Multiscale modeling of HBV infection integrating intra- and intercellular viral propagation to analyze extracellular viral markers.

Chronic infection with hepatitis B virus (HBV) is caused by the persistence of closed circular DNA (cccDNA) in the nucleus of infected hepatocytes. Despite available therapeutic anti-HBV agents, eliminating the cccDNA remains challenging. Thus, quantifying and understanding the dynamics of cccDNA are essential for developing effective treatment strategies and new drugs. However, such study requires repeated liver biopsy to measure the intrahepatic cccDNA, which is basically not accepted because liver biopsy is potentially morbid and not common during hepatitis B treatment. We here aimed to develop a noninvasive method for quantifying cccDNA in the liver using surrogate markers in peripheral blood. We constructed a multiscale mathematical model that explicitly incorporates both intracellular and intercellular HBV infection processes. The model, based on age-structured partial differential equations, integrates experimental data from in vitro and in vivo investigations. By applying this model, we roughly predicted the amount and dynamics of intrahepatic cccDNA within a certain range using specific viral markers in serum samples, including HBV DNA, HBsAg, HBeAg, and HBcrAg. Our study represents a significant step towards advancing the understanding of chronic HBV infection. The noninvasive quantification of cccDNA using our proposed method holds promise for improving clinical analyses and treatment strategies. By comprehensively describing the interactions of all components involved in HBV infection, our multiscale mathematical model provides a valuable framework for further research and the development of targeted interventions.

Anti-HTLV-1 immunity combined with proviral load as predictive biomarkers for adult T-cell leukemia-lymphoma.

Human T-cell leukemia virus type 1 (HTLV-1) establishes chronic infection in humans and induces a T-cell malignancy called adult T-cell leukemia-lymphoma (ATL) and several inflammatory diseases such as HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). Persistent HTLV-1 infection is established under the pressure of host immunity, and therefore the immune response against HTLV-1 is thought to reflect the status of the disease it causes. Indeed, it is known that cellular immunity against viral antigens is suppressed in ATL patients compared to HAM/TSP patients. In this study, we show that profiling the humoral immunity to several HTLV-1 antigens, such as Gag, Env, and Tax, and measuring proviral load are useful tools for classifying disease status and predicting disease development. Using targeted sequencing, we found that several carriers whom this profiling method predicted to be at high risk for developing ATL indeed harbored driver mutations of ATL. The clonality of HTLV-1-infected cells in those carriers was still polyclonal; it is consistent with an early stage of leukemogenesis. Furthermore, this study revealed significance of anti-Gag proteins to predict high risk group in HTLV-1 carriers. Consistent with this finding, anti-Gag cytotoxic T lymphocytes (CTLs) were increased in patients who received hematopoietic stem cell transplantation and achieved remission state, indicating the significance of anti-Gag CTLs for disease control. Our findings suggest that our strategy that combines anti-HTLV-1 antibodies and proviral load may be useful for prediction of the development of HTLV-1-associated diseases.

A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2.

The scientific community is focused on developing antiviral therapies to mitigate the impacts of the ongoing novel coronavirus disease 2019 (COVID-19) outbreak. This will be facilitated by improved understanding of viral dynamics within infected hosts. Here, using a mathematical model in combination with published viral load data, we compare within-host viral dynamics of SARS-CoV-2 with analogous dynamics of MERS-CoV and SARS-CoV. Our quantitative analyses using a mathematical model revealed that the within-host reproduction number at symptom onset of SARS-CoV-2 was statistically significantly larger than that of MERS-CoV and similar to that of SARS-CoV. In addition, the time from symptom onset to the viral load peak for SARS-CoV-2 infection was shorter than those of MERS-CoV and SARS-CoV. These findings suggest the difficulty of controlling SARS-CoV-2 infection by antivirals. We further used the viral dynamics model to predict the efficacy of potential antiviral drugs that have different modes of action. The efficacy was measured by the reduction in the viral load area under the curve (AUC). Our results indicate that therapies that block de novo infection or virus production are likely to be effective if and only if initiated before the viral load peak (which appears 2-3 days after symptom onset), but therapies that promote cytotoxicity of infected cells are likely to have effects with less sensitivity to the timing of treatment initiation. Furthermore, combining a therapy that promotes cytotoxicity and one that blocks de novo infection or virus production synergistically reduces the AUC with early treatment. Our unique modeling approach provides insights into the pathogenesis of SARS-CoV-2 and may be useful for development of antiviral therapies.

