Manipulating the selection forces during affinity maturation to generate cross-reactive HIV antibodies

Optimal evolutionary decision-making to store immune memory

The adaptive immune system provides a diverse set of molecules that can mount specific responses against a multitude of pathogens. Memory is a key feature of adaptive immunity, which allows organisms to respond more readily upon re-infections. However, differentiation of memory cells is still one of the least understood cell fate decisions. Here, we introduce a mathematical framework to characterize optimal strategies to store memory to maximize the utility of immune response over an organism's lifetime. We show that memory production should be actively regulated to balance between affinity and cross-reactivity of immune receptors for an effective protection against evolving pathogens. Moreover, we predict that specificity of memory should depend on the organism's lifespan, and shorter lived organisms with fewer pathogenic encounters should store more cross-reactive memory. Our framework provides a baseline to gauge the efficacy of immune memory in light of an organism's coevolutionary history with pathogens.

Uncovering antibody cross-reaction dynamics in influenza A infections

MOTIVATION

Influenza viruses are a cause of large outbreaks and pandemics with high death tolls. A key obstacle is that flu vaccines have inconsistent performance, in the best cases up to 60% effectiveness, but it can be as low as 10%. Uncovering the hidden pathways of how antibodies (Abs) induced by one influenza strain are effective against another, cross-reaction, is a central vexation for the design of universal flu vaccines.

RESULTS

We conceive a stochastic model that successfully represents the antibody cross-reactive data from mice infected with H3N2 influenza strains and further validation with cross-reaction data of H1N1 strains. Using a High-Performance Computing cluster, several aspects and parameters in the model were tested. Computational simulations highlight that changes in time of infection and the B-cells population are relevant, however, the affinity threshold of B-cells between consecutive infections is a necessary condition for the successful Abs cross-reaction. Our results suggest a 3-D reformulation of the current influenza antibody landscape for the representation and modeling of cross-reactive data.

AVAILABILITY AND IMPLEMENTATION

The full code as a testing/simulation platform is freely available here: https://github.com/systemsmedicine/Antibody_cross-reaction_dynamics.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Uncovering antibody cross-reaction dynamics in influenza A infections

MOTIVATION

Influenza viruses are a cause of large outbreaks and pandemics with high death tolls. A key obstacle is that flu vaccines have inconsistent performance, in the best cases up to 60% effectiveness, but it can be as low as 10%. Uncovering the hidden pathways of how antibodies (Abs) induced by one influenza strain are effective against another, cross-reaction, is a central vexation for the design of universal flu vaccines.

RESULTS

We conceive a stochastic model that successfully represents the antibody cross-reactive data from mice infected with H3N2 influenza strains and further validation with cross-reaction data of H1N1 strains. Using a High-Performance Computing cluster, several aspects and parameters in the model were tested. Computational simulations highlight that changes in time of infection and the B-cells population are relevant, however, the affinity threshold of B-cells between consecutive infections is a necessary condition for the successful Abs cross-reaction. Our results suggest a 3-D reformulation of the current influenza antibody landscape for the representation and modeling of cross-reactive data.

AVAILABILITY AND IMPLEMENTATION

The full code as a testing/simulation platform is freely available here: https://github.com/systemsmedicine/Antibody_cross-reaction_dynamics.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

MPL resolves genetic linkage in fitness inference from complex evolutionary histories

Genetic linkage causes the fate of new mutations in a population to be contingent on the genetic background on which they appear. This makes it challenging to identify how individual mutations affect fitness. To overcome this challenge, we developed marginal path likelihood (MPL), a method to infer selection from evolutionary histories that resolves genetic linkage. Validation on real and simulated data sets shows that MPL is fast and accurate, outperforming existing inference approaches. We found that resolving linkage is crucial for accurately quantifying selection in complex evolving populations, which we demonstrate through a quantitative analysis of intrahost HIV-1 evolution using multiple patient data sets. Linkage effects generated by variants that sweep rapidly through the population are particularly strong, extending far across the genome. Taken together, our results argue for the importance of resolving linkage in studies of natural selection.

Design of immunogens to elicit broadly neutralizing antibodies against HIV targeting the CD4 binding site

A vaccine which is effective against the HIV virus is considered to be the best solution to the ongoing global HIV/AIDS epidemic. In the past thirty years, numerous attempts to develop an effective vaccine have been made with little or no success, due, in large part, to the high mutability of the virus. More recent studies showed that a vaccine able to elicit broadly neutralizing antibodies (bnAbs), that is, antibodies that can neutralize a high fraction of global virus variants, has promise to protect against HIV. Such a vaccine has been proposed to involve at least three separate stages: First, activate the appropriate precursor B cells; second, shepherd affinity maturation along pathways toward bnAbs; and, third, polish the Ab response to bind with high affinity to diverse HIV envelopes (Env). This final stage may require immunization with a mixture of Envs. In this paper, we set up a framework based on theory and modeling to design optimal panels of antigens to use in such a mixture. The designed antigens are characterized experimentally and are shown to be stable and to be recognized by known HIV antibodies.

Optimal prediction with resource constraints using the information bottleneck

Responding to stimuli requires that organisms encode information about the external world. Not all parts of the input are important for behavior, and resource limitations demand that signals be compressed. Prediction of the future input is widely beneficial in many biological systems. We compute the trade-offs between representing the past faithfully and predicting the future using the information bottleneck approach, for input dynamics with different levels of complexity. For motion prediction, we show that, depending on the parameters in the input dynamics, velocity or position information is more useful for accurate prediction. We show which motion representations are easiest to re-use for accurate prediction in other motion contexts, and identify and quantify those with the highest transferability. For non-Markovian dynamics, we explore the role of long-term memory in shaping the internal representation. Lastly, we show that prediction in evolutionary population dynamics is linked to clustering allele frequencies into non-overlapping memories.

Adaptation is influenced by the complexity of environmental change during evolution in a dynamic environment

The environmental conditions of microorganisms' habitats may fluctuate in unpredictable ways, such as changes in temperature, carbon source, pH, and salinity to name a few. Environmental heterogeneity presents a challenge to microorganisms, as they have to adapt not only to be fit under a specific condition, but they must also be robust across many conditions and be able to deal with the switch between conditions itself. While experimental evolution has been used to gain insight into the adaptive process, this has largely been in either unvarying or consistently varying conditions. In cases where changing environments have been investigated, relatively little is known about how such environments influence the dynamics of the adaptive process itself, as well as the genetic and phenotypic outcomes. We designed a systematic series of evolution experiments where we used two growth conditions that have differing timescales of adaptation and varied the rate of switching between them. We used lineage tracking to follow adaptation, and whole genome sequenced adaptive clones from each of the experiments. We find that both the switch rate and the order of the conditions influences adaptation. We also find different adaptive outcomes, at both the genetic and phenotypic levels, even when populations spent the same amount of total time in the two different conditions, but the order and/or switch rate differed. Thus, in a variable environment adaptation depends not only on the nature of the conditions and phenotypes under selection, but also on the complexity of the manner in which those conditions are combined to result in a given dynamic environment.

