B cell receptors and free antibodies have different antigen-binding kinetics.

Since the pioneering works of Berg and Purcell, discriminating between diffusion followed by binding has played a central role in understanding cell signaling. B cell receptors (BCR) and antibodies (Ab) challenge that simplified view as binding to the antigen follows after a chain of diffusion and rotations, including whole molecule rotation and independent tilts and twists of their Fab arms due to their Y-shaped structure and flexibility. In this paper, we combine analytical calculations with Brownian simulations to derive the first-passage times due to these three rotations positioning the Fab paratopes at a proper distance and orientation required for antigen binding. Our results indicate that when measuring Ab-Ag effective kinetic binding rates, using experimental methods in which the analyte is in solution only gives values proportional to the intrinsic binding rates, [Formula: see text], and [Formula: see text], for values of [Formula: see text] up to [Formula: see text]. Beyond that, a plateau of the effective 3D on rate between [Formula: see text] and [Formula: see text] is attained. Additionally, for BCR-Ag interactions, the effective 2D on and off binding rates can only be inferred from the corresponding effective 3D on and off rates for values of effective 3D on rates lower than [Formula: see text]. This is highly relevant when trying to relate BCR-antigen-binding strength and B cell response, especially during germinal center reactions. Therefore, there is a pressing need to reexamine our current understanding of the BCR-antigen kinetic rates in germinal centers using the latest experimental assays for BCR-Ag interactions.

Dynamically consistent objective and subjective rationality.

A group of experts, for instance climate scientists, is to advise a decision maker about the choice between two policies f and g. Consider the following decision rule. If all experts agree that the expected utility of f is higher than the expected utility of g, the unanimity rule applies, and f is chosen. Otherwise, the precautionary principle is implemented and the policy yielding the highest minimal expected utility is chosen. This decision rule may lead to time inconsistencies when adding an intermediate period of partial resolution of uncertainty. We show how to coherently reassess the initial set of experts' beliefs so that precautionary choices become dynamically consistent: new beliefs should be added until one obtains the smallest "rectangular set" that contains the original one. Our analysis offers a novel behavioral characterization of rectangularity and a prescriptive way to aggregate opinions in order to avoid sure regret.

How oligoclonal are germinal centers? A new method for estimating clonal diversity from immunohistological sections.

BACKGROUND: The germinal center (GC) reaction leads to antibody affinity maturation and generation of memory B cells, but its underlying mechanisms are poorly understood. To assemble this puzzle, several key pieces of information are needed, one in particular being the number of participating B cell clones. Since this clonal diversity cannot be observed directly, earlier studies resorted to interpreting two types of available experimental data: Immunohistology of GCs containing two phenotypically distinct B-cell populations, and antibody gene sequences of small B-cell samples from GCs. Based on a simple model, investigators concluded that a typical GC was seeded by 2-8 B cells, endorsing the current notion that GCs are oligoclonal from the onset. RESULTS: A re-evaluation of these data showed that the used simple model is not statistically consistent with the original data. From an analysis of the experimental system, we propose a new model for estimating GC clonal diversity, including the initially neglected sampling and measurement errors, and making more general assumptions. Consistency analysis with the new model yielded an estimation of sampling and measurement errors in the experimental data of 10-11% for one B-cell population and 62-64% for the other population, and an average number of 19-23 seeder B cells. An independent analysis of antibody gene sequences of small B-cell samples from GCs, using an adapted Yule estimator of diversity, yielded a minimum estimation of 20-30 GC founder B cells, confirming the previous results. CONCLUSIONS: Our new experimental-based model provides a highly improved method to estimate the clonal diversity of GCs from immunohistochemistry data of chimeric animals. Calculations based on this model, and validated by an independent approach, indicate that GCs most likely contain broadly varying numbers of different B cell clones, averaging 5- to 10-fold more clones than previously estimated. These findings, in line with recent results showing that GC sizes and life times are also subject to high variability, dramatically change the picture of GC dynamics.

Software tool for 3D extraction of germinal centers.

