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Biomedical subjects

P H Sneath

Publications and source records attributed to P H Sneath.

At least 19 recordsLinked to original sources

The effect of evenly spaced constant sites on the distribution of the random division of a molecular sequence.

MOTIVATION: A modified Sherman statistic can be used to test whether the differences between two aligned sequences are distributed at random along the sequences, or whether they are clustered, which suggests anomalies of evolution such as partial gene recombination or functional constraints. The presence of evenly spaced constant sites (such as constancy at the second codon position in genes coding for proteins) lowers the statistic and makes the significance less than it should be. RESULTS: The magnitude of the constant-site effect is shown by simulation to depend mainly on the proportion of differences between two sequences and on the number of constant sites that are added after each variable site. This latter number can be estimated from the variance of sites in a sequence matrix at the first, second and third codon positions, to obtain a ratio that corrects the statistic. When expressed as standard errors, the uncorrected results are too low (typically half to one unit when almost all the variation is at the third codon position). Correction raises the standard errors to levels close to expectation. If the data show no marked ternary periodicity, the correction is very small. The method is illustrated with biological data that show close to random behaviour, and with data that exhibit strong clustering. AVAILABILITY: The software is available from the author and has also been placed on the EMBL file server (Software@embl-ebi.ac.uk). CONTACT: phas1@le.ac.uk

Algorithms↗

A new species of Neisseria from the dental plaque of the domestic cow, Neisseria dentiae sp. nov.

A new species of the genus Neisseria is proposed, Neisseria dentiae sp. nov. The organism is found in dental plaque of domestic cows. It resembles N. animalis, N. canis and N. iguanae phenotypically but is distinguished from the first two by being positive for acidification of gluconate, D-glucose and usually D-fructose, and from the third by lack of predominant tetrad arrangement, lack of distinct alpha-haemolysis and by growing on nutrient agar and usually acidifying D-fructose. It is suggested that it may have significance for dental microbiology because members of the genus rapidly utilize oxygen and this may contribute to the anaerobic microenvironment found in dental plaque.

Animals↗

Taxonomic note: the potential of dead bacterial specimens for systematic studies.

Consideration should be given to preserving nonliving bacterial specimens as dried material in herbaria for use in future systematic studies. Nucleic acid sequences can be recovered from such material, and it may be possible to utilize it in other techniques. Dried specimens are cheap to prepare and preserve and would record much bacterial variation without the expense of maintaining living cultures. They would also be useful for uncultivable microorganisms. Some technical suggestions are offered.

Bacteria↗

A numerical phenotypic taxonomic study of the genus Neisseria.

A numerical phenotypic taxonomic study of 315 strains of Neisseria and some allied bacteria examined for 155 phenotypic tests showed 31 groups, most of which were reasonably distinct. These fell into four major areas. Areas A, B and C contained species of Neisseria, whereas area D contained the organisms known as 'false neisserias' together with Branhamella, Moraxella and Kingella species. Area A contained N. gonorrhoeae (which showed two subgroups), N. meningitidis (with two subgroups, and N. cinerea closely associated), N. polysaccharea, N. elongata subsp, glycolytica and N. lactamica. Area B contained mainly organisms from the human nasopharynx, and the nine groups were not very distinct: only three, N. mucosa, N. perflava and N. sicca could be recognized by the presence of type strains, and there was little relationship between taxonomic position and species epithets. Area C contained several groups from animals, N. animalis, N. canis and two phenons that may be justified as new species of Neisseria, one from lizards and the other from dental plaque of herbivores. Area C also contained N. elongata, N. subflava (with N. flavescens), type strain of Morococcus cerebrosis and the CDC groups M-5 (N. weaveri) and EF-4. Area D contained Branhamella catarrhalis, a combined group which consists of strains of the 'false neisserias' N. caviae and N. cuniculi, the 'false neisseria' N. ovis, and a group of Moraxella strains. A small group representing Kingella kingae is included in area D. Mean test error was 1.7%.

Models, Biological↗

Optical DNA-DNA homology in the genus Listeria.

