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Biomedical subjects

Alan S Perelson

Publications and source records attributed to Alan S Perelson.

At least 19 recordsLinked to original sources
PubMed2006

Mathematical modeling of subgenomic hepatitis C virus replication in Huh-7 cells.

Cell-based hepatitis C virus (HCV) replicon systems have provided a means for understanding HCV replication mechanisms and for testing new antiviral agents. We describe here a mathematical model of HCV replication that assumes that the translation of the HCV polyprotein occurs in the cytoplasm, that HCV RNA synthesis occurs in vesicular-membrane structures, and that the strategy of replication involves a double-stranded RNA intermediate. Our results shed light on the intracellular dynamics of subgenomic HCV RNA replication from transfection to steady state within Huh-7 cells. We predict the following: (i) about 6 x 10(3) ribosomes are involved in generating millions of HCV NS5B-polymerase molecules in a Huh-7 cell, (ii) the observed 10:1 asymmetry of plus- to minus-strand RNA levels can be explained by a higher-affinity (200-fold) interaction of HCV NS5B polymerase-containing replication complexes with HCV minus-strand RNA over HCV plus-strand RNA in order to initiate synthesis, (iii) the latter higher affinity can also account for the observed approximately 6:1 plus-strand/minus-strand ratio in vesicular-membrane structures, and (iv) the introduction of higher numbers of HCV plus-strand RNA by transfection leads to faster attainment of steady-state but does not change the steady-state HCV RNA level. Fully permissive HCV replication systems have been developed, and the model presented here is a first step toward building a comprehensive model for complete HCV replication. Moreover, the model can serve as an important tool in understanding HCV replication mechanisms and should prove useful in designing and evaluating new antivirals against HCV.

Cell Line, Tumor↗
PubMed2006

Viral decay dynamics in HIV-infected patients receiving ritonavir-boosted saquinavir and efavirenz with or without enfuvirtide: a randomized, controlled trial (HIV-NAT 012).

The availability of enfuvirtide enables assessment of whether human immunodeficiency virus (HIV) decay can be enhanced by targeting reverse transcriptase, protease, and fusion. We performed a 12-week study of 22 patients randomized to receive ritonavir-boosted saquinavir and efavirenz with (the 3-target arm) or without (the 2-target arm) enfuvirtide. We observed no difference in the mean+/-SD elimination-rate constant for overall decay (0.142+/-0.040 per day and 0.128 +/- 0.033 per day in the 2- and 3-target arms, respectively; P>.1) or for modeled first-phase decay rate (-0.62+/-0.34 per day and -0.51+/-0.16 per day; P>.1). Antiretroviral therapy that inhibits HIV reverse transcriptase and protease exerts potent antiviral effects that might not be augmented by the addition of an HIV fusion inhibitor.

Alkynes↗
PubMed2006

Viral and latent reservoir persistence in HIV-1-infected patients on therapy.

Despite many years of potent antiretroviral therapy, latently infected cells and low levels of plasma virus have been found to persist in HIV-infected patients. The factors influencing this persistence and their relative contributions have not been fully elucidated and remain controversial. Here, we address these issues by developing and employing a simple, but mechanistic viral dynamics model. The model has two novel features. First, it assumes that latently infected T cells can undergo bystander proliferation without transitioning into active viral production. Second, it assumes that the rate of latent cell activation decreases with time on antiretroviral therapy due to the activation and subsequent loss of latently infected cells specific for common antigens, leaving behind cells that are successively less frequently activated. Using the model, we examined the quantitative contributions of T cell bystander proliferation, latent cell activation, and ongoing viral replication to the stability of the latent reservoir and persisting low-level viremia. Not surprisingly, proliferation of latently infected cells helped maintain the latent reservoir in spite of loss of latent infected cells through activation and death, and affected viral dynamics to an extent that depended on the magnitude of latent cell activation. In the limit of zero latent cell activation, the latent cell pool and viral load became uncoupled. However, as the activation rate increased, the plasma viral load could be maintained without depleting the latent reservoir, even in the absence of viral replication. The influence of ongoing viral replication on the latent reservoir remained insignificant for drug efficacies above the "critical efficacy" irrespective of the activation rate. However, for lower drug efficacies viral replication enabled the stable maintenance of both the latent reservoir and the virus. Our model and analysis methods provide a quantitative and qualitative framework for probing how different viral and host factors contribute to the dynamics of the latent reservoir and the virus, offering new insights into the principal determinants of their persistence.