Association between oral frailty and Prevotella percentage in the oral microbiota of community-dwelling older adults who participated in the CHEER Iwamizawa project, Japan.

BACKGROUND: Prevotella bacteria are associated with inherent diseases of the oral cavity, such as periodontal disease, and systemic diseases. Oral frailty (OF) has been associated with nursing necessity and death. However, the relationship between OF and oral microbiota has not been fully clarified. OBJECTIVE: This cross-sectional study investigated the association between OF and Prevotella percentage in the oral microbiota of community-dwelling older adults. METHODS: Oral bacteria species from saliva were identified in 208 community-dwelling older individuals aged ≥60 years in Japan. The proportion of Prevotella in the oral microbiota was classified into three tertile groups, and its relationship with each test item for OF (number of remaining teeth, masticatory performance, oral diadochokinesis, tongue pressure, difficulties eating tough foods, difficulties swallowing tea or soup, number of applicable OF judgement items, and existence of OF) was examined using ordinal logistic regression analysis. RESULTS: The Prevotella proportions were classified into lower, middle and upper groups, comprising 70, 69 and 69 participants, respectively. The three groups showed a significant relationship between the number of remaining teeth (odds ratio [OR]: 0.946, 95% confidence interval [CI]: 0.915-0.977), masticatory performance (OR: 0.897, 95% CI: 0.844-0.953), number of applicable OF judgement items (OR: 1.477, 95% CI: 1.14-1.915), and existence of OF (OR: 4.194, 95% CI: 1.519-11.576). CONCLUSION: The proportion of Prevotella in oral microbiota was high in individuals with OF. Among the older adults, the type of oral microbiota and systemic diseases may be related to the examination and management of oral function decline.

Should a viral genome stay in the host cell or leave? A quantitative dynamics study of how hepatitis C virus deals with this dilemma.

Virus proliferation involves gene replication inside infected cells and transmission to new target cells. Once positive-strand RNA virus has infected a cell, the viral genome serves as a template for copying ("stay-strategy") or is packaged into a progeny virion that will be released extracellularly ("leave-strategy"). The balance between genome replication and virion release determines virus production and transmission efficacy. The ensuing trade-off has not yet been well characterized. In this study, we use hepatitis C virus (HCV) as a model system to study the balance of the two strategies. Combining viral infection cell culture assays with mathematical modeling, we characterize the dynamics of two different HCV strains (JFH-1, a clinical isolate, and Jc1-n, a laboratory strain), which have different viral release characteristics. We found that 0.63% and 1.70% of JFH-1 and Jc1-n intracellular viral RNAs, respectively, are used for producing and releasing progeny virions. Analysis of the Malthusian parameter of the HCV genome (i.e., initial proliferation rate) and the number of de novo infections (i.e., initial transmissibility) suggests that the leave-strategy provides a higher level of initial transmission for Jc1-n, whereas, in contrast, the stay-strategy provides a higher initial proliferation rate for JFH-1. Thus, theoretical-experimental analysis of viral dynamics enables us to better understand the proliferation strategies of viruses, which contributes to the efficient control of virus transmission. Ours is the first study to analyze the stay-leave trade-off during the viral life cycle and the significance of the replication-release switching mechanism for viral proliferation.

Disentangling the growth curve of microbial culture.

