Memory B Cell Activation, Broad Anti-influenza Antibodies, and Bystander Activation Revealed by Single-Cell Transcriptomics

A platform for the rapid screening of equine immunoglobins F (ab)2 derived from single equine memory B cells able to cross-neutralize to influenza virus

Single B cells-based antibody platforms offer an effective approach for the discovery of useful antibodies for therapeutic or research purposes. Here we present a method for screening equine immunoglobins F(ab)2, which offers the potential advantage of reacting with multiple epitopes on the virus. Using equine influenza virus (EIV) as model, a hemagglutinin (HA) trimer was constructed to bait B cells in vaccinated horses. We screened 370 HA-specific B cells from 1 × 106 PBMCs and identified a diverse set of equine variable region gene sequences of heavy and light chains and then recombined with humanized Ig Fc. Recombinant equine Ig was then self-assembled in co-transfected 293 T cells, and subsequently optimized to obtain HA binding B-cell receptor (s). The recombinant antibodies exhibited a high binding affinity to the HA protein. Antibody H81 exhibited the highest cross neutralizing activities against EIV strains in vitro. Furthermore, it effectively protected EIV-challenged mice, resulting in significantly improved survival, reduced pulmonary inflammation and decreased viral titers. In silico predication identified a functional region of H81 comprising 27 key amino acids cross the main circulating EIV strains. The 12 amino acid residues in this region with the highest binding affinities were screened. Notably, the predicted epitopes of H81 encompassed the documented equine HA receptor binding site, validating its cross-neutralization. In summary, a rapid platform was successfully established to investigate the profiling of equine antigen-recognizing receptors (BCRs) following infection. This platform has the potential to optimize the screening of virus-neutralizing antibodies and aid in vaccine design.

Correlation of cTfh cells and memory B cells with AMR after renal transplantation

Renal transplantation is the preferred treatment option for patients with end-stage renal disease (ESRD) in a clinical setting. Antibody mediated rejection (AMR) is one of the leading causes of graft dysfunction. To address the current shortcomings in the early diagnosis and treatment of AMR in clinical practice, this article analyzes the distribution of different circulating T follicular helper (cTfh) cell subtypes and B cell subpopulations in peripheral blood and detects the cytokine levels of chemokine ligand 13 (CXCL13), interleukin-21 (IL-21), and interleukin-4 (IL-4) related to cTfh cells in peripheral blood of kidney transplant recipients. Moreover, we also explore the correlation between cTfh cells, peripheral blood memory B cells, and AMR, their value as early predictive indicators of AMR, and explore potential therapeutic targets for AMR patients. Our results indicate that the proportion of cTfh cells increased at the onset of AMR, which plays an important role in antigen-specific B-cell immune regulation. Activation of cTfh cells in AMR patients correlates with phenotypes of memory B cells and plasma blasts. cTfh cells and memory B cells have promising diagnostic efficacies and predictive values for AMR. The proportion of cTfh cells to CD4+ T cells and the proportion of memory B cells to CD19+ B cells are correlated with serum creatinine levels, indicating that cTfh cells and memory B cells may be involved in the progression of AMR. In addition, the CXCL13, IL-21, and IL-4, which were associated with cTfh cells, may be involved in the onset of AMR.

B-cell characteristics define HCV reinfection outcome

BACKGROUND & AIMS

In individuals highly exposed to HCV, reinfection is common, suggesting that natural development of sterilising immunity is difficult. In those that are reinfected, some will develop a persistent infection, while a small proportion repeatedly clear the virus, suggesting natural protection is possible. The aim of this study was to characterise immune responses associated with rapid natural clearance of HCV reinfection.

METHODS

Broad neutralising antibodies (nAbs) and Envelope 2 (E2)-specific memory B cell (MBC) responses were examined longitudinally in 15 individuals with varied reinfection outcomes.

RESULTS

Broad nAb responses were associated with MBC recall, but not with clearance of reinfection. Strong evidence of antigen imprinting was found, and the B-cell receptor repertoire showed a high level of clonality with ongoing somatic hypermutation of many clones over subsequent reinfection events. Single-cell transcriptomic analyses showed that cleared reinfections featured an activated transcriptomic profile in HCV-specific B cells that rapidly expanded upon reinfection.

CONCLUSIONS

MBC quality, but not necessarily breadth of nAb responses, is important for protection against antigenically diverse variants, which is encouraging for HCV vaccine development.

IMPACT AND IMPLICATIONS

HCV continues to have a major health burden globally. Limitations in the health infrastructure for diagnosis and treatment, as well as high rates of reinfection, indicate that a vaccine that can protect against chronic HCV infection will greatly complement current efforts to eliminate HCV-related disease. With alternative approaches to testing vaccines, such as controlled human inoculation trials under consideration, we desperately need to identify the correlates of immune protection. In this study, in a small but rare cohort of high-risk injecting drug users who were reinfected multiple times, breadth of neutralisation was not associated with ultimate clearance of the reinfection event. Alternatively, characteristics of the HCV-specific B-cell response associated with B-cell proliferation were. This study indicates that humoral responses are important for protection and suggests that for genetically very diverse viruses, such as HCV, it may be beneficial to look beyond just antibodies as correlates of protection.

Unraveling the intricacies of host-pathogen interaction through single-cell genomics

Single-cell genomics provide researchers with tools to assess host-pathogen interactions at a resolution previously inaccessible. Transcriptome analysis, epigenome analysis, and immune profiling techniques allow for a better comprehension of the heterogeneity underlying both the host response and infectious agents. Here, we highlight technological advancements and data analysis workflows that increase our understanding of host-pathogen interactions at the single-cell level. We review various studies that have used these tools to better understand host-pathogen dynamics in a variety of infectious disease contexts, including viral, bacterial, and parasitic diseases. We conclude by discussing how single-cell genomics can advance our understanding of host-pathogen interactions.

Computational detection of antigen-specific B cell receptors following immunization

B cell receptors (BCRs) play a crucial role in recognizing and fighting foreign antigens. High-throughput sequencing enables in-depth sampling of the BCRs repertoire after immunization. However, only a minor fraction of BCRs actively participate in any given infection. To what extent can we accurately identify antigen-specific sequences directly from BCRs repertoires? We present a computational method grounded on sequence similarity, aimed at identifying statistically significant responsive BCRs. This method leverages well-known characteristics of affinity maturation and expected diversity. We validate its effectiveness using longitudinally sampled human immune repertoire data following influenza vaccination and SARS-CoV-2 infections. We show that different lineages converge to the same responding Complementarity Determining Region 3, demonstrating convergent selection within an individual. The outcomes of this method hold promise for application in vaccine development, personalized medicine, and antibody-derived therapeutics.

Pan-cancer single-cell dissection reveals phenotypically distinct B cell subtypes

Characterizing the compositional and phenotypic characteristics of tumor-infiltrating B cells (TIBs) is important for advancing our understanding of their role in cancer development. Here, we establish a comprehensive resource of human B cells by integrating single-cell RNA sequencing data of B cells from 649 patients across 19 major cancer types. We demonstrate substantial heterogeneity in their total abundance and subtype composition and observe immunoglobulin G (IgG)-skewness of antibody-secreting cell isotypes. Moreover, we identify stress-response memory B cells and tumor-associated atypical B cells (TAABs), two tumor-enriched subpopulations with prognostic potential, shared in a pan-cancer manner. In particular, TAABs, characterized by a high clonal expansion level and proliferative capacity as well as by close interactions with activated CD4 T cells in tumors, are predictive of immunotherapy response. Our integrative resource depicts distinct clinically relevant TIB subsets, laying a foundation for further exploration of functional commonality and diversity of B cells in cancer.

Association between COVID-19 vaccination and stroke: a nationwide case-control study in Qatar

OBJECTIVE

This study investigated the association between Coronavirus Disease 2019 mRNA vaccination and stroke in Qatar.

