Optimizing immunization protocols to elicit broadly neutralizing antibodies

Mechanism for evolution of diverse autologous antibodies upon broadly neutralizing antibody therapy of people with HIV

Antiretroviral therapy (ART) inhibits Human Immunodeficiency Virus (HIV) replication to maintain undetectable viral loads in people living with HIV, but does not result in a cure. Due to the significant challenges of lifelong ART for many, there is strong interest in therapeutic strategies that result in cure. Recent clinical trials have shown that administration of broadly neutralizing antibodies (bnAbs) when there is some viremia can lead to ART-free viral control in some people; however, the underlying mechanisms are unclear. Our computational modeling shows that bnAbs administered in the presence of some viremia promote the evolution of autologous antibodies (aAbs) that target diverse epitopes of HIV spike proteins. This "net" of polyclonal aAbs could confer control since evasion of this response would require developing mutations in multiple epitopes. Our results provide a common mechanistic framework underlying recent clinical observations upon bnAb/ART therapy, and they should also motivate and inform new trials.

Retrospective SARS-CoV-2 human antibody development trajectories are largely sparse and permissive

Immunological interventions, like vaccinations, are enabled by the predictive control of humoral responses to novel antigens. While the development trajectories for many broadly neutralizing antibodies (bnAbs) have been measured, it is less established how human subtype-specific antibodies develop from their precursors. In this work, we evaluated the retrospective development trajectories for eight anti-SARS-CoV-2 Spike human antibodies (Abs). To mimic the immunological process of BCR selection during affinity maturation in germinal centers (GCs), we performed deep mutational scanning on anti-S1 molecular Fabs using yeast display coupled to fluorescence-activated cell sorting. Focusing only on changes in affinity upon mutation, we found that human Ab development pathways have few mutations which impart changes in monovalent binding dissociation constants and that these mutations can occur in nearly any order. Maturation pathways of two bnAbs showed that while they are only slightly less permissible than subtype-specific Abs, more development steps on average are needed to reach the same level of affinity. Many of the subtype-specific Abs had inherent affinity for antigen, and these results were robust against different potential inferred precursor sequences. To evaluate the effect of differential affinity for precursors on GC outcomes, we adapted a coarse-grained affinity maturation model. This model showed that antibody precursors with minimal affinity advantages rapidly outcompete competitors to become the dominant clonotype.

Epistatic hotspots organize antibody fitness landscape and boost evolvability

The course of evolution is strongly shaped by interaction between mutations. Such epistasis can yield rugged sequence-function maps and constrain the availability of adaptive paths. While theoretical intuition is often built on global statistics of large, homogeneous model landscapes, mutagenesis measurements necessarily probe a limited neighborhood of a reference genotype. It is unclear to what extent local topography of a real epistatic landscape represents its global shape. Here, we demonstrate that epistatic landscapes can be heterogeneously rugged and this heterogeneity may render biomolecules more evolvable. By characterizing a multipeaked fitness landscape of a SARS-CoV-2 antibody mutant library, we show that heterogeneous ruggedness arises from sparse epistatic hotspots, whose mutation impacts the fitness effect of numerous sequence sites. Surprisingly, mutating an epistatic hotspot may enhance, rather than reduce, the accessibility of the fittest genotype, while increasing the overall ruggedness. Further, migratory constraints in real space alleviate mutational constraints in sequence space, which not only diversify direct paths taken but may also turn a road-blocking fitness peak into a stepping stone leading toward the global optimum. Our results suggest that a hierarchy of epistatic hotspots may organize the fitness landscape in such a way that path-orienting ruggedness confers global smoothness.

Parallel HIV-1 fitness landscapes shape viral dynamics in humans and macaques that develop broadly neutralizing antibodies

Human immunodeficiency virus (HIV)-1 exhibits remarkable genetic diversity. For this reason, an effective HIV-1 vaccine must elicit antibodies that can neutralize many variants of the virus. While broadly neutralizing antibodies (bnAbs) have been isolated from HIV-1 infected individuals, a general understanding of the virus-antibody coevolutionary processes that lead to their development remains incomplete. We performed a quantitative study of HIV-1 evolution in two individuals who developed bnAbs. We observed strong selection early in infection for mutations affecting HIV-1 envelope glycosylation and escape from autologous strain-specific antibodies, followed by weaker selection for bnAb resistance later in infection. To confirm our findings, we analyzed data from rhesus macaques infected with viruses derived from the same two individuals. We inferred remarkably similar fitness effects of HIV-1 mutations in humans and macaques. Moreover, we observed a striking pattern of rapid HIV-1 evolution, consistent in both humans and macaques, that precedes the development of bnAbs. Our work highlights strong parallels between infection in rhesus macaques and humans, and it reveals a quantitative evolutionary signature of bnAb development.

