Skip to content
1887

Microbiology Society logo Microbiology

Volume 129, Issue 6

A Probability Matrix for Identification of some Streptomycetes Free

Abstract

The character state data obtained for clusters defined at the 77·5% similarity level in the phenetic numerical classification described by Williams . (1983) were used to construct a probabilistic identification matrix. The 23 phena included were the major clusters (19 2 and ) and one minor cluster (). The characters most diagnostic for these clusters were selected using Sneath’s CHARSEP and DIACHAR programs. The resulting matrix consisted of 41 characters × 23 phena.

Identification scores, determined by Sneath’s MATIDEN program were used to evaluate the matrix. Theoretical assessment was achieved by determination of the cluster overlap (OVERMAT), the identification scores for the Hypothetical Medium Organism of each cluster (MOSTTYP), and the scores for randomly selected cluster representatives using the classification data of Williams . (1983) . The matrix was evaluated practically by the independent re-determination of the characters for the same cluster representatives, which-also provided a measure of test error. Finally it was used to identify unknown isolates from a range of habitats.

The results showed that the matrix was theoretically sound. Test error was within acceptable limits and did not distort identifications. Of the unknown isolates, 80% were clearly identified with a cluster. It is suggested that the matrix could form the basis for a more objective identification and grouping of the large number of species which have been described.

  • Received:
  • Published Online:
© Society for General Microbiology, 1983
Loading

Article metrics loading...

/content/journal/micro/10.1099/00221287-129-6-1815
1983-06-01
2025-11-07

Metrics

Loading full text...

Full text loading...

/deliver/fulltext/micro/129/6/mic-129-6-1815.html?itemId=/content/journal/micro/10.1099/00221287-129-6-1815&mimeType=html&fmt=ahah

