Modular Metabolic Engineering for Biobased Chemical Production

2019 ◽  
Vol 37 (2) ◽  
pp. 152-166 ◽  
Author(s):  
Hongyuan Lu ◽  
Juan C. Villada ◽  
Patrick K.H. Lee
2013 ◽  
Vol 31 (8) ◽  
pp. 1200-1223 ◽  
Author(s):  
Xianzhong Chen ◽  
Li Zhou ◽  
Kangming Tian ◽  
Ashwani Kumar ◽  
Suren Singh ◽  
...  

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Kaushik Raj ◽  
Naveen Venayak ◽  
Patrick Diep ◽  
Sai Akhil Golla ◽  
Alexander F. Yakunin ◽  
...  

Abstract Background Microorganisms can be metabolically engineered to produce a wide range of commercially important chemicals. Advancements in computational strategies for strain design and synthetic biological techniques to construct the designed strains have facilitated the generation of large libraries of potential candidates for chemical production. Consequently, there is a need for high-throughput laboratory scale techniques to characterize and screen these candidates to select strains for further investigation in large scale fermentation processes. Several small-scale fermentation techniques, in conjunction with laboratory automation have enhanced the throughput of enzyme and strain phenotyping experiments. However, such high throughput experimentation typically entails large operational costs and generate massive amounts of laboratory plastic waste. Results In this work, we develop an eco-friendly automation workflow that effectively calibrates and decontaminates fixed-tip liquid handling systems to reduce tip waste. We also investigate inexpensive methods to establish anaerobic conditions in microplates for high-throughput anaerobic phenotyping. To validate our phenotyping platform, we perform two case studies—an anaerobic enzyme screen, and a microbial phenotypic screen. We used our automation platform to investigate conditions under which several strains of E. coli exhibit the same phenotypes in 0.5 L bioreactors and in our scaled-down fermentation platform. We also propose the use of dimensionality reduction through t-distributed stochastic neighbours embedding (t-SNE) in conjunction with our phenotyping platform to effectively cluster similarly performing strains at the bioreactor scale. Conclusions Fixed-tip liquid handling systems can significantly reduce the amount of plastic waste generated in biological laboratories and our decontamination and calibration protocols could facilitate the widespread adoption of such systems. Further, the use of t-SNE in conjunction with our automation platform could serve as an effective scale-down model for bioreactor fermentations. Finally, by integrating an in-house data-analysis pipeline, we were able to accelerate the ‘test’ phase of the design-build-test-learn cycle of metabolic engineering.


mSystems ◽  
2021 ◽  
Author(s):  
Ke Zhang ◽  
Weishu Zhao ◽  
Dmitry A. Rodionov ◽  
Gabriel M. Rubinstein ◽  
Diep N. Nguyen ◽  
...  

The extremely thermophilic cellulolytic bacterium, Caldicellulosiruptor bescii , degrades plant biomass at high temperatures without any pretreatments and can serve as a strategic platform for industrial applications. The metabolic engineering of C. bescii , however, faces potential bottlenecks in bio-based chemical productions.


2021 ◽  
Author(s):  
Kaushik Raj ◽  
Naveen Venayak ◽  
Patrick Diep ◽  
Sai Akhil Golla ◽  
Alexander F. Yakunin ◽  
...  

Microorganisms can be metabolically engineered to produce a wide range of commercially important chemicals. Advancements in computational strategies for strain design and synthetic biological techniques to construct the designed strains have facilitated the generation of large libraries of potential candidates for chemical production. Consequently, there is a need for a high-throughput, laboratory scale methods to characterize and screen these candidates to select strains for further investigation in large scale fermentation processes. Several small-scale fermentation techniques, in conjunction with laboratory automation have enhanced the throughput of enzyme and strain phenotyping experiments. However, such high throughput experimentation typically entails large operational costs and generate massive amounts of laboratory plastic waste. In this work, we develop an eco-friendly automation workflow that effectively calibrates and decontaminates fixed-tip liquid handling systems to reduce tip waste. We also investigate inexpensive methods to establish anaerobic conditions in microplates for high-throughput anaerobic phenotyping. To validate our phenotyping platform, we assess its performance in two case studies - an anaerobic enzyme screen, and a microbial phenotypic screen. We used our automation platform to investigate conditions under which several strains of E. coli exhibit the same phenotypes in 0.5 L bioreactors and in our scaled-down fermentation platform. Further, we propose the use of dimensionality reduction through t-distributed stochastic neighbours embedding, in conjunction with our phenotyping platform to serve as an effective scale-down model for bioreactor phenotypes. By integrating an in-house data-analysis pipeline, we were able to accelerate the 'test' phase of the design-build-test-learn cycle of metabolic engineering.


2020 ◽  
Vol 20 (6) ◽  
Author(s):  
Lisset Duran ◽  
José Montaño López ◽  
José L Avalos

ABSTRACT The mitochondria, often referred to as the powerhouse of the cell, offer a unique physicochemical environment enriched with a distinct set of enzymes, metabolites and cofactors ready to be exploited for metabolic engineering. In this review, we discuss how the mitochondrion has been engineered in the traditional sense of metabolic engineering or completely bypassed for chemical production. We then describe the more recent approach of harnessing the mitochondria to compartmentalize engineered metabolic pathways, including for the production of alcohols, terpenoids, sterols, organic acids and other valuable products. We explain the different mechanisms by which mitochondrial compartmentalization benefits engineered metabolic pathways to boost chemical production. Finally, we discuss the key challenges that need to be overcome to expand the applicability of mitochondrial engineering and reach the full potential of this emerging field.


