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Osteoarthritis (OA) is the most common joint disease in the body, characterized by limited mobility due to the degradation of cartilage. Age, weight, and genetic profiles have been identified as clear risk factors for OA; women are also more likely to suffer from OA compared to men. While previous research indicates that postmenopausal women have an increased likelihood of developing OA due to decreasing estrogen, few studies have investigated metabolic differences between diseased males and females. This study seeks to understand the differences between global metabolic profiles of males and females with OA. In order to investigate metabolic discrepancies, metabolites were extracted from joint-effusion-related OA synovial fluid. Global metabolomic profiling by liquid chromatography-mass spectrometry (LC-MS) was then employed to identify significant metabolic differences between sexes. The results of this study suggested a distinct metabolic response to OA in males and females, most notably a significant difference between fatty acid and amino acid metabolism. This study provides a greater understanding of metabolism in OA pathogenesis and suggests opportunities for more individualized, therapeutic interventions that target sex differences. In the future, researchers should replicate this experiment with a larger sample size and employ targeted metabolomics to further elucidate the role of fatty acid and amino acid metabolism in OA responses.

Abnormal mechanical joint loading leads to an imbalance in chondrocyte metabolism that results in cartilage degeneration – a hallmark of osteoarthritis (OA). Microgravity exposure in space significantly reduces mechanical loads applied to the joints, leading to increased catabolic activity of chondrocytes and thus increasing the risk of OA. This study assesses how chondrocyte metabolism is altered in response to simulated microgravity (SM) exposure to gain insight into the mechanisms responsible for cartilage degeneration in reduced-loading environments. Healthy post-mortem human cartilage explants were exposed to SM for one or four days using a Rotating Wall Vessel (RWV) bioreactor and compared with the control explants exposed to normal gravitational forces. A subset of the control and SM explants were analyzed for cell viability by staining and measuring relative fluorescence. Metabolites were extracted from explants and surrounding media, and data were generated by liquid chromatography-mass spectrometry. Pathways upregulated in response to SM include the metabolism of pyrimidine, amino acids, and sugars, which may be suggestive of extracellular matrix remodeling. Changes in metabolites secreted from explants into the surrounding media mapped to lysine and vitamin E metabolism. These pathway changes have been previously detected in human synovial fluid from osteoarthritic donors, suggesting that even short-term SM exposure may induce metabolic shifts similar to that of early OA. Notably, this study is the first to map global metabolic changes in cartilage in response to short-term SM exposure to gain insight into the risk of developing OA post-spaceflight.

Lead pollution has extremely negative effects on both the environment and the organisms living in it. The work done in this project serves to demonstrate the effects of the East Helena smelting operation on the microbiome of the soil in the area, as well as the effects of subsequent soil remediation efforts. The smelting operation and its pollutants have drastically impacted the area, as seen by the EPA’s designation of the area as a Superfund site. We hypothesized that the soil’s microbiome has been affected as well, both in species variation and population. Soil samples were procured from different locations around the East Helena smelter site varying in remediation levels. Microbial DNA was extracted from the samples, and a Nanopore sequencer was used to sequence the DNA and identify the microbial taxa present in each sample. From an analysis of the microbial community composition data, we were able to understand the patterns of different species and populations present in the soil. By gathering soil samples and microbiome data from locations at various positions and stages of remediation around the smelting site, the goal was to determine the impacts of both pollution and soil remediation on the microbiome of the area.

A commonly unknown contributor toward plant growth is the microbial community that exists within the soil. The microbial community is composed of bacteria, fungi, protozoa, and archaea. The interaction between members of the microbial community and the associated plant is not clearly understood. In this study, seven key bacteria associated with the maize plant root were used to begin understanding and predicting potential interactions using KBase, a biological computation modeling program. Individual models of the metabolism of each bacterial species were created using their sequenced genome along with a designed nutrient medium, followed by the creation of two and three member community models. Each model was analyzed using flux balance analysis (FBA), a linear programming algorithm that optimizes the bacterial metabolic process for a specific objective such as biomass optimization. FBA simulations developed a complex nutrient exchange (amino acids, carbon sources, and vitamins) prediction that was used to create maps to simplify the interpretation of bacterial interactions. Collaborators at North Carolina State University use the models to improve the design of experimental trials and increase the rate of discovery. Improved understanding of the interaction between the microbial community and the plant can benefit agricultural production efficiency.

In light of the COVID-19 pandemic, individuals have become exceedingly health-conscious. When in public, water fountains such as the Elkay ezH2O have allowed accessibility to filtered water that supposedly minimizes harmful pathogens as well as chemicals. The objective of this experiment was to determine whether the color of the filter status on Elkay ezH2O water fountains makes a difference in microbial diversity in drinking water on campus. After collecting water samples from one green filter status (healthy) and four red filter status (needs replacement) fountains across Carroll College campus, the microbial DNA of each sample was extracted and amplified. Additionally, wastewater was used as a control to compare to the water fountain samples. The microbiome of each fountain and the control was analyzed using Nanopore sequencing, which provided an in depth analysis of the community composition present in the water samples. Based on the results of the microbiome, a comparison between the red and green status water fountains was performed to determine the necessity and effectiveness of new filters on the water fountains around Carroll College.