steven.kleinstein@yale.edu.
Analyses of somatic hypermutation (SHM) patterns in B cell immunoglobulin (Ig) sequences contribute to our basic understanding of adaptive immunity, and have broad applications not only for understanding the immune response to pathogens, but also to determining the role of SHM in autoimmunity and B cell cancers. Although stochastic, SHM displays intrinsic biases that can confound statistical analysis, especially when combined with the particular codon usage and base composition in Ig sequences. Analysis of B cell clonal expansion, diversification, and selection processes thus critically depends on an accurate background model for SHM micro-sequence targeting (i.e., hot/cold-spots) and nucleotide substitution. Existing models are based on small numbers of sequences/mutations, in part because they depend on data from non-coding regions or non-functional sequences to remove the confounding influences of selection. Here, we combine high-throughput Ig sequencing with new computational analysis methods to produce improved models of SHM targeting and substitution that are based only on synonymous mutations, and are thus independent of selection. The resulting “S5F” models are based on 806,860 Synonymous mutations in 5-mer motifs from 1,145,182 Functional sequences and account for dependencies on the adjacent four nucleotides (two bases upstream and downstream of the mutation). The estimated profiles can explain almost half of the variance in observed mutation patterns, and clearly show that both mutation targeting and substitution are significantly influenced by neighboring bases. While mutability and substitution profiles were highly conserved across individuals, the variability across motifs was found to be much larger than previously estimated. The model and method source code are made available at
Adaptive immunity is driven by the expansion, somatic hypermutation, and selection of B cell clones. Each clone is the progeny of a single B cell responding to antigen, with diversified Ig receptors. These receptors can now be profiled at large-scale by next-generation sequencing. Such data provide a window into the micro-evolutionary dynamics that drive successful immune responses and the dysregulation that occurs with aging or disease. Clonal relationships are not directly measured, but must be computationally inferred from these sequencing data. While several hierarchical clustering-based methods have been proposed, they vary in distance and linkage methods and have not yet been rigorously compared. Here we use a combination of human experimental and simulated data to characterize the performance of hierarchical clustering-based methods for partitioning sequences into clones. We find that single linkage clustering has high performance, with specificity, sensitivity, and positive predictive value (PPV) all over 99%, whereas other linkages result in a significant loss of sensitivity. Surprisingly, distance metrics that incorporate the biases of somatic hypermutation do not outperform simple Hamming distance. Although errors were more likely in sequences with short junctions, using the entire dataset to choose a single distance threshold for clustering is near optimal. Our results suggest that hierarchical clustering using single linkage with Hamming distance identifies clones with high confidence and provides a fully automated method for clonal grouping. The performance estimates we develop provide important context to interpret clonal analysis of repertoire sequencing data and allow for rigorous testing of other clonal grouping algorithms.
SUMMARY The B cell response to Salmonella typhimurium (STm) occurs massively at extrafollicular sites, without notable germinal centers (GCs). Little is known in terms of its specificity. To expand the knowledge of antigen targets, we screened plasmablast (PB)-derived monoclonal antibodies (mAbs) for Salmonella specificity, using ELISA, flow cytometry, and antigen microarray. Only a small fraction (0.5%–2%) of the response appeared to be Salmonella-specific. Yet, infection of mice with limited B cell receptor (BCR) repertoires impaired the response, suggesting that BCR specificity was important. We showed, using laser microdissection, that somatic hypermutation (SHM) occurred efficiently at extrafollicular sites leading to affinity maturation that in turn led to detectable STm Ag-binding. These results suggest a revised vision of how clonal selection and affinity maturation operate in response to Salmonella. Clonal selection initially is promiscuous, activating cells with virtually undetectable affinity, yet SHM and selection occur during the extrafollicular response yielding higher affinity, detectable antibodies.
CD4+ follicular regulatory T cells (Tfr cells) suppress B cell responses through modulation of follicular helper T cells (Tfh cells) and germinal center (GC) development. We found that Tfr cells also can promote the GC response through provision of IL-10 following acute infection with lymphocytic choriomeningitis virus (LCMV). Sensing of IL-10 by B cells was necessary for optimal development of the GC response. GC B cells formed in the absence of Treg-cell derived IL-10 displayed an altered dark zone state and decreased expression of the transcription factor FOXO1. IL-10 promoted nuclear translocation of FOXO1 in activated B cells. These data indicate that Tfr cells play a multifaceted role in the fine-tuning of the GC response and identify IL-10 as an important mediator by which Tfr cells support the GC reaction.
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