Physical 'strength' of the multi-protein chain connecting immune cells: Does the weakest link limit antibody affinity maturation?: The weakest link in the multi-protein chain facilitating antigen acquisition by B cells in germinal centres limits antibody affinity maturation

The affinities of antibodies (Abs) for their target antigens (Ags) gradually increase in vivo following an infection or vaccination, but reach saturation at values well below those realisable in vitro. This 'affinity ceiling' could in many cases restrict our ability to fight infections and compromise vaccines. What determines the affinity ceiling has been an unresolved question for decades. Here, we argue that it arises from the strength of the chain of protein complexes that is pulled by B cells during the process of Ag acquisition. The affinity ceiling is determined by the strength of the weakest link in the chain. We identify the weakest link and show that the resulting affinity ceiling can explain the Ab affinities realized in vivo, providing a conceptual understanding of Ab affinity maturation. We explore plausible evolutionary underpinnings of the affinity ceiling, examine supporting evidence and alternative hypotheses and discuss implications for vaccination strategies.

A Multiscale and Comparative Model for Receptor Binding of 2019 Novel Coronavirus and the Implication of its Life Cycle in Host Cells

The respiratory syndrome caused by a new type of coronavirus has been emerging from China and caused more than one million death globally since December 2019. This new virus, called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uses the same receptor called Angiotensin-converting enzyme 2 (ACE2) to attack humans as the coronavirus that caused the severe acute respiratory syndrome (SARS) seventeen years ago. Both viruses recognize ACE2 through the spike proteins (S-protein) on their surfaces. It was found that the S-protein from the SARS coronavirus (SARS-CoV) bind stronger to ACE2 than SARS-CoV-2. However, function of a bio-system is often under kinetic, rather than thermodynamic, control. To address this issue, we constructed a structural model for complex formed between ACE2 and the S-protein from SARS-CoV-2, so that the rate of their association can be estimated and compared with the binding of S-protein from SARS-CoV by a multiscale simulation method. Our simulation results suggest that the association of new virus to the receptor is slower than SARS, which is consistent with the experimental data obtained very recently. We further integrated this difference of association rate between virus and receptor into a mathematical model which describes the life cycle of virus in host cells and its interplay with the innate immune system. Interestingly, we found that the slower association between virus and receptor can result in longer incubation period, while still maintaining a relatively higher level of viral concentration in human body. Our computational study therefore provides, from the molecular level, one possible explanation that this new pandemic by far spread much faster than SARS.

Shaping Polyclonal Responses via Antigen-Mediated Antibody Interference

Broadly neutralizing antibodies (bnAbs) recognize conserved features of rapidly mutating pathogens and confer universal protection, but they emerge rarely in natural infection. Increasing evidence indicates that seemingly passive antibodies may interfere with natural selection of B cells. Yet, how such interference modulates polyclonal responses is unknown. Here we provide a framework for understanding the role of antibody interference—mediated by multi-epitope antigens—in shaping B cell clonal makeup and the fate of bnAb lineages. We find that, under heterogeneous interference, clones with different intrinsic fitness can collectively persist. Furthermore, antagonism among fit clones (specific for variable epitopes) promotes expansion of unfit clones (targeting conserved epitopes), at the cost of repertoire potency. This trade-off, however, can be alleviated by synergy toward the unfit. Our results provide a physical basis for antigen-mediated clonal interactions, stress system-level impacts of molecular synergy and antagonism, and offer principles to amplify naturally rare clones.

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Multi-epitope antigens mediate antibody interference that couples B cell lineages

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Trade-off exists between repertoire potency and persistence of broad lineages

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Antigen-mediated synergy toward intrinsically unfit clones alleviates the trade-off

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Amplifying rare clones by leveraging molecular interference structure

Defining and Manipulating B Cell Immunodominance Hierarchies to Elicit Broadly Neutralizing Antibody Responses against Influenza Virus

The antibody repertoire possesses near-limitless diversity, enabling the adaptive immune system to accommodate essentially any antigen. However, this diversity explores the antigenic space unequally, allowing some pathogens like influenza virus to impose complex immunodominance hierarchies that distract antibody responses away from key sites of virus vulnerability. We developed a computational model of affinity maturation to map the patterns of immunodominance that evolve upon immunization with natural and engineered displays of hemagglutinin (HA), the influenza vaccine antigen. Based on this knowledge, we designed immunization protocols that subvert immune distraction and focus serum antibody responses upon a functionally conserved, but immunologically recessive, target of human broadly neutralizing antibodies. We tested in silico predictions by vaccinating transgenic mice in which antibody diversity was humanized to mirror clinically relevant humoral output. Collectively, our results demonstrate that complex patterns in antibody immunogenicity can be rationally defined and then manipulated to elicit engineered immunity.

Successive Immunization With Epitope-Decreasing Dengue Antigens Induced Conservative Anti-Dengue Immune Responses

Repeated homologous antigen immunization has been hypothesized to hinder antibody diversification, whereas sequential immunization with heterologous immunogens can educate B cell differentiations towards conserved residues thereby facilitating the generation of cross-reactive immunity. In this study, we developed a sequential vaccination strategy that utilized epitope-decreasing antigens to reinforce the cross-reactivity of T and B cell immune responses against all four serotypes dengue virus. The epitope-decreasing immunization was implemented by sequentially inoculating mice with antigens of decreasing domain complexity that first immunized with DENV1 live-attenuated virus, following by the Envelope protein (Env), and then Env domain III (EDIII) subunit protein. When compared to mice immunized with DENV1 live-attenuated virus three times, epitope-decreasing immunization induced higher TNF-α CD8⁺ T cell immune response against consensus epitopes. Epitope-decreasing immunization also significantly improved neutralizing antibody response to heterologous serotypes. Moreover, this sequential approach promoted somatic hypermutations in the immunoglobulin gene of antigen-specific memory B cells in comparison to repeated immunization. This proof-of-concept work on epitope-decreasing sequential vaccination sheds light on how successively exposing the immune system to decreasing-epitope antigens can better induce cross-reactive antibodies.

