title: Encyclopedia of bacterial gene circuits whose presence or absence correlate with pathogenicity--a large-scale system analysis of decoded bacterial genomes.
abstract: BACKGROUND
  Bacterial infections comprise a global health challenge as the incidences of antibiotic resistance increase. Pathogenic potential of bacteria has been shown to be context dependent, varying in response to environment and even within the strains of the same genus.
  
  
  RESULTS
  We used the KEGG repository and extensive literature searches to identify among the 2527 bacterial genomes in the literature those implicated as pathogenic to the host, including those which show pathogenicity in a context dependent manner. Using data on the gene contents of these genomes, we identified sets of genes highly abundant in pathogenic but relatively absent in commensal strains and vice versa. In addition, we carried out genome comparison within a genus for the seventeen largest genera in our genome collection. We projected the resultant lists of ortholog genes onto KEGG bacterial pathways to identify clusters and circuits, which can be linked to either pathogenicity or synergy. Gene circuits relatively abundant in nonpathogenic bacteria often mediated biosynthesis of antibiotics. Other synergy-linked circuits reduced drug-induced toxicity. Pathogen-abundant gene circuits included modules in one-carbon folate, two-component system, type-3 secretion system, and peptidoglycan biosynthesis. Antibiotics-resistant bacterial strains possessed genes modulating phagocytosis, vesicle trafficking, cytoskeletal reorganization, and regulation of the inflammatory response. Our study also identified bacterial genera containing a circuit, elements of which were previously linked to Alzheimer's disease.
  
  
  CONCLUSIONS
  Present study produces for the first time, a signature, in the form of a robust list of gene circuitry whose presence or absence could potentially define the pathogenicity of a microbiome. Extensive literature search substantiated a bulk majority of the commensal and pathogenic circuitry in our predicted list. Scanning microbiome libraries for these circuitry motifs will provide further insights into the complex and context dependent pathogenicity of bacteria.
authors.affiliation: School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, USA. ms3389@drexel.edu.
authors.forename: Maksim
authors.initials: M
authors.lastname: Shestov
authors.affiliation: College of Computing and Informatics, Drexel University, Philadelphia, PA, USA. santi@cs.drexel.edu.
authors.forename: Santiago
authors.initials: S
authors.lastname: Ontañón
authors.affiliation: School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, USA. aydin.tozeren@drexel.edu.
authors.forename: Aydin
authors.initials: A
authors.lastname: Tozeren
mesh_terms: D000900:Anti-Bacterial Agents / Q000494:pharmacology; D001419:Bacteria / Q000187:drug effects / Q000235:genetics* / Q000472:pathogenicity*; D001424:Bacterial Infections / Q000382:microbiology; D019295:Computational Biology / Q000379:methods; D024881:Drug Resistance, Bacterial; D053263:Gene Regulatory Networks; D005798:Genes, Bacterial; D016680:Genome, Bacterial; D023281:Genomics / Q000379:methods*; D054884:Host-Pathogen Interactions; D005810:Multigene Family
chemical_list: D000900:Anti-Bacterial Agents