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| Content Provider | frontiers |
|---|---|
| Author | Zhang, Chao Bzikadze, Andrey V. Safonova, Yana Mirarab, Siavash |
| Abstract | Affinity maturation (AM) of B cells through somatic hypermutations (SHMs) enables the immune system to evolve to recognize diverse pathogens. The accumulation of SHMs leads to the formation of clonal lineages of antibody secreting b cells that have evolved from a common naive B cell. Advances in high-throughput sequencing have enabled deep scans of B cell receptor repertoires, paving the way for reconstructing clonal trees. However, it is not clear if clonal trees, which capture microevolutionary time scales, can be reconstructed using traditional phylogenetic reconstruction methods with adequate accuracy. In fact, several clonal tree reconstruction methods have been developed to fix supposed shortcomings of phylogenetic methods. Nevertheless, no consensus has been reached regarding the relative accuracy of these methods, partially because evaluation is challenging. Benchmarking the performance of existing methods and developing better methods would both benefit from realistic models of clonal lineage evolution specifically designed for emulating B cell evolution. In this paper, we propose a model for modeling B cell clonal lineage evolution and use this model to benchmark several existing clonal tree reconstruction methods. Our model, designed to be extensible, has several features: by evolving the clonal tree and sequences simultaneously, it allows modeling selective pressure due to changes in affinity binding; it enables scalable simulations of large numbers of cells; it enables several rounds of infection by an evolving pathogen; and, it models building of memory. In addition, we also suggest a set of metrics for comparing clonal trees and for measuring their properties. Our benchmarking results show that while maximum likelihood phylogenetic reconstruction methods can fail to capture key features of clonal tree expansion if applied naively, a very simple post-processing of their results, where super short branches are contracted, leads to inferences that are better than alternative methods. |
| ISSN | 16643224 |
| DOI | 10.3389/fimmu.2022.1014439 |
| Volume Number | 13 |
| Journal | Frontiers in Immunology |
| Language | English |
| Publisher Date | 2022-12-06 |
| Access Restriction | Open |
| Subject Keyword | Clonal trees Antibody evolution Method benchmarking Joint tree and sequence evolution Birth-death models |
| Content Type | Text |
| Resource Type | Article |
| Subject | Immunology and Allergy Immunology |
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