Minimal framework for optimizing vaccination protocols targeting highly mutable pathogens

A persistent public health challenge is identifying immunization schemes that are effective against highly mutable pathogens such as HIV and influenza viruses. To address this, we analyze a simplified model of affinity maturation, the Darwinian evolutionary process B cells undergo during immunization. The vaccination protocol determines the selection forces that steer affinity maturation to generate antibodies. We focus on identifying the optimal selection forces exerted by a generic time-dependent vaccination protocol to maximize the production of broadly neutralizing antibodies (bnAbs) that can protect against a broad spectrum of pathogen strains. The model utilizes a path integral representation and operator approximations within a mean-field limit and provides guiding principles for optimizing time-dependent vaccine-induced selection forces to enhance bnAb generation. We compare our analytical mean-field results with the outcomes of stochastic simulations, and we discuss their similarities and differences.

Vaccination against rapidly evolving pathogens and the entanglements of memory

Immune memory determines infection risk and responses to future infections and vaccinations over potentially decades of life. Despite its centrality, the dynamics of memory to antigenically variable pathogens remains poorly understood. This Review examines how past exposures shape B cell responses to vaccinations with influenza and SARS-CoV-2. An overriding feature of vaccinations with these pathogens is the recall of primary responses, often termed 'imprinting' or 'original antigenic sin'. These recalled responses can inhibit the generation of new responses unless some incompletely defined conditions are met. Depending on the context, immune memory can increase or decrease the total neutralizing antibody response to variant antigens, with apparent consequences for protection. These effects are easier to measure experimentally than epidemiologically, but there is evidence that both early and recent exposures influence vaccine effectiveness. A few immunological interactions between adaptive immune responses and antigens might explain the seemingly discrepant effects of memory. Overall, the complex observations point to a need for more quantitative approaches to integrate high-dimensional immune data from populations with diverse exposure histories. Such approaches could help identify optimal vaccination strategies against antigenically diverse pathogens.

Discovery, recognized antigenic structures, and evolution of cross-serotype broadly neutralizing antibodies from porcine B-cell repertoires against foot-and-mouth disease virus

It is a great challenge to isolate the broadly neutralizing antibodies (bnAbs) against foot-and-mouth disease virus (FMDV) due to its existence as seven distinct serotypes without cross-protection. Here, by vaccination of pig with FMDV serotypes O and A whole virus antigens, we obtained 10 bnAbs against serotypes O, A and/or Asia1 by dissecting 216 common clonotypes of two serotypes O and A specific porcine B-cell receptor (BCR) gene repertoires containing total 12720 B cell clones, indicating the induction of cross-serotype bnAbs after sequential vaccination with serotypes O and A antigens. The majority of porcine bnAbs (9/10) were derived from terminally differentiated B cells of different clonal lineages, which convergently targeted the conserved "RGDL" motif on structural protein VP1 of FMDV by mimicking receptor recognition to inhibit viral attachment to cells. Cryo-EM complex structures revealed that the other bnAb pOA-2 specifically targets a novel inter-pentamer antigen structure surrounding the viral three-fold axis, with a highly conserved determinant at residue 68 on VP2. This unique binding pattern enabled cross-serotype neutralization by destabilizing the viral particle. The evolutionary analysis of pOA-2 demonstrated its origin from an intermediate B-cell, emphasizing the crucial role of somatic hypermutations (SHMs) in balancing the breadth and potency of neutralization. However, excessive SHMs may deviate from the trajectory of broad neutralization. This study provides a strategy to uncover bnAbs against highly mutable pathogens and the cross-serotype antigenic structures to explore broadly protective FMDV vaccine.

Recapitulation of HIV-1 Neutralization Breadth in Plasma by the Combination of Two Broadly Neutralizing Antibodies from Different Lineages in the Same SHIV-Infected Rhesus Macaque

Viral infection generally induces polyclonal neutralizing antibody responses. However, how many lineages of antibody responses can fully represent the neutralization activities in sera has not been well studied. Using the newly designed stable HIV-1 Env trimer as hook, we isolated two distinct broadly neutralizing antibodies (bnAbs) from Chinese rhesus macaques infected with SHIV1157ipd3N4 for 5 years. One lineage of neutralizing antibodies (JT15 and JT16) targeted the V2-apex in the Env trimers, similar to the J038 lineage bnAbs identified in our previous study. The other lineage neutralizing antibody (JT18) targeted the V3 crown region in the Env, which strongly competed with human 447-52D. Each lineage antibody neutralized a different set of viruses. Interestingly, when the two neutralizing antibodies from different lineages isolated from the same macaque were combined, the mixture had a neutralization breath very similar to that from the cognate sera. Our study demonstrated that a minimum of two different neutralizing antibodies can fully recapitulate the serum neutralization breadth. This observation can have important implications in AIDS vaccine design.

