The GC reaction begins with the activation of a limited number of antigen (Ag)-specific B cells that start to proliferate (clonal expansion) to form the so-called GC dark zone (DZ), as defined by histology staining. These structures are responsible for a process called affinity maturation during which the affinity and specificity of the BcR for the Ag is improved over the course of several weeks. GCs are microanatomical structures found in secondary lymphoid organs and are formed when an adaptive response is initiated. The germinal center (GC) plays a crucial role in the adaptive immune response 1, 2, 3. Results from these simulations guide data interpretation and the design of follow-up experiments. 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. Our simulations suggest that low-abundance clones and subclones, might also be of interest since they may have high affinity for the Ag. 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. We compare the extent that these simulated repertoires deviate from experimental repertoires established from single GCs, blood, or tissue. 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. 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. Sequencing 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. Npj Systems Biology and Applications volume 9, Article number: 8 ( 2023) Understanding repertoire sequencing data through a multiscale computational model of the germinal center
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