Towards biosensor-assisted directed evolution of myo-inositol oxygenase

Biosensors are powerful tools that leverage transcriptional regulation mechanisms to modulate gene expression in response to a variety of stimuli. This can allow for metabolic pathway regulation, high throughput screening, and many other applications. In this work, we focus on their uses in high throughput screening, the roadblocks that prevent their effective operation and the ways in which we overcame these challenges, and an example of the application of a biosensor in an optimized system. The intended application of the biosensor for this work was the directed evolution of myo-inositol oxygenase (MIOX), the enzyme that catalyzed the penultimate, rate-limiting step in the metabolic production of glucarate from glucose in E. coli. Here, we develop a biosensor that recognizes glucuronate, the direct product of MIOX, and optimize our system towards screening a library of MIOX genes for an improved enzyme variant. Biosensors for fructuronate and glucuronate were developed and investigated for their ability to indirectly and directly detect glucuronate levels via the UxuR and ExuR transcription factors (TFs), respectively. Ultimately, due to its ability to directly detect glucuronate, the ExuR biosensor was selected for application to high throughput screening. This biosensor was characterized via exogenous glucuronate addition and endogenous glucuronate production from MI, the substrate of MIOX, and from glucose, the initial substrate of the glucarate pathway. In characterizing the biosensor, we found that it was strongly impacted by experimental conditions as varying fluorescent output was observed when glucuronate was produced from differing MIOX homologs. It appeared that the capacity of the biosensor was limited when burden was imposed on the system. A variety of rational engineering approaches were attempted and evaluated in regards to their ability to yield a more consistent biosensor output. Finally, the optimal biosensor configuration and experimental setup was applied to successfully detect the difference between two homologs that differed in productivity. This work investigated the challenges that prevent biosensors from successfully aiding high-throughput screening. Even with these challenges we were able to display the ability of the biosensor to distinguish between enzyme variants of differing productivity levels, indicating its promise should these barriers be fully overcome.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Chemical Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2023

Author dc:creator

• Nash, Jennifer Kaczmarek

Advisor dc:contributor.advisor

• Prather, Kristala L. J.

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright MIT

Licence dc:rights.uri

• http://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/150164

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/150164