Literature DB >> 10074506

Evaluation of accuracy and repeatability of identification of food-borne pathogens by automated bacterial identification systems.

J A Odumeru1, M Steele, L Fruhner, C Larkin, J Jiang, E Mann, W B McNab.   

Abstract

The performances of five automated microbial identification systems, relative to that of a reference identification system, for their ability to accurately and repeatedly identify six common food-borne pathogens were assessed. The systems assessed were the MicroLog system (Biolog Inc., Hayward, Calif.), the Microbial Identification System (MIS; MIDI Inc., Newark, Del.), the VITEK system (bioMérieux Vitek, Hazelwood, Mo.), the MicroScan WalkAway 40 system (Dade-MicroScan International, West Sacramento, Calif.), and the Replianalyzer system (Oxoid Inc., Nepean, Ontario, Canada). The sensitivities and specificities of these systems for the identification of food-borne isolates of Bacillus cereus, Campylobacter jejuni, Listeria monocytogenes, Staphylococcus aureus, Salmonella spp., and verotoxigenic Escherichia coli were determined with 40 reference positive isolates and 40 reference negative isolates for each pathogen. The sensitivities of these systems for the identification of these pathogens ranged from 42.5 to 100%, and the specificities of these systems for the identification of these pathogens ranged from 32.5 to 100%. Some of the systems had difficulty correctly identifying the reference isolates when the results were compared to those from the reference identification tests. The sensitivity of MIS for the identification of S. aureus, B. cereus, E. coli, and C. jejuni, for example, ranged from 47.5 to 72. 5%. The sensitivity of the Microlog system for the identification of E. coli was 72.5%, and the sensitivity of the VITEK system for the identification of B. cereus was 42.5%. The specificities of four of the five systems for the identification of all of the species tested with the available databases were greater than or equal to 97.5%; the exception was MIS for the identification of C. jejuni, which displayed a specificity of 32.5% when it was tested with reference negative isolates including Campylobacter coli and other Campylobacter species. All systems had >80% sensitivities for the identification of Salmonella species and Listeria species at the genus level. The repeatability of these systems for the identification of test isolates ranged from 30 to 100%. Not all systems included all six pathogens in their databases; thus, some species could not be tested with all systems. The choice of automated microbial identification system for the identification of a food-borne pathogen would depend on the availability of identification libraries within the systems and the performance of the systems for the identification of the pathogen.

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Mesh:

Year:  1999        PMID: 10074506      PMCID: PMC88629     

Source DB:  PubMed          Journal:  J Clin Microbiol        ISSN: 0095-1137            Impact factor:   5.948


  22 in total

1.  Evaluation of the Biolog automated microbial identification system.

Authors:  J M Klingler; R P Stowe; D C Obenhuber; T O Groves; S K Mishra; D L Pierson
Journal:  Appl Environ Microbiol       Date:  1992-06       Impact factor: 4.792

2.  Evaluation of the autoSCAN-W/A system for rapid (2-hour) identification of members of the family Enterobacteriaceae.

Authors:  C M O'Hara; J M Miller
Journal:  J Clin Microbiol       Date:  1992-06       Impact factor: 5.948

3.  Evaluation of MicroScan Rapid Pos Combo panels for identification of staphylococci.

Authors:  L Stoakes; B C Schieven; E Ofori; P Ewan; R Lannigan; Z Hussain
Journal:  J Clin Microbiol       Date:  1992-01       Impact factor: 5.948

4.  Identification of clinical isolates of gram-negative nonfermentative bacteria by an automated cellular fatty acid identification system.

Authors:  G J Osterhout; V H Shull; J D Dick
Journal:  J Clin Microbiol       Date:  1991-09       Impact factor: 5.948

5.  Comparison of Crystal Enteric/Nonfermenter system, API 20E system, and Vitek AutoMicrobic system for identification of gram-negative bacilli.