BACKGROUND: Germinal Centers (GC) are short-lived micro-anatomical structures, within lymphoid organs, where affinity maturation is initiated. Theoretical modeling of the dynamics of the GC reaction including follicular CD4+ T helper and the recently described follicular regulatory CD4+ T cell populations, predicts that the intensity and life span of such reactions is driven by both types of T cells, yet controlled primarily by follicular regulatory CD4+ T cells. In order to calibrate GC models, it is necessary to properly analyze the kinetics of GC sizes. Presently, the estimation of spleen GC volumes relies upon confocal microscopy images from 20-30 slices spanning a depth of ~ 20 - 50 µm, whose GC areas are analyzed, slice-by-slice, for subsequent 3D reconstruction and quantification. The quantity of data to be analyzed from such images taken for kinetics experiments is usually prohibitively large to extract semi-manually with existing software. As a result, the entire procedure is highly time-consuming, and inaccurate, thereby motivating the need for a new software tool that can automatically identify and calculate the 3D spot volumes from GC multidimensional images. RESULTS: We have developed pyBioImage, an open source cross platform image analysis software application, written in python with C extensions that is specifically tailored to the needs of immunologic research involving 4D imaging of GCs. The software provides 1) support for importing many multi-image formats, 2) basic image processing and analysis, and 3) the ExtractGC module, that allows for automatic analysis and visualization of extracted GC volumes from multidimensional confocal microscopy images. We present concrete examples of different microscopy image data sets of GC that have been used in experimental and theoretical studies of mouse model GC dynamics. CONCLUSIONS: The pyBioImage software framework seeks to be a general purpose image application for immunological research based on 4D imaging. The ExtractGC module uses a novel clustering algorithm for automatically extracting quantitative spatial information of a large number of GCs from a collection of confocal microscopy images. In addition, the software provides 3D visualization of the GCs reconstructed from the image stacks. The application is available for public use at http://sourceforge.net/projects/pybioimage/.

An automated algorithm for extracting functional immunologic V-genes from genomes in jawed vertebrates.

Variable (V) domains of immunoglobulins (Ig) and T cell receptors (TCR) are generated from genomic V gene segments (V-genes). At present, such V-genes have been annotated only within the genome of a few species. We have developed a bioinformatics tool that accelerates the task of identifying functional V-genes from genome datasets. Automated recognition is accomplished by recognizing key V-gene signatures, such as recombination signal sequences, size of the exon region, and position of amino acid motifs within the translated exon. This algorithm also classifies extracted V-genes into either TCR or Ig loci. We describe the implementation of the algorithm and validate its accuracy by comparing V-genes identified from the human and mouse genomes with known V-gene annotations documented and available in public repositories. The advantages and utility of the algorithm are illustrated by using it to identify functional V-genes in the rat genome, where V-gene annotation is still incomplete. This allowed us to perform a comparative human-rodent phylogenetic analysis based on V-genes that supports the hypothesis that distinct evolutionary pressures shape the TCRs and Igs V-gene repertoires. Our program, together with a user graphical interface, is available as open-source software, downloadable at http://code.google.com/p/vgenextract/.

Regulation of the germinal center reaction by Foxp3+ follicular regulatory T cells.

Follicular helper T (T(FH)) cells participate in humoral responses providing selection signals to germinal center B cells. Recently, expression of CXCR5, PD-1, and the transcription factor Bcl-6 has allowed the identification of T(FH) cells. We found that a proportion of follicular T cells, with phenotypic characteristics of T(FH) cells and expressing Foxp3, are recruited during the course of a germinal center (GC) reaction. These Foxp3(+) cells derive from natural regulatory T cells. To establish the in vivo physiologic importance of Foxp3(+) follicular T cells, we used CXCR5-deficient Foxp3(+) cells, which do not have access to the follicular region. Adoptive cell transfers of CXCR5-deficient Foxp3(+) cells have shown that Foxp3(+) follicular T cells are important regulators of the GC reaction following immunization with a thymus-dependent Ag. Our in vivo data show that Foxp3(+) follicular T cells can limit the magnitude of the GC reaction and also the amount of secreted Ag-specific IgM, IgG1, IgG2b, and IgA. Therefore, Foxp3(+) follicular regulatory T cells appear to combine characteristics of T(FH) and regulatory T cells for the control of humoral immune responses.

A Method to Analyze Models of the Dynamics of Germinal Centers.

Germinal centers (GC) are dynamic, short-lived anatomical structures generated within lymphoid follicles during immune responses to protein-containing antigens. There, follicular dendritic cells, antigen-specific B cells, and follicular T helper cells engage with each other in an antigen dependent way, setting into play a mini-evolutionary ecosystem that ultimately lead to antibody affinity maturation, with the resulting GC reaction following a rise-and-fall dynamics. The complexity of the cell-to-cell interaction processes makes very difficult to mechanistically understand the GC dynamics. Different mathematical or computational models have been or can be developed to help clarify the mechanisms driving and regulating the GC dynamics. However, the very important question of which are the dominant model parameters is not frequently studied for most of those models. Here we describe in detail one method to perform such a parameter analysis-known as parameter sensitivity analysis-which can be applied to many models of the GC dynamics.

