Melanoma is the most aggressive type of skin cancer. It can quickly metastasize and usually develops drug resistance to standard treatments. Our lab is working on investigating the transcription factors (TF) responsible for drug resistance in melanoma to help create more effective drug treatments. Single cell RNA-seq and ATAC-seq (assay for transposase accessible chromatin) was used, with single-cell level resolution, to ascertain transcriptome and epigenome information, respectively. This data was analyzed using bioinformatic toolkits to predict the transcription factors that control drug resistance. These predictions were validated using CRISPR knockout cell lines and melanoma cells with a specific transcription factor removed. Analysis of single cell RNA-seq data of melanoma cells after 24 days of drug treatment, when the cells typically become drug resistant, reveal the co-existence of four distinct subpopulations. These four subpopulations can be categorized into two groups, drug sensitive (melanocytic and neural crest) and drug resistant (mesenchymal and novel). We also gathered single cell RNA-seq and ATAC-seq on a timeline with days 0, 3, 6, 13, 17, and 24 to monitor the trajectories cells undertake to obtain the drug-resistant state. Analysis of the timeline single cell RNA-seq mapped out this trajectory from drug sensitivity to drug resistance and associated changes in cellular phenotypes. We expect analysis of the timeline single cell ATAC-seq data will show similar results and through an integration of the two layers of information, more solid predictions can be made for the TFs driving the transition towards drug resistance. We expect the cells with these TFs knocked out to be unable to form drug resistant subpopulations, as they can no longer activate drug resistance. Discovery of such TFs would suggest additional or more effective treatments that could halt drug resistance and mitigate the effects of melanoma.

Long-term exposure to traffic-related air pollutants (TRAPs) has been associated with multiple adverse health effects. However, many TRAPs, such as ultrafine particles, are poorly measured and thus their association with health outcomes is difficult to characterize. Our objective is to identify geographic characteristics that distinguish diurnal trends in TRAP concentrations at monitoring sites in order to estimate spatial contrasts in long-term average concentrations. Mobile monitoring (driving to many locations with multiple instruments) permits us to measure many TRAPs at many locations, but these measurements have short durations and may not capture the pollutant’s underlying trends. Therefore, these measurements may not reflect a site’s true long-term average due to our inability to fully sample the diurnal trend of the pollutant. In order to quantify the role of diurnal trends on annual averages, we use hourly measurements of CO, NO₂, and PM2.5 from California Environmental Protection Agency’s (CalEPA) monitoring sites where the true long-term averages are known. Using Principal Component Analysis (PCA) to reduce the number of dimensions, we will regress the pollutant levels against the time of day, the physical covariates and their interaction terms. The geographical variables include, but are not limited to, distance to a highway, distance to bodies of water, Normalized Difference Vegetation Index (NDVI), and population density. We utilize Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) as our model selection criteria and we assess model performance via leave-one-out cross-validation. We identify the most influential geographic factors that are associated with two to three categories of similar diurnal trends for each pollutant. With these variables, we will be able to group Seattle monitoring sites and distinguish their diurnal trends. Appropriate adjustment for diurnal trends in our mobile measurements will permit us to estimate spatial contrasts more accurately.

Early initiation of antiretroviral therapy (ART) among people living with HIV significantly improves health outcomes and survival rates. Based on these findings, the World Health Organization recommended provision of ART to all people living with HIV regardless of disease status. In 2019, the Government of Tanzania initiated task-sharing to nurse-initiated HIV care as a way to mitigate health systems challenges associated with increasing numbers of patients eligible for ART. As health providers take on new responsibilities, it is critical to assess the quality of HIV care. We are presenting observational data collected during a technical assistance program across 5 regions in Tanzania. Supportive supervision teams visited 20 health care facilities to observe provision of HIV care. During baseline observations, teams used a 41-point checklist to assess individual health care providers administering HIV care. Domains within the checklist included visit type, introduction, adherence counseling, consultation, and communication and support. Following the observations, the teams reviewed individual results with the providers and offered feedback. A repeat evaluation was performed after 3-months. Data has been summarized as counts, proportions, means, and standard deviations. Chi-squared tests of proportions have been used to compare pre/post data. Data analysis has yet to be completed. Findings from our analysis will measure differences in quality of HIV care over time in the context of HIV task-sharing and will provide specific information about domains of quality of HIV care. Results will be shared with the Government of Tanzania to inform future program directions. Quality assessment is important in providing HIV treatment in accordance with national guidelines. Our data analysis will inform future clinical training and health systems monitoring to ensure efficient and effective HIV care in Tanzania.

