Deriving a germinal center lymphocyte migration model from two-photon data

Soluble ACE2 correlates with severe COVID-19 and can impair antibody responses

Identifying immune modulators that impact neutralizing antibody responses against severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is of great relevance. We postulated that high serum concentrations of soluble angiotensin-converting enzyme 2 (sACE2) might mask the spike and interfere with antibody maturation toward the SARS-CoV-2-receptor-binding motif (RBM). We tested 717 longitudinal samples from 295 COVID-19 patients and showed a 2- to 10-fold increase of enzymatically active sACE2 (a-sACE2), with up to 1 μg/mL total sACE2 in moderate and severe patients. Fifty percent of COVID-19 sera inhibited ACE2 activity, in contrast to 1.3% of healthy donors and 4% of non-COVID-19 pneumonia patients. A mild inverse correlation of a-sACE2 with RBM-directed serum antibodies was observed. In silico, we show that sACE2 concentrations measured in COVID-19 sera can disrupt germinal center formation and inhibit timely production of high-affinity antibodies. We suggest that sACE2 is a biomarker for COVID-19 and that soluble receptors may contribute to immune suppression informing vaccine design.

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.

Suppressive might of a few: T follicular regulatory cells impede auto-reactivity despite being outnumbered in the germinal centres

The selection of high-affinity B cells and the production of high-affinity antibodies are mediated by T follicular helper cells (Tfhs) within germinal centres (GCs). Therein, somatic hypermutation and selection enhance B cell affinity but risk the emergence of self-reactive B cell clones. Despite being outnumbered compared to their helper counterpart, the ablation of T follicular regulatory cells (Tfrs) results in enhanced dissemination of self-reactive antibody-secreting cells (ASCs). The specific mechanisms by which Tfrs exert their regulatory action on self-reactive B cells are largely unknown. We developed computer simulations to investigate how Tfrs regulate either selection or differentiation of B cells to prevent auto-reactivity. We observed that Tfr-induced apoptosis of self-reactive B cells during the selection phase impedes self-reactivity with physiological Tfr numbers, especially when Tfrs can access centrocyte-enriched GC areas. While this aided in selecting non-self-reactive B cells by restraining competition, higher Tfr numbers distracted non-self-reactive B cells from receiving survival signals from Tfhs. Thus, the location and number of Tfrs must be regulated to circumvent such Tfr distraction and avoid disrupting GC evolution. In contrast, when Tfrs regulate differentiation of selected centrocytes by promoting recycling to the dark zone phenotype of self-reactive GC resident pre-plasma cells (GCPCs), higher Tfr numbers were required to impede the circulation of self-reactive ASCs (s-ASCs). On the other hand, Tfr-engagement with GCPCs and subsequent apoptosis of s-ASCs can control self-reactivity with low Tfr numbers, but does not confer selection advantage to non-self-reactive B cells. The simulations predict that to restrict auto-reactivity, natural redemption of self-reactive B cells is insufficient and that Tfrs should increase the mutation probability of self-reactive B cells.

Amount of antigen, T follicular helper cells and affinity of founder cells shape the diversity of germinal center B cells: A computational study

A variety of B cell clones seed the germinal centers, where a selection stringency expands the fitter clones to generate higher affinity antibodies. However, recent experiments suggest that germinal centers often retain a diverse set of B cell clones with a range of affinities and concurrently carry out affinity maturation. Amid a tendency to flourish germinal centers with fitter clones, how several B cell clones with differing affinities can be concurrently selected remains poorly understood. Such a permissive selection may allow non-immunodominant clones, which are often rare and of low-affinity, to somatically hypermutate and result in a broad and diverse B cell response. How the constituent elements of germinal centers, their quantity and kinetics may modulate diversity of B cells, has not been addressed well. By implementing a state-of-the-art agent-based model of germinal center, here, we study how these factors impact temporal evolution of B cell clonal diversity and its underlying balance with affinity maturation. While we find that the extent of selection stringency dictates clonal dominance, limited antigen availability on follicular dendritic cells is shown to expedite the loss of diversity of B cells as germinal centers mature. Intriguingly, the emergence of a diverse set of germinal center B cells depends on high affinity founder cells. Our analysis also reveals a substantial number of T follicular helper cells to be essential in balancing affinity maturation with clonal diversity, as a low number of T follicular helper cells impedes affinity maturation and also contracts the scope for a diverse B cell response. Our results have implications for eliciting antibody responses to non-immunodominant specificities of the pathogens by controlling the regulators of the germinal center reaction, thereby pivoting a way for vaccine development to generate broadly protective antibodies.

IL-21R signal reprogramming cooperates with CD40 and BCR signals to select and differentiate germinal center B cells

Both B cell receptor (BCR) and CD40 signaling are rewired in germinal center (GC) B cells (GCBCs) to synergistically induce c-MYC and phosphorylated S6 ribosomal protein (p-S6), markers of positive selection. How interleukin-21 (IL-21), a key T follicular helper (TFH)-derived cytokine, affects GCBCs is unclear. Like BCR and CD40 signals, IL-21 receptor (IL-21R) plus CD40 signals also synergize to induce c-MYC and p-S6 in GCBCs. However, IL-21R plus CD40 stimulation differentially affects GCBC fate compared with BCR plus CD40 ligation-engaging unique molecular mechanisms-as revealed by bulk RNA sequencing (RNA-seq), single-cell RNA-seq, and flow cytometry of GCBCs in vitro and in vivo. Whereas both signal pairs induced BLIMP1 in some GCBCs, only the IL-21R/CD40 combination induced IRF4hi/CD138+ cells, indicative of plasma cell differentiation, along with CCR6+/CD38+ memory B cell precursors. These findings reveal a second positive selection pathway in GCBCs, document rewired IL-21R signaling in GCBCs, and link specific TFH- and Ag-derived signals to GCBC differentiation.

Antibody Mediated Intercommunication of Germinal Centers

Antibody diversification and selection of B cells occur in dynamic structures called germinal centers (GCs). Passively administered soluble antibodies regulate the GC response by masking the antigen displayed on follicular dendritic cells (FDCs). This suggests that GCs might intercommunicate via naturally produced soluble antibodies, but the role of such GC-GC interactions is unknown. In this study, we performed in silico simulations of interacting GCs and predicted that intense interactions by soluble antibodies limit the magnitude and lifetime of GC responses. With asynchronous GC onset, we observed a higher inhibition of late formed GCs compared to early ones. We also predicted that GC-GC interactions can lead to a bias in the epitope recognition even in the presence of equally dominant epitopes due to differences in founder cell composition or initiation timing of GCs. We show that there exists an optimal range for GC-GC interaction strength that facilitates the affinity maturation towards an incoming antigenic variant during an ongoing GC reaction. These findings suggest that GC-GC interactions might be a contributing factor to the unexplained variability seen among individual GCs and a critical factor in the modulation of GC response to antigenic variants during viral infections.

