Preliminary findings from the Dynamics of the Immune Responses to Repeat Influenza Vaccination Exposures (DRIVE I) Study: a Randomized Controlled Trial.

BACKGROUND: Studies have reported that repeated annual vaccination may influence influenza vaccination effectiveness in the current season. METHODS: We established a 5-year randomized placebo-controlled trial of repeated influenza vaccination (Flublok, Sanofi Pasteur) in adults 18-45 years of age. In the first two years, participants received vaccination (V) or saline placebo (P) as follows: P-P, P-V, or V-V. Serum samples were collected each year just before vaccination and after 30 and 182 days. A subset of sera collected at 5 timepoints from 95 participants were tested for antibodies against vaccine strains. RESULTS: From 23 October 2020 through 11 March 2021 we enrolled and randomized 447 adults. Among vaccinated individuals, antibody titers increased between days 0 and 30 against each of the vaccine strains, with smaller increases for repeat vaccinees who on average had higher pre-vaccination titers in year 2. There were statistically significant differences in the proportion of participants achieving >=four-fold rises in antibody titer for the repeat vaccinees for influenza A(H1N1), B/Victoria and B/Yamagata, but not for A(H3N2). Among participants who received vaccination in year 2, there were no statistically significant differences between the P-V and V-V groups in geometric mean titers at day 30 or the proportions of participants with antibody titers ≥40 at day 30 for any of the vaccine strains. CONCLUSIONS: In the first two years, during which influenza did not circulate, repeat vaccinees and first-time vaccinees had similar post-vaccination geometric mean titers to all four vaccine strains, indicative of similar levels of clinical protection.

Antibody modulation of B cell responses-Incorporating positive and negative feedback.

Antibodies are powerful modulators of ongoing and future B cell responses. While the concept of antibody feedback has been appreciated for over a century, the topic has seen a surge in interest due to the evidence that the broadening of antibody responses to SARS-CoV-2 after a third mRNA vaccination is a consequence of antibody feedback. Moreover, the discovery that slow antigen delivery can lead to more robust humoral immunity has put a spotlight on the capacity for early antibodies to augment B cell responses. Here, we review the mechanisms whereby antibody feedback shapes B cell responses, integrating findings in humans and in mouse models. We consider the major influence of epitope masking and the diverse actions of complement and Fc receptors and provide a framework for conceptualizing the ways antigen-specific antibodies may influence B cell responses to any form of antigen, in conditions as diverse as infectious disease, autoimmunity, and cancer.

A hybrid demultiplexing strategy that improves performance and robustness of cell hashing.

Cell hashing, a nucleotide barcode-based method that allows users to pool multiple samples and demultiplex in downstream analysis, has gained widespread popularity in single-cell sequencing due to its compatibility, simplicity, and cost-effectiveness. Despite these advantages, the performance of this method remains unsatisfactory under certain circumstances, especially in experiments that have imbalanced sample sizes or use many hashtag antibodies. Here, we introduce a hybrid demultiplexing strategy that increases accuracy and cell recovery in multi-sample single-cell experiments. This approach correlates the results of cell hashing and genetic variant clustering, enabling precise and efficient cell identity determination without additional experimental costs or efforts. In addition, we developed HTOreader, a demultiplexing tool for cell hashing that improves the accuracy of cut-off calling by avoiding the dominance of negative signals in experiments with many hashtags or imbalanced sample sizes. When compared to existing methods using real-world datasets, this hybrid approach and HTOreader consistently generate reliable results with increased accuracy and cell recovery.

Lack of memory recall in human CD4 T cells elicited by the first encounter with SARS-CoV-2.

The studies reported here focus on the impact of pre-existing CD4 T cell immunity on the first encounter with SARS-CoV-2. They leverage PBMC samples from plasma donors collected after a first SARS-CoV-2 infection, prior to vaccine availability and compared to samples collected prior to the emergence of SARS-CoV-2. Analysis of CD4 T cell specificity across the entire SARS-CoV-2 proteome revealed that the recognition of SARS-CoV-2-derived epitopes by CD4 memory cells prior to the pandemic are enriched for reactivity toward non-structural proteins conserved across endemic CoV strains. However, CD4 T cells after primary infection with SARS-CoV-2 focus on epitopes from structural proteins. We observed little evidence for preferential recall to epitopes conserved between SARS-CoV-2 and seasonal CoV, a finding confirmed through use of selectively curated conserved and SARS-unique peptides. Our data suggest that SARS-CoV-2 CD4 T cells elicited by the first infection are primarily established from the naive CD4 T cell pool.

