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Metabolomics of Bacillus Thuringiensis Toxin Resistant (BRE) Mutants in Caenorhabditis Elegans

Undergraduate #165
Discipline: Chemistry and Chemical Sciences
Subcategory: Biochemistry (not Cell and Molecular Biology and Genetics)

Gideon Anning Adu - Claflin University
Co-Author(s): Olatomiwa O. Bifarin and Dr. Arthur S. Edison, University of Georgia, Athens, GA



Glycosyltransferases (GTs) are enzymes that catalyze the formation of glycosidic bonds and as a result coordinate majority of biological processes. They mediate glycosylation between carbohydrates, proteins, lipids and even nucleic acids. In Caenorhabditis elegans, GTs have been identified to be involved in several developmental and physiological processes. The purpose of this project was to explore the systems role of Bacillus thuringiensis toxin resistant (bre) proteins – GTs involved in glycolipid biosynthesis – in C. elegans. This was done by studying the differences in their metabolome when compared to the wildtype, N2. Bre strain is unsusceptible to the bacterial toxin because they cannot glycosylate the required oligosaccharide receptors needed to interact with the toxin. The mutants (bre 3 and bre 4) used in this study were obtained from the Caenorhabditis Genetics Center (CGC). Having synchronized the worms to L1 developmental stage, 10 replicates of each strain were grown into a mixed population. The worms’ endometabolites were then extracted and a 1D proton noesypr spectrum was acquired on a Bruker 600 MHz NMR machine. This was subsequently followed by data analysis using MATLAB. Partial Least Square Discriminant Analysis (PLS-DA) models were generated to determine how separate (different) the data points are based on their respective NMR signals. The PLS-DA score plots displayed promising separations among the strains which indicates the metabolic difference among them. Statistical Total Correlation Spectroscopy (STOCSY) was used for the identification of NMR features that correlate positively between samples. Based on the selected signals (3.259 and 5.189 ppm), Colmar database was used to obtain Betaine and Trehalose as two of the probable metabolites that brought about the observed differences between the subjects under study. More metabolites will be identified and analyzed in metabolic pathways database in order to predict the biochemical pathways that seems to have been perturbed in the mutants.

Abstract.docx

Funder Acknowledgement(s): Georgia Research Alliance

Faculty Advisor: Dr. Arthur S. Edison, aedison@uga.edu

Role: I worked on this project from start to finish under the supervision of my principal investigator.

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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