Seasonal and pandemic influenza A virus (IAV) continues to be a public health threat. However, we lack a detailed and quantitative understanding of the immune response kinetics to IAV infection and which biological parameters most strongly influence infection outcomes. To address these issues, we use modeling approaches combined with experimental data to quantitatively investigate the innate and adaptive immune responses to primary IAV infection. Mathematical models were developed to describe the dynamic interactions between target (epithelial) cells, influenza virus, cytotoxic T lymphocytes (CTLs), and virus-specific IgG and IgM. IAV and immune kinetic parameters were estimated by fitting models to a large data set obtained from primary H3N2 IAV infection of 340 mice. Prior to a detectable virus-specific immune response (before day 5), the estimated half-life of infected epithelial cells is ∼1.2 days, and the half-life of free infectious IAV is ∼4 h. During the adaptive immune response (after day 5), the average half-life of infected epithelial cells is ∼0.5 days, and the average half-life of free infectious virus is ∼1.8 min. During the adaptive phase, model fitting confirms that CD8 + CTLs are crucial for limiting infected cells, while virus-specific IgM regulates free IAV levels. This may imply that CD4 T cells and class-switched IgG antibodies are more relevant for generating IAV-specific memory and preventing future infection via a more rapid secondary immune response. Also, simulation studies were performed to understand the relative contributions of biological parameters to IAV clearance. This study provides a basis to better understand and predict influenza virus immunity.

https://jvi.asm.org/content/jvi/84/13/6687.full.pdf

Quantifying the Early Immune Response and Adaptive Immune Response Kinetics in Mice Infected with Influenza A Virus

Ex vivo characterization and isolation of rare memory B cells with antigen tetramers

Arrays of subnanoliter wells (nanowells) provide a useful system to isolate single cells and analyze their secreted proteins. Two general approaches have emerged: one that uses open arrays and local capture of secreted proteins, and a second (called microengraving) that relies on closed arrays to capture secreted proteins on a solid substrate, which is subsequently removed from the array. However, the design and operating parameters for efficient capture from these two approaches to analyze single-cell secretion have not been extensively considered. Using numerical simulations, we analyzed the operational envelope for both open and closed formats, as a function of the spatial distribution of capture ligands, their affinities for the protein, and the rates of single-cell secretion. Based on these analyses, we present a modified approach to capture secreted proteins in-well for highly active secreting cells. This simple method for in-well detection should facilitate rapid identification of cell lines with high specific productivities.

Nanowell-based immunoassays for measuring single-cell secretion: characterization of transport and surface binding.

To identify sources of inter-subject variation in vaccine responses, we performed high-frequency sampling of human peripheral blood cells post-vaccination, followed by a novel systems biology analysis. Functional principal component analysis was used to examine time varying B cell vaccine responses. In subjects vaccinated within the previous three years, 90% of transcriptome variation was explained by a single subject-specific mathematical pattern. Within individual vaccine response patterns, a common subset of 742 genes was strongly correlated with migrating plasma cells. Of these, 366 genes were associated with human plasmablasts differentiating in vitro. Additionally, subject-specific temporal transcriptome patterns in peripheral blood mononuclear cells identified migration of myeloid/dendritic cell lineage cells one day after vaccination. Upstream analyses of transcriptome changes suggested both shared and subject-specific transcription groups underlying larger patterns. With robust statistical methods, time-varying response characteristics of individual subjects were effectively captured along with a shared plasma cell gene signature.

/pdf/high-resolution-temporal-response-patterns-to-influenza-3eagii7gy7.pdf

High-Resolution Temporal Response Patterns to Influenza Vaccine Reveal a Distinct Human Plasma Cell Gene Signature