Affinity Selection in Germinal Centers: Cautionary Tales and New Opportunities.

Our current quantitative knowledge of the kinetics of antibody-mediated immunity is partly based on idealized experiments throughout the last decades. However, new experimental techniques often render contradictory quantitative outcomes that shake previously uncontroversial assumptions. This has been the case in the field of T-cell receptors, where recent techniques for measuring the 2-dimensional rate constants of T-cell receptor-ligand interactions exposed results contradictory to those obtained with techniques measuring 3-dimensional interactions. Recently, we have developed a mathematical framework to rationalize those discrepancies, focusing on the proper fine-grained description of the underlying kinetic steps involved in the immune synapse. In this perspective article, we apply this approach to unveil potential blind spots in the case of B-cell receptors (BCR) and to rethink the interactions between B cells and follicular dendritic cells (FDC) during the germinal center (GC) reaction. Also, we elaborate on the concept of "catch bonds" and on the recent observations that B-cell synapses retract and pull antigen generating a "retracting force", and propose some testable predictions that can lead to future research.

Ovarian aging increases small extracellular vesicle CD81+ release in human follicular fluid and influences miRNA profiles.

Ovarian aging affects female reproductive potential and is characterized by alterations in proteins, mRNAs and non-coding RNAs inside the ovarian follicle. Ovarian somatic cells and the oocyte communicate with each other secreting different molecules into the follicular fluid, by extracellular vesicles. The cargo of follicular fluid vesicles may influence female reproductive ability; accordingly, analysis of extracellular vesicle content could provide information about the quality of the female germ cell.In order to identify the most significant deregulated microRNAs in reproductive aging, we quantified the small extracellular vesicles in human follicular fluid from older and younger women and analyzed the expression of microRNAs enclosed inside the vesicles. We found twice as many small extracellular vesicles in the follicular fluid from older women and several differentially expressed microRNAs. Correlating microRNA expression profiles with vesicle number, we selected 46 deregulated microRNAs associated with aging. Bioinformatic analyses allowed us to identify six miRNAs involved in TP53 signaling pathways. Specifically, miR-16-5p, miR214-3p and miR-449a were downregulated and miR-125b, miR-155-5p and miR-372 were upregulated, influencing vesicle release, oocyte maturation and stress response. We believe that this approach allowed us to identify a battery of microRNAs strictly related to female reproductive aging.

A Sensitivity Analysis Comparison of Three Models for the Dynamics of Germinal Centers.

Germinal centers (GCs) are transient anatomical microenvironments where antibody affinity maturation and memory B cells generation takes place. In the past, models of Germinal Center (GC) dynamics have focused on understanding antibody affinity maturation rather than on the main mechanism(s) driving their rise-and-fall dynamics. Here, based on a population dynamics model core, we compare three mechanisms potentially responsible for this GC biphasic behavior dependent on follicular dendritic cell (FDC) maturation, follicular T helper (Tfh) cell maturation, and antigen depletion. Analyzing the kinetics of B and T cells, as well as its parameter sensitivities, we found that only the FDC-maturation-based model could describe realistic GC dynamics, whereas the simple Tfh-maturation and antigen-depletion mechanisms, as implemented here, could not. We also found that in all models the processes directly related to Tfh cell kinetics have the highest impact on GC dynamics. This suggests the existence of some still unknown mechanism(s) tuning GC dynamics by affecting Tfh cell response to proliferation-inducing stimuli.

Assessing methods for blood cell cytotoxic responses to inorganic nanoparticles and nanoparticle aggregates.

Inorganic nanoparticles (NPs) show great potential for medicinal therapy. However, biocompatibility studies are essential to determine if they are safe. Here, five different NPs are compared for their cytotoxicity, internalization, aggregation in medium, and reactive oxygen species (ROS) production, using tumoral and normal human blood cells. Differences depending on the cell type are analyzed, and no direct correlation between ROS production and cell toxicity is found. Results are discussed with the aim of standardizing the procedures for the evaluation of the toxicity.

Cancer cell mitochondria are direct proapoptotic targets for the marine antitumor drug lamellarin D.

