Synthetic auxotrophs accelerate cell factory development through growth-coupled models
Liangpo Li, Linwei Yu, Xinxiao Sun, Qipeng Yuan, Xiaolin Shen, Jia Wang
Synthetic auxotrophs accelerate cell factory development through growth-coupled models
The engineering of microbial cell factories for the production of high-value chemicals from renewable resources presents several challenges, including the optimization of key enzymes, pathway fluxes and metabolic networks. Addressing these challenges involves the development of synthetic auxotrophs, a strategy that links cell growth with enzyme properties or biosynthetic pathways. This linkage allows for the improvement of enzyme properties by in vivo directed enzyme evolution, the enhancement of metabolic pathway fluxes under growth pressure, and remodeling of metabolic networks through directed strain evolution. The advantage of employing synthetic auxotrophs lies in the power of growth-coupled selection, which is not only high-throughput but also labor-saving, greatly simplifying the development of both strains and enzymes. Synthetic auxotrophs play a pivotal role in advancing microbial cell factories, offering benefits from enzyme optimization to the manipulation of metabolic networks within single microbes. Furthermore, this strategy extends to coculture systems, enabling collaboration within microbial communities. This review highlights the recently developed applications of synthetic auxotrophs as microbial cell factories, and discusses future perspectives, aiming to provide a practical guide for growth-coupled models to produce value-added chemicals as part of a sustainable biorefinery.
synthetic auxotrophs / growth-coupled / directed enzyme evolution / pathway flux / directed strain evolution / coculture
[1] |
Yilmaz S , Nyerges A , van der Oost J , Church G M , Claassens N J . Towards next-generation cell factories by rational genome-scale engineering. Nature Catalysis, 2022, 5(9): 751–765
CrossRef
Google scholar
|
[2] |
Nielsen J R , Weusthuis R A , Huang W E . Growth-coupled enzyme engineering through manipulation of redox cofactor regeneration. Biotechnology Advances, 2023, 63: 108102
CrossRef
Google scholar
|
[3] |
Kawai R , Toya Y , Shimizu H . Metabolic pathway design for growth-associated phenylalanine production using synthetically designed mutualism. Bioprocess and Biosystems Engineering, 2022, 45(9): 1539–1546
CrossRef
Google scholar
|
[4] |
Orsi E , Claassens N J , Nikel P I , Lindner S N . Optimizing microbial networks through metabolic bypasses. Biotechnology Advances, 2022, 60: 108035
CrossRef
Google scholar
|
[5] |
Zengler K , Zaramela L S . The social network of microorganisms—how auxotrophies shape complex communities. Nature Reviews. Microbiology, 2018, 16(6): 383–390
CrossRef
Google scholar
|
[6] |
Zhang X , Reed J L . Adaptive evolution of synthetic cooperating communities improves growth performance. PLoS One, 2014, 9(10): e108297
CrossRef
Google scholar
|
[7] |
Chen J , Wang Y , Zheng P , Sun J . Engineering synthetic auxotrophs for growth-coupled directed protein evolution. Trends in Biotechnology, 2022, 40(7): 773–776
CrossRef
Google scholar
|
[8] |
Li Z , Deng Y , Yang G Y . Growth-coupled high throughput selection for directed enzyme evolution. Biotechnology Advances, 2023, 68: 108238
CrossRef
Google scholar
|
[9] |
He H , Hoper R , Dodenhoft M , Marliere P , Bar-Even A . An optimized methanol assimilation pathway relying on promiscuous formaldehyde-condensing aldolases in E. coli. Metabolic Engineering, 2020, 60: 1–13
CrossRef
Google scholar
|
[10] |
Vidal L , Pinsach J , Striedner G , Caminal G , Ferrer P . Development of an antibiotic-free plasmid selection system based on glycine auxotrophy for recombinant protein overproduction in Escherichia coli. Journal of Biotechnology, 2008, 134(1-2): 127–136
CrossRef
Google scholar
|
[11] |
Von Kamp A , Klamt S . Growth-coupled overproduction is feasible for almost all metabolites in five major production organisms. Nature Communications, 2017, 8(1): 15956
CrossRef
Google scholar
|
[12] |
Femmer C , Bechtold M , Held M , Panke S . In vivo directed enzyme evolution in nanoliter reactors with antimetabolite selection. Metabolic Engineering, 2020, 59: 15–23
CrossRef
Google scholar
|
[13] |
Boersma Y L , Dröge M J , Van der Sloot A M , Pijning T , Cool R H , Dijkstra B W , Quax W J . A novel genetic selection system for improved enantioselectivity of Bacillus subtilis lipase A. ChemBioChem, 2008, 9(7): 1110–1115
CrossRef
Google scholar
|
[14] |
Khosla C , Luo H , Hansen A S L , Yang L , Schneider K , Kristensen M , Christensen U , Christensen H B , Du B , Özdemir E .
