Corepressors are proteins recruited by partner proteins to negatively influence the transcription of genes. TPL is a corepressor from the model plant Arabidopsis thaliana, and while we understand a lot about how TPL works, many mysteries still remain. My project aims to identify other proteins that work with TPL to form a transcriptional repression complex at a single-engineered promoter site. First, we created a synthetic repressor called dCas9-TPL that binds and represses the transcription of the RUBY reporter. The RUBY reporter is a visual marker designed to express throughout the entire plant, turning the green plant a bright purple. Our engineered RUBY line also carries two guide RNA binding sites in its promoter with sequences not found anywhere else in the Arabidopsis genome. This allows dCas9-TPL to bind to and repress this synthetic gene and not affect the transcription of other genes. Many of these plants have morphological phenotypes, and visual screening of the repressed RUBY line showed the plants turn a faint whitish-pink instead of bright purple, signifying that the repression by TPL is working. I have screened mutagenized populations of 40,000 individuals from the validated repressed RUBY plant strains using the Ethyl methanesulfonate (EMS) protocol, which creates new point mutations. I identified 257 individuals from 129 mutagenized families with bright purple organs, which signifies that the RUBY reporter is no longer repressing due to a putative TPL interactor being mutated. I will then proceed to form complementation groups and subsequent DNA sequencing to map the mutations. By identifying regulators of corepressor function in plant biology through downstream whole genome sequencing, I hope to learn principles that can inform cellular engineering across many organisms and better understand why certain mutations associated with transcriptional repression cause developmental defects or diseases like cancer in humans.

The Pacific Northwest (PNW) saw an unprecedented heatwave between June 25 to July 3 of 2021, with temperatures reaching up to 15℃ above the climatological mean. Previous research has examined the impact of this event on plants in Western Washington and Oregon through observational studies, and has focused on the economic implications for poor crop turnout. We used remote sensing data to take a top-down approach and examined how all plants throughout the PNW fared during and after this historical heatwave. Solar induced fluorescence (SIF) and Near-Infrared Reflectance of vegetation (NIRv) are two remotely sensed products that have been used to estimate plant health and gross primary productivity (GPP). SIF is more closely connected to plant processes like photosynthesis but has a short record (2018-2021) compared to VIIRS NIRv (2012-2021). We compared the responses of SIF to NIRv and found that both vegetation indices increased in trees and woody savannas, but decreased in grasslands and crops. However, SIF showed more intense and geographically larger increases in areas covered by trees. We then compared these vegetation indices to in-situ flux tower measurements of carbon fluxes, which did not always agree with SIF during the heatwave in woody areas. This study shows how remote sensing can further our understanding of how extreme events impact plant health, which is increasingly important as heatwaves become more intense and frequent in the future.

Bacterial CRISPR immune systems defend against foreign genetic material, such as bacteriophage viruses. CRISPR systems are classified into six types with diverse protein components and mechanisms of interference. Among these, our research investigates the function of CRISPR-Cas13 systems, which uniquely target RNA rather than DNA. To overcome immunity, bacteriophages have evolved anti-CRISPR mechanisms that are designed to inhibit specific CRISPR types, restoring infection and proliferation of the viral invader. We recently discovered a novel anti-CRISPR mechanism, in which a noncoding RNA provides inhibition of CRISPR-Cas13 function. The central questions surrounding this RNA anti-CRISPR (rnAcr) are how it associates with CRISPR-Cas13 in order to inhibit its function, as well as the boundaries of its length and anticipated mechanism of inhibition. rnAcr is predicted to have three vital stem loops, which have been experimentally deleted and structurally disrupted by performing site directed mutagenesis to mutate select regions of nucleotides in each stem’s structure. We did this in order to determine if the stem loops’ structures were necessary for rnAcr’s anti-CRISPR function. We found that these were all essential for its function, which gives rise to the hypothesis that its structure is interacting with the bacterial host’s CRISPR-Cas13 system to effectuate its inhibitory mechanism. In order to test anti-CRISPR function, we conjugated a target and nontarget plasmid, in which the target plasmid would be recognized by Cas13, and cellular RNA would be cleaved, leaving no growth if no anti-CRISPR mechanism is present. We have shown that rnAcr is sufficient for anti-CRISPR function, allowing for tolerance of these target plasmids and cellular growth. rnAcr suggests a novel anti-CRISPR mechanism, as until now, the majority of reported anti-CRISPRs have been composed of small proteins produced during phage infection, suggesting rnAcr’s significant implications when considering new players in the host-bacteriophage evolutionary competition.

