Translation initiation factor eIF2Bε promotes Wnt-mediated clonogenicity and global translation in intestinal epithelial cells.

Modulation of global mRNA translation, which is essential for intestinal stem cell function, is controlled by Wnt signaling. Loss of tumor supressor APC in stem cells drives adenoma formation through hyperactivion of Wnt signaling and dysregulated translational control. It is unclear whether factors that coordinate global translation in the intestinal epithelium are needed for APC-driven malignant transformation. Here we identified nucleotide exchange factor eIF2Bε as a translation initiation factor involved in Wnt-mediated intestinal epithelial stemness. Using eIF2BεArg191His mice with a homozygous point mutation that leads to dysfunction in the enzymatic activity, we demonstrate that eIF2Bε is involved in small intestinal crypt formation, stemness marker expression, and secreted Paneth cell-derived granule formation. Wnt hyperactivation in ex vivo eIF2BεArg191His organoids, using a GSK3ß inhibitor to mimic Apc driven transformation, shows that eIF2Bε is essential for Wnt-mediated clonogenicity and associated increase of the global translational capacity. Finally, we observe high eIF2Bε expression in human colonic adenoma tissues, exposing eIF2Bε as a potential target of CRC stem cells with aberrant Wnt signaling.

Induction of appropriate Th-cell phenotypes: cellular decision-making in heterogeneous environments.

Helper T (Th)-cell differentiation is a key event in the development of the adaptive immune response. By the production of a range of cytokines, Th cells determine the type of immune response that is raised against an invading pathogen. Th cells can adopt many different phenotypes, and Th-cell phenotype decision-making is crucial in mounting effective host responses. This review discusses the different Th-cell phenotypes that have been identified and how Th cells adopt a particular phenotype. The regulation of Th-cell phenotypes has been studied extensively using mathematical models, which have explored the role of regulatory mechanisms such as autocrine cytokine signalling and cross-inhibition between self-activating transcription factors. At the single cell level, Th responses tend to be heterogeneous, but corrections can be made soon after T-cell activation. Although pathogens and the innate immune system provide signals that direct the induction of Th-cell phenotypes, these instructive mechanisms could be easily subverted by pathogens. We discuss that a model of success-driven feedback would select the most appropriate phenotype for clearing a pathogen. Given the heterogeneity in the induction phase of the Th response, such a success-driven feedback loop would allow the selection of effective Th-cell phenotypes while terminating incorrect responses.

Identification of helper T cell master regulator candidates using the polar score method.

The T helper paradigm is currently being revised from the Th1-Th2 dichotomy to a multi-state paradigm involving a number of different cell phenotypes. Transcriptional profiling using microarrays has been used to study the development of these phenotypes. There is however no clear consensus on how to approach the analysis of this data, especially in the context of cells that are triggered to expand rapidly, and massively change their gene expression pattern. We develop a method we call 'polar score' to identify genes that are related to T helper cell polarization. This method is designed to identify polarizing genes in a set where many genes change expression. To illustrate the use of this technique, we apply it to published T cell microarray data and compare it to conventional analysis methods. With the new method, we find evidence for the existence of IL9 producing T cells ('Th9 cells') that are induced by a combination of TGFß and IL4. We identify several candidate master regulator genes for this phenotype. Furthermore, treatment with TGFß and IL12 results in a Treg and Th17 hybrid cell phenotype.

Quantifying how MHC polymorphism prevents pathogens from adapting to the antigen presentation pathway.

The classical antigen presentation pathway consists of two monomorphic (proteasome and TAP) and one polymorphic components (MHC Class I). Viruses can escape CTL responses by mutating an epitope so that it is no longer correctly processed by the pathway. Whereas escape mutations that affect MHC binding are typically no longer under selection pressure in the next host of the virus (as hosts differ in their MHC alleles), escape mutations that affect the antigen processing of epitope precursors prevent the use of those epitope precursors by any of the MHC alleles in a host population. Viruses might therefore be under selection pressure to adapt to the monomorphic proteasome and TAP. We designed an agent-based model of a host population, in which an HIV-1 like virus adapts to the antigen presentation pathway of individual hosts, as the virus spreads through the population. We studied how the polymorphism of the MHC and the monomorphism of the proteasome and TAP affected the level of adaptation to the host population that the virus could reach. We found that due to the polymorphism and high specificity of the MHC class I molecules, the CTL epitopes that are targeted by the CTL responses of different hosts do not share many epitope precursors. Therefore, escape mutations in epitope precursors are frequently released from immune selection pressure, and can revert back to the virus wildtype sequence. As a result, the selection pressure on the virus to adapt to the proteasome and TAP is relatively small, which explains the low level of adaptation of the virus to the monomorphic steps in the antigen presentation pathway.

