4 resultados para Aggregation pheromone
em CaltechTHESIS
Resumo:
A unique chloroplast Signal Recognition Particle (SRP) in green plants is primarily dedicated to the post-translational targeting of light harvesting chlorophyll-a/b binding (LHC) proteins. Our study of the thermodynamics and kinetics of the GTPases of the system demonstrates that GTPase complex assembly and activation are highly coupled in the chloroplast GTPases, suggesting they may forego the GTPase activation step as a key regulatory point. This reflects adaptations of the chloroplast SRP to the delivery of their unique substrate protein. Devotion to one highly hydrophobic family of proteins also may have allowed the chloroplast SRP system to evolve an efficient chaperone in the cpSRP43 subunit. To understand the mechanism of disaggregation, we showed that LHC proteins form micellar, disc-shaped aggregates that present a recognition motif (L18) on the aggregate surface. Further molecular genetic and structure-activity analyses reveal that the action of cpSRP43 can be dissected into two steps: (i) initial recognition of L18 on the aggregate surface; and (ii) aggregate remodeling, during which highly adaptable binding interactions of cpSRP43 with hydrophobic transmembrane domains of the substrate protein compete with the packing interactions within the aggregate. We also tested the adaptability of cpSRP43 for alternative substrates, specifically in attempts to improve membrane protein expression and inhibition of amyloid beta fibrillization. These preliminary results attest to cpSRP43’s potential as a molecular chaperone and provides the impetus for further engineering endeavors to address problems that stem from protein aggregation.
Resumo:
How animals use sensory information to weigh the risks vs. benefits of behavioral decisions remains poorly understood. Inter-male aggression is triggered when animals perceive both the presence of an appetitive resource, such as food or females, and of competing conspecific males. How such signals are detected and integrated to control the decision to fight is not clear. Here we use the vinegar fly, Drosophila melanogaster, to investigate the manner in which food and females promotes aggression.
In the first chapter, we explore how food controls aggression. As in many other species, food promotes aggression in flies, but it is not clear whether food increases aggression per se, or whether aggression is a secondary consequence of increased social interactions caused by aggregation of flies on food. Furthermore, nothing is known about how animals evaluate the quality and quantity of food in the context of competition. We show that food promotes aggression independently of any effect to increase the frequency of contact between males. Food increases aggression but not courtship between males, suggesting that the effect of food on aggression is specific. Next, we show that flies tune the level of aggression according to absolute amount of food rather than other parameters, such as area or concentration of food. Sucrose, a sugar molecule present in many fruits, is sufficient to promote aggression, and detection of sugar via gustatory receptor neurons is necessary for food-promoted aggression. Furthermore, we show that while food is necessary for aggression, too much food decreases aggression. Finally, we show that flies exhibit strategies consistent with a territorial strategy. These data suggest that flies use sweet-sensing gustatory information to guide their decision to fight over a limited quantity of a food resource.
Following up on the findings of the first chapter, we asked how the presence of a conspecific female resource promotes male-male aggression. In the absence of food, group-housed male flies, who normally do not fight even in the presence of food, fight in the presence of females. Unlike food, the presence of females strongly influences proximity between flies. Nevertheless, as group-housed flies do not fight even when they are in small chambers, it is unlikely that the presence of female indirectly increases aggression by first increasing proximity. Unlike food, the presence of females also leads to large increases in locomotion and in male-female courtship behaviors, suggesting that females may influence aggression as well as general arousal. Female cuticular hydrocarbons are required for this effect, as females that do not produce CH pheromones are unable to promote male-male aggression. In particular, 7,11-HD––a female-specific cuticular hydrocarbon pheromone critical for male-female courtship––is sufficient to mediate this effect when it is perfumed onto pheromone-deficient females or males. Recent studies showed that ppk23+ GRNs label two population of GRNs, one of which detects male cuticular hydrocarbons and another labeled by ppk23 and ppk25, which detects female cuticular hydrocarbons. I show that in particular, both of these GRNs control aggression, presumably via detection of female or male pheromones. To further investigate the ways in which these two classes of GRNs control aggression, I developed new genetic tools to independently test the male- and female-sensing GRNs. I show that ppk25-LexA and ppk25-GAL80 faithfully recapitulate the expression pattern of ppk25-GAL4 and label a subset of ppk23+ GRNs. These tools can be used in future studies to dissect the respective functions of male-sensing and female-sensing GRNs in male social behaviors.
