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Sana B, Ding K, Siau JW, Pasula RR, Chee S, Kharel S, Lena JBH, Goh E, Rajamani L, Lam YM, Lim S, Ghadessy JF. Thermostability enhancement of polyethylene terephthalate degrading PETase using self- and nonself-ligating protein scaffolding approaches. Biotechnol Bioeng 2023; 120:3200-3209. [PMID: 37555384 DOI: 10.1002/bit.28523] [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] [Revised: 07/17/2023] [Accepted: 07/23/2023] [Indexed: 08/10/2023]
Abstract
Polyethylene terephthalate (PET) hydrolase enzymes show promise for enzymatic PET degradation and green recycling of single-use PET vessels representing a major source of global pollution. Their full potential can be unlocked with enzyme engineering to render activities on recalcitrant PET substrates commensurate with cost-effective recycling at scale. Thermostability is a highly desirable property in industrial enzymes, often imparting increased robustness and significantly reducing quantities required. To date, most engineered PET hydrolases show improved thermostability over their parental enzymes. Here, we report engineered thermostable variants of Ideonella sakaiensis PET hydrolase enzyme (IsPETase) developed using two scaffolding strategies. The first employed SpyCatcher-SpyTag technology to covalently cyclize IsPETase, resulting in increased thermostability that was concomitant with reduced turnover of PET substrates compared to native IsPETase. The second approach using a GFP-nanobody fusion protein (vGFP) as a scaffold yielded a construct with a melting temperature of 80°C. This was further increased to 85°C when a thermostable PETase variant (FAST PETase) was scaffolded into vGFP, the highest reported so far for an engineered PET hydrolase derived from IsPETase. Thermostability enhancement using the vGFP scaffold did not compromise activity on PET compared to IsPETase. These contrasting results highlight potential topological and dynamic constraints imposed by scaffold choice as determinants of enzyme activity.
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Affiliation(s)
- Barindra Sana
- Disease Intervention Technology Laboratory, Institute of Molecular and Cell Biology, Agency for Science Technology and Research, Singapore, Singapore
| | - Ke Ding
- Disease Intervention Technology Laboratory, Institute of Molecular and Cell Biology, Agency for Science Technology and Research, Singapore, Singapore
| | - Jia Wei Siau
- Disease Intervention Technology Laboratory, Institute of Molecular and Cell Biology, Agency for Science Technology and Research, Singapore, Singapore
| | - Rupali Reddy Pasula
- School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological Univeristy, Singapore, Singapore
| | - Sharon Chee
- Disease Intervention Technology Laboratory, Institute of Molecular and Cell Biology, Agency for Science Technology and Research, Singapore, Singapore
| | - Sharad Kharel
- School of Materials Science and Engineering, Nanyang Technological University, Singapore, Singapore
| | - Jean-Baptise Henri Lena
- School of Materials Science and Engineering, Nanyang Technological University, Singapore, Singapore
| | - Eunice Goh
- Singapore Eye Research Institute, The Academia, Singapore, Singapore
| | | | - Yeng Ming Lam
- School of Materials Science and Engineering, Nanyang Technological University, Singapore, Singapore
| | - Sierin Lim
- School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological Univeristy, Singapore, Singapore
| | - John F Ghadessy
- Disease Intervention Technology Laboratory, Institute of Molecular and Cell Biology, Agency for Science Technology and Research, Singapore, Singapore
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Yang A, Jude KM, Lai B, Minot M, Kocyla AM, Glassman CR, Nishimiya D, Kim YS, Reddy ST, Khan AA, Garcia KC. Deploying synthetic coevolution and machine learning to engineer protein-protein interactions. Science 2023; 381:eadh1720. [PMID: 37499032 PMCID: PMC10403280 DOI: 10.1126/science.adh1720] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 06/16/2023] [Indexed: 07/29/2023]
Abstract
Fine-tuning of protein-protein interactions occurs naturally through coevolution, but this process is difficult to recapitulate in the laboratory. We describe a platform for synthetic protein-protein coevolution that can isolate matched pairs of interacting muteins from complex libraries. This large dataset of coevolved complexes drove a systems-level analysis of molecular recognition between Z domain-affibody pairs spanning a wide range of structures, affinities, cross-reactivities, and orthogonalities, and captured a broad spectrum of coevolutionary networks. Furthermore, we harnessed pretrained protein language models to expand, in silico, the amino acid diversity of our coevolution screen, predicting remodeled interfaces beyond the reach of the experimental library. The integration of these approaches provides a means of simulating protein coevolution and generating protein complexes with diverse molecular recognition properties for biotechnology and synthetic biology.
