Literature DB >> 11248519

Rapid identification of pathogenic bacteria by single-enzyme amplified fragment length polymorphism analysis.

N Velappan1, J L Snodgrass, J R Hakovirta, B L Marrone, S Burde.   

Abstract

Despite major progress in their treatment and prevention, bacterial infections remain a significant cause of morbidity and mortality worldwide. In responding to a disease outbreak, rapid and accurate identification of the bacterial species involved is of paramount importance. Strain level discrimination is desirable to allow selection of treatment modalities, and in the case of a deliberate release, for identification of the source. Single-enzyme amplified fragment length polymorphism (SE-AFLP) analysis was used to perform species and strain identification of subgroup I Bacilli, Yersinia, Staphylococci and Escherichia coli. By careful selection of AFLP primers, it was possible to obtain reproducible and sensitive identification to strain level, even within the highly monomorphic species Bacillus anthracis. SE-AFLP fragments can be analyzed using standard gel electrophoresis, and can be easily scored by visual inspection, due to the low complexity of the fingerprint obtained by this method. These features make SE-AFLP suitable for use in either field or laboratory applications.

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Year:  2001        PMID: 11248519     DOI: 10.1016/s0732-8893(00)00235-2

Source DB:  PubMed          Journal:  Diagn Microbiol Infect Dis        ISSN: 0732-8893            Impact factor:   2.803


  4 in total

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2.  Structural Variation (SV) Markers in the Basidiomycete Volvariella volvacea and Their Application in the Construction of a Genetic Map.

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Journal:  Int J Mol Sci       Date:  2015-07-22       Impact factor: 5.923

3.  Genome-Wide Linkage Mapping of QTL for Adult-Plant Resistance to Stripe Rust in a Chinese Wheat Population Linmai 2 × Zhong 892.

Authors:  Jindong Liu; Zhonghu He; Ling Wu; Bin Bai; Weie Wen; Chaojie Xie; Xianchun Xia
Journal:  PLoS One       Date:  2015-12-29       Impact factor: 3.240

Review 4.  A Systematic Review of Risk Analysis Tools for Differentiating Unnatural From Natural Epidemics.

Authors:  Xin Chen; Abrar Ahmad Chughtai; C Raina MacIntyre
Journal:  Mil Med       Date:  2017-11       Impact factor: 1.437

  4 in total

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