − /pixel/s with 200 ms exposure per frame and 50 frames per image collected. Estimated defocus ranged from 1.7 to 3.5 μm. Data were collected in two separate sessions with a total of 6,475 micrographs using the automated data collection software Leginon ( Carragher et al., 2000 ). All data processing steps were performed within the Relion (version 3.0.7) software setup ( Scheres, 2012 ). Frame alignment and dose-weighting were performed using MotionCor2 ( Zheng et al., 2017 ), and CTF estimation was done using CTFFIND4 ( Rohou and Grigorieff, 2015 ). Further processing was continued with Relion. A total of 1,082,742 particles were picked using the LOG-based automatic particle picking routine. The particles were initially extracted at 4x binning with a pixel size of 10.8Å/pixel. The binned particle stack was subjected to two rounds of unsupervised 2D classification, out of which classes that clearly showed SOSIPs with three Fabs bound were selected. A total of 113,470 particles from these classes were used for 3D refinement. The previously published negative stain reconstruction of BG505.SOSIP.664 complexed to QA013.2 Fab (EMD-7471) was used as an initial model ( Williams et al., 2018 ). The initial model was low-pass filtered to 60 Å and refinement was performed on the full particle stack with C3 symmetry imposed. Subsequent map sharpening and post processing in Relion resulted in a 4.186 Å structure using the “gold-standard” FSC cutoff of 0.143. The unbinned particle stack was further subjected to CTF-refinement at per micrograph level which improved the map to its final resolution of 4.15 Å ( Fig. 3 – figure supplement 2 ). The atomic model of BG505.SOSIP.664 trimer (PDB ID: 5ACO) ( Lee et al., 2015 ) was rigid body fitted into the 4.18 Å resolution map using UCSF Chimera ( Pettersen et al., 2004 ). No further modification to the SOSIP model was performed as the atomic model agreed well with the map. In the cryo-EM map, the variable region of the Fab domain was well-resolved with separation in beta-sheets observable, but the constant domain of the Fab was only partially resolved. Thus, a QA013.2 Fab model consisting of only its variable heavy and light chains was generated using the SWISS model software ( Waterhouse et al., 2018 , p.). Five different models for QA013.2 Fab variable domain model were computationally generated using available PDB structure templates. All five models were comparable when superposed onto one another, except for the orientation of the variable CDRH3 loop. The Fab model generated by homology modeling with the crystal structure of an infant antibody ADI 19425 (PDB ID:6apc) (sequence identity of 71.18% and 0.97 coverage) was selected as the final model for further analysis. The cryo-EM map was sharpened with BG505.SOSIP.664 atomic model (PDB ID:5ACO) input using the Autosharpen program ( Terwilliger et al., 2018 ) in the Phenix software suite ( Liebschner et al., 2019 ), in order to enhance features in the Fab density. The QA013.2 Fab model was then computationally docked into the map using ‘Dock In Map’ program in the Phenix software suite ( Liebschner et al., 2019 ). The SOSIP+Fab model was then refined using Realspace Refinement in the Phenix package using reference model restraints from a high resolution atomic model of BG505.SOSIP.664 (PDB ID:6mu6) ( Liebschner et al., 2019 ). The data collection, refinement parameters and final model statistics are summarized in Figure 3 – Source Data 1 , and the cryo-EM map and coordinates are included in Figure 3 – Source Data 2. Mutational Antigenic Profiling Mutational antigenic profiling was performed as previously described ( Dingens et al., 2017 ). Briefly, 0.5-1.0×10 6 TZM-bl infectious units of independent BG505.W6.C2 T332N mutant proviral DNA libraries ( Haddox et al., 2018 ) were incubated with the QA013.2 bnAb at ≥ IC 95 concentration for one hour. One million SupT1.CCR5 cells were then infected with these mutant libraries in the presence of 100 μg/mL DEAE-dextran. In parallel to QA013.2 antibody selection, each mutant virus library was also infected into 1×10 6 SupT1.CCR5 cells without antibody selection to serve as the non-selected control. Non-integrated viral DNA was isolated from each pool of infected cells at 12 hours post infection using a Qiagen Miniprep kit. The env gene was amplified from each sample (selected and non-selected) using a barcoded subamplicon sequencing approach that generates seven tiling subamplicons across env as previously described ( Haddox et al., 2018 ). These pools of amplicons were then deep sequenced on an Illumina HiSeq using 250 bp paired-end reads. Following deep sequencing, differential selection values were calculated as described in Doud et al. ( Doud et al., 2017 ). This included calculating the enrichment of each amino acid at individual sites relative to the wild-type by comparing the mutation counts of each residue in the antibody selected sample to the mock treated sample. Percent infectivity and correlation values between replicates are provided as Fig. 7 – figure supplement 1 . We took the median values across all experimental replicates and visualized the differential selection data on logoplots rendered by dms_tools2 using weblogo ( Crooks, 2004 ). Throughout this manuscript, we focused only on positively enriched mutations. To validate the mutational antigenic profiling data, TZM-bl neutralization assays were performed using BG505.T332N pseudoviruses bearing single point mutants representing residues that were enriched for viral escape at individual sites across Env . TZM-bl neutralization assays were performed as described above in at least two independent assays, each performed in technical duplicate (see Figures 2 , 4 - 7 – Neut Source