Invasion Ability and Disease Dynamics of Environmentally Growing Opportunistic Pathogens under Outside-Host Competition

Most theories of the evolution of virulence concentrate on obligatory host-pathogen relationship. Yet, many pathogens replicate in the environment outside-host where they compete with non-pathogenic forms. Thus, replication and competition in the outside-host environment may have profound influence on the evolution of virulence and disease dynamics. These environmentally growing opportunistic pathogens are also a logical step towards obligatory pathogenicity. Efficient treatment methods against these diseases, such as columnaris disease in fishes, are lacking because of their opportunist nature. We present a novel epidemiological model in which replication and competition in the outside-host environment influences the invasion ability of a novel pathogen. We also analyze the long-term host-pathogen dynamics. Model parameterization is based on the columnaris disease, a bacterial fresh water fish disease that causes major losses in fish farms worldwide. Our model demonstrates that strong competition in the outside-host environment can prevent the invasion of a new environmentally growing opportunist pathogen and long-term disease outbreaks.     

Loss of Competition in the Outside Host Environment Generates Outbreaks of Environmental Opportunist Pathogens

Environmentally transmitted pathogens face ecological interactions (e.g., competition, predation, parasitism) in the outside-host environment and host immune system during infection. Despite the ubiquitousness of environmental opportunist pathogens, traditional epidemiology focuses on obligatory pathogens incapable of environmental growth. Here we ask how competitive interactions in the outside-host environment affect the dynamics of an opportunist pathogen. We present a model coupling the classical SI and Lotka–Volterra competition models. In this model we compare a linear infectivity response and a sigmoidal infectivity response. An important assumption is that pathogen virulence is traded off with competitive ability in the environment. Removing this trade-off easily results in host extinction. The sigmoidal response is associated with catastrophic appearances of disease outbreaks when outside-host species richness, or overall competition pressure, decreases. This indicates that alleviating outside-host competition with antibacterial substances that also target the competitors can have unexpected outcomes by providing benefits for opportunist pathogens. These findings may help in developing alternative ways of controlling environmental opportunist pathogens.     

Outside-host phage therapy as a biological control against environmental infectious diseases

Background

Environmentally growing pathogens present an increasing threat for human health, wildlife and food production. Treating the hosts with antibiotics or parasitic bacteriophages fail to eliminate diseases that grow also in the outside-host environment. However, bacteriophages could be utilized to suppress the pathogen population sizes in the outside-host environment in order to prevent disease outbreaks. Here, we introduce a novel epidemiological model to assess how the phage infections of the bacterial pathogens affect epidemiological dynamics of the environmentally growing pathogens. We assess whether the phage therapy in the outside-host environment could be utilized as a biological control method against these diseases. We also consider how phage-resistant competitors affect the outcome, a common problem in phage therapy. The models give predictions for the scenarios where the outside-host phage therapy will work and where it will fail to control the disease. Parameterization of the model is based on the fish columnaris disease that causes significant economic losses to aquaculture worldwide. However, the model is also suitable for other environmentally growing bacterial diseases.

Results

Transmission rates of the phage determine the success of infectious disease control, with high-transmission phage enabling the recovery of the host population that would in the absence of the phage go asymptotically extinct due to the disease. In the presence of outside-host bacterial competition between the pathogen and phage-resistant strain, the trade-off between the pathogen infectivity and the phage resistance determines phage therapy outcome from stable coexistence to local host extinction.

Conclusions

We propose that the success of phage therapy strongly depends on the underlying biology, such as the strength of trade-off between the pathogen infectivity and the phage-resistance, as well as on the rate that the phages infect the bacteria. Our results indicate that phage therapy can fail if there are phage-resistant bacteria and the trade-off between pathogen infectivity and phage resistance does not completely inhibit the pathogen infectivity. Also, the rate that the phages infect the bacteria should be sufficiently high for phage-therapy to succeed.