Preferential Presentation of High-Affinity Immune Complexes in Germinal Centers Can Explain How Passive Immunization Improves the Humoral Response

Passive immunization (PI) with external antibodies has been used classically for rapid but temporary alleviation of disease. Transcending this role, recent studies have shown PI to induce lasting improvements in natural antibody production, suggesting that PI could become a powerful tool to engineer humoral responses. We propose a mechanism with which PI can alter the humoral response. Antigen-specific B cells evolve and get selected in germinal centers (GCs) on the basis of their ability to acquire antigen from antibody-antigen complexes presented in GCs. When external antibodies of high affinity for antigen are used, they form the majority of the complexes in GCs, letting only B cells with even higher affinities be selected. Using an in silico GC reaction model, we show that this mechanism explains the improved humoral responses following PI. The model also synthesizes several independent experimental observations, indicating the robustness of the mechanism, and proposes tunable handles to optimize PI.

Optimizing immunization protocols to elicit broadly neutralizing antibodies

Natural infections and vaccination with a pathogen typically stimulate the production of potent antibodies specific for the pathogen through a Darwinian evolutionary process known as affinity maturation. Such antibodies provide protection against reinfection by the same strain of a pathogen. A highly mutable virus, like HIV or influenza, evades recognition by these strain-specific antibodies via the emergence of new mutant strains. A vaccine that elicits antibodies that can bind to many diverse strains of the virus-known as broadly neutralizing antibodies (bnAbs)-could protect against highly mutable pathogens. Despite much work, the mechanisms by which bnAbs emerge remain uncertain. Using a computational model of affinity maturation, we studied a wide variety of vaccination strategies. Our results suggest that an effective strategy to maximize bnAb evolution is through a sequential immunization protocol, wherein each new immunization optimally increases the pressure on the immune system to target conserved antigenic sites, thus conferring breadth. We describe the mechanisms underlying why sequentially driving the immune system increasingly further from steady state, in an optimal fashion, is effective. The optimal protocol allows many evolving B cells to become bnAbs via diverse evolutionary paths.

Eco-evolutionary control of pathogens

Vaccinations and therapies targeting evolving pathogens aim to curb the pathogen and to steer it toward a controlled evolutionary state. Control is leveraged against the pathogen’s intrinsic evolutionary forces, which in turn, can drive an escape from control. Here, we analyze a simple model of control, in which a host produces antibodies that bind the pathogen. We show that the leverages of host (or external intervention) and pathogen are often highly imbalanced: an error threshold separates parameter regions of efficient control from regions of compromised control, where the pathogen retains the upper hand. Because control efficiency can be predicted from few measurable fitness parameters, our results establish a proof of principle how control theory can guide interventions against evolving pathogens.

Control can alter the eco-evolutionary dynamics of a target pathogen in two ways, by changing its population size and by directed evolution of new functions. Here, we develop a payoff model of eco-evolutionary control based on strategies of evolution, regulation, and computational forecasting. We apply this model to pathogen control by molecular antibody–antigen binding with a tunable dosage of antibodies. By analytical solution, we obtain optimal dosage protocols and establish a phase diagram with an error threshold delineating parameter regimes of successful and compromised control. The solution identifies few independently measurable fitness parameters that predict the outcome of control. Our analysis shows how optimal control strategies depend on mutation rate and population size of the pathogen, and how monitoring and computational forecasting affect protocols and efficiency of control. We argue that these results carry over to more general systems and are elements of an emerging eco-evolutionary control theory.

Sequential immunization induces strong and broad immunity against all four dengue virus serotypes

A major challenge in dengue vaccine development is the need to induce immunity against four dengue (DENV) serotypes. Dengvaxia®, the only licensed dengue vaccine, consists of four variant dengue antigens, one for each serotype. Three doses of immunization with the tetravalent vaccine induced only suboptimal protection against DENV1 and DENV2. Furthermore, vaccination paradoxically and adversely primes dengue naïve subjects to more severe dengue. Here, we have tested whether sequential immunization induces stronger and broader immunity against four DENV serotypes than tetravalent-formulated immunization. Mice were immunized with four DNA plasmids, each encoding the pre-membrane and envelope from one DENV serotype, either sequentially or simultaneously. The sequential immunization induced significantly higher levels of interferon (IFN)γ- or tumor necrosis factor (TNF)α-expressing CD4⁺ and CD8⁺ T cells to both serotype-specific and conserved epitopes than tetravalent immunization. Moreover, sequential immunization induced higher levels of neutralizing antibodies to all four DENV serotypes than tetravalent vaccination. Consistently, sequential immunization resulted in more diversified immunoglobulin repertoire, including increased complementarity determining region 3 (CDR3) length and more robust germinal center reactions. These results show that sequential immunization offers a simple approach to potentially overcome the current challenges encountered with tetravalent-formulated dengue vaccines.

The Chimpanzee SIV Envelope Trimer: Structure and Deployment as an HIV Vaccine Template

Epitope-targeted HIV vaccine design seeks to focus antibody responses to broadly neutralizing antibody (bnAb) sites by sequential immunization. A chimpanzee simian immunodeficiency virus (SIV) envelope (Env) shares a single bnAb site, the variable loop 2 (V2)-apex, with HIV, suggesting its possible utility in an HIV immunization strategy. Here, we generate a chimpanzee SIV Env trimer, MT145K, which displays selective binding to HIV V2-apex bnAbs and precursor versions, but no binding to other HIV specificities. We determine the structure of the MT145K trimer by cryo-EM and show that its architecture is remarkably similar to HIV Env. Immunization of an HIV V2-apex bnAb precursor Ab-expressing knockin mouse with the chimpanzee MT145K trimer induces HIV V2-specific neutralizing responses. Subsequent boosting with an HIV trimer cocktail induces responses that exhibit some virus cross-neutralization. Overall, the chimpanzee MT145K trimer behaves as expected from design both in vitro and in vivo and is an attractive potential component of a sequential immunization regimen to induce V2-apex bnAbs.

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A designed chimpanzee SIV Env trimer binds HIV V2-apex bnAbs specifically

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The trimer (MT145K) is engineered to bind inferred unmutated versions of HIV V2-apex bnAbs

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The cryo-EM structure of the SIV MT145K trimer closely resembles that of HIV trimers

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The MT145K SIV trimer induces HIV-specific nAb responses in a favorable animal model

Quantitative modeling of the effect of antigen dosage on B-cell affinity distributions in maturating germinal centers

Affinity maturation is a complex dynamical process allowing the immune system to generate antibodies capable of recognizing antigens. We introduce a model for the evolution of the distribution of affinities across the antibody population in germinal centers. The model is amenable to detailed mathematical analysis and gives insight on the mechanisms through which antigen availability controls the rate of maturation and the expansion of the antibody population. It is also capable, upon maximum-likelihood inference of the parameters, to reproduce accurately the distributions of affinities of IgG-secreting cells we measure in mice immunized against Tetanus Toxoid under largely varying conditions (antigen dosage, delay between injections). Both model and experiments show that the average population affinity depends non-monotonically on the antigen dosage. We show that combining quantitative modeling and statistical inference is a concrete way to investigate biological processes underlying affinity maturation (such as selection permissiveness), hardly accessible through measurements.

