152 research outputs found

    Population genetics of trypanosoma brucei rhodesiense: clonality and diversity within and between foci

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    African trypanosomes are unusual among pathogenic protozoa in that they can undergo their complete morphological life cycle in the tsetse fly vector with mating as a non-obligatory part of this development. Trypanosoma brucei rhodesiense, which infects humans and livestock in East and Southern Africa, has classically been described as a host-range variant of the non-human infective Trypanosoma brucei that occurs as stable clonal lineages. We have examined T. b. rhodesiense populations from East (Uganda) and Southern (Malawi) Africa using a panel of microsatellite markers, incorporating both spatial and temporal analyses. Our data demonstrate that Ugandan T. b. rhodesiense existed as clonal populations, with a small number of highly related genotypes and substantial linkage disequilibrium between pairs of loci. However, these populations were not stable as the dominant genotypes changed and the genetic diversity also reduced over time. Thus these populations do not conform to one of the criteria for strict clonality, namely stability of predominant genotypes over time, and our results show that, in a period in the mid 1990s, the previously predominant genotypes were not detected but were replaced by a novel clonal population with limited genetic relationship to the original population present between 1970 and 1990. In contrast, the Malawi T. b. rhodesiense population demonstrated significantly greater diversity and evidence for frequent genetic exchange. Therefore, the population genetics of T. b. rhodesiense is more complex than previously described. This has important implications for the spread of the single copy T. b. rhodesiense gene that allows human infectivity, and therefore the epidemiology of the human disease, as well as suggesting that these parasites represent an important organism to study the influence of optional recombination upon population genetic dynamics

    Phylogeography and Taxonomy of Trypanosoma brucei

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    Trypanosoma brucei, the parasite causing human African trypanosomiasis (sleeping sickness) across sub-Saharan Africa is traditionally split into three subspecies: T. b. gambiense (Tbg), causing a chronic form of human disease in West and Central Africa; T. b. rhodesiense (Tbr), causing an acute form of human disease in East and Southern Africa; and T. b. brucei (Tbb), which is restricted to animals. Tbg is further split into Tbg group 1 and Tbg group 2. Better understanding the evolutionary relationships between these groups may help to shed light on the epidemiology of sleeping sickness. Here, we used three different types of genetic markers to investigate the phylogeographic relationships among the four groups across a large portion of their range. Our results confirm the distinctiveness of Tbg group 1 while highlighting the extremely close relationships among the other three taxa. In particular, Tbg group 2 was closely related to Tbb, while Tbr appeared to be a variant of Tbb, differing only in its phenotype of human infectivity. The wide geographic distribution of the gene conferring human infectivity (SRA) and the fact that it is readily exchanged among lineages of T. brucei in eastern Africa suggests that human-infective trypanosomes have access to an extensive gene pool with which to respond to selective pressures such as drugs

    Hypomineralized Second Primary Molars as Predictor of Molar Incisor Hypomineralization

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    Molar incisor hypomineralization (MIH) is a developmental defect of dental enamel that shares features with hypomineralized second primary molars (HSPM). Prior to permanent tooth eruption, second primary molars could have predictive value for permanent molar and incisor hypomineralization. To assess this possible relationship, a cross-sectional study was conducted in a sample of 414 children aged 8 and 9 years from the INMA cohort in Valencia (Spain). A calibrated examiner (linear-weighted Kappa 0.83) performed the intraoral examinations at the University of Valencia between November 2013 and 2014, applying the diagnostic criteria for MIH and HSPM adopted by the European Academy of Paediatric Dentistry. 100 children (24.2%) presented MIH and 60 (14.5%) presented HSPM. Cooccurrence of the two defects was observed in 11.1% of the children examined. The positive predictive value was 76.7% (63.9-86.6) and the negative predictive value 84.7% (80.6-88.3). The positive likelihood ratio (S/1-E) was 10.3 (5.9-17.9) and the negative likelihood ratio (1-S/E) 0.57 (0.47-0.68). The odds ratio was 18.2 (9.39-35.48). It was concluded that while the presence of HSPM can be considered a predictor of MIH, indicating the need for monitoring and control, the absence of this defect in primary dentition does not rule out the appearance of MIH

    Reconstructing the 2003/2004 H3N2 influenza epidemic in Switzerland with a spatially explicit, individual-based model