Cell Proliferation↗
PubMed2006

Estimating lymphocyte division and death rates from CFSE data.

The division tracking dye, carboxyfluorescin diacetate succinimidyl ester (CFSE) is currently the most informative labeling technique for characterizing the division history of cells in the immune system. Gett and Hodgkin [Nat. Immunol. 1:239-244, 2000] have pioneered the quantitative analysis of CFSE data. We confirm and extend their data analysis approach using simple mathematical models. We employ the extended Gett and Hodgkin [Nat. Immunol. 1:239-244, 2000] method to estimate the time to first division, the fraction of cells recruited into division, the cell cycle time, and the average death rate from CFSE data on T cells stimulated under different concentrations of IL-2. The same data is also fitted with a simple mathematical model that we derived by reformulating the numerical model of Deenick et al. [J. Immunol. 170:4963-4972, 2003]. By a non-linear fitting procedure we estimate parameter values and confidence intervals to identify the parameters that are influenced by the IL-2 concentration. We obtain a significantly better fit to the data when we assume that the T cell death rate depends on the number of divisions cells have completed. We provide an outlook on future work that involves extending the Deenick et al. [J. Immunol. 170:4963-4972, 2003] model into the classical smith-martin model, and into a model with arbitrary probability distributions for death and division through subsequent divisions.

Cell Death↗
PubMed2006

Pharmacodynamics of antiretroviral agents in HIV-1 infected patients: using viral dynamic models that incorporate drug susceptibility and adherence.

We developed a novel HIV-1 dynamic model with consideration of pharmacokinetics, drug adherence and drug susceptibility to link plasma drug concentration to the long-term changes in HIV-1 RNA observation after initiation of therapy. A Bayesian approach is proposed to fit this model to clinical data from ACTG A5055, a study of two dosage regimens of indinavir (IDV) with ritonavir (RTV) in subjects failing their first protease inhibitor treatment. The HIV RNA testing was completed at days 0, 7, 14, 28, 56, 84, 112, 140, and 168. An intensive pharmacokinetic (PK) evaluation was performed on day 14 and multiple trough concentrations were subsequently collected. Pill counts were used to monitor adherence. IC(50) for IDV and RTV were determined at baseline and at virologic failure. Viral dynamic model fitting residuals were used to assess the significance of covariate effects on long-term virologic response. As univariate predictors, none of the four PK parameters C(trough), C(12 hour), C(max), and AUC was significantly related to virologic response (p > 0.05). By including drug susceptibility (IC(50)), or IC(50) and adherence measured by pill counts together, C(trough), C(12 hour), C(max) and AUC were each significantly correlated to long-term virologic response (p = 0.0055,0.0002,0.0136,0.0002 with IC(50) and adherence measured by pill counts considered). The IC(50) and adherence measured by pill counts alone were not related to the virologic response. In predicting virologic response adherence measured by pill counts did not provide any additional information to PK parameters (p = 0.064), to drug susceptibility IC(50) (p = 0.086), and to their combination (p = 0.22). Simple regression approaches did not detect any significant pharmacodynamic (PD) relationships. Any single factor of PK, adherence measured by pill counts and drug susceptibility did not contribute to long-term virologic response. But their combinations in viral dynamic modeling significantly predicted virologic response. The HIV dynamic modeling can appropriately capture complicated nonlinear relationships and interactions among multiple covariates.

