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Wang H, Chen M, Wei X, Xia R, Pei D, Huang X, Han B. Computational tools for plant genomics and breeding. SCIENCE CHINA. LIFE SCIENCES 2024; 67:1579-1590. [PMID: 38676814 DOI: 10.1007/s11427-024-2578-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 03/25/2024] [Indexed: 04/29/2024]
Abstract
Plant genomics and crop breeding are at the intersection of biotechnology and information technology. Driven by a combination of high-throughput sequencing, molecular biology and data science, great advances have been made in omics technologies at every step along the central dogma, especially in genome assembling, genome annotation, epigenomic profiling, and transcriptome profiling. These advances further revolutionized three directions of development. One is genetic dissection of complex traits in crops, along with genomic prediction and selection. The second is comparative genomics and evolution, which open up new opportunities to depict the evolutionary constraints of biological sequences for deleterious variant discovery. The third direction is the development of deep learning approaches for the rational design of biological sequences, especially proteins, for synthetic biology. All three directions of development serve as the foundation for a new era of crop breeding where agronomic traits are enhanced by genome design.
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Affiliation(s)
- Hai Wang
- State Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, Joint International Research Laboratory of Crop Molecular Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.
- Sanya Institute of China Agricultural University, Sanya, 572025, China.
- Hainan Yazhou Bay Seed Laboratory, Sanya, 572025, China.
| | - Mengjiao Chen
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of the State Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China
| | - Xin Wei
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, 200234, China
| | - Rui Xia
- College of Horticulture, South China Agricultural University, Guangzhou, 510640, China
| | - Dong Pei
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of the State Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China
| | - Xuehui Huang
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, 200234, China
| | - Bin Han
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai, 200233, China
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2
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Hoersten J, Ruiz-Gómez G, Paszkowski-Rogacz M, Gilioli G, Guillem-Gloria P, Lansing F, Pisabarro MT, Buchholz F. Engineering spacer specificity of the Cre/loxP system. Nucleic Acids Res 2024; 52:8017-8031. [PMID: 38869070 PMCID: PMC11260471 DOI: 10.1093/nar/gkae481] [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: 01/19/2024] [Revised: 05/16/2024] [Accepted: 06/07/2024] [Indexed: 06/14/2024] Open
Abstract
Translational research on the Cre/loxP recombination system focuses on enhancing its specificity by modifying Cre/DNA interactions. Despite extensive efforts, the exact mechanisms governing Cre discrimination between substrates remains elusive. Cre recognizes 13 bp inverted repeats, initiating recombination in the 8 bp spacer region. While literature suggests that efficient recombination proceeds between lox sites with non-loxP spacer sequences when both lox sites have matching spacers, experimental validation for this assumption is lacking. To fill this gap, we investigated target site variations of identical pairs of the loxP 8 bp spacer region, screening 6000 unique loxP-like sequences. Approximately 84% of these sites exhibited efficient recombination, affirming the plasticity of spacer sequences for catalysis. However, certain spacers negatively impacted recombination, emphasizing sequence dependence. Directed evolution of Cre on inefficiently recombined spacers not only yielded recombinases with enhanced activity but also mutants with reprogrammed selective activity. Mutations altering spacer specificity were identified, and molecular modelling and dynamics simulations were used to investigate the possible mechanisms behind the specificity switch. Our findings highlight the potential to fine-tune site-specific recombinases for spacer sequence specificity, offering a novel concept to enhance the applied properties of designer-recombinases for genome engineering applications.