Many researchers have studied the population dynamics of microbe of microbes as a typical example of population dynamics. The Monod equation, which mainly focuses on the growth and stationary phases, is used when plotting a growth curve. However, the growth potential in the late stage of culture has been overlooked. Previous studies considered the direct degradation of products to the limiting substrate. In this study, we considered microbial growth during the stationary phase, which enables us to describe the dynamics precisely. The microbes were divided into two populations: one grew by consuming the limiting substrate and the other degraded the products by metabolism. According to the numerical analysis of our model, microbes may choose one of two strategies: one consumes substrates and expands quickly, and the other grows slowly while cleaning up the environment in which they thrive. Furthermore, we found three types of microbial growth depending on their ability to detect metabolite accumulation. Using experimentally measured data, this model can estimate the dynamics of cell density, the substrates, and the metabolites used. The model's disentangling of growth curves offers novel interpretive possibilities for culture system dynamics.

Antithetic effect of interferon-α on cell-free and cell-to-cell HIV-1 infection.

In HIV-1-infected individuals, transmitted/founder (TF) virus contributes to establish new infection and expands during the acute phase of infection, while chronic control (CC) virus emerges during the chronic phase of infection. TF viruses are more resistant to interferon-alpha (IFN-α)-mediated antiviral effects than CC virus, however, its virological relevance in infected individuals remains unclear. Here we perform an experimental-mathematical investigation and reveal that IFN-α strongly inhibits cell-to-cell infection by CC virus but only weakly affects that by TF virus. Surprisingly, IFN-α enhances cell-free infection of HIV-1, particularly that of CC virus, in a virus-cell density-dependent manner. We further demonstrate that LY6E, an IFN-stimulated gene, can contribute to the density-dependent enhancement of cell-free HIV-1 infection. Altogether, our findings suggest that the major difference between TF and CC viruses can be explained by their resistance to IFN-α-mediated inhibition of cell-to-cell infection and their sensitivity to IFN-α-mediated enhancement of cell-free infection.

Oral frailty and carriage of oral Candida in community-dwelling older adults (Check-up to discover Health with Energy for senior Residents in Iwamizawa; CHEER Iwamizawa).

OBJECTIVE: To examine the association between oral frailty and oral Candida carriage as a general indicator of deteriorating oral function in older adults. BACKGROUND: Older adults exhibit an elevated risk of oral candidiasis caused by Candida. Although many studies have identified factors associated with oral Candida carriage, none have evaluated its relationship with oral function. MATERIALS AND METHODS: This study included 210 community-dwelling older adults aged ≥60 years who participated in wellness checks. Fungal flora expression in saliva samples was evaluated to identify oral C. albicans and C. glabrata. Participants were categorised by detection of neither strain (group 1), either one of the strains (group 2), or both strains (group 3). The relationship between oral Candida carriage and oral frailty was evaluated by multinomial logistic regression analysis. RESULTS: The participants included 58 men and 152 women with a mean age of 74.2 ± 6.1 years. A total of 88 (41.9%), 94 (44.8%) and 28 (13.3%) participants were assigned to groups 1, 2 and 3 respectively. In the multinomial logistic regression analysis, significant associations were observed between group 1 and group 2 for "Have you choked on your tea or soup recently?" and the number of applicable oral frailty items. Between group 1 and group 3, significant associations were observed for the number of remaining teeth, masticatory performance and the number of applicable oral frailty items. CONCLUSION: We obtained basic data useful for intervention studies aimed at verifying whether oral function management prevents deterioration of the oral bacterial flora.

Detection of significant antiviral drug effects on COVID-19 with reasonable sample sizes in randomized controlled trials: A modeling study.

BACKGROUND: Development of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials. METHODS AND FINDINGS: A modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d-1 (95% CI: 1.06 to 1.27 d-1), 0.777 d-1 (0.716 to 0.838 d-1), and 0.450 d-1 (0.378 to 0.522 d-1) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies). Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome. We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation. CONCLUSIONS: In this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

Modeling Borna Disease Virus In Vitro Spread Reveals the Mode of Antiviral Effect Conferred by an Endogenous Bornavirus-Like Element.