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    ABSTRACT: BACKGROUND: Simulation models of influenza spread play an important role for pandemic preparedness. However, as the world has not faced a severe pandemic for decades, except the rather mild H1N1 one in 2009, pandemic influenza models are inherently hypothetical and validation is, thus, difficult. We aim at reconstructing a recent seasonal influenza epidemic that occurred in Switzerland and deem this to be a promising validation strategy for models of influenza spread. METHODS: We present a spatially explicit, individual-based simulation model of influenza spread. The simulation model bases upon (i) simulated human travel data, (ii) data on human contact patterns and (iii) empirical knowledge on the epidemiology of influenza. For model validation we compare the simulation outcomes with empirical knowledge regarding (i) the shape of the epidemic curve, overall infection rate and reproduction number, (ii) age-dependent infection rates and time of infection, (iii) spatial patterns. RESULTS: The simulation model is capable of reproducing the shape of the 2003/2004 H3N2 epidemic curve of Switzerland and generates an overall infection rate (14.9 percent) and reproduction numbers (between 1.2 and 1.3), which are realistic for seasonal influenza epidemics. Age and spatial patterns observed in empirical data are also reflected by the model: Highest infection rates are in children between 5 and 14 and the disease spreads along the main transport axes from west to east. CONCLUSIONS: We show that finding evidence for the validity of simulation models of influenza spread by challenging them with seasonal influenza outbreak data is possible and promising. Simulation models for pandemic spread gain more credibility if they are able to reproduce seasonal influenza outbreaks. For more robust modelling of seasonal influenza, serological data complementing sentinel information would be beneficia

    Computational Identification of Transcriptional Regulators in Human Endotoxemia

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    One of the great challenges in the post-genomic era is to decipher the underlying principles governing the dynamics of biological responses. As modulating gene expression levels is among the key regulatory responses of an organism to changes in its environment, identifying biologically relevant transcriptional regulators and their putative regulatory interactions with target genes is an essential step towards studying the complex dynamics of transcriptional regulation. We present an analysis that integrates various computational and biological aspects to explore the transcriptional regulation of systemic inflammatory responses through a human endotoxemia model. Given a high-dimensional transcriptional profiling dataset from human blood leukocytes, an elementary set of temporal dynamic responses which capture the essence of a pro-inflammatory phase, a counter-regulatory response and a dysregulation in leukocyte bioenergetics has been extracted. Upon identification of these expression patterns, fourteen inflammation-specific gene batteries that represent groups of hypothetically β€˜coregulated’ genes are proposed. Subsequently, statistically significant cis-regulatory modules (CRMs) are identified and decomposed into a list of critical transcription factors (34) that are validated largely on primary literature. Finally, our analysis further allows for the construction of a dynamic representation of the temporal transcriptional regulatory program across the host, deciphering possible combinatorial interactions among factors under which they might be active. Although much remains to be explored, this study has computationally identified key transcription factors and proposed a putative time-dependent transcriptional regulatory program associated with critical transcriptional inflammatory responses. These results provide a solid foundation for future investigations to elucidate the underlying transcriptional regulatory mechanisms under the host inflammatory response. Also, the assumption that coexpressed genes that are functionally relevant are more likely to share some common transcriptional regulatory mechanism seems to be promising, making the proposed framework become essential in unravelling context-specific transcriptional regulatory interactions underlying diverse mammalian biological processes

    Habitat correlates of Eurasian woodcock Scolopax rusticola abundance in a declining resident population

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    In Europe, woodland bird populations have been declining since at least the 1970s, and in Britain, around one third of woodland bird species have undergone declines over this period. Habitat change has been highlighted as a possible cause, but for some species clear evidence of this is lacking owing to an incomplete knowledge of the species’ habitat requirements. Here, we analyse national data to explain the variation in abundance of a declining woodland bird, the Eurasian Woodcock. A nationwide, species-specific survey of breeding Woodcock was conducted in 2003 and 2013 at 807 and 823 randomly selected 1-km squares respectively. The counts were compared with a range of landscape-scale habitat variables as well as local habitat measures recorded by surveyors, using generalised linear mixed models. Habitat variables were measured at a variety of spatial scales using ring buffers, although our analyses show that strong collinearity between scales hinders interpretation. At large landscape scales, breeding Woodcock abundance was correlated with total woodland area and the way this interacted with woodland type. Woodcock were more abundant in woods containing a more heterogeneous mix of woodland habitat types and in woods further from urban areas. On a smaller spatial scale, Woodcock were less likely to be found at sites dominated by beech Fagus spp. and more likely to occur in woods containing birch Betula spp. The Woodcock’s association with large, heterogeneous woods and the apparent attractiveness of certain woodland types present the most relevant topics for future research into the role of habitat change in long-term declines
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