Tuning environmental timescales to evolve and maintain generalists

Natural environments can present diverse challenges, but some genotypes remain fit across many environments. Such "generalists" can be hard to evolve, outcompeted by specialists fitter in any particular environment. Here, inspired by the search for broadly neutralizing antibodies during B cell affinity maturation, we demonstrate that environmental changes on an intermediate timescale can reliably evolve generalists, even when faster or slower environmental changes are unable to do so. We find that changing environments on timescales comparable with evolutionary transients in a population enhance the rate of evolving generalists from specialists, without enhancing the reverse process. The yield of generalists is further increased in more complex dynamic environments, such as a "chirp" of increasing frequency. Our work offers design principles for how nonequilibrium fitness "seascapes" can dynamically funnel populations to genotypes unobtainable in static environments.

Strategies for inducing effective neutralizing antibody responses against HIV-1

Introduction: Despite intensive research efforts, there is still no effective prophylactic vaccine available against HIV-1. Currently, substantial efforts are devoted to the development of vaccines aimed at inducing broadly neutralizing antibodies (bNAbs), which are capable of neutralizing most HIV-1 strains. All bNAbs target the HIV-1 envelope glycoprotein (Env), but Env immunizations usually only induce neutralizing antibodies (NAbs) against the sequence-matched virus and not against other strains.Areas covered: We describe the different strategies that have been explored to improve the breadth and potency of anti-HIV-1 NAb responses. The discussed strategies include the application of engineered Env immunogens, optimization of (bNAb) epitopes, different cocktail and sequential vaccination strategies, nanoparticles and nucleic acid-based vaccines.Expert opinion: A combination of the strategies described in this review and future approaches are probably needed to develop an effective HIV-1 vaccine that can induce broad, potent and long-lasting NAb responses.

Evolving generalists in switching rugged landscapes

Evolving systems, be it an antibody repertoire in the face of mutating pathogens or a microbial population exposed to varied antibiotics, constantly search for adaptive solutions in time-varying fitness landscapes. Generalists refer to genotypes that remain fit across diverse selective pressures; while multi-drug resistant microbes are undesired yet prevalent, broadly-neutralizing antibodies are much wanted but rare. However, little is known about under what conditions such generalists with a high capacity to adapt can be efficiently discovered by evolution. In addition, can epistasis-the source of landscape ruggedness and path constraints-play a different role, if the environment varies in a non-random way? We present a generative model to estimate the propensity of evolving generalists in rugged landscapes that are tunably related and alternating relatively slowly. We find that environmental cycling can substantially facilitate the search for fit generalists by dynamically enlarging their effective basins of attraction. Importantly, these high performers are most likely to emerge at intermediate levels of ruggedness and environmental relatedness. Our approach allows one to estimate correlations across environments from the topography of experimental fitness landscapes. Our work provides a conceptual framework to study evolution in time-correlated complex environments, and offers statistical understanding that suggests general strategies for eliciting broadly neutralizing antibodies or preventing microbes from evolving multi-drug resistance.

Multi-Lineage Evolution in Viral Populations Driven by Host Immune Systems

Viruses evolve in the background of host immune systems that exert selective pressure and drive viral evolutionary trajectories. This interaction leads to different evolutionary patterns in antigenic space. Examples observed in nature include the effectively one-dimensional escape characteristic of influenza A and the prolonged coexistence of lineages in influenza B. Here, we use an evolutionary model for viruses in the presence of immune host systems with finite memory to obtain a phase diagram of evolutionary patterns in a two-dimensional antigenic space. We find that, for small effective mutation rates and mutation jump ranges, a single lineage is the only stable solution. Large effective mutation rates combined with large mutational jumps in antigenic space lead to multiple stably co-existing lineages over prolonged evolutionary periods. These results combined with observations from data constrain the parameter regimes for the adaptation of viruses, including influenza.

A sensitive and rapid chemiluminescence immunoassay for point-of-care testing (POCT) of copeptin in serum based on high-affinity monoclonal antibodies via cytokine-assisted immunization

Purpose: Antibodies are key reagents in the development of immunoassay. We attempted to develop high-performance CPP immunoassays using high-affinity monoclonal antibodies prepared via cytokine-assisted immunization.

Methods: We used fetal liver tyrosine kinase 3 ligand (Flt3L), CC subtype chemokine ligand 20 (CCL20), and granulocyte-macrophage colony-stimulating factor (GM-CSF) to assist traditional subcutaneous immunization of preparing high-affinity monoclonal antibodies, and further to develop high-performance immunoassay methods for CPP.

Results: This novel immune strategy significantly enhanced immune response against CPP. Six anti-CPP monoclonal antibodies (mAbs) with high affinity were successfully screened and selected for application in a fully automated magnetic chemiluminescence immunoassay (CLIA). This robust and rapid assay can efficiently detect CPP in the range of 1.2–1250 pmol L^–1 with a detection limit of 6.25 pmol L^–1. Significantly, the whole incubation process can be completed in 30 min as compared to about 4.5 hr for the control ELISA kit. Furthermore, this assay exhibited high sensitivity and specificity, low intra-assay and inter-assay coefficients of variation (CVs < 15%). The developed assay was applied in the detection of CPP in 115 random serum samples and results showed a high correlation with data obtained using a commercially available ELISA kit (correlation coefficient, 0.9737).

Conclusion: Our assay could be applied in the point-of-care testing of CPP in the serum samples, and also the method developed in this study could be adopted to explore the detection and diagnosis of other biomarkers for various diseases.

