Rapid identification of Streptococcus and Enterococcus species using diffuse reflectance-absorbance Fourier transform infrared spectroscopy and artificial neural networks
Diffuse reflectance-absorbance Fourier transform infrared spectroscopy (FT-IR) was used to analyse 19 hospital isolates which had been identified by conventional means to one of Enterococcus faecalis, E. faecium, Streptococcus bovis, S. mitis, S. pneumoniae, or S. pyogenes. Principal components anal...
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Published in | FEMS microbiology letters Vol. 140; no. 2; pp. 233 - 239 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
01.07.1996
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Subjects | |
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Abstract | Diffuse reflectance-absorbance Fourier transform infrared spectroscopy (FT-IR) was used to analyse 19 hospital isolates which had been identified by conventional means to one of
Enterococcus faecalis, E. faecium, Streptococcus bovis, S. mitis, S. pneumoniae, or
S. pyogenes. Principal components analysis of the FT-IR spectra showed that this ‘unsupervised’ learning method failed to form six separable clusters (one for each species) and thus could not be used to identify these bacteria based on their FT-IR spectra. By contrast, artificial neural networks (ANNs) could be trained by ‘supervised’ learning (using the back-propagation algorithm) with the principal components scores of derivatised spectra to recognise the strains from their FT-IR spectra. These results demonstrate that the combination of FT-IR and ANNs provides a rapid, novel and accurate bacterial identification technique. |
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AbstractList | Diffuse reflectance-absorbance Fourier transform infrared spectroscopy (FT-IR) was used to analyse 19 hospital isolates which had been identified by conventional means to one of
Enterococcus faecalis, E. faecium, Streptococcus bovis, S. mitis, S. pneumoniae, or
S. pyogenes. Principal components analysis of the FT-IR spectra showed that this ‘unsupervised’ learning method failed to form six separable clusters (one for each species) and thus could not be used to identify these bacteria based on their FT-IR spectra. By contrast, artificial neural networks (ANNs) could be trained by ‘supervised’ learning (using the back-propagation algorithm) with the principal components scores of derivatised spectra to recognise the strains from their FT-IR spectra. These results demonstrate that the combination of FT-IR and ANNs provides a rapid, novel and accurate bacterial identification technique. |
Author | Timmins, Eadaoin M. Rowland, Jem J. Rooney, Paul J. Goodacre, Royston Kell, Douglas B. |
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Keywords | Streptococcus Artificial neural network Chemometrics Fourier transform infrared spectroscopy (FT-IR) |
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References | Mitchell (BIB10) 1993; 236 Naumann, Helm, Labischinski, Giesbrecht (BIB6) 1991 Nelson, Manoharan, Sperry (BIB4) 1992; 27 Goodacre, Kell (BIB1) 1996; 7 Goodacre, Neal, Kell (BIB17) 1994; 66 Blanco, Coello, Iturriaga, Maspoch, Redon (BIB20) 1995; 67 Glauninger, Kovar, Hoffmann (BIB9) 1990; 338 Bishop (BIB18) 1995 Helm, Labischinski, Schallehn, Naumann (BIB5) 1991; 137 Everitt (BIB7) 1993 Goodacre, Kell, Blanchi (BIB8) 1992; 359 Jolliffe (BIB14) 1986 Bouffard, Katon, Sommer, Danielson (BIB11) 1994; 66 Seasholtz, Kowalski (BIB19) 1993; 277 Griffiths, de Haseth (BIB12) 1986 Goodacre, Neal, Kell, Greenham, Noble, Harvey (BIB15) 1994; 76 Goodacre (BIB3) 1994; 2 Magee (BIB2) 1993 Savitzky, Golay (BIB13) 1964; 36 Goodacre, Trew, Wrigley-Jones, Saunders, Neal, Porter, Kell (BIB16) 1995; 313 |
