Megan L. Matthews
For More Information
- B.S. Electrical Engineering, North Carolina State University, 2011
- M.S. Electrical Engineering, North Carolina State University, 2012
- Ph.D. Electrical Engineering, North Carolina State University, 2019
Megan L. Matthews holds a B.S., M.S., and Ph.D. in electrical engineering from North Carolina State University, where she developed a multiscale model of lignin biosynthesis in poplar trees. Megan came to the University of Illinois as a postdoctoral researcher to develop multiscale crop models for the RIPE and Crops in silico projects. Megan joined the CEE Department as an Assistant Professor in January 2021. Here, her research will focus on developing multiscale plant models that integrate information across multiple levels of biological organization, and using those models to (1) explore the impacts of a changing environment on plants and (2) identify engineering strategies for improving plant development and growth.
- Assistant Professor, Dept of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 1/2021 - Present
- Postdoctoral Research Associate, Institute for Sustainability, Energy, and Environment, UIUC, 7/2019-12/2020
Food security, energy security, and environmental sustainability in a world with a growing population and a changing climate are current challenges facing the global community. Genetic and metabolic engineering of crops to improve photosynthetic efficiency, carbon and nutrient allocation, and nutrient and water use efficiencies in food and bioenergy crops are potential avenues to address these challenges.
Using methods frequently implemented by engineers to study and develop models that describe efficient and robust man-made and environmental systems (e.g., ordinary differential equation modeling, constraint-based and multi-objective optimization, machine learning, and system identification and analysis), we can also develop mathematical models that describe biological systems like crops. With these models, we can explore a wider array of potential strategies for engineering crops than would be feasible to experimentally test due to cost and time constraints.
Since plants cannot move to new locations when faced with environmental stressors, they have developed complex regulatory strategies to adapt to changes in their environments. As such, plants are regulated at multiple levels of biological organization (e.g., genes, RNA, proteins, metabolites, physiology, etc.). Vertical integration of these biological levels through multiscale modeling is necessary to understand how plants respond to stressors and how plants can be engineered to achieve specific objectives (e.g., improved photosynthetic efficiency).
My research aims include developing multiscale models of photosynthesis and plant growth to (1) explore how photosynthesis will respond to individual and combined environmental stressors, (2) identify genetic and metabolic engineering strategies for improving photosynthetic efficiency and other crop processes while maintaining or improving crop acclimation, adaptation, sustainability, yield, and/or nutritional content, and (3) exploring how engineering crops can impact their surrounding environments and other civil and environmental infrastructures.
- Multiscale plant and crop modeling (gene regulation, protein regulation, metabolism, physiology, ecosystem, etc.)
- Photosynthesis modeling and engineering
- Crop and environmental sustainability
- Control systems theory in biological modeling
- Data-driven modeling
Chapters in Books
- Matthews M.L., Williams C.M. 2021. Multiscale Modeling of Cross-Regulatory Transcript and Protein Influences. In: MUKHTAR S. (eds) Modeling Transcriptional Regulation. Methods in Molecular Biology, vol 2328. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1534-8_7
Selected Articles in Journals
- Lochocki, E.B., Rhode, S., Jaiswal, D., Matthews, M.L., Miguez, F.E., Long, S.P., McGrath, J.M. 2022. BioCro II: a Software Packages for Modular Crop Growth Simulations. in silico Plants. 4(1):diac003.
- Matthews, M.L., Marshall-Colón, A., McGrath, J.M., Lochocki, E.B., Long, S.P. 2022. Soybean-BioCro: a semi-mechanistic model of soybean growth. in silico Plants 4(1):diab032. [First and corresponding author]
- Matthews, M.L. and Marshall-Colón, A. 2021. Multiscale plant modeling: From genome to phenome and beyond. Emerging Topics in Life Sciences. ETLS20200276.
- Matthews, M.L., Wang, J.P., Sederoff, R., Chiang, V.L., and Williams, C.M. 2021. A multiscale model of lignin biosynthesis for predicting bioenergy traits in Populus trichocarpa. Computational and Structural Biotechnology Journal. 19:168-182.
- Matthews, M.L., Wang, J.P., Sederoff, R., Chiang, V.L., and Williams, C.M. 2020. Modeling cross-regulatory influences on monolignol transcripts and proteins under single and combinatorial gene knockdowns in Populus trichocarpa. PLoS Computational Biology 16(4):e1007197
- Wang, J.P., Matthews, M.L., Naik, P.P., Williams, C.M., Ducoste, J.J., Sederoff, R.R., and Chiang, V.L. 2019. Flux modeling for monolignol biosynthesis. Current Opinion in Biotechnology 56:187-192.
- Wang, J.P., Matthews, M.L., Williams, C.M., Shi, R., Yang, C., Tunlaya-anukit, S., Chen, H-C., Li, Q., Liu, J., Lin, C-Y., Naik, P., Sun, Y-H., Loziuk, P.L., Yeh, T-F., Kim, H., Gjersing, E., Shollenberger, T., Shuford, C.M., Song, J., Miller, Z., Huang, Y-Y., Edmunds, C.W., Liu, B., Sun, Y., Lin, Y-C.J., Li, W., Chen, H., Peszlen, I., Ducoste, J.J., Ralph, J., Chang, H-M., Muddiman, D.C., Davis, M.F., Smith, C., Isik, F., Sederoff, R., and Chiang, V.L., 2018. Improving wood properties for wood utilization through multi-omics integration in lignin biosynthesis. Nature Communications 9(1):1579.
Recent Courses Taught
- CEE 340 - Energy and Global Environment
- CEE 498 MPG (CEE 498 MPO) - Modeling Plants Gene-Ecosystem
- CEE 535 - Environmental Systems II
- CEE 595 W - Hydro Seminar