Interplay between pleiotropy and secondary selection determines rise and fall of mutators in stress response

Dramatic rise of mutators has been found to accompany adaptation of bacteria in response to many kinds of stress. Two views on the evolutionary origin of this phenomenon emerged: the pleiotropic hypothesis positing that it is a byproduct of environmental stress or other specific stress response mechanisms and the second order selection which states that mutators hitchhike to fixation with unrelated beneficial alleles. Conventional population genetics models could not fully resolve this controversy because they are based on certain assumptions about fitness landscape. Here we address this problem using a microscopic multiscale model, which couples physically realistic molecular descriptions of proteins and their interactions with population genetics of carrier organisms without assuming any a priori fitness landscape. We found that both pleiotropy and second order selection play a crucial role at different stages of adaptation: the supply of mutators is provided through destabilization of error correction complexes or fluctuations of production levels of prototypic mismatch repair proteins (pleiotropic effects), while rise and fixation of mutators occur when there is a sufficient supply of beneficial mutations in replication-controlling genes. This general mechanism assures a robust and reliable adaptation of organisms to unforeseen challenges. This study highlights physical principles underlying physical biological mechanisms of stress response and adaptation

Visualisation of Integrated Patient-Centric Data as Pathways: Enhancing Electronic Medical Records in Clinical Practice

Routinely collected data in hospital Electronic Medical Records (EMR) is rich and abundant but often not linked or analysed for purposes other than direct patient care. We have created a methodology to integrate patient-centric data from different EMR systems into clinical pathways that represent the history of all patient interactions with the hospital during the course of a disease and beyond. In this paper, the literature in the area of data visualisation in healthcare is reviewed and a method for visualising the journeys that patients take through care is discussed. Examples of the hidden knowledge that could be discovered using this approach are explored and the main application areas of visualisation tools are identified. This paper also highlights the challenges of collecting and analysing such data and making the visualisations extensively used in the medical domain. This paper starts by presenting the state-of-the-art in visualisation of clinical and other health related data. Then, it describes an example clinical problem and discusses the visualisation tools and techniques created for the utilisation of these data by clinicians and researchers. Finally, we look at the open problems in this area of research and discuss future challenges

Patterns of co-speciation and host switching in primate malaria parasites

<p>Abstract</p> <p>Background</p> <p>The evolutionary history of many parasites is dependent on the evolution of their hosts, leading to an association between host and parasite phylogenies. However, frequent host switches across broad phylogenetic distances may weaken this close evolutionary link, especially when vectors are involved in parasites transmission, as is the case for malaria pathogens. Several studies suggested that the evolution of the primate-infective malaria lineages may be constrained by the phylogenetic relationships of their hosts, and that lateral switches between distantly related hosts may have been occurred. However, no systematic analysis has been quantified the degree of phylogenetic association between primates and their malaria parasites.</p> <p>Methods</p> <p>Here phylogenetic approaches have been used to discriminate statistically between events due to co-divergence, duplication, extinction and host switches that can potentially cause historical association between <it>Plasmodium </it>parasites and their primate hosts. A Bayesian reconstruction of parasite phylogeny based on genetic information for six genes served as basis for the analyses, which could account for uncertainties about the evolutionary hypotheses of malaria parasites.</p> <p>Results</p> <p>Related lineages of primate-infective <it>Plasmodium </it>tend to infect hosts within the same taxonomic family. Different analyses testing for congruence between host and parasite phylogenies unanimously revealed a significant association between the corresponding evolutionary trees. The most important factor that resulted in this association was host switching, but depending on the parasite phylogeny considered, co-speciation and duplication may have also played some additional role. Sorting seemed to be a relatively infrequent event, and can occur only under extreme co-evolutionary scenarios. The concordance between host and parasite phylogenies is heterogeneous: while the evolution of some malaria pathogens is strongly dependent on the phylogenetic history of their primate hosts, the congruent evolution is less emphasized for other parasite lineages (e.g. for human malaria parasites). Estimation of ancestral states of host use along the phylogenetic tree of parasites revealed that lateral transfers across distantly related hosts were likely to occur in several cases. Parasites cannot infect all available hosts, and they should preferentially infect hosts that provide a similar environment for reproduction. Marginally significant evidence suggested that there might be a consistent variation within host ranges in terms of physiology.</p> <p>Conclusion</p> <p>The evolution of primate malarias is constrained by the phylogenetic associations of their hosts. Some parasites can preserve a great flexibility to infect hosts across a large phylogenetic distance, thus host switching can be an important factor in mediating host ranges observed in nature. Due to this inherent flexibility and the potential exposure to various vectors, the emergence of new malaria disease in primates including humans cannot be predicted from the phylogeny of parasites.</p