Search

U-insertion/deletion (U-indel) RNA editing in trypanosome mitochondria is directed by guide RNAs (gRNAs). This editing may developmentally control respiration in bloodstream forms (BSF) and insect procyclic forms (PCF). Holo-editosomes include the accessory RNA Editing Substrate Binding Complex (RESC) and RNA Editing Helicase 2 Complex (REH2C), but the specific proteins controlling differential editing remain unknown. Also, RNA editing appears highly error prone because most U-indels do not match the canonical pattern. However, despite extensive non-canonical editing of unknown functions, accurate canonical editing is required for normal cell growth. In PCF, REH2C controls editing fidelity in RESC-bound mRNAs. Here, we report that KREH2, a REH2C-associated helicase, developmentally controls programmed non-canonical editing, including an abundant 3′ element in ATPase subunit 6 (A6) mRNA. The 3′ element sequence is directed by a proposed novel regulatory gRNA. In PCF, KREH2 RNAi-knockdown up-regulates the 3′ element, which establishes a stable structure hindering element removal by canonical initiator-gRNA-directed editing. In BSF, KREH2-knockdown does not up-regulate the 3′ element but reduces its high abundance. Thus, KREH2 differentially controls extensive non-canonical editing and associated RNA structure via a novel regulatory gRNA, potentially hijacking factors as a ‘molecular sponge’. Furthermore, this gRNA is bifunctional, serving in canonical CR4 mRNA editing whilst installing a structural element in A6 mRNA.

Mitochondrial DNA of protists of order Kinetoplastida comprises thousands of interlinked circular molecules arranged in a network. There are two types of molecules called minicircles and maxicircles. Minicircles encode guide RNA (gRNA) genes whose transcripts mediate post-transcriptional editing of maxicircle encoded genes. Minicircles are diverse. The human sleeping sickness parasite Trypanosoma brucei has one of the most diverse sets of minicircle classes of all studied trypanosomatids with hundreds of different classes, each encoding one to four genes mainly within cassettes framed by 18 bp inverted repeats. A third of cassettes have no identifiable gRNA genes even though their sequence structures are similar to cassettes with identifiable genes. Only recently have almost all minicircle classes for some subspecies and isolates of T. brucei been sequenced and annotated with corresponding verification of gRNA expression by small-RNA transcriptome data. These data sets provide a rich resource for understanding the structure of minicircle classes, cassettes and gRNA genes and their transcription. Here, we provide a statistical description of the functionality, expression status, structure and sequence of gRNA genes in a differentiation-competent, laboratory-adapted strain of T. brucei. We obtain a clearer definition of what is a gRNA gene. Our analysis supports the idea that many, if not all, cassettes without an identifiable gRNA gene contain decaying remnants of once functional gRNA genes. Finally, we report several new, unexplained discoveries such as the association between cassette position on the minicircle and gene expression and functionality, and the association between gene initiation sequence and anchor position.

The World Health Organization targeted

Persistent pathogens have evolved to avoid elimination by the mammalian immune system including mechanisms to evade complement. Infections with African trypanosomes can persist for years and cause human and animal disease throughout sub-Saharan Africa. It is not known how trypanosomes limit the action of the alternative complement pathway. Here we identify an African trypanosome receptor for mammalian factor H, a negative regulator of the alternative pathway. Structural studies show how the receptor binds ligand, leaving inhibitory domains of factor H free to inactivate complement C3b deposited on the trypanosome surface. Receptor expression is highest in developmental stages transmitted to the tsetse fly vector and those exposed to blood meals in the tsetse gut. Receptor gene deletion reduced tsetse infection, identifying this receptor as a virulence factor for transmission. This demonstrates how a pathogen evolved a molecular mechanism to increase transmission to an insect vector by exploitation of a mammalian complement regulator., African trypanosome infections can persist for years, but immune evasion mechanisms are not fully understood. Here, Macleod et al. identify a trypanosome receptor for mammalian factor H, a negative regulator of the alternative complement pathway, that increases parasite transmission to tsetse flies.

The World Health Organization targeted Trypanosoma brucei gambiense (Tbg) human African trypanosomiasis for elimination of transmission by 2030. Sensitive molecular markers that specifically detect Tbg type 1 (Tbg1) parasites will be important tools to assist in reaching this goal. Here, we aim at improving molecular diagnosis of Tbg1 infections by targeting the abundant mitochondrial minicircles within the kinetoplast of Trypanosoma brucei parasites. Using Next-Generation Sequencing of total cellular DNA extracts, we assembled and annotated the kinetoplast genome and investigated minicircle sequence diversity in 38 animal- and human-infective trypanosome strains. Computational analyses recognized a total of 241 Minicircle Sequence Classes as Tbg1-specific, of which three were shared by the 18 studied Tbg1 strains. We then developed a novel multiplex quantitative PCR assay (g-qPCR3) targeting one Tbg1-specific minicircle and three Tbg1-specific or Trypanozoon-specific markers. Molecular analyses revealed that the minicircle-based assay is applicable on animals and is as specific as the TgsGP-based assay, the current golden standard for molecular detection of Tbg1. The median copy number of the targeted minicircle was equal to eight, suggesting that our minicircle-based assay may be used for the sensitive detection of Tbg1 parasites. Finally, annotation of the targeted minicircle sequence indicated that it encodes genes essential for the survival of the parasite, and will thus likely be preserved in natural Tbg1 populations. These results demonstrated that our minicircle-based assay is a promising new tool for reliable and sensitive detection of Tbg1 infections in humans and animals.

