Dataset Information

Improving designer glycan production in Escherichia coli through model-guided metabolic engineering.

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.

SUBMITTER: Wayman JA

PROVIDER: S-EPMC6454127 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Improving designer glycan production in Escherichia coli through model-guided metabolic engineering.

Wayman Joseph A JA Glasscock Cameron C Mansell Thomas J TJ DeLisa Matthew P MP Varner Jeffrey D JD

Metabolic engineering communications 20190329

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 int ...[more]

PMID: 31008057

Similar Datasets

Project description:BACKGROUND:The biosynthesis of high value-added compounds using metabolically engineered strains has received wide attention in recent years. Myo-inositol (inositol), an important compound in the pharmaceutics, cosmetics and food industries, is usually produced from phytate via a harsh set of chemical reactions. Recombinant Escherichia coli strains have been constructed by metabolic engineering strategies to produce inositol, but with a low yield. The proper distribution of carbon flux between cell growth and inositol production is a major challenge for constructing an efficient inositol-synthesis pathway in bacteria. Construction of metabolically engineered E. coli strains with high stoichiometric yield of inositol is desirable. RESULTS:In the present study, we designed an inositol-synthesis pathway from glucose with a theoretical stoichiometric yield of 1 mol inositol/mol glucose. Recombinant E. coli strains with high stoichiometric yield (>?0.7 mol inositol/mol glucose) were obtained. Inositol was successfully biosynthesized after introducing two crucial enzymes: inositol-3-phosphate synthase (IPS) from Trypanosoma brucei, and inositol monophosphatase (IMP) from E. coli. Based on starting strains E. coli BW25113 (wild-type) and SG104 (?ptsG::glk, ?galR::zglf, ?poxB::acs), a series of engineered strains for inositol production was constructed by deleting the key genes pgi, pfkA and pykF. Plasmid-based expression systems for IPS and IMP were optimized, and expression of the gene zwf was regulated to enhance the stoichiometric yield of inositol. The highest stoichiometric yield (0.96 mol inositol/mol glucose) was achieved from recombinant strain R15 (SG104, ?pgi, ?pgm, and RBSL5-zwf). Strain R04 (SG104 and ?pgi) reached high-density in a 1-L fermenter when using glucose and glycerol as a mixed carbon source. In scaled-up fed-batch bioconversion in situ using strain R04, 0.82 mol inositol/mol glucose was produced within 23 h, corresponding to a titer of 106.3 g/L (590.5 mM) inositol. CONCLUSIONS:The biosynthesis of inositol from glucose in recombinant E. coli was optimized by metabolic engineering strategies. The metabolically engineered E. coli strains represent a promising method for future inositol production. This study provides an essential reference to obtain a suitable distribution of carbon flux between glycolysis and inositol synthesis.

Project description:UNLABELLED:Engineering microbial hosts for the production of fungible fuels requires mitigation of limitations posed on the production capacity. One such limitation arises from the inherent toxicity of solvent-like biofuel compounds to production strains, such as Escherichia coli. Here we show the importance of host engineering for the production of short-chain alcohols by studying the overexpression of genes upregulated in response to exogenous isopentenol. Using systems biology data, we selected 40 genes that were upregulated following isopentenol exposure and subsequently overexpressed them in E. coli. Overexpression of several of these candidates improved tolerance to exogenously added isopentenol. Genes conferring isopentenol tolerance phenotypes belonged to diverse functional groups, such as oxidative stress response (soxS, fpr, and nrdH), general stress response (metR, yqhD, and gidB), heat shock-related response (ibpA), and transport (mdlB). To determine if these genes could also improve isopentenol production, we coexpressed the tolerance-enhancing genes individually with an isopentenol production pathway. Our data show that expression of 6 of the 8 candidates improved the production of isopentenol in E. coli, with the methionine biosynthesis regulator MetR improving the titer for isopentenol production by 55%. Additionally, expression of MdlB, an ABC transporter, facilitated a 12% improvement in isopentenol production. To our knowledge, MdlB is the first example of a transporter that can be used to improve production of a short-chain alcohol and provides a valuable new avenue for host engineering in biogasoline production. IMPORTANCE:The use of microbial host platforms for the production of bulk commodities, such as chemicals and fuels, is now a focus of many biotechnology efforts. Many of these compounds are inherently toxic to the host microbe, which in turn places a limit on production despite efforts to optimize the bioconversion pathways. In order to achieve economically viable production levels, it is also necessary to engineer production strains with improved tolerance to these compounds. We demonstrate that microbial tolerance engineering using transcriptomics data can also identify targets that improve production. Our results include an exporter and a methionine biosynthesis regulator that improve isopentenol production, providing a starting point to further engineer the host for biogasoline production.