Objectives To predict the spread of coronavirus disease (COVID-19), information regarding the immunological memory for disease-specific antigens is necessary The possibility of reinfection, as well as the efficacy of vaccines for COVID-19 that are currently under development, will largely depend on the quality and longevity of immunological memory in patients To elucidate the process of humoral immunity development, we analysed the generation of plasmablasts and virus receptor-binding domain (RBD)-specific memory B (Bmem) cells in patients during the acute phase of COVID-19 Methods The frequencies of RBD-binding plasmablasts and RBD-specific antibody-secreting cells (ASCs) in the peripheral blood samples collected from patients with COVID-19 were measured using flow cytometry and the ELISpot assay Results The acute phase of COVID-19 was characterised by the transient appearance of total as well as RBD-binding plasmablasts ELISpot analysis indicated that most patients exhibited a spontaneous secretion of RBD-specific ASCs in the circulation with good correlation between the IgG and IgM subsets IL-21/CD40L stimulation of purified B cells induced the activation and proliferation of Bmem cells, which led to the generation of plasmablast phenotypic cells as well as RBD-specific ASCs No correlation was observed between the frequency of Bmem cell-derived and spontaneous ASCs, suggesting that the two types of ASCs were weakly associated with each other Conclusion Our findings reveal that SARS-CoV-2-specific Bmem cells are generated during the acute phase of COVID-19 These findings can serve as a basis for further studies on the longevity of SARS-CoV-2-specific B-cell memory

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cti2.1245

Pattern of circulating SARS‐CoV‐2‐specific antibody‐secreting and memory B‐cell generation in patients with acute COVID‐19

V-set and immunoglobulin domain-containing 4 (VSIG4) is a complement receptor of the immunoglobulin superfamily that is specifically expressed on tissue resident macrophages, and its many reported functions and binding partners suggest a complex role in immune function. VSIG4 is reported to have a role in immune surveillance as well as in modulating diverse disease phenotypes such as infections, autoimmune conditions, and cancer. However, the mechanism(s) governing VSIG4's complex, context-dependent role in immune regulation remain elusive. Here, we identify cell surface and soluble glycosaminoglycans (GAGs), specifically heparan sulfates, as novel binding partners of VSIG4. We demonstrate that genetic deletion of heparan sulfate synthesis enzymes or cleavage of cell-surface heparan sulfates reduced VSIG4 binding to the cell surface. Furthermore, binding studies demonstrate that VSIG4 interacts directly with heparan sulfates, with a preference for highly sulfated moieties and longer GAG chains. To assess the impact on VSIG4 biology, we show that heparan sulfates compete with known VSIG4 binding partners C3b and iC3b. Further, mutagenesis studies indicate this competition occurs through overlapping binding epitopes for heparan sulfates and complement on VSIG4. Together these data suggest a novel role for heparan sulfates in VSIG4-dependent immune modulation.

/pdf/vsig4-interaction-with-heparan-sulfates-inhibits-vsig4-ecw4a4ii.pdf

VSIG4 interaction with heparan sulfates inhibits VSIG4-complement binding.

During the recall response by CD27(+) IgG class-switched human memory B cells, total IgG secreted is a function of the following: 1) the number of IgG-secreting cells (IgG-SC), and 2) the secretion rate of each cell In this study, we report the quantitative ELISPOT method for simultaneous estimation of single-cell IgG secretion rates and secreting cell frequencies in human B cell populations We found that CD27(+) IgM(-) memory B cells activated with CpG and cytokines had considerable heterogeneity in the IgG secretion rates, with two major secretion rate subpopulations BCR cross-linking reduced the frequency of cells with high per-cell IgG secretion rates, with a parallel decrease in CD27(high) B cell blasts Increased cell death may account for the BCR-stimulated reduction in high-rate IgG-SC CD27(high) B cell blasts In contrast, the addition of IL-21 to CD40L plus IL-4-activated human memory B cells induced a high-rate IgG-SC population in B cells with otherwise low per-cell IgG secretion rates The profiles of human B cell IgG secretion rates followed the same biphasic distribution and range irrespective of division class This, along with the presence of non-IgG-producing, dividing B cells in CpG plus cytokine-activated B memory B cell populations, is suggestive of an on/off switch regulating IgG secretion Finally, these data support a mixture model of IgG secretion in which IgG secreted over time is modulated by the frequency of IgG-SC and the distribution of their IgG secretion rates

Modulation of single-cell IgG secretion frequency and rates in human memory B cells by CpG DNA, CD40L, IL-21, and cell division.

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VSIG4 interaction with heparan sulfates inhibits VSIG4-complement binding.

Modulation of single-cell IgG secretion frequency and rates in human memory B cells by CpG DNA, CD40L, IL-21, and cell division.