The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“(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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
In vitro selection of RNA molecules that bind specific ligands
Ellington, A. D., & Szostak, J. W. (1990) · Nature · doi:10.1038/346818a0 · Cited by 9,845 · cited 1×
“7); (2) induce cells for allelic replacement via 42 uC heat shock for 15 min; (3) chill cells at 4 uC to halt cellular metabolism; (4) wash cells through 15–20 iterations of filtration and resuspension with dH2O; (5) mix cell suspension and synthetic DNA; (6) deliver DNA into cells by electroporation; and (7) resuspen…”
BackgroundEnvironmental genome shotgun sequencing of the sargasso sea
Venter, J. C., Remington, K., Heidelberg, J. F., Halpern, A. L., Rusch, D., Eisen, J. A., Wu, D., Paulsen, I., Nelson, K. E., Nelson, W., et al. (2004) · Science · doi:10.1126/science.1093857 · Cited by 4,376 · cited 3×
“The device then executed repeatedly and continuously through the following steps: (1) grow cells at 30 uC to a pre-set density (that is, OD600 nm of 0.”
BackgroundMethodAn efficient recombination system for chromosome engineering in Escherichia coli
Yu, D., Ellis, H. M., Lee, E.-C., Jenkins, N. A., Copeland, N. G., & Court, D. L. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.100127597 · Cited by 1,688
Comparative Metagenomics of Microbial Communities
Tringe, S. G., von Mering, C., Kobayashi, A., Salamov, A. A., Chen, K., Chang, H. W., Podar, M., Short, J. M., Mathur, E. J., Detter, J. C., et al. (2005) · Science · doi:10.1126/science.1107851 · Cited by 1,677 · cited 3×
“Oligonucleotides used in the MAGE process contained the following modifications: (1) 30–110 bp in length for optimization experiments; (2) different numbers of phosphorothioated bases; and (3) degenerate nucleotides as described elsewhere in this paper.”
BackgroundMethodAccurate Multiplex Polony Sequencing of an Evolved Bacterial Genome
Shendure, J., Porreca, G. J., Reppas, N. B., Lin, X., McCutcheon, J. P., Rosenbaum, A. M., Wang, M. D., Zhang, K., Mitra, R. D., & Church, G. M. (2005) · Science · doi:10.1126/science.1117389 · Cited by 1,402
Self-citationEvolution Experiments with Microorganisms: The Dynamics and Genetic Bases of Adaptation
Elena, S. F., & Lenski, R. E. (2003) · Nature Reviews Genetics · doi:10.1038/nrg1088 · Cited by 1,386 · cited 3×
“Oligonucleotides used in the MAGE process contained the following modifications: (1) 30–110 bp in length for optimization experiments; (2) different numbers of phosphorothioated bases; and (3) degenerate nucleotides as described elsewhere in this paper.”
BackgroundMethodComplete Chemical Synthesis, Assembly, and Cloning of a Mycoplasma genitalium Genome
Gibson, D. G., Benders, G. A., Andrews-Pfannkoch, C., Denisova, E. A., Baden-Tillson, H., Zaveri, J., Stockwell, T. B., Brownley, A., Thomas, D. W., Algire, M. A., et al. (2008) · Science · doi:10.1126/science.1151721 · Cited by 1,243
A new logic for DNA engineering using recombination in Escherichia coli
Zhang, Y., Buchholz, F., Muyrers, J. P. P., & Stewart, A. F. (1998) · Nature Genetics · doi:10.1038/2417 · Cited by 1,225
Randomization of genes by PCR mutagenesis.Preprint
Cadwell, R. C., & Joyce, G. F. (1992) · Genome Research · doi:10.1101/gr.2.1.28 · Cited by 1,082
DINAMelt web server for nucleic acid melting prediction
Markham, N. R., & Zuker, M. (2005) · Nucleic Acids Research · doi:10.1093/nar/gki591 · Cited by 947
Cited by
Sorted by citations
Repurposing CRISPR as an RNA-Guided Platform for Sequence-Specific Control of Gene Expression
Qi, L. S., Larson, M. H., Gilbert, L. A., Doudna, J. A., Weissman, J. S., Arkin, A. P., & Lim, W. A. (2013) · Cell · doi:10.1016/j.cell.2013.02.022 · Cited by 5,016
“coli MG1655 strain was transformed with a temperature-sensitive plasmid pKD46 that contained l-Red recombination proteins (Exo, Beta, and Gam) (Wang et al., 2009).”
