The Lake Washington, and Sammamish basin contains a complex mix of life history strategies of Oncorhynchus nerka. These life history strategies include 1) Anadromous sockeye that remain in the lake for one or two years before migrating to the ocean and returning to fresh water as mature adults; 2) “Residual” sockeye salmon that breed with and are genetically a part of the anadromous population but do not migrate to the ocean, and 3) “kokanee” salmon that are genetically distinct from anadromous and residual sockeye. Kokanee salmon are native to the basin and are thought to have evolved when glaciers or other barriers restricted access to the ocean. Although once extremely abundant throughout the basin, native kokanee are now thought to be found only in Lake Sammamish. Large numbers of kokanee-like fish continue to occasionally migrate from Lake Washington into the Sammamish river and its tributaries. Intriguingly, these “mystery nerka” migrate and spawn later than the sockeye/residual population and may represent a fourth distinct O. nerka population (e.g. a remnant of native Lake Washington kokanee, or a newly evolved kokanee population derived from sockeye ancestors). Sockeye, residuals, and kokanee use gill rakers, bony extensions in the throat, to capture prey. In other cases where kokanee have evolved from sockeye ancestors, the number and size of gill rakers differs – a reflection of the of the different types environments they mature in and the different types of prey available in freshwater vs. saltwater. In this research we document the variation in gill raker number and length in the Lake Washington/Sammamish populations of O. nerka in an attempt to 1) investigate trophic adaptations within the basin associated with life history strategy and location of maturation, and 2) to assess the relationship of “mystery nerka” to the other populations known to occur in the basin.

In the last decade, a large amount of studies have been done using virtual environment (VE) because of the increased control over the sensory stimuli used and the detailed observation of the associated behavioral and sometimes neuronal responses. In this study, we placed honeybee in a VE and exposed them to visual stimulus in closed-loop. We showed that honeybees are able to fixate the stimulus regardless of the level of feedback fed to the sensors(e.g., the gain between the animal motion and the stimulus motion on the VE). Our next step is to investigate how different neuromodulators such as the octopamine and dopamine, may be important for fixation and adaptation to the different level of sensor feedback. Octopamine (OA) is key in modulates physiological process in invertebrates including honeybees. Recent studies have identified OA neurons that are critical for visual behaviors and that increase their activity during active behavioral state. To identify the effects on octopamine and dopamine (DA) on honeybee’s ability to fixate, we are injecting bees with OA, DA or their respective antagonists in a visual processing brain area. Potential results of this study will impact the fields of neuroethology, providing insights on the modularity of neural processes and the feedback between sensory and motor pathways.

Barcoding of physical objects with molecular tags holds an advantage over traditional paper or electronic barcodes in that they are discreet, durable, and difficult to falsify. Here, we developed a DNA tagging system that labels objects to verify their authenticity and trace their origin. We chose DNA as our tagging medium due to its information storage capacity and chemical stability, allowing us to generate a wide variety of unique barcode sequences that can be read by Oxford Nanopore’s MinION sequencing device. The MinION contains an array of thousands of nanopore sensors that are capable of sequencing single strands of DNA. The nanopore sequencing process creates distinct disruptions in the ionic current through the sensors that are indicative of the DNA sequence. However, the DNA basecalling software that processes the raw ionic current is computationally expensive, making it impractical when our goal is to quickly “scan” and identify a tagged sample. Because of this, we designed our barcode sequences to generate unique current patterns that are identified using a simple classification algorithm as opposed to arduous basecalling. So far, we have synthesized and classified a set of 96 barcodes that can be indiscriminately combined to create multi-bit tags. In a given tag, each bit is defined by the presence or absence of a particular barcode, and in practice, we have assembled and read up to 16-bits. We have also explored increasing bit capacity by independently varying barcode lengths, which adds another dimension to the barcode space. We also tested the durability of our barcodes by drying them onto filter paper and sequencing them 24 hours later, proving that our barcodes could survive in a dehydrated state. Future experiments will aim to lengthen this duration and expose the barcodes to different environments, in order to better simulate intended tagging conditions.

