[show abstract][hide abstract] ABSTRACT: We assessed the role of myeloid dendritic cells (mDCs) in the outcome of SIV infection by comparing and contrasting their frequency, mobilization, phenotype, cytokine production and apoptosis in pathogenic (pigtailed macaques, PTMs), nonpathogenic (African green monkeys, AGMs) and controlled (rhesus macaques, RMs) SIVagmSab infection. Through the identification of recently replicating cells, we demonstrated that mDC mobilization from the bone marrow occurred in all species postinfection, being most prominent in RMs. Circulating mDCs were depleted with disease progression in PTMs, recovered to baseline values after the viral peak in AGMs, and significantly increased at the time of virus control in RMs. Rapid disease progression in PTMs was associated with low baseline levels and incomplete recovery of circulating mDCs during chronic infection. mDC recruitment to the intestine occurred in all pathogenic scenarios, but loss of mucosal mDCs was associated only with progressive infection. Sustained mDC immune activation occurred throughout infection in PTMs and was associated with increased bystander apoptosis in blood and intestine. Conversely, mDC activation occurred only during acute infection in nonprogressive and controlled infections. Postinfection, circulating mDCs rapidly became unresponsive to TLR7/8 stimulation in all species. Yet, stimulation with LPS, a bacterial product translocated in circulation only in SIV-infected PTMs, induced mDC hyperactivation, apoptosis and excessive production of proinflammatory cytokines. After infection, spontaneous production of proinflammatory cytokines by mucosal mDCs increased only in progressor PTMs. We thus propose that mDCs promote tolerance to SIV in the biological systems that lack intestinal dysfunction. In progressive infections, mDC loss and excessive activation of residual mDCs by SIV and additional stimuli, such as translocated microbial products, enhance generalized immune activation and inflammation. Our results thus provide a mechanistic basis for the role of mDCs in the pathogenesis of AIDS and elucidate the causes of mDC loss during progressive HIV/SIV infections.
[show abstract][hide abstract] ABSTRACT: Hepatitis C virus (HCV) predominantly infects hepatocytes, but many hepatocytes are not infected; studies have shown that HCV antigens cluster within the liver. We investigated spatial distribution and determinants of HCV replication in human liver samples.
We analyzed liver samples from 4 patients with chronic HCV infection (genotype 1, Metavir scores 0-1) to estimate the proportion of infected hepatocytes and amount of HCV viral RNA (vRNA) per cell. Single-cell laser capture microdissection was used to capture approximately >1000 hepatocytes in grids, to preserve geometric relationships. HCV vRNA and IFITM3 mRNA (the transcript of an interferon-stimulated gene) were measured in the same hepatocytes by quantitative PCR and assembled to identify areas of high and low HCV replication.
Patients' serum levels of HCV RNA ranged from 6.87 to 7.40 log10 IU/mL; the proportion of HCV-infected hepatocytes per person ranged from 21% to 45% and the level of vRNA ranged from 1 to 50 IU/hepatocyte. Infection was not random; we identified clustering of HCV-positive hepatocytes using infected-neighbor analysis (P<.0005) and distance to the k(th) nearest neighbor compared with random distributions, obtained by bootstrap simulations (P<0.02). Hepatocytes that expressed IFITM3 did not appear to cluster and were largely HCV-negative.
We used single-cell laser capture and high-resolution analysis to show that in human liver, HCV infects hepatocytes in non-random clusters, whereas expression of antiviral molecules is scattered among hepatocytes. These findings show that quantitative single-cell RNA measurements can be used to estimate the abundance of HCV vRNA per infected human hepatocyte, and are consistent with cell-cell propagation of infection in the absence of clustered IFITM3.
[show abstract][hide abstract] ABSTRACT: The new field of viral dynamics, based on within-host modeling of viral infections, began with models of human immunodeficiency virus (HIV), but now includes many viral infections. Here we review developments in HIV modeling, emphasizing quantitative findings about HIV biology uncovered by studying acute infection, the response to drug therapy and the rate of generation of HIV variants that escape immune responses. We show how modeling has revealed many dynamical features of HIV infection and how it may provide insight into the ultimate cure for this infection.