Algorithms↗
PubMed2006

Pharmacodynamics of PEG-IFN alpha differentiate HIV/HCV coinfected sustained virological responders from nonresponders.

Pegylated interferon (PEG-IFN) has become standard therapy for hepatitis C virus (HCV) infection. We evaluated whether PEG-IFN pharmacodynamics and pharmacokinetics account for differences in treatment outcome and whether these parameters might be predictors of therapeutic outcome. Twenty-four IFN-naïve, HCV/human immunodeficiency virus-coinfected patients received PEG-IFN alpha-2b (1.5 microg/kg) once weekly plus daily ribavirin (1000 or 1200 mg) for up to 48 weeks. HCV RNA and PEG-IFN alpha concentrations were obtained from samples collected frequently after the first 3 PEG-IFN doses. We modeled HCV kinetics incorporating pharmacokinetic and pharmacodynamic parameters. Although PEG-IFN concentrations and pharmacokinetic parameters were similar in sustained virological responders (SVRs) and nonresponders (NRs), the PEG-IFN alpha-2b concentration that decreases HCV production by 50% (EC50) was lower in SVRs compared with NRs (0.04 vs. 0.45 microg/L [P = .014]). Additionally, the median therapeutic quotient (i.e., the ratio between average PEG-IFN concentration and EC50 [C/EC50]), and the PEG-IFN concentration at day 7 divided by EC50 (C(7)/EC50) were significantly increased in SVRs compared with NRs after the first (10.1 vs. 1.0 [P = .012], 2.8 vs. 0.3 [P = .007], respectively) and second (14.0 vs. 1.1 [P = .016], 5.4 vs. 0.4 [P = .02], respectively) PEG-IFN doses. All 3 parameters may be used to identify NRs. In conclusion, PEG-IFN concentrations and pharmacokinetic parameters do not differ between SVRs and NRs. In contrast, pharmacodynamic measurements-namely EC50, the therapeutic quotient, and C(7)/EC50--are different in coinfected SVRs and NRs. These parameters might be useful predictors of treatment outcome during the first month of therapy.

Antiviral Agents↗
PubMed2006

Kinetics of hepatitis C virus reinfection after liver transplantation.

Improved understanding of hepatitis C virus (HCV) dynamics during and after liver transplantation can be useful in optimizing antiviral therapy in transplant recipients. We analyzed serum HCV ribonucleic acid (RNA) levels during and after cadaveric liver transplantation in 6 HCV patients. After removal of the liver and before the new liver started producing virions, HCV RNA levels dropped with an average half-life (t(1/2)) of 0.8 hours. Viral loads then continued to drop up to 23 hours postimplantation (t(1/2) = 3.4 hours), and began to rise (doubling-time = 2.0 days) as soon as 15 hours after the anhepatic phase. In 3 patients the viral load reached a plateau before rising, suggesting that a nonhepatic source supplied virions and balanced their intrinsic clearance. However, from the decline in viral load over the first 24 hours of the postanhepatic phase, we estimate that nonhepatic sources can at most correspond to 4% of total viral production, 96% of which occurs in the liver, even after we corrected for fluid exchanges during surgery. As the new liver was reinfected, production increased and viral load rose to a new steady state. Using nonlinear regression, we were able to fit the patients' HCV RNA data to a viral dynamic model and estimate the de novo infection rate (mean 1.5 x 10(-6) mL/virion/day), as well as the average percentage of hepatocytes infected at the posttransplantation steady state (19%). In conclusion, we have quantified liver reinfection dynamics in the absence of posttransplantation antiviral therapy. Our findings support the notion that early antiviral therapy may delay or prevent reinfection.

Adult↗
PubMed2006

Influence of peak viral load on the extent of CD4+ T-cell depletion in simian HIV infection.

