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Modular Cell Design for Rapid, Efficient Strain Engineering Toward Available online at www.sciencedirect.com ScienceDirect Modular cell design for rapid, efficient strain engineering toward industrialization of biology 1,2,3 1,3 Cong T Trinh and Brian Mendoza Transforming biology into an engineering practice has great to exploration [4]. For biosynthesized products to com- potential to shape the industrialization of biology that will drive pete with current solutions economically and in a variety rapid development of novel microbial manufacturing platforms. of applications, research efforts must endeavor to achieve These platforms will be capable of producing a vast number of an understanding of the combinatorial space available, sustainable industrial chemicals at scale from alternative and devise an effective means for rapid strain engineering renewable feedstocks or wastes (e.g., biomass residues, to produce these products based on nature’s inherent biogas methane, syngas, CO2) without harming the modularity and synergies. environment. The challenge is to develop microbial platforms to produce targeted chemicals with high efficiency in a rapid, In this paper, we explore the progress made in rational predictable, and reproducible fashion. This paper highlights design of heterologous pathways and highlight the im- recent progress in rational design of heterologous pathways for portance of engineering dynamic control of heterologous combinatorial biosynthesis of a large space of chemicals and pathways coupled with the host cell metabolism to modular cell design for rapid strain engineering. achieve improved pathway efficiency. We envision the Addresses development of modular cell design principles will enable 1 Department of Chemical and Biomolecular Engineering, The University rapid strain engineering for combinatorial biosynthesis of of Tennessee, Knoxville, United States a large, sustainable chemical space in a plug-and-play 2 Bredesen Center for Interdisciplinary Research and Graduate fashion requiring minimum strain optimization cycles. Education, The University of Tennessee, Knoxville, United States 3 Bioenergy Science Center (BESC), Oak Ridge National Laboratory, Oak Ridge, United States Probing the combinatorial space of biobased chemicals Corresponding author: Trinh, Cong T ([email protected]) Cellular metabolisms are diverse and complex, generat- ing thousands of unique chemicals. Advancements in Current Opinion in Chemical Engineering 2016, 14:18–25 comparative genomics, systems and synthetic biology, This review comes from a themed issue on Biotechnology and and metabolic engineering have enabled researchers to bioprocess engineering access a multitude of biological parts to assemble heter- Edited by Terry Papoutsakis and Nigel Titchener-Hooker ologous pathways and start probing a combinatorial space of biobased chemicals (Figure 1). Characterized biologi- cal parts have been compiled into databases such as the Synthetic Biology Parts Registry (http://parts.igem.org/ http://dx.doi.org/10.1016/j.coche.2016.07.005 Main_Page), KEGG [5], and Biocyc [6] among others that 2211-3398/# 2016 Elsevier Ltd. All rights reserved. continue to expand as new genomes are discovered. While these databases continue to add to the breadth of biological parts information, the minimal depth of quantitative knowledge (e.g., transcription rates, enzyme kinetics, etc.) is limited, and will be the next challenge to address as the databases evolve to encompass a greater Introduction understanding of parts and their interactions with cellular Underlying the rapid advancement of technological in- systems. novation during the 20th century was the harnessing of petroleum for its diverse library of potential products. Recent achievements in harnessing biological parts for Recent research and socioeconomic developments have chemical biosynthesis include: (i) rewiring central metab- revealed the dangers of relying on fossil fuels as a singular olism for making non-natural bioplastics from sustainable source of specialty fuels and chemicals [1]. Chemicals feedstocks [7], (ii) redesigning fermentative pathways for derived from engineered microorganisms have been combinatorial biosynthesis of unique esters with tunable lauded as a promising sustainable alternative to the thou- carbon backbones [8,9 ], (iii) harnessing synthetic path- sands of chemicals derived from petroleum [2]. While ways of reverse beta-oxidation and non-decarboxylative some success stories of biosynthesized molecules Claisen condensation coupled with subsequent beta-re- achieved commercialization in recent years [3], the com- duction reactions for combinatorial biosynthesis of alco- plexity of constructing these microbial cell factories is hols, dicarboxylic acids, hydroxyl acids, and lactones surpassed by