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Affiliation(s)
- Jenna Hoersten
- Medical Faculty and University Hospital Carl Gustav Carus, UCC Section Medical Systems Biology, TU Dresden, 01307 Dresden, Germany
| | - Gloria Ruiz-Gómez
- Structural Bioinformatics, BIOTEC TU Dresden, Tatzberg 47/49, 01307 Dresden, Germany
| | - Maciej Paszkowski-Rogacz
- Medical Faculty and University Hospital Carl Gustav Carus, UCC Section Medical Systems Biology, TU Dresden, 01307 Dresden, Germany
| | - Giorgio Gilioli
- Medical Faculty and University Hospital Carl Gustav Carus, UCC Section Medical Systems Biology, TU Dresden, 01307 Dresden, Germany
| | | | - Felix Lansing
- Medical Faculty and University Hospital Carl Gustav Carus, UCC Section Medical Systems Biology, TU Dresden, 01307 Dresden, Germany
| | - M Teresa Pisabarro
- Structural Bioinformatics, BIOTEC TU Dresden, Tatzberg 47/49, 01307 Dresden, Germany
| | - Frank Buchholz
- Medical Faculty and University Hospital Carl Gustav Carus, UCC Section Medical Systems Biology, TU Dresden, 01307 Dresden, Germany
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3
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Foster MP, Benedek MJ, Billings TD, Montgomery JS. Dynamics in Cre-loxP site-specific recombination. Curr Opin Struct Biol 2024; 88:102878. [PMID: 39029281 DOI: 10.1016/j.sbi.2024.102878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2024] [Revised: 06/15/2024] [Accepted: 06/17/2024] [Indexed: 07/21/2024]
Abstract
Cre recombinase is a phage-derived enzyme that has found utility for precise manipulation of DNA sequences. Cre recognizes and recombines pairs of loxP sequences characterized by an inverted repeat and asymmetric spacer. Cre cleaves and religates its DNA targets such that error-prone repair pathways are not required to generate intact DNA products. Major obstacles to broader applications are lack of knowledge of how Cre recognizes its targets, and how its activity is controlled. The picture emerging from high resolution methods is that the dynamic properties of both the enzyme and its DNA target are important determinants of its activity in both sequence recognition and DNA cleavage. Improved understanding of the role of dynamics in the key steps along the pathway of Cre-loxP recombination should significantly advance our ability to both redirect Cre to new sequences and to control its DNA cleavage activity in the test tube and in cells.
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Affiliation(s)
- Mark P Foster
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, USA.
| | - Matthew J Benedek
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, USA
| | - Tyler D Billings
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, USA
| | - Jonathan S Montgomery
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, USA
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4
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Tune T, Kooiker KB, Davis J, Daniel T, Moussavi-Harami F. Identifying Mechanisms and Therapeutic Targets in Muscle using Bayesian Parameter Estimation with Conditional Variational Autoencoders. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.08.593035. [PMID: 38766103 PMCID: PMC11100674 DOI: 10.1101/2024.05.08.593035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Cardiomyopathies, often caused by mutations in genes encoding muscle proteins, are traditionally treated by phenotyping hearts and addressing symptoms post irreversible damage. With advancements in genotyping, early diagnosis is now possible, potentially preventing such damage. However, the intricate structure of muscle and its myriad proteins make treatment predictions challenging. Here we approach the problem of estimating therapeutic targets for a mutation in mouse muscle using a spatially explicit half sarcomere muscle model. We selected 9 rate parameters in our model linked to both small molecules and cardiomyopathy-causing mutations. We then randomly varied these rate parameters and simulated an isometric twitch for each combination to generate a large training dataset. We used this dataset to train a Conditional Variational Autoencoder (CVAE), a technique used in Bayesian parameter estimation. Given simulated or experimental isometric twitches, this machine learning model is able to then predict the set of rate parameters which are most likely to yield that result. We then predict the set of rate parameters associated with both control and the cardiac Troponin C (cTnC) I61Q variant in mouse trabeculae and model parameters that recover the abnormal I61Q cTnC twitches. SIGNIFICANCE Machine learning techniques have potential to accelerate discoveries in biologically complex systems. However, they require large data sets and can be challenging in high dimensional systems such as cardiac muscle. In this study, we combined experimental measures of cardiac muscle twitch forces with mechanistic simulations and a newly developed mixture of Bayesian inference with neural networks (in autoencoders) to solve the inverse problem of determining the underlying kinetics for observed force generation by cardiac muscle. The autoencoders are trained on millions of simulations spanning parameter spaces that correspond to the mechanochemistry of cardiac sarcomeres. We apply the trained model to experimental data in order to infer parameters that can explain a diseased twitch and ways to recover it.
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Tou CJ, Kleinstiver BP. Programmable RNA-guided enzymes for next-generation genome editing. Nature 2024; 630:827-828. [PMID: 38926618 DOI: 10.1038/d41586-024-01461-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/28/2024]
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Van Duyne GD, Landy A. Bacteriophage lambda site-specific recombination. Mol Microbiol 2024; 121:895-911. [PMID: 38372210 PMCID: PMC11096046 DOI: 10.1111/mmi.15241] [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: 08/29/2023] [Revised: 01/29/2024] [Accepted: 01/31/2024] [Indexed: 02/20/2024]
Abstract
The site-specific recombination pathway of bacteriophage λ encompasses isoenergetic but highly directional and tightly regulated integrative and excisive reactions that integrate and excise the vial chromosome into and out of the bacterial chromosome. The reactions require 240 bp of phage DNA and 21 bp of bacterial DNA comprising 16 protein binding sites that are differentially used in each pathway by the phage-encoded Int and Xis proteins and the host-encoded integration host factor and factor for inversion stimulation proteins. Structures of higher-order protein-DNA complexes of the four-way Holliday junction recombination intermediates provided clarifying insights into the mechanisms, directionality, and regulation of these two pathways, which are tightly linked to the physiology of the bacterial host cell. Here we review our current understanding of the mechanisms responsible for regulating and executing λ site-specific recombination, with an emphasis on key studies completed over the last decade.