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.

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.

Simulating CXCR5 Dynamics in Complex Tissue Microenvironments

To effectively navigate complex tissue microenvironments, immune cells sense molecular concentration gradients using G-protein coupled receptors. However, due to the complexity of receptor activity, and the multimodal nature of chemokine gradients in vivo, chemokine receptor activity in situ is poorly understood. To address this issue, we apply a modelling and simulation approach that permits analysis of the spatiotemporal dynamics of CXCR5 expression within an in silico B-follicle with single-cell resolution. Using this approach, we show that that in silico B-cell scanning is robust to changes in receptor numbers and changes in individual kinetic rates of receptor activity, but sensitive to global perturbations where multiple parameters are altered simultaneously. Through multi-objective optimization analysis we find that the rapid modulation of CXCR5 activity through receptor binding, desensitization and recycling is required for optimal antigen scanning rates. From these analyses we predict that chemokine receptor signaling dynamics regulate migration in complex tissue microenvironments to a greater extent than the total numbers of receptors on the cell surface.

A molecular theory of germinal center B cell selection and division

The selection of B cells (BCs) in germinal centers (GCs) is pivotal to the generation of high-affinity antibodies and memory BCs, but it lacks global understanding. Based on the idea of a single Tfh-cell signal that controls BC selection and division, experiments appear contradictory. Here, we use the current knowledge on the molecular pathways of GC BCs to develop a theory of GC BC selection and division based on the dynamics of molecular factors. This theory explains the seemingly contradictory experiments by the separation of signals for BC fate decision from signals controlling the number of BC divisions. Three model variants are proposed and experiments are predicted that allow one to distinguish those. Understanding information processing in molecular BC states is critical for targeted immune interventions, and the proposed theory implies that selection and division can be controlled independently in GC reactions.

Coevolutionary transitions emerging from flexible molecular recognition and eco-evolutionary feedback

Highly mutable viruses evolve to evade host immunity that exerts selective pressure and adapts to viral dynamics. Here, we provide a framework for identifying key determinants of the mode and fate of viral-immune coevolution by linking molecular recognition and eco-evolutionary dynamics. We find that conservation level and initial diversity of antigen jointly determine the timing and efficacy of narrow and broad antibody responses, which in turn control the transition between viral persistence, clearance, and rebound. In particular, clearance of structurally complex antigens relies on antibody evolution in a larger antigenic space than where selection directly acts; viral rebound manifests binding-mediated feedback between ecology and rapid evolution. Finally, immune compartmentalization can slow viral escape but also delay clearance. This work suggests that flexible molecular binding allows a plastic phenotype that exploits potentiating neutral variations outside direct contact, opening new and shorter paths toward highly adaptable states.

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A scale-crossing framework identifies key determinants of viral-immune coevolution

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Fast specific response influences slow broad response by shaping antigen dynamics

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Antibody footprint shift enables breadth acquisition and viral clearance

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Model explains divergent kinetics and outcomes of HCV infection in humans

B Cell Speed and B-FDC Contacts in Germinal Centers Determine Plasma Cell Output via Swiprosin-1/EFhd2

Plasma cells secreting affinity-matured antibodies develop in germinal centers (GCs), where B cells migrate persistently and directionally over defined periods of time. How modes of GC B cell migration influence plasma cell development remained unclear. Through genetic deletion of the F-actin bundling protein Swiprosin-1/EF-hand domain family member 2 (EFhd2) and by two-photon microscopy, we show that EFhd2 restrains B cell speed in GCs and hapten-specific plasma cell output. Modeling the GC reaction reveals that increasing GC B cell speed promotes plasma cell generation. Lack of EFhd2 also reduces contacts of GC B cells with follicular dendritic cells in vivo. Computational modeling uncovers that both GC output and antibody affinity depend quantitatively on contacts of GC B cells with follicular dendritic cells when B cells migrate more persistently. Collectively, our data explain how GC B cells integrate speed and persistence of cell migration with B cell receptor affinity.

Preferential Presentation of High-Affinity Immune Complexes in Germinal Centers Can Explain How Passive Immunization Improves the Humoral Response

Passive immunization (PI) with external antibodies has been used classically for rapid but temporary alleviation of disease. Transcending this role, recent studies have shown PI to induce lasting improvements in natural antibody production, suggesting that PI could become a powerful tool to engineer humoral responses. We propose a mechanism with which PI can alter the humoral response. Antigen-specific B cells evolve and get selected in germinal centers (GCs) on the basis of their ability to acquire antigen from antibody-antigen complexes presented in GCs. When external antibodies of high affinity for antigen are used, they form the majority of the complexes in GCs, letting only B cells with even higher affinities be selected. Using an in silico GC reaction model, we show that this mechanism explains the improved humoral responses following PI. The model also synthesizes several independent experimental observations, indicating the robustness of the mechanism, and proposes tunable handles to optimize PI.

High CXCR4 expression impairs rituximab response and the prognosis of R-CHOP-treated diffuse large B-cell lymphoma patients

Survival of diffuse large B-cell lymphoma (DLBCL) patients has improved by inclusion of rituximab. Refractory/recurrent disease caused by treatment resistance is, however, a major problem. Determinants of rituximab sensitivity are not fully understood, but effect of rituximab are enhanced by antagonizing cell surface receptor CXCR4. In a two-step strategy, we tested the hypothesis that prognostic value of CXCR4 in DLBCL relates to rituximab treatment, due to a hampering effect of CXCR4 on the response of DLBCL cells to rituximab. First, by investigating the prognostic impact of CXCR4 mRNA expression separately for CHOP (n=181) and R-CHOP (n=233) cohorts and, second, by assessing the interaction between CXCR4 and rituximab in DLBCL cell lines. High CXCR4 expression level was significantly associated with poor outcome only for R-CHOP-treated patients, independent of IPI score, CD20 expression, ABC/GCB and B-cell-associated gene signature (BAGS) classifications. s. For responsive cell lines, inverse correlation was observed between rituximab sensitivity and CXCR4 surface expression, rituximab induced upregulation of surface-expressed CXCR4, and growth-inhibitory effect of rituximab increased by plerixafor, supporting negative impact of CXCR4 on rituximab function. In conclusion, CXCR4 is a promising independent prognostic marker for R-CHOP-treated DLBCL patients, possibly due to inverse correlation between CXCR4 expression and rituximab sensitivity.

