Precision enzyme discovery through targeted mining of metagenomic data

doi:10.1007/s13659-023-00426-8

Natural Products and Bioprospecting ›› 2024, Vol. 14 ›› Issue (1): 7-7.DOI: 10.1007/s13659-023-00426-8

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Precision enzyme discovery through targeted mining of metagenomic data

Shohreh Ariaeenejad¹, Javad Gharechahi², Mehdi Foroozandeh Shahraki³, Fereshteh Fallah Atanaki³, Jian-Lin Han^4,5, Xue-Zhi Ding⁶, Falk Hildebrand^7,8, Mohammad Bahram^9,10, Kaveh Kavousi³, Ghasem Hosseini Salekdeh¹¹

1. Department of Systems and Synthetic Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research Education and Extension Organization (AREEO), Karaj, Iran;
2. Human Genetics Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran;
3. Laboratory of Complex Biological Systems and Bioinformatics (CBB), Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran;
4. Livestock Genetics Program, International Livestock Research, Institute (ILRI), Nairobi, 00100, Kenya;
5. CAAS-ILRI Joint Laboratory On Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, China;
6. Key Laboratory of Yak Breeding Engineering, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences (CAAS), Lanzhou, 730050, China;
7. Gut Microbes and Health, Quadram Institute Bioscience, Norwich, Norfolk, UK;
8. Digital Biology, Earlham Institute, Norwich, Norfolk, UK;
9. Department of Ecology, Swedish University of Agricultural Sciences, Ulls Väg 16, 756 51, Uppsala, Sweden;
10. Department of Botany, Institute of Ecology and Earth Sciences, University of Tartu, 40 Lai St, Tartu, Estonia;
11. Faculty of Natural Sciences, Macquarie University, Sydney, NSW, Australia

Received:2023-10-25 Online:2024-02-19 Published:2024-02-24
Contact: Kaveh Kavousi,E-mail:kkavousi@ut.ac.ir;Ghasem Hosseini Salekdeh,E-mail:hsalekdeh@yahoo.com
Supported by:
Funding was provided by the Agricultural Biotechnology Research Institute of Iran (ABRII), Swedish Research Council (Vetenskapsrådet grant no.: 2017‐05019), and the BBSRC Institute Strategic Programme Gut Microbes and Health (BB/r012490/1, its constituent project BBS/e/F/000Pr10355).

Precision enzyme discovery through targeted mining of metagenomic data

1. Department of Systems and Synthetic Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research Education and Extension Organization (AREEO), Karaj, Iran;
2. Human Genetics Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran;
3. Laboratory of Complex Biological Systems and Bioinformatics (CBB), Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran;
4. Livestock Genetics Program, International Livestock Research, Institute (ILRI), Nairobi, 00100, Kenya;
5. CAAS-ILRI Joint Laboratory On Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, China;
6. Key Laboratory of Yak Breeding Engineering, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences (CAAS), Lanzhou, 730050, China;
7. Gut Microbes and Health, Quadram Institute Bioscience, Norwich, Norfolk, UK;
8. Digital Biology, Earlham Institute, Norwich, Norfolk, UK;
9. Department of Ecology, Swedish University of Agricultural Sciences, Ulls Väg 16, 756 51, Uppsala, Sweden;
10. Department of Botany, Institute of Ecology and Earth Sciences, University of Tartu, 40 Lai St, Tartu, Estonia;
11. Faculty of Natural Sciences, Macquarie University, Sydney, NSW, Australia

通讯作者: Kaveh Kavousi,E-mail:kkavousi@ut.ac.ir;Ghasem Hosseini Salekdeh,E-mail:hsalekdeh@yahoo.com
基金资助:
Funding was provided by the Agricultural Biotechnology Research Institute of Iran (ABRII), Swedish Research Council (Vetenskapsrådet grant no.: 2017‐05019), and the BBSRC Institute Strategic Programme Gut Microbes and Health (BB/r012490/1, its constituent project BBS/e/F/000Pr10355).

Abstract

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.

Key words: Metagenomics, Enzyme bioprospecting, Functional-based screening, Sequence-based screening, Protein structure prediction, Natural products

摘要： 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.

关键词: Metagenomics, Enzyme bioprospecting, Functional-based screening, Sequence-based screening, Protein structure prediction, Natural products

Shohreh Ariaeenejad, Javad Gharechahi, Mehdi Foroozandeh Shahraki, Fereshteh Fallah Atanaki, Jian-Lin Han, Xue-Zhi Ding, Falk Hildebrand, Mohammad Bahram, Kaveh Kavousi, Ghasem Hosseini Salekdeh. Precision enzyme discovery through targeted mining of metagenomic data[J]. Natural Products and Bioprospecting, 2024, 14(1): 7-7.

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Precision enzyme discovery through targeted mining of metagenomic data

Precision enzyme discovery through targeted mining of metagenomic data

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