Note: This section may not be updated as I focus on building a better website. For the most accurate information, please see my CV.
Merkel cell polyomavirus (MCPyV) is a ubiquitous skin virus that is linked to the transformation of skin fibroblasts to polyomavirus-induced Merkel cell carcinoma (MCCP), which shows a Merkel-like neuroendocrine phenotype. While previous studies have indicated the expression of its small and large tumor antigens (sT and LT) and atonal growth hormone (ATOH1) as necessary for the transformation process, the molecular mechanism and environmental requirements remain unclear. Research in other neuroendocrine-differentiated cancers has implicated p53 and pRb in suppressing cell lineage plasticity, both of which are typically suppressed in MCCP tumors and will need to be evaluated. To this end, we produced a custom lentivirus with sT, LT, and ATOH1 genes that validates successful infection and transformation of fibroblast and cuSCC models, eliminating confounding genes present in MCPyV. By using both p53 -/- and skin fibroblasts alongside Rb1 inhibition via siRNA, we may elucidate which additional factors are important to MCCP neuroendocrine differentiation. This work adds a perspective on viral oncogenesis of MCPyV and novel methods of studying cancer.
To learn more about what my lab is doing, please visit our website!
This project was fully student-led and part of Engineering Biology Core's projects program.
Research has shown that epigenetic regulation and spatial distribution of neurotransmitter receptors is linked to the expression of a variety of social behaviors and neurodevelopmental disorders. Studies on relevant receptor neurobiology have focused on signaling patterns as a therapeutic basis and have been successful in modulating behavior in several model organisms. Structure-based approaches may offer insight to molecular mechanisms contributing to observed irregularities in social behavior across species and contribute further investigation of neural circuitry. We examined receptors for dopamine (DRD1 and DRD2), oxytocin (OXTR1), and vasopressin (AVPR1) from a wide array of phylogenies totaling 465 proteins and conducted molecular docking with their respective ligand to compare binding affinity and other interactions. We highlight how this study contributes to our understanding of the role of receptor structure in broader neurobiological mechanisms and possible novel therapies.
Github repository with my contributions: github:ebc-neuro
Conferences we've presented at: 2023 Castle Conference, 2023 USF Undergraduate Research Conference
Publications with Uversky Lab: bioRxiv Preprint
This project was fully student-led and part of Engineering Biology Core's projects program.
Previous EBC research identified Merkel Cell Polyomavirus (MCPyV) proteins that play an important role in the oncogenesis of Merkel Cell Carcinoma (MCC). This project will identify specific bindings between target proteins via a variety of bioinformatic tools to characterize these intereactions. The interactive model displays one of these proteins, VP1, used for attachment to host cell receptors. Possible methods will include genome mining, protein modeling, moelcular dynamics, molecular docking, disorder analysis, and more. Characterization of these relatively unnown interactions will contribute to knowledge and serve as a therapeutic basis.
To learn more about what EBC is doing, follow @ebc.usf on Instagram!
It is important to note that these projects were completed before my professional academic career. While still done with the best of my ability at the time, with the exception of Project STEM, none of these should be considered serious academic research.
This opportunity was part of IUPUI's Project STEM program's collaboration with Eli Lilly, where after a competitive application/interview process some high school students were able to do virtual (due to COVID-19) research with Eli Lilly staff. My work consisted of sequencing multiple gene databases to do error analysis. While the specific nature of the work is confidential due to Eli Lilly guidelines, it involved using R to run supercomputer jobs and BLAST sequences. I would like to thank Dr. Simone Gupta for being an amazing mentor during my time with her, along with Mr. Sanders for running Project STEM and getting us in touch.
This opportunity was done through IUPUI's Project STEM. My mentor, Dr. Eneida Mendonca, interviewed several candidates and selected me to work with her team on collecting and analyzing data from the then-new COVID-19 pandemic. My project involved using command line and Python to calculate COVID-19 comorbidity and ICU correlations from the INPC Hospital database of over 49,000 patients. This helped predict which patients would be likely to require hospitalization or admittance to the ICU along with the mortality rate. I would like to thank Dr. Mendonca for this opportunity, along with the rest of the Regenstrief team (Ms. Katie Allen, Dr. Siu Hui, and Mr. Jack Van Schaik) and Mr. Sanders.
You can access my presentation materials here and view the presentation here.
Read more about the CTSI program at the news release here!
I did this study as part of the AP Research program, where I analyzed what characteristics of teachers' technology use are the strongest determiners of the level at which they implement technology in the classroom. While accessibility and the teacher's own use seemed to be determinative, the subject area was not. While the research is not very applicable to other schools due to its narrow score, it provides insight into the interactions between teachers, students, and technology. This project was meant to be an introduction to academic research, where the project required IRB approval, had proper statistic analyses, and resulted in a full academic paper. I would like to thank Ms. Allison Malloy and Mr. Matthew Wernke for their mentorship.
Working in certain industries has been correlated with higher rates of Parkinson's disease onset, and one important mechanism found is the oxidative effects of highly penetrative xylene and toluene in neurons. The goal of the project was to design a filter that would be effective in removing these molecules from the air. I was the project leader for this group, and we presented at Cummins Engineering, Eli Lilly, and IUPUI. While industry experts reviewed the idea as theoretically sound, our next steps include creating a prototype and further design. I would like to thank the people at Cummins and Eli Lilly for their time, and the staff at Health and Science Innovations for this opportunity and mentorship.
You can access our research poster here and our presentation materials here.
