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Qiao C, Wang C, Luo H, Ma Y, Luo X, Zhang S, Huo D, Hou C. Development of a Zn-Based Single-Atom Nanozyme for Efficient Hydrolysis of Glycosidic Bonds. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024:e2402674. [PMID: 39096071 DOI: 10.1002/smll.202402674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 07/17/2024] [Indexed: 08/04/2024]
Abstract
Hydrolytic enzymes are essential components in second-generation biofuel technology and food fermentation processes. Nanozymes show promise for large-scale industrial applications as replacements for natural enzymes due to their distinct advantages. However, there remains a research gap concerning glycosidase nanozymes. In this study, a Zn-based single-atom nanozyme (ZnN4-900) is developed for efficient glycosidic bond hydrolysis in an aqueous solution. The planar structure of the class-porphyrin N4 material approximatively mimicked the catalytic centers of natural enzymes, facilitating oxidase-like (OXD-like) activity and promoting glycosidic bond cleavage. Theoretical calculations show that the Zn site can act as Lewis acids, attacking the C─O bond in glycosidic bonds. Additionally, ZnN4-900 has the ability to degrade starch and produce reducing sugars that increased yeast cell biomass by 32.86% and ethanol production by 14.56%. This catalyst held promising potential for enhancing processes in ethanol brewing and starch degradation industries.
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Affiliation(s)
- Cailin Qiao
- Key Laboratory for Biorheological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing, 400044, P. R. China
| | - Chao Wang
- Key Laboratory for Biorheological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing, 400044, P. R. China
- National Engineering Research Center of Solid-State Brewing, Luzhou Laojiao Group Co. Ltd., Luzhou, 646000, P. R. China
| | - Huibo Luo
- Liquor Making Biology Technology and Application of Key Laboratory of Sichuan Province, College of Bioengineering, Sichuan University of Science and Engineering, 188 University Town, Yi bin, 644000, P. R. China
| | - Yi Ma
- Liquor Making Biology Technology and Application of Key Laboratory of Sichuan Province, College of Bioengineering, Sichuan University of Science and Engineering, 188 University Town, Yi bin, 644000, P. R. China
| | - Xiaogang Luo
- Key Laboratory for Biorheological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing, 400044, P. R. China
| | - Suyi Zhang
- National Engineering Research Center of Solid-State Brewing, Luzhou Laojiao Group Co. Ltd., Luzhou, 646000, P. R. China
| | - Danqun Huo
- Key Laboratory for Biorheological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing, 400044, P. R. China
| | - Changjun Hou
- Key Laboratory for Biorheological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing, 400044, P. R. China
- Liquor Making Biology Technology and Application of Key Laboratory of Sichuan Province, College of Bioengineering, Sichuan University of Science and Engineering, 188 University Town, Yi bin, 644000, P. R. China
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Elisée E, Ducrot L, Méheust R, Bastard K, Fossey-Jouenne A, Grogan G, Pelletier E, Petit JL, Stam M, de Berardinis V, Zaparucha A, Vallenet D, Vergne-Vaxelaire C. A refined picture of the native amine dehydrogenase family revealed by extensive biodiversity screening. Nat Commun 2024; 15:4933. [PMID: 38858403 PMCID: PMC11164908 DOI: 10.1038/s41467-024-49009-2] [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: 09/21/2023] [Accepted: 05/20/2024] [Indexed: 06/12/2024] Open
Abstract
Native amine dehydrogenases offer sustainable access to chiral amines, so the search for scaffolds capable of converting more diverse carbonyl compounds is required to reach the full potential of this alternative to conventional synthetic reductive aminations. Here we report a multidisciplinary strategy combining bioinformatics, chemoinformatics and biocatalysis to extensively screen billions of sequences in silico and to efficiently find native amine dehydrogenases features using computational approaches. In this way, we achieve a comprehensive overview of the initial native amine dehydrogenase family, extending it from 2,011 to 17,959 sequences, and identify native amine dehydrogenases with non-reported substrate spectra, including hindered carbonyls and ethyl ketones, and accepting methylamine and cyclopropylamine as amine donor. We also present preliminary model-based structural information to inform the design of potential (R)-selective amine dehydrogenases, as native amine dehydrogenases are mostly (S)-selective. This integrated strategy paves the way for expanding the resource of other enzyme families and in highlighting enzymes with original features.
