How instruction and feedback can select the appropriate T helper response

The decision of the immune system to trigger immune responses that are, respectively, induced by Th1 or Th2 effectors is a critical one, because it profoundly influences disease outcome. We have recently constructed a mathematical model of Th1-Th2-pathogen interactions that shows that the major decisional events can often be successfully determined by the intrinsic behaviour of the T helper system itself. For certain dangerous types of pathogens, however, which replicate rapidly or have developed strategies to evade the immune response, additional stimuli may be necessary. As a possible mechanism for the decision-making process innate immune recognition has been proposed. Here we present an enlarged version of our model, which incorporates signals created from the innate immune system after pathogen recognition. The model analysis suggests that there is fault-tolerance of the T helper system to incorrect Th1 signals. In the presence of incorrect Th1 stimuli an initial Th1 response is shifted to the correct Th2-dominated response owing to the intrinsic T helper dynamics. By contrast, according to our model there is no fault-tolerance for incorrect Th2 signals. In fact, if timing is unimportant then Th2 signals are superfluous since the intrinsic T helper dynamics provide an automatic switch to Th2 if Th1 effectors fail to control the pathogen. Th2 signals may, however, be required to accelerate the onset of the Th2 response. Additionally, we discuss the role of feedback where successful pathogen destruction leads to up-regulation of activation of the effective T helper type. As one possibility we examine the role of CpG motifs as indicators for successful pathogen destruction. Differences between instructive and feedback mechanisms are highlighted.     

Architectural analysis and modelling of the branching process of the young oil-palm root system

An architectural analysis of the root system of young oil-palm (Elaeis guineensis Jacq.) seedlings was made. In this analysis, root branching was modelled by a Markov chain (discrete-time, discrete-state space stochastic process). This study has been realized on radicles of young oil-palm seedlings which were considered as main axes which branch. We defined an elementary length unit as the smallest length between two successive lateral roots. The model was based on the analysis of a sequence of events, each event being indexed by the rank of the elementary length unit on the main axis. An event was defined as the state of the length unit, chosen between unbranched state and three branched-state categories. The branching process of the oil-palm radicle was modelled by a four-state first-order Markov chain. Consequently, the state of an elementary length unit depended only on the state of the previous one. The Markov chain was homogeneous, i.e. the transition probabilities did not depend on the rank of the elementary length unit.This study allowed us to identify a probabilistic model of root branching which was the first step in the elaboration of a stochastic model of the architecture of the oil-palm root system.     

A stochastic model for the sigmoidal behaviour of cooperative biological systems

A stochastic model for cooperative transitions in biological systems based on a Markov chain is proposed. This model requires only two parameters, the mean probability, p, and the coupling capacity, Deltap, which measure the probability of forming a new weak bond depending on the number of similar bonds already formed and it is also responsible for the transition. In this paper we show how the model works for a large number of identical molecules and how it can be useful for studying the noise around the centre of the transition where, increasing the degree of cooperativity, i.e. the number n in the well-known Hill equation, the width of the noise increases along with its fractal dimension. A simple relationship between the degree of cooperativity and the parameter Deltap is proposed, suggesting that the cooperativity of real biological transitions is related to the coupling capacity Deltap of the present model.     

Leishmania major infection: the overture

Local infection of mice with Leishmania major results in either healing or death depending on the preferential action of Th1 or Th2 T helper cells, respectively. Although the parasite-induced T-cell responses and their consequences for the disease are well understood, relatively little is known about the initial events that kindle the adaptive immune response. Werner Salbach and Tamás Laskay here discuss how differences in parasites spreading from the site of infection to different immune organs during the first 10-24 hours and, in consequence, the 'where and when' of the first encounter of Leishmania with the cells of the immune system may well be the starting point for the development of resistance or susceptibility.     

