Alan S. Perelson

Los Alamos National Laboratory, Лос-Аламос, California, United States

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Publications (695)

  • Sung Yong Park · Tanzy M. T. Love · Alan S. Perelson · [...] · Ha Youn Lee
    [Show abstract] [Hide abstract] ABSTRACT: Background: The molecular clock hypothesis that genes or proteins evolve at a constant rate is a key tool to reveal phylogenetic relationships among species. Using the molecular clock, we can trace an infection back to transmission using HIV-1 sequences from a single time point. Whether or not a strict molecular clock applies to HIV-1's early evolution in the presence of immune selection has not yet been fully examined. Results: We identified molecular clock signatures from 1587 previously published HIV-1 full envelope gene sequences obtained since acute infection in 15 subjects. Each subject's sequence diversity linearly increased during the first 150 days post infection, with rates ranging from 1.54 × 10-5 to 3.91 × 10-5 with a mean of 2.69 × 10-5 per base per day. The rate of diversification for 12 out of the 15 subjects was comparable to the neutral evolution rate. While temporal diversification was consistent with evolution patterns in the absence of selection, mutations from the founder virus were highly clustered on statistically identified selection sites, which diversified more than 65 times faster than non-selection sites. By mathematically quantifying deviations from the molecular clock under various selection scenarios, we demonstrate that the deviation from a constant clock becomes negligible as multiple escape lineages emerge. The most recent common ancestor of a virus pair from distinct escape lineages is most likely the transmitted founder virus, indicating that HIV-1 molecular dating is feasible even after the founder viruses are no longer detectable. Conclusions: The ability of HIV-1 to escape from immune surveillance in many different directions is the driving force of molecular clock persistence. This finding advances our understanding of the robustness of HIV-1's molecular clock under immune selection, implying the potential for molecular dating.
    Article · Dec 2016 · Retrovirology
  • Frederik Graw · Alan S. Perelson
    [Show abstract] [Hide abstract] ABSTRACT: The way in which a viral infection spreads within a host is a complex process that is not well understood. Different viruses, such as human immunodeficiency virus type 1 and hepatitis C virus, have evolved different strategies, including direct cell-to-cell transmission and cell-free transmission, to spread within a host. To what extent these two modes of transmission are exploited in vivo is still unknown. Mathematical modeling has been an essential tool to get a better systematic and quantitative understanding of viral processes that are difficult to discern through strictly experimental approaches. In this review, we discuss recent attempts that combine experimental data and mathematical modeling in order to determine and quantify viral transmission modes. We also discuss the current challenges for a systems-level understanding of viral spread, and we highlight the promises and challenges that novel experimental techniques and data will bring to the field. Expected final online publication date for the Annual Review of Virology Volume 3 is September 29, 2016. Please see for revised estimates.
    Article · Nov 2016
  • Naveen K. Vaidya · Ruy M. Ribeiro · Alan S. Perelson · Anil Kumar
    [Show abstract] [Hide abstract] ABSTRACT: Complications of HIV-1 infection in individuals who utilize drugs of abuse is a significant problem, because these drugs have been associated with higher virus replication and accelerated disease progression as well as severe neuropathogenesis. To gain further insight it is important to quantify the effects of drugs of abuse on HIV-1 infection dynamics. Here, we develop a mathematical model that incorporates experimentally observed effects of morphine on inducing HIV-1 co-receptor expression. For comparison we also considered viral dynamic models with cytolytic or noncytolytic effector cell responses. Based on the small sample size Akaike information criterion, these models were inferior to the new model based on changes in co-receptor expression. The model with morphine affecting co-receptor expression agrees well with the experimental data from simian immunodeficiency virus infections in morphine-addicted macaques. Our results show that morphine promotes a target cell subpopulation switch from a lower level of susceptibility to a state that is about 2-orders of magnitude higher in susceptibility to SIV infection. As a result, the proportion of target cells with higher susceptibility remains extremely high in morphine conditioning. Such a morphine-induced population switch not only has adverse effects on the replication rate, but also results in a higher steady state viral load and larger CD4 count drops. Moreover, morphine conditioning may pose extra obstacles to controlling viral load during antiretroviral therapy, such as pre-exposure prophylaxis and post infection treatments. This study provides, for the first time, a viral dynamics model, viral dynamics parameters, and related analytical and simulation results for SIV dynamics under drugs of abuse.
