A DUAL-FUNCTION FILAMENTOUS PF BACTERIOPHAGE PROTEIN MODULATES PSEUDOMONAS AERUGINOSA VIRULENCE POTENTIAL

Pseudomonas aeruginosa is an opportunistic pathogen that often plagues hospitals. More than half of P. aeruginosa isolates are infected by temperate Pf bacteriophage. Pf virions protect bacteria from antibiotics, promote biofilm formation, and modulate animal immune responses in ways that promote chronic infection. These virions can be produced without lysing P. aeruginosa, but lysis may occur during superinfection. Superinfection is the process whereby virions of the same or similar phage infect an already infected host. Temperate phages typically encode superinfection exclusion mechanisms. Here we elucidate one such mechanism in Pf phage. We observed that superinfection-surviving P. aeruginosa were transiently resistant to Pf-infection and deficient in twitch motility. Twitch motility requires type IV pili (T4P), a bacterial cell surface receptor used by Pf to gain entry. We tested the hypothesis that T4P are suppressed by a Pf-encoded protein. We observed that the Pf protein PA0721, which we termed Pf superinfection exclusion (PfsE), suppressed twitch motility, and promoted resistance to Pf infection by binding the T4P protein PilC. Beyond this superinfection exclusion mechanism, we elucidated a second function for PfsE. Upon overexpression, PfsE reduced the production of the virulence factor pyocyanin and transcription of pqs quorum sensing genes. Quorum sensing is density-dependent bacterial communication, whereby bacteria can coordinate complex processes, including pathogenesis and phage defense. We found that PfsE interacts with PqsA by folding into an alternate kinked conformation. We subsequently sought to understand how these quorum system effects affect P. aeruginosa virulence. P. aeruginosa cured of their Pf infection (ΔPf) unsurprisingly show greater pqs activation and pyocyanin production. However, we report that this resulted in a loss of virulence against Caenorhabditis elegans. This seemingly contradictory finding may be explained by our observation that C. elegans mutants were unable to sense bacterial pigments, such as pyocyanin, through their aryl hydrocarbon receptor and are more susceptible to ΔPf infection compared to wild-type C. elegans. Collectively, we describe a dual-function Pf-encoded protein PfsE, which conveys superinfection exclusion and suppresses quorum sensing. Furthermore, the suppression of quorum sensing and downstream virulence factors by Pf allows P. aeruginosa to evade detection by innate host immune responses

Mathematical models of gonorrhoea and chlamydia: Biology, behaviour and interactions

Gonorrhoea and chlamydia are curable, bacterial, sexually transmitted infections (STIs) of humans, with important long term consequences for health. Their epidemiology and biology are reviewed in chapter one. The way the biology of the organisms and the behaviour of human hosts interact to influence the patterns of infection and the potential impact of interventions is the subject of the main body of the thesis. Mathematical models are presented, together with empirical data, to gain a better understanding of the epidemiology of gonorrhoea and chlamydia. New approaches are applied, using more complex measures of disease occurrence including reinfection (subsequent infection by the same organism) or coinfection (infection with both organisms simultaneously). Coinfection with gonorrhoea and chlamydia is investigated in chapter two. The third chapter investigates the importance of heterogeneity in human behaviour (i.e. level of sexual activity, mixing patterns within and between populations) on the spread of disease in subpopulations, using a model incorporating race, gender and sexual activity level. This was parameterised and validated using data collected in South East London. In chapter four, models of reinfection are used to investigate the interaction of population level parameters such as degree of assortative mixing and rates of reinfection. In chapter five, the characteristics of individuals coinfected with both organisms are shown to provide additional information useful in determining how infection is distributed across a population. The biology of the organism is demonstrated, in the fifth chapter, to play an important role in the prevalence and incidence of disease within the host population. The impact of the emergence of resistant or asymptomatic phenotypes under selective pressure by different treatment regimens is quantified using a two strain model, including asymptomatic and symptomatic infections. The final chapter considers the contribution of the research and discusses the implications of the results for STI intervention strategies

