TY - JOUR
T1 - Identification of clinical isolates of gram-negative nonfermentative bacteria by an automated cellular fatty acid identification system
AU - Osterhout, G. J.
AU - Shull, V. H.
AU - Dick, J. D.
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 1991
Y1 - 1991
N2 - An automated cellular fatty acid (CFA) bacterial identification system, Microbial Identification System (MIS; Microbial ID, Newark, Del.), was compared with a conventional system for the identification of 573 strains of gram-negative nonfermentative bacteria. MIS identifications were based exclusively on the CFA composition following 22 to 26 h of growth at 28°C on Trypticase soy agar. MIS identifications were listed with a confidence measurement (similarity index [SI]) on a scale of 0 to 1.0 A value of ≥0.5 was considered a good match. The MIS correctly listed as the first choice 478 of 532 (90%) strains contained in the data base. However, only 314 (59%) had SI values of ≥ 0.5. Of the 54 strains in which there was not agreement, 37 belonged to the genera Acinetobacter, Moraxella, or Alcaligenes or were Pseudomonas pickettii. Reproducibility studies suggest that SI variation is most likely a function of a difference in culture age at the time of analysis, which is due to the relatively low temperature and time of incubation. Other discrepancies were attributable to insufficiently characterized library entries or an inability to differentiate chemotaxonomically closely related species. The MIS, as the first automated CFA identification system, is an accurate, efficient, and relatively rapid method for the identification of gram-negative nonfermentative bacteria. The development of a CFA library with the media and incubation conditions routinely used for the isolation of clinical pathogens could further decrease the identification time and provide an increase in accuracy.
AB - An automated cellular fatty acid (CFA) bacterial identification system, Microbial Identification System (MIS; Microbial ID, Newark, Del.), was compared with a conventional system for the identification of 573 strains of gram-negative nonfermentative bacteria. MIS identifications were based exclusively on the CFA composition following 22 to 26 h of growth at 28°C on Trypticase soy agar. MIS identifications were listed with a confidence measurement (similarity index [SI]) on a scale of 0 to 1.0 A value of ≥0.5 was considered a good match. The MIS correctly listed as the first choice 478 of 532 (90%) strains contained in the data base. However, only 314 (59%) had SI values of ≥ 0.5. Of the 54 strains in which there was not agreement, 37 belonged to the genera Acinetobacter, Moraxella, or Alcaligenes or were Pseudomonas pickettii. Reproducibility studies suggest that SI variation is most likely a function of a difference in culture age at the time of analysis, which is due to the relatively low temperature and time of incubation. Other discrepancies were attributable to insufficiently characterized library entries or an inability to differentiate chemotaxonomically closely related species. The MIS, as the first automated CFA identification system, is an accurate, efficient, and relatively rapid method for the identification of gram-negative nonfermentative bacteria. The development of a CFA library with the media and incubation conditions routinely used for the isolation of clinical pathogens could further decrease the identification time and provide an increase in accuracy.
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U2 - 10.1128/jcm.29.9.1822-1830.1991
DO - 10.1128/jcm.29.9.1822-1830.1991
M3 - Article
C2 - 1774302
AN - SCOPUS:0025938283
SN - 0095-1137
VL - 29
SP - 1822
EP - 1830
JO - Journal of Clinical Microbiology
JF - Journal of Clinical Microbiology
IS - 9
ER -