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Rozhoňová H, Martí-Gómez C, McCandlish DM, Payne JL. Robust genetic codes enhance protein evolvability. PLoS Biol 2024; 22:e3002594. [PMID: 38754362 PMCID: PMC11098591 DOI: 10.1371/journal.pbio.3002594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 03/19/2024] [Indexed: 05/18/2024] Open
Abstract
The standard genetic code defines the rules of translation for nearly every life form on Earth. It also determines the amino acid changes accessible via single-nucleotide mutations, thus influencing protein evolvability-the ability of mutation to bring forth adaptive variation in protein function. One of the most striking features of the standard genetic code is its robustness to mutation, yet it remains an open question whether such robustness facilitates or frustrates protein evolvability. To answer this question, we use data from massively parallel sequence-to-function assays to construct and analyze 6 empirical adaptive landscapes under hundreds of thousands of rewired genetic codes, including those of codon compression schemes relevant to protein engineering and synthetic biology. We find that robust genetic codes tend to enhance protein evolvability by rendering smooth adaptive landscapes with few peaks, which are readily accessible from throughout sequence space. However, the standard genetic code is rarely exceptional in this regard, because many alternative codes render smoother landscapes than the standard code. By constructing low-dimensional visualizations of these landscapes, which each comprise more than 16 million mRNA sequences, we show that such alternative codes radically alter the topological features of the network of high-fitness genotypes. Whereas the genetic codes that optimize evolvability depend to some extent on the detailed relationship between amino acid sequence and protein function, we also uncover general design principles for engineering nonstandard genetic codes for enhanced and diminished evolvability, which may facilitate directed protein evolution experiments and the bio-containment of synthetic organisms, respectively.
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Affiliation(s)
- Hana Rozhoňová
- Institute of Integrative Biology, ETH Zürich, Zürich, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Carlos Martí-Gómez
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - David M. McCandlish
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Joshua L. Payne
- Institute of Integrative Biology, ETH Zürich, Zürich, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
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2
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Wagner A. Evolvability-enhancing mutations in the fitness landscapes of an RNA and a protein. Nat Commun 2023; 14:3624. [PMID: 37336901 PMCID: PMC10279741 DOI: 10.1038/s41467-023-39321-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 06/05/2023] [Indexed: 06/21/2023] Open
Abstract
Can evolvability-the ability to produce adaptive heritable variation-itself evolve through adaptive Darwinian evolution? If so, then Darwinian evolution may help create the conditions that enable Darwinian evolution. Here I propose a framework that is suitable to address this question with available experimental data on adaptive landscapes. I introduce the notion of an evolvability-enhancing mutation, which increases the likelihood that subsequent mutations in an evolving organism, protein, or RNA molecule are adaptive. I search for such mutations in the experimentally characterized and combinatorially complete fitness landscapes of a protein and an RNA molecule. I find that such evolvability-enhancing mutations indeed exist. They constitute a small fraction of all mutations, which shift the distribution of fitness effects of subsequent mutations towards less deleterious mutations, and increase the incidence of beneficial mutations. Evolving populations which experience such mutations can evolve significantly higher fitness. The study of evolvability-enhancing mutations opens many avenues of investigation into the evolution of evolvability.
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Affiliation(s)
- Andreas Wagner
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.
- Swiss Institute of Bioinformatics, Quartier Sorge-Batiment Genopode, Lausanne, Switzerland.
- The Santa Fe Institute, Santa Fe, NM, USA.
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3
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Cano AV, Gitschlag BL, Rozhoňová H, Stoltzfus A, McCandlish DM, Payne JL. Mutation bias and the predictability of evolution. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220055. [PMID: 37004719 PMCID: PMC10067271 DOI: 10.1098/rstb.2022.0055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2023] Open
Abstract
Predicting evolutionary outcomes is an important research goal in a diversity of contexts. The focus of evolutionary forecasting is usually on adaptive processes, and efforts to improve prediction typically focus on selection. However, adaptive processes often rely on new mutations, which can be strongly influenced by predictable biases in mutation. Here, we provide an overview of existing theory and evidence for such mutation-biased adaptation and consider the implications of these results for the problem of prediction, in regard to topics such as the evolution of infectious diseases, resistance to biochemical agents, as well as cancer and other kinds of somatic evolution. We argue that empirical knowledge of mutational biases is likely to improve in the near future, and that this knowledge is readily applicable to the challenges of short-term prediction. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.