Preliminary findings from the Dynamics of the Immune Responses to Repeat Influenza Vaccination Exposures (DRIVE I) Study: a Randomized Controlled Trial.

Background: Studies have reported that repeated annual vaccination may influence the effectiveness of the influenza vaccination in the current season. The mechanisms underlying these differences are unclear but might include "focusing" of the adaptive immune response to older strains. Methods: We established a 5-year randomized placebo-controlled trial of repeated influenza vaccination (Flublok, Sanofi Pasteur) in adults 18-45 years of age. Participants were randomized equally between five groups, with planned annual receipt of vaccination (V) or saline placebo (P) as follows: P-P-P-P-V, P-P-P-V-V, P-P-V-V-V, P-V-V-V-V, or V-V-V-VV. Serum samples were collected each year just before vaccination and after 30 and 182 days. A subset of sera were tested by hemagglutination inhibition assays, focus reduction neutralization tests and enzyme-linked immunosorbent assays against vaccine strains. Results: From 23 October 2020 through 11 March 2021 we enrolled and randomized 447 adults. We selected sera from 95 participants at five timepoints from the first two study years for testing. Among vaccinated individuals, antibody titers increased between days 0 and 30 against each of the vaccine strains, with substantial increases for first-time vaccinees and smaller increases for repeat vaccinees, who had higher pre-vaccination titers in year 2. There were statistically significant reductions in the proportion of participants achieving a four-fold greater rise in antibody titer for the repeat vaccinees for A(H1N1), B/Victoria and B/Yamagata, but not for influenza A(H3N2). There were no statistically significant differences between groups in geometric mean titers at day 30 or the proportions of participants with antibody titers ≥40 at day 30 for any of the vaccine strains. Conclusions: In the first two years, repeat vaccinees and first-time vaccinees had similar post-vaccination geometric mean titers to all four vaccine strains, indicative of similar levels of clinical protection. The vaccine strains of A(H1N1) and A(H3N2) were updated in year 2, providing an opportunity to explore antigenic distances between those strains in humans in subsequent years.

Biochemical and biophysical characterization of natural polyreactivity in antibodies.

To become specialized binders, antibodies undergo a process called affinity maturation to maximize their binding affinity. Despite this process, some antibodies retain low-affinity binding to diverse epitopes in a phenomenon called polyreactivity. Here we seek to understand the molecular basis of this polyreactivity in antibodies. Our results highlight that polyreactive antigen-binding fragments (Fabs) bind their targets with low affinities, comparable to T cell receptor recognition of autologous classical major histocompatibility complex. Extensive mutagenic studies find no singular amino acid residue or biochemical property responsible for polyreactive interaction, suggesting that polyreactive antibodies use multiple strategies for engagement. Finally, our crystal structures and all-atom molecular dynamics simulations of polyreactive Fabs show increased rigidity compared to their monoreactive relatives, forming a neutral and accessible platform for diverse antigens to bind. Together, these data support a cooperative strategy of rigid neutrality in establishing the polyreactive status of an antibody molecule.

Effects of drinking water treatment residual amendments to biosolids on plant uptake of per- and polyfluoroalkyl substances.

Drinking water treatment residuals (DWTRs), solid by-products of drinking water treatment, are dominated by calcium (Ca), iron (Fe), or aluminum (Al), depending on the coagulant used. DWTRs are often landfilled, but current research is exploring options for beneficial reuse. Previous studies have shown that Al- and Fe-rich materials have potential to reduce the mobility of per- and polyfluoroalkyl substances (PFAS). Here, we investigated how amending biosolids with 5% wt/wt DWTRs affected plant bioavailable PFAS in two different simulated scenarios: (1) agricultural scenario with Solanum lycopersicum (tomato) grown in soil amended with an agronomically relevant rate of DWTR-amended biosolids (0.9% w/w, resulting in 0.045% w/w DWTR in the biosolids-amended soil) and (2) mine reclamation scenario examining PFAS uptake by Lolium perenne (perennial ryegrass) grown in soil that received DWTR-amended biosolids amendment at a rate consistent with the mine remediation (13% w/w, resulting in 0.65% w/w DWTR in the biosolids-amended soil). Amending biosolids with Ca-DWTR significantly reduced perfluorobutanoic acid (PFBA) uptake in ryegrass and perfluorohexanoic acid uptake in tomatoes, possibly due to DWTR-induced pH elevation, while Fe-DWTR amendment reduced PFBA bioaccumulation in ryegrass. The Al-DWTR did not induce a significant reduction in accumulated PFAS compared to controls. Although the reasons for this finding are unclear, the relatively low PFAS concentrations in the biosolids and relatively high Al content in the biosolids and soil may be partially responsible.

