Chorismate mutase/prephenate dehydratase from Escherichia coli K12. Effect of phenylalanine, NaCl and pH on the protein conformation.

The effects of phenylalanine, NaCl and pH on the conformation of chorismate mutase/prephenate dehydratase have been investigated, using measurements of far and near-ultraviolet circular dichroic spectra and ultraviolet difference spectra. At pH 8.2 in 20 mM Tris-Cl buffer the enzyme was found to contain 10-20% helix and 40-50% beta-structure. There was little or no change in these values on the addition of 1 mM phenylalanine (the allosteric effector) or 0.4 M NaCl or by decreasing the pH to 7.4. Both phenylalanine and NaCl caused significant changes in the conformation of the enzyme. The most prominent of these was the movement of a tryptophan residue into a more hydrophobic environment. There was also a slight perturbation of this tryptophan when the pH was decreased to 7.4. The conformational changes can explain sigmoidal kinetic behaviour observed previously [Gething et al. (1976) Eur. J. Biochem. 71, 317-325].     

Prioritising Infectious Disease Mapping

BackgroundIncreasing volumes of data and computational capacity afford unprecedented opportunities to scale up infectious disease (ID) mapping for public health uses. Whilst a large number of IDs show global spatial variation, comprehensive knowledge of these geographic patterns is poor. Here we use an objective method to prioritise mapping efforts to begin to address the large deficit in global disease maps currently available.Conclusions/SignificanceA quantitative, easily-updated and flexible framework for prioritising diseases is presented here. The study identifies a possible future strategy for those diseases where significant knowledge gaps remain, as well as recognising those where global mapping programs have already made significant progress. For many conditions, potential shared epidemiological information has yet to be exploited.     

Hypermutation in stationary-phaseE. coli: tales from thelac operon

Escherichia coli cells are capable of complex regulatory responses to environmental conditions and stresses. In some circumstances, the response includes an increase in the mutation rate, effectively mutagenizing the genome. The classic example is the SOS response to DNA damage. Recent work indicates that other environmental stresses can also result in mutation of the genome. Modulation of mutation rate may be a more prevalent stress response than previously thought. In this review we focus on genome-wide mutation inE. coli cells subjected to a nonlethal genetic selection for reversion of alac frameshift allele. Reversion of thelac frameshift allele occurs via a novel mechanism that requires homologous recombination functions, and is enhanced by transiently diminished postsynthesis mismatch repair. A model for recombination-dependent stationary-phase mutation will be presented and its relevance for genome-wide mutation discussed.     

Modeling Within-Host Effects of Drugs on Plasmodium falciparum Transmission and Prospects for Malaria Elimination

Achieving a theoretical foundation for malaria elimination will require a detailed understanding of the quantitative relationships between patient treatment-seeking behavior, treatment coverage, and the effects of curative therapies that also block Plasmodium parasite transmission to mosquito vectors. Here, we report a mechanistic, within-host mathematical model that uses pharmacokinetic (PK) and pharmacodynamic (PD) data to simulate the effects of artemisinin-based combination therapies (ACTs) on Plasmodium falciparum transmission. To contextualize this model, we created a set of global maps of the fold reductions that would be necessary to reduce the malaria R_C (i.e. its basic reproductive number under control) to below 1 and thus interrupt transmission. This modeling was applied to low-transmission settings, defined as having a R₀<10 based on 2010 data. Our modeling predicts that treating 93–98% of symptomatic infections with an ACT within five days of fever onset would interrupt malaria transmission for ∼91% of the at-risk population of Southeast Asia and ∼74% of the global at-risk population, and lead these populations towards malaria elimination. This level of treatment coverage corresponds to an estimated 81–85% of all infected individuals in these settings. At this coverage level with ACTs, the addition of the gametocytocidal agent primaquine affords no major gains in transmission reduction. Indeed, we estimate that it would require switching ∼180 people from ACTs to ACTs plus primaquine to achieve the same transmission reduction as switching a single individual from untreated to treated with ACTs. Our model thus predicts that the addition of gametocytocidal drugs to treatment regimens provides very small population-wide benefits and that the focus of control efforts in Southeast Asia should be on increasing prompt ACT coverage. Prospects for elimination in much of Sub-Saharan Africa appear far less favorable currently, due to high rates of infection and less frequent and less rapid treatment.     

Tree line identification from pollen data: beyond the limit?