     

The Utilization of Oropharyngeal Intratracheal PAMP Administration and Bronchoalveolar Lavage to Evaluate the Host Immune Response in Mice

The host immune response to pathogens is a complex biological process. The majority of in vivo studies classically employed to characterize host-pathogen interactions take advantage of intraperitoneal injections of select bacteria or pathogen associated molecular patterns (PAMPs) in mice. While these techniques have yielded tremendous data associated with infectious disease pathobiology, intraperitoneal injection models are not always appropriate for host-pathogen interaction studies in the lung. Utilizing an acute lung inflammation model in mice, it is possible to conduct a high resolution analysis of the host innate immune response utilizing lipopolysaccharide (LPS). Here, we describe the methods to administer LPS using nonsurgical oropharyngeal intratracheal administration, monitor clinical parameters associated with disease pathogenesis, and utilize bronchoalveolar lavage fluid to evaluate the host immune response. The techniques that are described are widely applicable for studying the host innate immune response to a diverse range of PAMPs and pathogens. Likewise, with minor modifications, these techniques can also be applied in studies evaluating allergic airway inflammation and in pharmacological applications.     

Resource competition and within-host disease dynamics

The host organism is a complex mosaic of cell populations that requires adequate supplies of nutrients for maintenance, growth and proliferation. Because many nutrient requirements may be shared by host cells, pathogens and indigenous microflora, all these cells may potentially compete for growth-limiting resources. Ecological theory can explain some of the dynamics commonly seen in host-pathogen interactions; and mechanistic resource-consumer theory provides an instructive framework for viewing the disease process.     

Environmental Variation Generates Environmental Opportunist Pathogen Outbreaks

Many socio-economically important pathogens persist and grow in the outside host environment and opportunistically invade host individuals. The environmental growth and opportunistic nature of these pathogens has received only little attention in epidemiology. Environmental reservoirs are, however, an important source of novel diseases. Thus, attempts to control these diseases require different approaches than in traditional epidemiology focusing on obligatory parasites. Conditions in the outside-host environment are prone to fluctuate over time. This variation is a potentially important driver of epidemiological dynamics and affect the evolution of novel diseases. Using a modelling approach combining the traditional SIRS models to environmental opportunist pathogens and environmental variability, we show that epidemiological dynamics of opportunist diseases are profoundly driven by the quality of environmental variability, such as the long-term predictability and magnitude of fluctuations. When comparing periodic and stochastic environmental factors, for a given variance, stochastic variation is more likely to cause outbreaks than periodic variation. This is due to the extreme values being further away from the mean. Moreover, the effects of variability depend on the underlying biology of the epidemiological system, and which part of the system is being affected. Variation in host susceptibility leads to more severe pathogen outbreaks than variation in pathogen growth rate in the environment. Positive correlation in variation on both targets can cancel the effect of variation altogether. Moreover, the severity of outbreaks is significantly reduced by increase in the duration of immunity. Uncovering these issues helps in understanding and controlling diseases caused by environmental pathogens.     

Parameter estimation and sensitivity analysis in an agent-based model of Leishmania major infection

Computer models of disease take a systems biology approach toward understanding host-pathogen interactions. In particular, data driven computer model calibration is the basis for inference of immunological and pathogen parameters, assessment of model validity, and comparison between alternative models of immune or pathogen behavior. In this paper we describe the calibration and analysis of an agent-based model of Leishmania major infection. A model of macrophage loss following uptake of necrotic tissue is proposed to explain macrophage depletion following peak infection. Using Gaussian processes to approximate the computer code, we perform a sensitivity analysis to identify important parameters and to characterize their influence on the simulated infection. The analysis indicates that increasing growth rate can favor or suppress pathogen loads, depending on the infection stage and the pathogen's ability to avoid detection. Subsequent calibration of the model against previously published biological observations suggests that L. major has a relatively slow growth rate and can replicate for an extended period of time before damaging the host cell.     

