• DocumentCode
    1784730
  • Title

    Identification and characterization of accessory genomes in bacterial species based on genome comparison and metagenomic recruitment

  • Author

    Mingjie Wang ; Haixu Tang ; Yuzhen Ye

  • Author_Institution
    Sch. of Inf. & Comput., Indiana Univ. Bloomington, Bloomington, IN, USA
  • fYear
    2014
  • fDate
    2-5 Nov. 2014
  • Firstpage
    17
  • Lastpage
    24
  • Abstract
    Accessory genomes in bacterial species carry important genetic elements that are frequently related to antibiotic resistance, virulence factors, and the biotransformation of xenobiotics. Facilitated by the recent advances in sequencing technology, bacterial genomes and metagenomes are accumulating at an unprecedented pace, providing opportunities for studies of accessory genomes. Comparison of closely related genomes reveals potential (and static) accessory genomes, and metagenomic recruitment (i.e., mapping metagenomic sequences onto reference genomes) provides insights into the nature and the dynamics of the accessory portion of the genomes. Recent metagenomic recruitment approaches focus on the identification of `metagenomic islands´ (MIs), segments in reference genomes that are under-recruiting in metagenomic samples and therefore likely to be mobile genetic elements (MGEs) in accessory genomes. However, the discovery of MIs often relies on manual inspection of the read recruitment plots. Here we introduce a method that integrates comparison of closely related genomes using A-Bruijn graph, metagenomic recruitment, and recurrent analysis for the identification and characterization of accessory genomes. In addition to metage-nomic islands (valleys), our method reveals `metagenomic peaks´ (MPs), segments in a reference genome that disproportionally recruit more metagenomic sequencing reads as compared to the remaining of the reference genome, indicating an enrichment of those segments in specific environments. Our method facilitates automated detection and characterization of accessory genomes at a large scale, and leads to the observation that MGEs are largely specific to environments, as demonstrated in the discovery of MGEs related to Streptococcus mitis in human microbiomes.
  • Keywords
    bioinformatics; drugs; genetics; genomics; graph theory; microorganisms; A-Bruijn graph; MGE; MP; Streptococcus mitis; accessory genome characterization; accessory genome identification; antibiotic resistance; automated detection; bacterial genomes; bacterial species; biotransformation; environments; genome comparison; human microbiomes; metagenomes; metagenomic island identification; metagenomic peaks; metagenomic recruitment; metagenomic sequences; metagenomic sequencing; mobile genetic elements; read recruitment plots; recurrent analysis; reference genomes; sequencing technology; virulence factors; xenobiotics; Bioinformatics; Genomics; Iterative methods; Microorganisms; Recruitment; Sequential analysis; Strain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine (BIBM), 2014 IEEE International Conference on
  • Conference_Location
    Belfast
  • Type

    conf

  • DOI
    10.1109/BIBM.2014.6999121
  • Filename
    6999121