Biology subjects

Dixit, N. M.

Publications and source records attributed to Dixit, N. M..

15 recordsLinked to original sources

bioRxiv2026

Decoding Clade-Specific bNAb-HIV-1 Env Interactions Using Machine Learning

Human immunodeficiency virus type 1 (HIV-1) exhibits extensive genetic diversity, posing a major challenge to AIDS vaccine development. Broadly neutralizing antibodies (bNAbs) isolated from HIV-1-infected individuals offer valuable templates for designing broadly protective immunogens. Here, structural and energetic descriptors extracted from experimentally resolved bNAb/HIV-1 Envelope (Env) protein-protein complexes were used to develop machine-learning (ML) models predicting binding free energies ({triangleup}G) and dissociation constants (KD) across multiple HIV-1 clades. Among the algorithms evaluated, extreme gradient boosting (XGBoost) achieved the best predictive performance, with training and test R2 values of 0.92 and 0.658, respectively. Applying the optimized model to HIV-1 datasets revealed clade-dependent binding patterns, with clade B showing the greatest variability and clade G exhibiting signatures associated with reduced neutralization potency. Predicted {triangleup}G of different bNAb classes followed the trend gp120-gp41 interface {approx} fusion domain > CD4 binding site (CD4bs) > V1V2 loop {approx} V3-glycan, consistent with experimentally reported affinity profiles of benchmark bNAbs. Clade C exhibited intermediate {triangleup}G with PGT121, VRC01, and 10-1074 maintaining high-affinity interactions, whereas PG9 and 2G12 show reduced binding affinity. These findings offer quantitative insight into clade-specific bNAb binding energetics and demonstrate the potential of machine-learning approaches to guide HIV-1 immunogen design and vaccine development.

biochemistry↗

bioRxiv2026

Modeling how memory CD8 T cells can elicit post-treatment control of HIV infection

While most people living with HIV suffer progressive disease following cessation of antiretroviral therapy, a small fraction elicits lasting post-treatment control. Understanding the mechanisms underlying this control is key to devising effective HIV remission strategies. Although recent studies implicate memory CD8 T cells, how these cells establish lasting viremic control remains unknown. Here, we combine mathematical modeling and analysis of data from SIV-infected non-human primates to elucidate the underlying mechanisms. We recognized that sustained antigenic stimulation leads to heritable epigenetic remodeling of the CD8 T cell pool, impairing memory cell survivability. Antiretroviral therapy rapidly suppresses viremia, thereby arresting antigenic stimulation and preserving memory potential. The greater this preservation is, the better would be the memory recall response following viral rebound post-treatment. Our mathematical model based on this hypothesis predicts that post-treatment control is an alternative steady state to progressive infection, realized by strong memory-driven recall responses. Our model fits longitudinal virological data spanning the pre-, during-, and post-antiretroviral treatment phases of infection, and recapitulates the outcomes of progressive disease and long-term remission realized, the latter predominantly with early treatment initiation. It shows, consistently with data, that memory CD8 T cells could drive post-treatment control independently of the size of the latent reservoir, explaining how such control may be realized more widely than estimated with prevalent hypotheses. Our model further explains the existence of a window of treatment initiation times that maximizes the chances of post-treatment control. Finally, model predictions inform interventions targeting memory CD8 T cells for HIV remission.

immunology↗

bioRxiv2025

Clade-specific influences of glycans on the interactions between HIV-1 envelope and broadly neutralizing antibodies

