Pseudomonas aeruginosa is a ubiquitous environmental bacterium and an opportunistic pathogen of wounds, cornea, and the Cystic Fibrosis lung. P. aeruginosa is also a model organism for the study of bacterial biofilm formation. Biofilms are multicellular communities that form from bacterial growth concomitant with the production of extracellular polymeric substances (EPS). EPS includes polymers such as polysaccharides, DNA, and proteins; these polymers provide structure and protection to the biofilm cells. Proteomics experiments by the Parsek Lab and others have demonstrated that a notable component of the biofilm matrix are the secreted proteases. Secreted proteases have defined roles in virulence and nutrient acquisition, but their role in the biofilm matrix of P. aeruginosa has not been explored. I hypothesize that these secreted proteases recycle nutrients, remove cell waste, and protect cells from host immunity. To test my hypothesis, I generated a mutant strain of P. aeruginosa that lacks the six major secreted proteases. While we see that loss of the proteases does not impact planktonic growth, preliminary data suggests that loss of proteolytic activity results in moderately increased biofilm formation. Using a general proteolysis assay relying on casein hydrolysis, I have determined the relative contribution of each of the six proteases to the total proteolytic capacity of P. aeruginosa in planktonic growth. I will further test the impact of the proteases on biofilm growth in different growth environments, including under flow conditions and in artificial sputum medium. I will also assess which proteases contribute the most to proteolysis during biofilm growth. My work fits into a growing body of literature that suggests that the biofilm matrix is not an inert scaffold, but is instead a dynamic and active network.

Global Positioning Systems (GPS) technology plays a pivotal role in ensuring the safe and efficient navigation of drones by providing near real-time tracking of location and speed. The precision and reliability of GPS receivers are crucial for effective planning, sensing, and control applications in various domains. As Unmanned Aerial Vehicles (UAVs) continue to rise in demand and predominantly rely on GPS, minimizing the uncertainty in GPS performance becomes imperative. UAVs utilize the cost-effective nature of Micro-electromechanical Systems (MEMS) GPS receivers. This study identifies and analyzes GPS errors, specifically within consumer-grade MEMS receivers. The MEMS receivers are preferred for their low cost, low power, and low weight, making them ideal for integration into UAVs. Our methods include a series of controlled experiments in urban and semi-urban environments, encompassing varying weather conditions such as sunny and cloudy days. Static experiments evaluate GPS signal accuracy under stationary conditions, while dynamic experiments monitor GPS performance during drone flights. Our preliminary findings have shown a range of inaccuracies in GPS signal measurements. Horizontal signal accuracy varied from +/-1 to +/-14 meters, while vertical signal accuracy ranged from +/-3 to +/-12 meters. These results underscore the significance of further investigation to enhance GPS reliability, particularly in scenarios critical for UAV operations. In ongoing research, we are conducting more testing in other geographical locations and weather conditions to ensure the robustness of our conclusion. Additionally, we are developing environment-specific error detection algorithms utilizing the sensor fusion approach. Merging data from multiple sensors can reduce the uncertainty of an object's location, helping us when the GPS technology is not fully reliable. Our research contributes to advancing GPS technology capabilities, particularly for UAVs where accurate localization is important.

Bacteria face a variety of threats, including antagonistic killing by other bacteria in competition for space and resources. In response to this antagonism, many bacteria have evolved specific defense systems. One pertinent example is the Pseudomonas aeruginosa Response to Antagonism (PARA) in P. aeruginosa, which provides defense against various antagonists by activating a suite of genes, mediated by two-component pathway Gac/Rsm, in response to kin cell lysis. The Gac/Rsm machinery is conserved across the Pseudomonas genus, but its function in defense has not been studied outside of P. aeruginosa. Here, we investigate whether two divergent Pseudomonas species, P. putida (KT2440) and P. protegens (Pf-5), similarly use Gac/Rsm in defense. To do this, we performed competitive growth assays against an antagonistic competitor, Enterobacter cloacae, comparing Gac/Rsm deletion mutants against wild-type, and quantified relative survival as an indicator of competitive fitness. Preliminary data indicate that the deletion of the core Gac/Rsm gene gacS results in dramatically decreased competitive fitness for Pf-5, but not for KT2440. This indicates that Pf-5 uses the Gac/Rsm system in a similar manner to P. aeruginosa and that, while Gac/Rsm is conserved, it may differ in function between species. To identify additional specific genes involved in defense systems, we set up a genome-wide screen. The screen indicated that genes related to the flagellum and lipopolysaccharide biosynthesis may be involved in defense against antagonism, which was surprising because these well-characterized structures have never before been implicated in defense. Work is currently underway to validate these genes as true defense factors and determine the mechanism by which they confer survival. Our findings advance the understanding of defense systems among Pseudomonas species by shedding light on their conservation and complexity, thus providing a foundation for future work on defense systems across bacterial phyla.

The interplay between physical environments, particularly indoor spaces, and psychological well-being is an emergent research area with significant practical implications. Despite acknowledging the positive effects of clean and luminous spaces, robust methodologies to evaluate such environments objectively are scarce. This study addresses the challenge by proposing to estimate an environment's influence on well-being from a single photograph. Support Vector Machines, a type of machine learning algorithm particularly effective for pattern recognition tasks by finding the optimal hyperplane that best separates data points of different classes, are employed to analyze specific features like messiness and brightness, which have been empirically linked to comfort and mood. This analysis is part of a broader set of variables our comprehensive model assesses, aiming to provide a nuanced environmental quality assessment tool. The aim is to quantify this analysis into a suitability score that reflects an indoor space's potential to enhance well-being, based on the model’s confidence. Our model is trained on a diverse and ethically sourced dataset, including anonymized student contributions and internet images, preparing it to offer refined classifications. The ultimate objective is to inform non-clinical, preliminary evaluations of environmental quality and suggest enhancements for spaces used in daily life.

Plainfin midshipman (Porichthys notatus) are seasonally reproducing teleost fish found along the Pacific Coast of North America. During the non-reproductive months (December-February), midshipman live offshore in deep waters. Between March and July, they migrate to the intertidal zone to reproduce. During the reproductive period, dominant (type I) males build and defend nests and hum to attract female mates. Unlike most vertebrates, courtship (humming to attract mates) and parental care (egg cleaning, nest defense) are both conducted only by type I males. These males therefore face energetic and temporal trade-offs between courtship to parental care within a single reproductive season. Our research investigates the neural mechanisms underlying the transition from courtship to paternal care in type I males during the reproductive period. We propose that this behavioral shift is regulated by steroid hormones (i.e. testosterone and estrogen) and neuropeptides (i.e. galanin). We are measuring hormone levels in blood and brain of midshipman fish across various conditions of courtship and parental care. We show the relationship between changes in steroid and neuropeptide levels in both blood and brain and changes in courtship and parental care behavior in type I males. Understanding these mechanisms in midshipman fish is crucial, as the steroid and neuropeptide pathways that regulate social behaviors share similar pathways across vertebrates. Therefore, studying this in teleost fish can provide valuable insights into the broader regulatory mechanisms of reproductive life-stage transitions in vertebrates.