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Affiliation(s)
- Alejandro V Cano
- Institute of Integrative Biology, ETH Zurich, 8092 Zurich, Switzerland
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Bryan L Gitschlag
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Hana Rozhoňová
- Institute of Integrative Biology, ETH Zurich, 8092 Zurich, Switzerland
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Arlin Stoltzfus
- Office of Data and Informatics, Material Measurement Laboratory, National Institute of Standards and Technology, Rockville, MD 20899, USA
- Institute for Bioscience and Biotechnology Research, Rockville, MD 20850, USA
| | - David M McCandlish
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Joshua L Payne
- Institute of Integrative Biology, ETH Zurich, 8092 Zurich, Switzerland
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
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4
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Romesberg FE. Discovery, implications and initial use of semi-synthetic organisms with an expanded genetic alphabet/code. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220030. [PMID: 36633274 PMCID: PMC9835597 DOI: 10.1098/rstb.2022.0030] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 08/25/2022] [Indexed: 01/13/2023] Open
Abstract
Much recent interest has focused on developing proteins for human use, such as in medicine. However, natural proteins are made up of only a limited number of canonical amino acids with limited functionalities, and this makes the discovery of variants with some functions difficult. The ability to recombinantly express proteins containing non-canonical amino acids (ncAAs) with properties selected to impart the protein with desired properties is expected to dramatically improve the discovery of proteins with different functions. Perhaps the most straightforward approach to such an expansion of the genetic code is through expansion of the genetic alphabet, so that new codon/anticodon pairs can be created to assign to ncAAs. In this review, I briefly summarize more than 20 years of effort leading ultimately to the discovery of synthetic nucleotides that pair to form an unnatural base pair, which when incorporated into DNA, is stably maintained, transcribed and used to translate proteins in Escherichia coli. In addition to discussing wide ranging conceptual implications, I also describe ongoing efforts at the pharmaceutical company Sanofi to employ the resulting 'semi-synthetic organisms' or SSOs, for the production of next-generation protein therapeutics. This article is part of the theme issue 'Reactivity and mechanism in chemical and synthetic biology'.
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Affiliation(s)
- Floyd E. Romesberg
- Platform Innovation, Synthorx, a Sanofi Company, 11099 N. Torrey Pines Road, Suite 190, La Jolla, CA 92037, USA
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5
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Abbate E, Andrion J, Apel A, Biggs M, Chaves J, Cheung K, Ciesla A, Clark-ElSayed A, Clay M, Contridas R, Fox R, Hein G, Held D, Horwitz A, Jenkins S, Kalbarczyk K, Krishnamurthy N, Mirsiaghi M, Noon K, Rowe M, Shepherd T, Tarasava K, Tarasow TM, Thacker D, Villa G, Yerramsetty K. Optimizing the strain engineering process for industrial-scale production of bio-based molecules. J Ind Microbiol Biotechnol 2023; 50:kuad025. [PMID: 37656881 PMCID: PMC10548853 DOI: 10.1093/jimb/kuad025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 08/29/2023] [Indexed: 09/03/2023]
Abstract
Biomanufacturing could contribute as much as ${\$}$30 trillion to the global economy by 2030. However, the success of the growing bioeconomy depends on our ability to manufacture high-performing strains in a time- and cost-effective manner. The Design-Build-Test-Learn (DBTL) framework has proven to be an effective strain engineering approach. Significant improvements have been made in genome engineering, genotyping, and phenotyping throughput over the last couple of decades that have greatly accelerated the DBTL cycles. However, to achieve a radical reduction in strain development time and cost, we need to look at the strain engineering process through a lens of optimizing the whole cycle, as opposed to simply increasing throughput at each stage. We propose an approach that integrates all 4 stages of the DBTL cycle and takes advantage of the advances in computational design, high-throughput genome engineering, and phenotyping methods, as well as machine learning tools for making predictions about strain scale-up performance. In this perspective, we discuss the challenges of industrial strain engineering, outline the best approaches to overcoming these challenges, and showcase examples of successful strain engineering projects for production of heterologous proteins, amino acids, and small molecules, as well as improving tolerance, fitness, and de-risking the scale-up of industrial strains.