References

  1. Bascomb S., Lapage S. P., Curtis M. A., Willcox W. R. 1973; Identification of bacteria by computer: identification of reference strains. Journal of General Microbiology 77:291–315
     [Google Scholar]
  2. Dietz A., Mathews J. 1971; Classification of Streptomyces spore surfaces into five groups. Applied Microbiology 21:527–533
     [Google Scholar]
  3. Feltham R. K. A., Sneath P. H. A. 1982; Construction of matrices for computer-assisted identification of aerobic Gram-positive cocci. Journal of General Microbiology 128:713–720
     [Google Scholar]
  4. Gavini F., Oger C., Lefebvre B., Izard D., Leclerc H. 1982; Development of a computer identification system for coliform strains. Journal of Applied Bacteriology 52:329–332
     [Google Scholar]
  5. Gordon R. E. 1968; The taxonomy of soil bacteria. In The Ecology of Soil Bacteria pp. 293–321 Gray T. R. G., Parkinson D. Edited by Liverpool: Liverpool University Press;
     [Google Scholar]
  6. Gyllenberg H. G. 1963; A general method for deriving determination schemes for random collections of microbial isolates. Annales Academiae scientiarum fennicae, Series A (IV. Biologica) 69:1–23
     [Google Scholar]
  7. Gyllenberg H. G. 1970; Factor analytical evaluation of patterns of correlated characteristics in streptomycetes. In The Actinomycetales pp. 101–105 Prauser H. Edited by Jena: Gustav Fischer Verlag;
     [Google Scholar]
  8. Gyllenberg H. G. 1974; Identification models for streptomycetes. Postepy higieny i medycyny doświadc-zalnej 28:409–418
     [Google Scholar]
  9. Gyllenberg H. G. 1976; Application of automation to the identification of streptomycetes. In Actinomycetes: The Boundary Microorganisms pp. 299–321 Arai T. Edited by Tokyo: Toppan Co.;
     [Google Scholar]
  10. Gyllenberg H. G., WÓznicka W., Kurylowicz W. 1967; Application of factor analysis in microbiology. 3. A study of the “yellow series” of streptomycetes. Annales Academiae scientiarium fennicae, Series A (IV. Biologica) 114:3–15
     [Google Scholar]
  11. Gyllenberg H. G., Niemela T. K., Niemi J. S. 1975; A model for automatic identification of streptomycetes. Postepy higieny i medycyny doś-wiadczalnej 29:357–383
     [Google Scholar]
  12. Hankin L., Zucker M., Sands D. C. 1971; Improved solid medium for the detection and enumeration of pectolytic bacteria. Applied Microbiology 22:205–209
     [Google Scholar]
  13. Hill L. R. 1974; Theoretical aspects of numerical identification. International Journal of Systematic Bacteriology 24:494–499
     [Google Scholar]
  14. Hill L. R., Silvestri L. G. 1962; Quantitative methods in the systematics of Actinomycetales. III. The taxonomic significance of physiological-biochemical characters and the construction of a diagnostic key. Giornale di microbiologia 10:1–28
     [Google Scholar]
  15. Hill L. R., Lapage S. P., Bowie I. S. 1978; Computer assisted identification of coryneform bacteria. In Coryneform Bacteria pp. 181–215 Bousfield I. J., Callely A. G. Edited by London: Academic Press.;
     [Google Scholar]
  16. Hütter R. 1967 Systematik der Streptomyceten. Basel: Karger;
     [Google Scholar]
  17. Kelley R. W., Kellogg S. T. 1978; Computer- assisted identification of anaerobic bacteria. Applied and Environmental Microbiology 35:507–511
     [Google Scholar]
  18. Küster E. 1959; Outline of a comparative study of criteria used in the characterization of the actinomycetes. International Bulletin of Bacteriological Nomenclature and Taxonomy 9:97–104
     [Google Scholar]
  19. Küster E., Williams S. T. 1964; Production of hydrogen sulphide by streptomycetes and methods for its detection. Applied Microbiology 12:46–52
     [Google Scholar]
  20. Kutzner H. J. 1976 Methoden zur Untersuchung von Streptomyceten und einigen anderen Actinomyceten. Darmstadt: Teilsammlung Darmstadt am Institut für Mikrobiologie der Technischen Hochschule.;
     [Google Scholar]
  21. Lapage S. P. 1974; Practical aspects of probabilistic identification of bacteria. International Journal of Systematic Bacteriology 24:500–507
     [Google Scholar]
  22. Lapage S. P., Bascomb S., Willcox W. R., Curtis M. A. 1970; Computer identification of bacteria. In Automation, Mechanization and Data Handling in Microbiology pp. 1–22 Baillie A., Gilbert R. J. Edited by London: Academic Press.;
     [Google Scholar]
  23. Lapage S. P., Bascomb S., Willcox W. R., Curtis M. A. 1973; Identification of bacteria by computer: general aspects and perspectives. Journal of General Microbiology 77:273–290
     [Google Scholar]
  24. Lefebvre B., Gavini F. 1982; Theory and programming of a computer identification system for coliform strains. Journal of Applied Bacteriology 52:325–328
     [Google Scholar]
  25. Möller F. 1962; Quantitative methods in the systematics of Actinomycetales. IV. The theory and application of a probabilistic identification key. Giornale di microbiologia 10:29–47
     [Google Scholar]
  26. Niemalä S.L, Hopkins J. W., Quadling C. 1068; Selecting an economical binary test battery for a set of microbial cultures. Canadian Journal of Microbiology 14:271–279
     [Google Scholar]
  27. Prauser H. 1964; Aptness and application of colour codes for exact description of colours of streptomycetes. Zeitschrift für allgemeine Mikrobiologie 4:95–98
     [Google Scholar]
  28. Pridham T. G. 1976; Contemporary species concepts in Actinomycetales. In Actinomycetes: The Boundary Microorganisms pp. 163–174 Arai T. Edited by Tokyo: Toppan Co.;
     [Google Scholar]
  29. Pridham T. G., Gottlieb D. 1948; The utilization of carbon compounds by some Actinomycetales as aid for species determination. Journal of Bacteriology 56:107–114
     [Google Scholar]
  30. Pridham T. G., Tresner H. D. 1974; Streptomyces Waksman and Henrici 1943. In Bergey’s Manual of Determinative Bacteriology, 8th edn.. pp. 758–829 Buchanan R. E., Gibbons N. E. Edited by Baltimore: Williams & Wilkins.;
     [Google Scholar]
