Multiscale Modeling of Germinal Center Recapitulates the Temporal Transition From Memory B Cells to Plasma Cells Differentiation as Regulated by Antigen Affinity-Based Tfh Cell Help

ENCORE: a practical implementation to improve reproducibility and transparency of computational research

Reproducibility of computational research is often challenging despite established guidelines and best practices. Translating these guidelines into practical applications remains difficult. Here, we present ENCORE, an approach to enhance transparency and reproducibility by guiding researchers in how to structure and document a computational project. ENCORE builds on previous efforts in computational reproducibility and integrates all project components into a standardized file system structure. It utilizes pre-defined files as documentation templates, leverages GitHub for software versioning, and includes an HTML-based navigator. ENCORE is designed to be agnostic to the type of computational project, data, programming language, and ICT infrastructure, and does not rely on specific software tools. We also share our group's experience using ENCORE, highlighting that the most significant challenge to the routine adoption of approaches like ours is the lack of incentives to motivate researchers to dedicate sufficient time and effort to ensure reproducibility.

A multiscale spatial modeling framework for the germinal center response

The germinal center response or reaction (GCR) is a hallmark event of adaptive humoral immunity. Unfolding in the B cell follicles of the secondary lymphoid organs, a GC culminates in the production of high-affinity antibody-secreting plasma cells along with memory B cells. By interacting with follicular dendritic cells (FDC) and T follicular helper (Tfh) cells, GC B cells exhibit complex spatiotemporal dynamics. Driving the B cell dynamics are the intracellular signal transduction and gene regulatory network that responds to cell surface signaling molecules, cytokines, and chemokines. As our knowledge of the GC continues to expand in depth and in scope, mathematical modeling has become an important tool to help disentangle the intricacy of the GCR and inform novel mechanistic and clinical insights. While the GC has been modeled at different granularities, a multiscale spatial simulation framework - integrating molecular, cellular, and tissue-level responses - is still rare. Here, we report our recent progress toward this end with a hybrid stochastic GC framework developed on the Cellular Potts Model-based CompuCell3D platform. Tellurium is used to simulate the B cell intracellular molecular network comprising NF-κB, FOXO1, MYC, AP4, CXCR4, and BLIMP1 that responds to B cell receptor (BCR) and CD40-mediated signaling. The molecular outputs of the network drive the spatiotemporal behaviors of B cells, including cyclic migration between the dark zone (DZ) and light zone (LZ) via chemotaxis; clonal proliferative bursts, somatic hypermutation, and DNA damage-induced apoptosis in the DZ; and positive selection, apoptosis via a death timer, and emergence of plasma cells in the LZ. Our simulations are able to recapitulate key molecular, cellular, and morphological GC events, including B cell population growth, affinity maturation, and clonal dominance. This novel modeling framework provides an open-source, customizable, and multiscale virtual GC simulation platform that enables qualitative and quantitative in silico investigations of a range of mechanistic and applied research questions on the adaptive humoral immune response in the future.

Stochastic modeling of a gene regulatory network driving B cell development in germinal centers

Germinal centers (GCs) are the key histological structures of the adaptive immune system, responsible for the development and selection of B cells producing high-affinity antibodies against antigens. Due to their level of complexity, unexpected malfunctioning may lead to a range of pathologies, including various malignant formations. One promising way to improve the understanding of malignant transformation is to study the underlying gene regulatory networks (GRNs) associated with cell development and differentiation. Evaluation and inference of the GRN structure from gene expression data is a challenging task in systems biology: recent achievements in single-cell (SC) transcriptomics allow the generation of SC gene expression data, which can be used to sharpen the knowledge on GRN structure. In order to understand whether a particular network of three key gene regulators (BCL6, IRF4, BLIMP1), influenced by two external stimuli signals (surface receptors BCR and CD40), is able to describe GC B cell differentiation, we used a stochastic model to fit SC transcriptomic data from a human lymphoid organ dataset. The model is defined mathematically as a piecewise-deterministic Markov process. We showed that after parameter tuning, the model qualitatively recapitulates mRNA distributions corresponding to GC and plasmablast stages of B cell differentiation. Thus, the model can assist in validating the GRN structure and, in the future, could lead to better understanding of the different types of dysfunction of the regulatory mechanisms.

