GLaMST: grow lineages along minimum spanning tree for b cell receptor sequencing data

Activation and maturation of antigen-specific B cells in nonectopic lung infiltrates are independent of germinal center reactions in the draining lymph node

Pulmonary T and B cells are important for protection of this mucosal barrier site. While viral infections lead to the development of ectopic lymphoid structures highly similar to those in germinal centers in secondary lymphoid organs, little is known about how T/B cooperation occurs in the unstructured, diffuse tissue infiltrates characteristic of autoimmune diseases and nonviral infections. Using a mouse model of interstitial lung inflammation, we found that naive B cells are directly activated in lung tissue. Despite the absence of any germinal center-like structures, the interaction of B cells with peripheral T helper cells results in efficient somatic hypermutation and class switching. As antigen-presenting cells, macrophages are critical for this process. Unique B-cell repertoires indicated that the lung response was autonomous from the lung-draining lymph node. Only lung GC-like B cells were switched to IgA and had a broader repertoire, making them ideal candidates for producing broadly neutralizing immunoglobulins against respiratory pathogens.

Isotype-aware inference of B cell clonal lineage trees from single-cell sequencing data

Single-cell RNA sequencing (scRNA-seq) enables comprehensive characterization of the micro-evolutionary processes of B cells during an adaptive immune response, capturing features of somatic hypermutation (SHM) and class switch recombination (CSR). Existing phylogenetic approaches for reconstructing B cell evolution have primarily focused on the SHM process alone. Here, we present tree inference of B cell clonal lineages (TRIBAL), an algorithm designed to optimally reconstruct the evolutionary history of B cell clonal lineages undergoing both SHM and CSR from scRNA-seq data. Through simulations, we demonstrate that TRIBAL produces more comprehensive and accurate B cell lineage trees compared to existing methods. Using real-world datasets, TRIBAL successfully recapitulates expected biological trends in a model affinity maturation system while reconstructing evolutionary histories with more parsimonious class switching than state-of-the-art methods. Thus, TRIBAL significantly improves B cell lineage tracing, useful for modeling vaccine responses, disease progression, and the identification of therapeutic antibodies.

Protocol for fast clonal family inference and analysis from large-scale B cell receptor repertoire sequencing data

The expeditious identification and comprehensive analysis of clonal families from extensive B cell receptor (BCR) repertoire sequencing data are imperative for elucidating the intricacies of B cell immune responses. Here, we introduce a computational pipeline designed to swiftly deduce clonal families from bulk BCR heavy-chain sequencing data, accompanied by a suite of functional modules tailored to streamline post-clustering analysis. The outlined methodology encompasses guidelines for software installation, meticulous data preparation, and the systematic inference and analysis of clonal families. For complete details on the use and execution of this protocol, please refer to Wang et al.1.

B cell phylogenetics in the single cell era

The widespread availability of single-cell RNA sequencing (scRNA-seq) has led to the development of new methods for understanding immune responses. Single-cell transcriptome data can now be paired with B cell receptor (BCR) sequences. However, RNA from BCRs cannot be analyzed like most other genes because BCRs are genetically diverse within individuals. In humans, BCRs are shaped through recombination followed by mutation and selection for antigen binding. As these processes co-occur with cell division, B cells can be studied using phylogenetic trees representing the mutations within a clone. B cell trees can link experimental timepoints, tissues, or cellular subtypes. Here, we review the current state and potential of how B cell phylogenetics can be combined with single-cell data to understand immune responses.