MethodCreation of a Bacterial Cell Controlled by a Chemically Synthesized Genome
Gibson, D. G., Glass, J. I., Lartigue, C., Noskov, V. N., Chuang, R.-Y., Algire, M. A., Benders, G. A., Montague, M. G., Ma, L., Moodie, M. M., et al. (2010) · Science · doi:10.1126/science.1190719 · Cited by 2,638
Isoprenoid Pathway Optimization for Taxol Precursor Overproduction in Escherichia coli
Ajikumar, P. K., Xiao, W., Tyo, K. E. J., Wang, Y., Simeon, F., Leonard, E., Mucha, O., Too, H., Pfeifer, B. A., & Stephanopoulos, G. N. (2010) · Science · doi:10.1126/science.1191652 · Cited by 1,681
Synthetic biology: applications come of age
Khalil, A. S., & Collins, J. J. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2775 · Cited by 1,413
“In an alternative method of relieving regulatory control over the large number of DXP pathway components, Wang et al.121 diversified and, as a result, optimized the native DXP biosynthetic pathway in E. coli (see the figure, part a).”
MethodMultigene editing in the Escherichia coli genome via the CRISPR-Cas9 system
Jiang, Y., Chen, B., Duan, C., Sun, B., Yang, J., & Yang, S. (2015) · Applied and Environmental Microbiology · doi:10.1128/aem.04023-14 · Cited by 1,362
“The recombination efficiency might be improved by using ssDNA as the donor DNA, as -Red-like proteins also facilitate the recombination of smaller ssDNA fragments, such as those used in MAGE.”
MethodInfluentialMethods for the directed evolution of proteins
Packer, M. S., & Liu, D. R. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3927 · Cited by 1,002
A brief history of synthetic biology
Cameron, D. E., Bashor, C. J., & Collins, J. J. (2014) · Nature Reviews Microbiology · doi:10.1038/nrmicro3239 · Cited by 988
Genomically Recoded Organisms Expand Biological Functions
Lajoie, M. J., Rovner, A. J., Goodman, D. B., Aerni, H. R., Haimovich, A. D., Kuznetsov, G., Mercer, J. A. M., Wang, H. H., Carr, P. A., Mosberg, J. A., et al. (2013) · Science · doi:10.1126/science.1241459 · Cited by 874
Self-citationManufacturing Molecules Through Metabolic Engineering
Keasling, J. D. (2010) · Science · doi:10.1126/science.1193990 · Cited by 829
Adaptive laboratory evolution—Principles and applications for biotechnology
Dragosits, M., & Mattanovich, D. (2013) · Microbial Cell Factories · doi:10.1186/1475-2859-12-64 · Cited by 827
“coli and accelerate evolution [180].”
Systems metabolic engineering of microorganisms for natural and non-natural chemicals
Lee, J. W., Na, D., Park, J. M., Lee, J., Choi, S., & Lee, S. Y. (2012) · Nature Chemical Biology · doi:10.1038/nchembio.970 · Cited by 736
Directed Evolution: Methodologies and Applications
Wang, Y., Xue, P., Cao, M., Yu, T., Lane, S., & Zhao, H. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00260 · Cited by 745
A system for the continuous directed evolution of biomolecules
Esvelt, K. M., Carlson, J. C., & Liu, D. R. (2011) · Nature · doi:10.1038/nature09929 · Cited by 694
Microbial 2,3-butanediol production: A state-of-the-art review
Ji, X., Huang, H., & Ouyang, P. (2011) · Biotechnology Advances · doi:10.1016/j.biotechadv.2011.01.007 · Cited by 694
Semi-synthetic artemisinin: a model for the use of synthetic biology in pharmaceutical development
Paddon, C. J., & Keasling, J. D. (2014) · Nature Reviews Microbiology · doi:10.1038/nrmicro3240 · Cited by 675
Metabolic engineering of Escherichia coli using synthetic small regulatory RNAs
Na, D., Yoo, S. M., Chung, H., Park, H., Park, J. H., & Lee, S. Y. (2013) · Nature Biotechnology · doi:10.1038/nbt.2461 · Cited by 623
Syntrophic exchange in synthetic microbial communities
Mee, M. T., Collins, J. J., Church, G. M., & Wang, H. H. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1405641111 · Cited by 619
“coli derivative of MG1655, which carried an integrated, temperatureinducible, λ-Red prophage for recombineering (37).”
