Indoor air pollution is a major issue in urban homes, where hazardous volatile organic carcinogens (VOCs), including formaldehyde, can accumulate in the air. This study aims to investigate the potential of genetically modified Epipremnum aureum (pothos ivy) in reducing indoor air pollution by degrading formaldehyde into the non-harmful chemical formate. The study will use a flow-through bioreactor and spectrophotometer to measure the rate of formaldehyde degradation. Preliminary work includes creating standard curves of different formaldehyde concentrations and analyzing them using a spectrophotometer. Then, during the experiment, a stream of air containing formaldehyde concentrations typically found in homes will be exposed to three experimental groups: no plant, wild-type plant, and genetically modified plant. The genetically modified plants are engineered to express the enzyme formaldehyde dehydrogenase (FALDH) cloned from the bacterium Brevibacillus brevis, which oxidizes formaldehyde to formate. Any remaining formaldehyde will be collected in an effluent trap and derivatized with DNPH for analysis. Its amount will be measured using a spectrophotometer to determine the percentage of removal. The genetically modified pothos ivy is expected to exhibit a higher rate of formaldehyde degradation than the wild-type plant, owing to its FALDH enzyme. The results of this research aim to provide support for the use of plant-based strategies in combating indoor air pollution and improving human health.

 Reconstructing past environments can help us understand plant community evolution over time. For example, plant silica (phytoliths) can help us reconstruct canopy openness. Phytoliths are formed when plants uptake monosilicic acid from the surrounding soil through their roots and deposit it as opalized silica in and around cells; they have been used as a tool in paleoecology because they are well-preserved in the fossil record. For phytoliths formed in the outermost layers of leaves (epidermis), there is a relationship between morphology and light availability. A previous method established this correlation using modern soils in Costa Rica to apply to sites in the Eocene-Miocene of Argentina. However, it is unclear whether this model can make accurate inferences in other geographic regions. Here, we expand the method using modern phytolith samples from the Southeastern United States to generate a dataset and apply it to fossil phytolith assemblages from the North American Great Plains Region to reconstruct changes in vegetation during Oligocene-Miocene grassland expansion. For this work, we use an optical microscope to observe and count the phytolith assemblages to reflect a range of vegetation types in North America. We focus on phytolith morphotypes representing silicified epidermal pavement cells and measure their size and shape using ImageJ. We expect a linear trend between LAI (Leaf Area Index, the quantified relationship between morphology and light availability) from phytoliths and observed LAI which can be used to form the model for North American environments and applied to the fossil phytolith record of the Great Plains Region. Expanding on this method could make its use more widespread and lead to similar research in other regions of the world. Current models suggest the persistence of closed forests through this entire interval, a result we wish to further test using this updated model.

Methanotrophs are prokaryotes that naturally consume the potent greenhouse gas methane for energy. Through metabolic engineering at an industrial scale, these microorganisms hold potential to mitigate the contribution of methane emissions to global warming. In particular, Methylotuvimicrobium buryatense can sustain robust growth both in nature and experimental settings; it is a promising engineering candidate. To develop a robust metabolic engineering platform using M. buryatense, biologists require a deeper understanding of the genetic mechanisms by which it functions. Here, I present an open-source software tool designed to interactively explore the transcriptome of M. buryatense. By integrating bulk RNA-seq datasets collected from experiments over the past decade and applying an array of unsupervised machine learning clustering algorithms, we cluster genes by their expression profiles in differing growth conditions. These gene clusters are annotated with gene ontology (GO) terms using statistical enrichment analysis to assist in functional interpretation of the clusters and the genes that comprise them. To enhance domain-expert researchers’ ability to explore and drill-down into specific queries, I unify these cluster-specific analyses in a web-hosted tool using interactive data visualization techniques centered on a ReactJS frontend and Azure Cloud backend. With both exploratory and query-focused use cases, this software tool can support M. buryatense biologist workflows for predicting functions of hypothetical proteins, showcase new or confirming putative regulatory processes, and generate new experimental hypotheses from the presented transcriptomic trends.