CrossRef
Google scholar
|
[15] |
Umeyama T , Okada S , Ito T . Synthetic gene circuit-mediated monitoring of endogenous metabolites: identification of GAL11 as a novel multicopy enhancer of S-adenosylmethionine level in yeast. ACS Synthetic Biology, 2013, 2(8): 425–430
CrossRef
Google scholar
|
[16] |
Kawai R , Toya Y , Miyoshi K , Murakami M , Niide T , Horinouchi T , Maeda T , Shibai A , Furusawa C , Shimizu H . Acceleration of target production in co-culture by enhancing intermediate consumption through adaptive laboratory evolution. Biotechnology and Bioengineering, 2021, 119(3): 936–945
CrossRef
Google scholar
|
[17] |
Zhang C , Chen Q , Fan F , Tang J , Zhan T , Wang H , Zhang X . Directed evolution of alditol oxidase for the production of optically pure D-glycerate from glycerol in the engineered Escherichia coli. Journal of Industrial Microbiology & Biotechnology, 2021, 48(7-8): kuab041
CrossRef
Google scholar
|
[18] |
Dele-Osibanjo T , Li Q , Zhang X , Guo X , Feng J , Liu J , Sun X , Wang X , Zhou W , Zheng P .
CrossRef
Google scholar
|
[19] |
Wang J , Zhang R , Zhang Y , Yang Y , Lin Y , Yan Y . Developing a pyruvate-driven metabolic scenario for growth-coupled microbial production. Metabolic Engineering, 2019, 55: 191–200
CrossRef
Google scholar
|
[20] |
An N , Xie C , Zhou S , Wang J , Sun X , Yan Y , Shen X , Yuan Q . Establishing a growth-coupled mechanism for high-yield production of β-arbutin from glycerol in Escherichia coli. Bioresource Technology, 2023, 369: 128491
CrossRef
Google scholar
|
[21] |
Lin B , Fan K , Zhao J , Ji J , Wu L , Yang K , Tao Y . Reconstitution of TCA cycle with DAOCS to engineer Escherichia coli into an efficient whole cell catalyst of penicillin G. Proceedings of the National Academy of Sciences of the United States of America, 2015, 112(32): 9855–9859
CrossRef
Google scholar
|
[22] |
Tang E , Shen X , Wang J , Sun X , Yuan Q . Synergetic utilization of glucose and glycerol for efficient myo-inositol biosynthesis. Biotechnology and Bioengineering, 2020, 117(4): 1247–1252
CrossRef
Google scholar
|
[23] |
Wu Y , Sun X , Lin Y , Shen X , Yang Y , Jain R , Yuan Q , Yan Y . Establishing a synergetic carbon utilization mechanism for non-catabolic use of glucose in microbial synthesis of trehalose. Metabolic Engineering, 2017, 39: 1–8
CrossRef
Google scholar
|
[24] |
Pei Y , Wang Y , Shen X , Wang J , Sun X , Yuan Q . Synergistic utilization of carbon sources for efficient biosynthesis of N-acetylglucosamine. Green Chemical Engineering, 2023, 4(2): 233–238
CrossRef
Google scholar
|
[25] |
Tokuyama K , Toya Y , Horinouchi T , Furusawa C , Matsuda F , Shimizu H . Application of adaptive laboratory evolution to overcome a flux limitation in an Escherichia coli production strain. Biotechnology and Bioengineering, 2018, 115(6): 1542–1551
CrossRef
Google scholar
|
[26] |
Wirth N T , Gurdo N , Krink N , Vidal-Verdú À , Donati S , Férnandez-Cabezón L , Wulff T , Nikel P I . A synthetic C2 auxotroph of Pseudomonas putida for evolutionary engineering of alternative sugar catabolic routes. Metabolic Engineering, 2022, 74: 83–97
CrossRef
Google scholar
|
[27] |
Yu T , Zhou Y J , Huang M , Liu Q , Pereira R , David F , Nielsen J . Reprogramming yeast metabolism from alcoholic fermentation to lipogenesis. Cell, 2018, 174(6): 1549–1558.e151428
CrossRef
