期刊论文详细信息
BMC Microbiology
A species independent universal bio-detection microarray for pathogen forensics and phylogenetic classification of unknown microorganisms
Research Article
L Garry Adams1  Jenni N Weeks2  Zhaohui Sun3  John McCormick3  Shamira J Shallom3  Cristi L Galindo3  Harold R Garner3  Lauren McIver3 
[1] Department of Veterinary Pathobiology, College of Veterinary Medicine, Texas A & M University, College Station, TX, USA;St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, USA;Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, USA;
关键词: Lactobacillus Plantarum;    Rift Valley Fever Virus;    Francisella Tularensis;    Brucella Abortus;    Brucella Species;   
DOI  :  10.1186/1471-2180-11-132
 received in 2011-01-10, accepted in 2011-06-14,  发布年份 2011
来源: Springer
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【 摘 要 】

BackgroundThe ability to differentiate a bioterrorist attack or an accidental release of a research pathogen from a naturally occurring pandemic or disease event is crucial to the safety and security of this nation by enabling an appropriate and rapid response. It is critical in samples from an infected patient, the environment, or a laboratory to quickly and accurately identify the precise pathogen including natural or engineered variants and to classify new pathogens in relation to those that are known. Current approaches for pathogen detection rely on prior genomic sequence information. Given the enormous spectrum of genetic possibilities, a field deployable, robust technology, such as a universal (any species) microarray has near-term potential to address these needs.ResultsA new and comprehensive sequence-independent array (Universal Bio-Signature Detection Array) was designed with approximately 373,000 probes. The main feature of this array is that the probes are computationally derived and sequence independent. There is one probe for each possible 9-mer sequence, thus 49 (262,144) probes. Each genome hybridized on this array has a unique pattern of signal intensities corresponding to each of these probes. These signal intensities were used to generate an un-biased cluster analysis of signal intensity hybridization patterns that can easily distinguish species into accepted and known phylogenomic relationships. Within limits, the array is highly sensitive and is able to detect synthetically mixed pathogens. Examples of unique hybridization signal intensity patterns are presented for different Brucella species as well as relevant host species and other pathogens. These results demonstrate the utility of the UBDA array as a diagnostic tool in pathogen forensics.ConclusionsThis pathogen detection system is fast, accurate and can be applied to any species. Hybridization patterns are unique to a specific genome and these can be used to decipher the identity of a mixed pathogen sample and can separate hosts and pathogens into their respective phylogenomic relationships. This technology can also differentiate between different species and classify genomes into their known clades. The development of this technology will result in the creation of an integrated biomarker-specific bio-signature, multiple select agent specific detection system.

【 授权许可】

Unknown   
© Shallom et al; licensee BioMed Central Ltd. 2011. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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【 参考文献 】
  • [1]
  • [2]
  • [3]
  • [4]
  • [5]
  • [6]
  • [7]
  • [8]
  • [9]
  • [10]
  • [11]
  • [12]
  • [13]
  • [14]
  • [15]
  • [16]
  • [17]
  • [18]
  • [19]
  • [20]
  • [21]
  • [22]
  • [23]
  • [24]
  • [25]
  • [26]
  • [27]
  • [28]
  • [29]
  • [30]
  • [31]
  • [32]
  • [33]
  • [34]
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