With rising greenhouse gas emissions, both emissions reductions and greenhouse gas capture and conversion are necessary to mitigate the impacts of climate change. Though carbon dioxide comprises the largest proportion of global greenhouse gas emissions, methane causes over 80 times more global warming per unit than carbon dioxide. While methane can be converted catalytically at high temperatures and pressures, bacteria called methanotrophs transform methane into biomass at ambient temperatures and pressures. Engineering these organisms to consume methane globally can help slow climate change. At the Lidstrom Lab, I study the relationship between the methanotroph genome and metabolic regulation. Through this work, I have focused on finding genes that facilitate responses to environmental conditions and am now looking at genes that impact overall growth rate. I design and construct mutant strains, eliminating genes that appear to use the cell’s energy unnecessarily based on transcriptomics data. We expect that eliminating such genes will allow the cells to devote more energy to methane consumption and growth, improving growth rates under low methane conditions. This work is being extended to experiments in a bioreactor to observe how selected mutations and growth conditions impact growth rate at low methane. For this work, I am setting up the bioreactor to maintain the intended reaction conditions and utilizing a gas chromatogram to monitor methane consumption over time. These experiments reveal how the methanotrophs grow under specific conditions. I am also analyzing the results of the experiments using Python, MATLAB, and Excel. Long-term, this research will help prepare methanotrophs for deployment in the field to consume methane in areas of atmospheric methane release including landfills and agricultural sites.

Phytoliths, silica bodies formed within and around plant cells, are a key part of a plant's physiological structure that can vary in shape between species. These phytolith shapes (so-called morphotypes) can be found abundantly within grasses and vary between taxa within a subfamily either in shape or in their relative abundances and could therefore provide important evolutionary data on how specific grass subfamilies may be related. Previous work has been done on certain grass subfamilies, including Bambusoideae, to identify similarities and differences in shape within a grass subfamily. This study aims to investigate the distribution of phytolith morphotypes among three closely related grass subfamilies (Arundinoideae, Danthonioideae, and Micrairoideae). To collect this data, we conducted a morphological study on over 300 phytoliths in samples from many species within our three subfamilies. The samples were taken from leaf clearings wherein the phytoliths were isolated through chemical treatment and centrifuging to remove other organic material before staining. Samples are imaged using a confocal microscope and then patched together with computer processing to form three-dimensional phytolith images. These sample objects were compared based on phytolith morphotype three-dimensional shape, their relative abundance, location in plant tissues, and size. In addition to the morphological study of individual phytoliths, we studied cleared leaves to obtain a greater sense of the composition of morphotypes within the tissue of the grasses. The results are expected to show an overlap in similar phytolith morphotypes across clades that have similar ecological niches such as photosynthetic systems. Overall, this research aims to find a link between these three close modern subfamilies that could be compared to fossil phytoliths in order to document their evolutionary history and past distribution.

In the 400 million years since they first emerged on land, plants have acquired numerous adaptations to the terrestrial environment. One of these adaptations is modification of the photosynthetic pathway, from C3 to C4. The C3 pathway, the ancestral form of photosynthesis found in most plants, has limited efficiency under high temperatures and light intensities, whereas the C4 pathway offers improved productivity. C4 photosynthesis has evolved numerous times in flowering plants in the last 66 million years, with C4 grasses being the most diverse and ecologically dominant. Despite their current importance, we still do not understand exactly when and where the evolution of C4 photosynthesis in grasses occurred because the fossil record of grasses is sparse. Phytoliths (hardened silica structures precipitated within plant cells) offer a novel tool for tracking C4 evolution. We will use phytoliths as a comparative tool to examine morphological changes associated with C4 evolution. All C4 grasses are contained within the PACMAD (Panicoideae, Arundinoideae, Chloridoideae, Micrairoideae, Aristidoideae, and Danthonioideae) clade of grasses. Panicoideae, one of the largest and most diverse subfamilies within PACMAD, containing both C3 and C4 species, is an ideal group to study the ecological and evolutionary factors that drive the distribution of C4 photosynthesis. Through analysis of phytolith morphology, as well as overall density and distribution of phytoliths within leaf tissue using leaf clearings, we will examine a broad sampling of Panicoideae, looking for common trends amongst C4 photosynthesizing groups as compared to their C3 counterparts. To extend the scope of these conclusions beyond Panicoideae, we will seek to confirm these trends by comparison to Aristidoideae, another clade that evolved C4 photosynthesis. Preliminary data indicate that the majority of phytolith morphotypes will be bilobates, crenates, and rondels. We expect these results to correspond between observed leaf clearings and the 3D models.

