A probability matrix for the identification of vibrios

Dawson, Christine A.; Sneath, P. H. A.

doi:10.1111/j.1365-2672.1985.tb01480.x

Cited by 25 publications

(17 citation statements)

References 49 publications

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“…Although the data base they present is smaller than the matrix described here, it is purely for the Enterobacteriaceae, and so for this family it covers a larger number of taxa than does our matrix. A probability matrix for the identification of vibrios and related taxa has been published by Dawson & Sneath (1985). Half the tests in their matrix comprised the API 20E system and the other half conventional tests.…”

Section: G E N E R a L Discussionmentioning

confidence: 99%

A Revised Probability Matrix for the Identification of Gram-negative, Aerobic, Rod-shaped, Fermentative Bacteria

Holmes¹,

Dawson²,

Pinning³

1986

Microbiology

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The results of the identification of 933 strains of Gram-negative, aerobic, rod-shaped, fermentative bacteria ( Enterobacteriaceae, Pasteurellaceae, Vibrionaceae) by a probabilistic method, in a computer, are given. The identification rate on the matrix was 89.2%. Many of the strains were atypical and had caused difficulty in identification in medical diagnostic laboratories. The results are given for each taxon by genus and species. I N T R O D U C T I O NA computer-assisted conditional probability method for the identification of enterobacteria was first described by Dybowski & Franklin (1968) and Lapage et al. (1970) used a similar scheme to successfully identify up to 80% of 279 freshly isolated strains. Later, Bascomb et al. (1973) published a matrix for the identification of Gram-negative rods of clinical importance and discussed its use in the identification of 1079 reference strains; the general aspects of probabilistic identification and the mathematical model used were described by Lapage et al. (1973) and Willcox et al. (1973), respectively. This latter matrix was then used as the basis for an identification service in our laboratory, the methods for which were reviewed by Willcox et al. (1980). In the operation of the identification service, the test results obtained for strains submitted for identification were accumulated by computer. These results were then sorted by taxon and printed in the form of summaries, as described by Holmes & Hill (1985). From these summarized results a revised matrix was derived for the fermentative organisms and, following evaluation, this matrix is now in current use for the routine identification service.In this paper we present the results obtained in the identification of 933 strains of bacteria belonging to 110 taxa in the revised probability matrix. METHODS Overallprocedure.A matrix was constructed which gave the probability of a strain of any given taxon yielding a positive result in each of the chosen tests (Table 1). Individual strains were then identified on the basis of these results.Taxa. Of the taxa chosen for the matrix (Table I), the majority gave a fermentative result in the oxidation/fermentation (O/F test) of Hugh & Leifson (1953). A few non-fermentative taxa were also included; these were taxa that produce acid from glucose in peptone/water/sugar media and that may possess other characteristics by which they may be confused with fermentative organisms.Although the range of taxa was selected primarily to include those of known medical importance and those likely to occur in medical specimens, efforts were made to include as many recently described species as possible, so as to facilitate recognition of the latter should they occur in human clinical or veterinary material. Particular attention was paid to ensure inclusion of all Enterobacteriaceae taxa described in Bergeys Manual of Systematic Bacteriology (Brenner, 1984). The majority of the taxa are recognized species, genera or subgenera. Some are t Present address: Gibco-Sensititre, Imberhorne La...

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Section: G E N E R a L Discussionmentioning

confidence: 99%

A Revised Probability Matrix for the Identification of Gram-negative, Aerobic, Rod-shaped, Fermentative Bacteria

Holmes¹,

Dawson²,

Pinning³

1986

Microbiology

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“…Using ribosomal RNA gene sequence similarity, pioneered by Woese & Fox (1977), systematists have invented robust method of creating evolutionary trees. With the help of this common method, bacteriologists widely recognize that bacterial diversity is organized into discrete phenotypic and genetic clusters, which are separated by phenotypic and genetic gaps, and these clusters are recognized as species (Dawson & Sneath, 1985).…”

Section: The Problem Of Species Usage In Cyanobacteriamentioning

confidence: 99%

Taxonomy of cyanobacteria: a contribution to consensus approach

Palińska

Surosz

2014

Hydrobiologia

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Diversity of Cyanophyceae/cyanobacteria is expressed by their morphological, biochemical and physiological properties, which enable them to settle and persist in a wide range of habitats. Their diverse morphology determined their taxonomic distinction based on phenotypic properties. The oxygenic photosynthesis which characterizes cyanobacteria and their sharing of ecological niches with eukaryotic algae, prompted their treatment in the phycological circles, where they were called blue-green algae, although their prokaryotic nature, akin to bacteria, has been recognized for over a century. The cyanobacteria are named under Botanical and Bacteriological Codes, and the usage of both systems at the same time causes considerable confusion as the rules of the Botanical Code are quite different from those of the Bacteriological one. Herbarium collections are perfect subjects for intensive phylogenetic studies and therefore can contribute to discussions on the traditional and newly emerging concepts of species and speciation in prokaryotes. This article reviews the present status of the taxonomy of cyanobacteria, describes earlier, classical and recent taxonomic approaches and the trends for future, emphasizing improvements in methodology as major catalysts for the progress of this field.

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“…Procedures for character selection have been described by . These calculations have been successfully applied in various studies (10,23,24,30,36,51).…”

Section: Methodsmentioning

confidence: 99%

“…Gram-negative non-fermentative bacteria (18,31), vibrios (1,10), Gram-negative fermentative bacteria (17), bacilli (21, 36), micrococci (12), nocardioform bacteria (23), and streptomycetes (24,30,51). For some `coryneform' bacteria, Hill et al (16) VOL.…”

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Probabilistic identification of coryneform bacteria.

Kämpfer

Seiler²

1993

J. Gen. Appl. Microbiol.

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A frequency matrix of positive results was constructed for major phena defined in a previous phenetic classification of several species of coryneform and related taxa. A total of 280 physiological characters from 441 strains were taken as basis for this identification matrix. Minimum number of diagnostic characters for the matrix was selected using computer programs for calculation of different separation indices (CHA-RSEP) and selection of group diagnostic properties (DIACHAR). The resulting matrix consisted of 31 phena versus 58 characters. Phena overlap within the matrix was found to be relatively small (OVERMAT program). For each phenon, the identification scores for the most typical hypothetical organism was satisfactory (MOSTTYP program).The matrix was evaluated theoretically and practically (MATIDEN program). The overall identification rate (442 strains) of the theoretical evaluation (Willcox probability >0.99) was 92.0%. In the practical evaluation (40 strains) a total of 33 strains (82.5%) were identified with a Willcox probability >0.9. For minor clusters and single strains belonging to genetically and chemotaxonomically defined species, additional identification tables are provided. When used in combination with chemotaxonomic methods, the identification matrix can improve the identification of coryneform bacteria.The use of numerical identification and the development of matrices for routine use has been successfully applied to various bacteria, e.g. Gram-negative non-fermentative bacteria (18, 31), vibrios (1,10), Gram-negative fermentative bacteria (17), bacilli (21, 36), micrococci (12), nocardioform bacteria (23), and streptomycetes (24, 30, 51). For some `coryneform ' bacteria, Hill et al. (16)

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A probability matrix for the identification of vibrios

Cited by 25 publications

References 49 publications

A Revised Probability Matrix for the Identification of Gram-negative, Aerobic, Rod-shaped, Fermentative Bacteria

A Revised Probability Matrix for the Identification of Gram-negative, Aerobic, Rod-shaped, Fermentative Bacteria

Taxonomy of cyanobacteria: a contribution to consensus approach

Probabilistic identification of coryneform bacteria.

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