[show abstract][hide abstract] ABSTRACT: Secondary bacterial infections are a leading cause of illness and death during epidemic and pandemic influenza. Experimental studies suggest a lethal synergism between influenza and certain bacteria, particularly Streptococcus pneumoniae, but the precise processes involved are unclear. To address the mechanisms and determine the influences of pathogen dose and strain on disease, we infected groups of mice with either the H1N1 subtype influenza A virus A/Puerto Rico/8/34 (PR8) or a version expressing the 1918 PB1-F2 protein (PR8-PB1-F2(1918)), followed seven days later with one of two S. pneumoniae strains, type 2 D39 or type 3 A66.1. We determined that, following bacterial infection, viral titers initially rebound and then decline slowly. Bacterial titers rapidly rise to high levels and remain elevated. We used a kinetic model to explore the coupled interactions and study the dominant controlling mechanisms. We hypothesize that viral titers rebound in the presence of bacteria due to enhanced viral release from infected cells, and that bacterial titers increase due to alveolar macrophage impairment. Dynamics are affected by initial bacterial dose but not by the expression of the influenza 1918 PB1-F2 protein. Our model provides a framework to investigate pathogen interaction during coinfections and to uncover dynamical differences based on inoculum size and strain.
[show abstract][hide abstract] ABSTRACT: Systems immunology is an emerging paradigm that aims at a more systematic and quantitative understanding of the immune system. Two major approaches have been utilized to date in this field: unbiased data-driven modeling to comprehensively identify molecular and cellular components of a system and their interactions; and hypothesis-based quantitative modeling to understand the operating principles of a system by extracting a minimal set of variables and rules underlying them. In this review, we describe applications of the two approaches to the study of viral infections and autoimmune diseases in humans, and discuss possible ways by which these two approaches can synergize when applied to human immunology.
Seminars in Immunology 01/2013; · 5.93 Impact Factor
[show abstract][hide abstract] ABSTRACT: Hepatitis C virus (HCV) is present in the host with multiple variants generated by its error prone RNA-dependent RNA polymerase. Little is known about the initial viral diversification and the viral life cycle processes that influence diversity. We studied the diversification of HCV during acute infection in 17 plasma donors, with frequent sampling early in infection. To analyze these data, we developed a new stochastic model of the HCV life cycle. We found that the accumulation of mutations is surprisingly slow: at 30 days, the viral population on average is still 46% identical to its transmitted viral genome. Fitting the model to the sequence data, we estimate the median in vivo viral mutation rate is 2.5×10⁻⁵ mutations per nucleotide per genome replication (range 1.6-6.2×10⁻⁵), about 5-fold lower than previous estimates. To confirm these results we analyzed the frequency of stop codons (N = 10) among all possible non-sense mutation targets (M = 898,335), and found a mutation rate of 2.8-3.2×10⁻⁵, consistent with the estimate from the dynamical model. The slow accumulation of mutations is consistent with slow turnover of infected cells and replication complexes within infected cells. This slow turnover is also inferred from the viral load kinetics. Our estimated mutation rate, which is similar to that of other RNA viruses (e.g., HIV and influenza), is also compatible with the accumulation of substitutions seen in HCV at the population level. Our model identifies the relevant processes (long-lived cells and slow turnover of replication complexes) and parameters involved in determining the rate of HCV diversification.