Current Strategies and Applications for Precision Drug Design

Since Human Genome Project (HGP) revealed the heterogeneity of individuals, precision medicine that proposes the customized healthcare has become an intractable and hot research. Meanwhile, as the Precision Medicine Initiative launched, precision drug design which aims at maximizing therapeutic effects while minimizing undesired side effects for an individual patient has entered a new stage. One of the key strategies of precision drug design is target based drug design. Once a key pathogenic target is identified, rational drug design which constitutes the major part of precision drug design can be performed. Examples of rational drug design on novel druggable targets and protein-protein interaction surfaces are summarized in this review. Besides, various kinds of computational modeling and simulation approaches increasingly benefit for the drug discovery progress. Molecular dynamic simulation, drug target prediction and in silico clinical trials are discussed. Moreover, due to the powerful ability in handling high-dimensional data and complex system, deep learning has efficiently promoted the applications of artificial intelligence in drug discovery and design. In this review, deep learning methods that tailor to precision drug design are carefully discussed. When a drug molecule is discovered, the development of specific targeted drug delivery system becomes another key aspect of precision drug design. Therefore, state-of-the-art techniques of drug delivery system including antibody-drug conjugates (ADCs), and ligand-targeted conjugates are also included in this review.

Germinal center entry not selection of B cells is controlled by peptide-MHCII complex density

B cells expressing high affinity antigen receptors are advantaged in germinal centers (GC), perhaps by increased acquisition of antigen for presentation to follicular helper T cells and improved T-cell help. In this model for affinity-dependent selection, the density of peptide/MHCII (pMHCII) complexes on GC B cells is the primary determinant of selection. Here we show in chimeric mice populated by B cells differing only in their capacity to express MHCII (MHCII+/+ and MHCII+/-) that GC selection is insensitive to halving pMHCII density. Alone, both B cell types generate identical humoral responses; in competition, MHCII+/+ B cells are preferentially recruited to early GCs but this advantage does not persist once GCs are established. During GC responses, competing MHCII+/+ and MHCII+/- GC B cells comparably accumulate mutations and have indistinguishable rates of affinity maturation. We conclude that B-cell selection by pMHCII density is stringent in the establishment of GCs, but relaxed during GC responses.

Dimensionality of Motion and Binding Valency Govern Receptor-Ligand Kinetics As Revealed by Agent-Based Modeling

Mathematical modeling and computer simulations have become an integral part of modern biological research. The strength of theoretical approaches is in the simplification of complex biological systems. We here consider the general problem of receptor–ligand binding in the context of antibody–antigen binding. On the one hand, we establish a quantitative mapping between macroscopic binding rates of a deterministic differential equation model and their microscopic equivalents as obtained from simulating the spatiotemporal binding kinetics by stochastic agent-based models. On the other hand, we investigate the impact of various properties of B cell-derived receptors—such as their dimensionality of motion, morphology, and binding valency—on the receptor–ligand binding kinetics. To this end, we implemented an algorithm that simulates antigen binding by B cell-derived receptors with a Y-shaped morphology that can move in different dimensionalities, i.e., either as membrane-anchored receptors or as soluble receptors. The mapping of the macroscopic and microscopic binding rates allowed us to quantitatively compare different agent-based model variants for the different types of B cell-derived receptors. Our results indicate that the dimensionality of motion governs the binding kinetics and that this predominant impact is quantitatively compensated by the bivalency of these receptors.

Mast cells acquire MHCII from dendritic cells during skin inflammation

Dudeck et al. demonstrate that inflammatory conditions induce dynamic interactions between mast cells (MCs) and dendritic cells (DCs) culminating in protein exchange. Resident MCs are equipped with DC MHCII and empowered to initiate T cell–driven inflammation during migration-based DC absence.

Mast cells (MCs) and dendritic cells (DCs) are essential innate sentinels populating host-environment interfaces. Using longitudinal intravital multiphoton microscopy of DC^GFP/MC^RFP reporter mice, we herein provide in vivo evidence that migratory DCs execute targeted cell-to-cell interactions with stationary MCs before leaving the inflamed skin to draining lymph nodes. During initial stages of skin inflammation, DCs dynamically scan MCs, whereas at a later stage, long-lasting interactions predominate. These innate-to-innate synapse-like contacts ultimately culminate in DC-to-MC molecule transfers including major histocompatibility complex class II (MHCII) proteins enabling subsequent ex vivo priming of allogeneic T cells with a specific cytokine signature. The extent of MHCII transfer to MCs correlates with their T cell priming efficiency. Importantly, preventing the cross talk by preceding DC depletion decreases MC antigen presenting capacity and T cell–driven inflammation. Consequently, we identify an innate intercellular communication arming resident MCs with key DC functions that might contribute to the acute defense potential during critical periods of migration-based DC absence.

A Population Dynamics Model for Clonal Diversity in a Germinal Center

Germinal centers (GCs) are micro-domains where B cells mature to develop high affinity antibodies. Inside a GC, B cells compete for antigen and T cell help, and the successful ones continue to evolve. New experimental results suggest that, under identical conditions, a wide spectrum of clonal diversity is observed in different GCs, and high affinity B cells are not always the ones selected. We use a birth, death and mutation model to study clonal competition in a GC over time. We find that, like all evolutionary processes, diversity loss is inherently stochastic. We study two selection mechanisms, birth-limited and death limited selection. While death limited selection maintains diversity and allows for slow clonal homogenization as affinity increases, birth limited selection results in more rapid takeover of successful clones. Finally, we qualitatively compare our model to experimental observations of clonal selection in mice.

Model-Driven Experimentation: A New Approach to Understand Mechanisms of Tertiary Lymphoid Tissue Formation, Function, and Therapeutic Resolution

The molecular and cellular processes driving the formation of secondary lymphoid tissues have been extensively studied using a combination of mouse knockouts, lineage-specific reporter mice, gene expression analysis, immunohistochemistry, and flow cytometry. However, the mechanisms driving the formation and function of tertiary lymphoid tissue (TLT) experimental techniques have proven to be more enigmatic and controversial due to differences between experimental models and human disease pathology. Systems-based approaches including data-driven biological network analysis (gene interaction network, metabolic pathway network, cell-cell signaling, and cascade networks) and mechanistic modeling afford a novel perspective from which to understand TLT formation and identify mechanisms that may lead to the resolution of tissue pathology. In this perspective, we make the case for applying model-driven experimentation using two case studies, which combined simulations with experiments to identify mechanisms driving lymphoid tissue formation and function, and then discuss potential applications of this experimental paradigm to identify novel therapeutic targets for TLT pathology.