Mitochondrial DNA of protists of order

Kinetoplastids are protists defined by one of the most complex mitochondrial genomes in nature, the kinetoplast. In the sleeping sickness parasite Trypanosoma brucei, the kinetoplast is a chain mail-like network of two types of interlocked DNA molecules: a few dozen ∼23-kb maxicircles (homologs of the mitochondrial genome of other eukaryotes) and thousands of ∼1-kb minicircles. Maxicircles encode components of respiratory chain complexes and the mitoribosome. Several maxicircle-encoded mRNAs undergo extensive post-transcriptional RNA editing via addition and deletion of uridines. The process is mediated by hundreds of species of minicircle-encoded guide RNAs (gRNAs), but the precise number of minicircle classes and gRNA genes was unknown. Here we present the first essentially complete assembly and annotation of the kinetoplast genome of T. brucei. We have identified 391 minicircles, encoding not only ∼930 predicted ‘canonical’ gRNA genes that cover nearly all known editing events (accessible via the web at http://hank.bio.ed.ac.uk), but also ∼370 ‘non-canonical’ gRNA genes of unknown function. Small RNA transcriptome data confirmed expression of the majority of both categories of gRNAs. Finally, we have used our data set to refine definitions for minicircle structure and to explore dynamics of minicircle copy numbers.

Infection can dramatically alter behavioural and physiological traits as hosts become sick and subsequently return to health. Such “sickness behaviours” include disrupted circadian rhythms in both locomotor activity and body temperature. Host sickness behaviours vary in pathogen species-specific manners but the influence of pathogen intraspecific variation is rarely studied. We examine how infection with the murine malaria parasite, Plasmodium chabaudi, shapes sickness in terms of parasite genotype-specific effects on host circadian rhythms. We reveal that circadian rhythms in host locomotor activity patterns and body temperature become differentially disrupted and in parasite genotype-specific manners. Locomotor activity and body temperature in combination provide more sensitive measures of health than commonly used virulence metrics for malaria (e.g. anaemia). Moreover, patterns of host disruption cannot be explained simply by variation in replication rate across parasite genotypes or the severity of anaemia each parasite genotype causes. It is well known that disruption to circadian rhythms is associated with non-infectious diseases, including cancer, type 2 diabetes, and obesity. Our results reveal that disruption of host circadian rhythms is a genetically variable virulence trait of pathogens with implications for host health and disease tolerance.

Significance Parasites are interesting models for studying speciation processes because they have a high potential for specialization, thanks to the intimate ecological association with their hosts and vectors. Yet little is known about the circumstances under which new parasite lineages emerge. Here we studied the genome diversity of parasites of the Leishmania braziliensis species complex that inhabit both Amazonian and Andean biotas in Peru. We identify three major parasite lineages that occupy particular ecological niches and show that these emerged during forestation changes over the past 150,000 y. We furthermore discovered that meiotic recombination between Amazonian and Andean lineages resulted in full-genome hybrids presenting mixed mitochondrial genomes, providing insights into the genetic consequences of hybridization in parasitic protozoa., The tropical Andes are an important natural laboratory to understand speciation in many taxa. Here we examined the evolutionary history of parasites of the Leishmania braziliensis species complex based on whole-genome sequencing of 67 isolates from 47 localities in Peru. We first show the origin of Andean Leishmania as a clade of near-clonal lineages that diverged from admixed Amazonian ancestors, accompanied by a significant reduction in genome diversity and large structural variations implicated in host–parasite interactions. Within the Andean species, patterns of population structure were strongly associated with biogeographical origin. Molecular clock and ecological niche modeling suggested that the history of diversification of the Andean lineages is limited to the Late Pleistocene and intimately associated with habitat contractions driven by climate change. These results suggest that changes in forestation over the past 150,000 y have influenced speciation and diversity of these Neotropical parasites. Second, genome-scale analyses provided evidence of meiotic-like recombination between Andean and Amazonian Leishmania species, resulting in full-genome hybrids. The mitochondrial genome of these hybrids consisted of homogeneous uniparental maxicircles, but minicircles originated from both parental species. We further show that mitochondrial minicircles—but not maxicircles—show a similar evolutionary pattern to the nuclear genome, suggesting that compatibility between nuclear-encoded mitochondrial genes and minicircle-encoded guide RNA genes is essential to maintain efficient respiration. By comparing full nuclear and mitochondrial genome ancestries, our data expand our appreciation on the genetic consequences of diversification and hybridization in parasitic protozoa.

Background The ability of malaria (Plasmodium) parasites to adjust investment into sexual transmission stages versus asexually replicating stages is well known, but plasticity in other traits underpinning the replication rate of asexual stages in the blood has received less attention. Such traits include burst size (the number of merozoites produced per schizont), the duration of the asexual cycle, and invasion preference for different ages of red blood cell (RBC). Methods Here, plasticity [environment (E) effects] and genetic variation [genotype (G) effects] in traits relating to asexual replication rate are examined for 4 genotypes of the rodent malaria parasite Plasmodium chabaudi. An experiment tested whether asexual dynamics differ between parasites infecting control versus anaemic hosts, and whether variation in replication rate can be explained by differences in burst size, asexual cycle, and invasion rates. Results The within-host environment affected each trait to different extents but generally had similar impacts across genotypes. The dynamics of asexual densities exhibited a genotype by environment effect (G×E), in which one of the genotypes increased replication rate more than the others in anaemic hosts. Burst size and cycle duration varied between the genotypes (G), while burst size increased and cycle duration became longer in anaemic hosts (E). Variation in invasion rates of differently aged RBCs was not explained by environmental or genetic effects. Plasticity in burst size and genotype are the only traits making significant contributions to the increase in asexual densities observed in anaemic hosts, together explaining 46.4% of the variation in replication rate. Conclusions That host anaemia induces several species of malaria parasites to alter conversion rate is well documented. Here, previously unknown plasticity in other traits underpinning asexual replication is revealed. These findings contribute to mounting evidence that malaria parasites deploy a suite of sophisticated strategies to maximize fitness by coping with, or exploiting the opportunities provided by, the variable within-host conditions experienced during infections. That genetic variation and genotype by environment interactions also shape these traits highlights their evolutionary potential. Asexual replication rate is a major determinant of virulence and so, understanding the evolution of virulence requires knowledge of the ecological (within-host environment) and genetic drivers of variation among parasites. Electronic supplementary material The online version of this article (10.1186/s12936-019-2857-0) contains supplementary material, which is available to authorized users.

