Surfactant-induced bacterial community changes correlated with increased polycyclic aromatic hydrocarbon degradation in contaminated soil

Bioremediation as a method for removing polycyclic aromatic hydrocarbons (PAHs) from contaminated environments has been criticized for poor removal of potentially carcinogenic but less bioavailable high-molecular-weight (HMW) compounds. As a partial remedy to this constraint, we studied surfactant addition at sub-micellar concentrations to contaminated soil to enhance the biodegradation of PAHs remaining after conventional aerobic bioremediation. We demonstrated increased removal of 4- and 5-ring PAHs using two nonionic surfactants, polyoxyethylene(4)lauryl ether (Brij 30) and polyoxyethylene sorbitol hexaoleate (POESH), and analyzed bacterial community shifts associated with those conditions. Eight groups of abundant bacteria were implicated as potentially being involved in increased HMW PAH removal. A group of unclassified Alphaproteobacteria and members of the Phenylobacterium genus in particular showed significantly increased relative abundance in the two conditions exhibiting increased PAH removal. Other implicated groups included members of the Sediminibacterium, Terrimonas, Acidovorax, and Luteimonas genera, as well as uncharacterized organisms within the families Chitinophagaceae and Bradyrhizobiaceae. Targeted isolation identified a subset of the community likely using the surfactants as a growth substrate but few of the isolates exhibited PAH-degradation capability. Isolates recovered from the Acidovorax and uncharacterized Bradyrhizobiaceae groups suggest the abundance of those groups may have been attributable to growth on surfactants. Understanding the specific bacteria responsible for HMW PAH removal in natural and engineered systems and their response to stimuli such as surfactant amendment may improve bioremediation efficacy during treatment of contaminated environmental media

Improving Polycyclic Aromatic Hydrocarbon Biodegradation in Contaminated Soil Through Low-Level Surfactant Addition After Conventional Bioremediation

Efficacy of bioremediation for soil contaminated with polycyclic aromatic hydrocarbons (PAHs) may be limited by the fractions of soil-bound PAHs that are less accessible to PAH-degrading microorganisms. In previous test-tube-scale work, submicellar doses of nonionic surfactants were screened for their ability to enhance the desorption and biodegradation of residual PAHs in soil after conventional bioremediation in a laboratory-scale, slurry-phase bioreactor. Polyoxyethylene sorbitol hexaoleate (POESH) was the optimum surfactant for enhancing PAH removal, especially the high–molecular weight PAHs. This work extends that concept by treating the effluent from the slurry-phase bioreactor in a second-stage batch reactor, to which POESH was added, for an additional 7 or 12 days. Surfactant amendment removed substantial amounts of the PAHs and oxy-PAHs remaining after conventional slurry-phase bioremediation, including more than 80% of residual 4-ring PAHs. Surfactant-amended treatment decreased soil cytotoxicity, but often increased the genotoxicity of the soil as measured using the DT-40 chicken lymphocyte DNA damage response assay. Potential ecotoxicity, measured using a seed germination assay, was reduced by bioreactor treatment and was reduced further after second-stage treatment with POESH. Of bacteria previously implicated as potential PAH degraders under POESH-amended conditions in a prior study, members of the Terrimonas genus were associated with differences in high–molecular weight PAH removal in the current study. Research using submicellar doses of surfactant as a second-stage treatment step is limited and these findings can inform the design of bioremediation systems at field sites treating soil contaminated with PAHs and other hydrophobic contaminants that have low bioaccessibility

Efficacy and safety of betahistine treatment in patients with Meniere’s disease: primary results of a long term, multicentre, double blind, randomised, placebo controlled, dose defining trial (BEMED trial)

Study question What is the long term efficacy of betahistine dihydrochloride on the incidence of vertigo attacks in patients with Meniere’s disease, compared with placebo? Methods The BEMED trial is a multicentre, double blind, randomised, placebo controlled, three arm, parallel group, phase III, dose defining superiority trial conducted in 14 German tertiary referral centres (for neurology or ear, nose, and throat). Adults aged 21-80 years (mean age 56 years) with definite unilateral or bilateral Meniere’s disease were recruited from March 2008 to November 2012. Participants received placebo (n=74), low dose betahistine (2×24 mg daily, (n=73)), or high dose betahistine (3×48 mg daily, (n=74)) over nine months. The primary outcome was the number of attacks per 30 days, based on patients’ diaries during a three month assessment period at months seven to nine. An internet based randomisation schedule performed a concealed 1:1:1 allocation, stratified by study site. Secondary outcomes included the duration and severity of attacks, change in quality of life scores, and several observer-reported parameters to assess changes in audiological and vestibular function. Study answer and limitations Incidence of attacks related to Meniere’s disease did not differ between the three treatment groups (P=0.759). Compared with placebo, attack rate ratios were 1.036 (95% confidence interval 0.942 to 1.140) and 1.012 (0.919 to 1.114) for low dose and high dose betahistine, respectively. The overall monthly attack rate fell significantly by the factor 0.758 (0.705 to 0.816; P<0.001). The population based, mean monthly incidence averaged over the assessment period was 2.722 (1.304 to 6.309), 3.204 (1.345 to 7.929), and 3.258 (1.685 to 7.266) for the placebo, low dose betahistine, and high dose betahistine groups, respectively. Results were consistent for all secondary outcomes. Treatment was well tolerated with no unexpected safety findings. Without a control group of patients who did not receive any intervention to follow the natural course of the disease, the placebo effect could not be accurately assessed and differentiated from spontaneous remission and fluctuation of symptoms. What this study adds Current evidence is limited as to whether betahistine prevents vertigo attacks caused by Meniere’s disease, compared with placebo. The trial provides information on symptom relief on placebo intervention which is relevant for the design of future studies on potential disease modifying treatments in patients with Meniere’s disease. Funding, competing interests, data sharing Support from the German Federal Ministry of Education and Research (BMBF support code 01KG0708). Potential competing interests have been reported in full at the end of the paper on thebmj.com. Data are available from the corresponding author ([email protected]) or biostatistician ([email protected]). Study registration EudraCT no 2005-000752-32; ISRCTN no ISRCTN44359668