Data 1 ). The fold change in IC 50 of each point mutant relative to BG505.T332N wild-type pseudovirus was calculated independently for each experiment and then averaged across all replicates. Figure Generation Portions of figures 1 - 2 and 4 - 6 were generated using Biorender.com. All figure panels were compiled using Adobe Illustrator. Data and Code Availability Longitudinal antibody gene sequencing data of QA013’s B cell repertoire can be found at BioProject SRA, accession PRJNA674442. The EM map and atomic coordinates for QA013.2 complexed to BG505.SOSIP.664 are deposited under accession codes EMD-XXXX and PDB XXXX. The computationally-inferred antibody variable region sequences, chimeras, and mutant antibody chains produced in this study have not been deposited into GenBank because computationally-generated sequences are not accepted, but they are available in Supplemental Files 1 and 3 . Mature QA013.2 antibody chain GenBank accession numbers are MH003558.1 (VH) and MH003564.1 (VL). GenBank accession numbers for HIV Env variants used in this study are MG992347 (QA013.70I.H1), MG992331 (QA013.765M.C1), DQ208458.1 (BG505.W6.C2), EU123924 (SF162), and FJ866133 (QC406.70M.F3). The open-source software used in this study is publicly available on GitHub: partis ( https://github.com/psathyrella/partis ), pruning of clonal family sequences ( https://github.com/matsengrp/cft/blob/master/bin/prune.py ), linearham ( https://github.com/matsengrp/linearham ), and Blast validation ( https://github.com/matsengrp/cft/blob/master/bin/blast.py ). The specific commands and run logs for the lineage analysis can be found at https://zenodo.org under the digital object identifier (DOI) 10.5281/zenodo.4574672. Open-source software to analyze mutational antigenic profiling datasets is available at https://jbloomlab.github.io/dms_tools2/ . Competing Interests The authors declare no conflicts of interest. Supplemental Figures Download figure Open in new tab Figure 1 – figure supplement 1: Phylogenetic relationship of sampled QA013.2 heavy and light chain clonal family sequences from four longitudinal PBMC samples. A) Maximum-likelihood (ML) tree of the 42 sampled clonal family sequences for QA013.2 heavy chain colored by NGS timepoint. B) ML tree of the pruned clonal family containing 100 sequences for QA013.2 light chain colored by NGS timepoint. Nodes on each tree represent ancestral sequences that have been computationally inferred using the tool linearham ( https://github.com/matsengrp/linearham ) ( Dhar et al., 2020 ). ML clonal family trees were visualized using Olmsted ( https://github.com/matsengrp/olmsted ). Tree branch width depicts the local branching index (lbi) ( Neher et al., 2014 ). The x-axis depicts the number of nucleotide substitutions per site relative to the inferred naïve for each antibody chain. Download figure Open in new tab Figure 1 – figure supplement 2: Linearham lineage trajectory graphics of QA013.2 A) VH and B) VL inferred lineage members from naïve to mature. Nodes represent inferred ancestral sequences, while arrows in between each node represent amino acid transitions. The red shading of nodes is proportional to the posterior probability that this ancestral sequence was present in the true lineage, and these probability values are listed in each node following each inferred intermediate (i.e. intermediate_x_probability). The VH lineage was analyzed using 0.04 probability cutoff such that any edge with probability less than this threshold was discarded. The VL lineage used a probability cutoff of 0.08. Since low probability nodes were filtered out, there are some incomplete pathways within the graphics. For each given node, the blue shading of arrows arising from that node is proportional to the posterior probability of the associated amino acid sequence transition. Lineage members have been renamed for clarity in the main text and numbers listed here do not correspond with those in the main text. Refer to Figure 1 for lineage intermediate numbering scheme. Download figure Open in new tab Figure 1 – figure supplement 3: Partis clonal family cluster for QA013.2 clonal family containing VH sequences sampled from QA013 over four longitudinal timepoints. Partis software was run on the aggregated IgG NGS dataset from QA013 using the ‘seeded’ method (see Methods section) where QA013.2 variable heavy (VH) chain was the seed sequence of interest. These clonal family clustering data demonstrate shared mutations of sampled VH sequences from pre-HIV infection (dm379 and dm351) with the QA013.2 mature bnAb VH sequence. The red nucleotides represent mutated bases relative to the inferred naïve, with germline sequences listed at the top of the alignment. Supplemental File 1: Fasta file of all computationally-inferred QA013.2 lineage members. Sequence file includes inferred naïves, computationally-inferred lineage intermediates, and mature sequences for both VH and VL lineages. Supplemental File 2: Fasta file of sampled NGS sequences with high percent identity to computationally-inferred lineage members. Sequence file includes sampled NGS sequences with the highest nucleotide identity to all QA013.2 inferred lineage members and mature sequences. Supplemental File 3: Fasta file of all QA013.2 VH and VL chimeras and mutant variants. Sequence file includes all VH and VL chimeras (presented in Figures 4 and 6 ), and VH mutants (presented in Figure 5 ) generated to interrogate QA013.2 functional evolution in this study. Download figure Open in new tab Figure 2 – figure supplement 1: QA013.2 inferred naïve antibody binding to initial infecting virus Env-gp120 monomer. Biolayer interferometry kinetic curve of inferred naïve antibody (10 μg mL -1 ) bound to autologous clade D Env-gp120 monomer from the initial virus (2 μM). BLI curves were subjected to double reference background subtraction and data were fit to a global model of 1:1 ligand:analyte binding to obtain K D , k on , and k dis values. Dotted line across the graph marks 0.00 on the y-axis. Data are representative of two independent experiments. Download figure Open in new tab Figure 3 – Source Data 1: BG505.SOSIP + QA013.2 Fab cryo-EM data collection, refinement parameters, and model statistics. Download figure Open in new tab Figure 3 – figure supplement 1: Cryo-EM features of QA013.2 Fab heavy chain. A) Left: Ribbon diagram of Fab QA013.2. Light chain in green and heavy chain in orange. Right: Electrostatic coulombic surface coloring of QA013.2 Fab. Red areas indicate negative charge, blue areas indicate positive charge and white areas indicate non-polar regions. B) QA013.2 Fab exhibits common quaternary architecture to other V3-specific bNAbs. Ribbon diagram of QA013.2 Fab model, crystal structure of Fab PGT121(PDB ID: 4FQ1), and crystal structure of Fab 10-1074 (PDB ID: 4FQ2). Heavy chains are colored in red and light chains in blue. Cleft formed between CDRH3 and the remainder of Fab heavy chain domain due to tilting toward the light chain is indicated by a black arrow ( Mouquet et al., 2012 ). Download figure Open in new tab Figure 3 – figure supplement 2: Fourier Shell Correlation curves. Lines representing correlation corrected (black), masked (blue), unmasked (green), and phase randomized (red) Fourier Shell correlation curve maps. Dashed line represents the “gold-standard” FSC cutoff of 0.143. Download figure Open in new tab Figure 7 – figure supplement 1: Correlation of positive site differential selection between mutational antigenic profiling replicates. For each replicate, the axes label the concentration of QA013.2 used, which mutant virus library was used, and the percent infectivity (based on qPCR). Download figure Open in new tab Figure 7 – figure supplement 2: Mature bnAb QA013.2 binding to gp120 monomers that lack the N332 glycan. A) Biolayer interferometry kinetic curve of mature bnAb QA013.2 (10 μg mL -1 ) bound to autologous clade D gp120 monomer from the initial virus (2 μM). B) Biolayer interferometry kinetic curve of mature bnAb QA013.2 (10 μg mL -1 ) bound to BG505.W6.C1 gp120 monomer (2 μM). BLI curves were subjected to double reference background subtraction and data were fit to a global model of 1:1 ligand:analyte binding to obtain K D , k on , and k dis values. The resulting lines of best fit are shown in green. Dotted line across the graph marks 0.00 on the y-axis. Data are representative of two independent experiments. Download figure Open in new tab Figure 8 – figure supplement 1: QA013.2 bnAb polyreactivity as measured by ELISA. Control antibodies were tested at 25 μg/mL in technical duplicate, in which VRC01 serves as a negative control ( Li et al., 2011 , p. 01) and NIH 45-46, 8ANC195, and 4E10 serve as positive controls ( Liu et al., 2015 ; Prigent et al., 2018 ). QA013.2 bnAb was tested in technical duplicate in a serial dilution series ranging from 25 μg/mL – 0.4 μg/mL. Tested antigens at 1 μg/mL include double-stranded DNA (dsDNA, blue), single-stranded DNA (ssDNA, light purple), lipopolysaccharide (LPS, pink), keyhole limpet (green), insulin (teal), and cardiolipin (dark purple) as previously described ( Wardemann, 2003 ). Acknowledgements We thank all of the participants, staff, Scott McClelland, and Ludo Lavreys for their continued involvement and contributions to the Mombasa cohort. We would like to acknowledge Vladimir Vigdorovich and D. Noah Sather for their technical assistance with NGS library preparation and sequence processing. This work was supported by NIH grants R01 AI140891 to J.D.B., R01 AI146028, U19 AI117891, and U19 AI128914 F.A.M., R01 AI140868 to K.K.L., and R01 AI138709 to J.O. J.D.B. is an investigator of the Howard Hughes Medical Institute. The research of Frederick Matsen was supported in part by a Faculty Scholar grant from the Howard Hughes Medical Institute and the Simons Foundation. References ↵ Abbott RK , Lee JH , Menis S , Skog P , Rossi M , Ota T , Kulp DW , Bhullar D , Kalyuzhniy O , Havenar-Daughton C , Schief WR , Nemazee D , Crotty S . 2018 . Precursor Frequency and Affinity Determine B Cell Competitive Fitness in Germinal Centers, Tested with Germline-Targeting HIV Vaccine Immunogens . Immunity 48 : 133 – 146 .e6. doi: 10.1016/j.immuni.2017.11.023 OpenUrl CrossRef PubMed ↵ Andrabi R , Bhiman JN , Burton DR . 2018 . Strategies for a multi-stage neutralizing antibody-based HIV vaccine . Current Opinion in Immunology 53 : 143 – 151 . doi: 10.1016/j.coi.2018.04.025 OpenUrl CrossRef PubMed ↵ Andrabi R , Su C-Y , Liang C-H , Shivatare SS , Briney B , Voss JE , Nawazi SK , Wu C-Y , Wong C-H , Burton DR . 2017 . Glycans Function as Anchors for Antibodies and Help Drive HIV Broadly Neutralizing Antibody Development . Immunity 47 : 524 – 537 .e3. doi: 10.1016/j.immuni.2017.08.006 OpenUrl CrossRef ↵ Barnes CO , Gristick HB , Freund NT , Escolano A , Lyubimov AY , Hartweger H , West AP , Cohen AE , Nussenzweig MC , Bjorkman PJ . 2018 . Structural characterization of a highly-potent V3-glycan broadly neutralizing antibody bound to natively-glycosylated HIV envelope . Nat Commun 9 : 1251 . doi: 10.1038/s41467-018-03632-y OpenUrl CrossRef PubMed ↵ Bar-On Y , Gruell H , Schoofs T , Pai JA , Nogueira L , Butler AL , Millard K , Lehmann C , Suárez I , Oliveira TY , Karagounis T , Cohen YZ , Wyen C , Scholten S , Handl L , Belblidia S , Dizon JP , Vehreschild JJ , Witmer-Pack M , Shimeliovich I , Jain K , Fiddike K , Seaton KE , Yates NL , Horowitz J , Gulick RM , Pfeifer N , Tomaras GD , Seaman MS , Fätkenheuer G , Caskey M , Klein F , Nussenzweig MC . 