A Multiscale Spatial Modeling Framework for the Germinal Center Response

The germinal center response or reaction (GCR) is a hallmark event of adaptive humoral immunity. Unfolding in the B cell follicles of the secondary lymph organs, a GC culminates in the production of high-affinity antibody-secreting plasma cells along with memory B cells. By interacting with follicular dendritic cells (FDC) and T follicular helper (Tfh) cells, GC B cells exhibit complex spatiotemporal dynamics. Driving the B cell dynamics are the intracellular signal transduction and gene regulatory network that responds to cell surface signaling molecules, cytokines, and chemokines. As our knowledge of the GC continues to expand in depth and in scope, mathematical modeling has become an important tool to help disentangle the intricacy of the GCR and inform novel mechanistic and clinical insights. While the GC has been modeled at different granularities, a multiscale spatial simulation framework - integrating molecular, cellular, and tissue-level responses - is still rare. Here, we report our recent progress toward this end with a hybrid stochastic GC framework developed on the Cellular Potts Model-based CompuCell3D platform. Tellurium is used to simulate the B cell intracellular molecular network comprising NF-κB, FOXO1, MYC, AP4, CXCR4, and BLIMP1 that responds to B cell receptor (BCR) and CD40-mediated signaling. The molecular outputs of the network drive the spatiotemporal behaviors of B cells, including cyclic migration between the dark zone (DZ) and light zone (LZ) via chemotaxis; clonal proliferative bursts, somatic hypermutation, and DNA damage-induced apoptosis in the DZ; and positive selection, apoptosis via a death timer, and emergence of plasma cells in the LZ. Our simulations are able to recapitulate key molecular, cellular, and morphological GC events including B cell population growth, affinity maturation, and clonal dominance. This novel modeling framework provides an open-source, customizable, and multiscale virtual GC simulation platform that enables qualitative and quantitative in silico investigations of a range of mechanic and applied research questions in future.

Understanding repertoire sequencing data through a multiscale computational model of the germinal center

Sequencing of B-cell and T-cell immune receptor repertoires helps us to understand the adaptive immune response, although it only provides information about the clonotypes (lineages) and their frequencies and not about, for example, their affinity or antigen (Ag) specificity. To further characterize the identified clones, usually with special attention to the particularly abundant ones (dominant), additional time-consuming or expensive experiments are generally required. Here, we present an extension of a multiscale model of the germinal center (GC) that we previously developed to gain more insight in B-cell repertoires. We compare the extent that these simulated repertoires deviate from experimental repertoires established from single GCs, blood, or tissue. Our simulations show that there is a limited correlation between clonal abundance and affinity and that there is large affinity variability among same-ancestor (same-clone) subclones. Our simulations suggest that low-abundance clones and subclones, might also be of interest since they may have high affinity for the Ag. We show that the fraction of plasma cells (PCs) with high B-cell receptor (BcR) mRNA content in the GC does not significantly affect the number of dominant clones derived from single GCs by sequencing BcR mRNAs. Results from these simulations guide data interpretation and the design of follow-up experiments.