Estimation of the breadth of CD4bs targeting HIV antibodies by molecular modeling and machine learning

HIV is a highly mutable virus for which all attempts to develop a vaccine have been unsuccessful. Nevertheless, few long-infected patients develop antibodies, called broadly neutralizing antibodies (bnAbs), that have a high breadth and can neutralize multiple variants of the virus. This suggests that a universal HIV vaccine should be possible. A measure of the efficacy of a HIV vaccine is the neutralization breadth of the antibodies it generates. The breadth is defined as the fraction of viruses in the Seaman panel that are neutralized by the antibody. Experimentally the neutralization ability is measured as the half maximal inhibitory concentration of the antibody (IC50). To avoid such time-consuming experimental measurements, we developed a computational approach to estimate the IC50 and use it to determine the antibody breadth. Given that no direct method exists for calculating IC50 values, we resort to a combination of atomistic modeling and machine learning. For each antibody/virus complex, an all-atoms model is built using the amino acid sequence and a known structure of a related complex. Then a series of descriptors are derived from the atomistic models, and these are used to train a Multi-Layer Perceptron (an Artificial Neural Network) to predict the value of the IC50 (by regression), or if the antibody binds or not to the virus (by classification). The neural networks are trained by use of experimental IC50 values collected in the CATNAP database. The computed breadths obtained by regression and classification are reported and the importance of having some related information in the data set for obtaining accurate predictions is analyzed. This approach is expected to prove useful for the design of HIV bnAbs, where the computation of the potency must be accompanied by a computation of the breadth, and for evaluating the efficiency of potential vaccination schemes developed through modeling and simulation.

Epistasis in a Fitness Landscape Defined by Antibody-Antigen Binding Free Energy

Epistasis is the phenomenon by which the effect of a mutation depends on its genetic background. While it is usually defined in terms of organismal fitness, for single proteins, it must reflect physical interactions among residues. Here, we systematically extract the specific contribution pairwise epistasis makes to the physical affinity of antibody-antigen binding relevant to affinity maturation, a process of accelerated Darwinian evolution. We find that, among competing definitions of affinity, the binding free energy is the most appropriate to describe epistasis. We show that epistasis is pervasive, accounting for 25%-35% of variability, of which a large fraction is beneficial. This work suggests that epistasis both constrains, through negative epistasis, and enlarges, through positive epistasis, the set of possible evolutionary paths that can produce high-affinity sequences during repeated rounds of mutation and selection.

Adjuvanted influenza vaccine dynamics

Adjuvanted influenza vaccines constitute a key element towards inducing neutralizing antibody responses in populations with reduced responsiveness, such as infants and elderly subjects, as well as in devising antigen-sparing strategies. In particular, squalene-containing adjuvants have been observed to induce enhanced antibody responses, as well as having an influence on cross-reactive immunity. To explore the effects of adjuvanted vaccine formulations on antibody response and their relation to protein-specific immunity, we propose different mathematical models of antibody production dynamics in response to influenza vaccination. Data from ferrets immunized with commercial H1N1pdm09 vaccine antigen alone or formulated with different adjuvants was instrumental to adjust model parameters. While the affinity maturation process complexity is abridged, the proposed model is able to recapitulate the essential features of the observed dynamics. Our numerical results suggest that there exists a qualitative shift in protein-specific antibody response, with enhanced production of antibodies targeting the NA protein in adjuvanted versus non-adjuvanted formulations, in conjunction with a protein-independent boost that is over one order of magnitude larger for squalene-containing adjuvants. Furthermore, simulations predict that vaccines formulated with squalene-containing adjuvants are able to induce sustained antibody titers in a robust way, with little impact of the time interval between immunizations.

HIV-1 immunogens and strategies to drive antibody responses towards neutralization breadth

Despite enormous efforts no HIV-1 vaccine has been developed that elicits broadly neutralizing antibodies (bNAbs) to protect against infection to date. The high antigenic diversity and dense N-linked glycan armor, which covers nearly the entire HIV-1 envelope protein (Env), are major roadblocks for the development of bNAbs by vaccination. In addition, the naive human antibody repertoire features a low frequency of exceptionally long heavy chain complementary determining regions (CDRH3s), which is a typical characteristic that many HIV-1 bNAbs use to penetrate the glycan armor. Native-like Env trimer immunogens can induce potent but strain-specific neutralizing antibody responses in animal models but how to overcome the many obstacles towards the development of bNAbs remains a challenge. Here, we review recent HIV-1 Env immunization studies and discuss strategies to guide strain-specific antibody responses towards neutralization breadth.

Adeno-associated virus gene delivery of broadly neutralizing antibodies as prevention and therapy against HIV-1

Vectored gene delivery of HIV-1 broadly neutralizing antibodies (bNAbs) using recombinant adeno-associated virus (rAAV) is a promising alternative to conventional vaccines for preventing new HIV-1 infections and for therapeutically suppressing established HIV-1 infections. Passive infusion of single bNAbs has already shown promise in initial clinical trials to temporarily decrease HIV-1 load in viremic patients, and to delay viral rebound from latent reservoirs in suppressed patients during analytical treatment interruptions of antiretroviral therapy. Long-term, continuous, systemic expression of such bNAbs could be achieved with a single injection of rAAV encoding antibody genes into muscle tissue, which would bypass the challenges of eliciting such bNAbs through traditional vaccination in naïve patients, and of life-long repeated passive transfers of such biologics for therapy. rAAV delivery of single bNAbs has already demonstrated protection from repeated HIV-1 vaginal challenge in humanized mouse models, and phase I clinical trials of this approach are underway. Selection of which individual, or combination of, bNAbs to deliver to counter pre-existing resistance and the rise of escape mutations in the virus remains a challenge, and such choices may differ depending on use of this technology for prevention versus therapy.

Development of broadly neutralizing antibodies in HIV-1 infected elite neutralizers

Broadly neutralizing antibodies (bNAbs), able to prevent viral entry by diverse global viruses, are a major focus of HIV vaccine design, with data from animal studies confirming their ability to prevent HIV infection. However, traditional vaccine approaches have failed to elicit these types of antibodies. During chronic HIV infection, a subset of individuals develops bNAbs, some of which are extremely broad and potent. This review describes the immunological and virological factors leading to the development of bNAbs in such "elite neutralizers". The features, targets and developmental pathways of bNAbs from their precursors have been defined through extraordinarily detailed within-donor studies. These have enabled the identification of epitope-specific commonalities in bNAb precursors, their intermediates and Env escape patterns, providing a template for vaccine discovery. The unusual features of bNAbs, such as high levels of somatic hypermutation, and precursors with unusually short or long antigen-binding loops, present significant challenges in vaccine design. However, the use of new technologies has led to the isolation of more than 200 bNAbs, including some with genetic profiles more representative of the normal immunoglobulin repertoire, suggesting alternate and shorter pathways to breadth. The insights from these studies have been harnessed for the development of optimized immunogens, novel vaccine regimens and improved delivery schedules, which are providing encouraging data that an HIV vaccine may soon be a realistic possibility.