BackgroundSelf-citationSystems strategies for developing industrial microbial strains
Lee, S. Y., & Kim, H. U. (2015) · Nature Biotechnology · doi:10.1038/nbt.3365 · Cited by 600
Choi, K. R., Jang, W. D., Yang, D., Cho, J. S., Park, D., & Lee, S. Y. (2019) · Trends in biotechnology · doi:10.1016/j.tibtech.2019.01.003 · Cited by 579
Precise Manipulation of Chromosomes in Vivo Enables Genome-Wide Codon Replacement
Isaacs, F. J., Carr, P. A., Wang, H. H., Lajoie, M. J., Sterling, B., Kraal, L., Tolonen, A. C., Gianoulis, T. A., Goodman, D. B., Reppas, N. B., et al. (2011) · Science · doi:10.1126/science.1205822 · Cited by 557
Self-citationIndustrial biomanufacturing: The future of chemical production
Clomburg, J. M., Crumbley, A. M., & González, R. (2017) · Science · doi:10.1126/science.aag0804 · Cited by 565
“Genome engineering technologies for making mutations to microbial genes and genomes in a targeted, multiplexed manner, such as CRISPR/ Cas9-based systems (79–81) andmultiplexed automated genome engineering (82), are becoming standard tools for model industrial organisms.”
Total Synthesis of a Functional Designer Eukaryotic Chromosome
Annaluru, N., Muller, H., MITCHELL, L. A., Ramalingam, S., Stracquadanio, G., Richardson, S. M., Dymond, J. S., Kuang, Z., Scheifele, L. Z., Cooper, E. M., et al. (2014) · Science · doi:10.1126/science.1249252 · Cited by 547
Revisiting lab-on-a-chip technology for drug discovery
Neužil, P., Giselbrecht, S., Länge, K., Huang, T. J., & Manz, A. (2012) · Nature Reviews Drug Discovery · doi:10.1038/nrd3799 · Cited by 495
Metabolic engineering of Escherichia coli using CRISPR–Cas9 meditated genome editing
Li, Y., Lin, Z., Huang, C., Zhang, Y., Wang, Z., Ya-jie Tang, A., Chen, T., & Zhao, X. (2015) · Metabolic Engineering · doi:10.1016/j.ymben.2015.06.006 · Cited by 480
“Multiplex recombineering techniques such as MAGE and TRMR can be more powerful when working in combination with CRISPR (Esvelt and Wang, 2013).”
BackgroundMethodInfluentialSynthetic biology to access and expand nature's chemical diversity
Smanski, M. J., Zhou, H. L., Claesen, J., Shen, B., Fischbach, M. A., & Voigt, C. A. (2016) · Nature Reviews Microbiology · doi:10.1038/nrmicro.2015.24 · Cited by 487
Biocontainment of genetically modified organisms by synthetic protein design
Mandell, D. J., Lajoie, M. J., Mee, M. T., Takeuchi, R., Kuznetsov, G., Norville, J. E., Gregg, C. J., Stoddard, B. L., & Church, G. M. (2015) · Nature · doi:10.1038/nature14121 · Cited by 483
Self-citationMicrobial production of vitamin B12: a review and future perspectives
Fang, H., Kang, J., & Zhang, D. (2017) · Microbial Cell Factories · doi:10.1186/s12934-017-0631-y · Cited by 488
“Multiplex automated genome engineering (MAGE) can be used for genome-scale optimization of gene expression on the chromosome [61].”
