RT Journal Article
SR Electronic(1)
A1 Plikaytis, Brian D.
A1 Plikaytis, Bonnie B.
A1 Shinnick, Thomas M.YR 1992
T1 Computer-assisted pattern recognition model for the identification of slowly growing mycobacteria including Mycobacterium tuberculosis
JF Microbiology,
VO 138
IS 11
SP 2265
OP 2273
DO https://doi.org/10.1099/00221287-138-11-2265
PB Microbiology Society,
SN 1465-2080,
AB We present a computerized pattern recognition model used to speciate mycobacteria based on their restriction fragment length polymorphism (RFLP) banding patterns. DNA fragment migration distances were normalized to minimize lane-to-lane variability of band location both within and among gels through the inclusion of two internal size standards in each sample. The computer model used a library of normalized RFLP patterns derived from samples of known origin to create a probability matrix which was then used to classify the RFLP patterns from samples of unknown origin. The probability matrix contained the proportion of bands that fell within defined migration distance windows for each species in the library of reference samples. These proportions were then used to compute the likelihood that the banding pattern of an unknown sample corresponded to that of each species represented in the probability matrix. As a test of this process, we developed an automated, computer-assisted model for the identification of Mycobacterium species based on their normalized RFLP banding patterns. The probability matrix contained values for the M. tuberculosis complex, M. avium, M. intracellulare, M. kansasii and M. gordonae species. Thirty-nine independent strains of known origin, not included in the probability matrix, were used to test the accuracy of the method in classifying unknowns: 37 of 39 (94.9%) were classified correctly. An additional set of 16 strains of known origin representing species not included in the model were tested to gauge the robustness of the probability matrix. Every sample was correctly identified as an outlier, i.e. a member of a species not included in the original matrix. This strategy may be readily adapted to other chromatographic and electrophoretic systems that generate peak profiles or banding patterns.,
UL https://www.microbiologyresearch.org/content/journal/micro/10.1099/00221287-138-11-2265