[show abstract][hide abstract] ABSTRACT: A precise molecular identification of transmitted hepatitis C virus (HCV) genomes could illuminate key aspects of transmission biology, immunopathogenesis and natural history. We used single genome sequencing of 2,922 half or quarter genomes from plasma viral RNA to identify transmitted/founder (T/F) viruses in 17 subjects with acute community-acquired HCV infection. Sequences from 13 of 17 acute subjects, but none of 14 chronic controls, exhibited one or more discrete low diversity viral lineages. Sequences within each lineage generally revealed a star-like phylogeny of mutations that coalesced to unambiguous T/F viral genomes. Numbers of transmitted viruses leading to productive clinical infection were estimated to range from 1 to 37 or more (median = 4). Four acutely infected subjects showed a distinctly different pattern of virus diversity that deviated from a star-like phylogeny. In these cases, empirical analysis and mathematical modeling suggested high multiplicity virus transmission from individuals who themselves were acutely infected or had experienced a virus population bottleneck due to antiviral drug therapy. These results provide new quantitative and qualitative insights into HCV transmission, revealing for the first time virus-host interactions that successful vaccines or treatment interventions will need to overcome. Our findings further suggest a novel experimental strategy for identifying full-length T/F genomes for proteome-wide analyses of HCV biology and adaptation to antiviral drug or immune pressures.
[show abstract][hide abstract] ABSTRACT: Injecting drug users (IDUs) are a driving force for the spread of HIV-1 in Latvia and other Baltic States, accounting for a majority of cases. However, in recent years, heterosexual cases have increased disproportionately. It is unclear how the changes in incidence patterns in Latvia can be explained, and how important IDUs are for the heterosexual sub-epidemic. We introduce a novel epidemic model and use phylogenetic analyses in parallel to examine the spread of HIV-1 in Latvia between 1987 and 2010. Using a hybrid framework with a mean-field description for the susceptible population and an agent-based model for the infecteds, we track infected individuals and follow transmission histories dynamically formed during the simulation. The agent-based simulations and the phylogenetic analysis show that more than half of the heterosexual transmissions in Latvia were caused by IDU, which sustain the heterosexual epidemic. Indeed, we find that heterosexual clusters are characterized by short transmission chains with up to 63% of the chains dying out after the first introduction. In the simulations, the distribution of transmission chain sizes follows a power law distribution, which is confirmed by the phylogenetic data. Our models indicate that frequent introductions reduced the extinction probability of an autonomously spreading heterosexual HIV-1 epidemic, which now has the potential to dominate the spread of the overall epidemic in the future. Furthermore, our model shows that social heterogeneity of the susceptible population can explain the shift in HIV-1 incidence in Latvia over the course of the epidemic. Thus, the decrease in IDU incidence may be due to local heterogeneities in transmission, rather than the implementation of control measures. Increases in susceptibles, through social or geographic movement of IDU, could lead to a boost in HIV-1 infections in this risk group. Targeting individuals that bridge social groups would help prevent further spread of the epidemic.
[show abstract][hide abstract] ABSTRACT: HIV infection is associated with increased risk of cardiovascular complications, the underlying mechanism of which remains unclear. Plasma levels of the coagulation biomarker D-dimer (DD) correlate with increased mortality and cardiovascular events in HIV-infected patients. We compared the incidence of cardiovascular lesions and the levels of the coagulation markers DD and thrombin antithrombin in pathogenic SIV infections of rhesus and pigtailed macaques (PTMs) and in nonpathogenic SIV infection of African green monkeys (AGMs) and sooty mangabeys. Hypercoagulability and cardiovascular pathology were only observed in pathogenic SIV infections. In PTMs infected with SIV from AGMs (SIVagm), DD levels were highly indicative of AIDS progression and increased mortality and were associated with cardiovascular lesions, pointing to SIVagm-infected PTMs as an ideal animal model for the study of HIV-associated cardiovascular disease. In pathogenic SIV infection, DD increased early after infection, was strongly correlated with markers of immune activation/inflammation and microbial translocation (MT), and was only peripherally associated with viral loads. Endotoxin administration to SIVagm-infected AGMs (which lack chronic SIV-induced MT and immune activation) resulted in significant increases of DD. Our results demonstrate that hypercoagulation and cardiovascular pathology are at least in part a consequence of excessive immune activation and MT in SIV infection.