Universal characterization of epitope immunodominance from a multiscale model of clonal competition in germinal centers

We introduce a multiscale model for affinity maturation, which aims to capture the intraclonal, interclonal, and epitope-specific organization of the B-cell population in a germinal center. We describe the evolution of the B-cell population via a quasispecies dynamics, with species corresponding to unique B-cell receptors (BCRs), where the desired multiscale structure is reflected on the mutational connectivity of the accessible BCR space, and on the statistical properties of its fitness landscape. Within this mathematical framework, we study the competition among classes of BCRs targeting different antigen epitopes, and we construct an effective immunogenic space where epitope immunodominance relations can be universally characterized. We finally study how varying the relative composition of a mixture of antigens with variable and conserved domains allows for a parametric exploration of this space, and we identify general principles for the rational design of two-antigen cocktails.

Immunization-induced antigen archiving enhances local memory CD8+ T cell responses following an unrelated viral infection

Antigens from viruses or immunizations can persist or are archived in lymph node stromal cells such as lymphatic endothelial cells (LEC) and fibroblastic reticular cells (FRC). Here, we find that, during the time frame of antigen archiving, LEC apoptosis caused by a second, but unrelated, innate immune stimulus such as vaccina viral infection or CpG DNA administration resulted in cross-presentation of archived antigens and boosted memory CD8 + T cells specific to the archived antigen. In contrast to "bystander" activation associated with unrelated infections, the memory CD8 + T cells specific to the archived antigen from the immunization were significantly higher than memory CD8 + T cells of a different antigen specificity. Finally, the boosted memory CD8 + T cells resulted in increased protection against Listeria monocytogenes expressing the antigen from the immunization, but only for the duration that the antigen was archived. These findings outline an important mechanism by which lymph node stromal cell archived antigens, in addition to bystander activation, can augment memory CD8 + T cell responses during repeated inflammatory insults.

Bringing immunofocusing into focus

Immunofocusing is a strategy to create immunogens that redirect humoral immune responses towards a targeted epitope and away from non-desirable epitopes. Immunofocusing methods often aim to develop "universal" vaccines that provide broad protection against highly variant viruses such as influenza virus, human immunodeficiency virus (HIV-1), and most recently, severe acute respiratory syndrome coronavirus (SARS-CoV-2). We use existing examples to illustrate five main immunofocusing strategies-cross-strain boosting, mosaic display, protein dissection, epitope scaffolding, and epitope masking. We also discuss obstacles for immunofocusing like immune imprinting. A thorough understanding, advancement, and application of the methods we outline here will enable the design of high-resolution vaccines that protect against future viral outbreaks.

Antibody and Cell-Based Therapies against Virus-Induced Cancers in the Context of HIV/AIDS

Infectious agents, notably viruses, can cause or increase the risk of cancer occurrences. These agents often disrupt normal cellular functions, promote uncontrolled proliferation and growth, and trigger chronic inflammation, leading to cancer. Approximately 20% of all cancer cases in humans are associated with an infectious pathogen. The International Agency for Research on Cancer (IARC) recognizes seven viruses as direct oncogenic agents, including Epstein-Barr Virus (EBV), Kaposi's Sarcoma-associated herpesvirus (KSHV), human T-cell leukemia virus type-1 (HTLV-1), human papilloma virus (HPV), hepatitis C virus (HCV), hepatitis B virus (HBV), and human immunodeficiency virus type 1 (HIV-1). Most viruses linked to increased cancer risk are typically transmitted through contact with contaminated body fluids and high-risk behaviors. The risk of infection can be reduced through vaccinations and routine testing, as well as recognizing and addressing risky behaviors and staying informed about public health concerns. Numerous strategies are currently in pre-clinical phases or undergoing clinical trials for targeting cancers driven by viral infections. Herein, we provide an overview of risk factors associated with increased cancer incidence in people living with HIV (PLWH) as well as other chronic viral infections, and contributing factors such as aging, toxicity from ART, coinfections, and comorbidities. Furthermore, we highlight both antibody- and cell-based strategies directed against virus-induced cancers while also emphasizing approaches aimed at discovering cures or achieving complete remission for affected individuals.

Steering and controlling evolution - from bioengineering to fighting pathogens

Control interventions steer the evolution of molecules, viruses, microorganisms or other cells towards a desired outcome. Applications range from engineering biomolecules and synthetic organisms to drug, therapy and vaccine design against pathogens and cancer. In all these instances, a control system alters the eco-evolutionary trajectory of a target system, inducing new functions or suppressing escape evolution. Here, we synthesize the objectives, mechanisms and dynamics of eco-evolutionary control in different biological systems. We discuss how the control system learns and processes information about the target system by sensing or measuring, through adaptive evolution or computational prediction of future trajectories. This information flow distinguishes pre-emptive control strategies by humans from feedback control in biotic systems. We establish a cost-benefit calculus to gauge and optimize control protocols, highlighting the fundamental link between predictability of evolution and efficacy of pre-emptive control.

