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Animal-associated microbial communities can play major roles in the physiology, development, ecology, and evolution of their hosts, but the study of their diversity has yet focused on a limited number of host species. In this study, we used high-throughput sequencing of partial sequences of the bacterial 16S rRNA gene to assess the diversity of the gut-inhabiting bacterial communities of 212 specimens of tropical anuran amphibians from Brazil and Madagascar. The core gut-associated bacterial communities among tadpoles from two different continents strongly overlapped, with eight highly represented operational taxonomic units (OTUs) in common. In contrast, the core communities of adults and tadpoles from Brazil were less similar with only one shared OTU. This suggests a community turnover at metamorphosis. Bacterial diversity was higher in tadpoles compared to adults. Distinct differences in composition and diversity occurred among gut bacterial communities of conspecific tadpoles from different water bodies and after experimental fasting for 8 days, demonstrating the influence of both environmental factors and food on the community structure. Communities from syntopic tadpoles clustered by host species both in Madagascar and Brazil, and the Malagasy tadpoles also had species-specific isotope signatures. We recommend future studies to analyze the turnover of anuran gut bacterial communities at metamorphosis, compare the tadpole core communities with those of other aquatic organisms, and assess the possible function of the gut microbiota as a reservoir for protective bacteria on the amphibian skin.
Species diversity promotes the delivery of multiple ecosystem functions (multifunctionality). However, the relative functional importance of rare and common species in driving the biodiversity multifunctionality relationship remains unknown. We studied the relationship between the diversity of rare and common species (according to their local abundances and across nine different trophic groups), and multifunctionality indices derived from 14 ecosystem functions on 150 grasslands across a land use intensity (LUI) gradient. The diversity of above- and below-ground rare species had opposite effects, with rare above-ground species being associated with high levels of multifunctionality, probably because their effects on different functions did not trade off against each other. Conversely, common species were only related to average, not high, levels of multifunctionality, and their functional effects declined with LUI. Apart from the community level effects of diversity, we found significant positive associations between the abundance of individual species and multifunctionality in 6% of the species tested. Species specific functional effects were best predicted by their response to LUI: species that declined in abundance with land use intensification were those associated with higher levels of multifunctionality. Our results highlight the importance of rare species for ecosystem multifunctionality and help guiding future conservation priorities.
Behavioral choice can be characterized along two axes. One axis distinguishes reflexive, model-free systems that slowly accumulate values through experience and a model-based system that uses knowledge to reason prospectively. The second axis distinguishes Pavlovian valuation of stimuli from instrumental valuation of actions or stimulus–action pairs. This results in four values and many possible interactions between them, with important consequences for accounts of individual variation. We here explored whether individual variation along one axis was related to individual variation along the other. Specifically, we asked whether individuals' balance between model-based and model-free learning was related to their tendency to show Pavlovian interferences with instrumental decisions. In two independent samples with a total of 243 participants, Pavlovian–instrumental transfer effects were negatively correlated with the strength of model-based reasoning in a two-step task. This suggests a potential common underlying substrate predisposing individuals to both have strong Pavlovian interference and be less model-based and provides a framework within which to interpret the observation of both effects in addiction.
The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008-2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0.
Antibodies against spike proteins of influenza are used as a tool for characterization of viruses and therapeutic approaches. However, development, production and quality control of antibodies is expensive and time consuming. To circumvent these difficulties, three peptides were derived from complementarity determining regions of an antibody heavy chain against influenza A spike glycoprotein. Their binding properties were studied experimentally, and by molecular dynamics simulations. Two peptide candidates showed binding to influenza A/Aichi/2/68 H3N2. One of them, termed PeB, with the highest affinity prevented binding to and infection of target cells in the micromolar region without any cytotoxic effect. PeB matches best the conserved receptor binding site of hemagglutinin. PeB bound also to other medical relevant influenza strains, such as human-pathogenic A/California/7/2009 H1N1, and avian-pathogenic A/MuteSwan/Rostock/R901/2006 H7N1. Strategies to improve the affinity and to adapt specificity are discussed and exemplified by a double amino acid substituted peptide, obtained by substitutional analysis. The peptides and their derivatives are of great potential for drug development as well as biosensing.
Air pollution is the number one environmental cause of premature deaths in Europe. Despite extensive regulations, air pollution remains a challenge, especially in urban areas. For studying summertime air quality in the Berlin–Brandenburg region of Germany, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) is set up and evaluated against meteorological and air quality observations from monitoring stations as well as from a field campaign conducted in 2014. The objective is to assess which resolution and level of detail in the input data is needed for simulating urban background air pollutant concentrations and their spatial distribution in the Berlin–Brandenburg area. The model setup includes three nested domains with horizontal resolutions of 15, 3 and 1 km and anthropogenic emissions from the TNO-MACC III inventory. We use RADM2 chemistry and the MADE/SORGAM aerosol scheme. Three sensitivity simulations are conducted updating input parameters to the single-layer urban canopy model based on structural data for Berlin, specifying land use classes on a sub-grid scale (mosaic option) and downscaling the original emissions to a resolution of ca. 1 km × 1 km for Berlin based on proxy data including traffic density and population density. The results show that the model simulates meteorology well, though urban 2 m temperature and urban wind speeds are biased high and nighttime mixing layer height is biased low in the base run with the settings described above. We show that the simulation of urban meteorology can be improved when specifying the input parameters to the urban model, and to a lesser extent when using the mosaic option. On average, ozone is simulated reasonably well, but maximum daily 8 h mean concentrations are underestimated, which is consistent with the results from previous modelling studies using the RADM2 chemical mechanism. Particulate matter is underestimated, which is partly due to an underestimation of secondary organic aerosols. NOx (NO + NO2) concentrations are simulated reasonably well on average, but nighttime concentrations are overestimated due to the model's underestimation of the mixing layer height, and urban daytime concentrations are underestimated. The daytime underestimation is improved when using downscaled, and thus locally higher emissions, suggesting that part of this bias is due to deficiencies in the emission input data and their resolution. The results further demonstrate that a horizontal resolution of 3 km improves the results and spatial representativeness of the model compared to a horizontal resolution of 15 km. With the input data (land use classes, emissions) at the level of detail of the base run of this study, we find that a horizontal resolution of 1 km does not improve the results compared to a resolution of 3 km. However, our results suggest that a 1 km horizontal model resolution could enable a detailed simulation of local pollution patterns in the Berlin–Brandenburg region if the urban land use classes, together with the respective input parameters to the urban canopy model, are specified with a higher level of detail and if urban emissions of higher spatial resolution are used.