Google scholar
|
[28] |
Maxel S , Aspacio D , King E , Zhang L , Acosta A P , Li H . A growth-based, high-throughput selection platform enables remodeling of 4-hydroxybenzoate hydroxylase active site. ACS Catalysis, 2020, 10(12): 6969–6974
CrossRef
Google scholar
|
[29] |
Maxel S , Zhang L , King E , Acosta A P , Luo R , Li H . In vivo, high-throughput selection of thermostable cyclohexanone monooxygenase (CHMO). Catalysts, 2020, 10(8): 935
CrossRef
Google scholar
|
[30] |
Maxel S , King E , Zhang Y , Luo R , Li H . Leveraging oxidative stress to regulate redox balance-based, in vivo growth selections for oxygenase engineering. ACS Synthetic Biology, 2020, 9(11): 3124–3133
CrossRef
Google scholar
|
[31] |
Bouzon M , Döring V , Dubois I , Berger A , Stoffel G M M , Calzadiaz Ramirez L , Meyer S N , Fouré M , Roche D , Perret A .
CrossRef
Google scholar
|
[32] |
Boecker S , Schulze P , Klamt S . Growth-coupled anaerobic production of isobutanol from glucose in minimal medium with Escherichia coli. Biotechnology for Biofuels and Bioproducts, 2023, 16(1): 148
CrossRef
Google scholar
|
[33] |
Liang K , Shen C R . Selection of an endogenous 2,3-butanediol pathway in Escherichia coli by fermentative redox balance. Metabolic Engineering, 2017, 39: 181–191
CrossRef
Google scholar
|
[34] |
Shen C R , Lan E I , Dekishima Y , Baez A , Cho K M , Liao J C . Driving forces enable high-titer anaerobic 1-butanol synthesis in Escherichia coli. Applied and Environmental Microbiology, 2011, 77(9): 2905–2915
CrossRef
Google scholar
|
[35] |
Zhang X , Jantama K , Moore J C , Shanmugam K T , Ingram L O . Production of L-alanine by metabolically engineered Escherichia coli. Applied Microbiology and Biotechnology, 2007, 77(2): 355–366
CrossRef
Google scholar
|
[36] |
Pontrelli S , Fricke R C B , Sakurai S S M , Putri S P , Fitz-Gibbon S , Chung M , Wu H Y , Chen Y J , Pellegrini M , Fukusaki E .
CrossRef
Google scholar
|
[37] |
Laviña W A , Sakurai S S M , Pontrelli S , Putri S P , Fukusaki E . Metabolomics analysis reveals global metabolic changes in the evolved E. coli strain with improved growth and 1-butanol production in minimal medium. Metabolites, 2020, 10(5): 192
CrossRef
Google scholar
|
[38] |
Flores A D , Holland S C , Mhatre A , Sarnaik A P , Godar A , Onyeabor M , Varman A M , Wang X , Nielsen D R . A coculture-coproduction system designed for enhanced carbon conservation through inter-strain CO2 recycling. Metabolic Engineering, 2021, 67: 387–395
CrossRef
Google scholar
|
[39] |
Xiao H , Bao Z , Zhao H . High throughput screening and selection methods for directed enzyme evolution. Industrial & Engineering Chemistry Research, 2014, 54(16): 4011–4020
CrossRef
Google scholar
|
[40] |
Maxel S , Saleh S , King E , Aspacio D , Zhang L , Luo R , Li H . Growth-based, high-throughput selection for NADH preference in an oxygen-dependent biocatalyst. ACS Synthetic Biology, 2021, 10(9): 2359–2370
CrossRef
Google scholar
|
[41] |
Buerger J , Gronenberg L S , Genee H J , Sommer M O A . Wiring cell growth to product formation. Current Opinion in Biotechnology, 2019, 59: 85–92
CrossRef
Google scholar
|
[42] |
Biz A , Proulx S , Xu Z , Siddartha K , Mulet Indrayanti A , Mahadevan R . Systems biology based metabolic engineering for non-natural chemicals. Biotechnology Advances, 2019, 37(6): 107379