Antigen pressure from two founder viruses induces multiple insertions at a single antibody position to generate broadly neutralizing HIV antibodies

Vaccination strategies aimed at maturing broadly neutralizing antibodies (bnAbs) from naïve precursors are hindered by unusual features that characterize these Abs, including insertions and deletions (indels). Longitudinal studies of natural HIV infection cases shed light on the complex processes underlying bnAb development and have suggested a role for superinfection as a potential enhancer of neutralization breadth. Here we describe the development of a potent bnAb lineage that was elicited by two founder viruses to inform vaccine design. The V3-glycan targeting bnAb lineage (PC39-1) was isolated from subtype C-infected IAVI Protocol C elite neutralizer, donor PC39, and is defined by the presence of multiple independent insertions in CDRH1 that range from 1-11 amino acids in length. Memory B cell members of this lineage are predominantly atypical in phenotype yet also span the class-switched and antibody-secreting cell compartments. Development of neutralization breadth occurred concomitantly with extensive recombination between founder viruses before each virus separated into two distinct population "arms" that evolved independently to escape the PC39-1 lineage. Ab crystal structures show an extended CDRH1 that can help stabilize the CDRH3. Overall, these findings suggest that early exposure of the humoral system to multiple related Env molecules could promote the induction of bnAbs by focusing Ab responses to conserved epitopes.

The changing health impact of vaccines in the COVID-19 pandemic: A modeling study

Much of the world's population had already been infected with COVID-19 by the time the Omicron variant emerged at the end of 2021, but the scale of the Omicron wave was larger than any that had come before or has happened since, and it left a global imprinting of immunity that changed the COVID-19 landscape. In this study, we simulate a South African population and demonstrate how population-level vaccine effectiveness and efficiency changed over the course of the first 2 years of the pandemic. We then introduce three hypothetical variants and evaluate the impact of vaccines with different properties. We find that variant-chasing vaccines have a narrow window of dominating pre-existing vaccines but that a variant-chasing vaccine strategy may have global utility, depending on the rate of spread from setting to setting. Next-generation vaccines might be able to overcome uncertainty in pace and degree of viral evolution.

Mechanisms that promote the evolution of cross-reactive antibodies upon vaccination with designed influenza immunogens

Immunogens that elicit broadly neutralizing antibodies targeting the conserved receptor-binding site (RBS) on influenza hemagglutinin may serve as candidates for a universal influenza vaccine. Here, we develop a computational model to interrogate antibody evolution by affinity maturation after immunization with two types of immunogens: a heterotrimeric "chimera" hemagglutinin that is enriched for the RBS epitope relative to other B cell epitopes and a cocktail composed of three non-epitope-enriched homotrimers of the monomers that comprise the chimera. Experiments in mice find that the chimera outperforms the cocktail for eliciting RBS-directed antibodies. We show that this result follows from an interplay between how B cells engage these antigens and interact with diverse helper T cells and requires T cell-mediated selection of germinal center B cells to be a stringent constraint. Our results shed light on antibody evolution and highlight how immunogen design and T cells modulate vaccination outcomes.

Common framework mutations impact antibody interfacial dynamics and flexibility

Introduction

With the flood of engineered antibodies, there is a heightened need to elucidate the structural features of antibodies that contribute to specificity, stability, and breadth. While antibody flexibility and interface angle have begun to be explored, design rules have yet to emerge, as their impact on the metrics above remains unclear. Furthermore, the purpose of framework mutations in mature antibodies is highly convoluted.

Methods

To this end, a case study utilizing molecular dynamics simulations was undertaken to determine the impact framework mutations have on the VH-VL interface. We further sought to elucidate the governing mechanisms by which changes in the VH-VL interface angle impact structural elements of mature antibodies by looking at root mean squared deviations, root mean squared fluctuations, and solvent accessible surface area.

Results and discussion

Overall, our results suggest framework mutations can significantly shift the distribution of VH-VL interface angles, which leads to local changes in antibody flexibility through local changes in the solvent accessible surface area. The data presented herein highlights the need to reject the dogma of static antibody crystal structures and exemplifies the dynamic nature of these proteins in solution. Findings from this work further demonstrate the importance of framework mutations on antibody structure and lay the foundation for establishing design principles to create antibodies with increased specificity, stability, and breadth.

