Research Updates in the Basic and Biomedical Sciences, Part II
When: June 11, 2021, 9:00 am - Friday
Where: Swang 100
Through basic and biomedical science research, we are able to identify the molecular basis of disease and basic molecular processes, which provide us with strategies for developing therapeutics, pesticides, and other life-improving chemicals. Our commission to “fill the earth and subdue it” (Genesis 1:28) brings a great responsibility to carefully steward the creation. This session will highlight research efforts among basic and biomedical science researchers at three Christian universities.
(Presenting authors denoted with an *)
Beth Conway*, Reed Haga, Purva Patel, Caleb Obregon, Jazmine Stubblefield, Lipscomb University, Nashville, TN, “Neprilysin: a potential regulator of PI3K signaling in Triple Negative Breast Cancers”
Neprilysin is a cell-surface protease with important activity in the brain and vascular system; more recently, it has been implicated in cancer including breast cancer. Our lab previously found that neprilysin is often silenced in aggressive breast cancers and inhibits breast cancer invasion. To better understand the mechanisms underlying neprilysin in breast cancer, we conducted bioinformatics analysis and found a strong link between neprilysin and the phosphatidylinositol 3-kinase (PI3K) pathway in triple negative breast cancers (TNBCs). Our preliminary data support our hypothesis that neprilysin positively regulates PI3K signaling, suggesting that neprilysin expression could predict sensitivity to PI3K-targeted therapies.
Caroline Schwab*1, Hannah Shaver1, Lindsey J. Long1, Laura Reed2, and the Genomics Education Partnership2, 1Oklahoma Christian University, Edmond, OK; 2University of Alabama, Tuscaloosa, AL, “Understanding Gene Evolution of the Insulin Pathway through Synteny”
This study focused on the evolution of the Insulin/TOR signaling pathway of fruit flies (Drosophila) by investigating genetic divergence of eIF4E1 and Akt1—genes within the insulin pathway—across several Drosophila species. Web-based tools and bioinformatic data were used to annotate these genes. The gene architecture and genomic neighborhoods (synteny) of eIF4E1 and Akt1 in these species were compared to orthologous genes in D. melanogaster, which was used as the reference species. Ultimately, gene annotation data from classmates in several other Drosophila species were meta-analyzed to draw preliminary conclusions regarding the rates of evolution of these genes in Drosophila.
Joseph E. Deweese*1, Thomas T. Townsley1, Timothy L. Wallace1, Salvador Cordova2, and Kirk Durston3, 1Lipscomb University, Nashville, TN; 2FMS Foundation, Canandiagua, NY; 3Digital Strategies, Langley, BC, Canada, “PSICalc: Development of a Software Tool for Exploring Protein Sequence Interdependencies”
Proteins share sequence similarities that have been studied in order to determine whether these similarities can provide information about protein structure. Previous work has demonstrated that multiple sequence alignments (MSAs) of proteins can be used to predict features of three-dimensional protein structure using the k-modes algorithm. We employed this approach to develop a software tool for analyzing MSAs in order to predict interdependencies between amino acids within a protein. We call the tool PSICalc for Protein Sequence Interdependency Calculator. We will present our latest results with the software tool.
Joseph E. Deweese, Lipscomb University, Convener
- Beth Conway*, Reed Haga, Purva Patel, Caleb Obregon, and Jazmine Stubblefield, Lipscomb University, “Neprilysin: a potential regulator of PI3K signaling in Triple Negative Breast Cancers”
- G. Caroline Schwab*, Hannah Shaver, Lindsey J. Long, Laura Reed, and the Genomics Education Partnership, Oklahoma Christian University; University of Alabama, “Understanding Gene Evolution of the Insulin Pathway through Synteny”
- Joseph E. Deweese*, Thomas T. Townsley, Timothy L. Wallace, Salvador Cordova, and Kirk Durston, Lipscomb University; FMS Foundation; Digital Strategies, “PSICalc: Development of a Software Tool for Exploring Protein Sequence Interdependencies”