METHODS

Between December 1, 2020, and April 11, 2023, a matched case-control study was conducted to investigate the association between 3036 acute stroke cases and 3036 controls drawn from the entire population of Qatar.

RESULTS

The adjusted odds ratio (aOR) for vaccination among cases compared to controls was 0.87 (95% CI: 0.75-1.00). The aOR was 0.74 (95% CI: 0.45-1.23) for a single vaccine dose, 0.87 (95% CI: 0.73-1.04) for primary-series vaccination (two doses), and 0.91 (95% CI: 0.66-1.25) for booster vaccination (three or more doses). The aOR was 0.87 (95% CI: 0.72-1.04) for BNT162b2 and 0.86 (95% CI: 0.67-1.11) for mRNA-1273. Subgroup analyses, considering different durations since vaccination, also demonstrated no association. Subgroup analyses based on nationality, age, number of coexisting conditions, or prior infection status yielded similar results. Subgroup analysis, stratified by stroke type, suggested an association between vaccination and cerebral venous sinus thrombosis (aOR of 2.50 [95% CI: 0.97-6.44]), but it did not reach statistical significance.

CONCLUSION

There was no evidence of an increased risk of stroke following vaccination, both in the short term and in the long term, extending beyond a year after receiving the vaccine.

Parallel single B cell transcriptomics to elucidate pig B cell repertoire

Pork is the most widely consumed meat on the planet, placing swine health as a critical factor for both the world economy and the food industry. Infectious diseases in pigs not only threaten these sectors but also raise zoonotic concerns, as pigs can act as "mixing vessels" for several animals and human viruses and can lead to the emergence of new viruses that are capable of infecting humans. Several efforts are ongoing to develop pig vaccines, albeit with limited success. This has been largely attributed to the complex nature of pig infections and incomplete understanding of the pig immune responses. Additionally, pig has been suggested to be a good experimental model to study viral infections (e.g., human influenza). Despite the significant importance of studying pig immunology for developing infection models, zoonosis, and the crucial need to develop better swine vaccines, there is still very limited information on the response of the swine adaptive immune system to several emerging pathogens. Particularly, very little is known about the pig B cell repertoire upon infection. Understanding the B cell repertoire is especially crucial towards designing better vaccines, predicting zoonosis and can provide insights into developing new diagnostic agents. Here, we developed methods for performing parallel single pig B cell (up to 10,000 B cells) global and immunoglobulin transcriptome sequencing. We then adapted a computational pipeline previously built for human/mouse sequences, to now analyze pig sequences. This allowed us to comprehensively map the B cell repertoire and get paired antibody sequences from pigs in a single parallel sequencing experiment. We believe that these approaches will have significant implications for swine diseases, particularly in the context of swine mediated zoonosis and swine and human vaccine development.

Diversification of the VH3-53 immunoglobulin gene segment by somatic hypermutation results in neutralization of SARS-CoV-2 virus variants

COVID-19 induces re-circulating long-lived memory B cells (MBC) that, upon re-encounter with the pathogen, are induced to mount immunoglobulin responses. During convalescence, antibodies are subjected to affinity maturation, which enhances the antibody binding strength and generates new specificities that neutralize virus variants. Here, we performed a single-cell RNA sequencing analysis of spike-specific B cells from a SARS-CoV-2 convalescent subject. After COVID-19 vaccination, matured infection-induced MBC underwent recall and differentiated into plasmablasts. Furthermore, the transcriptomic profiles of newly activated B cells transiently shifted toward the ones of atypical and CXCR3+ B cells and several B-cell clonotypes massively expanded. We expressed monoclonal antibodies (mAbs) from all B-cell clones from the largest clonotype that used the VH3-53 gene segment. The in vitro analysis revealed that some somatic hypermutations enhanced the neutralization breadth of mAbs in a putatively stochastic manner. Thus, somatic hypermutation of B-cell clonotypes generates an anticipatory memory that can neutralize new virus variants.

RAIN: machine learning-based identification for HIV-1 bNAbs

Broadly neutralizing antibodies (bNAbs) are promising candidates for the treatment and prevention of HIV-1 infections. Despite their critical importance, automatic detection of HIV-1 bNAbs from immune repertoires is still lacking. Here, we develop a straightforward computational method for the Rapid Automatic Identification of bNAbs (RAIN) based on machine learning methods. In contrast to other approaches, which use one-hot encoding amino acid sequences or structural alignment for prediction, RAIN uses a combination of selected sequence-based features for the accurate prediction of HIV-1 bNAbs. We demonstrate the performance of our approach on non-biased, experimentally obtained and sequenced BCR repertoires from HIV-1 immune donors. RAIN processing leads to the successful identification of distinct HIV-1 bNAbs targeting the CD4-binding site of the envelope glycoprotein. In addition, we validate the identified bNAbs using an in vitro neutralization assay and we solve the structure of one of them in complex with the soluble native-like heterotrimeric envelope glycoprotein by single-particle cryo-electron microscopy (cryo-EM). Overall, we propose a method to facilitate and accelerate HIV-1 bNAbs discovery from non-selected immune repertoires.

Inferring B Cell Phylogenies from Paired H and L Chain BCR Sequences with Dowser

Abs are vital to human immune responses and are composed of genetically variable H and L chains. These structures are initially expressed as BCRs. BCR diversity is shaped through somatic hypermutation and selection during immune responses. This evolutionary process produces B cell clones, cells that descend from a common ancestor but differ by mutations. Phylogenetic trees inferred from BCR sequences can reconstruct the history of mutations within a clone. Until recently, BCR sequencing technologies separated H and L chains, but advancements in single-cell sequencing now pair H and L chains from individual cells. However, it is unclear how these separate genes should be combined to infer B cell phylogenies. In this study, we investigated strategies for using paired H and L chain sequences to build phylogenetic trees. We found that incorporating L chains significantly improved tree accuracy and reproducibility across all methods tested. This improvement was greater than the difference between tree-building methods and persisted even when mixing bulk and single-cell sequencing data. However, we also found that many phylogenetic methods estimated significantly biased branch lengths when some L chains were missing, such as when mixing single-cell and bulk BCR data. This bias was eliminated using maximum likelihood methods with separate branch lengths for H and L chain gene partitions. Thus, we recommend using maximum likelihood methods with separate H and L chain partitions, especially when mixing data types. We implemented these methods in the R package Dowser: https://dowser.readthedocs.io.

Antibodies from dengue patients with prior exposure to Japanese encephalitis virus are broadly neutralizing against Zika virus

Exposure to multiple mosquito-borne flaviviruses within a lifetime is not uncommon; however, how sequential exposures to different flaviviruses shape the cross-reactive humoral response against an antigen from a different serocomplex has yet to be explored. Here, we report that dengue-infected individuals initially primed with the Japanese encephalitis virus (JEV) showed broad, highly neutralizing potencies against Zika virus (ZIKV). We also identified a rare class of ZIKV-cross-reactive human monoclonal antibodies with increased somatic hypermutation and broad neutralization against multiple flaviviruses. One huMAb, K8b, binds quaternary epitopes with heavy and light chains separately interacting with overlapping envelope protein dimer units spanning domains I, II, and III through cryo-electron microscopy and structure-based mutagenesis. JEV virus-like particle immunization in mice further confirmed that such cross-reactive antibodies, mainly IgG3 isotype, can be induced and proliferate through heterologous dengue virus (DENV) serotype 2 virus-like particle stimulation. Our findings highlight the role of prior immunity in JEV and DENV in shaping the breadth of humoral response and provide insights for future vaccination strategies in flavivirus-endemic countries.

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.