High-Dimensional Cytometry Dissects Immunological Fingerprints of Idiopathic Inflammatory Myopathies

Chronic inflammation of skeletal muscle is the common feature of idiopathic inflammatory myopathies (IIM). Given the rarity of the disease and potential difficulty of routinely obtaining target tissue, i.e., standardized skeletal muscle, our understanding of immune signatures of the IIM spectrum remains incomplete. Further insight into the immune topography of IIM is needed to determine specific treatment targets according to clinical and immunological phenotypes. Thus, we used high-dimensional flow cytometry to investigate the immune phenotypes of anti-synthetase syndrome (ASyS), dermatomyositis (DM) and inclusion-body myositis (IBM) patients as representative entities of the IIM spectrum and compared them to healthy controls. We studied the CD8, CD4 and B cell compartments in the blood aiming to provide a contemporary overview of the immune topography of the IIM spectrum. ASyS was characterized by altered CD4 composition and expanded T follicular helper cells supporting B cell-mediated autoimmunity. For DM, unsupervised clustering identified expansion of distinct B cell subtypes highly expressing immunoglobulin G4 (IgG4) and CD38. Lastly, terminally differentiated, cytotoxic CD8 T cells distinguish IBM from other IIM. Interestingly, these terminally differentiated CD8 T cells highly expressed the integrin CD18 mediating cellular adhesion and infiltration. The distinct immune cell topography of IIM might provide the framework for targeted treatment approaches potentially improving therapeutic outcomes.

Termination of CD40L co-stimulation promotes human B cell differentiation into antibody-secreting cells

Human naïve B cells are notoriously difficult to differentiate into antibody-secreting cells (ASCs) in vitro while maintaining sufficient cell numbers to evaluate the differentiation process. B cells require T follicular helper (T_FH ) cell-derived signals like CD40L and IL-21 during germinal center (GC) responses to undergo differentiation into ASCs. Cognate interactions between B and T_FH cells are transient; after T_FH contact, B cells cycle between GC light and dark zones where T_FH contact is present and absent, respectively. Here, we elucidated that the efficacy of naïve B cells in ACS differentiation is dramatically enhanced by the release of CD40L stimulation. Multiparameter phospho-flow and transcription factor (TF)-flow cytometry revealed that termination of CD40L stimulation downmodulates NF-κB and STAT3 signaling. Furthermore, the termination of CD40 signaling downmodulates C-MYC, while promoting ASC TFs BLIMP1 and XBP-1s. Reduced levels of C-MYC in the differentiating B cells are later associated with crucial downmodulation of the B cell signature TF PAX5 specifically upon the termination of CD40 signaling, resulting in the differentiation of BLIMP1 high expressing cells into ASCs. The data presented here are the first steps to provide further insights how the transient nature of CD40 signaling is in fact needed for efficient human naïve B cell differentiation to ASCs.

Investigating the Mechanism of Germinal Center Shutdown

Germinal centers (GCs) are transient structures where affinity maturation of B cells gives rise to high affinity plasma and memory cells. The mechanism of GC shutdown is unclear, despite being an important phenomenon maintaining immune homeostasis. In this study, we used a mathematical model to identify mechanisms that can independently promote contraction of GCs leading to shutdown. We show that GC shutdown can be promoted by antigen consumption by B cells, antigen masking by soluble antibodies, alterations in follicular dendritic cell (FDC) network area, modulation of immune complex cycling rate constants, alterations in T follicular helper signaling, increased terminal differentiation and reduced B cell division capacity. Proposed mechanisms promoted GC contraction by ultimately decreasing the number of B cell divisions and recycling cells. Based on the in-silico predictions, we suggest a combination of experiments that can be potentially employed by future studies to unravel the mechanistic basis of GC shutdown such as measurements of the density of pMHC presentation of B cells, FDC network size per B cell, fraction of cells expressing differentiation markers. We also show that the identified mechanisms differentially affect the efficiency of GC reaction estimated based on the quantity and quality of resulting antibodies.

The role of geometric features in a germinal center

The germinal center (GC) is a self-organizing structure produced in the lymphoid follicle during the T-dependent immune response and is an important component of the humoral immune system. However, the impact of the special structure of GC on antibody production is not clear. According to the latest biological experiments, we establish a spatiotemporal stochastic model to simulate the whole self-organization process of the GC including the appearance of two specific zones: the dark zone (DZ) and the light zone (LZ), the development of which serves to maintain an effective competition among different cells and promote affinity maturation. A phase transition is discovered in this process, which determines the critical GC volume for a successful growth in both the stochastic and the deterministic model. Further increase of the volume does not make much improvement on the performance. It is found that the critical volume is determined by the distance between the activated B cell receptor (BCR) and the target epitope of the antigen in the shape space. The observation is confirmed in both 2D and 3D simulations and explains partly the variability of the observed GC size.