MethodSynthetic DNA Synthesis and Assembly: Putting the Synthetic in Synthetic Biology
Hughes, R. A., & Ellington, A. D. (2017) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a023812 · Cited by 411
Synthetic biology and the development of tools for metabolic engineering
Keasling, J. D. (2012) · Metabolic Engineering · doi:10.1016/j.ymben.2012.01.004 · Cited by 430
Cell-free synthetic biology: Thinking outside the cell
Hodgman, C. E., & Jewett, M. C. (2011) · Metabolic Engineering · doi:10.1016/j.ymben.2011.09.002 · Cited by 432
Multiplex metabolic pathway engineering using CRISPR/Cas9 in Saccharomyces cerevisiae
Jakočiūnas, T., Bonde, I., Herrgård, M. J., Harrison, S. J., Kristensen, M., Pedersen, L. E., Jensen, M. K., & Keasling, J. D. (2015) · Metabolic Engineering · doi:10.1016/j.ymben.2015.01.008 · Cited by 422
Composability of regulatory sequences controlling transcription and translation in Escherichia coli
Kosuri, S., Goodman, D. B., Cambray, G., Mutalik, V. K., Gao, Y., Arkin, A. P., Endy, D., & Church, G. M. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1301301110 · Cited by 392
Self-citationGrowth of E. coli on formate and methanol via the reductive glycine pathway
Kim, S., Lindner, S. N., Aslan, S., Yishai, O., Wenk, S., Schann, K., & Bar‐Even, A. (2020) · Nature Chemical Biology · doi:10.1038/s41589-020-0473-5 · Cited by 385
CRISPR–Cas9-assisted recombineering in Lactobacillus reuteri
Oh, J., & van Pijkeren, J. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku623 · Cited by 398
“Also, our work combined with current developments in CRISPR–Cas9 genome editing makes the application of MAGE in lactobacilli and bifidobacteria tantalizing, yet not unreasonable (45,46).”
BackgroundEscherichia coli as a host for metabolic engineering
Pontrelli, S., Chiu, T., Lan, E. I., Chen, F. Y.-H., Chang, P., & Liao, J. C. (2018) · Metabolic Engineering · doi:10.1016/j.ymben.2018.04.008 · Cited by 397
Biotechnological domestication of pseudomonads using synthetic biology
Nikel, P. I., Martínez‐García, E., & de Lorenzo, V. (2014) · Nature Reviews Microbiology · doi:10.1038/nrmicro3253 · Cited by 372
Recoded organisms engineered to depend on synthetic amino acids
Rovner, A. J., Haimovich, A. D., Katz, S. R., Li, Z., Grome, M. W., Gassaway, B. M., Amiram, M., Patel, J. R., Gallagher, R. R., Rinehart, J., et al. (2015) · Nature · doi:10.1038/nature14095 · Cited by 366
“Strains were grown to mid-log phase in 1 mL of permissive LB, and MAGE was performed as described 12 with modifications described here.”
Self-citationNext-generation synthetic gene networks
Lu, T. K., Khalil, A. S., & Collins, J. J. (2009) · Nature Biotechnology · doi:10.1038/nbt.1591 · Cited by 365
Garst, A. D., Bassalo, M. C., Pines, G., Lynch, S. A., Halweg‐Edwards, A. L., Liu, R., Liang, L., Wang, Z., Zeitoun, R. I., Alexander, W. G., et al. (2016) · Nature Biotechnology · doi:10.1038/nbt.3718 · Cited by 361
Bioremediation 3.0: Engineering pollutant-removing bacteria in the times of systemic biology
Dvořák, P., Nikel, P. I., Damborský, J., & de Lorenzo, V. (2017) · Biotechnology Advances · doi:10.1016/j.biotechadv.2017.08.001 · Cited by 364
“This problem is now being challenged by new protocols that profit from the type II bacterial Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and CRISPRassociated protein (Cas), Multiple Automated Genome Editing (MAGE), and combinations thereof (Barrangou and van Pijkeren, 2016; Wang et al., 2009).”
MethodCRISPR RNA-guided integrases for high-efficiency, multiplexed bacterial genome engineering
Vo, P. L. H., Ronda, C., Klompe, S. E., Chen, E. E., Acree, C., Wang, H. H., & Sternberg, S. H. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-00745-y · Cited by 339
Self-citationCRISPR-guided DNA polymerases enable diversification of all nucleotides in a tunable window
Halperin, S. O., Tou, C. J., Wong, E. B., Modavi, C., Schaffer, D. V., & Dueber, J. E. (2018) · Nature · doi:10.1038/s41586-018-0384-8 · Cited by 348
Cell‐free metabolic engineering: Biomanufacturing beyond the cell
Dudley, Q. M., Karim, A. S., & Jewett, M. C. (2014) · Biotechnology Journal · doi:10.1002/biot.201400330 · Cited by 342
“Moreover, strain modification techniques, such as MAGE [122], could be leveraged to add protease cleavage sites [23] or affinity tags [123] to essential enzymes; this would allow selective degradation or physical removal of unwanted pathways critical for growth.”
