Characterization of mycobacteria species by HPLC and pattern recognition.
Multivariate methods of analysis are used to characterize 36 mycobacteria species following high-performance liquid chromatography (HPLC) of extracts of mycolic acids. After growth of the bacterial cultures, cell wall mycolic acids are saponified, extracted, then derivatized to the p-bromophenacyl esters. Reversed-phase HPLC with gradient elution separates 38 peaks in 10 min, plus an internal standard. A training set of 276 samples is composed and classification models are developed to predict the mycobacteria species. Classifications during the training phase are 91 and 95% accurate for single-pass and multilevel approaches, respectively. Validation is performed with a 549-sample set; successful classifications of known species are 87 and 92%, respectively. Bunching the predictions of MAIS complex species into one category improves the latter result to 97% correctly classified species. Fourteen of the 27 species (including M. tuberculosis) are classified without error in the validation data set.
Ramos
L S
LS
Infometrix, Inc., Seattle, Washington 98121.
D015373:Bacterial Typing Techniques; D002851:Chromatography, High Pressure Liquid / Q000379:methods*; D015999:Multivariate Analysis; D009161:Mycobacterium / Q000737:chemistry / Q000145:classification* / Q000302:isolation & purification; D009171:Mycolic Acids / Q000032:analysis; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D013045:Species Specificity
D009171:Mycolic Acids