2018 . Safety and antiviral activity of combination HIV broadly neutralizing antibodies in viremic individuals . Nat Med 24 : 1701 – 1707 . doi: 10.1038/s41591-018-0186-4 OpenUrl CrossRef PubMed ↵ Bonsignori M , Kreider EF , Fera D , Meyerhoff RR , Bradley T , Wiehe K , Alam SM , Aussedat B , Walkowicz WE , Hwang K-K , Saunders KO , Zhang R , Gladden MA , Monroe A , Kumar A , Xia S-M , Cooper M , Louder MK , McKee K , Bailer RT , Pier BW , Jette CA , Kelsoe G , Williams WB , Morris L , Kappes J , Wagh K , Kamanga G , Cohen MS , Hraber PT , Montefiori DC , Trama A , Liao H-X , Kepler TB , Moody MA , Gao F , Danishefsky SJ , Mascola JR , Shaw GM , Hahn BH , Harrison SC , Korber BT , Haynes BF . 2017a . Staged induction of HIV glycan–dependent broadly neutralizing antibodies . Sci Transl Med 9 : eaai7514 . doi: 10.1126/scitranslmed.aai7514 OpenUrl Abstract / FREE Full Text ↵ Bonsignori M , Liao H-X , Gao F , Williams WB , Alam SM , Montefiori DC , Haynes BF . 2017b . Antibody-virus co-evolution in HIV infection: paths for HIV vaccine development . Immunol Rev 275 : 145 – 160 . doi: 10.1111/imr.12509 OpenUrl CrossRef PubMed ↵ Briney B , Sok D , Jardine JG , Kulp DW , Skog P , Menis S , Jacak R , Kalyuzhniy O , de Val N , Sesterhenn F , Le KM , Ramos A , Jones M , Saye-Francisco KL , Blane TR , Spencer S , Georgeson E , Hu X , Ozorowski G , Adachi Y , Kubitz M , Sarkar A , Wilson IA , Ward AB , Nemazee D , Burton DR , Schief WR . 2016 . Tailored Immunogens Direct Affinity Maturation toward HIV Neutralizing Antibodies . Cell 166 : 1459 – 1470 .e11. doi: 10.1016/j.cell.2016.08.005 OpenUrl CrossRef PubMed ↵ Burton DR , Hangartner L . 2016 . Broadly Neutralizing Antibodies to HIV and Their Role in Vaccine Design . Annual Review of Immunology 34 : 635 – 659 . doi: 10.1146/annurev-immunol-041015-055515 OpenUrl CrossRef PubMed ↵ Carragher B , Kisseberth N , Kriegman D , Milligan RA , Potter CS , Pulokas J , Reilein A . 2000 . Leginon: An Automated System for Acquisition of Images from Vitreous Ice Specimens . Journal of Structural Biology 132 : 33 – 45 . doi: 10.1006/jsbi.2000.4314 OpenUrl CrossRef PubMed Web of Science ↵ Caskey M , Schoofs T , Gruell H , Settler A , Karagounis T , Kreider EF , Murrell B , Pfeifer N , Nogueira L , Oliveira TY , Learn GH , Cohen YZ , Lehmann C , Gillor D , Shimeliovich I , Unson-O’Brien C , Weiland D , Robles A , Kümmerle T , Wyen C , Levin R , Witmer-Pack M , Eren K , Ignacio C , Kiss S , West AP , Mouquet H , Zingman BS , Gulick RM , Keler T , Bjorkman PJ , Seaman MS , Hahn BH , Fätkenheuer G , Schlesinger SJ , Nussenzweig MC , Klein F . 2017 . Antibody 10-1074 suppresses viremia in HIV-infected individuals . Nat Med 23 : 185 – 191 . doi: 10.1038/nm.4268 OpenUrl CrossRef PubMed ↵ Chohan B , Lavreys L , Rainwater SMJ , Overbaugh J . 2005 . Evidence for Frequent Reinfection with Human Immunodeficiency Virus Type 1 of a Different Subtype . Journal of Virology 79 : 10701 – 10708 . doi: 10.1128/JVI.79.16.10701-10708.2005 OpenUrl Abstract / FREE Full Text ↵ Cortez V , Odem-Davis K , McClelland RS , Jaoko W , Overbaugh J . 2012 . HIV Superinfection in Women Broadens and Strengthens the Neutralizing Antibody Response . PLoS Pathogens 8 : e1002611 . doi: 10.1371/journal.ppat.1002611 OpenUrl CrossRef PubMed ↵ Cortez V , Wang B , Dingens A , Chen MM , Ronen K , Georgiev IS , McClelland RS , Overbaugh J . 2015 . The Broad Neutralizing Antibody Responses after HIV Superinfection Are Not Dominated by Antibodies Directed to Epitopes Common in Single Infection . PLOS Pathogens 11 : e1004973 . doi: 10.1371/journal.ppat.1004973 OpenUrl CrossRef ↵ Crooks GE . 2004 . WebLogo: A Sequence Logo Generator . Genome Research 14 : 1188 – 1190 . doi: 10.1101/gr.849004 OpenUrl Abstract / FREE Full Text ↵ Demaison C , David D , Letourneur F , Thze J , Saragosti S , Zouali M. n.d. Analysis of human VH gene repertoire expression in peripheral CD19+ B cells 11 . ↵ Dhar A , Ralph DK , Minin VN , Matsen FA . 2020 . A Bayesian phylogenetic hidden Markov model for B cell receptor sequence analysis . PLoS Comput Biol 16 : e1008030 . doi: 10.1371/journal.pcbi.1008030 OpenUrl CrossRef ↵ Dingens AS , Arenz D , Weight H , Overbaugh J , Bloom JD . 2019 . An Antigenic Atlas of HIV Escape from Broadly Neutralizing Antibodies Distinguishes Functional and Structural Epitopes . Immunity 50 : 520 – 532 .e3. doi: 10.1016/j.immuni.2018.12.017 OpenUrl CrossRef PubMed ↵ Dingens AS , Haddox HK , Overbaugh J , Bloom JD . 2017 . Comprehensive Mapping of HIV Escape from a Broadly Neutralizing Antibody . Cell Host & Microbe 21 : 777 – 787 .e4. doi: 10.1016/j.chom.2017.05.003 OpenUrl CrossRef ↵ Doores KJ , Kong L , Krumm SA , Le KM , Sok D , Laserson U , Garces F , Poignard P , Wilson IA , Burton DR. 2015 . Two Classes of Broadly Neutralizing Antibodies within a Single Lineage Directed to the High-Mannose Patch of HIV Envelope . J Virol 89 : 1105 – 1118 . doi: 10.1128/JVI.02905-14 OpenUrl Abstract / FREE Full Text ↵ Doria-Rose NA . 2010 . HIV Neutralizing Antibodies: Clinical Correlates and Implications for Vaccines . J INFECT DIS 201 : 981 – 983 . doi: 10.1086/651143 OpenUrl CrossRef PubMed ↵ Doria-Rose NA , Bhiman JN , Roark RS , Schramm CA , Gorman J , Chuang G-Y , Pancera M , Cale EM , Ernandes MJ , Louder MK , Asokan M , Bailer RT , Druz A , Fraschilla IR , Garrett NJ , Jarosinski M , Lynch RM , McKee K , O’Dell S , Pegu A , Schmidt SD , Staupe RP , Sutton MS , Wang K , Wibmer CK , Haynes BF , Abdool-Karim S , Shapiro L , Kwong PD , Moore PL , Morris L , Mascola JR . 2016 . New Member of the V1V2-Directed CAP256-VRC26 Lineage That Shows Increased Breadth and Exceptional Potency . J Virol 90 : 76 – 91 . doi: 10.1128/JVI.01791-15 OpenUrl Abstract / FREE Full Text ↵ Doria-Rose NA , Joyce MG . 