N-linked glycans are important in the elicitation and the activity of many broadly neutralizing antibodies (bNAbs) against HIV-1. The high conformational flexibility of glycans hindered detailed atomistic investigations of glycan-bNAb interactions, including glycan shielding of bN-Abs. Importantly, how these interactions vary across different HIV-1 clades remains unclear. The variability in the number and location of potential N-linked glycosylation sites (PNGS) on the HIV-1 envelope (Env) protein across clades can lead to differences in glycan dynamics and topology, potentially affecting Env-bNAb interactions and the clade-specific efficacy of bNAb-based therapies. Here, we combined comprehensive glycan conformational sampling, using the software glycoSHIELD, and molecular dynamics (MD) simulations to model fully glycosylated trimeric Env for six HIV-1 strains, one from each of the major clades A, B, C, G, CRF01 AE (01 AE) and CRF07 BC (07 BC). We assessed the interactions of 50 different bNAbs, drawn from all the major bNAb classes, with each of these strains, quantifying glycan shielding, glycan-bNAb interactions, and their clade-specific variations for each bNAb in microscopic detail. Our findings reveal that while glycans cover most of the exposed surface area in all clades, the amount of accessible surface varies, with clade B having the minimum and clade 07 BC the maximum antibody accessible surface area. The number of glycan conformers per glycosylation site also varies with clades, even for conserved sites. Overall, we observed that bNAbs interact with more glycans than previously reported in experimental and computational studies. Important variations emerge in Env-bNAb interactions with clade and bNAb-class. These atomic-level insights will be valuable for improving bNAb-based therapies and vaccine design strategies against HIV-1. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/655089v2_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@eedc04org.highwire.dtl.DTLVardef@1aebf67org.highwire.dtl.DTLVardef@1982a02org.highwire.dtl.DTLVardef@ee08e5_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2024

Disentangling competitive and cooperative components of the interactions between microbial species

Interactions between microbial species have been characterized by the net influences, positive or negative, that each species in a pair exerts on the other. This conventional view of interactions being either positive or negative proves restrictive in predicting the behaviour of microbial communities and, more importantly, influencing them towards desired community structures. Here, we propose a more fundamental characterization of the interactions. The net interactions typically comprise positive and negative underlying components. Yet, the conventional view prevails because the components have been difficult to disentangle. We have developed a methodology to disentangle them when metabolic interactions predominate. We conceived a theoretical resource partitioning between species that helps estimate the positive components. The negative components then follow from knowledge of the net interactions. The interactions between two species are then characterized by the quartet of these components. We applied the methodology in silico to 28 species pairs from the human oral microbiome, yielding 56 net interactions and their 112 quartet components. We found that on average the net interactions comprised positive and negative components of comparable strengths. Interestingly, weak net interactions often arose from the cancellation of strong underlying components. Furthermore, we found species pairs with similar net interactions but vastly different underlying components. Extant community ecology theories, based on net interactions, cannot distinguish between such pairs. The quartet explained several confounding experimental observations and offered new insights into microbial community ecology. We envision its implications in the construction of more refined ecological theories and the engineering of synthetic microbial communities.

ecology↗

bioRxiv2023

Antiviral capacity of the early CD8 T-cell response is predictive of natural control of SIV infection

While most individuals suffer progressive disease following HIV infection, a small fraction spontaneously controls the infection. Although CD8 T-cells have been implicated in this natural control, their mechanistic roles are yet to be established. Here, we combined mathematical modeling and analysis of data from 16 SIV-infected macaques, of which 12 were natural controllers, to elucidate the role of CD8 T-cells in natural control. For each macaque, we considered, in addition to the canonical in vivo plasma viral load and SIV DNA data, longitudinal ex vivo measurements of the virus suppressive capacity of CD8 T-cells. Available mathematical models do not allow analysis of such combined in vivo-ex vivo datasets. By explicitly modeling the ex vivo assay and integrating it with in vivo dynamics, we developed a new framework that enabled the analysis. Our model fit the data well and estimated that the recruitment rate and/or maximal killing rate of CD8 T-cells was up to 2-fold higher in controllers than non-controllers (p=0.013). Importantly, the cumulative suppressive capacity of CD8 T-cells over the first 4-6 weeks of infection was associated with virus control (Spearmans {rho}=- 0.51; p=0.05). Thus, our analysis identified the early cumulative suppressive capacity of CD8 T-cells as a predictor of natural control. Furthermore, simulating a large virtual population, our model quantified the minimum capacity of this early CD8 T-cell response necessary for long-term control. Our study presents new, quantitative insights into the role of CD8 T-cells in the natural control of HIV infection and has implications for remission strategies.

microbiology↗

bioRxiv2022

Molecular Dynamics Simulations Show How Antibodies May Rescue HIV-1 Mutants Incapable of Infecting Host Cells

