Abstract
Antimicrobial agents play a vital role in human and environmental health, with applications spanning medicine, food preservation, agriculture, and biotechnology. Among them, enzybiotics enzyme-based antimicrobials have emerged as powerful alternatives to conventional antibiotics due to their targeted mechanisms and lower propensity for resistance. Beyond their medical relevance, enzybiotics have emerging applications in food preservation, animal health, and agriculture, thereby broadening their industrial and environmental value. To support the discovery and characterization of these versatile biomolecules, we present the first genome-resolved metagenomic gene and protein targeted enzybiotic catalog focused on enzybiotics, derived from diverse environmental microbiomes. The Microbial Enzybiotic Gene and Protein Catalog (MiGPC), integrates 15 whole-metagenome datasets from oceans, soils, fecal samples, vegetation, and plastic-contaminated environments, capturing a wide ecological spectrum. Enzybiotic sequences were compiled through a hybrid strategy combining public database mining and manual literature curation, yielding over 136,000 enzybiotic sequences, 7654 metagenome-assembled genomes (MAGs), and ~ 100 million unique genes and proteins. MiGPC integrates taxonomic and enzybiotic gene profiles, offering a robust platform for the discovery, annotation, and ecological mapping of antimicrobial enzymes. Functional analyses using KEGG and eggNOG revealed that approximately 62% of the genes remained uncharacterized, highlighting a rich source of potentially novel functions. Glycoside hydrolases and glycosyl transferases were the most prevalent CAZyme families, while the dominant enzybiotic-producing taxa belonged primarily to the Pseudomonadota and Bacillota phyla. Statistical modeling uncovered two major ecological clusters that distinguished polluted from relatively pristine environments. MiGPC enables high-throughput screening of previously unexplored metagenomes, facilitating the identification of novel antimicrobial agents from under characterized ecosystems. Overall, MiGPC represents a landmark resource that will support multi-omics research, microbial ecology, and the development of next-generation biotechnological solutions based on enzybiotics.
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Data availability
The metagenomic sequencing data used in this study are publicly available in the NCBI Sequence Read Archive (SRA) under the following accession numbers: SRR6441339, SRR28167100, SRR26623185, ERR4298344, SRR15826900, ERR9631090, SRR28167096, SRR28167104, SRR25490518, SRR26901926, SRR13060942, SRR29090698, SRR23085642, and SRR12059165. Additionally, the final integrated gene and protein catalogs, as well as the catalog of predicted antimicrobial enzymes (enzybiotics) generated in this study, are available in a publicly accessible GitHub repository (https://github.com/kkavousi/MiGPC-Catalog).
Abbreviations
- MiGPC:
Microbial enzybiotic gene and protein catalog
- MDR:
Multidrug-resistant
- MAGs:
Metagenome assemble genome
- GH:
Glycoside hydrolases
- AA:
Auxiliary activity
- CBM:
Carbohydrate-binding modules
- GT:
Glycosyl transferase
- CE:
Carbohydrate esterase
- PL:
Polysaccharide lyase
- AMR:
Antimicrobial resistance
- PIGC:
Pig integrated gene catalog
- PDEC:
Plastic-degrading enzyme catalog
- MeSH:
Medical subject headings
- GTDB-tk:
Genome taxonomy database toolkit
- GMM:
Gaussian mixture model
- MeTarEnz:
Metagenomic targeted enzyme miner
- CAZy:
Carbohydrate-active enzymes
- PE:
Polyethylene
- PET:
Polyethylene terephthalate
- PS:
Polyester
- ROS:
Reactive oxygen species
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Acknowledgements
This research was carried out by the support of the Institute of Biochemistry and Biophysics (IBB), University of Tehran and Department of Systems and Synthetic Biology, Agricultural Biotechnology Research Institute of Iran (ABRII).
Funding
This research was supported by grants from Agricultural Biotechnology Research Institute of Iran (ABRII) and Center for International Scientific Studies & Collaborations (CISSC) (funding reference number 4020052).
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**Shohreh Ariaeenejad: ** Conceptualization, Experimental Methodology, Writing – original draft, Resources, Project administration, Writing – review & editing.**Kaveh Kavousi: ** Conceptualization, Methodology, computational and machine learning approaches and bioinformatics data analysis, Project administration, Writing – review & editing.**Donya Afshar Jahanshahi: ** Contributed to the computational and machine learning approaches and bioinformatics data analysis, Writing – original draft.**Mohammad Reza Zabihi: ** Contributed to the computational and machine learning approaches, Writing – original draft.**Arad Ariaeenejad: ** Contributed to the computational and machine learning approaches and bioinformatics data analysis, Writing – original draft.**Arman Hasannejad; ** Contributed to the computational and machine learning approaches and bioinformatics data analysis, Writing – original draft.**Mohammad Reza Ghaffari: ** Conceptualization, Experimental Methodology, Writing – original draft, Resources, Project administration, Writing – review & editing.
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Statistical analysis
Statistical analyses and visualizations were conducted in the Python 3.11.0 and PyCharm 2022.2.4 environment, utilizing the Matplotlib and Seaborn packages. Additionally, the diversity of taxa and taxonomic phylogenetic tree were visualized using Interactive Tree Of Life (iTOL) v5 65, respectively. Further information can be obtained from the corresponding author upon request.
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Afshar Jahanshahi, D., Ariaeenejad, A., Hasannejad, A. et al. MiGPC: a comprehensive catalog of enzybiotics from environmental metagenomes.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-44250-9
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DOI: https://doi.org/10.1038/s41598-026-44250-9
Keywords
- Enzybiotics
- Antimicrobial enzymes
- Metagenomic catalog
- Genome-resolved metagenomics
- Functional annotation
- Microbial ecology
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