Next-generation sequencing has the potential to uncover the complex nature of B cell immunity by revealing the full complexity of B cell receptor (BCR) repertoires in health and disease. However, there are drawbacks which can compromise the validity of the repertoire analysis caused by quantitative bias and accumulation of sequencing errors during the library preparation and sequencing. Here, we provide an optimized protocol designed to minimize bias for reproducible and accurate preparation of human BCR repertoire libraries for high-throughput sequencing.

B cells are central to the adaptive immune response and provide long-lasting immunity after infection. B cell activation is mediated by the surface membrane-bound B cell receptor (BCR) following recognition of a specific antigen. The BCR has been challenging to analyse using mass spectrometry (MS) due to the difficulty of isolating and enriching this membrane-bound protein complex. There are approximately 120,000 BCRs on the B cell surface; however, depending on the B cell activation state, there may be hundreds-of-millions to billions of proteins in a B cell. Consequently, advanced proteomic techniques such as MS workflows that use purified proteins to yield structural and protein-interaction information have not been published for the BCR complex. This paper describes a method for enriching the BCR complex that is MS-compatible. The method involves a Protein G pull down on agarose beads using an intermediary antibody to each of the BCR complex subcomponents (CD79a, CD79b, and membrane immunoglobulin). The enrichment process is shown to pull down the entire BCR complex and has the advantage of being readily compatible with further proteomic study including MS analysis. Using intermediary antibodies has the potential to enrich all isotypes of the BCR, unlike previous methods described in the literature that use protein G-coated beads to directly pull down the membrane IgG (mIgG) but cannot be used for other mIg isotypes.

B cell malignancies, comprising over 80 heterogeneous blood cancers, pose significant prognostic challenges due to intricate oncogenic signaling. Emerging evidence emphasizes the pivotal role of disrupted lipid metabolism in the development of these malignancies. Variations in lipid species, such as phospholipids, cholesterol, sphingolipids, and fatty acids, are widespread across B cell malignancies, contributing to uncontrolled cell proliferation and survival. Phospholipids play a crucial role in initial signaling cascades leading to B cell activation and malignant transformation through constitutive B cell receptor (BCR) signaling. Dysregulated cholesterol and sphingolipid homeostasis support lipid raft integrity, crucial for propagating oncogenic signals. Sphingolipids impact malignant B cell stemness, proliferation, and survival, while glycosphingolipids in lipid rafts modulate BCR activation. Additionally, cancer cells enhance fatty acid-related processes to meet heightened metabolic demands. In obese individuals, the obesity-derived lipids and adipokines surrounding adipocytes rewire lipid metabolism in malignant B cells, evading cytotoxic therapies. Genetic drivers such as MYC translocations also intrinsically alter lipid metabolism in malignant B cells. In summary, intrinsic and extrinsic factors converge to reprogram lipid metabolism, fostering aggressive phenotypes in B cell malignancies. Therefore, targeting altered lipid metabolism has translational potential for improving risk stratification and clinical management of diverse B cell malignancy subtypes.

The etiology of hemorrhagic fever with renal syndrome (HFRS) is significantly impacted by a variety of immune cells. Nevertheless, the existing techniques for sequencing peripheral blood T cell receptor (TCR) or B cell receptor (BCR) libraries in HFRS are constrained by both limitations and high costs. In this investigation, we utilized the computational tool TRUST4 to generate TCR and BCR libraries utilizing comprehensive RNA-seq data from peripheral blood specimens of HFRS patients. This facilitated the examination of clonality and diversity within immune libraries linked to the condition. Despite previous research on immune cell function, the underlying mechanisms remain intricate, and differential gene expression across immune cell types and cell-to-cell interactions within immune cell clusters have not been thoroughly explored. To address this gap, we performed clustering analysis on 11 cell subsets derived from raw single-cell RNA-seq data, elucidating characteristic changes in cell subset proportions under disease conditions. Additionally, we utilized CellChat, a tool for cell-cell communication analysis, to investigate the impact of MIF family, CD70 family, and GALECTIN family cytokines-known to be involved in cell communication-on immune cell subsets. Furthermore, hdWGCNA analysis identified core genes implicated in HFRS pathogenesis within T cells and B cells. Trajectory analysis revealed that most cell subsets were in a developmental stage, with high expression of transcription factors such as NFKB and JUN in Effector CD8+ T cells, as well as in Naive CD4+ T cells and Naive B cells. Our findings provide a comprehensive understanding of the dynamic changes in immune cells during HFRS pathogenesis, identifying specific V genes and J genes in TCR and BCR that contribute to advancing our knowledge of HFRS. These insights offer potential implications for the diagnosis and treatment of this autoimmune disease.

Glucocorticoids have been used for decades to treat lymphomas without an established mechanism of action. Using functional genomic, proteomic, and chemical screens, we discover that glucocorticoids inhibit oncogenic signaling by the B cell receptor (BCR), a recurrent feature of aggressive B cell malignancies, including diffuse large B cell lymphoma and Burkitt lymphoma. Glucocorticoids induce the glucocorticoid receptor (GR) to directly transactivate genes encoding negative regulators of BCR stability (LAPTM5; KLHL14) and the PI3 kinase pathway (INPP5D; DDIT4). GR directly represses transcription of CSK, a kinase that limits the activity of BCR-proximal Src-family kinases. CSK inhibition attenuates the constitutive BCR signaling of lymphomas by hyperactivating Src-family kinases, triggering their ubiquitination and degradation. With the knowledge that glucocorticoids disable oncogenic BCR signaling, they can now be deployed rationally to treat BCR-dependent aggressive lymphomas and used to construct mechanistically sound combination regimens with inhibitors of BTK, PI3 kinase, BCL2, and CSK.

