GGAssembler: Precise and economical design and synthesis of combinatorial mutation libraries.
DNA library synthesis
Golden Gate assembly
biotechnology
combinatorial mutation libraries
Journal
Protein science : a publication of the Protein Society
ISSN: 1469-896X
Titre abrégé: Protein Sci
Pays: United States
ID NLM: 9211750
Informations de publication
Date de publication:
Oct 2024
Oct 2024
Historique:
revised:
21
08
2024
received:
06
03
2024
accepted:
26
08
2024
medline:
17
9
2024
pubmed:
17
9
2024
entrez:
16
9
2024
Statut:
ppublish
Résumé
Golden Gate assembly (GGA) can seamlessly generate full-length genes from DNA fragments. In principle, GGA could be used to design combinatorial mutation libraries for protein engineering, but creating accurate, complex, and cost-effective libraries has been challenging. We present GGAssembler, a graph-theoretical method for economical design of DNA fragments that assemble a combinatorial library that encodes any desired diversity. We used GGAssembler for one-pot in vitro assembly of camelid antibody libraries comprising >10
Substances chimiques
DNA
9007-49-2
Peptide Library
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e5169Subventions
Organisme : Dr. Barry Sherman Institute for Medicinal Chemistry
Organisme : Donation in memory of Sam Switzer
Organisme : Israel Science Foundation (1844)
Organisme : European Research Council through a Consolidator Award (815379)
Organisme : Volkswagen Foundation (94747)
Informations de copyright
© 2024 The Author(s). Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.
Références
Alejaldre L, Pelletier JN, Quaglia D. Methods for enzyme library creation: which one will you choose? BioEssays. 2021;43(8):2100052.
Alon N, Yuster R, Zwick U. Color‐coding. J ACM. 1995;42(4):844–856.
Andreou AI, Nakayama N. Mobius assembly: a versatile Golden‐Gate framework towards universal DNA assembly. PLoS One. 2018;13(1):e0189892.
Blecher‐Gonen R, Barnett‐Itzhaki Z, Jaitin D, Amann‐Zalcenstein D, Lara‐Astiaso D, Amit I. High‐throughput chromatin immunoprecipitation for genome‐wide mapping of in vivo protein‐DNA interactions and epigenomic states. Nat Protoc. 2013;8(3):539–554.
Bushnell B, Rood J, Singer E. BBMerge—accurate paired shotgun read merging via overlap. PLoS One. 2017;12(10):e0185056.
Chen L, Li X, Shi Y. The complexity of determining the rainbow vertex‐connection of a graph. Theor Comput Sci. 2011;412(35):4531–4535.
Choi H, Choi Y, Choi J, Lee AC, Yeom H, Hyun J, et al. Purification of multiplex oligonucleotide libraries by synthesis and selection. Nat Biotechnol. 2022;40(1):47–53.
Cock PJA, Antao T, Chang JT, Chapman BA, Cox CJ, Dalke A, et al. Biopython: freely available python tools for computational molecular biology and bioinformatics. Bioinformatics. 2009;25(11):1422–1423.
Daffern N, Francino‐Urdaniz IM, Baumer ZT, Whitehead TA. Standardizing cassette‐based deep mutagenesis by Golden Gate assembly. Biotechnol Bioeng. 2023;121:281–290. https://doi.org/10.1002/bit.28564
Daily J. Parasail: SIMD C library for global, semi‐global, and local pairwise sequence alignments. BMC Bioinformatics. 2016;17(February):81.
Dijkstra EW. A note on two problems in Connexion with graphs. Numer Math. 1959;1(1):269–271.
Engler C, Gruetzner R, Kandzia R, Marillonnet S. Golden Gate shuffling: a one‐pot DNA shuffling method based on type IIs restriction enzymes. PLoS One. 2009;4(5):e5553.
Engler C, Kandzia R, Marillonnet S. A one pot, one step, precision cloning method with high throughput capability. PLoS One. 2008;3(11):e3647.
Fowler DM, Araya CL, Fleishman SJ, Kellogg EH, Stephany JJ, Baker D, et al. High‐resolution mapping of protein sequence‐function relationships. Nat Methods. 2010;7(9):741–746.
Gietz RD, Schiestl RH. Large‐scale high‐efficiency yeast transformation using the LiAc/SS carrier DNA/PEG method. Nat Protoc. 2007;2(1):38–41.
Goldenzweig A, Goldsmith M, Hill SE, Gertman O, Laurino P, Ashani Y, et al. Automated structure‐ and sequence‐based design of proteins for high bacterial expression and stability. Mol Cell. 2016;63(2):337–346.