Endogenous retroviruses have demonstrated exaptation during long-term evolution with hosts, e.g., resulting in acquisition of antiviral effect on related extant viral infections. While empirical studies have found that an endogenous bornavirus-like element derived from viral nucleoprotein (itEBLN) in the ground squirrel genome shows antiviral effect on virus replication and de novo infection, the antiviral mechanism, dynamics, and quantitative effect of itEBLN remain unknown. In this study, we experimentally and theoretically investigated the dynamics of how an extant bornavirus, Borna disease virus 1 (BoDV-1), spreads and replicates in uninfected, BoDV-1-infected, and itEBLN-expressing cultured cells. Quantifying antiviral effect based on time course data sets, we found that the antiviral effects of itEBLN are estimated to be 75% and 34% on intercellular virus spread and intracellular virus replication, respectively. This discrepancy between intercellular virus spread and intracellular viral replication suggests that viral processes other than the replication of viral ribonucleoprotein complex (RNP) contributed to the suppression of virus spread in itEBLN-expressing cells. Because itEBLN binds to the BoDV-1 RNP, the suppression of viral RNP trafficking can be an attractive candidate explaining this discrepancy.IMPORTANCE Accumulating evidence suggests that some endogenous viral elements (EVEs), including endogenous retroviruses and endogenous nonretroviral virus elements, have acquired functions in the host as a result of long-term coevolution. Recently, an endogenous bornavirus-like element (itEBLN) found in the ground squirrel genome has been shown to have antiviral activity against exogenous bornavirus infection. In this study, we first quantified bornavirus spread in cultured cells and then calculated the antiviral activity of itEBLN on bornavirus infection. The calculated antiviral activity of itEBLN suggests its suppression of multiple processes in the viral life cycle. To our knowledge, this is the first study quantifying the antiviral activity of EVEs and speculating on a model of how some EVEs have acquired antiviral activity during host-virus arms races.

Sporadic on/off switching of HTLV-1 Tax expression is crucial to maintain the whole population of virus-induced leukemic cells.

Viruses causing chronic infection artfully manipulate infected cells to enable viral persistence in vivo under the pressure of immunity. Human T-cell leukemia virus type 1 (HTLV-1) establishes persistent infection mainly in CD4+ T cells in vivo and induces leukemia in this subset. HTLV-1-encoded Tax is a critical transactivator of viral replication and a potent oncoprotein, but its significance in pathogenesis remains obscure due to its very low level of expression in vivo. Here, we show that Tax is expressed in a minor fraction of leukemic cells at any given time, and importantly, its expression spontaneously switches between on and off states. Live cell imaging revealed that the average duration of one episode of Tax expression is ∼19 hours. Knockdown of Tax rapidly induced apoptosis in most cells, indicating that Tax is critical for maintaining the population, even if its short-term expression is limited to a small subpopulation. Single-cell analysis and computational simulation suggest that transient Tax expression triggers antiapoptotic machinery, and this effect continues even after Tax expression is diminished; this activation of the antiapoptotic machinery is the critical event for maintaining the population. In addition, Tax is induced by various cytotoxic stresses and also promotes HTLV-1 replication. Thus, it seems that Tax protects infected cells from apoptosis and increases the chance of viral transmission at a critical moment. Keeping the expression of Tax minimal but inducible on demand is, therefore, a fundamental strategy of HTLV-1 to promote persistent infection and leukemogenesis.

Quantifying the antiviral effect of APOBEC3 on HIV-1 infection in humanized mouse model.

