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

2020 ◽  
Author(s):  
Marco Molari ◽  
Klaus Eyer ◽  
Jean Baudry ◽  
Simona Cocco ◽  
Rémi Monasson

AbstractAffinity 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 modelling and statistical inference is a concrete way to investigate biological processes underlying affinity maturation (such as selection permissiveness), hardly accessible through measurements.

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Marco Molari ◽  
Klaus Eyer ◽  
Jean Baudry ◽  
Simona Cocco ◽  
Rémi Monasson

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.


2020 ◽  
Vol 117 (23) ◽  
pp. 12693-12699 ◽  
Author(s):  
Vedant Sachdeva ◽  
Kabir Husain ◽  
Jiming Sheng ◽  
Shenshen Wang ◽  
Arvind Murugan

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.


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