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Updated: Oct 1, 2026

Direct Microbial Identification using An Automated Microbial Identification System to Facilitate the EUCAST RAST Method Without Mass Spectrometry
Published on: May 24, 2024
Identification of medically relevant Nocardia species with an abbreviated battery of tests
Deanna L Kiska1, Karen Hicks, David J Pettit
1Department of Clinical Pathology, SUNY Upstate Medical University, Syracuse, New York 13210, USA. KISKAD@upstate.edu
Abstract:
Identification of Nocardia to the species level is useful for predicting antimicrobial susceptibility patterns and defining the pathogenicity and geographic distribution of these organisms. We sought to develop an identification method which was accurate, timely, and employed tests which would be readily available in most clinical laboratories. We evaluated the API 20C AUX yeast identification system as well as several biochemical tests and Kirby-Bauer susceptibility patterns for the identification of 75 isolates encompassing the 8 medically relevant Nocardia species. There were few biochemical reactions that were sufficiently unique for species identification; of note, N. nova were positive for arylsulfatase, N. farcinica were positive for opacification of Middlebrook 7H11 agar, and N. brasiliensis and N. pseudobrasiliensis were the only species capable of liquefying gelatin. API 20C sugar assimilation patterns were unique for N. transvalensis, N. asteroides IV, and N. brevicatena. There was overlap among the assimilation patterns for the other species. Species-specific patterns of susceptibility to gentamicin, tobramycin, amikacin, and erythromycin were obtained for N. nova, N. farcinica, and N. brevicatena, while there was overlap among the susceptibility patterns for the other isolates. No single method could identify all Nocardia isolates to the species level; therefore, a combination of methods was necessary. An algorithm utilizing antibiotic susceptibility patterns, citrate utilization, acetamide utilization, and assimilation of inositol and adonitol accurately identified all isolates. The algorithm was expanded to include infrequent drug susceptibility patterns which have been reported in the literature but which were not seen in this study.
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