1887

Abstract

SUMMARY

An artificial neural network (ANN) was trained to distinguish between and . with averaged pyrolysis mass spectra from duplicate subcultures of four strains of each of these species, each pyrolysed in triplicate. Once trained, the ANN was interrogated with spectrum data from the original organisms (the “training set” and from 26 other mycobacterial isolates (the “ challenge set ”) of the . complex (MTBC). Eight strains of . and 13 of . , whether sensitive or variously resistant to antituberculosis drugs, were identified in agreement with conventional identification. Four strains of “. ” were identified as . . Of two atypical . strains from South India, one was identified as . and the other as . . Six strains of BCG proved heterogeneous; two gave equivocal identifications, three were identified as . and one was identified as . .

Loading

Article metrics loading...

/content/journal/jmm/10.1099/00222615-40-3-170
1994-03-01
2024-03-28
Loading full text...

Full text loading...

/deliver/fulltext/jmm/40/3/medmicro-40-3-170.html?itemId=/content/journal/jmm/10.1099/00222615-40-3-170&mimeType=html&fmt=ahah

References

  1. Heifets L. Gene-probe test should not be considered final in Mycobacterium tuberculosis identification. J Clin Microbiol 1989; 27:229
    [Google Scholar]
  2. Fries JWU, Patel RJ, Piessens WF, Wirth DF. Detection of untreated mycobacteria by using polymerase chain reaction and specific DNA probes. J Clin Microbiol 1991; 29:1774–1747
    [Google Scholar]
  3. Butler WR, Jost KC, Kilburn JO. Identification of myco-bacteria by high-performance liquid chromatography. J Clin Microbiol 1991; 29:2468–2472
    [Google Scholar]
  4. Rumelhart DE, McLelland JL. and the PDP Research Group. Parallel distributed processing. Explorations in the microstructure of cognition Cambridge: MA, MIT Press; 1986
    [Google Scholar]
  5. Wasserman PD. Neural computing: theory and practice. New York: Van Nostrand Reinhold; 1989
    [Google Scholar]
  6. Chun J, Atalan E, Ward AC, Goodfellow M. Artificial neural network analysis of pyrolysis mass spectrometric data in the identification of Streptomyces strains. FEMS Microbiol Lett 1993; 107:321–325
    [Google Scholar]
  7. Goodacre R, Kell DB. Rapid and quantitative analysis of bioprocesses using pyrolysis mass spectrometry and neural networks: application to indole production. Analyt Chim Ada 1993; 279:17–26
    [Google Scholar]
  8. Goodacre R, Kell DB, Bianchi G. Neural networks and olive oil. Nature 1992; 359:594
    [Google Scholar]
  9. Wieten G, Haverkamp J, Meuzelaar HLC, Engel HWB, Berwald LG. Pyrolysis mass spectrometry: a new method to differentiate between the mycobacteria of the ‘tuberculosis complex’ and other mycobacteria. J Gen Microbiol 1981; 122:109–118
    [Google Scholar]
  10. Sisson PR, Freeman R, Magee JG, Lightfoot NF. Differentiation between mycobacteria of the Mycobacterium tuberculosis complex by pyrolysis mass spectrometry. Tubercle 1991; 72:206–209
    [Google Scholar]
  11. Goodfellow M, Wayne LG. Taxonomy and nomenclature. Ratledge C, Stanford J. The biology of the mycobacteria 1 Physiology, identification and classification London: Academic Press; 1982471–521
    [Google Scholar]
  12. Yates MD, Collins CH, Grange JM. “Classical ” and “Asian” variants of Mycobacterium tuberculosis isolated in South East England 1977-1980. Tubercle 1982; 62:55–61
    [Google Scholar]
  13. Osborn TW. Changes in BCG strains. Tubercle 1983; 64:1–13
    [Google Scholar]
  14. Sisson PR, Freeman R, Magee JG, Lightfoot NF. Rapid differentiation of Mycobacterium xenopi from mycobacteria of the Mycobacterium avium-intracellulare complex by pyrolysis mass spectrometry. J Clin Pathol 1992; 45:355–357
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/jmm/10.1099/00222615-40-3-170
Loading
/content/journal/jmm/10.1099/00222615-40-3-170
Loading

Data & Media loading...

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