Germline-encoded specificities and the predictability of the B cell response.

Antibodies result from the competition of B cell lineages evolving under selection for improved antigen recognition, a process known as affinity maturation. High-affinity antibodies to pathogens such as HIV, influenza, and SARS-CoV-2 are frequently reported to arise from B cells whose receptors, the precursors to antibodies, are encoded by particular immunoglobulin alleles. This raises the possibility that the presence of particular germline alleles in the B cell repertoire is a major determinant of the quality of the antibody response. Alternatively, initial differences in germline alleles' propensities to form high-affinity receptors might be overcome by chance events during affinity maturation. We first investigate these scenarios in simulations: when germline-encoded fitness differences are large relative to the rate and effect size variation of somatic mutations, the same germline alleles persistently dominate the response of different individuals. In contrast, if germline-encoded advantages can be easily overcome by subsequent mutations, allele usage becomes increasingly divergent over time, a pattern we then observe in mice experimentally infected with influenza virus. We investigated whether affinity maturation might nonetheless strongly select for particular amino acid motifs across diverse genetic backgrounds, but we found no evidence of convergence to similar CDR3 sequences or amino acid substitutions. These results suggest that although germline-encoded specificities can lead to similar immune responses between individuals, diverse evolutionary routes to high affinity limit the genetic predictability of responses to infection and vaccination.

IgG3 subclass antibodies recognize antigenically drifted influenza viruses and SARS-CoV-2 variants through efficient bivalent binding.

The constant domains of antibodies are important for effector functions, but less is known about how they can affect binding and neutralization of viruses. Here, we evaluated a panel of human influenza virus monoclonal antibodies (mAbs) expressed as IgG1, IgG2, or IgG3. We found that many influenza virus-specific mAbs have altered binding and neutralization capacity depending on the IgG subclass encoded and that these differences result from unique bivalency capacities of the subclasses. Importantly, subclass differences in antibody binding and neutralization were greatest when the affinity for the target antigen was reduced through antigenic mismatch. We found that antibodies expressed as IgG3 bound and neutralized antigenically drifted influenza viruses more effectively. We obtained similar results using a panel of SARS-CoV-2-specific mAbs and the antigenically advanced B.1.351 and BA.1 strains of SARS-CoV-2. We found that a licensed therapeutic mAb retained neutralization breadth against SARS-CoV-2 variants when expressed as IgG3, but not IgG1. These data highlight that IgG subclasses are not only important for fine-tuning effector functionality but also for binding and neutralization of antigenically drifted viruses.

Antigen-driven colonic inflammation is associated with development of dysplasia in primary sclerosing cholangitis.

Primary sclerosing cholangitis (PSC) is an immune-mediated disease of the bile ducts that co-occurs with inflammatory bowel disease (IBD) in almost 90% of cases. Colorectal cancer is a major complication of patients with PSC and IBD, and these patients are at a much greater risk compared to patients with IBD without concomitant PSC. Combining flow cytometry, bulk and single-cell transcriptomics, and T and B cell receptor repertoire analysis of right colon tissue from 65 patients with PSC, 108 patients with IBD and 48 healthy individuals we identified a unique adaptive inflammatory transcriptional signature associated with greater risk and shorter time to dysplasia in patients with PSC. This inflammatory signature is characterized by antigen-driven interleukin-17A (IL-17A)+ forkhead box P3 (FOXP3)+ CD4 T cells that express a pathogenic IL-17 signature, as well as an expansion of IgG-secreting plasma cells. These results suggest that the mechanisms that drive the emergence of dysplasia in PSC and IBD are distinct and provide molecular insights that could guide prevention of colorectal cancer in individuals with PSC.

A hybrid demultiplexing strategy that improves performance and robustness of cell hashing.

