A novel allele of the Arabidopsis thaliana MACPF protein CAD1 results in deregulated immune signaling

Immune recognition in plants is governed by two major classes of receptors: pattern recognition receptors (PRRs) and nucleotide-binding leucine-rich repeat receptors (NLRs). Located at the cell surface, PRRs bind extracellular ligands originating from microbes (indicative of “non-self”) or damaged plant cells (indicative of “infected-self”), and trigger signaling cascades to protect against infection. Located intracellularly, NLRs sense pathogen-induced physiological changes and trigger localized cell death and systemic resistance. Immune responses are under tight regulation in order to maintain homeostasis and promote plant health. In a forward-genetic screen to identify regulators of PRR-mediated immune signaling, we identified a novel allele of the membrane-attack complex and perforin (MACPF)-motif containing protein CONSTITUTIVE ACTIVE DEFENSE 1 (CAD1) resulting from a missense mutation in a conserved N-terminal cysteine. We show that cad1-5 mutants display deregulated immune signaling and symptoms of autoimmunity dependent on the lipase-like protein ENHANCED DISEASE SUSCEPTIBILITY 1 (EDS1), suggesting that CAD1 integrity is monitored by the plant immune system. We further demonstrate that CAD1 localizes to both the cytosol and plasma membrane using confocal microscopy and subcellular fractionation. Our results offer new insights into immune homeostasis and provide tools to further decipher the intriguing role of MACPF proteins in plants.     

Will You Accept the Government's Friend Request? Social Networks and Privacy Concerns

Participating in social network websites entails voluntarily sharing private information, and the explosive growth of social network websites over the last decade suggests shifting views on privacy. Concurrently, new anti-terrorism laws, such as the USA Patriot Act, ask citizens to surrender substantial claim to privacy in the name of greater security. I address two important questions regarding individuals'' views on privacy raised by these trends. First, how does prompting individuals to consider security concerns affect their views on government actions that jeopardize privacy? Second, does the use of social network websites alter the effect of prompted security concerns? I posit that prompting individuals to consider security concerns does lead to an increased willingness to accept government actions that jeopardize privacy, but that frequent users of websites like Facebook are less likely to be swayed by prompted security concerns. An embedded survey experiment provides support for both parts of my claim.     

AMPK Is a Negative Regulator of the Warburg Effect and Suppresses Tumor Growth In Vivo

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Highlights? Loss of AMPKα1 cooperates with the Myc oncogene to accelerate lymphomagenesis ? AMPKα dysfunction enhances aerobic glycolysis (Warburg effect) ? Inhibiting HIF-1α reverses the metabolic effects of AMPKα loss ? HIF-1α mediates the growth advantage of tumors with reduced AMPK signaling     

Seascape genetics of the stalked kelp Pterygophora californica and comparative population genetics in the Santa Barbara Channel

We conducted a population genetic analysis of the stalked kelp, Pterygophora californica, in the Santa Barbara Channel, California, USA. The results were compared with previous work on the genetic differentiation of giant kelp, Macrocystis pyrifera, in the same region. These two sympatric kelps not only share many life history and dispersal characteristics but also differ in that dislodged P. californica does not produce floating rafts with buoyant fertile sporophytes, commonly observed for M. pyrifera. We used a comparative population genetic approach with these two species to test the hypothesis that the ability to produce floating rafts increases the genetic connectivity among kelp patches in the Santa Barbara Channel. We quantified the association of habitat continuity and oceanographic distance with the genetic differentiation observed in stalked kelp, like previously conducted for giant kelp. We compared both overall (across all patches) and pairwise (between patches) genetic differentiation. We found that oceanographic transit time, habitat continuity, and geographic distance were all associated with genetic connectivity in P. californica, supporting similar previous findings for M. pyrifera. Controlling for differences in heterozygosity between kelp species using Jost's D_EST, we showed that global differentiation and pairwise differentiation were similar among patches between the two kelp species, indicating that they have similar dispersal capabilities despite their differences in rafting ability. These results suggest that rafting sporophytes do not play a significant role in effective dispersal of M. pyrifera at ecologically relevant spatial and temporal scales.     

Effect of Metalaxyl on the incidence and severity of Pearl millet downy mildew disease in Northern Nigeria

Pearl millet downy mildew (DM) incidence, severity and yield losses of two pearl millet varieties (local and improved) due to the disease were determined in the field. Significant differences in the disease incidence and severity were recorded in the plots sown with metalaxyl-treated seeds and those sown with non-treated seeds, indicating the efficacy of the fungicide on the fungus. Yield losses due to non-treatment of seeds with metalaxyl was 40.88 and 45.39% in a local variety and 43.00 and 18.60% in an improved variety in the 2000 and 2001 cropping seasons respectively. Significant differences between plots sown with metalaxyl-treated and those sown with non-treated seeds were obtained for other yield components such as 1000-grains weight, panicle length and weight.     

Transfer of Natural Micro Structures to Bionic Lightweight Design Proposals

The abstraction of complex biological lightweight structure features into a producible technical component is a funda- mental step within the transfer of design principles from nature to technical lightweight solutions. A major obstacle for the transfer of natural lightweight structures to technical solutions is their peculiar geometry. Since natural lightweight structures possess irregularities and often have extremely complex forms due to elaborate growth processes, it is usually necessary to simplify their design principles. This step of simplification/abstraction has been used in different biomimetic methods, but so far, it has an arbitrary component, i.e. it crucially depends on the competence of the person who executes the abstraction. This paper describes a new method for abstraction and specialization of natural micro structures for technical lightweight compo- nents. The new method generates stable lightweight design principles by using topology optimization within a design space of preselected biological archetypes such as diatoms or radiolarian. The resulting solutions are adapted to the technical load cases and production processes, can be created in a large variety, and may be further optimized e.g. by using parametric optimization.     

Kinetic Characterization of 100 Glycoside Hydrolase Mutants Enables the Discovery of Structural Features Correlated with Kinetic Constants

The use of computational modeling algorithms to guide the design of novel enzyme catalysts is a rapidly growing field. Force-field based methods have now been used to engineer both enzyme specificity and activity. However, the proportion of designed mutants with the intended function is often less than ten percent. One potential reason for this is that current force-field based approaches are trained on indirect measures of function rather than direct correlation to experimentally-determined functional effects of mutations. We hypothesize that this is partially due to the lack of data sets for which a large panel of enzyme variants has been produced, purified, and kinetically characterized. Here we report the k_cat and K_M values of 100 purified mutants of a glycoside hydrolase enzyme. We demonstrate the utility of this data set by using machine learning to train a new algorithm that enables prediction of each kinetic parameter based on readily-modeled structural features. The generated dataset and analyses carried out in this study not only provide insight into how this enzyme functions, they also provide a clear path forward for the improvement of computational enzyme redesign algorithms.