the vastness of the biochemical space open [10,11 ], (iv) manipulating polyketide and isoprenoid Current Opinion in Chemical Engineering 2016, 14:18–25 www.sciencedirect.com Modular cell design for industrialization of biology Trinh and Mendoza 19 Figure 1 (a) Opportunities Tools/Techniques Parts library Current Products In silico Promoters COBRA RBS BNICE Protein orthologs Antibiotic-EV -035 Farnesene Vector NTI, GeneDesign, Gene Biosensors AIA1 Polybutylene- Composer Regulators Drug EV-077 Succinate In vitro RNAs Hydrocortisone 1,3 propanediol Golden Gate Assembly Artemisinin 1,4 butanediol Gibson Assembly Sitagliptin Adipic acid Overlapping PCR Cephlaxin Acrylic In vivo Saffron Myristoyl glutamate Stable plasmids Heterologous Stevia Isoprene Homologous recombination pathway Resveratrol PHA CRISPR/Cas modules Valencene Butadiene DNA transformation techniques Vanillin Acrylamide Feedstocks Unexplored Biological Possibilities Ethanol Isobutene >1050 Butanol Methionine Lignocellulosic biomass Isobutanol Surfactants C1 feedstocks Lactic acid Bio-dispersants (methane, CO ) 2 Isomeric and Heterologous Succinic acid Syngas + Organic wastes Combinations + ~1012 Secondary Future Directions Specialty chemicals including: Metabolites 6 FAMEs/FAEEs ~10 Pesticides Antibiotics Host organisms Fuel Additives Model organisms (e.g., Saccharomyces cerevisiae, Primary Specialty polymers precursors Escherichia coli, Bacillus subtilis) Metabolites Food additives Non-model organisms (e.g., Clostridium thermocellum, ~102 Flavors and fragrances thermoanaerobacter saccharolyticum, etc.) C&I cleaning solvents Adhesives Lubricants Biochemical Space Commodity chemicals including: Synthetic palm oil Aviation fuel blends and more … (b) Challenges (i) Develop reusable genetic tools and parts to be compatible across species. (ii) Exploit non-model organisms with novel phenotypes (e.g., assimilation of C1 substrates, lignocellulosic biomass degradation ). (iii) Rapidly develop modular microbial platform to synthesize biochemical space. Current Opinion in Chemical Engineering The power (a) and the daunting challenge (b) for microbial synthesis of the potential combinatorial space of specialty fuels and chemicals. biosynthesis pathways to produce alcohol fuels [12], (v) efficient heterologous pathway and choose a proper com- engineering fatty acid biosynthesis for producing hydro- bination and assembly of parts for the pathway to create carbons [13–16], and (vi) rerouting amino acid biosynthe- optimal phenotypes (e.g., efficient production of desir- sis pathways for making alcohols, drug precursors, and able chemicals at high yields, titers, and productivities) industrial chemicals [17,18]. These chemicals have broad without going through extensive screening. For instance, applications related to health, energy, and the environ- designing an optimal multi-gene pathway in a bacterial ment, but are sometimes difficult to synthesize by a host can generate a vast space of solutions that depend on conventional chemical method. finding the best pairing of appropriate promoters, ribo- some binding sites, terminators, gene orders, tunable Rational design of heterologous pathways intergenic regions, and orthologous genes. In recent years, Engineering heterologous pathways in a recombinant a collection of computation-based techniques has been host can become very challenging especially as the path- developed to assist heterologous pathway design and can way complexity increases as seen in the production of be classified into three groups: pathway prediction, yield opioids in Saccharomyces cerevisiae [19 ]. For assembling analysis, and parts identification. multiple parts into a heterologous pathway, it is critical to balance and optimize fluxes through not only the heter- Pathway prediction is an essential tool to identify all ologous pathway to produce a desirable chemical but also thermodynamically feasible routes and associated the host’s native pathways to maintain good cell viability enzymes to produce desirable chemicals from the existing [20–22]. The challenge is how one can identify an databases. Hatzimanikatis and coworkers first developed www.sciencedirect.com Current Opinion in Chemical Engineering 2016, 14:18–25 20 Biotechnology and bioprocess engineering the BNICE (Biochemical Network Integrated Computa- ribosome binding sites to fine-tune translation rates and tional Explorer) framework to identify novel heterologous narrow the experimental strain engineering space [31 ]. pathways [23]. Currently, there are a variety of available tools for pathway prediction [24 ] with improved search Once the heterologous pathway is designed with appro- algorithms to address the computational challenge in priate parts, a variety of tools and techniques exist for identifying heterologous pathways
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