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Affiliation(s)
- Eddy Elisée
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 91057, Evry, France
| | - Laurine Ducrot
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 91057, Evry, France
| | - Raphaël Méheust
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 91057, Evry, France
| | - Karine Bastard
- School of Pharmacy, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, 2006, Australia
| | - Aurélie Fossey-Jouenne
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 91057, Evry, France
| | - Gideon Grogan
- York Structural Biology Laboratory, Department of Chemistry, University of York, Heslington, York, YO10 5DD, UK
| | - Eric Pelletier
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 91057, Evry, France
| | - Jean-Louis Petit
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 91057, Evry, France
| | - Mark Stam
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 91057, Evry, France
| | - Véronique de Berardinis
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 91057, Evry, France
| | - Anne Zaparucha
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 91057, Evry, France
| | - David Vallenet
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 91057, Evry, France.
| | - Carine Vergne-Vaxelaire
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 91057, Evry, France.
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Ariaeenejad S, Gharechahi J, Foroozandeh Shahraki M, Fallah Atanaki F, Han JL, Ding XZ, Hildebrand F, Bahram M, Kavousi K, Hosseini Salekdeh G. Precision enzyme discovery through targeted mining of metagenomic data. NATURAL PRODUCTS AND BIOPROSPECTING 2024; 14:7. [PMID: 38200389 PMCID: PMC10781932 DOI: 10.1007/s13659-023-00426-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 12/19/2023] [Indexed: 01/12/2024]
Abstract
Metagenomics has opened new avenues for exploring the genetic potential of uncultured microorganisms, which may serve as promising sources of enzymes and natural products for industrial applications. Identifying enzymes with improved catalytic properties from the vast amount of available metagenomic data poses a significant challenge that demands the development of novel computational and functional screening tools. The catalytic properties of all enzymes are primarily dictated by their structures, which are predominantly determined by their amino acid sequences. However, this aspect has not been fully considered in the enzyme bioprospecting processes. With the accumulating number of available enzyme sequences and the increasing demand for discovering novel biocatalysts, structural and functional modeling can be employed to identify potential enzymes with novel catalytic properties. Recent efforts to discover new polysaccharide-degrading enzymes from rumen metagenome data using homology-based searches and machine learning-based models have shown significant promise. Here, we will explore various computational approaches that can be employed to screen and shortlist metagenome-derived enzymes as potential biocatalyst candidates, in conjunction with the wet lab analytical methods traditionally used for enzyme characterization.
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Affiliation(s)
- Shohreh Ariaeenejad
- Department of Systems and Synthetic Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research Education and Extension Organization (AREEO), Karaj, Iran
| | - Javad Gharechahi
- Human Genetics Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Mehdi Foroozandeh Shahraki
- Laboratory of Complex Biological Systems and Bioinformatics (CBB), Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran
| | - Fereshteh Fallah Atanaki
- Laboratory of Complex Biological Systems and Bioinformatics (CBB), Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran
| | - Jian-Lin Han
- Livestock Genetics Program, International Livestock Research, Institute (ILRI), Nairobi, 00100, Kenya
- CAAS-ILRI Joint Laboratory On Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, China
| | - Xue-Zhi Ding
- Key Laboratory of Yak Breeding Engineering, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences (CAAS), Lanzhou, 730050, China
| | - Falk Hildebrand
- Gut Microbes and Health, Quadram Institute Bioscience, Norwich, Norfolk, UK
- Digital Biology, Earlham Institute, Norwich, Norfolk, UK
| | - Mohammad Bahram
- Department of Ecology, Swedish University of Agricultural Sciences, Ulls Väg 16, 756 51, Uppsala, Sweden
- Department of Botany, Institute of Ecology and Earth Sciences, University of Tartu, 40 Lai St, Tartu, Estonia
| | - Kaveh Kavousi
- Laboratory of Complex Biological Systems and Bioinformatics (CBB), Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran.