When managing our natural resources and assessing human impacts on ecosystems, it is important to understand how plant communities respond to disturbance events. The geologic record has the potential to provide an important source of information for scientists to observe how plant communities of the past have responded to disturbances. Currently, there is a limited ability to recognize disturbance as the primary driver of change because there is limited evidence of how functional traits - plant traits that relate directly with plant function and ecological strategy that are measurable in fossil leaves - vary across succession. To improve this ability, I am measuring the carbon stable isotopic composition (δ¹³C) of bulk organic matter in leaves sampled across a successional gradient. This functional trait is often preserved during leaf fossilization and is representative of a plant's water use efficiency (WUE), an important ecological strategy representing the carbon assimilated per water lost in a plant during photosynthesis. The extent to which carbon isotopes measured at the community scale reflect the successional stage of a plant community is not currently known. To improve this knowledge, I am testing the hypothesis that the WUE of plant species within a community will become more conservative in later successional stages. In support of this hypothesis, I predict that the abundance-weighted community average of leaf δ¹³C will increase through succession. In addition, I hypothesize that δ¹³C as a proxy for WUE will be most confounded in early succession, before a tree canopy forms, due to seedling utilizing water resources more rapidly without having established root systems and thus predict a higher variance of δ¹³C values in this earliest stage of succession. This research is helping develop a method of identifying disturbances within geologic records which can give guidance on management decisions regarding modern ecosystems

Uridine-5'-triphosphate (UTP) is a precursor for RNA synthesis. Ura3 catalyzes the conversion of orotidine-5'-phosphate (OMP) into uridine monophosphate (UMP) and is commonly used as a selection marker to characterize mutation rates of S. cerevisiae. URA3 can be positively selected for by growing cells in the absence of uracil and can be selected against by growing cells in the presence of the toxic fluorinated UTP precursor, 5-Fluoroorotic acid (5-FOA). While mutations in URA3 make up the majority of 5-FOA-resistant mutants, mutations in a small number of other loci can also cause this phenotype. We whole genome sequenced the 5-FOA-resistant mutants with a wild type URA3 and identified mutations to URA6 in each of these individuals. URA6 is an essential gene that encodes an enzyme that catalyzes the conversion of uridine monophosphate (UMP) into uridine-5'-diphosphate (UDP). Here, we describe 41 non-synonymous mutations to URA6 that permit growth in both the absence of uracil and in the presence of 5-FOA. It remains unclear how the URA6 mutants can maintain a functioning UTP synthesis pathway while remaining resistant to the toxic fluorinated precursors. We hypothesize that these mutations alter the protein structure in a manner that decreases the affinity for fluorinated substrates while maintaining the affinity for UDP. To test this, we will evaluate the structural changes to URA6 resulting from these non-synonymous mutations. Our goal is that our findings can benefit our understanding of the UTP biosynthesis pathway and encourage further investigation of the mechanisms involving fluorinated substrate analogues.

The geologic record provides opportunity to provide actual examples of how plant communities have responded to climatic changes, providing important perspective for modern anthropogenic-driven climate change. Two important climatic events in the Miocene offer such an opportunity, including a global warming event, the Miocene Climatic Optimum (MCO; 17-14 million years ago), and a global cooling event, the Middle Miocene Climatic Transition (MMCT; 14-12 million years ago). This study is assessing how the diversity and prevalence of ecological strategies within Pacific Northwest (PNW) plant communities changed in response to these events, by analyzing ~6 PNW fossil plant sites that span these events in time. At each site I characterize ecological strategies of taxa comprising these ancient communities by measuring leaf vein density (LVD) of fossil angiosperm leaves, which relates strongly to the maximum photosynthetic rates of the plant. Photosynthetic rates influence ecological strategy by placing plants along a spectrum with fast growth but low tolerance to resource scarcity at one end, and slow growth and high tolerance at the other. I am digitally measuring leaf vein density using microscope images of fossil leaves previously taken at several museums where these fossils are housed. I expect that during the MCO, evergreen plants with slower growth rates become more dominant and the diversity of ecological strategies increased (lower mean and higher variance of LVD). Across the MMCT, I expect that deciduous plants with high growth rates became more dominant and stronger abiotic filtering caused a decrease in the diversity of ecological strategies present (higher mean and lower variance of LVD). This study provides a real-life example of how climatic events reshaped the assembly of plant communities and provide an important perspective for present and future climate change.

