Metapopulation dynamics of Escherichia coli O157 in cattle: an exploratory model.

Livestock movement is thought to be a risk factor for the transmission of infectious diseases of farm animals. Simple mathematical models were constructed for the transmission of Escherichia coli serogroup O157 between Scottish cattle farms, and the models were used in a preliminary exploration of factors contributing to the levels of infection reported in the field. The results suggest that cattle movement can make a significant contribution to the observed prevalence of E. coli O157-positive farms, but is not by itself sufficient for the persistence of E. coli O157. The results also suggest that cattle movements involving infected farms with cattle shedding an exceptional amount of E. coli O157, 'super-shedders', also make a substantial contribution to the prevalence of infected farms. Simulations indicate that E. coli O157 could have reached the currently observed prevalence levels in less than a decade. Implications and findings from our models are discussed in relation to possible control of E. coli O157 in Scottish cattle.     

The dynamic balance of import and export of zinc in Escherichia coli suggests a heterogeneous population response to stress

Zinc is essential for life, but toxic in excess. Thus all cells must control their internal zinc concentration. We used a systems approach, alternating rounds of experiments and models, to further elucidate the zinc control systems in Escherichia coli. We measured the response to zinc of the main specific zinc import and export systems in the wild-type, and a series of deletion mutant strains. We interpreted these data with a detailed mathematical model and Bayesian model fitting routines. There are three key findings: first, that alternate, non-inducible importers and exporters are important. Second, that an internal zinc reservoir is essential for maintaining the internal zinc concentration. Third, our data fitting led us to propose that the cells mount a heterogeneous response to zinc: some respond effectively, while others die or stop growing. In a further round of experiments, we demonstrated lower viable cell counts in the mutant strain tested exposed to excess zinc, consistent with this hypothesis. A stochastic model simulation demonstrated considerable fluctuations in the cellular levels of the ZntA exporter protein, reinforcing this proposal. We hypothesize that maintaining population heterogeneity could be a bet-hedging response allowing a population of cells to survive in varied and fluctuating environments.     

In-roads to the spread of antibiotic resistance: regional patterns of microbial transmission in northern coastal Ecuador

The evolution of antibiotic resistance (AR) increases treatment cost and probability of failure, threatening human health worldwide. The relative importance of individual antibiotic use, environmental transmission and rates of introduction of resistant bacteria in explaining community AR patterns is poorly understood. Evaluating their relative importance requires studying a region where they vary. The construction of a new road in a previously roadless area of northern coastal Ecuador provides a valuable natural experiment to study how changes in the social and natural environment affect the epidemiology of resistant Escherichia coli. We conducted seven bi-annual 15 day surveys of AR between 2003 and 2008 in 21 villages. Resistance to both ampicillin and sulphamethoxazole was the most frequently observed profile, based on antibiogram tests of seven antibiotics from 2210 samples. The prevalence of enteric bacteria with this resistance pair in the less remote communities was 80 per cent higher than in more remote communities (OR = 1.8 [1.3, 2.3]). This pattern could not be explained with data on individual antibiotic use. We used a transmission model to help explain this observed discrepancy. The model analysis suggests that both transmission and the rate of introduction of resistant bacteria into communities may contribute to the observed regional scale AR patterns, and that village-level antibiotic use rate determines which of these two factors predominate. While usually conceived as a main effect on individual risk, antibiotic use rate is revealed in this analysis as an effect modifier with regard to community-level risk of resistance.     

Microbial synthesis of core/shell gold/palladium nanoparticles for applications in green chemistry

We report a novel biochemical method based on the sacrificial hydrogen strategy to synthesize bimetallic gold (Au)–palladium (Pd) nanoparticles (NPs) with a core/shell configuration. The ability of Escherichia coli cells supplied with H₂ as electron donor to rapidly precipitate Pd(II) ions from solution is used to promote the reduction of soluble Au(III). Pre-coating cells with Pd(0) (bioPd) dramatically accelerated Au(III) reduction, with the Au(III) reduction rate being dependent upon the initial Pd loading by mass on the cells. Following Au(III) addition, the bioPd–Au(III) mixture rapidly turned purple, indicating the formation of colloidal gold. Mapping of bio-NPs by energy dispersive X-ray microanalysis suggested Au-dense core regions and peripheral Pd but only Au was detected by X-ray diffraction (XRD) analysis. However, surface analysis of cleaned NPs by cyclic voltammetry revealed large Pd surface sites, suggesting, since XRD shows no crystalline Pd component, that layers of Pd atoms surround Au NPs. Characterization of the bimetallic particles using X-ray absorption spectroscopy confirmed the existence of Au-rich core and Pd-rich shell type bimetallic biogenic NPs. These showed comparable catalytic activity to chemical counterparts with respect to the oxidation of benzyl alcohol, in air, and at a low temperature (90°C).     

