The secret of success

Parts of Antarctica have experienced warming almost an order of magnitude greater than the global average over the past 50 years, with the Antarctic Peninsula ranking among the three fastest-warming regions on Earth. Antarctic ecosystems have been affected by the warming that has taken place. Perhaps the most notable impact has been a dramatic expansion of the two species of flowering plant that occur on the continent \u2014 Antarctic pearlwort and Antarctic hair gras

An acidic microenvironment in Tuberculosis increases extracellular matrix degradation by regulating macrophage inflammatory responses

Mycobacterium tuberculosis (M.tb) infection causes marked tissue inflammation leading to lung destruction and morbidity. The inflammatory extracellular microenvironment is acidic, however the effect of this acidosis on the immune response to M.tb is unknown. Using RNA-seq we show that acidosis produces system level transcriptional change in M.tb infected human macrophages regulating almost 4000 genes. Acidosis specifically upregulated extracellular matrix (ECM) degradation pathways with increased expression of Matrix metalloproteinases (MMPs) which mediate lung destruction in Tuberculosis. Macrophage MMP-1 and -3 secretion was increased by acidosis in a cellular model. Acidosis markedly suppresses several cytokines central to control of M.tb infection including TNF-α and IFN-γ. Murine studies demonstrated expression of known acidosis signaling G-protein coupled receptors OGR-1 and TDAG-8 in Tuberculosis which are shown to mediate the immune effects of decreased pH. Receptors were then demonstrated to be expressed in patients with TB lymphadenitis. Collectively, our findings show that an acidic microenvironment modulates immune function to reduce protective inflammatory responses and increase extracellular matrix degradation in Tuberculosis. Acidosis receptors are therefore potential targets for host directed therapy in patients

Phylogenetic Codivergence Supports Coevolution of Mimetic Heliconius Butterflies

The unpalatable and warning-patterned butterflies _Heliconius erato_ and _Heliconius melpomene_ provide the best studied example of mutualistic Müllerian mimicry, thought – but rarely demonstrated – to promote coevolution. Some of the strongest available evidence for coevolution comes from phylogenetic codivergence, the parallel divergence of ecologically associated lineages. Early evolutionary reconstructions suggested codivergence between mimetic populations of _H. erato_ and _H. melpomene_, and this was initially hailed as the most striking known case of coevolution. However, subsequent molecular phylogenetic analyses found discrepancies in phylogenetic branching patterns and timing (topological and temporal incongruence) that argued against codivergence. We present the first explicit cophylogenetic test of codivergence between mimetic populations of _H. erato_ and _H. melpomene_, and re-examine the timing of these radiations. We find statistically significant topological congruence between multilocus coalescent population phylogenies of _H. erato_ and _H. melpomene_, supporting repeated codivergence of mimetic populations. Divergence time estimates, based on a Bayesian coalescent model, suggest that the evolutionary radiations of _H. erato_ and _H. melpomene_ occurred over the same time period, and are compatible with a series of temporally congruent codivergence events. This evidence supports a history of reciprocal coevolution between Müllerian co-mimics characterised by phylogenetic codivergence and parallel phenotypic change

Identifying hypothetical genetic influences on complex disease phenotypes

<p>Abstract</p> <p>Background</p> <p>Statistical interactions between disease-associated loci of complex genetic diseases suggest that genes from these regions are involved in a common mechanism impacting, or impacted by, the disease. The computational problem we address is to discover relationships among genes from these interacting regions that may explain the observed statistical interaction and the role of these genes in the disease phenotype.</p> <p>Results</p> <p>We describe a heuristic algorithm for generating hypothetical gene relationships from loci associated with a complex disease phenotype. This approach, called Prioritizing Disease Genes by Analysis of Common Elements (PDG-ACE), mines biomedical keywords from text descriptions of genes and uses them to relate genes close to disease-associated loci. A keyword common to, and significantly over-represented in, a pair of gene descriptions may represent a preliminary hypothesis about the biological relationship between the genes, and suggest the role the genes play in the disease phenotype.</p> <p>Conclusion</p> <p>Our experimentation shows that the approach finds previously published relationships, while failing to find relationships that don't exist. The results also indicate that the approach is robust to differences in keyword vocabulary. We outline a brief case study in which results from a recently published Type 2 Diabetes association study are used to identify potential hypotheses.</p