APOBEC3 proteins inhibit human immunodeficiency virus (HIV)-1 infection by independently impairing viral reverse transcription and inducing G-to-A mutations in viral DNA. An HIV-1-encoded protein, viral infectivity factor (Vif), can counteract these antiviral activities of APOBEC3 proteins. Although previous studies using in vitro cell culture systems have revealed the molecular mechanisms of the antiviral action of APOBEC3 proteins and their antagonism by Vif, it remains unclear how APOBEC3 proteins affect the kinetics of HIV-1 replication in vivo. Here we quantified the time-series of viral load datasets from humanized mice infected with HIV-1 variants in the presence of APOBEC3F, APOBEC3G, or both APOBEC3F/G using a simple mathematical model that accounted for inter-individual variability. Through experimental and mathematical investigation, we formulated and calculated the total antiviral activity of APOBEC3F and APOBEC3G based on the estimated initial growth rates of viral loads in vivo. Interestingly, we quantitatively demonstrated that compared with APOBEC3G, the antiviral activity of APOBEC3F was widely distributed but skewed toward lower activity, although their mean values were similar. We concluded that APOBEC3G markedly and robustly restricted the initial stages of viral growth in vivo. This is the first report to quantitatively elucidate how APOBEC3F and APOBEC3G differ in their anti-HIV-1 modes in vivo.

Correction: HIV-1 competition experiments in humanized mice show that APOBEC3H imposes selective pressure and promotes virus adaptation.

[This corrects the article DOI: 10.1371/journal.ppat.1006348.].

HIV-1 competition experiments in humanized mice show that APOBEC3H imposes selective pressure and promotes virus adaptation.

APOBEC3 (A3) family proteins are DNA cytosine deaminases recognized for contributing to HIV-1 restriction and mutation. Prior studies have demonstrated that A3D, A3F, and A3G enzymes elicit a robust anti-HIV-1 effect in cell cultures and in humanized mouse models. Human A3H is polymorphic and can be categorized into three phenotypes: stable, intermediate, and unstable. However, the anti-viral effect of endogenous A3H in vivo has yet to be examined. Here we utilize a hematopoietic stem cell-transplanted humanized mouse model and demonstrate that stable A3H robustly affects HIV-1 fitness in vivo. In contrast, the selection pressure mediated by intermediate A3H is relaxed. Intriguingly, viral genomic RNA sequencing reveled that HIV-1 frequently adapts to better counteract stable A3H during replication in humanized mice. Molecular phylogenetic analyses and mathematical modeling suggest that stable A3H may be a critical factor in human-to-human viral transmission. Taken together, this study provides evidence that stable variants of A3H impose selective pressure on HIV-1.

T-Cell mediated adaptive immunity and antibody-dependent enhancement in secondary dengue infection.

Dengue infection results in a significant number of deaths, mostly in the tropical and subtropical regions across the world. Yet, despite the seriousness of this disease, vaccine, and antiviral drugs that could be employed in dengue treatment remain elusive. The desire to establish the factors determining the disease severity and the growing need for efficient drugs has prompted extensive research interest in within-host viral dynamics. However, very few mathematical models of within-host dengue dynamics pertaining to secondary dengue infection with another serotype are presently available. To address this gap in the pertinent literature, in this work, a secondary dengue infection model with T-cell mediated adaptive immunity and antibody-dependent enhancement was developed by considering the memory cell and heterogeneous antibody as the main factor. In particular, the explicit role of cytokines is considered for both virus and infected cell clearance, along with both extrinsic and intrinsic mechanisms for antibody-dependent enhancement. In case of secondary dengue infection, both the virus and homogeneous antibody production are enhanced due to the influence of memory cells remaining from the previous (primary) dengue infection. Owing to the high model sensitivity, it was possible to establish that, among antibody-dependent enhancement mechanisms, the increased virus replication inside the infected cell, which increases the overall virus burst size, exerts the maximum effect on disease severity during secondary infection. Moreover, the role of initial memory cell concentrations and half-saturation constant in the secretion of memory cell in the disease severity was studied. The obtained results concur with the clinical observations and may be helpful in further research on antibody-dependent enhancements aimed at producing schemes relevant for the dengue vaccine design and development.

