همایش ملی بیوانفورماتیک ایران

صفحه اصلی / 4th international edition and 13th Iranian Conference on Bioinformatics

Comprehensive Gene and Protein Catalog for Antimicrobial Environments: A Metagenomic Approach to Mitigate Antimicrobial Resistance

نویسندگان :

Donya Afshar Jahanshahi¹ Arad Ariaeenejad² Arman Hasannejad³ Mohammad Reza Zabihi⁴ Shohreh Ariaeenejad⁵ Kaveh Kavousi⁶

1- University of Tehran 2- University of Tehran 3- Post-doctoral researcher، Agricultural Biotechnology Research Institute of IRAN (ABRII), Karaj 4- University of Tehran 5- Post-doctoral researcher، Agricultural Biotechnology Research Institute of IRAN (ABRII), Karaj 6- University of Tehran

کلمات کلیدی :

Enzybiotics،Gene catalog،Genome،Metagenomic analysis،Environments for antimicrobial agents

چکیده :

Currently, the rise of antibiotic-resistant microorganisms presents substantial challenges to critical sectors such as healthcare, agriculture, and poultry production (Danis-Wlodarczyk et al., 2021; Thallinger et al., 2013; Wang et al., 2023). Tackling this issue requires the discovery of new antimicrobial agents, such as enzybiotics, that are capable of bypassing resistance mechanisms. A promising approach to identify such agents involves exploring biomolecules found in extreme microbiome environments, where microbial communities compete for survival and develop powerful antimicrobial properties. The role of antimicrobial-exposed environment microbiomes is pivotal for identifying microbes and enzymes to enhance antimicrobial resistance mitigation. Integrating computational methods and metagenomic approaches is essential to improve current strategies for combating antimicrobial resistance. Catalogs of genes, proteins, and metagenome-assembled genomes facilitate taxonomic and functional analysis of antimicrobial metagenome samples. To the best of our knowledge, no integrated gene and protein catalogs exist for environments containing antimicrobial agents. In this study, 15 whole-metagenome samples (including soil, seawater, groundwater, and plastic-contaminated metagenome samples) were combined. A total of 550 Gb of high-quality data were obtained with an average library fragment size. A comprehensive gene and protein catalog was generated by expanding a computational workflow comprising the quality control of reads, trimming, assembly, and binning of contigs from 15 source environments for antimicrobial agents. This catalog comprises of 46.8 million nonredundant genes and proteins. Among the carbohydrate-active enzymes (CAZymes), glycoside hydrolases (GHs) were the most abundant, as determined using the dbCAN2 (Zhang et al., 2018) software. The dbCAN2 analysis identified 465,325 CAZyme-encoding genes in the catalog. Our workflow and the catalog generated from 15 source environment samples provide an efficient resource for identifying antimicrobial enzymes and microorganisms, enabling researchers to enhance their understanding of genes and proteins in this metagenomic environment with minimal time and cost.

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