How to Simulate a Germinal Center

Germinal centers host a mini-evolutionary environment where B cells can mutate their receptor and be selected depending on its affinity to target antigens in a process called affinity maturation. Starting from founder cells with a weak B cell receptor affinity, germinal centers release output cells as antibody-secreting cells or memory cells with a very high affinity, a property which is essential for pathogen clearance and immune memory. Therapeutic interventions on the germinal centers are tantalizing approaches to improve vaccines or to support rejection of chronic pathogens such as HIV. However, the complexity of the selection processes makes it very hard to make reliable predictions. Here, we present in detail how to build an agent-based model (hyphasma), accounting for the dynamics of the germinal center. It encompasses the core quantitative traits of affinity maturation, and allowed to make reliable predictions in previous studies.

Implications of Intravital Imaging of Murine Germinal Centers on the Control of B Cell Selection and Division

Intravital imaging of antibody optimization in germinal center (GC) reactions has set a new dimension in the understanding of the humoral immune response during the last decade. The inclusion of spatio-temporal cellular dynamics in the research on GCs required analysis using the agent-based mathematical models. In this study, we integrate the available intravital imaging data from various research groups and incorporate these into a quantitative mathematical model of GC reactions and antibody affinity maturation. Interestingly, the integration of data concerning the spatial organization of GCs and B cell motility allows to draw conclusions on the strength of the selection pressure and the control of B cell division by T follicular helper cells.

Evidence of perturbed germinal center dynamics, but preserved antibody diversity, in end-stage renal disease

INTRODUCTION

End-stage renal disease (ESRD) is associated with increased infectious susceptibility and with reduced vaccine responses consistent with compromised humoral immunity. Whether the compromised humoral immunity is due to reduced antibody diversity (reduced somatic hypermutation [SHM]) or altered germinal center (GC) dynamics is not known. The GC-derived chemokine CXCL13 as well as peripheral T follicular helper cells (pTFH) reflect GC dynamics, but have, similar to SHM, never been characterized in relation to ESRD.

METHODS

Serum CXCL 13 was determined by ELISA. PTFH were flow-cytometrically defined as CD4⁺ CD45RA^- CCR7⁺ CXCR5⁺ lymphocytes. Apoptotic lymphocyte subsets were in addition annexin V⁺. SHM was determined, by next-generation sequencing and bioinformatics, as nucleotide mutations within the IgG V_H (comprising the important antigen-binding domains of IgG, CDR1, and CDR2).

RESULTS

Elevated CXCL13 levels characterized ESRD (n = 19; [median] 90 pg/ml, P < 0.01) (controls, n = 18; 62 pg/ml). ESRD pTFH frequencies (n = 19; 11.6% [of CD4⁺ memory T cells], P < 0.02*, *Bonferroni corrected) (controls, n = 22; 14.9%) and concentrations (n = 19; 0.03 × 10⁹/L, P < 0.02*) (controls, n = 22; 0.07 × 10⁹/L) were reduced. ESRD pTFH were more apoptotic (n = 9; 25.7%, P = 0.04*) (controls, n = 10; 15.9%). SHM did not discriminate between ESRD (n = 10; 7.4%, P = 0.21) and controls (n = 10; 8.4%).

CONCLUSIONS

Elevated CXCL13 levels, reduced pTFH levels, and increased pTFH apoptosis suggest that perturbed GC dynamics, and not reduced antibody diversity, underlie the diminished vaccine responses and the compromised humoral immunity in ESRD. However, largely preserved SHM provides a rationale for pursuing vaccination in relation to ESRD.

A Stochastic Model of the Germinal Center Integrating Local Antigen Competition, Individualistic T-B Interactions, and B Cell Receptor Signaling

The germinal center (GC) reaction underlies productive humoral immunity by orchestrating competition-based affinity maturation to produce plasma cells and memory B cells. T cells are limiting in this process. How B cells integrate signals from T cells and BCRs to make fate decisions while subjected to a cyclic selection process is not clear. In this article, we present a spatiotemporally resolved stochastic model that describes cell behaviors as rate-limited stochastic reactions. We hypothesize a signal integrator protein integrates follicular helper T (Tfh)- and Ag-derived signals to drive different B cell fates in a probabilistic manner and a dedicated module of Tfh interaction promoting factors control the efficiency of contact-dependent Tfh help delivery to B cells. Without assuming deterministic affinity-based decisions or temporal event sequence, this model recapitulates GC characteristics, highlights the importance of efficient T cell help delivery during individual contacts with B cells and intercellular positive feedback for affinity maturation, reveals the possibility that antagonism between BCR signaling and T cell help accelerates affinity maturation, and suggests that the dichotomy between affinity and magnitude of GC reaction can be avoided by tuning the efficiency of contact-dependent help delivery during reiterative T-B interactions.

Computational immuno-biology for organ transplantation and regenerative medicine

Organ transplantation and regenerative medicine are adopted platforms that provide replacement tissues and organs from natural or engineered sources. Acceptance, tolerance and rejection depend greatly on the proper control of the immune response against graft antigens, motivating the development of immunological and genetical therapies that prevent organ failure. They rely on a complete, or partial, understanding of the immune system. Ultimately, they are innovative technologies that ensure permanent graft tolerance and indefinite graft survival through the modulation of the immune system. Computational immunology has arisen as a tool towards a mechanistic understanding of the biological and physicochemical processes surrounding an immune response. It comprehends theoretical and computational frameworks that simulate immuno-biological systems. The challenge is centered on the multi-scale character of the immune system that spans from atomistic scales, during peptide-epitope and protein interactions, to macroscopic scales, for lymph transport and organ-organ reactions. In this paper, we discuss, from an engineering perspective, the biological processes that are involved during the immune response of organ transplantation. Previous computational efforts, including their characteristics and visible limitations, are described. Finally, future perspectives and challenges are listed to motivate further developments.

Trade-offs in antibody repertoires to complex antigens

Pathogens vary in their antigenic complexity. While some pathogens such as measles present a few relatively invariant targets to the immune system, others such as malaria display considerable antigenic diversity. How the immune response copes in the presence of multiple antigens, and whether a trade-off exists between the breadth and efficacy of antibody (Ab)-mediated immune responses, are unsolved problems. We present a theoretical model of affinity maturation of B-cell receptors (BCRs) during a primary infection and examine how variation in the number of accessible antigenic sites alters the Ab repertoire. Naive B cells with randomly generated receptor sequences initiate the germinal centre (GC) reaction. The binding affinity of a BCR to an antigen is quantified via a genotype-phenotype map, based on a random energy landscape, that combines local and distant interactions between residues. In the presence of numerous antigens or epitopes, B-cell clones with different specificities compete for stimulation during rounds of mutation within GCs. We find that the availability of many epitopes reduces the affinity and relative breadth of the Ab repertoire. Despite the stochasticity of somatic hypermutation, patterns of immunodominance are strongly shaped by chance selection of naive B cells with specificities for particular epitopes. Our model provides a mechanistic basis for the diversity of Ab repertoires and the evolutionary advantage of antigenically complex pathogens.