Lamellarin D is a marine alkaloid with a pronounced cytotoxicity against a large panel of cancer cell lines and is a potent inhibitor of topoisomerase I. However, lamellarin D maintains a marked cytotoxicity toward cell lines resistant to the reference topoisomerase I poison camptothecin. We therefore hypothesized that topoisomerase I is not the only cellular target for the drug. Using complementary cell-based assays, we provide evidence that lamellarin D acts on cancer cell mitochondria to induce apoptosis. Lamellarin D, unlike camptothecin, induces early disruption of the inner mitochondrial transmembrane potential (Deltapsi(m)) in the P388 leukemia cell line. The functional alterations are largely prevented by cyclosporin A, an inhibitor of the mitochondrial permeability transition (MPT), but not by the inhibitor of caspases, benzyloxycarbonyl-Val-Ala-Asp(Ome)-fluoromethylketone. Deltapsi(m) disruption is associated with mitochondrial swelling and cytochrome c leakage. Using a reliable real-time flow cytometric monitoring of Deltapsi(m) and swelling of mitochondria isolated from leukemia cells, we show that lamellarin D has a direct MPT-inducing effect. Furthermore, mitochondria are required in a cell-free system to mediate lamellarin D-induced nuclear apoptosis. The direct mitochondrial effect of lamellarin D accounts for the sensitivity of topoisomerase I-mutated P388CPT5 cells resistant to camptothecin. Interestingly, a tumor-active analogue of lamellarin D, designated PM031379, also exerts a direct proapoptotic action on mitochondria, with a more pronounced activity toward mitochondria of tumor cell lines compared with nontumor cell lines. Altogether, this work reinforces the pharmacologic interest of the lamellarins and defines lamellarin D as a lead in the search for treatments against chemoresistant cancer cells.

A unifying mathematical framework for experimental TCR-pMHC kinetic constants.

Receptor binding and triggering are central in Immunology as T cells activated through their T cell receptors (TCR) by protein antigens orchestrate immune responses. In order to understand receptor-ligand interactions, many groups working with different experimental techniques and assays have generated a vast body of knowledge during the last decades. However, in recent years a type of assays, referred to as two-dimensional or membrane-to-membrane, has questioned our current understanding of the role of different kinetic constants (for instance, on- versus off-rate constants) on TCR-ligand interaction and subsequent T cell activation. Here we present a general mathematical framework that provides a unifying umbrella to relate fundamental and effective (or experimentally determined) kinetic constants, as well as describe and compare state-of-the-art experimental methods. Our framework is able to predict the correlations between functional output, such as 1/EC50, and effective kinetic constants for a range of different experimental assays (in two and three dimensions). Furthermore, our approach can be applied beyond Immunology, and serve as a "translation method" for the biochemical characterization of receptor-ligand interactions.

T follicular helper and T follicular regulatory cells have different TCR specificity.

Immunization leads to the formation of germinal centres (GCs) that contain both T follicular helper (Tfh) and T follicular regulatory (Tfr) cells. Whether T-cell receptor (TCR) specificity defines the differential functions of Tfh and Tfr cells is unclear. Here we show that antigen-specific T cells after immunization are preferentially recruited to the GC to become Tfh cells, but not Tfr cells. Tfh cells, but not Tfr cells, also proliferate efficiently on restimulation with the same immunizing antigen in vitro. Ex vivo TCR repertoire analysis shows that immunization induces oligoclonal expansion of Tfh cells. By contrast, the Tfr pool has a TCR repertoire that more closely resembles that of regulatory T (Treg) cells. Our data thus indicate that the GC Tfh and Tfr pools are generated from distinct TCR repertoires, with Tfh cells expressing antigen-responsive TCRs to promote antibody responses, and Tfr cells expressing potentially autoreactive TCRs to suppress autoimmunity.

Variolin B and its derivate deoxy-variolin B: new marine natural compounds with cyclin-dependent kinase inhibitor activity.

Variolin B (VAR-B) is a natural product isolated from the sponge Kirkpatrickia variolosa, found in Antarctica. VAR-B has been shown previously to possess potent pro-apoptotic activity. This study was undertaken to investigate the mechanism of action of chemically synthesised VAR-B and its analogue deoxy-variolin B (dVAR-B). In different human cancer cell lines both compounds inhibited colony formation, caused cell cycle perturbations and induced apoptosis at concentrations ranging from 0.1 to 2 microM. LoVo/Dx cells over-expressing Pgp were equally sensitive as the parental cell line to VAR-B and dVAR-B, indicating that variolins are not substrates of Pgp. Although variolins induced an increase in the levels of p53 with an increase in p21, their cytotoxicities did not appear to be dependent on p53 status as their potency was comparable in cells with wild-type p53, or in sub-lines with inactivated p53. Both VAR-B and dVAR-B prevent the cells from entering S phase, blocking cells in G1 and cause an accumulation of cells in G2. The apoptosis induced by VAR-B and dVAR-B occurs very rapidly in some cell lines (e.g., Jurkat leukaemia cells) and is already evident 4h after the beginning of treatment. Although intercalation of dVAR-B in DNA has been demonstrated, neither VAR-B nor dVAR-B produce detectable breaks in DNA. These results are consistent with the in vitro biochemical assays that also demonstrated that dVAR-B is not topoisomerase I or II poison. Instead, each of these variolins appears to inhibit cyclin-dependent kinases (CDKs) in the muM range. CDK1-cyclin B, CDK2-cyclin A and CDK2/cylin E complexes were inhibited in a range of concentrations lower than those required to inhibit the activity of CDK4/cyclin D or CDK7/cyclin H complexes. In conclusion, these variolins are a new class of CDK inhibitors that activate apoptosis in a p53-independent fashion and thus they may be effective against tumours with p53 mutations or deletions.