Simian HIV (SHIV) infection of macaques with CXCR4 tropic viruses results in early and profound CD4 T-cell depletion in the first few weeks of infection. Analyzing data from a large study of vaccination and SHIV-89.6P challenge, we observe a strong correlation between peak viral load and the extent of CD4 T-cell depletion in acute infection, consistent with a simple kinetic model of viral infection of CD4 T cells. We have modeled the dynamics of the interaction of virus and CD4 T cells over time to investigate the rate of CD4 T-cell infection and death. This analysis indicates that up to 80% of CD4 T cells are infected at peak viremia and that the proportion of CD4 T cells destroyed is correlated with the peak viral load. The simple relation between viral load and CD4 T-cell depletion allows prediction of the level of viral control required to prevent CD4 T-cell depletion in acute SHIV infection. Whether such a simple relation also holds for HIV or simian immunodeficiency virus infections remains to be determined, particularly in the gut and other anatomic sites in which most early T-cell depletion occurs.

Animals↗
PubMed2006

Kinetics of influenza A virus infection in humans.

Currently, little is known about the viral kinetics of influenza A during infection within an individual. We utilize a series of mathematical models of increasing complexity, which incorporate target cell limitation and the innate interferon response, to examine influenza A virus kinetics in the upper respiratory tracts of experimentally infected adults. The models were fit to data from an experimental H1N1 influenza A/Hong Kong/123/77 infection and suggest that it is important to include the eclipse phase of the viral life cycle in viral dynamic models. Doing so, we estimate that after a delay of approximately 6 h, infected cells begin producing influenza virus and continue to do so for approximately 5 h. The average lifetime of infected cells is approximately 11 h, and the half-life of free infectious virus is approximately 3 h. We calculated the basic reproductive number, R(0), which indicated that a single infected cell could produce approximately 22 new productive infections. This suggests that antiviral treatments have a large hurdle to overcome in moderating symptoms and limiting infectiousness and that treatment has to be initiated as early as possible. For about 50% of patients, the curve of viral titer versus time has two peaks. This bimodal behavior can be explained by incorporating the antiviral effects of interferon into the model. Our model also compared well to an additional data set on viral titer after experimental infection and treatment with the neuraminidase inhibitor zanamivir, which suggests that such models may prove useful in estimating the efficacies of different antiviral therapies for influenza A infection.

Administration, Intranasal↗
PubMed2006

Naïve and memory cell turnover as drivers of CCR5-to-CXCR4 tropism switch in human immunodeficiency virus type 1: implications for therapy.

Early human immunodeficiency virus infection is characterized by the predominance of CCR5-tropic (R5) virus. However, in many individuals CXCR4-tropic (X4) virus appears in late infection. The reasons for this phenotypic switch are unclear. The patterns of chemokine receptor expression suggest that X4 and R5 viruses have a preferential tropism for naïve and memory T cells, respectively. Since memory cells divide approximately 10 times as often as naïve cells in uninfected individuals, a tropism for memory cells in early infection may provide an advantage. However, with disease progression both naïve and memory cell division frequencies increase, and at low CD4 counts, the naïve cell division frequency approaches that of memory cells. This may provide a basis for the phenotypic switch from R5 to X4 virus observed in late infection. We show that a model of infection using observed values for cell turnover supports this mechanism. The phenotypic switch from R5 to X4 virus occurs at low CD4 counts and is accompanied by a rapid rise in viral load and drop in CD4 count. Thus, low CD4 counts are both a cause and an effect of X4 virus dominance. We also investigate the effects of different antiviral strategies. Surprisingly, these results suggest that both conventional antiretroviral regimens and CCR5 receptor-blocking drugs will promote R5 virus over X4 virus.

Anti-HIV Agents↗
PubMed2006

Modeling and estimation of replication fitness of human immunodeficiency virus type 1 in vitro experiments by using a growth competition assay.