Aim The boreal tree line is a prominent biogeographic feature, the position of which reflects climatic conditions. Pollen is the key sensor used to reconstruct past tree line patterns. Our aims in this study were to investigate pollen–vegetation relationships at the boreal tree line and to assess the success of a modified version of the biomization method that incorporates pollen productivity and dispersal in distinguishing the tree line. Location Northern Canada (307 sites) and Alaska (316 sites). Methods The REVEALS method for estimating regional vegetation composition from pollen data was simplified to provide correction factors to account for differential production and dispersal of pollen among taxa. The REVEALS‐based correction factors were used to adapt the biomization method and applied as a set of experiments to pollen data from lake sediments and moss polsters from the boreal tree line. Proportions of forest and tundra predicted from modern pollen samples along two longitudinal transects were compared with those derived from a vegetation map by: (1) a tally of ‘correct’ versus ‘incorrect’ assignments using vegetation in the relevant map pixels, and (2) a comparison of the shape and position of north–south forest‐cover curves generated from all transect pixels and from pollen data. Possible causes of bias in the misclassifications were assessed. Results Correcting for pollen productivity alone gave fewest misclassifications and the closest estimate of the modern mapped tree line position (Canada, + 300 km; Alaska, + 10 km). In Canada success rates were c. 40–70% and all experiments over‐predicted forest cover. Most corrections improved results over uncorrected biomization; using only lakes improved success rates to c. 80%. In Alaska success rates were 70–80% and classification errors were more evenly distributed; there was little improvement over uncorrected biomization. Main conclusions Corrected biomization should improve broad‐scale reconstructions of spatial patterns in forest/non‐forest vegetation mosaics and across climate‐sensitive ecotones. The Canadian example shows this is particularly the case in regions affected by taxa with extremely high pollen productivity (such as Pinus). Improved representation of actual vegetation distribution is most likely if pollen data from lake sediments are used because the REVEALS algorithm is based on the pollen dynamics of lake‐based systems.     

Quantifying Aggregated Uncertainty in Plasmodium falciparum Malaria Prevalence and Populations at Risk via Efficient Space-Time Geostatistical Joint Simulation

Risk maps estimating the spatial distribution of infectious diseases are required to guide public health policy from local to global scales. The advent of model-based geostatistics (MBG) has allowed these maps to be generated in a formal statistical framework, providing robust metrics of map uncertainty that enhances their utility for decision-makers. In many settings, decision-makers require spatially aggregated measures over large regions such as the mean prevalence within a country or administrative region, or national populations living under different levels of risk. Existing MBG mapping approaches provide suitable metrics of local uncertainty—the fidelity of predictions at each mapped pixel—but have not been adapted for measuring uncertainty over large areas, due largely to a series of fundamental computational constraints. Here the authors present a new efficient approximating algorithm that can generate for the first time the necessary joint simulation of prevalence values across the very large prediction spaces needed for global scale mapping. This new approach is implemented in conjunction with an established model for P. falciparum allowing robust estimates of mean prevalence at any specified level of spatial aggregation. The model is used to provide estimates of national populations at risk under three policy-relevant prevalence thresholds, along with accompanying model-based measures of uncertainty. By overcoming previously unchallenged computational barriers, this study illustrates how MBG approaches, already at the forefront of infectious disease mapping, can be extended to provide large-scale aggregate measures appropriate for decision-makers.     

The expression of influenza virus hemagglutinin in the pancreatic beta cells of transgenic mice results in autoimmune diabetes

Insulin-dependent diabetes mellitus results from the autoimmune destruction of the insulin-producing beta cells of the pancreatic islets. The target antigen(s) involved in this immunopathological process has not been identified. Our strategy was to determine whether expression of a novel surface antigen by murine pancreatic beta cells would result in insulin-dependent diabetes mellitus. We have generated lines of transgenic mice (RIP-HA) that express the hemagglutinin of the A/Japan/305/57 strain of influenza virus on their insulin-producing beta cells. Hyperglycemia developed in mice derived from all three founders at a frequency varying from 13% to 27%, and was associated with lymphocytic infiltration of the islets and a humoral response against beta cell antigens, including hemagglutinin. These results suggest that the RIP-HA mice should provide a useful system in which to study the cellular interactions involved in the induction of self-tolerance and autoimmunity.     

Estimating the Number of Paediatric Fevers Associated with Malaria Infection Presenting to Africa's Public Health Sector in 2007

Background

As international efforts to increase the coverage of artemisinin-based combination therapy in public health sectors gather pace, concerns have been raised regarding their continued indiscriminate presumptive use for treating all childhood fevers. The availability of rapid-diagnostic tests to support practical and reliable parasitological diagnosis provides an opportunity to improve the rational treatment of febrile children across Africa. However, the cost effectiveness of diagnosis-based treatment polices will depend on the presumed numbers of fevers harbouring infection. Here we compute the number of fevers likely to present to public health facilities in Africa and the estimated number of these fevers likely to be infected with Plasmodium falciparum malaria parasites.

Methods and Findings

We assembled first administrative-unit level data on paediatric fever prevalence, treatment-seeking rates, and child populations. These data were combined in a geographical information system model that also incorporated an adjustment procedure for urban versus rural areas to produce spatially distributed estimates of fever burden amongst African children and the subset likely to present to public sector clinics. A second data assembly was used to estimate plausible ranges for the proportion of paediatric fevers seen at clinics positive for P. falciparum in different endemicity settings. We estimated that, of the 656 million fevers in African 0–4 y olds in 2007, 182 million (28%) were likely to have sought treatment in a public sector clinic of which 78 million (43%) were likely to have been infected with P. falciparum (range 60–103 million).

