Maximum parsimony distance on phylogenetictrees: a linear kernel and constant factor approximation algorithm

Maximum parsimony distance is a measure used to quantify the dissimilarity of two unrooted phylogenetic trees. It is NP-hard to compute, and very few positive algorithmic results are known due to its complex combinatorial structure. Here we address this shortcoming by showing that the problem is fixed parameter tractable. We do this by establishing a linear kernel i.e., that after applying certain reduction rules the resulting instance has size that is bounded by a linear function of the distance. As powerful corollaries to this result we prove that the problem permits a polynomial-time constant-factor approximation algorithm; that the treewidth of a natural auxiliary graph structure encountered in phylogenetics is bounded by a function of the distance; and that the distance is within a constant factor of the size of a maximum agreement forest of the two trees, a well studied object in phylogenetics

Maximum parsimony distance on phylogenetic trees: A linear kernel and constant factor approximation algorithm

Maximum parsimony distance is a measure used to quantify the dissimilarity of two unrooted phylogenetic trees. It is NP-hard to compute, and very few positive algorithmic results are known due to its complex combinatorial structure. Here we address this shortcoming by showing that the problem is fixed parameter tractable. We do this by establishing a linear kernel i.e., that after applying certain reduction rules the resulting instance has size that is bounded by a linear function of the distance. As powerful corollaries to this result we prove that the problem permits a polynomial-time constant-factor approximation algorithm; that the treewidth of a natural auxiliary graph structure encountered in phylogenetics is bounded by a function of the distance; and that the distance is within a constant factor of the size of a maximum agreement forest of the two trees, a well studied object in phylogenetics

Prevalence of systemic immunoreactivity to Aggregatibacter actinomycetemcomitans leukotoxin in relation to the incidence of myocardial infarction

<p>Abstract</p> <p>Background</p> <p>Chronic infections and associated inflammatory markers are suggested risk factors for cardiovascular disease (CVD). The proinflammatory cytokine, interleukin (IL)-1β, is suggested to play a role in the regulation of local inflammatory responses in both CVD and periodontitis. The leukotoxin from the periodontal pathogen <it>Aggregatibacter actinomycetemcomitans </it>has recently been shown to cause abundant secretion of IL-1β from macrophages. The aim of the present study was to compare the prevalence of systemic immunoreactivity to <it>A. actinomycetemcomitans </it>leukotoxin in myocardial infarction (MI) cases (n = 532) and matched controls (n = 1,000) in a population-based case and referents study in northern Sweden.</p> <p>Methods</p> <p>Capacity to neutralize <it>A. actinomycetemcomitans </it>leukotoxin was analyzed in a bioassay with leukocytes, purified leukotoxin, and plasma. Plasma samples that inhibited lactate-dehydrogenase release from leukotoxin-lysed cells by ≥50% were classified as positive.</p> <p>Results</p> <p>Neutralizing capacity against <it>A. actinomycetemcomitans </it>leukotoxin was detected in 53.3% of the plasma samples. The ability to neutralize leukotoxin was correlated to increasing age in men (n = 1,082) but not in women (n = 450). There was no correlation between presence of systemic leukotoxin-neutralization capacity and the incidence of MI, except for women (n = 146). Women with a low neutralizing capacity had a significantly higher incidence of MI than those who had a high neutralizing capacity.</p> <p>Conclusion</p> <p>Systemic immunoreactivity against <it>A. actinomycetemcomitans </it>leukotoxin was found at a high prevalence in the analyzed population of adults from northern Sweden. The results from the present study do not support the hypothesis that systemic leukotoxin-neutralizing capacity can decrease the risk for MI.</p

Applicability of several rooted phylogenetic network algorithms for representing the evolutionary history of SARS-CoV-2

Background: Rooted phylogenetic networks are used to display complex evolutionary history involving so-called reticulation events, such as genetic recombination. Various methods have been developed to construct such networks, using for example a multiple sequence alignment or multiple phylogenetic trees as input data. Coronaviruses are known to recombine frequently, but rooted phylogenetic networks have not yet been used extensively to describe their evolutionary history. Here, we created a workflow to compare the evolutionary history of SARS-CoV-2 with other SARS-like viruses using several rooted phylogenetic network inference algorithms. This workflow includes filtering noise from sets of phylogenetic trees by contracting edges based on branch length and bootstrap support, followed by resolution of multifurcations. We explored the running times of the network inference algorithms, the impact of filtering on the properties of the produced networks, and attempted to derive biological insights regarding the evolution of SARS-CoV-2 from them. Results: The network inference algorithms are capable of constructing rooted phylogenetic networks for coronavirus data, although running-time limitations require restricting such datasets to a relatively small number of taxa. Filtering generally reduces the number of reticulations in the produced networks and increases their temporal consistency. Taxon bat-SL-CoVZC45 emerges as a major and structural source of discordance in the dataset. The tested algorithms often indicate that SARS-CoV-2/RaTG13 is a tree-like clade, with possibly some reticulate activity further back in their history. A smaller number of constructed networks posit SARS-CoV-2 as a possible recombinant, although this might be a methodological artefact arising from the interaction of bat-SL-CoVZC45 discordance and the optimization criteria used. Conclusion: Our results demonstrate that as part of a wider workflow and with careful attention paid to running time, rooted phylogenetic network algorithms are capable of producing plausible networks from coronavirus data. These networks partly corroborate existing theories about SARS-CoV-2, and partly produce new avenues for exploration regarding the location and significance of reticulate activity within the wider group of SARS-like viruses. Our workflow may serve as a model for pipelines in which phylogenetic network algorithms can be used to analyse different datasets and test different hypotheses

A ‘Tripadvisor’ for disability? Social enterprise and ‘digital disruption’ in Australia

We explore how social enterprises can use platform technologies to plug ‘informational gaps’ in the provision of disability services. Such gaps are made more apparent by policies promoting self-directed care as a means of giving service users more choice and control. We use a case study of a start-up social enterprise seeking to provide a TripAdvisor style service to examine the potential for social innovation to ‘disrupt’ current models of service. The case study suggests that any disruptive effects of such changes are not due to new digital technology per se, nor to novel platform business models, but rather rest in the manner in which the moral orders which justify current patterns of social disablement can be challenged by social innovation

Ancient dispersal of the human fungal pathogen Cryptococcus gattii from the Amazon rainforest.

Over the past two decades, several fungal outbreaks have occurred, including the high-profile 'Vancouver Island' and 'Pacific Northwest' outbreaks, caused by Cryptococcus gattii, which has affected hundreds of otherwise healthy humans and animals. Over the same time period, C. gattii was the cause of several additional case clusters at localities outside of the tropical and subtropical climate zones where the species normally occurs. In every case, the causative agent belongs to a previously rare genotype of C. gattii called AFLP6/VGII, but the origin of the outbreak clades remains enigmatic. Here we used phylogenetic and recombination analyses, based on AFLP and multiple MLST datasets, and coalescence gene genealogy to demonstrate that these outbreaks have arisen from a highly-recombining C. gattii population in the native rainforest of Northern Brazil. Thus the modern virulent C. gattii AFLP6/VGII outbreak lineages derived from mating events in South America and then dispersed to temperate regions where they cause serious infections in humans and animals