2015 . Strategies to guide the antibody affinity maturation process . Current Opinion in Virology 11 : 137 – 147 . doi: 10.1016/j.coviro.2015.04.002 OpenUrl CrossRef PubMed ↵ Doud MB , Hensley SE , Bloom JD . 2017 . Complete mapping of viral escape from neutralizing antibodies . PLoS Pathog 13 : e1006271 . doi: 10.1371/journal.ppat.1006271 OpenUrl CrossRef PubMed ↵ Fera D , Lee MS , Wiehe K , Meyerhoff RR , Piai A , Bonsignori M , Aussedat B , Walkowicz WE , Ton T , Zhou JO , Danishefsky S , Haynes BF , Harrison SC . 2018 . HIV envelope V3 region mimic embodies key features of a broadly neutralizing antibody lineage epitope . Nat Commun 9 : 1111 . doi: 10.1038/s41467-018-03565-6 OpenUrl CrossRef PubMed ↵ Freund NT , Wang H , Scharf L , Nogueira L , Horwitz JA , Bar-On Y , Golijanin J , Sievers SA , Sok D , Cai H , Cesar Lorenzi JC , Halper-Stromberg A , Toth I , Piechocka-Trocha A , Gristick HB , van Gils MJ , Sanders RW , Wang L-X , Seaman MS , Burton DR , Gazumyan A , Walker BD , West AP , Bjorkman PJ , Nussenzweig MC . 2017 . Coexistence of potent HIV broadly neutralizing antibodies and antibody-sensitive viruses in a viremic controller . Sci Transl Med 9 : eaal2144 . doi: 10.1126/scitranslmed.aal2144 OpenUrl Abstract / FREE Full Text ↵ Garces F , Lee JH , de Val N , Torrents de la Pena A , Kong L , Puchades C , Hua Y , Stanfield RL , Burton DR , Moore JP , Sanders RW , Ward AB , Wilson IA. 2015 . Affinity Maturation of a Potent Family of HIV Antibodies Is Primarily Focused on Accommodating or Avoiding Glycans . Immunity 43 : 1053 – 1063 . doi: 10.1016/j.immuni.2015.11.007 OpenUrl CrossRef PubMed ↵ Goo L , Milligan C , Simonich CA , Nduati R , Overbaugh J . 2012 . Neutralizing Antibody Escape during HIV Mother-to-Child Transmission Involves Conformational Masking of Distal Epitopes in Envelope . J Virol 86 : 9566 – 9582 . doi: 10.1128/JVI.00953-12 OpenUrl Abstract / FREE Full Text ↵ Haddox HK , Dingens AS , Hilton SK , Overbaugh J , Bloom JD . 2018 . Mapping mutational effects along the evolutionary landscape of HIV envelope . eLife 7 : e34420 . doi: 10.7554/eLife.34420 OpenUrl CrossRef PubMed ↵ Höhna S , Landis MJ , Heath TA , Boussau B , Lartillot N , Moore BR , Huelsenbeck JP , Ronquist F . 2016 . RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language . Syst Biol 65 : 726 – 736 . doi: 10.1093/sysbio/syw021 OpenUrl CrossRef PubMed ↵ Horns F , Vollmers C , Dekker CL , Quake SR . 2019 . Signatures of selection in the human antibody repertoire: Selective sweeps, competing subclones, and neutral drift . Proc Natl Acad Sci USA 116 : 1261 – 1266 . doi: 10.1073/pnas.1814213116 OpenUrl Abstract / FREE Full Text ↵ Julien J-P , Sok D , Khayat R , Lee JH , Doores KJ , Walker LM , Ramos A , Diwanji DC , Pejchal R , Cupo A , Katpally U , Depetris RS , Stanfield RL , McBride R , Marozsan AJ , Paulson JC , Sanders RW , Moore JP , Burton DR , Poignard P , Ward AB , Wilson IA . 2013 . Broadly Neutralizing Antibody PGT121 Allosterically Modulates CD4 Binding via Recognition of the HIV gp120 V3 Base and Multiple Surrounding Glycans . PLoS Pathog 9 : e1003342 . doi: 10.1371/journal.ppat.1003342 OpenUrl CrossRef PubMed ↵ Klein F , Diskin R , Scheid JF , Gaebler C , Mouquet H , Georgiev IS , Pancera M , Zhou T , Incesu R-B , Fu BZ , Gnanapragasam PNP , Oliveira TY , Seaman MS , Kwong PD , Bjorkman PJ , Nussenzweig MC . 2013 . Somatic Mutations of the Immunoglobulin Framework Are Generally Required for Broad and Potent HIV Neutralization . Cell 153 : 126 – 138 . doi: 10.1016/j.cell.2013.03.018 OpenUrl CrossRef PubMed Web of Science ↵ Klein F , Halper-Stromberg A , Horwitz JA , Gruell H , Scheid JF , Bournazos S , Mouquet H , Spatz LA , Diskin R , Abadir A , Zang T , Dorner M , Billerbeck E , Labitt RN , Gaebler C , Marcovecchio PM , Incesu R-B , Eisenreich TR , Bieniasz PD , Seaman MS , Bjorkman PJ , Ravetch JV , Ploss A , Nussenzweig MC . 2012 . HIV therapy by a combination of broadly neutralizing antibodies in humanized mice . Nature 492 : 118 – 122 . doi: 10.1038/nature11604 OpenUrl CrossRef PubMed Web of Science ↵ Kwong PD , Mascola JR . 2018 . HIV Vaccines Based on Antibody Identification, B Cell Ontogeny, and Epitope Structure . Immunity 48 : 855 – 871 . doi: 10.1016/j.immuni.2018.04.029 OpenUrl CrossRef PubMed ↵ Laserson U , Vigneault F , Gadala-Maria D , Yaari G , Uduman M , Vander Heiden JA , Kelton W , Taek Jung S , Liu Y , Laserson J , Chari R , Lee J-H , Bachelet I , Hickey B , Lieberman-Aiden E , Hanczaruk B , Simen BB , Egholm M , Koller D , Georgiou G , Kleinstein SH , Church GM . 2014 . High-resolution antibody dynamics of vaccine-induced immune responses . Proc Natl Acad Sci USA 111 : 4928 – 4933 . doi: 10.1073/pnas.1323862111 OpenUrl Abstract / FREE Full Text ↵ Lee JH , de Val N , Lyumkis D , Ward AB. 2015 . Model Building and Refinement of a Natively Glycosylated HIV Env Protein by High-Resolution Cryoelectron Microscopy . Structure 23 : 1943 – 1951 . doi: 10.1016/j.str.2015.07.020 OpenUrl CrossRef PubMed ↵ Li Y , O’Dell S , Walker LM , Wu X , Guenaga J , Feng Y , Schmidt SD , McKee K , Louder MK , Ledgerwood JE , Graham BS , Haynes BF , Burton DR , Wyatt RT , Mascola JR . 2011 . Mechanism of Neutralization by the Broadly Neutralizing HIV Monoclonal Antibody VRC01 . J VIROL 85 : 14 . OpenUrl ↵ Liebschner D , Afonine PV , Baker ML , Bunkóczi G , Chen VB , Croll TI , Hintze B , Hung L-W , Jain S , McCoy AJ , Moriarty NW , Oeffner RD , Poon BK , Prisant MG , Read RJ , Richardson JS , Richardson DC , Sammito MD , Sobolev OV , Stockwell DH , Terwilliger TC , Urzhumtsev AG , Videau LL , Williams CJ , Adams PD . 2019 . Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix . Acta Crystallogr D Struct Biol 75 : 861 – 877 . doi: 10.1107/S2059798319011471 OpenUrl CrossRef PubMed ↵ Liu L , Cimbro R , Lusso P , Berger EA. 2011 . Intraprotomer masking of third variable loop (V3) epitopes by the first and second variable loops (V1V2) within the native HIV envelope glycoprotein trimer . PNAS 6 . ↵ Liu M , Yang G , Wiehe K , Nicely NI , Vandergrift NA , Rountree W , Bonsignori M , Alam SM , Gao J , Haynes BF , Kelsoe G . 2015 . Polyreactivity and Autoreactivity among HIV Antibodies . J Virol 89 : 784 – 798 . doi: 10.1128/JVI.02378-14 OpenUrl Abstract / FREE Full Text ↵ MacLeod DT , Choi NM , Briney B , Garces F , Ver LS , Landais E , Murrell B , Wrin T , Kilembe W , Liang C-H , Ramos A , Bian CB , Wickramasinghe L , Kong L , Eren K , Wu C-Y , Wong C-H , Kosakovsky Pond SL , Wilson IA , Burton DR , Poignard P , Price MA , Gilmour J , Fast P , Kamali A , Sanders EJ , Anzala O , Allen S , Hunter E , Karita E , Kilembe W , Lakhi S , Inambao M , Edward V , Bekker L-G . 2016 . Early Antibody Lineage Diversification and Independent Limb Maturation Lead to Broad HIV Neutralization Targeting the Env High-Mannose Patch . Immunity 44 : 1215 – 1226 . doi: 10.1016/j.immuni.2016.04.016 OpenUrl CrossRef PubMed Martin , Jr. HL , Nyange PM , Richardson BA , Lavreys L , Mandaliya K , Jackson DJ , Ndinya-Achola JO , Kreiss J . 1998 . Hormonal Contraception, Sexually Transmitted Diseases, and Risk of Heterosexual Transmission of Human Immunodeficiency Virus Type 1 . The Journal of Infectious Diseases 178 : 1053 – 1059 . doi: 10.1086/515654 OpenUrl CrossRef PubMed Web of Science ↵ Mascola JR , Haynes BF . 2013 . HIV neutralizing antibodies: understanding nature’s pathways . Immunological Reviews 254 : 225 – 244 . doi: 10.1111/imr.12075 OpenUrl CrossRef PubMed ↵ Mendoza P , Gruell H , Nogueira L , Pai JA , Butler AL , Millard K , Lehmann C , Suárez I , Oliveira TY , Lorenzi JCC , Cohen YZ , Wyen C , Kümmerle T , Karagounis T , Lu C-L , Handl L , Unson-O’Brien C , Patel R , Ruping C , Schlotz M , Witmer-Pack M , Shimeliovich I , Kremer G , Thomas E , Seaton KE , Horowitz J , West AP , Bjorkman PJ , Tomaras GD , Gulick RM , Pfeifer N , Fätkenheuer G , Seaman MS , Klein F , Caskey M , Nussenzweig MC . 2018 . Combination therapy with anti-HIV antibodies maintains viral suppression . Nature 561 : 479 – 484 . doi: 10.1038/s41586-018-0531-2 OpenUrl CrossRef PubMed ↵ Mouquet H , Scharf L , Euler Z , Liu Y , Eden C , Scheid JF , Halper-Stromberg A , Gnanapragasam PNP , Spencer DIR , Seaman MS , Schuitemaker H , Feizi T , Nussenzweig MC , Bjorkman PJ . 2012 . Complex-type N-glycan recognition by potent broadly neutralizing HIV antibodies . Proceedings of the National Academy of Sciences 109 : E3268 – E3277 . doi: 10.1073/pnas.1217207109 OpenUrl Abstract / FREE Full Text ↵ N. Doria-Rose , Gorman J , Moore PL , Bhiman JN , DeKosky BJ , Ernandes MJ , Georgiev IS , Kim HJ , Pancera M , Staupe RP , Altae-Tran HR , Bailer RT , Crooks ET , Cupo A , Druz A , Garrett NJ , Hoi KH , Kong R , Louder MK , Longo NS , McKee K , Nonyane M , O’Dell S , Roark RS , Rudicell RS , Schmidt SD , Sheward DJ , Soto C , Wibmer CK , Yang Y , Zhang Z , Mullikin JC , Binley JM , Sanders RW , Wilson IA , Moore JP , Ward AB , Georgiou G , Williamson C , Abdool Karim SS , Morris L , Kwong PD , Shapiro L , Mascola JR . 2014 . Developmental pathway for potent V1V2-directed HIV-neutralizing antibodies . Nature 509 : 55 – 62 . doi: 10.1038/nature13036 OpenUrl CrossRef PubMed ↵ Neher RA , Russell CA , Shraiman BI . 2014 . Predicting evolution from the shape of genealogical trees . eLife 3 : e03568 . doi: 10.7554/eLife.03568 OpenUrl CrossRef ↵ Pegu A , Hessell AJ , Mascola JR , Haigwood NL . 2017 . Use of broadly neutralizing antibodies for HIV prevention . Immunol Rev 275 : 296 – 312 . doi: 10.1111/imr.12511 OpenUrl CrossRef PubMed ↵ Pejchal R , Doores KJ , Walker LM , Khayat R , Huang P-S , Wang S-K , Stanfield RL , Julien J-P , Ramos A , Crispin M , Depetris R , Katpally U , Marozsan A , Cupo A , Maloveste S , Liu Y , McBride R , Ito Y , Sanders RW , Ogohara C , Paulson JC , Feizi T , Scanlan CN , Wong C-H , Moore JP , Olson WC , Ward AB , Poignard P , Schief WR , Burton DR , Wilson IA . 2011 . A Potent and Broad Neutralizing Antibody Recognizes and Penetrates the HIV Glycan Shield . Science 334 : 1097 – 1103 . doi: 10.1126/science.1213256 OpenUrl Abstract / FREE Full Text ↵ Pettersen EF , Goddard TD , Huang CC , Couch GS , Greenblatt DM , Meng EC , Ferrin TE . 2004 . UCSF Chimera--a visualization system for exploratory research and analysis . J Comput Chem 25 : 1605 – 1612 . doi: 10.1002/jcc.20084 OpenUrl CrossRef PubMed Web of Science ↵ Powell RLR , Kinge T , Nyambi PN . 2010 . Infection by Discordant Strains of HIV Markedly Enhances the Neutralizing Antibody Response against Heterologous Virus . JVI 84 : 9415 – 9426 . doi: 10.1128/JVI.02732-09 OpenUrl Abstract / FREE Full Text ↵ Powell RLR , Totrov M , Itri V , Liu X , Fox A , Zolla-Pazner S . 2017 . Plasticity and Epitope Exposure of the HIV Envelope Trimer . J Virol 91 : e00410 – 17 , e00410-17. doi: 10.1128/JVI.00410-17 OpenUrl Abstract / FREE Full Text ↵ Price MN , Dehal PS , Arkin AP . 2010 . FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments . PLoS ONE 5 : e9490 . doi: 10.1371/journal.pone.0009490 OpenUrl CrossRef PubMed ↵ Prigent J , Jarossay A , Planchais C , Eden C , Dufloo J , Kök A , Lorin V , Vratskikh O , Couderc T , Bruel T , Schwartz O , Seaman MS , Ohlenschläger O , Dimitrov JD , Mouquet H . 2018 . Conformational Plasticity in Broadly Neutralizing HIV Antibodies Triggers Polyreactivity . Cell Reports 23 : 2568 – 2581 . doi: 10.1016/j.celrep.2018.04.101 OpenUrl CrossRef ↵ Ralph DK , Matsen FA . 2016 . Likelihood-Based Inference of B Cell Clonal Families . PLoS Comput Biol 12 : e1005086 . doi: 10.1371/journal.pcbi.1005086 OpenUrl CrossRef ↵ Rohou A , Grigorieff N . 