The acquisition of hypovirulence in host-pathogen systems with three trophic levels

A major focus of research on the dynamics of host-pathogen interactions has been the evolution of pathogen virulence, which is defined as the loss in host fitness due to infection. It is usually assumed that changes in pathogen virulence are the result of selection to increase pathogen fitness. However, in some cases, pathogens have acquired hypovirulence by themselves becoming infected with hyperparasites. For example, the chestnut blight fungus Cryphonectria parasitica has become hypovirulent in some areas by acquiring a double-stranded RNA hyperparasite that debilitates the pathogen, thereby reducing its virulence to the host. In this article, we develop and analyze a mathematical model of the dynamics of host-pathogen interactions with three trophic levels. The system may be dominated by either uninfected (virulent) or hyperparasitized (hypovirulent) pathogens, or by a mixture of the two. Hypovirulence may allow some recovery of the host population, but it can also harm the host population if the hyperparasite moves the transmission rate of the pathogen closer to its evolutionarily stable strategy. In the latter case, the hyperparasite is effectively a mutualist of the pathogen. Selection among hyperparasites will often minimize the deleterious effects, or maximize the beneficial effects, of the hyperparasite on the pathogen. Increasing the frequency of multiple infections of the same host individual promotes the acquisition of hypovirulence by increasing the opportunity for horizontal transmission of the hyperparasite. This effect opposes the usual theoretical expectation that multiple infections promote the evolution of more virulent pathogens via selection for rapid growth within hosts.     

Ecophysiology meets conservation: understanding the role of disease in amphibian population declines

Infectious diseases are intimately associated with the dynamics of biodiversity. However, the role that infectious disease plays within ecological communities is complex. The complex effects of infectious disease at the scale of communities and ecosystems are driven by the interaction between host and pathogen. Whether or not a given host-pathogen interaction results in progression from infection to disease is largely dependent on the physiological characteristics of the host within the context of the external environment. Here, we highlight the importance of understanding the outcome of infection and disease in the context of host ecophysiology using amphibians as a model system. Amphibians are ideal for such a discussion because many of their populations are experiencing declines and extinctions, with disease as an important factor implicated in many declines and extinctions. Exposure to pathogens and the host's responses to infection can be influenced by many factors related to physiology such as host life history, immunology, endocrinology, resource acquisition, behaviour and changing climates. In our review, we discuss the relationship between disease and biodiversity. We highlight the dynamics of three amphibian host-pathogen systems that induce different effects on hosts and life stages and illustrate the complexity of amphibian-host-parasite systems. We then review links between environmental stress, endocrine-immune interactions, disease and climate change.     

The impact of non-lethal synergists on the population and evolutionary dynamics of host-pathogen interactions

Multiple pathogenic infections can influence disease transmission and virulence, and have important consequences for understanding the community ecology and epidemiology of host-pathogen interactions. Here the population and evolutionary dynamics of a host-pathogen interaction with free-living stages are explored in the presence of a non-lethal synergist that hosts must tolerate. Through the coupled effects on pathogen transmission, host mass gain and allometry it is shown how investing in tolerance to a non-lethal synergist can lead to a broad range of different population dynamics. The effects of the synergist on pathogen fitness are explored through a series of life-history trait trade-offs. Coupling trade-offs between pathogen yield and pathogen speed of kill and the presence of a synergist favour parasites that have faster speeds of kill. This evolutionary change in pathogen characteristics is predicted to lead to stable population dynamics. Evolutionary analysis of tolerance of the synergist (strength of synergy) and lethal pathogen yield show that decreasing tolerance allows alternative pathogen strategies to invade and replace extant strategies. This evolutionary change is likely to destabilise the host-pathogen interaction leading to population cycles. Correlated trait effects between speed of kill and tolerance (strength of synergy) show how these traits can interact to affect the potential for the coexistence of multiple pathogen strategies. Understanding the consequences of these evolutionary relationships is important for the both the evolutionary and population dynamics of host-pathogen interactions.     