    Article · Sep 2016 · PLoS Computational Biology
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    Article · Sep 2016 · Journal of Viral Hepatitis
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    Full-text Article · Jul 2016
  • [Show abstract] [Hide abstract] ABSTRACT: Legalon SIL (SIL) is a chemically hydrophilized version of silibinin, an extract of milk thistle (Silybum marianum) seeds that has exhibited hepatoprotective and antiviral effectiveness against hepatitis C virus (HCV) in patients leading to viral clearance in combination with ribavirin. To elucidate the incompletely understood mode of action of SIL against HCV, mathematical modelling of HCV kinetics and human hepatocyte gene expression studies were performed in uPA-SCID-chimeric mice with humanized livers. Chronically HCV-infected mice (n = 15) were treated for 14 days with daily intravenous SIL at 469, 265 or 61.5 mg/kg. Serum HCV and human albumin (hAlb) were measured frequently, and liver HCV RNA was analysed at days 3 and 14. Microarray analysis of human hepatocyte gene expression was performed at days 0, 3 and 14 of treatment. While hAlb remained constant, a biphasic viral decline in serum was observed consisting of a rapid 1st phase followed by a second slower phase (or plateau with the two lower SIL dosings). SIL effectiveness in blocking viral production was similar among dosing groups (median ε = 77%). However, the rate of HCV-infected hepatocyte decline, δ, was dose-dependent. Intracellular HCV RNA levels correlated (r = 0.66, P = 0.01) with serum HCV RNA. Pathway analysis revealed increased anti-inflammatory and antiproliferative gene expression in human hepatocytes in SIL-treated mice. The results suggest that SIL could lead to a continuous second-phase viral decline, that is potentially viral clearance, in the absence of adaptive immune response along with increased anti-inflammatory and antiproliferative gene expression in human hepatocytes.
    Article · Jun 2016 · Journal of Viral Hepatitis
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    Soumya Banerjee · Jeremie Guedj · Ruy M. Ribeiro · [...] · Alan S. Perelson
    Full-text Dataset · Apr 2016
  • Soumya Banerjee · Jeremie Guedj · Ruy M. Ribeiro · [...] · Alan S. Perelson
    [Show abstract] [Hide abstract] ABSTRACT: West Nile virus (WNV) is an emerging pathogen that has decimated bird populations and caused severe outbreaks of viral encephalitis in humans. Currently, little is known about the within-host viral kinetics of WNV during infection. We developed mathematical models to describe viral replication, spread and host immune response in wild-type and immunocompromised mice. Our approach fits a target cell-limited model to viremia data from immunocompromised knockout mice and an adaptive immune response model to data from wild-type mice. Using this approach, we first estimate parameters governing viral production and viral spread in the host using simple models without immune responses. We then use these parameters in a more complex immune response model to characterize the dynamics of the humoral immune response. Despite substantial uncertainty in input parameters, our analysis generates relatively precise estimates of important viral characteristics that are composed of nonlinear combinations of model parameters: we estimate the mean within-host basic reproductive number, R0, to be 2.3 (95% of values in the range 1.7-2.9); the mean infectious virion burst size to be 2.9 plaqueforming units (95% of values in the range 1.7-4.7); and the average number of cells infected per infectious virion to be between 0.3 and 0.99. Our analysis gives mechanistic insights into the dynamics of WNV infection and produces estimates of viral characteristics that are difficult to measure experimentally. These models are a first step towards a quantitative understanding of the timing and effectiveness of the humoral immune response in reducing host viremia and consequently the epidemic spread of WNV. © 2016 The Author(s) Published by the Royal Society. All rights reserved.