Rational spatio-temporal strategies for controlling a Chagas disease vector in urban environments

The rational design of interventions is critical to controlling communicable diseases, especially in urban environments. In the case of the Chagas disease vector Triatoma infestans, successful control is stymied by the return of the insect after the effectiveness of the insecticide wanes. Here, we adapt a genetic algorithm, originally developed for the travelling salesman problem, to improve the spatio-temporal design of insecticide campaigns against T. infestans, in a complex urban environment. We find a strategy that reduces the expected instances of vector return 34-fold compared with the current strategy of sequential insecticide application to spatially contiguous communities. The relative success of alternative control strategies depends upon the duration of the effectiveness of the insecticide, and it shows chaotic fluctuations in response to unforeseen delays in a control campaign. We use simplified models to analyse the outcomes of qualitatively different spatio-temporal strategies. Our results provide a detailed procedure to improve control efforts for an urban Chagas disease vector, as well as general guidelines for improving the design of interventions against other disease agents in complex environments.     

Population structure in the Neisseria, and the biological significance of fuzzy species

Phenotypic and genetic variation in bacteria can take bewilderingly complex forms even within a single genus. One of the most intriguing examples of this is the genus Neisseria, which comprises both pathogens and commensals colonizing a variety of body sites and host species, and causing a range of disease. Complex relatedness among both named species and previously identified lineages of Neisseria makes it challenging to study their evolution. Using the largest publicly available collection of bacterial sequence data in combination with a population genetic analysis and experiment, we probe the contribution of inter-species recombination to neisserial population structure, and specifically whether it is more common in some strains than others. We identify hybrid groups of strains containing sequences typical of more than one species. These groups of strains, typical of a fuzzy species, appear to have experienced elevated rates of inter-species recombination estimated by population genetic analysis and further supported by transformation experiments. In particular, strains of the pathogen Neisseria meningitidis in the fuzzy species boundary appear to follow a different lifestyle, which may have considerable biological implications concerning distribution of novel resistance elements and meningococcal vaccine development. Despite the strong evidence for negligible geographical barriers to gene flow within the population, exchange of genetic material still shows directionality among named species in a non-uniform manner.     

Constraint-based network model of pathogen–immune system interactions

Pathogenic bacteria such as Bordetella bronchiseptica modulate host immune responses to enable their establishment and persistence; however, the immune response is generally successful in clearing these bacteria. Here, we model the dynamic outcome of the interplay between host immune components and B. bronchiseptica virulence factors. The model extends our previously published interaction network of B. bronchiseptica and includes the existing experimental information on the relative timing of IL10 and IFNγ activation in the form of qualitative inequalities. The current model improves the previous one in two directions: (i) by augmenting the network with new nodes with specific function in T helper cell differentiation and effector mechanisms and (ii) by using a dynamic approach that allows us to quantify node states and mechanisms revealed to be important from our previous model. The model makes predictions about the time scales of each process, the activity thresholds of each node and novel regulatory interactions. For example, the model predicts that the activity threshold of IL4 is higher than that of IL12 and that pro-inflammatory cytokines regulate the activity of Th2 cells. Some of these predictions are supported by the literature, and many can serve as targets of future experiments.     

A combined within-host and between-hosts modelling framework for the evolution of resistance to antimalarial drugs

The spread of drug resistance represents a significant challenge to many disease control efforts. The evolution of resistance is a complex process influenced by transmission dynamics between hosts as well as infection dynamics within these hosts. This study aims to investigate how these two processes combine to impact the evolution of resistance in malaria parasites. We introduce a stochastic modelling framework combining an epidemiological model of Plasmodium transmission and an explicit within-human infection model for two competing strains. Immunity, treatment and resistance costs are included in the within-host model. We show that the spread of resistance is generally less likely in areas of intense transmission, and therefore of increased competition between strains, an effect exacerbated when costs of resistance are higher. We also illustrate how treatment influences the spread of resistance, with a trade-off between slowing resistance and curbing disease incidence. We show that treatment coverage has a stronger impact on disease prevalence, whereas treatment efficacy primarily affects resistance spread, suggesting that coverage should constitute the primary focus of control efforts. Finally, we illustrate the importance of feedbacks between modelling scales. Overall, our results underline the importance of concomitantly modelling the evolution of resistance within and between hosts.     