The North American Nanohertz Observatory for Gravitational Waves (NANOGrav) uses an array of galactic millisecond pulsars to search for low frequency gravitational waves. The stability of millisecond pulsars allows their pulse time of arrival (TOA) to be used as precise clocks. Gravitational waves will produce timing delays that are are correlated across pulsars. In order to detect such correlations in TOAs, we must also understand the noise processes in the pulsar signal. Noise model selection aims to produce custom noise descriptions for each pulsar. Using NANOGrav's search code enterprise a Markov Chain Monte Carlo (MCMC) algorithm is used to search for the most favored model. A hyper model framework is used to explore across a set of models, which have different red noise and dispersion measure (interstellar medium effect) processes. The posterior odds ratio is then represented by the relative amount of time the chain spends in a model. An iterative approach is taken, where one model selection analysis is used to inform the next set of models from which to choose. The resulting noise descriptions will aid in mitigating its effects within the pulsar signals, increasing chances of gravitational wave detection.

Nanopore sequencing is a “third-generation” sequencing approach in which a constant electric voltage is applied across a nanoscale pore and the changes in the ionic current flow through the pore are measured as single molecules such as RNA or DNA pass through it. It is our goal to expand and adapt this sensing technology to enable single-molecule proteomics. Specifically, being able to characterize protein post-translational modifications at the single-molecule level is important for quantifying protein complexity and understanding how different protein mod-forms contribute to cellular processes such as differentiation and the progression of disease states like cancer. In this project, we modified a model protein to contain a protein kinase A phosphorylation motif with the purpose of demonstrating the ability to discriminate the modified protein from the unmodified with the Oxford Nanopore MinION, a high-throughput nanopore sequencing device. We hypothesize that the observed ionic current pattern will change upon phosphorylation and enable direct quantification of modified peptides. Ultimately, these analyses will inform us of the general ionic current signature that phosphorylated residues generate, which can then be added to our growing library of nanopore signal signatures that are informative of protein sequence and structure at the single-molecule level.

The interactions between pollinators and plants have a strong correlation to the fitness and reproductive success of both parties involved. These interactions are responsible for most of plant reproduction by seeds and they also drive evolutionary diversification of both plant and pollinator species. Wind turbulence plays an important role in navigation by smell, which is important for many pollinators while locating flowers. Climate change may alter wind patterns, which in turn may affect the ability of pollinators to locate flowers. The goal for this project was to determine the effect of wind on pollinator success. We determined the visitation rate of pollinators at Oenothera pallida flowers in the field by analyzing infrared camera videos recorded last summer at a field site in Grant County WA. Next we ran a multiple linear regression to determine the effects of wind speed, temperature, humidity, and ozone levels on floral visitation rates. Pollinators of Oenothera pallida include the hawkmoths Hyles lineata and Manduca sp., various bee species including Andrenids, Apids, Lassioglossum sp. and Megachilids, Bembix wasps, and various flies. Wind speed is the strongest variable that affects pollinator visitation at different times of day, which implies that changing wind patterns significantly impact plant-pollinator interactions.

Mosquitoes primarily navigate using their olfactory system, and can use this system to form “memories” that influence their choice in hosts. When a mosquito encounters an odor, information is sent through the antennal lobes in the brain to the mushroom bodies, which are structures responsible for learning and memory consolidation. This odor-learning pathway is mediated by neurotransmitters like dopamine and serotonin. Recent research has shown that the mosquito Culex quinquefasciatus has extremely low levels of dopamine in the antennal lobes compared to other species, and is unable to learn to avoid odors associated with a negative response. This led us to predict that dopamine is essential for aversive learning in mosquitoes. We hypothesized that Cx. quinquefasciatus differed from other mosquitoes in learning ability because they were previously tested in the light and they are the most nocturnal of the originally tested species. To test this hypothesis, we conditioned the mosquitoes in the absence of light in an aversive learning paradigm to measure how frequently they chose to avoid the conditioned odor. An inability to learn regardless of light condition would indicate that the role of dopamine as a neuromodulator in the antennal lobes evolved partly to allow diurnal mosquitoes to avoid defensive hosts. Next, specific neurotransmitters in the antennal lobe were mapped using confocal microscopy, revealing their concentrations which may explain behavioral differences from other mosquitoes. Most mosquito species show some plasticity in host selection, which can lead to the transmission of animal diseases, like West Nile Virus, to humans. Mosquitoes are the world’s deadliest disease vector, killing over 700,000 people globally each year, so understanding how and why this adaptation occurs can help us understand the framework that underlies the spread of mosquito borne diseases and bring us one step closer to solving this global issue.