    Article · Apr 2016 · Journal of The Royal Society Interface
  • Laetitia Canini · Jeremie Guedj · Alan S Perelson
    Article · Apr 2016 · Antiviral therapy
  • K E Sherman · R Ke · S D Rouster · [...] · A S Perelson
    [Show abstract] [Hide abstract] ABSTRACT: Aim: Chronic hepatitis C virus (HCV) infection is an important source of morbidity and mortality among haemophiliacs. Limited data are available regarding treatment intervention using direct-acting antivirals (DAAs) and theoretical concerns regarding accumulation of drug-associated resistance variants (RAVs) remain. We conducted a pilot study of treatment with telaprevir/pegylated interferon-alfa/ribavirin to evaluate treatment response and the role of lead-in DAA therapy on mutational selection of resistance variants. Methods: Ultra-deep sequence analysis was performed at baseline, 48 hours and 168 hours after treatment initiation. Results: No dominant RAVs were identified at baseline, but low-level RAVs were noted at baseline in all subjects. Viral dynamic models were used to assess treatment responses. The efficacy parameter (Ɛ) for lead-in ranged from 0 to 0.9745 (mean = 0.514). Subsequent addition of telaprevir resulted in a mean efficacy of more than 0.999. This was comparable to subjects who started all three medications simultaneously. A total of 80% achieved SVR. While rapid shifts in the RAV population following DAA initiation were observed, treatment failure associated with A156V was observed in only one patient. Adverse event profiles were similar to that observed in non-haemophilia cohorts. There was no evidence of factor inhibitor formation. There was no evidence that lead-in provided benefit in terms of response efficacy. Conclusion: These data support DAA-based therapy in those with inherited bleeding disorders.
    Article · Mar 2016 · Haemophilia
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    Jessica M Conway · Alan S Perelson
    [Show abstract] [Hide abstract] ABSTRACT: Antiretroviral therapy (ART) effectively controls HIV infection, suppressing HIV viral loads. However, some residual virus remains, below the level of detection, in HIV-infected patients on ART. The source of this viremia is an area of debate: does it derive primarily from activation of infected cells in the latent reservoir, or from ongoing viral replication? Observations seem to be contradictory: there is evidence of short term evolution, implying that there must be ongoing viral replication, and viral strains should thus evolve. However, phylogenetic analyses, and rare emergent drug resistance, suggest no long-term viral evolution, implying that virus derived from activated latent cells must dominate. We use simple deterministic and stochastic models to gain insight into residual viremia dynamics in HIV-infected patients. Our modeling relies on two underlying assumptions for patients on suppressive ART: that latent cell activation drives viral dynamics and that the reproductive ratio of treated infection is less than 1. Nonetheless, the contribution of viral replication to residual viremia in patients on ART may be non-negligible. However, even if the portion of viremia attributable to viral replication is significant, our model predicts (1) that latent reservoir re-seeding remains negligible, and (2) some short-term viral evolution is permitted, but long-term evolution can still be limited: stochastic analysis of our model shows that de novo emergence of drug resistance is rare. Thus, our simple models reconcile the seemingly contradictory observations on residual viremia and, with relatively few parameters, recapitulates HIV viral dynamics observed in patients on suppressive therapy.