From affinity selection to kinetic selection in Germinal Centre modelling

Affinity maturation is an evolutionary process by which the affinity of antibodies (Abs) against specific antigens (Ags) increases through rounds of B-cell proliferation, somatic hypermutation, and positive selection in germinal centres (GC). The positive selection of B cells depends on affinity, but the underlying mechanisms of affinity discrimination and affinity-based selection are not well understood. It has been suggested that selection in GC depends on both rapid binding of B-cell receptors (BcRs) to Ags which is kinetically favourable and tight binding of BcRs to Ags, which is thermodynamically favourable; however, it has not been shown whether a selection bias for kinetic properties is present in the GC. To investigate the GC selection bias towards rapid and tight binding, we developed an agent-based model of GC and compared the evolution of founder B cells with initially identical low affinities but with different association/dissociation rates for Ag presented by follicular dendritic cells in three Ag collection mechanisms. We compared an Ag collection mechanism based on association/dissociation rates of B-cell interaction with presented Ag, which includes a probabilistic rupture of bonds between the B-cell and Ag (Scenario-1) with a reference scenario based on an affinity-based Ag collection mechanism (Scenario-0). Simulations showed that the mechanism of Ag collection affects the GC dynamics and the GC outputs concerning fast/slow (un)binding of B cells to FDC-presented Ags. In particular, clones with lower dissociation rates outcompete clones with higher association rates in Scenario-1, while remaining B cells from clones with higher association rates reach higher affinities. Accordingly, plasma cell and memory B cell populations were biased towards B-cell clones with lower dissociation rates. Without such probabilistic ruptures during the Ag extraction process (Scenario-2), the selective advantage for clones with very low dissociation rates diminished, and the affinity maturation level of all clones decreased to the reference level.

Adaptive immunity is one of the vital defence mechanisms of the human body to fight virtually unlimited types of pathogens by producing antigen-specific high-affinity antibodies that bind to pathogens and neutralise them or mark them for further elimination. Affinity is a quantity used to measure and report the strength of interaction between antibodies and antigens that depends both on how fast antibodies bind to antigens (association rate) and how long the bond lasts (dissociation rate). The affinity of produced antibodies for a specific antigen increases in germinal centres through a process called affinity maturation, during which B cells with higher affinities have a competitive advantage and get positively selected to differentiate to antibody-producing plasma cells. Our research shows that the mechanism by which B cells capture Ag affects GC dynamics and GC output with respect to B-cell receptor kinetics. Notably, in a mechanism where rupture of CC-FDC bonds is possible during Ag extraction, B-cell clones with low dissociation rates outcompete clones with high association rates over time. Understanding how B cells get selected in germinal centres could help to develop an optimised and effective immune response against a disease through vaccination for a fast-operating and long-lasting immune response.

System-Level Scenarios for the Elucidation of T Cell-Mediated Germinal Center B Cell Differentiation

