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Title: Pathogenicity island mobility and gene content.

Technical Report ·
DOI:https://doi.org/10.2172/1104780· OSTI ID:1104780

Key goals towards national biosecurity include methods for analyzing pathogens, predicting their emergence, and developing countermeasures. These goals are served by studying bacterial genes that promote pathogenicity and the pathogenicity islands that mobilize them. Cyberinfrastructure promoting an island database advances this field and enables deeper bioinformatic analysis that may identify novel pathogenicity genes. New automated methods and rich visualizations were developed for identifying pathogenicity islands, based on the principle that islands occur sporadically among closely related strains. The chromosomally-ordered pan-genome organizes all genes from a clade of strains; gaps in this visualization indicate islands, and decorations of the gene matrix facilitate exploration of island gene functions. A %E2%80%9Clearned phyloblocks%E2%80%9D method was developed for automated island identification, that trains on the phylogenetic patterns of islands identified by other methods. Learned phyloblocks better defined termini of previously identified islands in multidrug-resistant Klebsiella pneumoniae ATCC BAA-2146, and found its only antibiotic resistance island.

Research Organization:
Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
DOE Contract Number:
AC04-94AL85000
OSTI ID:
1104780
Report Number(s):
SAND2013-8906; 477342
Country of Publication:
United States
Language:
English

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