2 Characterization Tests for Numerical Taxonomy Studies

O’Brien, Mark F.; Colwell, Rita R.

doi:10.1016/s0580-9517(08)70408-2

Cited by 13 publications

(10 citation statements)

References 105 publications

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“…The test error (p = 2.71 %) was within the acceptable limits (38) and comparable to those obtained in other studies (p = 3.7, Goodfellow and Alderson (7); p = 7.1, Orchard and Goodfellow (28)). The classification in most cases gave clear groupings of species already defined by genetic and chemotaxonomic methods, although the choice of tests (carbon substrate utilization tests and qualitative enzyme tests) may be an overrepresentation of test groups discussed by O'Brien and Colwell (27). The recovery of the Nocardia farcinica strains and Nocardia asteroides strains in separate clusters was surprising, because these organisms share many properties.…”

Section: Discussionmentioning

confidence: 96%

Numerical classification and identification of some nocardioform bacteria.

Kämpfer

Dott

Kroppenstedt

1990

J. Gen. Appl. Microbiol.

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A total of 254 strains of the genera Nocardia, Rhodococcus, Amycolata, Amycolatopsis, Gordona and Pseudoamycolata were compared using numerical taxonomic techniques based on 273 physiological characters with the aid of miniaturized tests. Clustering was achieved using the unweighted pair group method with arithmetic averages (UPGMA) and the simple-matching coefficient (SSM) as the measure for similarity. Test error and overlap between the phena were within acceptable limits. Cluster groups were defined at the 87.4 to 91.3 % levels (SSM). A total of 25 clusters were obtained in the SSM/UPGMA analysis beside 16 single member clusters, which in most cases were marker strains of different species. For the 25 clusters, containing two or more strains, a matrix comprising frequencies for positive results of 35 tests was constructed. The minimum number of diagnostic characters was selected by computer programs (CHARSEP, DIACHAR, MOSTTYP). The final matrix consisting of 35 tests versus 25 phena was theoretically evaluated using a computer program (MATIDEN) and out of 238 strains, a total of 157 strains (65.96%) were correctly identified with a Willcox probability >0.999, further 18 strains (7.56%) achieved Willcox probabilities above 0.900 and 2 strains (0.84%) were identified correctly with a Willcox probability above 0.800. Correct identification results were obtained for a total of 56 strains (23.52%), but with low Willcox probabilities ranging between 0.500 and 0.800. A total of 5 strains (2.10%) could not be assigned to the correct phenon. In a subsequent practical evaluation of the matrix 32 of 40 tested strains (80.0%) were correctly identified with Willcox probabilities above 0.900.The genera Rhodococcus and Nocardia belong to the actinomycetes which are now largely defined on the basis of cell envelope lipids and peptidoglycan composition (8,40). The cell walls of representative nocardiae and rhodococci * Address reprint requests to: Dr . P. Kampfer, Fachgebiet Hygiene,

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Section: Discussionmentioning

confidence: 96%

Numerical classification and identification of some nocardioform bacteria.

Kämpfer

Dott

Kroppenstedt

1990

J. Gen. Appl. Microbiol.

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“…Possible problems in numerical taxonomic studies can be minimized by the choice of suitable tests and statistics (Sneath & Johnson, 1972;Austin & Colwell, 1977;O'Brien & Colwell, 1987). It is necessary that all the tests can be employed for all strains, that test reproducibility is high and that the majority of phena show a low overlap with other phena (Sneath, 1974(Sneath, , 1979.…”

Section: Discussionmentioning

confidence: 99%

A numerical classification of the genera Streptomyces and Streptoverticillium using miniaturized physiological tests

Kämpfer

Kroppenstedt

Dott

1991

Journal of General Microbiology

154

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Eight hundred and twenty-one strains of the genera Streptomyces and Streptoverticillium were physiologically characterized using a total of 329 miniaturized tests. Overall similarities of all strains were determined by numerical taxonomic techniques using the UPGMA algorithm and the SSM and the SJ coefficients as measures of similarity. Test error was within acceptable limits. Comparison of photometric and visual test reading revealed overall differences of 7.45%. A total of 15 major clusters (six or more strains), 34 minor clusters (less than six strains) and 40 single-member clusters were defined at the 81.5% similarity level (SSM). Two clusters containing physiologically, and in some cases morphologically and genetically, different groups could be further subdivided at the 84.0% similarity level (SSM). Generally, similar groupings were obtained with the Jaccard coefficient at similarity levels ranging from 59.6% to 64.6% similarity (SJ), with changes in the definition of clusters and subclusters. The cophenetic correlation coefficients r,, for the UPGMA/Sj and the UPGMA/SsM analysis were 0-6929 and 0.8239, respectively. Several phena showed significant overlap with others, indicating the physiological variability within the species. The phenetic data in most cases confirm the major phena of the study of Williams et al. (1983), Journal of General Microbiology 129, 1743-1813 (although the cluster-groups defined in that study could only be detected in part) and the results indicate that the genus Streptomyces is still overspeciated. Some of the major groupings obtained were very much in line with chemotaxonomic and genetical data. However, several clusters containing only a few strains should be regarded as preliminary 'species' until further information is available. The majority of Streptoverticillium strains presently assigned to different species formed a homogeneous subcluster defined at the 84.0% similarity level (SSM). Thus, on the basis of numerical phenetic and (published) molecular genetic and chemotaxonomic data, our study supports the suggestion that members of the genus Stveptoverticillium be reclassified into the genus Streptomyces.

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“…Improved enzyme activity. Extension of this approach to include microelectronics and computer-aided interpretation of data numerical identification (120) or automated systems to anahave also facilitated numerous applications of GLC in clinlyze results often strengthens conclusions. Immunodiagnosical microbiology.…”

Section: Introductionmentioning

confidence: 98%

Applications of cellular fatty acid analysis

1991

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More than ever, new technology is having an impact on the tools of clinical microbiologists. The analysis of cellular fatty acids by gas-liquid chromatography (GLC) has become markedly more practical with the advent of the fused-silica capillary column, computer-controlled chromatography and data analysis, simplified sample preparation, and a commercially available GLC system dedicated to microbiological applications. Experience with applications in diagnostic microbiology ranges from substantial success in work with mycobacteria, legionellae, and nonfermentative gram-negative bacilli to minimal involvement with fungi and other nonbacterial agents. GLC is a good alternative to other means for the identification of mycobacteria or legionellae because it is rapid, specific, and independent of other specialized testing, e.g., DNA hybridization. Nonfermenters show features in their cellular fatty acid content that are useful in identifying species and, in some cases, subspecies. Less frequently encountered nonfermenters, including those belonging to unclassified groups, can ideally be characterized by GLC. Information is just beginning to materialize on the usefulness of cellular fatty acids for the identification of gram-positive bacteria and anaerobes, despite the traditional role of GLC in detecting metabolic products as an aid to identification of anaerobes. When species identification of coagulase-negative staphylococci is called for, GLC may offer an alternative to biochemical testing. Methods for direct analysis of clinical material have been developed, but in practical and economic terms they are not yet ready for use in the clinical laboratory. Direct analysis holds promise for detecting markers of infection due to an uncultivable agent or in clinical specimens that presently require cultures and prolonged incubation to yield an etiologic agent.

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2 Characterization Tests for Numerical Taxonomy Studies

Cited by 13 publications

References 105 publications

Numerical classification and identification of some nocardioform bacteria.

Numerical classification and identification of some nocardioform bacteria.

A numerical classification of the genera Streptomyces and Streptoverticillium using miniaturized physiological tests

Applications of cellular fatty acid analysis

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