Revealing uninfected and infected target cell dynamics from peripheral blood data in highly and less pathogenic simian/human immunodeficiency virus infected Rhesus macaque.

Since chimeric simian and human immunodeficiency viruses (SHIVs) used here, that is, SHIV-#64 and -KS661 utilize both CCR5 and CXCR4 chemokine receptors, they have broad target cell properties. A highly pathogenic SHIV strain, SHIV-KS661, causes an infection that systemically depletes the CD4+ T cells of Rhesus macaques, while a less pathogenic strain, SHIV-#64, does not cause severe symptoms in the macaques. In our previous studies, we established in vitro quantification system for virus infection dynamics, and concluded that SHIV-KS661 effectively produces infectious virions compared with SHIV-#64 in the HSC-F cell culture. However, in vivo dynamics of SHIV infection have not been well understood. To quantify SHIV-#64 and -KS661 infection dynamics in Rhesus macaques, we developed a novel approach and analyzed total CD4+ T cells and viral load in peripheral blood, and reproduced the expected dynamics for the uninfected and infected CD4+ T cells in silico. Using our previous cell culture experimental datasets, we revealed that an infection rate constant is different between SHIV-#64 and -KS661, but the viral production rate and the death rate are similar for the both strains. Thus, here, we assumed these relations in our in vivo data and carried out the data fitting. We performed Bayesian estimation for the whole dataset using MCMC sampling, and simultaneously fitted our novel model to total CD4+ T cells and viral load of SHIV-#64 and -KS661 infection. Our analyses explained that the Malthusian parameter (i.e., fitness of virus infection) and the basic reproduction number (i.e., potential of virus infection) for SHIV-KS661 are significantly higher than those of SHIV-#64. In addition, we demonstrated that the number of uninfected CD4+ T cells in SHIV-KS661 infected Rhesus macaques decreases to the significantly lower value than that before the inoculation several days earlier compared with SHIV-#64 infection. Taken together, the differences between SHIV-#64 and -KS661 infection before the peak viral load might determine the subsequent destiny, that is, whether the systemic CD4+ T cell depletion occurs or the host immune response develop.

Mathematical Analysis of a Transformed ODE from a PDE Multiscale Model of Hepatitis C Virus Infection.

Mathematical modeling has revealed the quantitative dynamics during the process of viral infection and evolved into an important tool in modern virology. Coupled with analyses of clinical and experimental data, the widely used basic model of viral dynamics described by ordinary differential equations (ODEs) has been well parameterized. In recent years, age-structured models, called "multiscale model," formulated by partial differential equations (PDEs) have also been developed and become useful tools for more detailed data analysis. However, in general, PDE models are considerably more difficult to subject to mathematical and numerical analyses. In our recently reported study, we successfully derived a mathematically identical ODE model from a PDE model, which helps to overcome the limitations of the PDE model with regard to clinical data analysis. Here, we derive the basic reproduction number from the identical ODE model and provide insight into the global stability of all possible steady states of the ODE model.

A PDE multiscale model of hepatitis C virus infection can be transformed to a system of ODEs.

Direct-acting antivirals (DAAs) treat hepatitis C virus (HCV) by targeting its intracellular viral replication. DAAs are effective and deliver high clinical performance against HCV infection, but optimization of the DAA treatment regimen is ongoing. Different classes of DAAs are currently under development, and HCV treatments that combine two or three DAAs with different action mechanisms are being improved. To accurately quantify the antiviral effect of these DAA treatments and optimize multi-drug combinations, we must describe the intracellular viral replication processes corresponding to the action mechanisms by multiscale mathematical models. Previous multiscale models of HCV treatment have been formulated by partial differential equations (PDEs). However, estimating the parameters from clinical datasets requires comprehensive numerical PDE computations that are time consuming and often converge poorly. Here, we propose a user-friendly approach that transforms a standard PDE multiscale model of HCV infection (Guedj J et al., Proc. Natl. Acad. Sci. USA 2013; 110(10):3991-6) to mathematically identical ordinary differential equations (ODEs) without any assumptions. We also confirm consistency between the numerical solutions of our transformed ODE model and the original PDE model. This relationship between a detailed structured model and a simple model is called ``model aggregation problem'' and a fundamental important in theoretical biology. In particular, as the parameters of ODEs can be estimated by already established methods, our transformed ODE model and its modified version avoid the time-consuming computations and are broadly available for further data analysis.

