Natural variation in HIV infection: Monte Carlo estimates that include CD8 effector cells

Viral load and CD4 T-cell counts in patients infected with the human immunodeficiency virus (HIV) are commonly used to guide clinical decisions regarding drug therapy or to assess therapeutic outcomes in clinical trials. However, random fluctuations in these markers of infection can obscure clinically significant change. We employ a Monte Carlo simulation to investigate contributing factors in the expected variability in CD4 T-cell count and viral load due solely to the stochastic nature of HIV infection. The simulation includes processes that contribute to the variability in HIV infection including CD4 and CD8 T-cell population dynamics as well as T-cell activation and proliferation. The simulation results may reconcile the wide range of variabilities in viral load observed in clinical studies, by quantifying correlations between viral load measurements taken days or weeks apart. The sensitivity of variability in T-cell count and viral load to changes in the lifetimes of CD4 and CD8 T-cells is investigated, as well as the effects of drug therapy.     

The relationship between cell and population growth

A steady-state model of cell volume frequency distribution using the method of Williams (1971) is derived. Results are compared to a Monte Carlo simulation of cell growth and division. It is suggested that the Monte Carlo method might be of value for investigating cell and population properties for which analytic methods are not currently available.     

Modeling and Estimation of Kinetic Parameters and Replicative Fitness of HIV-1 from Flow-Cytometry-Based Growth Competition Experiments

Growth competition assays have been developed to quantify the relative fitness of HIV-1 mutants. In this article, we develop mathematical models to describe viral/cellular dynamic interactions in the assay system from which the competitive fitness indices or parameters are defined. In our previous HIV-viral fitness experiments, the concentration of uninfected target cells was assumed to be constant (Wu et al. 2006). But this may not be true in some experiments. In addition, dual infection may frequently occur in viral fitness experiments and may not be ignorable. Here, we relax these two assumptions and extend our earlier viral fitness model (Wu et al. 2006). The resulting models then become nonlinear ODE systems for which closed-form solutions are not achievable. In the new model, the viral relative fitness is a function of time since it depends on the target cell concentration. First, we studied the structure identifiability of the nonlinear ODE models. The identifiability analysis showed that all parameters in the proposed models are identifiable from the flow-cytometry-based experimental data that we collected. We then employed a global optimization approach (the differential evolution algorithm) to directly estimate the kinetic parameters as well as the relative fitness index in the nonlinear ODE models using nonlinear least square regression based on the experimental data. Practical identifiability was investigated via Monte Carlo simulations.     

Neuraminidase enhances the initial steps of human T-cell leukemia virus type 1 replication

Human T-cell leukemia virus type 1 (HTLV-1) infection is involved in the development of adult T-cell leukemia and HTLV-1-associated myelopathy/tropical spastic paraparesis. A high HTLV-1 proviral load in circulating lymphocytes of HTLV-1 carriers is a risk factor for HTLV-1-related diseases. The virus–cell interaction is linked to viral tropism and pathogenesis. Characterization of the factors that affect HTLV-1 infection is important for preventing HTLV-1 infection. HTLV-1 virions are believed to be weakly infectious under cell culture conditions; however, we found that the treatment of HTLV-1 virions with microbial neuraminidase, an enzyme catalyzing the removal of sialic acid residues from various glycoconjugates, enhanced the number of proviral DNAs in infected cells in a dose-dependent manner. Neuraminidase treatment of virions, but not target cells, enhanced viral binding and entry into cells and viral infectivity; treatment of target cells prior to infection had no effect. Moreover, the number of HTLV-1-mediated syncytia was higher in the presence of neuraminidase. Our results suggest a possible contribution of microbial agents carrying neuraminidase activity to HTLV-1 pathogenesis.     

How the transition frequencies of microtubule dynamic instability (nucleation, catastrophe, and rescue) regulate microtubule dynamics in interphase and mitosis: analysis using a Monte Carlo computer simulation.