Growth competition assays have been developed to quantify the relative fitnesses of human immunodeficiency virus (HIV-1) mutants. In this article we develop mathematical models to describe viral/cellular dynamic interactions in the assay experiment, from which new competitive fitness indices or parameters are defined. These indices include the log fitness ratio (LFR), the log relative fitness (LRF), and the production rate ratio (PRR). From the population genetics perspective, we clarify the confusion and correct the inconsistency in the definition of relative fitness in the literature of HIV-1 viral fitness. The LFR and LRF are easier to estimate from the experimental data than the PRR, which was misleadingly defined as the relative fitness in recent HIV-1 research literature. Calculation and estimation methods based on two data points and multiple data points were proposed and were carefully studied. In particular, we suggest using both standard linear regression (method of least squares) and a measurement error model approach for more-accurate estimates of competitive fitness parameters from multiple data points. The developed methodologies are generally applicable to any growth competition assays. A user-friendly computational tool also has been developed and is publicly available on the World Wide Web at http://www.urmc.rochester.edu/bstools/vfitness/virusfitness.htm.

HIV-1↗
PubMed2005

Hepatitis C virus genotype 1a NS5A pretreatment sequence variation and viral kinetics in African American and white patients.

In hepatitis C virus (HCV) infection, race is a determinant of treatment response and interferon (IFN) effectiveness. Here, we investigated whether there were differences in the pretreatment viral strains between African American patients and white patients and whether these differences correlated with viral kinetics. IFN effectiveness was calculated using a viral kinetic model. The HCV NS5A region from 21 treated patients with HCV genotype 1a was sequenced and analyzed. White patients displayed more mutations in the V3 region (mean+/-SD, 4.5+/-1.4 vs. 2.9+/-1.6; P=.016), and treatment responders tended to have more mutations in this region than did nonresponders. There was a significant positive correlation between IFN effectiveness and the number of mutations in the V3 region (P=.03). There was no clustering of strains by race, treatment response, or IFN effectiveness in phylogenetic analyses. The results of this study, in conjunction with those of a previous study illustrating the impaired IFN effectiveness in African Americans, suggest a role for host-related factors.

Black or African American↗
PubMed2005

Modeling long-term HIV dynamics and antiretroviral response: effects of drug potency, pharmacokinetics, adherence, and drug resistance.

We propose a long-term HIV-1 dynamic model by considering drug potency, drug exposure, and drug susceptibility. Using a Bayesian approach, HIV-1 dynamic parameters were estimated by fitting the model to viral load data from a phase 1/2 randomized clinical study of 2 indinavir (IDV)/ritonavir (RTV)-containing highly active antiretroviral (ARV) therapy regimens in HIV-infected subjects who had previously failed protease inhibitor-containing ARV therapies. A large between-subject variation in estimated viral dynamic parameters was observed, even after accounting for variations in drug exposure and drug susceptibility, suggesting that characteristics of HIV-1 dynamics are host dependent. Significant correlations of baseline factors such as HIV-1 RNA levels and CD4 cell counts with viral dynamic parameters were found. These correlations coincide with biologic interaction mechanisms between HIV and the host immune system and also provide an explanation for the correlations between the baseline viral load and phase 1 viral decay rate, for which inconsistent results have been reported in the literature. The relations between viral dynamic parameters and virologic response were established, and these results suggest that viral dynamic parameters may play an important role in determining treatment success or failure. In particular, we estimated a drug efficacy threshold for each patient that can be used to assess whether an ARV regimen is potent enough to suppress HIV viruses in the individual patient. Our findings indicate that it is necessary to individualize the ARV regimen to treat HIV-1-infected patients. The proposed mathematic models and statistical techniques may provide a framework to simulate and predict antiviral response for individual patients.

Anti-HIV Agents↗
PubMed2005

HIV dynamics with multiple infections of target cells.