Malaria infection is often accompanied by periodic fevers, triggered by synchronous cycles of parasite replication within the host. The degree of synchrony in parasite development influences the efficacy of drugs and immune defenses and is therefore relevant to host health and infectiousness. Synchrony is thought to vary over the course of infection and across different host-parasite genotype or species combinations, but the evolutionary significance - if any - of this diversity remains elusive. Standardized methods are lacking, but the most common metric for quantifying synchrony is the percentage of parasites in a particular developmental stage. We use a heuristic model to show that this metric is often unacceptably biased. Methodological challenges must be addressed to characterize diverse patterns of synchrony and their consequences for disease severity and spread.

Circadian rhythms enable organisms to synchronise the processes underpinning survival and reproduction to anticipate daily changes in the external environment. Recent work shows that daily (circadian) rhythms also enable parasites to maximise fitness in the context of ecological interactions with their hosts. Because parasite rhythms matter for their fitness, understanding how they are regulated could lead to innovative ways to reduce the severity and spread of diseases. Here, we examine how host circadian rhythms influence rhythms in the asexual replication of malaria parasites. Asexual replication is responsible for the severity of malaria and fuels transmission of the disease, yet, how parasite rhythms are driven remains a mystery. We perturbed feeding rhythms of hosts by 12 hours (i.e. diurnal feeding in nocturnal mice) to desynchronise the host’s peripheral oscillators from the central, light-entrained oscillator in the brain and their rhythmic outputs. We demonstrate that the rhythms of rodent malaria parasites in day-fed hosts become inverted relative to the rhythms of parasites in night-fed hosts. Our results reveal that the host’s peripheral rhythms (associated with the timing of feeding and metabolism), but not rhythms driven by the central, light-entrained circadian oscillator in the brain, determine the timing (phase) of parasite rhythms. Further investigation reveals that parasite rhythms correlate closely with blood glucose rhythms. In addition, we show that parasite rhythms resynchronise to the altered host feeding rhythms when food availability is shifted, which is not mediated through rhythms in the host immune system. Our observations suggest that parasites actively control their developmental rhythms. Finally, counter to expectation, the severity of disease symptoms expressed by hosts was not affected by desynchronisation of their central and peripheral rhythms. Our study at the intersection of disease ecology and chronobiology opens up a new arena for studying host-parasite-vector coevolution and has broad implications for applied bioscience.Author summaryHow cycles of asexual replication by malaria parasites are coordinated to occur in synchrony with the circadian rhythms of the host is a long-standing mystery. We reveal that rhythms associated with the time-of-day that hosts feed are responsible for the timing of rhythms in parasite development. Specifically, we altered host feeding time to phase-shift peripheral rhythms, whilst leaving rhythms driven by the central circadian oscillator in the brain unchanged. We found that parasite developmental rhythms remained synchronous but changed their phase, by 12 hours, to follow the timing of host feeding. Furthermore, our results suggest that parasites themselves schedule rhythms in their replication to coordinate with rhythms in glucose in the host’s blood, rather than have rhythms imposed upon them by, for example, host immune responses. Our findings reveal a novel relationship between hosts and parasites that if disrupted, could reduce both the severity and transmission of malaria infection.

Circadian rhythms enable organisms to synchronise the processes underpinning survival and reproduction to anticipate daily changes in the external environment. Recent work shows that daily (circadian) rhythms also enable parasites to maximise fitness in the context of ecological interactions with their hosts. Because parasite rhythms matter for their fitness, understanding how they are regulated could lead to innovative ways to reduce the severity and spread of diseases. Here, we examine how host circadian rhythms influence rhythms in the asexual replication of malaria parasites. Asexual replication is responsible for the severity of malaria and fuels transmission of the disease, yet, how parasite rhythms are driven remains a mystery. We perturbed feeding rhythms of hosts by 12 hours (i.e. diurnal feeding in nocturnal mice) to desynchronise the host’s peripheral oscillators from the central, light-entrained oscillator in the brain and their rhythmic outputs. We demonstrate that the rhythms of rodent malaria parasites in day-fed hosts become inverted relative to the rhythms of parasites in night-fed hosts. Our results reveal that the host’s peripheral rhythms (associated with the timing of feeding and metabolism), but not rhythms driven by the central, light-entrained circadian oscillator in the brain, determine the timing (phase) of parasite rhythms. Further investigation reveals that parasite rhythms correlate closely with blood glucose rhythms. In addition, we show that parasite rhythms resynchronise to the altered host feeding rhythms when food availability is shifted, which is not mediated through rhythms in the host immune system. Our observations suggest that parasites actively control their developmental rhythms. Finally, counter to expectation, the severity of disease symptoms expressed by hosts was not affected by desynchronisation of their central and peripheral rhythms. Our study at the intersection of disease ecology and chronobiology opens up a new arena for studying host-parasite-vector coevolution and has broad implications for applied bioscience., Author summary How cycles of asexual replication by malaria parasites are coordinated to occur in synchrony with the circadian rhythms of the host is a long-standing mystery. We reveal that rhythms associated with the time-of-day that hosts feed are responsible for the timing of rhythms in parasite development. Specifically, we altered host feeding time to phase-shift peripheral rhythms, whilst leaving rhythms driven by the central circadian oscillator in the brain unchanged. We found that parasite developmental rhythms remained synchronous but changed their phase, by 12 hours, to follow the timing of host feeding. Furthermore, our results suggest that parasites themselves schedule rhythms in their replication to coordinate with rhythms in glucose in the host’s blood, rather than have rhythms imposed upon them by, for example, host immune responses. Our findings reveal a novel relationship between hosts and parasites that if disrupted, could reduce both the severity and transmission of malaria infection.