CrossRef
Google scholar
|
[43] |
Orsi E , Claassens N J , Nikel P I , Lindner S N . Growth-coupled selection of synthetic modules to accelerate cell factory development. Nature Communications, 2021, 12(1): 5295
CrossRef
Google scholar
|
[44] |
Graef M D , Alexeeva S , Snoep J L , Mattos M J T D . The steady-state internal redox state (NADH/NAD) reflects the external redox state and is correlated with catabolic adaptation in Escherichia coli. Journal of Bacteriology, 1999, 181(8): 2351–2357
CrossRef
Google scholar
|
[45] |
Machado H B , Dekishima Y , Luo H , Lan E I , Liao J C . A selection platform for carbon chain elongation using the CoA-dependent pathway to produce linear higher alcohols. Metabolic Engineering, 2012, 14(5): 504–511
CrossRef
Google scholar
|
[46] |
Zhang W , Song M , Yang Q , Dai Z , Zhang S , Xin F , Dong W , Ma J , Jiang M . Current advance in bioconversion of methanol to chemicals. Biotechnology for Biofuels, 2018, 11(1): 260
CrossRef
Google scholar
|
[47] |
Wang C , Ren J , Zhou L , Li Z , Chen L , Zeng A P . An aldolase-catalyzed new metabolic pathway for the assimilation of formaldehyde and methanol to synthesize 2-keto-4-hydroxybutyrate and 1,3-propanediol in Escherichia coli. ACS Synthetic Biology, 2019, 8(11): 2483–2493
CrossRef
Google scholar
|
[48] |
Liang B , Sun G , Wang Z , Xiao J , Yang J . Production of 3-hydroxypropionate using a novel malonyl-CoA-mediated biosynthetic pathway in genetically engineered E. coli strain. Green Chemistry, 2019, 21(22): 6103–6115
CrossRef
Google scholar
|
[49] |
Wang J , Shen X , Jain R , Wang J , Yuan Q , Yan Y . Establishing a novel biosynthetic pathway for the production of 3,4-dihydroxybutyric acid from xylose in Escherichia coli. Metabolic Engineering, 2017, 41: 39–45
CrossRef
Google scholar
|
[50] |
Cros A , Alfaro-Espinoza G , De Maria A , Wirth N T , Nikel P I . Synthetic metabolism for biohalogenation. Current Opinion in Biotechnology, 2022, 74: 180–193
CrossRef
Google scholar
|
[51] |
Pentjuss A , Bolmanis E , Suleiko A , Didrihsone E , Suleiko A , Dubencovs K , Liepins J , Kazaks A , Vanags J . Pichia pastoris growth-coupled heme biosynthesis analysis using metabolic modelling. Scientific Reports, 2023, 13(1): 15816
CrossRef
Google scholar
|
[52] |
Sandberg T E , Salazar M J , Weng L L , Palsson B O , Feist A M . The emergence of adaptive laboratory evolution as an efficient tool for biological discovery and industrial biotechnology. Metabolic Engineering, 2019, 56: 1–16
CrossRef
Google scholar
|
[53] |
Wu Y , Jameel A , Xing X H , Zhang C . Advanced strategies and tools to facilitate and streamline microbial adaptive laboratory evolution. Trends in Biotechnology, 2022, 40(1): 38–59
CrossRef
Google scholar
|
[54] |
Ohtake T , Pontrelli S , Laviña W A , Liao J C , Putri S P , Fukusaki E . Metabolomics-driven approach to solving a CoA imbalance for improved 1-butanol production in Escherichia coli. Metabolic Engineering, 2017, 41: 135–143
CrossRef
Google scholar
|
[55] |
Dong H , Zhao C , Zhang T , Zhu H , Lin Z , Tao W , Zhang Y , Li Y . A systematically chromosomally engineered Escherichia coli efficiently produces butanol. Metabolic Engineering, 2017, 44: 284–292
CrossRef
Google scholar
|
[56] |
Lee S Y , Kim H U , Chae T U , Cho J S , Kim J W , Shin J H , Kim D I , Ko Y S , Jang W D , Jang Y S .
