Production, Purification, and Characterization of recombinant β-glucosidase F57Y
Elena Flores Cabrera and Fabiana Pena Medina
Saddleback College Department of Biological Sciences
Saddleback College, Mission Viejo, CA and UC Davis, Davis, CA
Abstract
The purpose of the experiment was to work with a larger network of labs alongside UC Davis, in an effort to harness the power of crowdsourcing in science research. The experiment aimed to identify a specific plasmid whose mutations have led to a change in enzyme activity. In order to do this, competent BLR21 E. coli cells were transformed with a plasmid which contained a mutated sequence of the Glucosidase gene. This was done by using the Design-to-Data workflow developed by the Siegel Lab at UC Davis. To begin, BRL21 E. coli cells were transformed with the plasmid F57Y. Subsequently, protein expression was induced using IPTG. Afterward, the BLR cells were grown overnight, to be used in the next step, Immobilized Metal Affinity Chromatography. This step uses the histidine-tagged protein which interacts with nickel beads in a chromatography column for protein purification. A kinetic assay was used to compare activity of the enzyme against the wild-type. A final step of SDS-PAGE allowed for analysis of protein purity.
BLR21
TRANSFORMATION
BACTERIAL
GROWTH
PROTEIN
PURIFICATION
Materials and Methods
Transformed Cells Growth and Expression Lysed Cell Pellet Affinity Chromatography Purified Protein
KINETIC ASSAY &
SDS-PAGE
Materials and Methods
Results
Figure 2. Analysis of the purity of the protein using SDS-PAGE.
Figure 1. Comparison of several mutants against the wild type control. Mutant 22 and mutant 23 correlated with the expected result; substrate concentration increases as the velocity of reaction also increases.
Conclusion/Future Experiments
References/Literature Cited
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Mariano, D., Pantuza, N., Santos, L. H., Rocha, R. E. O., de Lima, L. H. F., Bleicher, L., & de Melo-Minardi, R. C. (2020). Glutantβase: a database for improving the rational design of glucose-tolerant β-glucosidases. BMC molecular and cell biology, 21(1), 50. https://doi.org/10.1186/s12860-020-00293-y
Srivastava, N., Rathour, R., Jha, S., Pandey, K., Srivastava, M., Thakur, V. K., Sengar, R. S., Gupta, V. K., Mazumder, P. B., Khan, A. F., & Mishra, P. K. (2019). Microbial Beta Glucosidase Enzymes: Recent Advances in Biomass Conversation for Biofuels Application. Biomolecules, 9(6), 220. https://doi.org/10.3390/biom9060220
Huang, P., Chu, S. K. S., Frizzo, H. N., Connolly, M. P., Caster, R. W., & Siegel, J. B. (2020). Evaluating Protein Engineering Thermostability Prediction Tools Using an Independently Generated Dataset. ACS omega, 5(12), 6487–6493. https://doi.org/10.1021/acsomega.9b04105
Kathryn G. Guggenheim, Lauren M. Crawford, Francesca Paradisi, Selina C. Wang, and Justin B. Siegel ACS Omega 2018 3 (11), 15754-15762 DOI: 10.1021/acsomega.8b02169
Acknowledgments
We would like to thank the Saddleback College Department of Biological Sciences, our Bio 3C: Biochemistry and Molecular Biology cohort, Dr. Monica Friedrich, and the UC Davis Siegel Lab for the resources and support needed to accomplish this experiment. We would also like to thank NSF, ThermoFisher, Rosetta Commons, Justin Siegel, and Ashley Vater.