contributed by Sophia Pogranichniy
My name is Sophia Pogranichniy and I am a second year student studying Animal Biology in hopes of becoming a veterinarian one day. Currently, I am in the Early Admission Program for KSU’s veterinary school, contingent on keeping up with classes, extracurricular activities, and animal experience hours. I joined the Lee Lab in the spring semester of my first year at K-State and over the summer I got the amazing opportunity to lead my own independent research project thanks to the Mark Chapman Scholarship. I learned so much throughout this experience and I cannot wait to continue learning new things as I examine the results of this project during the school year.
The goal of this microbiology project was to examine how a swine farm impacts the microbial environment surrounding it. My team and I went out to a swine farm every other week to collect water, soil, and swine fecal samples. We ended up going to the farm five times before the end of the summer, and I was able to collect many samples for my data analysis.
After processing all the samples, the next step was extracting microbial DNA from them. The gut microbes help with digestion, fighting infection, and play a crucial role in the environment they are in. There are microbes in the swine gut as well as in the soil and the water, and my project is looking at how many of these microbes are the same and how many are different. The extraction process takes about 4 hours for each type of sample (fecal, soil, water) and I did molecular microbial DNA extractions every day of the week that I did not go to the farm. It was a very long, tedious process but it is gratifying to see all my hard work pay off when I quantify my extractions and find high values of microbial DNA!
After describing all that I did this summer, you may be wondering- what happens next? I was able to send off the DNA exudates for 16S (bacterial) sequencing. Although I do not have the results back yet, when I do they will tell me what microbes were found in the swines’ gut and what microbes were found in the environment, and how many are similar and how many are different. This project has a very open-ended research question so I am excited about what I will find. I hope to find an association between the swine host and the environment. The significance of these findings may impact how scientists, engineers, farmers, and policy makers develop approaches to sustain food production systems while preserving important biodiversity and ecosystem health. I also collected samples in a linear direction from the swine barn towards the retention pond, so another hypothesis is that perhaps as the samples get further away from the farm the microbial environment will deviate more from what is found in the host. These are some of the research questions I am considering right now but I am excited to start the next step in this project and learn even more as I go!
contributed by Kourtney Rumback
During the summer before my sophomore year, I was taking a microbiology course and learned how the gut microbiome can impact mental health. Using this knowledge, I proposed to add a microbiome analysis to the rats in my psychology lab, the RTD lab, that was examining how high-fat diets impacted impulsive choice. To propose a project like this required much work and convincing of the graduate students and my PI. I found a research article by Dr. Alexandria Vaughn examining a similar concept, but I was confused about the analytical aspects that goes into microbiome sequencing. From here, I reached out to one of my old professors that I knew quite well, Dr. Ari Jumpponen, who guided me through the process of 16S sequencing and gave me some direction on how to proceed with the project further. At this point I was becoming discouraged due to the cost it would take my psychology lab to be able to extract the DNA independently and to send off the DNA for sequencing. This is when I learned about Dr. Sonny Lee and I reached out to him for collaboration.
After talking to Sonny, I was able to get this project approved by my psychology lab and was able to apply for an Arts & Sciences Undergraduate Research Award, and later, an OURCI award. Due to Covid, I had to postpone this project until my junior year, but this allowed me to work closer with Sonny and was offered a position in his lab. Once the project was up and rolling, I extracted the DNA from 48 rat samples I collected pre-Covid. This was a great opportunity for me to practice my lab techniques and gain more skills with new equipment. The DNA was then prepared and sent to the K-State Genomics lab.
Before I continue more, I want to share about the core project that this analysis stemmed from. In the RTD lab, we wanted to examine how high-fat vs low-fat diets effected impulsive choice. We had 48 rats split into four groups of 12. Group one received a normal chow only, group two received normal chow with Crisco, group 3 received a low-lard commercially produced chow, and group four received a high-lard commercially produced chow. Groups three and four were enriched with vitamins and minerals. We were also curious as to whether fat type can impact impulsivity, hence the Crisco and lard diets. The overall results of this core study were that the rats consuming low fat diets (groups one and three) made more self-controlled choices overall and the high-fat diets (groups two and four) were more impulsive. We also did not see a difference between the two fat types.
The fun part now, after two years of preparation, is finally here: Data! The data analysis portion of this project was by far the most overwhelming and intimidating. It required programs that I was not used to and data sets that were not compatible with Excel. Sonny and Brandi were both great about helping me through this process and making sure I knew exactly what each graph entailed. I received two graphs that were used for this analysis. The PCA clustering plot which places points on a graph to represent each subject’s microbiome composition relative to one another. Within this plot, I was able to see that there was a separation between the two fat types (Crisco vs lard). There was also some evidence of the groups that received high-fat diets being closer together which suggests that their microbiome compositions were more similar. The second graph represented the relative abundance of individual phyla in each sample. Overall, we did not see a significant difference between any of the phyla between groups. This could be due to the high variability of abundance of phyla. Another point to mention is although the relative abundance of phyla was not significant, this does not mean that the phyla have the same identity in each group. Due to this, I would like to further cultivate the remaining samples to see if there is a similarity when examining the specific phyla of interest.
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