Antibody Isolation in C. neoformans

The importance of humoral immunity to fungal infections remains to be elucidated. In cryptococcosis, patients that fail to generate antibodies against antigens of the fungus Cryptococcus neoformans are more susceptible to the disease, demonstrating the importance of these molecules to the antifungal immune response. Historically, antibodies against C. neoformans have been applied in diagnosis, therapeutics, and as important research tools to elucidate fungal biology. Throughout the process of generating monoclonal antibodies (mAbs) from a single B-cell clone and targeting a single epitope, several immunization steps might be required for the detection of responsive antibodies to the antigen of interest in the serum. This complex mixture of antibodies comprises the polyclonal antibodies. To obtain mAbs, B-lymphocytes are harvested (from spleen or peripheral blood) and fused with tumor myeloma cells, to generate hybridomas that are individually cloned and specifically screened for mAb production. In this chapter, we describe all the necessary steps, from the immunization to polyclonal antibody harvesting, hybridoma generation, and mAb production and purification. Additionally, we discuss new cutting-edge approaches for generating interspecies mAbs, such as humanized mAbs, or for similar species in distinct host backgrounds.

Co-evolution of immunity and seasonal influenza viruses

Seasonal influenza viruses cause recurring global epidemics by continually evolving to escape host immunity. The viral constraints and host immune responses that limit and drive the evolution of these viruses are increasingly well understood. However, it remains unclear how most of these advances improve the capacity to reduce the impact of seasonal influenza viruses on human health. In this Review, we synthesize recent progress made in understanding the interplay between the evolution of immunity induced by previous infections or vaccination and the evolution of seasonal influenza viruses driven by the heterogeneous accumulation of antibody-mediated immunity in humans. We discuss the functional constraints that limit the evolution of the viruses, the within-host evolutionary processes that drive the emergence of new virus variants, as well as current and prospective options for influenza virus control, including the viral and immunological barriers that must be overcome to improve the effectiveness of vaccines and antiviral drugs.

Insights gained from single-cell analysis of chimeric antigen receptor T-cell immunotherapy in cancer

Advances in chimeric antigen receptor (CAR)-T cell therapy have significantly improved clinical outcomes of patients with relapsed or refractory hematologic malignancies. However, progress is still hindered as clinical benefit is only available for a fraction of patients. A lack of understanding of CAR-T cell behaviors in vivo at the single-cell level impedes their more extensive application in clinical practice. Mounting evidence suggests that single-cell sequencing techniques can help perfect the receptor design, guide gene-based T cell modification, and optimize the CAR-T manufacturing conditions, and all of them are essential for long-term immunosurveillance and more favorable clinical outcomes. The information generated by employing these methods also potentially informs our understanding of the numerous complex factors that dictate therapeutic efficacy and toxicities. In this review, we discuss the reasons why CAR-T immunotherapy fails in clinical practice and what this field has learned since the milestone of single-cell sequencing technologies. We further outline recent advances in the application of single-cell analyses in CAR-T immunotherapy. Specifically, we provide an overview of single-cell studies focusing on target antigens, CAR-transgene integration, and preclinical research and clinical applications, and then discuss how it will affect the future of CAR-T cell therapy.

Inferring B cell phylogenies from paired heavy and light chain BCR sequences with Dowser

Antibodies are vital to human immune responses and are composed of genetically variable heavy and light chains. These structures are initially expressed as B cell receptors (BCRs). BCR diversity is shaped through somatic hypermutation and selection during immune responses. This evolutionary process produces B cell clones, cells that descend from a common ancestor but differ by mutations. Phylogenetic trees inferred from BCR sequences can reconstruct the history of mutations within a clone. Until recently, BCR sequencing technologies separated heavy and light chains, but advancements in single cell sequencing now pair heavy and light chains from individual cells. However, it is unclear how these separate genes should be combined to infer B cell phylogenies. In this study, we investigated strategies for using paired heavy and light chain sequences to build phylogenetic trees. We found incorporating light chains significantly improved tree accuracy and reproducibility across all methods tested. This improvement was greater than the difference between tree building methods and persisted even when mixing bulk and single cell sequencing data. However, we also found that many phylogenetic methods estimated significantly biased branch lengths when some light chains were missing, such as when mixing single cell and bulk BCR data. This bias was eliminated using maximum likelihood methods with separate branch lengths for heavy and light chain gene partitions. Thus, we recommend using maximum likelihood methods with separate heavy and light chain partitions, especially when mixing data types. We implemented these methods in the R package Dowser: https://dowser.readthedocs.io.

Discovery of neutralizing SARS-CoV-2 antibodies enriched in a unique antigen specific B cell cluster

Despite development of effective SARS-CoV-2 vaccines, a sub-group of vaccine non-responders depends on therapeutic antibodies or small-molecule drugs in cases of severe disease. However, perpetual viral evolution has required continuous efficacy monitoring as well as exploration of new therapeutic antibodies, to circumvent resistance mutations arising in the viral population. We performed SARS-CoV-2-specific B cell sorting and subsequent single-cell sequencing on material from 15 SARS-CoV-2 convalescent participants. Through screening of 455 monoclonal antibodies for SARS-CoV-2 variant binding and virus neutralization, we identified a cluster of activated B cells highly enriched for SARS-CoV-2 neutralizing antibodies. Epitope binning and Cryo-EM structure analysis identified the majority of neutralizing antibodies having epitopes overlapping with the ACE2 receptor binding motif (class 1 binders). Extensive functional antibody characterization identified two potent neutralizing antibodies, one retaining SARS-CoV-1 neutralizing capability, while both bind major common variants of concern and display prophylactic efficacy in vivo. The transcriptomic signature of activated B cells harboring broadly binding neutralizing antibodies with therapeutic potential identified here, may be a guide in future efforts of rapid therapeutic antibody discovery.

Pleiotropic Effects of Influenza Vaccination

Influenza vaccines are designed to mimic natural influenza virus exposure and stimulate a long-lasting immune response to future infections. The evolving nature of the influenza virus makes vaccination an important and efficacious strategy to reduce healthcare-related complications of influenza. Several lines of evidence indicate that influenza vaccination may induce nonspecific effects, also referred to as heterologous or pleiotropic effects, that go beyond protection against infection. Different explanations are proposed, including the upregulation and downregulation of cytokines and epigenetic reprogramming in monocytes and natural killer cells, imprinting an immunological memory in the innate immune system, a phenomenon termed "trained immunity". Also, cross-reactivity between related stimuli and bystander activation, which entails activation of B and T lymphocytes without specific recognition of antigens, may play a role. In this review, we will discuss the possible nonspecific effects of influenza vaccination in cardiovascular disease, type 1 diabetes, cancer, and Alzheimer's disease, future research questions, and potential implications. A discussion of the potential effects on infections by other pathogens is beyond the scope of this review.

Immunotherapy in hematologic malignancies: achievements, challenges and future prospects

The immune-cell origin of hematologic malignancies provides a unique avenue for the understanding of both the mechanisms of immune responsiveness and immune escape, which has accelerated the progress of immunotherapy. Several categories of immunotherapies have been developed and are being further evaluated in clinical trials for the treatment of blood cancers, including stem cell transplantation, immune checkpoint inhibitors, antigen-targeted antibodies, antibody-drug conjugates, tumor vaccines, and adoptive cell therapies. These immunotherapies have shown the potential to induce long-term remission in refractory or relapsed patients and have led to a paradigm shift in cancer treatment with great clinical success. Different immunotherapeutic approaches have their advantages but also shortcomings that need to be addressed. To provide clinicians with timely information on these revolutionary therapeutic approaches, the comprehensive review provides historical perspectives on the applications and clinical considerations of the immunotherapy. Here, we first outline the recent advances that have been made in the understanding of the various categories of immunotherapies in the treatment of hematologic malignancies. We further discuss the specific mechanisms of action, summarize the clinical trials and outcomes of immunotherapies in hematologic malignancies, as well as the adverse effects and toxicity management and then provide novel insights into challenges and future directions.