Process noise: an explanation for the fluctuations in the immune response during acute viral infection.

The parameters of the immune response dynamics are usually estimated by the use of deterministic ordinary differential equations that relate data trends to parameter values. Since the physical basis of the response is stochastic, we are investigating the intensity of the data fluctuations resulting from the intrinsic response stochasticity, the so-called process noise. Dealing with the CD8+ T-cell responses of virus-infected mice, we find that the process noise influence cannot be neglected and we propose a parameter estimation approach that includes the process noise stochastic fluctuations. We show that the variations in data can be explained completely by the process noise. This explanation is an alternative to the one resulting from standard modeling approaches which say that the difference among individual immune responses is the consequence of the difference in parameter values.

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A 4-week-old girl presented with annular skin lesions caused by neonatal lupus syndrome.

The race between initial T-helper expansion and virus growth upon HIV infection influences polyclonality of the response and viral set-point.

Infection with HIV is characterized by very diverse disease-progression patterns across patients, associated with a wide variation in viral set-points. Progression is a multifactorial process, but an important role has been attributed to the HIV-specific T-cell response. To explore the conditions under which different set-points may be explained by differences in initial CD4 and CD8 T-cell responses and virus inoculum, we have formulated a model assuming that HIV-specific CD4 cells are both targets for infection and mediators of a monoclonal or polyclonal immune response. Clones differ in functional avidity for HIV epitopes. Importantly, in contrast to previous models, in this model we obtained coexistence of multiple clones at steady-state viral set-point, as seen in HIV infection. We found that, for certain parameter conditions, multiple steady states are possible: with few initial CD4 helper cells and high virus inoculum, no immune response is established and target-cell-limited infection follows, with associated high viral load; when CD4 clones are initially large and virus inoculum is low, infection can be controlled by several clones. The conditions for the dependence of viral set-point on initial inoculum and CD4 T-helper clone availability are investigated in terms of the effector mechanism of the clones involved.

Mathematical models of human CD4+ T-cell population kinetics.

We review how mathematical models help the interpretation of data measuring CD4+ T-cell kinetics by two recently-developed techniques. Mathematical models are developed for the average content of T-cell receptor excision circles (TRECs) and the average telomeric restriction fragment (TRF) in T-cells in the peripheral blood. Changes in the TRECs were supposed to indicate changes in thymic production. The rate at which naive and memory CD4+ T-cells erode their telomeres was supposed to reflect their respective division rates. Analysing the mathematical models, we show that rapid changes in the TRECs per naive T-cell are most likely due to changes in the division rates, and that the rates of telomere erosion fail to reflect naive and memory division rates. The model is applied to explain data showing that rheumatoid arthritis (RA) patients have abnormal TRECs and telomeres.

Recruitment times, proliferation, and apoptosis rates during the CD8(+) T-cell response to lymphocytic choriomeningitis virus.

The specific CD8(+) T-cell response during acute lymphocytic choriomeningitis virus (LCMV) infection of mice is characterized by a rapid proliferation phase, followed by a rapid death phase and long-term memory. In BALB/c mice the immunodominant and subdominant CD8(+) responses are directed against the NP118 and GP283 epitopes. These responses differ mainly in the magnitude of the epitope-specific CD8(+) T-cell expansion. Using mathematical models together with a nonlinear parameter estimation procedure, we estimate the parameters describing the rates of change during the three phases and thereby establish the differences between the responses to the two epitopes. We find that CD8(+) cell proliferation begins 1 to 2 days after infection and occurs at an average rate of 3 day(-1), reaching the maximum population size between days 5 and 6 after immunization. The 10-fold difference in expansion to the NP118 and GP283 epitopes can be accounted for in our model by a 3.5-fold difference in the antigen concentration of these epitopes at which T-cell stimulation is half-maximal. As a consequence of this 3.5-fold difference in the epitope concentration needed for T-cell stimulation, the rates of activation and proliferation of T cells specific for the two epitopes differ during the response and in combination can account for the large difference in the magnitude of the response. After the peak, during the death phase, the population declines at a rate of 0.5 day(-1), i.e., cells have an average life time of 2 days. The model accounts for a memory cell population of 5% of the peak population size by a reversal to memory of 1 to 2% of the activated cells per day during the death phase.