High mutation and replication rates of HIV-1 result in the continuous generation of variants, allowing it to adapt to changing host environments. Mutations often have deleterious effects, but variants carrying them are rapidly purged. Surprisingly, a particular variant incapable of entering host cells was found to be rescued by host antibodies targeting HIV-1. Understanding the molecular mechanism of this rescue is important to develop and improve antibody-based therapies. To unravel the underlying mechanisms, we performed fully atomistic molecular dynamics simulations of the HIV-1 gp41 trimer responsible for viral entry into host cells, its entry-deficient variant, and its complex with the rescuing antibody. We find that the Q563R mutation, which the entry-deficient variant carries, prevents the native conformation of the gp41 6-helix bundle required for entry and stabilizes an alternative conformation instead. This is the consequence of substantial changes in the secondary structure and interactions between the domains of gp41. Binding of the antibody F240 to gp41 reverses these changes and re-establishes the native conformation, resulting in rescue. To test the generality of this mechanism, we performed simulations with the entry-deficient L565A variant and antibody 3D6. We find that 3D6 binding was able to reverse structural and interaction changes introduced by the mutation and restore the native gp41 conformation. Viral variants may not only escape antibodies but be aided by them in their survival, potentially compromising antibody-based therapies, including vaccination and passive immunization. Our simulation framework could serve as a tool to assess the likelihood of such resistance against specific antibodies.

biophysics↗

bioRxiv2022

An evolutionary paradigm favoring crosstalk between bacterial two-component signaling systems

The prevalent paradigm governing bacterial two-component signaling systems (TCSs) is specificity, wherein the histidine kinase (HK) of a TCS exclusively activates its cognate response regulator (RR). Crosstalk, where HKs activate noncognate RRs, is considered evolutionarily disadvantageous because it can compromise adaptive responses by leaking signals. Yet, crosstalk is observed in several bacteria. Here, to resolve this paradox, we propose an alternative paradigm where crosstalk can be advantageous. We envisioned programmed environments, wherein signals appear in predefined sequences. In such environments, crosstalk that primes bacteria to upcoming signals may improve adaptive responses and confer evolutionary benefits. To test this hypothesis, we employed mathematical modeling of TCS signaling networks and stochastic evolutionary dynamics simulations. We considered the comprehensive set of bacterial phenotypes, comprising thousands of distinct crosstalk patterns, competing in varied signaling environments. Our simulations predicted that in programmed environments phenotypes with crosstalk facilitating priming would outcompete phenotypes without crosstalk. In environments where signals appear randomly, bacteria without crosstalk would dominate, explaining the specificity widely seen. Additionally, a testable prediction was that the phenotypes selected in programmed environments would display one-way crosstalk, ensuring priming to future signals. Interestingly, the crosstalk networks we deduced from available data on TCSs of Mycobacterium tuberculosis all displayed one-way crosstalk, offering strong support to our predictions. Our study thus identifies potential evolutionary underpinnings of crosstalk in bacterial TCSs, suggests a reconciliation of specificity and crosstalk, makes testable predictions of the nature of crosstalk patterns selected, and has implications for understanding bacterial adaptation and the response to interventions. IMPORTANCEBacteria use two-component signaling systems (TCSs) to sense and respond to environmental changes. The prevalent paradigm governing TCSs is specificity, where signal flow through TCSs is insulated; leakage to other TCSs is considered evolutionarily disadvantageous. Yet, crosstalk between TCSs is observed in many bacteria. Here, we present a potential resolution of this paradox. We envision programmed environments, wherein stimuli appear in predefined sequences. Crosstalk that primes bacteria to upcoming stimuli could then confer evolutionary benefits. We demonstrate this benefit using mathematical modeling and evolutionary simulations. Interestingly, we found signatures of predicted crosstalk patterns in Mycobacterium tuberculosis. Furthermore, specificity was selected in environments where stimuli occurred randomly, thus reconciling specificity and crosstalk. Implications follow for understanding bacterial evolution and for interventions.

microbiology↗

bioRxiv2022

Evidence of increased Cathepsin B/L and decreased TMPRSS2 usage for cell entry by the SARS-CoV-2 Omicron variant

The SARS-CoV-2 Omicron variant harbours mutations in its spike protein, which may affect its cell entry, tropism, and response to interventions. To elucidate these effects, we developed a mathematical model of SARS-CoV-2 entry into cells and applied it to analyse recent in vitro data. SARS-CoV-2 enters cells using host proteases, either Cathepsin B/L or TMPRSS2. We estimated >4-fold increase and >3-fold decrease in entry efficiency using Cathepsin B/L and TMPRSS2, respectively, of the Omicron variant relative to the original or other strains in a cell type-dependent manner. Our model predicted that Cathepsin B/L inhibitors would be more and TMPRSS2 inhibitors less efficacious against the Omicron than the original strain. Furthermore, the two inhibitor classes would exhibit synergy, although the drug concentrations maximizing synergy would have to be tailored to the Omicron variant. These findings provide insights into the cell entry mechanisms of the Omicron variant and have implications for interventions.