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Affiliation(s)
- Gregory D Van Duyne
- Department of Biochemistry & Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Arthur Landy
- Department of Molecular Biology, Cell Biology, and Biochemistry, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA
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Johnson SR, Fu X, Viknander S, Goldin C, Monaco S, Zelezniak A, Yang KK. Computational scoring and experimental evaluation of enzymes generated by neural networks. Nat Biotechnol 2024:10.1038/s41587-024-02214-2. [PMID: 38653796 DOI: 10.1038/s41587-024-02214-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 03/20/2024] [Indexed: 04/25/2024]
Abstract
In recent years, generative protein sequence models have been developed to sample novel sequences. However, predicting whether generated proteins will fold and function remains challenging. We evaluate a set of 20 diverse computational metrics to assess the quality of enzyme sequences produced by three contrasting generative models: ancestral sequence reconstruction, a generative adversarial network and a protein language model. Focusing on two enzyme families, we expressed and purified over 500 natural and generated sequences with 70-90% identity to the most similar natural sequences to benchmark computational metrics for predicting in vitro enzyme activity. Over three rounds of experiments, we developed a computational filter that improved the rate of experimental success by 50-150%. The proposed metrics and models will drive protein engineering research by serving as a benchmark for generative protein sequence models and helping to select active variants for experimental testing.
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Affiliation(s)
| | - Xiaozhi Fu
- Department of Life Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | - Sandra Viknander
- Department of Life Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | - Clara Goldin
- Department of Life Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | | | - Aleksej Zelezniak
- Department of Life Sciences, Chalmers University of Technology, Gothenburg, Sweden.
- Institute of Biotechnology, Life Sciences Centre, Vilnius University, Vilnius, Lithuania.
- Randall Centre for Cell & Molecular Biophysics, King's College London, Guy's Campus, London, UK.
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Sundaram SS, Kannan A, Chintaluri PG, Sreekala AGV, Nathan VK. Thermostable bacterial L-asparaginase for polyacrylamide inhibition and in silico mutational analysis. Int Microbiol 2024:10.1007/s10123-024-00493-y. [PMID: 38519776 DOI: 10.1007/s10123-024-00493-y] [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: 11/29/2023] [Revised: 02/07/2024] [Accepted: 02/27/2024] [Indexed: 03/25/2024]
Abstract
The L-asparaginase (ASPN) enzyme has received recognition in various applications including acrylamide degradation in the food industry. The synthesis and application of thermostable ASPN enzymes is required for its use in the food sector, where thermostable enzymes can withstand high temperatures. To achieve this goal, the bacterium Bacillus subtilis was isolated from the hot springs of Tapovan for screening the production of thermostable ASPN enzyme. Thus, ASPN with a maximal specific enzymatic activity of 0.896 U/mg and a molecular weight of 66 kDa was produced from the isolated bacteria. The kinetic study of the enzyme yielded a Km value of 1.579 mM and a Vmax of 5.009 µM/min with thermostability up to 100 min at 75 °C. This may have had a positive indication for employing the enzyme to stop polyacrylamide from being produced. The current study has also been extended to investigate the interaction of native and mutated ASPN enzymes with acrylamide. This concluded that the M10 (with 10 mutations) has the highest protein and thermal stability compared to the wild-type ASPN protein sequence. Therefore, in comparison to a normal ASPN and all other mutant ASPNs, M10 is the most favorable mutation. This research has also demonstrated the usage of ASPN in food industrial applications.
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Affiliation(s)
| | - Aravind Kannan
- School of Chemical and Biotechnology, SASTRA Deemed to Be University, Thanjavur, Tamil Nadu, India
| | - Pratham Gour Chintaluri
- School of Chemical and Biotechnology, SASTRA Deemed to Be University, Thanjavur, Tamil Nadu, India
| | | | - Vinod Kumar Nathan
- School of Chemical and Biotechnology, SASTRA Deemed to Be University, Thanjavur, Tamil Nadu, India.