Marek's disease virus (MDV), a commercially important disease of poultry, has become substantially more virulent over the last 60 years. This evolution was presumably a consequence of changes in virus ecology associated with the intensification of the poultry industry. Here, we assess whether vaccination or reduced host life span could have generated natural selection, which favored more virulent strains. Using previously published experimental data, we estimated viral fitness under a range of cohort durations and vaccine treatments on broiler farms. We found that viral fitness maximized at intermediate virulence, as a result of a trade-off between virulence and transmission previously reported. Our results suggest that vaccination, acting on this trade-off, could have led to the evolution of increased virulence. By keeping the host alive, vaccination prolongs infectious periods of virulent strains. Improvements in host genetics and nutrition, which reduced broiler life spans below 50 days, could have also increased the virulence of the circulating MDV strains because shortened cohort duration reduces the impact of host death on viral fitness. These results illustrate the dramatic impact anthropogenic change can potentially have on pathogen virulence.

In this paper we investigate the within-host dynamics of the foot-and-mouth disease virus (FMDV) in cattle using previously published data for 8 experimentally infected cows. An 8-compartment, 14-parameter differential equation model was fitted to data collected from each cow every 24 h over the course of an infection on: (i) the concentration of FMDV genomes in the blood, (ii) the concentration of infectious virus in the blood, (iii) antibody levels, and (iv) interferon levels. Model parameters were estimated using maximum-likelihood methods. The likelihood surface was sampled using Markov chain Monte Carlo methods giving credible intervals for each of the model parameters. The model was able to capture the within-host dynamics well for 6 of the infections, with both the innate (type 1 interferon) and antibody responses playing key roles in determining the height and duration of peak levels of virus. There was considerable variation between virus dynamics in individual cattle which was only partly accounted for by inferred differences in the dose of virus received. A better understanding of the within-host dynamics also provides insights into the dynamics of infectiousness and the transmission of virus to new hosts.

During their life cycle, trypanosomes must overcome conflicting demands to ensure their survival and transmission. First, they must evade immunity without overwhelming the host. Second, they must generate and maintain transmission stages at sufficient levels to allow passage into their tsetse vector. Finally, they must rapidly commit to onward development when they enter the tsetse fly. On the basis of recent quantification and modelling of Trypanosoma brucei infection dynamics, we propose that the interplay between immune evasion and development achieves both infection chronicity and transmissibility. Moreover, we suggest that a novel form of bistable regulation ensures developmental commitment on entry into the tsetse fly midgut.

Parasite strategies for exploiting host resources are key determinants of disease severity (i.e., virulence) and infectiousness (i.e., transmission between hosts). By iterating the development of theory and empirical tests, we investigated whether variation in parasite traits across two genetically distinct clones of the rodent malaria parasite, Plasmodium chabaudi, explains differences in within-host infection dynamics and virulence. First, we experimentally tested key predictions of our earlier modeling work. As predicted, the more virulent genotype produced more progeny parasites per infected cell (burst size), but in contrast to predictions, invasion rates of red blood cells (RBCs) did not differ between the genotypes studied. Second, we further developed theory by confronting our earlier model with these new data, testing a new set of models that incorporate more biological realism, and developing novel theoretical tools for identifying differences between parasite genotypes. Overall, we found robust evidence that differences in burst sizes contribute to variation in dynamics and that differential interactions between parasites and host immune responses also play a role. In contrast to previous work, our model predicts that RBC age structure is not important for explaining dynamics. Integrating theory and empirical tests is a potentially powerful way of progressing understanding of disease biology.

Mathematical model-based statistical inference applied to within-host dynamics of infectious diseases can help dissect complex interactions between hosts and microbes. This work has applied advances in model-based inference to understand colonization of cattle by enterohaemorrhagic Escherichia coli O157 : H7 at the terminal rectum. A mathematical model was developed based on niche replication and transition rates at this site. A nested-model comparison, applied to excretion curves from 25 calves, was used to reduce complexity while maintaining integrity. We conclude that, 5–9 days post inoculation, the innate immune response negates bacterial replication on the epithelium and either reduces attachment to or increases detachment from the epithelium of the terminal rectum. Thus, we provide a broadly applicable model that gives novel insights into bacterial replication rates in vivo and the timing and impact of host responses.

Summary Sleeping sickness is characterized by waves of the extracellular parasite Trypanosoma brucei in host blood, with infections continuing for months or years until inevitable host death. These waves reflect the dynamic conflict between the outgrowth of a succession of parasite antigenic variants and their control by the host immune system. Although a contributor to these dynamics is the density-dependent differentiation from proliferative “slender forms” to transmissible “stumpy forms,” an absence of markers discriminating stumpy forms has prevented accurate parameterization of this component. Here, we exploit the stumpy-specific PAD1 marker, which functionally defines transmission competence, to quantitatively monitor stumpy formation during chronic infections. This allows reconstruction of the temporal events early in infection. Mathematical modeling of these data describes the parameters controlling trypanosome within-host dynamics and provides strong support for a quorum-sensing-like mechanism. Our data reveal the dominance of transmission stages throughout infection, a consequence being austere use of the parasite's antigen repertoire., Graphical Abstract Highlights ► Quantification of trypanosome transmission stages in chronic infections ► The temporal order of developmental events early in infection defined ► Mathematical data modeling provides support for parasite quorum sensing ► The dominance of transmission stages has key implications for VSG switch frequency

Controlling an epidemic would be aided by establishing whether particular individuals in infected populations are more likely to transmit infection. However, few analyses have characterised such individuals. Such analyses require both data on who infected whom and on the likely determinants of transmission; data that are available at the farm level for the 2001 Foot and Mouth Disease epidemic in Great Britain. Using these data a putative number of daughter infected premises (IPs) resulting from each IP was calculated where these daughters were within 3 km of the IP. A set of possible epidemiological, demographic, spatial and temporal risk factors were analysed, with the final multivariate generalised linear model (Poisson error term) having 6 statistically significant (p

