A Prototype for Modular Cell Engineering

Wilbanks, Brandon; Layton, Donovan S.; Garcia, Sergio; Trinh, Cong T.

doi:10.1021/acssynbio.7b00269

Cited by 17 publications

(13 citation statements)

References 61 publications

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“…Such a platform strain that maximizes productivity could be realized by placing a minimal number of control reactions under dynamically repressible/inducible promoters to throttle biomass production flux. This is similar to the concept of a modular cellular chassis for the production of many different compounds, that has gained interest recently 49,50 .…”

Section: Discussionmentioning

confidence: 68%

Novel two-stage processes for optimal chemical production in microbes

Raj

Venayak

Mahadevan

2019

Preprint

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1Microbial metabolism can be harnessed to produce a broad range of industrially important chemicals. 2 Often, three key process variables: Titer, Rate and Yield (TRY) are the target of metabolic engineering 3 efforts to improve microbial hosts toward industrial production. Previous research into improving the 4 TRY metrics have examined the efficacy of having distinct growth and production stages to achieve 5 enhanced productivity. However, these studies assumed a switch from a maximum growth to a maximum 6 production phenotype. Hence, the choice of operating points for the growth and production stages of 7 two-stage processes is yet to be explored. The impact of reduced growth rates on substrate uptake adds 8 to the need for intelligent choice of operating points while designing two-stage processes. In this work, we 9 present a computational framework that scans the phenotypic space of microbial metabolism to identify 10 ideal growth and production phenotypic targets, to achieve optimal TRY values. Using this framework, 11 with Escherichia coli as a model organism, we compare two-stage processes that use dynamic pathway 12 regulation, with one-stage processes that use static intervention strategies. Our results indicate that 13 two-stage processes with intermediate growth during the production stage always result in the highest 14 productivity. By analyzing the flux distributions for the production enhancing strategies, we identify 15 key reactions and reaction subsystems that need to be downregulated for a wide range of metabolites 16 in E. coli. We also elucidate the importance of flux perturbations that increase phosphoenolpyruvate 17 and NADPH availability among strategies to design production platforms. Furthermore, reactions in 18 the pentose phosphate pathway emerge as key control nodes that function together to increase the 19 availability of precursors to most products in E. coli. Due to the presence of these common patterns 20 in the flux perturbations, we propose the possibility of a universal production strain that enhances the 21 production of a large number of metabolites. 22 23 Keywords: dynamic pathway engineering, two-stage processes, industrial bioprocesses, phenotypic choices, 24 production platforms, substrate uptake effects 25 1 26The use of microbes for the production of chemicals through metabolic engineering has garnered significant 27 interest in the past few decades. The naturally modular arrangement of metabolic networks makes micro-28 bial strains amenable to be used as chemical production platforms 1 . Metabolic networks have a bow-tie 29 architecture which allows a large number of metabolites to be produced from a few universal precursors 2 . 30This has allowed us to successfully engineer microbes to be biocatalysts for the production of a wide range of 31 commodity chemicals 3,4 , pharmaceuticals 5,6 , biofuels, 7,8 and other natural and non-natural compounds 9 . 32While few such processes have been successful at an industrial scale 10,11 , large strain development costs 3...

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Section: Discussionmentioning

confidence: 68%

Novel two-stage processes for optimal chemical production in microbes

Raj

Venayak

Mahadevan

2019

Preprint

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“…This modular cell design approach, known as ModCell, uses multi-objective optimization to account for the competing cellular objectives when cellular metabolism is (re)designed in a modular fashion to produce a diverse class of target chemicals. ModCell has been experimentally demonstrated for biosynthesis of alcohols [7,11,12] and esters [13][14][15][16][17] in Escherichia coli.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Multi-Objective Evolutionary Algorithms to Solve the Modular Cell Design Problem for Novel Biocatalysis

Garcia

Trinh

2019

Processes

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A large space of chemicals with broad industrial and consumer applications could be synthesized by engineered microbial biocatalysts. However, the current strain optimization process is prohibitively laborious and costly to produce one target chemical and often requires new engineering efforts to produce new molecules. To tackle this challenge, modular cell design based on a chassis strain that can be combined with different product synthesis pathway modules has recently been proposed. This approach seeks to minimize unexpected failure and avoid task repetition, leading to a more robust and faster strain engineering process. In our previous study, we mathematically formulated the modular cell design problem based on the multi-objective optimization framework. In this study, we evaluated a library of state-of-the-art multi-objective evolutionary algorithms (MOEAs) to identify the most effective method to solve the modular cell design problem. Using the best MOEA, we found better solutions for modular cells compatible with many product synthesis modules. Furthermore, the best performing algorithm could provide better and more diverse design options that might help increase the likelihood of successful experimental implementation. We identified key parameter configurations to overcome the difficulty associated with multi-objective optimization problems with many competing design objectives. Interestingly, we found that MOEA performance with a real application problem, e.g., the modular strain design problem, does not always correlate with artificial benchmarks. Overall, MOEAs provide powerful tools to solve the modular cell design problem for novel biocatalysis.

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“…[1,[8][9][10] This modular cell design approach, known as ModCell, uses multi-objective optimization to account for the competing cellular objectives when cellular metabolism is (re)designed in a modular fashion to produce a diverse class of target chemicals. ModCell has been experimentally demonstrated for biosynthesis of alcohols [8,11,12] and esters [13][14][15][16][17] in Escherichia coli.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Multi-objective Evolutionary Algorithms to Solve the Modular Cell Design Problem for Novel Biocatalysis

Garcia

Trinh

2019

Preprint

Self Cite

View full text Add to dashboard Cite

A large space of chemicals with broad industrial and consumer applications could be synthesized by engineered microbial biocatalysts. However, the current strain optimization process is prohibitively laborious and costly to produce one target chemical and often requires new engineering efforts to produce new molecules. To tackle this challenge, modular cell design based on a chassis strain that can be combined with different product synthesis pathway modules has been recently proposed. This approach seeks to minimize unexpected failure and avoid task repetition, leading to a more robust and faster strain engineering process. The modular cell design problem was mathematically formulated using a multi-objective optimization framework.[1] In this study, we evaluated a library of the state-of-the-art multi-objective evolutionary algorithms (MOEAs) to identify the most effective method to solve the modular cell design problem. Using the best MOEA, we found better solutions for modular cells compatible with many product synthesis modules. Furthermore, the best performing algorithm could provide better and more diverse design options that might help increase the likelihood of successful experimental implementation. We identified key parameter configurations to overcome the difficulty associated with multi-objective optimization problems with many competing design objectives. Interestingly, we found that MOEA performance with a real application problem, e.g., the modular strain design problem, does not always correlate with artificial benchmarks. Overall, MOEAs provide powerful tools to solve the modular cell design problem for novel biocatalysis.

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A Prototype for Modular Cell Engineering

Cited by 17 publications

References 61 publications

Novel two-stage processes for optimal chemical production in microbes

Novel two-stage processes for optimal chemical production in microbes

Comparison of Multi-Objective Evolutionary Algorithms to Solve the Modular Cell Design Problem for Novel Biocatalysis

Comparison of Multi-objective Evolutionary Algorithms to Solve the Modular Cell Design Problem for Novel Biocatalysis

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