Understanding repertoire sequencing data through a multiscale computational model of the germinal center

Author:

García-Valiente RodrigoORCID,Merino Tejero Elena,Stratigopoulou Maria,Balashova DariaORCID,Jongejan AldoORCID,Lashgari Danial,Pélissier Aurélien,Caniels Tom G.,Claireaux Mathieu A. F.,Musters Anne,van Gils Marit J.ORCID,Rodríguez Martínez MaríaORCID,de Vries NiekORCID,Meyer-Hermann MichaelORCID,Guikema Jeroen E. J.ORCID,Hoefsloot HuubORCID,van Kampen Antoine H. C.ORCID

Abstract

AbstractSequencing of B-cell and T-cell immune receptor repertoires helps us to understand the adaptive immune response, although it only provides information about the clonotypes (lineages) and their frequencies and not about, for example, their affinity or antigen (Ag) specificity. To further characterize the identified clones, usually with special attention to the particularly abundant ones (dominant), additional time-consuming or expensive experiments are generally required. Here, we present an extension of a multiscale model of the germinal center (GC) that we previously developed to gain more insight in B-cell repertoires. We compare the extent that these simulated repertoires deviate from experimental repertoires established from single GCs, blood, or tissue. Our simulations show that there is a limited correlation between clonal abundance and affinity and that there is large affinity variability among same-ancestor (same-clone) subclones. Our simulations suggest that low-abundance clones and subclones, might also be of interest since they may have high affinity for the Ag. We show that the fraction of plasma cells (PCs) with high B-cell receptor (BcR) mRNA content in the GC does not significantly affect the number of dominant clones derived from single GCs by sequencing BcR mRNAs. Results from these simulations guide data interpretation and the design of follow-up experiments.

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Drug Discovery,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation

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