Project description:BACKGROUND: Riboflavin (vitamin B2), the precursor of the flavin cofactors flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD), is used commercially as an animal feed supplement and food colorant. E. coli is a robust host for various genetic manipulations and has been employed for efficient production of biofuels, polymers, amino acids, and bulk chemicals. Thus, the aim of this study was to understand the metabolic capacity of E. coli for the riboflavin production by modification of central metabolism, riboflavin biosynthesis pathway and optimization of the fermentation conditions. RESULTS: The basic producer RF01S, in which the riboflavin biosynthesis genes ribABDEC from E. coli were overexpressed under the control of the inducible trc promoter, could accumulate 229.1 mg/L of riboflavin. Further engineering was performed by examining the impact of expression of zwf (encodes glucose 6-phosphate dehydrogenase) and gnd (encodes 6-phosphogluconate dehydrogenase) from Corynebacterium glutamicum and pgl (encodes 6-phosphogluconolactonase) from E. coli on riboflavin production. Deleting pgi (encodes glucose-6-phosphate isomerase) and genes of Entner-Doudoroff (ED) pathway successfully redirected the carbon flux into the oxidative pentose phosphate pathway, and overexpressing the acs (encodes acetyl-CoA synthetase) reduced the acetate accumulation. These modifications increased riboflavin production to 585.2 mg/L. By further modulating the expression of ribF (encodes riboflavin kinase) for reducing the conversion of riboflavin to FMN in RF05S, the final engineering strain RF05S-M40 could produce 1036.1 mg/L riboflavin in LB medium at 37°C. After optimizing the fermentation conditions, strain RF05S-M40 produced 2702.8 mg/L riboflavin in the optimized semi-defined medium, which was a value nearly 12-fold higher than that of RF01S, with a yield of 137.5 mg riboflavin/g glucose. CONCLUSIONS: The engineered strain RF05S-M40 has the highest yield among all reported riboflavin production strains in shake flask culture. This work collectively demonstrates that E. coli has a potential to be a microbial cell factory for riboflavin bioproduction.

Project description:BackgroundBioprocessing offers a sustainable and green approach to manufacture various chemicals and materials. Development of bioprocesses requires transforming common producer strains to cell factories. 13C metabolic flux analysis (13C-MFA) can be applied to identify relevant targets to accomplish the desired phenotype, which has become one of the major tools to support systems metabolic engineering. In this research, we applied 13C-MFA to identify bottlenecks in the bioconversion of glycerol into acetol by Escherichia coli. Valorization of glycerol, the main by-product of biodiesel, has contributed to the viability of biofuel economy.ResultsWe performed 13C-MFA and measured intracellular pyridine nucleotide pools in a first-generation acetol producer strain (HJ06) and a non-producer strain (HJ06C), and identified that engineering the NADPH regeneration is a promising target. Based on this finding, we overexpressed nadK encoding NAD kinase or pntAB encoding membrane-bound transhydrogenase either individually or in combination with HJ06, obtaining HJ06N, HJ06P and HJ06PN. The step-wise approach resulted in increasing the acetol titer from 0.91 g/L (HJ06) to 2.81 g/L (HJ06PN). To systematically characterize and the effect of mutation(s) on the metabolism, we also examined the metabolomics and transcriptional levels of key genes in four strains. The pool sizes of NADPH, NADP+ and the NADPH/NADP+ ratio were progressively increased from HJ06 to HJ06PN, demonstrating that the sufficient NADPH supply is critical for acetol production. Flux distribution was optimized towards acetol formation from HJ06 to HJ06PN: (1) The carbon partitioning at the DHAP node directed gradually more carbon from the lower glycolytic pathway through the acetol biosynthetic pathway; (2) The transhydrogenation flux was constantly increased. In addition, 13C-MFA showed the rigidity of upper glycolytic pathway, PP pathway and the TCA cycle to support growth. The flux patterns were supported by most metabolomics data and gene expression profiles.ConclusionsThis research demonstrated how 13C-MFA can be applied to drive the cycles of design, build, test and learn implementation for strain development. This succeeding engineering strategy can also be applicable for rational design of other microbial cell factories.

Dataset Information

Improving designer glycan production in Escherichia coli through model-guided metabolic engineering.

Publications

Improving designer glycan production in <i>Escherichia coli</i> through model-guided metabolic engineering.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets