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Computational Model Reveals a Stochastic Mechanism behind Germinal Center Clonal Bursts

Germinal centers (GCs) are specialized compartments within the secondary lymphoid organs where B cells proliferate, differentiate, and mutate their antibody genes in response to the presence of foreign antigens. Through the GC lifespan, interclonal competition between B cells leads to increased affi...

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Autores principales: Pélissier, Aurélien, Akrout, Youcef, Jahn , Katharina, Kuipers , Jack, Klein , Ulf, Beerenwinkel, Niko, Rodríguez Martínez , María
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349200/
https://www.ncbi.nlm.nih.gov/pubmed/32532145
http://dx.doi.org/10.3390/cells9061448
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author Pélissier, Aurélien
Akrout, Youcef
Jahn , Katharina
Kuipers , Jack
Klein , Ulf
Beerenwinkel, Niko
Rodríguez Martínez , María
author_facet Pélissier, Aurélien
Akrout, Youcef
Jahn , Katharina
Kuipers , Jack
Klein , Ulf
Beerenwinkel, Niko
Rodríguez Martínez , María
author_sort Pélissier, Aurélien
collection PubMed
description Germinal centers (GCs) are specialized compartments within the secondary lymphoid organs where B cells proliferate, differentiate, and mutate their antibody genes in response to the presence of foreign antigens. Through the GC lifespan, interclonal competition between B cells leads to increased affinity of the B cell receptors for antigens accompanied by a loss of clonal diversity, although the mechanisms underlying clonal dynamics are not completely understood. We present here a multi-scale quantitative model of the GC reaction that integrates an intracellular component, accounting for the genetic events that shape B cell differentiation, and an extracellular stochastic component, which accounts for the random cellular interactions within the GC. In addition, B cell receptors are represented as sequences of nucleotides that mature and diversify through somatic hypermutations. We exploit extensive experimental characterizations of the GC dynamics to parameterize our model, and visualize affinity maturation by means of evolutionary phylogenetic trees. Our explicit modeling of B cell maturation enables us to characterise the evolutionary processes and competition at the heart of the GC dynamics, and explains the emergence of clonal dominance as a result of initially small stochastic advantages in the affinity to antigen. Interestingly, a subset of the GC undergoes massive expansion of higher-affinity B cell variants (clonal bursts), leading to a loss of clonal diversity at a significantly faster rate than in GCs that do not exhibit clonal dominance. Our work contributes towards an in silico vaccine design, and has implications for the better understanding of the mechanisms underlying autoimmune disease and GC-derived lymphomas.
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spelling pubmed-73492002020-07-22 Computational Model Reveals a Stochastic Mechanism behind Germinal Center Clonal Bursts Pélissier, Aurélien Akrout, Youcef Jahn , Katharina Kuipers , Jack Klein , Ulf Beerenwinkel, Niko Rodríguez Martínez , María Cells Article Germinal centers (GCs) are specialized compartments within the secondary lymphoid organs where B cells proliferate, differentiate, and mutate their antibody genes in response to the presence of foreign antigens. Through the GC lifespan, interclonal competition between B cells leads to increased affinity of the B cell receptors for antigens accompanied by a loss of clonal diversity, although the mechanisms underlying clonal dynamics are not completely understood. We present here a multi-scale quantitative model of the GC reaction that integrates an intracellular component, accounting for the genetic events that shape B cell differentiation, and an extracellular stochastic component, which accounts for the random cellular interactions within the GC. In addition, B cell receptors are represented as sequences of nucleotides that mature and diversify through somatic hypermutations. We exploit extensive experimental characterizations of the GC dynamics to parameterize our model, and visualize affinity maturation by means of evolutionary phylogenetic trees. Our explicit modeling of B cell maturation enables us to characterise the evolutionary processes and competition at the heart of the GC dynamics, and explains the emergence of clonal dominance as a result of initially small stochastic advantages in the affinity to antigen. Interestingly, a subset of the GC undergoes massive expansion of higher-affinity B cell variants (clonal bursts), leading to a loss of clonal diversity at a significantly faster rate than in GCs that do not exhibit clonal dominance. Our work contributes towards an in silico vaccine design, and has implications for the better understanding of the mechanisms underlying autoimmune disease and GC-derived lymphomas. MDPI 2020-06-10 /pmc/articles/PMC7349200/ /pubmed/32532145 http://dx.doi.org/10.3390/cells9061448 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pélissier, Aurélien
Akrout, Youcef
Jahn , Katharina
Kuipers , Jack
Klein , Ulf
Beerenwinkel, Niko
Rodríguez Martínez , María
Computational Model Reveals a Stochastic Mechanism behind Germinal Center Clonal Bursts
title Computational Model Reveals a Stochastic Mechanism behind Germinal Center Clonal Bursts
title_full Computational Model Reveals a Stochastic Mechanism behind Germinal Center Clonal Bursts
title_fullStr Computational Model Reveals a Stochastic Mechanism behind Germinal Center Clonal Bursts
title_full_unstemmed Computational Model Reveals a Stochastic Mechanism behind Germinal Center Clonal Bursts
title_short Computational Model Reveals a Stochastic Mechanism behind Germinal Center Clonal Bursts
title_sort computational model reveals a stochastic mechanism behind germinal center clonal bursts
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349200/
https://www.ncbi.nlm.nih.gov/pubmed/32532145
http://dx.doi.org/10.3390/cells9061448
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