References_xml | – volume: 313 start-page: 25 year: 1995 end-page: 43 ident: BIB16 article-title: Rapid and quantitative analysis of metabolites in fermenter broths using pyrolysis mass spectrometry with supervised learning: application to the screening of publication-title: Anal. Chim. Acta contributor: fullname: Kell – volume: 236 start-page: 351 year: 1993 end-page: 375 ident: BIB10 article-title: Fundamentals and applications of diffuse reflectance infrared fourier transform (DRIFT) spectroscopy publication-title: Adv. Chem. Ser. contributor: fullname: Mitchell – volume: 27 start-page: 67 year: 1992 end-page: 124 ident: BIB4 article-title: UV resonance Raman studies of bacteria publication-title: Appl. Spectrosc. Rev. contributor: fullname: Sperry – start-page: 43 year: 1991 end-page: 96 ident: BIB6 article-title: The characterization of microorganisms by Fourier-transform infrared spectroscopy (FT-IR) publication-title: Modern Techniques for Rapid Microbiological Analysis contributor: fullname: Giesbrecht – year: 1993 ident: BIB7 article-title: Cluster Analysis contributor: fullname: Everitt – start-page: 383 year: 1993 end-page: 427 ident: BIB2 article-title: Whole-organism fingerprinting publication-title: Handbook of New Bacterial Systematics contributor: fullname: Magee – volume: 67 start-page: 4477 year: 1995 end-page: 4483 ident: BIB20 article-title: Artificial neural networks for multicomponent kinetic determinations publication-title: Anal. Chem. contributor: fullname: Redon – volume: 66 start-page: 1937 year: 1994 end-page: 1940 ident: BIB11 article-title: Development of microchannel thin layer chromatography with infrared microspectroscopic detection publication-title: Anal. Chem. contributor: fullname: Danielson – volume: 76 start-page: 124 year: 1994 end-page: 134 ident: BIB15 article-title: Rapid identification using pyrolysis mass spectrometry and artificial neural networks of publication-title: J. Appl. Bacteriol. contributor: fullname: Harvey – volume: 137 start-page: 69 year: 1991 end-page: 79 ident: BIB5 article-title: Classification and identification of bacteria by Fourier transform infrared spectroscopy publication-title: J. Gen. Microbiol. contributor: fullname: Naumann – volume: 36 start-page: 1627 year: 1964 end-page: 1633 ident: BIB13 article-title: Smoothing and differentiation of data by simplified least squares procedures publication-title: Anal. Chem. contributor: fullname: Golay – volume: 66 start-page: 1070 year: 1994 end-page: 1085 ident: BIB17 article-title: Rapid and quantitative analysis of the pyrolysis mass spectra of complex binary and tertiary mixtures using multivariate calibration and artificial neural networks publication-title: Anal. Chem. contributor: fullname: Kell – volume: 2 start-page: 16 year: 1994 end-page: 22 ident: BIB3 article-title: Characterisation and quantification of inicrobial systems using pyrolysis mass spectrometry: Introducing neural networks to analytical pyrolysis publication-title: Microbiol. Eur. contributor: fullname: Goodacre – year: 1986 ident: BIB14 article-title: Principal Component Analysis contributor: fullname: Jolliffe – volume: 338 start-page: 710 year: 1990 end-page: 716 ident: BIB9 article-title: Possibilities and limits of an online coupling of thin-layer chromatography and FTIR spectroscopy. Fresenius publication-title: J. Anal. Chem. contributor: fullname: Hoffmann – volume: 359 start-page: 594 year: 1992 end-page: 594 ident: BIB8 article-title: Neural networks and olive oil publication-title: Nature contributor: fullname: Blanchi – volume: 277 start-page: 165 year: 1993 end-page: 177 ident: BIB19 article-title: The parsimony principle applied to multivariate calibration publication-title: Anal. Chim. Acta contributor: fullname: Kowalski – year: 1986 ident: BIB12 article-title: Fourier Transform Infrared Spectrometry contributor: fullname: de Haseth – year: 1995 ident: BIB18 article-title: Neural Networks for Pattern Recognition contributor: fullname: Bishop – volume: 7 start-page: 20 year: 1996 end-page: 28 ident: BIB1 article-title: Pyrolysis mass spectrometry and its applications in biotechnology publication-title: Cur. Opin. Biotechnol. contributor: fullname: Kell |
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SubjectTerms | Artificial neural network Chemometrics Fourier transform infrared spectroscopy (FT-IR) Streptococcus |
Title | Rapid identification of Streptococcus and Enterococcus species using diffuse reflectance-absorbance Fourier transform infrared spectroscopy and artificial neural networks |
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