microbiology↗

bioRxiv2021

Sequestration of histidine kinases by non-cognate response regulators establishes a threshold level of stimulation for bacterial two-component signaling

Two-component signaling systems (TCSs) in bacteria are often positively auto-regulated, where the histidine kinase (HK) and response regulator (RR) proteins comprising a TCS are expressed downstream of the signal they transduce. This auto-regulation improves the sensitivity of the TCS to stimuli and amplifies adaptive responses. The downside, however, is that the TCS may mount disproportionately large responses to weak or fleeting signals. How bacteria prevent such disproportionate responses is not known. Here, we show that sequestration of phosphorylated HKs by non-cognate RRs serves as a design to prevent such disproportionate responses. Using TCSs of M. tuberculosis as model systems, we found that with every one of the five HKs we studied, there was at least one non-cognate RR with higher affinity than that of the cognate RR for the HK. Phosphorylated HKs would thus preferentially bind the non-cognate RRs, suppressing signal transduction through the cognate pathways, which we demonstrated in vitro. Using mathematical modeling of TCS signaling in vivo, we predicted that this sequestration would introduce a threshold level of stimulation for a significant response, preventing responses to signals below this threshold. Finally, we showed in vivo using tunable expression systems in M. bovis that upregulation of a higher affinity non-cognate RR substantially suppressed the output from the cognate TCS pathway, presenting strong evidence of sequestration by non-cognate RRs as a design to regulate TCS signaling. Blocking this sequestration may be a novel intervention strategy, as it would compromise bacterial fitness by letting it respond unnecessarily to signals.

systems biology↗

bioRxiv2021

Mechanistic Insights into the Effects of Key Mutations on SARS-CoV-2 RBD-ACE2 Binding

Some recent SARS-CoV-2 variants appear to have increased transmissibility than the original strain. An underlying mechanism could be the improved ability of the variants to bind receptors on target cells and infect them. In this study, we provide atomic-level insight into the binding of the receptor binding domain (RBD) of the wild-type SARS-CoV-2 spike protein and its single (N501Y), double (E484Q, L452R) and triple (N501Y, E484Q, L452R) mutated variants to the human ACE2 receptor. Using extensive all-atom molecular dynamics simulations and advanced free energy calculations, we estimate the associated binding affinities and binding hotspots. We observe significant secondary structural changes in the RBD of the mutants, which lead to different binding affinities. We find higher binding affinities of the double (E484Q, L452R) and triple (N501Y, E484Q, L452R) mutated variants than the wild type and the N501Y variant, which could contribute to the higher transmissibility of recent variants containing these mutations.

biophysics↗

bioRxiv2020

Concerted interactions between multiple gp41 trimers and the target cell lipidome may be required for HIV-1 entry

The HIV-1 envelope glycoprotein gp41 mediates the fusion between viral and host cell membranes leading to virus entry and target cell infection. Despite years of research, important aspects of this process such as the number of gp41 trimers involved and how they orchestrate the rearrangement of the lipids in the apposed membranes along the fusion pathway remain obscure. To elucidate these molecular underpinnings, we performed coarse-grained molecular dynamics simulations of HIV-1 virions pinned to the CD4 T cell membrane by different numbers of gp41 trimers. We built realistic cell and viral membranes by mimicking their respective lipid compositions. We found that a single gp41 was inadequate for mediating fusion. Lipid mixing between membranes, indicating the onset of fusion, was efficient when 3 or more gp41 trimers pinned the membranes. The gp41 trimers interacted strongly with many different lipids in the host cell membrane, triggering lipid configurational rearrangements, exchange, and mixing. Simpler membranes, comprising fewer lipid types, displayed strong resistance to fusion, revealing the crucial role of the lipidomes in HIV-1 entry. Performing simulations at different temperatures, we estimated the free energy barrier to lipid mixing, and hence membrane stalk formation, with 4 tethering gp41 trimers to be ~6.2 kcal/mol, a >4-fold reduction over estimates without gp41. Together, these findings present molecular-level, quantitative insights into the early stages of gp41-mediated HIV-1 entry. Preventing the requisite gp41 molecules from tethering the membranes or altering membrane lipid compositions may be potential intervention strategies. SIGNIFICANCEInteractions between viral envelope proteins and host cell surface receptors leading to HIV-1 entry are well studied, however the role of membrane lipids remains obscure, although entry hinges on lipid mixing and the fusion of viral and cell membranes. We performed detailed simulations of HIV-1 and target cell membranes tethered by viral gp41 trimeric proteins to elucidate the proteo-lipidic contributions to viral entry. We found that the cooperative effects of multiple gp41 trimers and natural lipidomes of the membranes facilitate membrane fusion. The functional domains of gp41 altered local lipid concentrations, reduced membrane repulsions, and facilitated inter-membrane lipid mixing. These molecular-level insights offer a glimpse of the cryptic mechanisms underlying HIV-1 entry and suggest new interventions to combat HIV-1 infection.