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9
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Notin P, Rollins N, Gal Y, Sander C, Marks D. Machine learning for functional protein design. Nat Biotechnol 2024; 42:216-228. [PMID: 38361074 DOI: 10.1038/s41587-024-02127-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 01/05/2024] [Indexed: 02/17/2024]
Abstract
Recent breakthroughs in AI coupled with the rapid accumulation of protein sequence and structure data have radically transformed computational protein design. New methods promise to escape the constraints of natural and laboratory evolution, accelerating the generation of proteins for applications in biotechnology and medicine. To make sense of the exploding diversity of machine learning approaches, we introduce a unifying framework that classifies models on the basis of their use of three core data modalities: sequences, structures and functional labels. We discuss the new capabilities and outstanding challenges for the practical design of enzymes, antibodies, vaccines, nanomachines and more. We then highlight trends shaping the future of this field, from large-scale assays to more robust benchmarks, multimodal foundation models, enhanced sampling strategies and laboratory automation.
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Affiliation(s)
- Pascal Notin
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
- Department of Computer Science, University of Oxford, Oxford, UK.
| | | | - Yarin Gal
- Department of Computer Science, University of Oxford, Oxford, UK
| | - Chris Sander
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Debora Marks
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
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10
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Mukhametzyanova L, Schmitt LT, Torres-Rivera J, Rojo-Romanos T, Lansing F, Paszkowski-Rogacz M, Hollak H, Brux M, Augsburg M, Schneider PM, Buchholz F. Activation of recombinases at specific DNA loci by zinc-finger domain insertions. Nat Biotechnol 2024:10.1038/s41587-023-02121-y. [PMID: 38297187 DOI: 10.1038/s41587-023-02121-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 12/22/2023] [Indexed: 02/02/2024]
Abstract
Recombinases have several potential advantages as genome editing tools compared to nucleases and other editing enzymes, but the process of engineering them to efficiently recombine predetermined DNA targets demands considerable investment of time and labor. Here we sought to harness zinc-finger DNA-binding domains (ZFDs) to program recombinase binding by developing fusions, in which ZFDs are inserted into recombinase coding sequences. By screening libraries of hybrid proteins, we optimized the insertion site, linker length, spacing and ZFD orientation and generated Cre-type recombinases that remain dormant unless the insertionally fused ZFD binds its target site placed in the vicinity of the recombinase binding site. The developed fusion improved targeted editing efficiencies of recombinases by four-fold and abolished measurable off-target activity in mammalian cells. The ZFD-dependent activity is transferable to a recombinase with relaxed specificity, providing the means for developing fully programmable recombinases. Our engineered recombinases provide improved genome editing tools with increased precision and efficiency.
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Affiliation(s)
- Liliya Mukhametzyanova
- Medical Systems Biology, Medical Faculty, Technical University Dresden, Dresden, Germany
| | - Lukas Theo Schmitt
- Medical Systems Biology, Medical Faculty, Technical University Dresden, Dresden, Germany
- Seamless Therapeutics GmbH, Dresden, Germany
| | - Julia Torres-Rivera
- Medical Systems Biology, Medical Faculty, Technical University Dresden, Dresden, Germany
| | - Teresa Rojo-Romanos
- Medical Systems Biology, Medical Faculty, Technical University Dresden, Dresden, Germany
- Seamless Therapeutics GmbH, Dresden, Germany
| | - Felix Lansing
- Medical Systems Biology, Medical Faculty, Technical University Dresden, Dresden, Germany
- Seamless Therapeutics GmbH, Dresden, Germany
| | | | - Heike Hollak
- Medical Systems Biology, Medical Faculty, Technical University Dresden, Dresden, Germany
- Seamless Therapeutics GmbH, Dresden, Germany
| | - Melanie Brux
- Medical Systems Biology, Medical Faculty, Technical University Dresden, Dresden, Germany
| | - Martina Augsburg
- Medical Systems Biology, Medical Faculty, Technical University Dresden, Dresden, Germany
| | - Paul Martin Schneider
- Medical Systems Biology, Medical Faculty, Technical University Dresden, Dresden, Germany
- Seamless Therapeutics GmbH, Dresden, Germany
| | - Frank Buchholz
- Medical Systems Biology, Medical Faculty, Technical University Dresden, Dresden, Germany.