Microtubules (MTs) in newt mitotic spindles grow faster than MTs in the interphase cytoplasmic microtubule complex (CMTC), yet spindle MTs do not have the long lengths or lifetimes of the CMTC microtubules. Because MTs undergo dynamic instability, it is likely that changes in the durations of growth or shortening are responsible for this anomaly. We have used a Monte Carlo computer simulation to examine how changes in the number of MTs and changes in the catastrophe and rescue frequencies of dynamic instability may be responsible for the cell cycle dependent changes in MT characteristics. We used the computer simulations to model interphase-like or mitotic-like MT populations on the basis of the dynamic instability parameters available from newt lung epithelial cells in vivo. We started with parameters that produced MT populations similar to the interphase newt lung cell CMTC. In the simulation, increasing the number of MTs and either increasing the frequency of catastrophe or decreasing the frequency of rescue reproduced the changes in MT dynamics measured in vivo between interphase and mitosis.     

Modeling sequence evolution in acute HIV-1 infection

We describe a mathematical model and Monte Carlo (MC) simulation of viral evolution during acute infection. We consider both synchronous and asynchronous processes of viral infection of new target cells. The model enables an assessment of the expected sequence diversity in new HIV-1 infections originating from a single transmitted viral strain, estimation of the most recent common ancestor (MRCA) of the transmitted viral lineage, and estimation of the time to coalesce back to the MRCA. We also calculate the probability of the MRCA being the transmitted virus or an evolved variant. Excluding insertions and deletions, we assume HIV-1 evolves by base substitution without selection pressure during the earliest phase of HIV-1 infection prior to the immune response. Unlike phylogenetic methods that follow a lineage backwards to coalescence, we compare the observed data to a model of the diversification of a viral population forward in time. To illustrate the application of these methods, we provide detailed comparisons of the model and simulations results to 306 envelope sequences obtained from eight newly infected subjects at a single time point. The data from patients were in good agreement with model predictions, and hence compatible with a single-strain infection evolving under no selection pressure. The diversity of the samples from the other two patients was too great to be explained by the model, suggesting multiple HIV-1-strains were transmitted. The model can also be applied to longitudinal patient data to estimate within-host viral evolutionary parameters.     

A linear mixed-effects model for multivariate censored data

We apply a linear mixed-effects model to multivariate failure time data. Computation of the regression parameters involves the Buckley-James method in an iterated Monte Carlo expectation-maximization algorithm, wherein the Monte Carlo E-step is implemented using the Metropolis-Hastings algorithm. From simulation studies, this approach compares favorably with the marginal independence approach, especially when there is a strong within-cluster correlation.     

Constrained pattern of viral evolution in acute and early HCV infection limits viral plasticity

Cellular immune responses during acute Hepatitis C virus (HCV) and HIV infection are a known correlate of infection outcome. Viral adaptation to these responses via mutation(s) within CD8+ T-cell epitopes allows these viruses to subvert host immune control. This study examined HCV evolution in 21 HCV genotype 1-infected subjects to characterise the level of viral adaptation during acute and early HCV infection. Of the total mutations observed 25% were within described CD8+ T-cell epitopes or at viral adaptation sites. Most mutations were maintained into the chronic phase of HCV infection (75%). The lack of reversion of adaptations and high proportion of silent substitutions suggests that HCV has structural and functional limitations that constrain evolution. These results were compared to the pattern of viral evolution observed in 98 subjects during a similar phase in HIV infection from a previous study. In contrast to HCV, evolution during acute HIV infection is marked by high levels of amino acid change relative to silent substitutions, including a higher proportion of adaptations, likely reflecting strong and continued CD8+ T-cell pressure combined with greater plasticity of the virus. Understanding viral escape dynamics for these two viruses is important for effective T cell vaccine design.     

Acutely dysregulated, chronically disabled by the enemy within: T-cell responses to HIV-1 infection

Human immunodeficiency virus (HIV) infection causes chronic progressive immunodeficiency and immune dysregulaton. Although simple depletion of the major target of HIV infection, the CD4+ T cell, can explain much of the immunosuppression seen, there are multiple other factors contributing to the immune dysregulation. CD4+ T-cell depletion induces a range of homeostatic mechanisms that contribute to immune activation and cell turnover, providing a milieu conducive to further viral replication and cell destruction, resulting in functional defects in various lymphoid organs. These changes are progressive and in turn compromise the homeostatic processes. Further, the infection, like any other viral infection, provokes an active immune response consisting of both CD4+ and CD8+ T-cell responses. Both appear compromised, displaying aberrant memory cell production. While some of these defects result from viral variation and the chronicity of antigen presentation, other defects of memory cell production appear very early during the primary immune response limiting the viral specific T-cell responses from the outset. This, combined with the ability of the virus to escape any successful immune responses, results in an attenuated immune response that eventually becomes exhausted, characterized by progressive deficits in T-cell repertoire. Furthermore, negative regulatory mechanisms that normally control the immune response may be aberrantly invoked, perhaps directly by the virus, further compromising the efficacy of the immune response. Rational design of effective immunotherapies depends on a clear understanding of the processes compromising the immune response to HIV.     