Covariate Adjustment of Event Histories Estimated from Markov Chains: The Additive Approach

Markov chain models are frequently used for studying event histories that include transitions between several states. An empirical transition matrix for nonhomogeneous Markov chains has previously been developed, including a detailed statistical theory based on counting processes and martingales. In this article, we show how to estimate transition probabilities dependent on covariates. This technique may, e.g., be used for making estimates of individual prognosis in epidemiological or clinical studies. The covariates are included through nonparametric additive models on the transition intensities of the Markov chain. The additive model allows for estimation of covariate-dependent transition intensities, and again a detailed theory exists based on counting processes. The martingale setting now allows for a very natural combination of the empirical transition matrix and the additive model, resulting in estimates that can be expressed as stochastic integrals, and hence their properties are easily evaluated. Two medical examples will be given. In the first example, we study how the lung cancer mortality of uranium miners depends on smoking and radon exposure. In the second example, we study how the probability of being in response depends on patient group and prophylactic treatment for leukemia patients who have had a bone marrow transplantation. A program in R and S-PLUS that can carry out the analyses described here has been developed and is freely available on the Internet.     

Therapeutic potential of phosphodiesterase-4 and -3 inhibitors in Th1-mediated autoimmune diseases

Phosphodiesterase-4 (PDE4) inhibitors have the potential to modulate immune responses from the Th1 toward the Th2 phenotype and are considered candidate therapies for Th1-mediated autoimmune disorders. However, depending on the model and cell types employed, studies of atopic individuals have come to the opposite conclusion, i.e., that PDE inhibitors may be beneficial in asthma. Using in vitro immunopharmacologic techniques we analyzed the effects of PDE4 and PDE3 inhibitors on human immune cells to address these discrepancies and broaden our understanding of their mechanism of action. Our results indicate that PDE inhibitors have complex inhibitory effects within in vivo achievable concentration ranges on Th1-mediated immunity, whereas Th2-mediated responses are mostly unaffected or enhanced. The Th2 skewing of the developing immune response is explained by the effects of PDE inhibitors on several factors contributing to T cell priming: the cytokine milieu; the type of costimulatory signal, i.e., up-regulation of CD86 and down-regulation of CD80; and the Ag avidity. The combination of PDE4 and PDE3 inhibitors expresses synergistic effects and may broaden the therapeutic window. Finally, we observed a differential sensitivity to PDE inhibition in autoreactive vs foreign Ag-specific T cells and cells derived from multiple sclerosis patients vs those derived from healthy donors. This suggests that PDE inhibition weakens the strength of the T cell stimulus and corrects the underlying disease-associated cytokine skew in T cell-mediated autoimmune disorders. These new findings broaden the understanding of the immunomodulatory actions of PDE inhibitors and underscore their promising drug profile for the treatment of autoimmune disorders.     

Bayesian restoration of a hidden Markov chain with applications to DNA sequencing.

Hidden Markov models (HMMs) are a class of stochastic models that have proven to be powerful tools for the analysis of molecular sequence data. A hidden Markov model can be viewed as a black box that generates sequences of observations. The unobservable internal state of the box is stochastic and is determined by a finite state Markov chain. The observable output is stochastic with distribution determined by the state of the hidden Markov chain. We present a Bayesian solution to the problem of restoring the sequence of states visited by the hidden Markov chain from a given sequence of observed outputs. Our approach is based on a Monte Carlo Markov chain algorithm that allows us to draw samples from the full posterior distribution of the hidden Markov chain paths. The problem of estimating the probability of individual paths and the associated Monte Carlo error of these estimates is addressed. The method is illustrated by considering a problem of DNA sequence multiple alignment. The special structure for the hidden Markov model used in the sequence alignment problem is considered in detail. In conclusion, we discuss certain interesting aspects of biological sequence alignments that become accessible through the Bayesian approach to HMM restoration.     

Decision-making by the immune response

Decisions by uncommitted cells to differentiate down one lineage pathway or another is fundamental to developmental biology. In the immune system, lymphocyte precursors commit to T- or B-cell lineages and T-cell precursors to CD4 or CD8 independently of foreign antigen. T and B cells must also decide whether or not to respond to antigen and when a response is initiated, what sort of response to make such as the type of antibody, CD4 or CD8, and CD4 Th1 or Th2. The two basic mechanisms for these decision-making processes are selection and instruction. Selection depends on prior stochastic production of precommitted cells, which are then selected to respond by an appropriate signal; for example, CD8 and CD4 responses selected by peptide presented in association with major histocompatibility complex class I or II. In contrast, instruction occurs when an uncommitted precursor embarks upon a differentiation pathway in response to a particular set of signals; for example, Th1 and Th2 lineage commitment. In this paper, the signals that determine Th1 and Th2 differentiation are examined with a mathematical model and shown to act as a bistable switch permitting either Tbet or Gata3 to be expressed in an individual cell but not both. The model is used to show how the Tbet Gata3 network within an individual cell interacts with cytokine signals between cells and suggests how Th1 and Th2 lineage commitment can become irreversible. These considerations provide an example of how mathematical models can be used to gain a better understanding of lymphocyte differentiation in an immune response.     