Drosophila suzukii: the genetic footprint of a recent, world-wide invasion

Native to Asia, the soft-skinned fruit pest Drosophila suzukii has recently invaded the United States and Europe. The eastern United States represents the most recent expansion of their range, and presents an opportunity to test alternative models of colonization history. Here we investigate the genetic population structure of this invasive fruit fly, with a focus on the eastern United States. We sequenced six X-linked gene fragments from 246 individuals collected from a total of 12 populations. We examine patterns of genetic diversity within and between populations and explore alternative colonization scenarios using Approximate Bayesian Computation. Our results indicate high levels of nucleotide diversity in this species and suggest that the recent invasions of Europe and the continental United States are independent demographic events. More broadly speaking, our results highlight the importance of integrating population structure into demographic models, particularly when attempting to reconstruct invasion histories. Finally, our simulation results illustrate the general challenge of reconstructing invasion histories using genetic data and suggest that genome-level data are often required to distinguish among alternative demographic scenarios

Health care costs, utilization and patterns of care following Lyme disease

BACKGROUND:Lyme disease is the most frequently reported vector borne infection in the United States. The Centers for Disease Control have estimated that approximately 10% to 20% of individuals may experience Post-Treatment Lyme Disease Syndrome - a set of symptoms including fatigue, musculoskeletal pain, and neurocognitive complaints that persist after initial antibiotic treatment of Lyme disease. Little is known about the impact of Lyme disease or post-treatment Lyme disease symptoms (PTLDS) on health care costs and utilization in the United States. OBJECTIVES:1) to examine the impact of Lyme disease on health care costs and utilization, 2) to understand the relationship between Lyme disease and the probability of developing PTLDS, 3) to understand how PTLDS may impact health care costs and utilization. METHODS:This study utilizes retrospective data on medical claims and member enrollment for persons aged 0-64 years who were enrolled in commercial health insurance plans in the United States between 2006-2010. 52,795 individuals treated for Lyme disease were compared to 263,975 matched controls with no evidence of Lyme disease exposure. RESULTS:Lyme disease is associated with $2,968 higher total health care costs (95$3,798 higher total health care costs (95% CI: 3,542-4,055, p<.001) and 66% more outpatient visits (95% CI: 64%-69%, p<.001) over a 12-month period, relative to those with no PTLDS-related diagnoses. CONCLUSIONS:Lyme disease is associated with increased costs above what would be expected for an easy to treat infection. The presence of PTLDS-related diagnoses after treatment is associated with significant health care costs and utilization

A community-maintained standard library of population genetic models

The explosion in population genomic data demands ever more complex modes of analysis, and increasingly, these analyses depend on sophisticated simulations. Recent advances in population genetic simulation have made it possible to simulate large and complex models, but specifying such models for a particular simulation engine remains a difficult and error-prone task. Computational genetics researchers currently re-implement simulation models independently, leading to inconsistency and duplication of effort. This situation presents a major barrier to empirical researchers seeking to use simulations for power analyses of upcoming studies or sanity checks on existing genomic data. Population genetics, as a field, also lacks standard benchmarks by which new tools for inference might be measured. Here, we describe a new resource, stdpopsim, that attempts to rectify this situation. Stdpopsim is a community-driven open source project, which provides easy access to a growing catalog of published simulation models from a range of organisms and supports multiple simulation engine backends. This resource is available as a well-documented python library with a simple command-line interface. We share some examples demonstrating how stdpopsim can be used to systematically compare demographic inference methods, and we encourage a broader community of developers to contribute to this growing resource.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone

CFH, C3 and ARMS2 Are Significant Risk Loci for Susceptibility but Not for Disease Progression of Geographic Atrophy Due to AMD

Age-related macular degeneration (AMD) is a prevalent cause of blindness in Western societies. Variants in the genes encoding complement factor H (CFH), complement component 3 (C3) and age-related maculopathy susceptibility 2 (ARMS2) have repeatedly been shown to confer significant risks for AMD; however, their role in disease progression and thus their potential relevance for interventional therapeutic approaches remains unknown. Here, we analyzed association between variants in CFH, C3 and ARMS2 and disease progression of geographic atrophy (GA) due to AMD. A quantitative phenotype of disease progression was computed based on longitudinal observations by fundus autofluorescence imaging. In a subset of 99 cases with pure bilateral GA, variants in CFH (Y402H), C3 (R102G), and ARMS2 (A69S) are associated with disease (P = 1.6x10(-9), 3.2x10(-3), and P = 2.6x10(-12), respectively) when compared to 612 unrelated healthy control individuals. In cases, median progression rate of GA over a mean follow-up period of 3.0 years was 1.61 mm(2)/year with high concordance between fellow eyes. No association between the progression rate and any of the genetic risk variants at the three loci was observed (P>0.13). This study confirms that variants at CFH, C3, and ARMS2 confer significant risks for GA due to AMD. In contrast, our data indicate no association of these variants with disease progression which may have important implications for future treatment strategies. Other, as yet unknown susceptibilities may influence disease progression