2020 ◽  
Vol 49 (14) ◽  
pp. 4615-4636 ◽  
Author(s):  
Yoo-Sung Ko ◽  
Je Woong Kim ◽  
Jong An Lee ◽  
Taehee Han ◽  
Gi Bae Kim ◽  
...  

This tutorial review covers tools, strategies, and procedures of systems metabolic engineering facilitating the development of microbial cell factories efficiently producing chemicals and materials.


mBio ◽  
2017 ◽  
Vol 8 (3) ◽  
Author(s):  
J. Andrew Jones ◽  
Victoria R. Vernacchio ◽  
Shannon M. Collins ◽  
Abhijit N. Shirke ◽  
Yu Xiu ◽  
...  

ABSTRACT Fermentation-based chemical production strategies provide a feasible route for the rapid, safe, and sustainable production of a wide variety of important chemical products, ranging from fuels to pharmaceuticals. These strategies have yet to find wide industrial utilization due to their inability to economically compete with traditional extraction and chemical production methods. Here, we engineer for the first time the complex microbial biosynthesis of an anthocyanin plant natural product, starting from sugar. This was accomplished through the development of a synthetic, 4-strain Escherichia coli polyculture collectively expressing 15 exogenous or modified pathway enzymes from diverse plants and other microbes. This synthetic consortium-based approach enables the functional expression and connection of lengthy pathways while effectively managing the accompanying metabolic burden. The de novo production of specific anthocyanin molecules, such as calistephin, has been an elusive metabolic engineering target for over a decade. The utilization of our polyculture strategy affords milligram-per-liter production titers. This study also lays the groundwork for significant advances in strain and process design toward the development of cost-competitive biochemical production hosts through nontraditional methodologies. IMPORTANCE To efficiently express active extensive recombinant pathways with high flux in microbial hosts requires careful balance and allocation of metabolic resources such as ATP, reducing equivalents, and malonyl coenzyme A (malonyl-CoA), as well as various other pathway-dependent cofactors and precursors. To address this issue, we report the design, characterization, and implementation of the first synthetic 4-strain polyculture. Division of the overexpression of 15 enzymes and transcription factors over 4 independent strain modules allowed for the division of metabolic burden and for independent strain optimization for module-specific metabolite needs. This study represents the most complex synthetic consortia constructed to date for metabolic engineering applications and provides a new paradigm in metabolic engineering for the reconstitution of extensive metabolic pathways in nonnative hosts. IMPORTANCE To efficiently express active extensive recombinant pathways with high flux in microbial hosts requires careful balance and allocation of metabolic resources such as ATP, reducing equivalents, and malonyl coenzyme A (malonyl-CoA), as well as various other pathway-dependent cofactors and precursors. To address this issue, we report the design, characterization, and implementation of the first synthetic 4-strain polyculture. Division of the overexpression of 15 enzymes and transcription factors over 4 independent strain modules allowed for the division of metabolic burden and for independent strain optimization for module-specific metabolite needs. This study represents the most complex synthetic consortia constructed to date for metabolic engineering applications and provides a new paradigm in metabolic engineering for the reconstitution of extensive metabolic pathways in nonnative hosts.


2021 ◽  
Author(s):  
Kaushik Venkatesan ◽  
Naveen Venayak ◽  
Patrick Diep ◽  
Sai Akhil Golla ◽  
Alexander Yakunin ◽  
...  

Abstract Background: Microorganisms can be metabolically engineered to produce a wide range of commercially important chemicals. Advancements in computational strategies for strain design and synthetic biological techniques to construct the designed strains have facilitated the generation of large libraries of potential candidates for chemical production. Consequently, there is a need for a high-throughput, laboratory scale techniques to characterize and screen these candidates to select strains for further investigation in large scale fermentation processes. Several small-scale fermentation techniques, in conjunction with laboratory automation have enhanced the throughput of enzyme and strain phenotyping experiments. However, such high throughput experimentation typically entails large operational costs and generate massive amounts of laboratory plastic waste. Results: In this work, we develop an eco-friendly automation work ow that effectively calibrates and decontaminates fixed-tip liquid handling systems to reduce tip waste. We also investigate inexpensive methods to establish anaerobic conditions in microplates for high-throughput anaerobic phenotyping. To validate our phenotyping platform, we perform two case studies - an anaerobic enzyme screen, and a microbial phenotypic screen. We used our automation platform to investigate conditions under which several strains of E. coli exhibit the same phenotypes in 0.5 L bioreactors and in our scaled-down fermentation platform. We also propose the use of dimensionality reduction through t-distributed stochastic neighbours embedding (t-SNE) in conjunction with our phenotyping platform to effectively cluster similarly performing strains at the bioreactor scale. Conclusions: Fixed-tip liquid handling systems can significantly reduce the amount of plastic waste generated in biological laboratories and our decontamination and calibration protocols could facilitate the widespread adoption of such systems. Further, the use of t-SNE in conjunction with our automation platform could serve as an effective scale-down model for bioreactor fermentations. Finally, by integrating an in-house data-analysis pipeline, we were able to accelerate the 'test' phase of the design-build-test-learn cycle of metabolic engineering.


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