ICEO, a biological ontology for representing and analyzing bacterial integrative and conjugative elements.

Journal: Scientific data
PMID: 35058462

Abstract

Bacterial integrative and conjugative elements (ICEs) are highly modular mobile genetic elements critical to the horizontal transfer of antibiotic resistance and virulence factor genes. To better understand and analyze the ongoing increase of ICEs, we developed an Integrative and Conjugative Element Ontology (ICEO) to represent the gene components, functional modules, and other information of experimentally verified ICEs. ICEO is aligned with the upper-level Basic Formal Ontology and reuses existing reliable ontologies. There are 31,081 terms, including 26,814 classes from 14 ontologies and 4128 ICEO-specific classes, representing the information of 271 known experimentally verified ICEs from 235 bacterial strains in ICEO currently and 311 predicted ICEs of 272 completely sequenced Klebsiella pneumoniae strains. Three ICEO use cases were illustrated to investigate complex joins of ICEs and their harboring antibiotic resistance or virulence factor genes by using SPARQL or DL query. ICEO has been approved as an Open Biomedical Ontology library ontology. It may be dedicated to facilitating systematical ICE knowledge representation, integration, and computer-assisted queries.

Authors

  • Meng Liu
  • Jialin Liu
    School of Pharmacy, Second Military Medical University, Shanghai, 200433, China.
  • Guitian Liu
    State Key Laboratory of Microbial Metabolism, Joint International Laboratory on Metabolic & Developmental Sciences, School of Life Sciences & Biotechnology, Shanghai Jiao Tong University, Shanghai, 200030, China.
  • Hui Wang
    Department of Vascular Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
  • Xiaoli Wang
    Demonstration Center of Future Product, Beijing Aircraft Technology Research Institute, COMAC, Beijing, China.
  • Zixin Deng
    State Key Laboratory of Microbial Metabolism, Joint International Laboratory on Metabolic & Developmental Sciences, School of Life Sciences & Biotechnology, Shanghai Jiao Tong University, Shanghai, 200030, China.
  • Yongqun He
    University of Michigan Medical School, Ann Arbor, MI 48109 USA ; Unit for Laboratory Animal Medicine, Department of Microbiology and Immunology, Center for Computational Medicine and Bioinformatics, and Comprehensive Cancer Center, University of Michigan Medical School, 1301 MSRB III, 1150 W. Medical Dr., Ann Arbor, MI 48109 USA.
  • Hong-Yu Ou
    State Key Laboratory of Microbial Metabolism, Joint International Laboratory on Metabolic & Developmental Sciences, School of Life Sciences & Biotechnology, Shanghai Jiao Tong University, Shanghai, 200030, China. hyou@sjtu.edu.cn.

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