Identifying risk factors for the presence of Escherichia coli O157 infection on cattle farms is important for understanding the epidemiology of this zoonotic infection in its main reservoir and for informing the design of interventions to reduce the public health risk. Here, we use data from a large-scale field study carried out in Scotland to fit both "SIS"-type dynamical models and statistical risk factor models. By comparing the fit (assessed using maximum likelihood) of different dynamical models we are able to identify the most parsimonious model (using the AIC statistic) and compare it with the model suggested by risk factor analysis. Both approaches identify 2 key risk factors: the movement of cattle onto the farm and the number of cattle on the farm. There was no evidence for a role of other livestock species or seasonality, or of significant risk of local spread. However, the most parsimonious dynamical model does predict that farms can infect other farms through routes other than cattle movement, and that there is a nonlinear relationship between the force of infection and the number of infected farms. An important prediction from the most parsimonious model is that although only approximately 20% farms may harbour E. coli O157 infection at any given time approximately 80% may harbour infection at some point during the course of a year.

Background: An understanding of the factors that determine the risk of members of a susceptible population becoming infected is essential for estimating the potential for disease spread, as opposed to just focusing on transmission from an infected population. Furthermore, analysis of the risk factors can reveal important characteristics of an epidemic and further develop understanding of the processes operating. Methods: This paper describes the development of a mixed effects logistic regression model of susceptibility of holdings to foot and mouth disease (FMD) during the 2001 epidemic in Great Britain following the imposition of a national ban on the movements of susceptible animals (NMB). Results: The principal risk factors identified in the model were shorter distances to the nearest infectious seed (a holding infected before the NMB) and the county of the holding (principally Cumbria). Additional risk factors included holdings that are mixed species rather than single species, the surface area of the holding, and the number of cattle within 10 km (all p 0.1). The fit of the model was evaluated using the area under the receiver operator characteristic curve (ROC) and the Hosmer and Lemeshow Chi-squared statistic; the fit was good with both tests (area under the ROC = 0.962 and Hosmer and Lemeshow Chi-squared statistic = 49.98 (p > 0.1)). Conclusions: Holdings at greatest risk of infection can be identified using simple readily available risk factors; this information could be employed in the control of future FMD epidemics. (C) 2009 International Society for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Despite considerable success elucidating important immunological and resource-based mechanisms that control the dynamics of infection in some diseases, little is known about how differences in these mechanisms result in strain differences in patterns of pathogenesis. Using a combination of data and theory, we disentangle the role of ecological factors (e.g., resource abundance) in the dynamics of pathogenesis for the malaria species Plasmodium chabaudi in CD4+ T cell-depleted mice. We build a series of nested models to systematically test a number of potential regulatory mechanisms and determine the "best" model using statistical techniques. The best-fit model is further tested using an independent data set from mixed-clone competition experiments. We find that parasites preferentially invade older red blood cells even when they are more fecund in younger reticulocytes and that inoculum size has a strong effect on burst size in reticulocytes. Importantly, the results suggest that strain-specific differences in virulence arise from differences in red blood cell age-specific invasion rates and burst sizes, since these are lower for the less virulent strain, as well as from differences in levels of erythropoesis induced by each strain. Our analyses highlight the importance of model selection and validation for revealing new biological insights.

On average, more than two new species of human virus are reported every year. We constructed the cumulative species discovery curve for human viruses going back to 1901. We fitted a statistical model to these data; the shape of the curve strongly suggests that the process of virus discovery is far from complete. We generated a 95% credible interval for the pool of as yet undiscovered virus species of 38–562. We extrapolated the curve and generated an estimate of 10–40 new species to be discovered by 2020. Although we cannot predict the level of health threat that these new viruses will present, we conclude that novel virus species must be anticipated in public health planning. More systematic virus discovery programmes, covering both humans and potential animal reservoirs of human viruses, should be considered.

Individual Level Models (ILMs), a new class of models, are being applied to infectious epidemic data to aid in the understanding of the spatio-temporal dynamics of infectious diseases. These models are highly flexible and intuitive, and can be parameterised under a Bayesian framework via Markov chain Monte Carlo (MCMC) methods. Unfortunately, this parameterisation can be difficult to implement due to intense computational requirements when calculating the full posterior for large, or even moderately large, susceptible populations, or when missing data are present. Here we detail a methodology that can be used to estimate parameters for such large, and/or incomplete, data sets. This is done in the context of a study of the UK 2001 foot-and-mouth disease (FMD) epidemic.

Most of the mathematical models that were developed to study the UK 2001 foot-and-mouth disease epidemic assumed that the infectiousness of infected premises was constant over their infectious periods. However, there is some controversy over whether this assumption is appropriate. Uncertainty about which farm infected which in 2001 means that the only method to determine if there were trends in farm infectiousness is the fitting of mechanistic mathematical models to the epidemic data. The parameter values that are estimated using this technique, however, may be influenced by missing and inaccurate data. In particular to the UK 2001 epidemic, this includes unreported infectives, inaccurate farm infection dates and unknown farm latent periods. Here, we show that such data degradation prevents successful determination of trends in farm infectiousness.

Foot-and-mouth disease (FMD) in the UK provides an ideal opportunity to explore optimal control measures for an infectious disease. The presence of fine-scale spatio-temporal data for the 2001 epidemic has allowed the development of epidemiological models that are more accurate than those generally created for other epidemics and provide the opportunity to explore a variety of alternative control measures. Vaccination was not used during the 2001 epidemic; however, the recent DEFRA (Department for Environment Food and Rural Affairs) contingency plan details how reactive vaccination would be considered in future. Here, using the data from the 2001 epidemic, we consider the optimal deployment of limited vaccination capacity in a complex heterogeneous environment. We use a model of FMD spread to investigate the optimal deployment of reactive ring vaccination of cattle constrained by logistical resources. The predicted optimal ring size is highly dependent upon logistical constraints but is more robust to epidemiological parameters. Other ways of targeting reactive vaccination can significantly reduce the epidemic size; in particular, ignoring the order in which infections are reported and vaccinating those farms closest to any previously reported case can substantially reduce the epidemic. This strategy has the advantage that it rapidly targets new foci of infection and that determining an optimal ring size is unnecessary.

