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Differentiation of Taxonomically Closely Related Species of the Genus Acinetobacter Using Raman Spectroscopy and Chemometrics
AM. Teixeira, A. Nemec, C. Sousa,
Jazyk angličtina Země Švýcarsko
Typ dokumentu časopisecké články
NLK
Directory of Open Access Journals
od 1997
Free Medical Journals
od 1997
PubMed Central
od 2001
Europe PubMed Central
od 2001
ProQuest Central
od 1997-01-01
Open Access Digital Library
od 1997-01-01
Medline Complete (EBSCOhost)
od 2009-03-01
Health & Medicine (ProQuest)
od 1997-01-01
- MeSH
- Acinetobacter baumannii chemie klasifikace izolace a purifikace MeSH
- Acinetobacter calcoaceticus chemie klasifikace izolace a purifikace MeSH
- bakteriologické techniky MeSH
- infekce spojené se zdravotní péčí diagnóza mikrobiologie MeSH
- klasifikace MeSH
- lidé MeSH
- Ramanova spektroskopie * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
In recent years, several efforts have been made to develop quick and low cost bacterial identification methods. Genotypic methods, despite their accuracy, are laborious and time consuming, leaving spectroscopic methods as a potential alternative. Mass and infrared spectroscopy are among the most reconnoitered techniques for this purpose, with Raman having been practically unexplored. Some species of the bacterial genus Acinetobacter are recognized as etiological agents of nosocomial infections associated with high rates of mortality and morbidity, which makes their accurate identification important. The goal of this study was to assess the ability of Raman spectroscopy to discriminate between 16 Acinetobacter species belonging to two phylogroups containing taxonomically closely related species, that is, the Acinetobacter baumannii-Acinetobacter calcoaceticus complex (six species) and haemolytic clade (10 species). Bacterial spectra were acquired without the need for any sample pre-treatment and were further analyzed with multivariate data analysis, namely partial least squares discriminant analysis (PLSDA). Species discrimination was achieved through a series of sequential PLSDA models, with the percentage of correct species assignments ranging from 72.1% to 98.7%. The obtained results suggest that Raman spectroscopy is a promising alternative for identification of Acinetobacter species.
Citace poskytuje Crossref.org
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- $a Teixeira, A Margarida $u LAQV/REQUIMTE, Departamento de Ciências Químicas, Faculdade de Farmácia, Universidade do Porto, Rua Jorge Viterbo Ferreira, 228, 4050-313 Porto, Portugal. up201404495@ff.up.pt.
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- $a In recent years, several efforts have been made to develop quick and low cost bacterial identification methods. Genotypic methods, despite their accuracy, are laborious and time consuming, leaving spectroscopic methods as a potential alternative. Mass and infrared spectroscopy are among the most reconnoitered techniques for this purpose, with Raman having been practically unexplored. Some species of the bacterial genus Acinetobacter are recognized as etiological agents of nosocomial infections associated with high rates of mortality and morbidity, which makes their accurate identification important. The goal of this study was to assess the ability of Raman spectroscopy to discriminate between 16 Acinetobacter species belonging to two phylogroups containing taxonomically closely related species, that is, the Acinetobacter baumannii-Acinetobacter calcoaceticus complex (six species) and haemolytic clade (10 species). Bacterial spectra were acquired without the need for any sample pre-treatment and were further analyzed with multivariate data analysis, namely partial least squares discriminant analysis (PLSDA). Species discrimination was achieved through a series of sequential PLSDA models, with the percentage of correct species assignments ranging from 72.1% to 98.7%. The obtained results suggest that Raman spectroscopy is a promising alternative for identification of Acinetobacter species.
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