The grass family, Poaceae, dominates over 40% of land ecosystems and is found in every biome except areas covered by ice sheets. Within Poaceae are two major clades, one being the PACMAD clade, named for the six subfamilies: Panicoideae, Arundinoideae, Chloridoideae, Micrairoideae, Aristidoideae, and Danthonoideae. The PACMAD clade is the only lineage of grasses that evolved C₄ photosynthesis. This derived trait allows plants to efficiently photosynthesize under low CO₂ concentrations and in hot, arid climates. Chloridoideae is the largest subfamily within the PACMAD clade with over 1,500 species across five tribes. Most Chloridoideae species use C₄ photosynthesis and it is likely that some of the first transitions from C₃ to C₄ occurred in this subfamily; however, fossil evidence for this deep history is currently lacking. Phytoliths, which are silica bodies that form in living grass tissues and can be preserved in soils for millions of years, have great potential for filling this gap. We are studying the three-dimensional shape of phytoliths from modern Chloridoideae grasses to better recognize them in the fossil record. By linking modern Chloridoid phytolith shapes to their respective climatic conditions, we will be able to create a robust reference database to be used for future research to identify past Chloridoids and their past growing environments. To do this, we are processing 3D Chloridoid phytolith models from 2D confocal microscope images to analyze and characterize the morphology, abundance, distribution, and diversity of Chloridoid phytoliths. Thus far, preliminary data suggests our findings will be especially useful in making comparisons between past and present bilobate or saddle-shaped phytoliths, though we expect to conduct further analysis on current phytolith shapes. Future studies will be able to compare our 3D modern renderings to fossil phytoliths to infer periods of climatic warming through deep time.

The Miocene Climatic Optimum (MCO) was a period of global warming 17-14 million years ago, where temperatures increased 2-4°C and CO₂ levels increased to ~400-600 ppm. Overlapping with the MCO were the Columbia River Basalt eruptions (CRB: 6.6-15.9 Ma), where extensive lava flows spread across the Pacific Northwest, resulting in primary succession. My study is focused on reconstructing the vegetation across the MCO and during CRB eruptions using epidermal phytoliths (i.e., Microscopic Biosilica) to understand how these conditions impacted plant communities. Epidermal phytoliths are formed within living plant matter reflecting the current environmental conditions in their size and undulation. The plant matter then falls to the forest floor and decays leaving behind the resilient Microscopic Biosilica, which is preserved within that sediment. Leaves formed in ecosystems with an abundance of sunlight reflect open-canopy vegetation, with small circular phytoliths; while large-undulated phytoliths come from closed-canopy, shady environments. Previous work has shown a correlation between the average size and undulation of epidermal phytoliths with leaf area index (LAI; i.e., a measure of canopy openness). I am using this process with sediment samples collected across four sites in Central Oregon to calculate ancient reconstructed LAI (rLAI), and thus reconstruct the canopy cover. Each site was chosen due to the time period it represents, with different exposure to increasing variations of CO₂ and CRB impacts. I hypothesize increased temperature and atmospheric CO₂ concentrations during the MCO created favorable conditions for plant communities, which promoted a productive closed-canopy forest structure. Additionally I hypothesize, the primary succession induced by CRB volcanism prevented the re-establishment of forests, leading to open-canopy vegetation structure. As modern day anthropogenic-driven climate change invokes alterations in our planet's ecosystems, we need to better predict and anticipate future responses of plant communities to these environmental perturbations. 

Morphology of leaves informs plant functions from structure to growth rate, all summing to diverse strategies that plant communities employ to thrive. By analyzing strategy changes over time, morphology can describe the strategic response to disturbance events - particularly those precipitated by human activity. My study aims to develop a framework for characterizing those strategies on a temporal scale during ecological succession based on leaf vein density (LVD), which is the length of vein tissue within a given leaf area. I am accomplishing this through the chemical isolation of vein tissues, analytic microscopy, and image analysis, examining temperate deciduous leaves from 5 sites in North Carolina with varying amounts of time since the plot was clear-cut for timber harvest. Once I prepared slides of 4 cm2 of leaf matter, I began imaging the leaves under 8x magnification and following this, I plan on using image analysis software to measure LVD over 2-3 mm2. Based on correlations between early successional species - species populating a cleared area before slow-growth taxa regenerate - and high vein density organisms demonstrating faster growth, I hypothesize that taxa prioritize growth via resource allocation during initial phases of recovery post-disruption due to the increased availability of sunlight due to altered canopy openness, increasing photosynthetic rate. This would be characterized by higher LVD observed in early successional species. Should this prediction bear out, it indicates that LVD can be used to better understand varying ecological strategies in a community over time. Specifically, we will be able to use it to analyze how that spectrum changes based on environmental changes and determine which strategies are prioritized in which stages of community change. By garnering a clearer grasp on the diversity in early versus late successional strategies, I plan on connecting the prevalence of certain functional traits and environmental changes across time.