CD4+ T-Cell Help Is Required for Effective CD8+ T Cell-Mediated Resolution of Acute Viral Hepatitis in Mice

Cytotoxic CD8+ T cells are essential for the control of viral liver infections, such as those caused by HBV or HCV. It is not entirely clear whether CD4+ T-cell help is necessary for establishing anti-viral CD8+ T cell responses that successfully control liver infection. To address the role of CD4+ T cells in acute viral hepatitis, we infected mice with Lymphocytic Choriomeningitis Virus (LCMV) of the strain WE; LCMV-WE causes acute hepatitis in mice and is cleared from the liver by CD8+ T cells within about two weeks. The role of CD4+ T-cell help was studied in CD4+ T cell-lymphopenic mice, which were either induced by genetic deficiency of the major histocompatibility (MHC) class II transactivator (CIITA) in CIITA−/− mice, or by antibody-mediated CD4+ cell depletion. We found that CD4+ T cell-lymphopenic mice developed protracted viral liver infection, which seemed to be a consequence of reduced virus-specific CD8+ T-cell numbers in the liver. Moreover, the anti-viral effector functions of the liver-infiltrating CD8+ T cells in response to stimulation with LCMV peptide, notably the IFN-γ production and degranulation capacity were impaired in CIITA−/− mice. The impaired CD8+ T-cell function in CIITA−/− mice was not associated with increased expression of the exhaustion marker PD-1. Our findings indicate that CD4+ T-cell help is required to establish an effective antiviral CD8+ T-cell response in the liver during acute viral infection. Insufficient virus control and protracted viral hepatitis may be consequences of impaired initial CD4+ T-cell help.     

Hepatic transcriptome analysis of hepatitis C virus infection in chimpanzees defines unique gene expression patterns associated with viral clearance

Hepatitis C virus infection leads to a high rate of chronicity. Mechanisms of viral clearance and persistence are still poorly understood. In this study, hepatic gene expression analysis was performed to identify any molecular signature associated with the outcome of hepatitis C virus (HCV) infection in chimpanzees. Acutely HCV-infected chimpanzees with self-limited infection or progression to chronicity were studied. Interferon stimulated genes were induced irrespective of the outcome of infection. Early induction of a set of genes associated with cell proliferation and immune activation was associated with subsequent viral clearance. Specifically, two of the genes: interleukin binding factor 3 (ILF3) and cytotoxic granule-associated RNA binding protein (TIA1), associated with robust T-cell response, were highly induced early in chimpanzees with self-limited infection. Up-regulation of genes associated with CD8+ T cell response was evident only during the clearance phase of the acute self-limited infection. The induction of these genes may represent an initial response of cellular injury and proliferation that successfully translates to a "danger signal" leading to induction of adaptive immunity to control viral infection. This primary difference in hepatic gene expression between self-limited and chronic infections supports the concept that successful activation of HCV-specific T-cell response is critical in clearance of acute HCV infection.     

Monte Carlo method for bioluminescence tomography

Bioluminescence imaging plays an important role in the areas of cancer biology, cell biology, gene therapy, and so on. The 2D planar bioluminescent imaging has been transformed into a 3D framework by bioluminescence tomography (BLT) that enables bioluminescent source reconstruction in a mouse using a modality fusion approach. To solve this BLT problem, a geometrical model of the mouse is usually built from a CT/micro-CT/micro-MRI scan, which facilitates the assignment of optical parameters to various anatomical regions in the model. This optical model is then used to facilitate BLT. The forward model is based on Monte Carlo simulation to calculate the diffuse light flux on the surface of the mouse. The forward model data are used to define the imaging system and perform the BLT reconstruction. In this paper, we report the reconstruction of sources inside a heterogeneous highly scattering physical phantom to demonstrate the feasibility of this Monte Carlo based BLT method.     

