CAREER: Systems-Level Identification and Characterization of Cellular Export and Efflux Systems for Renewable Chemicals

Project: Research project

Project Details

Description

Overview
Product export is an important, but elusive aspect of metabolic engineering for renewable biochemicals production. This CAREER plan aims to provide a systematic and comprehensive understanding of export and efflux systems in Escherichia coli for renewable chemicals including short chain mono- and dicarboxylic acids and small aromatics. Aided by large amount of experimental dataset obtained in the proposed research, machine-learning prediction algorithms will be developed and optimized to accurately predict native exporters for ten select representative mono- and dicarboxylic acids. The predicted exporters will be experimentally validated for their potential export functions. Using similar approaches, the heterologous efflux systems with activities for nine representative aromatics will also be identified. The iterative optimization aided by integrated experimental and computational data will improve the prediction algorithm. Finally, in order to facilitate systems-level study of E. coli membrane proteome, we will build a complete plasmid collection encoding all putative E. coli membrane proteins and use it to identify uncharacterized transporters and useful membrane proteins in support of efficient microbial renewable production.

Intellectual Merit
The intellectual merits of this project are at least threefold. First, the proposed research will provide comprehensive insights into the mechanisms of product export across the membrane, an important but understudied research area in metabolic engineering. Second, the integrated approaches combining experimental validation and computational optimization in machine learning context will develop an effective prediction algorithm to identify transporters with desired substrate specificity. This innovative computational approach is flexible to streamline the search for desired transporters to enhance production or chemical tolerance. Third, the proposed research will yield a complete plasmid collection encoding E. coli membrane proteome suitable for diverse types of research focused on bacterial membrane proteins.

Broader Impacts
The development of technologies that solve the potential bottlenecks for microbial renewable production will increase the production metrics of microbial processes and eventually enhance economic viability for renewable bioproduction. Moreover, the computational algorithms developed for predicting transporter activities and the E. coli membrane proteome plasmid collection are universally useful to the synthetic biology and microbiology communities. Core concepts from the proposed research will furthermore be integrated into a series of impactful learning experiences designed to engage and train students at multiple stages along the STEM education pipeline, especially for Hispanic undergraduate students. Hispanic students will be proactively recruited and engaged in the proposed research to promote their interest in pursuing advanced studies in STEM areas. Meanwhile, Hispanic graduate students interdisciplinary research experiences and mentoring skills will be enhanced through the proposed educational and outreach activities. The scientific content of the proposed research will be incorporated in online and in-person education. As a unique and important component, the PI will develop an outreach program to help the career development of Ph.D. students at ASU in biology related programs.

StatusActive
Effective start/end date2/1/201/31/25

Funding

  • National Science Foundation (NSF): $712,632.00

Fingerprint Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.