Selection by AZT and rapid replacement in the absence of drugs of HIV type 1 resistant to multiple nucleoside analogs.

We studied the intrahost evolution and dynamics of a multidrug-resistant HIV-1, which contains an insertion of two amino acids (aa) and several aa changes within the reverse transcriptase (RT) gene. From an individual receiving intermittent therapy, sequences of 231 full-length molecular clones of HIV-1 RT were obtained from serum-derived viruses at 12 consecutive time points over a period of 6 years, 17 to 20 clones per time point. In the 3.5-year period prior to the first course of therapy, only wild-type (wt) viruses were found. As soon as 6 months after the start of zidovudine (AZT) monotherapy, all viruses contained an insertion of two aa between positions 68 and 69 of the RT and aa changes at positions 67 and 215, a combination conferring resistance to multiple nucleoside analogs. After termination of therapy, the insertion mutants were rapidly and completely replaced by the wt viruses. In turn, the insertion mutants replaced the wt viruses after initiation of therapy with 3TC, d4T, and saquinavir. After termination of triple therapy, the wt viruses completely replaced the mutants within 1 month, which is markedly faster than has been observed earlier for the replacement of AZT-resistant viruses. Fast replacements of the mutant virus populations after termination of therapy indicate gross competitive disadvantage of the insertion mutant in the absence of therapy, which we estimated by using several models. The insertion mutants attained high virus loads, demonstrating that virus load cannot be used as a direct measure of virus fitness.

Release of virus from lymphoid tissue affects human immunodeficiency virus type 1 and hepatitis C virus kinetics in the blood.

Kinetic parameters of human immunodeficiency virus type 1 (HIV-1) and hepatitis C virus (HCV) infections have been estimated from plasma virus levels following perturbation of the chronically infected (quasi-) steady state. We extend previous models by also considering the large pool of virus localized in the lymphoid tissue (LT) compartment. The results indicate that the fastest time scale of HIV-1 plasma load decay during therapy probably reflects the clearance rate of LT virus and not, as previously supposed, the clearance rate of virus in plasma. This resolves the discrepancy between the clearance rate estimates during therapy and those based on plasma apheresis experiments. In the extended models plasma apheresis measurements are indeed expected to reflect the plasma decay rate. We can reconcile all current HIV-1 estimates with this model when, on average, the clearance rate of virus in plasma is approximately 20 day(-1), that of LT virus is approximately 3 day(-1), and the death rate of virus-producing cells is approximately 0.5 day(-1). The fast clearance in the LT compartment increases current estimates for total daily virus production. Because HCV is produced in the liver, we let virus be produced into the blood compartment of our model. The results suggest that extending current HCV models with an LT compartment is not likely to affect current estimates for kinetic parameters and virus production. Estimates for treatment efficacy might be affected, however.

Small variations in multiple parameters account for wide variations in HIV-1 set-points: a novel modelling approach.

Steady-state levels of HIV-1 viraemia in the plasma vary more than a 1,000-fold between HIV-positive patients and are thought to be influenced by several different host and viral factors such as host target cell availability, host anti-HIV immune response and the virulence of the virus. Previous mathematical models have taken the form of classical ecological food-chain models and are unable to account for this multifactorial nature of the disease. These models suggest that the steady-state viral load (i.e. the set-point) is determined by immune response parameters only. We have devised a generalized consensus model in which the conventional parameters are replaced by so-called 'process functions'. This very general approach yields results that are insensitive to the precise form of the mathematical model. Here we applied the approach to HIV-1 infections by estimating the steady-state values of several process functions from published patient data. Importantly, these estimates are generic because they are independent of the precise form of the underlying processes. We recorded the variation in the estimated steady-state values of the process functions in a group of HIV-1 patients. We developed a novel model by providing explicit expressions for the process functions having the highest patient-to-patient variation in their estimated values. Small variations from patient to patient for several parameters of the new model collectively accounted for the large variations observed in the steady-state viral burden. The novel model remains in full agreement with previous models and data.