The predictive and prognostic value of peripheral blood antigen-specific memory B cells in phospholipase A2 receptor-associated membranous nephropathy

Background

Phospholipase A2 receptor-associated membranous nephropathy (PLA2R-MN) is an anti-PLA2R antibody (PLA2R-Ab) mediated autoimmune kidney disease. Although antibody titer correlates closely with disease activity, whether it can provide longer-term predictions on disease course and progression is unclear. Rituximab, a B-cell depletion therapy, has become the first-line treatment option for PLA2R-MN; however, the response to Rituximab varies among patients.

Methods

We developed a flow cytometry-based test that detects and quantifies PLA2R antigen-specific memory B cells (PLA2R-MBCs) in peripheral blood, the primary source for PLA2R-Ab production upon disease relapse. We applied the test to 159 blood samples collected from 28 patients with PLA2R-MN (at diagnosis, during and after immunosuppressive treatment, immunological remission, and relapse) to evaluate the relationship between circulating PLA2R-MBC levels and disease activity.

Results

The level of PLA2R-MBCs in healthy controls (n=56) is less than or equal to 1.5% of the total MBC compartment. High circulating PLA2R-MBC levels were detected in two patients post-Rituximab despite achieving immunologic and proteinuric remission, as well as in two patients with negative serum autoantibody but increasing proteinuria. Elimination of these cells with Rituximab improved clinical outcomes. Moreover, five patients exhibited elevated PLA2R-MBC levels before disease relapse, followed by a rapid decline to baseline when relapse became clinically evident. COVID-19 vaccination or SARS-CoV-2 infection significantly affected the dynamics of circulating PLA2R-MBCs.

Conclusions

This study suggests that monitoring PLA2R-MBC levels in patients with PLA2R-MN may help refine and individualize immunosuppressive therapy and predict disease course and progression. The technology and findings may also have broader applications in the clinical management of other autoimmune diseases.

Upregulated CD8+ MAIT cell differentiation and KLRD1 gene expression after inactivated SARS-CoV-2 vaccination identified by single-cell sequencing

Background

The primary strategy for reducing the incidence of COVID-19 is SARS-CoV-2 vaccination. Few studies have explored T cell subset differentiation and gene expressions induced by SARS-CoV-2 vaccines. Our study aimed to analyze T cell dynamics and transcriptome gene expression after inoculation with an inactivated SARS-CoV-2 vaccine by using single-cell sequencing.

Methods

Single-cell sequencing was performed after peripheral blood mononuclear cells were extracted from three participants at four time points during the inactivated SARS-CoV-2 vaccination process. After library preparation, raw read data analysis, quality control, dimension reduction and clustering, single-cell T cell receptor (TCR) sequencing, TCR V(D)J sequencing, cell differentiation trajectory inference, differentially expressed genes, and pathway enrichment were analyzed to explore the characteristics and mechanisms of postvaccination immunodynamics.

Results

Inactivated SARS-CoV-2 vaccination promoted T cell proliferation, TCR clone amplification, and TCR diversity. The proliferation and differentiation of CD8+ mucosal-associated invariant T (MAIT) cells were significantly upregulated, as were KLRD1 gene expression and the two pathways of nuclear-transcribed mRNA catabolic process, nonsense-mediated decay, and translational initiation.

Conclusion

Upregulation of CD8+ MAIT cell differentiation and KLRD1 expression after inactivated SARS-CoV-2 vaccination was demonstrated by single-cell sequencing. We conclude that the inactivated SARS-CoV-2 vaccine elicits adaptive T cell immunity to enhance early immunity and rapid response to the targeted virus.

Gene regulatory network study of rheumatoid arthritis in single-cell chromatin landscapes of peripheral blood mononuclear cells

OBJECTIVES

Assays for transposase-accessible chromatin with single-cell sequencing (scATAC-seq) contribute to the progress in epigenetic studies. The purpose of our project was to discover the transcription factors (TFs) that were involved in the pathogenesis of rheumatoid arthritis (RA) at a single-cell resolution using epigenetic technology.

METHODS

Peripheral blood mononuclear cells of seven RA patients and seven natural controls were extracted nuclei suspensions for library construction. Subsequently, scATAC-seq was performed to generate a high-resolution map of active regulatory DNA for bioinformatics analysis.

RESULTS

We obtained 22 accessible chromatin patterns. Then, 10 key TFs were involved in RA pathogenesis by regulating the activity of mitogen-activated protein kinase. Consequently, two genes (PTPRC and SPAG9) regulated by 10 key TFs were found, which may be associated with RA disease pathogenesis, and these TFs were obviously enriched in RA patients (P < .05, fold change value > 1.2). With further quantitative polymerase chain reaction validation on PTPRC and SPAG9 in monocytes, we found differential expression of these two genes, which were regulated by eight TFs [ZNF384, HNF1B, DMRTA2, MEF2A, NFE2L1, CREB3L4 (var. 2), FOSL2::JUNB (var. 2), and MEF2B], showing highly accessible binding sites in RA patients.

CONCLUSIONS

These findings demonstrate the value of using scATAC-seq to reveal transcriptional regulatory variation in RA-derived peripheral blood mononuclear cells, providing insights into therapy from an epigenetic perspective.

High-throughput single-cell profiling of B cell responses following inactivated influenza vaccination in young and older adults

Seasonal influenza contributes to a substantial disease burden, resulting in approximately 10 million hospital visits and 50 thousand deaths in a typical year in the United States. 70 - 85% of the mortality occurs in people over the age of 65. Influenza vaccination is the best protection against the virus, but it is less effective for the elderly, which may be in part due to differences in the quantity or type of B cells induced by vaccination. To investigate this possibility, we sorted pre- and post-vaccination peripheral blood B cells from three young and three older adults with strong antibody responses to the inactivated influenza vaccine and employed single-cell technology to simultaneously profile the gene expression and the B cell receptor (BCR) of the B cells. Prior to vaccination, we observed a higher somatic hypermutation frequency and a higher abundance of activated B cells in older adults than in young adults. Following vaccination, young adults mounted a more clonal response than older adults. The expanded clones included a mix of plasmablasts, activated B cells, and resting memory B cells in both age groups, with a decreased proportion of plasmablasts in older adults. Differential abundance analysis identified additional vaccine-responsive cells that were not part of expanded clones, especially in older adults. We observed broadly consistent gene expression changes in vaccine-responsive plasmablasts and greater heterogeneity among activated B cells between age groups. These quantitative and qualitative differences in the B cells provide insights into age-related changes in influenza vaccination response.

The ClusPro AbEMap web server for the prediction of antibody epitopes

Antibodies play an important role in the immune system by binding to molecules called antigens at their respective epitopes. These interfaces or epitopes are structural entities determined by the interactions between an antibody and an antigen, making them ideal systems to analyze by using docking programs. Since the advent of high-throughput antibody sequencing, the ability to perform epitope mapping using only the sequence of the antibody has become a high priority. ClusPro, a leading protein-protein docking server, together with its template-based modeling version, ClusPro-TBM, have been re-purposed to map epitopes for specific antibody-antigen interactions by using the Antibody Epitope Mapping server (AbEMap). ClusPro-AbEMap offers three different modes for users depending on the information available on the antibody as follows: (i) X-ray structure, (ii) computational/predicted model of the structure or (iii) only the amino acid sequence. The AbEMap server presents a likelihood score for each antigen residue of being part of the epitope. We provide detailed information on the server's capabilities for the three options and discuss how to obtain the best results. In light of the recent introduction of AlphaFold2 (AF2), we also show how one of the modes allows users to use their AF2-generated antibody models as input. The protocol describes the relative advantages of the server compared to other epitope-mapping tools, its limitations and potential areas of improvement. The server may take 45-90 min depending on the size of the proteins.

