Metabolic engineering of glycoprotein biosynthesis in bacteria

2018 ◽  
Vol 2 (3) ◽  
pp. 419-432 ◽  
Author(s):  
Aravind Natarajan ◽  
Thapakorn Jaroentomeechai ◽  
Mingji Li ◽  
Cameron J. Glasscock ◽  
Matthew P. DeLisa
Keyword(s):  
Escherichia Coli ◽  
Metabolic Engineering ◽  
Campylobacter Jejuni ◽  
Rational Design ◽  
Strain Engineering ◽  
Protein Glycosylation ◽  
Microbial Cell ◽  
Evolutionary Engineering ◽  
Escherichia Coli Cells ◽  
Genome Wide

The demonstration more than a decade ago that glycoproteins could be produced in Escherichia coli cells equipped with the N-linked protein glycosylation machinery from Campylobacter jejuni opened the door to using simple bacteria for the expression and engineering of complex glycoproteins. Since that time, metabolic engineering has played an increasingly important role in developing and optimizing microbial cell glyco-factories for the production of diverse glycoproteins and other glycoconjugates. It is becoming clear that future progress in creating efficient glycoprotein expression platforms in bacteria will depend on the adoption of advanced strain engineering strategies such as rational design and assembly of orthogonal glycosylation pathways, genome-wide identification of metabolic engineering targets, and evolutionary engineering of pathway performance. Here, we highlight recent advances in the deployment of metabolic engineering tools and strategies to develop microbial cell glyco-factories for the production of high-value glycoprotein targets with applications in research and medicine.

scholarly journals Metabolic engineering of Escherichia coli for de novo production of 3-phenylpropanol via retrobiosynthesis approach

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Zhenning Liu ◽  
Xue Zhang ◽  
Dengwei Lei ◽  
Bin Qiao ◽  
Guang-Rong Zhao
Keyword(s):  
Escherichia Coli ◽  
Metabolic Engineering ◽  
De Novo ◽  
Microbial Cell ◽  
Cell Factory ◽  
Phosphopantetheinyl Transferase ◽  
Chromosome Engineering ◽  
Microbial Cell Factory ◽  
E Coli ◽  
Artificial Pathway

Abstract Background 3-Phenylpropanol with a pleasant odor is widely used in foods, beverages and cosmetics as a fragrance ingredient. It also acts as the precursor and reactant in pharmaceutical and chemical industries. Currently, petroleum-based manufacturing processes of 3-phenypropanol is environmentally unfriendly and unsustainable. In this study, we aim to engineer Escherichia coli as microbial cell factory for de novo production of 3-phenypropanol via retrobiosynthesis approach. Results Aided by in silico retrobiosynthesis analysis, we designed a novel 3-phenylpropanol biosynthetic pathway extending from l-phenylalanine and comprising the phenylalanine ammonia lyase (PAL), enoate reductase (ER), aryl carboxylic acid reductase (CAR) and phosphopantetheinyl transferase (PPTase). We screened the enzymes from plants and microorganisms and reconstructed the artificial pathway for conversion of 3-phenylpropanol from l-phenylalanine. Then we conducted chromosome engineering to increase the supply of precursor l-phenylalanine and combined the upstream l-phenylalanine pathway and downstream 3-phenylpropanol pathway. Finally, we regulated the metabolic pathway strength and optimized fermentation conditions. As a consequence, metabolically engineered E. coli strain produced 847.97 mg/L of 3-phenypropanol at 24 h using glucose-glycerol mixture as co-carbon source. Conclusions We successfully developed an artificial 3-phenylpropanol pathway based on retrobiosynthesis approach, and highest titer of 3-phenylpropanol was achieved in E. coli via systems metabolic engineering strategies including enzyme sources variety, chromosome engineering, metabolic strength balancing and fermentation optimization. This work provides an engineered strain with industrial potential for production of 3-phenylpropanol, and the strategies applied here could be practical for bioengineers to design and reconstruct the microbial cell factory for high valuable chemicals.

scholarly journals Genome-wide investigation of mRNA lifetime determinants in Escherichia coli cells cultured at different growth rates

BMC Genomics ◽  
2015 ◽  
Vol 16 (1) ◽  
Author(s):  
Thomas Esquerré ◽  
Annick Moisan ◽  
Hélène Chiapello ◽  
Liisa Arike ◽  
Raivo Vilu ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Growth Rates ◽  
Escherichia Coli Cells ◽  
Genome Wide ◽  
Cells Cultured

scholarly journals Metabolic Engineering for l-Glutamine Overproduction by Using DNA Gyrase Mutations in Escherichia coli

2013 ◽  
Vol 79 (9) ◽  
pp. 3033-3039 ◽  
Author(s):  
Mikiro Hayashi ◽  
Kazuhiko Tabata
Keyword(s):  
Escherichia Coli ◽  
Metabolic Engineering ◽  
Topoisomerase I ◽  
Dna Gyrase ◽  
Chromosomal Dna ◽  
Topoisomerase Iv ◽  
Α Subunit ◽  
Content Type ◽  
Genome Wide ◽  
K 12