Resource competition determines selection of B cell repertoires.

Previous experiments with mouse chimeras demonstrated that cellular competition for antigen-specific survival signals plays a crucial role in the maintenance of the naive B cell repertoire. Transgenic (Tg) B cell populations in these chimeras have a shortened lifespan and poor competitive abilities as compared to more diverse non-Tg populations in the same mice. We develop a mathematical model to investigate the mechanism of B cell competition. The model allows for various B cell clones, generated in the bone marrow, to go into the peripheral circulation, where they compete specifically for various ligands providing survival signals. In the model we also find the observed poor competitive abilities of the Tg repertoire. Investigating the nature of the competition in the model, we find that most of the competition is "intraspecific" occurring largely within the clone of truly Tg B cells, and within the repertoire of leaky Tg and non-Tg B cells. This is confirmed by analysing a simplified version of the model, which only allows for intraspecific competition, and resembles a simple ecological model with density-dependent death. The fact that our model accounts for the data, casts doubt on a previous interpretation of the same data arguing that more diverse repertoires outcompete repertoires of lower diversity. Here, we conclude that most of the data can be explained with intraspecific competition, and formulate an experimental prediction that allows one to distinguish between the previous interpretation of inter-specific competition between repertoires, and the current interpretation of intraspecific competition.

The dominant source of CD4+ and CD8+ T-cell activation in HIV infection is antigenic stimulation.

To distinguish between antigenic stimulation and CD4+ T-cell homeostasis as the cause of T-cell hyperactivation in HIV infection, we studied T-cell activation in 47 patients before and during highly active antiretroviral therapy (HAART). We show that expression of human leukocyte antigen (HLA)-DR, CD38, and Ki67 on T cells decreased during HAART but remained elevated over normal values until week 48 of therapy. We confirm previous reports that T-cell activation correlates positively with plasma HIV RNA levels (suggesting antigenic stimulation), and negatively with CD4 count (suggesting CD4+ T-cell homeostasis). However, these correlations may be spurious, because misleading, due to the well-established negative correlation between CD4 count and plasma HIV RNA levels. To resolve this conflict, we computed partial correlation coefficients. Correcting for CD4 counts, we show that plasma HIV RNA levels contributed to T-cell hyperactivation. Correcting for plasma HIV RNA levels, we show that CD4+ T-cell depletion contributed to T-cell activation. Correcting for both, activation of CD4+ and CD8+ T cells remained positively correlated. Because this suggests that CD4+ and CD8+ T-cell activation is caused by a common additional factor, we conclude that antigenic stimulation by HIV or other (opportunistic) infections is the most parsimonious explanation for T-cell activation in HIV infection. Persistence of HIV antigens may explain why T-cell activation fails to revert to levels found in healthy individuals after 48 weeks of therapy.

Estimating relative fitness in viral competition experiments.

The relative fitness of viral variants has previously been defined as the slope of the logarithmic ratio of the genotype or phenotype frequencies in time plots of pairwise competition experiments. Developing mathematical models for such experiments by employing the conventional coefficient of selection s, we demonstrate that this logarithmic ratio gives the fitness difference, rather than the relative fitness. This fitness difference remains proportional to the actual replication rate realized in the particular experimental setup and hence cannot be extrapolated to other situations. Conversely, the conventional relative fitness (1 + s) should be more generic. We develop an approach to compute the generic relative fitness in conventional competition experiments. This involves an estimation of the total viral replication during the experiment and requires an estimate of the average lifetime of productively infected cells. The novel approach is illustrated by estimating the relative fitness, i.e., the relative replication rate, of a set of zidovudine-resistant human immunodeficiency virus type 1 variants. A tool for calculating the relative fitness from observed changes in viral load and genotype (or phenotype) frequencies is publically available on the website at http://www-binf.bio.uu.nl/( approximately )rdb/fitness.html.

Increased cell division but not thymic dysfunction rapidly affects the T-cell receptor excision circle content of the naive T cell population in HIV-1 infection.

