Faculty Mentor
Dr. Elaine Vanterpool
Files
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Description
Cystic fibrosis (CF) is an autosomal recessive disease commonly recognized by thick mucus and loud coughs. The manifestation of these symptoms is due to the inability of chloride ions to diffuse out of the cell. Thus, preventing osmosis resulting in a thick mucus on the lung’s surface. Those who suffer from this disease have difficulty breathing and require a modulator with a vest to increase gas exchange in the lungs. Moreover, the disease can result in much pain due to coughs, which destroys ciliated epithelial cells. Patients who have cystic fibrosis can suffer from pneumonia and other bronchial infections. They also experience difficulties with secretions out of exocrine glands. The low-frequency gene, Mannose Binding Lectin-2 (MBL2) associated with cystic fibrosis was analyzed for this study. This gene encodes for a protein that plays an integral role in the innate immune system. It binds to the mannose and N-acetylglucosamine found on the surface of pathogens. It then removes the pathogen by signaling the lectin complement system and phagocytic cells. The purpose of this study was to observe the missense mutations within this gene. Computational tools were used to view the mutated variants, the 3-D modelling, and conserved domains. The simple ClinVar database identified variants within this gene. Polyhen2 was used to analyze the pathogenicity of Gly54Asp and Pro101Leu. The computational tool predicted Gly54Asp as "probably damaging” with a 1.00 sensitivity score. The Pro101Leu swap was deemed to be “benign” with a sensitivity score of 0.043. Upon further analysis, the SIFT tool predicted the substitution to affect the protein. The second variant, Pro101Leu was predicted to be "tolerated". The SWISS modelling further identified the physical changes in the protein structure. Analysis of mutations within this gene can prevent other infections; ultimately, preventing the exhibition of cystic fibrosis.
Publication Date
2025
City
Huntsville
Disciplines
Biology
Recommended Citation
Vanterpool, Elaine and Cameron, Kiar-Ra, "Bioinformatics Analysis of the MBL2 Missense Variants Associated with Cystic fibrosis" (2025). Student Posters. 59.
https://ouscholars.oakwood.edu/student-posters/59