Immunoprofiling Identifies Functional B and T Cell Subsets Induced by an Attenuated Whole Parasite Malaria Vaccine as Correlates of Sterile Immunity

Immune correlates of protection remain elusive for most vaccines. An identified immune correlate would accelerate the down-selection of vaccine formulations by reducing the need for human pathogen challenge studies that are currently required to determine vaccine efficacy. Immunization via mosquito-delivered, radiation-attenuated P. falciparum sporozoites (IMRAS) is a well-established model for efficacious malaria vaccines, inducing greater than 90% sterile immunity. The current immunoprofiling study utilized samples from a clinical trial in which vaccine dosing was adjusted to achieve only 50% protection, thus enabling a comparison between protective and non-protective immune signatures. In-depth immunoprofiling was conducted by assessing a wide range of antigen-specific serological and cellular parameters and applying our newly developed computational tools, including machine learning. The computational component of the study pinpointed previously un-identified cellular T cell subsets (namely, TNFα-secreting CD8+CXCR3−CCR6− T cells, IFNγ-secreting CD8+CCR6+ T cells and TNFα/FNγ-secreting CD4+CXCR3−CCR6− T cells) and B cell subsets (i.e., CD19+CD24hiCD38hiCD69+ transitional B cells) as important factors predictive of protection (92% accuracy). Our study emphasizes the need for in-depth immunoprofiling and subsequent data integration with computational tools to identify immune correlates of protection. The described process of computational data analysis is applicable to other disease and vaccine models.

Dysregulated B cell differentiation towards antibody-secreting cells in neuromyelitis optica spectrum disorder

Background Anti-aquaporin 4 (AQP4) antibody (AQP4-Ab) is involved in the pathogenesis of neuromyelitis optica spectrum disorder (NMOSD). However, the mechanism involved in AQP4-Ab production remains unclear. Methods We analyzed the immunophenotypes of patients with NMOSD and other neuroinflammatory diseases as well as healthy controls (HC) using flow cytometry. Transcriptome analysis of B cell subsets obtained from NMOSD patients and HCs was performed. The differentiation capacity of B cell subsets into antibody-secreting cells was analyzed. Results The frequencies of switched memory B (SMB) cells and plasmablasts were increased and that of naïve B cells was decreased in NMOSD patients compared with relapsing–remitting multiple sclerosis patients and HC. SMB cells from NMOSD patients had an enhanced potential to differentiate into antibody-secreting cells when cocultured with T peripheral helper cells. Transcriptome analysis revealed that the profiles of B cell lineage transcription factors in NMOSD were skewed towards antibody-secreting cells and that IL-2 signaling was upregulated, particularly in naïve B cells. Naïve B cells expressing CD25, a receptor of IL-2, were increased in NMOSD patients and had a higher potential to differentiate into antibody-secreting cells, suggesting CD25+ naïve B cells are committed to differentiate into antibody-secreting cells. Conclusions To the best of our knowledge, this is the first study to demonstrate that B cells in NMOSD patients are abnormally skewed towards antibody-secreting cells at the transcriptome level during the early differentiation phase, and that IL-2 might participate in this pathogenic process. Our study indicates that CD25+ naïve B cells are a novel candidate precursor of antibody-secreting cells in autoimmune diseases.

Multimodal repertoire analysis unveils B cell biology in health and immune-mediated diseases

Despite involvement of B cells in the pathogenesis of immune-mediated diseases, biological mechanisms underlying their function are scarcely understood. To overcome this gap, comprehensive analysis of the B cell repertoire is essential. Here, we cataloged and investigated the repertoire of five B cell subsets from 595 cases under immune-mediated diseases and health. CDR-H3 length among naive B cells was shortened among autoimmune diseases in an interferon signature-dependent manner. VDJ gene usage was skewed especially in plasmablasts and unswitched-memory B cells of systemic lupus erythematosus patients with frequent usage of VDJ genes used mainly in naive B cells and not unswitched-memory B cells of healthy controls. We developed a scoring system for this skewing, and it correlated with peripheral helper T cell transcriptomic signatures and disease activity and decreased after belimumab treatment. Moreover, genetic association analysis identified three molecules possibly involved in somatic hyper-mutation processes in humans. Our multimodal repertoire analysis brings new insights to B cell biology.

