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Novel physico-chemical diagnostic tools for high throughput identification of bovine mastitis associated gram-positive, catalase-negative cocci
BACKGROUND: The routine diagnosis of Streptococcus spp. and other mastitis associated gram-positive, catalase-negative cocci is still based upon biochemical tests and serological methods, which frequently provide ambiguous identification results. We therefore aimed to establish an accurate identific...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4105049/ https://www.ncbi.nlm.nih.gov/pubmed/25015262 http://dx.doi.org/10.1186/1746-6148-10-156 |
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author | Schabauer, Lydia Wenning, Mareike Huber, Ingrid Ehling-Schulz, Monika |
author_facet | Schabauer, Lydia Wenning, Mareike Huber, Ingrid Ehling-Schulz, Monika |
author_sort | Schabauer, Lydia |
collection | PubMed |
description | BACKGROUND: The routine diagnosis of Streptococcus spp. and other mastitis associated gram-positive, catalase-negative cocci is still based upon biochemical tests and serological methods, which frequently provide ambiguous identification results. We therefore aimed to establish an accurate identification system for differential diagnosis of mastitis associated Streptococcus spp. and related species using biophysical techniques such as Fourier-transform infrared (FTIR) spectroscopy and MALDI – TOF/MS. RESULTS: Based on a panel of 210 isolates from cases of bovine mastitis, an unsupervised FTIR spectral reference library was established and an artificial neural network (ANN) - assisted identification system was developed. All bacterial isolates were previously identified by species-specific PCR and/or 16S rRNA gene sequence analysis. An overall identification rate of 100% at species level for 173 strains unknown to the ANN and the library was achieved by combining ANN and the spectral database, thus demonstrating the suitability of our FTIR identification system for routine diagnosis. In addition, we investigated the potential of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for the identification of mastitis associated Streptococcus spp. and related bacteria. Using the Microflex LT System, MALDI Biotyper software™ (V3.3) we achieved an accuracy rate of 95.2%. A blind study, including 21 clinical samples from dairy cows, revealed a 100% correct species identification rate for FTIR and 90.5% for MALDI-TOF MS, indicating that these techniques are valuable tools for diagnosis. CONCLUSIONS: This study clearly demonstrates that FTIR spectroscopy as well as MALDI-TOF MS can significantly improve and facilitate the identification and differentiation of mastitis associated Streptococcus spp. and related species. Although the FTIR identification system turned out being slightly superior to MALDI-TOF MS in terms of identification on species level, both methods offer interesting alternatives to conventional methods currently used in mastitis diagnosis as both of them provide high accuracy at low operating costs once the instrument is acquired. |
format | Online Article Text |
id | pubmed-4105049 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41050492014-07-22 Novel physico-chemical diagnostic tools for high throughput identification of bovine mastitis associated gram-positive, catalase-negative cocci Schabauer, Lydia Wenning, Mareike Huber, Ingrid Ehling-Schulz, Monika BMC Vet Res Methodology Article BACKGROUND: The routine diagnosis of Streptococcus spp. and other mastitis associated gram-positive, catalase-negative cocci is still based upon biochemical tests and serological methods, which frequently provide ambiguous identification results. We therefore aimed to establish an accurate identification system for differential diagnosis of mastitis associated Streptococcus spp. and related species using biophysical techniques such as Fourier-transform infrared (FTIR) spectroscopy and MALDI – TOF/MS. RESULTS: Based on a panel of 210 isolates from cases of bovine mastitis, an unsupervised FTIR spectral reference library was established and an artificial neural network (ANN) - assisted identification system was developed. All bacterial isolates were previously identified by species-specific PCR and/or 16S rRNA gene sequence analysis. An overall identification rate of 100% at species level for 173 strains unknown to the ANN and the library was achieved by combining ANN and the spectral database, thus demonstrating the suitability of our FTIR identification system for routine diagnosis. In addition, we investigated the potential of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for the identification of mastitis associated Streptococcus spp. and related bacteria. Using the Microflex LT System, MALDI Biotyper software™ (V3.3) we achieved an accuracy rate of 95.2%. A blind study, including 21 clinical samples from dairy cows, revealed a 100% correct species identification rate for FTIR and 90.5% for MALDI-TOF MS, indicating that these techniques are valuable tools for diagnosis. CONCLUSIONS: This study clearly demonstrates that FTIR spectroscopy as well as MALDI-TOF MS can significantly improve and facilitate the identification and differentiation of mastitis associated Streptococcus spp. and related species. Although the FTIR identification system turned out being slightly superior to MALDI-TOF MS in terms of identification on species level, both methods offer interesting alternatives to conventional methods currently used in mastitis diagnosis as both of them provide high accuracy at low operating costs once the instrument is acquired. BioMed Central 2014-07-11 /pmc/articles/PMC4105049/ /pubmed/25015262 http://dx.doi.org/10.1186/1746-6148-10-156 Text en Copyright © 2014 Schabauer et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Article Schabauer, Lydia Wenning, Mareike Huber, Ingrid Ehling-Schulz, Monika Novel physico-chemical diagnostic tools for high throughput identification of bovine mastitis associated gram-positive, catalase-negative cocci |
title | Novel physico-chemical diagnostic tools for high throughput identification of bovine mastitis associated gram-positive, catalase-negative cocci |
title_full | Novel physico-chemical diagnostic tools for high throughput identification of bovine mastitis associated gram-positive, catalase-negative cocci |
title_fullStr | Novel physico-chemical diagnostic tools for high throughput identification of bovine mastitis associated gram-positive, catalase-negative cocci |
title_full_unstemmed | Novel physico-chemical diagnostic tools for high throughput identification of bovine mastitis associated gram-positive, catalase-negative cocci |
title_short | Novel physico-chemical diagnostic tools for high throughput identification of bovine mastitis associated gram-positive, catalase-negative cocci |
title_sort | novel physico-chemical diagnostic tools for high throughput identification of bovine mastitis associated gram-positive, catalase-negative cocci |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4105049/ https://www.ncbi.nlm.nih.gov/pubmed/25015262 http://dx.doi.org/10.1186/1746-6148-10-156 |
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