Habitat selection by adult Golden Eagles Aquila chrysaetos during the breeding season and implications for wind farm establishment

Capsule: Global Positioning System (GPS)-tagged adult Golden Eagles Aquila chrysaetos breeding in forests in northern Sweden selected clear-cuts, coniferous forests with lichens and steep slopes during the breeding season but avoided wetlands and mixed forest.

Aims: To investigate the habitat selection patterns of tree-nesting Golden Eagles, and identify how potential conflicts with wind farm development could be minimized.

Methods: The study is based on GPS tracking data from 22 adult eagles. We estimated home range sizes using a biased random bridge approach and habitat selection patterns using resource selection functions following a use-availability design.

Results: Core home range size among adults was variable during the breeding season (5–30?km²). Individual movement extents were variable, but sexes did not significantly differ in their scale of movement. At the landscape scale, individuals selected for clear-cuts and coniferous forest with ground lichens, whereas wetland, water bodies and mixed forest were avoided. Steeper and south facing slopes were selected for, whereas, north facing slopes were avoided.

Conclusions: Potential conflicts between eagles and wind energy establishment can be reduced if wind farms are placed away from steep slopes, minimizing areas that are clear-cut during construction, and locating turbines within dense, young and other less favoured forest habitats.     

Gatekeeper role of brain antigen‐presenting CD11c+ cells in neuroinflammation

Multiple sclerosis is the most frequent chronic inflammatory disease of the CNS. The entry and survival of pathogenic T cells in the CNS are crucial for the initiation and persistence of autoimmune neuroinflammation. In this respect, contradictory evidence exists on the role of the most potent type of antigen‐presenting cells, dendritic cells. Applying intravital two‐photon microscopy, we demonstrate the gatekeeper function of CNS professional antigen‐presenting CD11c⁺ cells, which preferentially interact with Th17 cells. IL‐17 expression correlates with expression of GM‐CSF by T cells and with accumulation of CNS CD11c⁺ cells. These CD11c⁺ cells are organized in perivascular clusters, targeted by T cells, and strongly express the inflammatory chemokines Ccl5, Cxcl9, and Cxcl10. Our findings demonstrate a fundamental role of CNS CD11c⁺ cells in the attraction of pathogenic T cells into and their survival within the CNS. Depletion of CD11c⁺ cells markedly reduced disease severity due to impaired enrichment of pathogenic T cells within the CNS.     

Genetic Manipulation of Glycogen Allocation Affects Replicative Lifespan in E. coli

In bacteria, replicative aging manifests as a difference in growth or survival between the two cells emerging from division. One cell can be regarded as an aging mother with a decreased potential for future survival and division, the other as a rejuvenated daughter. Here, we aimed at investigating some of the processes involved in aging in the bacterium Escherichia coli, where the two types of cells can be distinguished by the age of their cell poles. We found that certain changes in the regulation of the carbohydrate metabolism can affect aging. A mutation in the carbon storage regulator gene, csrA, leads to a dramatically shorter replicative lifespan; csrA mutants stop dividing once their pole exceeds an age of about five divisions. These old-pole cells accumulate glycogen at their old cell poles; after their last division, they do not contain a chromosome, presumably because of spatial exclusion by the glycogen aggregates. The new-pole daughters produced by these aging mothers are born young; they only express the deleterious phenotype once their pole is old. These results demonstrate how manipulations of nutrient allocation can lead to the exclusion of the chromosome and limit replicative lifespan in E. coli, and illustrate how mutations can have phenotypic effects that are specific for cells with old poles. This raises the question how bacteria can avoid the accumulation of such mutations in their genomes over evolutionary times, and how they can achieve the long replicative lifespans that have recently been reported.     

The rate of environmental fluctuations shapes ecological dynamics in a two‐species microbial system

Species interactions change when the external conditions change. How these changes affect microbial community properties is an open question. We address this question using a two‐species consortium in which species interactions change from exploitation to competition depending on the carbon source provided. We built a mathematical model and calibrated it using single‐species growth measurements. This model predicted that low frequencies of change between carbon sources lead to species loss, while intermediate and high frequencies of change maintained both species. We experimentally confirmed these predictions by growing co‐cultures in fluctuating environments. These findings complement more established concepts of a diversity peak at intermediate disturbance frequencies. They also provide a mechanistic understanding for how the dynamics at the community level emerges from single‐species behaviours and interspecific interactions. Our findings suggest that changes in species interactions can profoundly impact the ecological dynamics and properties of microbial systems.     

Quantification of serine enantiomers in rat brain microdialysate using Marfey's reagent and LC/MS/MS

The ability to selectively measure serine enantiomer concentrations in rat brain microdialysate is essential during drug discovery to study the interaction of d-serine with the N-methyl-d-aspartate (NMDA) subtype of the glutamate receptor. NMDA receptor-stimulating agents, such as d-serine, have been shown to reduce the negative symptoms and cognitive dysfunction in individuals with schizophrenia when added to conventional or atypical antipsychotic drug regimens. In the work presented here, an LC/MS/MS assay was developed and validated to simultaneously measure d-serine and l-serine concentrations in rat brain microdialysate. Reverse phase chromatographic resolution of the enantiomers was obtained through derivatization with 1-fluoro-2,4-dinitrophenyl-5-l-alanine amide (Marfey's reagent). The assay was validated to determine concentrations over the range of 10-7500 ng/mL using electrospray ionization and multiple reaction monitoring (MRM). Both intra- and inter-day precision and accuracy were less than 16.5% (RE) and 7% (CV) for both analytes, respectively, and assay throughput was increased significantly relative to existing methodologies.     

