The mechanisms by which antibodies confer protection vary across vaccines, ranging from simple neutralization to functions requiring innate immune recruitment via Fc-dependent mechanisms. The role of ...adjuvants in shaping the maturation of antibody-effector functions remains under investigated. Using systems serology, we compared adjuvants in licensed vaccines (AS01
/AS01
/AS03/AS04/Alum) combined with a model antigen. Antigen-naive adults received two adjuvanted immunizations followed by late revaccination with fractional-dosed non-adjuvanted antigen ( NCT00805389 ). A dichotomy in response quantities/qualities emerged post-dose 2 between AS01
/AS01
/AS03 and AS04/Alum, based on four features related to immunoglobulin titers or Fc-effector functions. AS01
and AS03 induced similar robust responses that were boosted upon revaccination, suggesting that memory B-cell programming by the adjuvanted vaccinations dictated responses post non-adjuvanted boost. AS04 and Alum induced weaker responses, that were dissimilar with enhanced functionalities for AS04. Distinct adjuvant classes can be leveraged to tune antibody-effector functions, where selective vaccine formulation using adjuvants with different immunological properties may direct antigen-specific antibody functions.
Comorbid medical illnesses, such as obesity and diabetes, are associated with more severe COVID-19, hospitalization, and death. However, the role of the immune system in mediating these clinical ...outcomes has not been determined. We used multiparameter flow cytometry and systems serology to comprehensively profile the functions of T cells and antibodies targeting spike, nucleocapsid, and envelope proteins in a convalescent cohort of COVID-19 subjects who were either hospitalized (n = 20) or not hospitalized (n = 40). To avoid confounding, subjects were matched by age, sex, ethnicity, and date of symptom onset. Surprisingly, we found that the magnitude and functional breadth of virus-specific CD4+ T cell and antibody responses were consistently higher among hospitalized subjects, particularly those with medical comorbidities. However, an integrated analysis identified more coordination between polyfunctional CD4+ T cells and antibodies targeting the S1 domain of spike among subjects who were not hospitalized. These data reveal a functionally diverse and coordinated response between T cells and antibodies targeting SARS-CoV-2, which is reduced in the presence of comorbid illnesses that are known risk factors for severe COVID-19.
•Generalizes hierarchical population model to various distribution assumptions.•Provides framework for efficient calibration of the hierarchical population model.•Simulation study and application to ...experimental data reveal improved robustness and optimization performance.
Cellular heterogeneity is known to have important effects on signal processing and cellular decision making. To understand these processes, multiple classes of mathematical models have been introduced. The hierarchical population model builds a novel class which allows for the mechanistic description of heterogeneity and explicitly takes into account subpopulation structures. However, this model requires a parametric distribution assumption for the cell population and, so far, only the normal distribution has been employed. Here, we incorporate alternative distribution assumptions into the model, assess their robustness against outliers and evaluate their influence on the performance of model calibration in a simulation study and a real-world application example. We found that alternative distributions provide reliable parameter estimates even in the presence of outliers, and can in fact increase the convergence of model calibration.
Modifications to vaccine delivery that increase serum antibody longevity are of great interest for maximizing efficacy. We have previously shown that a delayed fractional (DFx) dosing schedule (0-1-6 ...month) - using AS01B-adjuvanted RH5.1 malaria antigen - substantially improves serum IgG durability as compared with monthly dosing (0-1-2 month; NCT02927145). However, the underlying mechanism and whether there are wider immunological changes with DFx dosing were unclear. Here, PfRH5-specific Ig and B cell responses were analyzed in depth through standardized ELISAs, flow cytometry, systems serology, and single-cell RNA-Seq (scRNA-Seq). Data indicate that DFx dosing increases the magnitude and durability of circulating PfRH5-specific B cells and serum IgG1. At the peak antibody magnitude, DFx dosing was distinguished by a systems serology feature set comprising increased FcRn binding, IgG avidity, and proportion of G2B and G2S2F IgG Fc glycans, alongside decreased IgG3, antibody-dependent complement deposition, and proportion of G1S1F IgG Fc glycan. Concomitantly, scRNA-Seq data show a higher CDR3 percentage of mutation from germline and decreased plasma cell gene expression in circulating PfRH5-specific B cells. Our data, therefore, reveal a profound impact of DFx dosing on the humoral response and suggest plausible mechanisms that could enhance antibody longevity, including improved FcRn binding by serum Ig and a potential shift in the underlying cellular response from circulating short-lived plasma cells to nonperipheral long-lived plasma cells.
Abstract
Motivation
Mathematical models are nowadays important tools for analyzing dynamics of cellular processes. The unknown model parameters are usually estimated from experimental data. These ...data often only provide information about the relative changes between conditions, hence, the observables contain scaling parameters. The unknown scaling parameters and corresponding noise parameters have to be inferred along with the dynamic parameters. The nuisance parameters often increase the dimensionality of the estimation problem substantially and cause convergence problems.
Results
In this manuscript, we propose a hierarchical optimization approach for estimating the parameters for ordinary differential equation (ODE) models from relative data. Our approach restructures the optimization problem into an inner and outer subproblem. These subproblems possess lower dimensions than the original optimization problem, and the inner problem can be solved analytically. We evaluated accuracy, robustness and computational efficiency of the hierarchical approach by studying three signaling pathways. The proposed approach achieved better convergence than the standard approach and required a lower computation time. As the hierarchical optimization approach is widely applicable, it provides a powerful alternative to established approaches.