biophysics↗

bioRxiv2020

Pre-existing resistant proviruses can compromise maintenance of remission by VRC01 in chronic HIV-1 infection

Broadly neutralizing antibodies (bNAbs) of HIV-1 hold promise of eliciting long-term HIV-1 remission. Surprisingly, the bNAb VRC01, when administered concomitantly with the cessation of successful antiretroviral therapy (ART), failed rapidly in chronic HIV-1 patients. We hypothesized that the failure was due to VRC01-resistant strains that were formed before ART initiation, survived ART in latently infected cells, and were reactivated during VRC01 therapy. Current assay limitations preclude testing this hypothesis experimentally. We developed a mathematical model based on the hypothesis and challenged it with available clinical data. The model integrated within-host HIV-1 evolution, stochastic latency reactivation and viral dynamics with multiple dose VRC01 pharmacokinetics. With a virtual patient population, model predictions quantitatively captured data from two independent clinical trials. Accordingly, we attributed VRC01 failure to single-mutant VRC01-resistant proviruses in the latent reservoir triggering viral recrudescence, particularly during trough VRC01 levels. Accounting for pre-existing resistance may help bNAb therapies maximize HIV-1 remission.

microbiology↗

bioRxiv2019

Modeling how early passive immunization with broadly neutralizing antibodies elicits lasting control of SHIV infection

Antiretroviral therapy (ART) for HIV-1 infection is life-long. Stopping therapy typically leads to the reignition of infection and progressive disease. In a major breakthrough, recent studies have shown that early initiation of ART can lead to sustained post-treatment control of viremia, raising hopes of long-term HIV-1 remission. ART, however, elicits post-treatment control in a small fraction of individuals treated. Strikingly, passive immunization with broadly neutralizing antibodies (bNAbs) of HIV-1 early in infection was found recently to elicit long-term control in a majority of SHIV-infected macaques, suggesting that HIV-1 remission may be more widely achievable. The mechanisms underlying the control elicited by bNAb therapy, however, remain unclear. Untreated infection typically leads to progressive disease. We hypothesized that viremic control represents an alternative but rarely realized outcome of the infection and that early bNAb therapy triggers a dynamical switch to this outcome. To test this hypothesis, we constructed a model of viral dynamics with bNAb therapy and applied it to analyse clinical data. The model fit quantitatively the complex longitudinal viral load data from macaques that achieved lasting control. The model predicted, consistently with our hypothesis, that the underlying system exhibited bistability, indicating two potential outcomes of infection. The first had high viremia, weak cytotoxic effector responses, and high effector exhaustion, marking progressive disease. The second had low viremia, strong effector responses, and low effector exhaustion, indicating lasting viremic control. Further, model predictions suggest that early bNAb therapy elicited lasting control via pleiotropic effects. bNAb therapy lowers viremia, which would also limit immune exhaustion. Simultaneously, it can improve effector stimulation via cross-presentation. Consequently, viremia may resurge post-therapy, but would encounter a primed effector population and eventually get controlled. ART suppresses viremia but does not enhance effector stimulation, explaining its limited ability to elicit post-treatment control relative to bNAb therapy. Author SummaryIn a remarkable advance in HIV cure research, a recent study showed that 3 weekly doses of HIV-1 broadly neutralizing antibodies (bNAbs) soon after infection kept viral levels controlled for years in most macaques treated. If translated to humans, this bNAb therapy may elicit a functional cure, or long-term remission, of HIV-1 infection, eliminating the need for life-long antiretroviral therapy (ART). How early bNAb therapy works remains unknown. Here, we elucidate the mechanism using mathematical modeling and analysis of in vivo data. We predict that early bNAb therapy suppresses viremia, which reduces exhaustion of cytotoxic effector cells, and enhances antigen uptake and effector stimulation. Collectively, these effects drive infection to lasting control. Model predictions based on these effects fit in vivo data quantitatively. ART controls viremia but does not improve effector stimulation, explaining its weaker ability to induce lasting control post-treatment. Our findings may help improve strategies for achieving functional cure of HIV-1 infection.

immunology↗

bioRxiv2019

A dynamical motif comprising the interactions between antigens and CD8 T cells may underlie the outcomes of viral infections

Some viral infections culminate in very different outcomes in different individuals. They can be rapidly cleared in some, cause persistent infection in others, and mortality from immunopathology in yet others. The conventional view is that the different outcomes arise as a consequence of the complex interactions between a large number of different factors (virus, different immune cells and cytokines). Here, we identify a simple dynamical motif comprising the essential interactions between antigens and CD8 T cells and posit it as predominantly determining the outcomes. Antigen can activate CD8 T cells, which in turn can kill infected cells. Sustained antigen stimulation, however, can cause CD8 T cell exhaustion, compromising effector function. Using mathematical modelling, we show that the motif comprising these interactions recapitulates all the outcomes observed. The motif presents a new conceptual framework to understand the variable outcomes of infection. It also explains a number of confounding experimental observations, including the variation in outcomes with the viral inoculum size, the evolutionary advantage of exhaustion in preventing lethal pathology, the ability of NK cells to act as rheostats tuning outcomes, and the role of the innate immune response in the spontaneous clearance of hepatitis C. Interventions that modulate the interactions in the motif may present novel routes to clear persistent infections or limit immunopathology.

immunology↗

bioRxiv2018

Stochastic simulations show how passive immunization can influence the germinal centre reaction and optimize host humoral responses

Passive immunization with antigen-specific antibodies was shown recently to induce lasting improvements in endogenous antibody production, raising the prospect of using passive immunization as a tool to engineer host humoral responses. The mechanism with which administered antibodies alter endogenous antibody production remains unknown. B cells that produce antigen-specific antibodies evolve and get selected in germinal centres (GCs). This selection requires that B cells acquire antigen presented in GCs. We hypothesized that passive immunization biases this selection in favour of B cells with high affinities for antigen. Administered antibodies form immune complexes with antigen which only B cells with higher affinities than the administered antibodies for antigen can rupture and acquire antigen, thus increasing the selection stringency in GCs. With this mechanistic hypothesis, we constructed a stochastic simulation model of the GC reaction. The simulations recapitulated and synthesized several independent experimental observations, presenting strong evidence in support of our hypothesis. Further, the simulations revealed a quality-quantity trade-off constraining the GC response. As the selection stringency increased, surviving B cells had higher affinities for antigen but fewer B cells survived. Increasing antigen availability in the GC relaxed this constraint. The affinity of the administered antibodies and/or antigen availability could thus be tuned to maximize the GC output. Comprehensively spanning parameter space, we predict passive immunization protocols that exploit the quality-quantity trade-off and maximize the GC output. Our study thus presents a new conceptual understanding of the GC reaction and a computational framework for the rational optimization of passive immunization strategies.\n\nSignificance statementWhen natural antibody production is inadequate, passive immunization with external antibodies can alleviate disease. Remarkably, passive immunization induced lasting improvements in natural antibody production in recent studies, suggesting that it could be deployed to engineer natural antibody responses. However, how administered antibodies alter natural antibody production remains unknown. B cells that produce antibodies targeting specific antigen evolve in germinal centres (GCs). We hypothesized that administered antibodies form complexes with antigen, preferentially allowing B cells with higher affinities to acquire antigen and be selected, thus altering antibody production. With this mechanistic hypothesis, we performed stochastic simulations of the GC reaction, which recapitulated experiments, unravelled a quality-quantity trade-off constraining the GC response, and predicted passive immunization protocols that maximized the GC output.

immunology↗