BackgroundCalero, P., & Nikel, P. I. (2018) · Microbial Biotechnology · doi:10.1111/1751-7915.13292 · Cited by 331
“, 2013) and multiplex automated genome editing (MAGE; Wang et al., 2009) have enormously helped to boost our ability to construct engineered E.”
BackgroundSynthesis and Accumulation of Aromatic Aldehydes in an Engineered Strain of Escherichia coli
Kunjapur, A. M., Tarasova, Y., & Prather, K. L. J. (2014) · Journal of the American Chemical Society · doi:10.1021/ja506664a · Cited by 330
Engineering an allosteric transcription factor to respond to new ligands
Taylor, N. D., Garruss, A. S., Moretti, R., Chan, S., Arbing, M. A., Cascio, D., Rogers, J. K., Isaacs, F. J., Kosuri, S., Baker, D., et al. (2016) · Nature Methods · doi:10.1038/nmeth.3696 · Cited by 328
Self-citationCombinatorial metabolic engineering using an orthogonal tri-functional CRISPR system
Lian, J., HamediRad, M., Hu, S., & Zhao, H. (2017) · Nature Communications · doi:10.1038/s41467-017-01695-x · Cited by 319
The future of metabolic engineering and synthetic biology: Towards a systematic practice
Yadav, V. G., Mey, M. D., Lim, C. G., Ajikumar, P. K., & Stephanopoulos, G. N. (2012) · Metabolic Engineering · doi:10.1016/j.ymben.2012.02.001 · Cited by 323
“(Wang et al., 2009).”
MethodHigh-Throughput Metabolic Engineering: Advances in Small-Molecule Screening and Selection
Dietrich, J. A., McKee, A. E., & Keasling, J. D. (2010) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-062608-095938 · Cited by 333
Genome‐scale engineering for systems and synthetic biology
Esvelt, K. M., & Wang, H. H. (2013) · Molecular Systems Biology · doi:10.1038/msb.2012.66 · Cited by 324
“Iterative cycling enables further multiplexing and enrichment of mutants that are otherwise found at low frequencies in the population, which can be automated (Wang et al, 2009).”
BackgroundMethodInfluentialSelf-citationProgrammable autonomous synthesis of single-stranded DNA
Kishi, J. Y., Schaus, T. E., Gopalkrishnan, N., Xuan, F., & Yin, P. (2017) · Nature Chemistry · doi:10.1038/nchem.2872 · Cited by 321
Review: Engineering of thermostable enzymes for industrial applications
Rigoldi, F., Donini, S., Redaelli, A. C. L., Parisini, E., & Gautieri, A. (2018) · APL Bioengineering · doi:10.1063/1.4997367 · Cited by 315
DNA assembly for synthetic biology: from parts to pathways and beyond
Ellis, T., Adie, T., & Baldwin, G. S. (2011) · Integrative Biology · doi:10.1039/c0ib00070a · Cited by 307
Scalable, Continuous Evolution of Genes at Mutation Rates above Genomic Error Thresholds
Ravikumar, A., Arzumanyan, G. A., Obadi, M. K. A., Javanpour, A. A., & Liu, C. C. (2018) · Cell · doi:10.1016/j.cell.2018.10.021 · Cited by 305
Horwitz, A. A., Walter, J. M., Schubert, M. G., Kung, S. H., Hawkins, K. M., Platt, D., Hernday, A. D., Mahatdejkul-Meadows, T., Szeto, W., Chandran, S. S., et al. (2015) · Cell Systems · doi:10.1016/j.cels.2015.02.001 · Cited by 288
“coli, the yeast equivalent (YOGE) functions at a much lower efficiency (Wang et al., 2009; DiCarlo et al., 2013b).”
BackgroundEngineering microbes for tolerance to next-generation biofuels
Dunlop, M. J. (2011) · Biotechnology for Biofuels · doi:10.1186/1754-6834-4-32 · Cited by 293
“In addition, recent advances in recombineering methodologies introduce powerful tools for rapid introduction of mutations and subsequent analysis [47-49].”