Recent advances in single cell RNA sequencing allow users to pool multiple samples and demultiplex in downstream analysis, which greatly increase experimental efficiency and cost-effectiveness. Among all the demultiplexing methods, nucleotide barcode-based cell hashing has gained widespread popularity due to its compatibility and simplicity. Despite these advantages, certain issues of this technic remain to be solved, such as challenges in distinguishing true positive from background, high reagent cost for samples with large cell numbers, and unpredictable false negative and false doublet rates. Here, we propose a hybrid demultiplexing strategy that increases calling accuracy and cell recovery of cell hashing without adding experimental cost. In this approach, we computationally cluster all single cells based on their natural genetic variations and assign donor identity by finding the dominant hashtag in each genotype cluster. This hybrid strategy assigns donor identity to any cell that is identified as singlet by either genotype clustering or cell hashing, which allows us to demultiplex most majority of cells even if only a small fraction of cells are labeled with hashtags. When comparing its performance with cell hashing on multiple real-world datasets, this hybrid approach consistently generates reliable demultiplexing results with increased cell recovery and accuracy.

Site of vulnerability on SARS-CoV-2 spike induces broadly protective antibody against antigenically distinct Omicron subvariants.

The rapid evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variants has emphasized the need to identify antibodies with broad neutralizing capabilities to inform future monoclonal therapies and vaccination strategies. Herein, we identified S728-1157, a broadly neutralizing antibody (bnAb) targeting the receptor-binding site (RBS) that was derived from an individual previously infected with WT SARS-CoV-2 prior to the spread of variants of concern (VOCs). S728-1157 demonstrated broad cross-neutralization of all dominant variants, including D614G, Beta, Delta, Kappa, Mu, and Omicron (BA.1/BA.2/BA.2.75/BA.4/BA.5/BL.1/XBB). Furthermore, S728-1157 protected hamsters against in vivo challenges with WT, Delta, and BA.1 viruses. Structural analysis showed that this antibody targets a class 1/RBS-A epitope in the receptor binding domain via multiple hydrophobic and polar interactions with its heavy chain complementarity determining region 3 (CDR-H3), in addition to common motifs in CDR-H1/CDR-H2 of class 1/RBS-A antibodies. Importantly, this epitope was more readily accessible in the open and prefusion state, or in the hexaproline (6P)-stabilized spike constructs, as compared with diproline (2P) constructs. Overall, S728-1157 demonstrates broad therapeutic potential and may inform target-driven vaccine designs against future SARS-CoV-2 variants.

IgG3 subclass antibodies recognize antigenically drifted influenza viruses and SARS-CoV-2 variants through efficient bivalent binding.

The constant domains of antibodies are important for effector functions, but less is known about how they can affect binding and neutralization of viruses. Here we evaluated a panel of human influenza virus monoclonal antibodies (mAbs) expressed as IgG1, IgG2 or IgG3. We found that many influenza virus-specific mAbs have altered binding and neutralization capacity depending on the IgG subclass encoded, and that these differences result from unique bivalency capacities of the subclasses. Importantly, subclass differences in antibody binding and neutralization were greatest when the affinity for the target antigen was reduced through antigenic mismatch. We found that antibodies expressed as IgG3 bound and neutralized antigenically drifted influenza viruses more effectively. We obtained similar results using a panel of SARS-CoV-2-specific mAbs and the antigenically advanced B.1.351 strain of SARS-CoV-2. We found that a licensed therapeutic mAb retained neutralization breadth against SARS-CoV-2 variants when expressed as IgG3, but not IgG1. These data highlight that IgG subclasses are not only important for fine-tuning effector functionality, but also for binding and neutralization of antigenically drifted viruses. Significance: Influenza viruses and coronaviruses undergo continuous change, successfully evading human antibodies elicited from prior infections or vaccinations. It is important to identify features that allow antibodies to bind with increased breadth. Here we examined the effect that different IgG subclasses have on monoclonal antibody binding and neutralization. We show that IgG subclass is a determinant of antibody breadth, with IgG3 affording increased neutralization of antigenically drifted variants of influenza virus and SARS-CoV-2. Future studies should evaluate IgG3 therapeutic antibodies and vaccination strategies or adjuvants that may skew antibody responses toward broadly reactive isotypes.

Severe COVID-19 induces autoantibodies against angiotensin II that correlate with blood pressure dysregulation and disease severity.