Granger BE, Pérez F. Jupyter: thinking and storytelling with code and data. Comput Sci Eng. 2021;23(2):7–14.
Guntas G, Purbeck C, Kuhlman B. Engineering a protein–protein interface using a computationally designed library. Proc Natl Acad Sci U S A. 2010;107(45):19296–19301.
Harris CR, Jarrod Millman K, van der Walt SJ, Gommers R, Virtanen P, Cournapeau D, et al. Array programming with NumPy. Nature. 2020;585(7825):357–362.
Hoch SY, Netzer R, Hakeny K, Fleishman SJ. GGAssembler library construction. 2023 https://doi.org/10.17504/protocols.io.81wgbxqkolpk/v3
Jacobs TM, Yumerefendi H, Kuhlman B, Leaver‐Fay A. SwiftLib: rapid degenerate‐codon‐library optimization through dynamic programming. Nucleic Acids Res. 2015;43(5):e34.
Khersonsky O, Lipsh R, Avizemer Z, Ashani Y, Goldsmith M, Leader H, et al. Automated design of efficient and functionally diverse enzyme repertoires. Mol Cell. 2018;72(1):178.e5–186.e5.
Kirby MB, Medina‐Cucurella AV, Baumer ZT, Whitehead TA. Optimization of multi‐site nicking mutagenesis for generation of large, user‐defined combinatorial libraries. Protein Eng Des Sel. 2021;34:gzab017.
Knuth DE. Dancing links. arXiv. 2000 https://doi.org/10.48550/arXiv.cs/0011047
Lipsh‐Sokolik R, Khersonsky O, Schröder SP, de Boer C, Hoch S‐Y, Davies GJ, et al. Combinatorial assembly and Design of Enzymes. Science. 2023;379(6628):195–201.
Lipsh‐Sokolik R, Fleishman SJ. Addressing epistasis in the design of protein function. Proc Natl Acad Sci U S A. 2024;121(34):e2314999121. https://doi.org/10.1073/pnas.2314999121
Listov D, Goverde CA, Correia BE, Fleishman SJ. Opportunities and challenges in design and optimization of protein function. Nat Rev Mol Cell Biol. 2024;25(8):639–653.
Lohman GJS, Bauer RJ, Nichols NM, Mazzola L, Bybee J, Rivizzigno D, et al. A high‐throughput assay for the comprehensive profiling of DNA ligase Fidelity. Nucleic Acids Res. 2016;44(2):e14.
Lozano L, Medaglia AL. On an exact method for the constrained shortest path problem. Comput Oper Res. 2013;40(1):378–384.
Lund S, Potapov V, Johnson SR, Buss J, Tanner NA. Highly parallelized construction of DNA from low‐cost oligonucleotide mixtures using data‐optimized assembly design and Golden Gate. ACS Synth Biol. 2024;13(3):745–751.
Markel U, Essani KD, Besirlioglu V, Schiffels J, Streit WR, Schwaneberg U. Advances in ultrahigh‐throughput screening for directed enzyme evolution. Chem Soc Rev. 2020;49(1):233–262.
Mayer H. Optimization of the EcoRI*‐activity of EcoRI endonuclease. FEBS Lett. 1978;90(2):341–344.
McKinney W. (2010). Data structures for statistical computing in Python. Proceedings of the 9th Python in Science Conference, 56–61. https://doi.org/10.25080/majora-92bf1922-00a
Öling D, Lan‐Chow‐Wing O, Martella A, Gilberto S, Chi J, Cooper E, et al. FRAGLER: a fragment recycler application enabling rapid and scalable modular DNA assembly. ACS Synth Biol. 2022;11(7):2229–2237.
Plesa C, Sidore AM, Lubock NB, Zhang D, Kosuri S. Multiplexed gene synthesis in emulsions for exploring protein functional landscapes. Science. 2018;359(6373):343–347.
Potapov V, Ong JL, Kucera RB, Langhorst BW, Bilotti K, Pryor JM, et al. Comprehensive profiling of four base overhang ligation Fidelity by T4 DNA ligase and application to DNA assembly. ACS Synth Biol. 2018;7(11):2665–2674.
Potapov V, Ong JL, Langhorst BW, Bilotti K, Cahoon D, Canton B, et al. A single‐molecule sequencing assay for the comprehensive profiling of T4 DNA ligase fidelity and bias during DNA end‐joining. Nucleic Acids Res. 2018;46(13):e79.
Pryor JM, Potapov V, Bilotti K, Pokhrel N, Lohman GJS. Rapid 40 kb genome construction from 52 parts through data‐optimized assembly design. ACS Synth Biol. 2022;11(6):2036–2042.