BackgroundFast track assembly of multigene constructs using Golden Gate cloning and the MoClo system
Werner, S., Engler, C., Weber, E., Gruetzner, R., & Marillonnet, S. (2012) · Bioengineered · doi:10.4161/bbug.3.1.18223 · Cited by 293
“Automated Genome Engineering (MAGE) can also be very useful to introduce large amount of genetic variation at multiple selected positions in a genome.(17) In fact, MoClo and MAGE are complementary technologies (for use in prokaryotes), since MoClo can be used to combine multiple genes from one or several source organi…”
BackgroundDesign, synthesis, and testing toward a 57-codon genome
Ostrov, N., Landon, M., Güell, M., Kuznetsov, G., Teramoto, J., Cervantes, N., Zhou, M. H., Singh, K., Napolitano, M. G., Moosburner, M., et al. (2016) · Science · doi:10.1126/science.aaf3639 · Cited by 287
Self-citationBricks and blueprints: methods and standards for DNA assembly.
Casini, A., Storch, M., Baldwin, G. S., & Ellis, T. (2015) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm4014 · Cited by 286
Rapid profiling of a microbial genome using mixtures of barcoded oligonucleotides
Warner, J. R., Reeder, P. J., Karimpour‐Fard, A., Woodruff, L. B. A., & Gill, R. T. (2010) · Nature Biotechnology · doi:10.1038/nbt.1653 · Cited by 284
“Recently, a recombineering-based method, called MAGE, was reporte”
MethodAmiram, M., Haimovich, A. D., Fan, C., Wang, Y., Aerni, H. R., Ntai, I., Moonan, D. W., Ma, N. J., Rovner, A. J., Hong, S. H., et al. (2015) · Nature Biotechnology · doi:10.1038/nbt.3372 · Cited by 283
Self-citationMicrobial laboratory evolution in the era of genome‐scale science
Conrad, T. M., Lewis, N. E., & Palsson, B. Ø. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.42 · Cited by 282
“Thus, they may be used to study gene function or as raw material for ‘accelerated evolution’ (Wang et al, 2009).”
BackgroundSynthetic biology in mammalian cells: next generation research tools and therapeutics
Lienert, F., Lohmueller, J. J., Garg, A. D., & Silver, P. A. (2014) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3738 · Cited by 283
Evolution-guided optimization of biosynthetic pathways
Raman, S., Rogers, J. K., Taylor, N. D., & Church, G. M. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1409523111 · Cited by 278
“MAGE (6) mutagenesis targeted 20 endogenous genes (SI Appendix, Table S3) for expression and coding changes in this strain.”
BackgroundMethodInfluentialSelf-citationFoundations for the design and implementation of synthetic genetic circuits
Slusarczyk, A. L., Lin, A. Y., & Weiss, R. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3227 · Cited by 276
Continuous directed evolution of aminoacyl-tRNA synthetases
Bryson, D. I., Fan, C., Guo, L., Miller, C. A., Söll, D. G., & Liu, D. R. (2017) · Nature Chemical Biology · doi:10.1038/nchembio.2474 · Cited by 267
LaCroix, R. A., Sandberg, T. E., O'Brien, E. J., Utrilla, J., Ebrahim, A., Guzmán, G. I., Szubin, R., Palsson, B. Ø., & Feist, A. M. (2014) · Applied and Environmental Microbiology · doi:10.1128/aem.02246-14 · Cited by 254
“Despite the growing availability of genome engineering tools (22, 25, 26), determining causality is still a time-consuming process.”
BackgroundPyne, M. E., Moo‐Young, M., Chung, D. A., & Chou, C.-H. P. (2015) · Applied and Environmental Microbiology · doi:10.1128/aem.01248-15 · Cited by 263
“3 billion genomic mutants per day (13).”
Multi‐input CRISPR/Cas genetic circuits that interface host regulatory networks
Nielsen, A. A. K., & Voigt, C. A. (2014) · Molecular Systems Biology · doi:10.15252/msb.20145735 · Cited by 259
Integrating Biological Redesign: Where Synthetic Biology Came From and Where It Needs to Go
Way, J. C., Collins, J. J., Keasling, J. D., & Silver, P. A. (2014) · Cell · doi:10.1016/j.cell.2014.02.039 · Cited by 259
“A number of methods for genome editing have surfaced in the last 10 years, making major changes in genomic DNA faster and more predictable (Wang et al., 2009; Gaj et al., 2013).”
