Do contaminants originating from state-of-the-art treated wastewater impact the ecological quality of surface waters?

Since the 1980s, advances in wastewater treatment technology have led to considerably improved surface water quality in the urban areas of many high income countries. However, trace concentrations of organic wastewater-associated contaminants may still pose a key environmental hazard impairing the ecological quality of surface waters. To identify key impact factors, we analyzed the effects of a wide range of anthropogenic and environmental variables on the aquatic macroinvertebrate community. We assessed ecological water quality at 26 sampling sites in four urban German lowland river systems with a 0–100% load of state-of-the-art biological activated sludge treated wastewater. The chemical analysis suite comprised 12 organic contaminants (five phosphor organic flame retardants, two musk fragrances, bisphenol A, nonylphenol, octylphenol, diethyltoluamide, terbutryn), 16 polycyclic aromatic hydrocarbons, and 12 heavy metals. Non-metric multidimensional scaling identified organic contaminants that are mainly wastewater-associated (i.e., phosphor organic flame retardants, musk fragrances, and diethyltoluamide) as a major impact variable on macroinvertebrate species composition. The structural degradation of streams was also identified as a significant factor. Multiple linear regression models revealed a significant impact of organic contaminants on invertebrate populations, in particular on Ephemeroptera, Plecoptera, and Trichoptera species. Spearman rank correlation analyses confirmed wastewater-associated organic contaminants as the most significant variable negatively impacting the biodiversity of sensitive macroinvertebrate species. In addition to increased aquatic pollution with organic contaminants, a greater wastewater fraction was accompanied by a slight decrease in oxygen concentration and an increase in salinity. This study highlights the importance of reducing the wastewater-associated impact on surface waters. For aquatic ecosystems in urban areas this would lead to: (i) improvement of the ecological integrity, (ii) reduction of biodiversity loss, and (iii) faster achievement of objectives of legislative requirements, e.g., the European Water Framework Directive

A Bayesian Approach to Analyse Genetic Variation within RNA Viral Populations

The development of modern and affordable sequencing technologies has allowed the study of viral populations to an unprecedented depth. This is of particular interest for the study of within-host RNA viral populations, where variation due to error-prone polymerases can lead to immune escape, antiviral resistance and adaptation to new host species. Methods to sequence RNA virus genomes include reverse transcription (RT) and polymerase chain reaction (PCR). RT-PCR is a molecular biology technique widely used to amplify DNA from an RNA template. The method itself relies on the in vitro synthesis of copy DNA from RNA followed by multiple cycles of DNA amplification. However, this method introduces artefactual errors that can act as confounding factors when the sequence data are analysed. Although there are a growing number of published studies exploring the intra- and inter-host evolutionary dynamics of RNA viruses, the complexity of the methods used to generate sequences makes it difficult to produce probabilistic statements about the likely sources of observed sequence variants. This complexity is further compounded as both the depth of sequencing and the length of the genome segment of interest increase. Here we develop a Bayesian method to characterise and differentiate between likely structures for the background viral population. This approach can then be used to identify nucleotide sites that show evidence of change in the within-host viral population structure, either over time or relative to a reference sequence (e.g. an inoculum or another source of infection), or both, without having to build complex evolutionary models. Identification of these sites can help to inform the design of more focussed experiments using molecular biology tools, such as site-directed mutagenesis, to assess the function of specific amino acids. We illustrate the method by applying to datasets from experimental transmission of equine influenza, and a pre-clinical vaccine trial for HIV-1

The distribution of pond snail communities across a landscape: separating out the influence of spatial position from local habitat quality for ponds in south-east Northumberland, UK

Ponds support a rich biodiversity because the heterogeneity of individual ponds creates, at the landscape scale, a diversity of habitats for wildlife. The distribution of pond animals and plants will be influenced by both the local conditions within a pond and the spatial distribution of ponds across the landscape. Separating out the local from the spatial is difficult because the two are often linked. Pond snails are likely to be affected by both local conditions, e.g. water hardness, and spatial patterns, e.g. distance between ponds, but studies of snail communities struggle distinguishing between the two. In this study, communities of snails were recorded from 52 ponds in a biogeographically coherent landscape in north-east England. The distribution of snail communities was compared to local environments characterised by the macrophyte communities within each pond and to the spatial pattern of ponds throughout the landscape. Mantel tests were used to partial out the local versus the landscape respective influences. Snail communities became more similar in ponds that were closer together and in ponds with similar macrophyte communities as both the local and the landscape scale were important for this group of animals. Data were collected from several types of ponds, including those created on nature reserves specifically for wildlife, old field ponds (at least 150 years old) primarily created for watering livestock and subsidence ponds outside protected areas or amongst coastal dunes. No one pond type supported all the species. Larger, deeper ponds on nature reserves had the highest numbers of species within individual ponds but shallow, temporary sites on farm land supported a distinct temporary water fauna. The conservation of pond snails in this region requires a diversity of pond types rather than one idealised type and ponds scattered throughout the area at a variety of sites, not just concentrated on nature reserves

Ancient Ancestry of KFDV and AHFV Revealed by Complete Genome Analyses of Viruses Isolated from Ticks and Mammalian Hosts