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11
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Barghout RA, Xu Z, Betala S, Mahadevan R. Advances in generative modeling methods and datasets to design novel enzymes for renewable chemicals and fuels. Curr Opin Biotechnol 2023; 84:103007. [PMID: 37931573 DOI: 10.1016/j.copbio.2023.103007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 09/12/2023] [Accepted: 09/13/2023] [Indexed: 11/08/2023]
Abstract
Biotechnology has revolutionized the development of sustainable energy sources by harnessing biomass as a feedstock for energy production. However, challenges such as recalcitrant feedstocks and inefficient metabolic pathways hinder the large-scale integration of renewable energy systems. Enzyme engineering has emerged as a powerful tool to address these challenges by enhancing enzyme activity, specificity, and stability. Generative machine learning (ML) models have shown great promise in accelerating protein design, allowing for the generation of novel protein sequences with desired properties by navigating vast spaces. This review paper aims to summarize the state of the art in generative models for protein design and how they can be applied to bioenergy applications, including the underlying architectures and training strategies. Additionally, it highlights the importance of high-quality datasets for training and evaluating generative models, organizes available datasets for generative protein design, and discusses the potential of applying generative models to strain design for bioenergy production.
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Affiliation(s)
- Rana A Barghout
- Department of Chemical Engineering & Applied Chemistry, University of Toronto, 200 College St, Toronto, ON, Canada.
| | - Zhiqing Xu
- Department of Chemical Engineering & Applied Chemistry, University of Toronto, 200 College St, Toronto, ON, Canada
| | - Siddharth Betala
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, India
| | - Radhakrishnan Mahadevan
- Department of Chemical Engineering & Applied Chemistry, University of Toronto, 200 College St, Toronto, ON, Canada
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12
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Schmitt LT, Schneider A, Posorski J, Lansing F, Jelicic M, Jain M, Sayed S, Buchholz F, Sürün D. Quantification of evolved DNA-editing enzymes at scale with DEQSeq. Genome Biol 2023; 24:254. [PMID: 37932818 PMCID: PMC10626641 DOI: 10.1186/s13059-023-03097-3] [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: 04/06/2023] [Accepted: 10/24/2023] [Indexed: 11/08/2023] Open
Abstract
We introduce DEQSeq, a nanopore sequencing approach that rationalizes the selection of favorable genome editing enzymes from directed molecular evolution experiments. With the ability to capture full-length sequences, editing efficiencies, and specificities from thousands of evolved enzymes simultaneously, DEQSeq streamlines the process of identifying the most valuable variants for further study and application. We apply DEQSeq to evolved libraries of Cas12f-ABEs and designer-recombinases, identifying variants with improved properties for future applications. Our results demonstrate that DEQSeq is a powerful tool for accelerating enzyme discovery and advancing genome editing research.
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Affiliation(s)
- Lukas Theo Schmitt
- Medical Faculty and University Hospital Carl Gustav Carus, UCC Section Medical Systems Biology, Dresden, TU Dresden, 01307, Germany
- Present Address: Seamless Therapeutics GmbH, Tatzberg 47/49, 01307, Dresden, Germany
| | - Aksana Schneider
- Medical Faculty and University Hospital Carl Gustav Carus, UCC Section Medical Systems Biology, Dresden, TU Dresden, 01307, Germany
- Present Address: Seamless Therapeutics GmbH, Tatzberg 47/49, 01307, Dresden, Germany
| | - Jonas Posorski
- Medical Faculty and University Hospital Carl Gustav Carus, UCC Section Medical Systems Biology, Dresden, TU Dresden, 01307, Germany
| | - Felix Lansing
- Medical Faculty and University Hospital Carl Gustav Carus, UCC Section Medical Systems Biology, Dresden, TU Dresden, 01307, Germany
- Present Address: Seamless Therapeutics GmbH, Tatzberg 47/49, 01307, Dresden, Germany
| | - Milica Jelicic
- Medical Faculty and University Hospital Carl Gustav Carus, UCC Section Medical Systems Biology, Dresden, TU Dresden, 01307, Germany
| | - Manavi Jain
- Medical Faculty and University Hospital Carl Gustav Carus, UCC Section Medical Systems Biology, Dresden, TU Dresden, 01307, Germany
| | - Shady Sayed
- Medical Faculty and University Hospital Carl Gustav Carus, UCC Section Medical Systems Biology, Dresden, TU Dresden, 01307, Germany
| | - Frank Buchholz
- Medical Faculty and University Hospital Carl Gustav Carus, UCC Section Medical Systems Biology, Dresden, TU Dresden, 01307, Germany.
| | - Duran Sürün
- Medical Faculty and University Hospital Carl Gustav Carus, UCC Section Medical Systems Biology, Dresden, TU Dresden, 01307, Germany.