The low spike density of HIV may have evolved because of the effects of T helper cell depletion on affinity maturation

The spikes on virus surfaces bind receptors on host cells to propagate infection. High spike densities (SDs) can promote infection, but spikes are also targets of antibody-mediated immune responses. Thus, diverse evolutionary pressures can influence virus SDs. HIV's SD is about two orders of magnitude lower than that of other viruses, a surprising feature of unknown origin. By modeling antibody evolution through affinity maturation, we find that an intermediate SD maximizes the affinity of generated antibodies. We argue that this leads most viruses to evolve high SDs. T helper cells, which are depleted during early HIV infection, play a key role in antibody evolution. We find that T helper cell depletion results in high affinity antibodies when SD is high, but not if SD is low. This special feature of HIV infection may have led to the evolution of a low SD to avoid potent immune responses early in infection.

The Bayesian optimist's guide to adaptive immune receptor repertoire analysis

Probabilistic modeling is fundamental to the statistical analysis of complex data. In addition to forming a coherent description of the data-generating process, probabilistic models enable parameter inference about given datasets. This procedure is well developed in the Bayesian perspective, in which one infers probability distributions describing to what extent various possible parameters agree with the data. In this paper, we motivate and review probabilistic modeling for adaptive immune receptor repertoire data then describe progress and prospects for future work, from germline haplotyping to adaptive immune system deployment across tissues. The relevant quantities in immune sequence analysis include not only continuous parameters such as gene use frequency but also discrete objects such as B-cell clusters and lineages. Throughout this review, we unravel the many opportunities for probabilistic modeling in adaptive immune receptor analysis, including settings for which the Bayesian approach holds substantial promise (especially if one is optimistic about new computational methods). From our perspective, the greatest prospects for progress in probabilistic modeling for repertoires concern ancestral sequence estimation for B-cell receptor lineages, including uncertainty from germline genotype, rearrangement, and lineage development.

DNA prime/MVTT boost regimen with HIV-1 mosaic Gag enhances the potency of antigen-specific immune responses

HIV-1 diversity and latent reservoir are the major challenges for the development of an effective AIDS vaccine. It is well indicated that Gag-specific CD8⁺ T cells serve as the dominant host immune surveillance for HIV-1 control, but it still remains a challenge for vaccine design to induce broader and stronger cytotoxic T cell immunity against the virus. Genetic variation of the HIV-1 gag gene across different clades is one of the reasons for the reduction of antigenic epitope coverage. Here, we report an immunization strategy with heterologous vaccines expressing a mosaic Gag antigen aimed to increase antigenic breadth against a wider spectrum of HIV-1 strains. Priming using a DNA vaccine via in vivo electroporation, followed by boosting with a live replication-competent modified vaccinia TianTan (MVTT) vectored vaccine, elicited greater and broader protective Gag-specific immune responses in mice. Compared to DNA or MVTT homologous immunization, the heterologous DNA/MVTT vaccination resulted in higher frequencies of broadly reactive, Gag-specific, polyfunctional, long-lived cytotoxic CD8⁺ T cells, as well as increased anti-Gag antibody titer. Importantly, the DNA/MVTT heterologous vaccination induced protection against EcoHIV and mesothelioma AB1-Gag challenges. In summary, the stronger protective Gag-specific immunity induced by the heterologous regimen using two safe vectors shows promise for further development to enhance anti-HIV-1 immunity. Our study has important implications for immunogen design and the development of an effective HIV-1 heterologous vaccination strategy.

Antibody-Mediated Therapy against HIV/AIDS: Where Are We Standing Now?

Acquired immunodeficiency syndrome (AIDS) cases are on the rise globally. To date, there is still no effective measure to eradicate the causative agent, human immunodeficiency virus (HIV). Highly active antiretroviral therapy (HAART) is being used in HIV/AIDS management, but it results in long-term medication and has major drawbacks such as multiple side effects, high cost, and increasing the generation rate of escape mutants. In addition, HAART does not control HIV-related complications, and hence more medications and further management are required. With this, other alternatives are urgently needed. In the past, small-molecule inhibitors have shown potent antiviral effects, and some of them are now being evaluated in clinical trials. The challenges in developing these small molecules for clinical use include the off-target effect, poor stability, and low bioavailability. On the other hand, antibody-mediated therapy has emerged as an important therapeutic modality for anti-HIV therapeutics development. Many antiviral antibodies, namely, broad neutralizing antibodies (bnAbs) against multiple strains of HIV, have shown promising effects in vitro and in animal studies; further studies are ongoing in clinical trials to evaluate their uses in clinical applications. This short review aims to discuss the current development of therapeutic antibodies against HIV and the challenges in adopting them for clinical use.

Strategies for a multi-stage neutralizing antibody-based HIV vaccine

A critical property of a prophylactic HIV vaccine is likely to be its ability to elicit broadly neutralizing antibodies (bnAbs). BnAbs typically have multiple unusual features and are generated in a fraction of HIV-infected individuals through complex pathways. Current vaccine design approaches seek to trigger rare B cell precursors and then steer affinity maturation toward bnAbs in a multi-stage multi-component immunization approach. These vaccine design strategies have been facilitated by molecular descriptions of bnAb interactions with stabilized HIV trimers, the use of an array of sophisticated approaches for immunogen design, the development of novel animal models for immunogen evaluation and advanced technologies to interrogate antibody responses. In this review, we will discuss leading HIV bnAb vaccine immunogens, immunization strategies and future improvements.

Variant proteins stimulate more IgM+ GC B-cells revealing a mechanism of cross-reactive recognition by antibody memory

Vaccines induce memory B-cells that provide high affinity secondary antibody responses to identical antigens. Memory B-cells can also re-instigate affinity maturation, but how this happens against antigenic variants is poorly understood despite its potential impact on driving broadly protective immunity against pathogens such as Influenza and Dengue. We immunised mice sequentially with identical or variant Dengue-virus envelope proteins and analysed antibody and germinal-centre (GC) responses. Variant protein boosts induced GCs with a higher proportion of IgM+ B cells. The most variant protein re-stimulated GCs with the highest proportion of IgM+ cells with the most diverse, least mutated V-genes and with a slower but efficient serum antibody response. Recombinant antibodies from GC B-cells showed a higher affinity for the variant antigen than antibodies from a primary response, confirming a memory origin. This reveals a new process of antibody memory, that IgM memory cells with fewer mutations participate in secondary responses to variant antigens, demonstrating how the hierarchical structure of B-cell memory is used and indicating the potential and limits of cross-reactive antibody based immunity.