[show abstract][hide abstract] ABSTRACT: Telaprevir, a novel hepatitis C virus (HCV) NS3-4A serine protease inhibitor, has demonstrated substantial antiviral activity in patients infected with HCV. However, drug-resistant HCV variants were detected in vivo at relatively high frequency a few days after drug administration. Here we use a two-strain mathematical model to explain the rapid emergence of drug resistance in HCV patients treated with telaprevir monotherapy. We examine the effects of backward mutation and liver cell proliferation on the preexistence of the mutant virus and the competition between wild-type and drug-resistant virus during therapy. We also extend the two-strain model to a general model with multiple viral strains. Mutations during therapy only have a minor effect on the dynamics of various viral strains, although they are capable of generating low levels of HCV variants that would otherwise be completely suppressed because of fitness disadvantages. Liver cell proliferation may not affect the pretreatment frequency of mutant variants, but is able to influence the quasispecies dynamics during therapy. It is the relative fitness of each mutant strain compared with wild-type that determines which strain(s) will dominate the virus population. This study provides a theoretical framework for exploring the prevalence of preexisting mutant variants and the evolution of drug resistance during treatment with other HCV protease inhibitors or polymerase inhibitors.
Bulletin of Mathematical Biology 05/2012; 74(8):1789-817. · 2.02 Impact Factor
[show abstract][hide abstract] ABSTRACT: To study the kinetics of lymphocytes, models have divided the cell population into subpopulations with different turnover rates. These have been called 'kinetic heterogeneity models' so as to distinguish them from 'temporal heterogeneity models', in which a cell population may have different turnover rates at different times, e.g. when resting versus when activated. We model labelling curves for temporally heterogeneous populations, and predict that they exhibit equal biphasic up- and downslopes. We show when cells divide only once upon activation, these slopes are dominated by the slowest exponent, yielding underestimates of the average turnover rate. When cells undergo more than one division, the labelling curves allow fitting of the two exponential slopes in the temporal heterogeneity model. The same data can also be described with a two-compartment kinetic heterogeneity model. In both instances, the average turnover rate is correctly estimated. Because both models assume a different cell biology but describe the data equally well, the parameters of either model have no simple biological interpretation, as each parameter could reflect a combination of parameters of another biological process. Thus, even if there are sufficient data to reliably estimate all exponentials, one can only accurately estimate an average turnover rate. We illustrate these issues by re-fitting labelling data from healthy and HIV-infected individuals.
Journal of The Royal Society Interface 04/2012; 9(74):2191-200. · 4.91 Impact Factor
[show abstract][hide abstract] ABSTRACT: Simian immunodeficiency virus (SIV) infection in African nonhuman primate (NHP) natural hosts is usually nonpathogenic, despite high levels of virus replication. We have previously shown that chronic SIV infection in sooty mangabeys (SMs) and African green monkeys (AGMs) is associated with low levels of immune activation and bystander T cell apoptosis. To compare these features with those observed in another natural host, the mandrill (MND), we conducted a cross-sectional survey of the 23 SIV-infected and 25 uninfected MNDs from the only semifree colony of mandrills available worldwide. Viral loads (VLs) were determined and phenotypic and functional analysis of peripheral blood- and lymph node-derived lymphocytes was performed. We found that mandrills chronically infected with SIVmnd-1 or SIVmnd-2 have similar levels of viral replication, and we observed a trend toward lower CD4+ T cell counts in chronically SIVmnd-2-infected MNDs than SIVmnd-1-infected MNDs. No correlation between CD4+ T cell counts and VLs in SIV-infected MNDs could be established. Of note, the levels of T cell activation, proliferation, and apoptosis were comparable between SIVmnd-1- and SIVmnd-2-infected MNDs and to those observed in uninfected animals, with the only exception being an increase in tumor necrosis factor alpha-producing CD8+ T cells in SIVmnd-2-infected MNDs. Overall, these findings recapitulate previous observations in SIV-infected SMs and AGMs and lend further evidence to the hypothesis that low levels of immune activation protect natural SIV hosts from disease progression.