The no-SCAR (Scarless Cas9 Assisted Recombineering) system for genome editing in Escherichia coli
Reisch, C. R., & Prather, K. L. J. (2015) · Scientific Reports · doi:10.1038/srep15096 · Cited by 250
Codon usage of highly expressed genes affects proteome-wide translation efficiency
Frumkin, I., Lajoie, M. J., Gregg, C. J., Hornung, G., Church, G. M., & Pilpel, Y. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1719375115 · Cited by 247
Self-citationFunctional genomics of the rapidly replicating bacterium Vibrio natriegens by CRISPRi
Lee, H. H., Ostrov, N., Wong, B. G., Gold, M. A., Khalil, A. S., & Church, G. M. (2019) · Nature Microbiology · doi:10.1038/s41564-019-0423-8 · Cited by 251
Self-citationLázár, V., Nagy, I., Spohn, R., Csörgő, B., Györkei, Á., Nyerges, Á., Horváth, B., Vörös, A., Busa‐Fekete, R., Hrtyan, M., et al. (2014) · Nature Communications · doi:10.1038/ncomms5352 · Cited by 250
Fast, A. G., & Papoutsakis, E. T. (2012) · Current Opinion in Chemical Engineering · doi:10.1016/j.coche.2012.07.005 · Cited by 251
Recent advances in systems metabolic engineering tools and strategies
Chae, T. U., Choi, S. Y., Kim, J. W., Ko, Y., & Lee, S. Y. (2017) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2017.06.007 · Cited by 251
Reprogramming the genetic code
de la Torre, D., & Chin, J. W. (2020) · Nature Reviews Genetics · doi:10.1038/s41576-020-00307-7 · Cited by 248
Realizing the potential of synthetic biology
Church, G. M., Elowitz, M. B., Smolke, C. D., Voigt, C. A., & Weiss, R. (2014) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3767 · Cited by 226
Self-citationSynthetic Biology: An Emerging Engineering Discipline
Cheng, A. A., & Lu, T. K. (2012) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-071811-150118 · Cited by 241
“(47) developed multiplex automated genome engineering (MAGE), a method of generating substantial sequence diversity on a genomewide scale.”
BackgroundCustomized optimization of metabolic pathways by combinatorial transcriptional engineering
Du, J., Yuan, Y., Si, T., Lian, J., & Zhao, H. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks549 · Cited by 239
“Recently, a number of innovative approaches have been developed that balance metabolic flux at a global level through either perturbation of global transcription machinery (13), genomic-scale mapping of fitness altering genes (14,15) or multiplex automated genome engineering (16).”
Biosensor-based engineering of biosynthetic pathways
Rogers, J. K., Taylor, N. D., & Church, G. M. (2016) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2016.03.005 · Cited by 234
“were able to optimize the bioproduction of lycopene, a bright red carotenoid, by generating an estimated 15 billion unique genetic variants and visually screening almost 10(6) of these to identify mutants with the highest reported production titer in just three days [10].”
Self-citationWong, B. G., Mancuso, C. P., Kiriakov, S., Bashor, C. J., & Khalil, A. S. (2018) · Nature Biotechnology · doi:10.1038/nbt.4151 · Cited by 237
“These include functional genomic library screening and selection 4,5 , characterization of natural and synthetic cellular systems 6–8 , and directed evolution to either study evolutionary processes 9–11 or evolve new functions 12–15 .”
BackgroundEfficient search, mapping, and optimization of multi-protein genetic systems in diverse bacteria
Farasat, I., Kushwaha, M., Collens, J., Easterbrook, M., Guido, M., & Salis, H. M. (2014) · Molecular Systems Biology · doi:10.15252/msb.20134955 · Cited by 235
“(Wang et al , 2009), targeting its lacI-lacZYA locus and controlling lacZ protein expression levels (Fig 3B).”
BackgroundMethodInfluentialSynthetic microbial consortia: from systematic analysis to construction and applications
Song, H., Ding, M., Jia, X., Ma, Q., & Yuan, Y. (2014) · Chemical Society Reviews · doi:10.1039/c4cs00114a · Cited by 235
New applications of synthetic biology tools for cyanobacterial metabolic engineering
Santos-Merino, M., Singh, A. K., & Ducat, D. C. (2019) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2019.00033 · Cited by 222
Microbial production of building block chemicals and polymers
Lee, J. W., Kim, H. U., Choi, S., Yi, J., & Lee, S. Y. (2011) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2011.02.011 · Cited by 240
Synthetic biosensors for precise gene control and real-time monitoring of metabolites
Rogers, J. K., Guzman, C. D., Taylor, N. D., Raman, S., Anderson, K. E., & Church, G. M. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv616 · Cited by 230
“All standard induction plasmids contained the rrnB strong terminator (47) followed by the inducible promoter and the strong g10 RBS (48) ‘tttaactttaagaaggagatatacat,’ driving the expression of sfGFP (49) (except in the case of CdaR which used the native RBS).”
