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Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy for Rapid Identification of Non-Fermenting Gram-Negative Bacilli Isolated from Patients with Cystic Fibrosis
BACKGROUND: Chronic respiratory infections with non-fermenting Gram-negative bacilli are a key feature of cystic fibrosis (CF). For microbiology laboratories, rapid and accurate identification of these bacteria is often challenging and labor intensive. This study was undertaken to evaluate whether a...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5631018/ http://dx.doi.org/10.1093/ofid/ofx163.1553 |
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author | Vallieres, Emilie Quach, Caroline Lam, Lisa Rallu, Fabien Langella, Michele Sedman, Jacqueline Raymond, Martin Lebel, Pierre Ismail, Ashraf |
author_facet | Vallieres, Emilie Quach, Caroline Lam, Lisa Rallu, Fabien Langella, Michele Sedman, Jacqueline Raymond, Martin Lebel, Pierre Ismail, Ashraf |
author_sort | Vallieres, Emilie |
collection | PubMed |
description | BACKGROUND: Chronic respiratory infections with non-fermenting Gram-negative bacilli are a key feature of cystic fibrosis (CF). For microbiology laboratories, rapid and accurate identification of these bacteria is often challenging and labor intensive. This study was undertaken to evaluate whether attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy could rapidly discriminate Pseudomonas aeruginosa (mucoid and non-mucoid), Burkholderia cepacia complex, Burkholderia gladioli, Achromobacter spp. and Stenotrophomonas maltophilia. METHODS: A total of 263 well-characterized clinical strains isolated from respiratory samples of patients with CF attending the CHU Sainte-Justine CF clinic were included in this study, consisting of 70 P. aeruginosa, 83 Burkholderia spp., 52 Achromobacter spp. and 58 Stenotrophomonas maltophilia isolates from the biobank. Isolates were thawed and sub-cultured twice on sheep blood (5%) agar. ATR-FTIR spectral acquisition was performed in triplicate for each isolate. Multivariate statistical analysis of the ATR-FTIR spectra was performed by hierarchical cluster analysis (HCA) and principal component analysis (PCA) in conjunction with the use of a feature selection algorithm. RESULTS: An ATR-FTIR spectral database consisting of 789 spectra of P. aeruginosa, Burkholderia spp., Achromobacter spp. and Stenotrophomonas maltophilia was created in this study. Complete discrimination among all four genera as well as among three species within the B. cepacia complex and B. gladioli was achieved based on HCA and PCA of the spectra in the database. ATR-FTIR analysis of a validation set consisting of 30 isolates was conducted in parallel with identification by MALDI-TOF mass spectrometry and yielded >95% concordance between the two techniques. CONCLUSION: ATR-FTIR spectroscopy is a promising tool for rapid, inexpensive and accurate identification of non-fermenting Gram-negative bacilli. Additional work is needed to further expand the spectral database, particularly with mucoid strains. DISCLOSURES: All authors: No reported disclosures. |
format | Online Article Text |
id | pubmed-5631018 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-56310182017-11-07 Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy for Rapid Identification of Non-Fermenting Gram-Negative Bacilli Isolated from Patients with Cystic Fibrosis Vallieres, Emilie Quach, Caroline Lam, Lisa Rallu, Fabien Langella, Michele Sedman, Jacqueline Raymond, Martin Lebel, Pierre Ismail, Ashraf Open Forum Infect Dis Abstracts BACKGROUND: Chronic respiratory infections with non-fermenting Gram-negative bacilli are a key feature of cystic fibrosis (CF). For microbiology laboratories, rapid and accurate identification of these bacteria is often challenging and labor intensive. This study was undertaken to evaluate whether attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy could rapidly discriminate Pseudomonas aeruginosa (mucoid and non-mucoid), Burkholderia cepacia complex, Burkholderia gladioli, Achromobacter spp. and Stenotrophomonas maltophilia. METHODS: A total of 263 well-characterized clinical strains isolated from respiratory samples of patients with CF attending the CHU Sainte-Justine CF clinic were included in this study, consisting of 70 P. aeruginosa, 83 Burkholderia spp., 52 Achromobacter spp. and 58 Stenotrophomonas maltophilia isolates from the biobank. Isolates were thawed and sub-cultured twice on sheep blood (5%) agar. ATR-FTIR spectral acquisition was performed in triplicate for each isolate. Multivariate statistical analysis of the ATR-FTIR spectra was performed by hierarchical cluster analysis (HCA) and principal component analysis (PCA) in conjunction with the use of a feature selection algorithm. RESULTS: An ATR-FTIR spectral database consisting of 789 spectra of P. aeruginosa, Burkholderia spp., Achromobacter spp. and Stenotrophomonas maltophilia was created in this study. Complete discrimination among all four genera as well as among three species within the B. cepacia complex and B. gladioli was achieved based on HCA and PCA of the spectra in the database. ATR-FTIR analysis of a validation set consisting of 30 isolates was conducted in parallel with identification by MALDI-TOF mass spectrometry and yielded >95% concordance between the two techniques. CONCLUSION: ATR-FTIR spectroscopy is a promising tool for rapid, inexpensive and accurate identification of non-fermenting Gram-negative bacilli. Additional work is needed to further expand the spectral database, particularly with mucoid strains. DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2017-10-04 /pmc/articles/PMC5631018/ http://dx.doi.org/10.1093/ofid/ofx163.1553 Text en © The Author 2017. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Abstracts Vallieres, Emilie Quach, Caroline Lam, Lisa Rallu, Fabien Langella, Michele Sedman, Jacqueline Raymond, Martin Lebel, Pierre Ismail, Ashraf Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy for Rapid Identification of Non-Fermenting Gram-Negative Bacilli Isolated from Patients with Cystic Fibrosis |
title | Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy for Rapid Identification of Non-Fermenting Gram-Negative Bacilli Isolated from Patients with Cystic Fibrosis |
title_full | Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy for Rapid Identification of Non-Fermenting Gram-Negative Bacilli Isolated from Patients with Cystic Fibrosis |
title_fullStr | Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy for Rapid Identification of Non-Fermenting Gram-Negative Bacilli Isolated from Patients with Cystic Fibrosis |
title_full_unstemmed | Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy for Rapid Identification of Non-Fermenting Gram-Negative Bacilli Isolated from Patients with Cystic Fibrosis |
title_short | Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy for Rapid Identification of Non-Fermenting Gram-Negative Bacilli Isolated from Patients with Cystic Fibrosis |
title_sort | attenuated total reflectance fourier transform infrared spectroscopy for rapid identification of non-fermenting gram-negative bacilli isolated from patients with cystic fibrosis |
topic | Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5631018/ http://dx.doi.org/10.1093/ofid/ofx163.1553 |
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