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Title: | Evolving Engineered S. Cerevisiae Toward Efficient Production of Lactic Acid |
Authors: | Davidoff, Erika |
Advisors: | Avalos, Jose L. |
Department: | Chemical and Biological Engineering |
Certificate Program: | Neuroscience Program |
Class Year: | 2017 |
Abstract: | Lactic acid-producing yeast strains have been in development for several years with the aim of efficiently producing poly-lactic acid, a renewable and biodegradable substitute for fossil fuel-derived plastics. Currently, Lactobacillus bacteria generate most lactic acid on an industrial scale; however, lactic acid-producing yeast are an economically attractive alternative. When put under evolutionary pressure to metabolize glucose, existing engineered strains of lactic acid-producing yeast developed through knocking out pyruvate decarboxylase (PDC) have all developed mutations in the transcription regulator MTH1. The overall goal of this work was to evolve PDC knockout strains in hopes of developing an alternative evolution that resulted in greater lactic acid production. Multiple strains of lactic acid-producing Saccharomyces cerevisiae were produced by deleting endogenous enzymes, including PDC and G3P dehydrogenase (GPD) and introducing a lactate dehydrogenase (LDH) pathway through ∂-integration. The resultant strains demonstrated some ability to grow using glucose as the sole carbon source, likely due to the large increase in LDH copy number using the ∂-integration technique. Three strains were able to produce lactic acid on a comparable scale to previous work, and a strain in which both ethanol and glycerol production were eliminated produced the largest amount of lactic acid. Though the evolutionary goals were not reached, this work highlights the potential of ∂-integration and manipulation of endogenous pathways with known function for the development of strains that can produce lactic acid from glucose media on an industrial scale. |
URI: | http://arks.princeton.edu/ark:/88435/dsp01w6634625g |
Type of Material: | Princeton University Senior Theses |
Language: | en_US |
Appears in Collections: | Chemical and Biological Engineering, 1931-2019 Neuroscience, 2017-2020 |
Files in This Item:
File | Size | Format | |
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Davidoff_SeniorThesis2017.pdf | 7.57 MB | Adobe PDF | Request a copy |
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