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Affiliation(s)
- Eric Abbate
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Jennifer Andrion
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Amanda Apel
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Matthew Biggs
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Julie Chaves
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Kristi Cheung
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Anthony Ciesla
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Alia Clark-ElSayed
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Michael Clay
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Riarose Contridas
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Richard Fox
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Glenn Hein
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Dan Held
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Andrew Horwitz
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Stefan Jenkins
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | | | | | - Mona Mirsiaghi
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Katherine Noon
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Mike Rowe
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Tyson Shepherd
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Katia Tarasava
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Theodore M Tarasow
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Drew Thacker
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
| | - Gladys Villa
- Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA
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6
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Zürcher JF, Robertson WE, Kappes T, Petris G, Elliott TS, Salmond GPC, Chin JW. Refactored genetic codes enable bidirectional genetic isolation. Science 2022; 378:516-523. [PMID: 36264827 PMCID: PMC7614150 DOI: 10.1126/science.add8943] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
The near-universal genetic code defines the correspondence between codons in genes and amino acids in proteins. We refactored the structure of the genetic code in Escherichia coli and created orthogonal genetic codes that restrict the escape of synthetic genetic information into natural life. We developed orthogonal and mutually orthogonal horizontal gene transfer systems, which permit the transfer of genetic information between organisms that use the same genetic code but restrict the transfer of genetic information between organisms that use different genetic codes. Moreover, we showed that locking refactored codes into synthetic organisms completely blocks invasion by mobile genetic elements, including viruses, which carry their own translation factors and successfully invade organisms with canonical and compressed genetic codes.
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Affiliation(s)
- Jérôme F. Zürcher
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK
| | | | - Tomás Kappes
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Gianluca Petris
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK
| | - Thomas S. Elliott
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK
| | | | - Jason W. Chin
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK,Correspondence to:
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7
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Pines G, Pines A, Eckert CA. Highly Efficient Libraries Design for Saturation Mutagenesis. Synth Biol (Oxf) 2022; 7:ysac006. [PMID: 35734540 PMCID: PMC9205323 DOI: 10.1093/synbio/ysac006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Revised: 04/24/2022] [Accepted: 05/11/2022] [Indexed: 11/30/2022] Open
Abstract
Saturation mutagenesis is a semi-rational approach for protein engineering where sites are saturated either entirely or partially to include amino acids of interest. We previously reported on a codon compression algorithm, where a set of minimal degenerate codons are selected according to user-defined parameters such as the target organism, type of saturation and usage levels. Here, we communicate an addition to our web tool that considers the distance between the wild-type codon and the library, depending on its purpose. These forms of restricted collections further reduce library size, lowering downstream screening efforts or, in turn, allowing more comprehensive saturation of multiple sites. The library design tool can be accessed via http://www.dynamcc.com/dynamcc_d/.
Graphical Abstract
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Affiliation(s)
- Gur Pines
- Department of Entomology, Institute of Plant Protection, Agricultural Research Organization, Rishon LeTsiyon, 7528809, Israel
| | | | - Carrie A Eckert
- Biosciences Division, Oak Ridge National Laboratory, P.O. Box 2008, MS6060, Oak Ridge, Tennessee, 37831, USA
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8
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Castle SD, Grierson CS, Gorochowski TE. Towards an engineering theory of evolution. Nat Commun 2021; 12:3326. [PMID: 34099656 PMCID: PMC8185075 DOI: 10.1038/s41467-021-23573-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 05/04/2021] [Indexed: 02/07/2023] Open
Abstract
Biological technologies are fundamentally unlike any other because biology evolves. Bioengineering therefore requires novel design methodologies with evolution at their core. Knowledge about evolution is currently applied to the design of biosystems ad hoc. Unless we have an engineering theory of evolution, we will neither be able to meet evolution's potential as an engineering tool, nor understand or limit its unintended consequences for our biological designs. Here, we propose the evotype as a helpful concept for engineering the evolutionary potential of biosystems, or other self-adaptive technologies, potentially beyond the realm of biology.
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Affiliation(s)
- Simeon D Castle
- School of Biological Sciences, University of Bristol, Bristol, UK
| | - Claire S Grierson
- School of Biological Sciences, University of Bristol, Bristol, UK
- BrisSynBio, University of Bristol, Bristol, UK
| | - Thomas E Gorochowski
- School of Biological Sciences, University of Bristol, Bristol, UK.
- BrisSynBio, University of Bristol, Bristol, UK.