Stem cells in the basal layer of human interfollicular epidermis form clusters that can be reconstituted in vitro. In order to supply the interfollicular epidermis with differentiated cells, the size of these clusters must be controlled. Evidence suggests that control is regulated via differentiation of stem cells on the periphery of the clusters. Moreover, there is growing evidence that this regulation is mediated by the Notch signalling pathway. In this paper, we develop theoretical arguments, in conjunction with computer simulations of a model of the basal layer, to show that regulation of differentiation is the most likely mechanism for cluster control. In addition, we show that stem cells must adhere more strongly to each other than they do to differentiated cells. Developing our model further we show that lateral-induction, mediated by the Notch signalling pathway, is a natural mechanism for cluster control. It can not only indicate to cells the size of the cluster they are in and their position within it, but it can also control the cluster size. This can only be achieved by postulating a secondary, cluster wide, differentiation signal, and cells with high Delta expression being deaf to this signal.

There are three categories of keratinocytes in the germinative compartment of the epidermis - stem, transit-amplifying and post-mitotic. Their population structure is hierarchical. This means that stem cells differentiate into transit-amplifying cells which, after a few rounds of division, become post-mitotic cells. The cell processes of birth, differentiation, death and migration affect the composition and proliferation rate of the germinative compartment. These phenomena are quantified by various cell kinetic para- meters. In this paper we derive equations that relate these parameters for different models of hierarchically structured cell populations in equilibrium. We include in the models asymmetric and symmetric division, variations in cell-cycle times, apoptosis and variation in the number of transit generations. We conclude that variation in cell-cycle times need only be considered if apoptosis is not negligible. If it is negligible, then only average cell-cycle times are needed. Unfortunately, it is impossible to predict the importance of apoptosis from the available experimental data. However, the strength of its effect is determined by the other parameters, especially the fraction of cycling stem cells. We show that variation in the number of transit generations can have a potentially large effect on cell birth rate. We also show that cell birth rate does not directly depend on the mean transit-amplifying cell-cycle time, only on the mean stem cell-cycle time. We argue that 'homogeneous cell population' equations should not be used to study hierarchical cell populations as has been done in the past. Finally we argue that stem cell parameters and transit-amplifying cell parameters should not be lumped together.

Recent experiments have shown that in patients with psoriasis, highly elevated levels of nitric oxide (NO) are released at the surface of psoriatic plaques. Nitric oxide is a central biological regulator of many aspects of physiology, and it is a natural possibility that the high nitric oxide levels in psoriasis play a causal role in the onset of the disease. Here, we use mathematical modelling to investigate this possibility. We begin by discussing a simple model consisting of a single equation for nitric oxide concentration, which enables nitric oxide secretion rates in the basal epidermis to be calculated from the observed NO release rates at the skin surface. Using this key parameter value, we then develop an extended model that tests the hypothesis that nitric oxide regulates the formation of the extended rete pegs seen in psoriatic plaques. This occurs via the peroxynitrite-dependent activation of the collagenase MMP-8, which is produced by neutrophils present at high levels in psoriatic plaques. The plausibility of the hypothesis is demonstrated and specific testable quantitative predictions about the roles of the various cell types and signalling molecules are made.

We test models for the evolution of helical regions of RNA sequences, where the base pairing constraint leads to correlated compensatory substitutions occurring on either side of the pair. These models are of three types: 6-state models include only the four Watson-Crick pairs plus GU and UG; 7-state models include a single mismatch state that combines all of the 10 possible mismatches; 16-state models treat all mismatch states separately. We analyzed a set of eubacterial ribosomal RNA sequences with a well-established phylogenetic tree structure. For each model, the maximum-likelihood values of the parameters were obtained. The models were compared using the Akaike information criterion, the likelihood-ratio test, and Cox’s test. With a high significance level, models that permit a nonzero rate of double substitutions performed better than those that assume zero double substitution rate. Some models assume symmetry between GC and CG, between AU and UA, and between GU and UG. Models that relaxed this symmetry assumption performed slightly better, but the tests did not all agree on the significance level. The most general time-reversible model significantly outperformed any of the simplifications. We consider the relative merits of all these models for molecular phylogenetics.

Marek's disease virus (MDV), a commercially important disease of poultry, has become substantially more virulent over the last 60 years. This evolution was presumably a consequence of changes in virus ecology associated with the intensification of the poultry industry. Here, we assess whether vaccination or reduced host life span could have generated natural selection, which favored more virulent strains. Using previously published experimental data, we estimated viral fitness under a range of cohort durations and vaccine treatments on broiler farms. We found that viral fitness maximized at intermediate virulence, as a result of a trade-off between virulence and transmission previously reported. Our results suggest that vaccination, acting on this trade-off, could have led to the evolution of increased virulence. By keeping the host alive, vaccination prolongs infectious periods of virulent strains. Improvements in host genetics and nutrition, which reduced broiler life spans below 50 days, could have also increased the virulence of the circulating MDV strains because shortened cohort duration reduces the impact of host death on viral fitness. These results illustrate the dramatic impact anthropogenic change can potentially have on pathogen virulence.

Protective immunity against human schistosome infection develops slowly, for reasons that are not yet fully understood. For many decades, researchers have attempted to infer properties of the immune response from epidemiological studies, with mathematical models frequently being used to bridge the gap between immunological theory and population-level data on schistosome infection and immune responses. Here, building upon earlier model findings, stochastic individual-based models were used to identify model structures consistent with observed field patterns of Schistosoma haematobium infection and antibody responses, including their distributions in cross-sectional surveys, and the observed treatment-induced antibody switch. We found that the observed patterns of infection and antibody were most consistent with models in which a long-lived protective antibody response is stimulated by the death of adult S. haematobium worms and reduces worm fecundity. These findings are discussed with regard to current understanding of human immune responses to schistosome infection.