Genotype-phenotype landscapes for immune-pathogen coevolution

Our immune systems constantly coevolve with the pathogens that challenge them, as pathogens adapt to evade our defense responses, with our immune repertoires shifting in turn. These coevolutionary dynamics take place across a vast and high-dimensional landscape of potential pathogen and immune receptor sequence variants. Mapping the relationship between these genotypes and the phenotypes that determine immune-pathogen interactions is crucial for understanding, predicting, and controlling disease. Here, we review recent developments applying high-throughput methods to create large libraries of immune receptor and pathogen protein sequence variants and measure relevant phenotypes. We describe several approaches that probe different regions of the high-dimensional sequence space and comment on how combinations of these methods may offer novel insight into immune-pathogen coevolution.

Germline-encoded amino acid-binding motifs drive immunodominant public antibody responses

Despite the vast diversity of the antibody repertoire, infected individuals often mount antibody responses to precisely the same epitopes within antigens. The immunological mechanisms underpinning this phenomenon remain unknown. By mapping 376 immunodominant "public epitopes" at high resolution and characterizing several of their cognate antibodies, we concluded that germline-encoded sequences in antibodies drive recurrent recognition. Systematic analysis of antibody-antigen structures uncovered 18 human and 21 partially overlapping mouse germline-encoded amino acid-binding (GRAB) motifs within heavy and light V gene segments that in case studies proved critical for public epitope recognition. GRAB motifs represent a fundamental component of the immune system's architecture that promotes recognition of pathogens and leads to species-specific public antibody responses that can exert selective pressure on pathogens.

A cluster of broadly neutralizing IgG against BK polyomavirus in a repertoire dominated by IgM

The BK polyomavirus (BKPyV) is an opportunistic pathogen, which is only pathogenic in immunosuppressed individuals, such as kidney transplant recipients, in whom BKPyV can cause significant morbidity. To identify broadly neutralizing antibodies against this virus, we used fluorescence-labeled BKPyV virus-like particles to sort BKPyV-specific B cells from the PBMC of KTx recipients, then single-cell RNAseq to obtain paired heavy- and light-chain antibody sequences from 2,106 sorted B cells. The BKPyV-specific repertoire was highly diverse in terms of both V-gene usage and clonotype diversity and included most of the IgM B cells, including many with extensive somatic hypermutation. In two patients where sufficient data were available, IgM B cells in the BKPyV-specific dataset had significant differences in V-gene usage compared with IgG B cells from the same patient. CDR3 sequence-based clustering allowed us to identify and characterize three broadly neutralizing "41F17-like" clonotypes that were predominantly IgG, suggesting that some specific BKPyV capsid epitopes are preferentially targeted by IgG.

Systemic immune dysregulation in severe tuberculosis patients revealed by a single-cell transcriptome atlas

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb) infection, is currently the deadliest infectious disease in human that can evolve to severe forms. A comprehensive immune landscape for Mtb infection is critical for achieving TB cure, especially for severe TB patients. We performed single-cell RNA transcriptome and T-cell/B-cell receptor (TCR/BCR) sequencing of 213,358 cells from 27 samples, including 6 healthy donors and 21 active TB patients with varying severity (6 mild, 6 moderate and 9 severe cases). Two published profiles of latent TB infection were integrated for the analysis. We observed an obviously elevated proportion of inflammatory immune cells (e.g., monocytes), as well as a markedly decreased abundance of various lymphocytes (e.g., NK and γδT cells) in severe patients, revealing that lymphopenia might be a prominent feature of severe disease. Further analyses indicated that significant activation of cell apoptosis pathways, including perforin/granzyme-, TNF-, FAS- and XAF1-induced apoptosis, as well as cell migration pathways might confer this reduction. The immune landscape in severe patients was characterized by widespread immune exhaustion in Th1, CD8⁺T and NK cells as well as high cytotoxic state in CD8⁺T and NK cells. We also discovered that myeloid cells in severe TB patients may involve in the immune paralysis. Systemic upregulation of S100A12 and TNFSF13B, mainly by monocytes in the peripheral blood, may contribute to the inflammatory cytokine storms in severe patients. Our data offered a rich resource for understanding of TB immunopathogenesis and designing effective therapeutic strategies for TB, especially for severe patients.

T-bethighCD21low B cells: the need to unify our understanding of a distinct B cell population in health and disease

After many years of a niche research in a few laboratories of the world, T-bet^highCD21^low B cells have entered the limelight during the last years after the discovery of T-bet as common transcription factor of this unconventional B cell population and the increasing awareness of the expansion of these cells in autoimmune and infectious diseases. This population consists of different subsets which share large parts of their transcriptome, essential phenotypic markers, and reduced B cell receptor (BCR) signaling capacity. Inborn errors of immunity have helped to delineate essential signals for their differentiation. While our comprehension of their origin has improved, future research will hopefully profit from a common definition of the different T-bet^highCD21^low subpopulations in order to better define their specific roles during normal and aberrant immune responses.

Persistent virus-specific and clonally expanded antibody-secreting cells respond to induced self-antigen in the CNS

B cells contribute to the pathogenesis of both cellular- and humoral-mediated central nervous system (CNS) inflammatory diseases through a variety of mechanisms. In such conditions, B cells may enter the CNS parenchyma and contribute to local tissue destruction. It remains unexplored, however, how infection and autoimmunity drive transcriptional phenotypes, repertoire features, and antibody functionality. Here, we profiled B cells from the CNS of murine models of intracranial (i.c.) viral infections and autoimmunity. We identified a population of clonally expanded, antibody-secreting cells (ASCs) that had undergone class-switch recombination and extensive somatic hypermutation following i.c. infection with attenuated lymphocytic choriomeningitis virus (rLCMV). Recombinant expression and characterisation of these antibodies revealed specificity to viral antigens (LCMV glycoprotein GP), correlating with ASC persistence in the brain weeks after resolved infection. Furthermore, these virus-specific ASCs upregulated proliferation and expansion programs in response to the conditional and transient induction of the LCMV GP as a neo-self antigen by astrocytes. This class-switched, clonally expanded, and mutated population persisted and was even more pronounced when peripheral B cells were depleted prior to autoantigen induction in the CNS. In contrast, the most expanded B cell clones in mice with persistent expression of LCMV GP in the CNS did not exhibit neo-self antigen specificity, potentially a consequence of local tolerance induction. Finally, a comparable population of clonally expanded, class-switched, and proliferating ASCs was detected in the cerebrospinal fluid of relapsing multiple sclerosis (RMS) patients. Taken together, our findings support the existence of B cells that populate the CNS and are capable of responding to locally encountered autoantigens.

High activation levels maintained in receptor-binding domain-specific memory B cells in people with severe coronavirus disease 2019

The long-term health consequences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are still being understood. The molecular and phenotypic properties of SARS-CoV-2 antigen-specific T cells suggest a dysfunctional profile that persists in convalescence in those who were severely ill. By contrast, the antigen-specific memory B-cell (MBC) population has not yet been analyzed to the same degree, but phenotypic analysis suggests differences following recovery from mild or severe coronavirus disease 2019 (COVID-19). Here, we performed single-cell molecular analysis of the SARS-CoV-2 receptor-binding domain (RBD)-specific MBC population in three patients after severe COVID-19 and four patients after mild/moderate COVID-19. We analyzed the transcriptomic and B-cell receptor repertoire profiles at ~2 months and ~4 months after symptom onset. Transcriptomic analysis revealed a higher level of tumor necrosis factor-alpha (TNF-α) signaling via nuclear factor-kappa B in the severe group, involving CD80, FOS, CD83 and TNFAIP3 genes that was maintained over time. We demonstrated the presence of two distinct activated MBCs subsets based on expression of CD80hi TNFAIP3hi and CD11chi CD95hi at the transcriptome level. Both groups revealed an increase in somatic hypermutation over time, indicating progressive evolution of humoral memory. This study revealed distinct molecular signatures of long-term RBD-specific MBCs in convalescence, indicating that the longevity of these cells may differ depending on acute COVID-19 severity.

