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Woodruff LBA, Gorochowski TE, Roehner N, Mikkelsen TS, Densmore D, Gordon DB, Nicol R, Voigt CA. Registry in a tube: multiplexed pools of retrievable parts for genetic design space exploration. Nucleic Acids Res 2017; 45:1553-1565. [PMID: 28007941 PMCID: PMC5388403 DOI: 10.1093/nar/gkw1226] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Accepted: 11/22/2016] [Indexed: 11/14/2022] Open
Abstract
Genetic designs can consist of dozens of genes and hundreds of genetic parts. After evaluating a design, it is desirable to implement changes without the cost and burden of starting the construction process from scratch. Here, we report a two-step process where a large design space is divided into deep pools of composite parts, from which individuals are retrieved and assembled to build a final construct. The pools are built via multiplexed assembly and sequenced using next-generation sequencing. Each pool consists of ∼20 Mb of up to 5000 unique and sequence-verified composite parts that are barcoded for retrieval by PCR. This approach is applied to a 16-gene nitrogen fixation pathway, which is broken into pools containing a total of 55 848 composite parts (71.0 Mb). The pools encompass an enormous design space (1043 possible 23 kb constructs), from which an algorithm-guided 192-member 4.5 Mb library is built. Next, all 1030 possible genetic circuits based on 10 repressors (NOR/NOT gates) are encoded in pools where each repressor is fused to all permutations of input promoters. These demonstrate that multiplexing can be applied to encompass entire design spaces from which individuals can be accessed and evaluated.
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Affiliation(s)
- Lauren B A Woodruff
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA.,Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Thomas E Gorochowski
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA.,Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Nicholas Roehner
- Biological Design Center, Department of Electrical and Computer Engineering, Boston University, Boston, MA, USA
| | - Tarjei S Mikkelsen
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Douglas Densmore
- Biological Design Center, Department of Electrical and Computer Engineering, Boston University, Boston, MA, USA
| | - D Benjamin Gordon
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA.,Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Robert Nicol
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Christopher A Voigt
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA.,Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
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Abstract
Faced with a protein engineering challenge, a contemporary researcher can choose from myriad design strategies. Library-scale computational protein design (LCPD) is a hybrid method suitable for the engineering of improved protein variants with diverse sequences. This chapter discusses the background and merits of several practical LCPD techniques. First, LCPD methods suitable for delocalized protein design are presented in the context of example design calculations for cellobiohydrolase II. Second, localized design methods are discussed in the context of an example design calculation intended to shift the substrate specificity of a ketol-acid reductoisomerase Rossmann domain from NADPH to NADH.
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Verma D, Grigoryan G, Bailey-Kellogg C. Structure-based design of combinatorial mutagenesis libraries. Protein Sci 2015; 24:895-908. [PMID: 25611189 DOI: 10.1002/pro.2642] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2014] [Revised: 12/14/2014] [Accepted: 01/11/2015] [Indexed: 01/27/2023]
Abstract
The development of protein variants with improved properties (thermostability, binding affinity, catalytic activity, etc.) has greatly benefited from the application of high-throughput screens evaluating large, diverse combinatorial libraries. At the same time, since only a very limited portion of sequence space can be experimentally constructed and tested, an attractive possibility is to use computational protein design to focus libraries on a productive portion of the space. We present a general-purpose method, called "Structure-based Optimization of Combinatorial Mutagenesis" (SOCoM), which can optimize arbitrarily large combinatorial mutagenesis libraries directly based on structural energies of their constituents. SOCoM chooses both positions and substitutions, employing a combinatorial optimization framework based on library-averaged energy potentials in order to avoid explicitly modeling every variant in every possible library. In case study applications to green fluorescent protein, β-lactamase, and lipase A, SOCoM optimizes relatively small, focused libraries whose variants achieve energies comparable to or better than previous library design efforts, as well as larger libraries (previously not designable by structure-based methods) whose variants cover greater diversity while still maintaining substantially better energies than would be achieved by representative random library approaches. By allowing the creation of large-scale combinatorial libraries based on structural calculations, SOCoM promises to increase the scope of applicability of computational protein design and improve the hit rate of discovering beneficial variants. While designs presented here focus on variant stability (predicted by total energy), SOCoM can readily incorporate other structure-based assessments, such as the energy gap between alternative conformational or bound states.