Hierarchical sequence-affinity landscapes shape the evolution of breadth in an anti-influenza receptor binding site antibody

Broadly neutralizing antibodies (bnAbs) that neutralize diverse variants of a particular virus are of considerable therapeutic interest. Recent advances have enabled us to isolate and engineer these antibodies as therapeutics, but eliciting them through vaccination remains challenging, in part due to our limited understanding of how antibodies evolve breadth. Here, we analyze the landscape by which an anti-influenza receptor binding site (RBS) bnAb, CH65, evolved broad affinity to diverse H1 influenza strains. We do this by generating an antibody library of all possible evolutionary intermediates between the unmutated common ancestor (UCA) and the affinity-matured CH65 antibody and measure the affinity of each intermediate to three distinct H1 antigens. We find that affinity to each antigen requires a specific set of mutations - distributed across the variable light and heavy chains - that interact non-additively (i.e., epistatically). These sets of mutations form a hierarchical pattern across the antigens, with increasingly divergent antigens requiring additional epistatic mutations beyond those required to bind less divergent antigens. We investigate the underlying biochemical and structural basis for these hierarchical sets of epistatic mutations and find that epistasis between heavy chain mutations and a mutation in the light chain at the V_H-V_L interface is essential for binding a divergent H1. Collectively, this is the first work to comprehensively characterize epistasis between heavy and light chain mutations and shows that such interactions are both strong and widespread. Together with our previous study analyzing a different class of anti-influenza antibodies, our results implicate epistasis as a general feature of antibody sequence-affinity landscapes that can potentiate and constrain the evolution of breadth.

Moving the needle: Employing deep reinforcement learning to push the boundaries of coarse-grained vaccine models

Highly mutable infectious disease pathogens (hm-IDPs) such as HIV and influenza evolve faster than the human immune system can contain them, allowing them to circumvent traditional vaccination approaches and causing over one million deaths annually. Agent-based models can be used to simulate the complex interactions that occur between immune cells and hm-IDP-like proteins (antigens) during affinity maturation-the process by which antibodies evolve. Compared to existing experimental approaches, agent-based models offer a safe, low-cost, and rapid route to study the immune response to vaccines spanning a wide range of design variables. However, the highly stochastic nature of affinity maturation and vast sequence space of hm-IDPs render brute force searches intractable for exploring all pertinent vaccine design variables and the subset of immunization protocols encompassed therein. To address this challenge, we employed deep reinforcement learning to drive a recently developed agent-based model of affinity maturation to focus sampling on immunization protocols with greater potential to improve the chosen metrics of protection, namely the broadly neutralizing antibody (bnAb) titers or fraction of bnAbs produced. Using this approach, we were able to coarse-grain a wide range of vaccine design variables and explore the relevant design space. Our work offers new testable insights into how vaccines should be formulated to maximize protective immune responses to hm-IDPs and how they can be minimally tailored to account for major sources of heterogeneity in human immune responses and various socioeconomic factors. Our results indicate that the first 3 to 5 immunizations, depending on the metric of protection, should be specially tailored to achieve a robust protective immune response, but that beyond this point further immunizations require only subtle changes in formulation to sustain a durable bnAb response.

Determinants of anti-S immune response at 6 months after COVID-19 vaccination in a multicentric European cohort of healthcare workers – ORCHESTRA project

Background

The duration of immune response to COVID-19 vaccination is of major interest. Our aim was to analyze the determinants of anti-SARS-CoV-2 IgG titer at 6 months after 2-dose vaccination in an international cohort of vaccinated healthcare workers (HCWs).

Methods

We analyzed data on levels of anti-SARS-CoV-2 Spike antibodies and sociodemographic and clinical characteristics of 6,327 vaccinated HCWs from 8 centers from Germany, Italy, Romania and Slovakia. Time between 1st dose and serology ranged 150-210 days. Serological levels were log-transformed to account for the skewness of the distribution and normalized by dividing them by center-specific standard errors, obtaining standardized values. We fitted center-specific multivariate regression models to estimate the cohort-specific relative risks (RR) of an increase of 1 standard deviation of log antibody level and corresponding 95% confidence interval (CI), and finally combined them in random-effects meta-analyses.

Results

A 6-month serological response was detected in 99.6% of HCWs. Female sex (RR 1.10, 95%CI 1.00-1.21), past infection (RR 2.26, 95%CI 1.73-2.95) and two vaccine doses (RR 1.50, 95%CI 1.22-1.84) predicted higher IgG titer, contrary to interval since last dose (RR for 10-day increase 0.94, 95%CI 0.91-0.97) and age (RR for 10-year increase 0.87, 95%CI 0.83-0.92). M-RNA-based vaccines (p<0.001) and heterologous vaccination (RR 2.46, 95%CI 1.87-3.24, one cohort) were associated with increased antibody levels.

Conclusions

Female gender, young age, past infection, two vaccine doses, and m-RNA and heterologous vaccination predicted higher antibody level at 6 months. These results corroborate previous findings and offer valuable data for comparison with trends observed with longer follow-ups.

