Julliana Renales
Author: Julliana Renales | Major: Biomedical Engineering | Semester: Fall 2022
In the 2022 fall grant term, I worked with my honors mentor, Dr. Christopher Nelson, to use bioinformatic methods to understand genetic expression within diabetic wounds. As someone with a large family history of diabetes, I felt a high importance in understanding the many unknowns about diabetes. One major symptom of Type 2 Diabetes (T2D) is the reduced ability for the skin to heal wounds, causing chronic wounds and infection. These wounds occur specifically on the feet, which is a condition known as diabetic foot ulcers (DFU). Though they are treated through normal wound care, wounds often become infected. This can lead to amputation of the foot or even death in severe cases.
My mentor introduced me to the spatial transcriptomic method when I expressed interest in wanting to pursue a more computational project. I thought this method was exciting as it is new and applicable to many different research areas. This project allowed me to not only challenge myself by developing my computational skills, but also apply it to a topic I felt was increasingly important due to the increasing prevalence of diabetes.
My goal this semester was to first understand the spatial transcriptomic methods and what tools I needed to carry it out. At the beginning of the semester, my mentor and I established that our biggest challenge was possible lack of resources that we had. Since no one we knew had necessarily done this before, much of the work would have to be done by figuring it out by ourselves. I spent much of my time finding the correct tools and software that the analysis could be done on. Once I felt I couldn’t get any further, I began to reach out to other labs and look to other resources for help, using the suggestions of my mentor. I also attended bioinformatic seminars online to better understand how to apply different software to my project. Although many had a small amount of knowledge on the subject, everyone had the willingness to help as well as learn with me.
The spatial transcriptomics method allows us to analyze gene expression in the context of its position. This allows us to not only examine the function of cell groups but also their position within the tissue of interest. Some things I have learned over the semester are the different platforms and methods used to analyze single cell RNA and spatial RNA sequencing data. Throughout finding these resources, it taught me a lot about bioinformatics through examining code and functions of data analysis platforms. My future plans are to apply these methods to spatial RNA data sets to map out gene expression in diabetic wounds. By using the resources, I have found over the last grant term, I hope to finalize an efficient method for analyzing spatial data for our lab, so it can be done efficiently in the future. In doing so, I hope to examine the function of cell groups in diabetic wounds and determine why these wounds are not healing. This can also be used for vast number of applications further than diabetic wounds, including cancer research and muscle regeneration.