Positive coping styles and perigenual ACC volume: two related mechanisms for conferring resilience?
(2016)
Stress exposure has been linked to increased rates of depression and anxiety in adults, particularly in females, and has been associated with maladaptive changes in the anterior cingulate cortex (ACC), which is an important brain structure involved in internalizing disorders. Coping styles are important mediators of the stress reaction by establishing homeostasis, and may thus confer resilience to stress-related psychopathology. Anatomical scans were acquired in 181 healthy participants at age 25 years. Positive coping styles were determined using a self-report questionnaire (German Stress Coping Questionnaire, SVF78) at age 22 years. Adult anxiety and depression symptoms were assessed at ages 22, 23 and 25 years with the Young Adult Self-Report. Information on previous internalizing diagnoses was obtained by diagnostic interview (2-19 years). Positive coping styles were associated with increased ACC volume. ACC volume and positive coping styles predicted anxiety and depression in a sex-dependent manner with increased positive coping and ACC volume being related to lower levels of psychopathology in females, but not in males. These results remained significant when controlled for previous internalizing diagnoses. These findings indicate that positive coping styles and ACC volume are two linked mechanisms, which may serve as protective factors against internalizing disorders.
Converging evidence emphasizes the role of an interaction between monoamine oxidase A (MAOA) genotype, environmental adversity, and sex in the pathophysiology of aggression. The present study aimed to clarify the impact of this interaction on neural activity in aggression-related brain systems. Functional magnetic resonance imaging was performed in 125 healthy adults from a high-risk community sample followed since birth. DNA was genotyped for the MAOA-VNTR (variable number of tandem repeats). Exposure to childhood life stress (CLS) between the ages of 4 and 11 years was assessed using a standardized parent interview, aggression by the Youth/Young Adult Self-Report between the ages of 15 and 25 years, and the VIRA-R (Vragenlijst Instrumentele En Reactieve Agressie) at the age of 15 years. Significant interactions were obtained between MAOA genotype, CLS, and sex relating to amygdala, hippocampus, and anterior cingulate cortex (ACC) response, respectively. Activity in the amygdala and hippocampus during emotional face-matching increased with the level of CLS in male MAOA-L, while decreasing in male MAOA-H, with the reverse pattern present in females. Findings in the opposite direction in the ACC during a flanker NoGo task suggested that increased emotional activity coincided with decreased inhibitory control. Moreover, increasing amygdala activity was associated with higher Y(A)SR aggression in male MAOA-L and female MAOA-H carriers. Likewise, a significant association between amygdala activity and reactive aggression was detected in female MAOA-H carriers. The results point to a moderating role of sex in the MAOAx CLS interaction for intermediate phenotypes of emotional and inhibitory processing, suggesting a possible mechanism in conferring susceptibility to violence-related disorders.
Land-use intensification is a major driver of biodiversity loss(1,2). Alongside reductions in local species diversity, biotic homogenization at larger spatial scales is of great concern for conservation. Biotic homogenization means a decrease in beta-diversity (the compositional dissimilarity between sites). Most studies have investigated losses in local (alpha)-diversity(1,3) and neglected biodiversity loss at larger spatial scales. Studies addressing beta-diversity have focused on single or a few organism groups (for example, ref. 4), and it is thus unknown whether land-use intensification homogenizes communities at different trophic levels, above-and belowground. Here we show that even moderate increases in local land-use intensity (LUI) cause biotic homogenization across microbial, plant and animal groups, both above- and belowground, and that this is largely independent of changes in alpha-diversity. We analysed a unique grassland biodiversity dataset, with abundances of more than 4,000 species belonging to 12 trophic groups. LUI, and, in particular, high mowing intensity, had consistent effects on beta-diversity across groups, causing a homogenization of soil microbial, fungal pathogen, plant and arthropod communities. These effects were nonlinear and the strongest declines in beta-diversity occurred in the transition from extensively managed to intermediate intensity grassland. LUI tended to reduce local alpha-diversity in aboveground groups, whereas the alpha-diversity increased in belowground groups. Correlations between the alpha-diversity of different groups, particularly between plants and their consumers, became weaker at high LUI. This suggests a loss of specialist species and is further evidence for biotic homogenization. The consistently negative effects of LUI on landscape-scale biodiversity underscore the high value of extensively managed grasslands for conserving multitrophic biodiversity and ecosystem service provision. Indeed, biotic homogenization rather than local diversity loss could prove to be the most substantial consequence of land-use intensification.