Conclusions

Spatial estimates of childhood fevers and care-seeking rates can be combined with a relational risk model of infection prevalence in the community to estimate the degree of parasitemia in those fevers reaching public health facilities. This quantification provides an important baseline comparison of malarial and nonmalarial fevers in different endemicity settings that can contribute to ongoing scientific and policy debates about optimum clinical and financial strategies for the introduction of new diagnostics. These models are made publicly available with the publication of this paper. Please see later in the article for the Editors'' Summary     

The International Limits and Population at Risk of Plasmodium vivax Transmission in 2009

Background

A research priority for Plasmodium vivax malaria is to improve our understanding of the spatial distribution of risk and its relationship with the burden of P. vivax disease in human populations. The aim of the research outlined in this article is to provide a contemporary evidence-based map of the global spatial extent of P. vivax malaria, together with estimates of the human population at risk (PAR) of any level of transmission in 2009.

Methodology

The most recent P. vivax case-reporting data that could be obtained for all malaria endemic countries were used to classify risk into three classes: malaria free, unstable (<0.1 case per 1,000 people per annum (p.a.)) and stable (≥0.1 case per 1,000 p.a.) P. vivax malaria transmission. Risk areas were further constrained using temperature and aridity data based upon their relationship with parasite and vector bionomics. Medical intelligence was used to refine the spatial extent of risk in specific areas where transmission was reported to be absent (e.g., large urban areas and malaria-free islands). The PAR under each level of transmission was then derived by combining the categorical risk map with a high resolution population surface adjusted to 2009. The exclusion of large Duffy negative populations in Africa from the PAR totals was achieved using independent modelling of the gene frequency of this genetic trait. It was estimated that 2.85 billion people were exposed to some risk of P. vivax transmission in 2009, with 57.1% of them living in areas of unstable transmission. The vast majority (2.59 billion, 91.0%) were located in Central and South East (CSE) Asia, whilst the remainder were located in America (0.16 billion, 5.5%) and in the Africa+ region (0.10 billion, 3.5%). Despite evidence of ubiquitous risk of P. vivax infection in Africa, the very high prevalence of Duffy negativity throughout Central and West Africa reduced the PAR estimates substantially.

Conclusions

After more than a century of development and control, P. vivax remains more widely distributed than P. falciparum and is a potential cause of morbidity and mortality amongst the 2.85 billion people living at risk of infection, the majority of whom are in the tropical belt of CSE Asia. The probability of infection is reduced massively across Africa by the frequency of the Duffy negative trait, but transmission does occur on the continent and is a concern for Duffy positive locals and travellers. The final map provides the spatial limits on which the endemicity of P. vivax transmission can be mapped to support future cartographic-based burden estimations.     

Bayesian geostatistical analysis and prediction of Rhodesian human African trypanosomiasis

Background

The persistent spread of Rhodesian human African trypanosomiasis (HAT) in Uganda in recent years has increased concerns of a potential overlap with the Gambian form of the disease. Recent research has aimed to increase the evidence base for targeting control measures by focusing on the environmental and climatic factors that control the spatial distribution of the disease.

Objectives

One recent study used simple logistic regression methods to explore the relationship between prevalence of Rhodesian HAT and several social, environmental and climatic variables in two of the most recently affected districts of Uganda, and suggested the disease had spread into the study area due to the movement of infected, untreated livestock. Here we extend this study to account for spatial autocorrelation, incorporate uncertainty in input data and model parameters and undertake predictive mapping for risk of high HAT prevalence in future.

Materials and Methods

Using a spatial analysis in which a generalised linear geostatistical model is used in a Bayesian framework to account explicitly for spatial autocorrelation and incorporate uncertainty in input data and model parameters we are able to demonstrate a more rigorous analytical approach, potentially resulting in more accurate parameter and significance estimates and increased predictive accuracy, thereby allowing an assessment of the validity of the livestock movement hypothesis given more robust parameter estimation and appropriate assessment of covariate effects.

Results

Analysis strongly supports the theory that Rhodesian HAT was imported to the study area via the movement of untreated, infected livestock from endemic areas. The confounding effect of health care accessibility on the spatial distribution of Rhodesian HAT and the linkages between the disease''s distribution and minimum land surface temperature have also been confirmed via the application of these methods.

Conclusions

Predictive mapping indicates an increased risk of high HAT prevalence in the future in areas surrounding livestock markets, demonstrating the importance of livestock trading for continuing disease spread. Adherence to government policy to treat livestock at the point of sale is essential to prevent the spread of sleeping sickness in Uganda.