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9
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Schmidt M, Kubyshkin V. How To Quantify a Genetic Firewall? A Polarity-Based Metric for Genetic Code Engineering. Chembiochem 2021; 22:1268-1284. [PMID: 33231343 PMCID: PMC8049029 DOI: 10.1002/cbic.202000758] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 11/20/2020] [Indexed: 12/14/2022]
Abstract
Genetic code engineering aims to produce organisms that translate genetic information in a different way from that prescribed by the standard genetic code. This endeavor could eventually lead to genetic isolation, where an organism that operates under a different genetic code will not be able to transfer functional genes with other living species, thereby standing behind a genetic firewall. It is not clear however, how distinct the code should be, or how to measure the distance. We have developed a metric (Δcode ) where we assigned polarity indices (clog D7 ) to amino acids to calculate the distances between pairs of genetic codes. We then calculated the distance between a set of 204 genetic codes, including the 24 known distinct natural codes, 11 extreme-distance codes created computationally, nine theoretical special purpose codes from literature and 160 codes in which canonical amino acids were replaced by noncanonical chemical analogues. The metric can be used for building strategies towards creating semantically alienated organisms, and testing the strength of genetic firewalls. This metric provides the basis for a map of the genetic codes that could guide future efforts towards novel biochemical worlds, biosafety and deep barcoding applications.
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Affiliation(s)
| | - Vladimir Kubyshkin
- Department of ChemistryUniversity of ManitobaDysart Road 144WinnipegR3T 2N2Canada
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10
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Pines G, Fankhauser RG, Eckert CA. Predicting Drug Resistance Using Deep Mutational Scanning. Molecules 2020; 25:E2265. [PMID: 32403408 PMCID: PMC7248951 DOI: 10.3390/molecules25092265] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Revised: 05/05/2020] [Accepted: 05/05/2020] [Indexed: 12/12/2022] Open
Abstract
Drug resistance is a major healthcare challenge, resulting in a continuous need to develop new inhibitors. The development of these inhibitors requires an understanding of the mechanisms of resistance for a critical mass of occurrences. Recent genome editing technologies based on high-throughput DNA synthesis and sequencing may help to predict mutations resulting in resistance by testing large mutagenesis libraries. Here we describe the rationale of this approach, with examples and relevance to drug development and resistance in malaria.
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Affiliation(s)
- Gur Pines
- Department of Entomology, Agricultural Research Organization, Volcani Center, P.O.B 15159, Rishon LeZion 7505101, Israel
| | - Reilly G. Fankhauser
- Department of Dermatology, Oregon Health & Science University, Baird Hall 3225 SW Pavilion Loop, Portland, OR 97239, USA;
| | - Carrie A. Eckert
- Renewable and Sustainable Energy Institute, University of Colorado Boulder, 027 UCB, Boulder, CO 80309, USA
- Biosciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO 80401, USA
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11
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Calles J, Justice I, Brinkley D, Garcia A, Endy D. Fail-safe genetic codes designed to intrinsically contain engineered organisms. Nucleic Acids Res 2019; 47:10439-10451. [PMID: 31511890 PMCID: PMC6821295 DOI: 10.1093/nar/gkz745] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 08/13/2019] [Accepted: 08/19/2019] [Indexed: 11/24/2022] Open
Abstract
One challenge in engineering organisms is taking responsibility for their behavior over many generations. Spontaneous mutations arising before or during use can impact heterologous genetic functions, disrupt system integration, or change organism phenotype. Here, we propose restructuring the genetic code itself such that point mutations in protein-coding sequences are selected against. Synthetic genetic systems so-encoded should fail more safely in response to most spontaneous mutations. We designed fail-safe codes and simulated their expected effects on the evolution of so-encoded proteins. We predict fail-safe codes supporting expression of 20 or 15 amino acids could slow protein evolution to ∼30% or 0% the rate of standard-encoded proteins, respectively. We also designed quadruplet-codon codes that should ensure all single point mutations in protein-coding sequences are selected against while maintaining expression of 20 or more amino acids. We demonstrate experimentally that a reduced set of 21 tRNAs is capable of expressing a protein encoded by only 20 sense codons, whereas a standard 64-codon encoding is not expressed. Our work suggests that biological systems using rationally depleted but otherwise natural translation systems should evolve more slowly and that such hypoevolvable organisms may be less likely to invade new niches or outcompete native populations.