Insect pollination is crucial to agriculture and conservation, but little is known about the ecology and evolution of floral scent, which is one of the strategies that plants use to attract pollinators. Flowers that rely on insect pollinators have floral scent compositions that attract certain types of pollinators more than others. Oenothera pallida is a plant which is pollinated by both daytime and nighttime pollinators, so examining its floral volatiles gives us an idea of what attracts the different pollinators to this flower. My research examines how floral scent emissions from Oenothera palllida differ between the day and nighttime, and how these differences in floral scent emission affect the attractiveness of the flowers to different pollinators. I extracted the floral scent from Oenothera pallida that is grown in the lab. I used Porapak traps to sample volatiles from each plant for six-hour periods in the evening and in the morning, which allowed me to see the change in composition depending on the time of day. I analyzed the floral scent samples using gas chromatography - mass spectrometry (GCMS). Then I created artificial scent blends in mineral oil that reflected the scent compositions of daytime and nighttime floral scent emissions. I exposed the hawkmoths and honeybees to the different scent compositions in a wind tunnel and observed the different responses of the two species. Finally, I determined what proportion of the moths or bees were able to locate the scent source by counting the number of individuals that flew upwind and landed on the artificial flower. 

Labeling objects with DNA-based tags can provide a secure, difficult to fake identifier that is particularly useful for objects of high value or those that cannot be physically tagged. In this problem setup, a tag is a bit string, where each bit represents the presence or absence of a DNA strand containing a particular barcode. Our goal is to consistently and accurately identify the tag. These DNA barcodes were designed for use on a MinION nanopore sequencer, which outputs a time series signal corresponding to the DNA sequence. Ideally, each barcode should generate a dissimilar signal, which makes it easier to distinguish from other barcodes. We designed 96 barcodes that are signal orthogonal (i.e the signal output from the MinION was as dissimilar as possible), and detected them using signal processing algorithms. Using this system, I created an error analysis pipeline to ensure that we can identify tags both quickly and accurately. In order to optimize the time it takes to identify a tag, it was important to minimize the number of sequencing reads we needed to observe on the MinION, without sacrificing accuracy. I found that using a subset of the reads produced approximately the same error rate as a full run. Therefore, we can run the MinION for a shorter amount of time, and still identify tags at a similar error rate compared to a longer runtime.

Skin plays an important function as a highly innervated sensory organ. This sensory function is critical to organism survival, but the skin, and its axons, are easily damaged and need to be repaired to maintain homeostasis. Zebrafish are an excellent model to study tissue repair because they regenerate tissue efficiently and share conserved skin architecture with other vertebrates. A cell type shown in previous lab experiments to contribute to skin repair is a macrophage like cell, the Langerhans Cell. I hypothesize that if Langerhans Cells are not present within zebrafish epidermis then tissue repair will be incomplete or delayed. I investigated these cells using two different methods. First, I analyzed mutations that cause a loss of function in genes required for Langerhans Cell development. Second, I used the transgenic ablation technique to inducibly kill Langerhans Cells in the skin by addition of the antibiotic metronidazole. I imaged fluorescent Langerhans Cells in the zebrafish epidermis in both of these genetic scenarios to quantify the reduction in Langerhans Cells. Following the completion of these experiments, we expect to see that a lack of Langerhans Cells will induce slower or halted recovery from damage. In the loss of function method, I expect that various mutants will not have as many Langerhans Cells and that following induced ablation, Langerhans Cells will die out when the drug is introduced and slowly recover following metronidazole removal. The key implication of this is finding more about our own biology that can lead to faster healing. In theory, if Langerhans Cells have a major effect on this process then knowing more about our own skin can help us translate this understanding to our own healing process.