Extending the Cellulosome Paradigm: the Modular Clostridium thermocellum Cellulosomal Serpin PinA Is a Broad-Spectrum Inhibitor of Subtilisin-Like Proteases

Clostridium thermocellum encodes a cellulosomal, modular, and thermostable serine protease inhibitor (serpin), PinA. PinA stability but not inhibitory activity is affected by the Fn(III) and Doc(I) domains, and PinA is a broad inhibitor of subtilisin-like proteases and may play a key role in protecting the cellulosome from protease attack.     

Plant phylogeny drives arboreal caterpillar assemblages across the Holarctic

1. Assemblages of insect herbivores are structured by plant traits such as nutrient content, secondary metabolites, physical traits, and phenology. Many of these traits are phylogenetically conserved, implying a decrease in trait similarity with increasing phylogenetic distance of the host plant taxa. Thus, a metric of phylogenetic distances and relationships can be considered a proxy for phylogenetically conserved plant traits and used to predict variation in herbivorous insect assemblages among co‐occurring plant species.
2. Using a Holarctic dataset of exposed‐feeding and shelter‐building caterpillars, we aimed at showing how phylogenetic relationships among host plants explain compositional changes and characteristics of herbivore assemblages.
3. Our plant–caterpillar network data derived from plot‐based samplings at three different continents included >28,000 individual caterpillar–plant interactions. We tested whether increasing phylogenetic distance of the host plants leads to a decrease in caterpillar assemblage overlap. We further investigated to what degree phylogenetic isolation of a host tree species within the local community explains abundance, density, richness, and mean specialization of its associated caterpillar assemblage.
4. The overlap of caterpillar assemblages decreased with increasing phylogenetic distance among the host tree species. Phylogenetic isolation of a host plant within the local plant community was correlated with lower richness and mean specialization of the associated caterpillar assemblages. Phylogenetic isolation had no effect on caterpillar abundance or density. The effects of plant phylogeny were consistent across exposed‐feeding and shelter‐building caterpillars.
5. Our study reveals that distance metrics obtained from host plant phylogeny are useful predictors to explain compositional turnover among hosts and host‐specific variations in richness and mean specialization of associated insect herbivore assemblages in temperate broadleaf forests. As phylogenetic information of plant communities is becoming increasingly available, further large‐scale studies are needed to investigate to what degree plant phylogeny structures herbivore assemblages in other biomes and ecosystems.

     

Purified viral neuraminidase vaccine to control influenza.

The control of influenza by immunoprophylaxis is difficult because of the antigenic mutability of the influenza virus and the unpredictability of its epidemiologic behaviour. The inactivated whole-virus vaccine currently used is not ideal. Vaccination with pure neuraminidase is suggested. The induced antineuraminidase antibody will restrict viral invasion. Mild illness may or may not occur. On subsequent exposure to influenza virus the individual will produce antihemagglutinin and antineuraminidase antibodies and will be resistant to both infection and illness. Since antigenic changes are less frequent in the viral neuraminidase than in the viral hemagglutinin, the vaccine would be usable for longer periods than the presently used inactivated whole-virus vaccine.     

Improved Working Memory but No Effect on Striatal Vesicular Monoamine Transporter Type 2 after Omega-3 Polyunsaturated Fatty Acid Supplementation

Studies in rodents indicate that diets deficient in omega-3 polyunsaturated fatty acids (n–3 PUFA) lower dopamine neurotransmission as measured by striatal vesicular monoamine transporter type 2 (VMAT2) density and amphetamine-induced dopamine release. This suggests that dietary supplementation with fish oil might increase VMAT2 availability, enhance dopamine storage and release, and improve dopamine-dependent cognitive functions such as working memory. To investigate this mechanism in humans, positron emission tomography (PET) was used to measure VMAT2 availability pre- and post-supplementation of n–3 PUFA in healthy individuals. Healthy young adult subjects were scanned with PET using [¹¹C]-(+)-α-dihydrotetrabenzine (DTBZ) before and after six months of n–3 PUFA supplementation (Lovaza, 2 g/day containing docosahexaenonic acid, DHA 750 mg/d and eicosapentaenoic acid, EPA 930 mg/d). In addition, subjects underwent a working memory task (n-back) and red blood cell membrane (RBC) fatty acid composition analysis pre- and post-supplementation. RBC analysis showed a significant increase in both DHA and EPA post-supplementation. In contrast, no significant change in [¹¹C]DTBZ binding potential (BP_ND) in striatum and its subdivisions were observed after supplementation with n–3 PUFA. No correlation was evident between n–3 PUFA induced change in RBC DHA or EPA levels and change in [¹¹C]DTBZ BP_ND in striatal subdivisions. However, pre-supplementation RBC DHA levels was predictive of baseline performance (i.e., adjusted hit rate, AHR on 3-back) on the n-back task (y = 0.19+0.07, r² = 0.55, p = 0.009). In addition, subjects AHR performance improved on 3-back post-supplementation (pre 0.65±0.27, post 0.80±0.15, p = 0.04). The correlation between n-back performance, and DHA levels are consistent with reports in which higher DHA levels is related to improved cognitive performance. However, the lack of change in [¹¹C]DBTZ BP_ND indicates that striatal VMAT2 regulation is not the mechanism of action by which n–3 PUFA improves cognitive performance.     

A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning

A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i) learn probabilistic models of actions through self-discovery and experience, (ii) utilize these learned models for inferring the goals of human actions, and (iii) perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i) a simulated robot that learns human-like gaze following behavior, and (ii) a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration.     

Prioritizing Tiger Conservation through Landscape Genetics and Habitat Linkages

Even with global support for tiger (Panthera tigris) conservation their survival is threatened by poaching, habitat loss and isolation. Currently about 3,000 wild tigers persist in small fragmented populations within seven percent of their historic range. Identifying and securing habitat linkages that connect source populations for maintaining landscape-level gene flow is an important long-term conservation strategy for endangered carnivores. However, habitat corridors that link regional tiger populations are often lost to development projects due to lack of objective evidence on their importance. Here, we use individual based genetic analysis in combination with landscape permeability models to identify and prioritize movement corridors across seven tiger populations within the Central Indian Landscape. By using a panel of 11 microsatellites we identified 169 individual tigers from 587 scat and 17 tissue samples. We detected four genetic clusters within Central India with limited gene flow among three of them. Bayesian and likelihood analyses identified 17 tigers as having recent immigrant ancestry. Spatially explicit tiger occupancy obtained from extensive landscape-scale surveys across 76,913 km² of forest habitat was found to be only 21,290 km². After accounting for detection bias, the covariates that best explained tiger occupancy were large, remote, dense forest patches; large ungulate abundance, and low human footprint. We used tiger occupancy probability to parameterize habitat permeability for modeling habitat linkages using least-cost and circuit theory pathway analyses. Pairwise genetic differences (F _ST) between populations were better explained by modeled linkage costs (r>0.5, p<0.05) compared to Euclidean distances, which was in consonance with observed habitat fragmentation. The results of our study highlight that many corridors may still be functional as there is evidence of contemporary migration. Conservation efforts should provide legal status to corridors, use smart green infrastructure to mitigate development impacts, and restore habitats where connectivity has been lost.