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Affiliation(s)
- Aerin Yang
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Kevin M. Jude
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Ben Lai
- Toyota Technological Institute at Chicago, Chicago, IL 60637, USA
| | - Mason Minot
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Anna M. Kocyla
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Caleb R. Glassman
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Daisuke Nishimiya
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Yoon Seok Kim
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Sai T. Reddy
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Aly A. Khan
- Toyota Technological Institute at Chicago, Chicago, IL 60637, USA
- Departments of Pathology, and Family Medicine, University of Chicago, Chicago, IL 60637, USA
| | - K. Christopher Garcia
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA
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Xie VC, Styles MJ, Dickinson BC. Methods for the directed evolution of biomolecular interactions. Trends Biochem Sci 2022; 47:403-416. [PMID: 35427479 PMCID: PMC9022280 DOI: 10.1016/j.tibs.2022.01.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 12/27/2021] [Accepted: 01/13/2022] [Indexed: 02/06/2023]
Abstract
Noncovalent interactions between biomolecules such as proteins and nucleic acids coordinate all cellular processes through changes in proximity. Tools that perturb these interactions are and will continue to be highly valuable for basic and translational scientific endeavors. By taking cues from natural systems, such as the adaptive immune system, we can design directed evolution platforms that can generate proteins that bind to biomolecules of interest. In recent years, the platforms used to direct the evolution of biomolecular binders have greatly expanded the range of types of interactions one can evolve. Herein, we review recent advances in methods to evolve protein-protein, protein-RNA, and protein-DNA interactions.
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Affiliation(s)
| | - Matthew J Styles
- Department of Chemistry, The University of Chicago, Chicago, IL 60637, USA
| | - Bryan C Dickinson
- Department of Chemistry, The University of Chicago, Chicago, IL 60637, USA.
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Fukunaga K, Yokobayashi Y. Directed evolution of orthogonal RNA-RBP pairs through library-vs-library in vitro selection. Nucleic Acids Res 2021; 50:601-616. [PMID: 34219162 PMCID: PMC8789040 DOI: 10.1093/nar/gkab527] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 06/03/2021] [Accepted: 06/08/2021] [Indexed: 12/30/2022] Open
Abstract
RNA-binding proteins (RBPs) and their RNA ligands play many critical roles in gene regulation and RNA processing in cells. They are also useful for various applications in cell biology and synthetic biology. However, re-engineering novel and orthogonal RNA-RBP pairs from natural components remains challenging while such synthetic RNA-RBP pairs could significantly expand the RNA-RBP toolbox for various applications. Here, we report a novel library-vs-library in vitro selection strategy based on Phage Display coupled with Systematic Evolution of Ligands by EXponential enrichment (PD-SELEX). Starting with pools of 1.1 × 1012 unique RNA sequences and 4.0 × 108 unique phage-displayed L7Ae-scaffold (LS) proteins, we selected RNA-RBP complexes through a two-step affinity purification process. After six rounds of library-vs-library selection, the selected RNAs and LS proteins were analyzed by next-generation sequencing (NGS). Further deconvolution of the enriched RNA and LS protein sequences revealed two synthetic and orthogonal RNA-RBP pairs that exhibit picomolar affinity and >4000-fold selectivity.
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Affiliation(s)
- Keisuke Fukunaga
- Nucleic Acid Chemistry and Engineering Unit, Okinawa Institute of Science and Technology Graduate University, Onna, Okinawa 904 0495, Japan
| | - Yohei Yokobayashi
- Nucleic Acid Chemistry and Engineering Unit, Okinawa Institute of Science and Technology Graduate University, Onna, Okinawa 904 0495, Japan
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