Biochemical Exploration of DYNLL1 Protein
For my senior capstone project, I collaborated with two other students to perform a large biomolecular laboratory experiment. The goal was to apply as many laboratory techniques and methodologies as we had learned throughout our undergraduate studies. We utilized non-canonical amino acid insertion techniques, which allowed us to incorporate novel amino acids into a genetically engineered protein. The protein of interest was Dynein light chain 1 (DYNLL1/LC8), and it was chosen due to its significance in Dynein Complex regulation and cellular transportation.
With lots of lab hours and despite facing numerous technical challenges, we were able to successfully express the new recombinant proteins. The recombinant proteins were examined using a range of biochemical and biophysical assays. In fact, our work marked the first time phosphoserine had ever been expressed on that particular residue of LC8. Our results not only confirmed the expression of the novel amino acid but also challenged previous understandings of the protein’s regulation, as suggested by previous studies. These findings were to be followed up and investigated by one of the department’s graduate students and his PI.
This project served as a showcase of our extensive knowledge and comprehension of various laboratory techniques and methodologies. It also highlighted the potential for non-canonical amino acid insertion techniques to provide novel insights into crucial biological systems.
RNA-Seq Statistical Analysis
In addition to my interests in molecular biology and genomics, I also have a fascination for bioinformatics and statistics. So as an aspiring molecular biology student, I was excited to explore the fields of bioinformatics and statistics more deeply in my graduate-level Statistical Genomics class. My interest in understanding the aging process led me to choose a project that involved a comprehensive RNA-Seq analysis of LRRK2 mutants, a gene known to play a role in aging.
Using transcriptomic data archived in publicly accessible databases, I delved into the details of RNA-Seq. In my project I explain both the biological and statistical backgrounds of RNA-Seq, providing details to help understand what’s going on “under the hood”. I also presented evidence of a connection between LRRK2 mutants and aging biomarkers through the creation of tables, plots, and figures. The dataset originated from an experiment examining neurodegenerative diseases, like Parkinson’s, in mice. My analysis also supported the author’s original results, which was a rewarding experience.
Although my project became larger than anticipated, it allowed me to explore various statistical and bioinformatic tools and techniques, bringing together many aspects of my education into a cohesive understanding of how they all connect. Despite being too big for the professor’s preference (gotta rush to get in grades before the end of finals week), I was grateful for the opportunity to combine my interests and learn in a meaningful way. It allowed me to really synthesize my education and comprehend all the different relationships between its various fields (biochemistry, genetics, statistics, bioinformatics, etc.).