Increased Production of B-Cell Activating Cytokines and Altered Peripheral B-Cell Subset Distribution during HIV-Related Classical Hodgkin Lymphoma

Classical Hodgkin Lymphoma incidence increases in HIV-1-infected patients (HIV-cHL). HIV infection is associated with higher B-cell activation. Here, in 38 HIV-cHL patients from the French cohort ANRS-CO16 Lymphovir, we examined longitudinally over 24 months the serum levels of the B-cell activating cytokines IL10, IL6, and BAFF, and blood distribution of B-cell subsets. Fourteen HIV-cHL patients were also compared to matched HIV-infected controls without cHL. IL10, IL6, and BAFF levels were higher in HIV-cHL patients than in controls (p < 0.0001, p = 0.002, and p < 0.0001, respectively). Cytokine levels increased in patients with advanced-stage lymphoma compared to those with limited-stage (p = 0.002, p = 0.03, and p = 0.01, respectively). Cytokine levels significantly decreased following HIV-cHL diagnosis and treatment. Blood counts of whole B-cells were similar in HIV-cHL patients and controls, but the distribution of B-cell subsets was different with higher ratios of naive B-cells over memory B-cells in HIV-cHL patients. Blood accumulation of naive B-cells was more marked in patients with advanced cHL stages (p = 0.06). During the follow-up, total B-cell counts increased (p < 0.0001), and the proportion of naive B-cells increased further (p = 0.04). Together the results suggest that in HIV-infected patients, cHL is associated with a particular B-cell-related environment that includes increased production of B-cell-activating cytokines and altered peripheral distribution of B-cell subsets. This B-cell-related environment may fuel the process of tumorigenesis.

A Single-Cell Transcriptome Profiling of Anterior Kidney Leukocytes From Nile Tilapia (Oreochromis niloticus)

Teleost fish anterior kidney (AK) is an important hematopoietic organ with multifarious immune cells, which have immune functions comparable to mammalian bone marrow. Myeloid and lymphoid cells locate in the AK, but the lack of useful specific gene markers and antibody-based reagents for the cell subsets makes the identification of the different cell types difficult. Single-cell transcriptome sequencing enables single-cell capture and individual library construction, making the study on the immune cell heterogeneity of teleost fish AK possible. In this study, we examined the transcriptional patterns of 11,388 AK leukocytes using 10× Genomics single-cell RNA sequencing (scRNA-seq). A total of 22 clusters corresponding to five distinct immune cell subsets were identified, which included B cells, T cells, granulocytes, macrophages, and dendritic cells (DCs). However, the subsets of myeloid cells (granulocytes, macrophages, and DCs) were not identified in more detail according to the known specific markers, even though significant differences existed among the clusters. Thereafter, we highlighted the B-cell subsets and identified them as pro/pre B cells, immature/mature B cells, activated B/plasmablasts, or plasma cells based on the different expressions of the transcription factors (TFs) and cytokines. Clustering of the differentially modulated genes by pseudo-temporal trajectory analysis of the B-cell subsets showed the distinct kinetics of the responses of TFs to cell conversion. Moreover, we classified the T cells and discovered that CD3+CD4−CD8−, CD3+CD4+CD8+, CD4+CD8−, and CD4−CD8+ T cells existed in AK, but neither CD4+CD8− nor CD4−CD8+ T cells can be further classified into subsets based on the known TFs and cytokines. Pseudotemporal analysis demonstrated that CD4+CD8− and CD4−CD8+ T cells belonged to different states with various TFs that might control their differentiation. The data obtained above provide a valuable and detailed resource for uncovering the leukocyte subsets in Nile tilapia AK, as well as more potential markers for identifying the myeloid and lymphoid cell types.

Two doses of mRNA vaccine elicit cross-neutralizing memory B-cells against SARS-CoV-2 Omicron variant

SARS-CoV-2 Beta and Omicron variants have multiple mutations in the receptor-binding domain (RBD) allowing antibody evasion. Despite the resistance to circulating antibodies in those who received two doses of mRNA vaccine, the third dose prominently recalls cross-neutralizing antibodies with expanded breadth to these variants. Herein, we longitudinally profiled the cellular composition of persistent memory B-cell subsets and their antibody reactivity against these variants following the second vaccine dose. The vaccination elicited a memory B-cell subset with resting phenotype that dominated the other subsets at 4.9 months. Notably, most of the resting memory subset retained the ability to bind the Beta variant, and the memory-derived antibodies cross-neutralized the Beta and Omicron variants at frequencies of 59% and 29%, respectively. The preservation of cross-neutralizing antibody repertoires in the durable memory B-cell subset likely contributes to the prominent recall of cross-neutralizing antibodies following the third dose of the vaccine.