Invasion,persistence and control in epidemic models for plant pathogens: the effect of host demography

Many epidemiological models for plant disease include host demography to describe changes in the availability of susceptible tissue for infection. We compare the effects of using two commonly used formulations for host growth, one linear and the other nonlinear, upon the outcomes for invasion, persistence and control of pathogens in a widely used, generic model for botanical epidemics. The criterion for invasion, reflected in the basic reproductive number, R₀, is unaffected by host demography: R₀ is simply a function of epidemiological parameters alone. When, however, host growth is intrinsically nonlinear, unexpected results arise for persistence and the control of disease. The endemic level of infection (I_∞) also depends upon R₀. We show, however, that the sensitivity of I_∞ to changes in R₀ > 1 depends upon which underlying epidemiological parameter is changed. Increasing R₀ by shortening the infectious period results in a monotonic increase in I_∞. If, however, an increase in R₀ is driven by increases in transmission rates or by decreases in the decay of free-living inoculum, I_∞ first increases (R₀ < 2), but then decreases (R₀ > 2). This counterintuitive result means that increasing the intensity of control can result in more endemic infection.     

A metapopulation modelling framework for gonorrhoea and other sexually transmitted infections in heterosexual populations

Gonorrhoea continues to be a public health problem in the UK, and is the second most common bacterial sexually transmitted infection (STI) after chlamydia. In the UK, gonorrhoea is disproportionately concentrated in epidemiologically distinct subpopulations, with much higher incidence rates in young people, some ethnic minorities and inner city subpopulations. The original model of STI transmission proposed by Hethcote and Yorke explained some of these features through the concept of the ‘core group’. Since then, several authors have modified the original model approach to include multiple sexual activity classes, but found this modelling approach to be inadequate when applied to low-prevalence settings such as the UK. We present a metapopulation framework for modelling gonorrhoea and other STIs. The model proposes that the epidemiology of gonorrhoea is largely driven by subpopulations with higher than average concentrations of individuals with high sexual risk activity. We show how this conceptualization of gonococcal epidemiology overcomes key limitations associated with some of the prior efforts to model gonorrhoea. We also use the model to explain several epidemiological features of gonorrhoea, such as its asymmetric distribution across subpopulations, and the contextual risk experienced by members of at-risk subpopulations. Finally, we extend the model to explain the distribution of other STIs, using chlamydia as an example of a more ubiquitous bacterial STI.     

The effect of individual variation on the structure and function of interaction networks in harvester ants

Social insects exhibit coordinated behaviour without central control. Local interactions among individuals determine their behaviour and regulate the activity of the colony. Harvester ants are recruited for outside work, using networks of brief antennal contacts, in the nest chamber closest to the nest exit: the entrance chamber. Here, we combine empirical observations, image analysis and computer simulations to investigate the structure and function of the interaction network in the entrance chamber. Ant interactions were distributed heterogeneously in the chamber, with an interaction hot-spot at the entrance leading further into the nest. The distribution of the total interactions per ant followed a right-skewed distribution, indicating the presence of highly connected individuals. Numbers of ant encounters observed positively correlated with the duration of observation. Individuals varied in interaction frequency, even after accounting for the duration of observation. An ant''s interaction frequency was explained by its path shape and location within the entrance chamber. Computer simulations demonstrate that variation among individuals in connectivity accelerates information flow to an extent equivalent to an increase in the total number of interactions. Individual variation in connectivity, arising from variation among ants in location and spatial behaviour, creates interaction centres, which may expedite information flow.     

