Muconic acid production from glucose and xylose in Pseudomonas putida via evolution and metabolic engineering

Chen Ling, George L. Peabody, Davinia Salvachúa, Young Mo Kim, Colin M. Kneucker, Christopher H. Calvey, Michela A. Monninger, Nathalie Munoz Munoz, Brenton C. Poirier, Kelsey J. Ramirez, Peter C. St. John, Sean P. Woodworth, Jon K. Magnuson, Kristin E. Burnum-Johnson, Adam M. Guss, Christopher W. Johnson, Gregg T. Beckham

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69 Scopus citations

Abstract

Muconic acid is a bioprivileged molecule that can be converted into direct replacement chemicals for incumbent petrochemicals and performance-advantaged bioproducts. In this study, Pseudomonas putida KT2440 is engineered to convert glucose and xylose, the primary carbohydrates in lignocellulosic hydrolysates, to muconic acid using a model-guided strategy to maximize the theoretical yield. Using adaptive laboratory evolution (ALE) and metabolic engineering in a strain engineered to express the D-xylose isomerase pathway, we demonstrate that mutations in the heterologous D-xylose:H+ symporter (XylE), increased expression of a major facilitator superfamily transporter (PP_2569), and overexpression of aroB encoding the native 3-dehydroquinate synthase, enable efficient muconic acid production from glucose and xylose simultaneously. Using the rationally engineered strain, we produce 33.7 g L−1 muconate at 0.18 g L−1 h−1 and a 46% molar yield (92% of the maximum theoretical yield). This engineering strategy is promising for the production of other shikimate pathway-derived compounds from lignocellulosic sugars.

Original languageEnglish
Article number4925
JournalNature Communications
Volume13
Issue number1
DOIs
StatePublished - Dec 2022

Funding

This work was authored in part by Alliance for Sustainable Energy, LLC, the manager and operator of the National Renewable Energy Laboratory for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. This work was also partially authored by Oak Ridge National Laboratory, which is managed by UT-Battelle, LLC, for the U.S. DOE under contract DE-AC05-00OR22725. A portion of this research was performed at Pacific Northwest National Laboratory (PNNL) using EMSL (grid.436923.9), a DOE Office of Science User Facility sponsored by the Office of Biological and Environmental Research. PNNL is a multiprogram national laboratory operated by Battelle for the Department of Energy (DOE) under Contract DE-AC05-76RLO 1830. Funding was provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Bioenergy Technologies Office (BETO) for the Agile BioFoundry. We thank Stefan Haugen, William Michener, Morgan Ingraham, and Kelley Hestmark for their efforts in analytics. We thank Scott Saunders from University of Texas Southwestern Medical Center for the growth curve fitting tool FittR. We thank Eugene Kuatsjah for help with Pymol. We thank Taraka Dale from Los Alamos National Laboratory for a critical reading of the manuscript. We thank Jay Fitzgerald and Gayle Bentley at DOE, Prof. Eiji Masai from Nagaoka University of Technology, Kevin McNaught, and members of the Agile BioFoundry for helpful discussions. This work was authored in part by Alliance for Sustainable Energy, LLC, the manager and operator of the National Renewable Energy Laboratory for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. This work was also partially authored by Oak Ridge National Laboratory, which is managed by UT-Battelle, LLC, for the U.S. DOE under contract DE-AC05-00OR22725. A portion of this research was performed at Pacific Northwest National Laboratory (PNNL) using EMSL (grid.436923.9), a DOE Office of Science User Facility sponsored by the Office of Biological and Environmental Research. PNNL is a multiprogram national laboratory operated by Battelle for the Department of Energy (DOE) under Contract DE-AC05-76RLO 1830. Funding was provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Bioenergy Technologies Office (BETO) for the Agile BioFoundry. We thank Stefan Haugen, William Michener, Morgan Ingraham, and Kelley Hestmark for their efforts in analytics. We thank Scott Saunders from University of Texas Southwestern Medical Center for the growth curve fitting tool FittR. We thank Eugene Kuatsjah for help with Pymol. We thank Taraka Dale from Los Alamos National Laboratory for a critical reading of the manuscript. We thank Jay Fitzgerald and Gayle Bentley at DOE, Prof. Eiji Masai from Nagaoka University of Technology, Kevin McNaught, and members of the Agile BioFoundry for helpful discussions.

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