I was given the opportunity to shadow my current mentor where he saw kids that struggled with rheumatic disorders. I was pulled into the world of immunology research, after learning that his work extended into basic science research. Seeing the patients as well the science behind their conditions made me reevaluate the significance of basic science research. As I continued to the learn about the field itself, I started to ask the questions no one had the answers to. My experience has taught me a lot about what it takes to be a good scientist. I learned that some questions might require a whole paper to answer, and some questions can be answered with a simple PCR reaction. My advice to any student starting out in basic science research is to not worry about the mountain of knowledge you do not have about the field that a lab specializes in. I found that asking the simple questions behind each step of an experiment was the first step. It is important to know what techniques you need to answer certain questions. Understanding the different techniques I could use helped me build a foundation before I started to think about big questions concerning the uncharted territory.
COVID-19 presented it’s own set of obstacle for anyone that was in the research field. When I wasn’t able to come into lab and conduct experiments, suddenly I thought the questions I could ask narrowed. I was fortunate enough to have been able to continue learning, but my project moved to behind a screen. I was given an RNA sequencing dataset. My goal was to see if there were any significant gene expression difference in the Innate cells from the mouse that was chronically exposed to IL-18. It was a hypothesis generating exercise. My whole project started with that huge question. We suspected that these innate cells may be contributing to the pathology of high IL-18 diseases. Every question I’ve had since analyzing that dataset taught be the importance of thinking critically about how you can answer your question. How can I validate the answers I have to my question? The importance of establishing control for any experiment has become engrained in my understanding of what good science looks like. Since November of 2020, my goal was to tell a story. I wanted to tell the story of Natural killer cells (Innate Lymphoid cells) that have been chronically exposed to high IL-18. They would possibly tell us about how innate cells were contributing to high IL-18 diseases like Macrophage Activation Syndrome. A large part of my question was whether or not these cells were functional. We needed to challenge NK cells with a model infection that would tell us it they could do their primary function, kill. We found a model that required IL-18 mediated perforin release (Perforin is a cytotoxic molecule that will cause lysis of cells infected with the intracellular pathogen). Pervious findings pointed to looking at clearance of Chromobacterium violaceum from livers which required perforin release from NK cells that were activated with IL-18. We could see if NK function (cytotoxicity) is maintained with the cells were constitutively activated by high levels of IL-18. If I homogenized livers from mice infected with C.v. and plated them on agar plates I was able to see colonies of C.v. per volume of homogenate. The negative control (C.v. killing) would be perforin deficient mice because although their NK cells may be activated by IL-18 they are unable to produce perforin, therefore, not kill. The positive control were wild type mice that would be able to kill the C.v. infected hepatocytes. The experimental group was IL-18 transgenic mice. Contrary to what we expected, we could not replicate the increased bacterial burden that was seen in perforin deficient mice. We saw that our negative control was clearing just as fine as the positive controls. This meant that clearance was not fully perforin mediated, invalidating what we saw in IL-18 transgenic livers. We found that in high IL-18 environments the models seemed to clear even better than the positive control, but we cannot confirm that this was because their NK cells were better killers. My next aim is to synthesize or adopt an in vivo model that would allow us to selectively test NK function. This was a major drawback in the questions I wanted to answer about NK cell function, but I am confident that there are other techniques I can employ.
The biggest lesson I have learned from my research experience so far is that the complexity of the science is irrelevant as long as you are doing good science. My experiments were simple (in the context of the other projects in the lab), but I have started to become more critical of having proper controls, and questioning whether I am answering the question I want to answer at each step. I know that my immediate goal is not to become an expert in any field, but I want to learn how I can gain the characteristics of a good scientist. I believe that building these traits will one day allow other scientists to trust what I have to say.