Background Marek's disease virus (MDV) is an economically important oncogenic herpesvirus of poultry. Since the 1960s, increasingly virulent strains have caused continued poultry industry production losses worldwide. To understand the mechanisms of this virulence evolution and to evaluate the epidemiological consequences of putative control strategies, it is imperative to understand how virulence is defined and how this correlates with host mortality and infectiousness during MDV infection. We present a mathematical approach to quantify key epidemiological parameters. Host lifespan, virus latent periods and host viral shedding rates were estimated for unvaccinated and vaccinated birds, infected with one of three MDV strains. The strains had previously been pathotyped to assign virulence scores according to pathogenicity of strains in hosts. Results Our analyses show that strains of higher virulence have a higher viral shedding rate, and more rapidly kill hosts. Vaccination enhances host life expectancy but does not significantly reduce the shedding rate of the virus. While the primary latent period of the virus does not vary with challenge strain nor vaccine treatment of host, the time until the maximum viral shedding rate is increased with vaccination. Conclusions Our approach provides the tools necessary for a formal analysis of the evolution of virulence in MDV, and potentially simpler and cheaper approaches to comparing the virulence of MDV strains.

An outbreak of foot-and-mouth disease (FMD) occurred in Surrey on August 3, 2007. A Great Britain-wide ban on livestock movements was implemented immediately. This coincided with the start of seasonal sheep movements off the hills in Scotland; the majority of these animals are sold via markets. The ban therefore posed severe economic and animal-welfare hardships if it was to last through September and beyond. The Scottish Government commissioned an analysis to assess the risk of re-opening markets given the uncertainty about whether FMD had entered Scotland. Tracing of livestock moved from within the risk zone in England between July 16 and August 3 identified contact chains to 12 Scottish premises; veterinary field inspections found a further three unrecorded movements. No signs of infection were found on these holdings. Under the conservative assumption that a single unknown Scottish holding was infected with FMD, an estimate of the time-dependent probability of Scotland being FMD free given no detection was made. Analyses indicated that if FMD was not detected by early to mid-September then it was highly probable that Scotland was FMD free. Risk maps were produced to visualise the potential spread of FMD across Scotland if it was to spread either locally or via market sales.

Urogenital schistosomiasis is a tropical disease infecting more than 100 million people in sub-Saharan Africa. Individuals in endemic areas endure repeated infections with long-lived schistosome worms, and also encounter larval and egg stages of the life cycle. Protective immunity against infection develops slowly with age. Distinctive age-related patterns of infection and specific antibody responses are seen in endemic areas, including an infection ‘peak shift’ and a switch in the antibody types produced. Deterministic models describing changing levels of infection and antibody with age in homogeneously exposed populations were developed to identify the key mechanisms underlying the antibody switch, and to test two theories for the slow development of protective immunity: that (i) exposure to dying (long-lived) worms, or (ii) experience of a threshold level of antigen, is necessary to stimulate protective antibody. Different model structures were explored, including alternative stages of the life cycle as the main antigenic source and the principal target of protective antibody, different worm survival distributions, antigen thresholds and immune cross-regulation. Models were identified which could reproduce patterns of infection and antibody consistent with field data. Models with dying worms as the main source of protective antigen could reproduce all of these patterns, but so could some models with other continually-encountered life stages acting as the principal antigen source. An antigen threshold enhanced the ability of the model to replicate these patterns, but was not essential for it to do so. Models including either non-exponential worm survival or cross-regulation were more likely to be able to reproduce field patterns, but neither of these was absolutely required. The combination of life cycle stage stimulating, and targeted by, antibody was found to be critical in determining whether models could successfully reproduce patterns in the data, and a number of combinations were excluded as being inconsistent with field data., Author Summary Urogenital schistosomiasis is a tropical infectious disease caused by schistosome blood flukes, infecting more than 100 million people in sub-Saharan Africa. Protective immunity develops against schistosomes, but takes many years to do so, with children acquiring multiple infections with long-lived parasites. It is important to understand how this protection develops, both to aid vaccine development, and to understand the long-term implications of other control strategies which may reduce or alter natural exposure to the parasite. We used mathematical models to investigate possible explanations for this slow development of protection, including the possibility that when worms die (after surviving in the host for 3–10 years) they release large quantities of the molecules needed to stimulate a protective immune response, or the idea that an individual's infection burden needs to exceed a threshold number of parasites before they mount a protective immune response. We found that these mechanisms were consistent with patterns of levels of infection and antibody measured in populations with schistosome infection, but that neither was essential to explain these patterns. We found that the combination of the stage of the parasite life cycle which stimulated protective immunity, and the life cycle stage targeted by this immunity, was critical.