Productive infection of cultured human lymphoid cells by adenovirus.

We investigated infection of cultures from established human B- and T-cell lines by adenoviruses. Infection by adenovirus type 2 or 5 was productive by the criteria of viral DNA replication, RNA synthesis, immunofluorescent staining of viral proteins, and assembly of biologically active virions. Whereas the kinetics of infection were reproducible and characteristic for each cell line, there appeared to be no correlation between the kinetics of infection and the origin from which the cell lines were established. In a myeloma and a T-cell line, the kinetics of infection approached those in HeLa cells. The presence of the Epstein-Barr virus genome in B lymphoid cells was not a prerequisite for adenoviral infection. Furthermore, expression of the E1A gene was repressed in myeloma cells in comparison with HeLa cells.     

Estimating immunoregulatory gene networks in human herpesvirus type 6-infected T cells

The immune response to viral infection involves complex network of dynamic gene and protein interactions. We present here the dynamic gene network of the host immune response during human herpesvirus type 6 (HHV-6) infection in an adult T-cell leukemia cell line. Using a pathway-focused oligonucleotide DNA microarray, we found a possible association between chemokine genes regulating Th1/Th2 balance and genes regulating T-cell proliferation during HHV-6B infection. Gene network analysis using an integrated comprehensive workbench, VoyaGene, revealed that a gene encoding a TEC-family kinase, ITK, might be a putative modulator in the host immune response against HHV-6B infection. We conclude that Th2-dominated inflammatory reaction in host cells may play an important role in HHV-6B-infected T cells, thereby suggesting the possibility that ITK might be a therapeutic target in diseases related to dysregulation of Th1/Th2 balance. This study describes a novel approach to find genes related with the complex host-virus interaction using microarray data employing the Bayesian statistical framework.     

Calculation of resonance energy transfer in crowded biological membranes.

Analytical and numerical models were developed to describe fluorescence resonance energy transfer (RET) in crowded biological membranes. It was assumed that fluorescent donors were linked to membrane proteins and that acceptors were linked to membrane lipids. No restrictions were placed on the location of the donor within the protein or the partitioning of acceptors between the two leaflets of the bilayer; however, acceptors were excluded from the area occupied by proteins. Analytical equations were derived that give the average quantum yield of a donor at low protein concentrations. Monte Carlo simulations were used to generate protein and lipid distributions that were linked numerically with RET equations to determine the average quantum yield and the distribution of donor fluorescence lifetimes at high protein concentrations, up to 50% area fraction. The Monte Carlo results show such crowding always reduces the quantum yield, probably because crowding increases acceptor concentrations near donor-bearing proteins; the magnitude of the reduction increases monotonically with protein concentration. The Monte Carlo results also show that the distribution of fluorescence lifetimes can differ markedly, even for systems possessing the same average lifetime. The dependence of energy transfer on acceptor concentration, protein radius, donor position within the protein, and the fraction of acceptors in each leaflet was also examined. The model and results are directly applicable to the analysis of RET data obtained from biological membranes; their application should result in a more complete and accurate determination of the structures of membrane components.     

Differential dose contributions on total dose distribution of 125I brachytherapy source

This work provides an improvement of the approach using Monte Carlo simulation for the Amersham Model 6711 ¹²⁵I brachytherapy seed source, which is well known by many theoretical and experimental studies. The source which has simple geometry was researched with respect to criteria of AAPM Tg-43 Report. The approach offered by this study involves determination of differential dose contributions that come from virtual partitions of a massive radioactive element of the studied source to a total dose at analytical calculation point. Some brachytherapy seeds contain multi-radioactive elements so the dose at any point is a total of separate doses from each element. It is momentous to know well the angular and radial dose distributions around the source that is located in cancerous tissue for clinical treatments. Interior geometry of a source is effective on dose characteristics of a distribution. Dose information of inner geometrical structure of a brachytherapy source cannot be acquired by experimental methods because of limits of physical material and geometry in the healthy tissue, so Monte Carlo simulation is a required approach of the study. EGSnrc Monte Carlo simulation software was used. In the design of a simulation, the radioactive source was divided into 10 rings, partitioned but not separate from each other. All differential sources were simulated for dose calculation, and the shape of dose distribution was determined comparatively distribution of a single-complete source. In this work anisotropy function was examined also mathematically.     