Design,synthesis, and immunologic evaluation of vaccine adjuvant conjugates based on QS-21 and tucaresol

Immunoadjuvants are used to potentiate the activity of modern subunit vaccines that are based on molecular antigens. An emerging approach involves the combination of multiple adjuvants in a single formulation to achieve optimal vaccine efficacy. Herein, to investigate such potential synergies, we synthesized novel adjuvant conjugates based on the saponin natural product QS-21 and the aldehyde tucaresol via chemoselective acylation of an amine at the terminus of the acyl chain domain in QS saponin variants. In a preclinical mouse vaccination model, these QS saponin–tucaresol conjugates induced antibody responses similar to or slightly higher than those generated with related QS saponin variants lacking the tucaresol motif. The conjugates retained potent adjuvant activity, low toxicity, and improved activity–toxicity profiles relative to QS-21 itself and induced IgG subclass profiles similar to those of QS-21, indicative of both Th1 cellular and Th2 humoral immune responses. This study opens the door to installation of other substituents at the terminus of the acyl chain domain to develop additional QS saponin conjugates with desirable immunologic properties.     

A compact statistical model of the song syntax in Bengalese finch

Songs of many songbird species consist of variable sequences of a finite number of syllables. A common approach for characterizing the syntax of these complex syllable sequences is to use transition probabilities between the syllables. This is equivalent to the Markov model, in which each syllable is associated with one state, and the transition probabilities between the states do not depend on the state transition history. Here we analyze the song syntax in Bengalese finch. We show that the Markov model fails to capture the statistical properties of the syllable sequences. Instead, a state transition model that accurately describes the statistics of the syllable sequences includes adaptation of the self-transition probabilities when states are revisited consecutively, and allows associations of more than one state to a given syllable. Such a model does not increase the model complexity significantly. Mathematically, the model is a partially observable Markov model with adaptation (POMMA). The success of the POMMA supports the branching chain network model of how syntax is controlled within the premotor song nucleus HVC, but also suggests that adaptation and many-to-one mapping from the syllable-encoding chain networks in HVC to syllables should be included in the network model.     

Memory and effector T cells modulate subsequently primed immune responses to unrelated antigens

Memory and effector T cells modulate subsequently primed T cell responses to the same antigen. However, little is known about the impact of pre-existing memory and effector T cell immunity on subsequently primed immune responses to unrelated antigens. Here, we show that an antigen-primed first wave of Th1 and Th2 immunity enhanced or inhibited the subsequently primed T cell immunity to an unrelated antigen, depending on whether the second antigen was administered in the same or opposite type of adjuvant. The regulatory effects of the first wave of T cell immunity on the subsequent T cell responses to an unrelated antigen attenuated over time. Notably, following challenge with the second antigen, there was a mutual cross-regulation between the first and second wave of humoral responses to unrelated antigens. Thus, immunization with one antigen not only primes immune responses to that antigen, but also influences subsequently primed immune responses to unrelated antigens.     

Schistosoma mansoni and alpha-galactosylceramide: prophylactic effect of Th1 Immune suppression in a mouse model of Graves' hyperthyroidism

Graves' hyperthyroidism, an organ-specific autoimmune disease mediated by stimulatory thyrotropin receptor (TSHR) autoantibodies, has been considered a Th2-dominant disease. However, recent data with mouse Graves' models are conflicting. For example, we recently demonstrated that injection of BALB/c mice with adenovirus coding the TSHR induced Graves' hyperthyroidism characterized by mixed Th1 and Th2 immune responses against the TSHR, and that transient coexpression of the Th2 cytokine IL-4 by adenovirus skewed Ag-specific immune response toward Th2 and suppressed disease induction. To gain further insight into the relationship between immune polarization and Graves' disease, we evaluated the effect of Th2 immune polarization by helminth Schistosoma mansoni infection and alpha-galactosylceramide (alpha-GalCer), both known to bias the systemic immune response to Th2, on Graves' disease. S. mansoni infection first induced mixed Th1 and Th2 immune responses to soluble worm Ags, followed by a Th2 response to soluble egg Ags. Prior infection with S. mansoni suppressed the Th1-type anti-TSHR immune response, as demonstrated by impaired Ag-specific IFN-gamma secretion of splenocytes and decreased titers of IgG2a subclass anti-TSHR Abs, and also prevented disease development. Similarly, alpha-GalCer suppressed Ag-specific splenocyte secretion of IFN-gamma and prevented disease induction. However, once the anti-TSHR immune response was fully induced, S. mansoni or alpha-GalCer was ineffective in curing disease. These data support the Th1 theory in Graves' disease and indicate that suppression of the Th1-type immune response at the time of Ag priming may be crucial for inhibiting the pathogenic anti-TSHR immune response.     