CrossRef
Google scholar
|
[57] |
Zhao S , Li F , Yang F , Ma Q , Liu L , Huang Z , Fan X , Li Q , Liu X , Gu P . Microbial production of valuable chemicals by modular co-culture strategy. World Journal of Microbiology & Biotechnology, 2022, 39(1): 6
CrossRef
Google scholar
|
[58] |
Li X , Zhou Z , Li W , Yan Y , Shen X , Wang J , Sun X , Yuan Q . Design of stable and self-regulated microbial consortia for chemical synthesis. Nature Communications, 2022, 13(1): 1554
CrossRef
Google scholar
|
[59] |
Yang M , Meng H , Li X , Wang J , Shen X , Sun X , Yuan Q . Coculture engineering for efficient production of vanillyl alcohol in Escherichia coli. aBIOTECH, 2022, 3(4): 292–300
CrossRef
Google scholar
|
[60] |
Jones J A , Vernacchio V R , Sinkoe A L , Collins S M , Ibrahim M H A , Lachance D M , Hahn J , Koffas M A G . Experimental and computational optimization of an Escherichia coli co-culture for the efficient production of flavonoids. Metabolic Engineering, 2016, 35: 55–63
CrossRef
Google scholar
|
[61] |
Wang R , Zhao S , Wang Z , Koffas M A G . Recent advances in modular co-culture engineering for synthesis of natural products. Current Opinion in Biotechnology, 2020, 62: 65–71
CrossRef
Google scholar
|
[62] |
Kong W , Meldgin D R , Collins J J , Lu T . Designing microbial consortia with defined social interactions. Nature Chemical Biology, 2018, 14(8): 821–829
CrossRef
Google scholar
|
[63] |
Douglas A E . The microbial exometabolome: ecological resource and architect of microbial communities. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 2020, 375(1798): 20190250
CrossRef
Google scholar
|
[64] |
Alter T B , Ebert B E . Determination of growth-coupling strategies and their underlying principles. BMC Bioinformatics, 2019, 20(1): 447
CrossRef
Google scholar
|
[65] |
Klamt S , Mahadevan R . On the feasibility of growth-coupled product synthesis in microbial strains. Metabolic Engineering, 2015, 30: 166–178
CrossRef
Google scholar
|
[66] |
Jensen K , Broeken V , Hansen A S L , Sonnenschein N , Herrgård M J . OptCouple: joint simulation of gene knockouts, insertions and medium modifications for prediction of growth-coupled strain designs. Metabolic Engineering Communications, 2019, 8: e00087
CrossRef
Google scholar
|
[67] |
Burgard A P , Pharkya P , Maranas C D . Optknock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Biotechnology and Bioengineering, 2003, 84(6): 647–657
CrossRef
Google scholar
|
[68] |
Legon L , Corre C , Bates D G , Mannan A A . gcFront: a tool for determining a Pareto front of growth-coupled cell factory designs. Bioinformatics, 2022, 38(14): 3657–3659
CrossRef
Google scholar
|
[69] |
Long M , Xu M , Qiao Z , Ma Z , Osire T , Yang T , Zhang X , Shao M , Rao Z . Directed evolution of ornithine cyclodeaminase using an volvR-based growth-coupling strategy for efficient biosynthesis of L-proline. ACS Synthetic Biology, 2020, 9(7): 1855–1863
CrossRef
Google scholar
|
[70] |
Crook N , Abatemarco J , Sun J , Wagner J M , Schmitz A , Alper H S . In vivo continuous evolution of genes and pathways in yeast. Nature Communications, 2016, 7(1): 13051
CrossRef
Google scholar
|
[71] |
Luan G , Cai Z , Li Y , Ma Y . Genome replication engineering assisted continuous evolution (GREACE) to improve microbial tolerance for biofuels production. Biotechnology for Biofuels, 2013, 6(1): 137
CrossRef
Google scholar
|
[72] |
Gach P C , Iwai K , Kim P W , Hillson N J , Singh A K . Droplet microfluidics for synthetic biology. Lab on a Chip, 2017, 17(20): 3388–3400
CrossRef
Google scholar
|
[73] |
Tu R , Li L , Yuan H , He R , Wang Q . Biosensor-enabled droplet microfluidic system for the rapid screening of 3-dehydroshikimic acid produced in Escherichia coli. Journal of Industrial Microbiology & Biotechnology, 2020, 47(12): 1155–1160
CrossRef
Google scholar
|
/
〈 | 〉 |