2015 . CTFFIND4: Fast and accurate defocus estimation from electron micrographs . Journal of Structural Biology 192 : 216 – 221 . doi: 10.1016/j.jsb.2015.08.008 OpenUrl CrossRef PubMed ↵ Rusert P , Krarup A , Magnus C , Brandenberg OF , Weber J , Ehlert A-K , Regoes RR , Günthard HF , Trkola A . 2011 . Interaction of the gp120 V1V2 loop with a neighboring gp120 unit shields the HIV envelope trimer against cross-neutralizing antibodies . Journal of Experimental Medicine 208 : 15 . OpenUrl ↵ Saunders KO , Wiehe K , Tian M , Acharya P , Bradley T , Alam SM , Go EP , Scearce R , Sutherland L , Henderson R , Hsu AL , Borgnia MJ , Chen H , Lu X , Wu NR , Watts B , Jiang C , Easterhoff D , Cheng H-L , McGovern K , Waddicor P , Chapdelaine-Williams A , Eaton A , Zhang J , Rountree W , Verkoczy L , Tomai M , Lewis MG , Desaire HR , Edwards RJ , Cain DW , Bonsignori M , Montefiori D , Alt FW , Haynes BF. 2019 . Targeted selection of HIV-specific antibody mutations by engineering B cell maturation 19 . ↵ Scheid JF , Horwitz JA , Bar-On Y , Kreider EF , Lu C-L , Lorenzi JCC , Feldmann A , Braunschweig M , Nogueira L , Oliveira T , Shimeliovich I , Patel R , Burke L , Cohen YZ , Hadrigan S , Settler A , Witmer-Pack M , West , AP , Juelg B , Keler T , Hawthorne T , Zingman B , Gulick RM , Pfeifer N , Learn GH , Seaman MS , Bjorkman PJ , Klein F , Schlesinger SJ , Walker BD , Hahn BH , Nussenzweig MC , Caskey M . 2016 . HIV antibody 3BNC117 suppresses viral rebound in humans during treatment interruption . Nature 535 : 556 – 560 . doi: 10.1038/nature18929 OpenUrl CrossRef PubMed ↵ Scherer EM , Smith RA , Simonich CA , Niyonzima N , Carter JJ , Galloway DA . 2014 . Characteristics of Memory B Cells Elicited by a Highly Efficacious HPV Vaccine in Subjects with No Pre-existing Immunity . PLoS Pathog 10 : e1004461 . doi: 10.1371/journal.ppat.1004461 OpenUrl CrossRef PubMed ↵ Scheres SHW . 2012 . RELION: Implementation of a Bayesian approach to cryo-EM structure determination . Journal of Structural Biology 180 : 519 – 530 . doi: 10.1016/j.jsb.2012.09.006 OpenUrl CrossRef PubMed ↵ Sheward DJ , Marais J , Bekker V , Murrell B , Eren K , Bhiman JN , Nonyane M , Garrett N , Woodman ZL , Abdool Karim Q , Abdool Karim SS , Morris L , Moore PL , Williamson C . 2018 . HIV Superinfection Drives De Novo Antibody Responses and Not Neutralization Breadth . Cell Host & Microbe 24 : 593 – 599 .e3. doi: 10.1016/j.chom.2018.09.001 OpenUrl CrossRef PubMed ↵ Simonich CA , Doepker L , Ralph D , Williams JA , Dhar A , Yaffe Z , Gentles L , Small CT , Oliver B , Vigdorovich V , Mangala Prasad V , Nduati R , Sather DN , Lee KK , Matsen IV FA , Overbaugh J . 2019 . Kappa chain maturation helps drive rapid development of an infant HIV broadly neutralizing antibody lineage . Nat Commun 10 : 2190 . doi: 10.1038/s41467-019-09481-7 OpenUrl CrossRef ↵ Sok D , Pauthner M , Briney B , Lee JH , Saye-Francisco KL , Hsueh J , Ramos A , Le KM , Jones M , Jardine JG , Bastidas R , Sarkar A , Liang C-H , Shivatare SS , Wu C-Y , Schief WR , Wong C-H , Wilson IA , Ward AB , Zhu J , Poignard P , Burton DR. 2016 . A Prominent Site of Antibody Vulnerability on HIV Envelope Incorporates a Motif Associated with CCR5 Binding and Its Camouflaging Glycans . Immunity 45 : 31 – 45 . doi: 10.1016/j.immuni.2016.06.026 OpenUrl CrossRef PubMed ↵ Terwilliger TC , Sobolev OV , Afonine PV , Adams PD . 2018 . Automated map sharpening by maximization of detail and connectivity . Acta Crystallogr D Struct Biol 74 : 545 – 559 . doi: 10.1107/S2059798318004655 OpenUrl CrossRef PubMed ↵ Trkola A , Purtscher M , Muster T , Ballaun C , Buchacher A , Sullivan N , Srinivasan K , Sodroski J , Moore JP , Katinger H . 1996 . Human monoclonal antibody 2G12 defines a distinctive neutralization epitope on the gp120 glycoprotein of human immunodeficiency virus type 1 . Journal of virology 70 : 1100 – 1108 . doi: 10.1128/JVI.70.2.1100-1108.1996 OpenUrl Abstract / FREE Full Text ↵ Turchaninova MA , Davydov A , Britanova OV , Shugay M , Bikos V , Egorov ES , Kirgizova VI , Merzlyak EM , Staroverov DB , Bolotin DA , Mamedov IZ , Izraelson M , Logacheva MD , Kladova O , Plevova K , Pospisilova S , Chudakov DM . 2016 . High-quality full-length immunoglobulin profiling with unique molecular barcoding . Nat Protoc 11 : 1599 – 1616 . doi: 10.1038/nprot.2016.093 OpenUrl CrossRef PubMed ↵ Umotoy J , Bagaya BS , Joyce C , Schiffner T , Menis S , Saye-Francisco KL , Biddle T , Mohan S , Vollbrecht T , Kalyuzhniy O , Madzorera S , Kitchin D , Lambson B , Nonyane M , Kilembe W , Poignard P , Schief WR , Burton DR , Murrell B , Moore PL , Briney B , Sok D , Landais E . 2019 . Rapid and Focused Maturation of a VRC01-Class HIV Broadly Neutralizing Antibody Lineage Involves Both Binding and Accommodation of the N276-Glycan . Immunity 51 : 141 – 154 .e6. doi: 10.1016/j.immuni.2019.06.004 OpenUrl CrossRef ↵ Verkerke HP , Williams JA , Guttman M , Simonich CA , Liang Y , Filipavicius M , Hu S-L , Overbaugh J , Lee KK . 2016 . Epitope-Independent Purification of Native-Like Envelope Trimers from Diverse HIV Isolates . J Virol 90 : 9471 – 9482 . doi: 10.1128/JVI.01351-16 OpenUrl Abstract / FREE Full Text ↵ Vigdorovich V , Oliver BG , Carbonetti S , Dambrauskas N , Lange MD , Yacoob C , Leahy W , Callahan J , Stamatatos L , Sather DN . 2016 . Repertoire comparison of the B-cell receptor-encoding loci in humans and rhesus macaques by next-generation sequencing . Clin Trans Immunol 5 : e93 . doi: 10.1038/cti.2016.42 OpenUrl CrossRef ↵ Walker LM , Huber M , Doores KJ , Falkowska E , Pejchal R , Julien J-P , Wang S-K , Ramos A , Chan-Hui P-Y , Moyle M , Mitcham JL , Hammond PW , Olsen OA , Phung P , Fling S , Wong C-H , Phogat S , Wrin T , Simek MD , Principal Investigators PG , Koff WC , Wilson IA , Burton DR , Poignard P . 