Development of a genome scale metabolic model for Auxenochlorella protothecoides for rational engineering of biofuels production
Project Goals and Description:
Alga based biofuels and bioproducts are a sustainable source for petroleum replacements. In the Boyle lab, we take advantage of photosynthesis to convert carbon dioxide into useful products. The overall goal of this project is to manually curate a genome scale metabolic model of the green alga, A. protothecoides. This requires a student who is interested in both experimental and computational research. Experimentally, the student will collect data to build the model (growth rate, biomass composition, uptake/excretion rates). Then they will perform a detailed bioinformatics study of the model to fill in gaps and make sure that all reactions are present. Ultimately, the model will then be used to identify gene targets for engineering higher biofuel productivity
Grand Challenge: Develop carbon sequestration methods.
doi: https://doi.org/10.1101/2021.06.22.449518 https://doi.org/10.1016/j.algal.2020.101967
Nanette Boyle firstname.lastname@example.org
The ideal student for this project will have a working knowledge of biology and some lab experience (aseptic technique, cell culture) as well as some computer programming experience (matlab and or python). However, this can be overcome by a passion for the subject and a desire to learn these techniques.
TIME COMMITMENT (HRS/WK)
The student will be trained in scientific communication (how to write and present their work as well as how to read and interpret journal articles). The student will also learn aseptic technique, cell culturing, biomass composition measurements, preparation of media, chlorophyll assays, how to properly use a biochemistry analyzer, and some analytical chemistry (GC/MS). On the computational side, the student will learn how to use CobraPy
The student will be required to attend group meetings every other week and have individual meetings with the graduate student mentor once a week at least and the PI once a month. During these meetings, we will discuss progress on the project, troubleshooting and next steps. The student will also be provided career mentoring and advice about summer internships/projects/research if they should choose to pursue that. Lab/computational techniques will be taught to the student by the graduate student mentor.
PREFERRED STUDENT STATUS