Mauricio Antunes

http://bdi.unt.edu/mauricio-antunes

Highlights: 

• Dr. Antunes’ research interests include plant molecular biology, synthetic biology and biotechnology.

/antunes-lab-plant-synthetic-biology

Google Scholar

Dr. Mauricio Antunes teaches classes in the following subjects: general biology, biochemistry & molecular biology, and a molecular microbiology research laboratory.

Degrees:

Doctor of Philosophy in Plant Molecular Biology, Purdue University

Master of Science in Crop Production, Universidade Federal de Viçosa, Brazil

Bachelor of Science in Agronomy, Universidade Federal de Viçosa, Brazil

Experience:

Antunes' specific research projects are in the following topics:

• Synthetic transcriptional and post-transcriptional control systems modulated by inputs.
• Small RNAs as mobile signaling molecules in plants.
• Engineering complex synthetic genetic circuits to improve plant production and biosynthesis.
• Re-wiring metabolic pathways in plants using gene regulatory controls.

Selected Publications:

1. Amack, S.C.; Ferreira, S.S.; Antunes, M.S. (2023) Tuning the Transcriptional Activity of the CaMV 35S Promoter in Plants by Single-Nucleotide Changes in the TATA Box. ACS Synthetic Biology 12(1): 178-185. https://doi.org/10.1021/acssynbio.2c00457
2. Ferreira, S.S.; Antunes, M.S. (2021) Re-engineering plant phenylpropanoid metabolism with the aid of synthetic biosensors. Frontiers in Plant Science 12:701385. https://doi.org/10.3389/fpls.2021.701385
3. Amack, S.C.; Antunes, M.S. (2020) CaMV35S promoter - A plant biology and biotechnology workhorse in the era of synthetic biology. Current Plant Biology 24: 100179. https://doi.org/10.1016/j.cpb.2020.100179
4. Kassaw, T.K.; Donayre-Torres, A.J.; Antunes, M.S.; Morey, K.J.; Medford, J.I. (2018) Engineering Synthetic Regulatory Circuits in Plants. Plant Science 273: 13-22. https://doi.org/10.1016/j.plantsci.2018.04.005
5. Bick, M.J.; Greisen, P.J.; Morey, K.J.; Antunes, M.S.; La, D.; Sankaran, B.; Reymond, L.; Johnsson, K.; Medford, J.I.; Baker, D. (2017) Computational design of environmental sensors for the potent opioid fentanyl. eLife 6: e28909. https://doi.org/10.7554/eLife.28909