Comparison of Some Bacterial Identification Methods

Yıl 2019, Cilt: 3 Sayı: 1, 9 - 12, 30.04.2019

Özgül Gülaydın İsmail Hakkı Ekin Cihat Öztürk Ziya İlhan Erdal Öğün

Öz

Objective:
















In
this study, three different methods were compared for the identification of
some Gram positive and Gram negative reference bacteria.

Materials and Methods:
















For
this purpose the identification accuracy rates of Enterococcus faecalis, Enterococcus faecium, Streptococcus agalactiae,
Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Salmonella
typhimurium, Serratia marcescens were analysed by conventional bacteriological
methods, commercial bacterial identification test kit (Microgen™ ID) and automated
bacteria identification system (BD Phoenix 100™).

Results:
















As a
result of analyses, the identification accuracy rates of examined cultures were
94.5%, 95.2%, 94.6%, 89.6%, 91.1%, 92.5%, 86.9%, 96.4% by conventional
bacteriological methods, 93.84%, 89.2%, 98.86%, 96.55%, 97.98%, 95.43%, 86.69%,
92.39% by commercial bacterial identification test kit and 98%, 99%, 99%, 96%,
96%, 97%, 99%, 98% by automated bacteria identification system, respectively.

Conclusion: In comparison of methods, the identification accuracy
values obtained from the automated system were higher than the other methods. It
was concluded that automated identification systems that developed for
accurate, reliable and rapid identification of bacteria, could be used as an
alternative to conventional methods and commercial kits. In addition, it was
thought that it would be useful to evaluate the identification of biotypes
obtained from clinical isolates by similar methods.

Anahtar Kelimeler

Bacteria, Identification, Conventional methods, Automated systems

Kaynakça

• Arda M (2006). Temel Mikrobiyoloji, 3. Baskı, 80-102, Medisan Yayınları, Ankara.Barenfanger J, Drake C, Kacich G (1999). Clinical and financial benefits of rapid bacterial identification and antimicrobial susceptibility testing. J Clin Microbiol, 37 (5):1415-1418.Berktaş M (2009). Otomatize tanımlama sistemleri tanımlamada artıları ve eksileri. Klinik Mikrobiyoloji Uzmanlığı ve Laboratuvar Uygulamaları Sempozyumu, 23-24 Ekim 2009 Ankara.Blankenfeld-Enkvist GV, Brannback M (2002). Technological trends and needs in food diagnostics. Technol Review, 132/2002.Carroll KC, Glanz BD, Borek AP, Burger C, Bhally HS, Henciak S, Flayhart D (2006). Evaluation of the BD Phoenix Automated Microbiology System for Identification and Antimicrobial Susceptibility Testing of Enterobacteriaceae, J Clin Microbiol, 44 (10), 3506-3509.Carter GR (1984). Diagnostic Procedurs in Veterinary Bacteriology and Mycology. Fourth edition. Springfield,Illinois, USA.Felmingham D, Brown DFJ (2001). Instrumentation in antimicrobial susceptibility testing. J Antimicrobial Chemother, 48 (Suppl 1): 81-85.Ferraro MJ, Jorgenson JH (1999). Manual of clinical microbiology, susceptibility testing instrumentation and computirized expert sysytems for data analysis and interpretation. In: Murray PR, Baron EJ, Pfalller MA, Tenover FC and Yolken RH (eds). 7th ed. Washington, DC: American Society for Microbiology, pp:1539-600.Fung DYC (2002). Rapid methods and automation in microbiology. Compreh Rev Food Sci Food Safety, 1: 3-21.Fung DYC (2006). Rapid methods and automation in microbiology: 25 years of development and predictions. Bull Tech U Ist, 54 (4): 45-55.Gülaydın Ö (2018). Sığırların solunum yolundan izole edilen Pasteurella multocida fenotip ve genotiplerinde virülens genlerin dağılımı. Van Yüzüncü Yıl Üniversitesi Sağlık Bilimleri Enstitüsü Mikrobiyoloji Anabilim Dalı Doktora Tezi, Van.Koneman EW, Allen SD, Dowel VR, Janda WM, Sommers HM, Winn WC (1988). Color Atlas and Text Book of Diagnostic Microbiology. Third edition. Lippincott Comp. Philadelphia, USA.Koneman EW, Allen SD, Janda WM, Schreckenberger PC, Winn WC (1997). Guidelines for the collection, transport, processing, analysis and reporting of cultures from specific specimen sources. In: Koneman EW, Allen SD, Janda WM, Schreckenberger PC, Winn WC (eds). Color Atlas and Textbook of Diagnostic Microbiology. 5th ed. New York: Lippincott Philadelphia, pp:121-70.Layer F, Ghebremedhin B, Moder KA, König W, König B (2006). Comparative study using various methods for identification of Staphylococcus species in clinical specimens. J Clin Microbiol. 44 (8): 2824-2830.Lenette EH, Balows A, Hausler JWJ, Shadomy JH (1985). Manual of Clinical Microbiology. USA. 4, 1149.Lizarazo YAV, Ferri EFR, Martı´n CBG (2008). Evaluation of different API systems for identification of porcine Pasteurella multocida isolates. Res Vet Sci, 85, 453-456.Menozzi MG,Eigner U, Covan S, Rossi S, Somenzi P, Dettori G, Chezzi C, Fahr AM (2006). Two center collaborative evaluation of performance of the BD Phoenix micribiology system for identification and antimicrobial susceptibility testing of Gram Negative Bacteria. J Clin Microbiol. 44 (11): 4085–4094.O’Hara CM (2006). Evaluation of the Phoenix 100 ID/AST System and NID panel for identification of Enterobacteriaceae, Vibrionaceae, and commonly isolated nonenteric Gram negative bacilli. J Clin Microbiol. 44 (3): 928–933.Snyder JW, Munier GK, Johnson CL (2008). Direct comparison of the BD phoenix system with the MicroScan WalkAway system for identification and antimicrobial susceptibility testing of Enterobacteriaceae and nonfermentative Gram negative organisms. J Clin Microbiol. 46 (7): 2327-2333. Stefaniuk E, Baraniak A, Gniadkowski M, Hryniewicz W (2003). Evaluation of the BD Phoenix Automated Identification and Susceptibility Testing System in Clinical Microbiology Laboratory Practice, Eur J Clin Microbiol Infect Dis, 22, 479–485.