Alkhurma hemorrhagic fever (AHF) and Kyasanur Forest disease (KFD) viruses both cause serious and sometimes fatal human disease in their respective ranges, Saudi Arabia and India. AHFV was first identified in the mid-1990s and due to its strong genetic similarity to KFDV it has since been considered the result of a recent introduction of KFDV into Saudi Arabia. To gain a better understanding of the evolutionary history of AHFV and KFDV, we sequenced the full-length genomes of 3 KFDV and 16 AHFV. Sequence analyses show a greater genetic diversity within AHFV than previously thought, particularly within the tick population. The phylogeny constructed with these 19 full-length sequences and two AHFV sequences from GenBank indicates AHFV diverged from KFDV almost 700 years ago. Given the presence of competent tick vectors in the regions between and surrounding Saudi Arabia and India and the recent identification of AHFV in Egypt, these results suggest a broader geographic range of AHFV and KFDV, and raise the possibility of other AHFV/KFDV–like viruses circulating in these regions

Evidence of HIV-1 adaptation to host HLA alleles following chimp-to-human transmission

<p>Abstract</p> <p>Background</p> <p>The cytotoxic T-lymphocyte immune response is important in controlling HIV-1 replication in infected humans. In this immune pathway, viral peptides within infected cells are presented to T-lymphocytes by the polymorphic human leukocyte antigens (HLA). HLA alleles exert selective pressure on the peptide regions and immune escape mutations that occur at some of the targeted sites can enable the virus to adapt to the infected host. The pattern of ongoing immune escape and reversion associated with several human HLA alleles has been studied extensively. Such mutations revert upon transmission to a host without the HLA allele because the escape mutation incurs a fitness cost. However, to-date there has been little attempt to study permanent loss of CTL epitopes due to escape mutations without an effect on fitness.</p> <p>Results</p> <p>Here, we set out to determine the extent of adaptation of HIV-1 to three well-characterized HLA alleles during the initial exposure of the virus to the human cytotoxic immune responses following transmission from chimpanzee. We generated a chimpanzee consensus sequence to approximate the virus sequence that was initially transmitted to the human host and used a method based on peptide binding affinity to HLA crystal structures to predict peptides that were potentially targeted by the HLA alleles on this sequence. Next, we used codon-based phylogenetic models to quantify the average selective pressure that acted on these regions during the period immediately following the zoonosis event, corresponding to the branch of the phylogenetic tree leading to the common ancestor of all of the HIV-1 sequences. Evidence for adaptive evolution during this period was observed at regions recognised by HLA A*6801 and A*0201, both of which are common in African populations. No evidence of adaptive evolution was observed at sites targeted by HLA-B*2705, which is a rare allele in African populations.</p> <p>Conclusion</p> <p>Our results suggest that the ancestral HIV-1 virus experienced a period of positive selective pressure due to immune responses associated with HLA alleles that were common in the infected human population. We propose that this resulted in permanent escape from immune responses targeting unconstrained regions of the virus.</p

'A good fit?' Bringing the Sociology of Footwear to the Clinical Encounter in Podiatry Services : A Narrative Review

Background: This narrative review explores the ways in which drawing on theories and methods used in sociological work on footwear and identity can contribute to healthcare research with podiatrists and their patients, highlighting recent research in this field, implications for practice and potential areas for future development. Traditionally, research within Podiatry Services has tended to adopt a quantitative, positivist focus, developing separately from a growing body of sociological work exploring the importance of shoes in constructing identity and self-image. Bringing qualitative research drawing on sociological theory and methods to the clinical encounter has real potential to increase our understanding of patient values, motivations and – crucially – any barriers to adopting ‘healthier’ footwear that they may encounter. Such work can help practitioners to understand why patients may resist making changes to their footwear practices, and help us to devise new ways for practitioners to explore and ultimately break down individual barriers to change (including their own preconceptions as practitioners). This, in turn, may lead to long-term, sustainable changes to footwear practices and improvements in foot health for those with complex health conditions and the wider population. Conclusion: A recognition of the complex links between shoes and identity is opening up space for discussion of patient resistance to footwear changes, and paving the way for future research in this field beyond the temporary ‘moment’ of the clinical encounter

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

MPI-PHYLIP: Parallelizing Computationally Intensive Phylogenetic Analysis Routines for the Analysis of Large Protein Families

Background: Phylogenetic study of protein sequences provides unique and valuable insights into the molecular and genetic basis of important medical and epidemiological problems as well as insights about the origins and development of physiological features in present day organisms. Consensus phylogenies based on the bootstrap and other resampling methods play a crucial part in analyzing the robustness of the trees produced for these analyses. Methodology: Our focus was to increase the number of bootstrap replications that can be performed on large protein datasets using the maximum parsimony, distance matrix, and maximum likelihood methods. We have modified the PHYLIP package using MPI to enable large-scale phylogenetic study of protein sequences, using a statistically robust number of bootstrapped datasets, to be performed in a moderate amount of time. This paper discusses the methodology used to parallelize the PHYLIP programs and reports the performance of the parallel PHYLIP programs that are relevant to the study of protein evolution on several protein datasets. Conclusions: Calculations that currently take a few days on a state of the art desktop workstation are reduced to calculations that can be performed over lunchtime on a modern parallel computer. Of the three protein methods tested, the maximum likelihood method scales the best, followed by the distance method, and then the maximum parsimony method. However, the maximum likelihood method requires significant memory resources, which limits its application to mor

Bringing Molecules Back into Molecular Evolution

Much molecular-evolution research is concerned with sequence analysis. Yet these sequences represent real, three-dimensional molecules with complex structure and function. Here I highlight a growing trend in the field to incorporate molecular structure and function into computational molecular-evolution work. I consider three focus areas: reconstruction and analysis of past evolutionary events, such as phylogenetic inference or methods to infer selection pressures; development of toy models and simulations to identify fundamental principles of molecular evolution; and atom-level, highly realistic computational modeling of molecular structure and function aimed at making predictions about possible future evolutionary events