The hydration shell of myoglobin

The space in the unit cell of a metmyoglobin crystal not occupied by myoglobin atoms was filled with water using Monte Carlo calculations. Independent calculations with different amounts of water have been performed. Structure factors were calculated using the water coordinates thus obtained and the known coordinates of the myoglobin atoms. A comparison with experimental structure factors showed that both the low and the high resolution regime could be well reproduced with 814 Monte Carlo water molecules per unit cell with a B-value of 50 Ų. The Monte Carlo water molecules yield a smaller standard R-value (0.166) than using a homogeneous electron density for the simulation of the crystal water (R = 0.212). A reciprocal space refinement of the water and the protein coordinates has been performed. Monte Carlo calculations can be used to obtain information for crystallographically invisible parts of the unit cell and yield better coordinates for the visible part in the refinement. Correspondence to: F. Parak     

Detecting linkage disequilibrium in bacterial populations.

The distribution of the number of pairwise differences calculated from comparisons between n haploid genomes has frequently been used as a starting point for testing the hypothesis of linkage equilibrium. For this purpose the variance of the pairwise differences, VD, is used as a test statistic to evaluate the null hypothesis that all loci are in linkage equilibrium. The problem is to determine the critical value of the distribution of VD. This critical value can be estimated either by Monte Carlo simulation or by assuming that VD is distributed normally and calculating a one-tailed 95% critical value for VD, L, L = EVD + 1.645 sqrt(VarVD), where E(VD) is the expectation of VD, and Var(VD) is the variance of VD. If VD (observed) > L, the null hypothesis of linkage equilibrium is rejected. Using Monte Carlo simulation we show that the formula currently available for Var(VD) is incorrect, especially for genetically highly diverse data. This has implications for hypothesis testing in bacterial populations, which are often genetically highly diverse. For this reason we derive a new, exact formula for Var(VD). The distribution of VD is examined and shown to approach normality as the sample size increases. This makes the new formula a useful tool in the investigation of large data sets, where testing for linkage using Monte Carlo simulation can be very time consuming. Application of the new formula, in conjunction with Monte Carlo simulation, to populations of Bradyrhizobium japonicum, Rhizobium leguminosarum, and Bacillus subtilis reveals linkage disequilibrium where linkage equilibrium has previously been reported.     

Viruses Roll the Dice: The Stochastic Behavior of Viral Genome Molecules Accelerates Viral Adaptation at the Cell and Tissue Levels

Recent studies on evolutionarily distant viral groups have shown that the number of viral genomes that establish cell infection after cell-to-cell transmission is unexpectedly small (1–20 genomes). This aspect of viral infection appears to be important for the adaptation and survival of viruses. To clarify how the number of viral genomes that establish cell infection is determined, we developed a simulation model of cell infection for tomato mosaic virus (ToMV), a positive-strand RNA virus. The model showed that stochastic processes that govern the replication or degradation of individual genomes result in the infection by a small number of genomes, while a large number of infectious genomes are introduced in the cell. It also predicted two interesting characteristics regarding cell infection patterns: stochastic variation among cells in the number of viral genomes that establish infection and stochastic inequality in the accumulation of their progenies in each cell. Both characteristics were validated experimentally by inoculating tobacco cells with a library of nucleotide sequence–tagged ToMV and analyzing the viral genomes that accumulated in each cell using a high-throughput sequencer. An additional simulation model revealed that these two characteristics enhance selection during tissue infection. The cell infection model also predicted a mechanism that enhances selection at the cellular level: a small difference in the replication abilities of coinfected variants results in a large difference in individual accumulation via the multiple-round formation of the replication complex (i.e., the replication machinery). Importantly, this predicted effect was observed in vivo. The cell infection model was robust to changes in the parameter values, suggesting that other viruses could adopt similar adaptation mechanisms. Taken together, these data reveal a comprehensive picture of viral infection processes including replication, cell-to-cell transmission, and evolution, which are based on the stochastic behavior of the viral genome molecules in each cell.