Simulating affinity maturation under sequential SARS-CoV-2 infections

Part of the immune response upon infection involves B cells and a process known as affinity maturation. During affinity maturation, produced antibodies increase in affinity to presented antigen. Additionally, plasma B cells and memory B cells are created. This is to allow the system to remember and quickly mount a response to the presented antigen in the case of a repeat infection. Repeated exposures to the same antigen will produce antibodies of successively greater affinities. However, as antigen move away in antigenic distance from the initial strain (antigenic drift), the ability of the body to cross-reactively neutralize the antigen decreases. This issue has been well documented in cases of influenza and there is a concern it is occurring in SARS-CoV-2 given successive variants of concern (VOC). Such VOCs would be less susceptible to any immune protection gained from vaccination and prior infection. We modeled these processes using an agent-based model (ABM) that considers B cells (naïve, plasma, memory), antibodies, and antigens. We represent receptor (B cells, antibodies) and epitope (antigens) proteins in Euclidean shape space, simulating binding between these agents based on Hamming distance. We also consider the formation of immune complexes—free antibodies bound to antigen which limits the antigen’s ability to infect more cells. We simulated SARS-CoV-2 infections using our ABM. We present results that examine immune responses when presented with various VOCs and differing immune imprinting.

Simulating affinity maturation under sequential SARS-CoV-2 infections

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Jasmine Kreig

"Simulating affinity maturation under sequential SARS-CoV-2 infections"

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