Germinal center (GC) reactions are vital to the correct functioning of the adaptive immune system, through formation of high affinity, class switched antibodies. GCs are transient anatomical structures in secondary lymphoid organs where specific B cells, after recognition of antigen and with T cell help, undergo class switching. Subsequently, B cells cycle between zones of proliferation and somatic hypermutation and zones where renewed antigen acquisition and T cell help allows for selection of high affinity B cells (affinity maturation). Eventually GC B cells first differentiate into long-lived memory B cells (MBC) and finally into plasma cells (PC) that partially migrate to the bone marrow to encapsulate into long-lived survival niches. The regulation of GC reactions is a highly dynamically coordinated process that occurs between various cells and molecules that change in their signals. Here, we present a system-level perspective of T cell-mediated GC B cell differentiation, presenting and discussing the experimental and computational efforts on the regulation of the GCs. We aim to integrate Systems Biology with B cell biology, to advance elucidation of the regulation of high-affinity, class switched antibody formation, thus to shed light on the delicate functioning of the adaptive immune system. Specifically, we: i) review experimental findings of internal and external factors driving various GC dynamics, such as GC initiation, maturation and GCBC fate determination; ii) draw comparisons between experimental observations and mathematical modeling investigations; and iii) discuss and reflect on current strategies of modeling efforts, to elucidate B cell behavior during the GC tract. Finally, perspectives are specifically given on to the areas where a Systems Biology approach may be useful to predict novel GCBC-T cell interaction dynamics.

Advances in understanding the formation and fate of B-cell memory in response to immunization or infection

Immunological memory has the potential to provide lifelong protection against recurrent infections. As such, it has been crucial to the success of vaccines. Yet, the recent pandemic has illuminated key gaps in our knowledge related to the factors influencing effective memory formation and the inability to predict the longevity of immune protection. In recent decades, researchers have acquired a number of novel and powerful tools with which to study the factors underpinning humoral memory. These tools have been used to study the B-cell fate decisions that occur within the germinal centre (GC), a site where responding B cells undergo affinity maturation and are one of the major routes for memory B cell and high-affinity long-lived plasma cell formation. The advent of single-cell sequencing technology has provided an enhanced resolution for studying fate decisions within the GC and cutting-edge techniques have enabled researchers to model this reaction with more accuracy both in vitro and in silico. Moreover, modern approaches to studying memory B cells have allowed us to gain a better appreciation for the heterogeneity and adaptability of this vital class of B cells. Together, these studies have facilitated important breakthroughs in our understanding of how these systems operate to ensure a successful immune response. In this review, we describe recent advances in the field of GC and memory B-cell biology in order to provide insight into how humoral memory is formed, as well as the potential for generating lasting immunity to novel pathogens such as severe acute respiratory syndrome coronavirus 2.

Coupled Antigen and BLIMP1 Asymmetric Division With a Large Segregation Between Daughter Cells Recapitulates the Temporal Transition From Memory B Cells to Plasma Cells and a DZ-to-LZ Ratio in the Germinal Center

Memory B cells and antibody-secreting plasma cells are generated within germinal centers during affinity maturation in which B-cell proliferation, selection, differentiation, and self-renewal play important roles. The mechanisms behind memory B cell and plasma cell differentiation in germinal centers are not well understood. However, it has been suggested that cell fate is (partially) determined by asymmetric cell division, which involves the unequal distribution of cellular components to both daughter cells. To investigate what level and/or probability of asymmetric segregation of several fate determinant molecules, such as the antigen and transcription factors (BCL6, IRF4, and BLIMP1) recapitulates the temporal switch and DZ-to-LZ ratio in the germinal center, we implemented a multiscale model that combines a core gene regulatory network for plasma cell differentiation with a model describing the cellular interactions and dynamics in the germinal center. Our simulations show that BLIMP1 driven plasma cell differentiation together with coupled asymmetric division of antigen and BLIMP1 with a large segregation between the daughter cells results in a germinal center DZ-to-LZ ratio and a temporal switch from memory B cells to plasma cells that have been observed in experiments.

Compartments and Connections Within the Germinal Center

Protective high affinity antibody responses emerge through an orchestrated developmental process that occurs in germinal centers (GCs). While GCs have been appreciated since 1930, a wealth of recent progress provides new insights into the molecular and cellular dynamics governing humoral immunity. In this review, we highlight advances that demonstrate that fundamental GC B cell function, selection, proliferation and SHM occur within distinct cell states. The resulting new model provides new opportunities to understand the evolution of immunity in infectious, autoimmune and neoplastic diseases.