FMSG: Bio: Integrated bioprocess and synthetic biology for future biomanufacturing of industrial products
- Institution
- OHIO STATE UNIVERSITY, THE, OH
- Principal investigator
- Shang-Tian Yang
- Funding
- $500K
- Duration
- 2023–2026
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Abstract
Future biomanufacturing of industrial products using novel synthetic biology tools and advanced bioprocesses that convert abundant biomass and waste resources into value-added products with comparable properties will enable circular bioeconomy with affordable energy, economic growth, and innovation in renewable energy and chemicals production. In this project, a multidisciplinary team will collaborate on the research to understand and mitigate bottlenecks limiting continuous production in industrial fermentation. The project team will focus on several non-model microorganisms that are currently used or have enormous potential as cell factories for producing industrial chemicals. The results from this project will guide and accelerate future biomanufacturing of chemicals and fuels and would have large and lasting impacts on the US biomanufacturing industry. The project will benefit the agricultural/rural communities by converting abundant low-value agricultural residues such as corn stover to value-added products and accelerate the growth of a sustainable bioeconomy. Biomanufacturing can also reduce greenhouse gas (GHG) emissions and make a major impact on reducing climate change. This project will also broaden the participation of underrepresented groups and train a diverse range of students and workforce participants with skills to engage in future biomanufacturing. Microbial lifespan and aging are fundamentally important phenomena that will impact industrial fermentation for chemicals production but have not been studied for most microbes including those with important industrial applications. This project focuses on understanding and modulating microbial lifespan genes and regulatory pathways in selected non-model but versatile microbes to produce chemicals and biofuels from renewable resources. This approach will integrate cell recycling to achieve high cell density and high volumetric productivity in continuous or semi-continuous (sequential batch/fed-batch) fermentation. Current production of chemicals and fuels in fermentation is limited by low product titer, productivity or rate, and yield (TRY), poor process stability, short production duration (longevity). These processes are also expensive for industrial application. This project will investigate genes and factors affecting microbial lifespan and aging, which impact cell viability, process performance (TRY), and longevity in industrial fermentation. First, selected microbial strains of industrial interest will be evaluated under different culture and stress conditions to study their effects on growth/fermentation kinetics and culture stability/longevity with population and transcriptomics analyses. The results will be used to identify genes/enzymes contributing to culture heterogeneity, production variability, and limited production duration or longevity. Then, novel synthetic biology tools including recombinase-based state machine (RSM) gene circuits and CRISPR genome engineering, will be used to engineer strains for attaining prolonged lifespan and mediated aging via enhanced stress tolerance. The research hypothesis is that microbial strains with increased lifespan or mitigated aging will be more productive for a longer duration in industrial fermentation. Such strains can be developed through the design-build-test-learn (DBTL) cycle and used in advanced continuous fermentation process with in-situ product recovery, achieving at least 50% improvements in TRY for an extended continuous production period.This Future Manufacturing award was supported by the Division of Molecular and Cellular Biosciences in the Directorate for Biological Sciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Research team
- Shang-Tian YangPI
- Marceline Egnin
- Jie Dong
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