A dose and time response Markov model for the in-host dynamics of infection with intracellular bacteria following inhalation: with application to Francisella tularensis

In a novel approach, the standard birth–death process is extended to incorporate a fundamental mechanism undergone by intracellular bacteria, phagocytosis. The model accounts for stochastic interaction between bacteria and cells of the immune system and heterogeneity in susceptibility to infection of individual hosts within a population. Model output is the dose–response relation and the dose-dependent distribution of time until response, where response is the onset of symptoms. The model is thereafter parametrized with respect to the highly virulent Schu S4 strain of Francisella tularensis, in the first such study to consider a biologically plausible mathematical model for early human infection with this bacterium. Results indicate a median infectious dose of about 23 organisms, which is higher than previously thought, and an average incubation period of between 3 and 7 days depending on dose. The distribution of incubation periods is right-skewed up to about 100 organisms and symmetric for larger doses. Moreover, there are some interesting parallels to the hypotheses of some of the classical dose–response models, such as independent action (single-hit model) and individual effective dose (probit model). The findings of this study support experimental evidence and postulations from other investigations that response is, in fact, influenced by both in-host and between-host variability.     

An analysis of synergistic and antagonistic behavior during BTEX removal in batch system using response surface methodology

The removal of benzene, toluene, ethylbenzene and xylene (BTEX) as quaternary mixtures were studied in batch systems using a well-defined mixed microbial culture. The synergistic and antagonistic effects of total BTEX removal (BTEXT-RE) due to the presence of mixed substrate was evaluated through experiments designed by response surface methodology (RSM). The low and high concentrations of individual BTEX were 15 and 75 mg l(-1), respectively. The results showed that, increasing the concentration of xylene increased the cumulative BTEX removal (BTEXT-RE), however the reverse occurred when benzene concentrations were increased from low to high levels. A mixed response of increasing and decreasing trend in the BTEXT-RE value was observed when either of toluene or ethylbenzene concentration was increased. When the concentrations of individual BTEX compounds were 30 mg l(-1), the BTEXT-RE was about 58%. Complete BTEXT-RE was achieved at optimal BTEX concentrations of 48.1, 45.6, 49.3 and 56.6 mg l(-1). The RSM approach was found efficient in explaining the main, squared and interaction effects among individual BTEX concentrations on the BTEXT-RE in a more statistically meaningful way.     

North–South divide: contrasting impacts of climate change on crop yields in Scotland and England

Effects of climate change on productivity of agricultural crops in relation to diseases that attack them are difficult to predict because they are complex and nonlinear. To investigate these crop–disease–climate interactions, UKCIP02 scenarios predicting UK temperature and rainfall under high- and low-CO₂ emission scenarios for the 2020s and 2050s were combined with a crop-simulation model predicting yield of fungicide-treated winter oilseed rape and with a weather-based regression model predicting severity of phoma stem canker epidemics. The combination of climate scenarios and crop model predicted that climate change will increase yield of fungicide-treated oilseed rape crops in Scotland by up to 0.5 t ha⁻¹ (15%). In contrast, in southern England the combination of climate scenarios, crop, disease and yield loss models predicted that climate change will increase yield losses from phoma stem canker epidemics to up to 50 per cent (1.5 t ha⁻¹) and greatly decrease yield of untreated winter oilseed rape. The size of losses is predicted to be greater for winter oilseed rape cultivars that are susceptible than for those that are resistant to the phoma stem canker pathogen Leptosphaeria maculans. Such predictions illustrate the unexpected, contrasting impacts of aspects of climate change on crop–disease interactions in agricultural systems in different regions.     

Ambiguities in Powder Indexing: Conjunction of a Ternary and Binary Lattice Metric Singularity in the Cubic System

A lattice metric singularity occurs when unit cells defining two (or more) lattices yield the identical set of unique calculated d-spacings. The existence of such singularities, therefore, has a practical and theoretical impact on the indexing of powder patterns. For example, in experimental practice an indexing program may find only the lower symmetry member of a singularity. Obviously, it is important to recognize such cases and know how to proceed. Recently, we described:

1. a binary singularity involving a monoclinic and a rhombohedral lattice in a subcell-supercell relationship and
2. a second type of singularity—a ternary singularity–in which two of the three lattices are in a derivative composite relationship. In this work, we describe a ternary lattice metric singularity involving a cubic P, a tetragonal P, and an orthorhombic C lattice. Furthermore, there is a binary singularity, involving a hexagonal P and orthorhombic P lattice, which is characterized by a set of unique d-spacings very close to that of the ternary singularity. The existence of such singularities is more common than once thought and requires a paradigm shift in experimental practice. In addition singularities provide opportunities in material design as they point to highly specialized lattices that may be associated with unusual physical properties.