Patients infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can experience life-threatening respiratory distress, blood pressure dysregulation, and thrombosis. This is thought to be associated with an impaired activity of angiotensin-converting enzyme 2 (ACE2), which is the main entry receptor of SARS-CoV-2 and which also tightly regulates blood pressure by converting the vasoconstrictive peptide angiotensin II (AngII) to a vasopressor peptide. Here, we show that a significant proportion of hospitalized patients with COVID-19 developed autoantibodies against AngII, whose presence correlates with lower blood oxygenation, blood pressure dysregulation, and overall higher disease severity. Anti-AngII antibodies can develop upon specific immune reaction to the SARS-CoV-2 proteins Spike or receptor-binding domain (RBD), to which they can cross-bind, suggesting some epitope mimicry between AngII and Spike/RBD. These results provide important insights on how an immune reaction against SARS-CoV-2 can impair blood pressure regulation.

Selecting Representative Samples From Complex Biological Datasets Using K-Medoids Clustering.

Rapid growth of single-cell sequencing techniques enables researchers to investigate almost millions of cells with diverse properties in a single experiment. Meanwhile, it also presents great challenges for selecting representative samples from massive single-cell populations for further experimental characterization, which requires a robust and compact sampling with balancing diverse properties of different priority levels. The conventional sampling methods fail to generate representative and generalizable subsets from a massive single-cell population or more complicated ensembles. Here, we present a toolkit called Cookie which can efficiently select out the most representative samples from a massive single-cell population with diverse properties. This method quantifies the relationships/similarities among samples using their Manhattan distances by vectorizing all given properties and then determines an appropriate sample size by evaluating the coverage of key properties from multiple candidate sizes, following by a k-medoids clustering to group samples into several clusters and selects centers from each cluster as the most representatives. Comparison of Cookie with conventional sampling methods using a single-cell atlas dataset, epidemiology surveillance data, and a simulated dataset shows the high efficacy, efficiency, and flexibly of Cookie. The Cookie toolkit is implemented in R and is freely available at https://wilsonimmunologylab.github.io/Cookie/.

Memory B cell diversity: insights for optimized vaccine design.

The overarching logos of mammalian memory B cells (MBCs) is to cache the potential for enhanced antibody production upon secondary exposure to cognate antigenic determinants. However, substantial phenotypic diversity has been identified across MBCs, hinting at the existence of unique origins or subfunctions within this compartment. Herein, we discuss recent advancements in human circulatory MBC subphenotyping as driven by high-throughput cell surface marker analysis and other approaches, as well as speculated and substantiated subfunctions. With this in mind, we hypothesize that the relative induction of specific circulatory MBC subsets might be used as a biomarker for optimally durable vaccines and inform vaccination strategies to subvert antigenic imprinting in the context of highly mutable pathogens such as influenza virus or SARS-CoV-2.

Teach 'em young: Influenza vaccines induce broadly neutralizing antibodies in children.

Antibodies against the influenza virus hemagglutinin stalk afford broad protection against antigenically drifted viruses. In this issue of Cell Reports Medicine, Yegorov et al.1 identify that current vaccine formulations induce neutralizing stalk antibodies in children-a highly vulnerable population.

Librator: a platform for the optimized analysis, design, and expression of mutable influenza viral antigens.

Artificial mutagenesis and protein engineering have laid the foundation for antigenic characterization and universal vaccine design for influenza viruses. However, many methods used in this process require manual sequence editing and protein expression, limiting their efficiency and utility in high-throughput applications. More streamlined in silico tools allowing researchers to properly analyze and visualize influenza viral protein sequences with accurate nomenclature are necessary to improve antigen design and productivity. To address this need, we developed Librator, a system for analyzing and designing custom protein sequences of influenza virus hemagglutinin (HA) and neuraminidase (NA) glycoproteins. Within Librator's graphical interface, users can easily interrogate viral sequences and phylogenies, visualize antigen structures and conservation, mutate target residues and design custom antigens. Librator also provides optimized fragment design for Gibson Assembly of HA and NA expression constructs based on peptide conservation of all historical HA and NA sequences, ensuring fragments are reusable and compatible across related subtypes, thereby promoting reagent savings. Finally, the program facilitates single-cell immune profiling, epitope mapping of monoclonal antibodies and mosaic protein design. Using Librator-based antigen construction, we demonstrate that antigenicity can be readily transferred between HA molecules of H3, but not H1, lineage viruses. Altogether, Librator is a valuable tool for analyzing influenza virus HA and NA proteins and provides an efficient resource for optimizing recombinant influenza antigen synthesis.