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Programming cells by multiplex genome engineering and accelerated evolution
Open accessAbstract
The breadth of genomic diversity found among organisms in nature allows populations to adapt to diverse environments. However, genomic diversity is difficult to generate in the laboratory and new phenotypes do not easily arise on practical timescales. Although in vitro and directed evolution methods have created genetic variants with usefully altered phenotypes, these methods are limited to laborious and serial manipulation of single genes and are not used for parallel and continuous directed evolution of gene networks or genomes. Here, we describe multiplex automated genome engineering (MAGE) for large-scale programming and evolution of cells. MAGE simultaneously targets many locations on the chromosome for modification in a single cell or across a population of cells, thus producing combinatorial genomic diversity. Because the process is cyclical and scalable, we constructed prototype devices that automate the MAGE technology to facilitate rapid and continuous generation of a diverse set of genetic changes (mismatches, insertions, deletions). We applied MAGE to optimize the 1-deoxy-D-xylulose-5-phosphate (DXP) biosynthesis pathway in Escherichia coli to overproduce the industrially important isoprenoid lycopene. Twenty-four genetic components in the DXP pathway were modified simultaneously using a complex pool of synthetic DNA, creating over 4.3 billion combinatorial genomic variants per day. We isolated variants with more than fivefold increase in lycopene production within 3 days, a significant improvement over existing metabolic engineering techniques. Our multiplex approach embraces engineering in the context of evolution by expediting the design and evolution of organisms with new and improved properties.
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“(c) epistasis is a major factor for adaptive optimization of gene regulation [89,157].”
From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [157]
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MethodInfluentialSynthetic small regulatory RNAs in microbial metabolic engineering
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Analysis of genetic variation and potential applications in genome-scale metabolic modeling
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“In the MAGE (multiplexed automated genome engineering) system, a library of 69 oligonucleotides is introduced into an organism to target multiple regions of the genome, 70 producing organisms with combinatorial diversity at the targeted regions [11].”
Bridging the gap between systems biology and synthetic biology
Liu, D., Hoynes-O’Connor, A., & Zhang, F. (2013) · Frontiers in Microbiology · doi:10.3389/fmicb.2013.00211 · Cited by 34
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“For this purpose, the use of high-throughput genome engineering such as MAGE method [42] is desirable.”
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Self-citationTotal synthesis of a eukaryotic chromosome: Redesigning and SCRaMbLE‐ing yeast
Jovicevic, D., Blount, B. A., & Ellis, T. (2014) · BioEssays · doi:10.1002/bies.201400086 · Cited by 30
“coli chromosome containing the DNA sequence changes required, the approach taken here was to use genome engineering tools [7, 8] to edit the natural chromosome at hundreds of positions in parallel.”
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“The rpsD* and rpsL* mutants were generated with a modified multiplex automated genome engineering (MAGE) method (38).”
MethodOptimizing complex phenotypes through model-guided multiplex genome engineering
Kuznetsov, G., Goodman, D. B., Filsinger, G. T., Landon, M., Rohland, N., Aach, J., Lajoie, M. J., & Church, G. M. (2017) · Genome biology · doi:10.1186/s13059-017-1217-z · Cited by 34
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“The proteins have also been exploited in powerful methods for bacterial genome engineering, most notably recombineering (15,16) and Multiplex Automated Genome Engineering (17).”
Self-citationDirected evolution of material-producing microorganisms
Laurent, J., Jain, A., Kan, A., Steinacher, M., Casimiro, N. E., Stavrakis, S., deMello, A. J., & Studart, A. R. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2403585121 · Cited by 34
Programmable genetic circuits for pathway engineering
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Toward Engineering Synthetic Microbial Metabolism
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Double Dutch: A Tool for Designing Combinatorial Libraries of Biological Systems
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BackgroundSynthetic biology expands chemical control of microorganisms
Ford, T. J., & Silver, P. A. (2015) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2015.05.012 · Cited by 32
“The authors designed and implemented mutations enhancing production using multiplex automated genome engineering [53] and negative selection strategies to kill off any strains with mutations that simply led to high basal levels of antibiotic resistance.”