A critical feature of autonomous cars is the ability to follow a road or predefined path. Classical methods often rely on extensive prior mapping with precise GPS positioning. These methods are labor intensive and struggle with changing, unstructured environments. Instead, machine learning (ML) models are trained to recognize paths and follow directions. In this work, we combine simulated and real-world data to train a neural network policy that controls an autonomous ground vehicle down a hallway, avoiding collisions. Training a ML road-following model consists of three steps: data collection and preprocessing, model training, and model evaluation. While all three steps pose challenges, collecting high-quality, real-world data can be expensive and dangerous in road environments. Because of this, simulator data is useful as it allows for data to be collected safely and inexpensively. Thus, we study how much the required amount of real-world data can be reduced to successfully train a road-following robot with the use of simulator data. So, we collected simulator data using AirSim to train a convolutional neural network that follows a path in simulation through live environment images. We then fine-tuned the model using real-world data collected from MuSHR cars through hallways of a building. Next, we test the fine-tuned model on the simulator to ensure limited degradation to the model solely trained from AirSim data. Finally, we deploy the model on a robotic car in a real-world environment and evaluate the model’s performance compared to the baseline model trained on real-world data. We demonstrate that we can successfully train a model in simulation (MSE <= 0.01radians), and we expect to show a comparable performance in reducing the number of collisions and minimizing trajectory differences between expert and learned controller from a model trained on simulator + less real-world data and a model trained solely on real-world data.

In response to changing conditions, organisms express genes to optimize the match between their phenotype and the environment. Understanding the mechanisms for how genes are turned on or off is therefore an important research area. One challenge in conducting this research is that many of the proteins involved in regulating gene expression are essential to life, and disrupting their function can lead to death. My research focuses on the essential gene SPT6, which encodes a protein that works with RNA polymerase during the elongation phase of transcription. Recently, the Nemhauser Lab has found that SPT6 also plays a role in transcriptional repression. My project aims to differentiate the role that SPT6 plays in transcriptional activation and repression by disrupting its expression in Arabidopsis. Given that SPT6 mutants do not survive, here I test the use of a new tool that allows me to remove my gene of interest in a particular tissue at a particular time. The tool is based on a molecular switch that relies on serine integrases which can recombine DNA between two specific sequences. So far, I have worked with my mentor to rescue SPT6 mutants with a target that expresses the wild-type version of SPT6. Once the integrase is expressed, the recombination turns off the SPT6 gene and turns on a fluorescent reporter. I express the integrase from a promoter that is active only in the first stages of making a new root, so I can observe the impact of loss of SPT6 function in a cell type unnecessary for plants to survive in lab conditions. This project promotes an understanding of the multiple roles of SPT6 during the transtition from repression to activation, and as SPT6 is highly conserved across eukaryotes, my work in plants may also contribute to understanding human diseases. 

Some genes are on all of the time in most cells, and carry out functions that are essential for life. Unsuprisingly, essential genes are difficult to study, as interfering with their function leads to death. One such critical component is the multi-protein Mediator complex, which is found at every eukaryotic promoter where it coordinates activation of gene expression. My project focuses on one of the core components of the Mediator complex, MEDIATOR21 (MED21). While MED21 is required for gene activation, the Nemhauser Lab recently found that it also plays a role in repression of gene expression through interaction with the corepressor protein TPL. I would like to be able to differentiate the role MED21 plays in activation versus repression using the plant model Arabadopsis. This work is made more complicated by the fact that most mutations in MED21 lead to lethal phenotypes. As an alternative I recently developed a new technology called a molecular switch that turns off MED21 in certain tissues or in reponse to addition of a chemical. The molecular switch relies on the expression of serine integrases that recognize, and recombine the DNA between, two specific DNA sequences. By expressing an integrase portein from a promoter that is only expressed in secondary roots, I can study MED21 loss of function in a small pool of stem cells while the rest of the plant is wild type and healthy. Plants that have undergone this cell-type-specfic switch exhibit several abnormal root phenotypes including agravitropism, increased root formation, and more root hairs. My next experiments include uisng a switch from wild-type MED21 to a mutant form incapable of binding to the corepressor TPL. This study will help us better understand the role MED21 plays in repression versus activation, and how state switching contributes to organogenesis.