Immune responses to polysaccharides: lessons from humans and mice.

This review focuses on the immune response to non-conjugated and conjugated polysaccharide vaccines derived from encapsulated pathogens, such as Streptococcus pneumoniae, Haemophilus influenzae and Neisseria meningitidis. Special attention is paid to a number of side effects observed following the use of some of these vaccines. For example, we discuss the long-lasting specific refractoriness induced by unconjugated polysaccharides, and the absence of an effective immune response in adults vaccinated with some conjugated vaccines. We argue that studies performed in the mouse model can help to understand those paradoxical effects observed in humans, and the mechanisms underlying such processes.

When three is not a crowd: a Crossregulation model of the dynamics and repertoire selection of regulatory CD4+ T cells.

Regulatory CD4(+) T cells, enriched in the CD25 pool of healthy individuals, mediate natural tolerance and prevent autoimmune diseases. Despite their fundamental and potential clinical significance, regulatory T (T(R)) cells have not yet been incorporated in a coherent theory of the immune system. This article reviews experimental evidence and theoretical arguments supporting a model of T(R) cell dynamics, uncovering some of its most relevant biological implications. According to this model, the persistence and expansion of T(R) cell populations depend strictly on specific interactions they make with antigen-presenting cells (APCs) and conventional effector T (T(E)) cells. This three-partner crossregulation imposes that T(R) cells feed on the specific autoimmune activities they suppress, with implications ranging from their interactions with other cells to their repertoire selection in the periphery and in the thymus, and to the relationship between these cells and the innate immune system. These implications stem from the basic prediction that the peripheral dynamics sort the CD4(+) T-cell repertoire into two subsets: a less diverse set of small clones of autoreactive effector and regulatory cells that regulate each other's growth, and a more diverse set of barely autoreactive T(E) cell clones, whose expansion is limited only by APC availability. It is argued that such partitioning of the repertoire sets the ground for self-non-self discrimination.

Re-evaluating the recycling hypothesis in the germinal centre.

Mathematical models have been used to study different aspects of the germinal centre reaction, in particular, affinity maturation of antibodies and the hypothesis of recycling. So far, interpretation of several theoretical and experimental results has pointed to the existence of recycling. However, theoretical models have seldom been compared with experimental data from specific immune responses and the potential relevance of recycling in the germinal centre is still an open problem. In this article, we propose a model without recycling that takes into account selection mechanisms that were previously uncovered experimentally. We apply the model to several experimental systems that use different Ag and compare the results with experimental data of affinity maturation whenever available. The results obtained for a primary immune response to the hapten (4-hydroxy-3-nitrophenyl)-acetyl show that recycling is not a necessary mechanism to achieve the level of affinity maturation observed in germinal centre reactions. Similar levels of affinity maturation are obtained for other responses, although for antibodies involving several affinity-enhancing mutations the affinity maturation obtained with the model is much lower. Interpretation of these results and consequences towards the concept of recycling are discussed.

Modelling two possible mechanisms for the regulation of the germinal center dynamics.

Research on the germinal center has tried to unravel the mechanisms that control its dynamics. In this study we focus on the termination of the germinal center reaction, which is still an open problem. We propose two hypothetical biological mechanisms that may be responsible for the control of germinal center dynamics and analyze them through mathematical models. The first one is based on the differentiation of follicular dendritic cells and/or T cells. Interaction of these cells in the differentiated state with germinal center B cells would promote B cell differentiation into memory B cells and Ab-forming cells, ending the germinal center reaction. The second mechanism applies only to a scenario without recycling and consists of the decay of a hypothetical proliferation signal for centroblasts that limits the number of cell divisions. Each of the models makes predictions that can be experimentally tested.