Differentiation of Taxonomically Closely Related Species of the Genus Acinetobacter Using Raman Spectroscopy and Chemometrics
Abstract
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.