Malaria, a disease caused by Plasmodium parasites, is an enormous public health burden, especially in resource-poor areas of the world. After the female Anopheles mosquito deposits the Plasmodium sporozoite stage to the host through its saliva during blood feeding, the sporozoite quickly makes its way to the liver where it selectively invades a hepatocyte. The parasite replicates within the host cell, eventually re-entering the blood stream where it causes symptomatic infection. My project focuses on the liver stage of malaria, where complex hepatocyte signaling pathways contribute to parasite development and replication. Previously, our lab demonstrated that host signaling pathways that control lipid peroxidation are crucial to regulating liver stage infection during the first 24 hours. Inhibiting SLC7a11, a protein associated with the regulation of lipid peroxidation, led to increased peroxidated lipids within the infected cell and reduced Plasmodium liver stage parasite infection. Interestingly, lipid peroxides were localized to the infected hepatocyte, leading us to question the kinetic and spatial distribution of peroxidated lipids within the infected hepatocyte. I cultured Hepa 1-6 cells and infected them with Plasmodium yoelii sporozoites. After infection, I treated the cultures with drugs that promote or inhibit SLC7a11. Lipid peroxide levels and localization were observed by fluorescent microscopy at six hours post-infection and mean fluorescent intensity was quantified. At six hours post-infection, I observed no significant difference in lipid peroxidation when comparing infected and uninfected cells, suggesting that lipid peroxidation in infected cells occurs at some point between 6 and 24 hours. This project will allow us to gain a better understanding of how the lipid peroxidation pathway contributes to limiting Plasmodium infection within the liver and how it might be targeted by therapeutics to selectively kill parasites without harming the host.

Malaria devastates communities around the world, and researchers are striving to solve this enormous global health problem. Vaccine candidates could control malaria in these areas. Unfortunately, producing a single dose of these vaccines requires millions of malaria parasites from thousands of mosquitoes. Currently mosquitoes are dissected by hand, and the parasites are extracted from the dissected material with a tiny pestle. This work is time-consuming, expensive, and produces low parasite counts. With current techniques, vaccines will be difficult and expensive to produce, preventing them from protecting malaria-endemic populations. My project is to overcome the technical challenges described above by developing a system that will automatically dissect mosquitoes and extract malaria parasites. Our team has built a mosquito dissection robot and an automatic grinder. By hand, an experienced technician can dissect 150 mosquitoes per hour, but we are designing our robot to dissect over 1200 in the same time. By automating this process we improve yields and save time. In the future we will manufacture and distribute these tools to other labs. To confirm the quality of the parasites our robots extract, we are conducting extensive biological testing.

Small cell lung cancer (SCLC) is a rapidly metastasizing disease with a 5-year relative survival rate of just ~6%, claiming 30,000 American lives annually. Like most cancers, diagnosis at early-stage disease has far better outcomes than at late stage (22% vs 3% 5-year survival, respectively). Unfortunately, computed tomography screenings that can detect early-stage non-small cell lung cancer have not been effective for SCLC despite an overlapping at-risk population. There is a clear need for better SCLC screening/detection and treatment. Using high-density antibody arrays, we previously found that overall levels of plasma autoantibody-antigen (AAb-Ag) complexes are >2x higher in SCLC compared to other cancer types. Additionally, we discovered and validated 8 IgG and 11 IgM AAb-Ag complexes highly-specific for SCLC in 3 independent cohorts (N=240). Because 9 of the complexed antigens are transmembrane proteins, we hypothesized that they were potential candidates for tumor detection by radioactively-labeled antibody positron emission tomography (immuno-PET) imaging and/or treatment by chimeric antigen receptor (CAR) T-cell therapy. To explore this, we tested antibodies against our top targets on various models, including patient-derived xenografts (PDX, N=8), SCLC cell lines (N=2), and primary tumor tissue biopsies (N=10). By immunoblotting and immunohistochemistry (IHC), 6/9 targets were expressed on ≥7/8 PDX samples. We confirmed cell surface expression of these 6 targets by flow cytometry on SCLC cell lines. IHC on primary tumor tissue sections also showed expression of all 6 targets in ≥50% of tumors. Our findings suggest the AAb-Ag complexes we identified in plasma are novel extracellular and immunogenic SCLC antigens with potential to be engineered into immuno-PET or CAR T-cell modalities.

Oral swab analysis (OSA) is an alternative to sputum testing for tuberculosis (TB) diagnosis. Sputum is a viscous material coughed up from human airways and the most common human specimen used to test for TB. However, obtaining sputum can be difficult for some patients and occupationally hazardous for whoever is collecting the sample. Oral swabs can be collected rapidly and non-invasively, and do not require extensive processing for analysis. A larger quantity of Mycobacterium tuberculosis (Mtb) DNA can be detected using tongue swabs as compared to cheek swabs. Measurements of oral microbiota have been found to align with this trend when measured using quantitative PCR (qPCR) for bacterial DNA genes encoding conserved regions of the 16S rRNA subunit, which are common across a large variety of bacterial species and useful for comparison of relative abundance using universal bacterial qPCR. Bacterial DNA as quantified by universal qPCR was used to test whether the capacity and efficiency for biomass collection and release of alternative swab types are significantly better than previously used swabs. The qPCR protocol was identified and validated through literature review, comparing different primer sets, and testing different conditions. Tongue swab samples were collected from healthy Seattle-based volunteers, spiked with an avirulent lab-strain of Mtb (H37Ra), and processed with the QIAGEN QIAamp DNA mini kit. Alternative swab types were tested via the aforementioned qPCR protocol. The swab product that collects the most bacterial DNA are subsequently used in clinical evaluations of OSA conducted on TB patients. Data are currently being collected for analysis, and we anticipate that qPCR will determine the effectiveness of different sampling methods for the quantification of universal bacterial 16s rDNA. It is expected that this study will lead to improved OSA-based diagnostic tests for the detection of tuberculosis.