Virus evolution reveals an exclusive role for LEDGF/p75 in chromosomal tethering of HIV

Retroviruses by definition insert their viral genome into the host cell chromosome. Although the key player of retroviral integration is viral integrase, a role for cellular cofactors has been proposed. Lentiviral integrases use the cellular protein LEDGF/p75 to tether the preintegration complex to the chromosome, although the existence of alternative host proteins substituting for the function of LEDGF/p75 in integration has been proposed. Truncation mutants of LEDGF/p75 lacking the chromosome attachment site strongly inhibit HIV replication by competition for the interaction with integrase. In an attempt to select HIV strains that can overcome the inhibition, we now have used T-cell lines that stably express a C-terminal fragment of LEDGF/p75. Despite resistance development, the affinity of integrase for LEDGF/p75 is reduced and replication kinetics in human primary T cells is impaired. Detection of the integrase mutations A128T and E170G at key positions in the LEDGF/p75-integrase interface provides in vivo evidence for previously reported crystallographic data. Moreover, the complementary inhibition by LEDGF/p75 knockdown and mutagenesis at the integrase-LEDGF/p75 interface points to the incapability of HIV to circumvent LEDGF/p75 function during proviral integration. Altogether, the data provide a striking example of the power of viral molecular evolution. The results underline the importance of the LEDGF/p75 HIV-1 interplay as target for innovative antiviral therapy. Moreover, the role of LEDGF/p75 in targeting integration will stimulate research on strategies to direct gene therapy vectors into safe landing sites.     

Individual‐ versus group‐optimality in the production of secreted bacterial compounds

How unicellular organisms optimize the production of compounds is a fundamental biological question. While it is typically thought that production is optimized at the individual‐cell level, secreted compounds could also allow for optimization at the group level, leading to a division of labor where a subset of cells produces and shares the compound with everyone. Using mathematical modeling, we show that the evolution of such division of labor depends on the cost function of compound production. Specifically, for any trait with saturating benefits, linear costs promote the evolution of uniform production levels across cells. Conversely, production costs that diminish with higher output levels favor the evolution of specialization–especially when compound shareability is high. When experimentally testing these predictions with pyoverdine, a secreted iron‐scavenging compound produced by Pseudomonas aeruginosa, we found linear costs and, consistent with our model, detected uniform pyoverdine production levels across cells. We conclude that for shared compounds with saturating benefits, the evolution of division of labor is facilitated by a diminishing cost function. More generally, we note that shifts in the level of selection from individuals to groups do not solely require cooperation, but critically depend on mechanistic factors, including the distribution of compound synthesis costs.     

Introducing “best single template” models as reference baseline for the Continuous Automated Model Evaluation (CAMEO)

Critical blind assessment of structure prediction techniques is crucial for the scientific community to establish the state of the art, identify bottlenecks, and guide future developments. In Critical Assessment of Techniques in Structure Prediction (CASP), human experts assess the performance of participating methods in relation to the difficulty of the prediction task in a biennial experiment on approximately 100 targets. Yet, the development of automated computational modeling methods requires more frequent evaluation cycles and larger sets of data. The “Continuous Automated Model EvaluatiOn (CAMEO)” platform complements CASP by conducting fully automated blind prediction evaluations based on the weekly pre-release of sequences of those structures, which are going to be published in the next release of the Protein Data Bank (PDB). Each week, CAMEO publishes benchmarking results for predictions corresponding to a set of about 20 targets collected during a 4-day prediction window. CAMEO benchmarking data are generated consistently for all methods at the same point in time, enabling developers to cross-validate their method's performance, and referring to their results in publications. Many successful participants of CASP have used CAMEO—either by directly benchmarking their methods within the system or by comparing their own performance to CAMEO reference data. CAMEO offers a variety of scores reflecting different aspects of structure modeling, for example, binding site accuracy, homo-oligomer interface quality, or accuracy of local model confidence estimates. By introducing the "bestSingleTemplate" method based on structure superpositions as a reference for the accuracy of 3D modeling predictions, CAMEO facilitates objective comparison of techniques and fosters the development of advanced methods.     

Drug development for the treatment of onchocerciasis: Population pharmacokinetic and adverse events modeling of emodepside

BackgroundTo accelerate the progress towards onchocerciasis elimination, a macrofilaricidal drug that kills the adult parasite is urgently needed. Emodepside has shown macrofilaricidal activity against a variety of nematodes and is currently under clinical development for the treatment of onchocerciasis. The aims of this study were i) to characterize the population pharmacokinetic properties of emodepside, ii) to link its exposure to adverse events in healthy volunteers, and iii) to propose an optimized dosing regimen for a planned phase II study in onchocerciasis patients.Methodology / Principal findingsPlasma concentration-time profiles and adverse event data were obtained from 142 subjects enrolled in three phase I studies, including a single-dose, and a multiple-dose, dose-escalation study as well as a relative bioavailability study. Nonlinear mixed-effects modeling was used to evaluate the population pharmacokinetic properties of emodepside. Logistic regression modeling was used to link exposure to drug-related treatment-emergent adverse events (TEAEs). Emodepside pharmacokinetics were well described by a transit-absorption model, followed by a 3-compartment disposition model. Body weight was included as an allometric function and both food and formulation had a significant impact on absorption rate and relative bioavailability. All drug-related TEAEs were transient, and mild or moderate in severity. An increase in peak plasma concentration was associated with an increase in the odds of experiencing a drug-related TEAE of interest.Conclusions/SignificancePharmacokinetic modeling and simulation was used to derive an optimized, body weight-based dosing regimen, which allows for achievement of extended emodepside exposures above target concentrations while maintaining acceptable tolerability margins.