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Affiliation(s)
- Jonathan Calles
- Bioengineering Department, Stanford University, Stanford, CA 94305, USA
| | - Isaac Justice
- Bioengineering Department, Stanford University, Stanford, CA 94305, USA
| | - Detravious Brinkley
- Department of Mathematics and Computer Science, Claflin University, Orangeburg, SC 29115, USA
| | - Alexa Garcia
- Bioengineering Department, Stanford University, Stanford, CA 94305, USA
| | - Drew Endy
- Bioengineering Department, Stanford University, Stanford, CA 94305, USA
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12
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Pines G, Oh EJ, Bassalo MC, Choudhury A, Garst AD, Fankhauser RG, Eckert CA, Gill RT. Genomic Deoxyxylulose Phosphate Reductoisomerase (DXR) Mutations Conferring Resistance to the Antimalarial Drug Fosmidomycin in E. coli. ACS Synth Biol 2018; 7:2824-2832. [PMID: 30462485 DOI: 10.1021/acssynbio.8b00219] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Sequence to activity mapping technologies are rapidly developing, enabling the generation and isolation of mutations conferring novel phenotypes. Here we used the CRISPR enabled trackable genome engineering (CREATE) technology to investigate the inhibition of the essential ispC gene in its native genomic context in Escherichia coli. We created a full saturation library of 33 sites proximal to the ligand binding pocket and challenged this library with the antimalarial drug fosmidomycin, which targets the ispC gene product, DXR. This selection is especially challenging since it is relatively weak in E. coli, with multiple naturally occurring pathways for resistance. We identified several previously unreported mutations that confer fosmidomycin resistance, in highly conserved sites that also exist in pathogens including the malaria-inducing Plasmodium falciparum. This approach may have implications for the isolation of resistance-conferring mutations and may affect the design of future generations of fosmidomycin-based drugs.
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Affiliation(s)
- Gur Pines
- Renewable and Sustainable Energy Institute, University of Colorado Boulder, 027 UCB, Boulder, Colorado 80309, United States
- Department of Chemical and Biological Engineering, University of Colorado Boulder, 596 UCB, Boulder, Colorado 80309, United States
| | - Eun Joong Oh
- Renewable and Sustainable Energy Institute, University of Colorado Boulder, 027 UCB, Boulder, Colorado 80309, United States
- Department of Chemical and Biological Engineering, University of Colorado Boulder, 596 UCB, Boulder, Colorado 80309, United States
| | - Marcelo C. Bassalo
- Renewable and Sustainable Energy Institute, University of Colorado Boulder, 027 UCB, Boulder, Colorado 80309, United States
- Department of Molecular, Cellular, and Developmental Biology, University of Colorado Boulder, 347 UCB, Boulder, Colorado 80309, United States
| | - Alaksh Choudhury
- Department of Chemical and Biological Engineering, University of Colorado Boulder, 596 UCB, Boulder, Colorado 80309, United States
| | - Andrew D. Garst
- Renewable and Sustainable Energy Institute, University of Colorado Boulder, 027 UCB, Boulder, Colorado 80309, United States
| | - Reilly G. Fankhauser
- Renewable and Sustainable Energy Institute, University of Colorado Boulder, 027 UCB, Boulder, Colorado 80309, United States
| | - Carrie A. Eckert
- Renewable and Sustainable Energy Institute, University of Colorado Boulder, 027 UCB, Boulder, Colorado 80309, United States
- Biosciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, Colorado 80401, United States
| | - Ryan T. Gill
- Renewable and Sustainable Energy Institute, University of Colorado Boulder, 027 UCB, Boulder, Colorado 80309, United States
- Department of Chemical and Biological Engineering, University of Colorado Boulder, 596 UCB, Boulder, Colorado 80309, United States
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13
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Abstract
Saturation mutagenesis is conveniently located between the two extremes of protein engineering, namely random mutagenesis, and rational design. It involves mutating a confined number of target residues to other amino acids, and hence requires knowledge regarding the sites for mutagenesis, but not their final identity. There are many different strategies for performing and designing such experiments, ranging from simple single degenerate codons to codon collections that code for distinct sets of amino acids. Here, we provide detailed information on the Dynamic Management for Codon Compression (DYNAMCC) approaches that allow us to precisely define the desired amino acid composition to be introduced to a specific target site. DYNAMCC allows us to set usage thresholds and to eliminate undesirable stop and wild-type codons, thus allowing us to control library size and subsequently downstream screening efforts. The DYNAMCC algorithms are free of charge and are implemented in a website for easy access and usage: www.dynamcc.com .
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Affiliation(s)
- Gur Pines
- Renewable and Sustainable Energy Institute (RASEI), University of Colorado Boulder, Boulder, CO, USA. .,Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA.
| | - Ryan T Gill
- Renewable and Sustainable Energy Institute (RASEI), University of Colorado Boulder, Boulder, CO, USA.,Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA
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