Biology subjects

Ke, R.

Publications and source records attributed to Ke, R..

22 records · Page 2Linked to original sources

bioRxiv2019

Report on the spatial spread of defective interfering particles and its role in suppressing infectious particles

Defective interfering particles (DIPs) are categorized as non-infectious viruses with large deletions in their genomic material. A cell infected by a DIP require co-infection by a wild-type virus to complete its replicative lifecycle. There is an increasing interest in developing DIP based therapies in the form of molecular parasites that steal genetic resources of infectious particles. This parasitic behavior is enhanced by constructing engineering designs of DIPs to optimize their role in suppressing the virus infection within-host. Recent experimental studies characterize viral infection as a spatial process and emphasize on its spread rate and the area populated by the infectious particles (IPs). We developed a spatio-temporal model in the framework of reaction-diffusion equations to depict the functional organization of virus particles distributed over a tissue surface. Our model investigates the scenarios and figures out the aspects that can play a vital role to suppress the infection within-host. We studied the impact of initial dose of DIPs, the efficiency of DIP production and the role of cell maturation. Our results show that an engineered DIP can substantially decrease the concentration of IPs. We assert that the decrease in the rate of spatial spread of IPs requires non-deterministic settings.

bioengineering↗

bioRxiv2019

Coinfection of semi-infectious particles can contribute substantially to influenza infection dynamics

AbstractInfluenza is an RNA virus with a genome comprised of eight gene segments. Recent experiments show that the vast majority of virions fail to express one or more gene segments and thus cannot cause a productive infection on their own. These particles, called semi-infectious particles (SIPs), can induce virion production through complementation when multiple SIPs are present in an infected cell. Previous within-host influenza models ignore the potential effects of coinfection and SIPs during virus infection. Here, to investigate the extent that SIPs and coinfection impact viral dynamics, we constructed two within-host models that explicitly keep track of SIPs and coinfection, and fitted the models to clinical data published previously. We found that the model making a more realistic assumption that viruses can only reach a limited number of target cells allows for frequent co-infection during early viral exponential growth and predicts that SIPs contribute substantially to viral load. Furthermore, the model provides a new interpretation of the determinants of viral growth and predicts that the virus within-host growth rate (a measure of viral fitness) is relatively insensitive to the fraction of virions being SIPs, consistent with biological observations. Our results highlight the important role that cellular co-infection can play in regulating infection dynamics and provide a potential explanation for why SIP production is not highly deleterious. More broadly, the model can be used as a general framework to understand coinfection/superinfection in other viral infections. Author SummaryInfluenza A viruses (IAVs) represent a large public health burden across the world. Currently, our understanding of their infection dynamics is incomplete, which hinders the development of effective vaccines and treatment strategies. Recently, it was shown that a large fraction of virions, called semi-infectious particles, do not cause productive infection on their own; however, coinfection of these particles leads to productive infection. The extent that semi-infectious particles and, more broadly, coinfection contribute to overall influenza infection dynamics is not clear. To address this question, we constructed mathematical models explicitly keeping track of semi-infectious particles and coinfection. We show that coinfection can be frequent over the course of infection and that SIPs play an important role in regulating infection dynamics. Our results have implications towards developing effective therapeutics.

microbiology↗

bioRxiv2019

The dynamics of the HIV-1 latent reservoir - considering the heterogeneous subpopulations

A major barrier to finding a cure for human immunodeficiency virus type-I (HIV-1) infection is the existence and persistence of the HIV-1 latent reservoir. Although the size of the reservoir is shown to be extremely stable under effective antiretroviral therapy, multiple lines of evidence suggest that the reservoir is composed of dynamic and heterogeneous subpopulations. Quantifying the dynamics of these subpopulations and the processes that maintain the latent reservoir is crucial to the development of effective strategies to eliminate this reservoir. Here, we constructed a mathematical model to consider four latently infected subpopulations, according to their ability to proliferate and the type of virus they are infected. Our model explains a wide range of clinical observations, including variable estimates of the reservoir half-life and dynamical turnover of cytotoxic T lymphocyte (CTL) escape viruses in the reservoir. It suggests that very early treatment leads to a reservoir that is small in size and is composed of less stable latently infected cells (compared to the reservoir in chronically infected individuals). The shorter half-lives estimated from individuals treated during acute infection is likely driven by cells that are less prone to proliferate; in contrast, the remarkably consistent estimate of the long half-lives in individuals who are treated during chronic infection are driven by fast proliferating cells that are likely to be infected by CTL escape mutants. Our model shed light on the dynamics of the reservoir in the absence and presence of antiretroviral therapy. More broadly, it can be used to estimate the turnover rates of subpopulations of the reservoir as well as to design and evaluate the impact of various therapeutic interventions to purge the HIV-1 reservoir. Author summaryHuman immunodeficiency virus (HIV) infects tens of millions of people globally and causes approximately a million death each year. Current treatment for HIV infection suppresses viral load but does not eradicates the virus. A major barrier to cure HIV infection is the existence and persistence of populations of cells that are latently infected by HIV, i.e. the HIV latent reservoir. Understanding and quantifying the kinetics of the reservoir is therefore critical for developing and evaluating effective therapies to purge the reservoir. Recent studies suggested that this reservoir is heterogenous in their population dynamics; yet most previous mathematical models consider this reservoir as a homogenous population. Here we developed a model explicitly tracking the heterogenous subpopulations of the reservoir. We show that this model explains a wide range of clinical observations, and then demonstrate its utility to make quantitative predictions about varies interventions that aim to restrict or reduce the size of the reservoir.

microbiology↗

bioRxiv2018

Within-host infectious disease models accommodating cellular coinfection, with an application to influenza

Within-host models are useful tools for understanding the processes regulating viral load dynamics. While existing models have considered a wide range of within-host processes, at their core these models have shown remarkable structural similarity. Specifically, the structure of these models generally consider target cells to be either uninfected or infected, with the possibility of accommodating further resolution (for example, cells that are refractory to infection and cells that are in an eclipse phase). Recent findings, however, indicate that cellular coinfection is the norm rather than the exception for many viral infectious diseases, and that cells with high multiplicity of infection are present over at least some duration of an infection. The reality of these cellular coinfection dynamics is not accommodated in current within-host models although it may be critical for understanding within-host dynamics. This is particularly the case if multiplicity of infection impacts infected cell phenotypes such as their death rate and their viral production rates. Here, we present a new class of within-host disease models that allow for cellular coinfection in a scalable manner by retaining the low-dimensionality that is a desirable feature of many current within-host models. The models we propose adopt the general structure of epidemiological macroparasite models that allow hosts to be variably infected by parasites such as nematodes and host phenotypes to flexibly depend on parasite burden. Specifically, our within-host models consider target cells as hosts and viral particles as macroparasites, and allow viral output and infected cell lifespans, among other phenotypes, to depend on a cells multiplicity of infection. We show with an application to influenza that these models can be statistically fit to viral load and other within-host data, that they can reproduce notable features of within-host viral dynamics, and that important in vivo quantities such as the mean multiplicity of cellular infection can be easily quantified with these models once parameterized. The within-host model structure we develop here provides an alternative approach for modeling within-host viral load dynamics and allows for a new class of questions to be addressed that consider the effects of cellular coinfection, collective viral interactions, and viral complementation in within-host viral dynamics and evolution.

epidemiology↗