Namita T. Gupta

Change-O: a toolkit for analyzing large-scale B cell immunoglobulin repertoire sequencing data

UNLABELLED Advances in high-throughput sequencing technologies now allow for large-scale characterization of B cell immunoglobulin (Ig) repertoires. The high germline and somatic diversity of the Ig repertoire presents challenges for biologically meaningful analysis, which requires specialized computational methods. We have developed a suite of utilities, Change-O, which provides tools for advanced analyses of large-scale Ig repertoire sequencing data. Change-O includes tools for determining the complete set of Ig variable region gene segment alleles carried by an individual (including novel alleles), partitioning of Ig sequences into clonal populations, creating lineage trees, inferring somatic hypermutation targeting models, measuring repertoire diversity, quantifying selection pressure, and calculating sequence chemical properties. All Change-O tools utilize a common data format, which enables the seamless integration of multiple analyses into a single workflow. AVAILABILITY AND IMPLEMENTATION Change-O is freely available for non-commercial use and may be downloaded from http://clip.med.yale.edu/changeo. CONTACT steven.kleinstein@yale.edu.

Models of Somatic Hypermutation Targeting and Substitution Based on Synonymous Mutations from High-Throughput Immunoglobulin Sequencing Data

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 http://clip.med.yale.edu/SHM

Salmonella Infection Drives Promiscuous B Cell Activation Followed by Extrafollicular Affinity Maturation

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.

Hierarchical Clustering Can Identify B Cell Clones with High Confidence in Ig Repertoire Sequencing Data

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 Ag, with diversified Ig receptors. These receptors can now be profiled on a large scale by next-generation sequencing. Such data provide a window into the microevolutionary dynamics that drive successful immune responses and the dysregulation that occurs with aging or disease. Clonal relationships are not directly measured, but they must be computationally inferred from these sequencing data. Although several hierarchical clustering-based methods have been proposed, they vary in distance and linkage methods and have not yet been rigorously compared. In this study, 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 all >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.

Interleukin-10 from CD4+ follicular regulatory T cells promotes the germinal center response

Follicular regulatory T cells promote the germinal center response after viral infection through provision of IL-10. Probing the functions of follicular regulatory T cells CD4+ follicular regulatory T (Tfr) cells express key molecules that are associated with regulatory T cell and follicular helper T cell functions. Although it is known that Tfr cells produce interleukin-10 (IL-10), it has been unclear whether IL-10 production by these cells regulates germinal center (GC) responses in vivo. By specifically ablating IL-10 expression in murine Tfr cells, Laidlaw et al. demonstrate that Tfr cell–derived IL-10 does support GC responses in the context of acute viral infection. They found dendritic cells and B cells in the GCs to be IL-10–responsive and showed that IL-10 promoted GC B cells to adopt a dark zone phenotype. CD4+ follicular regulatory T (Tfr) cells suppress B cell responses through modulation of follicular helper T (Tfh) cells and germinal center (GC) development. We found that Tfr cells can also promote the GC response through provision of interleukin-10 (IL-10) after 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 Forkhead box protein 1 (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.

Responsive population dynamics and wide seeding into the duodenal lamina propria of transglutaminase-2-specific plasma cells in celiac disease.

A hallmark of celiac disease is autoantibodies to transglutaminase 2 (TG2). By visualizing TG2-specific antibodies by antigen staining of affected gut tissue, we identified TG2-specific plasma cells in the lamina propria as well as antibodies in the subepithelial layer, inside the epithelium, and at the brush border. The frequency of TG2-specific plasma cells were found not to correlate with serum antibody titers, suggesting that antibody production at other sites may contribute to serum antibody levels. Upon commencement of a gluten-free diet, the frequency of TG2-specific plasma cells in the lesion dropped dramatically within 6 months, yet some cells remained. The frequency of TG2-specific plasma cells in the celiac lesion is thus dynamically regulated in response to gluten exposure. Laser microdissection of plasma cell patches, followed by antibody gene sequencing, demonstrated that clonal cells were seeded in distinct areas of the mucosa. This was confirmed by immunoglobulin heavy chain repertoire analysis of plasma cells isolated from individual biopsies of two untreated patients, both for TG2-specific and non-TG2-specific cells. Our results shed new light on the processes underlying the B-cell response in celiac disease, and the approach of staining for antigen-specific antibodies should be applicable to other antibody-mediated diseases.

VDJML: a file format with tools for capturing the results of inferring immune receptor rearrangements

BackgroundThe genes that produce antibodies and the immune receptors expressed on lymphocytes are not germline encoded; rather, they are somatically generated in each developing lymphocyte by a process called V(D)J recombination, which assembles specific, independent gene segments into mature composite genes. The full set of composite genes in an individual at a single point in time is referred to as the immune repertoire. V(D)J recombination is the distinguishing feature of adaptive immunity and enables effective immune responses against an essentially infinite array of antigens. Characterization of immune repertoires is critical in both basic research and clinical contexts. Recent technological advances in repertoire profiling via high-throughput sequencing have resulted in an explosion of research activity in the field. This has been accompanied by a proliferation of software tools for analysis of repertoire sequencing data. Despite the widespread use of immune repertoire profiling and analysis software, there is currently no standardized format for output files from V(D)J analysis. Researchers utilize software such as IgBLAST and IMGT/High V-QUEST to perform V(D)J analysis and infer the structure of germline rearrangements. However, each of these software tools produces results in a different file format, and can annotate the same result using different labels. These differences make it challenging for users to perform additional downstream analyses.ResultsTo help address this problem, we propose a standardized file format for representing V(D)J analysis results. The proposed format, VDJML, provides a common standardized format for different V(D)J analysis applications to facilitate downstream processing of the results in an application-agnostic manner. The VDJML file format specification is accompanied by a support library, written in C++ and Python, for reading and writing the VDJML file format.ConclusionsThe VDJML suite will allow users to streamline their V(D)J analysis and facilitate the sharing of scientific knowledge within the community. The VDJML suite and documentation are available from https://vdjserver.org/vdjml/. We welcome participation from the community in developing the file format standard, as well as code contributions.

Graded Vector Representations of Immunoglobulins Produced in Response to West Nile Virus

Semantic vector models generate high-dimensional vector representations of words from their occurrence statistics across large corpora of electronic text. In these models, an occurrence of a word or number is treated as a discrete event, including numerical measurements of continuous properties. Furthermore, the sequence in which words occur is often ignored. In earlier work we have developed approaches to address these limitations, using graded demarcator vectors to represent measured distances in high-dimensional space. This permits incorporation of continuous properties, such as the position of a character within a term or a year of birth, into semantic vector models. In this paper we extend this work by developing a novel representational approach for protein sequences, in which both the positions and the properties of the amino acid components of protein sequences are represented using graded vectors. Evaluation on a set of around 100,000 immunoglobulin receptor sequences derived from subjects recently infected with West Nile Virus (WNV) suggests that encoding positions and properties using graded vectors increases the similarity between immunoglobulin receptor sequences produced by cells from ancestral lines known to have developed in response to WNV, relative to those from other cell lines.