Image-based systems biology of infection

The successful treatment of infectious diseases requires interdisciplinary studies of all aspects of infection processes. The overarching combination of experimental research and theoretical analysis in a systems biology approach can unravel mechanisms of complex interactions between pathogens and the human immune system. Taking into account spatial information is especially important in the context of infection, since the migratory behavior and spatial interactions of cells are often decisive for the outcome of the immune response. Spatial information is provided by image and video data that are acquired in microscopy experiments and that are at the heart of an image-based systems biology approach. This review demonstrates how image-based systems biology improves our understanding of infection processes. We discuss the three main steps of this approach--imaging, quantitative characterization, and modeling--and consider the application of these steps in the context of studying infection processes. After summarizing the most relevant microscopy and image analysis approaches, we discuss ways to quantify infection processes, and address a number of modeling techniques that exploit image-derived data to simulate host-pathogen interactions in silico.

Overcoming the dichotomy of quantity and quality in antibody responses

Germinal centers (GCs) are specialized environments in which B cells mutate their BCR to identify new Abs with high affinity to a challenging Ag. B cells are selected in an evolutionary process of multiple rounds of mutation and selection. In the past decade, mechanisms of B cell migration, division, mutation, selection, and final differentiation have been extensively studied. Thereby, modulations of these mechanisms either optimize the quality, in terms of affinity, or the quantity of generated Abs, but never both, leading to an unclear effect on the overall efficiency of the Ab response. In this article, we predict with mathematical models that an affinity-dependent number of GC B cell divisions overcomes the dichotomy of quality and quantity, and has to be considered as a good target for immune interventions, in particular, in the elderly population with poor GC responses.

Random migration and signal integration promote rapid and robust T cell recruitment

To fight infections, rare T cells must quickly home to appropriate lymph nodes (LNs), and reliably localize the antigen (Ag) within them. The first challenge calls for rapid trafficking between LNs, whereas the second may require extensive search within each LN. Here we combine simulations and experimental data to investigate which features of random T cell migration within and between LNs allow meeting these two conflicting demands. Our model indicates that integrating signals from multiple random encounters with Ag-presenting cells permits reliable detection of even low-dose Ag, and predicts a kinetic feature of cognate T cell arrest in LNs that we confirm using intravital two-photon data. Furthermore, we obtain the most reliable retention if T cells transit through LNs stochastically, which may explain the long and widely distributed LN dwell times observed in vivo. Finally, we demonstrate that random migration, both between and within LNs, allows recruiting the majority of cognate precursors within a few days for various realistic infection scenarios. Thus, the combination of two-scale stochastic migration and signal integration is an efficient and robust strategy for T cell immune surveillance.

Automated characterization and parameter-free classification of cell tracks based on local migration behavior

Cell migration is the driving force behind the dynamics of many diverse biological processes. Even though microscopy experiments are routinely performed today by which populations of cells are visualized in space and time, valuable information contained in image data is often disregarded because statistical analyses are performed at the level of cell populations rather than at the single-cell level. Image-based systems biology is a modern approach that aims at quantitatively analyzing and modeling biological processes by developing novel strategies and tools for the interpretation of image data. In this study, we take first steps towards a fully automated characterization and parameter-free classification of cell track data that can be generally applied to tracked objects as obtained from image data. The requirements to achieve this aim include: (i) combination of different measures for single cell tracks, such as the confinement ratio and the asphericity of the track volume, and (ii) computation of these measures in a staggered fashion to retrieve local information from all possible combinations of track segments. We demonstrate for a population of synthetic cell tracks as well as for in vitro neutrophil tracks obtained from microscopy experiment that the information contained in the track data is fully exploited in this way and does not require any prior knowledge, which keeps the analysis unbiased and general. The identification of cells that show the same type of migration behavior within the population of all cells is achieved via agglomerative hierarchical clustering of cell tracks in the parameter space of the staggered measures. The recognition of characteristic patterns is highly desired to advance our knowledge about the dynamics of biological processes.

The distinctive germinal center phase of IgE+ B lymphocytes limits their contribution to the classical memory response

Direct class switching to IgE generates IgE⁺ GC cells that are highly apoptotic and do not contribute to the memory compartment, while sequential switching through an IgG⁺ intermediate results in the generation of long-lived IgE⁺ plasma cells.

The mechanisms involved in the maintenance of memory IgE responses are poorly understood, and the role played by germinal center (GC) IgE⁺ cells in memory responses is particularly unclear. IgE⁺ B cell differentiation is characterized by a transient GC phase, a bias toward the plasma cell (PC) fate, and dependence on sequential switching for the production of high-affinity IgE. We show here that IgE⁺ GC B cells are unfit to undergo the conventional GC differentiation program due to impaired B cell receptor function and increased apoptosis. IgE⁺ GC cells fail to populate the GC light zone and are unable to contribute to the memory and long-lived PC compartments. Furthermore, we demonstrate that direct and sequential switching are linked to distinct B cell differentiation fates: direct switching generates IgE⁺ GC cells, whereas sequential switching gives rise to IgE⁺ PCs. We propose a comprehensive model for the generation and memory of IgE responses.

Hydrodynamic immunization leads to poor CD8 T-cell expansion, low frequency of memory CTLs and ineffective antiviral protection

Hepatotropic pathogens, such as hepatitis B (HBV) and hepatitis C (HCV), often escape cellular immune clearance resulting in chronic infection. As HBV and HCV infections are the most common causes of hepatocellular carcinoma (HCC), prevention of these infections is believed to be key to the prevention of HCC. It is believed that an effective immune therapy must induce strong cytotonic T lymphocytes (CTLs) that can migrate into the liver, where they can clear infected hepatocytes. Here, we compared the induction of CD8 T cells by two different DNA immunization methods for T-cell differentiation, function, memory programming and their distribution within relevant tissues in a highly controlled fashion. We used hydrodynamic tail vein injection of plasmid to establish liver-specific LCMV-gp antigen (Ag) transient expression, and studied CD8 T cells induced using the P14 transgenic mouse model. CD8 T cells from this group exhibited unique and limited expansion, memory differentiation, polyfunctionality and cytotoxicity compared with T cells generated in intramuscularly immunized mice. This difference in liver-generated expansion resulted in lower memory CD8 T-cell frequency, leading to reduced protection against lethal viral challenge. These data show an unusual induction of naive CD8 T cells contributed to the lower frequency of Ag-specific CTLs observed after immunization in the liver, suggesting that limited priming in liver compared with peripheral tissues is responsible for this outcome.