Timing of IFN-beta exposure during human dendritic cell maturation and naive Th cell stimulation has contrasting effects on Th1 subset generation: a role for IFN-beta-mediated regulation of IL-12 family cytokines and IL-18 in naive Th cell differentiation

Type I IFNs, IFN-alpha and IFN-beta, are early effectors of innate immune responses against microbes that can also regulate subsequent adaptive immunity by promoting antimicrobial Th1-type responses. In contrast, the ability of IFN-beta to inhibit autoimmune Th1 responses is thought to account for some of the beneficial effects of IFN-beta therapy in the treatment of relapsing remitting multiple sclerosis. To understand the basis of the paradoxical effects of IFN-beta on the expression of Th1-type immune responses, we developed an in vitro model of monocyte-derived dendritic cell (DC)-dependent, human naive Th cell differentiation, in which one can observe both positive and negative effects of IFN-beta on the generation of Th1 cells. In this model we found that the timing of IFN-beta exposure determines whether IFN-beta will have a positive or a negative effect on naive Th cell differentiation into Th1 cells. Specifically, the presence of IFN-beta during TNF-alpha-induced DC maturation strongly augments the capacity of DC to promote the generation of IFN-gamma-secreting Th1 cells. In contrast, exposure to IFN-beta during mature DC-mediated primary stimulation of naive Th cells has the opposite effect, in that it inhibits Th1 cell polarization and promotes the generation of an IL-10-secreting T cell subset. Studies with blocking mAbs and recombinant cytokines indicate that the mechanism by which IFN-beta mediates these contrasting effects on Th1 cell generation is at least in part by differentially regulating DC expression of IL-12 family cytokines (IL-12 and/or IL-23, and IL-27) and IL-18.     

Induction of antigen-specific Th1-biased immune responses by plasmid DNA in schistosoma-infected mice with a preexistent dominant Th2 immune profile

A requisite for vaccines to confer protection against intracellular infections such as Human Immunodeficiency Virus or Mycobacterium tuberculosis is their capacity to induce Th1 immune responses. However, they may fail to do so in Africa and South East Asia, where most individuals have a dominant preexistent Th2 immune profile, due to persistent helminthic parasitic infections, which may undermine any Th1 response. It is well established that DNA vaccines induce strong Th1 biased immune responses against an encoded antigen, depending on the route and mode of immunization. Here, we demonstrate that intradermal immunization with plasmid DNA encoding beta-gal (pCMV-LacZ) of Schistosoma-infected mice, with preexistent dominant Th2 immune background, induce a strong Th1 anti-beta-gal response, as opposed to immunized with beta-gal only. Importantly, the established protective Th2 immune response to schistosomes was not disrupted. These findings strongly support the possibility of using plasmid DNA as a Th1 inducing adjuvant when immunizing populations with a strong preexistent Th2 immune profile.     

High expression of IL-22 suppresses antigen-induced immune responses and eosinophilic airway inflammation via an IL-10-associated mechanism