Finally, in the last chapter, I discuss quantitative approaches to describe how varying quantities of food and females could control the level of aggression. Flies show an inverse-U shaped aggressive response to varying quantities of food and a flat aggressive response to varying quantities of females. I show how two simple game theoretic models, “prisoner’s dilemma” and “coordination game” could be used to describe the level of aggression we observe. These results suggest that flies may use strategic decision-making, using simple comparisons of costs and benefits.
In conclusion, male-male aggression in Drosophila is controlled by simple gustatory cues from food and females, which are detected by gustatory receptor neurons. Different quantities of resource cues lead to different levels of aggression, and flies show putative territorial behavior, suggesting that fly aggression is a highly strategic adaptive behavior. How these resource cues are integrated with male pheromone cues and give rise to this complex behavior is an interesting subject, which should keep researchers busy in the coming years.
Resumo:
In three essays we examine user-generated product ratings with aggregation. While recommendation systems have been studied extensively, this simple type of recommendation system has been neglected, despite its prevalence in the field. We develop a novel theoretical model of user-generated ratings. This model improves upon previous work in three ways: it considers rational agents and allows them to abstain from rating when rating is costly; it incorporates rating aggregation (such as averaging ratings); and it considers the effect on rating strategies of multiple simultaneous raters. In the first essay we provide a partial characterization of equilibrium behavior. In the second essay we test this theoretical model in laboratory, and in the third we apply established behavioral models to the data generated in the lab. This study provides clues to the prevalence of extreme-valued ratings in field implementations. We show theoretically that in equilibrium, ratings distributions do not represent the value distributions of sincere ratings. Indeed, we show that if rating strategies follow a set of regularity conditions, then in equilibrium the rate at which players participate is increasing in the extremity of agents' valuations of the product. This theoretical prediction is realized in the lab. We also find that human subjects show a disproportionate predilection for sincere rating, and that when they do send insincere ratings, they are almost always in the direction of exaggeration. Both sincere and exaggerated ratings occur with great frequency despite the fact that such rating strategies are not in subjects' best interest. We therefore apply the behavioral concepts of quantal response equilibrium (QRE) and cursed equilibrium (CE) to the experimental data. Together, these theories explain the data significantly better than does a theory of rational, Bayesian behavior -- accurately predicting key comparative statics. However, the theories fail to predict the high rates of sincerity, and it is clear that a better theory is needed.
Resumo:
This thesis presents theories, analyses, and algorithms for detecting and estimating parameters of geospatial events with today's large, noisy sensor networks. A geospatial event is initiated by a significant change in the state of points in a region in a 3-D space over an interval of time. After the event is initiated it may change the state of points over larger regions and longer periods of time. Networked sensing is a typical approach for geospatial event detection. In contrast to traditional sensor networks comprised of a small number of high quality (and expensive) sensors, trends in personal computing devices and consumer electronics have made it possible to build large, dense networks at a low cost. The changes in sensor capability, network composition, and system constraints call for new models and algorithms suited to the opportunities and challenges of the new generation of sensor networks. This thesis offers a single unifying model and a Bayesian framework for analyzing different types of geospatial events in such noisy sensor networks. It presents algorithms and theories for estimating the speed and accuracy of detecting geospatial events as a function of parameters from both the underlying geospatial system and the sensor network. Furthermore, the thesis addresses network scalability issues by presenting rigorous scalable algorithms for data aggregation for detection. These studies provide insights to the design of networked sensing systems for detecting geospatial events. In addition to providing an overarching framework, this thesis presents theories and experimental results for two very different geospatial problems: detecting earthquakes and hazardous radiation. The general framework is applied to these specific problems, and predictions based on the theories are validated against measurements of systems in the laboratory and in the field.