Pryor JM, Potapov V, Kucera RB, Bilotti K, Cantor EJ, Lohman GJS. Enabling one‐pot Golden Gate assemblies of unprecedented complexity using data‐optimized assembly design. PLoS One. 2020;15(9):e0238592.
Püllmann P, Ulpinnis C, Marillonnet S, Gruetzner R, Neumann S, Weissenborn MJ. Golden mutagenesis: an efficient multi‐site‐saturation mutagenesis approach by Golden Gate cloning with automated primer design. Sci Rep. 2019;9(1):10932.
Sarrion‐Perdigones A, Falconi EE, Zandalinas SI, Juárez P, Fernández‐del‐Carmen A, Granell A, et al. GoldenBraid: an iterative cloning system for standardized assembly of reusable genetic modules. PLoS One. 2011;6(7):e21622.
Sarrion‐Perdigones A, Vazquez‐Vilar M, Palací J, Castelijns B, Forment J, Ziarsolo P, et al. GoldenBraid 2.0: a comprehensive DNA assembly framework for plant synthetic biology. Plant Physiol. 2013;162(3):1618–1631.
Shimko TC, Fordyce PM, Orenstein Y. DeCoDe: degenerate codon design for complete protein‐coding DNA libraries. Bioinformatics. 2020;36(11):3357–3364.
Sidore AM, Plesa C, Samson JA, Lubock NB, Kosuri S. DropSynth 2.0: high‐fidelity multiplexed gene synthesis in emulsions. Nucleic Acids Res. 2020;48(16):e95.
Sikkema AP, Kasra Tabatabaei S, Lee Y‐J, Lund S, Lohman GJS. High‐complexity one‐pot Golden Gate assembly. Curr Protoc. 2023;3(9):e882.
Swainston N, Currin A, Green L, Breitling R, Day PJ, Kell DB. CodonGenie: optimised ambiguous codon design tools. PeerJ Comput Sci. 2017;3(July):e120.
Tretyachenko V, Voráček V, Souček R, Fujishima K, Hlouchová K. CoLiDe: combinatorial library design tool for probing protein sequence space. Bioinformatics. 2020;37(4):482–489. https://doi.org/10.1093/bioinformatics/btaa804
Treynor TP, Vizcarra CL, Nedelcu D, Mayo SL. Computationally designed libraries of fluorescent proteins evaluated by preservation and diversity of function. Proc Natl Acad Sci U S A. 2007;104(1):48–53.
Uchański T, Zögg T, Yin J, Yuan D, Wohlkönig A, Fischer B, et al. An improved yeast surface display platform for the screening of Nanobody immune libraries. Sci Rep. 2019;9(1):382.
van der Walt S, Colbert SC, Varoquaux G. The NumPy Array: a structure for efficient numerical computation. Comput Sci Eng. 2011;13(2):22–30.
Vazquez‐Vilar M, Quijano‐Rubio A, Fernandez‐Del‐Carmen A, Sarrion‐Perdigones A, Ochoa‐Fernandez R, Ziarsolo P, et al. GB3.0: a platform for plant bio‐design that connects functional DNA elements with associated biological data. Nucleic Acids Res. 2017;45(4):2196–2209.
Weber E, Engler C, Gruetzner R, Werner S, Marillonnet S. A modular cloning system for standardized assembly of multigene constructs. PLoS One. 2011;6(2):e16765.
Weinstein JY, Martí‐Gómez C, Lipsh‐Sokolik R, Hoch SY, Liebermann D, Nevo R, et al. Designed active‐site library reveals thousands of functional GFP variants. Nat Commun. 2023;14(1):2890.
Whitehead TA, Baker D, Fleishman SJ. Computational design of novel protein binders and experimental affinity maturation. Methods Enzymol. 2013;523:1–19.
Whitehead TA, Chevalier A, Song Y, Dreyfus C, Fleishman SJ, De Mattos C, et al. Optimization of affinity, specificity and function of designed influenza inhibitors using deep sequencing. Nat Biotechnol. 2012;30(6):543–548.
Wójcik M, Telzerow A, Quax WJ, Boersma YL. High‐throughput screening in protein engineering: recent advances and future perspectives. Int J Mol Sci. 2015;16(10):24918–24945.
Wrenbeck EE, Klesmith JR, Stapleton JA, Adeniran A, Tyo KEJ, Whitehead TA. Plasmid‐based one‐pot saturation mutagenesis. Nat Methods. 2016;13(11):928–930.
Yamamoto Y, Terai T, Kumachi S, Nemoto N. In vitro construction of large‐scale DNA libraries from fragments containing random regions using Deoxyinosine‐containing oligonucleotides and endonuclease V. ACS Comb Sci. 2020;22(4):165–171.