The Relationship between Host Lifespan and Pathogen Reservoir Potential: An Analysis in the System Arabidopsis thaliana-Cucumber mosaic virus

Identification of the determinants of pathogen reservoir potential is central to understand disease emergence. It has been proposed that host lifespan is one such determinant: short-lived hosts will invest less in costly defenses against pathogens, so that they will be more susceptible to infection, more competent as sources of infection and/or will sustain larger vector populations, thus being effective reservoirs for the infection of long-lived hosts. This hypothesis is sustained by analyses of different hosts of multihost pathogens, but not of different genotypes of the same host species. Here we examined this hypothesis by comparing two genotypes of the plant Arabidopsis thaliana that differ largely both in life-span and in tolerance to its natural pathogen Cucumber mosaic virus (CMV). Experiments with the aphid vector Myzus persicae showed that both genotypes were similarly competent as sources for virus transmission, but the short-lived genotype was more susceptible to infection and was able to sustain larger vector populations. To explore how differences in defense against CMV and its vector relate to reservoir potential, we developed a model that was run for a set of experimentally-determined parameters, and for a realistic range of host plant and vector population densities. Model simulations showed that the less efficient defenses of the short-lived genotype resulted in higher reservoir potential, which in heterogeneous host populations may be balanced by the longer infectious period of the long-lived genotype. This balance was modulated by the demography of both host and vector populations, and by the genetic composition of the host population. Thus, within-species genetic diversity for lifespan and defenses against pathogens will result in polymorphisms for pathogen reservoir potential, which will condition within-population infection dynamics. These results are relevant for a better understanding of host-pathogen co-evolution, and of the dynamics of pathogen emergence.     

Modelling density-dependent resistance in insect-pathogen interactions.

We consider a mathematical model for a host-pathogen interaction where the host population is split into two categories: those susceptible to disease and those resistant to disease. Since the model was motivated by studies on insect populations, we consider a discrete-time model to reflect the discrete generations which are common among insect species. Whether an individual is born susceptible or resistant to disease depends on the local population levels at the start of each generation. In particular, we are interested in the case where the fraction of resistant individuals in the population increases as the total population increases. This may be seen as a positive feedback mechanism since disease is the only population control imposed upon the system. Moreover, it reflects recent experimental observations from noctuid moth-baculovirus interactions that pathogen resistance may increase with larval density. We find that the inclusion of a resistant class can stabilise unstable host-pathogen interactions but there is greatest regulation when the fraction born resistant is density independent. Nonetheless, inclusion of density dependence can still allow intrinsically unstable host-pathogen dynamics to be stabilised provided that this effect is sufficiently small. Moreover, inclusion of density-dependent resistance to disease allows the system to give rise to bistable dynamics in which the final outcome is dictated by the initial conditions for the model system. This has implications for the management of agricultural pests using biocontrol agents-in particular, it is suggested that the propensity for density-dependent resistance be determined prior to such a biocontrol attempt in order to be sure that this will result in the prevention of pest outbreaks, rather than their facilitation. Finally we consider how the cost of resistance to disease affects model outcomes and discover that when there is no cost to resistance, the model predicts stable periodic outbreaks of the insect population. The results are interpreted ecologically and future avenues for research to address the shortfalls in the present model system are discussed.     

Revealing mechanisms of infectious disease spread through empirical contact networks

The spread of pathogens fundamentally depends on the underlying contacts between individuals. Modeling the dynamics of infectious disease spread through contact networks, however, can be challenging due to limited knowledge of how an infectious disease spreads and its transmission rate. We developed a novel statistical tool, INoDS (Identifying contact Networks of infectious Disease Spread) that estimates the transmission rate of an infectious disease outbreak, establishes epidemiological relevance of a contact network in explaining the observed pattern of infectious disease spread and enables model comparison between different contact network hypotheses. We show that our tool is robust to incomplete data and can be easily applied to datasets where infection timings of individuals are unknown. We tested the reliability of INoDS using simulation experiments of disease spread on a synthetic contact network and find that it is robust to incomplete data and is reliable under different settings of network dynamics and disease contagiousness compared with previous approaches. We demonstrate the applicability of our method in two host-pathogen systems: Crithidia bombi in bumblebee colonies and Salmonella in wild Australian sleepy lizard populations. INoDS thus provides a novel and reliable statistical tool for identifying transmission pathways of infectious disease spread. In addition, application of INoDS extends to understanding the spread of novel or emerging infectious disease, an alternative approach to laboratory transmission experiments, and overcoming common data-collection constraints.     