Authors:  A Robinson; Y S McCarter; J Tetreault
Journal:  J Clin Microbiol       Date:  1995-02       Impact factor: 5.948

6.  Evaluation of Biolog system for identification of some gram-negative bacteria of clinical importance.

Authors:  B Holmes; M Costas; M Ganner; S L On; M Stevens
Journal:  J Clin Microbiol       Date:  1994-08       Impact factor: 5.948

7.  Comparative analysis of Bacillus anthracis, Bacillus cereus, and related species on the basis of reverse transcriptase sequencing of 16S rRNA.

Authors:  C Ash; J A Farrow; M Dorsch; E Stackebrandt; M D Collins
Journal:  Int J Syst Bacteriol       Date:  1991-07

8.  Gram-negative identification card for identification of Salmonella, Escherichia coli, and other Enterobacteriaceae isolated from foods: collaborative study.

Authors:  M T Knight; D W Wood; J F Black; G Gosney; R O Rigney; J R Agin; C K Gravens; S M Farnham
Journal:  J Assoc Off Anal Chem       Date:  1990 Sep-Oct

9.  Comparison of the MicroScan system with the API Staph-Ident system for species identification of coagulase-negative staphylococci.

Authors:  Z Hussain; L Stoakes; D L Stevens; B C Schieven; R Lannigan; C Jones
Journal:  J Clin Microbiol       Date:  1986-01       Impact factor: 5.948

10.  Gas-liquid chromatography of cellular fatty acids for identification of staphylococci.

Authors:  L Stoakes; M A John; R Lannigan; B C Schieven; M Ramos; D Harley; Z Hussain
Journal:  J Clin Microbiol       Date:  1994-08       Impact factor: 5.948

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Authors:  J Vivas; A I Sáa; A Tinajas; L Barbeyto; L A Rodríguez
Journal:  Appl Environ Microbiol       Date:  2000-04       Impact factor: 4.792

2.  Particular biochemical profiles for enterohemorrhagic Escherichia coli O157:H7 isolates on the ID 32E system.

Authors:  A Leclercq; B Lambert; D Pierard; J Mahillon
Journal:  J Clin Microbiol       Date:  2001-03       Impact factor: 5.948

Review 3.  Current and developing technologies for monitoring agents of bioterrorism and biowarfare.

Authors:  Daniel V Lim; Joyce M Simpson; Elizabeth A Kearns; Marianne F Kramer
Journal:  Clin Microbiol Rev       Date:  2005-10       Impact factor: 26.132

4.  Estimated Numbers of Community Cases of Illness Due to Salmonella, Campylobacter and Verotoxigenic Escherichia Coli: Pathogen-specific Community Rates.

Authors:  M Kate Thomas; Shannon E Majowicz; Paul N Sockett; Aamir Fazil; Frank Pollari; Kathryn Doré; James A Flint; Victoria L Edge
Journal:  Can J Infect Dis Med Microbiol       Date:  2006-07       Impact factor: 2.471

5.  Diagnostic challenges with accurate identification of Listeria monocytogenes isolates from food and environmental samples in South Africa.

Authors:  Teena S M Thomas; Juno Thomas; Karren le Roux; Sanelisiwe T Duze; Faith Mkhwanazi; Adriano Duse
Journal:  Afr J Lab Med       Date:  2022-05-23

6.  Physiologic and metabolic characterization of a new marine isolate (BM39) of Pantoea sp. producing high levels of exopolysaccharide.

Authors:  Silvia Silvi; Paolo Barghini; Arianna Aquilanti; Belen Juarez-Jimenez; Massimiliano Fenice
Journal:  Microb Cell Fact       Date:  2013-01-29       Impact factor: 5.328

7.  Development of a biosensor protein bullet as a fluorescent method for fast detection of Escherichia coli in drinking water.

Authors:  Ignacio Gutiérrez-Del-Río; Laura Marín; Javier Fernández; María Álvarez San Millán; Francisco Javier Ferrero; Marta Valledor; Juan Carlos Campo; Natalia Cobián; Ignacio Méndez; Felipe Lombó
Journal:  PLoS One       Date:  2018-01-05       Impact factor: 3.240

  7 in total

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