Design of immunogens for eliciting antibody responses that may protect against SARS-CoV-2 variants

The rise of SARS-CoV-2 variants and the history of outbreaks caused by zoonotic coronaviruses point to the need for next-generation vaccines that confer protection against variant strains. Here, we combined analyses of diverse sequences and structures of coronavirus spikes with data from deep mutational scanning to design SARS-CoV-2 variant antigens containing the most significant mutations that may emerge. We trained a neural network to predict RBD expression and ACE2 binding from sequence, which allowed us to determine that these antigens are stable and bind to ACE2. Thus, they represent viable variants. We then used a computational model of affinity maturation (AM) to study the antibody response to immunization with different combinations of the designed antigens. The results suggest that immunization with a cocktail of the antigens is likely to promote evolution of higher titers of antibodies that target SARS-CoV-2 variants than immunization or infection with the wildtype virus alone. Finally, our analysis of 12 coronaviruses from different genera identified the S2’ cleavage site and fusion peptide as potential pan-coronavirus vaccine targets.

SARS-CoV-2 variants have already emerged and future variants may pose greater threats to the efficacy of current vaccines. Rather than using a reactive approach to vaccine development that would lag behind the evolution of the virus, such as updating the sequence in the vaccine with a current variant, we sought to use a proactive approach that predicts some of the mutations that could arise that could evade current immune responses. Then, by including these mutations in a new vaccine antigen, we might be able to protect against those potential variants before they appear. Toward this end, we used various computational methods including sequence analysis and machine learning to design such antigens. We then used simulations of antibody development, and the results suggest that immunization with our designed antigens is likely to result in an antibody response that is better able to target SARS-CoV-2 variants than current vaccines. We also leveraged our sequence analysis to suggest that a particular site on the spike protein could serve as a useful target for a pan-coronavirus vaccine.

Repeated exposure to heterologous hepatitis C viruses associates with enhanced neutralizing antibody breadth and potency

A prophylactic hepatitis C virus (HCV) vaccine that elicits neutralizing antibodies could be key to HCV eradication. However, the genetic and antigenic properties of HCV envelope (E1E2) proteins capable of inducing anti-HCV broadly neutralizing antibodies (bNAbs) in humans have not been defined. Here, we investigated the development of bNAbs in longitudinal plasma of HCV-infected persons with persistent infection or spontaneous clearance of multiple reinfections. By measuring plasma antibody neutralization of a heterologous virus panel, we found that the breadth and potency of the antibody response increased upon exposure to multiple genetically distinct infections and with longer duration of viremia. Greater genetic divergence between infecting strains was not associated with enhanced neutralizing breadth. Rather, repeated exposure to antigenically related, antibody-sensitive E1E2s was associated with potent bNAb induction. These data reveal that a prime-boost vaccine strategy with genetically distinct, antibody-sensitive viruses is a promising approach to inducing potent bNAbs in humans.

A Recombinant Subunit Vaccine Induces a Potent, Broadly Neutralizing, and Durable Antibody Response in Macaques against the SARS-CoV-2 P.1 (Gamma) Variant

FDA-approved and emergency use-authorized vaccines using new mRNA and viral-vector technology are highly effective in preventing moderate to severe disease; however, information on their long-term efficacy and protective breadth against severe acute respiratory syndrome coronavirus 2 variants of concern (VOCs) is currently scarce. Here, we describe the durability and broad-spectrum VOC immunity of a prefusion-stabilized spike (S) protein adjuvanted with liquid or lyophilized CoVaccine HT in cynomolgus macaques. This recombinant subunit vaccine is highly immunogenic and induces robust spike-specific and broadly neutralizing antibody responses effective against circulating VOCs (B.1.351 [Beta], P.1 [Gamma], and B.1.617 [Delta]) for at least three months after the final boost. Protective efficacy and postexposure immunity were evaluated using a heterologous P.1 challenge nearly three months after the last immunization. Our results indicate that while immunization with both high and low S doses shorten and reduce viral loads in the upper and lower respiratory tract, a higher antigen dose is required to provide durable protection against disease as vaccine immunity wanes. Histologically, P.1 infection causes similar COVID-19-like lung pathology as seen with early pandemic isolates. Postchallenge IgG concentrations were restored to peak immunity levels, and vaccine-matched and cross-variant neutralizing antibodies were significantly elevated in immunized macaques indicating an efficient anamnestic response. Only low levels of P.1-specific neutralizing antibodies with limited breadth were observed in control (nonvaccinated but challenged) macaques, suggesting that natural infection may not prevent reinfection by other VOCs. Overall, these results demonstrate that a properly dosed and adjuvanted recombinant subunit vaccine can provide protective immunity against circulating VOCs for at least three months.