Immunogenicity in Rabbits of HIV-1 SOSIP Trimers from Clades A, B, and C, Given Individually, Sequentially, or in Combination

Recombinant soluble HIV-1 envelope glycoprotein (Env) SOSIP trimers are a design platform for inducing broadly neutralizing antibodies (bNAbs) by vaccination. To date, these and alternative designs of native-like trimers, given singly or in pairs, have not induced bNAbs in test animals such as rabbits or macaques. Here, we have evaluated whether trivalent and tetravalent combinations of SOSIP trimers from clades A, B, and C, delivered simultaneously or sequentially, induce better neutralizing antibody responses in rabbits than when given alone. None of the tested formulations led to the induction of bNAbs. We found that BG505 clade A trimers dominated the autologous NAb responses induced by combinations, which probably relates to the presence of immunodominant glycan holes on the BG505 trimer. Furthermore, autologous NAb responses to all individual trimers were reduced when they were delivered in combinations compared with when delivered alone, suggesting that immunogen interference had occurred. Finally, in a sequential regimen, a heterologous clade C trimer cross-boosted NAb responses that were primed by earlier immunizations with clade A and B trimers. Taken together, these findings should allow us to improve the design of immunization regimens based on native-like HIV-1 Env trimers.IMPORTANCE A successful HIV-1 vaccine most probably requires a trimeric envelope glycoprotein (Env) component, as Env is the only viral protein on the surface of the virus and therefore the only target for neutralizing antibodies. Native-like Env trimers can induce strain-specific neutralizing antibodies but not yet broadly neutralizing antibodies. To try to broaden the antibody response, we immunized rabbits with soluble native-like Env trimers from three different clades using monovalent, multivalent, and sequential regimens. We found that the neutralizing antibody response against each immunogen was reduced when the immunogens were delivered in combination or sequentially compared to the monovalent regimen. In contrast, when the Env trimers from different clades were delivered sequentially, the neutralizing antibody response could be cross-boosted. Although the combination of native-like Env trimers from different clades did not induce broadly neutralizing antibodies, the results provide clues on how to use native-like trimers in vaccination experiments.

Role of framework mutations and antibody flexibility in the evolution of broadly neutralizing antibodies

Eliciting antibodies that are cross reactive with surface proteins of diverse strains of highly mutable pathogens (e.g., HIV, influenza) could be key for developing effective universal vaccines. Mutations in the framework regions of such broadly neutralizing antibodies (bnAbs) have been reported to play a role in determining their properties. We used molecular dynamics simulations and models of affinity maturation to study specific bnAbs against HIV. Our results suggest that there are different classes of evolutionary lineages for the bnAbs. If germline B cells that initiate affinity maturation have high affinity for the conserved residues of the targeted epitope, framework mutations increase antibody rigidity as affinity maturation progresses to evolve bnAbs. If the germline B cells exhibit weak/moderate affinity for conserved residues, an initial increase in flexibility via framework mutations may be required for the evolution of bnAbs. Subsequent mutations that increase rigidity result in highly potent bnAbs. Implications of our results for immunogen design are discussed.

Fitness landscape of the human immunodeficiency virus envelope protein that is targeted by antibodies

HIV is a highly mutable virus, and over 30 years after its discovery, a vaccine or cure is still not available. The isolation of broadly neutralizing antibodies (bnAbs) from HIV-infected patients has led to renewed hope for a prophylactic vaccine capable of combating the scourge of HIV. A major challenge is the design of immunogens and vaccination protocols that can elicit bnAbs that target regions of the virus's spike proteins where the likelihood of mutational escape is low due to the high fitness cost of mutations. Related challenges include the choice of combinations of bnAbs for therapy. An accurate representation of viral fitness as a function of its protein sequences (a fitness landscape), with explicit accounting of the effects of coupling between mutations, could help address these challenges. We describe a computational approach that has allowed us to infer a fitness landscape for gp160, the HIV polyprotein that comprises the viral spike that is targeted by antibodies. We validate the inferred landscape through comparisons with experimental fitness measurements, and various other metrics. We show that an effective antibody that prevents immune escape must selectively bind to high escape cost residues that are surrounded by those where mutations incur a low fitness cost, motivating future applications of our landscape for immunogen design.

Structural Features of Broadly Neutralizing Antibodies and Rational Design of Vaccine

Despite sequence diversity, glycosylation, and conformational flexibility of the human immunodeficiency virus type 1 (HIV-1) envelope (Env), antibodies that neutralize diverse HIV-1 strains develop in selected HIV-1-infected individuals. The application of single B cell-based approaches has identified many broad and potent human antibodies from infected donors. Structural studies on antibody recognition of HIV Env have revealed that these broadly reactive antibodies target epitopes covering entire exposed and glycosylated surface on the viral spike; several classes of antibodies recognize the viral spike with converged modes. Critical structural features, such as antibody mimicry of cellular receptors, enable effective HIV-1 neutralization. However, other structural and genetic features, such as long CDR H3, fixed length of CDR L3, restricted germline usage, and high rate of somatic hypermutation, may explain the difficulties in eliciting these antibodies by vaccination. Accumulating information on antibody recognition of HIV-1 Env and ontogenesis suggests distinct pathways for generating effective HIV-1 vaccine based on specific antibody ontogeny or specific target site.

EDiP: the Epitope Dilution Phenomenon. Lessons learnt from a malaria vaccine antigen and its applicability to polymorphic antigens

INTRODUCTION

Polymorphism in vaccine antigens poses major challenges to vaccinologists. The Plasmodium falciparum Apical Membrane Antigen 1 (AMA1) poses such a challenge. We found that immunization with a mixture of three variants yielded functional antibody levels to all variants comparable to levels induced by monovalent immunization. The mechanism behind the observed broadening was shown to be an increase in the fraction of cross-reactive antibodies, most likely because strain-specific epitopes are present at lower frequency relative to conserved epitopes. Areas covered: We hereby introduce the Epitope Dilution Phenomenon (EDiP) as a practical strategy for the induction of broad, cross-variant antibody responses against polymorphic antigens and discuss the utility and applicability of this phenomenon for the development of vaccines against polymorphic antigens of pathogens like Influenza, HIV, Dengue and Plasmodium. Expert commentary: EDiP can be used to broaden antibody responses by immunizing with a mixture of at least 3 antigenic variants, where the variants included can differ, yet yield broadened responses.