ABSTRACTAnl-glutamine-overproducing mutant of anEscherichia coliK-12-derived strain was selected from randomly mutagenized cells in the course ofl-alanyl-l-glutamine strain development. Genome-wide mutation analysis unveiled a novel mechanism forl-glutamine overproduction in this mutant. Three mutations were identified that are related to thel-glutamine overproduction phenotype, namely, an intergenic mutation in the 5′-flanking region ofyeiGand two nonsynonymous mutations ingyrA(Gly821Ser and Asp830Asn). Expression ofyeiG, which encodes a putative esterase, was enhanced by the intergenic mutation. The nonsynonymous mutations ingyrA, a gene that encodes the DNA gyrase α subunit, affected the DNA topology of the cells. Gyrase is a type II topoisomerase that adds negative supercoils to double-stranded DNA. When the opposing DNA-relaxing activity was enhanced by overexpressing topoisomerase I (topA) and topoisomerase IV (parCandparE), an increase inl-glutamine production was observed. These results indicate that a reduction of chromosomal DNA supercoils in the mutant caused an increase inl-glutamine accumulation. The mechanism underlying this finding is discussed in this paper. We also constructed anl-glutamine-hyperproducing strain by attenuating cellularl-glutamine degradation activity. Although the reconstituted mutant (withyeiGtogether withgyrA) produced 200 mMl-glutamine, metabolic engineering finally enabled construction of a mutant that accumulated more than 500 mMl-glutamine.

scholarly journals In Silico Design for Systems-Based Metabolic Engineering In Escherichia Coli for The Bioconversion of Aerobic Glycerol to Succinic Acid

2020 ◽  
Author(s):  
Albert Enrique Tafur Rangel ◽  
Wendy Lorena Rios Guzman ◽  
Carmen Elvira Ojeda Cuella ◽  
Daissy Esther Mejia Perez ◽  
Ross Carlson ◽  
...  
Keyword(s):  
Machine Learning ◽  
Escherichia Coli ◽  
Metabolic Engineering ◽  
Succinic Acid ◽  
In Silico ◽  
Rational Design ◽  
Industrial Biotechnology ◽  
E Coli ◽  
Cell Factories ◽  
Transcriptomics Data

Abstract BackgroundGlycerol has become an interesting carbon source for industrial processes as consequence of the biodiesel business growth since it has shown promising results in terms of biomass/substrate yields. Selecting the appropriate metabolic targets to build efficient cell factories and maximize the desired chemical production in as little time as possible is a major challenge in industrial biotechnology. The engineering of microbial metabolism following rational design has been widely studied. However, it is a cost-, time-, and laborious-intensive process because of the cell network complexity; thus, to be proficient is needed known in advance the effects of gene deletions.ResultsAn in silico experiment was performed to model and understand the effects of metabolic engineering over the metabolism by transcriptomics data integration. In this study, systems-based metabolic engineering to predict the metabolic engineering targets was used in order to increase the bioconversion of glycerol to succinic acid by Escherichia coli. Transcriptomics analysis suggest insights of how increase the glycerol utilization of the cell for further design efficient cell factories. Three models were used; an E. coli core model, a model obtained after the integration of transcriptomics data obtained from E. coli growing in an optimized culture media, and a third one obtained after integration of transcriptomics data obtained from E. coli after adaptive laboratory evolution experiments. A total of 2402 strains were obtained from these three models. Fumarase and pyruvate dehydrogenase were frequently predicted in all the models, suggesting that these reactions are essential to increasing succinic acid production from glycerol. Finally, using flux balance analysis results for all the mutants predicted, a machine learning method was developed to predict new mutants as well as to propose optimal metabolic engineering targets and mutants based on the measurement of importance of each knockout’s (feature’s) contribution.ConclusionsThe combination of transcriptome, systems metabolic modeling, and machine learning analyses revealed versatile molecular mechanisms involved in the utilization of glycerol. These data provide a platform to improve the prediction of metabolic engineering targets to design efficient cell factories. Our results may also work a guide platform for the selection/engineering of microorganisms for production of interesting chemical compounds.

Genome-wide analysis of redox reactions reveals metabolic engineering targets for d-lactate overproduction in Escherichia coli

2013 ◽  
Vol 18 ◽  
pp. 44-52 ◽  
Author(s):  
Hyun Ju Kim ◽  
Bo Kyeng Hou ◽  
Sung Gun Lee ◽  
Joong Su Kim ◽  
Dong-Woo Lee ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Metabolic Engineering ◽  
Redox Reactions ◽  
Genome Wide Analysis ◽  
Genome Wide
Sign in / Sign up

Export Citation Format

Share Document