Host-Pathogen Coevolution and the Emergence of Broadly Neutralizing Antibodies in Chronic Infections

Abstract

The vertebrate adaptive immune system provides a flexible and diverse set of molecules to neutralize pathogens. Yet, viruses such as HIV can cause chronic infections by evolving as quickly as the adaptive immune system, forming an evolutionary arms race. Here we introduce a mathematical framework to study the coevolutionary dynamics between antibodies and antigens within a host. We focus on changes in the binding interactions between the antibody and antigen populations, which result from the underlying stochastic evolution of genotype frequencies driven by mutation, selection, and drift. We identify the critical viral and immune parameters that determine the distribution of antibody-antigen binding affinities. We also identify definitive signatures of coevolution that measure the reciprocal response between antibodies and viruses, and we introduce experimentally measurable quantities that quantify the extent of adaptation during continual coevolution of the two opposing populations. Using this analytical framework, we infer rates of viral and immune adaptation based on time-shifted neutralization assays in two HIV-infected patients. Finally, we analyze competition between clonal lineages of antibodies and characterize the fate of a given lineage in terms of the state of the antibody and viral populations. In particular, we derive the conditions that favor the emergence of broadly neutralizing antibodies, which may have relevance to vaccine design against HIV.

The size of the immune repertoire of bacteria

“…For both vertebrates and bacteria, a major challenge is to characterize dynamics of the immune system as it chases a diverse pathogenic population that is itself evolving to evade detection by its hosts. This out-ofequilibrium process can last over an extended evolutionary period [27]. Most models, including the one presented here, ignore these dynamical aspects of the co-evolving CRISPR-phage system, which may partly influence the statistics of stored memory, including the optimal cassette length.…”

A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy

“…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 tumors and rapidly evolving pathogens 7–9 . …”

“…1). Analogous fitness models based on immune interactions have been successfully applied to human influenza 7 , HIV 8 and chronic viral infections 9 . Checkpoint blockade exposes cancer cells to strong immune pressure on their neoantigens, reducing their reproductive success.…”

The genetic interaction between HIV and the antibody repertoire

“…Doria-Rose et al, 2010;Landais et al, 2016;Piantadosi et al, 2009). An interesting future study would be to use mathematical modeling (Nourmohammad, Otwinowski, & Plotkin, 2016), or simulation frameworks (Murugan et al, 2018) that include the introduction of novel naïve Ab lineages into the population, to gain a better understanding of which evolutionary parameters (e.g. population size, mutation rate, selection strength, population diversity, etc.)…”