Availability and implementation
The code is included in the MATLAB toolbox PESTO which is available at http://github.com/ICB-DCM/PESTO
Supplementary information
Supplementary data are available at Bioinformatics online.
Dynamics of cellular processes are often studied using mechanistic mathematical models. These models possess unknown parameters which are generally estimated from experimental data assuming normally ...distributed measurement noise. Outlier corruption of datasets often cannot be avoided. These outliers may distort the parameter estimates, resulting in incorrect model predictions. Robust parameter estimation methods are required which provide reliable parameter estimates in the presence of outliers.
In this manuscript, we propose and evaluate methods for estimating the parameters of ordinary differential equation models from outlier-corrupted data. As alternatives to the normal distribution as noise distribution, we consider the Laplace, the Huber, the Cauchy and the Student's t distribution. We assess accuracy, robustness and computational efficiency of estimators using these different distribution assumptions. To this end, we consider artificial data of a conversion process, as well as published experimental data for Epo-induced JAK/STAT signaling. We study how well the methods can compensate and discover artificially introduced outliers. Our evaluation reveals that using alternative distributions improves the robustness of parameter estimates.
The MATLAB implementation of the likelihood functions using the distribution assumptions is available at Bioinformatics online.
jan.hasenauer@helmholtz-muenchen.de.
Supplementary material are available at Bioinformatics online.
Ordinary differential equation models have become a standard tool for the mechanistic description of biochemical processes. If parameters are inferred from experimental data, such mechanistic models ...can provide accurate predictions about the behavior of latent variables or the process under new experimental conditions. Complementarily, inference of model structure can be used to identify the most plausible model structure from a set of candidates, and, thus, gain novel biological insight. Several toolboxes can infer model parameters and structure for small- to medium-scale mechanistic models out of the box. However, models for highly multiplexed datasets can require hundreds to thousands of state variables and parameters. For the analysis of such large-scale models, most algorithms require intractably high computation times. This chapter provides an overview of the state-of-the-art methods for parameter and model inference, with an emphasis on scalability.
Cellular signaling is essential in information processing and decision-making. Therefore, a variety of experimental approaches have been developed to study signaling on bulk and single-cell level. ...Single-cell measurements of signaling molecules demonstrated a substantial cell-to-cell variability, raising questions about its causes and mechanisms and about how cell populations cope with or exploit cellular heterogeneity. To gain insights from single-cell signaling data, analysis and modeling approaches have been introduced. This review discusses these modeling approaches, with a focus on recent advances in the development and calibration of mechanistic models. Additionally, it outlines current and future challenges.
•Humoral immunity is mediated by complex networks of polyclonal antibodies interacting with antigens and effector immune cells.•This network integrates properties of the Fab and Fc domains of ...antibodies, governed by regulatory processes within B-cells.•Current OMIC tools capture individual aspects of antibody Fab, Fc, and transcriptional B-cell properties separately.•Computational frameworks are required to integrate, as comprehensively as possible, the complexity of humoral immunity.
Humoral immunity is key to protection for nearly all licensed vaccines. Yet, the design of vaccines has been more difficult for some of our most deadly killers (e.g. HIV, influenza, Dengue virus, etc.), likely due to our incomplete understanding of the precise immunological mechanisms associated with protection. Humoral immunity is governed both by B-cells and their bi-functional secreted antibodies, all of which have a unique capacity to evolve during an immune response. Current OMIC technologies capture individual features of the humoral immune response, providing a glimpse into humoral components (Fab/Fc/B-cell-omic), but fail to provide a wholistic view of the humoral response as a collective functional arm. Here, we dissect current OMIC strategies reviewing experimental and computational approaches, that if integrated could provide a true systems-level view of the humoral immune response.
The urgent need for an effective SARS-CoV-2 vaccine has forced development to progress in the absence of well-defined correlates of immunity. While neutralization has been linked to protection ...against other pathogens, whether neutralization alone will be sufficient to drive protection against SARS-CoV-2 in the broader population remains unclear. Therefore, to fully define protective humoral immunity, we dissected the early evolution of the humoral response in 193 hospitalized individuals ranging from moderate to severe. Although robust IgM and IgA responses evolved in both survivors and non-survivors with severe disease, non-survivors showed attenuated IgG responses, accompanied by compromised Fcɣ receptor binding and Fc effector activity, pointing to deficient humoral development rather than disease-enhancing humoral immunity. In contrast, individuals with moderate disease exhibited delayed responses that ultimately matured. These data highlight distinct humoral trajectories associated with resolution of SARS-CoV-2 infection and the need for early functional humoral immunity.
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•IgA and IgM evolve rapidly across all levels of disease severity•Rapid and potent IgG class switching is linked to survival•Moderate disease is associated with a delay but ultimate convergence of IgG•Early S2-cross-reactivity is linked to survival after severe disease
Analyses of the functional humoral trajectories associated with the resolution of SARS-CoV-2 infection find that despite equivalent IgM and IgA immunity to the virus across all levels of disease severity, survival and recovery are linked to early class switching to IgG and the ability to leverage Fcγ receptors targeting the spike protein.
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