MethodError removal in microchip-synthesized DNA using immobilized MutS
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Stable Gene Targeting in Human Cells Using Single-Strand Oligonucleotides with Modified Bases
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BackgroundSelf-citationYeast synthetic biology toolbox and applications for biofuel production
Tsai, C., Kwak, S., Turner, T. L., & Jin, Y. (2014) · FEMS Yeast Research · doi:10.1111/1567-1364.12206 · Cited by 31
“Wang et al. (2009) exploited this fact and created a multiplex automated genome engineering (MAGE) platform to repeatedly introduce designedmutations into targeted sites of E. coli genome through the overexpression of the β-protein and electroporation of 90 bp oligonucleotides with intended…”
BackgroundGu, D., Zhang, C., Zhou, S., Wei, L., & Hua, Q. (2016) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2016.02.014 · Cited by 31
Molecular parts and genetic circuits for metabolic engineering of microorganisms
Kim, S. G., Noh, M. H., Lim, H. G., Jang, S., Jang, S., Koffas, M. A. G., & Jung, G. Y. (2018) · FEMS Microbiology Letters · doi:10.1093/femsle/fny187 · Cited by 31
Hao, W., Suo, F., Lin, Q., Chen, Q., Zhou, L., Liu, Z., Cui, W., & Zhou, Z. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.524676 · Cited by 31
A synthetic RNA-mediated evolution system in yeast
Jensen, E. D., Laloux, M., Lehka, B. J., Pedersen, L. E., Jakočiūnas, T., Jensen, M. K., & Keasling, J. D. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab472 · Cited by 31
Tang, H., Zhang, P., & Luo, X. (2021) · Journal of Molecular Biology · doi:10.1016/j.jmb.2021.167382 · Cited by 31
Non-enzymatic acetylation inhibits glycolytic enzymes in Escherichia coli
Schastnaya, E., Doubleday, P. F., Maurer, L., & Sauer, U. (2023) · Cell Reports · doi:10.1016/j.celrep.2022.111950 · Cited by 33
Synthetic Biology: A Bridge Between Functional and Evolutionary Biology
Morange, M. (2009) · Biological Theory · doi:10.1162/biot_a_00003 · Cited by 31
“New technologies are developed to generate the maximum number of possible mutations in one or a few cycles ( Wang et al. 2009 ).”
BackgroundCombinatorial and high-throughput screening approaches for strain engineering
Liu, W., & Jiang, R. (2015) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-015-6400-0 · Cited by 32
Programming the group behaviors of bacterial communities with synthetic cellular communication
Kong, W., Çelik, V., Liao, C., Hua, Q., & Lu, T. (2014) · Bioresources and Bioprocessing · doi:10.1186/s40643-014-0024-6 · Cited by 31
“In the last few years, the advances of synthetic circuits have been further expedited, empowered by recent breakthroughs in genetic engineering techniques such as novel DNA assembly [30-33] and genome editing tools [34-37], advances in methodologies including those for rational circuit design and optimization [38-40],…”
BackgroundGenome-Wide Tuning of Protein Expression Levels to Rapidly Engineer Microbial Traits
Freed, E. F., Winkler, J. D., Weiss, S. J., Garst, A. D., Mutalik, V. K., Arkin, A. P., Knight, R. D., & Gill, R. T. (2015) · ACS Synthetic Biology · doi:10.1021/acssynbio.5b00133 · Cited by 31
Accelerated adaptive laboratory evolution: A tool for evolutionary biotechnology
Declerck, L., Bouchon, F., Demeester, W., Guidi, C., & Mey, M. D. (2025) · Biotechnology Advances · doi:10.1016/j.biotechadv.2025.108741 · Cited by 32
A gene network engineering platform for lactic acid bacteria
Kong, W., Kapuganti, V. S., & Lu, T. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1093 · Cited by 30
“For small DNA fragments, we proposed to adopt a multiplex, continuous engineering strategy based on the concept of multiplex automated genome engineering (MAGE) (30).”
Designer microbes for biosynthesis
Quin, M. B., & Schmidt‐Dannert, C. (2014) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2014.02.014 · Cited by 30
“Current Opinion in Biotechnology 2014, 29:55–61 accelerated evolution (MAGE) [27].”
Näsvall, J. (2017) · PLoS ONE · doi:10.1371/journal.pone.0184126 · Cited by 30
Co-evolution of physical and social sciences in synthetic biology
Trump, B. D., Cegan, J. C., Wells, E., Poinsatte‐Jones, K., Rycroft, T., Warner, C. M., Martin, D., Perkins, E. J., Wood, M. D., & Linkov, I. (2019) · Critical Reviews in Biotechnology · doi:10.1080/07388551.2019.1566203 · Cited by 30
“’s description of the multiplex automated genome engineering (MAGE) for cell programming and evolution [85].”
BackgroundLiu, W., Tang, D., Wang, H., Lian, J., Huang, L., & Xu, Z. (2019) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-019-10118-4 · Cited by 30
Self-citationWang, J., Huang, C., Guo, K., Ma, L., Meng, X., Wang, N., & Huo, Y. (2020) · Synthetic and Systems Biotechnology · doi:10.1016/j.synbio.2020.10.005 · Cited by 30
Ye, C., Chen, X., Yang, M., Zeng, X., & Qiao, S. (2021) · Journal of Biological Engineering · doi:10.1186/s13036-021-00270-9 · Cited by 30
“These tools include well-characterized sets of expression vectors [10], promoters for dynamic pathway control [11, 12], tunable protein degradation [13], and advanced methods for genome editing [14, 15].”
MethodHigh-throughput genetic engineering tools for regulating gene expression in a microbial cell factory
Yeom, J., Park, J. S., Jung, S.-W., Lee, S., Kwon, H.-J., & Yoo, S. M. (2021) · Critical Reviews in Biotechnology · doi:10.1080/07388551.2021.2007351 · Cited by 30
“The degree of sequence variation at each locus can be obtained by varying the MAGE parameters, such as: oligo length, oligo concentration, oligo stability, oligo secondary structure, genetic modification size, and cycle time [24].”