2011 . Broad neutralization coverage of HIV by multiple highly potent antibodies . Nature 477 : 466 – 470 . doi: 10.1038/nature10373 OpenUrl CrossRef PubMed Web of Science ↵ Wardemann H . 2003 . Predominant Autoantibody Production by Early Human B Cell Precursors . Science 301 : 1374 – 1377 . doi: 10.1126/science.1086907 OpenUrl Abstract / FREE Full Text ↵ Waterhouse A , Bertoni M , Bienert S , Studer G , Tauriello G , Gumienny R , Heer FT , de Beer TAP , Rempfer C , Bordoli L , Lepore R , Schwede T. 2018 . SWISS-MODEL: homology modelling of protein structures and complexes . Nucleic Acids Research 46 : W296 – W303 . doi: 10.1093/nar/gky427 OpenUrl CrossRef PubMed ↵ Wei X , Decker JM , Wang S , Hui H , Kappes JC , Wu X , Salazar-Gonzalez JF , Salazar MG , Kilby JM , Saag MS , Komarova NL , Nowak MA , Hahn BH , Kwong PD , Shaw GM . 2003 . Antibody neutralization and escape by HIV . Nature 422 : 307 – 312 . doi: 10.1038/nature01470 OpenUrl CrossRef PubMed Web of Science ↵ Wibmer CK , Bhiman JN , Gray ES , Tumba N , Abdool Karim SS , Williamson C , Morris L , Moore PL . 2013 . Viral Escape from HIV Neutralizing Antibodies Drives Increased Plasma Neutralization Breadth through Sequential Recognition of Multiple Epitopes and Immunotypes . PLoS Pathog 9 : e1003738 . doi: 10.1371/journal.ppat.1003738 OpenUrl CrossRef PubMed ↵ Williams KL , Cortez V , Dingens AS , Gach JS , Rainwater S , Weis JF , Chen X , Spearman P , Forthal DN , Overbaugh J . 2015 . HIV-specific CD4-induced Antibodies Mediate Broad and Potent Antibody-dependent Cellular Cytotoxicity Activity and are Commonly Detected in Plasma from HIV-infected Humans . EBioMedicine 2 : 1464 – 1477 . doi: 10.1016/j.ebiom.2015.09.001 OpenUrl CrossRef ↵ Williams KL , Wang B , Arenz D , Williams JA , Dingens AS , Cortez V , Simonich CA , Rainwater S , Lehman DA , Lee KK , Overbaugh J . 2018 . Superinfection Drives HIV Neutralizing Antibody Responses from Several B Cell Lineages that Contribute to a Polyclonal Repertoire . Cell Reports 23 : 682 – 691 . doi: 10.1016/j.celrep.2018.03.082 OpenUrl CrossRef ↵ Wu X , Zhou T , Zhu J , Zhang B , Georgiev I , Wang C , Chen X , Longo NS , Louder M , McKee K , O’Dell S , Perfetto S , Schmidt SD , Shi W , Wu L , Yang Y , Yang Z-Y , Yang Z , Zhang Z , Bonsignori M , Crump JA , Kapiga SH , Sam NE , Haynes BF , Simek M , Burton DR , Koff WC , Doria-Rose NA , Connors M , NISC Comparative Sequencing Program , Mullikin JC , Nabel GJ , Roederer M , Shapiro L , Kwong PD , Mascola JR . 2011 . Focused Evolution of HIV Neutralizing Antibodies Revealed by Structures and Deep Sequencing . Science 333 : 1593 – 1602 . doi: 10.1126/science.1207532 OpenUrl Abstract / FREE Full Text ↵ Zheng SQ , Palovcak E , Armache J-P , Verba KA , Cheng Y , Agard DA . 2017 . MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy . Nat Methods 14 : 331 – 332 . doi: 10.1038/nmeth.4193 OpenUrl CrossRef PubMed ↵ Zolla-Pazner S , Cohen SS , Boyd D , Kong X-P , Seaman M , Nussenzweig M , Klein F , Overbaugh J , Totrov M . 2016 . Structure/Function Studies Involving the V3 Region of the HIV Envelope Delineate Multiple Factors That Affect Neutralization Sensitivity . J Virol 90 : 636 – 649 . doi: 10.1128/JVI.01645-15 OpenUrl Abstract / FREE Full Text Back to top Previous Next Posted March 17, 2021. Download PDF Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Functional development of a V3-specific broadly neutralizing antibody isolated from a case of HIV superinfection Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Functional development of a V3-specific broadly neutralizing antibody isolated from a case of HIV superinfection Mackenzie M. Shipley , Vidya Mangala Prasad , Laura E. Doepker , Adam Dingens , Duncan Ralph , Elias Harkins , Amrit Dhar , Dana Arenz , Vrasha Chohan , Haidyn Weight , Kishor Mandaliya , Jesse D. Bloom , Frederick A. Matsen IV , Kelly K. Lee , Julie M. Overbaugh bioRxiv 2021.03.15.435484; doi: https://doi.org/10.1101/2021.03.15.435484 Share This Article: Copy Citation Tools Functional development of a V3-specific broadly neutralizing antibody isolated from a case of HIV superinfection Mackenzie M. Shipley , Vidya Mangala Prasad , Laura E. Doepker , Adam Dingens , Duncan Ralph , Elias Harkins , Amrit Dhar , Dana Arenz , Vrasha Chohan , Haidyn Weight , Kishor Mandaliya , Jesse D. Bloom , Frederick A. Matsen IV , Kelly K. Lee , Julie M. Overbaugh bioRxiv 2021.03.15.435484; doi: https://doi.org/10.1101/2021.03.15.435484 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Microbiology Subject Areas All Articles Animal Behavior and Cognition (7806) Biochemistry (18223) Bioengineering (14391) Bioinformatics (43122) Biophysics (21998) Cancer Biology (19110) Cell Biology (26193) Clinical Trials (138) Developmental Biology (13651) Ecology (20405) Epidemiology (2067) Evolutionary Biology (24861) Genetics (15859) Genomics (22985) Immunology (18215) Microbiology (41375) Molecular Biology (17552) Neuroscience (90878) Paleontology (679) Pathology (2906) Pharmacology and Toxicology (4955) Physiology (7876) Plant Biology (15518) Scientific Communication and Education (2068) Synthetic Biology (4432) Systems Biology (10014) Zoology (2319) window.__CF$cv$params={r:'a1d65264dbee493d',t:'MTc4NDQyODQxMQ==',u:'019f7838c6ac7401bd99b6856ee39e03',ut:'ScMr41DdfuPic8Id_ZinfzOycpkds1B2Md6pdmPkd30-1784428414-1.2.1.1-7m_g_hbByGrRaDCORTvQikJQ1N2nZPWkFs0jTmDFTv.4JljJWyF6mc7FKyJocpUFpB22pKv686mkiEXVEWlJ5.K_sVFNxEc0vT9NfuMVt14',i:60};(function(){if(!document.body)return;var s=document.createElement('script');s.src='/cdn-cgi/challenge-platform/scripts/precursor/main.js';document.head.appendChild(s);})();