Twenty-three strains of the seven recognized Listeria species were studied by using DNA-DNA optical hybridization. The level of error in the data was low. Our results supported the results of Rocourt et al. (J. Rocourt, F. Grimont, P. A. D. Grimont, and H. P. R. Seeliger, Curr. Microbiol. 7:383-388, 1982), although there was some overlap between Listeria monocytogenes and Listeria innocua. We suggest that there may be more than one cluster in the species L. monocytogenes or the species may form a large spectrum of relatedness. The level of intraspecies homology in L. monocytogenes is very broad, as determined in both this study and other studies.

DNA, Bacterial↗

Actinobacillus rossii sp. nov., Actinobacillus seminis sp. nov., nom. rev., Pasteurella bettii sp. nov., Pasteurella lymphangitidis sp. nov., Pasteurella mairi sp. nov., and Pasteurella trehalosi sp. nov.

Evidence from numerical taxonomic analysis and DNA-DNA hybridization supports the proposal of new species in the genera Actinobacillus and Pasteurella. The following new species are proposed: Actinobacillus rossii sp. nov., from the vaginas of postparturient sows; Actinobacillus seminis sp. nov., nom. rev., associated with epididymitis of sheep; Pasteurella bettii sp. nov., associated with human Bartholin gland abscess and finger infections; Pasteurella lymphangitidis sp. nov. (the BLG group), which causes bovine lymphangitis; Pasteurella mairi sp. nov., which causes abortion in sows; and Pasteurella trehalosi sp. nov., formerly biovar T of Pasteurella haemolytica, which causes septicemia in older lambs.

Abscess↗

New probability matrices for identification of Streptomyces.

The character state data obtained for clusters defined in a previous phenetic classification were used to construct two probabilistic matrices for Streptomyces species. These superseded an original published identification matrix by exclusion of other genera and the inclusion of more Streptomyces species. Separate matrices were constructed for major and minor clusters. The minimum number of diagnostic characters for each matrix was selected by computer programs for determination of character separation indices (CHARSEP) and a selection of group diagnostic properties (DIACHAR). The resulting matrices consisted of 26 phena x 50 characters (major clusters) and 28 phena x 39 characters (minor clusters). Cluster overlap (OVERMAT program) was small in both matrices. Identification scores were used to evaluate both matrices. The theoretically best scores for the most typical example of each cluster (MOSTTYP program) were all satisfactory. Input of test data for randomly selected cluster representatives resulted in correct identification with high scores. The major cluster matrix was shown to be practically sound by its application to 35 unknown soil isolates, 77% of which were clearly identified. The minor cluster matrix provides tentative probabilistic identifications as the small number of strains in each cluster reduces its ability to withstand test variation. A diagnostic table for single-membered clusters, constructed using the CHARSEP and DIACHAR programs, was also produced.

Computers↗

A reappraisal of the terverticillate penicillia using biochemical, physiological and morphological features. I. Numerical taxonomy.

Three-hundred-and-forty-eight strains representing the major species of terverticillate penicillia, and including representatives of other closely and distantly related species, were included in a numerical taxonomic study. One-hundred characters were derived from morphological features, physiological and biochemical activities and SEM micrographs. Strains were compared by both Gower's coefficient and Pattern difference, and clustered using the average linkage algorithm. Thirty-seven species or species-complex clusters were recovered at approximately 70% similarity; they generally corresponded to existing taxonomic concepts. Several species were shown to contain variants or chemotypes which were often supported by differences in conidial shape and ornamentation. The use of different types of characters enabled a number of new and previously accepted species to be shown to be either variants or deteriorated examples of other species. Variation in properties both between and within species was considered, particularly in relation to strain stability.

Cluster Analysis↗

Detecting aberrant strains in bacterial groups as an aid to constructing databases for computer identification.