Journal of Virology 09/2011; 85(24):13077-87. · 5.08 Impact Factor
[show abstract][hide abstract] ABSTRACT: Understanding the mechanism of infection control in elite controllers (EC) may shed light on the correlates of control of disease progression in HIV infection. However, limitations have prevented a clear understanding of the mechanisms of elite controlled infection, as these studies can only be performed at randomly selected late time points in infection, after control is achieved, and the access to tissues is limited. We report that SIVagm infection is elite-controlled in rhesus macaques (RMs) and therefore can be used as an animal model for EC HIV infection. A robust acute infection, with high levels of viral replication and dramatic mucosal CD4(+) T cell depletion, similar to pathogenic HIV-1/SIV infections of humans and RMs, was followed by complete and durable control of SIVagm replication, defined as: undetectable VLs in blood and tissues beginning 72 to 90 days postinoculation (pi) and continuing at least 4 years; seroreversion; progressive recovery of mucosal CD4(+) T cells, with complete recovery by 4 years pi; normal levels of T cell immune activation, proliferation, and apoptosis; and no disease progression. This "functional cure" of SIVagm infection in RMs could be reverted after 4 years of control of infection by depleting CD8 cells, which resulted in transient rebounds of VLs, thus suggesting that control may be at least in part immune mediated. Viral control was independent of MHC, partial APOBEC restriction was not involved in SIVagm control in RMs and Trim5 genotypes did not impact viral replication. This new animal model of EC lentiviral infection, in which complete control can be predicted in all cases, permits research on the early events of infection in blood and tissues, before the defining characteristics of EC are evident and when host factors are actively driving the infection towards the EC status.
[show abstract][hide abstract] ABSTRACT: Analysis of a large number of HIV-1 genomes at multiple time points after antiretroviral treatment (ART) interruption allows determination of the evolution of drug-resistant viruses and viral fitness in vivo in the absence of drug selection pressure. Using a parallel allele-specific sequencing (PASS) assay, potential primary drug-resistant mutations in five individual patients were studied by analyzing over 18,000 viral genomes. A three-phase evolution of drug-resistant viruses was observed after termination of ART. In the first phase, viruses carrying various combinations of multiple-drug-resistant (MDR) mutations predominated with each mutation persisting in relatively stable proportions while the overall number of resistant viruses gradually increased. In the second phase, viruses with linked MDR mutations rapidly became undetectable and single-drug-resistant (SDR) viruses emerged as minority populations while wild-type viruses quickly predominated. In the third phase, low-frequency SDR viruses remained detectable as long as 59 weeks after treatment interruption. Mathematical modeling showed that the loss in relative fitness increased with the number of mutations in each viral genome and that viruses with MDR mutations had lower fitness than viruses with SDR mutations. No single viral genome had seven or more drug resistance mutations, suggesting that such severely mutated viruses were too unfit to be detected or that the resistance gain offered by the seventh mutation did not outweigh its contribution to the overall fitness loss of the virus. These data provide a more comprehensive understanding of evolution and fitness of drug-resistant viruses in vivo and may lead to improved treatment strategies for ART-experienced patients.
Journal of Virology 07/2011; 85(13):6403-15. · 5.08 Impact Factor
[show abstract][hide abstract] ABSTRACT: Relatively little is known about the viral factors contributing to the lethality of the 1918 pandemic, although its unparalleled virulence was likely due in part to the newly discovered PB1-F2 protein. This protein, while unnecessary for replication, increases apoptosis in monocytes, alters viral polymerase activity in vitro, enhances inflammation and increases secondary pneumonia in vivo. However, the effects the PB1-F2 protein have in vivo remain unclear. To address the mechanisms involved, we intranasally infected groups of mice with either influenza A virus PR8 or a genetically engineered virus that expresses the 1918 PB1-F2 protein on a PR8 background, PR8-PB1-F2(1918). Mice inoculated with PR8 had viral concentrations peaking at 72 hours, while those infected with PR8-PB1-F2(1918) reached peak concentrations earlier, 48 hours. Mice given PR8-PB1-F2(1918) also showed a faster decline in viral loads. We fit a mathematical model to these data to estimate parameter values. The model supports a higher viral production rate per cell and a higher infected cell death rate with the PR8-PB1-F2(1918) virus. We discuss the implications these mechanisms have during an infection with a virus expressing a virulent PB1-F2 on the possibility of a pandemic and on the importance of antiviral treatments.