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Affiliation(s)
- Deeptak Verma
- Department of Computer Science, Dartmouth College, Hanover, New Hampshire
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Villiers B, Hollfelder F. USER friendly DNA recombination (USERec): gene library construction requiring minimal sequence homology. Methods Mol Biol 2014; 1179:213-224. [PMID: 25055781 DOI: 10.1007/978-1-4939-1053-3_15] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
USER friendly DNA recombination (USERec) is based on near homology-independent recombination of DNA fragments (~40-400 bp) that are efficiently reassembled into full-length genes, proven for up to ten fragments. USERec requires a minimal crossover sequence (a 5'-AN(4-8)T-3' motif) of the fragments that can be implemented wherever structural or functional comparisons suggest a fragment boundary. The greatly reduced sequence constraints of this method facilitate directional assembly of gene fragments for applications such as exon or domain shuffling, loop grafting, reassembly of natural modular biosynthetic assembly lines, and rearrangement of structurally (but not sequence) homologous proteins.
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Affiliation(s)
- Benoit Villiers
- Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK
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Abstract
The best approach for creating libraries of functional proteins with large numbers of nondisruptive amino acid substitutions is protein recombination, in which structurally related polypeptides are swapped among homologous proteins. Unfortunately, as more distantly related proteins are recombined, the fraction of variants having a disrupted structure increases. One way to enrich the fraction of folded and potentially interesting chimeras in these libraries is to use computational algorithms to anticipate which structural elements can be swapped without disturbing the integrity of a protein's structure. Herein, we describe how the algorithm Schema uses the sequences and structures of the parent proteins recombined to predict the structural disruption of chimeras, and we outline how dynamic programming can be used to find libraries with a range of amino acid substitution levels that are enriched in variants with low Schema disruption.
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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:e5553. [PMID: 19436741 PMCID: PMC2677662 DOI: 10.1371/journal.pone.0005553] [Citation(s) in RCA: 688] [Impact Index Per Article: 45.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2009] [Accepted: 04/19/2009] [Indexed: 11/18/2022] Open
Abstract
We have developed a protocol to assemble in one step and one tube at least nine separate DNA fragments together into an acceptor vector, with 90% of recombinant clones obtained containing the desired construct. This protocol is based on the use of type IIs restriction enzymes and is performed by simply subjecting a mix of 10 undigested input plasmids (nine insert plasmids and the acceptor vector) to a restriction-ligation and transforming the resulting mix in competent cells. The efficiency of this protocol allows generating libraries of recombinant genes by combining in one reaction several fragment sets prepared from different parental templates. As an example, we have applied this strategy for shuffling of trypsinogen from three parental templates (bovine cationic trypsinogen, bovine anionic trypsinogen and human cationic trypsinogen) each divided in 9 separate modules. We show that one round of shuffling using the 27 trypsinogen entry plasmids can easily produce the 19,683 different possible combinations in one single restriction-ligation and that expression screening of a subset of the library allows identification of variants that can lead to higher expression levels of trypsin activity. This protocol, that we call ‘Golden Gate shuffling’, is robust, simple and efficient, can be performed with templates that have no homology, and can be combined with other shuffling protocols in order to introduce any variation in any part of a given gene.
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Affiliation(s)
- Carola Engler
- Icon Genetics GmbH, Biozentrum Halle, Halle, Germany
| | | | - Romy Kandzia
- Icon Genetics GmbH, Biozentrum Halle, Halle, Germany
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