Effectiveness of influenza vaccination against SARS-CoV-2 infection among healthcare workers in Qatar

BACKGROUND

Some studies have reported that influenza vaccination is associated with lower risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and/or coronavirus disease 2019 (COVID-19) morbidity and mortality. This study aims to estimate effectiveness of influenza vaccination, using Abbott's quadrivalent Influvac Tetra vaccine, against SARS-CoV-2 infection and against severe COVID-19.

METHODS

This matched, test-negative, case-control study was implemented on a population of 30,774 healthcare workers (HCWs) in Qatar during the 2020 annual influenza vaccination campaign, September 17, 2020-December 31, 2020, before introduction of COVID-19 vaccination.

RESULTS

Of 30,774 HCWs, 576 with PCR-positive tests and 10,033 with exclusively PCR-negative tests were eligible for inclusion in the study. Matching by sex, age, nationality, reason for PCR testing, and PCR test date yielded 518 cases matched to 2058 controls. Median duration between influenza vaccination and the PCR test was 43 days (IQR, 29-62). Estimated effectiveness of influenza vaccination against SARS-CoV-2 infection> 14 days after receiving the vaccine was 29.7% (95% CI: 5.5-47.7%). Estimated effectiveness of influenza vaccination against severe, critical, or fatal COVID-19 was 88.9% (95% CI: 4.1-98.7%). Sensitivity analyses confirmed the main analysis results.

CONCLUSIONS

Recent influenza vaccination is associated with a significant reduction in the risk of SARS-CoV-2 infection and COVID-19 severity.

Mapping of antibody epitopes based on docking and homology modeling

Antibodies are key proteins produced by the immune system to target pathogen proteins termed antigens via specific binding to surface regions called epitopes. Given an antigen and the sequence of an antibody the knowledge of the epitope is critical for the discovery and development of antibody based therapeutics. In this work, we present a computational protocol that uses template-based modeling and docking to predict epitope residues. This protocol is implemented in three major steps. First, a template-based modeling approach is used to build the antibody structures. We tested several options, including generation of models using AlphaFold2. Second, each antibody model is docked to the antigen using the fast Fourier transform (FFT) based docking program PIPER. Attention is given to optimally selecting the docking energy parameters depending on the input data. In particular, the van der Waals energy terms are reduced for modeled antibodies relative to x-ray structures. Finally, ranking of antigen surface residues is produced. The ranking relies on the docking results, that is, how often the residue appears in the docking poses' interface, and also on the energy favorability of the docking pose in question. The method, called PIPER-Map, has been tested on a widely used antibody-antigen docking benchmark. The results show that PIPER-Map improves upon the existing epitope prediction methods. An interesting observation is that epitope prediction accuracy starting from antibody sequence alone does not significantly differ from that of starting from unbound (i.e., separately crystallized) antibody structure.

Generation of a single-cell B cell atlas of antibody repertoires and transcriptomes to identify signatures associated with antigen specificity

Although new genomics-based pipelines have potential to augment antibody discovery, these methods remain in their infancy due to an incomplete understanding of the selection process that governs B cell clonal selection, expansion, and antigen specificity. Furthermore, it remains unknown how factors such as aging and reduction of tolerance influence B cell selection. Here we perform single-cell sequencing of antibody repertoires and transcriptomes of murine B cells following immunizations with a model therapeutic antigen target. We determine the relationship between antibody repertoires, gene expression signatures, and antigen specificity across 100,000 B cells. Recombinant expression and characterization of 227 monoclonal antibodies revealed the existence of clonally expanded and class-switched antigen-specific B cells that were more frequent in young mice. Although integrating multiple repertoire features such as germline gene usage and transcriptional signatures failed to distinguish antigen-specific from nonspecific B cells, other features such as immunoglobulin G (IgG) subtype and sequence composition correlated with antigen specificity.

Profiling of peripheral blood B-cell transcriptome in children who developed coeliac disease in a prospective study

Background

In coeliac disease (CoD), the role of B-cells has mainly been considered to be production of antibodies. The functional role of B-cells has not been analysed extensively in CoD.

Methods

We conducted a study to characterize gene expression in B-cells from children developing CoD early in life using samples collected before and at the diagnosis of the disease. Blood samples were collected from children at risk at 12, 18, 24 and 36 months of age. RNA from peripheral blood CD19⁺ cells was sequenced and differential gene expression was analysed using R package Limma.

Findings

Overall, we found one gene, HNRNPL, modestly downregulated in all patients (logFC -0·7; q = 0·09), and several others downregulated in those diagnosed with CoD already by the age of 2 years.

Interpretation

The data highlight the role of B-cells in CoD development. The role of HNRPL in suppressing enteroviral replication suggests that the predisposing factor for both CoD and enteroviral infections is the low level of HNRNPL expression.

Funding

EU FP7 grant no. 202063, EU Regional Developmental Fund and research grant PRG712, The Academy of Finland Centre of Excellence in Molecular Systems Immunology and Physiology Research (SyMMyS) 2012-2017, grant no. 250114) and, AoF Personalized Medicine Program (grant no. 292482), AoF grants 292335, 294337, 319280, 31444, 319280, 329277, 331790) and grants from the Sigrid Jusélius Foundation (SJF).

Hierarchical sequence-affinity landscapes shape the evolution of breadth in an anti-influenza receptor binding site antibody

Broadly neutralizing antibodies (bnAbs) that neutralize diverse variants of a particular virus are of considerable therapeutic interest. Recent advances have enabled us to isolate and engineer these antibodies as therapeutics, but eliciting them through vaccination remains challenging, in part due to our limited understanding of how antibodies evolve breadth. Here, we analyze the landscape by which an anti-influenza receptor binding site (RBS) bnAb, CH65, evolved broad affinity to diverse H1 influenza strains. We do this by generating an antibody library of all possible evolutionary intermediates between the unmutated common ancestor (UCA) and the affinity-matured CH65 antibody and measure the affinity of each intermediate to three distinct H1 antigens. We find that affinity to each antigen requires a specific set of mutations - distributed across the variable light and heavy chains - that interact non-additively (i.e., epistatically). These sets of mutations form a hierarchical pattern across the antigens, with increasingly divergent antigens requiring additional epistatic mutations beyond those required to bind less divergent antigens. We investigate the underlying biochemical and structural basis for these hierarchical sets of epistatic mutations and find that epistasis between heavy chain mutations and a mutation in the light chain at the V_H-V_L interface is essential for binding a divergent H1. Collectively, this is the first work to comprehensively characterize epistasis between heavy and light chain mutations and shows that such interactions are both strong and widespread. Together with our previous study analyzing a different class of anti-influenza antibodies, our results implicate epistasis as a general feature of antibody sequence-affinity landscapes that can potentiate and constrain the evolution of breadth.

Influenza vaccination features revealed by a single-cell transcriptome atlas

Emerging and re-emerging viruses like influenza virus pose a continuous global public health threat. Vaccines are one of the most effective public health strategies for controlling infectious diseases. However, little is known about the immunological features of vaccination at the single-cell resolution, including for influenza vaccination. Here, we report the single-cell transcriptome atlas of longitudinally collected peripheral blood mononuclear cells (PBMCs) in individuals immunized with an inactivated influenza vaccine. Overall, vaccination with the influenza vaccine only had a small impact on the composition of peripheral immune cells, but elicited global transcriptional changes in multiple immune cell subsets. In plasma and B cell subsets, transcriptomic changes, which were mostly involved in antibody production as well as B cell activation and differentiation, were observed after influenza vaccinations. In influenza-vaccinated individuals, we found a reduction in multiple biological processes (e.g., interferon response, inflammatory response, HLA-I/II molecules, cellular apoptosis, migration, and cytotoxicity, etc.,) 7 days postvaccination in multiple immune cell subsets. However, 14 days postvaccination, these levels returned to similar levels observed in prevaccination samples. Additionally, we did not observe significant upregulation of pro-inflammatory response genes and key thrombosis-related genes in influenza-vaccinated individuals. Taken together, we report a cell atlas of the peripheral immune response to influenza vaccination and provide a resource for understanding the immunological response mechanisms of influenza vaccination.