    Full-text Article · Jan 2016 · PLoS Computational Biology
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    Dataset: S1 Text
    Jessica M. Conway · Alan S. Perelson
    [Show abstract] [Hide abstract] ABSTRACT: Supporting information. Supporting mathematical analyses, tables, and figures. (PDF)
    Full-text Dataset · Jan 2016
  • [Show abstract] [Hide abstract] ABSTRACT: Motivation: Illustrating how HIV-1 is transmitted and how it evolves in the following weeks is an important step for developing effective vaccination and prevention strategies. It is currently possible through DNA sequencing to account for the diverse array of viral strains within an infected individual. This provides an unprecedented opportunity to pinpoint when each patient was infected and which viruses were transmitted. Results: Here we develop a mathematical tool for early HIV-1 evolution within a subject whose infection originates either from a single or multiple viral variants. The shifted Poisson mixture model (SPMM) provides a quantitative guideline for segregating viral lineages, which in turn enables us to assess when a subject was infected. The infection duration estimated by SPMM showed a statistically significant linear relationship with that by Fiebig laboratory staging (p=0.00059) among 37 acutely infected subjects. Our tool provides a functional approach to understanding early genetic diversity, one of the most important parameters for deciphering HIV-1 transmission and predicting the rate of disease progression. Availability: SPMM, webserver, is available at CONTACT:
    Article · Dec 2015 · Bioinformatics
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    Dataset: S3 Table
    [Show abstract] [Hide abstract] ABSTRACT: Simulation results when the sensitivity of the immune response to new viral antigens in varied, with and without recombination. Increasing the antigen frequency required for eliciting a new immune response in simulations with recombination decreases the survival of virus with latent genomic fragments and sequence diversity while sequence divergence increases. In simulations without recombination, latent persistency is rare. 50 simulations were performed for each value of antigen frequency. (DOC)
    Full-text Dataset · Dec 2015
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    Dataset: S1 Fig
    [Show abstract] [Hide abstract] ABSTRACT: The proportion of surviving lineages between samples is similar in phylogenies derived from simulated sequences and from clinical data. (A) Typical phylogeny from our simulations. The proportion of surviving lineages from earlier samples is representative of the tree shape (star- to ladder-like). The legend shows samples through time and the surviving proportion of lineages in parentheses. (B) Green dots represent the proportion of surviving lineages between samples at adjacent time points in clinical data, and black dots represent our simulated data. The stronger green color indicates overlapping data points. The phylogenetic trees were generated from 20 sequences sampled every year per simulation. (TIF)
    Full-text Dataset · Dec 2015
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    Dataset: S1 Table
    [Show abstract] [Hide abstract] ABSTRACT: Simulation results when the activation rate is varied, with and without recombination. Increasing the activation rate in simulations with recombination increases the proportion of simulations with persistence (≥ 10%) of virus with latent genomic fragments, and the mean proportion of virus sequences with latent genomic fragments. 100 simulations were performed for each activation rate. In simulations without recombination, latent persistence is rare. (DOC)
    Full-text Dataset · Dec 2015
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    [Show abstract] [Hide abstract] ABSTRACT: HIV-1 is subject to immune pressure exerted by the host, giving variants that escape the immune response an advantage. Virus released from activated latent cells competes against variants that have continually evolved and adapted to host immune pressure. Nevertheless, there is increasing evidence that virus displaying a signal of latency survives in patient plasma despite having reduced fitness due to long-term immune memory. We investigated the survival of virus with latent envelope genomic fragments by simulating within-host HIV-1 sequence evolution and the cycling of viral lineages in and out of the latent reservoir. Our model incorporates a detailed mutation process including nucleotide substitution, recombination, latent reservoir dynamics, diversifying selection pressure driven by the immune response, and purifying selection pressure asserted by deleterious mutations. We evaluated the ability of our model to capture sequence evolution in vivo by comparing our simulated sequences to HIV-1 envelope sequence data from 16 HIV-infected untreated patients. Empirical sequence divergence and diversity measures were qualitatively and quantitatively similar to those of our simulated HIV-1 populations, suggesting that our model invokes realistic trends of HIV-1 genetic evolution. Moreover, reconstructed phylogenies of simulated and patient HIV-1 populations showed similar topological structures. Our simulation results suggest that recombination is a key mechanism facilitating the persistence of virus with latent envelope genomic fragments in the productively infected cell population. Recombination increased the survival probability of latent virus forms approximately 13-fold. Prevalence of virus with latent fragments in productively infected cells was observed in only 2% of simulations when we ignored recombination, while the proportion increased to 27% of simulations when we allowed recombination. We also found that the selection pressures exerted by different fitness landscapes influenced the shape of phylogenies, diversity trends, and survival of virus with latent genomic fragments. Our model predicts that the persistence of latent genomic fragments from multiple different ancestral origins increases sequence diversity in plasma for reasonable fitness landscapes.