ViCloD, an interactive web tool for visualizing B cell repertoires and analyzing intraclonal diversities: application to human B-cell tumors

High throughput sequencing of adaptive immune receptor repertoire (AIRR-seq) has provided numerous human immunoglobulin (IG) sequences allowing specific B cell receptor (BCR) studies such as the antigen-driven evolution of antibodies (soluble forms of the membrane-bound IG part of the BCR). AIRR-seq data allows researchers to examine intraclonal differences caused primarily by somatic hypermutations in IG genes and affinity maturation. Exploring this essential adaptive immunity process could help elucidate the generation of antibodies with high affinity or broadly neutralizing activities. Retracing their evolutionary history could also clarify how vaccines or pathogen exposition drive the humoral immune response, and unravel the clonal architecture of B cell tumors. Computational methods are necessary for large-scale analysis of AIRR-seq properties. However, there is no efficient and interactive tool for analyzing intraclonal diversity, permitting users to explore adaptive immune receptor repertoires in biological and clinical applications. Here we present ViCloD, a web server for large-scale visual analysis of repertoire clonality and intraclonal diversity. ViCloD uses preprocessed data in the format defined by the Adaptive Immune Receptor Repertoire (AIRR) Community. Then, it performs clonal grouping and evolutionary analyses, producing a collection of useful plots for clonal lineage inspection. The web server presents diverse functionalities, including repertoire navigation, clonal abundance analysis, and intraclonal evolutionary tree reconstruction. Users can download the analyzed data in different table formats and save the generated plots as images. ViCloD is a simple, versatile, and user-friendly tool that can help researchers and clinicians to analyze B cell intraclonal diversity. Moreover, its pipeline is optimized to process hundreds of thousands of sequences within a few minutes, allowing an efficient investigation of large and complex repertoires.

Lineage Reconstruction of In Vitro Identified Antigen-Specific Autoreactive B Cells from Adaptive Immune Receptor Repertoires

The emergence, survival, growth and maintenance of autoreactive (AR) B-cell clones, the hallmark of humoral autoimmunity, leave their footprints in B-cell receptor repertoires. Collecting IgH sequences related to polyreactive (PR) ones from adaptive immune receptor repertoire (AIRR) datasets make the reconstruction and analysis of PR/AR B-cell lineages possible. We developed a computational approach, named ImmChainTracer, to extract members and to visualize clonal relationships of such B-cell lineages. Our approach was successfully applied on the IgH repertoires of patients suffering from monogenic hypomorphic RAG1 and 2 deficiency (pRD) or polygenic systemic lupus erythematosus (SLE) autoimmune diseases to identify relatives of AR IgH sequences and to track their fate in AIRRs. Signs of clonal expansion, affinity maturation and class-switching events in PR/AR and non-PR/AR B-cell lineages were revealed. An extension of our method towards B-cell expansion caused by any trigger (e.g., infection, vaccination or antibody development) may provide deeper insight into antigen specific B-lymphogenesis.

Antibody repertoire sequencing analysis

High-throughput sequencing for B cell receptor (BCR) repertoire provides useful insights for the adaptive immune system. With the continuous development of the BCR-seq technology, many efforts have been made to develop methods for analyzing the ever-increasing BCR repertoire data. In this review, we comprehensively outline different BCR repertoire library preparation protocols and summarize three major steps of BCR-seq data analysis, i. e., V(D)J sequence annotation, clonal phylogenetic inference, and BCR repertoire profiling and mining. Different from other reviews in this field, we emphasize background intuition and the statistical principle of each method to help biologists better understand it. Finally, we discuss data mining problems for BCR-seq data and with a highlight on recently emerging multiple-sample analysis.

Extrafollicular B cell responses correlate with neutralizing antibodies and morbidity in COVID-19

A wide spectrum of clinical manifestations has become a hallmark of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) COVID-19 pandemic, although the immunological underpinnings of diverse disease outcomes remain to be defined. We performed detailed characterization of B cell responses through high-dimensional flow cytometry to reveal substantial heterogeneity in both effector and immature populations. More notably, critically ill patients displayed hallmarks of extrafollicular B cell activation and shared B cell repertoire features previously described in autoimmune settings. Extrafollicular activation correlated strongly with large antibody-secreting cell expansion and early production of high concentrations of SARS-CoV-2-specific neutralizing antibodies. Yet, these patients had severe disease with elevated inflammatory biomarkers, multiorgan failure and death. Overall, these findings strongly suggest a pathogenic role for immune activation in subsets of patients with COVID-19. Our study provides further evidence that targeted immunomodulatory therapy may be beneficial in specific patient subpopulations and can be informed by careful immune profiling.