Background Key to the control of pandemic influenza are surveillance systems that raise alarms rapidly and sensitively. In addition, they must minimise false alarms during a normal influenza season. We develop a method that uses historical syndromic influenza data from the existing surveillance system 'SERVIS' (Scottish Enhanced Respiratory Virus Infection Surveillance) for influenza-like illness (ILI) in Scotland. Methods We develop an algorithm based on the weekly case ratio (WCR) of reported ILI cases to generate an alarm for pandemic influenza. From the seasonal influenza data from 13 Scottish health boards, we estimate the joint probability distribution of the country-level WCR and the number of health boards showing synchronous increases in reported influenza cases over the previous week. Pandemic cases are sampled with various case reporting rates from simulated pandemic influenza infections and overlaid with seasonal SERVIS data from 2001 to 2007. Using this combined time series we test our method for speed of detection, sensitivity and specificity. Also, the 2008-09 SERVIS ILI cases are used for testing detection performances of the three methods with a real pandemic data. Results We compare our method, based on our simulation study, to the moving-average Cumulative Sums (Mov-Avg Cusum) and ILI rate threshold methods and find it to be more sensitive and rapid. For 1% case reporting and detection specificity of 95%, our method is 100% sensitive and has median detection time (MDT) of 4 weeks while the Mov-Avg Cusum and ILI rate threshold methods are, respectively, 97% and 100% sensitive with MDT of 5 weeks. At 99% specificity, our method remains 100% sensitive with MDT of 5 weeks. Although the threshold method maintains its sensitivity of 100% with MDT of 5 weeks, sensitivity of Mov-Avg Cusum declines to 92% with increased MDT of 6 weeks. For a two-fold decrease in the case reporting rate (0.5%) and 99% specificity, the WCR and threshold methods, respectively, have MDT of 5 and 6 weeks with both having sensitivity close to 100% while the Mov-Avg Cusum method can only manage sensitivity of 77% with MDT of 6 weeks. However, the WCR and Mov-Avg Cusum methods outperform the ILI threshold method by 1 week in retrospective detection of the 2009 pandemic in Scotland. Conclusions While computationally and statistically simple to implement, the WCR algorithm is capable of raising alarms, rapidly and sensitively, for influenza pandemics against a background of seasonal influenza. Although the algorithm was developed using the SERVIS data, it has the capacity to be used at other geographic scales and for different disease systems where buying some early extra time is critical.

Malarial infection is associated with complex immune and erythropoietic responses in the host. A quantitative understanding of these processes is essential to help inform malaria therapy and for the design of effective vaccines. In this study, we use a statistical model-fitting approach to investigate the immune and erythropoietic responses in Plasmodium chabaudi infections of mice. Three mouse phenotypes (wildtype, T-cell-deficient nude mice, and nude mice reconstituted with T-cells taken from wildtype mice) were infected with one of two parasite clones (AS or AJ). Under a Bayesian framework, we use an adaptive population-based Markov chain Monte Carlo method and fit a set of dynamical models to observed data on parasite and red blood cell (RBC) densities. Model fits are compared using Bayes' factors and parameter estimates obtained. We consider three independent immune mechanisms: clearance of parasitised RBCs (pRBC), clearance of unparasitised RBCs (uRBC), and clearance of parasites that burst from RBCs (merozoites). Our results suggest that the immune response of wildtype mice is associated with less destruction of uRBCs, compared to the immune response of nude mice. There is a greater degree of synchronisation between pRBC and uRBC clearance than between either mechanism and merozoite clearance. In all three mouse phenotypes, control of the peak of parasite density is associated with pRBC clearance. In wildtype mice and AS-infected nude mice, control of the peak is also associated with uRBC clearance. Our results suggest that uRBC clearance, rather than RBC infection, is the major determinant of RBC dynamics from approximately day 12 post-innoculation. During the first 2–3 weeks of blood-stage infection, immune-mediated clearance of pRBCs and uRBCs appears to have a much stronger effect than immune-mediated merozoite clearance. Upregulation of erythropoiesis is dependent on mouse phenotype and is greater in wildtype and reconstitited mice. Our study highlights the informative power of statistically rigorous model-fitting techniques in elucidating biological systems., Author Summary Malaria is a disease caused by a protozoan parasite of the genus Plasmodium. Every year there are around 250 million human cases of malaria, resulting in around a million deaths. Most of the severe cases and deaths are due to Plasmodium falciparum, which is endemic in much of sub-Saharan Africa and other tropical areas. The pathology of malaria is related to the asexual stage of the parasite. Understanding the infection dynamics during this stage is therefore essential to inform malaria treatment and vaccine design. Experimental infections of rodents represent an important first step towards understanding the more complicated human infections. We developed a series of models representing different hypotheses about the main processes regulating the infection dynamics during the asexual stage. Models were fit to data on Plasmodium chabaudi infections of mice, using a Bayesian statistical framework. The accuracy of different models in explaining the RBC and parasite densities was quantified. We identify the role of different types of immune-mediated mechanism, and show that RBC production (erythropoiesis) increases during infection. Differences between mouse phenotypes are explained. Our study highlights the informative power of model-fitting techniques in explaining biological systems.

The aim of this analysis is to evaluate how generic properties of networks of livestock farms connected by movements of cattle impact on the potential for spread of infectious diseases. We focus on endemic diseases with long infectious periods in affected cattle, such as bovine tuberculosis. Livestock farm networks provide a rare example of large but fully specified directed contact networks, allowing investigations into how properties of such networks impact the potential for spread of infections within them. Here we quantify the latter in terms of the basic reproduction number, R0, and partition the contributions to R0 from first order moments (mean contact rates) and second order moments (variances and covariances of contact rates) of the farm contact matrices. We find that the second order properties make a substantial contribution to the magnitude of R0, similarly to that reported for other populations. Importantly, however, we find that the magnitude of these effects depends on exactly how the contacts between farms are defined or weighted. We note that the second order properties of a directed contact network may vary through time even with little change in the mean contact rates or in overall connectedness of the network. Keywords: Basic reproduction number, Infectious disease, Heterogeneity, 20â80 rule, Contact network, Bovine tuberculosis

This paper investigates the early viral dynamics of foot-and-mouth disease (FMD) within infected pigs. Using an existing within-host model, we investigate whether individual variation can be explained by the effect of the initial dose of FMD virus. To do this, we consider the experimental data on the concentration of FMD virus genomes in the blood (viral load). In this experiment, 12 pigs were inoculated with one of three different doses of FMD virus: low; medium; or high. Measurements of the viral load were recorded over a time course of approximately 11 days for every 8 hours. The model is a set of deterministic differential equations with the following variables: viral load; virus in the interstitial space; and the proportion of epithelial cells available for infection, infected and uninfected. The model was fitted to the data for each animal individually and also simultaneously over all animals varying only the initial dose. We show that the general trend in the data can be explained by varying only the initial dose. The higher the initial dose the earlier the development of a detectable viral load.