[show abstract][hide abstract] ABSTRACT: Hepatitis B e antigen (HBeAg)–negative chronic hepatitis B infection has a presentation and clinical course that is divergent from that of HBeAg‐positive infection. The former usually presents with lower viral levels but faster progression to liver disease. We sought to better understand the balance between replication and the immune response against hepatitis B virus (HBV).
Viral kinetics in 50 HBeAg‐negative patients under various treatment protocols with interferon α and/or nucleoside or nucleotide analogs was analyzed. HBV DNA level was measured frequently and the data fitted to a viral dynamic model. A meta‐analysis of all published studies of viral kinetics in HBeAg‐positive and HBeAg‐negative infection was also conducted.
We found that the clearance of both HBV virions and infected cells was significantly faster in HBeAg‐negative infection than in HBeAg‐positive infection. In HBeAg‐negative infection, there was also a negative correlation between baseline HBV DNA levels and infected cell half‐life, suggesting that the higher the viral load the faster the turnover of infected cells.
These results reveal the dual role played by the immune response in maintaining lower viral levels and inducing faster turnover of infected cells, the latter of which may be responsible for the more aggressive nature of HBeAg‐negative infection.
The Journal of Infectious Diseases 11/2010; 202(9):1309-18. · 5.85 Impact Factor
[show abstract][hide abstract] ABSTRACT: About 170 million people worldwide are infected with hepatitis C virus (HCV). The current standard therapy leads to sustained viral elimination in only approximately 50% of the treated patients. Telaprevir, an HCV protease inhibitor, has substantial antiviral activity in patients with chronic HCV infection. However, in clinical trials, drug-resistant variants emerge at frequencies of 5 to 20% of the total virus population as early as the second day after the beginning of treatment. Here, using probabilistic and viral dynamic models, we show that such rapid emergence of drug resistance is expected. We calculate that all possible single- and double-mutant viruses preexist before treatment and that one additional mutation is expected to arise during therapy. Examining data from a clinical trial of telaprevir therapy for HCV infection in detail, we show that our model fits the observed dynamics of both drug-sensitive and drug-resistant viruses and argue that therapy with only direct antivirals will require drug combinations that have a genetic barrier of four or more mutations.
Science translational medicine 05/2010; 2(30):30ra32. · 10.76 Impact Factor
[show abstract][hide abstract] ABSTRACT: The recent emergence of the H5N1 influenza virus from avian reservoirs has raised concern about future influenza strains of high virulence emerging that could easily infect humans. We analyzed differential gene expression of lung epithelial cells to compare the response to H5N1 infection with a more benign infection with Respiratory Syncytial Virus (RSV). These gene expression data are then used as seeds to find important nodes by using a novel combination of the Gene Ontology database and the Human Network of gene interactions. Additional analysis of the data is conducted by training support vector machines (SVM) with the data and examining the orientations of the optimal hyperplanes generated.
Analysis of gene clustering in the Gene Ontology shows no significant clustering of genes unique to H5N1 response at 8 hours post infection. At 24 hours post infection, however, a number of significant gene clusters are found for nodes representing "immune response" and "response to virus" terms. There were no significant clusters of genes in the Gene Ontology for the control (Mock) or RSV experiments that were unique relative to the H5N1 response. The genes found to be most important in distinguishing H5N1 infected cells from the controls using SVM showed a large degree of overlap with the list of significantly regulated genes. However, though none of these genes were members of the GO clusters found to be significant.
Characteristics of H5N1 infection compared to RSV infection show several immune response factors that are specific for each of these infections. These include faster timescales within the cell as well as a more focused activation of immunity factors. Many of the genes that are found to be significantly expressed in H5N1 response relative to the control experiments are not found to cluster significantly in the Gene Ontology. These genes are, however, often closely linked to the clustered genes through the Human Network. This may suggest the need for more diverse annotations of these genes and verification of their action in immune response.