Inference of B cell clonal families using heavy/light chain pairing information

Next generation sequencing of B cell receptor (BCR) repertoires has become a ubiquitous tool for understanding the antibody-mediated immune response: it is now common to have large volumes of sequence data coding for both the heavy and light chain subunits of the BCR. However, until the recent development of high throughput methods of preserving heavy/light chain pairing information, these samples contained no explicit information on which heavy chain sequence pairs with which light chain sequence. One of the first steps in analyzing such BCR repertoire samples is grouping sequences into clonally related families, where each stems from a single rearrangement event. Many methods of accomplishing this have been developed, however, none so far has taken full advantage of the newly-available pairing information. This information can dramatically improve clustering performance, especially for the light chain. The light chain has traditionally been challenging for clonal family inference because of its low diversity and consequent abundance of non-clonal families with indistinguishable naive rearrangements. Here we present a method of incorporating this pairing information into the clustering process in order to arrive at a more accurate partition of the data into clonally related families. We also demonstrate two methods of fixing imperfect pairing information, which may allow for simplified sample preparation and increased sequencing depth. Finally, we describe several other improvements to the partis software package.

The memory B cell response to influenza vaccination is impaired in older persons

Influenza infection imparts an age-related increase in mortality and morbidity. The most effective countermeasure is vaccination; however, vaccines offer modest protection in older adults. To investigate how aging impacts the memory B cell response, we track hemagglutinin-specific B cells by indexed flow sorting and single-cell RNA sequencing (scRNA-seq) in 20 healthy adults that were administered the trivalent influenza vaccine. We demonstrate age-related skewing in the memory B cell compartment 6 weeks after vaccination, with younger adults developing hemagglutinin-specific memory B cells with an FcRL5+ "atypical" phenotype, showing evidence of somatic hypermutation and positive selection, which happened to a lesser extent in older persons. We use publicly available scRNA-seq from paired human lymph node and blood samples to corroborate that FcRL5+ atypical memory B cells can derive from germinal center (GC) precursors. Together, this study shows that the aged human GC reaction and memory B cell response following vaccination is defective.

Single-cell transcriptomic atlas reveals distinct immunological responses between COVID-19 vaccine and natural SARS-CoV-2 infection

To control the ongoing coronavirus disease-2019 (COVID-19) pandemic, CoronaVac (Sinovac), an inactivated vaccine, has been granted emergency use authorization by many countries. However, the underlying mechanisms of the inactivated COVID-19 vaccine-induced immune response remain unclear, and little is known about its features compared to (Severe acute respiratory syndrome coronavirus 2) SARS-CoV-2 infection. Here, we implemented single-cell RNA sequencing (scRNA-seq) to profile longitudinally collected PBMCs (peripheral blood mononuclear cells) in six individuals immunized with CoronaVac and compared these to the profiles of COVID-19 infected patients from a Single Cell Consortium. Both inactivated vaccines and SARS-CoV-2 infection altered the proportion of different immune cell types, caused B cell activation and differentiation, and induced the expression of genes associated with antibody production in the plasma. The inactivated vaccine and SARS-COV-2 infection also caused alterations in peripheral immune activity such as interferon response, inflammatory cytokine expression, innate immune cell apoptosis and migration, effector T cell exhaustion and cytotoxicity, however, the magnitude of change was greater in COVID-19 patients, especially those with severe disease, than in immunized individuals. Further analyses revealed a distinct peripheral immune cell phenotype associated with CoronaVac immunization (HLA class II upregulation and IL21R upregulation in naïve B cells) versus SARS-CoV-2 infection (HLA class II downregulation and IL21R downregulation in naïve B cells from severe disease individuals). There were also differences in the expression of important genes associated with proinflammatory cytokines and thrombosis. In conclusion, this study provides a single-cell atlas of the systemic immune response to CoronaVac immunization and revealed distinct immune responses between inactivated vaccines and SARS-CoV-2 infection.

Comprehensive multi-omics single-cell data integration reveals greater heterogeneity in the human immune system

Single-cell transcriptomics enables the definition of diverse human immune cell types across multiple tissues and disease contexts. Further deeper biological understanding requires comprehensive integration of multiple single-cell omics (transcriptomic, proteomic, and cell-receptor repertoire). To improve the identification of diverse cell types and the accuracy of cell-type classification in multi-omics single-cell datasets, we developed SuPERR, a novel analysis workflow to increase the resolution and accuracy of clustering and allow for the discovery of previously hidden cell subsets. In addition, SuPERR accurately removes cell doublets and prevents widespread cell-type misclassification by incorporating information from cell-surface proteins and immunoglobulin transcript counts. This approach uniquely improves the identification of heterogeneous cell types and states in the human immune system, including rare subsets of antibody-secreting cells in the bone marrow.

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SuPERR removes heterotypic doublets and cell-type misclassifications in scRNA-seq

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Sequential gating on cell-surface proteins resolves major cell lineages in scRNA-seq

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Defining major cell lineages before clustering reduces cell-type misclassifications

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Antibody counts from single-cell V(D)J matrix accurately identify plasma cells

Echidna: integrated simulations of single-cell immune receptor repertoires and transcriptomes

Motivation

Single-cell sequencing now enables the recovery of full-length immune receptor repertoires [B cell receptor (BCR) and T cell receptor (TCR) repertoires], in addition to gene expression information. The feature-rich datasets produced from such experiments require extensive and diverse computational analyses, each of which can significantly influence the downstream immunological interpretations, such as clonal selection and expansion. Simulations produce validated standard datasets, where the underlying generative model can be precisely defined and furthermore perturbed to investigate specific questions of interest. Currently, there is no tool that can be used to simulate single-cell datasets incorporating immune receptor repertoires and gene expression.

Results

We developed Echidna, an R package that simulates immune receptors and transcriptomes at single-cell resolution with user-tunable parameters controlling a wide range of features such as clonal expansion, germline gene usage, somatic hypermutation, transcriptional phenotypes and spatial location. Echidna can additionally simulate time-resolved B cell evolution, producing mutational networks with complex selection histories incorporating class-switching and B cell subtype information. We demonstrated the benchmarking potential of Echidna by simulating clonal lineages and comparing the known simulated networks with those inferred from only the BCR sequences as input. Finally, we simulated immune repertoire information onto existing spatial transcriptomic experiments, thereby generating novel datasets that could be used to develop and integrate methods to profile clonal selection in a spatially resolved manner. Together, Echidna provides a framework that can incorporate experimental data to simulate single-cell immune repertoires to aid software development and bioinformatic benchmarking of clonotyping, phylogenetics, transcriptomics and machine learning strategies.

Availability and implementation

The R package and code used in this manuscript can be found at github.com/alexyermanos/echidna and also in the R package Platypus (Yermanos et al., 2021). Installation instructions and the vignette for Echidna is described in the Platypus Computational Ecosystem (https://alexyermanos.github.io/Platypus/index.html). Publicly available data and corresponding sample accession numbers can be found in Supplementary Tables S2 and S3.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Influenza vaccination and single cell multiomics reveal sex dimorphic immune imprints of prior mild COVID-19

Viral infections can have profound and durable functional impacts on the immune system. There is an urgent need to characterize the long-term immune effects of SARS-CoV-2 infection given the persistence of symptoms in some individuals and the continued threat of novel variants. Here we use systems immunology, including longitudinal multimodal single cell analysis (surface proteins, transcriptome, and V(D)J sequences) from 33 previously healthy individuals after recovery from mild, non-hospitalized COVID-19 and 40 age- and sex-matched healthy controls with no history of COVID-19 to comparatively assess the post-infection immune status (mean: 151 days after diagnosis) and subsequent innate and adaptive responses to seasonal influenza vaccination. Identification of both sex-specific and -independent temporally stable changes, including signatures of T-cell activation and repression of innate defense/immune receptor genes (e.g., Toll-like receptors) in monocytes, suggest that mild COVID-19 can establish new post-recovery immunological set-points. COVID-19-recovered males had higher innate, influenza-specific plasmablast, and antibody responses after vaccination compared to healthy males and COVID-19-recovered females, partly attributable to elevated pre-vaccination frequencies of a GPR56 expressing CD8+ T-cell subset in male recoverees that are "poised" to produce higher levels of IFNγ upon inflammatory stimulation. Intriguingly, by day 1 post-vaccination in COVID-19-recovered subjects, the expression of the repressed genes in monocytes increased and moved towards the pre-vaccination baseline of healthy controls, suggesting that the acute inflammation induced by vaccination could partly reset the immune states established by mild COVID-19. Our study reveals sex-dimorphic immune imprints and in vivo functional impacts of mild COVID-19 in humans, suggesting that prior COVID-19, and possibly respiratory viral infections in general, could change future responses to vaccination and in turn, vaccines could help reset the immune system after COVID-19, both in an antigen-agnostic manner.