Weighted enrichment method for prediction of transcription regulators from transcriptome and global chromatin immunoprecipitation data.

Predicting responsible transcription regulators on the basis of transcriptome data is one of the most promising computational approaches to understanding cellular processes and characteristics. Here, we present a novel method employing vast amounts of chromatin immunoprecipitation (ChIP) experimental data to address this issue. Global high-throughput ChIP data was collected to construct a comprehensive database, containing 8 578 738 binding interactions of 454 transcription regulators. To incorporate information about heterogeneous frequencies of transcription factor (TF)-binding events, we developed a flexible framework for gene set analysis employing the weighted t-test procedure, namely weighted parametric gene set analysis (wPGSA). Using transcriptome data as an input, wPGSA predicts the activities of transcription regulators responsible for observed gene expression. Validation of wPGSA with published transcriptome data, including that from over-expressed TFs, showed that the method can predict activities of various TFs, regardless of cell type and conditions, with results totally consistent with biological observations. We also applied wPGSA to other published transcriptome data and identified potential key regulators of cell reprogramming and influenza virus pathogenesis, generating compelling hypotheses regarding underlying regulatory mechanisms. This flexible framework will contribute to uncovering the dynamic and robust architectures of biological regulation, by incorporating high-throughput experimental data in the form of weights.

A highly pathogenic simian/human immunodeficiency virus effectively produces infectious virions compared with a less pathogenic virus in cell culture.

BACKGROUND: The host range of human immunodeficiency virus (HIV) is quite narrow. Therefore, analyzing HIV-1 pathogenesis in vivo has been limited owing to lack of appropriate animal model systems. To overcome this, chimeric simian and human immunodeficiency viruses (SHIVs) that encode HIV-1 Env and are infectious to macaques have been developed and used to investigate the pathogenicity of HIV-1 in vivo. So far, we have many SHIV strains that show different pathogenesis in macaque experiments. However, dynamic aspects of SHIV infection have not been well understood. To fully understand the dynamic properties of SHIVs, we focused on two representative strains-the highly pathogenic SHIV, SHIV-KS661, and the less pathogenic SHIV, SHIV-#64-and measured the time-course of experimental data in cell culture. METHODS: We infected HSC-F with SHIV-KS661 and -#64 and measured the concentration of Nef-negative (target) and Nef-positive (infected) HSC-F cells, the total viral load, and the infectious viral load daily for 9 days. The experiments were repeated at two different multiplicities of infection, and a previously developed mathematical model incorporating the infectious and non-infectious viruses was fitted to the full dataset of each strain simultaneously to characterize the infection dynamics of these two strains. RESULTS AND CONCLUSIONS: We quantified virological indices including virus burst sizes and basic reproduction number of both SHIV-KS661 and -#64. Comparing the burst size of total and infectious viruses (viral RNA copies and TCID50, respectively), we found that there was a statistically significant difference between the infectious virus burst size of SHIV-KS661 and -#64, while there was no significant difference between the total virus burst size. Furthermore, our analyses showed that the fraction of infectious virus among the produced SHIV-KS661 viruses, which is defined as the infectious viral load (TCID50/ml) divided by the total viral load (RNA copies/ml), is more than 10-fold higher than that of SHIV-#64 during overall infection (i.e., for 9 days). Taken together, we conclude that the highly pathogenic SHIV produces infectious virions more effectively than the less pathogenic SHIV in cell culture.