The Middle Miocene (23-5 Ma) represents a period of rapidly changing climate and active volcanism, particularly in the Pacific Northwest. Our understanding of the structure and composition of plant communities during this timeframe is complicated by a limited or degraded leaf fossil record. Plant fossil assemblages are also often time averaged, representing accumulation of plant material over an extended period. A plant community that was preserved because of a single, short-lived event can provide insight into the composition and structure of that community in life. The Watersnake locality of the Sucker Creek Formation in southwestern Idaho contains two thick (8-14 m) ignimbrite tuffs (volcanic ash layers) that preserve charcoal fragments, reflecting plants that were burned when the tuffs were deposited. In order to identify the woody taxa that made up this community, thin section microscopy is used to examine the preserved cellular detail of the fossil charcoal fragments from the lower tuff. Since ignimbrites are deposited as a part of a single event, the impacts of time-averaging are minimized. Although these deposits reflect a short time, they are likely to integrate across space, providing a view of the broader landscape. The results of this study will reveal the structure of this plant community immediately prior to the eruption that caused the ash flow. I hypothesize that the taxa identified within the ash will be very similar to those of the leaf fossil record found in the shale beds below. A lowland community consisting primarily of wetland Glyptostrobus oregonensis, and Quercus simulata found near flowing water will likely be represented. Upland vegetation consisting of conifers (Pinus, Tsuga) were also likely incorporated into the ash flow as it moved downhill. This study will provide insight into the dynamics of plant community change during the Miocene in relation to volcanic disturbance.

Fire is a fundamental disturbance that drives changes in biome structure. Knowledge of ancient fire regimes may help predict future fire regimes resulting from anthropogenic climate change. Charcoal morphometry (quantified shape of charcoal), particularly charcoal aspect ratio (length:width), is an emerging proxy of ancient fuel type wherein higher mean aspect ratios are associated with grassy fuels. This study aims to experimentally validate this proxy method. Thirty-four modern plant species were sampled from UW Herbarium collections, separating leaf, stem, and reproductive body tissues for each species. Each sample was burned at 500°C for 20 minutes, crushed in a water slurry, and imaged under a binocular microscope. Charcoal particles were enumerated and morphometrics were measured using ImageJ with charcoal particles 125-250 μm and >250 μm analyzed separately to account for differences due to differential particle breakage. Strong evidence was found in the 125-250 μm size fraction through an analysis of variance test (F = 2.66, p = 0.03), that aspect ratio varies as a function of taxonomic group. The strongest evidence for a difference in aspect ratio is found, through Tukey's Honestly Significant Differences to be between graminoid and conifer charcoal (p = 0.03). Evidence is even stronger for a taxonomic effect on aspect ratio in the >250 μm size fraction (F = 3.64, p= 0.007). This variation seems to also be driven by a difference between graminoid and conifer charcoal (p = 0.002), corroborating earlier findings. Future validation of this methodology will be focused on the potential effects of burn temperature and charcoal transport in charcoal morphometric records. Rigorous verification of charcoal morphometry as a proxy of fuel type will help increase confidence in paleo reconstructions of fuel type. 

Despite decades of research very little is known about how mitochondria control stress responses. Therefore, new and innovative models are needed to understand the mechanisms of mitochondrial stress response. We developed a new mouse model of skeletal muscle mitochondrial stress to mimic the aging process in young animals to determine if mitochondrial oxidative stress replicates age-related skeletal muscle and mitochondrial dysfunction. We generated a mouse model to induce skeletal muscle mitochondrial redox stress to mimic skeletal muscle aging by knocking down superoxide dismutase 2 (SOD2). My project was to determine whether this model works in vivo. I fed animals a Doxycycline (DOX) chow diet (0.625g/kg) to induce SOD2 knockdown (KD). After 3-week DOX feeding, tissues were collected and processed for western blotting (WB). WB's were run for SOD2 in gastrocnemius, quadriceps, liver, kidney, heart and brain tissue. Normally, SOD2 is expressed in all tissues that contain mitochondria, so comparing SOD2 expression levels across tissues in KD animals validates tissue specificity. HNE adducts, a marker of oxidative stress, were measured by WB to confirm increases in oxidative stress associated with SOD2 KD. Three-week DOX feeding showed significant decreases in SOD2 protein in gastrocnemius (p<0.001) and quadriceps muscles (p<0.0001) compared to unfed littermate controls of the same genotype. There were no differences in SOD2 protein in heart, brain, liver or kidneys between DOX and control groups. HNE protein adducts were also significantly increased in skeletal muscle of DOX compared to controls (p<0.05). SOD2 is knocked down in skeletal muscle in response to DOX feeding. The increase in HNE adducts confirms that the knockdown of SOD2 causes an increase in oxidative stress. This model can now be used to explore the physiological mechanisms of inducing mitochondrial redox stress in young animals to recapitulate the effects of aging in a controlled manner.