Islet autoantibodies predict type 1 diabetes (T1D) but can be transient in murine and human T1D and are not thought to be directly pathogenic. Rather, these autoantibodies signal B cell activity as antigen-presenting cells (APCs) that present islet autoantigen to diabetogenic T cells to promote T1D pathogenesis. Disrupting B cell APC function prevents T1D in mouse models and has shown promise in clinical trials. Autoantigen-specific B cells thus hold potential as sophisticated T1D biomarkers and therapeutic targets. B cell receptor (BCR) somatic hypermutation is a mechanism by which B cells increase affinity for islet autoantigen. High-affinity B and T cell responses are selected in protective immune responses, but immune tolerance mechanisms are known to censor highly autoreactive clones in autoimmunity, including T1D. Thus, different selection rules often apply to autoimmune disease settings (as opposed to protective host immunity), where different autoantigen affinity ceilings are tolerated based on variations in host genetics and environment. This review will explore what is currently known regarding B cell signaling, selection, and interaction with T cells to promote T1D pathogenesis.

The molecular landscape of chronic lymphocytic leukemia (CLL) has been extensively characterized, and various potent prognostic biomarkers were discovered. The genetic composition of the B-cell receptor (BCR) immunoglobulin (IG) was shown to be especially powerful for discerning indolent from aggressive disease at diagnosis. Classification based on the IG heavy chain variable gene (IGHV) somatic hypermutation status is routinely applied. Additionally, BCR IGH stereotypy has been implicated to improve risk stratification, through characterization of subsets with consistent clinical profiles. Despite these advances, it remains challenging to predict when CLL progresses to requiring first-line therapy, thus emphasizing the need for further refinement of prognostic indicators. Signaling pathways downstream of the BCR are essential in CLL pathogenesis, and dysregulated components within these pathways impact disease progression. Considering not only genomics but the entirety of factors shaping BCR signaling activity, this review offers insights in the disease for better prognostic assessment of CLL.

B cell receptors (BCRs) denote antigen specificity, while corresponding cell subsets indicate B cell functionality. Since each B cell uniquely encodes this combination, physical isolation and subsequent processing of individual B cells become indispensable to identify both attributes. However, this approach accompanies high costs and inevitable information loss, hindering high-throughput investigation of B cell populations. Here, we present BCR-SORT, a deep learning model that predicts cell subsets from their corresponding BCR sequences by leveraging B cell activation and maturation signatures encoded within BCR sequences. Subsequently, BCR-SORT is demonstrated to improve reconstruction of BCR phylogenetic trees, and reproduce results consistent with those verified using physical isolation-based methods or prior knowledge. Notably, when applied to BCR sequences from COVID-19 vaccine recipients, it revealed inter-individual heterogeneity of evolutionary trajectories towards Omicron-binding memory B cells. Overall, BCR-SORT offers great potential to improve our understanding of B cell responses.

Identifying individual functional B cell receptors (BCRs) is common, but two-dimensional analysis of B cell frequency versus BCR potency would delineate both quantity and quality of antigen-specific memory B cells. We efficiently determine quantitative BCR neutralizing activities using a single-cell-derived antibody supernatant analysis (SCAN) workflow and develop a frequency-potency algorithm to estimate B cell frequencies at various neutralizing activity or binding affinity cutoffs. In an HIV-1 fusion peptide (FP) immunization study, frequency-potency curves elucidate the quantity and quality of FP-specific immunoglobulin G (IgG)+ memory B cells for different animals, time points, and antibody lineages at single-cell resolution. The BCR neutralizing activities are mainly determined by their affinities to soluble envelope trimer. Frequency analysis definitively demonstrates dominant neutralizing antibody lineages. These findings establish SCAN and frequency-potency analyses as promising approaches for general B cell analysis and monoclonal antibody (mAb) discovery. They also provide specific rationales for HIV-1 FP-directed vaccine optimization.

Folic acid is a fully oxidized synthetic folate with high bioavailability and stability which has been extensively prescribed to prevent congenital disabilities. Here we revealed the immunosuppressive effect of folic acid by targeting splenic marginal zone B (MZB) cells. Folic acid demonstrates avid binding with the Fc domain of immunoglobulin M (IgM), targeting IgM positive MZB cells in vivo to destabilize IgM-B cell receptor (BCR) complex and block immune responses. The induced anergy of MZB cells by folic acid provides an immunological escaping window for antigens. Covalent conjugation of folic acid with therapeutic proteins and antibodies induces immunological evasion to mitigate the production of anti-drug antibodies, which is a major obstacle to the long-term treatment of biologics by reducing curative effects and/or causing adverse reactions. Folic acid acts as a safe and effective immunosuppressant via IgM-mediated MZB cells targeting to boost the clinical outcomes of biologics by inhibiting the production of anti-drug antibodies, and also holds the potential to treat other indications that adverse immune responses need to be transiently shut off.