The future of immunoimaging--deeper, bigger, more precise, and definitively more colorful

Immune cells are thoroughbreds, moving farther and faster and surveying more diverse tissue space than their nonhematopoietic brethren. Intravital 2-photon microscopy has provided insights into the movements and interactions of many immune cell types in diverse tissues, but more information is needed to link such analyses of dynamic cell behavior to function. Here, we describe additional methods whose application promises to extend our vision, allowing more complete, multiscale dissection of how immune cell positioning and movement are linked to system state, host defense, and disease.

Rgs13 constrains early B cell responses and limits germinal center sizes

Germinal centers (GCs) are microanatomic structures that develop in secondary lymphoid organs in response to antigenic stimulation. Within GCs B cells clonally expand and their immunoglobulin genes undergo class switch recombination and somatic hypermutation. Transcriptional profiling has identified a number of genes that are prominently expressed in GC B cells. Among them is Rgs13, which encodes an RGS protein with a dual function. Its canonical function is to accelerate the intrinsic GTPase activity of heterotrimeric G-protein α subunits at the plasma membrane, thereby limiting heterotrimeric G-protein signaling. A unique, non-canonical function of RGS13 occurs following translocation to the nucleus, where it represses CREB transcriptional activity. The functional role of RGS13 in GC B cells is unknown. To create a surrogate marker for Rgs13 expression and a loss of function mutation, we inserted a GFP coding region into the Rgs13 genomic locus. Following immunization GFP expression rapidly increased in activated B cells, persisted in GC B cells, but declined in newly generated memory B and plasma cells. Intravital microscopy of the inguinal lymph node (LN) of immunized mice revealed the rapid appearance of GFP⁺ cells at LN interfollicular regions and along the T/B cell borders, and eventually within GCs. Analysis of WT, knock-in, and mixed chimeric mice indicated that RGS13 constrains extra-follicular plasma cell generation, GC size, and GC B cell numbers. Analysis of select cell cycle and GC specific genes disclosed an aberrant gene expression profile in the Rgs13 deficient GC B cells. These results indicate that RGS13, likely acting at cell membranes and in nuclei, helps coordinate key decision points during the expansion and differentiation of naive B cells.

A one-shot germinal center model under protein structural stability constraints

The germinal center reaction is the process by which low-affinity B cells evolve into potent, immunoglobulin-secreting plasma and memory B cells. Since the recycling hypothesis was created, experimental studies have both tracked movement of a small population of B cells from the light zone into the dark zone, supporting the recycling model, and parallel to the light zone-dark zone interface, indicating a one-way trajectory. We present a novel, sequence-based ab initio model of protein stability and protein interactions. Our model contains a dark zone region of clonal expansion and somatic hypermutation and a light zone site of antigenic selection. We show not only that a one-shot model is sufficient to achieve biologically-realistic rates of affinity growth, population dynamics, and silent:non-silent mutation ratios in the complementary determining region and framework region of antibodies, but also that a stochastic recycling program with or without realistic constraints on the structural stabilities of GC antibodies cannot produce biologically-observed affinity growth, population dynamics or silent:non-silent mutation profiles. The effect of recycling erases affinity gains made by potent antibodies cycling back from the light zone and causes B cells to pool in the dark zone under high replication rates.

Germinal center B cells govern their own fate via antibody feedback

High-affinity antibodies reenter germinal centers (GCs) and limit antigen access, thus causing sustained directional evolution in GCs toward higher-affinity antibody production.

Affinity maturation of B cells in germinal centers (GCs) is a process of evolution, involving random mutation of immunoglobulin genes followed by natural selection by T cells. Only B cells that have acquired antigen are able to interact with T cells. Antigen acquisition is dependent on the interaction of B cells with immune complexes inside GCs. It is not clear how efficient selection of B cells is maintained while their affinity matures. Here we show that the B cells’ own secreted products, antibodies, regulate GC selection by limiting antigen access. By manipulating the GC response with monoclonal antibodies of defined affinities, we show that antibodies in GCs are in affinity-dependent equilibrium with antibodies produced outside and that restriction of antigen access influences B cell selection, seen as variations in apoptosis, plasma cell output, T cell interaction, and antibody affinity. Feedback through antibodies produced by GC-derived plasma cells can explain how GCs maintain an adequate directional selection pressure over a large range of affinities throughout the course of an immune response, accelerating the emergence of B cells of highest affinities. Furthermore, this mechanism may explain how spatially separated GCs communicate and how the GC reaction terminates.

A model for migratory B cell oscillations from receptor down-regulation induced by external chemokine fields

A long-standing paradigm in B cell immunology is that effective somatic hypermutation and affinity maturation require cycling between the dark zone and light zone of the germinal center. The cyclic re-entry hypothesis was first proposed based on considerations of the efficiency of affinity maturation using an ordinary differential equations model for B cell population dynamics. More recently, two-photon microscopy studies of B cell motility within lymph nodes in situ have revealed the complex migration patterns of B lymphocytes both in the preactivation follicle and post-activation germinal center. There is strong evidence that chemokines secreted by stromal cells and the regulation of cognate G-protein coupled receptors by these chemokines are necessary for the observed spatial cell distributions. For example, the distribution of B cells within the light and dark zones of the germinal center appears to be determined by the reciprocal interaction between the level of the CXCR4 and CXCR5 receptors and the spatial distribution of their respective chemokines CXCL12 and CXCL13. Computer simulations of individual-based models have been used to study the complex biophysical and mechanistic processes at the individual cell level, but such simulations can be challenging to parameterize and analyze. In contrast, ordinary differential equations are more tractable, but traditional compartment model formalizations ignore the spatial chemokine distribution that drives B cell redistribution. Motivated by the desire to understand the motility patterns observed in an individual-based simulation of B cell migration in the lymph node, we propose and analyze the dynamics of an ordinary differential equation model incorporating explicit chemokine spatial distributions. While there is experimental evidence that B cell migration patterns in the germinal center are driven by extrinsically regulated differentiation programs, the model shows, perhaps surprisingly, that feedback from receptor down-regulation induced by external chemokine fields can give rise to spontaneous interzonal and intrazonal oscillations in the absence of any extrinsic regulation. While the extent to which such simple feedback mechanisms contributes to B cell migration patterns in the germinal center is unknown, the model provides an alternative hypothesis for how complex B cell migration patterns might arise from very simple mechanisms.