Computer assisted identification systems require that databases on the test results of the species are of high quality. One reason for poor quality is the inadvertent inclusion of strains that do not belong to a taxon; this can readily occur in groups where ancillary criteria (e.g. serology) are not available. A possible strategy is to exclude strains that are very atypical in their properties, i.e. that are very outlying, provided an objective criterion can be used. A computer program, OUTLIER, for the detection of outlying strains in bacterial clusters was evaluated. A brief description of the theory and operation of the program is given. The program uses as an objective criterion the degree to which the strain data fits a chi-square. This allows easy identification of aberrant strains that should be excluded in constructing a database. The program utilizes 1.0 data and calculations are based upon a choice of one of four identification coefficients. The relative merits of these four coefficients were examined for eight sets of bacterial data. Two of the coefficients, -log10 Willcox likelihood and Taxonomic distance squared appear to show little significant differences and we recommend these for routine work, with the first being the more useful. The Pattern distance squared was useful in indicating where atypical strains may be metabolically less active or slow-growing members of a cluster rather than true outliers. The Variance-weighted Taxonomic distance squared behaved anomalously and we do not recommend it.

Bacteria↗

Construction of a database to identify Staphylococcus species.

A database was constructed for the routine identification of Staphylococcus species, isolated from man. The method comprised 15 conventional characterisation tests using substrates incorporated into agar plates and a multipoint inoculation system. The database was constructed from results of 125 reference strains and 1567 clinical isolates. In an evaluation trial, using a probability profile index generated from the database, 529 of 559 (94.6%) further clinical isolates were identified to species level. A further 20 (3.6%) gave low discrimination between two species. The proposed scheme was rapid, reliable, and inexpensive.

Bacteriological Techniques↗

Constructing a database for low cost identification of gram negative rods in clinical laboratories.

A database was constructed for the routine identification of Enterobacteriaceae and Gram negative rods growing aerobically on MacConkey agar. The test methods were based primarily on multipoint inoculation technology. The final database was constructed from the laboratory results of 4989 clinical isolates and 66 reference strains and was extensively analysed and evaluated. The proposed scheme is rapid, reliable, and cheap.

Enterobacteriaceae↗

A numerical taxonomic study of Actinobacillus, Pasteurella and Yersinia.

A numerical taxonomic study of strains of Actinobacillus, Pasteurella and Yersinia, with some allied bacteria, showed 23 reasonably distinct groups. These fell into three major areas. Area A contained species of Actinobacillus and Pasteurella: A. suis, A. equuli, A. lignieresii, P. haemolytica biovar A, P. haemolytica biovar T, P. multocida, A. actinomycetemcomitans, 'P. bettii', 'A. seminis', P. ureae and P. aerogenes. Also included in A was a composite group of Pasteurella pneumotropica and P. gallinarum, together with unnamed groups referred to as 'BLG', 'Mair', 'Ross' and 'aer-2'. Area B contained species of Yersinia: Y. enterocolitica, Y. pseudotuberculosis, Y. pestis and a group 'ent-b' similar to Y. enterocolitica. Area C contained non-fermenting strains: Y. philomiragia, Moraxella anatipestifer and a miscellaneous group 'past-b'. There were also a small number of unnamed single strains.

Actinobacillus↗

A probability matrix for the identification of vibrios.

A probability matrix for computer-assisted identification of vibrios has been constructed, based on the API 20E system. Data were gathered from 173 strains representing 31 taxa of vibrios and related organisms, from a variety of sources. The matrix was tested internally by four statistical programs. Program OVERMAT tested the separation and program MOSTTYP the discretion and homogeneity of the taxa. Most of the taxa were satisfactory but a few were less so; reasons for this are discussed. Program CHARSEP and program DIACHAR tested the separation and diagnostic values, respectively, of the characters used. The overall test error was 4.5%. The matrix was assessed externally by its performance in the identification of vibrio-like strains isolated from freshwater. Of 243 wild strains, 79.4% were identified with ten taxa, with a Willcox score of greater than or equal to 0.99.

Computers↗

A general-purpose system for characterizing medically important bacteria to genus level.

A computer program and accompanying data matrix have been prepared for bacteria of medical interest, to assist the assignment of an unidentified bacterium to the most likely genus. The results on a set of relatively simple tests are entered. The program prints the more likely genera, followed by a list of diagnostic tables in Cowan & Steel (1974) and Buchanan & Gibbons (1974). Where available, identification matrices for further computer-assisted study, are presented. This program may be of particular help in laboratories where a wide range of bacteria have to be identified.

Bacteria↗