BackgroundMethodInfluentialHost-parasite coevolution promotes innovation through deformations in fitness landscapes
Gupta, A., Zaman, L., Strobel, H. M., Gallie, J., Burmeister, A. R., Kerr, B., Tamar, E. S., Kishony, R., & Meyer, J. R. (2022) · eLife · doi:10.7554/elife.76162 · Cited by 28
“We used a genetic engineering technique called MAGE to construct the library (Wang et al., 2009).”
MethodInfluentialHao, W., Cui, W., Suo, F., Han, L., Cheng, Z., & Zhou, Z. (2022) · Chemical Science · doi:10.1039/d2sc05824c · Cited by 30
“9,10 The OrthoRep platform was established using a highly error-prone orthogonal DNA polymerase and an orthogonal plasmid to enable more speci c and precise genome editing; 11 accordingly, the EvolvR system was designed employing CRISPR-guided DNA polymerases, enabling multi-plexed and continuous…”
Rewriting the blueprint of life by synthetic genomics and genome engineering
Annaluru, N., Ramalingam, S., & Chandrasegaran, S. (2015) · Genome biology · doi:10.1186/s13059-015-0689-y · Cited by 30
“Genome editing approaches for genome-wide scale alteration that are not based on total synthesis of the genome are also being pursued and have proved powerful; for example, in the production of a reduced-size genome version of Escherichia coli [4] and engineering of bacterial genomes to include many different changes…”
BackgroundMethodInfluentialGlebes, T. Y., Sandoval, N. R., Gillis, J. H., & Gill, R. T. (2014) · Biotechnology and Bioengineering · doi:10.1002/bit.25325 · Cited by 30
“…(Cho et al., 1998; Gill et al., 2002; Lynch et al., 2007), phage-based recombineering technologies like multiplex automated genome engineering (Wang et al., 2009), a genome-wide barcoded promoter mutation library (trackable multiplex recombineering, or TRMR, (Warner et al., 2010)), among…”
BackgroundDistributed Classifier Based on Genetically Engineered Bacterial Cell Cultures
Didovyk, A., Игоревич, К. О., Ivanchenko, M., Hasty, J., Huerta, R., & Tsimring, L. S. (2014) · ACS Synthetic Biology · doi:10.1021/sb500235p · Cited by 31
Applications of systems biology towards microbial fuel production
Gowen, C. M., & Fong, S. S. (2011) · Trends in Microbiology · doi:10.1016/j.tim.2011.07.005 · Cited by 31
Aparicio, T., de Lorenzo, V., & Martínez‐García, E. (2018) · Biotechnology Journal · doi:10.1002/biot.201800483 · Cited by 30
Smanski, M. J., Aristidou, A. A., Carruth, R., Erickson, J., Gordon, M., Kedia, S. B., Lee, K. H., Prather, D., Schiel, J. E., Schultheisz, H., et al. (2022) · Journal of Industrial Microbiology & Biotechnology · doi:10.1093/jimb/kuac022 · Cited by 32
Simultaneous multi-site editing of individual genomes using retron arrays
González-Delgado, A., Lopez, S. C., Rojas-Montero, M., Fishman, C. B., & Shipman, S. L. (2024) · Nature Chemical Biology · doi:10.1038/s41589-024-01665-7 · Cited by 27
“We selected eight bacterial genes that have been shown to affect lycopene yield 3,37–39 (Fig.”
Influential
Metadata
- Authors
- Wang, H. H., Isaacs, F. J., Carr, P. A., Sun, Z. Z., Xu, G., Forest, C. R., & Church, G. M.
- Affiliations
- Harvard University (US)
- MIT Media Lab (US)
- Georgia Institute of Technology (US)
- Corresponding author
- Wang, Harris H.
- Isaacs, Farren J.
- ORCID
- Venue
- Nature
- Published
- 2009-07-26
- Volume
- 460
- Issue
- 7257
- Pages
- 894-898
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC4590770
- OpenAlex
- W2144779133
- Cited by
- 1,529
- References
- 32
- Citations by year
- 2026: 56 · 2025: 60 · 2024: 70 · 2023: 58 · 2022: 97 · 2021: 94 · 2020: 88 · 2019: 96 · 2018: 119 · 2017: 113 · 2016: 121 · 2015: 141 · 2014: 114 · 2013: 94 · 2012: 81
- FWCI
- 27.54
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Institutes of Health (DP5OD009172)
- National Defense Science and Engineering Graduate
- Hansjörg Wyss Institute for Biologically Inspired Engineering, Harvard University
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- accelerated evolution, directed evolution, genome editing, lycopene production, isoprenoid biosynthesis, Escherichia coli, synthetic DNA, metabolic engineering
- MeSH terms
- Lycopene, Alleles, Biotechnology, Carotenoids, Chromosomes, Bacterial, DNA, Escherichia coli, Pentosephosphates, Genetic Variation, Genome, Bacterial, Directed Molecular Evolution
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