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Improving Designer Glycan Production in Escherichia coli through Model-Guided Metabolic Engineering
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Abstract
Asparagine-linked (
N
-linked) glycosylation is the most common protein modification in eukaryotes, affecting over two-thirds of the proteome. Glycosylation is also critical to the pharmacokinetic activity and immunogenicity of many therapeutic proteins currently produced in complex eukaryotic hosts. The discovery of a protein glycosylation pathway in the pathogen
Campylobacter jejuni
and its subsequent transfer into laboratory strains of
Escherichia coli
has spurred great interest in glycoprotein production in prokaryotes. However, prokaryotic glycoprotein production has several drawbacks, including insufficient availability of non-native glycan precursors. To address this limitation, we used a constraint-based model of
E. coli
metabolism in combination with heuristic optimization to design gene knockout strains that overproduced glycan precursors. First, we incorporated reactions associated with
C. jejuni
glycan assembly into a genome-scale model of
E. coli
metabolism. We then identified gene knockout strains that coupled optimal growth to glycan synthesis. Simulations suggested that these growth-coupled glycan overproducing strains had metabolic imbalances that rerouted flux toward glycan precursor synthesis. We then validated the model-identified knockout strains experimentally by measuring glycan expression using a flow cytometric-based assay involving fluorescent labeling of cell surface-displayed glycans. Overall, this study demonstrates the promising role that metabolic modeling can play in optimizing the performance of a next-generation microbial glycosylation platform.
Title: Improving Designer Glycan Production in
Escherichia coli
through Model-Guided Metabolic Engineering
Description:
Abstract
Asparagine-linked (
N
-linked) glycosylation is the most common protein modification in eukaryotes, affecting over two-thirds of the proteome.
Glycosylation is also critical to the pharmacokinetic activity and immunogenicity of many therapeutic proteins currently produced in complex eukaryotic hosts.
The discovery of a protein glycosylation pathway in the pathogen
Campylobacter jejuni
and its subsequent transfer into laboratory strains of
Escherichia coli
has spurred great interest in glycoprotein production in prokaryotes.
However, prokaryotic glycoprotein production has several drawbacks, including insufficient availability of non-native glycan precursors.
To address this limitation, we used a constraint-based model of
E.
coli
metabolism in combination with heuristic optimization to design gene knockout strains that overproduced glycan precursors.
First, we incorporated reactions associated with
C.
jejuni
glycan assembly into a genome-scale model of
E.
coli
metabolism.
We then identified gene knockout strains that coupled optimal growth to glycan synthesis.
Simulations suggested that these growth-coupled glycan overproducing strains had metabolic imbalances that rerouted flux toward glycan precursor synthesis.
We then validated the model-identified knockout strains experimentally by measuring glycan expression using a flow cytometric-based assay involving fluorescent labeling of cell surface-displayed glycans.
Overall, this study demonstrates the promising role that metabolic modeling can play in optimizing the performance of a next-generation microbial glycosylation platform.
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