Multiscale affinity maturation simulations to elicit broadly neutralizing antibodies against HIV

The design of vaccines against highly mutable pathogens, such as HIV and influenza, requires a detailed understanding of how the adaptive immune system responds to encountering multiple variant antigens (Ags). Here, we describe a multiscale model of B cell receptor (BCR) affinity maturation that employs actual BCR nucleotide sequences and treats BCR/Ag interactions in atomistic detail. We apply the model to simulate the maturation of a broadly neutralizing Ab (bnAb) against HIV. Starting from a germline precursor sequence of the VRC01 anti-HIV Ab, we simulate BCR evolution in response to different vaccination protocols and different Ags, which were previously designed by us. The simulation results provide qualitative guidelines for future vaccine design and reveal unique insights into bnAb evolution against the CD4 binding site of HIV. Our model makes possible direct comparisons of simulated BCR populations with results of deep sequencing data, which will be explored in future applications.

Vaccination has saved more lives than any other medical procedure. But, we do not have robust ways to develop vaccines against highly mutable pathogens. For example, there is no effective vaccine against HIV, and a universal vaccine against diverse strains of influenza is also not available. The development of immunization strategies to elicit antibodies that can neutralize diverse strains of highly mutable pathogens (so-called ‘broadly neutralizing antibodies’, or bnAbs) would enable the design of universal vaccines against such pathogens, as well as other viruses that may emerge in the future. In this paper, we present an agent-based model of affinity maturation–the Darwinian process by which antibodies evolve against a pathogen–that, for the first time, enables the in silico investigation of real germline nucleotide sequences of antibodies known to evolve into potent bnAbs, evolving against real amino acid sequences of HIV-based vaccine-candidate proteins. Our results provide new insights into bnAb evolution against HIV, and can be used to qualitatively guide the future design of vaccines against highly mutable pathogens.

Protein engineering strategies for rational immunogen design

Antibody immunodominance refers to the preferential and asymmetric elicitation of antibodies against specific epitopes on a complex protein antigen. Traditional vaccination approaches for rapidly evolving pathogens have had limited success in part because of this phenomenon, as elicited antibodies preferentially target highly variable regions of antigens, and thus do not confer long lasting protection. While antibodies targeting functionally conserved epitopes have the potential to be broadly protective, they often make up a minority of the overall repertoire. Here, we discuss recent protein engineering strategies used to favorably alter patterns of immunodominance, and selectively focus antibody responses toward broadly protective epitopes in the pursuit of next-generation vaccines for rapidly evolving pathogens.

Binding affinity landscapes constrain the evolution of broadly neutralizing anti-influenza antibodies

Over the past two decades, several broadly neutralizing antibodies (bnAbs) that confer protection against diverse influenza strains have been isolated. Structural and biochemical characterization of these bnAbs has provided molecular insight into how they bind distinct antigens. However, our understanding of the evolutionary pathways leading to bnAbs, and thus how best to elicit them, remains limited. Here, we measure equilibrium dissociation constants of combinatorially complete mutational libraries for two naturally isolated influenza bnAbs (CR9114, 16 heavy-chain mutations; CR6261, 11 heavy-chain mutations), reconstructing all possible evolutionary intermediates back to the unmutated germline sequences. We find that these two libraries exhibit strikingly different patterns of breadth: while many variants of CR6261 display moderate affinity to diverse antigens, those of CR9114 display appreciable affinity only in specific, nested combinations. By examining the extensive pairwise and higher order epistasis between mutations, we find key sites with strong synergistic interactions that are highly similar across antigens for CR6261 and different for CR9114. Together, these features of the binding affinity landscapes strongly favor sequential acquisition of affinity to diverse antigens for CR9114, while the acquisition of breadth to more similar antigens for CR6261 is less constrained. These results, if generalizable to other bnAbs, may explain the molecular basis for the widespread observation that sequential exposure favors greater breadth, and such mechanistic insight will be essential for predicting and eliciting broadly protective immune responses.

Predicting in vivo escape dynamics of HIV-1 from a broadly neutralizing antibody

Broadly neutralizing antibodies are promising candidates for treatment and prevention of HIV-1 infections. Such antibodies can temporarily suppress viral load in infected individuals; however, the virus often rebounds by escape mutants that have evolved resistance. In this paper, we map a fitness model of HIV-1 interacting with broadly neutralizing antibodies using in vivo data from a recent clinical trial. We identify two fitness factors, antibody dosage and viral load, that determine viral reproduction rates reproducibly across different hosts. The model successfully predicts the escape dynamics of HIV-1 in the course of an antibody treatment, including a characteristic frequency turnover between sensitive and resistant strains. This turnover is governed by a dosage-dependent fitness ranking, resulting from an evolutionary trade-off between antibody resistance and its collateral cost in drug-free growth. Our analysis suggests resistance-cost trade-off curves as a measure of antibody performance in the presence of resistance evolution.