Chemotactic migration of T cells towards dendritic cells promotes the detection of rare antigens

In many immunological processes chemoattraction is thought to play a role in guiding cells to their sites of action. However, based on in vivo two-photon microscopy experiments in the absence of cognate antigen, T cell migration in lymph nodes (LNs) has been roughly described as a random walk. Although it has been shown that dendritic cells (DCs) carrying cognate antigen in some circumstances attract T cells chemotactically, it is currently still unclear whether chemoattraction of T cells towards DCs helps or hampers scanning. Chemoattraction towards DCs could on the one hand help T cells to rapidly find DCs. On the other hand, it could be deleterious if DCs become shielded by a multitude of attracted yet non-specific T cells. Results from a recent simulation study suggested that the deleterious effect dominates. We re-addressed the question whether T cell chemoattraction towards DCs is expected to promote or hamper the detection of rare antigens using the Cellular Potts Model, a formalism that allows for dynamic, flexible cellular shapes and cell migration. Our simulations show that chemoattraction of T cells enhances the DC scanning efficiency, leading to an increased probability that rare antigen-specific T cells find DCs carrying cognate antigen. Desensitization of T cells after contact with a DC further improves the scanning efficiency, yielding an almost threefold enhancement compared to random migration. Moreover, the chemotaxis-driven migration still roughly appears as a random walk, hence fine-tuned analysis of cell tracks will be required to detect chemotaxis within microscopy data.

Germinal center selection and the development of memory B and plasma cells

A hallmark of adaptive immune responses is the generation of long-lived protection after primary exposure to a pathogen. In humoral responses, this protection stems from a combination of sustained antibody titers and long-lived memory B cells (MBCs), with the former deriving from long-lived plasma cells (PCs). Both types of cell are thought to primarily derive from the germinal center (GC), a unique structure that forms during the immune response to many types of antigenic stimuli. GCs are seeded by antigen-specific B and T cells that were previously activated in the early stages of the response. The GC does not directly or immediately generate effector function; rather, it is a site of intense B-cell proliferation and cell death. GC B cells undergo both somatic hypermutation and isotype switch, and a Darwinian process very efficiently selects B cells with higher fitness for survival and expansion. GC B cells adopt a unique activation and transcriptional state, and the cells become poised to differentiate to either MBCs or PCs. Despite this general understanding of the events in the GC, the mechanisms that control both affinity selection as well as differentiation have not been well worked out. In this review, we address what is known about what determines whether GC B cells become MBCs or PCs. This is discussed in the broader context of the origins of both cell types, whether from the GC or potentially other sources. We present a model encompassing recent data from several laboratories including our own that suggests that the GC undergoes a temporal switch that alters the nature of its output from MBCs to PCs as the response progresses. We will discuss B-cell receptor signaling in the GC as it relates to potential mechanisms for affinity-based selection during the reaction.

Pairing experimentation and computational modeling to understand the role of tissue inducer cells in the development of lymphoid organs

The use of genetic tools, imaging technologies and ex vivo culture systems has provided significant insights into the role of tissue inducer cells and associated signaling pathways in the formation and function of lymphoid organs. Despite advances in experimental technologies, the molecular and cellular process orchestrating the formation of a complex three-dimensional tissue is difficult to dissect using current approaches. Therefore, a robust set of simulation tools have been developed to model the processes involved in lymphoid tissue development. Specifically, the role of different tissue inducer cell populations in the dynamic formation of Peyer’s patches has been examined. Utilizing approaches from systems engineering, an unbiased model of lymphoid tissue inducer cell function has been developed that permits the development of emerging behaviors that are statistically not different from that observed in vivo. These results provide the confidence to utilize statistical methods to explore how the simulator predicts cellular behavior and outcomes under different physiological conditions. Such methods, known as sensitivity analysis techniques, can provide insight into when a component part of the system (such as a particular cell type, adhesion molecule, or chemokine) begins to have an influence on observed behavior, and quantifies the effect a component part has on the end result: the formation of lymphoid tissue. Through use of such a principled approach in the design, calibration, and analysis of a computer simulation, a robust in silico tool can be developed which can both further the understanding of a biological system being explored, and act as a tool for the generation of hypotheses which can be tested utilizing experimental approaches.

A theory of germinal center B cell selection, division, and exit

High-affinity antibodies are generated in germinal centers in a process involving mutation and selection of B cells. Information processing in germinal center reactions has been investigated in a number of recent experiments. These have revealed cell migration patterns, asymmetric cell divisions, and cell-cell interaction characteristics, used here to develop a theory of germinal center B cell selection, division, and exit (the LEDA model). According to this model, B cells selected by T follicular helper cells on the basis of successful antigen processing always return to the dark zone for asymmetric division, and acquired antigen is inherited by one daughter cell only. Antigen-retaining B cells differentiate to plasma cells and leave the germinal center through the dark zone. This theory has implications for the functioning of germinal centers because compared to previous models, high-affinity antibodies appear one day earlier and the amount of derived plasma cells is considerably larger.

Systems biology of fungal infection

Elucidation of pathogenicity mechanisms of the most important human-pathogenic fungi, Aspergillus fumigatus and Candida albicans, has gained great interest in the light of the steadily increasing number of cases of invasive fungal infections. A key feature of these infections is the interaction of the different fungal morphotypes with epithelial and immune effector cells in the human host. Because of the high level of complexity, it is necessary to describe and understand invasive fungal infection by taking a systems biological approach, i.e., by a comprehensive quantitative analysis of the non-linear and selective interactions of a large number of functionally diverse, and frequently multifunctional, sets of elements, e.g., genes, proteins, metabolites, which produce coherent and emergent behaviors in time and space. The recent advances in systems biology will now make it possible to uncover the structure and dynamics of molecular and cellular cause-effect relationships within these pathogenic interactions. We review current efforts to integrate omics and image-based data of host-pathogen interactions into network and spatio-temporal models. The modeling will help to elucidate pathogenicity mechanisms and to identify diagnostic biomarkers and potential drug targets for therapy and could thus pave the way for novel intervention strategies based on novel antifungal drugs and cell therapy.

Chemotaxis in densely populated tissue determines germinal center anatomy and cell motility: a new paradigm for the development of complex tissues

Germinal centers (GCs) are complex dynamic structures that form within lymph nodes as an essential process in the humoral immune response. They represent a paradigm for studying the regulation of cell movement in the development of complex anatomical structures. We have developed a simulation of a modified cyclic re-entry model of GC dynamics which successfully employs chemotaxis to recapitulate the anatomy of the primary follicle and the development of a mature GC, including correctly structured mantle, dark and light zones. We then show that correct single cell movement dynamics (including persistent random walk and inter-zonal crossing) arise from this simulation as purely emergent properties. The major insight of our study is that chemotaxis can only achieve this when constrained by the known biological properties that cells are incompressible, exist in a densely packed environment, and must therefore compete for space. It is this interplay of chemotaxis and competition for limited space that generates all the complex and biologically accurate behaviors described here. Thus, from a single simple mechanism that is well documented in the biological literature, we can explain both higher level structure and single cell movement behaviors. To our knowledge this is the first GC model that is able to recapitulate both correctly detailed anatomy and single cell movement. This mechanism may have wide application for modeling other biological systems where cells undergo complex patterns of movement to produce defined anatomical structures with sharp tissue boundaries.