Optimizing Treatment Regimes to Hinder Antiviral Resistance in Influenza across Time Scales

abstract: The large-scale use of antivirals during influenza pandemics poses a significant selection pressure for drug-resistant pathogens to emerge and spread in a population. This requires treatment strategies to minimize total infections as well as the emergence of resistance. Here we propose a mathematical model in which individuals infected with wild-type influenza, if treated, can develop de novo resistance and further spread the resistant pathogen. Our main purpose is to explore the impact of two important factors influencing treatment effectiveness: i) the relative transmissibility of the drug-resistant strain to wild-type, and ii) the frequency of de novo resistance. For the endemic scenario, we find a condition between these two parameters that indicates whether treatment regimes will be most beneficial at intermediate or more extreme values (e.g., the fraction of infected that are treated). Moreover, we present analytical expressions for effective treatment regimes and provide evidence of its applicability across a range of modeling scenarios: endemic behavior with deterministic homogeneous mixing, and single-epidemic behavior with deterministic homogeneous mixing and stochastic heterogeneous mixing. Therefore, our results provide insights for the control of drug-resistance in influenza across time scales.The article is published at http://journals.plos.org/plosone/article?id=10.1371/journal.pone.005952

Endemicity and prevalence of multipartite viruses under heterogeneous between-host transmission

Multipartite viruses replicate through a puzzling evolutionary strategy. Their genome is segmented into two or more parts, and encapsidated in separate particles that appear to propagate independently. Completing the replication cycle, however, requires the full genome, so that a systemic infection of a host requires the concurrent presence of several particles. This represents an apparent evolutionary drawback of multipartitism, while its advantages remain unclear. A transition from monopartite to multipartite viral forms has been described in vitro under conditions of high multiplicity of infection, suggesting that cooperation between defective mutants is a plausible evolutionary pathway towards multipartitism. However, it is unknown how the putative advantages that multipartitism might enjoy at the microscopic level affect its epidemiology, or if an explicit advantange is needed to explain its ecological persistence. To disentangle which mechanisms might contribute to the rise and fixation of multipartitism, we investigate the interaction between viral spreading dynamics and host population structure. We set up a compartmental model of the spread of a virus in its different forms and explore its epidemiology using both analytical and numerical techniques. We uncover that the impact of host contact structure on spreading dynamics entails a rich phenomenology of ecological relationships that includes cooperation, competition, and commensality. We find that multipartitism might rise to fixation even in the absence of explicit microscopic advantages. Multipartitism allows the virus to colonize environments that could not be invaded by the monopartite form, facilitated by homogeneous contacts among hosts. We conjecture that these features might have led to an increase in the diversity and prevalence of multipartite viral forms concomitantly with the expansion of agricultural practices.Comment: 27 pages, 4 figures, 1 tabl

Dynamics of HIV treatment and social contagion

Modern-day management of infectious diseases is critically linked to the use of mathematical models to understand and predict dynamics at many levels, from the mechanisms of pathogenesis to the patterns of population-wide transmission and evolution. This thesis describes the development and application of mathematical techniques for HIV infection and dynamics on social networks. Treatment of HIV infection has improved dramatically in the past few decades but is still limited by the development of drug resistance and the inability of current therapies to completely eradicate the virus from an individual. We begin with a synthesis of the important evolutionary principles governing the HIV epidemic, emphasizing the role of modeling. We then describe a modeling framework to study the emergence of drug-resistant HIV within a patient. Our model integrates laboratory data and patient behavior, with the goal of predicting outcomes of clinical trials. Current results demonstrate how pharmacologic properties of antiretroviral drugs affect selection for drug resistance, and can explain drug-class-specific resistance risks. Thirdly, we describe models for a new class of drugs that aim to eliminate cells with latent viral infection. We provide estimates for the required efficacy of these drugs and describe the potential challenges of future clinical trials. Finally, models and mechanisms for understanding viral dynamics are increasingly finding applications outside traditional virology. They can be used to study the dynamics of behaviors, to help predict and intervene in their spread. We describe techniques for applying infectious disease models to social contagion, drawing on techniques for network epidemiology. We use this framework to interpret data on the interpersonal spread of health-related behaviors

HIV-Host Interactions

HIV remains the major global health threat, and neither vaccine nor cure is available. Increasing our knowledge on HIV infection will help overcome the challenge of HIV/AIDS. This book covers several aspects of HIV-host interactions in vitro and in vivo. The first section covers the interaction between cellular components and HIV proteins, Integrase, Tat, and Nef. It also discusses the clinical relevance of HIV superinfection. The next two chapters focus on the role of innate immunity including dendritic cells and defensins in HIV infection followed by the section on the impact of host factors on HIV pathogenesis. The section of co-infection includes the impact of Human herpesvirus 6 and Trichomonas vaginalis on HIV infection. The final section focuses on generation of HIV molecular clones that can be used in macaques and the potential use of cotton rats for HIV studies