How Germinal Centers Evolve Broadly Neutralizing Antibodies: the Breadth of the Follicular Helper T Cell Response

Many HIV-1-infected patients evolve broadly neutralizing antibodies (bnAbs). This evolutionary process typically takes several years and is poorly understood as selection taking place in germinal centers occurs on the basis of antibody affinity. B cells with the highest-affinity receptors tend to acquire the most antigen from the follicular dendritic cell (FDC) network and present the highest density of cognate peptides to follicular helper T (Tfh) cells, which provide survival signals to the B cell. bnAbs are therefore expected to evolve only when the B cell lineage evolving breadth is consistently capturing and presenting more peptides to Tfh cells than other lineages of more specific B cells. Here we develop mathematical models of Tfh cells in germinal centers to explicitly define the mechanisms of selection in this complex evolutionary process. Our results suggest that broadly reactive B cells presenting a high density of peptides bound to major histocompatibility complex class II molecules (pMHC) are readily outcompeted by B cells responding to lineages of HIV-1 that transiently dominate the within host viral population. Conversely, if broadly reactive B cells acquire a large variety of several HIV-1 proteins from the FDC network and present a high diversity of several pMHC, they can be rescued by a large fraction of the Tfh cell repertoire in the germinal center. Under such circumstances the evolution of bnAbs is much more consistent. Increasing either the magnitude of the Tfh cell response or the breadth of the Tfh cell repertoire markedly facilitates the evolution of bnAbs. Because both the magnitude and breadth can be increased by vaccination with several HIV-1 proteins, this calls for experimental testing.IMPORTANCE Many HIV-infected patients slowly evolve antibodies that can neutralize a large variety of viruses. Such broadly neutralizing antibodies (bnAbs) could in the future become therapeutic agents. bnAbs appear very late, and patients are typically not protected by them. At the moment, we fail to understand why this takes so long and how the immune system selects for broadly neutralizing capacity. Typically, antibodies are selected based on affinity and not on breadth. We developed mathematical models to study two different mechanisms by which the immune system can select for broadly neutralizing capacity. One of these is based upon the repertoire of different follicular helper T (Tfh) cells in germinal centers. We suggest that broadly reactive B cells may interact with a larger fraction of this repertoire and demonstrate that this would select for bnAbs. Intriguingly, this suggests that broadening the Tfh cell repertoire by vaccination may speed up the evolution of bnAbs.

A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy

Checkpoint blockade immunotherapies enable the host immune system to recognize and destroy tumour cells. Their clinical activity has been correlated with activated T-cell recognition of neoantigens, which are tumour-specific, mutated peptides presented on the surface of cancer cells. Here we present a fitness model for tumours based on immune interactions of neoantigens that predicts response to immunotherapy. Two main factors determine neoantigen fitness: the likelihood of neoantigen presentation by the major histocompatibility complex (MHC) and subsequent recognition by T cells. We estimate these components using the relative MHC binding affinity of each neoantigen to its wild type and a nonlinear dependence on sequence similarity of neoantigens to known antigens. To describe the evolution of a heterogeneous tumour, we evaluate its fitness as a weighted effect of dominant neoantigens in the subclones of the tumour. Our model predicts survival in anti-CTLA-4-treated patients with melanoma and anti-PD-1-treated patients with lung cancer. Importantly, low-fitness neoantigens identified by our method may be leveraged for developing novel immunotherapies. By using an immune fitness model to study immunotherapy, we reveal broad similarities between the evolution of tumours and rapidly evolving pathogens.

What Are the Most Powerful Immunogen Design Vaccine Strategies? Reverse Vaccinology 2.0 Shows Great Promise

Functional antibodies, i.e., those with antipathogen activity in in vitro assays, are generally the best correlate of vaccine protection. Mimics of natural infection, including live attenuated and killed pathogens, which induce such antibodies in vivo, have generated highly successful vaccines. However, pathogens that induce functional antibodies at lower levels or more sporadically have been more refractory to vaccine design. Such pathogens are being tackled by more systematic approaches involving identifying functional antibodies, templating immunogens from the antibodies, and then evaluating the immunogens iteratively. I believe this is a powerful new approach to vaccine design as discussed below.

Development of an anti-HIV vaccine eliciting broadly neutralizing antibodies

The extreme HIV diversity posts a great challenge on development of an effective anti-HIV vaccine. To solve this problem, it is crucial to discover an appropriate immunogens and strategies that are able to prevent the transmission of the diverse viruses that are circulating in the world. Even though there have been a number of broadly neutralizing anti-HIV antibodies (bNAbs) been discovered in recent years, induction of such antibodies to date has only been observed in HIV-1 infection. Here, in this mini review, we review the progress in development of HIV vaccine in eliciting broad immune response, especially production of bNAbs, discuss possible strategies, such as polyvalent sequential vaccination, that facilitates B cell maturation leading to bNAb response.

A Population Dynamics Model for Clonal Diversity in a Germinal Center

Germinal centers (GCs) are micro-domains where B cells mature to develop high affinity antibodies. Inside a GC, B cells compete for antigen and T cell help, and the successful ones continue to evolve. New experimental results suggest that, under identical conditions, a wide spectrum of clonal diversity is observed in different GCs, and high affinity B cells are not always the ones selected. We use a birth, death and mutation model to study clonal competition in a GC over time. We find that, like all evolutionary processes, diversity loss is inherently stochastic. We study two selection mechanisms, birth-limited and death limited selection. While death limited selection maintains diversity and allows for slow clonal homogenization as affinity increases, birth limited selection results in more rapid takeover of successful clones. Finally, we qualitatively compare our model to experimental observations of clonal selection in mice.

Modeling Kick-Kill Strategies toward HIV Cure

Although combinatorial antiretroviral therapy (cART) potently suppresses the virus, a sterile or functional cure still remains one of the greatest therapeutic challenges worldwide. Reservoirs are infected cells that can maintain HIV persistence for several years in patients with optimal cART, which is a leading obstacle to eradicate the virus. Despite the significant progress that has been made in our understanding of the diversity of cells that promote HIV persistence, many aspects that are critical to the development of effective therapeutic approaches able to purge the latent CD4+ T cell reservoir are poorly understood. Simultaneous purging strategies known as “kick-kill” have been pointed out as promising therapeutic approaches to eliminate the viral reservoir. However, long-term outcomes of purging strategies as well as the effect on the HIV reservoir are still largely fragmented. In this context, mathematical modeling can provide a rationale not only to evaluate the impact on the HIV reservoir but also to facilitate the formulation of hypotheses about potential therapeutic strategies. This review aims to discuss briefly the most recent mathematical modeling contributions, harnessing our knowledge toward the uncharted territory of HIV eradication. In addition, problems associated with current models are discussed, in particular, mathematical models consider only T cell responses but HIV control may also depend on other cell responses as well as chemokines and cytokines dynamics.