BackgroundInfluentialSelf-citationGenome-scale promoter engineering by coselection MAGE
Wang, H. H., Kim, H., Cong, L., Jeong, J., Bang, D., & Church, G. M. (2012) · Nature Methods · doi:10.1038/nmeth.1971 · Cited by 230
“Using the MAGE-competent EcNR2 strain 2 , we first removed known feedback regulation and allosteric inhibition associated with Trp biosynthesis 7–10 , which involved nonsense inactivation of trpR , P148L mutation in aroF , M293T mutation in trpE , and D146N mutation in aroG .”
Self-citationCRMAGE: CRISPR Optimized MAGE Recombineering
Ronda, C., Pedersen, L. E., Sommer, M. O. A., & Nielsen, A. T. (2016) · Scientific Reports · doi:10.1038/srep19452 · Cited by 228
High efficiency recombineering in lactic acid bacteria
van Pijkeren, J., & Britton, R. A. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks147 · Cited by 226
“This opens up the possibility to apply multiplex automated genome engineering (MAGE) (59) and trackable multiplex recombineering (TRMR) (60), elegant systems to perform genome-wide genetic engineering.”
BackgroundChen, X., Zhou, L., Tian, K., Kumar, A., Singh, S., Prior, B. A., & Wang, Z. (2013) · Biotechnology Advances · doi:10.1016/j.biotechadv.2013.02.009 · Cited by 236
“On the other hand, advances in genome sequencing, functional genomics, genome engineering and omics have had a substantial impact on our understanding of biosynthesis pathways and discovery of novel pathways and metabolites, and new functions of enzymes in relevant organisms (Posfai et al., 2006; Wang et al., 2009).”
BackgroundMetabolic engineering of microorganisms for the synthesis of plant natural products
Marienhagen, J., & Bott, M. H. (2012) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2012.06.001 · Cited by 222
López‐Gallego, F., & Schmidt‐Dannert, C. (2009) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2009.11.023 · Cited by 219
“Church and co-workers describe multiplex automated genome engineering (MAGE) by which via successive rounds of oligo-mediated allelic replacement increasing genetic diversity can be introduced simultaneously at dozens of predefined genetic loci [28].”
BackgroundCRISPR/Cas9 advances engineering of microbial cell factories
Jakočiūnas, T., Jensen, M. K., & Keasling, J. D. (2015) · Metabolic Engineering · doi:10.1016/j.ymben.2015.12.003 · Cited by 225
Deaminase-mediated multiplex genome editing in Escherichia coli
Banno, S., Nishida, K., Arazoe, T., Mitsunobu, H., & Kondo, A. (2018) · Nature Microbiology · doi:10.1038/s41564-017-0102-6 · Cited by 213
Nyerges, Á., Csörgő, B., Nagy, I., Bálint, B., Bihari, P., Lázár, V., Apjok, G., Umenhoffer, K., Bogos, B., Pósfai, G., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1520040113 · Cited by 217
“Bacterial recombineering has been optimized toward multiplexing and automation, resulting in MAGE (5).”
MethodInfluentialExpression-level optimization of a multi-enzyme pathway in the absence of a high-throughput assay
Lee, M. E., Aswani, A. J., Han, A. S., Tomlin, C. J., & Dueber, J. E. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt809 · Cited by 209
“coli were optimized using multiplex automated genome engineering (21).”
MethodDevelopment of potent in vivo mutagenesis plasmids with broad mutational spectra
Badran, A. H., & Liu, D. R. (2015) · Nature Communications · doi:10.1038/ncomms9425 · Cited by 211
Metabolic Engineering: Methodologies and Applications
Volk, M., Tran, V. G., Tan, S., Mishra, S., Fatma, Z., Boob, A. G., Li, H., Xue, P., Martin, T. A., & Zhao, H. (2022) · Chemical Reviews · doi:10.1021/acs.chemrev.2c00403 · Cited by 217
Reinvigorating natural product combinatorial biosynthesis with synthetic biology
Kim, E., Moore, B. S., & Yoon, Y. J. (2015) · Nature Chemical Biology · doi:10.1038/nchembio.1893 · Cited by 208
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review