Corepressors are proteins found in all eukaryotes that work with DNA-binding proteins to repress many genes. Keeping some genes off, yet ready to quickly turn of if needed, is essential for development and physiology. Our project aims to identify interacting proteins that work with TPL, a conserved plant corepressor, to form a transcriptional repressor complex. To uncover these proteins, we created a visually screenable plant line containing RUBY, a reporter that expresses throughout the plant, turning it dark pink to purple. We next created a synthetic repressor dCas9-TPL and guide RNA (gRNA) construct that binds to and represses the RUBY reporter. Roots of plants with both constructs appeared whitish-pink, indicating dCas9-TPL is transcriptionally repressing RUBY. We then mutagenized 40,000 individuals from this line using the chemical Ethyl methanesulfonante (EMS), which creates new point mutations in random locations throughout the genome. We identified 257 individuals from 129 mutagenized families with dark pink roots, which show that repression by dCas9-TPL has been impaired. Many of these adult plants had phenotypes in addition to appearing pink, including miniaturization, infertility, and irregular growth patterns, suggesting that the mutations we found are affecting other pathways that require TPL. Using Mendelian genetics, we are currently characterizing the mutation types (i.e. homozygosity, recessive, or dominant) as well as establishing complementation groups. We will then backcross the lines with the parent line to eliminate extraneous mutations and perform whole genome sequencing to determine the precise mutation causing loss of repression. This will also tell us if repression was due to mutating a TPL interactor, or mutating one of our reporter or repressor constructs. By finding genes required for TPL to act as a corepressor, we hope to understand conserved mechanisms of corepressor activity across diverse eukaryotes.

Sulfate aerosols cause pollution and affect climate by influencing cloud properties and incoming solar radiation. Emissions and abundances of sulfur-containing aerosols are one of the largest sources of uncertainties in global climate modeling. The largest biogenic and most uncertain emission source of sulfur aerosols is from phytoplankton in the form of dimethyl sulfide (DMS). In the atmosphere, DMS is oxidized to methanesulfonic acid (MSA), sulfur dioxide, and hydroperoxymethyl thioformate (HPMTF), all of which can form sulfate. Historical emissions of DMS are studied by measuring MSA concentrations in ice cores as a proxy for DMS oxidation. Declining levels of MSA have been found in ice core records, implying that production of DMS has also been decreasing; however, anthropogenically driven changes in atmospheric chemistry have altered the ratio of MSA to sulfate produced from DMS over time. To better understand DMS oxidation mechanisms and its relationship to the production of MSA and sulfate aerosols, we need more recent ice core records of MSA and sulfur isotopes of sulfate (δ³⁴S(SO₄^2–)) at higher temporal resolution. To measure δ³⁴S(SO₄^2–) at monthly resolution in an ice core, the measurement size is smaller than previously measured by an order of magnitude, at about 1 µg S per sample. We will develop a method to isolate 1 µg of sulfur from an ice core sample by concentrating the sulfur using an anion-retaining resin, precipitating with barium chloride, and drying in an oven. We will quantify the efficacy of our method using a stable isotope mass spectrometer compared to laboratory-prepared standards. We expect that we will reduce our sample size by an order of magnitude (to 0.1 μg sulfur) and improve the accuracy by 50%. Quantifying sulfur isotopes at this resolution will provide information about the seasonality and change in phytoplankton sulfate production.

Gas-phase emissions from sea-spray generate aerosols which are an important source of atmospheric halogens. Halogens (chlorine, bromine, and iodine-containing species) are important in the atmosphere because they affect the abundance of greenhouse gasses such as ozone and methane. The Bermuda boundary Layer Experiment on the Atmospheric Chemistry of Halogens (BLEACH) is a campaign that studies the abundance and cycling of atmospheric halogens. Filter samples from field campaigns are often frozen to preserve them for future analysis. However, after freezing a mixture of anion standards that replicate atmospheric composition for measurement on an Inductively Coupled Plasma Mass Spectrometer (ICP-MS), total aerosol iodine showed a tenfold increase in concentration in two separate trials compared to room temperature. Understanding the impact of freezing filter samples on aerosol iodine is crucial in interpreting BLEACH observations and could change the understanding of aerosol iodine speciation in the scientific community. I investigated this total iodine enrichment after a series of experiments on frozen and room temperature laboratory standards using Ion Chromatography (IC), which measures iodate and iodine separately. The tenfold iodine enrichment observed after freezing measured on ICP-MS was not replicated in IC trials. The total iodine ratio of frozen to room temperature was 1.1 on the IC and 9.8 on ICP-MS. Our results also show that the ratios iodide/iodate are the same for frozen (1.3) and room-temp (1.3) samples, suggesting that the conversion between iodide and iodate is not responsible for the enrichment in ICP-MS. Our observations of total aerosol iodine concentrations in Bermuda’s atmosphere are consistent with previous studies in the same region. This either suggests that the iodine enrichment after freezing is unique to the “simulated atmosphere” standard prepared in this study, or all field observations using ICP-MS may be overestimated by an order of magnitude.