    Full-text Article · Dec 2015 · PLoS Computational Biology
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    Dataset: S1 Text
    [Show abstract] [Hide abstract] ABSTRACT: The model algorithm. The pseudo-code of our computer simulations, implemented in R. (DOCX)
    Full-text Dataset · Dec 2015
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    Dataset: S5 Fig
    [Show abstract] [Hide abstract] ABSTRACT: The mean sequence divergence and diversity of HIV-1 populations simulated under the alternative model parameters. After approximately 2 years post-PHI, diversity starts to grow linearly in the latent reservoir (blue solid line) while it starts to saturate in plasma (green solid line). Divergence in the latent reservoir (blue dashed line) grows at a slightly slower rate than in plasma (green dashed line). (TIF)
    Full-text Dataset · Dec 2015
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    Dataset: S6 Fig
    [Show abstract] [Hide abstract] ABSTRACT: The effect of recombination on survival of latent lineages under the alternative model parameters. A) Simulations without recombination. B) Simulations with recombination. Grey lines show the proportion of latent lineages in the productively infected cell population of individual simulations, where the bold tan line is the mean proportion of latent lineages and the thin tan lines outline the 95% confidence envelope. Comparing panels A and B clearly shows that recombination facilitates survival of latent forms. (TIF)
    Full-text Dataset · Dec 2015

Publication Stats

45k Citations


  • 1987-2015
    • Los Alamos National Laboratory
      • Theoretical Biology and Biophysics Group
      Лос-Аламос, California, United States
  • 2007
    • Purdue University
      • Department of Mathematics
      ウェストラファイエット, Indiana, United States
  • 2006
    • Weill Cornell Medical College
      • Center for the Study of Hepatitis C
      New York City, New York, United States
    • University of Virginia
      Charlottesville, Virginia, United States
  • 1999-2006
    • The Rockefeller University
      • • Laboratory of Virology and Infectious Disease
      • • Aaron Diamond AIDS Research Center (ADARC)
      New York, New York, United States
    • University of Illinois at Chicago
      Chicago, Illinois, United States
  • 2005
    • Georgia Institute of Technology
      Atlanta, Georgia, United States
  • 2004
    • Columbia University
      New York, New York, United States
    • University of New South Wales
      Kensington, New South Wales, Australia
    • University of Oxford
      Oxford, England, United Kingdom
  • 2001-2004
    • University of Michigan
      • Department of Mathematics
      Ann Arbor, MI, United States
    • Royal Melbourne Hospital
      Melbourne, Victoria, Australia
  • 2002-2003
    • Cornell University
      • Department of Ecology and Evolutionary Biology
      Ithaca, NY, United States
  • 1997-2003
    • University of New Mexico
      • Department of Computer Science
      Albuquerque, NM, United States
  • 1993-2001
    • Santa Fe Institute
      Santa Fe, New Mexico, United States
    • Stanford University
      • Department of Mathematics
      Stanford, CA, United States
  • 1998
    • Northern Arizona University
      • Department of Chemistry and Biochemistry
      Flagstaff, Arizona, United States
    • Bar Ilan University
      • Faculty of Life Sciences
      Ramat Gan, Tel Aviv, Israel
    • Harvard University
      • Department of Molecular and Cell Biology
      Cambridge, Massachusetts, United States
    • University of Washington Seattle
      Seattle, Washington, United States
  • 1992-1997
    • Princeton University
      • • Department of Molecular Biology
      • • Department of Chemical and Biological Engineering
      Princeton, NJ, United States
  • 1994
    • Universiteit Utrecht
      • Division of Theoretical Biology and Bioinformatics
      Utrecht, Provincie Utrecht, Netherlands
  • 1981
    • Brown University
      • The Lefschetz Center for Dynamical Systems
      Providence, RI, United States
  • 1980
    • National Institutes of Health
      베서스다, Maryland, United States
    • University of California
      Oakland, California, United States
  • 1976-1979
    • University of California, Los Angeles
      Los Ángeles, California, United States
  • 1972-1974
    • University of California, Berkeley
      Berkeley, California, United States
    • University of Berkley
      Berkley, Michigan, United States