Altered Tim-1 and IL-10 Expression in Regulatory B Cell Subsets in Type 1 Diabetes

BackgroundType 1 diabetes (T1D) is an autoimmune disease with a complex aetiology. B cells play an important role in the pathogenesis of T1D. Regulatory B cells (Bregs) are a subset of B cells that produce and secrete the inhibitory factor interleukin-10 (IL-10), thereby exerting an anti-inflammatory effect. It was recently discovered that T-cell immunoglobulin mucin domain 1 (Tim-1) is essential for maintaining Bregs function related to immune tolerance. However, the detailed understanding of Tim-1+ Bregs and IL-10+ Bregs in T1D patients is lacking. This study aimed to characterize the profile of B cell subsets in T1D patients compared with that in controls and determine whether Tim-1+ Bregs and IL-10+ Bregs play roles in T1D.Materials and MethodsA total of 47 patients with T1D, 30 patients with type 2 diabetes (T2D) and 24 healthy controls were recruited in this study. Flow cytometry was used to measure the levels of different B cell subsets (including B cells, plasmablasts, and Bregs) in the peripheral blood. Radiobinding assays were performed to detect the antibody titres of T1D patients. In addition, the correlations between different B cell subsets and patient parameters were investigated.ResultsCompared with healthy controls, differences in frequency of Tim-1+ Bregs were significantly decreased in patients with T1D (36.53 ± 6.51 vs. 42.25 ± 6.83, P=0.02*), and frequency of IL-10+ Bregs were lower than healthy controls (17.64 ± 7.21vs. 24.52 ± 11.69, P=0.009**), the frequency of total Bregs in PBMC was also decreased in patients with T1D (1.42 ± 0.53vs. 1.99 ± 0.93, P=0.002.**). We analyzed whether these alterations in B cells subsets were associated with clinical features. The frequencies of Tim-1+ Bregs and IL-10+ Bregs were negatively related to fasting blood glucose (FBG) (r=-0.25 and -0.22; P=0.01* and 0.03*, respectively). The frequencies of Tim-1+ Bregs and IL-10+ Bregs are positively correlated with fast C-peptide (FCP) (r=0.23 and 0.37; P=0.02* and 0.0001***, respectively). In addition, the frequency of IL-10+ Breg was also negatively related to glycosylated haemoglobin (HbA1c) (r=-0.20, P=0.04*). The frequencies of Tim-1+ Bregs, IL-10+ Bregs and Bregs in T2D patients were reduced, but no statistically significant difference was found between other groups. Interestingly, there was positive correlation between the frequencies of Tim-1+ Bregs and IL-10+ Bregs in T1D (r=0.37, P=0.01*). Of note, it is worth noting that our study did not observe any correlations between B cell subsets and autoantibody titres.ConclusionsOur study showed altered Tim-1 and IL-10 expression in regulatory B cell in T1D patients. Tim-1, as suggested by the present study, is associated with islet function and blood glucose levels. These findings indicate that Tim-1+ Bregs and IL-10+ Bregs were involved in the pathogenesis of T1D.

Characterization of Definitive Regulatory B Cell Subsets by Cell Surface Phenotype, Function and Context

Regulatory B cell or “Breg” is a broad term that represents the anti-inflammatory activity of B cells, but does not describe their individual phenotypes, specific mechanisms of regulation or relevant disease contexts. Thus, given the variety of B cell regulatory mechanisms reported in human disease and their animal models, a more thorough and comprehensive identification strategy is needed for tracking and comparing B cell subsets between research groups and in clinical settings. This review summarizes the discovery process and mechanism of action for well-defined regulatory B cell subsets with an emphasis on the mouse model of multiple sclerosis experimental autoimmune encephalomyelitis. We discuss the importance of conducting thorough B cell phenotyping along with mechanistic studies prior to defining a particular subset of B cells as Breg. Since virtually all B cell subsets can exert regulatory activity, it is timely for their definitive identification across studies.