Single-cell immune repertoire sequencing of B and T cells in murine models of infection and autoimmunity

Adaptive immune repertoires are composed by the ensemble of B and T-cell receptors within an individual, reflecting both past and current immune responses. Recent advances in single-cell sequencing enable recovery of the complete adaptive immune receptor sequences in addition to transcriptional information. Here, we recovered transcriptome and immune repertoire information for polyclonal T follicular helper cells following lymphocytic choriomeningitis virus (LCMV) infection, CD8+ T cells with binding specificity restricted to two distinct LCMV peptides, and B and T cells isolated from the nervous system in the context of experimental autoimmune encephalomyelitis. We could relate clonal expansion, germline gene usage, and clonal convergence to cell phenotypes spanning activation, memory, naive, antibody secretion, T-cell inflation, and regulation. Together, this dataset provides a resource for immunologists that can be integrated with future single-cell immune repertoire and transcriptome sequencing datasets.

The development and function of CD11c+ atypical B cells - insights from single cell analysis

CD11c+ T-bet+ atypical B cells (ABCs) have been identified in the context of vaccination, acute and chronic infections and autoimmune disease. However, the origins and functions of ABCs remain elusive. A major obstacle in the study of ABCs, and human MBCs more generally, has been the use of different phenotypic markers in different contexts to identify what appear to be phenotypically similar cells. Advances in single-cell RNA sequencing (scRNA-seq) technology have allowed researchers to accurately identify ABCs in different immune contexts such as diseases and tissues. Notably, recent studies utilizing single cell techniques have demonstrated ABCs are a highly conserved memory B cell lineage. This analysis has also revealed that ABCs are more abundant in ostensibly healthy donors than previously thought. Nonetheless, the normal function of these cells remains elusive. In this review, we will focus on scRNA-seq studies to discuss recent advances in our understanding about the development and functions of ABCs.

Immunosuppressive landscape in hepatocellular carcinoma revealed by single-cell sequencing

Background/Aims

Hepatocellular carcinoma (HCC), accounting for 75-85% of primary liver cancer cases, is the third leading cause of cancer-related death worldwide. The purpose of this research was to examine the tumor immune microenvironment (TIME) in HCC.

Methods

We investigated the HCC TIME by integrated analysis of single-cell and bulk-tissue sequencing data to reveal the landscape of major immune cell types.

Results

Regulatory T(Treg) cells were found to be specifically distributed in the TIME of HCC. Several immune checkpoints, including TNFRSF4, TIGIT and CTLA4, were found to be uniquely overexpressed in Treg cells, and the glycolysis/gluconeogenesis pathway was enriched in Treg cells. We also discovered the presence of two NK-cell subsets with different cytotoxic capacities, one in an activated state with antitumor effects and another with an exhausted status. In addition, memory B cells in HCC were found to exist in a unique state, with high proliferation, low differentiation, and low activity, which was induced by overexpression of PRAP1 and activation of the MIF-CD74 axis.

Conclusions

We revealed the TIME landscape in HCC, highlighting the heterogeneity of major immune cell types and their potential mechanisms in the formation of an immunosuppressive environment. Hence, blocking the formation of the TIME could be a useful therapeutic strategy for HCC.

Cross-Protection Induced by Virus-like Particles Derived from the Influenza B Virus

The mismatch between the circulating influenza B virus (IBV) and the vaccine strain contributes to the rapid emergence of IBV infection cases throughout the globe, which necessitates the development of effective vaccines conferring broad protection. Here, we generated influenza B virus-like particle (VLP) vaccines expressing hemagglutinin, neuraminidase, or both antigens derived from the influenza B virus (B/Washington/02/2019 (B/Victoria lineage)-like virus, B/Phuket/3073/2013 (B/Yamagata lineage)-like virus. We found that irrespective of the derived antigen lineage, immunizing mice with the IBV VLPs significantly reduced lung viral loads, minimized bodyweight loss, and ensured 100% survival upon Victoria lineage virus B/Colorado/06/2017 challenge infection. These results were closely correlated with the vaccine-induced antibody responses and HI titer in sera, IgG, IgA antibody responses, CD4+ and CD8+ T cell responses, germinal center B cell responses, and inflammatory cytokine responses in the lungs. We conclude that hemagglutinin, neuraminidase, or both antigen-expressing VLPs derived from these influenza B viruses that were circulating during the 2020/21 season provide cross-protections against mismatched Victoria lineage virus (B/Colorado/06/2017) challenge infections.

Clonal structure, stability and dynamics of human memory B cells and circulating plasmablasts

Memory B cells persist for a lifetime and rapidly differentiate into antibody-producing plasmablasts and plasma cells upon antigen re-encounter. The clonal relationship and evolution of memory B cells and circulating plasmablasts is not well understood. Using single-cell sequencing combined with isolation of specific antibodies, we found that in two healthy donors, the memory B cell repertoire was dominated by large IgM, IgA and IgG2 clonal families, whereas IgG1 families, including those specific for recall antigens, were of small size. Analysis of multiyear samples demonstrated stability of memory B cell clonal families and revealed that a large fraction of recently generated plasmablasts was derived from long-term memory B cell families and was found recurrently. Collectively, this study provides a systematic description of the structure, stability and dynamics of the human memory B cell pool and suggests that memory B cells may be active at any time point in the generation of plasmablasts.

Learning the statistics and landscape of somatic mutation-induced insertions and deletions in antibodies

Affinity maturation is crucial for improving the binding affinity of antibodies to antigens. This process is mainly driven by point substitutions caused by somatic hypermutations of the immunoglobulin gene. It also includes deletions and insertions of genomic material known as indels. While the landscape of point substitutions has been extensively studied, a detailed statistical description of indels is still lacking. Here we present a probabilistic inference tool to learn the statistics of indels from repertoire sequencing data, which overcomes the pitfalls and biases of standard annotation methods. The model includes antibody-specific maturation ages to account for variable mutational loads in the repertoire. After validation on synthetic data, we applied our tool to a large dataset of human immunoglobulin heavy chains. The inferred model allows us to identify universal statistical features of indels in heavy chains. We report distinct insertion and deletion hotspots, and show that the distribution of lengths of indels follows a geometric distribution, which puts constraints on future mechanistic models of the hypermutation process.

Affinity maturation of B cell receptors is an important mechanism by which our body designs neutralizing antibodies to defend us against pathogens, including broadly neutralizing antibodies, which target a wide range of variants of the same pathogen. Such antibodies often contain key insertions and deletions to the germline gene, or “indels”, which are caused by somatic hypermutations. However, the mechanism, frequency and role of these indels are still elusive. We designed a computational method based on a probabilistic framework to infer the characteristics of this mutational process from high-throughput antibody sequencing experiments. Applied to human data, our approach provides a comprehensive quantitative description of insertions and deletions, opening avenues for better understanding the process of affinity maturation and the design of vaccines for eliciting a broad antibody response.