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.

• Klíčová slova
• bacteria, haemolytic clade, species, typing, vibrational spectroscopy,
• 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