Recovery and resilience of tropical forests after disturbance

The time taken for forested tropical ecosystems to re-establish post-disturbance is of widespread interest. Yet to date there has been no comparative study across tropical biomes to determine rates of forest re-growth, and how they vary through space and time. Here we present results from a meta-analysis of palaeoecological records that use fossil pollen as a proxy for vegetation change over the past 20,000 years. A total of 283 forest disturbance and recovery events, reported in 71 studies, are identified across four tropical regions. Results indicate that forests in Central America and Africa generally recover faster from past disturbances than those in South America and Asia, as do forests exposed to natural large infrequent disturbances compared with post-climatic and human impacts. Results also demonstrate that increasing frequency of disturbance events at a site through time elevates recovery rates, indicating a degree of resilience in forests exposed to recurrent past disturbance

Oil Palm Research in Context: Identifying the Need for Biodiversity Assessment

Oil palm cultivation is frequently cited as a major threat to tropical biodiversity as it is centered on some of the world's most biodiverse regions. In this report, Web of Science was used to find papers on oil palm published since 1970, which were assigned to different subject categories to visualize their research focus. Recent years have seen a broadening in the scope of research, with a slight growth in publications on the environment and a dramatic increase in those on biofuel. Despite this, less than 1% of publications are related to biodiversity and species conservation. In the context of global vegetable oil markets, palm oil and soyabean account for over 60% of production but are the subject of less than 10% of research. Much more work must be done to establish the impacts of habitat conversion to oil palm plantation on biodiversity. Results from such studies are crucial for informing conservation strategies and ensuring sustainable management of plantations

In silico prioritisation of candidate genes for prokaryotic gene function discovery: an application of phylogenetic profiles

Background: In silico candidate gene prioritisation (CGP) aids the discovery of gene functions by ranking genes according to an objective relevance score. While several CGP methods have been described for identifying human disease genes, corresponding methods for prokaryotic gene function discovery are lacking. Here we present two prokaryotic CGP methods, based on phylogenetic profiles, to assist with this task. Results: Using gene occurrence patterns in sample genomes, we developed two CGP methods (statistical and inductive CGP) to assist with the discovery of bacterial gene functions. Statistical CGP exploits the differences in gene frequency against phenotypic groups, while inductive CGP applies supervised machine learning to identify gene occurrence pattern across genomes. Three rediscovery experiments were designed to evaluate the CGP frameworks. The first experiment attempted to rediscover peptidoglycan genes with 417 published genome sequences. Both CGP methods achieved best areas under receiver operating characteristic curve (AUC) of 0.911 in Escherichia coli K-12 (EC-K12) and 0.978 Streptococcus agalactiae 2603 (SA-2603) genomes, with an average improvement in precision of >3.2-fold and a maximum of >27-fold using statistical CGP. A median AUC of >0.95 could still be achieved with as few as 10 genome examples in each group of genome examples in the rediscovery of the peptidoglycan metabolism genes. In the second experiment, a maximum of 109-fold improvement in precision was achieved in the rediscovery of anaerobic fermentation genes in EC-K12. The last experiment attempted to rediscover genes from 31 metabolic pathways in SA-2603, where 14 pathways achieved AUC >0.9 and 28 pathways achieved AUC >0.8 with the best inductive CGP algorithms. Conclusion: Our results demonstrate that the two CGP methods can assist with the study of functionally uncategorised genomic regions and discovery of bacterial gene-function relationships. Our rediscovery experiments also provide a set of standard tasks against which future methods may be compared.12 page(s

Measurement of the running of the QED coupling in small-angle Bhabha scattering at LEP

Using the OPAL detector at LEP, the running of the effective QED coupling alpha(t) is measured for space-like momentum transfer from the angular distribution of small-angle Bhabha scattering. In an almost ideal QED framework, with very favourable experimental conditions, we obtain: Delta alpha(-6.07GeV^2) - Delta alpha(-1.81GeV^2) = (440 pm 58 pm 43 pm 30) X 10^-5, where the first error is statistical, the second is the experimental systematic and the third is the theoretical uncertainty. This agrees with current evaluations of alpha(t).The null hypothesis that alpha remains constant within the above interval of -t is excluded with a significance above 5sigma. Similarly, our results are inconsistent at the level of 3sigma with the hypothesis that only leptonic loops contribute to the running. This is currently the most significant direct measurment where the running alpha(t) is probed differentially within the measured t range.Comment: 43 pages, 12 figures, Submitted to Euro. Phys. J.