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13
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Yu T, Boob AG, Singh N, Su Y, Zhao H. In vitro continuous protein evolution empowered by machine learning and automation. Cell Syst 2023; 14:633-644. [PMID: 37224814 DOI: 10.1016/j.cels.2023.04.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 11/19/2022] [Accepted: 04/20/2023] [Indexed: 05/26/2023]
Abstract
Directed evolution has become one of the most successful and powerful tools for protein engineering. However, the efforts required for designing, constructing, and screening a large library of variants can be laborious, time-consuming, and costly. With the recent advent of machine learning (ML) in the directed evolution of proteins, researchers can now evaluate variants in silico and guide a more efficient directed evolution campaign. Furthermore, recent advancements in laboratory automation have enabled the rapid execution of long, complex experiments for high-throughput data acquisition in both industrial and academic settings, thus providing the means to collect a large quantity of data required to develop ML models for protein engineering. In this perspective, we propose a closed-loop in vitro continuous protein evolution framework that leverages the best of both worlds, ML and automation, and provide a brief overview of the recent developments in the field.
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Affiliation(s)
- Tianhao Yu
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Carl R. Woese Institute for Genomic Biology, Urbana, IL, USA; NSF Molecule Maker Lab Institute, Urbana, IL, USA
| | - Aashutosh Girish Boob
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Carl R. Woese Institute for Genomic Biology, Urbana, IL, USA; DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Nilmani Singh
- DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Yufeng Su
- NSF Molecule Maker Lab Institute, Urbana, IL, USA; Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Huimin Zhao
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Carl R. Woese Institute for Genomic Biology, Urbana, IL, USA; NSF Molecule Maker Lab Institute, Urbana, IL, USA; DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
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Rojo-Romanos T, Karpinski J, Millen S, Beschorner N, Simon F, Paszkowski-Rogacz M, Lansing F, Schneider PM, Sonntag J, Hauber J, Thoma-Kress AK, Buchholz F. Precise excision of HTLV-1 provirus with a designer-recombinase. Mol Ther 2023; 31:2266-2285. [PMID: 36934299 PMCID: PMC10362392 DOI: 10.1016/j.ymthe.2023.03.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 02/06/2023] [Accepted: 03/12/2023] [Indexed: 03/19/2023] Open
Abstract
The human T cell leukemia virus type 1 (HTLV-1) is a pathogenic retrovirus that persists as a provirus in the genome of infected cells and can lead to adult T cell leukemia (ATL). Worldwide, more than 10 million people are infected and approximately 5% of these individuals will develop ATL, a highly aggressive cancer that is currently incurable. In the last years, genome editing tools have emerged as promising antiviral agents. In this proof-of-concept study, we use substrate-linked directed evolution (SLiDE) to engineer Cre-derived site-specific recombinases to excise the HTLV-1 proviral genome from infected cells. We identified a conserved loxP-like sequence (loxHTLV) present in the long terminal repeats of the majority of virus isolates. After 181 cycles of SLiDE, we isolated a designer-recombinase (designated RecHTLV), which efficiently recombines the loxHTLV sequence in bacteria and human cells with high specificity. Expression of RecHTLV in human Jurkat T cells resulted in antiviral activity when challenged with an HTLV-1 infection. Moreover, expression of RecHTLV in chronically infected SP cells led to the excision of HTLV-1 proviral DNA. Our data suggest that recombinase-mediated excision of the HTLV-1 provirus represents a promising approach to reduce proviral load in HTLV-1-infected individuals, potentially preventing the development of HTLV-1-associated diseases.
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Affiliation(s)
- Teresa Rojo-Romanos
- Medical Systems Biology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technical University Dresden, 01307 Dresden, Germany
| | - Janet Karpinski
- Medical Systems Biology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technical University Dresden, 01307 Dresden, Germany
| | - Sebastian Millen
- Institute of Clinical and Molecular Virology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany
| | - Niklas Beschorner
- PROVIREX Genome Editing Therapies GmbH, Luruper Hauptstrasse 1, 22547 Hamburg, Germany
| | - Florian Simon
- Institute of Clinical and Molecular Virology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany
| | - Maciej Paszkowski-Rogacz
- Medical Systems Biology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technical University Dresden, 01307 Dresden, Germany
| | - Felix Lansing
- Medical Systems Biology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technical University Dresden, 01307 Dresden, Germany
| | - Paul Martin Schneider
- Medical Systems Biology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technical University Dresden, 01307 Dresden, Germany
| | - Jan Sonntag
- Medical Systems Biology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technical University Dresden, 01307 Dresden, Germany
| | - Joachim Hauber
- PROVIREX Genome Editing Therapies GmbH, Luruper Hauptstrasse 1, 22547 Hamburg, Germany
| | - Andrea K Thoma-Kress
- Institute of Clinical and Molecular Virology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany
| | - Frank Buchholz
- Medical Systems Biology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technical University Dresden, 01307 Dresden, Germany.