Recent thymic emigrants can be identified by T cell receptor excision circles (TRECs) formed during T-cell receptor rearrangement. Decreasing numbers of TRECs have been observed with aging and in human immunodeficiency virus (HIV)-1 infected individuals, suggesting thymic impairment. Here, we show that in healthy individuals, declining thymic output will affect the TREC content only when accompanied by naive T-cell division. The rapid decline in TRECs observed during HIV-1 infection and the increase following HAART are better explained not by thymic impairment, but by changes in peripheral T-cell division rates. Our data indicate that TREC content in healthy individuals is only indirectly related to thymic output, and in HIV-1 infection is mainly affected by immune activation.

Predicting the duration of antiviral treatment needed to suppress plasma HIV-1 RNA.

Effective therapeutic interventions and clinical care of adults infected with HIV-1 require an understanding of factors that influence time of response to antiretroviral therapy. We have studied a cohort of 118 HIV-1-infected subjects naive to antiretroviral therapy and have correlated the time of response to treatment with a series of virological and immunological measures, including levels of viral load in blood and lymph node, percent of CD4 T cells in lymph nodes, and CD4 T-cell count in blood at study entry. Suppression of viremia below the limit of detection, 50 HIV-1 RNA copies/mL of plasma, served as a benchmark for a successful virological response. We employed these correlations to predict the length of treatment required to attain a virological response in each patient. Baseline plasma viremia emerged as the factor most tightly correlated with the duration of treatment required, allowing us to estimate the required time as a function of this one measure.

T-cell division in human immunodeficiency virus (HIV)-1 infection is mainly due to immune activation: a longitudinal analysis in patients before and during highly active antiretroviral therapy (HAART).

In human immunodeficiency virus (HIV)-1 infection, highly increased T-cell turnover was proposed to cause exhaustion of lymphocyte production and consequently development of AIDS. Here, we investigated cell proliferation, as measured by expression of the Ki-67 nuclear antigen, in peripheral blood CD4(+) and CD8(+) lymphocyte subpopulations before and during highly active antiretroviral therapy (HAART). In untreated HIV-1 infection, both the percentage and number of Ki-67(+) CD4(+) and CD8(+) lymphocytes were significantly increased, compared with values obtained from healthy individuals. A more than 10-fold increase in the percentage of dividing naive CD4(+) T cells in the blood was found when the number of these cells were below 100 per microL. HAART induced an immediate decline in Ki-67 antigen expression, despite often very low CD4(+) T-cell numbers, arguing against increased proliferation being a homeostatic response. After approximately 24 weeks of HAART treatment, a transient increase in the number of proliferating cells was seen, but only in the CD4(+) CD27(+) memory pool. In the CD8(+) T-cell compartment, the number of dividing cells was elevated 20- to 25-fold. This increase was most notable in the CD27(+) CD 45RO(+) and CD27(-) CD45RO(+) memory CD8(+) T-cell pool, corresponding with the degree of expansion of these subsets. Reduction of plasma HIV-RNA load by HAART was accompanied by a decrease in numbers and percentages of dividing cells in all CD8(+) T-cell subsets. Taken together, our results indicate that peripheral T-cell proliferation is a consequence of generalized immune activation. (Blood. 2000;95:249-255)

Competition for antigenic sites during T cell proliferation: a mathematical interpretation of in vitro data.

By fitting different mathematical T cell proliferation functions to in vitro T cell proliferation data, we studied T cell competition for stimulatory signals. In our lymphocyte proliferation assays both the antigen (Ag) availability and the concentration of T cells were varied. We show that proliferation functions involving T cell competition describe the data significantly better than classical proliferation functions without competition, thus providing direct evidence for T cell competition in vitro. Our mathematical approach allowed us to study the nature of T cell competition by comparing different proliferation functions involving (i) direct inhibitory T-T interactions, (ii) Ag-specific resource competition, or (iii) resource competition for nonspecific factors such as growth factors, and access to the surface of Ag-presenting cells (APCs). We show that resource competition is an essential ingredient of T cell proliferation. To discriminate between Ag-specific and nonspecific resource competition, the Ag availability was varied in two manners. In a first approach we varied the concentration of APCs, displaying equal ligand densities; in a second approach we varied the Ag density on the surface of the APCs, while keeping the APC concentration constant. We found that both resource competition functions described the data equally well when the Ag availability was increased by adding APCs. When the APC concentration was kept constant, the nonspecific resource competition function yielded the best description of the data. Our interpretation is that T cells were competing for "antigenic sites" on the APCs.