Coincidental Loss of Bacterial Virulence in Multi-Enemy Microbial Communities

The coincidental virulence evolution hypothesis suggests that outside-host selection, such as predation, parasitism and resource competition can indirectly affect the virulence of environmentally-growing bacterial pathogens. While there are some examples of coincidental environmental selection for virulence, it is also possible that the resource acquisition and enemy defence is selecting against it. To test these ideas we conducted an evolutionary experiment by exposing the opportunistic pathogen bacterium Serratia marcescens to the particle-feeding ciliate Tetrahymena thermophila, the surface-feeding amoeba Acanthamoeba castellanii, and the lytic bacteriophage Semad11, in all possible combinations in a simulated pond water environment. After 8 weeks the virulence of the 384 evolved clones were quantified with fruit fly Drosophila melanogaster oral infection model, and several other life-history traits were measured. We found that in comparison to ancestor bacteria, evolutionary treatments reduced the virulence in most of the treatments, but this reduction was not clearly related to any changes in other life-history traits. This suggests that virulence traits do not evolve in close relation with these life-history traits, or that different traits might link to virulence in different selective environments, for example via resource allocation trade-offs.     

Metabolic network model of a human oral pathogen

The microbial community present in the human mouth is engaged in a complex network of diverse metabolic activities. In addition to serving as energy and building-block sources, metabolites are key players in interspecies and host-pathogen interactions. Metabolites are also implicated in triggering the local inflammatory response, which can affect systemic conditions such as atherosclerosis, obesity, and diabetes. While the genome of several oral pathogens has been sequenced, quantitative understanding of the metabolic functions of any oral pathogen at the system level has not been explored yet. Here we pursue the computational construction and analysis of the genome-scale metabolic network of Porphyromonas gingivalis, a gram-negative anaerobe that is endemic in the human population and largely responsible for adult periodontitis. Integrating information from the genome, online databases, and literature screening, we built a stoichiometric model that encompasses 679 metabolic reactions. By using flux balance approaches and automated network visualization, we analyze the growth capacity under amino-acid-rich medium and provide evidence that amino acid preference and cytotoxic by-product secretion rates are suitably reproduced by the model. To provide further insight into the basic metabolic functions of P. gingivalis and suggest potential drug targets, we study systematically how the network responds to any reaction knockout. We focus specifically on the lipopolysaccharide biosynthesis pathway and identify eight putative targets, one of which has been recently verified experimentally. The current model, which is amenable to further experimental testing and refinements, could prove useful in evaluating the oral microbiome dynamics and in the development of novel biomedical applications.     

Deconstructing host-pathogen interactions in Drosophila

Many of the cellular mechanisms underlying host responses to pathogens have been well conserved during evolution. As a result, Drosophila can be used to deconstruct many of the key events in host-pathogen interactions by using a wealth of well-developed molecular and genetic tools. In this review, we aim to emphasize the great leverage provided by the suite of genomic and classical genetic approaches available in flies for decoding details of host-pathogen interactions; these findings can then be applied to studies in higher organisms. We first briefly summarize the general strategies by which Drosophila resists and responds to pathogens. We then focus on how recently developed genome-wide RNA interference (RNAi) screens conducted in cells and flies, combined with classical genetic methods, have provided molecular insight into host-pathogen interactions, covering examples of bacteria, fungi and viruses. Finally, we discuss novel strategies for how flies can be used as a tool to examine how specific isolated virulence factors act on an intact host.     

