Elucidating and Computing Metabolic Networks for Co-Valorization of Cellulose and Lignin Derivatives

Conversion of lignin and cellulose from trees and plants into valuable products could reduce our reliance on non-renewable feedstocks such as petroleum and natural gas. Pseudomonas are species of soil bacteria with robust and varied metabolisms. As a result, they can produce a variety of potentially important molecules. This project will develop a detailed map of the pathways involved in processing lignin and cellulose by Pseudomonas. The regulation of these pathways will also be studied. The project will extend research opportunities to undergraduates and will engage women with STEM outreach activities at a local high school. <br/><br/>The project aims to understand the mechanisms of the metabolic networks in wild-type and engineered Pseudomonas putida strains. Mixed-substrate utilization of sugars from cellulose and hemicellulose, and aromatic substrates from lignin will be the primary focus. There are three specific objectives. First, elucidate the metabolic architecture for simultaneous processing of carbons derived from cellulose and lignin monomers. Second, analyze the metabolic network fluxes towards relevant biosynthetic pathways quantitatively. Third, identify the metabolic nodes under regulatory control in the network. The project will employ a combination of stable isotope-assisted metabolomics, proteomics profiling, genome-scale quantitative flux modeling, and in silico predictions of optimal metabolic programming. The long-term goal of this research is to unravel metabolic pathway limitations to converting lignocellulosic feedstock derivatives to value-added building blocks.<br/><br/>This project is being supported jointly by the Cellular and Biochemical Engineering (ENG/CBET) and the Systems and Synthetic Biology (BIO/MCB) Programs.<br/><br/>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.