Allergic inflammation in the airway is generally considered a Th2-type immune response. However, Th17-type immune responses also play important roles in this process, especially in the pathogenesis of severe asthma. IL-22 is a Th17-type cytokine and thus might play roles in the development of allergic airway inflammation. There is increasing evidence that IL-22 can act as a proinflammatory or anti-inflammatory cytokine depending on the inflammatory context. However, its role in Ag-induced immune responses is not well understood. This study examined whether IL-22 could suppress allergic airway inflammation and its mechanism of action. BALB/c mice were sensitized and challenged with OVA-Ag to induce airway inflammation. An IL-22-producing plasmid vector was delivered before the systemic sensitization or immediately before the airway challenge. Delivery of the IL-22 gene before sensitization, but not immediately before challenge, suppressed eosinophilic airway inflammation. IL-22 gene delivery suppressed Ag-induced proliferation and overall cytokine production in CD4(+) T cells, indicating that it could suppress Ag-induced T cell priming. Antagonism of IL-22 by IL-22-binding protein abolished IL-22-induced immune suppression, suggesting that IL-22 protein itself played an essential role. IL-22 gene delivery neither increased regulatory T cells nor suppressed dendritic cell functions. The suppression by IL-22 was abolished by deletion of the IL-10 gene or neutralization of the IL-10 protein. Finally, IL-22 gene delivery increased IL-10 production in draining lymph nodes. These findings suggested that IL-22 could have an immunosuppressive effect during the early stage of an immune response. Furthermore, IL-10 plays an important role in the immune suppression by IL-22.     

PGI2 as a regulator of CD4+ subset differentiation and function

Prostaglandin (PG)I(2) has important regulatory functions on the innate and adaptive immune systems. Recent experimental evidence reveals that PGI(2) modulates the development and function of CD4+ T cells subsets, including Th1, Th2, and Th17 cell responses. In vitro and in vivo studies support that PGI(2) generally has an inhibitory effect on Th1 and Th2 activation, differentiation, and cytokine production. In contrast, PGI(2) seems to enhance Th17-favoring polarization conditions, resulting in Th17 cytokine production. Therefore, PGI(2) may either promote or inhibit individual CD4+ cell subsets and impact adaptive immune responses.     

Stochastic models for virus and immune system dynamics

New stochastic models are developed for the dynamics of a viral infection and an immune response during the early stages of infection. The stochastic models are derived based on the dynamics of deterministic models. The simplest deterministic model is a well-known system of ordinary differential equations which consists of three populations: uninfected cells, actively infected cells, and virus particles. This basic model is extended to include some factors of the immune response related to Human Immunodeficiency Virus-1 (HIV-1) infection. For the deterministic models, the basic reproduction number, R₀, is calculated and it is shown that if R₀<1, the disease-free equilibrium is locally asymptotically stable and is globally asymptotically stable in some special cases. The new stochastic models are systems of stochastic differential equations (SDEs) and continuous-time Markov chain (CTMC) models that account for the variability in cellular reproduction and death, the infection process, the immune system activation, and viral reproduction. Two viral release strategies are considered: budding and bursting. The CTMC model is used to estimate the probability of virus extinction during the early stages of infection. Numerical simulations are carried out using parameter values applicable to HIV-1 dynamics. The stochastic models provide new insights, distinct from the basic deterministic models. For the case R₀>1, the deterministic models predict the viral infection persists in the host. But for the stochastic models, there is a positive probability of viral extinction. It is shown that the probability of a successful invasion depends on the initial viral dose, whether the immune system is activated, and whether the release strategy is bursting or budding.     

Analysing grouping of nucleotides in DNA sequences using lumped processes constructed from Markov chains

The most commonly used models for analysing local dependencies in DNA sequences are (high-order) Markov chains. Incorporating knowledge relative to the possible grouping of the nucleotides enables to define dedicated sub-classes of Markov chains. The problem of formulating lumpability hypotheses for a Markov chain is therefore addressed. In the classical approach to lumpability, this problem can be formulated as the determination of an appropriate state space (smaller than the original state space) such that the lumped chain defined on this state space retains the Markov property. We propose a different perspective on lumpability where the state space is fixed and the partitioning of this state space is represented by a one-to-many probabilistic function within a two-level stochastic process. Three nested classes of lumped processes can be defined in this way as sub-classes of first-order Markov chains. These lumped processes enable parsimonious reparameterizations of Markov chains that help to reveal relevant partitions of the state space. Characterizations of the lumped processes on the original transition probability matrix are derived. Different model selection methods relying either on hypothesis testing or on penalized log-likelihood criteria are presented as well as extensions to lumped processes constructed from high-order Markov chains. The relevance of the proposed approach to lumpability is illustrated by the analysis of DNA sequences. In particular, the use of lumped processes enables to highlight differences between intronic sequences and gene untranslated region sequences.