  31. Pridham T. G., Hesseltine C. W., Benedict R. G. 1958; A guide for the classification of streptomy- cetes according to selected groups. Placement of strains in morphological sections. Applied Microbiology 6:52–79
     [Google Scholar]
  32. Rennie R. J. 1980; Dinitrogen-fixing bacteria: computer assisted identification of soil isolates. Canadian Journal of Microbiology 26:1275–1283
     [Google Scholar]
  33. Schindler J., Duben J., Lysenko O. 1979; Computer-aided numerical identification of Gramnegative fermentative rods on a desk-top computer. Journal of Applied Bacteriology 47:45–51
     [Google Scholar]
  34. Shirling E. B., Gottlieb D. 1968a; Co-operative description of type cultures of Streptomyces. II. Species descriptions from first study. International Journal of Systematic Bacteriology 18:69–189
     [Google Scholar]
  35. Shirling E. B., Gottlieb D. 1968b; Co-operative description of type cultures of Streptomyces. III. Additional species descriptions from first and second studies. International Journal of Systematic Bacteriology 18:279–391
     [Google Scholar]
  36. Shirling E. B., Gottlieb D. 1969; Co-operative descriptions of type cultures of Streptomyces. IV. Species descriptions from the second, third and fourth studies. International Journal of Systematic Bacteriology 19:391–512
     [Google Scholar]
  37. Shirling E. B., Gottlieb D. 1972; Co-operative description of type strains of Streptomyces. V. Additional descriptions. International Journal of Systematic Bacteriology 22:265–394
     [Google Scholar]
  38. Silvestri L. G., Turri M., Hill L. R., Gilardi E. 1962; A quantitative approach to the systematics of actinomycetes based on overall similarity. Symposia of the Society of General Microbiology 12:333–360
     [Google Scholar]
  39. Skerman V. B. D., Mcgowan V., Sneath P. H. A. 1980; Approved lists of bacterial names. International Journal of Systematic Bacteriology 30:225–420
     [Google Scholar]
  40. Sneath P. H. A. 1974; Test reproducibility in relation to identification. International Journal of Systematic Bacteriology 24:508–523
     [Google Scholar]
  41. Sneath P. H. A. 1978; Identification of microorganisms. In Essays in Microbiology pp. 10/1–10/32 Norris J. R., Richmond M. H. Edited by Chichester: Wiley;
     [Google Scholar]
  42. Sneath P. H. A. 1979a; BASIC program for identification of an unknown with presence-absence data against an identification matrix of percent positive characters. Computers and Geosciences 5:195–213
     [Google Scholar]
  43. Sneath P. H. A. 1979b; BASIC program for character separation indices from an identification matrix of percent positive characters. Computers and Geosciences 5:349–357
     [Google Scholar]
  44. Sneath P. H. A. 1980a; BASIC program for the most diagnostic properties of groups from an identification matrix of percent positive characters. Computers and Geosciences 6:21–26
     [Google Scholar]
  45. Sneath P. H. A. 1980b; BASIC program for determining the best identification scores possible for the most typical example when compared with an identification matrix of percent positive characters. Computers and Geosciences 6:27–34
     [Google Scholar]
  46. Sneath P. H. A. 1980c; BASIC program for determining overlap between groups in an identification matrix of percent positive characters. Computers and Geosciences 6:267–278
     [Google Scholar]
  47. Sneath P. H. A., Chater A. O. 1978; Information content of keys for identification. In Essays in Plant Taxonomy pp. 79–95 Street H. E. Edited by London: Academic Press.;
     [Google Scholar]
  48. Sneath P. H. A., Johnson R. 1972; The influence on numerical taxonomic similarities of errors in microbiological tests. Journal of General Microbiology 72:377–392
     [Google Scholar]
  49. Sneath P. H. A., Sokal R. R. 1973 Numerical Taxonomy. The Principles and Practice of Numerical Classification. San Francisco: W. H. Freeman.;
     [Google Scholar]
  50. Tresner H. D., Backus E. J. 1963; System of color wheels for streptomycete taxonomy. Applied Micro-biology 11:335–338
     [Google Scholar]
  51. Tresner H. D., Davies M. C., Backus E. J. 1961; Electron microscopy of Streptomyces spore morphology and its role in species differentiation. Journal of Bacteriology 81:70–80
     [Google Scholar]
  52. Waksman S. A. 1961 The Actinomycetes II Baltimore: Williams & Wilkins.;
     [Google Scholar]
  53. Wayne L. G., Krichevsky E. J., Love L. L., Johnson R., Krichevsky M. I. 1980; Taxonomic probability matrix for use with slowly growing mycobacteria. International Journal of Systematic Bacteriology 30:528–538
     [Google Scholar]
  54. Wellington E. M. H., Williams S. T. 1978; Preservation of actinomycete inoculum in frozen glycerol. Microbios Letters 6:151–157
     [Google Scholar]
  55. Willcox W. B., Lapage S. P., Bascomb S., Curtis M. A. 1973; Identification of bacteria by computer : theory and programming. Journal of General Microbiology 77:317–330
     [Google Scholar]
  56. Willcox W. R., Lapage S. P., Holmes B. 1980; A review of numerical methods in bacterial identification. Antonie van Leeuwenhoek 46:233–299
     [Google Scholar]
  57. Willemse-Collinet M. E., Tromp T. F. J., Huizinga T. 1980; A simple and rapid computer- assisted technique for the identification of some selected Bacillus species using biochemical tests. Journal of Applied Bacteriology 49:385–394
     [Google Scholar]
  58. Williams S. T., Goodfellow M., Alderson G., Wellington E. M. H., Sneath P. H. A., Sackin M. J. 1983; Numerical classification of Streptomyces and related genera. Journal of Microbiology 129:1743–1813
     [Google Scholar]
/content/journal/micro/10.1099/00221287-129-6-1815
Loading
A Probability Matrix for Identification of some Streptomycetes
Microbiology 129, 1815 (1983); https://doi.org/10.1099/00221287-129-6-1815
/content/journal/micro/10.1099/00221287-129-6-1815
/content/journal/micro/10.1099/00221287-129-6-1815
Loading

Data & Media loading...

Most cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An error occurred
Approval was partially successful, following selected items could not be processed due to error