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15
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Boukid F, Ganeshan S, Wang Y, Tülbek MÇ, Nickerson MT. Bioengineered Enzymes and Precision Fermentation in the Food Industry. Int J Mol Sci 2023; 24:10156. [PMID: 37373305 DOI: 10.3390/ijms241210156] [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: 05/20/2023] [Revised: 06/06/2023] [Accepted: 06/13/2023] [Indexed: 06/29/2023] Open
Abstract
Enzymes have been used in the food processing industry for many years. However, the use of native enzymes is not conducive to high activity, efficiency, range of substrates, and adaptability to harsh food processing conditions. The advent of enzyme engineering approaches such as rational design, directed evolution, and semi-rational design provided much-needed impetus for tailor-made enzymes with improved or novel catalytic properties. Production of designer enzymes became further refined with the emergence of synthetic biology and gene editing techniques and a plethora of other tools such as artificial intelligence, and computational and bioinformatics analyses which have paved the way for what is referred to as precision fermentation for the production of these designer enzymes more efficiently. With all the technologies available, the bottleneck is now in the scale-up production of these enzymes. There is generally a lack of accessibility thereof of large-scale capabilities and know-how. This review is aimed at highlighting these various enzyme-engineering strategies and the associated scale-up challenges, including safety concerns surrounding genetically modified microorganisms and the use of cell-free systems to circumvent this issue. The use of solid-state fermentation (SSF) is also addressed as a potentially low-cost production system, amenable to customization and employing inexpensive feedstocks as substrate.
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Affiliation(s)
- Fatma Boukid
- ClonBio Group Ltd., 6 Fitzwilliam Pl, D02 XE61 Dublin, Ireland
| | | | - Yingxin Wang
- Saskatchewan Food Industry Development Centre, Saskatoon, SK S7M 5V1, Canada
| | | | - Michael T Nickerson
- Department of Food and Bioproduct Sciences, University of Saskatchewan, Saskatoon, SK S7N 5A8, Canada
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16
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Glaser V, Flugel C, Kath J, Du W, Drosdek V, Franke C, Stein M, Pruß A, Schmueck-Henneresse M, Volk HD, Reinke P, Wagner DL. Combining different CRISPR nucleases for simultaneous knock-in and base editing prevents translocations in multiplex-edited CAR T cells. Genome Biol 2023; 24:89. [PMID: 37095570 PMCID: PMC10123993 DOI: 10.1186/s13059-023-02928-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 04/06/2023] [Indexed: 04/26/2023] Open
Abstract
BACKGROUND Multiple genetic modifications may be required to develop potent off-the-shelf chimeric antigen receptor (CAR) T cell therapies. Conventional CRISPR-Cas nucleases install sequence-specific DNA double-strand breaks (DSBs), enabling gene knock-out or targeted transgene knock-in. However, simultaneous DSBs provoke a high rate of genomic rearrangements which may impede the safety of the edited cells. RESULTS Here, we combine a non-viral CRISPR-Cas9 nuclease-assisted knock-in and Cas9-derived base editing technology for DSB free knock-outs within a single intervention. We demonstrate efficient insertion of a CAR into the T cell receptor alpha constant (TRAC) gene, along with two knock-outs that silence major histocompatibility complexes (MHC) class I and II expression. This approach reduces translocations to 1.4% of edited cells. Small insertions and deletions at the base editing target sites indicate guide RNA exchange between the editors. This is overcome by using CRISPR enzymes of distinct evolutionary origins. Combining Cas12a Ultra for CAR knock-in and a Cas9-derived base editor enables the efficient generation of triple-edited CAR T cells with a translocation frequency comparable to unedited T cells. Resulting TCR- and MHC-negative CAR T cells resist allogeneic T cell targeting in vitro. CONCLUSIONS We outline a solution for non-viral CAR gene transfer and efficient gene silencing using different CRISPR enzymes for knock-in and base editing to prevent translocations. This single-step procedure may enable safer multiplex-edited cell products and demonstrates a path towards off-the-shelf CAR therapeutics.