Real-time analysis of Drosophila post-embryonic haemocyte behaviour

Background

The larval stage of the model organism Drosophila is frequently used to study host-pathogen interactions. During embryogenesis the cellular arm of the immune response, consisting of macrophage-like cells known as plasmatocytes, is extremely motile and functions to phagocytise pathogens and apoptotic bodies, as well as produce extracellular matrix. The cellular branch of the larval (post-embryonic) innate immune system consists of three cell types—plasmatocytes, crystal cells and lamellocytes—which are involved in the phagocytosis, encapsulation and melanisation of invading pathogens. Post-embryonic haemocyte motility is poorly understood thus further characterisation is required, for the purpose of standardisation.

Methodology

In order to examine post-embryonic haemocyte cytoskeletal dynamics or migration, the most commonly used system is in vitro cell lines. The current study employs an ex vivo system (an adaptation of in vitro cell incubation using primary cells), in which primary larval or pre-pupal haemocytes are isolated for short term analysis, in order to discover various aspects of their behaviour during events requiring cytoskeleton dynamics.

Significance

The ex vivo method allows for real-time analysis and manipulation of primary post-embryonic haemocytes. This technique was used to characterise, and potentially standardised, larval and pre-pupal haemocyte cytoskeleton dynamics, assayed on different extracellular matrices. Using this method it was determined that, while larval haemocytes are unable to migrate, haemocytes recovered from pre-pupae are capable of migration.     

The Human-Bacterial Pathogen Protein Interaction Networks of Bacillus anthracis,Francisella tularensis,and Yersinia pestis

Background

Bacillus anthracis, Francisella tularensis, and Yersinia pestis are bacterial pathogens that can cause anthrax, lethal acute pneumonic disease, and bubonic plague, respectively, and are listed as NIAID Category A priority pathogens for possible use as biological weapons. However, the interactions between human proteins and proteins in these bacteria remain poorly characterized leading to an incomplete understanding of their pathogenesis and mechanisms of immune evasion.

Methodology

In this study, we used a high-throughput yeast two-hybrid assay to identify physical interactions between human proteins and proteins from each of these three pathogens. From more than 250,000 screens performed, we identified 3,073 human-B. anthracis, 1,383 human-F. tularensis, and 4,059 human-Y. pestis protein-protein interactions including interactions involving 304 B. anthracis, 52 F. tularensis, and 330 Y. pestis proteins that are uncharacterized. Computational analysis revealed that pathogen proteins preferentially interact with human proteins that are hubs and bottlenecks in the human PPI network. In addition, we computed modules of human-pathogen PPIs that are conserved amongst the three networks. Functionally, such conserved modules reveal commonalities between how the different pathogens interact with crucial host pathways involved in inflammation and immunity.

Significance

These data constitute the first extensive protein interaction networks constructed for bacterial pathogens and their human hosts. This study provides novel insights into host-pathogen interactions.     

Ancient Host–Pathogen Associations Maintained by Specificity of Chemotaxis and Antibiosis

Switching by parasites to novel hosts has profound effects on ecological and evolutionary disease dynamics. Switching requires that parasites are able to establish contact with novel hosts and to overcome host defenses. For most host–parasite associations, it is unclear as to what specific mechanisms prevent infection of novel hosts. Here, we show that parasitic fungal species in the genus Escovopsis, which attack and consume the fungi cultivated by fungus-growing ants, are attracted to their hosts via chemotaxis. This response is host-specific: Escovopsis spp. grow towards their natural host cultivars more rapidly than towards other closely related fungi. Moreover, the cultivated fungi secrete compounds that can suppress Escovopsis growth. These antibiotic defenses are likewise specific: in most interactions, cultivars can inhibit growth of Escovopsis spp. not known to infect them in nature but cannot inhibit isolates of their naturally infecting pathogens . Cases in which cultivars are susceptible to novel Escovopsis are limited to a narrow set of host–parasite strain combinations. Targeted chemotactic and antibiotic responses therefore explain why Escovopsis pathogens do not readily switch to novel hosts, consequently constraining long-term dynamics of host–parasite coevolution within this ancient association.