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Huang YY, Lv ZH, Zheng HZ, Zhu Q, Liu MT, Sang P, Wang F, Zhu D, Xian WD, Yin YR. Characterization of a thermophilic and glucose-tolerant GH1 β-glucosidase from hot springs and its prospective application in corn stover degradation. Front Microbiol 2023; 14:1286682. [PMID: 38179451 PMCID: PMC10764553 DOI: 10.3389/fmicb.2023.1286682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 12/05/2023] [Indexed: 01/06/2024] Open
Abstract
Introduction β-Glucosidase serves as the pivotal rate-limiting enzyme in the cellulose degradation process, facilitating the hydrolysis of cellobiose and cellooligosaccharides into glucose. However, the widespread application of numerous β-glucosidases is hindered by their limited thermostability and low glucose tolerance, particularly in elevated-temperature and high-glucose environments. Methods This study presents an analysis of a β-glucosidase gene belonging to the GH1 family, denoted lqbg8, which was isolated from the metagenomic repository of Hehua hot spring located in Tengchong, China. Subsequently, the gene was cloned and heterologously expressed in Escherichia coli BL21(DE3). Post expression, the recombinant β-glucosidase (LQBG8) underwent purification through a Ni affinity chromatography column, thereby enabling the in-depth exploration of its enzymatic properties. Results LQBG8 had an optimal temperature of 70°C and an optimum pH of 5.6. LQBG8 retained 100 and 70% of its maximum activity after 2-h incubation periods at 65°C and 70°C, respectively. Moreover, even following exposure to pH ranges of 3.0-10.0 for 24 h, LQBG8 retained approximately 80% of its initial activity. Notably, the enzymatic prowess of LQBG8 remained substantial at glucose concentrations of up to 3 M, with a retention of over 60% relative activity. The kinetic parameters of LQBG8 were characterized using cellobiose as substrate, with Km and Vmax values of 28 ± 1.9 mg/mL and 55 ± 3.2 μmol/min/mg, respectively. Furthermore, the introduction of LQBG8 (at a concentration of 0.03 mg/mL) into a conventional cellulase reaction system led to an impressive 43.7% augmentation in glucose yield from corn stover over a 24-h period. Molecular dynamics simulations offered valuable insights into LQBG8's thermophilic nature, attributing its robust stability to reduced fluctuations, conformational changes, and heightened structural rigidity in comparison to mesophilic β-glucosidases. Discussion In summation, its thermophilic, thermostable, and glucose-tolerant attributes, render LQBG8 ripe for potential applications across diverse domains encompassing food, feed, and the production of lignocellulosic ethanol.
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Affiliation(s)
- Yu-Ying Huang
- College of Agriculture and Biological Science, Dali University, Dali, China
| | - Zhi-Hua Lv
- College of Agriculture and Biological Science, Dali University, Dali, China
| | - Hong-Zhao Zheng
- College of Agriculture and Biological Science, Dali University, Dali, China
| | - Qian Zhu
- College of Agriculture and Biological Science, Dali University, Dali, China
| | - Meng-Ting Liu
- College of Agriculture and Biological Science, Dali University, Dali, China
- Key Laboratory of Bioinformatics and Computational Biology, Department of Education of Yunnan Province, Dali University, Dali, China
| | - Peng Sang
- College of Agriculture and Biological Science, Dali University, Dali, China
- Key Laboratory of Bioinformatics and Computational Biology, Department of Education of Yunnan Province, Dali University, Dali, China
| | - Fei Wang
- College of Agriculture and Biological Science, Dali University, Dali, China
| | - Dan Zhu
- College of Agriculture and Biological Science, Dali University, Dali, China
| | - Wen-Dong Xian
- Marine Microorganism Ecological and Application Lab, Marine Science and Technology College, Zhejiang Ocean University, Zhoushan, China
| | - Yi-Rui Yin
- College of Agriculture and Biological Science, Dali University, Dali, China
- Key Laboratory of Bioinformatics and Computational Biology, Department of Education of Yunnan Province, Dali University, Dali, China
- Cangshan Forest Ecosystem Observation and Research Station of Yunnan Province, Dali University, Dali, China
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