Coevolutionary transitions emerging from flexible molecular recognition and eco-evolutionary feedback

Highly mutable viruses evolve to evade host immunity that exerts selective pressure and adapts to viral dynamics. Here, we provide a framework for identifying key determinants of the mode and fate of viral-immune coevolution by linking molecular recognition and eco-evolutionary dynamics. We find that conservation level and initial diversity of antigen jointly determine the timing and efficacy of narrow and broad antibody responses, which in turn control the transition between viral persistence, clearance, and rebound. In particular, clearance of structurally complex antigens relies on antibody evolution in a larger antigenic space than where selection directly acts; viral rebound manifests binding-mediated feedback between ecology and rapid evolution. Finally, immune compartmentalization can slow viral escape but also delay clearance. This work suggests that flexible molecular binding allows a plastic phenotype that exploits potentiating neutral variations outside direct contact, opening new and shorter paths toward highly adaptable states.

•

A scale-crossing framework identifies key determinants of viral-immune coevolution

•

Fast specific response influences slow broad response by shaping antigen dynamics

•

Antibody footprint shift enables breadth acquisition and viral clearance

•

Model explains divergent kinetics and outcomes of HCV infection in humans

Mechanisms underlying vaccination protocols that may optimally elicit broadly neutralizing antibodies against highly mutable pathogens

Effective prophylactic vaccines usually induce the immune system to generate potent antibodies that can bind to an antigen and thus prevent it from infecting host cells. B cells produce antibodies by a Darwinian evolutionary process called affinity maturation (AM). During AM, the B cell population evolves in response to the antigen to produce antibodies that bind specifically and strongly to the antigen. Highly mutable pathogens pose a major challenge to the development of effective vaccines because antibodies that are effective against one strain of the virus may not protect against a mutant strain. Antibodies that can protect against diverse strains of a mutable pathogen have high "breadth" and are called broadly neutralizing antibodies (bnAbs). In spite of extensive studies, an effective vaccination strategy that can generate bnAbs in humans does not exist for any highly mutable pathogen. Here we study a minimal model to explore the mechanisms underlying how the selection forces imposed by antigens can be optimally chosen to guide AM to maximize the evolution of bnAbs. For logistical reasons, only a finite number of antigens can be administered in a finite number of vaccinations; that is, guiding the nonequilibrium dynamics of AM to produce bnAbs must be accomplished nonadiabatically. The time-varying Kullback-Leibler divergence (KLD) between the existing B cell population distribution and the fitness landscape imposed by antigens is a quantitative metric of the thermodynamic force acting on B cells. If this force is too small, adaptation is minimal. If the force is too large, contrary to expectations, adaptation is not faster; rather, the B cell population is extinguished for reasons that we describe. We define the conditions necessary for the force to be set optimally such that the flux of B cells from low to high breadth states is maximized. Even in this case we show why the dynamics of AM prevent perfect adaptation. If two shots of vaccination are allowed, the optimal protocol is characterized by a relatively low optimal KLD during the first shot that appropriately increases the diversity of the B cell population so that the surviving B cells have a high chance of evolving into bnAbs upon subsequently increasing the KLD during the second shot. Phylogenetic tree analysis further reveals the evolutionary pathways that lead to bnAbs. The connections between the mechanisms revealed by our analyses and recent simulation studies of bnAb evolution, the problem of generalist versus specialist evolution, and learning theory are discussed.

Phenotypes, Functions, and Clinical Relevance of Regulatory B Cells in Cancer

In immune system, B cells are classically positive modulators that regulate inflammation and immune responses. Regulatory B cells (Bregs) are a subset of B cells which play crucial roles in various conditions, including infection, allergies, autoimmune diseases, transplantation, and tumors. Until now, unequivocal surface markers for Bregs still lack consensus, although numerous Breg subsets have been identified. Generally, Bregs exert their immunoregulatory functions mainly through cytokine secretion and intercellular contact. In the tumor microenvironment, Bregs suppress effector T cells, induce regulatory T cells and target other tumor-infiltrating immune cells, such as myeloid-derived suppressor cells, natural killer cells and macrophages, to hamper anti-tumor immunity. Meanwhile, the cross-regulations between Bregs and tumor cells often result in tumor escape from immunosurveillance. In addition, accumulating evidence suggests that Bregs are closely associated with many clinicopathological factors of cancer patients and might be potential biomarkers for accessing patient survival. Thus, Bregs are potential therapeutic targets for future immunotherapy in cancer patients. In this review, we will discuss the phenotypes, functions, and clinical relevance of Bregs in cancer.