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Affiliation(s)
- Viktor Glaser
- Berlin Center for Advanced Therapies (BeCAT), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
- BIH Center for Regenerative Therapies (BCRT), Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Christian Flugel
- Berlin Center for Advanced Therapies (BeCAT), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
- BIH Center for Regenerative Therapies (BCRT), Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Jonas Kath
- Berlin Center for Advanced Therapies (BeCAT), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
- BIH Center for Regenerative Therapies (BCRT), Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Weijie Du
- Berlin Center for Advanced Therapies (BeCAT), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
- BIH Center for Regenerative Therapies (BCRT), Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Vanessa Drosdek
- Berlin Center for Advanced Therapies (BeCAT), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
- BIH Center for Regenerative Therapies (BCRT), Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Clemens Franke
- Berlin Center for Advanced Therapies (BeCAT), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
- BIH Center for Regenerative Therapies (BCRT), Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Maik Stein
- Berlin Center for Advanced Therapies (BeCAT), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
- BIH Center for Regenerative Therapies (BCRT), Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Axel Pruß
- Institute of Transfusion Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Campus Charité Mitte, Charitéplatz 1, 10117, Berlin, Germany
| | - Michael Schmueck-Henneresse
- Berlin Center for Advanced Therapies (BeCAT), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
- BIH Center for Regenerative Therapies (BCRT), Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Hans-Dieter Volk
- Berlin Center for Advanced Therapies (BeCAT), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
- BIH Center for Regenerative Therapies (BCRT), Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
- Institute of Medical Immunology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
- CheckImmune GmbH, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Petra Reinke
- Berlin Center for Advanced Therapies (BeCAT), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
- BIH Center for Regenerative Therapies (BCRT), Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Dimitrios L Wagner
- Berlin Center for Advanced Therapies (BeCAT), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany.
- BIH Center for Regenerative Therapies (BCRT), Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany.
- Institute of Transfusion Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Campus Charité Mitte, Charitéplatz 1, 10117, Berlin, Germany.
- Institute of Medical Immunology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany.
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17
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Chi H, Zhu X, Shen J, Lu Z, Lu F, Lyu Y, Zhu P. Thermostability enhancement and insight of L-asparaginase from Mycobacterium sp. via consensus-guided engineering. Appl Microbiol Biotechnol 2023; 107:2321-2333. [PMID: 36843197 DOI: 10.1007/s00253-023-12443-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 02/06/2023] [Accepted: 02/13/2023] [Indexed: 02/28/2023]
Abstract
Acrylamide alleviation in food has represented as a critical issue due to its neurotoxic effect on human health. L-Asparaginase (ASNase, EC 3.5.1.1) is considered a potential additive for acrylamide alleviation in food. However, low thermal stability hinders the application of ASNase in thermal food processing. To obtain highly thermal stable ASNase for its industrial application, a consensus-guided approach combined with site-directed saturation mutation (SSM) was firstly reported to engineer the thermostability of Mycobacterium gordonae L-asparaginase (GmASNase). The key residues Gly97, Asn159, and Glu249 were identified for improving thermostability. The combinatorial triple mutant G97T/N159Y/E249Q (TYQ) displayed significantly superior thermostability with half-life values of 61.65 ± 8.69 min at 50 °C and 5.12 ± 1.66 min at 55 °C, whereas the wild-type was completely inactive at these conditions. Moreover, its Tm value increased by 8.59 °C from parent wild-type. Interestingly, TYQ still maintained excellent catalytic efficiency and specific activity. Further molecular dynamics and structure analysis revealed that the additional hydrogen bonds, increased hydrophobic interactions, and favorable electrostatic potential were essential for TYQ being in a more rigid state for thermostability enhancement. These results suggested that our strategy was an efficient engineering approach for improving fundamental properties of GmASNase and offering GmASNase as a potential agent for efficient acrylamide mitigation in food industry. KEY POINTS: • The thermostability of GmASNase was firstly improved by consensus-guided engineering. • The half-life and Tm value of triple mutant TYQ were significantly increased. • Insight on improved thermostability of TYQ was revealed by MD and structure analysis.
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Affiliation(s)
- Huibing Chi
- College of Food Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
| | - Xiaoyu Zhu
- College of Food Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
| | - Juan Shen
- College of Food Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
| | - Zhaoxin Lu
- College of Food Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
| | - Fengxia Lu
- College of Food Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
| | - Yunbin Lyu
- College of Food Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China.
| | - Ping Zhu
- College of Food Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China.
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18
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Yu T, Boob AG, Volk MJ, Liu X, Cui H, Zhao H. Machine learning-enabled retrobiosynthesis of molecules. Nat Catal 2023. [DOI: 10.1038/s41929-022-00909-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
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