The high incidence of multiple infections of cells by HIV sets the stage for rapid HIV evolution by means of recombination. Yet how HIV dynamics proceeds with multiple infections remains poorly understood. Here, we present a mathematical model that describes the dynamics of viral, target cell, and multiply infected cell subpopulations during HIV infection. Model calculations reproduce several experimental observations and provide key insights into the influence of multiple infections on HIV dynamics. We find that the experimentally observed scaling law, that the number of cells coinfected with two distinctly labeled viruses is proportional to the square of the total number of infected cells, can be generalized so that the number of triply infected cells is proportional to the cube of the number of infected cells, etc. Despite the expectation from Poisson statistics, we find that this scaling relationship only holds under certain conditions, which we predict. We also find that multiple infections do not influence viral dynamics when the rate of viral production from infected cells is independent of the number of times the cells are infected, a regime expected when viral production is limited by cellular rather than viral factors. This result may explain why extant models, which ignore multiple infections, successfully describe viral dynamics in HIV patients. Inhibiting CD4 down-modulation increases the average number of infections per cell. Consequently, altering CD4 down-modulation may allow for an experimental determination of whether viral or cellular factors limit viral production.

CD4 Antigens↗
PubMed2005

Impact of thymectomy on the peripheral T cell pool in rhesus macaques before and after infection with simian immunodeficiency virus.

The goal of this study was to define, by surgical removal of the thymus in juvenile rhesus macaques, the role of the thymus in peripheral T cell homeostasis and to assess the significance of thymic output in SIV infection. By monitoring the changes in phenotypic T cell markers as well as in the numbers of TCR excisional circles--a recently described marker for recent thymic emigrants--following thymectomy, we present evidence that surgical thymectomy in juvenile macaques results in a faster decay of peripheral CD4(+) cells, but does not cause a substantial shift in CD45RA(+) and CD45RA(-) populations. We were able to measure a thymic output of 0.32% and 0.21% per day of CD4(+) and CD8(+) cells, respectively. No compensatory extra-thymic source was detected in lymphoid tissues, although there was a small compensatory increase in T cell proliferation in the peripheral T cell pool. After SIV infection, thymectomized animals did not have higher viral loads, greater T cell decay, or faster disease progression. We therefore conclude that peripheral destructive processes, rather than a loss of thymic output, appear to be the main causes of T cell depletion in SIV infection.

Animals↗
PubMed2005

The effects of thymic selection on the range of T cell cross-reactivity.

Based on the results of a computational model of thymic selection, we propose a mechanism that produces the observed wide range of T cell cross-reactivity. The model suggests that the cross-reactivity of a T cell that survives thymic selection is correlated with its affinity for self peptides. In order to survive thymic selection, a T cell with low affinity for all self peptides expressed in the thymus must have high affinity for major histocompatibility complex (MHC), which makes it highly cross-reactive. A T cell with high affinity for any self peptide must have low MHC affinity to survive selection, which makes it highly specific for its cognate peptide. Our model predicts that (1) positive selection reduces by only 17% the number of T cells that can detect any given foreign peptide, even though it eliminates over 95% of pre-selection cells; (2) negative selection decreases the average cross-reactivity of the pre-selection repertoire by fivefold; and (3) T cells responding to foreign peptides similar to self peptides will have a lower average cross-reactivity than cells responding to epitopes dissimilar to self.

Animals↗
PubMed2005

New kinetic models for the hepatitis C virus.

Viral kinetic modeling has played an important role in the analysis of HCV RNA decay after the initiation of antiviral therapy. Models have provided a means of evaluating the antiviral effectiveness of therapy, of estimating parameters such as the rate of virion clearance and the rate of clearance of hepatitis C virus (HCV)-infected cells, and they have suggested mechanisms of action for both interferon and ribavirin. Nevertheless, the models that were originally formulated were unable to explain all of the observed HCV RNA profiles. We provide an update on the state of HCV kinetic modeling and discuss new models that have taken into consideration the different pharmacokinetics of standard and pegylated forms of interferon, allow for changes in drug effectiveness as drug concentrations fall between dosing intervals, and that have incorporated alanine aminotransferase kinetics and aspects of immune responses to provide a more comprehensive picture of the biology underlying changes in HCV RNA during therapy.

Antiviral Agents↗