An incoherent regulatory network architecture that orchestrates B cell diversification in response to antigen signaling

B cell receptor signaling controls the expression of IRF-4, a transcription factor required for B cell differentiation. This study shows that IRF-4 regulates divergent B cell fates via a ‘kinetic-control' mechanism that determines the duration of a transient developmental state.

The intensity of signaling through the B cell receptor controls the level of expression of IRF-4, a transcription factor required for B cell differentiation. The rate of IRF-4 production dictates the extent of antibody gene diversification that B cells undergo upon antigen encounter before differentiating into antibody-secreting plasma cells.

Computational modeling and experimental analyses substantiate a model, whereby IRF-4 regulates B cell fate trajectories via a ‘kinetic-control' mechanism.

Kinetic control is a process by which B cells pass through an obligate state of variable duration that sets the degree of cellular diversification prior to their terminal differentiation.

An incoherent regulatory network architecture, within which IRF-4 is embedded, is the basis for realization of kinetic control.

The generation of a diverse set of pathogen-specific antibodies, with differing affinities and effector functions, by B lymphocytes is essential for efficient protection from many microorganisms. Antibody gene diversification in B cells is mediated by two molecular processes termed class-switch recombination and somatic hypermutation (CSR/SHM) (F1A). The former enables the generation of antibodies with the same antigen-binding specificity, but different effector domains, whereas the latter results in a repertoire of antibodies with a range of affinities for a given antigen containing the same effector domain. CSR/SHM occurs in antigen-activated B cells before their terminal differentiation into plasma cells. The transcription factor IRF-4 is required for CSR/SHM as well as plasma-cell differentiation, with its highest levels of expression being necessary for the latter. IRF-4 acts in the context of a network of regulators that include Blimp-1, Pax5, Bach2 and Bcl-6 (F1B). Despite extensive characterization of these individual factors, how the network responds to sensing of antigen by the B cell antigen receptor (BCR, antibody molecule expressed on cell surface) to regulate the extent of antibody gene diversification and plasma-cell differentiation remains to be addressed.

To address this issue, we assemble a computational model. The model reveals two contrasting scenarios that can underlie B cell fate dynamics. In one case, the initial rate of IRF-4 production controls a binary cell fate choice that involves either going to the CSR/SHM state or to the plasma-cell state; the time spent in the CSR state is relatively insensitive to the initial rate of IRF-4 production (herein called ‘basic bistability'). In the other case, IRF-4 drives all cells through a transient CSR/SHM state, but the initial rate of IRF-4 production sets its duration (‘kinetic control'). Both scenarios predict that increasing the initial rate of IRF-4 production favors the generation of plasma cells at the expense of CSR/SHM, but they differ fundamentally with respect to the underlying gene expression patterns.

To distinguish between these two scenarios experimentally, we utilize two different genetic models. The first involves the B1-8i transgenic mouse whose B cells express a rearranged V187.2 VDJ Ig heavy chain gene segment that is specific for the hapten nitrophenol (NP). The second is a newly developed mouse model that allows exogenous control of IRF-4 expression in naive primary B cells using a tet-inducible allele. Using these models, we show that (i) BCR signal strength sets the initial rate of IRF-4 accumulation and (ii) the concentration of IRF-4 is sensed by an incoherent gene regulatory network architecture to regulate the extent of CSR/SHM prior to plasma-cell differentiation. Our results are consistent with the ‘kinetic-control model' in which the levels of BCR-induced IRF-4 expression control the duration of an obligate CSR/SHM state that enables B cell diversification before terminal differentiation into plasma cells. Evidence for the transient CSR/SHM state is corroborated by both patterns of gene expression and the presence of AID-dependent mutations in individual non-switched plasmablasts.

Our results provide a molecular framework for understanding how B cells balance the competing demands for Ig CSR and SHM with the secretion of antibodies during humoral immune responses. The key feature of the network architecture that allows IRF-4 to coordinate the two competing states of gene expression in a temporal manner is that it simultaneously but asymmetrically activates both sides of a bistable mutual repression circuit. Because the two effects of the primary regulator antagonize each other, we describe the circuit as being based on an ‘incoherent' regulatory motif. Other incoherent regulatory motifs in varied biological systems are also associated with the acquisition of transient cell states, and we consider how the kinetic-control mechanism proposed by us could more generally serve to translate developmental cues into elaborate morphogenetic patterns.

The B-lymphocyte lineage is a leading system for analyzing gene regulatory networks (GRNs) that orchestrate distinct cell fate transitions. Upon antigen recognition, B cells can diversify their immunoglobulin (Ig) repertoire via somatic hypermutation (SHM) and/or class switch DNA recombination (CSR) before differentiating into antibody-secreting plasma cells. We construct a mathematical model for a GRN underlying this developmental dynamic. The intensity of signaling through the Ig receptor is shown to control the bimodal expression of a pivotal transcription factor, IRF-4, which dictates B cell fate outcomes. Computational modeling coupled with experimental analysis supports a model of ‘kinetic control', in which B cell developmental trajectories pass through an obligate transient state of variable duration that promotes diversification of the antibody repertoire by SHM/CSR in direct response to antigens. More generally, this network motif could be used to translate a morphogen gradient into developmental inductive events of varying time, thereby enabling the specification of distinct cell fates.

Defining the quantitative limits of intravital two-photon lymphocyte tracking

Two-photon microscopy has substantially advanced our understanding of cellular dynamics in the immune system. Cell migration can now be imaged in real time in the living animal. Strikingly, the migration of naive lymphocytes in secondary lymphoid tissue appears predominantly random. It is unclear, however, whether directed migration may escape detection in this random background. Using a combination of mathematical modeling and experimental data, we investigate the extent to which modern two-photon imaging can rule out biologically relevant directed migration. For naive T cells migrating in uninfected lymph nodes (LNs) at average 3D speeds of around 18 μm/min, we rule out uniform directed migration of more than 1.7 μm/min at the 95% confidence level, confirming that T cell migration is indeed mostly random on a timescale of minutes. To investigate whether this finding still holds for longer timescales, we use a 3D simulation of the naive T cell LN transit. A pure random walk predicts a transit time of around 16 h, which is in good agreement with experimental results. A directional bias of only 0.5 μm/min-less than 3% of the cell speed-would already accelerate the transit twofold. These results jointly strengthen the random walk analogy for naive T cell migration in LNs, but they also emphasize that very small deviations from random migration can still be important. Our methods are applicable to cells of any type and can be used to reanalyze existing datasets.